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HomeMy WebLinkAboutCORRESPONDENCE - WS-1 OPPOSITIONCity Council Meeting Correspondence 2/6/2018 Item No. ws-9PRESENTATION BY PANEL ON RENT CONTROL / STABILIZATION *RA - Recommended Action Thursday, February 8, 2018 Page 1 of 4 Date of Name Representative of In Favor In opposition Correspondence of RA*. of RA*. 1 211/2018 Julie Paule, Regional WMA No Yes Representative 2 2/212018 Tracy Meyers No Yes 3 2/212018 Matthew Buck, VP of Public CA Apartment Association No Yes Affairs 4 2/212018 Rochelle Smith, Project CCRM No Yes Manager 5 2/2/2018 Sal Ortiz, Regional Manager Newport Pacific No Yes 6 212/2018 Michael Smith, President MMS Management CO., Inc No Yes 7 212/2018 Showleh Tolbert No Yes 8 21212018 T.A. Clayton No Yes 9 21212018 CieloNungo Parkridge Villas Apartments No Yes 10 2/212018 Marissa Guess, Accounts API Property Management No Yes Payable 11 2/2/2018 Peter Gillin Santa Ana Resident No Yes 12 212/2018 Cathy Morehead No Yes 13 212/2018 Robert Elliott Santa Ana Resident No Yes 14 2/212018 Yenniffer Bejarano, Property Lincoln Pines Apartments No Yes Manager 15 21212018 Rory Ferlauto, Executive VP Farwest Management Corporation No Yes *RA - Recommended Action Thursday, February 8, 2018 Page 1 of 4 *RA - Recommended Action Thursday, February 8, 2018 Page 2 of 4 Date of Name Representative of In Favor In opposition Correspondence of RA*. of RA*. 16 2/2/2018 Gustavo Camacho, Property Medallion Court No Yes Manager 17 2/2/2018 Octavian Condrea No Yes 18 2/212018 Tin Shaw, Gov't Affair Pacific West Association of Realtors No Yes Director 19 2/2/2018 Vickie Talley, Executive MHET No Yes Director 20 215/2018 Discount Iron Fence and No Yes Gate, Inc. 21 2/5/2018 John Konwiser No Yes 22 2/5/2018 Richard Barbezed No Yes 23 2/5/2018 Tahwahnah Lyons No Yes 24 2/5/2018 Steven C. LaMotte, Chapter BIA No Yes Executive Officer 25 2/5/2018 Jon Dalton No Yes 26 2/5/2018 David Elliott, President Santa Ana Chamber of Commerce No Yes 27 2/5/2018 Kurtis Elliott No Yes 28 215/2018 Gene and Judy Opittek No Yes 29 2/6/2018 Craig Kirkpatrick No Yes 30 2/6/2018 Paul Julian, President Advances Real Estate Services, Inc. No Yes 31 2/6/2018 Korey Jorgensen No Yes 32 2/6/2018 Windsor Louie No Yes 33 2/6/2018 Donna Robbins No Yes 34 2/6/2018 Jay Kremer No Yes *RA - Recommended Action Thursday, February 8, 2018 Page 2 of 4 *RA -Recommended Action Thursday, February 8, 2018 Page 3 of 4 Date of Name Representative of In Favor In opposition Correspondence of RA*. of RA*. 35 2/6/2018 Gina Laroff No Yes 36 2/6/2118 Dick Mackaig No Yes 37 216/2018 Pamela Mundy No Yes 38 2/612018 Jan Hammon No Yes 39 2/612018 Leslie Manderscheid No Yes 40 21612018 Barbara Leigh Tonelli No Yes 41 216/2018 Ralph Siemion No Yes 42 21612118 Architopia No Yes 43 21612018 Richard A. Scudamore No Yes 44 21612018 Alan Wagner No Yes 45 2/6/2018 Liz Matthews No Yes 46 21612018 Temple Stratton, Realtor TNG Real Estate Consultants No Yes 47 2/612018 Chuck Fry Vista Communities, Inc. No Yes 48 2/612018 Conrad Wyszomirski OC Apartment Association No Yes 49 216/2018 Bridget Catalano Western Consolidated Equities No Yes 50 2/612018 Bruce Williams No Yes 51 2/612018 Debra Brown, Director of Bowers Properties, Inc. No Yes Property Management 52 21612018 Barbara Foster No Yes 53 2/612018 Rod Kossack No Yes *RA -Recommended Action Thursday, February 8, 2018 Page 3 of 4 *RA - Recommended Action Thursday, February 8, 2018 Page 4 of 4 Date of Name Representative of In Favor In opposition Correspondence of RA*. of RA*. 54 2/6/2018 Marie Balboa No Yes 55 2/6/2018 Lorraine Davis No Yes 56 2/6/2018 Amber Hall No Yes 57 216/2018 Jerry McLane No Yes 5g 216/2018 Shirley Laroff No Yes 59 2/612018 Farhad Nikoo No Yes 6Q 2/5/2018 Nicholas Dunlap, Vice Legislative Committee No Yes President 61 2/6/2018 John McCarthy, Real Estate C. McCarthy Properties LLC No Yes Consultant 62 217/2018 Ana Lamb AN Property Management No Yes 63 2/7/2018 Margie Tabrizi No Yes *RA - Recommended Action Thursday, February 8, 2018 Page 4 of 4 Mitre -Ramirez, Norma From: Sent: Thursday, February 1, 2018 12:19 PM To: eComment Subject: City Council Workshop on Rent Control 2-6-18 Attachments: 18_02_06 Santa Ana Rent Control Study.pdf Categories: Correspondence Attached is correspondence regarding the rent control workshop on the 2-6-18 city council agenda. Please include as part of the formal record/public comment. Thank you, Julie Paule, Regional Representative WMA 40335 Winchester Rd. #E-165 Temecula, CA 92591 (951)704-2427 iulie(a,pauleconsulting com Western M Manufactured Housing Communities Association February 1, 2018 Mayor Miguel Pulido City of Santa Ana 20 Civic Center Plaza PO Box 1988, M31 Santa Ana, CA 92701 Re: 2-6-18 Workshop Study on Rent Control Dear Mayor Pulido: Western Manufactured Housing Communities Association (WMA) is the oldest and largest statewide association of mobile home community owners and operators throughout California. We represent many communities in Santa Ana. We are pleased to submit our concerns about rent control, which the city council is studying and seeking input. WMA is always opposed to rent control or any government manipulation of rental housing pricing. We believe the free market is the only way to promote robust housing markets. Rent control is inherently unfair, erodes affordable housing, is divisive to your community and costly to administer. This housing policy should be soundly rejected. Rent control is inherently unfair. First, there is no means testing. When a city is administering a program for low-income residents and families, it requires an applicant to submit evidence or proof that income standards have been met and that the applicant is eligible to participate in the program. However, rent control is given to anyone who lives in a designated unit. They do not have to demonstrate need. And therefore, a millionaire would receive the same rent subsidy as a single mother with three children, who works two jobs just to make ends meet. Lack of affordable housing is a societal problem. As is public transportation, public education or meals and nutritional assistance. Programs to provide this aid are shouldered by all citizens across the 40335 Winchester Road, 5E-165 1 Temecula, CA 92591 phone 951704.2427 1 email iulieOpauleconsulting.com I web www.wma.org There are many alternatives to rent control that have been presented to us by the California Apartment Association. Subsidy programs, housing task force and educational programs can bring together all stakeholders and address pressing housing issues. Disagreements are often worked out between parties privately and do not require government intervention or a costly program to administer. Thank you in advance for your thoughtful consideration of this issue and for considering all sides of those who will be impacted if the City of Santa Ana moves forward to implement rent control. Please feel free to contact me directly with any questions at julie@pauleconsulting.com or (951) 704-2427. Sincerely, Julie Paule, Regional Representative cc: Council Member Vicente Sarmiento, Ward 2 Council Member Michele Martinez, Mayor Pro Tem Council Member Jose Solorio, Ward 3 Council Member David Benavides, Ward 4 Council Member Juan Villegas, Ward 5 Council Member Sal Tinajero, Ward 6 Mitre -Ramirez, Norma From: Huizar, Maria Sent: Friday, February 2, 2018 10:53 AM To: eComment Subject: FW: Rent Control /Just Cause Eviction Categories: Correspondence Correspondence for WorkStudy item. -----Original Message ----- From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 10:46 AM To: Huizar, Maria <MHuizar@santa-ana.org> Cc: Garcia, Jorge (CMO) <jgarcial0@santa-ana.org>; Cruz, Yesenia <YCruz5@santa-ana.org>; Flores, Rosa <RFlores@santa-ana.org>; Houston, Nicole <NHouston@santa-ana.org> Subject: FW: Rent Control / Just Cause Eviction Hi Maria, For the record, please see below. Best Regards, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Offices jcastro-cardenas@santa-ana.org 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 -----Original Message ----- Sent: Friday, February 2, 2018 10:43 AM To: City Council <CityCouncil@santa-ana.org> Subject: Rent Control / Just Cause Eviction Dear Mayor Pulido and City Council, I live in Costa Mesa and used to own rental property in San Francisco and Oakland. These two cities have the types of rent control and just cause eviction policies you are considering for Santa Ana. I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. It also creates barriers for landlords to rent to protected or marginal tenants. With limited financial resources, mom and pop landlords will not rent to these types of tenants because of the risks involved. If adopted, rent control and just cause eviction creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Tracy Myers Sent from my Phone Mitre -Ramirez, Norma From: Huizar, Maria Sent: Friday, February 2, 2018 10:54 AM To: eComment Subject: ECOMMENT - Letters to City Council from CAA: Rent Control, Just Cause Evictions Attachments: CAA Rent Control Letter to Santa Ana Council.pdf, CAA Just Cause Letter to Santa Ana Council.pdf Categories: Correspondence Sent: Friday, February 2, 2018 10:29 AM To: Huizar, Maria <MHuizar@santa-ana.org> Cc: Godinez, Raul <RGodinez@santa-ana.org> Subject: Letters to City Council from CAA: Rent Control, Just Cause Evictions A A California ApartmentAssoclation Orange County 23496 Madero Road, Suite 240 Mission Viejo, CA 92601 g49.9S5.3695 • caanet.org February 5, 2018 The Honorable Miguel Pulido Mayor, City of Santa Ana 22 Civic Center Plaza Santa Ana, CA 92701 Re: CAA Opposes Rent Control; Alternative Rental Housing Policies Dear Mayor Pulido and Council Members: The California Apartment Association, Orange County Division, which represents more than 100,000 units throughout Orange County vehemently opposes rent control or rent stabilization in any form. Studies clearly show that fixing the price of rent does not help solve an affordable housing crisis. Several studies on rent control can be found at whatisrenteontrol.org. Economists agree rent control increases the severity of the problem. 'Economists reckon a restrictive price ceiling reduces the supply ofproperty to the market. When prices are capped, people have less incentive to fix up and rent out their basement flat, or to build rental property. Slower supply growth exacerbates the price crunch. And those landlords who do rent out their properties might not bother to maintain them, because when supply and turnover in the market are limited by rent caps, landlords have little incentive to compete to attract tenants. " - The Economist (Aug. 201 S) Rent controls also lower the quality of life within communities. Plummeting property values adversely impact schools and city services. As home and apartment values decline, revenue from the county also declines. This jeopardizes the long-term health of schools and city infrastructure such as police, fire, and other services. While CAA is strongly opposed to any form of rent control or just cause eviction ordinances, we do applaud the city for exploring ways to address Santa Ana's affordable housing needs. The obvious long-term solution is to build and increase the city's housing supply; however, we do recognize there are immediate challenges between tenants and rental housing owners. Until our housing supply catches up to demand, we would like to present new ways to work with the community and City Hall on measures that will ease the pressures felt by all members of our community To begin, CAA recommends the city establish a Housing Task Force comprised of tenant advocates, local landlords, and other stakeholders. This group would be assigned with generating policies and programs that will better serve the communities in Santa Ana. As a proposed member of said Housing Task Force, CAA is prepared to elaborate on the following concepts: Landlord/Tenant Education Often local renters are unaware of their rights and responsibilities. Through better education and outreach we can ensure that renters understand the resources available to them. CAA is committed to working with the city to develop a multi-lingual, multi-media program to provide information to renters on local laws, their rights, and available resources to help residents resolve their housing issues, available funding sources for assistance, and prevent and defend evictions. CAA already publishes several educational tools to help renters with this information and we look forward to identifying ways to further promote this type of program in the city of Santa Ana. Voluntary Mediation Program CAA and our members support voluntary programs that provide opportunities for rental owners and their residents to engage in a dialogue. This would allow for both parties to understand each other's challenges on maintaining rising operational costs and living expenses in a neutral setting with the goal of arriving at a mutually agreeable solution. Minimum Lease Terms CAA does not oppose giving rental property owners the choice to offer residents the option a 6-month or 12-month lease at the inception of the tenancy. Contractual relationships between a landlord and tenant offer some assurance of stability under the terms of a written lease so as to minimize displacement of tenants into a housing market which may afford them few options. With the option of a 6-month or 12-month lease, residents who rent will have the ability to seek a guarantee of the rent to be paid for 6-months or one full year without fear of an increase and the residents can be assured that for the duration of this contract, they will not be evicted or asked to move unless there is a breach of the rental agreement. Relocation Assistance for Renovations A tenant relocation assistance ordinance would require landlords to provide relocation assistance to eligible tenants displaced from rental units because of renovations, redevelopment, and similar activities. This type of policy is intended to help residents with moving costs, deposits, and securing replacement housing. A targeted relocation assistance program would apply when the landlord seeks to recover possession to demolish or otherwise remove a residential rental housing unit from residential rental housing use to make repairs or renovations after having obtained all proper permits from the city, if any such permits are required. This program would NOT apply when an owner needs to recover possession of the unit to repair the damage or destruction of the unit which is caused by a fire or natural disaster or where tenants have been provided with alternative housing on site or nearby. Rather than tie the relocation assistance benefit to any formula based on tenancy or economic indicator, it should be a standard formula, for example: • Landlord must provide 90 days' notice to the tenant • Landlord must provide a full refund of the tenant's security deposit • Landlord must pay the cash equivalent of two months' rent City Funding for Affordable Housing Affordable housing is truly a community-wide issue and it warrants a community-wide solution. CAA recommends the city study the feasibility of broad based funding mechanisms to create affordable housing; for example, the consideration of a regional parcel tax, sales tax, and/or general obligation bond. These measures may provide an ongoing source of revenue for housing-voucher assistance and help finance the construction and preservation of housing. Such a measure would address affordable housing policy through community action and investment rather than placing the entire burden on one segment of our economy through increased fees, possibly lower land values, and ultimately higher market -rate rents. Funds generated from such measures could allow for the city to help subsidize rents for residents who meet certain income requirements, provide funding to help finance below market rate units, and could be used as loans/grants to rental owners to renovate and improve aging housing stock in exchange for maintaining below market rents. Housing Development Additional long-term solutions include supporting policies that allow for the construction of micro apartments. In September 2017, Gov. Jerry Brown signed CAA -sponsored legislation that will help to increase state's stock of micro apartments; these "efficiency dwelling units" are being used by some cities to provide housing for university students as well as shelter and services for homeless individuals. Conclusion CAA and its members appreciate the city tackling these tough issues. As a public policy trade association engaged in cities across Orange County and the state, we are able to offer a variety of solutions and best practices to the challenges you are facing that have been proven effective in the rental housing industry statewide. As the leading organization representing local Santa Ana rental property owners and managers, we are available to work with you on equitable policies or programs that you see best fit the housing needs and uniquely diverse characteristics of the city and its residents. We look forward to working closely with you, your staff, and the community in the coming months to discuss this issue further and identify mutually agreeable solutions to promote attainable and diversified housing options in Santa Ana. Sincerely, Matthew Buck Vice President of Public Affairs California Apartment Association Cc: Mayor Pro Tem Michele Martinez Councilmember Vicente Sarmiento Councilmember Jose Solorio Councilmember David Benavides Councilmember .Tuan Villegas Councilmember Sal Tmajero February 5, 2018 The Honorable Miguel Pulido Mayor, City of Santa Ana 22 Civic Center Plaza Santa Ana, CA 92701 Re: CAA Opposes `Just Cause' Eviction Policies Dear Mayor Pulido and Council Members: The California Apartment Association, Orange County Division, which represents more than 100,000 units throughout Orange County, applauds the city for being vigilant in exploring ways to promote ethical housing management practices throughout the City of Santa Ana. However, we are strongly opposed any form of `just cause' eviction policies on rental housing units. While well intentioned, `just cause' eviction ordinances can become the bane of neighborhood leaders seeking to rid a community from the impacts of a renter converting a home to a "gang house" or "drug den," where surrounding neighbors fear the prospect of testifying or offering declarations in support of an eviction proceeding. In addition to a myriad of unintended consequences, the State of California already has some of the most aggressive tenant rights laws in the nation. What are `Just Cause' Eviction Policies Most elected officials and members of the community are familiar with the concept of rent control and have a basic understanding of the ways in which it impacts the local economy. Less well known and understood is the companion to rent control, so-called "just cause" eviction. `Just cause' eviction ordinances take away a landlord's right to terminate a tenancy or refuse to renew a lease for any reason or no reason at all. The contents of this letter cover the effect of `just cause' eviction ordinances within neighborhoods, broader communities and local jurisdictions. `Just Cause' Eviction Policies are Unnecessary State Law Prohibits Retaliatory Evictions Both the common law and California Civil Code section 1942.5 prohibit a landlord from seeking to evict or otherwise taking adverse actions against a tenant because the tenant has engaged in a legally protected activity (which includes complaining about habitability issues). In fact, Civil Code Section 1942.5(a) provides greater protection than most `just cause' eviction ordinances because it establishes a presumption in favor of the tenant, stating that the landlord may not act to evict a tenant within 180 days after the tenant complains to the landlord or a government agency about habitability. The California anti -retaliation laws function as both a defense to an unlawful detainer action and as a basis for an affirmative lawsuit. M." ^� California Apartment Association Orange County 29436 Madero Road, Suite 240 Mission Viejo, CA 92691 949.955.3695 - caanet.org February 5, 2018 The Honorable Miguel Pulido Mayor, City of Santa Ana 22 Civic Center Plaza Santa Ana, CA 92701 Re: CAA Opposes `Just Cause' Eviction Policies Dear Mayor Pulido and Council Members: The California Apartment Association, Orange County Division, which represents more than 100,000 units throughout Orange County, applauds the city for being vigilant in exploring ways to promote ethical housing management practices throughout the City of Santa Ana. However, we are strongly opposed any form of `just cause' eviction policies on rental housing units. While well intentioned, `just cause' eviction ordinances can become the bane of neighborhood leaders seeking to rid a community from the impacts of a renter converting a home to a "gang house" or "drug den," where surrounding neighbors fear the prospect of testifying or offering declarations in support of an eviction proceeding. In addition to a myriad of unintended consequences, the State of California already has some of the most aggressive tenant rights laws in the nation. What are `Just Cause' Eviction Policies Most elected officials and members of the community are familiar with the concept of rent control and have a basic understanding of the ways in which it impacts the local economy. Less well known and understood is the companion to rent control, so-called "just cause" eviction. `Just cause' eviction ordinances take away a landlord's right to terminate a tenancy or refuse to renew a lease for any reason or no reason at all. The contents of this letter cover the effect of `just cause' eviction ordinances within neighborhoods, broader communities and local jurisdictions. `Just Cause' Eviction Policies are Unnecessary State Law Prohibits Retaliatory Evictions Both the common law and California Civil Code section 1942.5 prohibit a landlord from seeking to evict or otherwise taking adverse actions against a tenant because the tenant has engaged in a legally protected activity (which includes complaining about habitability issues). In fact, Civil Code Section 1942.5(a) provides greater protection than most `just cause' eviction ordinances because it establishes a presumption in favor of the tenant, stating that the landlord may not act to evict a tenant within 180 days after the tenant complains to the landlord or a government agency about habitability. The California anti -retaliation laws function as both a defense to an unlawful detainer action and as a basis for an affirmative lawsuit. Tenants Have Additional Protections Under Existing Law Existing law already provides many protections for the most vulnerable people in our society — low income, elderly, and disabled tenants in the eviction process. Some of these protections apply to all tenants. For example, landlords are held to a very strict standard in eviction cases. The smallest error, such as an inverted number in an address on a termination notice can cause a landlord to lose an eviction case even though the tenant may not have been misled by the mistake. In addition, the unlawful detainer process itself contains several built-in protections for tenants. For instance, when a landlord files an unlawful detainer action against a tenant, the court is required to send a "Notice of Filing of Unlawful Detainer" to the tenant. This notice contains, among other things, the name and telephone number of a legal services organization that provides legal services (typically free of charge) to low-income persons in the county. Other protections specifically target vulnerable populations. For example, landlords' duties to reasonably accommodate disabled tenants may include giving a disabled tenant additional time, beyond the 30 or 60 days provided for in the law to move out. Section 8 tenants have a statutory right to 90 days' notice when their lease is not being renewed or their tenancy is otherwise being terminated through no fault of their own. Tenants in other subsidized housing are already provided protection from no -cause evictions under the rules of the subsidy programs. In addition to these protections, the law gives judges who preside over unlawful detainer cases two powerful tools to assist tenants who have hardships. First, judges have discretion to stay the execution of an unlawful detainer judgment — which has the effect of delaying the lock -out — by up to 40 days after judgment is entered. Second, in cases of serious hardship, the judge has the discretion to grant a "motion for relief from forfeiture." The effect of this ruling is to restore the tenancy, thereby sparing the tenant from eviction. Because this remedy is limited to cases of hardship, it provides a valuable "safety valve" for the truly vulnerable without allowing intransigent tenants to avoid eviction despite their bad behavior. These are just a handful of examples at how California law currently protects tenants. `Just Cause' Eviction Laws Hurt Tenants Good Tenants Get Stuck with Bad Neighbors Due to the amount of evidence required to complete a `for cause' eviction, it takes months if not years to evict a bad tenant. Successful removal requires landlords to give bad tenants multiple written warnings, and to document the on-going issues with objective evidence (photos, security footage, tenant complaints, police involvement). Neighboring tenants suffer during this time as they're forced live with the bad tenant's behavior. The list of horror stories is endless. Tenants Receive Less Notice Landlords rarely terminate the tenancy of residents who pay the rent and comply with the lease. More often than not, a landlord serves a `no cause' termination notice in response to a tenant's violation of the lease. While the landlord could pursue a `for cause' notice, it is easier to give a 30/60 -day notice. So, under a `just cause' ordinance, landlords aren't going to stop evicting bad tenants, they will simply start issuing 3 -day notices versus 30/60 -day notices. Negative Impact on Tenants' Rental History As mentioned above, `just cause' ordinances result in more 3 -day notices being served. Being served with a 3 -day notice is a negative mark on a tenant's rental history, whereas being served with a 30/60 -day notice is not necessarily. This is because 30/60 -day notices can be served for reasons unrelated to the tenant (such as owner move -in or renovation). CAA's Rental Applicant Reference Form asks if a tenant has ever been served with a 3 -day notice but does not ask if a 30/60 -day notice was served. Under a `just cause' ordinance more tenants will have the negative mark of having been served with a 3 -day notice. This will negatively impact tenants' abilities to find new housing. More Unlawful Detainer Actions Will be Filed It's nearly impossible to find a new place to live, pack, and move in 3 days, tenants are more likely to stay in the unit after the expiration of a 3 -day notice versus a 30/60 -day notice. Thus, it is more likely that tenants will have an unlawful detainer action filed against them. Having a UD judgment on your rental history makes it nearly impossible to get approved for new rental housing. Tenants More Likely to Have to Pay Large Attorney's Fees Awards Many courts have attorney fee schedules that limit the amount of attorney's fees that can be awarded in unlawful detainer actions (often it is limited to a flat $500 or $750). However, if the case was more complicated, the court generally has discretion to award a higher amount. Because `for -cause' cases take more work to prove, landlords are more likely to be able to obtain higher awards which tenants have to pay. The average `for -cause' case that results in a pre-trial settlement incurs nearly $5,000 in attorney fees. However, in nuisance cases that went to trial it's not unusual for the fees to approach $15,000420,000. Most leases have an attorney's fee provision, which makes the tenants responsible for paying the landlord's costs to go to court. More Critical Landlords `For -cause' cases take a lot of evidence to prove. It is helpful to be able to show a long pattern of misbehavior in support of a case. Thus, tenants are more likely to be under a microscope when the landlord is subject to `just cause' requirements. Every rule violation will result in lease violation notices being served and every minor incident will be documented in tenants' files. Tenant advocates might say that this is a good thing because landlords should have to document and give warnings, but many tenants say they felt like the practices are too much. Conclusion As I have highlighted throughout this letter, there's an overwhelming amount of evidence that shows why `just cause' eviction ordinances are not appropriate solutions to a community's housing issues. Not only do they impede a rental housing provider's progress in providing quality rental housing, such ordinances are legally unnecessary and ultimately hurt tenants. CAA thanks you for allowing us to be a resource to the City of Santa Ana, please do not hesitate to contact us on any issues related to rental housing policy or if you have any questions on the contents of this letter. I can be reached directly at 951-809-4423 or MBuck@caanet.org. Sincerely, Matthew Buck Vice President of Public Affairs California Apartment Association Cc: Mayor Pro Tem Michele Martinez Councilmember Vicente Sarmiento Councilmember Jose Solorio Councilmember David Benavides Councilmember Juan Villegas Councilmember Sal Tinajero Mitre -Ramirez, Norma From: Huizar, Maria Sent: Friday, February 2, 2018 11:31 AM To: eComment Subject: FW: Opposed to rent control, just cause eviction policies in Santa Ana Categories: CMO Approved For the record. From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 11:02 AM To: Huizar, Maria <MHuizar@santa-ana.org> Cc: Garcia, Jorge (CMO) <jgarcia10@santa-ana.org> Subject: FW: Opposed to rent control, just cause eviction policies in Santa Ana Hi Maria, FYI — see below. Best Regards, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 10:58 AM To: City Council <CityCouncil@santa-ana.org> Subject: Opposed to rent control, just cause eviction policies in Santa Ana Dear Mayor Pulido and City Council, I manage a four -unit rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Property Manager, CCRM Mitre -Ramirez, Norma From: Huizar, Maria Sent: Friday, February 2, 2018 12:29 PM To: eComment Subject: FW: No to Rent Stabilzation Categories: CMO Approved Correspondence for record. From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 12:06 PM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: FW: No to Rent Stabilzation For the record Best Regards, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 12:01 PM To: City Council <CityCouncil@santa-ana.ore> Subject: No to Rent Stabilzation Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Sal Ortiz Newport Pacific Regional Manager 17300 Red Hill Ave. Suite 280 Irvine, CA 92614 P: 949.852.5575/F: 949.852.5582 Sal. OrtizgNewportPacific.com www.iiewportpacific.com 0 CONFIDENTIAL INFORMATION This e-mail transmission contains confidential information which is intended only for the addressee and which may be privileged under applicable law. Do not read, copy or disseminate it if you are not the addressee. If you have received this message in error, please notify the sender immediately and delete it. Thank you. Mitre -Ramirez, Norma From: Huizar, Maria Sent: Friday, February 2, 2018 1:27 PM To: eComment Subject: FW: NO Rent Control Categories: CMO Approved Correspondence for record. From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 12:37 PM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: FW: NO Rent Control For the record Best Regards, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 12:33 PM To: City Council <CityCouncil@santa-ana.ora> Subject: NO Rent Control Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and other cities across California and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannotbe achieved, through studying or adopting, rent control(akarent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Michael M. Smith President MMS Management Co., Inc. General Partner — Smith Brothers Company, Cedar Creek Properties, L.P., & Alameda & Garden Grove, L.P. Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 1:44 PM To: Huizar, Maria Subject: FW: NO Rent Control, Just Cause Eviction Policies For the record Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 1:35 PM To: City Council <CityCouncil@santa-ana.org> Subject: NO Rent Control, Just Cause Eviction Policies Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing However, this cannot be achieved through studying or adopting. rent control (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Showleh Tolbert Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 1:44 PM To: Huizar, Maria Subject: FW: rent control For the record. Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assislant City Manager's Office 1 Jcastro-Cardenas@santa-ana.orq 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 1:41 PM To: City Council <CityCouncil@santa-ana.org> Subject: rent control Dear Mayor Pulido and City Council, As an active stakeholder in your community, I support the eitya€TMs goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (alta rent stabilization) and just cause eviction policies. A Rent control is a counterproductive policy. It will not produce any new affordable housing or address the eitya€TMs long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property.A A Instead, I urge you to expand the citya€TMs efforts to produce more housing and promote available resources and programs for the citya€TMs renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical managementA practices. A I appreciate the citya€TMs collaborative approach to provide meaningful, long-term solutions to our regiona€TMs housing challenges. Thank you for your continued leadership on this important issue. A Sincerely, T. A. Clayton Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 2:13 PM To: Huizar, Maria Subject: FW: NO TO RENT CONTROL FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 2:05 PM To: City Council <CityCouncil@santa-ana.org> Subject: NO TO RENT CONTROL Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Cielo Nwigo Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 2:14 PM To: Huizar, Maria Subject: FW: Rent "stabilization"???? Fyi Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant Cily Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 2:05 PM To: City Council <CityCouncil@santa-ana.org> Subject: Rent "stabilization"???? Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Marissa Guess Accounts Payable marissa@apipropeLlymanagement.com (p) 714-505-5200 (ext. 20) (f) 714-505-5210 API Property Management 1400 N. Bristol Street Suite 245-A Newport Beach, CA 92660 Mitre -Ramirez, Norma From: Huizar, Maria Sent: Monday, February 5, 2018 1:54 PM To: Mitre -Ramirez, Norma Subject: ECOMMENT - Dear Mayor Pullido, Santa Ana Resident, Opposed to Rent Control Categories: Correspondence From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:01 PM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: FW: Dear Mayor Pullido, Santa Ana Resident, Opposed to Rent Control FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 3:41 PM To: City Council <CityCouncil@santa-ana.org> Subject: Dear Mayor Pullido, Santa Ana Resident, Opposed to Rent Control Dear Mayor Pulido and City Council, 1 live in Santa Ana. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies. - Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Peter Gitlin Mitre -Ramirez, Norma From: Huizar, Maria Sent: Monday, February 5, 2018 2:42 PM To: Mitre -Ramirez, Norma Subject: ECOMMENT - Rent Control Categories: Correspondence From: Castro -Cardenas, Julie Sent: Monday, February 5, 2018 2:42 PM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: Fwd: Rent Control Respectfully, Julie Castro -Cardenas City Manager's Office City of Santa Ana 714-673-3619 Sent from my iPhone Begin forwarded message: Date: February 5, 2018 at 1:57:51 PM PST To: <citycounciloa Santa-ana.org> Subject: Rent Control Reply -To: <moreheadcna gmail.com> Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing However, this cannot be achieved throughstudying or adopting rent control (aka rent stabilization) and just.causp.eviction policies. - .. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely„ Cathy Morehead Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:12 PM To: Huizar, Maria Subject: FW: No on Rent Control FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I ,jcastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 4:08 PM To: City Council <CityCouncil@santa-ana.org> Subject: Fw: No on Rent Control On Friday, February 2, 2018 3:47 PM, Robert Elliott < Dear Mayor Pulido and Council Members I have been a rental property owner in Santa Ana for over 60 years. My property has been awarded your Gold Seal every year since the program started. My properties always are clean and well maintained. Rent control takes away any incentive a property owners to maintain their properties. I donotbelieve rent control will solve the housing issues you are trying to resolve. Instead it be the beginning of owners who only do the absolute necessities to get by, Please DO NOT adopt rent controls in our city. Thanking you in advance for your support, Robert Elliott Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:13 PM To: Huizar, Maria Subject: FW: NO Rent Control FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 From: Yenniffer Bejarano[mailto:ybejarano@apipropertymanagement.comj Sent: Friday, February 2, 2018 3:32 PM To: City Council <CityCouncil@santa-ana.org> Cc: Margie Tabrizi<margie@apipropertymanagement.com>; Kim Montgomery<kim@apipropertymanagement.com>; Ana Lamb<alamb@apipropertymanagement.com> Subject: NO Rent Control Dear Mayor Pulido and City Council, We please ask you to NOT move forward with rent control. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Yenniffer R. Bejarano Property Manager Lincoln Pines Apartments 2555 W Lincoln Ave No 117 Anaheim CA 92801 (714) 761-3648 Phone / Fax vbeiaranona apipropertymanagement.com Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:19 PM To: Huizar, Maria Subject: FW: Rent Stabilization Won't Work FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-Cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 From: Rory Ferlauto[mailto:rf@farwestapartments.comj Sent: Friday, February 2, 2018 3:17 PM To: City Council <CityCouncil@santa-ana.org> Subject: Rent Stabilization Won't Work Dear Mayor Pulido and City Council, I operate 4 rental properties in Santa Ana totaling 1,178 units and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through,studying,or.adopting rent control (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long- term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Rory Ferlauto Executive Vice Presidnet 17941 Mitchell Street Irvine, CA 92614-6015 tel 949-863-1757 ext 118 fax 949-863-9293 rf(a)famestapartments. corn www farwestapartments.com Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:22 PM To: Huizar, Maria Subject: FW: Rent Control FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I jcastro-cardenas@santa-ana.org 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 From: Gustavo Camacho[mailto:gcamacho@apipropertymanagement.comj Sent: Friday, February 2, 2018 2:14 PM To: City Council <CityCouncil@santa-ana.org> Subject: Rent Control I -vote NO on Rest Control Gustavo Camacho Property Manager Medallion Court (714) 832-8002 www.ecamachoa,auivroDertvmanaeemeut.com 17045 Medallion Avenue Tustin, CA 92780 Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:22 PM To: Huizar, Maria Subject: FW: Rent Control FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Managemeni Assistani City Manager's Office I jcastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 From: Gustavo Camacho[mailto:gcamacho@apipropertymanagement.com] Sent: Friday, February 2, 2018 2:15 PM To: City Council <CityCouncil@santa-ana.org> Subject: Rent Control ®ear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this_cannot:be achieved through studying or adopting,.,rent,control .(aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the ostead, I urge you to expand the city's efforts to produce more housing nd promote available resources and programs for the city's renters. I ask tat you focus on these goals and look for ways to partner with the ommunity to ensure renters are aware of resources available to them nd educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long- term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Name Gustavo Camacho Gustavo Camacho Property Manager Medallion Court (714)832-8002 www.2camacho(&apipropertymanagement.com 17045 Medallion Avenue Tustin, CA 92780 Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Friday, February 2, 2018 4:22 PM To: Huizar, Maria Subject: FW: Rent control is a counterproductive policy FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Managemeni Assistant City Manager's Office I icastro-cardenas@santa-ana.ora 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Friday, February 2, 2018 2:31 PM To: City Council <CityCouncil@santa-ana.org> Subject: Rent control is a counterproductive policy Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot'be achieved through studying or adopting rent control. (aka rent stabilization) and just cause eviction policies. Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. I appreciate the city's collaborative approach to provide meaningful, long-term solutions to our region's housing challenges. Thank you for your continued leadership on this important issue. Sincerely, Octavian George Condrea Mitre -Ramirez, Norma From: Tim Shaw <TimS@pwr.net> Sent: Friday, February 2, 2018 5:01 PM To: eComment Subject: rent control Attachments: vnscanner_20180202_195831.pdf Categories: CMO Approved Please find the attached letter related to the rent control item on the agenda for next Tuesday. Thank you, Tim Shaw Government Affairs Director Pacific West Association of REALTORS® 1601 E. Orangewood Ave. Anaheim, CA 92805 www.i)wr.net p. (714) 221-8449 e. TimSQpwr.net PACIFIC WEST ASSOCIATION OF REALTORS' -+fie February 2, 2018 Mayor Miguel Polido 22 Civic Center Plaza Santa Ana, CA 92701 RE: Opposition to Rent Control Mayor Polido: At your February 6, 2018 City Council meeting you will hear a presentation on rent control/rent stabilization. The Pacific West Association of REALTORSCQ opposes rexrtcontrol and its affiliated policy "Just,Cause Eviction" inthe-strongest possible terms, - Rent Control is a well-intentioned policy "cure" for the serious problem of housing affordability, but it does not work. In fact, the "cure" is worse than the disease. By artificially constraining rental prices, rent control removes the incentive for landlords to improve their properties, A landlord who will not_reccive.afair rate of return on the property cannotaffordto spend money to, maintain it, When property maintenance declines, it has a spiraling effect on the community. Declining properties lower values. This lowers tax revenue to local government. Less tax revenue undermines governmental maintenance and services, and the cycle continues, Rent control is a disincentive for builders and investors to bring new properties to market. Fewer properties constrains an already tight supply of rental housing, putting even more upward pressure on the price of existing rentals. In other words, rent control exacerbates the very problem it is designed to solve. Rent control is not fair. Most landlords are decent, respectable business people who abide by their leases and who want to keep the tenants in their homes. Many are also small business persons, and in some cases retirees on a fixed income, who rely on the steady income of their rental to survive, Artificially constraining the price they can charge, and imposing burdensome bureaucracy on their business, hampers their way of life, (714) 245-5500 --www.pwnnet— FAX (714) 245-5599 Ld 1601 E. Orangewood Avenue—Anaheim, CA 92805 REALTOR 3750 (11roy Airport Way, Su ite 120-- Long Beach, CA 90806 Rent control creates a huge bureaucracy for local govermnent. The cost to local government to administer a rent control program is enormous. Finally, rent control does not help the very people it is intended to protect. Controlled units become a premium for tenants, who sublease them to family and friends "under the table" and at higher rates. This lowers turnover and only further limits the supply of affordable rental housing for the neediest. Again, the "cure" is worse than the problem, Anyone who doubts these problems with rent control need only look at many of the cities that have already tried it. Cities like New York, Los Angeles and San Francisco, for example, have lived with rent control for decades and are no closer to solving their affordability issues now than they were when those programs were adopted. The solution to the housing crisis is obvious, First and foremost, we need more housing. City government has a moral obligation to plan appropriately so that housing can be built to address the needs of all income levels, ownership and rental. It is short-sighted at best to limit supply then put a lid on prices, which sets the laws of economics against each other. The REALTORS associations at the national, state, and local level are all working to solve the housing affordability crisis. We ask that you adopt a "do no harm" mentality as you consider different policy prescriptions, first and foremost by opposing any attempt at rent control or just cause eviction. Thank you for your consideration Sincerely, '7_11(m A).— Tim Shaw Govermnent Affairs Director Pacific West Association of REALTORS® Mitre -Ramirez, Norma From: Vickie Talley <vickie@talleyassoc.com> Sent: Monday, February 5, 2018 9:16 AM To: Huizar, Maria Subject: Comment Letter City Council 2/6 Work Study Session Rent Control Attachments: 020418M H ETCo m mentRentControl.pdf Importance: High Dear Maria Huizar, Attached is a comment letter stating opposition torentcontrol the item to be discussed at the February 6, 2018 City Council Meeting. Thank you for distributing to the City Council and for making sure it is entered as part of the public record. Sincerely, Vickie Talley MHeT �Ao�niLial.:ut rl t3oirsir^^kat.%!H'.tilk�aa;tl Vickie Talley, Executive Director MHET Manufactured Housing Educational Trust 25241 Paseo de Alicia, Suite 120 Laguna Hills, California 92653 Email: vickie@mhet.com MHET has been working to protect mobile home park owners' property rights since 1982! If you are not a member, please ask me about joining today! This email is intended for the sole use of the intended recipient(s) and may contain confidential or privileged information. No one is authorized to copy, re -use, disclose, distribute, take action or rely on this email or any information contained in it. If you are not the intended recipient, we request that you please notify us by reply email and destroy all copies of the message and any attachments. Thank you for your prompt attention. A MH ting lalosalianrt February 4, 2018 BOSH!) of DIRECTORS Seat Via Email; City Clerk Maria Ituizar-- mhuizar@santa-ana.org santa-ana.org 4reridim 1 o"M l41411111rd hood Als q. n lira AWMI • Rent controlled units cause stagnation and etrcourages tenants paying bela)y- FAIM` RTh Honorable Mayor Miguel Pulido lh 4 KIthI„ rAN61114Ff Members of the Santa Ana City Council 8, rIan City of Santa Ana I.Wian f1stli'l 22 Civic Center Plaza 'agwmi �""``"' A'anHietla Santa Ana, California 92701 #Erin jfil} hmfi Rp ILJG — RE: Agenda item: Work Study Session --Rent Control Oppose IAM NiAiQ9 • Rent controlled ap p artntents and rupbhome >�lle harks all into disrepair because zee anu� the owners cannot afford to maintain the units lvith ever increasing Idinlrlm Dear Mayor Pulido and Members of the City Council: rtprmd afembers All on has to do is visit New York City to see abandoned rent -controlled 114 Oelurtfi apartments to know this statement is a fact. The City of Yucaipa wants to closed find bld1.ui44mid The Manufactured Housing Educational Trust_(MFIET) represents the manufactured n li 1 housing community owners of Orange, Riverside and San Bernardino County. As a Coxig ll"w'r clod IAV regional organization, MkIET is a resource for cities, manufactured community owners jdvilary calf„ nume and residents and is pleased to have worked with the City of Santa Ana over the years to Wtfl Phokooe address housing issues, JolloRuth, Ras*Thomas I wy Nvow r We recognize that the Study Session on Rent Control is designed to present the Council rant 1WR(nellra F,d Nalw with information on the subject. This is a subjrrct that has hada wealth of studies done J. It phinp, Ih t o Muni on examples of experimentation with controlling rents and why it is a failed public policy. We appreciate the Council's effort to become better informed on rent control )'RIi7IifK{lriF� Atiek GOW11 and also appreciate your consideration of the following facts. supporting our opposition. (111 i V rdl boAller 8"3" Joa+A , ulet�IM&N, all . Rent Control reduces landlord's incentives to rent out their apartments, JAM.MIRfairiz:, Kdlh wA c I have a friend whose daughter's mother-in-law owed apartments in Santa N-al0l"ftx r bon Oil kr It Monica. Because of rent control she took the units off of the market, This is a asad0E10l4ze Ullwit (1rilb common occurrence in fent controlledjurisdictions. tt�a tasrnDn,y ZI1.(/2i1ttlF IFremrar • Rent controlled units cause stagnation and etrcourages tenants paying bela)y- Award Ille.ciiieaftx sqfma(IaaRa market rents to stay in the unit even after they can well afford to prove. Jen"A°" Another friend brags that his daughter, an attorney, is really lucky because she N N NuA' has a cheap Santa Monica rent controlled apartment next to the beach. Rent Um j,"G In Qh.(f(fii control pits present renters against all future seekers of housing, sets high and .1?EY} flaw, Z.K�A�a 3c� middle-income against low-income families. #Erin {'loft tVktx riBare and RFpofxd • Rent controlled ap p artntents and rupbhome >�lle harks all into disrepair because deraldRnrtgtettu the owners cannot afford to maintain the units lvith ever increasing Ia11 113;all maintenance and 1'el}aiC costs aacl bellow market Y21t1S. lain lt�wi Pavlllms"a: All on has to do is visit New York City to see abandoned rent -controlled c, Ofivimars„ 31 apartments to know this statement is a fact. The City of Yucaipa wants to closed d6q! J mew lu' ftlm rundown mobile home parks which sit in disrepair because of the city's rent hwiae 6titlotiLL control laws, F:rraMtavrTlirRctor 4v.kir'fA9rT.°VI/Non) drNidmSoitol:n+6ariatat JIM,,!'RHlondaPkwlt NA Y0 2(11e}fr fn+"IR)AIIII, Email, hIMee"Walmit a ITHItdC: wtoo'dOxrara Solelllenz Gattjonfiu JUIGT Serrdrty Oranye, Puierside and Sfata I enturditio t onnl€cs sdaaec 14W Mitre -Ramirez, Norma From: Castro -Cardenas, Julie Sent: Monday, February 5, 2018 9:38 AM To: Huizar, Maria Subject: FW: Nq-to-rent control For the record, this one just had content on the subject line. Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.orq 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Monday, February 5, 2018 9:09 AM To: City Council <CityCouncil@santa-ana.org> Subject: NO to rent control Mitre -Ramirez, Norma From: Sent: Monday, February 5, 2018 11:49 AM To: eComment Subject: Rent Control Hello, I am writing to tell you rent control would'be the:worst possiblething forSanta Ana with its moderate income people who would be forced out by escalating rents under rent control. This is a free market county since 1776 and controlling either supply or demand will not work. Orange County is an expensive place to live and rent control will not cheapen it. Allowing higher density and more housing will and nothing else. Thanks for reading my thoughts, John Konwiser Mitre -Ramirez, Norma From: Flores, Rosa Sent: Monday, February 5, 2018 1:15 PM To: Huizar, Maria Cc: Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Subject: Phone Message on Rent Control Categories: CMO Approved FYI - Richard Barbezett called to say he is against rent control and that it would not be good for our city. Rosa ,'Cores City -Manager's Office X5222 Mitre -Ramirez, Norma From: Sent: Monday, February 5, 2018 4:18 PM To: eComment Subject: Concerns about rent control in Santa Ana! I understand that you are considering rent control in Santa Ana. I believe and have seen rent control become bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Please keep it out of Orange County and keep it out of Santa Ana! Santa Ana needs a true public/private partnership to address the housing crisis and that starts with: *Building more affordable and workforce housing *Expanding the Section 8 housing program *Building more conventional rental housing units I have seen that instituting rent control only leads to dilapidated and decreased housing stock and fails to plan for immediate and future needs. Rent control is a bad plan and the wrong vote for Santa Ana's future! Tahwahnah Lyons Commit yourself to constant improvement and be wise in all you do. Mitre -Ramirez, Norma From: Huizar, Maria Sent: Monday, February 5, 2018 4:29 PM To: eComment Subject: 131A/CC Comment Letter Attachments: BIAOC Comment Letter - Rent Control.pdf From: Adam Wood [mailto:awood@biaoc.com] Sent: Monday, February 5, 2018 4:22 PM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: BIA/OC Comment Letter Please see the attached letter for distribution regarding tomorrow night's council meeting. Thank you. Adam S. Wood Director of Government Affairs Building Industry Association I Orange County Chapter (BIA/OC) 24 Executive Park, Ste 100 Irvine, CA 92614 (949) 553-9500 ext. 860 (949) 777-3860 Direct AWood@biaoc.corn Building Industry Association of Southern California, Inc ORANGE COUNTY CHAPTER February 5, 2018 Mayor Miguel Pulido Honorable City Council Members City of Santa Ana 22 Civic Center Plaza Santa Ana, CA 92702 Re: Work Study Session on Rent Control / Stabilization Dear Mayor and Council: On behalf of our membership, I write to express our opposition to Rent Control and Stabilization Policies. The Building Industry Association of Southern California, Orange County Chapter (BIA/OC) is a non-profit trade association of over 1,100 member companies employing over 100,000 people in the home building industry. Counterintuitive to its intent, economists and public policy experts have consistently agreed that a "ceiling on rents reduces the quality and quantity of housing."' In a recent study published by the National Bureau of Economic Research, Stanford researchers found that rent control policies "ended up pulling properties from the rental market – shrinking the rental housing supply overall" and having a "counterproductive effect.'' Additionally, the Legislative Analyst's Office has stated that "many housing programs—vouchers, rent control, and inclusionary housing—attempt to make housing more affordable without increasing the overall supply of housing. This approach does very little to address the underlying cause of California's high housing costs: a housine shortaee." As our mission is to champion housing as the foundation of vibrant and sustainable communities, we can not support a policy that will limit housing in Santa Ana. To address affordability, the reasonable alternative is to produce more housing through smart policies like the City's recently enacted Innovative Housing / Small Lot Subdivision Ordinance. Thank you for your thoughtful consideration and dedication to solutions that facilitate housing. Respectfully, Steven C. LaMotte Chapter Executive Officer 1 Paul Krugman. "Reckonings; A Rent Affair," New York Times, June 7, 2000, accessed August 8, 2014. htto //www nytimes com/3000/Q6/Q7/opinion/reckonings a rent-affa'r hlml 2 Tanvi Misra. "Rent Control: A Reckoning" accessed February 2, 2018 bitg§ //www tvlap om/ qunv/2018/01/rent- ntmi a-recko 0/551168/ PRE§IPEfdT MIKE PART6AN K8 MQM€ VI9€ PRE§1PENT RISK 4!"QQP TRI PAINT€ I1QME6 TREANR€RtRPPR€TARP §UNT1 KkJMdIM MRKIIQM€§ IMM@PIAT@ PART PR€§!PPNT phPQPEM M€RITA§E NPME§ TRAP€ 99NTRACT9R Y,P. 4AN 99PPR€AP P.Q9PREAN PIP€NIN€ 9QR1RPRAT19N A5§991ATE VISE PR€§199NT MARK NIMME6§TEIN N€IMMEVER 4 P1419111 4P- M€M§€R-AT-1,AR9€ PETERVANEK FPRPMQ§T 9QMPANl€§ MEM6ER-AT76AR9E 6EAN MAT§6€R MANATTPNE6P§A PNIWR§, 4? €49UTIVE Q_FPQPR §TEV€ to MATT€ Mitre -Ramirez, Norma From: Huizar, Maria Sent: Monday, February 5, 2018 4:30 PM To: eComment Subject: FW: Rent Control Study Meeting From: Castro -Cardenas, Julie Sent: Monday, February 5, 2018 3:46 PM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: FW: Rent Control Study Meeting For the record please. Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I jcastro Cardenas@sonta-ana ora 714,673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Monday, February 5, 2018 3:38 PM To: City Council <CitvCouncil(Tsanta-ana.ore> Subject: Rent Control Study Meeting Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction policies. I am a small business operator with four condos. As I am nearing retirement, this is more and more serving as my main source of income. At present I have two tenants paying well under market. One is paying $1260.00 for a unit worth $1700.00 mo. the other is paying $1350.00 for a unit worth $1600.00. I only increase their rents once every two years and by a minimal amount as I know this is all they can afford. If the policy is adopted I will be forced to have them sign new contracts closer to market or move them out and get new renters closer to market rate. I will also be forced to increase their rents by the maximum allowable EVERY YEAR in order to avoid falling behind the market aggregate. Please think very seriously before adopting these policies. I live in Los Angeles and can plainly see that RC does not work. More and more units are being withdrawn from the market and being replaced with newer housing which does not fall under the RC remit. Sincerely, Jon Dalton Norma From: Huizar, Maria To: Tuesday, February 6, 2018 10:52 AM Subject: eComment Attachments: ECOMMENT - Santa Ana Chamber Opposes Rent Control Final 2.6.18 Rent Control Letter .pdf From: Dianna Mejia[mailto:dmejia@santaanachamber.comj Sent: Tuesday, February 6, 2018 9:48 AM To: Godinez, Raul <RGodinez@santa-ana.org> Cc: Huizar, Maria <MHuizar@santa-ana.org> Subject: Santa Ana Chamber Opposes Rent Control Dear Raul: Attached is our letter to the Mayor and Council members outlining our position on rent control. Regards, Executive Assistant Santa Ana Chamber of Commerce 1631 W. Sunflower Ave., Suite C-35 Santa Ana, CA 92704 (714) 541-5353 ext. 116 February 6, 2018 The Honorable Miguel Pulido Mayor, City of Santa Ana 22 Civic Center Plaza Santa Ana, CA 92701 Re: Santa Ana Chamber Opposes Rent Control; Alternative Rental Housing Policies Dear Mayor Pulido and Council Members: The Santa Ana Chamber of Commerce, which represents more than 500 businesses, educational institutions and nonprofits organizations, has serious concerns regarding rent control or rent stabilization in Santa Ana. Numerous studies indicate that fixing the price of rent does not help solve an affordable housing crisis. Many leading economists agree rent control increases the severity of the housing problem. Rent controls can also lower the quality of life within communities. While rent control may or may not affect the value of existing apartments, it can deter new rental projects when neighboring cities do not have rent control ordinances. If home and apartment values decline, revenue from the county also declines. This would jeopardize the long-term health of schools and city infrastructure such as police, fire, and other important services for residents. The Chamber is supportive of working with the council and city staff to explore ways to increase the supply of affordable housing. The long-term solution is to build and increase the city's housing supply; however, we do recognize there are current challenges between tenants and rental housing owners. Until housing supply catches up to demand, we would like to offer our support and expertise on working with the community, city staff and the City Council on measures that will ease the pressures felt by all members of our community We support the recommendation by the California Apartment Association to establish a Housing Task Force comprised of advocates, businesses, local landlords and others to review and recommend policies to better serve Santa Ana. The Chamber and our members appreciate the city tackling this tough issue and we want to be part of the solution. We look forward to working closely with you, your staff and the community in the coming months to discuss this issue further and identify mutually agreeable solutions to promote attainable and diversified housing options in Santa Ana. Sincerely, David Elliott President Santa Ana Chamber of Commerce 1631 W. Sunflower Ave #C-35, Santa Ana, CA 92704 (714) 541-5353 Mitre -Ramirez, Norma From: Huizar, Maria Sent: Tuesday, February 6, 2018 10:53 AM To: eComment Subject: ECOMMENT - No on rent control From: Castro -Cardenas, Julie Sent: Tuesday, February 6, 2018 8:48 AM To: Huizar, Maria <MHuizar@santa-ana.org> Subject: FW: No on rent control For the record. Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@canto-ano.org 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 Sent: Monday, February 5, 2018 8:07 PM To: City Council <CityCouncil@santa-ana.org> Subject: No on rent control I operate a rental property in Santa Ana. Rent control is a counter productive policy. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. Property owners are the financial backbone of the city. I appreciate the city's efforts, but this is not the solution. Thanks for your support Kurtis Elliott Mitre -Ramirez, Norma From: Sent: Tuesday, February 6, 2018 11:51 AM To: eComment Subject: Fwd: No,Q,n Santa,`Ana Rerit.Coiitrol To Santa Ana City Council for tonite's meeting. Begin forwarded message: > Subject: No on Santa Ana Rent Control Date: February 6, 2018 11:33:26 AM PST To: mgulido@santa-gng.org Our family has owned residential rental property in Santa Ana since the 1940's and maintained our property with fair rental rates. As you know a significant percentage of Santa Ana Residential property is over 50 years old so requires increasing maintenance expense. One way to assure increased blight and associated crime is to disincentivize owners expenditures on maintenance and also totally constipate future new building is thru rent control. It may be that a majority of renter/voters are in favor of rent control, but it is up to the Council to decide what is in the long term best interest of the city. For your consideration, Gene and Judy Opittek Orozco, Norma From: Roberto Herrera <roberto@resilienceoc.org> Sent: Tuesday, February 06, 2018 3:01 PM To: eComment Subject: Tenant Protections Attachments: Tenant Rights Support Letter.pdf Please include this in the minutes for today. February 5th, 2017 WWN.RESI6IENCEP .QRR IRFAORESMINIQU pRA Mayor Miguel Pulido and Councilmembers City of Santa Ana 20 Civic Center Plaza P.O. Box 1988, M31 Santa Ana CA, 92701 RE: Work Study Session on Rent Control/Stabilization - Support Tenant Protections Ordinance cc RUILIERMM The mission of Resilience Orange County is to promote resilient youth leaders that engage in the critical work of building youth -oriented institutions in Orange County. We are a youth oriented institution that works towards social -systemic transformation while promoting healing, trauma -informed and culturally relevant practices that are inclusive of all members of the community. Resilience Orange County supports the efforts by community groups and stakeholders to pass an ordinance that will afford tenants the protections that they need. Santa Ana has a large renter population with 56% of the city's total households serving as rental homes (2017 American Community Survey). We believe that tenants have the right to live in dignified housing; and we need a Tenant Protections Ordinance immediately as Santa Ana tenants live in fear of recurring rent increases and retaliation in the form of unjust evictions. The city's Housing Element illustrates the need for such ordinance for renters, especially our low income residents. `Approximately 54 percent of households earn lower incomes... Renters typically have the highest percentage of very low income households...' (pg A -1o). These low income households have very high rates of rent burden, as they're paying well over 30 percent of their household income on rent. `The eon ACS reports 31,676 households (43 percent) overpaid for housing. of this total, 57 percent were renters (21,496 households)... Housing overpayment is most severe among extremely low and low income households and special needs groups' (pg. A-20). It is important to protect our immigrants, workers, and youth from the traumatic effects that displacement has on our communities. Policies such as Just Cause Evictions have been successfully implemented in jurisdictions throughout California while protecting the rights of tenants and property owners. The City needs to deepen its commitment to working alongside the community in the development process, to ensure that the community's needs are being met and that tenants are being protected. Policies that include Just Cause Evictions, Rent Control, and Rent Stabilization represent a key opportunity to do this. Santa Ana has the opportunity to lead the way and set a high standard for tenant protections in Orange County. Resilience Orange County encourages the City of Santa Ana to establish a workgroup that includes community stakeholders such as: affected residents, non -profits organizations, and community groups that will create a Tenant Protections Ordinance. Sincerely, Roberto Herrera Community Engagement Coordinator Resilience Orange County Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:46 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent control session From: MultilInits Inc[mailto:multiunitsinc@gmail.comj Sent: Tuesday, February 06, 2018 1:04 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent control session Good Afternoon, I saw in Sunday's OC Register of a study session on Rent Control tonight. I want to give you my take on rent control as I've been involved in the rental business in Orange and LA counties since 1981. No doubt Southern California is a highly desirable place to live. I grew up in the Midwest and east coast and chose to move and live here in 1981. Because of this desirability and a shortage of housing units being built for decades, we are experiencing a housing affordability problem here as well as in many markets in the U.S. Rent control will not solve this problem. It will instead exacerbate the problem by reducing the incentive to build and own. Developers, builders, lenders and landlords all place money at risk in real estate to generate a return or profit on their investment. If this return is insufficient, they will all invest in a different type of real estate or area. Most landlords are good people! The landlords who jack up rents that the media refers to are few and far between. Rent control will cause the number of rental units to drop. Don't believe this? Check the trends in SF and other rent -controlled cities. Personally, I have several rental houses and would pull them off the market and sell them if they were under rent control. Rent control defies basic economics. How? Lower rents sound great if you're a current renter, but any price control makes it much more difficult for future renters to find housing. Reducing the profit that developers and landlords receive, compared to market rates, diminishes or eliminates the incentive to build additional housing in the first place. Sure a small number of renters who are lucky enough to obtain below-market apartments will benefit, but many others will not and they will be left with less affordable options than would exist without rent control. In some cases, rent -controlled buildings have been replaced with pricier, and more profitable, types of housing and rentals have been taken off the market or converted to for -sale units. Moreover, rent control diminishes the quality of housing since landlords have less cash flow with which to make upgrades or to keep their units current with the times. Regular maintenance also tends to suffer as landlords have less financial incentive to make timely repairs and improvements. Not to mention there's even less incentive to do so given the excessively high demand for rental units in the market today and probably tomorrow. Rent control has never built a new unit! The real focus in Santa Ana, Orange County and the state should be on increasing supply!! Thank you for your time, I hope I have successfully argued that rent control is bad and should be thwarted! Sincerely, Craig Kirkpatrick Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:49 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Letter Regarding Santa Ana Rent Control Attachments: 2-5-18 - Letter to Santa Ana Regarding Rent Control.pdf From: Paul Julian [mailto:pjulian@advancedonline.com] Sent: Tuesday, February 06, 2018 11:27 AM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown@santa-ana.org> Cc: Richard Julian <rjulian@advancedonline.com>; Frank Holloway <fholloway@advancedonline.com>; Vicki Binford <vbinford@amcliving.com>; Robb Cerruti <rcerruti@advancedonline.com> Subject: Letter Regarding Santa Ana Rent Control Hello Honorable Mayor, Councilmembers, City Manager, & Housing Division Manager; Please find attached a letter we have put together regarding the Rent Control discussion that will take place this evening. As you will see, we firmly believe that adopting rent control would have grave negative consequences for Sant Ana. Thank You, Paul Julian Advanced Real Estate services, Inc 15320 Barranca Pkwy I Sulte 100 I Irvine I CA 192618 0: 949.595.5900 1 M: 949.294.8110 I F: 949 595 5901 aiulian@advancedonline cgm I www advancedonllne com CA Broker Lic #01230527 This communication is confidential and may contain information or material that is proprietary, legally privileged and/or otherwise protected by law (all such rights and protections being expressly reserved hereby). If you have received it in error or if you are not the intended recipient, please immediately notify the sender by return message and permanently delete the message, including any attachments, and destroy any printed copies. Any unauthorized use, copying or dissemination of this communication is strictly prohibited and may be unlawful. Thank you. ARES, Inc. operating under California License # 00881503 C RIAIF.STAiIR 15020 OQrrgnCq Pkwy, Suite 100 Irvine, CA 92618 CA BRE Ucense # 00881503 February 6, 2018 Dear Mayor Pulido and members of the Council, Thank you for the opportunity to discuss the topic of rent control. Since we own nearly 1,400 apartment units in the City of Santa Ana, I feel that we might be able to share an applicable view of the apartment challenges in your City. This information might help you to understand that a rent control initiative could result in grave results that will undermine the positive progress made by your Council to date. The properties in Santa Ana that Advanced partnerships own are: Villa Del Sol (562 units), Park Plaza (242 units), Artists Village (204 units), California Palms (190 units), Villa Del Sur (112 units) and Washington Place (60 units). We have operated many of these properties for over 20 years. I am proud to say that our properties maintain a terrific record relative to maintenance, appearance, safety and resident satisfaction. We are consistently receiving the Gold Seal awards and have also been the recipients of special recognition for our management by different departments of the City including your Council. I welcome you to visit any time to see for yourself how we work hard to supply a quality of living for your citizens who live in our communities. Currently, you are being presented with information from groups who claim that rents are increasing at an unfair rate. You will hear about hardship cases and claims of unscrupulous landlords. I will not argue that there are some unscrupulous landlords just as there are some unscrupulous renters. Some of these renters abuse properties or fail to pay their rent and take advantage of the court system that will often allow them to remain living in an apartment without paying rent for several months. Unfortunately, the costs incurred by this small element negatively effects the costs of operations that are for the benefit (or detriment) of the majority of the people in this equation. Even so, the costs of these exceptions still exist and need to be accounted for by the Landlords. Those who are on the outside looking in, only see the big and obvious numbers and never account for the other expenses that need to considered through reasonable reserves. Fortunately, the majority of owners and renters are fair people who simply wish for an equitable arrangement between the two sides of the property relationship. That is the current case for most of the properties in your City. The system is working reasonably well. I have included some pertinent information as it relates to the properties that we own in Santa Ana. This is the most accurate information that you should consider. Data that is broad and generic is quite often quoted when it helps to build a case. With this included information you have accurate data from one of the largest owners of Apartments in your City. I hope that this helps you. If a rent control law were to be put in place, I am afraid that we could not afford to maintain the high level of quality housing that we currently do at all of our properties. The wonderful direction of bettering your City will move in the opposite direction. When owners can't raise the rent in order to have funds to make repairs, it will eventually lead to run-down, blighted properties in the city - which is the last thing Santa Ana needs. I encourage you to allow us to work with the good folks who are suggesting this action and share both sides of the issue in the hope that they will understand the challenges of the landlord as well as the renter. In the end, I believe that everyone will understand that the average rent increase rate that we have experienced is fair. Further, they will see that the higher rent increases that occur when an old and unsightly property is fully renovated is a fair motivation to fix up old and blighted apartments. I am happy to be on such a committee if you would like. I trust that you will do what is best for your City and reject the idea of entertaining Rent Control. It has been proven in many cases to be the beginning of blight in those Cities. Also, it is a "taking" of value from property owners and a denigration of property rights. When property rights degrade, the value of the community decreases as capital is less motivated to invest. I thank you for your considerations. Respectfully, s Rick Julian President Advances Real Estate Services, Inc. Apartment Communities Owned/Operated by ARES Partnerships in Santa Ana California Palms 190 Units • Converted to apartment complex from hotel in 2008. • Spent over $10,500,000 (over $55,000 per unit) renovating and converting the property. • Average rent increase for last 5 years 5.4% per year • Current Average Rent - $1,359 Villa del Sol • 562 units • Purchased 1994 • Spent $22,000,000 (over $39,000 per unit) renovating property, approximately $10,000,000 over last 5 years • Average rent increase for last 5 years 6.1 % per year • Current Average Rent - $1,621 Villa del Sur • 112 units • Purchased 2001 Spent over $6,000,000 (over $53,000 per unit) renovating the property since 2002, over $2,500,000 over the last 5 years. • Average rent increase for the last 5 years 5.4% per year • Current Average Rent- $1,512 Park Plaza • 242 units Purchased 2004 • Spent over $17,500,000 (over $70,000 per unit) renovating the property since 2004. Over $3,000,000 spent in the last 5 years. • Average rent increase for the last 5 years 4.5% per year Current Average Rent - $2,032 Artists Village • 196 units • Purchased 2009 • Spent over $3,500,000 (approximately $18,000 per unit) since 2010 • Average rent increase for the last 5 years 5.5% per year • Current Average Rent - $1,811 Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:50 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: housing Sent: Tuesday, February 06, 2018 10:54 AM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: housing Dear Mayor Pulido, Santa Ana needs more affordable housing, but rent control is a get us there — it is a bad idea. Where it has been tried elsewhere it has not worked. What does work is: 1. Expand section 8 2. Build more conventional rental housing units 3. Build more affordable and workforce housing Please vote against rent control in Santa Ana. Korey Jorgensen Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:53 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Santa Ana Rent Control Workshop From: Windsor Louie [ Sent: Tuesday, February 06, 2018 9:32 AM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown @santa-ana.org> Subject: Santa Ana Rent Control Workshop To our honorable City Manager, Mayor, Mayor Pro Tem, all Councilmembers & Housing Division Manager : I own rental property in Santa Ana for more than 40 years. My first hand knowledge in rental housing has confirmed the fact that "rent control", like any other price control, would have a far reaching negative impact on the housing industry and all other supporting industries as well. The "Supply & Demand" principle is the best way to regulate pricing without placing an artificial cap. Time and again, past experiences have shown that rent control would only lead to dilapidated housing conditions, decrease in housing supply and failure in meeting immediate and future housing needs. There are other ways to ease the housing supply situation and I would suggest the following in concepts to think about : 1. Set up programs to encourage investors/developers to convert City's vacant properties (or some dilapidated properties) into multifamily housing. 2. Selectively rezone areas to R-3 with higher density and less red -tape to get permit. It has to be a fast track program with minimum paper work to expedite housing production. The City and the developer have to work together to meet the funding needs and to satisfy City's new guidelines. 3. Tenants under these City programs should be chosen based on their ability to share the cost and a strong willingness to show -case their community as a "proud place to call home". This should not be free-bie program because all tenants have to take responsibility to work towards a common goal ---- that is to create an attractive living environment and not an instant slum. The above concepts shall be based on projected population growth, and bear in mind that most programs are not perfect and need to be adjusted, from time to time, to meet challenges. Decision on housing issues shall be based on sound economic principles, supply & demand, common sense, historic precedence and not over hyped sentiment. Respectfully, Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:54 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent control From: Donna Robbins [ Sent: Tuesday, February 06, 2018 9:12 AM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent control ATTN: Mayor Miguel Pulido Our city needs more housing and better housing, limiting profits on property ownership is not the answer. More Section 8 housing, More basic rental housing, More affordable new housing for the regular guy is needed. Please vote against any control of existing housings, so that the people who own and develop property will have an incentive to contribute to solve that problem. Without that freedom, property owners will only have the options of converting apartment buildings to co-op apartments for sale, and condos for sale, air B&B rooms to rent to tourists, and renters will sublet their rent controlled apartments to other people and skim the profits from the property owners and developers, as is happening now in Santa Monica, Oakland, San Francisco and West Hollywood. Thank you, Donna Robbins Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:54 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control Problems Attachments: Santa Ana Message.docx From: Jay Kremer [ Sent: Tuesday, February 06, 2018 9:OS AM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org> Cc: lou@aaoc.com Subject: Rent Control Problems To Santa Ana City Council; The attached memo gives some of the problems created in a city using rent control. Numerous economoc studies have verified these results. The titles and sources of these studies can be provided. The answer to problems of increasing rents is the construction of new rental housing that will stabilize or lower rents and will improve the status of rental units in your city. Rent control will substantially discourage this solution for investors. You are encouraged to avoid the downward spiral caused by rental control for your city. I am Jay Kremer, an owner of rental units in Orange Co. and a member of the Apartment Assoc. of Orange Co. Jay Kremer To: Santa Ana Council Members, Re: Rent Control Results The unintended results of rent control have resulted in negative impacts on the cities using it: 1. Rental property owners cannot afford to maintain the units so rental property will become run-down. Over time the city will also become a run-down city. 2. Owners will change the rental property to condominiums or to commercial property eliminating the rental units. 3. Number of available rental units will decrease in the city. 4. Homelessness numbers in the city will increase. 5. Persons taking rent control properties will increasingly be high income persons not low-income families. 6. Great differences between rent control and non -rent control properties will develop. Non -rent control units will be much higher in price than would be found in a normal rental market. Numerous studies by universities and economic experts have verified the above results. In many economics books, rent control is given as the prime example of unintended consequences of a law. The cure for increasing rents is the building of numbers of new homes and rental units. Rental unit owners will tell you that there were several recent years where rents could not be raised as there were too many vacant rental units. Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:54 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: no rent control, please From: Gina Laroff [ Sent: Tuesday, February 06, 2018 8:25 AM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: no rent control, please Rent control is bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Keep it out of Orange County and keep it out of Santa Ana! 1 Orono, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:56 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: workshop on rent control From: Dick [mailto: Sent: Monday, February 05, 2018 10:41 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; jsolorio@sana- ana.org; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa-ana.org>; Brown, Judson <JBrown @santa-ana.org> Subject: workshop on rent control Mayor, May Pro Tem, Councilmembers, City Manager and Housing Division Manager --- I am 87 years old and I am physically unable to attend the meeting tomorrow night. I am a small apartment owner living in Orange County for 43 years. Please compare the experience of other cities using rent controlled buildings and see the problems it produces; poorly maintained rentals and literally no upgrades, reduced sales and property tax revenue (I can tell you as a small property owner, I would NEVER buy a property under rent control and neither would most of other people I know in the business); it will reduce new residential housing starts which directly contravenes the desperate need to increase housing inventory, particularly low income housing; the answer is not rent control but rather more low income housing and expanding the Section 8 housing program; there are many many cases where rentals, in a rent controlled area, are swallowed up by higher income people, who don't need help with the rent, AND they never turn over the property because of the cheap rent (Santa Monica is a good example). Rent control is bad for business and bad for development. It is not a "PLAN" but rather a knee jerk reaction to the problem of trying to solve the need for more affordable housing. Rent Control does not work! I implore you to not make the mistakes other cities have, of trying to use rent control, which will not solve the problem you have, only create more. Thank you for your attention in this matter. Dick Mackaig Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:56 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control in Santa Ana From: Pamela Mundy[mailto: Sent: Monday, February 05, 2018 8:50 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown@santa-ana.org> Subject: Rent Control in Santa Ana Dear City Staff and Council, Rent control is bad business, bad for develpment and bad for Santa Ana. Please take a hard look at bringing rent control to Santa Ana. This does not help our communities. This will lead to neglected properties and developers hesitating to build badly needed housing stock. This discussion will have a significant repercussions on the housing climate, notjust in Santa Ana, but across Orange County. Take a close look at high housing costs in LA, New York and Santa Monica to name a few. Don't let this happen in Orange County and start with keeping it out of Santa Ana. Santa Ana needs a true public/private partnership to address the housing crisis and that starts with: • Building more affordable and workforce housing. • Expanding the section 8 housing program • Build more conventional rental housing units. Again, bringing rent control to Santa Ana will lead to unkept rental housing, decrease housing inventory, and this policy FAILS to plan for immediate and future needs. Rent control is a bad plan and the wrong vote for Santa Ana's future. Respectfully, Pamela Mundy Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:56 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Santa Ana Rent control From: Jan Hammon [mailto: Sent: Monday, February 05, 2018 8:15 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; jvillagas@santa-ana.org; Godinez, Raul <RGodinez@santa-ana.org>; slinajero@santa- ana.org Subject: Santa Ana Rent control My husband and I own 2 4-plexes in Orange County. What are you thinking to even think about rent control. You need to plan for the future and take care of the population and this will not work for rent control. I hope you will rethink whatever has prompted you to consider this measure. Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:58 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control Comments From: Leslie Manderscheid [mailto: Sent: Monday, February 05, 2018 6:50 PM Subject: Rent Control Comments Dear Mayor, City Council Members and Staff: Rent control is not a healthy alternative for improving the housing crisis in Santa Ana nor anywhere in Orange County. I was born in Santa Ana and still live and own property in OC. Your discussion and any actions will have significant repercussions on the housing climate not just in Santa Ana, but across Orange County. Santa Ana needs a true public/private partnership to address the housing crisis and that starts with: Building more affordable and workforce housing; Expanding the Section 8 housing program; and Building more conventional rental housing units Instituting rent control only leads to dilapidated and decreased housing stock and fails to plan for immediate and future needs. Rent control is a bad plan and the wrong vote for Santa Ana's future! Concerned property owner, Leslie Manderscheid Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:58 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent control is bad for business and bad for housing From: btonelli [mailto: Sent: Monday, February 05, 2018 6:49 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent control is bad for business and bad for housing Rent control is bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Keep it out of Orange County and keep it out of Santa Ana! Warmest regards, Dr. Barbara -Leigh Tonelli Sent from my Verizon 4G LTE smanphone Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:58 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control From: Ralph [mailto: Sent: Monday, February 05, 2018 6:43 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent Control Dear Sir, I am long term apartment owner in Santa Ana. We want the best for the city and our residents. Rent control is bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Keep it out of Orange County and keep it out of Santa Anal Sincerely Ralph Siemion Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:59 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: NO RENT CONTROL From: Architopia [mailto: Sent: Monday, February 05, 2018 6:01 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: NO RENT CONTROL I OWN A TRI-PLEX AND FIND EXPENSEES KEEP GOING UP EVERY YEAR; TAX, CITY FEES, GARDENING, UTILITY BILLS, MORTGAGE AND GENERAL UPKEEP OF BUILDING. IT TAKES TIME AND MONEY IN ORDER TO PROVIDE A CLEAN, COMFURTABLE AND SAFE HOME FOR PEOPLE TO RENT. WITH THE PROPER BACKING OF THE CITY WE WILL CONTINUE PROVIDING A POSITVE SERVICE TO OUR COMUNIY. Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 2:59 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent control study From: Richard Scudamore [mailto: Sent: Monday, February 05, 2018 5:17 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent control study Dear Mayor Pulido, I am a rental property owner in Orange Co. with many Section 8 tenants. I would urge you to study the expansion of the Section 8 program before you consider rent control which I feel is bad for business and will constrict the housing stock. Thank you for taking the time to read this. Sincerely, Richard A. Scudamore Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:00 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent control discussion -----Original Message ----- From: Alan Wagner [ Sent: Monday, February 05, 2018 4:17 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Fwd: Rent control discussion Dear Mr. Mayor Miguel >>> Our city needs more housing and better housing, limiting profits on property ownership is not the answer. >>> More Section 8 housing, More basic rental housing, More affordable new housing for the regular guy is needed. Please vote against any control of existing housings, so that the people who own and develop property will have an incentive to contribute to solve that problem. Without that freedom, property owners will only have the options of converting apartment buildings to co-op apartments for sale, and condos for sale, air B&B rooms to rent to tourists, and renters will sublet their rent controlled apartments to other people and skim the profits from the property owners and developers, as is happening now in Santa Monica, Oakland, San Francisco and West Hollywood. >>> Alan Wagner Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:02 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Fair Housing From: Liz Matthews [mailto: Sent: Monday, February 05, 2018 4:12 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Fair Housing I don't understand how you can stand with fair housing and rent controlled areas. What a sad state that we have become with this. Though I am in the lower middle class, I fear that all my housing choices that I can pick from might be rent controlled and set, which creates a lack of work ethic, a lack of ownership (even for a rental) and a lack of actually giving a crap. I have three small girls (5, 8, and 10). I don't live in the best part of town right now, but I know that if the areas around me become rent controlled, I will have to leave. I want a neighborhood for my children to ride bikes, to play, to be actual children, without the fear of what this decision might create for them. As I said, we already do not live in a great neighborhood; my pastor husband works for an air compressor shop and I work full time at a property management company. Though both of our incomes barely make life survivable for us, we only depend on ourselves, and work very hard to live where we do. If people were invited to live in our area without the means, without the care, with the "handout", my children's only option will be to play inside. When we moved to Fullerton, almost 8 years ago, my middle child was very young, and yet to start school. Once she was allowed to be in elementary, our district school was a mess due to all of the low income housing around us. We put her in our district school, hoping to make friends, and build her education.... all we found was fear, racism against my child, and judgement. How dare that because of this reform that my white child fear for herself, be bullied and discriminated against for being Caucasian AS A SIX YEAR OLD!!!!! Don't tell me that "minorities have it rough", my giant hearted child has NEVER looked at color, has NEVER cared of economic status, has NEVER care where someone has come from, and was being what she knew, loving, caring, and open hearted. Fast forward a couple of years; we are still in the same house, certain areas around us in Anaheim have become rent controlled, and the area has taken a dump and is shaken. I feel that I deserve the right of anyone who is working full time, taking care of my kids, and doing what is right in those situations (I don't get my nails done so my children can play softball; I don't get to eat out because I might have to buy a ticket to one of their shows at school). I make too much for the government to take care of me. So if someone moves in next to me that the government will take care of, sit at home, with Cheetos, beautiful mani and pedi, do you think that bodes well for not only my self esteem, but what about what the next generation will think? How dare anyone think that they can be taken care of without some sort of "give". I often say how my husband and I should get a divorce so we could live for free, free healthcare, and groceries! ! ! ! What a crock?! And now you want to bring all these people into my neighborhood to teach them not to work but to sit and be taken care of?! How will this be an example for the lives ahead of us?! How can this "rent control" idea benefit anyone from teaching people how to live and act in society?! Oh, I'm sorry, you don't like the president? Suck it up and be an adult and grow. Go to work, make money, live in somewhere you can afford. I work my ass off to live where I do, and if I had the opportunity to do/make more, I would to make a better place for my family. I don't as for anything for free, but if my new neighbor is given more rights than me just because they make less than me, you better believe I'm going to stand up for my own rights!! ! I'm the one paying taxes and supporting local businesses.... with little money I have. I'm also not the one to be at the store purchasing Cheetos and soda with a WIC card. Please, I beg, support my family. My lower class, working family, who fights every single day to survive. Warm Regards, Liz Matthews Liz C. Notary Public jjj/ `/ j The ..Day walker, crew, and supporter. Finding a cure for breast cancer one mile, blister, and step at a time. Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:02 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: NO on Rent Control From: TEMPLE STRATTON [mailto:templestratton@yahoo.com] Sent: Monday, February 05, 2018 3:47 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: NO on Rent Control PLEASE VOTE NO on RENT CONTROL! Santa Ana needs a true public/private partnership to address the housing crisis and that starts with: • Building more affordable and workforce housing • Expanding the Section 8 housing program • Building more conventional rental housing units Rent control only leads to dilapidated and decreased housing stock and FAILS to plan for immediate and future needs. Rent control is a bad plan and the wrong vote for Santa Ana's future! Thank You, Temple Stratton, Realtor TNG Real Estate Consultants Cell: 714-402-1325 Fax: 714-203-8556 Website: www.temolestrattanhomes.com License # 01438349 Since 2004 Selling Or Buying? FREE Consultations. Call Today! 1 Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:03 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control From: Chuck Fry [mailto:cfry@vistacommunities.com] Sent: Monday, February 05, 2018 3:32 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown@santa-ana.org>; info@aaoc.com; Tony Maggi <tony@mpmsinc.com> Subject: Rent Control Please watch this information and education short video on why rent control is not the answer to housing problems. Nicole Gelinas of the Manhattan Institute gives important arguments to consider. My company, Vista Communities develops affordable housing here is Southern California and has worked closely for state, federal and local agencies to preserve and improve affordable housing stock. I'd be happy to answer any questions that you may have https://wwwyoutube.com/watch?time continW@m91gy qlyrTFkU Chuck Fry Vista Communities, Inc. 14 Corporate Plaza Dr., Suite 100 Newport Beach, CA 92660 T: 949.474.1345 F: 949.313.0994 C: 949.244.5075 Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:03 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: No rent control in Santa Ana From: Conrad Wyszomirski [mailto: Sent: Monday, February 05, 2018 2:45 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: No rent control in Santa Ana Rent control is bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Keep it out of Orange County and keep it out of Santa Ana. Conrad Wyszomirski Orange County Apartment Association 1 Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:03 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: "No" on Rent Control / Santa Ana From: Bridget Catalano [ma iIto: Sent: Monday, February 05, 2018 2:31 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown@santa-ana.org> Subject: "No" on Rent Control / Santa Ana To Whoever It May Concern: Concerning the recent proposed hearing on rent control in Santa Ana, California, the owners of both The Monterey Santa Ana Apartments, as well as the property management company that maintains the property, we express our disapproval of rent control no matter where it is proposed. Studies have been conclusive that in order to maintain the integrity, safety, and value of properties, and that includes what tenants call "home," rent control has no business interfering with business, jobs, and development in Santa Ana. The more responsible and long-lasting solution is to build more affordable workforce housing, Section 8, and more affordable conventional rental housing units. Through parts of California where rent control has been put into play, buildings, business, and tenants have suffered as the properties are adversely affected. Therefore, we strongly oppose rent control in any form and maintain that other more long-term housing plans be pursued. Sincerely, Western Consolidated Equities, (714)630-3580 Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:04 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control From: Bruce Williams [mailto: Sent: Monday, February 05, 2018 1:16 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent Control Your Honor, Please vote no on rent control. It's bad for business and development. Thank you, Bruce Williams Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:05 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control - Santa Ana From: Debra Brown [mailto:debra@bowers-properties.comj Sent: Monday, February 05, 2018 12:43 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown@santa-ana.org> Subject: Rent Control - Santa Ana 91 Rent Control is bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Please keep Rent Control out of Orange County and keep it out of Santa Ana! Thank You! Debra Brown Director of Property Management BOWERS PROPERTIES, INC. 1001 Dove Street, Suite 106 Newport Beach, CA 92660 Direct: 949.296.0722 Office Main: 949.660.9044 Office Fax: 949.863.1688 Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:05 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Keep Rent Control out of Orange County From: Barbara [mailto: Sent: Monday, February 05, 2018 12:30 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown@santa-ana.org> Subject: Keep Rent Control out of Orange County Monday. February, 5, 2018 Ms. Martinez and Gentlemen: Geographic area determines the cost of living pretty much everywhere in the world. Sometimes it doesn't seem fair and/or reasonable. However, healthy business activity in the rental market is good for all by elevating the quality and supply of rental units at all price points. When business is overly controlled by government, there is a strong potential for unintended negative effects. Business owners, as in the case of rental property owners, will simply not build or not maintain their units at the optimal level most tenants would want, due to lower profits and less incentive. Regular maintenance and unforeseen repairs, etc. are expensive and the money to pay for them comes right out of the rent revenue. If there isn't adequate revenue, guess what, needed repairs get postponed and/or take longer. We have owned a few units in Orange County since the mid-70s. We have worked very hard to provide decent affordable units for our tenants and hope that we will be able to do so for the foreseeable future. Consider other options to rent control: 1. Encourage the building of more affordable and workforce housing 2. Support more conventional rental housing units in general by enhancing and streamlining the business climate in which builders must function. 3. Fight to keep property taxes less burdensome on us smaller rental property owners. 4. Support children and families with strong public schools. ( I know that's not your purview, but your moral support in many practical ways, is so important.) 5. Thank you for your strong law enforcement in Santa Ana. It makes a difference in the lives of so many people who are renters here. B. Arranaga-Foster, Santa Ana (We are a married couple: retired U.S. Navy Captain and former School Teacher/Freelance Writer/Community Volunteer) Rental Property Owners Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:05 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: rent control is bad!!!! From: Rod Kossack [mailto: Sent: Monday, February 05, 2018 12:26 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: rent control is bad!!!! Rent control is bad for the city for numerous reasons.. Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:06 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Santa Ana rent control -----Original Message ----- From: Marie [mailto: Sent: Monday, February 05, 2018 12:17 PM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Godinez, Raul <RGodinez@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; Godinez, Raul <RGodinez@santa-ana.org>; Godinez, Raul <RGodinez@santa- ana.org>; Brown, Judson <JBrown @santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <1Solorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Benavides, David <DBenavides@santa- ana.org> Subject: Santa Ana rent control Rent control has proven bad for other cities in California - why bring the booming economy in Santa Ana come to a halt with rent control. Other solutions might work but establishing rent control would defeat the purpose. Rent will soon go through the roof in anticipation. Thank you for your support in not voting for this bad "rent control' thought. Marie Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:06 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: RENT CONTROL From: Lorraine [mailto: Sent: Monday, February 05, 2018 12:00 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: RENT CONTROL Santa Ana needs a true public/private partnership to address the housing crisis and that starts with: • Building more affordable and workforce housing • Expanding the Section 8 housing program • Building more conventional rental housing units Instituting rent control only leads to dilapidated and decreased housing stock and FAILS to plan for immediate and future needs. Rent control is a bad plan and the wrong vote for Santa Ana's future! Rent control is bad for business and bad for housing and has driven housing costs sky high in Santa Monica, Oakland, San Francisco, Los Angeles, New York and West Hollywood. Keep it out of Orange County and keep it out of Santa Anal If you want average people like me to continue to buy and manage rental properties (I have 2 4 -family Bldgs in Santa Ana, 1 of which I bought and 1 I inherited from parents), then you need to forget about Rent Control. It will put me under! I do not charge exhorbitant rents, I honor the tenants who stay with me longer by keeping their rent increases minimal. I didn't increase rents for over 7 years. But if you institute rent control, I will sell my properties there and buy elsewhere, preferably out of California! Rent Control is a ridiculous idea for Santa Ana. We are not scalping the tenants. But if you drive the little guys like me out of the rental business, you'll be left with the big guys and corporations who don't give a darn about your city, the tenants, or maintaining the properties for the future of your city. You will be creating a true Mess Please don't do this to us. We love our small properties, we treat our tenants well, and we don't want to be driven out. Thank you for your consideration. K Orozco, Norma From: Houston, Nicole Sent: Tuesday, February 06, 2018 3:06 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: Rent Control Workshop From: Amber [mailto:amber@hallandassociatesinc.comj Sent: Monday, February 05, 2018 11:59 AM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: Rent Control Workshop Good Afternoon Mayor, It has been brought to the attention of myself and my clients that a rent control workshop will be held tomorrow night in Santa Ana. As a business owner, landlord, and realtor I implore you to consider the unintended negative effects rent control has had on other cities that have implemented it. Housing costs in rent control areas like San Francisco, West Hollywood, LA and New York are astronomical. Rent control has done nothing to drive housing costs down in those areas. Please consider some other solutions to our housing problem like expanding the Section 8 housing program & construction of more affordable work force housing. Thank you, Amber Hall Broker BRE#01370874 Hall and Associates, Inc. "Turning your dreams into Realty" (949)-496-5200 amber@hallandassociatesinc.com Mitre -Ramirez, Norma From: Sent: To: Subject: FYI Best Regards, Julie Castro -Cardenas Senior Management Assistant (714)647-5263 City Manage's Office City of Santa Ana Castro -Cardenas, Julie Tuesday, February 6, 2018 1:55 PM Mitre -Ramirez, Norma; Rojano, Michael FW: Rent Control From: Jerry McLane [mailto:Jerry@iassetmgmt.com] Sent: Tuesday, February 6, 2018 12:23 PM To: City Council <CityCouncil@santa-ana.org> Subject: Rent Control Dear Mayor Pulido and City Council, I operate rental property in Santa Ana and am proud to provide quality, safe housing for people of all income levels. As an active stakeholder in your community, I support the city's goal to improve the quantity, diversity, and affordability of housing. However, this cannot be achieved through studying or adopting rent control (aka rent stabilization) and just cause eviction Rent control is a counterproductive policy. It will not produce any new affordable housing or address the city's long-term housing concerns. If adopted, it creates a stagnant market and increases the cost of housing for everyone else. Worse, the unintended consequences are long-term and will eventually deteriorate the condition of housing since rent control often times prevents the owner in making capital improvements on the property. Instead, I urge you to expand the city's efforts to produce more housing and promote available resources and programs for the city's renters. I ask that you focus on these goals and look for ways to partner with the community to ensure renters are aware of resources available to them and educate rental owners on fair and ethical management practices. appreciate the city's collaborative approach to provide meaningful, long- :rm solutions to our region's housing challenges. Thank you for your ontinued leadership on this important issue. Sincerely, Jerry McLane Jerry McLane Alcala, Abigail From: Houston, Nicole Sent: Tuesday, February 6, 2018 4:23 PM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: no to rent control From: Shirley Laroff [mailto: Sent: Tuesday, February 06, 2018 3:15 PM To: Pulido, Miguel <MPulido@santa-ana.org> Subject: no to rent control Dear Mayor Pulido, Rent control is bad for business, bad for development and bad for Santa Ana. Sincerely, Shirley Laroff 1 Alcala, Abigail From: Castro -Cardenas, Julie Sent: Tuesday, February 6, 2018 7:33 PM To: Huizar, Maria; Mitre -Ramirez, Norma; Rojano, Michael Subject: FW: No to rent stabilization FYI Respectfully, Julie Castro -Cardenas Liaison for Mayor & Council Senior Management Assistant City Manager's Office I icastro-cardenas@santa-ana.orq 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 92701 From: Farhad G. Nikon [mailto: Sent: Tuesday, February 6, 2018 6:03 PM To: City Council <CityCouncil@santa-ana.org> Subject: No to rent stabilization Dear Mayor Pulido and City Council, I don't think rent control will solve any problem except producing poor quality rental properties and reducing number of available properties since no one will be investing in rental properties anymore. Rent control is a counterproductive policy and will not produce any new affordable housing Sincerely, Rarhad Nilcoo 1 Mitre -Ramirez, Norma From: Sent: To: Subject: Attachments: Importance: For the record. Respectfully, Julie Castro -Cardenas Castro -Cardenas, Julie Monday, February 5, 2018 11:25 AM Huizar, Maria FW: February 6th, 2018: Rent Control Workshop copier@aaoc.com20180131_142849.pdf; Sacramento State Report.pdf; harvard,jchs_americas rental housing 2017.pdf; EffectsofRentControlExpansiononTenantsLandlordsandlnequalityEvidencefromSanFranci sco.pdf High Liaison for Mayor & Council Senior Managemeni Assistant City Manager's Office I icastro-cardenas@santa-ana.org 714.673-3619 mobile 120 Civic Center Plaza, Santa Ana, CA 42701 From: Nicholas A. Dunlap [mailto: Sent: Monday, February 5, 2018 11:04 AM To: Pulido, Miguel <MPulido@santa-ana.org>; Sarmiento, Vicente <VSarmiento@santa-ana.org>; Martinez, Michele <MiMartinez@santa-ana.org>; Solorio, Jose <JSolorio@santa-ana.org>; Benavides, David <DBenavides@santa-ana.org>; Villegas, Juan <JVillegas@santa-ana.org>; Tinajero, Sal <STinajero@santa-ana.org>; City Council <CityCouncil@santa- ana.org> Cc: Lou Penrose <Lou@aaoc.com>; Godinez, Raul <RGodinez@santa-ana.org>; Brown, Judson <J Brown @santa-ana.org> Subject: February 6th, 2018: Rent Control Workshop Importance: High Dear Mayor and Council Members: Please find attached to this email our official letter and supporting.doeumentation in�support of affordable:housing solutions and in opposition to the exploration of rent control. We look forward to participating in a continued discussion and solution to the housing needs of the City of Santa Ana. Sincerely, Nicholas Dunlap Vice President, Legislative Committee Immediate Past President Apartment Association of Orange County 525 Cabrillo Park Drive, Suite 125 Santa Ana, CA 92701-5076 (714) 245-9500 Fax (714) 245-9505 www.AAOC.com February 111, 2018 Honorable Mayor and Councilmembers City of Santa Ana 22 Civic Center Plaza Santa Ana, CA. 92701 RE: February 61h, 2018—City Council Workshop Exploration of Rent Stabilization Dear Mayor and Councilmembers: Since 1994, the Apartment Association of Orange County has had a strong working relationship with the City of Santa Ana. By forming the Gold Seal Program, we were able to create the ideal model for monitoring quality rental housing within the city and helping to ensure that rental units were properly maintained and preserved for future use. Many of the repairs requested or required of apartment owners were outside of code and instituted simply because those who participated were consumed with being good corporate citizens. Through our membership network, we represent more than 25% of the rental housing stock in the city. Not only do we see ourselves as stakeholders in Santa Ana, we see ourselves as true partners with the city. As such, we were surprised to learn of the city's intent to explore rent control as a solution to housing affordability. We are writing today to go on the record opposing rent stabilization In the City of Santa Ana as this will have significant repercussions on the housing market both within and outside of city limits. Established in 1961, the Apartment Association of Orange County is a non-profit trade association and the original trade association serving the apartment industry in Orange County. We are proud to support policies and legislation that support the rental housing industry, improve or enhance economic development and help to create jobs. The health of the housing market and specifically the rental sector is our number one focus and concern. In times where affordability becomes an issue, we must explore and pursue solutions that create options and results. Unfortunately, and as proven in Berkeley, Oakland, San Francisco, West Hollywood, Santa Monica, Los Angeles and New York, rent stabilization fails to improve or enhance the availability of affordable housing stock and instead makes housing more expensive. Additionally, rent stabilization is a deterrent to new development and stifles economic growth and advancement not just for the present, but for the future. Workshops such as this one are a distraction and tend to remove focus from progress or potential solutions. Proven, more productive alternatives to the rent control discussion include: Expansion of the Section 8 voucher program with existing owner/operators. Delivery of additional purpose-built workforce and affordable rental housing stock. Delivery of additional conventional rental housing stock. Page 1 of 4 A non-profit organization serving the rental housing industry since 1961 Attached and included as a supplement to this letter are several reports on the rental housing market and more specifically the Impact of rent control. While I encourage you to review the data and utilize it In the course of your research, we have summarized some of the key points for you below. America's Rental Housing 2017 — December 2017; Joint Center for Housing Studies of Harvard University ■ Slowdown in rent growth has occurred in markets across the country, but is most evident in metros where multifamily construction had been the strongest. • Vacancy rates are up over the past year In 94 of the 100 metros tracked by industry research house Realpage. ■ The need for housing assistance continues to grow. From 2001 to 2015, HUD's Worst Case Housing Needs 2017 Report to Congress shows that in a time where 600k more people received rental assistance, the number of people needing assistance exceeded 4.3 million. • Subsidized housing is at risk of loss either due to under -maintenance or expiring affordability periods. Public housing is particularly under threat, with a backlog of repairs in excess of $26 billion dollars as of 2010. • Rental housing demand has grown at an unprecedented pace over the last decade. This surge in rental households replaced a decade where rental housing saw decreased demand (94.04). • This decade has seen an increase in high earning renters, also known as renters by choice. Households age 50 and over accounted for more than half of the recent surge in renters. • Although rental trends and rates vary, 2017 saw the third consecutive year over year decline in growth rates from 5.6% in 2015 to 4.7% in 2016 and now 2.7% in 2017. This growth has allowed property owners to reinvest in their units, as discretionary spending or capital expenditures increased by more than 10% or $1,486 per unit over that timeframe. • Growth in renter incomes has outpaced the rise in housing casts since 2011 in all income quartlles. The Effects of Rent Control Expansion on Tenants, Landlords and Inequality: Evidence from San Francisco—October 2017; Rebecca Diamond, Tim McQuade and Franklin Qian at Stanford University • Rent control spurs high-end new development and owner -occupied housing that likely fueled the gentrification of San Francisco as these housing types cater mostly to higher income individuals. • From 1995 to 2012, the per person benefit to residents of rent controlled buildings was between $2,300 and $6,600 each year, with aggregate benefits of more than $393 million dollars annually. Substantial welfare losses due to decreased housing supply could be mitigated if insurance against large rent increases was provided as a form of government social insurance, instead of as a regulated mandate on landlords. Page 2 of 4 • A 6% decrease in housing supply led to a 7% Increase in rental prices, causing an aggregate welfare loss to renters of $5 billion dollars. The Increased rents are the result of a decreased supply of housing. • Landlords are found to respond to rent control by converting their properties to condos, TICS or by redeveloping their buildings in such a way that it becomes exempt from rent control restrictions. In doing so, supply was decreased by an additional 15%. • Since 1994, tenants of rent controlled buildings received over $7.1 billion in benefits, mostly the results of being bought out or paid to leave. The losses to renters are in excess of $5 billion as the result of rent control's impact on decreased housing supply, failure to build and the subsequent increase in market rental rates. These results highlight that forcing landlords to provide social insurance against rent increases leads to large losses to tenants over time. • If society desires to provide social insurance against rent Increases, it would be more desirable to offer this subsidy in the form of a government subsidy or tax credit. This would remove the landlords' incentives to decrease housing supply and provide each household with the Insurance they desire. Yup, Rent Control Does More Harm Than Good —January 2018; Noah Smith, Assistant Professor at Stony Brook University and Columnist at Bloomberg (A Summary of the Stanford Study) ■ Assar Lindbeck, a Swedish economist who chaired the Nobel prize committee for many years, once reportedly declared that rent control is "the best way to destroy a city, other than bombing." How Rent Control Drives Out Affordable Housing — May 1997; William Tucker of the CATO Institute • Standard supply and demand theory predicts that any price controls, Including rent control, will produce an excess of demand over supply — resulting in an economic "shortage". These is virtually no disagreement on this premise. • In a survey, 75 leading economists, JR Kearl and his colleagues found that "a ceiling on rents will reduce the quality and quantity of housing". • Rent or price controls rarely work in a straightforward fashion as it is virtually impossible for a government to control and regulate the entire supply of a commodity. Once a shortage appears, alternative markets and black markets will arise. The government can react and criminalize or prosecute these markets, though extreme enforcement will result in an additional decrease in the availability of suitable, rentable housing stock. • Prices get pushed too low in the regulated sector; they Increase in the unregulated sector and as a result, they are forced higher and tend to end up about as a high as their otherwise free- market levels. • Rent controlled apartments are "hoarded" and creates the perception of a housing crisis in rent - controlled cities. Page 3 of 4 ■ Cities such as Dallas, Houston or Phoenix, where development is welcome, have often had vacancy rates above 8%. In these areas, there is a surplus of housing as opposed to a shortage. Landlords commonly advertise move -in specials, incentives and promotions with reduced rental rates. In markets such as New York, Oakland, San Francisco or Santa Monica, the vacancy rate is less than 3% and these specials or incentives are non-existent. ■ Providing housing is perceived by some as an illegitimate enterprise. Landlords are painted as "greedy" enemies of the public in rent -controlled jurisdictions. Rent Control Issues and Impacts —June 1994; School of Business Administration, California State University Sacramento Both Berkeley and Santa Monica lost rental housing units while their reference counties added housing stock, both single-family and multi -family structures of five or more units. • Both Berkeley and Santa Monica showed declines in renter -occupied rooms where as their reference counties saw an increase in renter -occupied rooms. • Rent ordinances may cause a blas against certain age groups as the data indicates family composition may be affected as the number of persons in their early child-bearing years is declining in both cities. The same can be said for the elderly population that is barely increasing In both of these cities and rapidly increasing in their reference counties. ■ The comparisons indicate that rent control ordinances offer a benefit to some renters, but it is not clear to whom they are intended. • Gentrification is the opposite of what the Berkeley and Santa Monica ordinances sought to achieve, but it is rapidly occurring in both cities. The data shows that the rent control ordinances do not meet their stated goals. The Apartment Association of Orange County welcomes the opportunity to participate in a thoughtful discussion and to help create and adopt policies that will lead to solutions. We thank you for your consideration and trust that your leadership will help Santa Ana continue on a path of progress and prosperity that always carries with it the fine culture and history that make the city special and unique. ncerely, 1 colas A. D n p Lou Penrose Vice President, Legislative Co mittee Executive Director Immediate Past President Page 4 of 4 Presented to: California Apartment Association (CAA) 1414 K Street, Suite 610 Sacramento, CA 95814.2439 9161447-7881 Prepared by: REAL ESTATE & LAND USE INSTITUTE SCHOOL OF BUSINESS ADMINISTRATION CALIFORNIA STATE UNIVERSITY, SACRAMENTO 7759 College Town Drive, Suite 102 Sacramento, CA 95826.2344 9161278-6633 1 Juno 1994 EXECUTIVE SUMMARY The objective of this project is to review the impact of restrictive rent control on several population and housing Issues; to compare objectives with results. The study concentrates on cities with restrictive rent control, because It is in these cities that the intent of the ordinances may not meet their intended goals. The 1980 and 1990 Census were compared to ascertain the percent change between Berkeley and 'a reference county, Alameda; and Santa Monica, and its reference county, Los Angeles. The results indicate that. • Both Berkeley and Santa Monica lost rental housing units (single-family detached and single-family attached units) while their reference counties added to their rental housing stock. Both cities lost structures with five or more units, while their reference counties gained this type of housing structure, • Both Berkeley and Santa Monica showed declines in renter -occupied rooms while their reference counties gained<renter-occupled rooms, Both cities and both counties gained owner -occupied rooms.; • Pent ordinances may cause biases against certain age groups. The data indicate that family composition may be affected as t}se:number ofpersons in their early child- bearing years is declining in both cities. Also, despite the rapidly aging society, the elderly population is either declining or barely increasing in both of these cities, while in their counties, the elderly population Is increasing rapidly, • Both cities saw declines in the percent of the population that rented. The greatest declines were among White renters. While the proportion of Hispanic renters increased for the subject and reference areas, that proportion did not increase as fast in the two cities as in their counties. • Overall, lower income renters declined in both cities., In Berkeley, the declines were greater. Although the proportion of lower income renters increased in Santa Monica, the Increase did not keep pace with the county increase. • The comparisons indicate that rent control ordinances offer a benefit to some renters; but It is not clear that the groups for whom the benefits were intended are the actual recipients. • Gentrification (that is, the displacement of lower economic and educational status renters by higher economic and educational status owners) is the opposite of what the rent control ordinances seek to achieve, but is occurring to both cities. The two restrictive rent control cities have become increasingly inhabited by higher -income; higher -educated home owners since rent control The data show that the restrictive rent control ordinances in Berkeley and Santa Monica do not meet their stated goals. Instead, the groups for whom the ordinances were written appear to be the least likely to receive the benefits, and appear to be leaving, these two cities to find rental housing elsewhere. rho Ofifor"h State Uns` MOY —Raaf Estate S L A adlya Instkute li TABLE OF CONTENTS EXECUTIVESUMMARY. ......... ............................. ........ ......... .,.,....... ..... ii METHODOLOGY...... ...... ................. ___ ........ _ HOUSING AND POPULATION........................................................ HousingStock ........ ____ ...... .............,........,.,........................ ....... .,,..,; 2 Population....-,.. .......::............ ............... ....... ...: 4 CULTURALIETHNIC AND ECONOMIC DIVERSITY ............ .... ......... ....... ECONOMIC ISSUES .......: .... s. .... ...... RENT CONTROL AS A BENEFIT .......................... ............ ..,....... ....., 8 EDUCATIONAL ATTAINMENT. ...... .............. .............. ........ ..:,.:;....:, 10 Table 1, Percent Change in Rental Housing Counts.... ___ .......... _......:..:... 3 Table 2: Percent Change in Aggregate Rooms in Rental and Owner -Occupied Housing..... .... 4 Table 3: ...:.:, Percent Change in Total Population.......... 5 Table 4: ......... ..........,... Percent Change in Households by Race of Householder Living in Renter -Occupied Housing,_. ............ B Table 5; ............. Percent Change in Female Householders with No Husband Present.____ .. 7 Table 6; ............ Percent Change in Annual Income for Rental Households.... ........ 8 "fable 7: Comparison of Median RentsandRental Price Benefits ................ 9 Table B. Educational Attainment (1990) ........ 10 Table 9: Educational Attainment (1980-1990):...... 11 The objective of this project is to analyze the impact of rent control on several population and housing Issues. The project is organized around six questions: • Goes rent control have an effect on the size of the resident population? • Does rent control have an impact on the quantity of rental housing stock? • Does rent control affect: household composition? • What are the major economic issues involving rent control? • Does rent control have any indirect effects on the demographics of the population? q•OF• =0 The effects of the restrictive rent controls in Berkeley and Santa Monica, implemented j ustprior to the 1980 Census, can be measured through the changes in population, housing, and other variables which occurred during the 1986.1990 decade tinder rent control, Natal[ cities with rent control are Included in thisstudy, as it is only those with restrictive rent control that may upset the balance between renters` needs and market forces, resulting In a systematic Was that may include those for whom the ordinances are supposed to protect. The restrictive rentcontrol ordinances in these t,wocities were created to meet perceived needs of the community by attempting to meet stated goals. These ordinances were designed to achieve the following goals: • Assist certain subgroups, such as the elderly and disabled, families with children; and minorities to find and remain in rental housing. • Preserve and protect affordable rental housing and existing rental housing stock. • Maintain the rich racial, ethnic; and economic diversity within the community, The research process used in this report was designed to test whether progress toward these goals have been achieved during the 10 years between the 1980 and 1990 Census. All data are from the STF-3 summary tables in the Census reports, A simple comparison of'population and housing variables for these two census years would not be a fair test, however, because external economic, social, and demographic factors unrelated to rent control have been operating, In orderto control for the effect of these external factors, the changes in these two cities were compared in each case to the changes which occurred over the same tune period in the counties in which they arelocated—Alameda and Los Angeles counties, The use of the counties for comparison should correct for external economic, social, and other factors which should have similar effects on the cities and Counties, The Caffornto State University-4eal fstete &.,Land Use lnstitum. t Itwould be incorrect to compare Berkeley to Alameda County, or Santa Monica to Los Angeles County, in any absolute sense, because these cities are certainly different in many respects from their counties. Our methodology was to compare the percentage changes in the cities with the percentage changes in their counties over the same time period. Comparing the percentage changes in the two cities with the percentage changes in their counties allows the analysis to be placed in a comparative, rather than absolute, frame of reference. Wherever changes in the cities occur in a very different way than occurred in their counties, it can be assumed that factors unique to the cities; such as a very restrictive rent control, are a major contributor. Strengthening this methodology is the use of two restrictive rent control cities which are very different from each other. Santa Mon Ica and Berkeley are very different from each other intheir economic composition, ethnic and age makeup, income, and other features. -Thesimilarity of their restrictive rent control laws is one of the greatestsimi larities between the two clues. If both of these cities have housing and population changes which are similar to each other, but which are very different from their counties, a strong argument can be made that these differences are related to the restrictive rent control laws. HOUSING AND POPULATION Frequently, rent control is .enacted to ensure that the cost of housing does not exceed the housing needs of a diverse population. Since maintaining a population diverse in socio- economic ociaeconomic characteristics is important to the health of a city, some local governments have chosen to pass ordinances with the i retention of preserving and protecting rental housing stock: The more complex the socio-economic structure of the community, the more important it is to maintain a diverse residential mix that houses the necessary labor force and consumers of goods and services, the more likely the communitywill choose somemethod to maintain parity between owner -occupied and rental housln& There is some doubt, however, that rent control meets these goals. Although the free market does trot always supply all housing needs fora diverse population, specifical ly housingforiow- ineome persons, it is not clear that rent control achieves that purpose, either. The "unknown" is the effect of rentcontrol ordinances that may erect barriers tothe stated goals of the taw, The fol lowing discussion of housing and population, cultural diversity, and economic issues seeks to add clarity to some of the questions forming the direction of this study, Housing Stock one of the undesired effects of restrictive rent control is that it limits the ability of investors to obtain adequate returns on their investments, Consequently, investors In residential rental properties will either convert to alternative investments or neglect to maintain their properties. U.S, Census data were used to determine if, underthe present ordinance, the quantity of rental housing stock in Berkeley and Santa Monica remained approximately the same, and if the changes in rental housing stock were consistent with those changes observed in the counties, The CaG)ixn7s Pate vnrvmtty—Rerl Estara & Land Use institute Assumption #1: Rent control is a disincentive to maintain and construct residential rental properties. If this assumption is corre4 it would be expected that, In Berkeley and Santa Monica, the total number of rental housing units would decrease, but similar declines would not be observed in the counties, Also, it should be observed that there appears to be greater decreases among large apartment houses, as those larger pieces of property can be more profitably converted to commercialuses. Table 1 contains city and county rental housing counts. MOLE r PERCENT CHANGE IN RENTAL HOUSING COUNTS BY TOTAL AND TYPE OF UNIT Berkeleyvs. Alameda County Santa Monica vs. Los Angeles County .1980.1990 Housing Variables Berkeley 7-9M1990 Percent Change Alameda Santa County Monica dos Angeles County Total Ranter -Occupied Housing Units -12.10% 1105010 -4.90% 10.07% Renter -Occupied Housing Units by Structure Single, detached -25.53 7.15 -11.24 3.73 Single, attached -29,02 24.56 -22.39 28,59 2 -unit structures -10,01 6.09 14:71 5.03 3-4 unit structures -17:64 7.65 6.855 8.27 5-9 unit structures -11.57 13.13 •8.84 10.95 10-49 unit structures -46,88 7.78 •15.19 13.14 Sources- t9Sd US. Census, Table 102, SMI r990 US, Ciettisus, Table tt2:2, 5TF3a.. The data show that the number of rental housing units declined in the two study cities, while the number increased in the counties. The greatest declines in Berkeley were in the buildings with 10 to 45 units. In Santa Monica, declines in 10 to 49 unit structures were not as dramatic as in Berkeley, but they exceeded the declines in the county by a significant amount. Of equal importance are the sharp declines in the single-family attached and detached rental homes In both Berkeley and Santa Monica. While the Census data do notshow what to these units, it can be suggested that they have been demolished in favor of other uses; or converted toowner-occupied housing. Since the city ordinances were focused onpreserving existing rental housing stock, the data clearly indicate a precipitous decline in this type of housing, The Calrldrnra 5tak uniyeYsrty—Real Estate& Land We Institute 3 The data for rental housing stock were reviewed from another perspective: aggregate rooms in rental housing. Table 2 contains the data for the cities and counties in this study. TAOLE PERCENT CHANGE IN AGGREGATE ROOMS IN RENTAL AND OWNER -OCCUPIED HOUSING Berkeley vs. Alameda County Santa Monica vs. Los Angeles County 1980-1990 'Sources: 1980 V.S. Census, Table 32, STF-3.. 1990 VS. Cer4us, Table H17, STF:3a. The data in Table 2 show that the total number of rooms declined in Berkeley and Santa Monica, while they! ncreased in Alameda and Los Angeles counties. The declines were caused by the loss of renter -occupied rooms, a decline of 15.1 percent in Berkeley and 7.4 percent in Santa Monica. The declines in the number of rooms in renter -occupied housing were accompanied by increases In the numberof rooms in owner -occupied housing,suggesting that both cities are losing rental space, and increasing the number of owner -occupied housing, or increasing the sire of the existing owner -occupied housing stock. The data for the less constrained counties are interesting; in themselves, in both cases, the numberof rooms in rental housing have increased fasterthan the numberof rooms in owner - occupied housing. It appears that the ordinances, written to preserve and protect rental housing stock, have not attained the goal of the ordinances -- to preserve rental housing. Population If the rental housing stock declined, it would be expected that the number of persons traditionally living in rental housing would changem thesame direction, Table3 contains the city -county total papulation comparisons. While the declines in total 'population were not large, they did occur in both cities. The Increases in the total population for the counties, however, were quite large, almost 19 percent for Alameda County and over 20 percent for Los Angeles County. Although it cannot be completely explained by the existence of the restrictive rent control, it is clearthat the declines in rental housing stock might be having an impact on the total population of the two cltles. The Qiifonv a. State Universily-»Real estate & Land use. 1nstl4ere 4 1980.1990 Percent Change :Alameda Santa Los Angeles Berkeley County Monica County Total Rooms 3,0% 8.64/4 -2.5% 2.6% Renter-occupled -15.1 1415 •7.4 4.5 owner -Occupied 7.5 7,6 6.2 1,4 'Sources: 1980 V.S. Census, Table 32, STF-3.. 1990 VS. Cer4us, Table H17, STF:3a. The data in Table 2 show that the total number of rooms declined in Berkeley and Santa Monica, while they! ncreased in Alameda and Los Angeles counties. The declines were caused by the loss of renter -occupied rooms, a decline of 15.1 percent in Berkeley and 7.4 percent in Santa Monica. The declines in the number of rooms in renter -occupied housing were accompanied by increases In the numberof rooms in owner -occupied housing,suggesting that both cities are losing rental space, and increasing the number of owner -occupied housing, or increasing the sire of the existing owner -occupied housing stock. The data for the less constrained counties are interesting; in themselves, in both cases, the numberof rooms in rental housing have increased fasterthan the numberof rooms in owner - occupied housing. It appears that the ordinances, written to preserve and protect rental housing stock, have not attained the goal of the ordinances -- to preserve rental housing. Population If the rental housing stock declined, it would be expected that the number of persons traditionally living in rental housing would changem thesame direction, Table3 contains the city -county total papulation comparisons. While the declines in total 'population were not large, they did occur in both cities. The Increases in the total population for the counties, however, were quite large, almost 19 percent for Alameda County and over 20 percent for Los Angeles County. Although it cannot be completely explained by the existence of the restrictive rent control, it is clearthat the declines in rental housing stock might be having an impact on the total population of the two cltles. The Qiifonv a. State Universily-»Real estate & Land use. 1nstl4ere 4 TARLE PERCENT CHANGE IN TOTAL POPULATION BY AGE COMPAPIStONS Berkeley vs. Alameda County Santa Monica vs. Los Angeles County 1990.1990 sources:'. 1980 US, Census, Table 15, ST". 1990 US. Census, Table Pia, W -3z. The greatest declines occur in the age groups to 14 and 15 to 24. The latter population, age 15 to 24, consists of those who are more likely to rent than own a home. In the subject cities, a large proportion of these persons are more likely to be in college or starting out in a new career. One argument that could accountfor the decline of almost 11 percent In the 15 to 24 year age group in Berkeley is that the college student population is declining, or moving out of Berkeley. The Census data show, however, thatthe proportion of col legestudents i n the city remained the same, 27,5 percent in 1980 and 27.4 percent in 1990. Also, the constant proportion of students suggest replacement, and that the declines are not students simply completing college and moving to another area for work or continued schooling. Therefore, it can be suggested that the persons moving out of Berkeley are other than college students. instead, they are persons who cannot afford to purchase a home in Berkeley and cannot find rental housing. The data show declines for the age group 5 to 14, also, This group is the most likely to be part of a family. The recent increases, slight but real, in the birth rate magnifies the large declines in this age group, compared to the increases shown for the counties. The last group that deserves attention is persons over the age of 64, another group that has a high probability of beinga renter, With respect to the overal I aging of the general population, it is not surprising to seethe extraordinary gains in both the counties, Berkeley, on the other hand, shows less than a one percent increase, and Santa Monica, an almost two percent decrease in the proportion of persons who fall Into this group, The data, once more, show that the restrictive rent control has not met their goals. In the case of the subjectcities, It appears that the age groups most likely to decline In size are those In which families are more likely to occur, affecting family composition, and In the elderly population. The Cal knia State Unhwshy--Real Costs h Land Use Matfute 1980-1990 Percent Change Alameda Santa Los Angeles Population and Age Berkeley County Monica County Total Population -0,580!e 18.74% -1 AD% 20,83% Age Groups tin years) Less than S 16.19 31.73 14.37 31.38 5-14 -11.48 9.39 -21,04 1340 15.24 „1041 -5.54 -3734 4.12 25-64 5.22 2636 10.16 27.04 More than 64 0,68 25.45 -1,70 23.51 sources:'. 1980 US, Census, Table 15, ST". 1990 US. Census, Table Pia, W -3z. The greatest declines occur in the age groups to 14 and 15 to 24. The latter population, age 15 to 24, consists of those who are more likely to rent than own a home. In the subject cities, a large proportion of these persons are more likely to be in college or starting out in a new career. One argument that could accountfor the decline of almost 11 percent In the 15 to 24 year age group in Berkeley is that the college student population is declining, or moving out of Berkeley. The Census data show, however, thatthe proportion of col legestudents i n the city remained the same, 27,5 percent in 1980 and 27.4 percent in 1990. Also, the constant proportion of students suggest replacement, and that the declines are not students simply completing college and moving to another area for work or continued schooling. Therefore, it can be suggested that the persons moving out of Berkeley are other than college students. instead, they are persons who cannot afford to purchase a home in Berkeley and cannot find rental housing. The data show declines for the age group 5 to 14, also, This group is the most likely to be part of a family. The recent increases, slight but real, in the birth rate magnifies the large declines in this age group, compared to the increases shown for the counties. The last group that deserves attention is persons over the age of 64, another group that has a high probability of beinga renter, With respect to the overal I aging of the general population, it is not surprising to seethe extraordinary gains in both the counties, Berkeley, on the other hand, shows less than a one percent increase, and Santa Monica, an almost two percent decrease in the proportion of persons who fall Into this group, The data, once more, show that the restrictive rent control has not met their goals. In the case of the subjectcities, It appears that the age groups most likely to decline In size are those In which families are more likely to occur, affecting family composition, and In the elderly population. The Cal knia State Unhwshy--Real Costs h Land Use Matfute CULTURAL/ETHNIC AND ECONOMIC DIVERSITY In general, as resources become scarce, the value of the resource! ncreases, In the caseof rental housing, if the supply of rental housing declines but the demand remains the same, it follows that the price of cental housing will increase. Since rent control imposes an artificial barrier to increased prices, rental property owners enhance their credit checking activities relative to prospective residents to increase the probability that rent will be paid. In this section, the impact of restrictive rent control on household composition, lower income households, and families or households with children is examined. Assumption #2: if the supply of rental housing decreases but the demand remains the same or increases, rent control will encourage property owners to favor tenants who appear to be better -able to pay the rent, Table 4 contains information for persons living in renter -occupied housings by total renters, race, and ethnicity. The racial andethniccategories are limited toWhite,Black, and Hispanic because the majority of the population fall into these categories, and the categories for Asian and Other are not comparable between the two Census years. AHL PERCENT CHANGE IN HOUSEHOLDS BY RACE of HOUSEHOLDER LIVING IN RENTER -OCCUPIED HOUSING Berkeley vs, Alameda County Santa Monica vs. Los Angeles County 1980-1990 --,-p—..--. u••— ....+v„"„ ,.a 1, 1.1 .lax 8pPI1EM heatl ot hQUWA01d O(lly, nct to total family memiaErs . Sources; 1980 U.5. Census, Table.98; 5T". 1990 U.& Census,Table H13,STF•3a, The cultural, racial, and ethnic diversity issue has an impact on household composition. Table 5 contains information on the percentchange in female householders with no husband present. The data are for total households in the subject cities and counties. The catitrirrrta Scare Unfverslfy Rest £state & Land Use Institute 6 7960-1990 Percent change Racial and Alameda Santa Los Angeles Ethnic Categories* Berkeley County Monica County Total Renters .11,69 12.09 •4.90 M10.07 White Renters -23,65 -.65 -7A4 -6.81 Black Renters -7A7 iS.SO 2.40 10.71 Hispanic Renters 16.32 37,93 7.35 46,40 --,-p—..--. u••— ....+v„"„ ,.a 1, 1.1 .lax 8pPI1EM heatl ot hQUWA01d O(lly, nct to total family memiaErs . Sources; 1980 U.5. Census, Table.98; 5T". 1990 U.& Census,Table H13,STF•3a, The cultural, racial, and ethnic diversity issue has an impact on household composition. Table 5 contains information on the percentchange in female householders with no husband present. The data are for total households in the subject cities and counties. The catitrirrrta Scare Unfverslfy Rest £state & Land Use Institute 6 The data in Table 5 are mixed, in Berkeley, the number of households headed by females with no husband present is declining for all racial and ethnic groups. Black females appear to be the most seriouslyaffected . For Santa Monica, the data are quite different. Female households are increasing for all racial and ethnic categories.: PERCENT CHANGE IN FEMALE HOUSEHOLDERS WITH NO HUSBAND PRESENT Rental and Ownership Households Berkeley vs. Alameda County Santa Monica vs. Los Angeles County 19wi 990 Racial and 1960.1990 Percent Change Alameda Santa Los Angeles Ethnic Categories` Berkeley County Monica County Total Female Householders -2,201. 5.9% 7.3% 31% White Female Householders -3.8 10.8 3:1 110 Black Female Householders -7,8 -BA 2.5 1.0 Hispanic Female Householders •5.4 -12:5 2.9 6.8 categories Asian and Other not included in N6 table. The racial and ethnic designation applies to head vt household only, not to total family members, souices. 1980 U.S. Census; Table 9ri, $TE 3. I"D US, census; Table Pt 7, STS -3 a. Two factors should be considered when reviewing these data. first, the data are for total households, as racial and ethnic data for renters only were not available in theSTF-3 data. The data already examined suggest that the impact of rentcontrol would fie more negative if renter - only data were available. Also, income data indicate that households with lower annual incomes are declining in bath cities. Since female -headed households with no husbands present usually have lower annual incomes, it can be suggested that the declines would be greater for renters than for the total population. The data for the cities and their counties are quite different also. if the county data represents the meant activity for all persons in these categories, the data show that the subject cities are exhibiting quite different characteristics. Thus, not only Is household composition being affected, the data show thateconomic and, i n some cases, cultural diversity are being affected also. State Unrverstty—Raol Estate & land. Use Institute ECONOMIC ISSUES if the goal is to maintain economic diversity by controlling rents, it would be expected that the percentof households earning lower annual Incomes would remain constant, or under the best circumstances, increase somewhat. The data In Table 6 contains data on income levels for households earning an Income of less than $20,000 a year. These data conform to Census categories. TABLI PERCENT CHANGE IN ANNUAL INCOME FOR RENTAL HOUSEHOLDS Berkeley vs. Alameda County Santa Monica vs. Los Angeles County 198iM1990 Sources; 1980 U.S, Census, Table 132, 5TF•3, 1990 US. Census, Table H50, STF-3a. The data show that, in the counties, the percent increase for both income groups is consistent. In Alameda, the percent increase is between 3,9 and4.1 percent, and in Los Angeles County, between 8.5 and 9.4 percent, The percent change for Berkeley and Santa Monica, however, are quite erratic. In Berkeley, there has been a decline in both income categories in the decade between the Censuses. in Santa Monica, there is an almost percent increase for the lowest income category, buta 9.1 percent decrease forthehousehold's earning between $10,000 and $19,999. The data suggest thatthe ordinances have not mettheil rgoal of maintaining economic diversity, and it appears that the ordinance has not preserved rental housing for the lower Income groups. RENT CONTROL AS A BENEFIT An importanteconomic Issue is the discussions of rent control as a benefit. The preceding table suggests that the ordi nancesfai i to benefit lower income groups, as both cities are losing renters at lower income levels. If rent control creates a benefit, then the size of the benefit and who pays the benefit become important questions that need to be addressed. Table 7 contains a calculation of the amount of annual rental benefits. The data are shown for the cities of Santa Monica and Berkeley, for the years 1980 and 1994. The Calttsirnia $rate Untversio—Real Wie & Land Use Watate 6 1980-1990 Percent Change Alameda Santa Los Angeles Income Group Berkeley County Monica county _ Less than $10,004 -3.1% 4.14Ja 3.8% 9.4°l0 $101000-$191999 -27.1 3.9 39.1 a's Sources; 1980 U.S, Census, Table 132, 5TF•3, 1990 US. Census, Table H50, STF-3a. The data show that, in the counties, the percent increase for both income groups is consistent. In Alameda, the percent increase is between 3,9 and4.1 percent, and in Los Angeles County, between 8.5 and 9.4 percent, The percent change for Berkeley and Santa Monica, however, are quite erratic. In Berkeley, there has been a decline in both income categories in the decade between the Censuses. in Santa Monica, there is an almost percent increase for the lowest income category, buta 9.1 percent decrease forthehousehold's earning between $10,000 and $19,999. The data suggest thatthe ordinances have not mettheil rgoal of maintaining economic diversity, and it appears that the ordinance has not preserved rental housing for the lower Income groups. RENT CONTROL AS A BENEFIT An importanteconomic Issue is the discussions of rent control as a benefit. The preceding table suggests that the ordi nancesfai i to benefit lower income groups, as both cities are losing renters at lower income levels. If rent control creates a benefit, then the size of the benefit and who pays the benefit become important questions that need to be addressed. Table 7 contains a calculation of the amount of annual rental benefits. The data are shown for the cities of Santa Monica and Berkeley, for the years 1980 and 1994. The Calttsirnia $rate Untversio—Real Wie & Land Use Watate 6 The median rents were used to calculate the benefits to renters living in Berkeley and Santa Monica. it was assumed that, If rent control were not in effect, the median rent in both cities would approximate the rents in the reference counties. The median rents at the county level represent the expected rent, and are used as a basis for suggesting the rental benefit. In 1980 and 1490, the Berkeley median rentwat below the county median, In Santa Monica, the median rantwas above the county median cent in 1980; however, aftera decade of the rent control being in effect, the median resit was lower in Santa Monica than in the county. TAX Fz COMPARISON OF MEDIAN RENTS AND RENTAL PRICE BENEFITS Berkeley vs. Alameda County Santa Monica vs. Los Angeles County 3980.1990 The table shows that the annual benefit to renters in 1980 was $252 in Berkeley, and by 1490, a littieover a decade after theordinancewas in effect, the annual benef itwas $2,400 for renters. In Santa Monica, there is no calculated benefit to renters in 1980; however, in 1990, the annual benefit to renters was estimated at $1,128. While the calculation of the benefit to rental households is generally stated, the conclusion comes from the magnitude of the estimate. in 1980, offering a benefit to rental households of $252 per year was a reasonable price to meet the stated goals of the ordinance. In 1990, the magnitude of the benefit has Increased 10 times in Berkeley and doubled in Santa Monica, without meeting the objectives of the ordinance. Since the data suggest that the restrictive rent control ordinances are not entirely meeting their goals, the benefits are apparently not going to the segments of the population for whom the benefits were intended. The Califainia State UniveroFly—Rea! Estate & Land Use rnstime Alameda Sacra Los Angeles Comparisons Berkeley County Mcntea County Median Rent 1980 $245 $266 $319 $276 1990 $426 $626 $532 $626 AnnualBenefit' 1980 $ 7,010,892 $07,644,104) 1990 $ 58,692,000 $ 36,682,560 Annual Benefit to Renters' 1980 $ ,252 $(516) 1990 $2,400 $1,128 1(VimenceinCtitiCounty median rent multiplied byunits annuatized. 5ourcest 1980 U.S, Census Table 124, STi-3- 1990 U.S. Census; Table .43, 5TF-1a. The table shows that the annual benefit to renters in 1980 was $252 in Berkeley, and by 1490, a littieover a decade after theordinancewas in effect, the annual benef itwas $2,400 for renters. In Santa Monica, there is no calculated benefit to renters in 1980; however, in 1990, the annual benefit to renters was estimated at $1,128. While the calculation of the benefit to rental households is generally stated, the conclusion comes from the magnitude of the estimate. in 1980, offering a benefit to rental households of $252 per year was a reasonable price to meet the stated goals of the ordinance. In 1990, the magnitude of the benefit has Increased 10 times in Berkeley and doubled in Santa Monica, without meeting the objectives of the ordinance. Since the data suggest that the restrictive rent control ordinances are not entirely meeting their goals, the benefits are apparently not going to the segments of the population for whom the benefits were intended. The Califainia State UniveroFly—Rea! Estate & Land Use rnstime EDUCATIONAL ATTAINMENT Frequently, education is used as a proxy for gentrification, that is, the upgrading of properties to the exclusion of low income persons. Table 8 contains the data for educational attainment for the subject cities and counties. The data are for 1990 only. They show an inverse relationship between the educational attainment level between each city and Its county, In both cases, as the attainment level increases for the cities, it declines in the counties. ,TABLE t3 EDUCATIONAL ATTAINMENT Berkeley vs. Alameda County Santa Monica vs. Las Angeles County 1990 Income Group Berkeley (k) Alameda County Santa Monica Las Angeles County Less than 9th grade 4.11% 7.38% 5.51% 15;58% 9th to 12th grade, no diploma 5,57 11A6 7,00 14.39 High school graduate (includes equivalency) 9.86 22,76 15.96 20,70 Bachelor's degree 26,22 17.90 24.78 14.48 Graduate or professional degree 30,45 10.91 18.60 7;84 Source:. 1930 U.$, Census, Table. P57, 5TF-3a Table 9 compares educational attainment between 1960 and 1990, The data show that, for both years, the proportion of the population with fouror more years of education is much larger in the subject cities than in the respective counties, The CalifomEa State t7ntversi4,—Rea! (slate & tand Uae k fl wte TAW EDL(CATIONAL ATTAINMENT Berkeley vs. Alameda County Santa Monica vs. Los Angeles County 1980-1990 Sources: 7980 U.S. Cenws, Table 50,: STr-3. 1990 u.S. Census, Table PS7, SIT -3a. The percent change data are somewhat inconclusive. The percent change is the same for Berkeley and Alameda County, but larger For Santa Monica than Los Angeles County, The data suggest that, in the City of Santa Monica, the papulation with four or more years of education is growing rapidly. Although the percentchange is not high for Berkeley, the data do notdistract from the argument thatthe population of the two cities with restrictive rent control are increasingly better educated and wealthier, a strong argument for the gentrification of the two cities,. 7ha C8U(Q(Wa Srate Univeniry--Reat £state & land Use tnuitule 11 Alameda Santa Los Angeles Berkeley County Monica County (°!) NO F°'a) (%) Four or more years t198tt) 52.3% 223% 33.6% 18.5% Four or more years (1990) .58.7 28.6 43.4 22:3 Percent Change 6.4 5.5 9.8 3.8 Sources: 7980 U.S. Cenws, Table 50,: STr-3. 1990 u.S. Census, Table PS7, SIT -3a. The percent change data are somewhat inconclusive. The percent change is the same for Berkeley and Alameda County, but larger For Santa Monica than Los Angeles County, The data suggest that, in the City of Santa Monica, the papulation with four or more years of education is growing rapidly. Although the percentchange is not high for Berkeley, the data do notdistract from the argument thatthe population of the two cities with restrictive rent control are increasingly better educated and wealthier, a strong argument for the gentrification of the two cities,. 7ha C8U(Q(Wa Srate Univeniry--Reat £state & land Use tnuitule 11 After a decade of broad-based growth, renter households are increasingly likely to have higher incomes, be older, and have children. The market has responded to this shift in demand with an expanded supply of high-end apartments and single-family homes, but with little new housing affordable to low- and moderate -income renters. As a result, part of the new normal emerging in the rental market is that nearly half of renter households are cost burdened. Addressing this affordability challenge thus requires not only the expansion of subsidies for the nation's lowest -income households, but also the fostering of private development of moderately priced housing. RENTER HOUSEHOLD GROWTH IN A SLOWDOWN Rental housing markets have seen an unprecedented run-up in demand over the last decade, with growth in renter housholds aver- aging just under one million annually since 2010. But the surge in demand now appears to be ending, with the three major government surveys reporting a sharp slowdown in renter household growth to the 136,000-625,000 range in 2016. Early indications for 2017 sug- gest a further deceleration, with one survey showing essentially no increase and another posting a substantial decline (Figure 11. While these estimates are notoriously volatile from year to year, the con- sistent trend across surveys provides some confidence that growth in renter households is indeed cooling. The recent wave in renter household growth reflects in part the sharp drop in the national homeownership rate after 2004. While many fac- tors drove that decline, the massive wave of foreclosures after the hous- ing crash was a key contributor, This drag on homeownership has now eased. And with the economy near full employment and incomes on the rise, more households that want to buy homes are able to do so. Still, the housing crisis no doubt generated renewed appreciation for the advantages of renting that will help sustain demand in the years ahead. Indeed, even as the homeownership rate stabilizes, renters are still likely to account for slightly more than a third of household growth. According to Joint Center projections, the number of renter households will increase by nearly 500,000 annually over the ten years from 2015 to 2025—a still robust pace by historical standards. The sweeping changes in the nature of rental demand, however, seem likely to persist, in particular, renting now appears to have greater appeal for households that could afford to buy homes if they desired. In 2006, 12 percent of households earning $100,000 or more were renters. In 2016, that share exceeded 18 percent, a cumulative increase of 2.9 million renters in this top income category. Indeed, these high-income households drove nearly 30 percent of the growth in renters over the decade. Even so, renting remains the primary housing option for those with the least means. A majority (53 per- cent) of households earning less than $35,000 rent their housing, including over 60 percent of households earning less than $15,000. 2 After a Decade of Expansion, the Pace of Growth in Renter Households Has Slowed Millions 1.6 1.4 7.2 1.0 0.8 0.6 04 02 0.0 -0.2 -0.4 Millions 2004 2005 2006 2007 2008 2009 2010 2011 2U12 2013 2014 2015 2016 2017 'al ChaUse in Renter Lyres holds (Loft scale) — Number of Rentor Households (Right salol Now. Utinnete in -2017 is the evam9e of second -and third quarter data. Soume, JCHS tahulotions of US Census Bureau, Rausing Vacancy Survey. In addition, renters are now much older on average than a decade ago, reflecting both an increase in middle-aged households that rent and the overall aging of the population. The median age of renters thus increased from 38 in 2006 to 40 in 2016. Although roughly a third of renters are under age 35, nearly as many are now age 50 and over. With renting more common across age and income groups, renter households are more representative of the broad cross-section of US families. Most notably, families with children now make up a larger share of households that rent (33 percent) than own (30 percent). Married couples without children, in contrast, make up 37 percent of homeowners and just 12 percent of renter households. Single per- sons are still the most common renter household type, accounting for fully 37 percent of all renter households. While whites accounted for a large share of the overall growth in renters, renter households are quite racially and ethnically diverse. Unlike homeowners, who are overwhelmingly white, renter house- holds include a large share (47 percent) of minorities. At the same time, one in five renter households is foreign bom, reflecting the importance of rental housing to new immigrants. EVOLUTION OF THE RENTAL SUPPLY Soaring demand sparked a sharp expansion of the rental stock over the past decade. Initially, most of the additions to supply came from conversions of formerly owner -occupied units, particularly single- family homes, which provided housing for the increasing number of families with children in the rental market. Between 2006 and 2016, the number of single-family homes available for rent increased by 44 42 40 38 36 34 32 30 28 26 24 nearly 4 million, lifting the total to 18.2 million. While single-family homes have always accounted for a large share of rental housing, they now make up 39 percent of the stock. More recently, though, growth in the single-family supply has slowed. The American Community Survey shows that the number of single-family rentals (including detached, attached, and mobile homes) increased by only 74,000 units between 2015 and 2016, substantially below the 400,000 annual increase averaged in 2005- 2015. With this slowdown in single-family conversions and a boom in multifamily construction, new multifamily units have come to account for a growing share of new rentals. Indeed, completions of new multifamily units intended for rent averaged 300,000 annually over the last two years, their highest level since the end of the 1980s. Much of this new housing is targeted to higher -income households and located primarily in high-rise buildings in downtown neigh- borhoods. Given that construction and land costs are particularly high in these locations, the median asking rent for new apartments increased by 27 percent between 2011 and 2016 in real terms, to $1,480. Using the 30 -percent -of -income standard for affordability, households would need an income of at least $59,000 to afford these new units, well above the median renter income of $37,300. At the same time, the supply of moderate- and lower-cost units has. increased only modestly (Figure 2). While the share of new units rent- ing for at least $1,100 jumped from 37 percent in 2001 to 65 percent in 2016, the share renting for under $850 shrank from just over two- fifths to under one-fifth. The lack of new, more affordable rentals is in part a consequence of sharply rising construction costs, includ- Additions to the Rental Stock Are Increasingly at the Higher End Share of recently Built Units 23% 15 1 22% 38°/a 29 2009 9% 9% , 40% 19% 15°!a 2016 Monthly Housing Cost Under$650 11 $050-849 Nd $650-1,090 N $1,100-1,499 ® $1,500 and Ovor Notes'. Recently built units In 2991 129181 were constructed In 1999-2991 12914-29181. Monthly housing posts include rent and utilities and are in constant 2016 dollars, adjusted for inflation using the CPI -U for All Itoms Less Shelter Data exclude vacant units and units for which no cash rent Is paid. Source: RIC tabulations of US Census Bureau. 2991 and 2916 American Community Survey 1 Year Gstimates, ing labor and materials. According to estimates from RS Means, the costs of building a basic, three-story apartment building increased by 8 percent from 2016 to 2017 alone. Tight land use regulations also add to costs by limiting the land zoned for higher -density housing and entailing lengthy approval processes. Given these high development costs, most of the demand for low- priced rentals must be met by older units. Only a fifth of existing units rented for under $650 a month in 2016, and nearly half of these units were built before 1970. Affordably priced rentals are frequently located in smaller multifamily structures, with one-quarter of low- cost units in buildings with 2-4 apartments. In many cases, the supply of these so-called naturally occurring affordable rentals is replenished as rents on older housing fall due to aging and obsolescence. But with overall rental demand strong, particularly in centrally located communities, rents for an increas- ing number of once -affordable units have become out of reach for lower-income households. At the same time, the rents charged for units in neighborhoods with weak demand may not support adequate maintenance, leaving those rentals at risk of deterioration and loss. Given the lack of new construction of lower-cost rentals, preserving the existing stock of privately owned affordable units is increasingly urgent. RENTAL MARKETS AT A TURNING POINT Rental construction led the housing recovery, rebounding nearly four -fold from the market trough in 2009 to 400,000 units in 2015— the highest annual level since the late 1980s. But after moving sideways in 2016, the pace of multifamily starts has fallen 9 per- cent through October 2017. The slowdown has occurred in markets across the country, but is most evident in metros where multifamily construction had been strongest. In addition to the slowdown in construction, a variety of measures sug- gest that the rental boom is cresting. RealPage reports increasing slack in the professionally managed apartment market, with vacancy rates rising over the past year in 94 of the 100 metros tracked. The clearest signs of loosening are in the higher -priced Class A segment, where the vacancy rate was up 1.5 percentage points year over year in the third quarter of 2017, to 6.0 percent (Figure 3). vacancy rates in the lower-cost Class C segment also rose but remain quite low at 4.1 percent. Apartment rents are also increasing more slowly in all three seg- ments of the market (Figure 4). This deceleration has appeared in all four regions of the country and in large and small markets alike. Even so, conditions in selected markets—particularly smaller metros and locations in the Midwest, such as Cincinnati and Minneapolis— were still heating up. Over the last six years, increases in the median rent have exceeded inflation in non -housing costs by more than a full percentage point annually, with the largest gains in the South and West. Median rents have risen at twice the national pace in markets with rapid popula- tion growth, such as Austin, Denver, and Seattle. And within these fast-growing metros, rents in previously low-cost neighborhoods rose nearly a percentage point faster each year than in high-cost neighborhoods. Meanwhile, rental property owners continue to benefit from still healthy increases in operating incomes and property values. According to the National Council of Real Estate Investment Fiduciaries, net 3 4 As Vacancy Rates Begin to Climb... Partial Vacancy Rate )Percent) 11 10 9 3 7 6 5 4 3 2 0 *7r,, nl f t.'.g 1''t 4 C f iWRipK # y P,. a"'. 'R�!d d✓ 11 Jv ,.�yY i t ., t �Siv G` -4 ai i e .4'1._ _. ,. .u3. 1+: rAca d r +.ro+s..., w.tai .v.a snr fj 2011 2012 2013 2014 2015 2016 2017 — Class A w Class 3 r Class C S 11 All Rantal Units Notes: Vacancy rates are calculated as smoothed faur-gnener trailing commas Vacancy rate for all rental units is from ma lli RealPage data cover promseenally managed apartments in buildings with five or mare units, Sources: JCHS tabulations of US Census Bureau, Housing Vacancy Survey IHVSI, and RealPage, Inc. operating incomes were up 3.8 percent in the third quarter of 2017 from a year earlier. In addition, Real Capital Analytics reports that real apartment prices climbed 6.3 percent in the second quarter of this year. Although declining, rates of return on investment remained relatively strong at 6.2 percent. The pace of investment, however, appears to be slowing, with the volume of large international and institutional deals falling in many major apartment markets. Even so, multifamily financing remains at an all-time high. According to the Mortgage Bankers Association, the volume of outstanding multifamily mortgage debt increased by about 20 percent in 2015-2016, rising to nearly $1.2 trillion in early 2017. Federally backed debt rose by 25 percent, while bank and thrift lending was up 29 percent. Meanwhile, multifamily loan delin- quencies are extremely low. Some caution appears to be creeping into the market, however, with the latest Federal Reserve loan officer surveys pointing to tightening credit and slowing demand. SLIGHT EASING OF AFFORDABILITY PRESSURES With the economy continuing to improve and income growth accel- erating, the share of renters with cost burdens (paying more than 30 percent of income for housing) fell in 2016 for the fourth time in five years, to 47 percent (Figure 5). The number of cost -burdened renters also fell for the second consecutive year, declining from 21.3 million in 2014 to 20.8 million in 2016, with the number of severely burdened households (paying more than 50 percent of income for housing) dip- ping from 11.4 million to 11.0 million. However, this progress comes ... Rent Growth Appears Set for a Steeper Slowdown Change in Rents (Percent) 7 G 5 4 3 2 0 2011 2612 2013 2014 2615 2016 2017 — Cloa. A — Class E — Class C 1 All Rental Units Nates', Growth in rents for all units is measured by the CPI for Rent of Primary Residence, including utilities, RealPage data cover professionally managed apartments In buildings with five or mom units, Soumen JCHS tabulatlons of Bureau of Labor Statistics, and RealPage, lard. only after a decade of steep increases. At the average rate of improve- ment from 2014 to 2016, it would take another 24 years for the num- ber of cost -burdened renters to return to the 2001 level. The high incidence of cost burdens reflects the divergent paths of rental housing costs and household incomes. Between 2001 and 2011, median rental housing costs rose 5 percent in real terms while median renter incomes dropped 15 percent. Since 2011, however, real housing costs have increased 6 percent while income growth has picked up 16 percent (due in part to the increasing share of renters with higher incomes). But even with the recent turnaround in incomes, the cumu- lative increase in rental housing costs since 2001 has been far larger. The rental market thus appears to be settling into a new normal where nearly half of renter households are cost burdened. An impor- tant element of this trend is that more middle-income renters are spending a disproportionate share of income for housing. indeed, the share of renters earning $30,000-45,000 with cost burdens jumped from 37 percent in 2001 to 50 percent in 2016, and the share earn- ing $45,000-75,000 nearly doubled from 12 percent to 23 percent. In addition, the cost -burdened share of lowest -income households (earning less than $15,000) was still a stunning 83 percent, with the vast majority experiencing severe burdens. Given the fundamental need for shelter, rent is typically the first bill paid each month. High housing costs erode renters' purchasing power, leaving little money left over for other essentials such as food, childcare, and healthcare. In 2016, the median renter in the bottom income quartile had just $488 per month to spend on other essen- tials -18 percent less than in 2001 after adjusting for inflation. The added costs of utilities and transportation further strain household budgets. Low-income households with children and older adults with severe rental cost burdens are in a particularly precarious posi- tion and may be unable to afford other goods and services that are critical to health and well-being. SHORTFALL IN RENTAL ASSISTANCE Need for housing assistance continues to grow. HUD's Worst Case Housing Needs 2017 Report to Congress shows that the number of very low-income households receiving rental assistance increased by 600,000 from 2001 to 2015. Over the same period, the number of very low-income households (making less than 50 percent of area median) grew by 4.3 million, with extremely low-income house- holds (making less than 30 percent of area median) accounting for more than half (2.6 million) of this increase. As a result, the share of renters potentially eligible for assistance and that were able to secure this support declined from 28 percent to 25 percent (Figure 6). Meanwhile, the share of very low-income renters facing worst case needs—that is, paying more than half their incomes for hous- ing and/or living in severely inadequate units—increased from 34 percent to 43 percent. Making matters worse, much of the subsidized rental stock is at risk of loss either due to under -maintenance or expiring affordability periods. Public housing is particularly under threat, with a backlog of deferred repairs last estimated at $26 billion in 2010. In fact, the number of occupied public housing units fell by 60,000 between 2006 and 2016. The Rental Assistance Demonstration (RAD) program was launched in 2012 to convert public housing into long-term project - based Section 8 contracts in order to provide more flexible financing for improvements. The RAD program quickly reached its initial cap of 60,000 units, which has since been increased to 225,000 units. The two main sources of rental housing assistance are the Housing Choice Voucher and Low Income Housing Tax Credit (LIHTC) pro- grams. Vouchers enable recipients to choose units on the open market as long as they meet rent and quality standards. Despite a 6.8 percent increase in funding between 2011 and 2016, rising rents kept growth in the number of voucher holders to just 5.8 percent. In contrast, the LIHTC program provides funding for new construc- tion as well as rehabilitation and preservation of existing assisted housing. In recent years, the LIHTC program has supported 70,000 affordable rental units per year, with roughly 55 percent added through new construction. But over the next decade, nearly 500,000 LIHTC units, along with over 650,000 other subsidized rentals, will come to the end of their required affordability periods. The need for funding to help rehabilitate and preserve this important stock will fuel significant demand for LIHTC funding, thus limiting opportuni- ties to build new affordable rentals. In recognition of the important role that the LIHTC program plays, the Congress is considering a bipartisan proposal to expand funding while also introducing reforms that would improve the ability of the program to serve both lower- and moderate -income households Despite Recent Declines, the Number and Share of Cost -Burdened Renters Remain Well Above Levels a Decade Ago Millions Percent 12 10 9 A 7 6 5 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 ■ Number ofMade rate lysuffered Ron Iurs (Left soahi G Number of Severely Burdened Renters (Left suite) a Shore of Renters with Cost burdens (Right scale) Notes: Moderately (severely) cost -hardened households pay 30 50% from then W%I of income for housing. Households with seen or negative income are assumed to hove. severe burdens, while households paying no cash rent are assumed to be where burdens. Source'. LUIS tabulations of US Census Bureau, Amednen Community survey 1 -Year Estimates. 52 50 48 46 44 42 40 38 5 6 Growth of Very Low -Income Renters Continues to Outpace Availability of Housing Assistance Millions 20 18 16 14 12 10 8 Percent —50 2001 2003 2005 2007 2009 2011 2013 2015 ?al Number of Very Low -Income Renters ILef sale) ^ Share with Woret Case Lending Need iRightscalel Shore Receiving Noising Assistance IRight sea Iul Notes: Very low income Is defined as less than 50% of area median. Households with worst case housing needs are very low-income renters paying more than 60% of income for rent or living in severely inadequate conditions, and do not receiva housing assistance, Soume', US Department of I lousing and Urban Development, 2003-2017 Worst Case Housing Needs Reports to Congress. The incidence and severity of natural disasters is on the rise. In devel- oping their recovery plans to improve resiliency after such events, governments at all levels must keep in mind the needs of renters— particularly very low-income renters—for replacement housing. 45 THE OUTLOOK Slower growth in rental housing demand could be good news if it 40 helps to check the rapid rise in rents. But even if the homeownership 35 rate stabilizes near current levels, the number of renter households 30 is likely to continue to increase at a healthy clip, driving up the need for additional supply. And given that a broader array of households 25 has turned to renting, this also means a growing need for a range of 20 rental housing options. in high-cost markets. However, tax reform proposals also under debate call for elimination of the 4 percent LIHTC program, which accounted for just under half of production in 2015. THE CHALLENGE OF REBUILDING AFTER DISASTERS The series of disasters this past year—including devastating hur- ricanes in Texas, Florida, and Puerto Rico, and massive wildfires in densely populated areas of California—have affected millions of owners and renters alike. A key lesson from previous disas- ters is that rental property owners are slower than homeowners to rebuild or replace their units. For example, five years after Hurricanes Katrina and Rita ravaged the Gulf coast, three-quar- ters of severely damaged owner -occupied housing in Louisiana and Mississippi had been rebuilt, compared with only 60 percent of small rental properties. A recent report by the Community Preservation Corporation recom- mends a series of improvements to the federal disaster response process, including provision of additional housing vouchers to help displaced renters and special allocation of LIHTC authority to speed rebuilding of affordable housing. The study notes that the award- ing of additional LIHTC authority supported development of 30,000 rentals on the Gulf Coast after Katrina. In contrast, the Northeast was without similar authority after Hurricane Sandy and has subse- quently struggled to rebuild its affordable stock. With the divergence between housing costs and household incomes after 2001, cost burdens are a fact of life for nearly half of all rent- ers (Online Figure 1). The lack of affordable rental housing is a conse- quence of not only strong growth in the number of lower-income households, but also steeply rising development costs. The complex set of forces driving these increases includes the escalating costs of inputs and a lack of innovation in production methods, the design of homes, and the means of financing housing. Addressing all of these challenges requires action on the parts of both the public and pri- vate sectors. Government at all levels has a role to play in ensuring that the regulatory environment does not stifle much-needed inno- vation, and that tax policy and public spending support the efficient provision of moderately priced housing. Industry has its own part to play in fostering and advancing new approaches. However, the market simply cannot supply housing at prices afford- able to the nation's lowest -income households. The best means of supporting these families and individuals depends on both local market conditions and the value placed on other policy goals, such as helping to revitalize communities and improving the geographic distribution of permanently affordable housing. Another consider- ation for policymakers is to find ways for housing assistance pro- grams to enable and encourage economic mobility. While there is much to debate about the best approaches to pursue, the current level of rental housing assistance is grossly inadequate. It is concerning that discussions about federal tax reform have not addressed ways to expand the availability of affordable housing, and proposed measures could even erode the limited support that currently exists. As a growing body of evidence shows, the costs that poor -quality, unstable housing situations impose on individuals and families—as well as on broader society in terms of lost productivity and the strain on public budgets—are simply too high to ignore. More than a third of US households live in rental housing. After the Great Recession and housing market crash, the number of renters surged across all ages, races/ethnicities, and household types, with especially large increases among higher -income and older households. Nevertheless, younger, lower- income, and minority households are still the most likely to rent and thus make up large shares of renters. While growth in rental demand now appears to be slowing, demographic changes will continue to drive strong increases in the number of renter households over the coming decades. A DECADE OF SOARING DEMAND COMING TO AN END Rental housing demand has grown at an unprecedented pace for more than a decade. According to the Census Bureau's Housing Vacancy Survey, the number of renter households jumped by nearly a third, or roughly 10 million, between the homeownership peak in 2004 and 2016, From 2010 through 2016, growth has averaged 976,000 renters per year, far exceeding the 430,000-500,000 added annually in the 1970s and 1980s when the baby boomers started to enter the rental market. As of mid -2017, the number of US renters stood at 43 million. The surge in renter households erased a decade of declining demand between 1994 and 2004, when the national rentership rate fell from 36 percent to just 31 percent (Figure 7). The share of renter households was back up above 36 percent by early 2015, where it has stabilized now that fewer owners are losing their homes to foreclosure and more young households are buying first homes. As a result, rental markets generally are drawing less demand from homeowner markets. The latest survey data are beginning to reflect these trends. All of three annual Census Bureau household surveys reported slow- downs in renter growth in 2016. Indeed, the Housing Vacancy Survey showed a year -over -year decline in the number of renter households in mid -2017. But given that the trend is new and survey data are unprecise, the full extent and duration of the decline in rental demand are still unclear. Assuming that the homeownership rate does stabilize, renters should continue to account for roughly a third of household growth in the years ahead. THE SURGE IN HIGH-INCOME RENTERS Households of all ages, incomes, races/ethnicities, and family types helped to fuel the recent growth in renters, but the role of high- income households is particularly noteworthy. According to the Current Population Survey, households with real annual incomes of $50,000 or more—a group that accounted for just one-third of all renter households in 2006—drove well over half (60 percent) of the growth in renter households from 2006 to 2016. Moreover, house - 7 8 61r—r �4a,'.�IISf rr"srt{"rati"� a'IG,, n a •. IAE zr '�n'X%J°" 4�tg by js >'sT�i vd t �'k AWn, Tµrzc y s�� t i,zm i t 5gn n 1 'z P�.,.../uE.,ave;Svxa3 �"1 �n:da,�rd'uMbf1E7 .i$�.w1,; ,'F�tafv�V�ta� �s.✓�'.ss.�="�s2a..� � �d,3 � . , xrtn t A =. `,k.,. k a _.� ..5.. a;J .:...e.,v.. r:°,.axS_ NAdt....v � �..,,t `' The Wave of Growth Since 2004 Has Lifted the Number and Share of Renter Households Millions 45,0 42Z 400 37.5 35.0 32.5 36.0 percent 1966 1967 1986 1969 1990 1991 1992 1993 1994 1995 1996 1997 1996 1999 2000 2001 2002 2063 2004 2095 2006 2967 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 yJ Renter Households (Left scale) — Hentarship Hato lRight scald Note', Estimate for 2017 is the average of second -end third quarter data. Source'. JCHS tabulations of BS Census Bureau, Housing Vacancy Survey. holds with real annual incomes of $100,000 or more—making up just 9 percent of renters in 2006—were responsible for 29 percent of the 9.9 million increase in renters over the decade (Figure 8). Many, though not all, of the outsized increases in higher -income renters were concentrated in high-cost metro areas. For example, households earning $100,000 or more accounted for 65 percent of the growth in renter households in the New York City metro and fully 93 percent in San Francisco (Figure 9). But even in metros where they were less prevalent, higher income households were respon- sible for significant shares of renter growth, including Miami (15 percent) and Phoenix (20 percent). Strong growth in high-income renter households was driven in large measure by sharply higher rentership rates among this group. Indeed, the share of households with incomes of at least $75,000 that rented their housing jumped by 6.9 percentage points in 2006-2016, more than twice the 3.3 percentage point increase among households earning less than $50,000. Without this increase in rentership rates among high-income households, there would be 3.4 million fewer renters today. The strong growth in higher -income households altered the distri- bution of renter household types. Unlike lower-income renters, who primarily live in single -person households, higher -income renters live in a variety of household settings that are likely to include mul- tiple adults, such as married couples or unmarried partners. These types of households, which are apt to have at least two earners, made up half of the growth in renters earning $50,000 or more over the past decade. 37 35 33 31 29 27 25 ROLES OF OLDER AND WHITE HOUSEHOLDS While the largest increase in rentership rates was among young, high-income households, much of the overall growth in renter house- holds was driven by older households. Indeed, adults age 50 and over accounted for half of the increase in the total number of renters in 2006-2016 (Figure 10). Although much of this increase simply reflects changes in the age structure of the population, rising rentership rates among this age group lifted the number of older renters well above what population aging alone would suggest. In addition, higher rentership rates among households in their SOS and 40s also helped to offset what would have otherwise been declines among that age group as the youngest baby -boomers moved into their 50s. Given that older adults are likely to live alone, the increase in older renters added significantly to the number of single -person house- holds. Single persons accounted for 37 percent of renter household growth overall in 2006-2016, but fully 52 percent of the growth in renter households age 50 and over. By comparison, single persons made up only 20 percent of the increase in renter households under age 50. As a result, three out of every four single -person renter households added over the decade were at least age 50. After single persons, married couples without children accounted for the next -largest share of renter growth (17 percent). This group includes older renter households with adult children no longer liv- ing at home. Running a distant third, married couples with children made up just 10 percent of the growth in renter households. A resurgence of renting among white households also helped to keep demand on the rise. The number of renter households headed by a Higher -Income Households Represent a Growing Share of Renters... Lessthan $25,600-- $50,000- $75,000- $100,000 $25,000 49,999 74,999 99,990 or More Household Income Share of Renter Households In 2006 °w1 Share of Renter Households in 2016 ■ Share of fleeter, Household Growth 2006-2016 Now Household incomesam In constant 2015 dollars, adjusted lar Inflation using the CPI -U Im All Items, Bomcn: JCHS tabulations of US Census Bureau, Current Papulation Survays. ...Particularly in High -Cost Metros Like New York, San Francisco, and Washington, DC Growth in Guntur Households, 2006-2015(Thousands) 350.................................................................................................._...__....................._...__.__...._........................... 300 250 200 150 100 50 0 ,50 _— --.._.........._-___ ................ _........ ....................... _.___.................... ._.�.._...__.... Naw York City L., ngelos Heroine Miami Washlnpaun. UC Phoenix San Pmnntsoo Metro Area Household Income it Less thin $25,000 Td$25,000-49,999 0$50,000-74,999 �$75,OW-9Q999 x$100,000 or More New Household incomes are in constant 2016 dollars, adjusted formulation using rhe CPI -U VAR Items. Source: JCHS tabulations of US Census Bureau, 2016Amerisan Community Survey l -year Estimates using the Missouri Census Data Center MABLB/Geomnl4, With Rising Rentership Rates and a Growing Adult Population, Households Age 50 and Over Accounted for Half of the Recent Surge in Renters Change in Renter Households, 2006- 2016{Nlillions{ 1A 0.5 Ho 0.5 Under 25 25-29 30-34 35--39 40-44 45-49 55-54 55-59 50-64 65-69 70-74 75--79 30 and Over IN Change Assuming 2066 RontersMp Oates -IActual Change Source, JCI IS tabulations of US Census Bureau, Current Papulation Surveys. Age of Household Head 9 white person was up by 3.6 million in 2006-2016, more than offset- ting the 2.6 million decline that had occurred over the previous 20 years. While minority renters collectively drove most of the increase in renter households over the decade, white households were responsible for the largest share of growth (37 percent), followed by Hispanics (27 percent), blacks (21 percent), and Asians/others (15 percent). The majority of the increase in white renters (65 percent) was among households age 50 and over, but younger households— particularly those in the 25-34 year-old age group—also contributed significantly to growth. PROFILE OF RENTER HOUSEHOLDS Despite the changing composition of renter household growth over the past decade, households that rent their housing differ in systematic ways from those that own homes (Figure 771. In particular, renters tend to be younger, with a median age of 40 in 2016 compared with 56 for homeowners. Rentership rates decline with age, dropping from more than two-thirds (68 percent) of households under age 35 to less than a quarter (24 percent) of households age 55 and over. Nevertheless, the overall aging of the population has meant that one in three renters is now over the age of 50. Although the majority of renter households are white, the minority share of renters (47 percent) is twice that of homeowners. As mea- sured by the Current Population Survey, rentership rates of Hispanic, black, and all other minority households are higher than for whites both overall and across age groups. Renters are also more apt to be foreign bom than homeowners, with immigrants accounting for 20 percent of renters but just 12 percent of owners. Renter households are smaller on average than owner households. Over a third of renter households (37 percent) are single persons living alone—far higher than the 23 percent share among owners. Still, families make up a significant share of renter households, and families with children in fact account for a larger share of renter households (33 percent) than homeowner households (30 percent) in the 2016 ACS. Household incomes for renters are lower than for owners. According to the American Community Survey, the median income for cash renters in 2016 was $37,300—more than 49 percent below the medi- an income of owners of $73,100. In addition, two-thirds of all renter households (30.5 million) were in the bottom half of the income distribution (below the US median household income). As measured by HUD's Worst Case Housing Needs 2017 Report to Congress, 64 percent of renters had low incomes (80 percent or less of area medi- ans) and 26 percent had extremely low incomes (30 percent or less of area medians). In addition to their lower incomes, renter households have very little savings and wealth. The latest Survey of Consumer Finances indicates that the median net worth of renter households was only $5,000 in 2016, a small fraction of the median owner's net worth of Renters Are More Likely than Owners to Be Young, Low Income, and Single Shore of HorsoheIus (Portant) 160 90 90 70 60 50 40 30 20 10 0 10 Reuters Owners 100 90 00 70 50 50 40 30 20 10 0 Renters Owners Age of Household Head Household Income ■ Under 29 IN 65-64 ! Undor$15,000 $45,00 74,999 '. '. 25-34 065 and Over 1:-$15,01129,999 0$75,000 and Over 039-54 $30144,999 Note. Families with children include any household with a child under the age of 18. Source'. JCHS tabulations of US Census Bureau, 2018 Amerhan Community Survey 1 -Year Estimates. 100 90 80 70 60 50 40 30 20 10 0 Renters Owners Household Tope N Single Person IN Marded/Partnered without Children Other Family/Nonfamily 0 Farniliaswith Children $230,000. The median amount of cash savings held by renters was similarly low at just $800, compared with $7,300 for owners. The discrepancy in wealth is even greater among households headed by adults age 65 and over, who generally need to draw down their assets in retirement. The median net wealth of older renters was $6,700 in 2016, compared with a median for older homeowners of $319,200. Not all of this difference is due to housing wealth, however. The non -housing wealth of renters in all age groups is also several times lower than that of homeowners. THE GEOGRAPHY OF RENTING The 2016 American Community Survey indicates that just under half (46 percent) of all renter households reside in principal cities of metropolitan areas. By comparison, about a quarter (26 percent) of homeowner households live in these locations. Among the nation's 100 largest metro areas, the highest rentership rates are in high-cost markets such as Los Angeles (S2 percent) and New York City (49 percent), as well as in fast-growing areas such as Las Vegas (49 percent) and Austin (42 percent). The shares of renters are much smaller in low-cost and slow -growth areas like Detroit (32 percent), Grand Rapids (29 percent), and Pittsburgh (31 percent). Rentership rates are also relatively low in metros with large shares of older householders, such as Cape Coral, Deltona, and several other Florida metros, consistent with the high homeownership rates among this age group. Higher -income households are more apt to rent in high-cost hous- ing markets (Figure 12). This makes the renter population in these areas somewhat more economically diverse than the US average. However, these metros still have large numbers of low-income renters and the highest rates of renting among low-income households. Given their greater income diversity, renters in high-cost metros are also more diverse in terms of household type. Nearly half (45 percent) of all married couples with children that live in Los Angeles and San Diego rent their housing. By comparison, the share of mar- ried couples with children that rent is just 15 percent in Pittsburgh and 18 percent in Philadelphia. At the same time, high-cost markets tend to have larger shares of nontraditional households, which may include extra workers to help afford the high rents. For example, households with three or more adults made up 13 percent of renter households nationally in 2015, but 23 percent in the Los Angeles metro area. RENTING THROUGH THE LIFECYCLE The vast majority of households rent at some point in their lives. According to a JCHS analysis of the Panel Study of Income Dynamics (PSID), about half (49 percent) of owners under age 60 in 2015 had been renters at some point within the previous 20 years. Among owners under age 50, the share was even higher at nearly three- quarters (72 percent). Renting Is More Common in High -Cost Housing Markets, Especially Among Higher -Income Households Rentership Rate(Percent) ag 70 so 50 40 30 20 19 Loss the o$15,000 $15,990-29,999 439,000-44,,999 $45,00074,999 $75,000 or More Total Household Income Largest 100 Mottos ®10 Highest Cost Mottos 0 Middle 30 Metros L�i 10 LowesFCost Mottos NBest of US Nom'. Mottos aro the bar mount by paper I at on 45 dullard in the 2016 Amu rican Community Survry. Somce'. JCHS tabulations of US Doasus Bureau. 2616 American Community Survey i Year Estimates using the Missouri Census Data Center MABLF/Gerro04, 12 Over the Next Ten Years, Aging of the Baby Boomers and Millennials Will Drive Growth in Renter Households Renter Households (Millions) 7 6 5 4 3 2 0 Undri 25-29 30-34 35-39 40-44 4549 50--94 55-59 66-64 65-50 70-74 75-79 80and Over Age of Household Head 0 2006 c` 2016 0 2025 Note: JCHS projection for2025 assumos homeawnershlp rates by five yearns group and raco/nthniuity hold st current valvas. Sources JCHS ta5ulalions of Us Contra Bureau, Current Population Surveys; JCHS 2016 Household and Tenure Projections. Without the downpayment and other costs entailed in buying and selling homes, renting is often an affordable housing option for young adults. Indeed, the 2015 American Housing Survey shows that 86 percent of all newly formed households were renters. Low trans- action costs also make renting a good choice for households that move frequently. As measured by the Current Population Survey, renters accounted for three out of four residential moves in 2016, as well as for the majority of moves made by all age groups. But renting is not merely a life phase or a steppingstone to home- ownership for all households. The JCHS analysis of PSID data also indicated that 17 percent of renters in 1995 remained rent- ers through 2015, In addition, 23 percent of homeowners in 1995 switched to renting sometime in the ensuing two decades, often in response to changes in family structure and other life events. For instance, renters made up over 80 percent of recent movers who were divorced or separated. Other owners shifted to renting to have less responsibility for home maintenance. This preference, along with the desire to downsize or to meet accessibility needs, is reflect- ed in the increasing shares of renters among the oldest age groups. PSID data indicate that 1 in 12 owners age 55-64, 1 in 8 owners age 65-74, and 1 in 5 owners age 75 and over made own -to -rent transi- tions between 2005 and 2015. THE OUTLOOK Given the sharp swings in rentership rates over the past two decades, predicting future rental demand is difficult. Shifting preferences, macroeconomic conditions and government policy help to shape many of the factors that determine rates of renting and owning, including housing affordability, mortgage accessibil- ity, labor markets, and household incomes. As a starting point, though, future rental demand depends on the rate of household growth. JCHS projections suggest that overall household growth will be strong over the next 10 years as increasing numbers of the large millennial generation reach adulthood (Figure 131. At the same time, the aging of the baby -boom generation will lift the number of older households. Household growth is therefore expected to total 13.6 million in 2015-2025, before moderating to 11.5 million in 2025-2035 when losses of older households begin to accelerate. Despite the aging of the adult population (which tends to favor high- er homeownership rates), certain other demographic forces should support healthy growth in rental demand. Over the next 10 years, the younger half of the millennial generation—the largest genera- tion in US history—will move into their 20s and 30s, the age groups most likely to rent. In addition, minority households are expected to account for nearly three-quarters of household growth in 2015-2025 and fully 90 percent in 2025-2035. If minority homeownership rates remain at current levels, the national rentership rate will increase in the coming decades. Taking all of these forces into account, the base scenario from the 2016 JCHS household tenure projections shows that, if homeowner- ship rates stabilize at their 2015 levels, underlying demographics— that is, growth and change in the composition of US households by age, race/ethnicity, and family type—will support the addition of 4.7 million renters and 8.9 million homeowners between 2015 and 2025. The nation's rental housing comes in all structure types, sizes, prices, and locations. But with the recent growth in high-income renter households, most additions to the stock have been at the upper end of the market. In contrast, the supply of rentals affordable to low- and moderate -income households has not kept pace with growth in demand, contributing to the spread of housing cost burdens. Atthe same time, the rising costs of land, materials, and construction make development of lower -rent units increasingly difficult. SNAPSHOT OF THE RENTAL STOCK ]CHS analysis of the 2016 American Community Survey indicates that the rental stock comprises 47.1 million units, or 35 percent of the national housing supply. Just under 44 million of these units are currently occupied. Of the 3.4 million units that are vacant, 82 per- cent are available for rent while the remaining 18 percent are rented but unoccupied. It is a common misconception that rental housing consists almost entirely of apartments in multifamily buildings. In fact, multifamily units account for 61 percent (28.9 million units) of the nation's rental stock, distributed across various -sized properties. Single-family homes make up a substantial—and, until recently, fast-growing— share of rentals (Figure 14). This stock includes 13.1 million detached homes, 2.9 million attached homes, and 2.1 million mobile homes, RVs, and similar dwellings. Nearly half (46 percent) of all renter -occupied units are located in the principal cities of metro areas, 42 percent in surrounding sub- urban communities, and the remaining 12 percent in non -metro areas. Types of rental housing vary substantially by location, with large apartment buildings of. at least 20 units concentrated in urban areas and single-family rentals found primarily in suburban and non -metro areas. GEOGRAPHIC VARIATION IN SUPPLY In the nation's 100 largest metros (home to almost 70 percent of all US households), detached single-family homes make up 24 percent of the rental stock while attached single-family units add another 7 percent. The remaining units are in multifamily structures, with 17 percent in small buildings of 2-4 units, 24 percent in mid-sized buildings of 5-19 units, and 25 percent in large buildings of 20 or more units. Mobile homes provide another 2 percent of the housing stock in the largest metros. But given differences in topography, density of development, and average age of the stock, the mix of rental housing varies widely across metro and rural areas. For example, detached single-family 14 Single -Family Homes Now Account for Well Over One -Third of the Nation's 47 Million Rental Units Share of National metal Stock Multitamilies with 2 -4 Units 18% , Multifamilics with 5-19 Units 22% O1n110-Family Homes H94'n Muhifamilies with 20 or Mora Units 21% Notes. Stack estimates include rentor -occupied units, vacant units torrent, and muted but unoccupied units. Single family homes include detached and attached units, mobile homes, and units such as Hi and boats, Source. JCI IS tabulations of US Census Bureau, 2016 American Community Survey 1 Year Estimates, Individual Investors Are the Largest Owners of Rental Stock, with Most of Their Units Concentrated in Small Buildings Share of Hental Units IPercent) too g0 30 70 60 50 40 30 20 10 0 All Urice ]Unit 2-4full 5-49made 50 of Moro Units Ownership ■ Individual Investor !3I nP/LP/LLC N NI Other Structure Type 0 HEIT/Real Estate Corporation 0 Non-Profltar Co op NoIn All other includes tenants in common, general partnerships, trustees forestate, and units far whleh ownership was act reported, Source'. JCHS tabulations of US Census Bureau, 2015 Rental Housing Finance Survey. rentals make up just 8 percent of rentals in Boston, but 51 percent in Stockton (Online Figure 2). Over a third (35 percent) of Boston's rental stock consists of units in buildings with 2-4 apartments. Another 22 percent of rentals are in buildings with 5-19 units, 29 percent are in buildings with 20 or more units, and the remaining 6 percent are divided between attached single-family homes (5 percent) and mobile homes and other structures (1 percent). In contrast, just over 10 percent of the rental units in Stockton are in buildings with 2-4 units, 14 percent are in buildings with 5-19 units, and slightly more than 12 percent are in buildings with 20 or more units. Attached single-family homes (10 percent of the rental stock) and mobile homes (just under 3 percent) are somewhat more common in Stockton than in Boston. In rural areas (as defined by the US Census Bureau), the rental stock primarily consists of single-family homes. Indeed, almost three- quarters of rural rentals are single-family units. The highest con- centrations of single-family rentals are in New Mexico (89 percent of the rural stock) and Oregon (86 percent). But even in states with the smallest shares (Massachusetts, New Hampshire, and Vermont), single-family homes still make up about half of rural rentals. Mobile homes are also an important component of the rural rental stock, contributing fully 20 percent of rural rental housing nationwide. At the state level, however, mobile homes are much more common in the rural communities of South Carolina (39 percent of the stock) and North Carolina (36 percent) than in the rural areas of Hawaii (0.4 percent of the stock) and Massachusetts (2.0 percent). OWNERSHIP OF RENTAL HOUSING Individual investors are the largest group of rental housing owners, followed by business entities such as limited partnerships (LPs), limited liability companies (LLCs), and limited liability partnerships (LLPs). Individual investors primarily own single-family rentals and small apartment properties, while LPs, LLCs, and LLPs own a majority of large apartment properties. As a result, individuals own three-quarters of rental properties (74 percent) but just under half of the nation's rental units (48 percent), while business entities own 15 percent of rental properties but a third of units (Figure 15). Housing cooperatives and nonprofit organizations own 2 percent of rental properties and 4 percent of rental units, while real estate corpora- tions and investment trusts own 1 percent of rental properties and 5 percent of rental units. The remaining 8 percent of properties and 10 percent of units are under other forms of ownership, such as trustee for estate, tenant in common, and general partnership. The latest Rental Housing Finance Survey reports that the single- family ownership share of individual investors slipped from 83 per- cent in 2001 to 76 percent in 2015 as institutional investors gained a foothold in the market. But this decline in individual ownership likely overstates institutional investment in single-family rentals. Indeed, real estate corporations and investment trusts owned only 250,000 single-family rentals in 2015. In addition, many individual investors reportedly transferred ownership of their properties to LLCs in recent decades to protect against legal problems and to take advantage of tax benefits. Along with shifting patterns of ownership, motivations for acquir- ing single-family rental units may have also changed. While there is little research available on this topic, one study suggests that prior to the housing market crash, the two major reasons that owners bought single-family rentals were as primary residences, which they then decided to rent, or as income -generating invest- ments. However, the housing boom and bust encouraged more speculation in the single-family rental market, including by mom- and-pop owners, which may mark a shift in their expectations. Institutional owners also jumped into the single-family rental market after the bust, but their longer-term presence in the mar- ket is unclear. Understanding the evolving nature and financial motivations of rental property owners is important for designing policies that protect naturally occurring affordable units that may be at risk of either under -investment and deterioration or of upgrading and gentrification. In both cases, these units would be lost from the low-cost stock. DUILDING AGE AND ACCESSIBILITY The median age of occupied rental units in 2015 was 42 years— somewhat higher than the median of 37 years for owner -occupied homes. The age gap between owned and rented units has been growing since 1985, when both types of units had an average age of 23 years. This disparity reflects the slowdown in rental construction in the 1990s following the booms of the 1970s and 1980s, as well as significant construction of owner -occupied housing in the early 2000s. In addition, a minor but still sizable share (8 percent) of rental housing was built before 1920. With the recent uptick in multifamily construction since 2015, however, the age gap between owned and rental units may be narrowing. Today, the oldest units in the occupied rental stock are apartments in multifamily buildings with 2-4 units (median age of 51 years) and detached single-family homes (median age of 49 years). The typical renter -occupied single-family home is 10 years older than the typical owner -occupied home. Meanwhile, apartments in buildings with 20 or more units had a median age of 38 years in 2015, and the typical mobile home rental had the lowest median age of 29 years. Older rental housing is more likely than newer housing to have qual- ity and safety issues that may jeopardize the health of occupants. Under HUD definitions, 13 percent of occupied rental units built before 1940 have physical inadequacies, compared with 6 percent of units built in 1990 or later. Although overall inadequacy rates for renter -occupied housing are low (9 percent), they are still more than double those for owner -occupied homes (4 percent). Larger Multifamily Properties Attract a Significant Share of Older Renters Share of Renters Urercentl 50 45 40 35 30 25 20 15 10 5 0 Undor25 25-34 35-44 45-54 55-64 65-74 75orBy., Age of Household Bead Strurlure Type MSingle-pamilyHome 11 Multdamilywith 2-4Unds ■ Multifamily with 3- 19 N Multifamily with 20 or More Units Note, Single-family homes include detached and attached units, mobile homes, and other units such as RVs and boats. Source, Ji tabulations of US Census Bureau, 2016 Amehean Community Survey 1 -Year Estimates. 15 Low -Cost Rentals Are More Evenly Distributed Across Building Types than High -Cost Rentals Pentyl Untie (Millions) 4.0 3.5 30 2.5 2.0 1.5 10 05 00 Under MO $650-049 $059 1,099 $1,100-1,499 S1,500 and Over Monthly Housing Cost Structure Type N5nele-Family,Home 0 Multifamily with 2—fUnns, 0Merril ilywith5-19here IN Multifamily with 20 or More Units ■ Mail Home/Other Nates: Monthly housing costs Include rent and utllitlae, Rental units axcluda vacant units and units where nocash rent Is paid, Single family human Include attached and detached author Other structures Include units such as boats and 6Vs, Smmv.JCHS tabulations of US Census Bureau, 2016 American Community Survey 1 -Year Fatimelve Another limitation of older rental units is that they are seldom accessible to households with mobility or other physical challenges. As of 2011, only 3 percent of rental units provided three basic uni- versal design features (extra -wide hallways and doors, bedroom and bathroom on the entry level, and a no -step entrance). Newer and larger buildings, however, tend to offer more of these amenities: one- fifth of apartments in buildings with 50 or more units dating from 1990 or later provided all three features. Given that accessibility needs increase with household age, it is therefore unsurprising that about half of the renters age 75 and over live in larger apartment buildings (Figure 16). Accessibility features are less common in the single-family and smaller multifamily rental stocks. Just 2.4 percent of renter -occupied detached single-family homes and apartments in buildings with 2-4 units have the three basic universal design features, along with 2.5 percent of attached single-family homes and 1.2 percent of mobile homes. The fact that the majority (52 percent) of renters in the 75 -and -over age group live in single-family homes and apartments in small buildings is cause for concern because these rental units are unlikely to provide the accessiblity features that would enable tenants to age safely in place. The availability of rentals with accessibility features varies by region. With its older stock of primarily small properties and multi -story structures, the Northeast has the lowest share of renter -occupied accessible units, with only 2.0 percent offering no -step entry, single -floor living, and extra -wide hallways and doors, followed by the South (3.3 percent), West (3.4 percent), and Midwest (3.6 percent). While no -step entries and single -floor liv- ing are more common in the South and West, in no region does the share of units with extra -wide hallways and doors exceed the single digits. VARIATION IN RENTS The median monthly housing cost (including rent and utilities) for all occupied rental units was $981 in 2016. Location is perhaps the strongest determinant of cost. In the high-priced San Francisco metro area, for example, well over half (62 percent) of occupied units rent for more than $1,500 per month, compared with 17 per- cent in mid -priced Dallas and just 5 percent in low-cost Cleveland (Online Figure 3). The median rent for a detached single-family home, typically the most expensive type of rental unit, was $2,125 in San Francisco, $1,240 in Dallas, and $920 in Cleveland. Monthly rents vary widely by structure type, ranging from $890 for apartments in buildings with 2-4 units, to $1,070 for those in build- ings with 50 or more units, to $1,087 for single-family homes. Rents also vary with age of the home, with the newest ones (built in 2014 or later) commanding the highest median rents ($1,318) and those built in the 1970s the lowest ($915). The low-cost stock (renting for under $650 per month, or roughly the bottom quintile for rents) consists of units in a broad mix of struc- ture types ]Figure 17). In 2016, the number of occupied low-cost rentals was distributed fairly evenly across structure types, with 1.8 million each in single family homes and buildings with 2-4 units, 1.9 mil- lion in buildings with 5-19 units, and 2.1 million in buildings with 20 or more units. Mobile homes account for another 724,000 low-cost units. In contrast, some 71 percent of higher -cost units (renting for at least $1,500 per month, or roughly the top quintile) are attached or detached single-family homes or in buildings with 20 or more units. Rental apartments in buildings with 2-4 units are the most likely to be affordable, accounting for 22 percent of the lowest -cost stock but just 13 percentof the highest -cost supply. Multifamily buildings with 5-19 apartments are also more likely to have moderate rents, provid- ing 27 percent of units renting for $850-1,099 and only 16 percent of highest -cost rentals. ADDITIONS TO THE RENTAL STOCK The number of single-family rentals shot up from 14.2 million units in 2001 to 18.2 million units in 2016—a 29 percent increase that far outpaced the 18 percent growth in the overall rental stock. Own - to -rent conversions drove almost all of this gain, with only 575,000 single-family homes built expressly for the rental market over this period. Indeed, in 2011-2013 alone (the last year for which a constant sample is available), tenure conversions of occupied housing units resulted in a net gain of more than 420,000 single-family rentals. However, this trend may be moderating. According to the American Community Survey, 2015 was the first year since 2006 when the number of single-family rentals declined, suggesting that there were at least some conversions back to owner occupancy. While turning up again in 2016, growth in the number of single-family rentals none- theless remained well below average annual levels in the previous decade. Additions to the Rental Stock Are Increasingly at the Higher End Share et Recently guilt Units Percanq 45.........._.._.............................................................................._........... 40 35 30 UntlorS650 $950-849 $950-1.099 $1,100-L499 $1,590 and Nor Monthly housing Cost '?:i 2001 02016 Notes: Recently bulltunits in 21101120161 warn bulli 18 6420012016) Monthly housing costa Include rent antl utilities card have bean adjusted to 2015 dollars using the CPI-0AII Items Less Solos, 0emal units exclude vacant units and units where no cash rent ie paid. Source : JCHS tabulations of US Census 6amau. 2001 and ell 6 American Community Santry 1 Yon Estimates. newly built units renting for less than $850 per month fell from 42 percent of the rental stock to 18 percent. RISING CONSTRUCTION COSTS At least part of the reason for the surge in high-end construction is that developing multifamily housing is increasingly expensive. Between 2012 and 2017, the price of vacant commercial land—a proxy for developable multifamily sites was up 62 percent. Over this same period, the combined costs of construction labor, materi- als, and contractor fees rose 25 percent, far faster than the general inflation rate of just 7 percent (Figure 19). Cost increases for key build- ing materials, such as gypsum, concrete, and lumber, have also out- paced inflation in recent years. Data obtained from RS Means indicate that construction of a three - Meanwhile, most new rental construction consists of larger proper- story, 22,500 square -foot apartment structure with a reinforced ties. Census construction data show that the share of completed rentals in buildings with 20 or more units grew from 54 percent in 2001 to 83 percent in 2016. As a result, apartments in these larger properties accounted for just over one-fifth of the rental stock (9.9 million units) in 2016, an increase of 37 percent—or more than 2.6 million units—since 2001. In addition to their concentration in large structures, many recent additions to the rental stock have high rents (Figure 18). The share of newly built units renting for $1,500 or more soared from 15 percent in 2001 to 40 percent in 2016. Over this same period, the share of concrete frame—including the cost of materials, labor at union wages, and fixed contractor and architectural fees, but excluding land costs would average $192 per square foot in 2017. The cost of building that same structure in 2016, however, would have been 8 percent lower. Of course, costs vary widely by location. For example, construction costs for this sample building would be 43 percent above the national average in New York City and 17 percent below the national average in Dallas. Adding to development costs, recent construction of rental hous- ing is largely concentrated in central cities. Between 2013 and 2016, 17 Construction Costs Are Rising Much Faster than Inflation Index 220 — - 200 - 160 160 —: 140 120 -' 100 -a 2001 2003 2005 2007 2009 2011 2013 2015 2017 —Co -Stn, Vacuum Commarcial Land Index — BLB Construction Cost Index r Conscuner Price Index Notes', The ALB Construction Cast Index measures the hid cost of construction, which !,,ludas lance building materials, and contractor fees. The Ca -sear Vacant Commerciol Land Index serves as a proxy for developable multifamily sites. Soumes: CaStarVacant Commemlal Land Index; ALB Construction Cost Ii and US Bureau of Labor Statistics, Consumer Price Index for All Urban Consumars. nearly 60 percent of new unfurnished units were built in the princi- pal cities of metro areas—up 10 percentage points from the period between 2000 and 2012. This trend appears to have continued in early 2017, with the share of rental completions in principal cities nudging above 65 percent. The supply of developable sites in central locations is extremely limited, which raises land prices and generally entails more exten- sive permitting, higher legal fees and site preparation costs, and the design of taller, more expensive buildings. According to the Survey of Market Absorption, these costs are reflected in the nearly 15 percent differential in median asking rents for new apartments built in prin- cipal cities ($1,600) than in suburbs ($1,390) in 2016. Regardless of location, though, new multifamily rentals are less affordable to the growing number of households with middle and lower incomes. The real median asking rent for newly completed multifamily units increased 27 percent between 2011 and 2016, to $1,480, while real median renter income increased only 16 percent over the same period. In addition to rising construction costs, this jump in asking rents also reflects increased construction of luxury apartments for higher -income renters. THE OUTLOOK Strong demand has sparked the addition of millions of rental units over the past decade. This growth has come from construction of new units, mainly in large apartment buildings, as well as conver- sion of single-family homes from owner occupancy. However, with the aging of the overall stock and new construction focused pri- marily on the high end of the market, concerns are mounting that the rental supply will have even less capacity to meet the needs of lower- and middle-income households or the growth in demand for accessible housing as the population ages. While local policymakers have little sway over the price of construc- tion materials, they do influence the amount of land available for high-density development, the process needed to gain approvals, and the characteristics of housing that is allowed—all of which help determine the amount, type, and cost of the housing that is built. Local governments can therefore promote construction of much- needed rental units (particularly lower -rent units) by expediting approvals; guaranteeing by -right development of small multifamily buildings, particularly those with affordable units; reducing parking and other property requirements; and allowing higher densities for projects that are transit -accessible. For their part, developers have increasingly adopted cost-saving technologies and switched to lower-cost building materials—for example, using plastics for plumbing and electrical boxes or relying more on prefabrication and modularization, which can significantly reduce waste and construction time. Collectively these efforts would reduce per unit development costs and the rents that households have to pay, ultimately encouraging more construction targeted to lower- and middle-income renters. Investments in energy efficiency would also provide long-term utility savings for tenants and could reduce maintenance costs for owners. Efforts to preserve the stock of older affordable rentals are also vital. Expanding existing approaches can help. For example, cer- tain states and localities allow the use of housing trust funds for operating and maintenance costs of affordable units, as well as for emergency repairs. The National Housing Trust Fund is also making a limited share of program funds available for these purposes. Real estate tax relief programs can also intent landlords to maintain their affordable units in good repair. Finally, programs that help nonprofits purchase lower -rent, unsubsidized units in exchange for affordability restrictions can help prevent further losses from the affordable supply, particularly in neighborhoods with rising rents. While the fundamentals remain strong for investors, there are signs that rental markets are at a turning point. Real rents are still climbing, but at a slower pace now that vacancy rates are ticking up. Returns to rental property investors remain healthy, but the influx of high-end supply has begun to dampen financial performance in many prime urban locations. Meanwhile, conditions in the vastly undersupplied low-cost segment continue to be extremely tight. RENTAL HOUSING'S ROLE IN THE ECONOMY Rental housing is an increasingly important contributor to the US economy. According to Bureau of Economic Analysis estimates, households spent $519 billion on rent alone last year, accounting for 2.8 percent of GDP in 2016—up substantially from the 2.2 percent share averaged during the boom years of the 2000s, Indeed, renters' real aggregate housing expenditures climbed a strong 3.2 percent annually in 2006-2016, and drove 58 percent of the growth in domes- tic personal housing consumption over the decade. With the sustained strength of rental demand and sluggish recovery in single-family construction, over a third of housing starts are now intended for the rental market. This is a larger share than in any year since 1974. Before the recent run-up in multifamily construction, rentals accounted for only about one in five new homes started in a single year. Among multifamily properties, the share of starts intend- ed for the rental market was 93 percent in 2016. Among single-family homes, 4.9 percent are now being built as rentals, significantly higher than the 2.2 percent share averaged in the 1980s and 1990s. Investments in new multifamily housing have also helped to drive the economy. The multifamily share of private domestic investment in new permanent residential structures grew from just 11 percent in 2000 to nearly 20 percent in 2016. The Census Bureau estimates that the value of private multifamily construction put in place (including labor, materials, soft costs, taxes, and profits) exceeded $62 billion in the 12 months ending in August 2017, similar to multi- family activity near the peak of the housing boom. In sharp contrast, the value of new single-family construction remained nearly 50 percent below the 2006 peak. ROBUST GROWTH IN RENTAL SUPPLY Unprecedented growth in renter households—totaling nearly 10 million between 2006 and 2016fueledone of the fastest rental construction recoveries in history. After hitting a low of just 90,000 units in early 2010, the number of rental housing starts peaked at a 408,000 unit annual rate in early 2017. While this represents the highest volume in any four -quarter period since the late 1980s, 20 ��' *X '4 .�k �j,a° aa;.c it ,r2.,fi. 5,,. � �' n x ➢}� oY While Completions Are Still on the Upswing, Starts of Rental Units Have Slowed Units Intended for Rent Thousands) 600 500 ago 300 200 100 0 1977 1979 1981 1983 198E 1997 1989 1991 1993 1995 1997 1999 2981 2003 2005 2007 2089 2911 2013 2015 2017 IS Completions . Starts Notes'. Date include both multifamily and single-family units, Estimate for 2017 is based on the four quarters ending in 2017:3 Source: Ji tabulations of US Census bureau, New Eesidential Ca emotion recent production of new multifamily units (which make up the lion's share of rental construction) is still slightly below the 420,000 unit annual rate averaged since 1960. Growth in single-family rent- als averaged some 390,000 annually from 2006 to 2016, supplement- ing new construction in meeting the sharp increase in demand. Although the national recovery has been robust, the pace of growth in multifamily construction varied widely across markets. Over the latest cycle from 2010 to 2016, multifamily starts added 15 percent or more to the multifamily stock in fast-growing metros such as Austin, Charlotte, Nashville, and Raleigh, but as little as 1 percent in slow- growing areas like Cleveland and Providence. The largest increases in multifamily supply occurred mainly in the South and West, where production was still catching up with rapid population growth. Overall, however, construction activity has begun to moderate (Figure 20). Indeed, multifamily starts are down 9 percent year-to-date through October 2017 on a seasonally adjusted basis. The slowdown was first evident in 2016 when permitting fell in nearly half of the nation's 50 largest markets. The five markets with the most multi- family permitting in 2013-2015 declined sharply, collectively regis- tering a 35 percent drop in 2016. This total includes declines of more than 50 percent in Houston and New York, as well as more moderate cuts in Dallas, Los Angeles, and Seattle. Permitting in other large markets, like Atlanta and Denver, continued to increase. Meanwhile, multifamily starts also fell in nearly half of the nation's 100 largest metros in the 12 months ending August 2017. By comparison, construction activity slowed in less than two-fifths of these markets just a year earlier. Multifamily starts were down across metro areas of all sizes, with the biggest declines reported in the South and Northeast. Even so, multifamily construction in many locations was still strong by historical standards. In the year ending August 2017, multifamily starts in nearly half of the nation's 100 largest metro areas exceeded their annual averages in the two decades leading up to the housing peak (1986-2005). In 26 of these areas, multifamily starts were up by more than 50 percent. Moreover, starts in several markets where multifamily construction had not fully recovered by 2017—including Jacksonville, Riverside, and Sacramento—remained on the rise. EASING MAINLY AT THE HIGH END With rental demand soaring, the national stock of vacant rental units shrank from nearly 4.5 million in mid -2010 to just 3.2 million in 2016. As a result, the rental vacancy rate fell sharply from 10.8 percent to 6.9 percent in the third quarter of 2016. However, the national vacancy rate rose to 7.2 percent in the third quarter of 2017, suggesting the rental market is at a turning point. Vacancy rates for professionally managed apartments in multifam- ily buildings are even lower. RealPage, Inc. reports a vacancy rate of 4.5 percent in the third quarter of 2017, comparable to those at the peak of the housing boom in 2006. Vacancy rates were under 4.0 percent in more than 40 of the 100 markets tracked, and under 3.0 percent in 16 markets. New High -End Units Have Become Harder to Fill, But Low -Rent Units Remain in High Demand Share of Neer Units Rented Larcent9 100 — _. .........................................--- 98 96 94 92 90 8s 88 84 82 8o Less than $850 $850-1,249 $1,258-1,849 $1,650-2,449 $2,450 or Moro Monthly Asking Rent Year 212015 02016 Nota: The annual absorption rate covers privately financed non-subsidizad, unfurnished rental apartments in buildings m1h five or more units complaint in the previous year, Souse', JCls tabulations of US Census Bureau, Survey of Market Absarnian. But there are signs that conditions are loosening. According to the US Census Bureau, the vacancy rate in multifamily buildings with 5 or more units rose 0.9 percentage point in the third quarter from a year earlier, to 8.5 percent, indicating some easing in that segment. RealPage also reports that the apartment vacancy rate rose by a full percentage point in the year ending in the third quarter, with increases in 95 of the 100 metro areas tracked. Underlying this shift is growing softness at the high end of the mar- ket. In the Class A segment where rents average $1,700 per month, the vacancy rate hovered near 6.0 percent in the first three quarters of 2017upfrom around 4.5 percent a year earlier. This is the high- est vacancy rate reported since 2011, and the highest rate for any property class. Newly constructed high-end apartment properties became more dif- ficult to fill last year. According to the Survey of Market Absorption, 10 percent of rentals completed in 2015 and priced at more than $2,450 remained vacant after 12 months. In contrast, only 2 percent of units with rents below $1,250 were still unfilled within one year (Figure 27). Apartment absorption rates fell most in the principal cities of metro areas, where most new supply has come online. In con- trast, absorption rates were up in suburban and non -metro markets, where fewer new rentals have been added. Demand for mid -market (Class B) rentals, which rent for $1,180 a month on average, has also begun to ease. The vacancy rate in this segment ticked up by a full percentage point to 4.6 percent in the third quarter of 2017. While the rate remains relatively low, this increase indicates that softness in the high-end market is beginning to affect mid -market conditions. Nearly 90 of the 100 apartment markets tracked by RealPage reported a year -over -year increase in Class B vacancies in the third quarter. Meanwhile, the vacancy rate in the lowest -cost segment of the pro- fessionally managed market (Class C) was down to just 3.3 percent in the second quarter of this year—its lowest reading since 2001— before jumping back up to 4.1 percent in the third quarter. Despite this uptick, Class C vacancy rates were at or below 3.0 percent in nearly half (46) of the 100 metros tracked by RealPage. With rents for Class C units about a third lower than the market average, tightness in this segment indicates both ongoing demand for modestly priced rentals as well as a persistent shortfall in supply. Broader measures of vacancy rates that include all rentals confirm these conditions. For example, 2016 American Community Survey data show that vacancy rates for less expensive units (with contract rents below the area median) were below those for more expensive units in 42 of the nation's 50 largest metros. Indeed, 14 large metros reported rates in the lower-cost segment at or below 5.0 percent last year, compared with just 3 metros in 2006. The tightest conditions were in Los Angeles, Portland, San Francisco, and Seattle, where vacancy rates for low-cost rentals were under 3.0 percent. Tlght conditions are also evident in certain rental structure types tracked by the Housing Vacancy Survey. For example, vacancy rates in buildings with 2-4 units—which tend to be older and less expensive—held at 7.0 percent in the third quarter of 2017. Rates for single-family rentals, however, declined to 6.2 percent in response to strong demand and limited inventory. RENTS STILL UNDER PRESSURE The CPI index for rent of primary residence, which covers the broad- est range of rental property types, was up 3.9 percent in the year ending September 2017. Although only a modest gain from the previous year, this increase is still noteworthy because it marks yet another year when housing costs have risen faster than the prices of non -housing goods (Figure 22). Rent increases were highest in the West (5.5 percent) and South (3.5 percent), held steady in the Midwest (at 2.9 percent), and slowed somewhat in the Northeast (from 2.9 per- cent to 2.6 percent). According to RealPage, the year -over -year increase in nominal rents for professionally managed apartments was 2.7 percent in the third quarter of 2017, continuing the slowdown from 4.0 percent a year earlier and 5.6 percent two years earlier. However, trends vary widely across apartment property types. At one extreme, a flood of 21 a erg i¢ y -MN` 5 t e ,+� ft s)Jfi 6k Increases in Rents Continue to Outstrip Inflation in Non -Housing Goods Annual Change (Percent) 7 — 6 5 4 3 2 t a -2 -3 -4 -5 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 E I Prices for All Consumer Items Less Shelter — Rents for Professionally Managed Apartments w Rent Index for Primary Residence Nates', Data are through 2017 3 foomPage annual rents are for professionally managed apartment pmpenles in Classes A theater C. Sources, JCHS lobulations of US Bureau of four Statislics, HealPago. Ina new construction brought annualized rent gains for recently built units down to just 1.1 percent in the third quarter (below the rate of inflation in non -housing goods). Rent increases for high-rise properties—which have the highest average rent of $1,890 per month—were also modest at only 1.1 percent. Meanwhile, rents for units in low-rise structures rose 3.1 percent, reflecting the strong demand for lower-cost housing. Rents for single-family homes (including condos) rose steadily for seven years, with growth hitting a high of 4.4 percent in early 2016, before slowing to 2.8 percent in mid -2017. Much of the slowdown was at the high end (units renting for more than 25 percent above median), where rent growth dropped tojust 1.9 percent. Meanwhile, though, rents for low-end single-family units (renting for at least 25 percent below median) climbed by a strong 4.4 percent. THE GEOGRAPHY OF RENT GROWTH Annual rent growth in some 70 of the 100 apartment mar- kets tracked by RealPage slowed in the third quarter of 2017 compared with a year earlier (Online Figure 4). Even so, nominal increases in almost three-quarters (73) of these markets still outpaced the 1.3 percent inflation in non -housing goods prices, with nearly one in five reporting strong growth above 4.0 per - The Largest Rent Hilces Have Occurred in Formerly Low -Cost Neighborhoods of Fast -Growing Metros Annualized Change in Rent, 2012-2017 ( Parcel- 0 4 3 2 1 0 22 Slow (Under 1.0) Moderate (1.0-59) Growth in Metro Area Population, 2612-2016 (Percent) Fast 16.0 and Over) Neighborhood Rent I'm a2612'103 Lowest ■Lower Middle 0Middle ■Upper Middle -L Highest Largest 100 Metro Areas Notes The top 10D metros are the largest by population as defined by the 2015 American Community Survey, but exclude Las Vegas end Tucson demanders limitations. Annualized growth in rent Is from Joly 2012 to July 2017, and adjusted for inflation using the CH U retail Items Less Shelter. Hent quintiles are based on rents wifhin each more in 2012. Neighborhood rent grow@ is weighted by threshold of renter houselio ds le each ZIP code over total renters In each metra. Slow hastd growth metres are in the bottom (top) quartile for population growth. Moderete-growth metros are arms middle two quartiles for population growth. SourceJCHS tabulations at the Zillow Hent Index and US Census Bureau, 2015 American Community Samoa Year Estimates, cent. Most of the areas with rapidly rising rents—including Las Vegas, Orlando, Sacramento, and Seattle—are located in the West and South. Other prominent metros in these two regions also had rent gains over the past few years, but these increases have either moderated (Dallas, Riverside, and Sacramento) or slowed consider- ably (Austin, Nashville, and Portland). Meanwhile, nominal rent growth in the Midwest and Northeast has remained slow to moderate, with only a handful of markets report- ing annual increases above 3.0 percent over the past year (including Cincinnati and Minneapolis). In contrast, several metros in these regions—Bridgeport, Dayton, Des Moines, Pittsburgh, Providence, Syracuse, and Wichita—posted nominal rent growth that lagged behind general inflation. Within metro areas, rent increases in once low-cost neighborhoods have been especially large. In the 100 metro areas tracked by Zillow, rents in lowest -tier neighborhoods in 2012 were up sharply by mid -2017 in metros with the highest population growth (Figure 231. In Denver and Houston, for example, annual rent increases in the lowest -cost neighborhoods exceeded those in the highest -cost neigh- borhoods by more than 2 percentage points. In metros where the population was either stable or declining, however, rents grew slowly across all neighborhood types. STRONG RENTAL PROPERTY PERFORMANCE The rental property market has been among the best -performing sec- tors of the economy. The National Council of Real Estate Investment Fiduciaries (NCREIF) reports that nominal growth in net operating income (NOI) for investment-grade properties averaged some 7.7 per- cent annually in the seven years ending in the third quarter of 2017, compared with just 2.8 percent annually on average in 1983-2010. These strong gains reflect high occupancy rates as well as rising rents. With apartment occupancy rates falling and rent growth slow- ing, however, NOI growth moderated to a 3.8 percent annual rate in the third quarter—still outpacing the national rate of inflation and in line with historical averages. Solid growth in operating incomes allows property owners to reinvest in their units. According to the National Apartment Association, real improvement spending per unit more than doubled from 2010 to 2016 (Figure 241. Owners of large apartment properties invested $1,480 per unit on average in 2016, or roughly 10 percent of gross potential rents, up from about 8 percent per year on average between 2001 and 2015. There is also little sign that single-family rentals are returning to the owner occupied market. According to the latest American Community Survey, growth in the total number of single-family rent - Owners Have Invested Heavily in Apartment Property Upgrades in Recent Years Spending per Upit12016 dollars 1,600 1,400 1,200 1,000 Soo 600 400 200 0 2007 2008 2000 2010 2011 2012 2013 2014 2015 2016 4i Repair &Maintenance 11 Improvements Notes', l ate include apartment properties with 50 or more units under professional management with stabilized operations. dollars adjusted for inflation using the GN J far All Items, Somme National Apartment Association Survey of Operating Income & Expenses in Rental Apartment Communities, 2008-2017. 23 With Apartment Prices at an All -Time High... Index 120014-1001 170 160 150 140 130 120 110 100 90 so Parc a lit 2001 2003 2005 2007 2000 2011 2013 2015 w Real Apartment Prices (Left scale) Rd Capitallzatlon Rate (Right somal 8.5 80 7.5 7.0 6.5 6,a 5.5 5,0 4,5 4.0 Notes: Data are adjusted for inflation using the CPIl for All Items, and updated through 20172, Capitalization rare is the initial annual unlevered return an an acquisition, and measures the retia between the net operating income produced by property and its capital cost (the original price paid to buy the asset, Source: JCHS tohulations of Real Capital Analytics dam. ...Growth in Acquisitions Has Slowed Not Apartment Acquisitions (Billions of 2016 dollars) 180 160 140 120 100 80 60 40 20 n 24 2001 2003 2005 2007 2009 2011 2013 2015 ■ Crass -Forcer r LL Institutional/Equity Fund 9 Ustod/REIT I Pi vata. Equity Notes: Data are adjusted for inflation using the CH J for All Items, and updated through 2x172. Net acquisitions Include transactions of$2,5 million ar more (calculated as aaquishlans net of dispecitions). Cross border means that ane or more buyers are headquartered outside of the tis, IJstad/REIT Includes reel estate investment trusts, publicly traded funds investing directly in reel estate, and real estate operating companies, Figure excludes unknown/other buyers. Source, JCHS tabulations of Real Capital Analytics data. als (both attached and detached, and including vacant units) was essentially flat between 2014 and 2016, and increased only slightly (by 0.6 percent) in 2015-2016. However, recent growth in occupied single-family rentals remained strong in fast-growing markets of the West and South, including Austin, Charlotte, Denver, Houston, Orlando, and Phoenix. Healthy investor appetite has driven up the real prices of investment- grade apartment properties by 9.3 percent annually over the past seven years. Real Capital Analytics data indicate that real apartment prices stood 24 percent above their 2007 peak in mid -2017 (Figure 25). Prices for properties in highly walkable central business districts are particularly high, up 84 percent from their previous peak. Properties in highly walkable suburbs have also appreciated rapidly, exceeding the previous peak by more than 40 percent, Although much slower to recover, rental property prices in more car dependent suburbs still surpassed previous peaks by 13 percent by mid -2017. The apartment property market is, however, cooling, Prices declined slightly for the Midwest and Northeast regions over the past year. And while prices in several metros in the West and South (includ- ing Atlanta, Los Angeles, Nashville, Phoenix, San Diego, Seattle, and Tampa) continued to climb through mid -year, prices in several others (Charlotte, Houston, Orlando, and San Jose) declined in real terms. NCREIF estimates show that the total return on investment in the multifamily sector, including net income and appreciation in proper- ty values, exceeded 10 percent annually from late 2010 through early 2016. But with price appreciation slowing, ROI ramped down to a still respectable 6.2 percent in mid -2017, Investor appetite nonetheless remains strong, with CBRE reporting historically low capitalization rates for multifamily assets in nearly all markets and tiers in the first half of this year. MULTIFAMILY SALES VOLUME SOFTENING According to Real Capital Analytics, the annual volume of large apart- ment purchases (prices of $2.5 million or more), net of dispositions, bit a record high of $169.6 billion in the third quarter of 2016 in real terms, a 30 percent increase from the previous peak in the second quarter of 2006. By mid -2017, though, deal volume edged down to 148.1 billion, with declines in both international and institutionaL/equity fund invest- ments. More than half (63 percent) of net acquisitions came through pri- vate domestic sources, while 33 percent were through institutional and equity funds, The shares of REITs and foreign investment were small by comparison, in the 5-6 percent range. With pricing at or near all-time highs and limited inventory on the market, large apartment deals in five of the six major metro areas tracked by RCA—Boston, Los Angeles, New York City, San Francisco, and Washington, DC—slowed in the first half of 2017 from a year earlier. The exception was Chicago, where net sales continued to pick up. Large purchases of high- and mid -rise apartment buildings also rose in nom major metros. Investors and lenders alike appear more cautious at this stage of the cycle. According to a recent Federal Reserve survey for the third quarter of 2017, bank loan officers on net reported weaken- ing demand for loans secured by multifamily residential structures, while also reporting more stringent lending standards—the ninth consecutive quarter of tightening. Nevertheless, the Mortgage Bankers Association reports that the vol- ume of multifamily loans outstanding (including both originations and repayment/write-offs of existing loans) hit a new high of $1.2 trillion in nominal terms in early 2017, a 9 percent increase from a year earlier and a 44 percent jump from early 2011. Federal lending sources were responsible for fully two-thirds of the net increase in debt financing over the past year. Banks and thrifts have also steadily expanded their lending, raising their share of mortgage debt outstanding from a quarter in 2011 to about a third. Despite signs that the rental market may be cresting and that inves- tors are facing greater headwinds, measures of credit risk remain low overall. only 0.15 percent of all FDIC -insured loans secured by multifamily residential properties were in noncurrent status (90 days past due or in nonaccrual status) in the second quarter of 2017, down from 0.23 percent a year earlier. According to Moody's Delinquency Tracker, the noncurrent rate for commercial mortgage- backed securities (60 days past due, in foreclosure, or REO), though higher, was still a modest 2.8 percent in August 2017, THE OUTLOOK After seven years of tightening, rental market conditions have begun to ease in many metro areas. So far, most of the slack is at the upper end of the market and in core urban areas, where most new rental units have come online. However, supply pressures may be lessen- ing in the moderately priced segment as well. While this does appear to be a turning point, the extent of any potential slowdown depends in large part on the strength of future rental demand. The most likely scenario is that renters will still account for about a third of household growth going forward, which would make for a soft landing from current market conditions. But if the downshift in renter household growth is more significant, the impact on markets would be more negative. Whatever the short-term outlook, there will be ongoing need for lower-cost rental housing. Now that the high end is saturated, devel- opers may turn their attention to the middle -market segments. But given the challenges of supplying lower-cost units amid high and rising development costs, government at all levels will have to find new ways to facilitate preservation and expansion of the affordable stock. The housing industry must also play its part in fostering inno- vation to meet the nation's rental affordability challenges. 25 26 While affordability has improved somewhat, the share of renter households with cost burdens remains well above levels in 2001. Although picking up since 2011, renter incomes still lag far behind the 15 -year rise in rents. Renters of all types and in all markets face affordability challenges, although lower- income households are especially hard- pressed to find units they can afford. Indeed, high housing costs have eroded the recent income gains among these households, leaving many renters with even less money to pay for other basic needs. RENTER INCOMES AND HOUSING COSTS Despite some recent improvement, the rental housing affordability gap remains wide. Median monthly rental costs were up 15 percent in real terms in 2000-2016, increasing from $850 to a high of $980. At the same time, median renter household income fell sharply between 2000 and 2011, from $38,000 to $32,000, before gradually recovering to $37,300 in 2016. Part of this rebound, however, reflects the growing presence of higher -income households in the rental market rather than income gains alone. Even so, growth in renter incomes across all income quartiles has outpaced the rise in housing costs since 2011, modestly narrowing the affordability gap. The median monthly income for renters in the bottom quartile increased 10 percent in real terms from $1,000 in 2011 to $1,100 in 2016, while their monthly housing costs rose 3 percent from $740 to $760. By comparison, the median monthly income for renter households in the top quartile grew 9 percent over this period, to $11,300, but their housing costs jumped 6 percent, from $1,600 to $1,700. With this pickup in income growth, the number of cost -burdened renter households (paying more than 30 percent of income for hous- ing, including utilities) receded from a high of 21.3 million in 2014 to 20.8 million in 2016. The number of severely cost -burdened renters (paying more than 50 percent of income for housing) also edged down from 11.4 million to 11.0 million. The declines in the number of cost - burdened households between 2015 and 2016 coincide with the larg- est increase in median renter income since 2000. While down sightly since its 2011 peak, the share of cost -burdened renter households remains high (Figure 26). After increasing from 39 percent in 2000 to 51 percent in 2011, the share of cost -burdened households dipped to 47 percent in 2016. The share of severely cost -burdened renters also fell from 28 percent in 2011 to 25 per- cent. Again, these small improvements reflect not only a drop in the number of cost -burdened renters but also rapid growth in the number of renters with higher incomes—the group least likely to be cost burdened. In fact, the number of renters earning at least $75,000 rose by 40 percent between 2011 and 2016, to 9.1 million, the fastest growth in renter households in any income group. Despite Rising Incomes, the Share of Cost -Burdened Renters Remains High Percent 52 110 105 100 95 90 95 80 2000 2002 2004 2006 2008 2010 2012 2014 2016 W Median Heater ITrump treft scale) � Median Rental Cost (Left scale) s.I Cast -Burdened Share of Benters(Right apple) Notes', Median costs and household incomes are a constant 2915 dollars, adjusted for inflation using the CPI U for All Items. Housing costs include cash rent and utilities. Cost burdened households pay more than 30% of income for housing. Households with zero or negative income are assumed to have severe burdens, while households paying no cash rent are assumed to he without burdens. Indexed values represent cumulative percent change. Source'. JCHS tabulations of US Census Bureau, American Community Surveys, 50 48 46 44 42 40 38 GEOGRAPHY OF COST BURDENS Despite declines in the majority of states between 2015 and 2016, large shares of renters across the country are housing cost burdened. Indeed, the shares in California, Colorado, Florida, Hawaii, and New York range from 51 percent to 54 percent, although for different reasons. For example, renters in Colorado, Florida, and New York have relatively moderate median incomes but face high housing costs. In contrast, renters in California and Hawaii have high incomes but even higher housing costs, with both rents and incomes ranking in the top five in the country. Alaska is currently the most affordable state, with the cost-bri dened share of renters at 37 percent. Although housing costs in Alaska are the sixth highest nationwide, median renter income is the second highest. Lower housing costs, however, do not mean greater affordabil- ity, Although median housing costs in Alabama, Kentucky, Maine, Mississippi, and West Virginia are in the bottom fifth for the nation, the shares of cost -burdened renters in these states are above 41 percent. The states with the smallest shares of cost -burdened renters are located primarily in the Great Plains region—includ- ing Montana, North Dakota, South Dakota, and Wyoming—where median housing costs are low and renter populations are small. But even in these states, more than one-third of renters have housing cost burdens. t .Ir 4fri 4, While Most Common in Large Metros, Cost Burdens Are Widespread in Markets of All Sizes Thu a so no s of 0 a l l ars Pe rc e in 4 60 Largest9 Matins Large Metres Mid -Sita Metros Sntall Metros Rural Areas @ver 5 million) 0-5millionl 1150000-Irellead (10,000-156,000) (Less than 10,000) Population Size PI Medan Household Inoarea 1Left soaIs) 0 Median Housing Costs ILeft sea le) — She roof Cost -Burdened Renters IBlghtsocial 50 40 30 20 Notes. Household income is monthly. Housing costs are monthly and include cash rent and utilities. Cost -burdened households pay more than 30% of income for housba. Households with zero or negative income are assumed to have severe burdens, while households paying no cash rent ere assumed to be without burdens. Small metros Include micmpolitan areas with populations between 10,000 and 50,000. Seeme', JCHS tabulations of US Censer Bureau, 2016 American Community Survey l -Year Estimates using the Missouri Census Data Center MABLE/Geoconl4, Cost -burdened renters live in communities of all sizes, but finding affordable housing in larger metro areas is particularly challeng- ing. About half (51 percent) of renter households in the nation's nine largest metros pay more than 30 percent of income for hous- ing (Figure 27). The median monthly housing cost in these areas is $1,200 while the median renter income is $3,600. Among this group of nine metros, Miami has the highest shares of cost -bur- dened renters at 61 percent. The shares of cost -burdened renters are slightly lower in large (47 percent), mid-size (47 percent), and small metros (42 percent). Small metros have the lowest median housing costs of any urbanized areas at $720 and the lowest median incomes at $2,400. From 2011 to 2016, the cost -burdened shares of renters declined in 220 out of the nation's 275 mid-size and larger metros (80 percent), but primarily because increasing numbers of moderate - and higher -income households had entered the rental market. The number of cost -burdened renters decreased in only 46 per- cent of these metros over this period. In 63 of the nation's 658 small metros (10 percent), more than half of renters were housing cost burdened in 2016. About two-thirds of small metros with majority shares of cost -burdened renters are in the South and West. Meanwhile, the number of cost -burdened renters in 385 small metros (59 percent) fell between 2011 and 2016. 27 28 The Share of Middle -Income Renters with Cost Burdens Is Growing Rapidly Share of Households (Percent 90 00 70 60 50 40 30 20 10 0 2001 2606 2011 2016 2001 2006 2011 2016 2001 2006 2011 2016 2001 2006 2011 2016 2001 2006 2011 2616 Under $15,000 $15,000-29,999 $30,000-44,999 $45,000-74,999 $75,000 and Over ® Severely Cost -burdened Eil Moderately Cost -Burdened Notes:Household Inconessore incanstant20113 dollars, ad)ustod torindadon usingthii UforAllitems , Modoataly (severely) cost -burdened households pay30-66%(more than 50%) of incomefor housing. Householdswith zeroer negative income are assumed to have severe burdens, while households paying target remain assumed to hewithout trusts. SourceJCHS tehulatians of US Census Bureau, American Community Surveys. Rural areas tend to have lower, but still sizable, shares of cost -bun dened renters (40 percent). Even so, more than 46 percent of rural renters in California, Maryland, New Hampshire, and New York are housing cost burdened. These states are largely urbanized, suggesting that high rents in metropolitan areas extend into rural areas. Cost - burdened households in rural areas are often more dispersed than in metro areas, making it difficult to target effective policy interventions. UNIVERSALITY OF COST BURDENS Renters in many demographic groups are cost burdened, but low- income households are the most likely to pay a disproportionate share of their incomes for housing. In 2016, 83 percent of renter households with incomes below $15,000 had cost burdens, includ- ing 72 percent with severe burdens. Some 77 percent of renters earning between $15,000 and $30,000 were also cost burdened. By comparison, only 6 percent of renters making at least $75,000 were cost burdened in 2016. Over the past 15 years, more than half of the growth in the number of cost -burdened renters has been among renters earning under $30,000. However, the largest increases in cost -burdened shares have been among moderate -income households. From 2001 to 2016, the number of cost -burdened renters earning $30,000-45,000 rose by 1.3 million, bringing the share for this income group from 37 percent to 50 percent (Figure 28). Similarly, the addition of 1.1 million cost -burdened households with incomes of $45,000-75,000 nearly doubled the share in this group from 12 percent to 23 percent. Being fully employed is no panacea. In 2016, some 56 percent of rent- ers with jobs in personal care and service occupations were hous- ing cost burdened (Online Figure 5). Indeed, more than half of renters working in food preparation and service, building and grounds maintenance, and healthcare support—industries with many low- wage jobshadcost burdens. Conversely, less than 20 percent of renters in higher -paying fields such as computer science, mathemat- ics, architecture, engineering, and oil extraction, were housing cost burdened in 2016. In addition to low income, several household characteristics—includ- ing race/ethnicity, age, household composition, and disability status— are associated with costburdens. For example, 55 percent of black and 54 percent of Hispanic renters were housing cost burdened in 2016, an increase of about 7 percentage points for both groups in 2001-2016. By comparison, 43 percent of white renters and 47 percent of Asian and other minority renters were cost burdened, up 5-6 percent over this period. In addition, cost burdens are common among households age 65 and over, as well as among those under age 25. As of 2016, 54 percent of older renters had cost burdens, along with 60 percent of younger renters. Many members of these age groups are out of the workforce or have low wages, either because of retirement and/or disability or because they are still students. Household composition also makes a difference. Married or partnered households with more than one potential earner are less frequently cost burdened. Those with children present are more frequently bur- dened, perhaps reflecting the more limited hours that parents are available to work. For these reasons, single parents have the highest cost -burdened share (63 percent) of any household type, well above that for married or partnered parents (39 percent). Finally, 55 percent of renter households that have a member with a disability have cost burdens, compared with 45 percent of those with no disabilities. Rental cost burdens can be particularly detrimental to households with disabilities in that high housing costs may constrain their ability to pay for medical and other essential needs. THE LOW -COS] HOUSING DEFICIT The prevalence of cost burdens among lower-income renters is due in part to a shortage of low-cost housing in the private market. To be low cost, housing must be affordable at the 30 -percent -of -income standard to very low-income renters (earning up to 50 percent of area median income). HUD's Worst Case Housing Needs 2017 Report to Congress docu- ments the growing gap between supply of and demand for low-cost rentals. Worst case needs are defined as the number of very low- income renters who are severely cost burdened or living in inad- equate housing. After a slight dip from 8.5 million in 2011 to 7.7 The Most Populous Counties Face the Largest Shortfalls in Affordable Supply Average Number of Units per 100 Extremely Low Income Renters 100 90 80 70 60 50 40 30 20 10 0 More it.... 590.009 250,000 Miele 100,099-249,099 orange 99,999 County Population Affordable Units N Market Fate 3 HUD Assisted 11 USDA Assisted ® Unaffordable, Inadagome, or Unavailable Nates'. Affordable Is defined as costing no more than 20% of Income for households with axrremely law Incomes learning up to 30% of area median. Adequate units have caroplete bathrooms, running water electricity, and no sign of major disrepair Available units are net occupied by higher income households. Source JCHS tabulations of Urban Institute, Mapping America's Rental Housing Crisis, 2017. million in 2013, the number of renter households with worst case needs increased to 8.3 million in 2015. Nearly all of these cases (98 percent) arise from lower-income households having to pay more than half their incomes for housing costs rather than from prob- lems of housing adequacy. Some of the pressures on the low-cost supply arise from the fact that households with moderate or even high incomes occupy the units that low-income renters could afford. HUD estimates that 93 units are affordable for every 100 very low-income renters, but of these, only 54 are both available and adequate. For extremely low-income renters, the supply of affordable housing nationally is just 66 units per 100 renters, with only 33 of those units meeting the available and adequate criteria. HUD adjusts incomes based on household size to determine afford- ability and eligibility for housing subsidies. Given that the median income of very low-income families nationally was $28,400 in 2015, a very low-income family of four could afford to pay $710 per month for rent. This number, however, is much lower in some counties. Moreover, the median family of four with extremely low income could afford only $430 in monthly housing costs. Recent data from the Urban Institute confirms the shortage of pri- vately owned affordable rental housing (also known as naturally H ZE Maintaining the Stocic of Rental Housing Depends Largely on Preservation Share, of Affordable Rental Stools in 2013 Constructed or Added after 1985 23% Preserved from 1985 Stack 32% Converted Owner -Occupied or Seasonal 22% Filtered Down from Higher Price 23% Nates. Affordable is defined as casing no mora than 30% of for households with vary law incomes teeming up to 50%ot area median), Units added after 1985 mature reals that were tem romily out of the stack in that year Source'. JCHS tabulations of Welcher, Eggers, and Moumen, 2016. 29 30 ¢j" uYxdr�, ;hM 'Y7`}� nHja u4 .dM 5'°".6 r d} 'SANj,�.4'., �u )bs�t4a-s,U . ay ,. 5.0..�". yM3 Rising Housing Costs Have Eroded Disposable Incomes... Median Income Left Over After Paying for Housing Costs (Indexed) 110 105 100 95 65 2001 2002 2003 2004 2085 2006 2007 2088 2003 2010 2011 2012 2613 2014 2815 2016 Income Quintile ■ Bottom ltl Lower Middle ■ Upper Middle ■ Top Notes. Income quartiles include both owners and renters. Median housing Costs and household incomes are in constant 2010 dollars, adjusted for Inflation using the CIR J to, All Items. Hoeing costs include cash mntacd utilities, Indexed values are cumulative percent change. Source'. JC -S tabulations of US Census Bureau, American Community Surveys. !$$['1� t2d¢�x• tsi"ne'-+�n.�u �..�se1 a..5�-. ai.y a, w-1riu.ns uxu-..i ±-,col9aaU >c3y ... Especially Among Lowest -Income Renters Median Iboards Left O you After Paying far Housing Costs (Thousands of dr llors) Bottom Lower Muscle Upper Middle Top Income Quartile Notes: Income quartiles Include bath renters and owners. Hansing tests include cash rent and utilities, Source: JCHS tabulations of 2016 American Community Surrey. occurring affordable housing) available to extremely low-income renters. In 2014, counties with populations of at least 20,000 had an average of 34 naturally occurring affordable, adequate, and available units per 100 extremely low-income renters. Of these counties, 29 (about 2 percent) had no units meeting the criteria, while the most affordable counties provided 81 units for every 100 extremely low- income renters. On average, smaller counties have a higher ratio of supply to demand than larger urban counties, while large urban counties have the greatest deficit (Figure 29). At the same time, a Hudson Institute report finds that losses of low-cost units are high. About 60 percent of the 15 million rentals affordable in 1985—some 8.7 million units—were lost by 2013. The biggest reductions were due to permanent removals, with 27 percent of affordable rentals in 1985 (4.1 million units) demolished, destroyed in disasters, or reconfigured into fewer units. About 18 percent (2.7 million units) were converted to owner -occupied or seasonal housing, while 12 percent (1.7 million units) were upgraded to higher rents through gentrification. The remaining 276,000 units were temporarily out of the affordable stock. This same report also documents how the low-cost rental stock is replenished over time. A little under a third of affordable rentals in 2013 were also affordable in 1985, highlighting the importance of preservation. Even so, a large majority of affordable rentals were added through a variety of other means over time, with roughly equal shares coming from new construction and conversion of non- residential structures, filtering from higher price points, and conver- sion of owner -occupied or seasonal housing to rentals (Figure 30). Given the lack of naturally occurring affordable units, federal housing assistance is crucial for lowest -income renters. The Urban Institute estimates that HUD and USDA programs assist 53 percent of units affordable to extremely low-income renters. In the largest counties where supplies of naturally occurring affordable units are especially tight, federal programs on average contribute an average of 24 units per 100 extremely low-income renters. In smaller and nommetropoli- tan counties, federal programs account for an average of 27 units per 100 extremely low-income renters. THE ADDED BURDEN OF UTILITY AND TRANSPORTATION COSTS For renters that pay for their own use, utilities can be a sizable compo- nent of total housing outlays. The 2016 American Community Survey reports that the median renter spent $140 per month on electricity, gas, heating fuel, and water bills beyond any utility costs included in the rent. Utility spending varies across income groups and geographies. Lowest - income renters (making less than $15,000) spend the least on utilities, or $120 per month at the median. Renters in this income group living in the East South Central census division, including Alabama, Kentucky Mississippi, and Tennessee, have the highest median outlays of $155 per month. Renters making $75,000 or more have the highest utility bills, amounting to $150 per month. Highest -income renters in the East South Central area spend the most, or $188 per month. Although lower-income households spend less than higher -income households on utilities, they must dedicate a larger share of their incomes to these costs. Renters in the lowest income group spend 17 percent of their annual incomes on utilities, and highest -income households spend only 2 percent. While the median share of income devoted to utility costs has fallen across all income groups over the last five years, these costs still contribute significantly to overall housing outlays. Some renter households make tradeoffs between housing they can afford and location, thus adding to their transportation costs. Indeed, the median household with no housing cost burden spends more on transportation than the median household that is cost burdened. The 2016 Consumer Expenditure Survey reports that transportation costs account for 31 percent of total housing and transportation spending for the median renter. Even excluding vehicle purchases, the median transportation cost represents 21 percent of housing and transportation costs combined. CONSEQUENCES OF HIGH HOUSING COSTS High housing costs have eroded renter incomes and exacerbated inequality among renter households. After paying for their housing, the amount of money that lowest -income renters had left over for all other expenses fell 18 percent from 2001 to 2016 (Figure 31). Over the same period, the amount of money that highest -income renters had to spend on other costs increased by 7 percent. In 2016, the median renter household in the bottom income quartile paid 60 percent of its income for housing. For the median renter in this income group, the amount left over for all other needs was less than $500 per month (Figure 32). By comparison, the median renter in the top quartile paid just 14 percent of household income for hous- ing and had nearly $9,700 left over for other expenses. A recent JCHS working paper assesses the gap between house- hold incomes and outlays for both housing and basic living expenses (including transportation, food, childcare, healthcare, and income taxes) in three metropolitan areas in 2015. Not sur- prisingly, low-income households faced significant challenges in paying for basic necessities after covering their rents, even if these households were fortunate enough to find housing they could afford. Despite lower living expenses, lowest -income single - person households still faced significant financial challenges in covering housing costs and necessities. The results also show that childcare costs incurred by families leave even moderate -income households with cost burdens. 1'HE OUTLOOK While the recent drop in the number of housing cost -burdened renters is good news, future meaningful progress is far from cer- tain. Indeed, at the average annual pace of decline from 2014 to 2016, it would take another 15 years just to return to the 2006 level of 17.0 million cost -burdened households and 24 years to hit the 2001 level of 14.8 million households. In effect, the latest economic cycle seems to have defined a new normal for the nation's rental affordability challenges. Improvement in rental affordability depends on the trajectories of household incomes and housing costs. The recent growth in renter incomes has come at a time when the economy is nearing full employment, so sustained gains are uncertain. In addition, the Bureau of Labor Statistics expects that the fastest employment growth will be in several low-wage occupations—such as personal care, healthcare support, and food preparationwithlarge shares of housing cost -burdened workers. For earners in these occupa- tions, full employment will not guarantee access to housing they can afford. Meanwhile, tight rental market conditions have propelled rapid growth in housing costs relative to incomes, although the recent rise in vacancy rates may help to ease some of the pressure on rents in the short term. Turning back the tide on the nation's rental afford- ability challenges thus requires efforts to address lagging incomes among those near the bottom of the economic ladder as well as steps to help reduce the cost of housing. And for those with low incomes, increasing access to rental assistance, expanding the low- cost stock, and preserving affordable housing will be necessary to close the gap between income and housing costs. 31 32 The gap between the supply of and demand for rental housing assistance is still growing. Reversing this trend will require increased efforts to preserve assisted units, construct new affordable rentals, and expand the availability of vouchers and other forms of assistance. More immediately, the lack of affordable rentals in high-cost metros may be putting low-income households at greater risk of housing instability, evictions, and homelessness. The need for additional rental housing is especially acute in areas recently devastated by hurricanes and wildfires. REDUCED ACCESS TO RENTAL ASSISTANCE Between 2001 and 2015, the number of very low-income households (making less than 50 percent of area median) was up 29 percent, from 14.9 million to 19.2 million. According to HUD's Worst Case Needs 2017 Report to Congress, this includes a comparably large increase in the number of extremely low-income households (mak- ing less than 30 percent of area median) from 8.7 million to 11.3 mil- lion households. At the same time, the number of very low-income households receiving rental assistance rose only 14 percent, from 4.2 million to 4.8 million. As a result, the share of very low-income households that receive rental assistance declined from 28 percent to 25 percent over this period. The growing gap between need and assistance is evident in the long waiting lists for rental assistance in most cities. In fact, many local housing agencies have closed their waitlists in response to oversubscribed demand, sometimes not accepting new applicants for years. In one extreme example, Los Angeles reopened its waitlist for housing choice vouchers in October 2017 for the first time in 13 years, anticipating as many as 600,000 applications for 20,000 spots on the list. The shortfall in rental assistance has been accompanied by changes in the stock of federally assisted units. HUD data indicate that the number of public housing units fell from 1.1 million in 2006 to 1.0 million in 2016, while the number of privately owned units with project -based subsidies was down from 1.4 million to 1.3 million. These declines have been offset by an increase in hous- ing choice vouchers, from 2.0 million to 2.3 million. The number of households receiving assistance from the US Department of Agriculture also rose modestly from 263,000 in 2008 to 269,000 in 2016. Although the net change across programs is positive, the increase has not kept pace with growth in the number of very low- income households. The Low Income Housing Tax Credit (LIHTC) program remains the primary source of support for new affordable rental units. Between 2006 and 2015, the stock of LIHTC units expanded from 1.6 mil- lion to 2.3 million. While adding to the overall supply of affordable Most Assisted Households Are Older Adults, Persons with Disabilities, or Families with Children Share of Assisted Households Adults with Disabilities III% Adults with Disa bilines with Cluddrer Va Adults without Children 12% Adults with Children 32% )lour Adults 13% Older Adults with Children 1% Notes. Household counts include those assisted by housing choice vouchers, public housing, incisor based Section 8, Source 202, and Section 811 Older adult households ere heeded by a person age 62 or older, Including therewith a dlsablllty ora car with a disability. Adults with disabilities are heuaeholds heeded by a person age 61 or younger with a disability or a spouse with a disability Adults with children Include households with It lesstone child under age 16 present. Source'. JIM tabulations of US Department of Housing and Urban Development. 2018 Public Use Microdata Sample, housing, these units generally have rents affordable to households with incomes 50-60 percent of the area median. To be affordable to extremely low-income households, LLHTC units often must be coupled with other subsidies. Indeed, a 2014 HUD analysis estimated that 38 percent or more of LIHTC tenants received rental assistance of some kind from federal, state, or local sources. Households receiving rental assistance are predominantly families with children, older adults, and persons with disabilities (Figure 33). According to HUD data for 2016, 38 percent of recipients were low- income families with children, including 5 percent with a household head with a disability and 1 percent with a household head age 62 or over. With the aging of the baby -boom generation, older adults now occupy one-third of assisted units and this share is and set to increase over the coming decades. Meanwhile, 18 percent of assisted house- holds in 2016 were headed by a person under age 62 with a disability. Only 12 percent of recipients were childless adults under age 62. PRESERVING THE AFFORDABLE HOUSING STOCK The nation's stock of both assisted and privately owned low-cost rentals includes many units at risk of loss. Public housing, in par- ticular, has a large backlog of needed repairs and improvements, last estimated at $26 billion in 2010, and its annual maintenance needs of $3.4 billion exceed Congressional appropriations. Although Congress has not addressed this deficit through additional capital funding, it did establish the Rental Assistance Demonstration (RAD) in 2012 to give public housing and other eligible properties more Affordability Restrictions on 1.1 Million Rental Units Will Expire by 2027 Cumulative Number of Units with Expiring Affordability (Millions) 1.25 1.00 0.75 0.50 025 000 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Typeuf Subsidy ®Project -Based Asmstance til Low Income Housing Tax Cr edit NOther Notes, Data Include proportion with active subsidies as of January t, 2017. Other includes units funded by I TOMS Rental Assistance FHA Insurance, Section 236 Insurance, Section 202 Direct loans, USDA Section 515 Rural Rental Housing Loans, and units In properties with more than one sueadytype aspiring on the came daµ For proportion with multiple subsidies, If one subsidy expires hotone or nom othem mmein eetive, the difference between the number of units assisted by the expiring subsidy and the number of units assisted by the manaidong subsidies are counted an expired, Somme JCI IS chulogreas of Pubic and Affordable Housing Research Conference and National Low Income housing Confirm, Nmiennl Housing Preservation Dabacase. '.33. 34 funding flexibility through conversion to project -based Section 8 contracts. After applications for participation in RAD reached the initial limits, Congress raised the cap to 225,000 units for fiscal year 2017. At last count 423 public housing authorities (14 percent) are currently participating in the demonstration. The impending expiration of affordability restrictions on federally subsidized units presents another preservation challenge. Over the next 10 years, 530,000 rentals with project -based rental assistance, 478,000 units with LIHTC subsidies, and 136,000 units with other types of subsidies will reach the end of their required affordability periods (Figure 341. While some of these properties are owned by nonprofits and other mission -driven organizations, many are pri- vately owned and at risk of converting to market rate. Properties located in areas with high or rising rents are particularly vulner- able to loss from the affordable stock. Expirations of LIHTC affordability restrictions are set to increase in 2020 as the oldest units built under the program reach the 30 -year mark. In response, several states have enacted mandates to extend the affordability periods of LIHTC properties. For example, California now requires 25 years of additional affordability, while New Hampshire, Utah, and Vermont require 69 years. However, these state -level actions do not include funding for maintenance expen- ditures and were mostly undertaken after 2000, implying that they will only have an impact after 2030. Additional preservation efforts are therefore necessary to keep LIHTC units with expiring afford- ability restrictions in the subsidized housing stock. Finally, after a decade of tight rental markets and rising rents, the stock of privately owned low-cost units continues to shrink. These losses are particularly concerning in metros with rapid rent growth, where downward filtering and conversions from the owner -occupied stock have done little to offset the disappearance of low-cost rentals. To combat losses of naturally occurring afford- able housing, nonprofit organizations have begun to acquire and manage at -risk properties to keep rents affordable to current and future tenants. TRACKING HOMELESSNESS In the early 2000s, HUD launched an initiative challenging cities to develop plans to end chronic homelessness within ten years. The 2010 Federal Strategic Plan to Prevent and End Homelessness sub- sequently broadened this effort, setting goals to end chronic and veteran homelessness within five years and homelessness among families with children and unaccompanied youth within ten years. Efforts to reduce homelessness appear to be working, at least at the national level. According to HUD's Annual Homelessness Assessment Report (AHAR), the number of people who were home- less on a single night in January fell 15 percent from 647,000 in 2007 to 550,000 in 2016. Nearly all of this decline is due to decreases in the number of unsheltered homeless people, with the number of shel- tered homeless people remaining almost constant. The reductions are also largest among the groups most likely to be unsheltered, including the chronically homeless (down 35 percent in 2007-2016) and homeless veterans (down 47 percent in 2010-2016). Less prog- ress has occurred in reducing homelessness among families with children (down 17 percent in 2007-2016). The point -in -time count, however, provides only a conservative esti- mate of the number of people and families that experience homeless- ness over the course of a year, An alternative AHAR measure of the extent of homelessness is that nearly 1.5 million people spent at least one night in a shelter in 2015. Even this figure is low, given that it does not include the unsheltered homeless or at -risk individuals living in doubled -up or other unstable housing situations. The national esti- mates also mask considerable variation across locations. Metros with the highest rates of homelessness are frequently those with the high- est median rents (Figure 35), raising concerns about the consequences of tight conditions in these high-cost markets. Achieving further reductions in homelessness will require atten- tion to the needs of multiple subpopulations. A recent analysis of HUD's Family Options Study suggests that housing vouchers may be nut �r mhh m�1st,e t ulSu,, n 4Ax , r ' Homelessness Is Especially High in More Expensive Rental Markets Homelessness Rate IForcenO 05 ...-...-..-. ............... _._.....___ ............. _. .._. _._........... ® Now York Da •...nla_'"° _� San ean.ia.. s 03:..:...: ............-_..._.. •Boston .......... .:..... • son plea. TS >Pnnlane, OR W"Irl mn, BC 5 Ant.iri. Innaepolla r ♦Bahama ! �Pho I marri 0.1 cto�ie' s•o.v.a ...sal a +rPwera as - pelma prlenao xauamn 0.0 $700 $900 $1,100 $1,300 $1,500 $1,700 Median Rent Nates, Included metros are the 21 metropolitan statistical areas IMSASI among rho 25 largest WAS by lots) population for which at least 80% of population fells within one or more metro Continuums of Care (COGS). Mom CtCs are defined here as having at least 90% of their population falling within one MSA. Median rent is median grass rent including utilities, Homelessness rate is the printintime count of inmates people, both sheltered and unsheltered, divided by the MSA population, Sources'. UCHS tabulations of US Department of Housing and Urban Development, 2016 Point mi Count of Homelessness, and US Census Bureau, 2015 American Community Survey 1 year Estimates. the best strategy for reducing family homelessness. This study was launched in 2008 to test the relative efficacy of several approaches, including priority access to long-term subsidies, temporary subsi- dies, project -based transitional housing, and usual care through the shelter system and other available supports. According to HUD's evaluation of long-term outcomes, priority access to housing choice vouchers significantly reduced the likelihood of homelessness, dou- bling up, and shelter stays three years after enrollment in the study. EVICTIONS AND FORCED RELOCATIONS The frequency and consequences of evictions and forced relocations have gained new attention from policymakers. According to the 2015 American Housing Survey, 7.5 percent of all renter households that moved in the prior two years did so because they were "forced to move by a landlord, a bank or other financial institution, the gov- ernment or because of a disaster or fire." It is difficult to know how many of these forced moves were due to formal evictions through the court system, informal evictions, or other events. Less is known about the relative effectiveness of strategies to reduce homelessness among the young. HUD's point -in -time estimates The Milwaukee Area Renters Study offers a more complete pic- found 36,000 unaccompanied homeless youths in January 2016, ture, reporting that 13 percent of renter households in the City of while the Homeless Management Information System shows that 137,000 unaccompanied homeless youths used the shelter system at some point in 2015. HUD continues to improve its data collection processes, and 2017 will be the initial year for estimating changes in the number of homeless youth over time. Findings from the Veterans' Homelessness Prevention Demonstration also highlight the unique physical and mental health needs of homeless veterans. For example, two-thirds of veterans in the dem- onstration reported experiencing serious depression, anxiety, or ten- sion—including 43 percent with symptoms of post-traumatic stress disorder. The project also revealed the need for service providers to have cultural competency in military norms and the ways in which veterans experience civilian life. A Milwaulcee Study Suggests that Informal Evictions May Be Twice as Frequent as Formal Evictions Share of Forced elders Final Evicl Building Condemnations 5% Land Forenlos 23% Milwaukee experienced a forced move within the two years pre- ceding the study. Of these moves, almost half (48 percent) resulted from informal evictions, 23 percent from landlord foreclosures, and 5 percent from building condemnations, and only a quarter were due to formal evictions (Figure 36). While not broadly generalizable, these estimates suggest that court records seriously understate the frequency of forced relocations of renters. In addition to stress and psychological trauma, evictions impose high costs on renter households in terms of both time and money, and can result in job absences, drain savings or increase debt, and damage credit histories. Forced moves can also disrupt children's school attendance and adults' employment options, particularly if the household moves to a new town or school district. And for the Low -Income Renters Are Likely to Live in Neighborhoods with Other Low -Income Households Average Share of Households to Neighborhood (Rsroontl 40 ___.......___...............................__.........................................._.. 30 Informal Evictions 20 48% 10 Notes Formal evictions are processed through the court system. Informal evictions include forted moves in cases where the mneais were threatened with eviction or moved in anticipation of eviction. Source: Milwaukee Area Renters Study data around in Desmond and Shollen oorger. 2015. Renters Eamtng UnderS20,000 All Renters All Households Household Income in Neighborhood IN Under $20,00l) -7$20,0060.9999 +i$%oodr -99.999 0$100,000 or Moro Note', Shams are calculated as the weighted average of households in each income categoryacross all US manus tracts. Sources, JCFIS tabulations of US Census Brom, 2015 American Community Survey 5 -Year Estimates, and the JCHS Neighborhood Change Database. _ 35 36 community at large, forced displacements entail direct public costs in the form of fees for court services, social services, and use of homeless shelters and emergency foster care. The recent focus on forced relocations has led several cities to review their eviction procedures. In 2017, New York City became the first city in the country to guarantee legal representation to low-income residents facing eviction, other cities have taken steps to limit the set of causes for which landlords can pursue eviction. Expanding support for emergency rental assistance and rapid re- housing programs would also help to protect households most at risk of homelessness. GROWING INCOME SEGREGATION Residential segregation by income has increased steadily in recent years, especially among households with the highest and lowest incomes. This trend adds to the challenges posed by entrenched residential segregation by race and ethnicity in many cities. It also raises concerns that low-income renters have increasingly limited access to a full range of neighborhoods. In 2015, the average renter household earning under $20,000 lived in a neighborhood where 28 percent of residents had comparably low incomes and only 15 percent had incomes above $100,000 (Figure37). In comparison, the average US household lived in a neigh - Rental Property Owners Are Slower than Homeowners to Rebuild Following Disasters Condition of Horricano-0am2ged Properties in Louisiana and Mississippi After Five Years (Percent) 90 go 70 60 50 40 30 20 10 0 Small Renal Properties Homeowner Propar0es ■Remin[l P'p Cleared Lot In Need of Suhsticaral Repairs Nates: Sample is representative of residential properties that experienced major or severe hurricane de mage and were located on significantly affected blocks. Rebuilt structures are resldeneas that do net show substantial repair needs, Cleared lots contain an empty lot ore foundation with no slanding structure, Source: Spade[ 2915. borhood where 18 percent of residents had incomes below $20,000 and 24 percent had incomes above $100,000. A recent JCHS working paper provides evidence of the detrimental effects of residential segregation on the educational attainment, employment, socioeconomic mobility, and health of low-income renters. Households living in areas of concentrated poverty are particularly vulnerable. Such segregation not only limits economic potential for individuals and society as a whole, but also reduces social cohesion and intergroup trust, increases prejudice, and erodes democratic participation. Reversing this trend is difficult and would require changes in both private markets and the location of assisted units. A key step would be to increase the supply of low-cost rental units in neighborhoods of all types, including construction of assisted units in a broader range of neighborhoods. Many states have in fact begun to incentiv- ize LIHTC applicants to propose projects that do just that. In addi- tion, the recently finalized Affirmatively Furthering Fair Housing (AFFH) rule establishes a planning process for local HUD grantees to assess current residential patterns and to take meaningful actions that foster inclusion. Reforms to the housing choice voucher program would also help to increase the options available to low-income households, outreach to landlords, protections against source -of -income discrimination, and mobility counseling would all serve to expand the range of prop- erties and neighborhoods available to voucher holders. For example, the results of Baltimore's Special Mobility Housing Choice Voucher program demonstrate that mobility counseling can help to increase neighborhood choice among voucher holders. HUD's Small Area Fair Market Rent demonstration is also testing whether adopting neigh- borhood -level fair market rents (FMRs) would induce moves into a broader set of neighborhoods. HUD currently sets a single fair mar- ket rent for each metropolitan area, often forcing voucher holders to choose from units clustered in a few neighborhoods where rents fall below the FMR. While the interim report on the demonstration found evidence that neighborhood -level FMRs broadened the loca- tion choices of voucher recipients in some areas, the results were less encouraging in other areas, and HUD has suspended expansion of the demonstration to additional metros. REBUILDING AFTER DISASTERS The damage wrought by natural disasters in 2017 will pose substan- tial rebuilding challenges for years to come. Much of the housing stock lost in the recent hurricanes, for example, was renter -occu- pied. Indeed, the latest American Community Survey indicates that rental units accounted for 41 percent of all housing in the Houston metro area, 36 percent in Florida, and 32 percent in Puerto Rico. one lesson from prior disasters is that rental housing is restored much more slowly than owner -occupied homes. This is likely due to several factors. While homeowners directly control the rebuild- ing of their properties, renters must depend on their landlords' decisions, owners of just a few rental properties may be especially slow to invest in rebuilding if their own homes are also damaged. In addition, policymakers have historically been more generous in assisting homeowners than rental property owners who lack adequate insurance coverage. According to a 2010 HUD survey, only 60 percent of rental properties that sustained major damage in Hurricanes Katrina and Rita in 2005 had been rebuilt by 2010, compared with 74 percent of homeowner properties with similar levels of damage (Figure 38). Instead, 12 per- cent of former rental properties were cleared lots and 28 percent contained residential structures with substantial remaining dam- age, including 13 percent that did not meet the Census criteria for habitability. While there are legitimate concerns about bailing out under -insured rental property investors, a secondary effect of lim- ited rebuilding in these disasterstrickenareas has been to reduce the housing available to renters. The rebuilding of public housing, project -based units, and units available to voucher recipients presents other challenges. Following Hurricane Katrina, Congress made appropriations for disaster recovery that included supplemental allocations of both low-income housing tax credits and housing choice vouchers. While providing much-needed resources, these allocations require attention to ensure that LIHTC units are completed quickly and that the supply of units available to voucher holders is sufficient. After the 2017 hurricanes, rebuilding of units available to voucher holders may be particularly urgent, given that these rentals account for 62 percent of the HUD -assisted stock in Houston and 64 percent in Thmpa. A recent report from the Community Preservation Corporation documents other lessons from the rebuilding effort following Hurricane Sandy and recommends multiple potential improvements to streamline the application process, speed delivery of rebuilding assistance, and allow federal agencies to better prepare for future events. Given that it is just a matter of time before the next natural disaster occurs, taking these steps in advance will help to protect renter households in the wake of future storms. THE OUTLOOK With the economic expansion now in its ninth year, the immediate challenges facing America's rental markets depend on the outlook for the broader economy and the policy decisions of Congress and the Administration. On the one hand, continued economic growth would give a further lift to household incomes, but could also put additional pressure on rents. On the other, though, a recession would put more renters at risk of unemployment and reduced income. Meanwhile, proposals for tax reform and changes to the LIHTC program make future funding for affordable housing production and preservation uncertain. While its prospects are unclear, a bipartisan bill in the Senate proposes to expand support for the LIHTC program and to change program rules to provide additional flexibility to states and improve the program's ability to serve extremely low-income households. In contrast, the tax reform pro- posals under consideration could substantially reduce production of LIHTC units by eliminating the important 4 percent credit. Regardless of the short-term outlook, however, the growing gap between the number of income -eligible households and the avail- ability of rental assistance is a long-term challenge. In some markets, demand-side subsidies—such as expanded access to housing choice vouchers—may be an effective response. However, in many metros across the country, increases in supply have not kept pace with population growth, putting even greater pressure on lowest -income households. In these markets, responding to rapid population growth requires both expansion of the overall rental supply and additional support for new construction and preservation of assisted units. While the federal government remains the primary source of rental assistance, states and localities must continue to take steps to pro- vide increased support for affordable housing through bond issues, trust funds, inclusionary zoning, and other approaches. Since states and localities also define the regulatory context for market -rate housing, they must also lead efforts to ensure that additions to the rental housing stock keep pace with population growth and to miti- gate losses of low-cost units in the private market. 37 38 Table A-1 .................. Characteristics of Growth in Renter Households: 2006-2016 Table A-2 .................. Characteristics of the Rental Housing Stock: 2016 Additional appendix tables, maps, and interactive tools are available at www.jchs.harvard,odu/americas-rental-housing Characteristics of Growth in Renter Households: 2006-2016 Renter Households (Thousands) Note'. Incomes are in constant 2015 dollars adjusted for inflation using the CPI -U for All Items. Source. JCHS tabulations of US Census Bureau, Current Population Surveys. 39 "I Number Percent All Renter Households Total 36,054 45,915 9,861 274% Household Income Less than $15,000 7,631 8,914 .1,283 168% $15-24,999 5,797 6,637 840 145% $25-34,999 _ 4,679 5,772 1,093 234% $35-49,999 5,997 6,715 718 12.0% $50-74,999 5,835 7,609 1,674 283% $75-99,999 2,857 4,243 1,386 48.5% $100,000 or More 3,258 6,125 .2,868 880% ". Race/Ethnicity. White 20,027 23,647 _ 3,620 `.181% Black. 7,064 9,116 2,055 29.1% Hispanic 6,416 9,093 2,677 41.7% Asian/Other 2,548 4,057 1,510 59.3% -- Age of Householder Under25 - 5,216 5,059 - (157) ....1,121 -3.0% 25-29. 5,445 6,566 ... 20.6% 30-34 4,384 5,795 1,411 .32.2% 35-39 3,714 4,829 1,115 30.0% 40-44 _ 3,512 4,108 596 .634. - 170% 4549.. 3,077 3,711 206%_ 50-54 _ 2,5633,437 .. 874 ' 34.1% 55-59 1,976 3,139 1,163 56,8% _ 60-64 1,473 2,716 1.,243 843% 65-69 1,200 2,154 954 795% 7094 933 1,326 393 '421% 75 and Over 2,562 3,076 514 201% Houshold Type Married Without Children 3,793 5,424 1,631 430% Married With Children 5,723 6,754 1,031 180% Single Parent (No Other Adults) 4,154 4,241 87 21% Other Family with Children 3,131 4,153 1,022 327% Single Person 13,513 17,144 3,632 269% Unmarried Partners Without Children 1,537 2,477 941 612% Other Family/Nonfamily, Without Children 4,204 5,722 1,516 361°% Note'. Incomes are in constant 2015 dollars adjusted for inflation using the CPI -U for All Items. Source. JCHS tabulations of US Census Bureau, Current Population Surveys. 39 40 Characteristics of the Rental Housing Stock: 2016 Rental Units (Thousands) Nates, Cate include vacant units that are far rent and rented but not yet occupied, Metro area status classifications include only occupied rental units due to date constraints. Source'. JCHS tabulations of US Census Bureau, 2016 American Community Survey 1 -Year Estimates, 50 Units Unhealed Attached 2 Units 3-4 Units 5-9 Units 10-19 Uatts 20-49 Unrrs or More r CCnSUS Her B,e Northeast 1,119 623 1,240 - 1,244 939 - 756 - :,.972 1,615 117 8,626 Midwest- 2,794 550 785 998 1,176 965 777 991 267 9,304 South 5,690 - 1,006 961 1,409 '.2,023 2,228 -- :1,239 1,720 1,341 17,617 -. West 3,537 763 527 1,185 1,322 1,244 1,086 1,531 411 11,606- E Metro Area Status ! t �, n F) G a Principal Coy 4,294 1,280 < 1,519 2,270 - > 2,551 2,516 n1,970 2,210 3,508 234 20,383 t Other City 5,908 1,336 1,295 1,742 2,058 1,257 1,120 1,051 18,338 Non -Metro 2,265 174 i 440 499 427 255 ` 219 167 671 5,117 1 x.552 1576 ��. Pre -1940 2,029 429 - 992 954 622 387 - 23 ,6,564 1940-1959 3,208 447 643 665 530 436 439 568 46 6,983 1960-1979 3,526 702 882 1,410 - 1,740 :1,625 1,151 1,641 612 13,290 1980-1999 2,626 603 661 1,281 1,779 1,80a 1,128 1,517 1,089 12,692 2000 or Later 1,752 560 335 526 789 937 804 1,556 365 7,023 b Monhhly Coats' - 4 ,... Less than$650 1,474 290 772 1,051 "1,100 C 822 774 1,309 724 8,316 $650-849 1,782 337 680 963 1,039 925 586 588 485 7,366 $B50-1,098 s.. 2,335 573 690 1 1,206 -:1,217 -1,020 - 807 - '819 - 311 8,958,, $1,100-1,499 2,528 673 549 779 955 799 965- 111 8,379 $1,500 or More 2,887 793 472 637 654 - 701 + 697 -- .1,643 31 8,515 No Cash Bent 1,403 - 107 - 101 64 58 48 53 75 294 2,203 Vacant 732 168 248 344 448 459 35B 459 180 3,395 JJ. ` Number of ! d 0 88 31 139 258 348 - 404 496 .939 - 35 2,737 1 - 672 265 685 1,384 1,788 1,945 1,800 2,830 154 11,523 2 3,266 1,295 1,784 2,393 2,691 - :2,377 - -:1,496 1,747 -906 -- 17,956 3 6,449 1,122 764 701 564 408 235 281 928 11,452 4 2,182 196 11B 86 60 51 . 33 - 39 97 .2,862 5 or More 484 33.. 23 14 10. 8 14 22 16 623 Nates, Cate include vacant units that are far rent and rented but not yet occupied, Metro area status classifications include only occupied rental units due to date constraints. Source'. JCHS tabulations of US Census Bureau, 2016 American Community Survey 1 -Year Estimates, t rP� �I. 4 America's Rental Housing 2077 was prepared by the Harvard Joint Center for Housing Studios. The Center advances understanding of housing issues and ` informs policy. Through its research, etlucation,and public outreach programs, the Center helps leaders in government, business, and the civic sectors makedecisions that effectively address tho needs of cities and communities. Through graduate and executive courses, as well as fellowships and internship' opportunities, the Joint Center also trains and inspires the next generation of housing leadars� STAFF FELLOWS Whitney Airgood-Obrycki Barbara Alexander Matthew Arck Frank Anton Kermit Baker ' William Apgar James Chaknis ' Michael Berman r` ' Kerry. Donahue ` Rachel Bran Angels Flynn ` Michael Carliner Riordan Frost `. Kent Colton Christopher Herbert, Dan Fulton + Alexander Hermann -: George Masnick Elizabeth LaJeunesse - Shaker Narasimhan Mary Lancaster '. Nicolas Retsines Hyojung Lee Mark Richardson + David: Luberoff Daniel McCue Eiji Miura +` Jennifer Molmsky,. Kristin Perkins Shannon Rieger Jonathan Spader Alexander van Hoffman Abbe Will The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco * Rebecca Diamondt, Tim McQuade$ , & Franklin Qian§ October 11, 2017 Abstract In this paper, we exploit quasi -experimental variation in the assignment of rent con- trol in San Francisco to study its impacts on tenants, landlords, and the rental market as a whole. Leveraging new micro data which tracks an individual's migration over time, we find that rent control increased the probability a renter stayed at their address by close to 20 percent. At the same time, we find that landlords whose properties were exogenously covered by rent control reduced their supply of available rental housing by 15%, by either converting to condos/TICS, selling to owner occupied, or redeveloping buildings. This led to a city-wide rent increase of 7% and caused $5 billion of welfare losses to all renters. We develop a dynamic, structural model of neighborhood choice to evaluate the welfare impacts of our reduced form effects. We find that rent con- trol offered large benefits to impacted tenants during the 1995-2012 period, averaging between $2300 and $6600 per person each year, with aggregate benefits totaling over $390 million annually. The substantial welfare losses due to decreased housing supply could be mitigated if insurance against large rent increases was provided as a form of government social insurance, instead of a regulated mandate on landlords. *Wc are grateful for comments from Ed Glaser, Christopher Palmer, Paul Scott, and seminar participants at the NEER, Real Estate Summer Institute, The Conference on Urban and Regional Economics, and the Stanford Finance Faculty Lunch. tStanford University & NBER. Email: diamondr@stanford.edu. tStanford University. Email: tmequadcUstanfbrd.edu . gStanfbrd University. Email: zgianl@stanford.edu . I Introduction Steadily rising housing rents in many of the US's large, productive cities has brought the issue of affordable housing to the forefront of the policy debate and reignited the discussion over expanding or enacting rent control provisions. State lawmakers in Illinois, Oregon, and California are considering repealing laws that limit cities' ability to pass or expand rent control. Already extremely popular around the San Rancisco Bay Area, with seven cities having imposed rent control regulations, five additional Bay Area cities placed rent control measures on the November 2016 ballot, with two passing. Rent control in the Bay Area consists of regulated price increases within the duration of a tenancy, but no price restrictions between tenants. Rent control also places restrictions on evictions. A substantial body of economic research has warned about potential negative efficiency consequences to limiting rent increases below market rates, including over -consumption of housing by tenants of rent controlled apartments (Olsen (1972), Gyourko and Linneman (1989)), mis-allocation of heterogeneous housing to heterogeneous tenants (Glaeser acid Luttrner (2003), Sims (2011)), negative spillovers onto neighboring housing (Sims (2007), Autor et al. (2014)) and, in particular, under -investment and neglect of required mainte- nance (Downs (1988)). Yet, due to incomplete markets, in the absence of rent control many tenants are unable to insure themselves against rent increases. A variety of affordable hous- ing advocates have argued that tenants greatly value these insurance benefits, allowing them to stay in neighborhoods in which they have spent many years and feel invested in. Due to a lack of detailed data and natural experiments, we have little well -identified em- pirical evidence evaluating the relative importance of these competing effects.' In this paper, we bring to bear new micro data, exploit quasi -experimental variation in the assignment of rent control provided by unique 1994 local San Rancisco ballot initiative, and employ struc- tural modeling to fill this gap. We find tenants covered by rent control do place a substantial rA notable exception to this is Sims (2007) and Autor e1; al. (2014) which use the repeal of rent control in Cambridge, MA to study it's spillover effects onto nearby property values and building maintenance. 2 value on the benefit, as revealed by their migration patterns. However, landlords of proper- ties impacted by the law change respond over the long term by substituting to other types of real estate, in particular by converting to condos and redeveloping buildings so as to ex- empt them from rent control. This substitution toward owner occupied and high-end new construction rental housing likely fueled the gentrification of San Francisco, as these types of properties cater to higher income individuals. The 1994 San Francisco ballot initiative created rent control protections for small multi- family housing built prior to 1980. This led to quasi -experimental rent control expansion in 1994 based on whether the multifamily housing was built prior to or post 1980. To examine rent control's effects on tenant migration and neighborhood choices, we make use of new panel data sources which provide the address -level migration decisions and housing charac- teristics for close to the universe of adults living in San Francisco in the early 1990s. This allows us to define our treatment group as renters who lived in small apartment buildings built prior to 1980 and our control group as renters living in small multifamily housing built between 1980 and 1990. Using our data, we can follow each of these groups over time up until the present, regardless of where they migrate to. On average, we find that in the medium to long term, the beneficiaries of rent control are between 10 and 20 percent more likely to remain at their 1994 address relative to the control group. These effects are significantly stronger among older households and among households that have already spent a number of years at their treated address. This is consistent with the fact both of these populations are less mobile in general, allowing them to accrue greater insurance benefits. On the other hand, for households with only a few years at their treated address, the impact of rent control can be negative. Perhaps even more surprisingly, the impact is only negative in census tracts which had the highest rate of ex -poste rent appreciation. This evidence suggests that landlords actively try to remove their tenants in those areas where the reward for resetting to market rents is greatest. In practice, landlords have a few possible 3 ways of removing tenants. First, landlords could move into the property themselves, known as move -in eviction. The Ellis Act also allow landlords to evict tenants if they intend to remove the property from the rental market - for instance, in order to convert the units to condos. Finally, landlords are legally allowed to offer their tenants monetary compensation for leaving. In practice, these transfer payments from landlords are quite common and can be quite large. Moreover, consistent with the empirical evidence, it seems likely that landlords would be most successful at removing tenants with the least built-up neighborhood capital, i.e. those tenants who have not lived in the neighborhood for long. To understand the reduced form impact of rent control on rental supply, we merge in historical parcel history data from the SF Assessor's Office, which allows us to observe parcel splits and condo conversions. We find that the owners of exogenously rent controlled properties substitute toward other types of real estate that are not regulated by rent control. In particular, we find that rent -controlled buildings were almost 10 percent more likely to convert to a condo or a Tenancy in Common (TIC) than buildings in the control group, representing a substantial reduction in the supply of rental housing. Consistent with these findings, we moreover find that, compared to the control group, there is a 15 percent decline in the number of renters living in these buildings and a 25 percent reduction in the number of renters living in rent -controlled units, relative to 1994 levels. In order to evaluate the welfare impacts of these reduced form effects, we construct and estimate a dynamic discrete choice model of neighborhood choice. Motivated by our reduced form evidence, we allow for household preferences to depend on neighborhood tenure and age, and allow for monetary "buyouts" where landlords of rent -controlled properties can pay their tenants to move out. The model features fixed moving costs and moving costs variable with distance. A key contribution of the paper, relative to the existing dynamic discrete choice literature, is to show how such models can be identified in a GMM framework using quasi -experimental evidence. We find that rent control offered large benefits to impacted tenants during the 1995-2012 4 period, averaging between $2300 and $6600 per person each year, with aggregate benefits totaling over $393 million annually. These effects are counterbalanced by landlords reducing supply in response to the introduction of the law. We conclude that this led to a city-wide rent increase of 7% and caused $5 billion of welfare losses to all renters. We discuss how the substantial welfare losses due to decreased housing supply could be mitigated if insurance against large rent increases was provided as a form of government social insurance, instead of a regulated mandate on landlords. Our paper is most related to the literature on rent control. Recent work by Autor et al. (2014) and Sims (2007) leverages policy variation in rent control laws in Cambridge, Massachusetts to study the property and neighborhood effects of removing rent control regulations. Our paper studies the effects of enacting rent control laws, which could have very different effects than decontrol. De -control studies the effects of removing rent control on buildings which remain covered. Indeed, we find a large share of landlords substitute away from supply of rent controlled housing, making those properties which remain subject to rent - control a selected set. Further, we are able to quantify how tenants use and benefit from rent control, a previously unstudied topic due to the lack of the combination of appropriate data, natural experiments and estimation methods. There also exists an older literature on rent control combining applied theory with cross- sectional empirical methods. These papers test whether the data are consistent with the theory being studied, but usually cannot quantify causal effects of rent control. (Early (2000), Glaeser and Lut.tnrer (2003), Gyouko and Linneman (1989), Gyourko and Linnernan (1990), Moon and S'totsky (1993) Olsen (1972)). Our estimation methods build on the dynamic discrete choice literature. Previous work using dynamic demand for housing and neighborhoods has required strong assumptions about how agents form expectations and how all neighborhood characteristics evolve over time (Bishop and Murphy (2011), Kennan and Walker (2011), Bayer et al. (2016), Davis et al. (2017), Murphy (2017)). We relax these assumptions by building on Scott (2013). His 5 key insight is to use realized values of agents' future expected utility as a noisy measure of agents' expectations. This method allows us to avoid needing to make explicit assumptions about how agents form expectations. Further, we do not need to assume how all state variables transition over time. Both of these assumptions are typically needed to estimate dynamic discrete choice models. Scott leverages "renewal" actions in tenants' choice sets which allows estimation to focus on specific actions in agents' choice sets which exhibit finite dynamic dependence, greatly simplifying the dynamic problem (Arcidiacono and Miller (2011), Arcidiacono and Ellickson (2011)). Our contribution is to show how Scott's method can be generalized to a set of difference -in -difference style linear and instrumental variable regressions that can be used in combination with a natural experiment to identify the model parameters. Finally, our paper is related to a separate strand of literature on community attachment in sociology. Kasarda and Jauowitz (1974) provide survey evidence that length of residence is correlated with various self-reported indicators of neighborhood attachment. We estimate households' attachments to their neighborhoods, as revealed by their migration decisions. Consistent with survey evidence, we find community attachment grows with years living in one's neighborhood, but it accumulates quite slowly over time. One additional year of residence increases one's community attachment by the equivalent of $300. The remainder of the paper proceeds as follows. Section 2 discusses the history of rent control in San Francisco. Section 3 discusses the data used for the analysis. Section 4 presents our reduced form results. Section 5 develops and estimates a dynamic discrete choice structural model. Section 6 discusses the welfare impacts of rent control. Section 7 concludes. 6 2 A History of Rent Control in San Francisco Rent Control in San Francisco began in 1979, when acting Mayor Dianne Feinstein signed San Francisco's first rent -control law. Pressure to pass rent control measures was mounting due to high inflation rates nationwide, strong housing demand in San Francisco, and recently passed Proposition 13.2 This law capped annual nominal rent increases to 7% and covered all rental units built before June 13th, 1979 with one key exemption: owner occupied buildings containing 4 units or less.s These "mom and pop" landlords were cast as less profit driven than the large scale, corporate landlords, and more similar to the tenants who were the ones being protected. These small multi -family structures made up about 30% of the rental housing stock in 1990, making this a large exemption to the rent control law. While this exemption was intended to target "mom and pop" landlords, small multi - families were increasingly purchased by larger businesses who would sell a small share of the building to a live-in owner, to satisfy the rent control law exemption. This became fuel for a new ballot initiative in 1994 to remove the small multi -family rent control exemption. This ballot initiative barely passed in November 1994. Beginning in 1995, all multi -family structures with four units or less built in 1979 or earlier were now subject to rent control. These small multi -family structures built prior to 1980 remain rent controlled today, while all of those built from 1980 or later are still not subject to rent control. 3 Data We bring together data from multiple sources to enable us to observe property characteristics, determine treatment and control groups, track migration decisions of tenants, and observe the property decisions of landlords. Our first dataset is frorn Infutor, which provides the 'Proposition 13, passed in 1978, limited annual property tax increases for owners. Tenants felt they were entitled to similar benefits by limiting their annual rent increases. aAnnual allowable rent increase was cut to 4% in 1944 and later to 60% of the CPI in 1992, where is remains today. 7 entire address history of individuals who resided in San Francisco at some point between the years of 1980 and 2016.1 The data include not only individuals' San Francisco addresses, but any other address within the United States at which that individual lived during the period of 1980-2016. The dataset provides the exact street address, the month and year at which the individual lived at that particular location, the name of the individual, and some demographic information including age and gender. To examine the representativeness of the Infutor data, we link all individuals reported as living in San Francisco in 1990 to their census tract, to create census tract population counts as measured in Infutor. We make similar census tract population counts for the year 2000 and compare these San Francisco census tract population counts to those reported in the 1990 and 2000 population counts for adults 18 ,years old and old. A regression of the Infutor populations on census population are shown in Figures A.1 and AY Figure A.1 shows that for each additional person recorded in the 1990 Census, Infutor contains an additional 0.45 people, suggesting we have a 45% sample of the population. While we do not observe the universe of San Francisco residents in 1990, the data appear quite representative, as the census tract population in the 1990 Census can explain 70% of the census tract variation in population measured from Infutor. Our data is even better in the year 2000. Figure A.2 shows that we appear to have 1.2 people in Infutor for each person observed in the 2000 US census. We likely over count the number of people in each tract in Infutor since we are not conditioning on year o death in theltrfut-GrdutT.,-lyding-tu-over counting of alive people. However, the Infutor data still track population well, as the census tract population in the 2000 Census can explain 90% of the census tract variation in population measured from Infutor. Now, Infutor matches well the level of the San Francisco population and generates an even higher R2 of 89.9%. We merge these data with public records information provided by DataQuick about the 4Infutor is a data aggregator of address data using many sources including sources such as phonebooks, magazine subscriptions, and credit header files. 'We only can do data validation relative to the US Censuses for census tracts in San Francisco because we only have address histories for people that lived in San Francisco at some point in their life. I particular property located at a given address. These data provide us with a variety of property characteristics, such as the use -code (single-family, multi -family, commercial, etc.), the year the building was built, and the number of units in the structure. For each property, the data also details its transaction history since 1988, including transaction prices, as well as the buyer and seller names. Again, we assess the quality of the matching procedure by comparing the distribution of the year buildings were built across census tracts among addresses listed as occupied in Infutor versus the 1990 and 2000 censuses. Figures A.3 and A.4 show the age distribution of the occupied stock by census tract. In both of the years 1990 and 2000, our R-squareds are high and we often cannot reject a slope of one. ' This highlights the extremely high quality of the linked Infutor-DataQuick data, as the addresses are clean enough to merge the outside data source DataQuick and still manage to recover the same distribution of building ages as reported in both 1990 and 2000 Censuses. To measure whether Infutor residents were owners or renters of their properties, we compare the last names of the property owners list in DataQuick to the last names of the residents listed in Infutor. Since property can be owned in trusts, under a business name, or by a partner or spouse with a different last name, we expect to under -classify residents as owners. Figures A.5 and A,6 plot the Infutor measure of ownership rates by census tract in 1990 and 2000, respectively, against measures constructed using the 1990 and 2000 censuses. In 1990 (2000), a one percentage point increase in the owner -occupied rate is leads to a 0.43 (0.56) percentage point increase in the ownership rate measured in Infutor. Despite the under counting, our cross-sectional variation across census tract matches the 1990 and 2000 censuses extremely well, with R-squareds over 90% in both decades. This further highlights the quality of the Infutor data. Next we match each address to its official parcel number from the San Francisco Assessor's office. Using the parcel ID number from the Secured Roll data, we also merge with any 6Since year built comes from the Census long form, these data are based only on a 20% sample of the true distribution of building ages in each tract, creating measurement error that is likely worse in the census than in the merged Infutor-DataQuick data. 9 building permits that have been associated with that property since 1980. These data come from the San Francisco Planning Office. This allows us to track large investments into renovations and changes in building use type over time based on the quantity and type of permit issued to each building over time. The parcel number also allows us to link to the parcel history file from the Assessor's office. This allows us to observe changes in the parcel structure over time. In particular, this allows us to determine whether parcels were split off over time, a common occurrence when a multi -family apartment building (one parcel) splits into separate parcels for each apartment during a condo conversion. Historical data on annual San Francisco wide market rents are from a dataset pro- duced by Eric Fisher, who collected historical apartment advertisements dating back to the 1950s. See https://experimental-geography.blogspot.ca/2016/05/employment-construction- and-cost-of-san.html for further details on the construction. Figure 1 shows the time series of SF rental rates generated by this data. We use an imputation procedure to construct annual rents at the zipcode level. Specifically, using census data we construct a relationship between zipcode house price deviations from the SF mean and zipcode rent deviations from the SF mean. We then use this relationship to construct zipcode level rent measures in the years we don't have census data.7 Summary statistics are provided in Table 1 and Table 2. 4 Reduced Form Effects Studying the effects of rent control is challenged by the usual endogeneity issues. The tenants who choose to live in rent -controlled housing, for example, are likely a selected sample. To overcome these issues, we exploit the particular institutional history of the expansion of rent control in San Francisco. Specifically, we exploit the successful 1994 ballot initiative which Census data reports rents paid by tenants, not asking rents. We therefore use a level adjustment to ensure that the average imputed market SF rent is equal to that reported by Eric Fisher. See the appendix for the exact details of the imputation procedure. 10 removed the original 1979 exemption for small multifamily housing of four units or less, as discussed in Section 2. In 1994, as a result of the ballot initiative, tenants who happened to live in small mul- tifamily housing built prior to 1980 were, all of a sudden, protected by statute against rent increases. Tenants who lived in small multifamily housing built 1980 and later continued to not receive rent control protections. We therefore use as our treatment group those renters who, as of December 31 1993, lived in multifamily buildings of less than or equal to 4 units, built between years 1900 and 1979. We use as our control group those renters who, as of December 31, 1993, lived in multifamily buildings of less than or equal to 4 units, built be- tween the years of 1980 and 1990. We exclude those renters who lived in small multifamily buildings constructed post 1990 since individuals who choose to live in new construction may constitute a selected sample and exhibit differential trends. We also exclude tenants who moved into their property prior to 1980, as the none of the control group buildings would have been constructed at the time. When examining the impact of rent control on the parcels themselves, we use small multifamily buildings built between the years of 1900 and 1979 as our treatment group and buildings built between the years of 1980 and 1990 as our control group. We once again exclude buildings constructed in the early 1990s to remove any differential effects of new construction. Figure 2 shows the geographic distribution of treated buildings and control buildings in San Francisco. 4.1 Tenant Effects We begin our analysis by studying the impact of rent control provisions on its tenant bene- ficiaries. We use a differences -in -differences design described above, with the following exact specification: Yt = Sit + of + Qt * Tz +'yst + Eit. (1) 11 Here, Yt are outcome variables equal to one if, in year t, the tenant i is still living at either the same address, in the same zipcode z, or in San Francisco as they were at the end of 1993. The variables S t and ai denote zipcode by year fixed effects and individual tenant fixed effects, respectively. The variable Tt denotes treatment, equal to one if, on December 31, 1993, the tenant is living in a multifamily building with less than or equal to four units built between the years 1900 and 1979. We include fixed effects -Y,t denoting the interaction of dummies for the year the tenant moved into the apartment s with calendar year t time dummies. These additional controls are needed since older buildings are mechanically more likely to have long-term, low turnover tenants; not all of the control group buildings were built when some tenants in older buildings moved in. Finally, note we have included a full set of zipcode by year fixed effects. In this way, we control for any differences in the geographic distribution of treated buildings vs, control buildings, ensuring that our identification is based off of individuals who live in the same neighborhood, as measured by zipcode,',' Our coefficient of interest, quantifying the effect of rent control on future residency, is denoted by Vit. Our estimated effects are shown in Figure 3, along with 90% confidence intervals. We can see that tenants who receive rent control protections are persistently more likely to remain at their 1993 address relative to the control group. Not only that, but they are also more likely to be living in San Francisco. This result indicates that the assignment of rent control not only impacts the type of property a tenant chooses to live in, but also their choice of location and neighborhood type. These figures also illustrate how the time pattern of our effects correlates with rental 8We have also ran our regressions with census tract by year fixed effects and our results are robust to this even finer neighborhood classification. Further, dropping the zip -year fixed effects also produces similar results. 9While there may be some sorting into older buildings based on personal characteristics, it seems likely that once neighborhood characteristics have been controlled for, as well as the number of years lived in the apartment as of December 31, 1993, these characteristics would not lead to differential trends in migration decisions which could contaminate our estimates. As a robustness test, we have restricted our treatment group to individuals who lived in structures built between 1960 and 1979, thereby comparing tenants in buildings built slightly before 1979 to tenants in buildings built slightly after 1979. We find very similar results. 12 rates in San Francisco. We would expect that our results would be particularly strong in those years when the outside option is worse due to quickly rising rents. Along with our yearly estimated effect of rent control, we plot the yearly deviation from the log trend in rental rates against our estimated effect of rent control in that given year. We indeed see that our effects grew quite strongly in the mid to late 1990s in conjunction with quickly rising rents, relative to trend. Our effects then stabilize and slightly decline in the early 2000s in the wake of the Dot-com bubble crash, which led to falling rental rates relative to trend. Overall, we measure a correlation of 49.4% between our estimated same address effects and median rents, and a correlation of 78.4% between out estimated SF effects and median rents. In Table 3, we collapse our estimated effects into a short-term 1994-1999 effect, a medium- term 2000-2004 effect, and a long-term post -2005 effect. We find that in the short -run, tenants in rent -controlled housing are 2.18 percentage points more likely to remain at the same address. This estimate reflects a 4.03 percent increase relative to the 1994-1999 control group mean of 54.10 percent. In the medium term, rent -controlled tenants are 3.54 percent- age points more likely to remain at the same address, reflecting a 19.38 percent increase over the 2000-2004 control group mean of 18.27 percent. Finally, in the long-term, rent -controlled tenants are 1.47 percentage points more likely to remain at the same address. This is a 12.95 percent increase over the control group mean of 11.35 percent. These effects are intuitive since we expect the utility benefits of staying in a rent controlled apartment to grow over time as the wedge between controlled and market rents widen. Tenants who benefit from rent control are 2.00 percentage points more likely to remain in San Francisco in the short, term, 4.51 percentage points more likely in the medium-term, and 3.66 percentage points more likely in the long-term. Relative to the control group means, these estimates reflect increases of 2.62 percent, 8.78 percent, and 8.42 percent respectively. Since these numbers are of the same magnitude as the treatment effects of stay at one's exact 1994 apartment, we find that absent rent control essentially all of those incentivized to stay in their apartments would have otherwise moved out of San Francisco. 13 These estimated overall effects mask interesting heterogeneity. We begin by cutting the data on two dimensions. First, we cut the data by age, sorting individuals into two groups, a young group who were aged 20-39 in 1993 and an old group who were aged 40-65 in 1993. We also sort the data based on the number of years the individual has been living at their 1993 address. We create a "low turnover" group of individuals who had been living at their address for greater than or equal to four years and a "high turnover" group of individuals who had been living at; their address for between four and fourteen years. Finally, we form four subsamples by taking the 2 x 2 cross across each of these two dimensions and re -estimate our effects for each subsample. The results are reported in Figure 4. We summarize the key implications. First, we find that the effects are weaker for younger individuals. We believe this is intuitive. Younger households are more likely to face larger idiosyncratic shocks to their neighborhood and housing preferences (such as changes in family structure and employment opportunities) which make staying in their current location particularly costly, relative to the types of shocks older households receive. Thus, younger households may feel more inclined to give up the benefits afforded by rent control to secure housing more appropriate for their circumstances. Moreover, among older individuals, there is a large gap between the estimated effects based on turnover. Older, low turnover households have a strong, positive response to rent control. That is, they are more likely to remain at their 1993 address relative to the control group. In contrast, older, high turnover individuals are estimated to have a negative response to rent control. They are less likely to remain at their 1993 address relative to the control group. To further explore the mechanism behind this result, we do another cut of the data, sorting individuals based on the 1990-2000 rent appreciation of their 1993 zipcode. Individ- uals are then sorted into two groups based on whether their zipcode experienced above or below median rent appreciation. We now estimate our effects by age, turnover, and zipcode rent appreciation. The results are in Figure 5 and Figure 6. Among older, lower turnover 14 individuals, we find that the effects are always positive and strongest in those areas which experienced the most rent appreciation between 1990 and 2000, as one might expect. For older, high turnover households, however, the results are quite different. For this subgroup, the effects are actually negative in the areas which experienced the highest rent appreciation. They are positive in the areas which experienced below median rent appreciation.1' This result suggests that landlords are likely actively trying to remove tenants in those areas where rent control is affording the most benefits, i.e. high rent appreciation areas. There are a few ways a landlord could accomplish this. First, landlords could try to legally evict their tenants by, for example, moving into the properties themselves, known as owner move -in eviction. Alternatively, landlords could evict tenants according to the provisions of the Ellis Act, which allows evictions when an owner wants to remove units from the rental market - for instance, in order to convert the units into condos or a tenancy in common. Finally, landlords are legally allowed to negotiate with tenants over a monetary transfer convincing them to leave. Such transfers are, in fact, quite prevalent in San Francisco. Moreover, it is likely that those individuals who have not lived in the neighborhood long, and thus not developed an attachment to the area, could be more readily convinced to accept such payments or are worse at fighting eviction. Indeed, since landlord can evict or pay tenants to move out, rent control need not inefficiently distort renters' decisions to remain in their rent controlled apartments. Tenants may "bring their rent control with them" in the form of a lump sum tenant buyout. Of course, if landlords predominantly use evictions, tenants are not compensated for their loss of rent protection, weakening the insurance value of rent control. These considerations help to rationalize some additional, final findings. In Figure 7 and Figure S, we examine the impact that rent control has on the types of neighborhoods tenants live in in a given year. We find that treated individuals, i.e. those who received rent control, ultimately live in census tracts with lower house prices, lower median incomes, and lower 1OA similar pattern holds for younger individuals as well, although the results are weaker. 15 college shares than the control group. As Figure 9 and Figure 10 show, this is not a function of the areas in which treated individuals lived in 1993. In this figure, we fix the location of those treated by rent control at their 1993 locations, but allow the control group to migrate as seen in the data. If rent -controlled renters were equally likely to remain in their 1993 apartments across all locations in San Francisco, we would see the sign of the treatment effects on each neighborhood characteristic to be the same as in the previous regression. Instead, we find strong evidence that the out -migration of rent -controlled tenants came from very selected neighborhoods. Had treated individuals remained in the 1993 addresses, they would have lived in census tracts which had significantly higher college shares and higher house prices than the control group. This evidence is consistent with the idea that landlords undertake efforts to remove their tenants or convince them to leave in improving, gentrifying areas. 4.2 Parcel and Landlord Effects We continue our analysis by studying the impact of rent control on the structures themselves. In particular, we examine how rent control impacts the nature of the tenants who live in the buildings, as well as its impact on investments that landlords choose to make in the properties. We run a similar specification to that above: Ykt = bzt + Ak +,dt * Tk + ckt, (2) where k now denotes the individual parcel and Ak represent parcel fixed effects. The variable Tk, denotes treatment, equal to one if, on December 31, 1993, the parcel is a multifamily building with less than or equal to four units built between the years 1900 and 1979. The 6,zt variables once again reflect zipcode by year fixed effects. Our outcome variables Ykt now include the number of renters and owners living in the building, whether the building sits vacant, the number of renovation permits associated with the building, and whether the 16 building is ever converted to a condo. The permits we look at specifically are addition/al- teration permits, taken out when major work is done to a property. We begin by plotting in Figure Ila the effects of rent control on the number of individuals living at a given parcel, calculated as percentage of the average number of individuals living at that parcel between the years 1990-1994. We estimate a decline of approximately 10 percent over the long -run, although this effect is not statistically significant. We next decompose this effect into the impact on the number of renters and the number of owners living at the treated buildings. As shown in Figure 111), we find that there is a significant decline in the number of renters living at a parcel, approximately equal to 20 percent in the late 2000s, relative to the 1990-1994 level. Figure Ile shows that the decline in renters was counterbalanced by an increase of approximately 10 percent in the number of owners in the late 2000s. This is our first evidence suggestive of the idea that landlords redeveloped or converted their properties so as to exempt them from the new rent control regulations. We now look more closely at the decline in renters. In Figure 12b, we see that there is an eventual decline of almost 30 percent in the number of renters living in rent -controlled apartments, relative to the 1990-1994 average." This decline is significantly larger than the overall decline in renters. This is because a number of buildings which were subject to rent control status in 1994 were redeveloped in such way so as to no longer be subject to it. These redevelopment activities include tearing down the existing structure and putting up new single family, condominium, or multifamily housing or simply converting the existing structure to condos. These redeveloped buildings replaced about 10 percent of the initial rental housing stock treated by rent control, as shown in Figure 12a. A natural question is whether this redevelopment activity was a response of landlords to the imposition of rent control or, instead, if such activity was also taking place within the control group and thus reflected other trends. Since we have the entire parcel history 11Note here that we mean relative to the number of individuals who lived at parcels which received rent control status clue to the 1994 law change. 17 for a property, we can check directly whether a multifamily property which fell under the rent control regulations in 1994 is more likely to have converted to condominium housing or a tenancy in common, relative to a multifamily property which did become subject to rent control. In Figure 12c, we show that treated buildings are 8 percentage points likely to convert to condo or TIC in response to the rent control law. This represents a significant loss in the supply of rent controlled housing. As a final test of whether landlords actively respond to the imposition of rent control, we examine whether the landlords of rent -controlled properties disproportionately take out addition/alteration (i.e. renovation) permits. We find this to strongly be the case, as shown in Figure 12d. Of course, conversions of multifamily housing to condos undoubtedly require significant alteration to the structural properties of the building and thus would require such a permit to be taken out. These results are thus consistent with our results regarding condo conversion. Moreover, under the San Francisco rent control regulations, capital improvements can be passed onto tenants in the form of higher rents. If the existing tenants are unable to afford the higher rents, capital improvements could be one way to get new tenants in the property and reset to market rents. It is important to note that this evidence contradicts the traditional view of rent control, that landlords will be disincentivized from investing in the property. On the contrary, we find that landlords appear to make significant investments in their properties. Taken together, we see rent controlled increased property investment, demolition and reconstruction of new buildings, conversion to owner occupied housing and a decline of the number of renters per building. All of these responses lead to a housing stock which caters to higher income individuals. Rent control has actually fueled the gentrification of San Francisco, the exact opposite of the policy's intended goal. 18 5 A Structural Spatial Equilibrium Model The reduced form shows that rent control can either increase or decreases tenancy durations depending on whether the tenant receives a buyout or eviction or instead remains at their residence at below market rents. To quantify how tenants trade off these decisions and to quantify the welfare impact of rent control to covered tenants, we estimate a dynamic discrete choice model of neighborhood choice. 5.1 Model Setup Each year t, a household decides whether to remain in its current home, a choice which we denote as S, or to move, in which case the households chooses a neighborhood j E j to live in. We denote the household's choice as x E {S} U J. The relevant state variables for the household's decision problem are the current neighborhood jt -1 E J, the number of years lived in the current neighborhood r,,,t_1 E NU {0} , the number of years lived in the current house Th,t-1 E NU {0}, and whether the residence is rent -controlled dt-1 E {0, 11 . We also have a state variable at -1 E {Y, M} denoting whether the household is in a young (Y) or mature (M) state of life. We let Bt -I _ (jt -1, 7a,t-1, 7h,t-1, dt-r, at -r) denote the household's current state variable. The transition dynamics of the state variable are straightforward. We . have it = j (xt), where: 7 (xt) = 7t --r if xt = S j (xt) = xt otherwise. This equation simply says that the neighborhood remains the same if the household decides to remain in its current home. Otherwise, the new neighborhood is given by the household's choice. The implications for years in the current neighborhood and years in the current 19 house are clearly similar, with: and Tn (xt) = Tn,t-1 + 1 if xt E {S, jt -1} T„ (xt) = 0 otherwise. Th (xt) = 7-h,t-1 + 1 if xt = S Tn, (xt) = 0 otherwise. Finally, we assume that each period young households transition to mature households with exogenous probability �. This is clearly a simplification, made due to limitations of the data, but captures the idea that households experience certain life events such as marriage and having children at different ages.12 Mature households do not transition back into young households. We denote the (probabilistic) transition function as Bt = O (xt, Bt -1) . We identify the set of neighborhood locations ,7 as the San Francisco zipcodes, the counties (other than San Francisco County) in the Bay Area, and an outside option denoting any location outside of the Bay Area. We assume that a household i has the following per -period utility from their housing decision: u (x, Wt, Fite Bt -1) = -ya eXp Rt (i, d, 7h) + n'aTn +W a, (x, jt-1,Tn,t-1) (3) + A (x, dt-1) +wjt + Est, where Rt (j, d, Th) denotes the rent paid at the chosen location, tpa (x, jt -1, Tn,t-1) are mov- ing costs, At (x, dt_1) are possible monetary transfers from landlords to tenants, w t is an unobservable neighborhood taste shock, and etxt is an idiosyncratic logit error taste shock 12I11 principle, we could tract the exact age as a stage variable, but this makes the state space very large. over the possible choices which is specific to household i." Note that we are suppressing the dependence of (j, 7, d) on x. If a tenant does not live in a rent -controlled property, she pays market rents, given by Rt (j, 0) . Thus, there is no dependence on 7h. In contrast, the rent paid by tenants in rent -controlled properties Rt (j, 1, 7h) is a function of the number of years lived in the property. Crucially, note that the household has utility over exponential rents, with coefficient gip,. We, of course, expect this coefficient to be negative. This assumption ensures, due to the effects of Jensen's inequality, that rent control offers real insurance value to tenants. We moreover allow for utility to depend on how long a household has lived in the current neighborhood, as measured by parameter aa. Intuitively, households may build up neighborhood capital over time which makes that location more attractive. For instance, over time people form meaningful friendships with their neighbors and acquire valuable local knowledge, such as that regarding local amenities. We allow both the rent utility parameter and neighborhood capital parameter to depend on whether the household is in the young or mature stage of life. Households incur moving costs when they switch homes. We assume that there is a fixed moving cost W0,. > 0, as well as a cost Va,o, > 0 that is variable with distance. We allow the variable moving cost parameter to depend on current neighborhood capital 7,,t-1, with the interaction effect measured by �T.a This allows for the possibility that the desirability of nearby neighborhoods changes as one accrues neighborhood capital. In particular, (Pa (x,it- r) = 0 if xt = S (Pa (X, it -1) = �00,a + (Pd,ad (it, it-,) +WT,a (d (it,it--r) x 7,a,t-r) otherwise, where d (jt, jt -r) denotes the distance between the old and new neighborhoods. We allow the moving costs to vary with age. For example, it seems likely that households with children will find moving more costly than households without children, since changing schools could 13We measure rents as monthly rents divided by 3000, measured in 2010 dollars. We divide by 3000 for computational convenience. 21 prove disruptive. We also allow for possible monetary transfers from landlords of rent -controlled properties to tenants incentivizing them to move. These may represent true tenant buyouts or the amount of buyout that would have been required to rationalize the tenant out -migration, even if in reality the migration was due to eviction. In practice, the city of San Francisco allows for such negotiations and these payments are, in practice, quite prevalent. We do not explicitly model the bargaining game between landlords and tenants. Instead, we proceed in more reduced form fashion and parameterize the transfers as: At (x, dt_r, at -r) = 0 if xt = 8 or dt-r = 0 At (x, dt-1, at -r) = ai [Rt (j, 0) - Rt (j, 1, 7h)] -I- a27n + Ayl [at -r = Y] otherwise. The first equation simply says that, if the tenant does not move or does not live in rent - controlled housing, he receives no transfers. The first term in the second equation denotes the difference between market rents and rent -controlled rents. We would expect the coefficient on this term, Ar, to be weakly positive. Intuitively, the greater the current difference between market rents and rent -controlled rents, the greater the incentive for landlords to remove tenants and thus the more landlords should be willing to pay to convince tenants to leave. We also allow for the outcome of the bargaining to depend on neighborhood tenure 7 ,,, with the impact measured by the coefficient %2. This allows for more invested tenants to receive a larger payment, since their outside option, i.e. choosing to stay, is likely better than that of a short term tenant who has not built up a large stock of neighborhood capital. Finally, we allow the level difference in transfers to differ between young and mature households, measured by Ay. We decompose the unobservable neighborhood amenity value wjt into w,jt = wj -4' w7t, 22 where wj is a time -invariant fixed effect and w t is a per -period neighborhood specific shock. We impose no structure on the distribution of w t beyond requiring that F(wj,t+llcjt, xit) = F(w ,t+l lcjjt). That is, the decision of any individual agent has no impact on the distribution of the neighborhood amenity value next period. Letting R denote the common discount factor, the household's dynamic optimization problem at time t is given by: V (0i,t-1, wt, Eit) = max E Qs—t'U' (`r*, wt, Eit, 9i,t-1) 10i,t-1, wt, Eit� x" s>t We next define the ex -ante value function V (Bit, wt) by integrating over the idiosyncratic errors: Vt (Bt -1) = J ... / V (Bt -1, wt, lElr ..., EJ+1)) dF (El) ... dF (EJ+1) , where J is the number of neighborhoods and EJ+l it the logit error associated with staying in the current home. From this we can define the value function conditional on actions: vt (x, Bt -1) = ut (x, Bt -1) +OEt [Vt+1 (n (x, et -1))] , where ut (x, Bt -1) = u (x, wt, 0, Bt -1), © (x, Bt -1) denotes the state transition function, and Et [•] denotes expectations conditional on time t information. Since the idiosyncratic taste shocks follow a logit specification, we get the standard results (see e.g. Hotz and Miller (1993)) relating conditional value functions to conditional choice probabilities pt (XjBt_1): pt(xIA-1) = exp (vt(x,Bt-1)) (4) E�, exp (vt (xt, Bt -1)) In what follows, we denote the log of the denominator of this expression as: It (Bt -1) = In ��, eXp (vt (x', dt-1)) X, / 23 We also have that the ex -ante value function is given by: Vt (Bt -1, wt) = It (Bt -1) + F, (5) where F is Euler's gamma. 5.2 Renewal Actions The key challenge in identifying dynamic discrete choice models is dealing with the ex- pected continuation values in the Bellman equation. To be able to calculate the expected continuation values, one generally must make assumptions about exactly how agents form expectations, including exactly what information is known to the agent and how they ex- pect market -level state variables to evolve. This normally requires assuming all market state variables (e.g. rents and amenities) are observed and follow assumed transition dynamics. We build on Scott (2013) and make no assumptions about how amenities evolve. We also do not assume how agents form expectations about future market states, other than that they are on average rational. Following work by Arcidiacono and Ellickson (2011) and Arcidia- cono and Miller (2011), we make extensive use of renewal actions, or action(s) which, given current states Bt_r and 0't_1, lead to the same state in the next period. This will allow us to difference out much of the long-term continuation values in the Bellman equation, which are impossible to estimate without strong assumptions. 5.2.1 Immediate Renewals Suppose we have two households in states Bt_r and 0t_1. In period t, these two households take the actions x and x' respectively. Using equation (9) and differencing we find that: vt (x; Bt -r) - vt (x', 0' t-1) = In pt (xI B t-1) + It (Bt -1) - It (Bi -r) 24 Substituting in for the conditional value functions, we get: ut (x, Bt -1) - ut (x , Bt -1) + �Et [V -t+1 (©(x, Bt -1))J - QEt IVt+1 (8 (x', Bt -r))] (6) In pt (x Bt -r) pt (x 1Bt-1) Now assume x and x' are renewal actions in the sense that 0 (x, Bt -1) = O (x', 0t_1) . Note that we do not require x = x', although this will often be the case. For example, if two households in non -rent controlled housing are living in the same neighborhood j and have the same level of neighborhood tenure, then x = S and x' = j, i.e. one household choosing to stay in the current home and the other moving to another house in the same neighborhood, constitute renewal actions. The key implication is that the future continuation values difference out, leaving: x Bt -1 ( ) ut (x Bt -1) - Tit, Bt -1) = In pt + It (Bt -1) - It (01t-1) (7) If Bt -1 0 0't-1, we also need to remove the difference of log sums, which implicitly involves future continuation values as well. To do so, suppose the households move to some neighborhood j* E J, with j* =h x and j* j x'. This always constitutes a renewal action, so we get equation (7) again with x and X' replaced with j*: 'at (j*, Bt -1) - ut (j* 0t-1) = In �A(j l Bt 1) +It (Bt -1) - It (Bt -1) (8) t-1 Differencing equations (7) and (8) yields: In A (xlBt-1) _ In pt (j*'Bt-t) _ �u x B _t) - ut �x >Bt -1)] (p) A (x'�Bt-t) A (j*lot-1) ( t 25 which removes the log sums. Intuitively, equation (9) compares the difference in utility between two different actions a household in state Ot-1 could take versus a household in state 0/ t_1. This "differences -in -differences" approach removes all long-term utility differences since actions are selected to create renewals. 5.2.2 One Period Ahead Renewals Now suppose that x and x' are not renewal actions in period t. Following Scott (2013), we substitute the expected difference in continuation values in equation (6) with its realization and expectational errors: where a (x, Ot-1) - ut W, Bt-.1� - In (Ptt(7 1) - [It (Ot-1) - It (Oi-1)� t-1 l� M+1 (0- (� , 0't-1)) - Vt+1(O (x, Ot-1))) + t (x�, Bt -1) - t (x, Ot-1) �(x, Ot-1) _ �3 (Et [Vt+1 (O (x, Ot-i))] - Vt+1 (O 1)) (x, Ot-) is the expectational error. We now again make use of renewals. Suppose that at time t + 1, both households move to the same neighborhood, that is xt+1 = xt+1 = j* E J. To see the effects of this, first substitute out the realized ex -ante value functions using equations (4) and (5). We have: ut (x,Ot-1) - at W, 0t-1) - In (Ptt(91� O1� [It (Ot-1) - It (0t-1)[ t-1 1) - (vt+1 (j*, (x,, 0,t-1)) - vt+1 W, O (x, Ot-0)) -a In (Pt+1 (I *, 0 (x� 0t-1) ) / + di (X1, 0t-1) - ci (x, 0t-1) . Pt+1 (j*, O (xI0t Since j* is a renewal action, the time t+ 2 expected value functions difference out and this 26 equation becomes: ut (x, Bt -1) - ut W, Bt -1) - In ( A (� t 1) _ [It (Ot-1) - It (Bt -0 (10) r r \ t-1 (ut+1 W , 0 / lxr' Ot-1/1\ -`Ut+1 U�, 8 (X, Bt -1))) C ( pt+1�pt+1 W,6VlHt-1/l1 V V - In », Q (xlet-1)) J + �t �x +Bt-1� - �t (� Bt -1)• To fully remove the conditional value functions, we once again must remove the difference in log sums It (Bt -1) - It (O'_1) . We follow the same procedure as previously, subtracting equation (8) from equation (10): In PtNot t 1)-1n(pt(7`Bt-1)�+0ln�Pt-pi (i',C(xet-1))� (11) AVl8-) A(j*I9-) pt+1(j'©(xrl86-1)) [Ut (x, Bt -1) - 4tt (x , Bt-1)� - [�'t (� , Bt -1) - 1tt (� ' Ot-1)] +0 (ut+1 U*' Q (x, Bt -1)) - ut+1 U*, E) (x, Bt -1))) +S2 (X Bt -1) - St (x, Bt -1) Equations (9) and (11) provide a linear regression framework which we can use to fully identify and estimate the parameters of the model. 5.3 Empirical Framework We now discuss how to empirically operationalize the preceding considerations. 5.3.1 Constructing Conditional Choice Probabilities We first need to construct empirical estimates of the conditional choice probabilities, pt (xI Bt -1). In a given year t, we focus on those households who were part of the 1994 treatment and control groups described in the previous section and who have not moved away from their 1994 residence. Given the latter restriction, we do not need to keep track of Th and we therefore suppress the dependence of Bt -1 on this state variable in what follows. 27 With a large enough dataset, we could simply compute empirical frequencies for all con- ditional choice probabilities. However, since there are many states, not all OCPs in our data are measured precisely. We therefore use kernel smoothing on the empirical frequencies to improve the prediction error. We smooth over distance, neighborhood tenure, and age. We use a Gaussian kernel. Distance is measured between the midpoints of zipeodes. Neighbor- hood tenure equals the number of years the renter has lived in that zipcode. Young renters are those under the age of 40, while mature/old renters are those 40 and older. We use k -fold cross validation to set the optimal bandwidths with k=5. 5.3.2 Identifying the Parameters of the Model We set R = .85.14 We estimate the various parameters of the model by estimating equa- tion (9) and (11) for appropriately chosen values of (01_1,Bt_1) and (x, x'). Intuitively, by examining the differential behavior of individuals in certain states of the world and follow- ing certain types of deviations, we can isolate the impact of the different parameters of the model. We begin by constructing a regression equation for -ym, ar, and A2. These are the (mature) rent utility parameter and the parameters of the transfer function. Normally, we would be confronted with a significant endogeneity problem in estimating these parameters since market rents Rt (j, 0) in neighborhood j are likely correlated with the amenity value w t unobservable to the econometrician. We overcome this essential endogeneity problem by exploiting the quasi -experimental na- lure of the 1994 San Francisco rent control ballot measure. This law change quasi -randomly assigned renters within a given neighborhood j to rent control status. As mentioned, we focus exclusively on this population for our regressions. Now let Ot_r = (j,T, 1, M) and Fl t_1 = (j,T, 0, M) for some j E J. We furthermore set X = x' = S and let j* be any element of ,7. In words, we consider two mature households who both lived in neighborhood j in 1994 and have not moved as of year t. The two households 14This choice is consistent with the evidence provided in De Groote and Verbovcn (2016), who estimate a household discount factor of .87. 28 are of equal tenure Tn. One was assigned to rent control status in 1994 and the other was not. We examine the relative probabilities of these individuals staying in neighborhood j in year t, using neighborhood j* as the renewal choice in the manner described in the previous section. Under these assumptions, equation (1.1) gives the regression: Yt . = yM [exp Rt (j, 1) - exp Rt (j, 0)] + +A, [(R In Rt+r (j, 0) - In Rt (j, 0)) - (0 In Rt+r (j,1) - In Rt (j, l))] +a2 [a (t+T� + 1) — (t+Tm,)] V +fit (Xl' Olt -0 - d (x, et -r) + Xjt,j" t In Pt (5l9, 1,'rn) In Pt (.7*�j, 1,Tn)� +0111 Pt+r (j* 1j, 1, 7n) Y = - Pt (5l9, 0,T�) Pt (j*h, 0,T.) Pt+r (j*lj, 0,7.) Intuitively, this regression compares the probability of staying in the neighborhood for one more year and then moving to j* versus moving to j* this year. This difference in probabilities is then differenced between treatment and control, which differences out all the utility impacts of living in j vs j* other than those which are impacted by rent control. Note that we have included an additional error term X',,., reflecting measurement er- ror in our constructed conditional choice probabilities. The key for identification is that the unobserved amenity value wit differences out. We furthermore know that: Et [(Rt (j, 1) - Rt (j, 0)) (� � , Bt-i� - � (x, Bt -1))] = 0 due to rational expectations. That is, the expectational error is uncorrelated with any time t information. In general, however, we do not have: Et [(Rt -i -t (j, 1) - Rt+r (j, 0))t (x dt-r� - � (x, Bt -1)) 0. The time t+1 rent difference may be correlated with the expectational error. This is intuitive. For instance, neighborhood j may be better at date t + 1 than was expected since market 29 rents are lower than anticipated. We, therefore, instrument for the time t + 1 rent difference Rt+1 (j,1) - Rt_1_1 (j, 0) with Zt, equal to the one -period lagged value Rt (j,1) - Rt -1 (j, 0). Since Zt is in the time t information set, we have: Rt [Zt (fit W, O't_l) - 5(x, Bt -r))] = 0. Thus, our exclusion restrictions are satisfied and the parameters are identified. To identify the impact of tenure on utility am, consider two mature households living in non -rent controlled housing in neighborhood j, with different levels of initial tenure, T,,, and T'n.Suppose both households move to j* after one year. We thus have Bt_1 = (j, T,, 0, M) and 0't_1 = (j,Tn, 0, M) for some j E j and x = x' = S. Then equation (11) becomes: Y`�. = am ('rm, - 7-,n) +' t W , Bt -1) - � (x, Bt -1) + Xt3,. t In CA(SIj, 0, 7.)In 1 �A(j*Ij,0,7.)+ ,(31n � �pt+1(.i*Ij,0,T,)� Y = J - pt(Sh,O,Tn) Pt(j*j,O,Tn) 7h+1(j*Ij,0,T') Since both households live in non -rent controlled housing in the same neighborhood, they pay the same rents and receive the same unobserved amenity value. Indeed, the only payoff - relevant difference between the two populations is the number of years they have lived in the neighborhood. Thus, appropriately examining the relative probabilities of staying in the neighborhood is informative of the importance of tenure on utility or, in other words, of the magnitude of nM. Intuitively, as one builds up more neighborhood capital, the benefits of staying in the neighborhood an additional year. Thus, the relative probability of staying one more year versus moving away should grow if neighborhood capital is accruing. To estimate moving costs, we consider two mature households of equal tenure T. living in non -rent controlled housing in neighborhood j. Suppose that one household immediately moves to another house in the same zipcode and one household stays in the same home. Formally, Bt -1 = 0' t-= (j, T., 0, M), x = S, and x' = j. As was discussed in Section 5.2.1, this constitutes an immediate renewal since rents do not change and neighborhood tenure 30 does not change. Since one is only changing the house they live in due to the logit error and the moving costs, we can identify the fixed cost of moving. If people move houses a lot within a zipcode, moving costs must be low. If they do it rarely, moving costs must be high. Equation (9) gives the regression: Yt =—YO,M+Xi Yt = InPt(SIj,0,Tn) Pt (jlj, o, Tom) which identifies the fixed moving cost parameter cpo,M . Note that there is only one log difference instead of two since the households begin in the same state. We also need the variable moving cost parameter, Od,M. Consider two mature households of equal tenure T., both living in non -rent controlled housing, one living in neighborhood j and the other in neighborhood j'. Suppose they immediately move to either neighborhood j* or j**. Both of these are choices constitute immediate renewals. Therefore, Equation (9) gives the specification: JJ'j*,i** _ Wd,M (dj,j* — dYJ-) — Pd,M (dj,j** — dj',j") +Xj,j',j*,j*. Yl,;.:*. = In Pt(j*9,01T,,)�-1n�Pt(j**j,0,T-)� 9.j ,J ,J Pt U* �j" 0,'r ,) Pt (j** lj', 0, Tiro) Intuitively, this compares the relative probabilities of moving to j* vs j** depending on whether one starts in j or j'. If j is very close to j*, but far from j**, then the difference in moving costs between the moves in large. However, if j' is equidistant between the two, the moving costs between the two locations are the same. The relationship between these differences in distances and differences in migration probabilities identifies the marginal cost of moving with respect to distance. Using similar considerations, one can estimate the interaction term parameter �oT M. The equation is detailed in the appendix. As one would expect, the equations for young households are very similar to the ones described above, but the probability of transitioning to a mature household must be taken 31 into account. Furthermore, one can use the treatment group as well as the control group to estimate the neighborhood tenure parameters and the variable moving cost parameters. All of these additional equations are detailed in the appendix. The model is then estimated via GMM. Finally, it remains to estimate the permanent component of amenities wj.l° We do so after estimating the full GMM system detailed above. We once again consider two mature households of equal tenure T,,,, living in neighborhoods j and j' respectively and suppose that both households move to some neighborhood j* after one year. We thus have, At -1 = (j, Tom, 0, M) , Ot_r = (j', T,,,, 0, M) , and x = x' = S. These choices yield the equation: Ytj',j* _ �j — ��' + wjt — wj,t + �t �� , 01 —r) — C (x, Bt—r) + Xj,j',j* Y = In Pt (SIj'O,T.In ) Pt (j* J,0,T.) Pt+1 (j*Ij,0, T.) ,, .. RJ ,9 (Pt (Slj',O,Ta)� (Pt U*Y'0!T.) Pt+1(j*Y,0,7.,) - (B - 1) toj,M (dj,j* - dj, j,) - ym [Rt (j, 0) - Rt (j', 0)] Identification comes from the fact that, averaging over time, we average out the per -period neighborhood amenity shocks and expectational error shocks. Moreover, note that we do not have an endogeneity problem since we have already estimated -ym and can therefore move the utility impact of the rent difference to the left hand side of the equation. We also account for the differential moving costs related to distance on the left hand side of the equation. Finally, note that we can only identify fixed amenity value differences between neighborhoods. We therefore choose a normalization, letting zipcode 94110, representing the Mission District and Bernal Heights, be our baseline zipcode. We set its amenity value fixed effect to zero. "We cannot identify amenities of the outside options, i.e. the rest of the Bay Area and the rest of the country, as no one in our 1994 cohorts started off living in those locations. 32 5.4 Model Estimates Table 4 shows the parameter estimates of the model. Panel A reports the parameters mea- sured in rent equivalent dollar units, with the exception of the transfer payments, which are measured in actual dollar amounts." Panel B reports the estimates in units of migra- tion elasticities. We will focus on the estimates in Panel A. Normalizing the coefficient on exponential rents to 1, we identify the standard deviation of tenants' idiosyncratic shocks to their location preferences. We find that young renters have annual location taste shocks with a standard deviation equivalent to $7,411. Mature renters face location shocks with a 12.7% lower standard deviation. These estimates are consistent with our previously dis- cussed hypothesis that young renters' migration decisions are more driven by idiosyncratic shocks than older households. Turning to the magnitudes of the tenant buyouts, we find young renters receive $1.631 more dollars from their landlords for each additional $1 below market their rent is. Mature renters face similar impact of $1.404. We also find buyout offers are larger as tenants live in their zipcodes longer. For each additional year a young (mature) tenant lives in their zipcode, they receive $164 ($141) additional dollars in the buyout offer from their landlord. Finally, we find mature tenants receive larger buyout offers overall by $70,702. This may reflect that landlords expect older tenants to remain in their apartments for the very long term. Along the same lines, to the extent that these transfers reflect evictions, landlords would be more incentivized to evict older renters. To get a better sense of the magnitudes of these buyout payments, Figure 14 plots the average buyout to young tenants offered in each year in the data, across all tenants and neighborhoods. By 2010, the average offer to tenants who still remain at their 1994 address is just over $30,000. Figure 15 plots the heterogeneity across zipcodes in mean buyout offers, highlighting that some zipcodes experience much large rent increases than others over this time period. In the most expensive zipcode, the average buyout in 2010 is just about $40,000, while in the cheapest zipcode the mean buyout offer is 16These are measured at the mean rent paid by rent -controlled households, $2350. 33 around $25,000. These numbers seem very much in line with popular press anecdotes about tenant buyouts in San Francisco. Moving along to our estimates of moving costs, we find the fixed cost of moving is equivalent, in rent -equivalent dollars, to $42,626 for young renters and $38,988 for old renters. These estimates seem quite reasonable and actually quite below what is typically found in the literature. A main driver of the magnitude of this estimate are the short -run migration elasticities with respect to a one-year temporary change. It is often quite hard to find a high quality instrument for rents that does not effect other omitted variables such as amenities. Likely, many instruments for rent also impact the supply and quality of amenities, leading to rent elasticities being biased towards 0. Our rent control policy experiment only affects rents and cannot effect amenities in our regressions, as we are comparing migration decisions between market rent and rent controlled households in the same neighborhood consuming the same amenities. In addition to the fixed costs of moving, we find that the moving costs increase with the distance of the move. A 1 percent increase in move distance is equivalent to $114 for the young and $101 for the old. Finally, we also consider whether these variable moving costs change as households live in their zipcodes longer. One might think that the longer a household has lived in the area the more familiar they are with further and further away neighborhoods, lowering those marginal moving costs. Indeed, we find this is the case, with each additional year a tenant has lived in their zipcode lowering the moving cost by $415 for the young and $357 for the old. Lastly, we turn to our neighborhood capital estimates. Proponents of rent control often argue that long-term residents are the ones in the most need of rent control as migrating away from their community forces them to lose many of the connections and investments they have been in the neighborhoods over time. We do find very statistically significant effects of neighborhood capital accumulation. However, the economic magnitude is small. Young (mature) households increasingly value living in their zipcode by $266 ($292) in dollar 34 rent equivalent terms. However, these effects can add up to a sizable effect over a lifetime. 6 Welfare Effects of Rent Control 6.1 Welfare Decomposition: 1994-2012 We begin our investigation of the welfare effects of rent control by decomposing the impacts of the 1994 ballot initiative on its beneficiaries, relative to the control group. We discuss here mature households. The expressions for young households are exactly analogous. 6.1.1 Derivations In any given year t between the years of 1994 and 2012, the average utility difference between the treatment group and the control group is given by: DU° _ (ut (� of -1) + Et [sz t x, of -1]) pt (x of -1) (pt (ot-1) —pt (ot-1)) (12) oz_, EE (ut (x, of -1) + Et [t ,:Xtl x, of -1]) (pt (x, of -1) — pc (x, of -1)) ox -1 v; where recall ut (x, of -1) = u (x, wt, 0, of -1) and the utility function is defined in equation (3). The expression pt (xl ot_1) again denotes the conditional probability of choosing x E {S} U,7, given that the current state is ot._I, pt (ot_1),p° (ot-1) denote the probabilities of being in state of -1 for the treatment group and control group respectively, and pt (x, ot_1) , p° (x, of -r) denote the joint probabilities. The conditional expectation Et [Eit,l x, ot_1] denotes the ex- pected logit error conditional on choosing x from state of -1. Of course, equation (12) simply says that the average utility difference is the weighted average utility received by the treat- ment group minus the weighted average utility received by the control group. We can decompose this average utility difference by substituting in for the utility function 35 from equation (3). We find that: AUM = Aut',Rent +DUtM'Payoff +AUy"NC (13) +QUtM,MC + AUMt,Miles + QUtM,Amenity + AUIV1t,Logit. That is, the average utility difference between the treatment group and the control arises from differences in average rent paid AutM,Rent in transfers received from landlords AUt f'PayoffI in accumulated neighborhood capital AU; f'Ne, in fixed costs AUtu'Mc in variable moving costs �UM,Miles in neighborhood amenity values AutM,Araenity and in idiosyncratic valuations Q UM,Logit Suppressing the dependence of j and T on x, we can formally write these terms as: AUt"at — E )7 ryM exp (Rt (.i, d, Th)) 1pt (x, Bt -1) - pt (x, Bt -1)/ dt-i x AUt ayoff = At (x, dt-1,M) (pi (x, Bt -1) -pt (x, Bt -1)) AUM'Nc = aMTa (Pt (x, Bt-].) - Pt (x, Bt -1)) Bt_i x DUtvr,Mc - Y, E t00,M1 [x =� S] (pi (x, Bt -1) - Pt (x, Bt -1)J yt-1 X AUtj'V Mi•le.s = d 1 x S T x B_ c x B_ t L� Pd,M yft- � j �pt ( 1) -pt (, t 1)) et-, X M,Anenity C ` DUt = Wjt �ptT (•x, Bt -1) — pt (x, Bt -1)J Ot-1 a We can measure each of these terms." We recover estimates of ym, AM, am, cpam, ,pd,M, and Wft from our structural model. We can then recover the other needed quantities from standard reduced form differences -in -differences analysis. For example, Eet_i E. exp (Rt (j, d, Th)) (pt (x, Bt -1) - pt (x, Bt -1)) is simply the average difference in rents paid between treatment and control in year t, Eot-1 EX Tn, (pt (x, Bt -1) - pt (x, Bt -1)) 17Since we measure rents as monthly rents/3000, we multiply by 36,000 to convert to an annual rent number. 36 is the average difference in accumulated neighborhood capital between treatment and con- trol, Eet_1 Em 1 [x � S] �pr (x, Bt -1) - pC (x, Bt -1)) is the average difference in number of moves between treatment and control, and EBt 1 Ex dj,j,-,1 [x � S] �pt (x, Bt_1) - pC (x, Bt -1)) is the average difference in distance moved between treatment and control. Each of these can be readily calculated using the reduced form methodology described in Section 4. The average utility difference due to transfers and the average utility difference due to amenities can be similarly calculated by combining our structural estimates with reduced form differences -in -differences analysis. Deriving an expression for the utility difference clue to idiosyncratic valuations AUtm,Logit is a bit more complicated. We have that: AUiWagit = �: �: Et [Eitx, Bt -11 (Pt (x, Bt -1) - Pt (x, Bt -1)) (14) et -1 .m We therefore need an expression for the conditional expectation Et [Eimtjx, Bt__1] . Using Bayes' rule, we get: (' j�j A (�dmt+mt �.'°�Bt-11—"t�m�,Bb-1 �� d —e Eamt dEi ,1 Eixt 1 1 '.Ax� E—2—et " E at Et [Eimt�xe Bt -1] = A (xI8t-1) 7�j—e—('iPt hlOt-11-1n pt (-'I —Eg¢t —e—Ei f Eixt l lm,�x e i®t � e e xt dEimt A (Ot-r) where in the second equality we used the Holz and Miller (1993) inversion vt (x, Bt -1) - vt (x', Bt -1) = lnpt (xlat— 1) -lnpt (x'1Bt-1) . Substituting into equation (14), we derive: Dut aIL,Logit = E E J E;mt (ri E e (�dat+ln en (=lee-1%-'lu nt('�'Ien—li�� c—ei: tee_=intd.E'xmtX � 0t-1 x X#x (pt (Ht -1) -p, (Ht -1)) (15) Since we have empirical estimates of each of the probabilities, we can estimate this utility 37 difference. We finally convert our estimated utility differences into rent equivalent dollar amounts. Consider an individual in the control group who pays the average San Rancisco rent in year t, which we denote as Rt. We now proceed iteratively. The dollar rent equivalent OWRent of the utility difference DUR`nt in year t due to rent differences can be calculated as the solution to : which gives: YM exp �Wt + OWRont) _ M exp (Rt) = AUR,e at ( AYVoURent Rent = In t +exp A) — Rt. 1'M The dollar rent equivalent incremental impact of transfers can then be calculated as: P°veii _ _ OWn"y°ff AU =1n +exp(Rt+AWRent) — (Rt+AWRent) GYM Now let AUt I'° denote the utility differences, with t E { 1, ..., 7} corresponding to the ordering in equation (13). Iterating on our procedure gives the dollar rent equivalent incremental impacts of each element of the decomposition: AUPayot9 OLVt = 1n + exp CWt + AWtl � — �Wt + E AWt, GYM e�<c L'<L 6.1.2 Results The results of this decomposition are reported in Table 5. We find that the beneficiaries of the 1994 rent control law received large welfare benefits between the 1994-2012 period. Older households received a total rent -equivalent dollar benefit of $119,625, reflecting an annual benefit of $6,646. These benefits were front loaded, with households earning a cumulative benefit of $74.514 and average annual benefit of $8,279 during the 1995-2003 period Cumu- lative benefits equaled $45,111 during the 2004-2012 period, reflecting an annual average of 38 $5,012. In terms of decomposition, most of the benefits from the rent control law came from pro- tection against rent increases and transfers." Respectively, protection against rent increases constituted 44.2% of the total benefit and transfers constituted 30.2% of the total. Lower moving costs, both fixed and variable, were 13.5% of the total. Increased neighborhood capital constituted only small fraction of the total benefit at 1.2%. The welfare benefits from increased amenity values were negligible. Interestinly, we find increased utility from the utility value of one's idosyncratic preference equal to 11.2% of the welfare gain. This likely due to the fact that we found some low neighborhood capital houseohlds were more likley to move due to rent control, allowing them to over come moving costs and live in a location that best suites their idiosyncratic preference. The benefits of the rent control expansion were smaller for younger households, although still large. That they are smaller is consistent with our estimate that younger households receive larger idiosyncratic shocks, which leads to more frequent moving and thus smaller benefits from rent control protections. Younger households are also estimated to receive smaller transfers. Cumulative welfare benefits for these households totaled $41,121, reflecting an annual average of $2,285. Similar to older households, the benefits were front loaded. Younger households received cumulative benefits of $32,960 during the 1995-2003 period and cumulative benefits of $8,162 during the 2004-2012 period. Annual averages were $3,662 and $907 respectively. Also similar to older households, most of the benefits came from protection against rent increases and transfers, constituting 79.6% and 45.4% respectively over the total period. The fraction due to moving costs is much smaller for younger households, at only 8%. Note this reinforces the idea that, due to a higher variance if idiosyncratic shocks, ,younger 18The model assumes that all observed moves are rational choices. The transfers we estimate are those which rationalize the observed empirical frequencies. It is possible that some of the moves we see in the data are forced evictions, rather than the result of negotiations between landlords and tenants over monetary compensation. To the extent that this is the case, our welfare benefits from transfer payments over overstated. However, even in the extreme case where the welfare benefits from transfers are zero, the benefits from protection against rent increases would still be large. 39 households optimally choose to move more often. The fraction due to neighborhood capital is once again small, constituting just 2.6% for the average. Welfare benefits due to increased amenity values now reflect a small, but non -negligible, fraction of the total benefit at 2.6%. Finally, the young face a substantial welfare loss due to living in places that are worse matches to their idiosyncratic preference under rent control, equal to -37.2%. This reflects that to stay in one's apartment to benefit from below market rents, one must give up living in the best apartment and location that suites one's preferences. Our estiamtes shows that idosyncratice preference variaince is higher for the young, making giving up the match value a larger sacrifice. We aggregate these numbers over the entire population of renters impacted by the rent control law. The aggregate welfare benefits are very large. Older households received a cumulative benefit of $4.440 billion dollars over the entire period, while younger households received a cumulative benefit of $2.64 billion dollars. Across the entire population, the aggregate benefit was $7.085 billion dollars, reflecting an annual average of $394 million dollars. Note also that these welfare numbers are only for the 1994 population impacted by the rent control expansion. It does not take into account the welfare benefits for renters who moved into the impacted properties in later years, which presumably were also quite large. 6.2 General Equilibrium Welfare Impact of Reduced Supply We finally turn to evaluating the GE welfare impact of the landlord supply response. Intu- itively, since landlords reduced supply in response to the 1994 law, as was shown in Section 4.2, average San Francisco rents were higher than they otherwise would have been. Using our structural framework, we quantify the magnitude of this cost. 6.2.1 Derivations We evaluate the welfare impact relative to the 1993 steady state, prior to the introduction of the law change. Aggregate welfare in this steady state is given by: 40 Nj In E exp (v (x, j)) I , i xE1S}U9 1 where Nj is the number of people living in neighborhood j. Note that the state variable now does not include rent control status since we are consider the pre -law steady state. Suppose that the law raises rents in zipcode j by San Francisco by a proportional amount equal to d In Rj. Using standard calculations, we find that the local welfare impact of a change in rents is given by: Nj p(xlj)E21�xR�)dInR,, (16) x k where p (xl j) are the pre -law conditional choice probabilities To compute this quantity we thus need to calculate av (x, j) /d 1nRk for all j, x, and k E 9 and we need to determine the zipcode level rent response to the measured reduced form supply reduction. Steady-state in the model is characterized by the equation: vj : Nj (1—p(slj)-p(jh))=ENj,p(jh')- (17) j'0j This simply says that, in steady state, the number of renters flowing out of neighborhood j must be equal to the number of renters flowing into neighborhood j. We now assume that the supply decrease is the same proportionally in each zipcode. Since small multifamily housing constituted 44% of 1994 non rent -controlled housing stock, our reduced form results indicate that rental supply in San Francisco decreased by 6 percent. Letting dIn Nj/d(D denote the supply response, where (1) is simply a convenient notation indicating the impact of the law, we have d In Nj— d In NSF A A) = —.06 for all ,j in SF We determine how much rents have to change by in the new long -run steady state given this 41 supply response. Taking a derivative of equation (17) with respect to (P gives: dInNj dp(xIj) = dInNy dp(j Y) dI N' ClE p(xlj) —Nj 1:d� d4, N3'p(jlj)+N, ad� E{S,j} xE{S,il YAJ (18) for all j So: Now, in steady state, the conditional probabilities are given by: exp (v (x, j)) P (x j) _ E., exp (v (x', j)) dp(xlj) _ ap(xlj)dlnRk (19) d(D aInRk d(P x (MLL _� av(x"A dInRk k p( j) aInRk X p( j) alnRk d(P To finish the calculation, we therefore need to determine av (x, j) /a In Rk. With these in place, we can plug equation (19) into equation (18) and solve the resulting system of equations for the rent responses dInRk/d(h. We note that in steady-state: v (x, j) = u (x, j) + a In I exp (v V, j (x))) Taking derivatives with respect to log rents, we get: av(x,j)="Yexp (Rj)RjID(x)=k1+/�� p(xlj(x))av(x'j(x)) a In Rk lX,,' a In Rk This is a system of equations which can be numerically solved for the partial derivatives. The system for young renters is similar, but takes into account the possibility of transitioning to a mature renter. 42 6.2.2 Results We find that 6% decrease in housing supply led to 7% increase in rental prices. These caused an aggregate welfare loss to renters of $5 Billion. This is almost as large as the benefits accrued by the lucky beneficiaries of rent control. These GB welfare losses only account for the increased rents due to the decreased supply of housing. We also found that rent control incentivized landlords to invest in their properties by renovating and building new housing, as well as converting to owner occupancy. These effects likely attached higher income tenants to San Francisco and further raised rents. It appears that the GE losses from the landlords' response to rent control essentially completely undoes the gains accrued to the households that were lucky enough to receive rent control in 1994. 7 Conclusion In this paper, we study the welfare impacts of rent control on its tenant beneficiaries as well as the welfare impacts of landlords' responses. To answer this question, we exploit a unique rent control expansion in San Francisco in 1994 that suddenly provided rent control protections for small multifamily housing built prior to 1980. By combining new panel micro data on individual migration decisions with detailed assessor data on individual SF parcels we get quasi -experimental variation in the assignment of rent control at both the individual tenant level and at the parcel level. We find that, on average, in the medium to long term the beneficiaries of rent control are between 10 and 20 percent more likely to remain at their 1994 address relative to the control group. These effects are significantly stronger among older households and among households that have already spent a number of years at their current address. On the other hand, individuals in areas with quickly rising rents and with few years at their 1994 address are less likely to remain at their current address, consistent with the idea that landlords try to remove tenants when the reward is high, through either eviction or negotiated payments. 43 We find that landlords actively respond to the imposition of rent control by converting their properties to condos and TICs or by redeveloping the building in such as a way as to exempt it from the regulations. In sum, we find that impacted landlords reduced the supply the available rental housing by 15 percent. Consistent with this evidence, we find that there was a 20 percent decline in the number of renters living in impacted buildings, relative to 1990-1994 levels, and a 30 percent decline in the number of renters living in units protected by rent control. We develop a dynamic, structural model of neighborhood choice to translate our reduced form impacts into welfare impacts. A key contribution of the paper is to show how quasi- experimental evidence can be leveraged to estimate to dynamic discrete choice model. We find that rent control offered large benefits to impacted tenants during the 1995-2012 period, averaging between $2200 and $6600 per person each year, with aggregate benefits totaling over $393 million annually. Over the entire period, tenants received cumulative benefits of around $7.1 billion. We find that most of these benefits came from protection against rent increases and transfer payments from landlords. However, we find losses to all renters of $5 billion due to rent control's effect on decreasing the rental housing and raising market rents. These results highlight that forcing landlords to provided insurance against rent increases leads to large losses to tenants. If society desires to provide social insurance against rent increases, it would be more desirable to offer this subsidy in the form of a government subsidy or tax credit. This would remove landlords' incentives to decrease the housing supply and could provide household with the insurance they desire. A point of future research would be to design an optimal social insurance program to insure renters against large rent increases. 44 References Arcidiacono, Peter and Paul B. Ellickson, "Practical Methods for Estimation of Dy- namic Discrete Choice Models," Annual Review of Economics, 2011, 3 (1), 363-394. and Robert A. Miller, "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, November 2011, 79 (6), 1823-1867. Autor, David H, Christopher J Palmer, and Parag A Pathak, "Housing Market Spillovers: Evidence from the End of Rent Control in Cambridge, Massachusetts," Journal of Political Economy, 2014, 122 (3), 661-717. Bayer, Patrick, Robert McMillan, Alvin Murphy, and Christopher Timmins, "A Dynamic Model of Demand for Houses and Neighborhoods," Econometrica, May 2016, 84 (3), 893-942. Bishop, Kelly C. and Alvin D. Murphy, "Estimating the Willingness to Pay to Avoid Violent Crime: A Dynamic Approach," American Economic Review, May 2011, 101 (3), 625-629. Davis, Morris A., Jess Gregory, Daniel A. Hartley, and Kegon Teng Kok Tan, "Neighborhood Choices, Neighborhood Effects and Housing Vouchers," 2017. Downs, Anthony, "Residential Rent Controls," Washington, DC: Urban Land Institute, 1988. Early, Dirk W., "Rent Control, Rental Housing Supply, and the Distribution of Tenant Benefits," Journal of Urban Economics, September 2000, 48 (2), 185-204. Glaeser, Edward L and Erzo FP Luttmer, "The Misallocation of Housing under Rent Control," The American Economic Review, 2003, 93 (4), 1027-1046. Gyourko, Joseph and Peter Linneman, "Equity and Efficiency Aspects of Rent Control: An Empirical Study of New York City," Journal of urban Economics, 1989, 26 (1), 54-74. and _ , "Rent Controls and Rental Housing Quality: A Note on the Effects of New York City's Old Controls," Journal of Urban Economics, May 1990, 27 (3), 398-409. Hotz, V. Joseph and Robert A. Miller, "Conditional Choice Probabilities and the Estimation of Dynamic Models," The Review of Economic Studies, 1993, 60 (3), 497-529. Kasarda, John D. and Morris Janowitz, "Community Attachment in Mass Society," American Sociological Review, 1974, 39 (3), 328-339. Kennan, John and James R. Walker, "The Effect of Expected Income on Individual Migration Decisions," Econometrica, January 2011, 79 (1), 211-251. 45 Moon, Choon-Geol and Janet G. Stotsky, "The Effect of Rent Control on Housing Quality Change: A Longitudinal Analysis," Journal of Political Economy, December 1993, 101 (6), 1114-1148. Murphy, Alvin, "A Dynamic Model of Housing Supply," SSRN Scholarly Paper ID 2200459, Social Science Research Network, Rochester, NY February 2017. Olsen, Edgar O, "An Econometric Analysis of Rent Control," Journal of'Political Economy, 1972, 80 (6), 1081-1100. Scott, Paul T., "Dynamic Discrete Choice Estimation of Agricultural Land Use," Toulouse School of Economics Working Paper, 2013, 526. Sims, David P, "Out of Control: What Can We Learn from the End of Massachusetts Rent Control?," Journal of Urban Economics, 2007, 61 (1), 129-151. _ , "Rent Control Rationing and Community Composition: Evidence from Massachusetts," The BE Journal of Economic Analysis & Policy, 2011, 11 (1). 46 Table 1: Sample Characteristics for Individual Regressions for Multi -Family Residence (2-4 Units) Mean S.D Demographics Age in 1993 38.584 10.707 Male 0.504 0.500 Is Landlord 0.144 0.352 Residency Living in SF 0.643 0.479 Living in Zipcode of Treated Address 0.443 0.497 Living in Treated Address 0.375 0.484 Years at 1993 Address 6.761 4.911 Years at Current Address 1.659 0.597 Observations 1508247 Notes: Sample consists of all tenants and landlords between 20 and 65 years old living in SF in 1993 and small multi -family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a landlord living there in 1993, we include it into the treatment group for rent control. Table reports the mean, standard deviation and median of demographic characteristics and various dependent variables during 1990 — 2016. 47 Table 2: Sample Characteristics for Multi -Family Properties (2-4 Units) Permits Cumulative Add/Alter/Repair per Unit 0.256 0.487 Ever Received Add/Alter/Repair 0.336 0.472 Observations 724037 Notes: Sample consists of all parcels that are multi -family residence with fewer than four units in SF that were built during 1900 —1990. If a building associated with a parcel is constructed post 1993 and we observe someone living there before 1993, we include it into the treatment group for rent control. Table reports the mean, standard deviation and median of various dependent variables during 1990 — 2016. 48 Mean S.D Residency Is Vacant 0.103 0.304 Population Population/Avg Pop 90-94 2.076 3.728 Renters/Avg Pop 90-94 1.541 3.276 Renters in Covered by Rent-Control/Avg Pop 90-94 1.311 1.808 Renters in Redeveloped Buildings/Avg Pop 90-94 0.108 0.679 Owners/Avg Pop 90-94 0.535 1.467 Permits Cumulative Add/Alter/Repair per Unit 0.256 0.487 Ever Received Add/Alter/Repair 0.336 0.472 Observations 724037 Notes: Sample consists of all parcels that are multi -family residence with fewer than four units in SF that were built during 1900 —1990. If a building associated with a parcel is constructed post 1993 and we observe someone living there before 1993, we include it into the treatment group for rent control. Table reports the mean, standard deviation and median of various dependent variables during 1990 — 2016. 48 w H * Ml x + C00 ob o ti o n O O GV O M O O O C:> O p 0 w N� 00 CO c0 Lo C:) N W V O Co CD O O CD Co CD 0 0 0® 0 0 O " O O , W .-I ti Cp O O® p O p 0 N Cq m ti 00 t0 ti O O O O ti N L- N O O N O CO 0 y i+J CV � � O O O p ti r GO CO O C'J O 49 0 O U] � h ' U O 1O � F � O d C= O O O Cq c� O O CqO N Cq m ti 00 t0 ti O O O O ti N L- N O O N O CO 0 y i+J CV � � O O O p ti r GO CO O C'J O 49 0 O U] � h ' U O 1O � F � w R O bA q O R Y �Q G a a N N 71 r� v M c°'oo�o�'o�wom 50 O bA Y 0. a N N ro a� o 0 0 0 0 0 0 elees�g �gel el � � L�ll S el N m M 0 m t t om�Mcoocn �tJ N ti e�ebg8�b9eS c m�� �m H H O N tfJ ti N 0 O N M O N 0 0 .1 o�co cn L—moo v� '� W H O 1tii m 0 � cNo Lr N O � c0 c0 M cp ti ti l� O ti 0 ti O M ti 0 V m 0 N ti cp N W `� Emco c�ooa�� ooi N P. U O M O M O O O Pl ti O H W 06 G � V U] CO M ti ti H N P. W M M d' itJ cl' N O c+J ,-- i C6 " ci C H o qq m a� a b y 71 xw�wQ�SH 51 M O N 0 0 0 0 0 0 00 (Do C f6 N m c Eo 00 Z� 0 r Figure 1: Historical 'Mend of Nominal Median Rent Year 52 Figure 2: Geographic Distribution of heated and Control Buildings in San Francisco 53 a � Aent-�oritofled Semp1� � � � z � a reskk . ,A 1101 he 4 r W sR n Y2 *1 i� V pg F � � '✓ a � �Y a*a Y�a9 '�Rt'1t LU IWI 11 £4 ta§e bterced Pwk • *a'`z4 n,4� a �+,t: a e � a � 53 Figure 3: Treatment Effect for Tenants in Multi -Family Residence (2-4 Units) (a) Staying at Same Address 06 N N a Q .04 0 E U .02 W C d � 0 F- -.02 Corr = 0.494 c a /I ro I I I � / I It i � \ r 1 / II 19x0 1995 2000 2005 2010 2015 .06 T c .04 W C .02 E M 0 -.02 Same Address — — — • Real Log Median Rent (Detrended) (b) Staying in San Francisco Corr = 0.784 a � 1 1 i I � 1 / II I Q.an in 0; 2nnn 9nnfi 2010 2015 In SF — — — - Real Log Median Rent (Detrended) Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Standard errors are clustered at the person level. Significance levels: * 10%, ** 5%, *** 1%. 54 Figure 4: Heterogeneity by Age and Tenure in Treatment Effect for Tenants of Multi -Family Residence (2-4 Units) Young & High Turnover Young & Low Turnover Old & High Turnover Old & Low Turnover Same Address Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small rnulti- f'amily residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. We sort the sample by age group. The young group refers to residents who were aged 20-39 in 1993 and the old group are residents who were aged 40-65 in 1993. We also cut the data by number of years the individual has been living at their 1993 address. We define a "low turnover" group of individuals who had been living at their 1993 address for greater than or equal to four years and a "high turnover" group of individuals who had been living at their address for less than four years. The average treatment effects in the post -1994 period along with 90% Cl are plotted. Standard errors are clustered at the person level. 55 Figure 5: Heterogeneity by Rent Appreciation, Age and Tenure in Treatment Effect for Tenants of Multi -Family Residence (2-4 Units) (a) High Rent Appreciation, Young and High Turnover(b) High Rent Appreciation, Young and Low Turnover w a a E E v, (c) High Rent Appreciation, Old and High Turnover (d) High Rent Appreciation, Old and Low Turnover a a E E a E E Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. We first individuals into two groups by whether their 1993 census tract experienced above or below median rent appreciation during 1990-2000. We further sort the sample by age group and tenure following the same definitions as in Figure 4. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 56 Figure 6: Heterogeneity by Rent Appreciation, Age and Tenure in 'I eatment Effect for Tenants of Multi -Family Residence (2-4 Units) (a) Low Rent Appreciation, Young and High Turnover (b) Low Rent Appreciation, Young and Low Turnover v a 4 E E v a E (c) Low Rent Appreciation, Old and High Turnover (d) Low Rent Appreciation, Old and Low Turnover v a E ------------ Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 —1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. We first individuals into two groups by whether their 1993 census tract experienced above or below median rent appreciation during 1990-2000. We further sort the sample by age group and tenure following the same definitions as in Figure 4. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 57 Figure 7: Treatment Effect at the Census Tracts level for Tenants of Multi -Family Residence (2-4 Units) — Dynamic Version IN -50 -100 U -1000 -2000 -3000 -4000 Median Rent --- ,__-------------- .-.--_-_-__-_ - nrnme — — — — — — — — — — — — — — — — - - - - - �. Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 - 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Median rent, median household income and share of residents with college education and above are measured in the census tract that an individual is living in a given year. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. W Figure 8: Treatment Effect at the Census Tracts level for Tenants of Multi -Family Residence (2-4 Units) — Dynamic Version 10000 0 -10000 -20000 -30000 .006 .004 .002 .01 S] 110 Median House Value mare in roverty Nates: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. if a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Median house value, share of unemployed and share of residents below poverty line are measured in the census tract that an individual is living in a given year. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 59 / / mare in roverty Nates: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. if a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Median house value, share of unemployed and share of residents below poverty line are measured in the census tract that an individual is living in a given year. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 59 Figure 9: Treatment Effect at the Census Tracts level for Tenants of Multi -Family Residence (2-4 Units) — Static Version 50 0 -50 2000 0 -2000 -4000 .06 .04 .02 0 Median Rent Nieman rtousenoia income snare conege __r� 2011 2012 Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Median rent, median household income and share of residents with college education and above are measured in the census tract that an individual is living in a given year for the control group, and are measured in their 1993 census tract for the treated group. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 60 _.___ —-..- ,..- I __r� 2011 2012 Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Median rent, median household income and share of residents with college education and above are measured in the census tract that an individual is living in a given year for the control group, and are measured in their 1993 census tract for the treated group. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 60 Figure 10: Treatment Effect at the Census Tracts level for Tenants of Multi -Family Residence (2-4 Units) — Static Version 150000 100000 50000 0 .005 0 -.005 -.01 .02 .015 .01 .005 0 Median House Value -------------------------- snare unempioyea _ I---------- ---------- ------------------ ------------- 1 AM) gene 9nln 9n11 grog 9n1Z Notes: Sample consists of all tenants between 20 and 65 years old living in SF in 1993 and in small multi- family residences that were built during 1900 — 1990. TF a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. Median house value, share of unemployed and share of residents below poverty line are measured in the census tract that an individual is living in a given year for the control group, and are measured in their 1993 census tract for the treated group. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the person level. 61 a Figure 11: Treatment Effect for Multi -Family Residence (2-4 Units) (a) Population/Average Population 1990-1994 (b) Renters/Average Population 1990-1994 i 0 1 (c) Owners/Average Population 1990-1994 -.3 (d) Vacancy Notes: Sample consists of all small multi -family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the parcel level. 62 Figure 12: Thatment Effect for Multi -Family Residence (2-4 Units) (a) Renters in Rent -Controlled Buildings/Average Population 1990-1994 (c) Conversion (b) Renters in Redeveloped Buildings/Average Population 1990-1994 (d) Accumulative Add/Alter/Repair per Unit Notes: Sample consists of all small multi -family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent; control. The treatment effects along with 90% CI are plotted. Standard errors are clustered at the parcel level. 63 Figure 13: Heterogeneity by Rent Appreciation in 'heatment Effect for Multi -Family Resi- dence (2-4 Units) (a) Conversion, High Rent Appreciation (b) Conversion, Low Rent Appreciation (c) Accumulative Add/Alter/Repair per Unit, High Rent Appreciation a -.02 (d) Accumulative Add/Alter/Repair per Unit, Low Rent Appreciation Notes: Sample consists of all small multi -family residences that were built during 1900 — 1990. If a building is constructed post 1993 and we observe a tenant living there in 1993, we include it into the treatment group for rent control. We sort our sample by whether their 1993 census tract experienced above or below median rent appreciation during 1990-2000. The treatment effects along with 90%n CI are plotted. Standard errors are clustered at the parcel level. 64 Figure 14: Average Annual Tenant Buyouts C, Mean Young Tenant Buyout C) Cool C Cl C) o U! r 1995 2000 2005 2010 Year 65 Ri . O :3o 0 >10 :3 C') m cu cu a) �0 ac) �0 N Figure 15: Annual Tenant Buyouts by Zipcode Mean Young Tenant Buyout By Zipcode 1995 2000 2005 2010 Year A Appendix Tables 66 U O t a y 'Cj N q w vJ C$ % nog d �oUoC ?o 00 o n VO i CL N 0 0 o c� yVl b 0 0 o qO w N V O U �q ooCam n'�-^'n' G 000c� o cco :d � m H O U od o c co o�� ti a 0 q o o i0 n � l� ym�roy p :J O b9 b O b d C u M W y O U M m w F U O odo �m w a' oS ti U H U � � v 67 I g a a N N U bob0�� bow U � � op � itJ � � ti N ti irJ h O d' O L x M. Figure A.1: Population Age 18 and above: 1990 Census R'= 0.e92 Obs =127 / / / / / / / / / p C / / p o p 00 / �iR•'� 0 CID e� c� om 0,[,�'%! �•p 008 0 p r✓ 0 0 �r Census Population 18+ 95%cl — — — — Fitted values ---- 45 degree Notes: The size of marker is proportional to the population of 18 and over in the Census in each census tract. The fitted line is by weighted least square using the population of 18 and over in the Census as weights. Figure A.2: Population Age 18 and above: 2000 Census a a 0 a O census Population 18+ - '! 95%CI — — — — Fitted values --•- 45 degree Notes: The size of marker is proportional to the population of 18 and over in the Census in each census tract. The fitted line is by weighted least square using the population of 18 and over in the Census as weights. 69 Figure A.3: Age of Occupied Housing: 1990 Census (a) Built 1970 to 1990: 1990 Census (b) Built 1950 to 1909: 1990 Census r. v mu N 1 95%CI -- Fltletl values 45 degree (c) Built 1940 to 1949: 1990 Census C . , 95%CI ---- Fltletl values — — — — 45 degree r. 95% C1 ---- Fitted values -- 45 degree (d) Built 1939 or earlier: 1990 Census 95-A CI ---- Fltletl values — — — 45 degree Notes: The size of marker is proportional to the number of occupied housing units in each census tract. The fitted line is by weighted least square using the number of occupied housing units as weights. 70 Figure A.4: Age of Occupied Housing: 2000 Census (a) Built 1980 to 2000: 2000 Census (b) Built 1960 to 1979: 2000 Census Census Fraction Built 1980-2000 "i — — —— Filled values — — — — 45 deers (c) Built 1950 to 1959: 2000 Census _ 95% cl — — — — Fitted valuee — — — — 45 tlegree m m r� m o< LL `0� — — — — FltteG values --- as aa9ree (d) Built 1940 to 1949: 2000 Census m 0=1.323(0.042) no I (e) Built 1930 or earlier: 2000 Census W `m N ,w I 0.88] =159 Census Fraction Built 1939 and earlier 95% cl — — — — Fitletl values — — — — 45 tlegree Census Fraction Built 191949 95% cl — — -- Flttetl values ---- a5 degree Nodes: The size of marker is proportional to the n1lber of occupied housing units in each census tract. The fitted line is by weighted least square using the number of occupied housing units as weights. Figure AA Ownership Rate at Person Level: 1990 Census O p = 0.432 (0.014) R'= 0.910 Obs =100 / / / / , , 0 e°= ° i 0 .2 .4 .6 .8 1 Census Ownership Rate =,j� 9 5 % C I — — — — Fitted values 45 degree Notes: Plot shows the ownership rate at the person level from our Infutor sample in 1990 against the ownership rate of occupied housing units in 1990 Census. The size of marker is proportional to the number of occupied housing units in each census tract. The fitted line is by weighted least square using the number of occupied housing units as weights. Figure A.6: Ownership Rate at Person Level: 2000 Census = 0.939 os=159 ' / / Census Ownership Rate 95%CI — — — — Fitted values — — — — 45 degree Notes: Plot shows the ownership rate at the person level from our Infutor sample in 1990 against the ownership rate of occupied housing units in 1990 Census. The size of marker is proportional to the number of occupied housing units in each census tract. The fitted line is by weighted least square using the number of occupied housing units as weights. 72 Alcala, Abigail From: Houston, Nicole Sent: Wednesday, February 7, 2018 8:49 AM To: Alcala, Abigail; Huizar, Maria; Mitre -Ramirez, Norma; Orozco, Norma; Rojano, Michael Cc: Castro -Cardenas, Julie Subject: FW: No to rent Control From: John McCarthylmailto: To: Pulido, Miguel <MPulido@santa-ana.org> Subject: No to rent Control Rent control for any city is bad for business and its residents, especially for a historic city like Santa Anna. It will cause a detrimental shift in development for the city. With the river bed infested with the homeless, rent control will only create slums and promote tent city's. Please focus on building more affordable housing and work force housing, expand section 8, and build modern, green and conventional rental housing instead of rent control please. Sincerely a property management company. Sent by SeanJohn McCarthy Local Real Estate Consultant BRE #01956215 C. McCarthy Properties LLC P.O. Box 5402 Garden Grove, CA 92846 1 -855 -MC -Props 1 Alcala, Abigail From: Mitre -Ramirez, Norma Sent: Wednesday, February 7, 2018 12:03 PM To: Alcala, Abigail Subject: FW: Costa -Hawkins Rental Housing Act Follow Up Flag: Follow up Flag Status: Flagged From: Ana Lamb Imailto:alamb@apipropertymanagement.comj Sent: Wednesday, February 7, 2018 11:52 AM To: eComment <eComment@santa-ana.org> Subject: Costa -Hawkins Rental Housing Act Hello, I attended the meeting at the Santa Ana Council Meetin on 2/6/18. I was fascinated by the turnout and the arguments for both for and against the rent control. Although both sides had valid points, I do urge you to please vote NO on rent control. The ultimate cons to rent control outweigh the pros and will substantially deteriorate the charm and appeal of Santa Ana. There is an immediate need to resolve our housing crisis, but rent control is not the solution. I thank you for your time, Sincerely, Ana Lamb API Property Management 1400 N Bristol St. Ste 245-A Newport Beach, CA 92660 714-505-5200 x24 714-858-1920 Cell alambL&aoipropertwnanagement.coin Alcala, Abigail From: Mitre -Ramirez, Norma Sent: Wednesday, February 7, 2018 10:14 AM To: Alcala, Abigail Subject: FW: Rent control Follow Up Flag: Follow up Flag Status: Flagged From: Margie Tabrizi[mailto:margie@apipropertymanagement.com] Sent: Wednesday, February 7, 2018 10:12 AM To: eComment <eComment@santa-ana.org> Subject: Rent control Good morning, I was at the meeting last night and was able to listen to Apartment Association, Mobile home Association, Builders Association, Santa Monica rent control representative, landlords, and tenants. The Santa Monica rent control representative discussed a need for another agency to mediate and work between the landlords and the tenants. We already have agencies where tenants can call or visit to solve retaliation, discrimination and other issues that they may have. The Santa Monica rent control representative repeatedly mentioned there would be no cost to the City of Santa Ana. Definitely, there would be a cost. As the other speaker mentioned, the City of Carlsbad is paying the rent control cost. Additionally, any city that has limited rents would be less attractive to the investors to purchase. Therefore, City of Santa Ana may be the first city to implement the rent control but it will be less attractive to investors to purchase properties. Shortage of housing is a big problem in California, but, the solution is not rent control, building more condos, apartments and single-family homes is the answer. Perhaps building tax credit properties and housing subsidize programs in the City of Santa Ana will help renters. This will be a win-win for all the parties. Please say no to rent control. Thank you for your time. Sincerely, Margie Tabrizi