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A lack of jobs can slow in-migration into an area drastically. Orange County has an increasing employment base which is continually decreasing its reliance on Los Angeles County employment. Currently, the type of employ- ment is largely professional or upper "white collar." The impact of this skewed employment distribution on job availability for thc potential migrant is open to question. PROJECTIONS: Recently, Urban Futures, prepared a report for the Orange County Administrative Office projecting aha allocating population to small geographic units in Orange County for the years 1975, 1980~ 1985 and 1990. The r~port determined the probable timing, location, and relative amounts of future population growth in Orange County, based on four alternative projected populations developed by the Forecast and Analysis Center of the County Administrative Office, the Southern California Association of Government (SCAG), the Orange County Planning Department, the California State Depart- ment of Finance, the Southern California Edison Company and the planning consulting firm of Urban Futuves, Inc. The County Administrative Office recommends that the population allocations prepared by Urban Futures, based on Southern California Edison Company projections, be used as a basis for policy decisions and budgeting regarding future growth and services. To carry out the project, a variety of primary data were generated and many advanced techniques were employed, including the development of a computer model The Urban Futures Population Allocation Model was prepared and was used to sirn-ulate the future population distribution and timing of devel0pment which are likely to result from the interplay of different key growth-variables. Five key growth attraction variables and three growth constraint factors were identified from work previously completed by the County's Growth Policy and Development Strategy Team. The key growth attraction variables are: (1) distance to employment centers and size of employment at destination points, (2) quality of physical environment, (3) socio-economic status, (4) abundance of local recreation land, and adequacy of transportation facilities. These variables were forecast in the future for the years 1975, 1980, 1985, and 1990, based on general plans and other relevant information. Operational definitions were developed for each growth attraction variable. Each census tract or split tract in Orange County was measured and scored according to the operational definitions for each variable. A weighting of the importance of each variable in relation to housing and population trends was determined from regression constants between the variable and population trends in the census tract or split tract. The regression constants for each key growth attraction variable were used as a~ "attraction multiplier". The attraction multiplier was .independently applied to each of the variable scores for each of the five variables. These scores were aggregated for each census tract or split tract. The aggregate score for each census tract represented the relative portion of the population the 000047