Urben research in ethnic, demographic and household-economic structures with small area, micro-databases (abstract only)
Authors: Harold Benenson, Steven Just
Venue: Proceedings of the joint conference on Easier and more productive use of computer systems. (Part - I): Information processing in the social sciences and humanities - Volume 1981 (1981)

Computerized U.S. Census data has been most widely used for (1) employment, fertility, demographic and stratification research involving Public Use Sample (PUS) microdata on the national level, and (2) applied research (for planning, administration, marketing, and other applications) with summary (aggregated) data for localized (i.e., block, tract, community, etc.) geographic units. A third, highly productive avenue of research, involving Census PUS micro-data for localized urban units (i.e., SMSAs, counties and especially selected large-city neighborhoods), has not received the attention it merits, either among sophisticated public data users or among novice users.Three forms of current or future small area, Census microdata constitute resources for urban research. First, conventional 1970 Census PUS data sets are available for counties and/or SMSAs (with minimum populations of 250,000). Second, special tabulations for the two largest U.S. cities permit analysis of 1970 household and person records group by (sub-county) urban neighborhoods (27 in New York City; 12 in Chicago). Third, 1980 Census microdata, by allowing identification of geographic areas of smaller population size (100,000 population), will vastly expand the applications of localized research with the conventional PUS or special tabulations. In addition, the 1980 PUS microdata will, for the first time, allow comparative time-series analyses of county (or SMSA) area populations, over the 1970-1980 decade.In contrast to national PUS microdata research, local level analyses have the advantages of (1) smaller data set size and processing costs, (2) more immediate integration of computerized research hypotheses with additional sources of (qualitative) information and questions (stemming from direct knowledge of the communities studied), and (3) increased ability to zero in on specialized ethnic, occupational-industrial, migrant, age, etc. urban population groups which are disproportionately represented in particular local environments. Our own research projects (at various stages of development) which attempt to exploit these advantages include computerized analysis of:1. Patterns of household composition, and source and structure of family income, among Upper East Side and Upper West Side Manhattan residents with family incomes of $ 50,000. or more (as reported in the 1970 Census)2. Employment patterns of married women of Cuban immigrant background, in relation to family class position and period of immigration, for Hudson County, New Jersey3. Contrasts in the occupational positions and household patterns of first-generation and second-generation husbands and wives of Italian background in a New York City working class community (Astoria-Long Island City, Queens)4. Wives' employment patterns in relation to ethnic background and husbands' occupations and income levels in a working class community located in a manufacturing center (South Side, Chicago)5. Change in the social and demographic characteristics of succeeding groups of migrants to an expanding "sunbelt" metropolitan area (Albuquerque, New Mexico)6. Contrasts in local housing markets and housing availability, involving analysis of the number and characteristics of vacant housing units for New Jersey counties.These, as well as other projects we have assisted, have been undertaken with varied software resources, including packages (such as CENTS-AID) with unique hierarchical file processing capabilities, as well as more versatile (non-hierarchical), general purpose packages (such as SPSS). The advantages and research applications of small area, micro-databases can be realized with a range of software techniques and user-formulated research strategies.