9320660 Mare This is a study of the effects of families on socioeconomic well-being, collecting data to test a variety of theories in the Human Capital and Human Resources traditions. It will field a module for the 1994 General Social Survey (GSS) that will focus on these effects. This module will supplement an established national survey and obtain information on family structure and socioeconomic achievement of respondents and their kin, including siblings, parents, offspring, and spouses. Sibling information will be obtained through face-to-face interviews with respondents and telephone interviews with one adult sibling of each respondent. This information will include socioeconomic and demographic measures routinely asked of GSS respondents plus information that will enrich our understanding of kinship and intergenerational mobility processes. It will include a reliable measure of cognitive ability for respondents and siblings. The module will support a richer array of studies of the intergenerational mechanisms that contribute to socioeconomic achievement and inequality than have been possible to date. Research issues that will be addressed by users of the data include, but are not limited to: sibling resemblance and family effects on socioeconomic achievement; measurement errors and their impact on inferences about the intergenerational transmission of socioeconomic statuses; the effects of grandparents on the success of their progeny; multi-generational models of mobility; marriage patterns and the socioeconomic makeup of families; and the effects of cognitive abilities on socioeconomic success. %%% The data collected in this research will be a valuable public resource for studies of the links between family structure, intergenerational processes, marriage, and socioeconomic welfare. By adding a module to both General Social Surveys administered in 1994, and through the parallel telephone survey of siblings, this project greatly expan ds the value of one of NSF's major, long-standing scientific survey projects. Policy makers concerned with careers, income and mobility will find the large resulting data set of great value to them in their important work. ***
