This application seeks to advance knowledge about the role that childhood family processes play in adult wealth ownership and inequality. Research has documented growing inequalities in wealth ownership in recent decades, but understanding the processes that explain wealth ownership is limited. We propose to develop a general theoretical and empirical model of wealth accumulation that incorporates family processes during childhood with adult attributes and structural elements. We propose to explore the effect of childhood processes, including how parental involvement in children's lives (specific aim 1.1), the allocation of resources among siblings (specific aim 1.2), and race (specific aim 1.3) on adult wealth accumulation. We also propose to examine the effect of individual and family processes on population outcomes. We will investigate relations in accumulation behaviors across generations (specific aim 2.1), link accumulation behaviors to distributional outcomes (specific aim 2.2), and conduct policy experiments and make future projections of family patterns and wealth (specific aim 2.3). We propose to take advantage of survey data that includes both wealth information and family background information (e.g., the National Longitudinal Survey of Youth), detailed case studies, and other data sets that include even more detailed information about wealth ownership (e.g., the Survey of Consumer Finances). We will use traditional regression methods to analyze the longitudinal survey data and case study data, focusing on the effects of parental involvement in children's lives, the allocation of resources among siblings, and racial and ethnic differences in family processes on adult wealth ownership. We will then develop a simulation model that synthesizes data from these and other surveys, from federal estate tax data, and from aggregate sources of information on household behaviors and wealth ownership. The simulation model will allow us to identify patterns that are evident only when information is merged from multiple data sources, and it will facilitate exploration of the effects of individual and family processes on population outcomes such as wealth distribution. The simulation model will also facilitate policy experimentation and projections of future patterns of well-being under various scenarios.
