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Conventional advice discourages controlling for postoutcome variables in regression analysis. By contrast, we show that controlling for commonly available postoutcome (i.e., future) values of the treatment variable can help detect, reduce, and even remove omitted variable bias (unobserved confounding). The premise is that the same unobserved confounder that affects treatment also affects the future value of the treatment. Future treatments thus proxy for the unmeasured confounder, and researchers can exploit these proxy measures productively. We establish several new results: Regarding a commonly assumed data-generating process involving future treatments, we (1) introduce a simple new approach and show that it strictly reduces bias, (2) elaborate on existing approaches and show that they can increase bias, (3) assess the relative merits of alternative approaches, and (4) analyze true state dependence and selection as key challenges. (5) Importantly, we also introduce a new nonparametric test that uses future treatments to detect hidden bias even when future-treatment estimation fails to reduce bias. We illustrate these results empirically with an analysis of the effect of parental income on children’s educational attainment.Free, publicly-accessible full text available August 1, 2023
Abstract Multiple imputation (MI) is a popular and well-established method for handling missing data in multivariate data sets, but its practicality for use in massive and complex data sets has been questioned. One such data set is the Panel Study of Income Dynamics (PSID), a longstanding and extensive survey of household income and wealth in the United States. Missing data for this survey are currently handled using traditional hot deck methods because of the simple implementation; however, the univariate hot deck results in large random wealth fluctuations. MI is effective but faced with operational challenges. We use a sequential regression/chained-equation approach, using the software IVEware, to multiply impute cross-sectional wealth data in the 2013 PSID, and compare analyses of the resulting imputed data with those from the current hot deck approach. Practical difficulties, such as non-normally distributed variables, skip patterns, categorical variables with many levels, and multicollinearity, are described together with our approaches to overcoming them. We evaluate the imputation quality and validity with internal diagnostics and external benchmarking data. MI produces improvements over the existing hot deck approach by helping preserve correlation structures, such as the associations between PSID wealth components and the relationships between the household net worthmore »
The Longitudinal Revolution: Sociological Research at the 50-Year Milestone of the Panel Study of Income DynamicsThe US Panel Study of Income Dynamics (PSID) celebrated its 50th anniversary in 2018. Initially designed to assess the nation's progress in combatting poverty, PSID's scope broadened quickly to a variety of topics and fields of inquiry. To date, sociologists are the second-most frequent users of PSID data after economists. Here, we describe the ways in which PSID's history reflects shifts in social science scholarship and funding priorities over half a century; take stock of the most important sociological breakthroughs it facilitated, in particular those relying on the longitudinal structure of the data; and critically assess the unique advantages and limitations of PSID and surveys like it for today's sociological scholarship.
The black-white gap in household wealth is large and well documented. Here, we visualize how this racial wealth gap persists across generations. Animating the flow of individuals between the relative wealth position of parents and their adult children, we show that the disadvantage of black families is a consequence both of wealth inequality in prior generations and race differences in the transmission of wealth positions across generations: Black children both have less wealthy parents on average and are far more likely to be downwardly mobile in household wealth. By displaying intergenerational movements between parental and offspring wealth quintiles, we underline how intergenerational fluctuation coexists with the maintenance of a severely racialized wealth structure.