Social science methods for twins data: integrating causality, endowments, and heritability.

Twins have been extensively used in economics, sociology, and behavioral genetics to investigate the role of genetic endowments on a broad range of social, demographic, and economic outcomes. However, the focus in these literatures has been distinct.: The economic literature has been primarily concerned with the need to control for unobserved endowments--including as an important subset, genetic endowments--in analyses that attempt to establish the impact of one variable, often schooling, on a variety of economic, demographic, and health outcomes. Behavioral genetic analyses have mostly been concerned with decomposing the variation in the outcomes of interest into genetic, shared environmental, and non-shared environmental components, with recent multivariate analyses investigating the contributions of genes and the environment to the correlation and causation between variables. Despite the fact that twins studies and the recognition of the role of endowments are central to both of these literatures, they have mostly evolved independently. In this paper we develop formally the relationship between the economic and behavioral genetic approaches to the analyses of twins, and we develop an integrative approach that combines the identification of causal effects, which dominates the economic literature, with the decomposition of variances and covariances into genetic and environmental factors that are the primary goal of behavioral genetic approaches. We apply this integrative ACE-beta approach to an illustrative investigation of the impact of schooling on several demographic outcomes such as fertility and nuptiality and health.