Determining (1) the direction of causation and (2) the size of causal effects between two constructs is a central challenge of the scientific study of humans. In the early 1990s, researchers in behavioral genetics invented what was termed the direction of causation (DoC) model to address exactly these two concerns. The model claims that for any two traits whose mode of inheritance is sufficiently different, the direction of causation can be ascertained using a sufficiently large genetically informative sample. Using a series of simulation studies, we demonstrate a major challenge to the DoC model, namely that it is extremely sensitive to even tiny amounts of non-shared confounding. Even under ideal conditions for the DoC model (a large sample, N = 10,000), a large causal relationship (e.g., a causal correlation of .50) with very different modes of inheritance between the two traits (e.g., a pure AE model for one trait and a pure CE model for another trait) and a modest degree (correlation of .10) of non-shared confounding between the two traits results in the choice of the wrong causal models and estimating the wrong causal effects.

Traditional theories of political participation have emphasized its social and normative components; however, recent evidence suggests that political participation has a strong additive genetic component. Accordingly, it is necessary to reevaluate the traditional empirical findings and begin to integrate the two approaches. To do so, a variety of analyses were conducted that explore the modes of genetic and environmental transmission. I find that the empirical estimates of the relationships between the phenotypic level traits are highly consistent with what has been found in the traditional literature, the vast majority of the variance in political participation that is accounted for by the predictor variables is being accounted for at the genetic level, and not at the environmental level. Thus, the current findings suggest that the empirical results found in prior studies are quite likely very accurate. However, the interpretation of those empirical findings, as well as the subsequent theoretical implications, require serious revision.