More on genes and political preferences

by Henry Farrell on May 16, 2012 · 4 comments

in Data,General Politics,Other social science,Science

Continuing Erik’s series on this, here’s a new article by Daniel Benjamin et al. from the Proceedings of the National Academy of Science.

We study four fundamental economic preferences—risk aversion, patience, trust, and fair-mindedness—and five dimensions of political preferences, derived from a factor analysis of a comprehensive battery of attitudinal items. The five attitudinal dimensions are immigration/crime, economic policy, environmentalism, feminism/equality, and foreign policy. … Under the key assumption of no environmental confounding, an estimator for heritability can be obtained by examining how the correlation in phenotype between pairs of individuals relates to the realized genetic distance between those individuals … . Our GREML-based heritability estimates, although noisy, are on average about half the size of the twin-based heritability estimates. This gap may imply that genotyped SNPs tag about half of the genetic variation in these traits or that twin-based estimates of narrow heritability are biased upward … Our results paint a picture of economic and political preferences as highly polygenic traits for which individual SNPs explain only a small fraction of variance … These findings fit well with an emerging consensus in medical genetics that genetic variants that individually explain a substantial share of the variation in complex traits are unlikely to exist. If anything, the problem is likely to pose an even greater challenge in the social sciences because the phenotypes are usually several degrees removed from genes in the chain of biological causation. Our results suggest that much of the “missing heritability” — the gulf between the cumulative explanatory power of common variants identified to date and the heritability estimated in behavior genetic studies — for social science traits reflects the fact that these traits have a complicated genetic architecture, with most causal variants explaining only a small fraction of the phenotypic variation. If so, then large samples will be needed to detect those variants.


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