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Recent developments in spatial voting have moved beyond finding the most appropriate utility function and started to assess individual differences in decision strategy. The question is not if a proximity or directional worldview performs better in general, rather under what conditions do people pick one strategy over the other? We draw on psychological theories to develop a survey-based measure of individual decision strategy and take a behavior genetic route to explaining the individual differences. We argue that dispositional traits shape whether an individual develops a directional or proximity worldview of the political arena. Utilizing a classical twin design, we capitalize on the documented relationship between partisanship and a directionalist worldview. We find that, in the Minnesota Twin Political Survey, both the strength of party identification and directional voting are moderately (~20 percent) but significantly (p < 0.05) heritable with no socialized component contributing to the variance. The covariation between the two traits is predominantly driven by common underlying genetic effects (p < 0.01). Implications for the rational voter models are discussed in light of the findings. [Reprinted by permission of Sage Publications Ltd., copyright holder.]

This study explains how behavior genetic analysis using a twin design can help us assess the validity of our measures. We test multiple indicators of response propensity, a measure used by survey researchers to better understand the similarities and differences between survey respondents and nonrespondents. The response propensity indicators evaluated include response to follow-up surveys and subsequent waves of a panel and the completion of a sensitive recontact information sheet to aid subsequent recontact efforts. A classical and the newly proposed method of validation all point to insufficient validity of our response propensity measures. Construct validation using data from the National Survey of Midlife Development in the United States exhibited little correlation between indicators. Genetic analysis suggests that the success of subsequent data-collection efforts is predominantly driven by additive genetic effects, while nonresponse to inquiries for recontact information is influenced predominantly by familial environmental predictors. Our results indicate that different underlying constructs drive the response propensity indicators, suggesting that nonresponse is, at minimum, multidimensional. Adapted from the source document.