Essays in Economics, Genetics, and Psychology

This thesis consists of four multidisciplinary essays that import insights from psychology and genetics into economics. The first essay uses new and comprehensive survey duct collected from more that 11,000 Swedish twins to study the psychometric properties of survey-based measures of economic risk attitudes. It provides a rich empirical characterization of the correlates of risk attitudes and documents their predictive validity in several domains of behavior. The essay also shows that models that adjust for measurement error yield substantially increased estimates relative to models without such adjustments and examines the role of family background in the determination of risk attitudes. It concludes by presenting extensions to a multivariate factor model of risk attitudes.;The second essay reports the results of an experiment in which risk preferences are elicited using the Multiple Price List (MPL) method. In a between-subject design, two types of manipulations are employed: one varies the distribution of the alternative gambles offered in the MPL and has robust effects on measured risk preferences; the other varies whether the expected values of the gambles are displayed and has no effect.;The third essay offers a cautious but hopeful appraisal of the nascent field of genoeconomics and reports the results of a Genome-Wide Association Study (GWAS) of educational attainment. It surveys the literature on behavioral genetics and economics and discusses potential benefits to economics of the use of molecular genetic data. After outlining the major steps of a GWAS and reporting the results, it concludes with a discussion of the challenges that arise when doing inference in genoeconomic research.;The last essay makes several contributions toward establishing the causes of the robust positive correlation between height and intelligence that has been robustly-established in the literature. It extends the standard bivariate ACE model to account for assortative mating and derives several key insights; it uses a large dataset of male Swedish twins to examine the factors that underlie the correlation and reports a significant within-family correlation between height and intelligence, suggesting that pleiotropy might be at play.