Benjamin Enke

The Nature and Predictive Power of Preferences: Global Evidence

This paper presents the Global Preference Survey, a globally representative dataset on risk and time preferences, positive and negative reciprocity, altruism, and trust. We collected these preference data as well as a rich set of covariates for 80,000 individuals, drawn as representative samples from 76 countries around the world, representing 90 percent of both the world’s population and global income. The global distribution of preferences exhibits substantial variation across countries, which is partly systematic: certain preferences appear in combination, and follow distinct economic, institutional, and geographic patterns. The heterogeneity in preferences across individuals is even more pronounced and varies systematically with age, gender, and cognitive ability. Around the world, our preference measures are predictive of a wide range of individual-level behaviors including savings and schooling decisions, labor market and health choices, prosocial behaviors, and family structure. We also shed light on the cultural origins of preference variation around the globe using data on language structure.

Measurement Error in Subjective Expectations and the Empirical Content of Economic Models

While stock market expectations are among the most important primitives of portfolio choice models, their measurement has proved challenging for some respondents. We argue that the magnitude of measurement error in subjective expectations can be used as an indicator of the degree to which economic models of portfolio choice provide an adequate representation of individual decision processes. In order to explore this conjecture empirically, we estimate a semiparametric double index model on a dataset specifically collected for this purpose. Stock market participation reacts strongly to changes in model parameters for respondents at the lower end of the measurement error distribution; these effects are much less pronounced for individuals at the upper end. Our findings indicate that measurement error in subjective expectations provides useful information to uncover heterogeneity in choice behavior.

Ancient Origins of the Global Variation in Economic Preferences

Variation in economic preferences is systematically related to both individual and aggregate economic outcomes, yet little is known about the origins of the worldwide preference variation. This paper uses globally representative data on risk aversion, time preference, altruism, positive reciprocity, negative reciprocity, and trust to uncover that contemporary preference heterogeneity has its roots in the structure of the temporally distant migration patterns of our very early ancestors: In dyadic regressions, differences in preferences between populations are significantly increasing in the length of time elapsed since the ancestors of the respective groups broke apart from each other. To document this pattern, we link genetic and linguistic distance measures to population-level preference differences (i) in a wide range of cross-country regressions, (ii) in within-country analyses across groups of migrants, and (iii) in analyses that leverage variation across linguistic groups. While temporal distance drives differences in all preferences, the patterns are strongest for risk aversion and prosocial traits.

Moral Values and Voting: Trump and Beyond

This paper studies the supply of and demand for moral values in recent US presidential elections. Using a combination of large-scale survey data and text analyses, I find support for the hypothesis...

Complexity, Mental Frames, and Neglect

Many decision contexts require economic actors to learn from something they do not see, yet corresponding evidence on people’s cognition is scarce. In a tightly structured and transparent laboratory experiment, many subjects fully neglect what they do not see. A series of treatment variations uncovers that such neglect arises because a particular aspect of complexity induces an excessively narrow mental frame, so that people do not even notice or think about what they do not see. Thus, complexity generates errors in deliberate – and highly confident – statistical reasoning through its effect on how people mentally frame updating problems.