Do beliefs about inequality depend on distributive preferences? What is the joint role of preferences and beliefs about inequality for support for redistribution? We study these questions in a staggered experiment with a broadly representative sample of the Swiss population conducted in the context of a vote on a highly redistributive policy proposal. Our sample comprises a majority of inequality averse subjects, a sizeable group of altruistic subjects, and a minority of predominantly selfish subjects. Irrespective of preference types, individuals overestimate the extent of income inequality. An information intervention successfully corrects these large misperceptions for all types, but essentially does not affect aggregate support for redistribution. These results hide, however, important heterogeneity because the effects of beliefs about inequality for demand for redistribution are preference-dependent: only inequality averse individuals, but not the selfish and altruistic ones, significantly reduce their support for redistribution. These findings cast a new light on the seemingly puzzling result that, in the aggregate, large changes in beliefs about inequality often do not translate into changes in demand for redistribution.

Standard economic models view risk taking and time discounting as two independent dimensions of decision making. However, mounting experimental evidence demonstrates striking parallels in patterns of risk taking and time discounting behavior and systematic interaction effects, which suggests that there may be common underlying forces driving these interactions. Here, we show that the inherent uncertainty associated with future prospects together with individuals’ proneness to probability weighting generates a unifying framework for explaining a large number of puzzling behavioral findings: delay-dependent risk tolerance, aversion to sequential resolution of uncertainty, preferences for the timing of the resolution of uncertainty, the differential discounting of risky and certain outcomes, hyperbolic discounting, subadditive discounting, and the order dependence of prospect valuation. Furthermore, all these phenomena can be accommodated by the same set of preference parameter values and plausible levels of inherent uncertainty.

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Rising inequality has brought redistribution back on the political agenda. In theory, inequality aversion drives people’s support for redistribution. People can dislike both advantageous inequality (comparison relative to those worse off) and disadvantageous inequality (comparison relative to those better off). Existing experimental evidence reveals substantial variation across people in these preferences. However, evidence is scarce on the broader role of these two distinct forms of inequality aversion for redistribution in society. We provide evidence by exploiting a unique combination of data. We use an incentivized experiment to measure inequality aversion in a large population sample (≈9,000 among 20- to 64-y-old Danes). We link the elicited inequality aversion to survey information on individuals’ support for public redistribution (policies that reduce income differences) and administrative records revealing their private redistribution (real-life donations to charity). In addition, the link to administrative data enables us to include a large battery of controls in the empirical analysis. Theory predicts that support for public redistribution increases with both types of inequality aversion, while private redistribution should increase with advantageous inequality aversion, but decrease with disadvantageous inequality aversion. A strong dislike for disadvantageous inequality makes people willing to sacrifice own income to reduce the income of people who are better off, thereby reducing the distance to people with more income than themselves. Public redistribution schemes achieve this but private donations to charity do not. Our empirical results provide strong support for these predictions and with quantitatively large effects compared to other predictors.

Parsimony is a desirable feature of economic models but almost all human behaviors are characterized by vast individual variation that appears to defy parsimony. How much parsimony do we need to give up to capture the fundamental aspects of a population’s distributional preferences and to maintain high predictive ability? Using a Bayesian nonparametric clustering method that makes the trade-off between parsimony and descriptive accuracy explicit, we show that three preference types—an inequality averse, an altruistic and a predominantly selfish type—capture the essence of behavioral heterogeneity. These types independently emerge in four different data sets and are strikingly stable over time. They predict out-of-sample behaviour equally well as a model that permits all individuals to differ and substantially better than a representative agent model and a state-of-the-art machine learning algorithm. Thus, a parsimonious model with three stable types captures key characteristics of distributional preferences and has excellent predictive power.

Understanding who commits crime and why is a key topic in social science and important for the design of crime prevention policy. In theory, people who commit crime face different social and economic incentives for criminal activity than other people, or they evaluate the costs and benefits of crime differently because they have different preferences. Empirical evidence on the role of preferences is scarce. Theoretically, risk-tolerant, impatient, and self-interested people are more prone to commit crime than risk-averse, patient, and altruistic people. We test these predictions with a unique combination of data where we use incentivized experiments to elicit the preferences of young men and link these experimental data to their criminal records. In addition, our data allow us to control extensively for other characteristics such as cognitive skills, socioeconomic background, and self-control problems. We find that preferences are strongly associated with actual criminal behavior. Impatience and, in particular, risk tolerance are still strong predictors when we include the full battery of controls. Crime propensities are 8 to 10 percentage points higher for the most risk-tolerant individuals compared to the most risk averse. This effect is half the size of the effect of cognitive skills, which is known to be a very strong predictor of criminal behavior. Looking into different types of crime, we find that preferences significantly predict property offenses, while self-control problems significantly predict violent, drug, and sexual offenses.

Abstract We study the link between social preferences and a behaviorally validated measure of support for redistribution. We uncover three fundamentally distinct social preference types: predominantly selfish, inequality averse and altruistic individuals. Inequality averse and altruistic individuals display a much stronger support for redistribution, particularly if they are more affluent. Beliefs about the role of effort and luck for success play no role for selfish individuals but are highly relevant for other-regarding individuals. Finally, while inequality averse individuals display strong support for policies aimed at reducing the incomes of the rich, altruistic individuals are considerably less supportive of these policies.

We study the intergenerational transmission of time preferences in a setting without reverse causality concerns. We find substantial transmission of patience from parents to children, which is insensitive to the inclusion of comprehensive sets of administratively reported controls and persists as children age. We further explore heterogeneity in the transmission with respect to two theoretically important but distinct dimensions of socialization through which parents can influence children's traits: parenting values and parental involvement. Our results show that, in contrast to authoritative parents, authoritarian and permissive parents transmit patience to their offspring. Meanwhile, parental involvement is not an important moderator. These patterns replicate in an independent sample with richer measures of parental involvement.

This paper documents a large association between individuals' time discounting in incentivized experiments and their positions in the real-life wealth distribution derived from Danish high-quality administrative data for a large sample of middle-aged individuals. The association is stable over time, exists through the wealth distribution and remains large after controlling for education, income profile, school grades, initial wealth, parental wealth, credit constraints, demographics, risk preferences, and additional behavioral parameters. Our results suggest that savings behavior is a driver of the observed association between patience and wealth inequality as predicted by standard savings theory.

The distribution of wealth in society is very unequal and has important economic and political consequences. According to standard life-cycle savings theory, differences in time discounting behavior across individuals can play an important role for their position in the wealth distribution. Empirical testing of this hypothesis has been difficult because of serious data limitations. We overcome these limitations by linking an experimental measure of time discounting for a large sample of middle-aged individuals to Danish high-quality administrative data with information about their real-life wealth over the life-cycle as well as a large number of background characteristics. The results show that individuals with relatively low time discounting are persistently positioned higher in the wealth distribution. The relationship is of the same magnitude as the association between years of education and the position in the wealth distribution, and it robustly persists after controlling for a large number of theoretically motivated confounders such as education, risk aversion, school grades, income, credit constraints, initial wealth, and parental wealth. These findings support the view that individual differences in time discounting affect individuals’ positions in the wealth distribution through the savings channel.

This document gives a brief overview of the design and measures of the 'Aarhus survey', a survey consisting of several incentivized online tasks, self-reported survey questions, and psychological scales. The survey was administered to first-semester students in business and social science programmes at Aarhus University in 2013 and subsequently linked with data from the university student registers.

This paper documents a large association between individuals’ time discounting in incentivized experiments and their positions in the real-life wealth distribution derived from Danish high-quality administrative data for a large sample of middle-aged individuals. The association is stable over time, exists through the wealth distribution and remains large after controlling for education, income profile, school grades, initial wealth, parental wealth, credit constraints, demographics, risk preferences and additional behavioral parameters. Our results suggest that savings behavior is a driver of the observed association between patience and wealth inequality as predicted by standard savings theory.

Intertemporal choices are a ubiquitous part of our economic lives. Decisions about education, savings and health, all involve tradeoffs between costs and benefits materializing at different points in time. Yet, a large body of experimental evidence questions the descriptive validity of the economic benchmark model (exponential discounted utility) by documenting a series of behavioral patterns allegedly violating its key predictions. Observed discount rates typically lie far beyond market interest rates, tend to decline in time horizon and in outcome magnitude, and seem to be larger for gains than for losses. Hyperbolic preference models resolve these issues only partly: These models accommodate excessive short-run discounting, but fail to predict both outcome dependence and sign dependence. This paper demonstrates that all these “anomalies” are rationalizable without introducing exotic preferences. Instead, an interplay between liquidity constraints and income expectations is able to produce these stylized facts, even if economic agents are fully rational and have a pure rate of time preference close to the market interest rate. Liquidity-constrained agents who dislike fluctuations in the consumption path, but expect their income to rise in the near future prefer to allocate newly available cash inflows at earlier dates than their pure rate of time preference suggests. The assumptions underlying this mechanism are likely to hold for typical participants in laboratory and field experiments. Beyond that, our approach also provides an explanation for a number of phenomena which have remained largely unexplained so far, such as reasons for observed discount rates to increase in time delay, the heterogeneity of discount rates across different commodities and regions, and the co-occurrence of stationarity and dynamic inconsistency. The mechanism is easily distinguished from hyperbolic preferences and optimistic outlook, and its key predictions are retained under bounded rationality and partial asset integration.

The probability triangle (also called the Marschak-Machina triangle) allows for compact and intuitive depictions of risk preferences. Here, we develop an analogous tool for choice under uncertainty – the ambiguity triangle – and show that indifference curves in this triangle capture preferences for unknown probabilities. In particular, the ambiguity triangle allows us to examine whether subjects adhere to the generalized axiom of revealed preference (GARP) and satisfy a non-parametric test for constant ambiguity attitudes. We find that more than 95% of subjects adhere to GARP and that about 60% satisfy our test for a constant ambiguity attitude. Yet, among these 60% of subjects there is substantial preference heterogeneity. We characterize this heterogeneity with finite-mixture estimates of a one-parameter extension of Expected Utility Theory wherein 48% of subjects are ambiguity averse, 22% are ambiguity seeking, and 30% are close to ambiguity neutral. The ambiguity triangle also highlights how variable ambiguity attitudes arise mainly because indifference curves are ’fanning-in’ across the triangle. This fanning-in property implies that aversion to ambiguity increases as the likelihood of receiving a good outcome increases. We capture this behavior with a simple parametric model that also allows for finite mixture characterizations of preference heterogeneity for these subjects. We show that for a substantial share of these subjects (43%) their fanning-in is so strong that, although they are initially ambiguity seeking, they become strongly ambiguity averse as the likelihood of receiving a good outcome increases.

In a recent experimental study of intertemporal risky decision making, Andreoni and Sprenger (2012) find that subjects exhibit a preference for intertemporal diversification, which is inconsistent with discounted expected utility theory. It was claimed that their results are also at odds with models involving probability weighting, such as rank-dependent utility and cumulative prospect theory. Here we demonstrate, however, that rank-dependent probability weighting explains intertemporal diversification if decision makers care about portfolio risk. Moreover, we provide a unified account of all of Andreoni and Sprenger's key findings. (JEL C91, D81, D91)

We study decision-making under Knightian uncertainty using lower envelope lotteries. Lower envelope lotteries specify lower bounds on probabilities for monetary outcomes and the aggregate amount of unassigned probability mass, an objective quantity we call ambiguity. To examine ambiguity preferences we adapt α-MaxMin Expected Utility (αMEU) to this setting. The αMEU model has one more parameter than expected utility, α, that measures an everywhereconstant ambiguity attitude. Using non-parametric tests we find that 120 of 203 participants (59%) in our experiment made choices consistent with the postulates of an αMEU representation. Parameter estimates from a finite mixture model reveal that, for these 120 participants, 48% exhibited ambiguity aversion, 30% ambiguity neutrality, and 22% ambiguity seeking. For the participants whose choices could not be rationalized with αMEU we introduce a generalization called αβ-MaxMin Expected Utility (αβMEU). The αβMEU model has one more parameter than αMEU. It retains the linear indifference curves of αMEU but allows for a nonconstant ambiguity attitude. For the 41% of participants who exhibited non-constant ambiguity attitudes, finite mixture estimates of αβMEU reveal that aversion to ambiguity increases as the expectation for receiving a good outcome increases. At an intuitive level these estimates typify behavior in which ambiguity is thought of as ’good’ when the expectation of getting a good outcome is low, but ’bad’ when the expectation of getting a good outcome is high. ∗Corresponding author. University of Zürich, Department of Economics, Blümlisalpstrasse 10, 8006 Zürich, Switzerland. dan.burghart@econ.uzh.ch †University of St. Gallen, School of Economics and Political Science, Varnbüelstrasse 19, 9000 St. Gallen, Switzerland, and University of Zürich, Department of Economics, Blümlisalpstrasse 10, 8006 Zürich, Switzerland. thomas.epper@unisg.ch ‡University of Zürich, Department of Economics, Blümlisalpstrasse 10, 8006 Zürich, Switzerland. ernst.fehr@econ.uzh.ch. All authors gratefully acknowledge valuable input from Charles Efferson, Tony Williams, participants in the micro workshops at UZH, and participants at the 2014 Economic Science Association North American meeting held in Fort Lauderdale, Florida. Sonja Vogt was instrumental in preparing the urn used to resolve uncertainty. And we also thank the students, faculty and staff in the Department of Economics at UZH for helping us in composing the urn. Stefan Wehrli, Oliver Brägger and Nadja Jehli provided exceptional technical and practical assistance during data collection. This work was supported by a grant from the European Research Council (#295642).