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The distributional preferences of Americans, 2013–2016

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Abstract

We study the distributional preferences of Americans during 2013–2016, a period of social and economic upheaval. We decompose preferences into two qualitatively different tradeoffs—fair-mindedness versus self-interest, and equality versus efficiency—and measure both at the individual level in a large and diverse sample. Although Americans are heterogeneous in terms of both fair-mindedness and equality-efficiency orientation, we find that the individual-level preferences in 2013 are highly predictive of those in 2016. Subjects that experienced an increase in household income became more self-interested, and those who voted for Democratic presidential candidates in both 2012 and 2016 became more equality-oriented.

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Notes

  1. We will not attempt to review the large and growing theoretical, empirical and experimental literatures on distributional preferences. Camerer (1995, 2003) and Cooper and Kagel (2016) provide a comprehensive discussion of experimental and theoretical work in economics focusing on dictator, ultimatum and trust games.

  2. Prior work that has measured distributional preferences across time is lacking in one or more of these features. The most immediate antecedent is Bruhin et al. (2019), which also characterizes distributional preferences in a lab setting, and compares responses across multiple points in time, though with a student population (as compared to a diverse national sample), and preferences measured several months (as opposed to several years) apart. Chuang and Schechter (2015) analyze distributional preferences data gathered in experiments conducted with Paraguayan villagers across a number of years, though the experiments they conduct vary across time periods, and are based on a relatively small number of discrete choices, making it difficult to interpret their findings of relatively unstable preferences.

  3. The ALP website provides information on panel composition, demographics, attrition and response rates, sampling weights, and a comparison with other data sources.

  4. The ALP also tracks respondents’ employment status. While both employment status and income are plausible measures of the financial well-being of a household, income is reported at the household level whereas employment status is that of the individual respondent. This might account for the very loose association between 2013-2016 changes in the employment and income variables (\(\rho =0.06\)) as there can be shifts in the household’s primary breadwinner.

  5. We restricted choices to allocations on the budget constraint so that subjects could not dispose of payoffs. In Fisman et al. (2007), each choice involved choosing a point on a graph representing a budget set over possible allocations. Since most of their subjects had no violations of budget balancedness in all following experiments we restricted choices to allocations on the budget constraint, which simplified the decision problem and made the computer program easier to use.

  6. Because the interface is extremely user-friendly, it is possible to present each subject with many choices in the course of the experiment, yielding a rich individual-level dataset. This makes it possible to analyze behavior at the level of the individual subject, without the need to pool data or assume that subjects are homogenous.

  7. The experimental platform is applicable to other types of individual choice problems. Choi et al. (2007) study risk preferences, and Ahn et al. (2014) extended the work to a settings with ambiguity. Choi et al. (2014) utilize the same experimental technique to study risk preferences in the CentERpanel (a nationally representative Dutch panel).

  8. It is possible that presenting choice problems graphically biases choice behavior in some particular way but there is no evidence that this is the case. For instance, although Fisman et al. (2007) test a much wider range of budget sets than can be tested using the pencil-and-paper questionnaire method of Andreoni and Miller (2002), over all prices, the behavior elicited graphically is consistent with the behavior elicited non-graphically, as well as with the behavior elicited in the split-the-pie dictator games reported in Camerer (2003).

  9. For further details see Fisman et al. (2017). For an overview of revealed preference theory, see Chambers and Echenique (2016) and the papers by Diewert (2012), Varian (2012) and Vermeulen (2012).

  10. Alternative measures that have been suggested, including Houtman and Maks (1985) and Varian (1991), yield similar conclusions. The Bronars (1987) test only shows that a significant majority of the subjects did much better than the randomly generated subjects. To test whether utility maximization is the correct model, Fisman et al. (2007) generate a sample of simulated subjects who maximize the CES utility function with an idiosyncratic preference shock that has a logistic distribution and show that a significant majority of the subjects did only slightly worse than an ideal (rational) subject.

  11. Note that this is not the result of selection into repeating the experiment. To see this, we may compare the preference parameters estimated in 2013 of subjects who repeated the experiment in 2016 to those of subjects who participated only in 2013. The median values of \({\hat{\alpha }}_{n}\) are 0.62 and 0.61 and those of \({\hat{\rho }}_{n}\) are -0.18 and -0.17 respectively.

  12. While its significance is marginal and thus we do not wish to ascribe too strong an interpretation to this finding, it fits with the increased focus on redistribution in much of the Democratic Party, as exemplified by support for, say, Elizabeth Warren’s proposed wealth tax and her relative success as a presidential candidate, as well as the enthusiasm for Bernie Sanders’ ultimately unsuccessful 2020 presidential bid.

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Correspondence to Shachar Kariv.

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We are grateful to Ernst Fehr and Daniel Markovits for helpful discussions and for suggestions from the audience at the Ben-Porath Annual Lecture at the Hebrew University of Jerusalem and a number of seminar participants. We thank the American Life Panel (ALP) team at the RAND Corporation for technical and administrative support. We acknowledge financial support from the Center for Equitable Growth (CEG) at the University of California, Berkeley. Any findings, opinions and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the institutions or any funding agency. The replication material for the study is available at https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/9EQJZE &faces-redirect=true.

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Fisman, R., Jakiela, P., Kariv, S. et al. The distributional preferences of Americans, 2013–2016. Exp Econ 26, 727–748 (2023). https://doi.org/10.1007/s10683-023-09792-z

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  • DOI: https://doi.org/10.1007/s10683-023-09792-z

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