Date/Time
Date(s) - 12/03/2026
2:00 pm - 4:00 pm

This year we are joined by Shachar Kariv from the University of California – Berkeley for the Hooker Distinguished Visiting Professor 2026.

Dr. Kariv will be presenting 3 lectures over his visit with the Department of Economics. Kariv is the Benjamin N. Ward Professor of Economics. Educated at Tel Aviv University and New York University, where he received his Ph.D. in economics in 2003, the same year he joined the Department of Economics at the University of California, Berkeley. He has been the Department Chair (2014-17 and 2021-22) the Faculty Director of UC Berkeley Experimental Social Science Laboratory (2009-2014), aka Xlab, a laboratory for conducting experiment-based investigations of issues of interest to social sciences.

Public Talk: The Distributional Preferences of the General (US) Population and of Elites

Thursday, March 12
2:00pm – 4:00pm
Council Chambers, Gilmour Hall 111
Register: Hooker Distinguished Visiting Professor 2026 – Register Here
Read about this study here on Slate.

Abstract
We study the distributional preferences of Americans by decomposing preferences into two qualitatively different tradeoffs—fairness versus self-interest, and equality versus efficiency—and measuring both at the individual level in a large and diverse sample of the US population. We also document the relationship between distributional preferences and voting decisions, shedding light on how American voters are motivated by their distributional preferences. We compare the distributional preferences of the general population to those of elite groups, including law and medical students at top universities. We show that elites are less fair-minded and, perhaps most importantly, substantially and significantly less inclined to sacrifice efficiency to reduce inequality. We further show that our experimental measure of equality-efficiency tradeoffs predicts elite students’ career choices.

Additional Seminars

Linking Social and Personal Preferences: Theory and Experiment

Wednesday, March 11
11:30am – 12:30pm
KTH 334
If you would like to read the paper, you can view it through Kariv’s research page.

Abstract
We ask whether an individual’s attitude toward risk in the personal domain connects to their attitude toward risk in the social domain. We offer formalizations, theoretical responses, and an experimental test. Our motivation is both intellectual and pragmatic: we choose individuals who make consequential decisions for us—Chairs, Deans, Mayors, Governors, Presidents. We care not only about a President’s policy preferences, but what risks they’ll take to achieve them. Blockading Soviet ships (as Kennedy did) risks war; pursuing tax reform and civil rights simultaneously (also as Kennedy did) risks accomplishing neither. Can we infer anything about a President’s risky social choices from personal choices like investing aggressively? Drawing inferences about (present and future) risky social choices from knowledge of (past and present) risky personal choices would seem useful, and also possible—provided that there is a linkage between attitude toward risk in the personal domain and attitude toward risk in the social domain.

Ever Since Allais and Ellsberg

Friday, March 13
11:00am – 12:30pm
KTH 334
If you would like to read the paper, you can view it through Kariv’s research page.

Abstract
The Allais critique of expected utility theory (EUT) has led to the development of theories of choice under risk that relax the independence axiom, but which adhere to the conventional axioms of ordering and monotonicity. Unlike many existing laboratory experiments designed to test independence, our experiment systematically tests the entire set of axioms, providing much richer evidence against which EUT can be judged. Our within-subjects analysis is nonparametric, using only information about revealed preference relations in the individual-level data. For most subjects, we find that departures from independence are statistically significant but minor relative to departures from ordering and/or monotonicity. We also extend the results in settings with risk (known probabilities) to settings with ambiguity (unknown probabilities) and also to time instead of risk tradeoffs.