SHACHAR KARIV
University of California, Berkeley
Department of Economics
kariv[at]berkeley[dot]edu
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RESEARCH
WORKING PAPERS
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Linking Social and Personal
Preferences: Theory and Experiment, with Bill Zame, UCLA, Bertil Tungodden, NHH, Erik Sørensen, NHH, and Alexander Cappelen, NHH. Version: Mar 16, 2025. Revise and resubmit, Journal
of Political Economy. [Appendix]
Abstract. We provide necessary and sufficient conditions for linking
preferences for personal and social consumption and attitudes toward risk. We
also offer an experimental test of the theory in which subjects were confronted
with risky personal choices, riskless social choices and risky social choices.
Revealed preference tests show that subject choices are generally consistent
within each choice domain but frequently involve at least some errors. We test
for consistency across choice domains using a revealed preference test that
accounts for these errors. The choices of a large majority of subjects are
consistent with the predictions of our theory.
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Scaling Up: Individual-Level
Transfer Performance of Models, with Keaton Ellis, UC Berkeley, and Erkut Ozbay, University of Maryland. Version: Nov 1, 2024.
Abstract. This study
investigates the transferability of economic models for individual
decision-making across different risk domains, specifically comparing
performance between two- and three-state budgetary environments. Utilizing
within-subject laboratory data, we evaluate the ability of Expected Utility
Theory (EUT), Disappointment Aversion (DA), and machine learning models to
predict choices when estimated in a simpler two-state environment and applied
to a more complex three-state environment at the individual level. Our findings
reveal two key insights: (i) there is substantial transferability across
domains for the vast majority of subjects; and (2) EUT demonstrates substantial
transferability, maintaining approximately 92.9% of its within-domain predictive
accuracy when generalized across domains, outperforming both DA and machine
learning models in terms of predictive consistency. These results underscore
the robustness of parsimonious economic models, particularly EUT, in providing
reliable extrapolations across experimental contexts, suggesting their utility
in applications where predictions span diverse risk settings.
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Predicting and Understanding
Individual-Level Choice Under Uncertainty, with Keaton Ellis, UC Berkeley, and Erkut Ozbay, University of Maryland. Version: Sep 30, 2024.
Abstract. Economic models
are founded on parsimony and interpretability, which is achieved through axioms
on choice behavior. We empirically evaluate the predictive accuracy of economic
models of choice under risk and ambiguity, and the strength of their axiomatic
foundations, using complementary methods of completeness (Fudenberg et al.,
2022) and restrictiveness (Fudenberg et al., 2023), respectively. To better
understand the tradeoff between the two concepts, we additionally relate their
performance to machine learning models. We use budgetary choice environments
with three dimensions to provide a strong test of axioms. We show that adding a
third dimension of choice marginally reduces completeness of economic models,
but significantly increases restrictiveness. Economic models are also more
complete than machine learning models, and are significantly more restrictive.
These results are robust to considering an environment of choice under
ambiguity rather than choice under risk. Overall, economic models capture the
behavior of individual subjects well.
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Predicting and Understanding
Individual-Level Choice Under Risk, with Keaton Ellis, UC Berkeley, and Erkut Ozbay, University of Maryland. Version: Sep 30, 2024. [Appendix]
Abstract. We compare the predictive performance of economic models of choice under risk
to various machine learning (ML) models by presenting nearly 1,000 subjects
with a consumer decision problem – the selection of a bundle of
contingent commodities from a budget set. We compare models' predictions at the
individual level and relate them to the consistency of decisions with revealed
preference axioms. Using dual measures of completeness and restrictiveness, we
show that Expected Utility Theory (EUT) performs as well as non-EUT and
outperforms all ML models, with a wider margin as choices align more with
utility maximization.
PUBLISHED AND
FORTHCOMING PAPERS
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Ever Since Allais,
with Aluma Dembo, Reichman University, Matthew Polisson, University of Leicester, and John K.-H. Quah, National University of Singapore. Forthcoming, Journal
of Political Economy. Version: Feb 13, 2025. [Appendix]
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 adhere to
the fundamental/conventional axioms of ordering (completeness and transitivity)
and monotonicity (with respect to first-order stochastic dominance). Unlike
experimental work designed to test independence, our experiment is
comprehensive—testing the entire set of axioms on which EUT is based. Our
econometric analysis is also nonparametric and performed at the level of each
individual subject. For the vast majority of subjects departures from
independence are small relative to departures from ordering and/or
monotonicity.
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Physician Altruism and Spending, Hospital Admissions,
and Emergency Department Visits,
with Jing Li, University
of Washington, Larry
Casalino, Cornell, Ray Fisman,
Boston University, and Daniel
Markovits, Yale Law School. JAMA Health Forum, 2024;5(10).
Abstract.
We
investigate the relationship between physician altruism, care quality, and
spending. Our study sample includes 250 US primary care physicians and
cardiologists, and over 7,500 Medicare beneficiaries. Altruism was measured
using a modified dictator-game experiment, where physicians allocated real
money between themselves and an anonymous individual randomly selected from a
broadly representative sample of the US population. We found that patients of
altruistic physicians had significantly fewer potentially preventable hospital
admissions and emergency department visits and incurred lower adjusted Medicare
spending. Further research is needed to identify modifiable factors influencing
altruism and to explore its impact across various medical practices,
specialties, and countries.
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The Development Gap in Economic Rationality of Future Elites, with Alexander Cappelen,
NHH, Erik Sørensen,
NHH, and Bertil Tungodden,
NHH. Games and Economic Behavior, November 2023, 142, pp. 866-78. [Appendix]
Abstract. We test the
touchstones of economic rationality – utility maximization, stochastic
dominance, and expected-utility maximization – of elite students in the
U.S. and in Africa. The choices of most students in both samples are generally
rationalizable, but the U.S. students' scores are substantially higher.
Nevertheless, the development gap in economic rationality between these future
elites is much smaller than the difference in performance on a canonical
cognitive ability test, often used as a proxy for economic decision-making
ability in studies of economic development and growth. We argue for the
importance of including consistency with economic rationality in studies of
decision-making ability.
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The Distributional Preferences of Americans, 2013-2016, with Ray Fisman, Boston University, Pamela Jakiela, Williams College, and Silvia
Vannutelli, Northwestern
University). Experimental Economics, September 2023, 26, pp.
727–48.
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
-- fairness 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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The Response of Consumer
Spending to Changes in Gasoline Prices,
with Michael Gelman, University of
Michigan, Yuriy Gorodnichenko,
UC Berkeley, Dmitri Koustas, University of
Chicago, Matthew Shapiro,
University of Michigan, Dan Silverman, Arizona State University, and Steven Tadelis, UC Berkeley. American Economic Journal:
Macroeconomics, April 2023, 15(2), pp. 129-60.[Appendix]
Abstract. This paper
estimates how overall consumer spending responds to changes in gasoline prices.
It uses the differential impact across consumers of the sharp drop in gasoline
prices in 2014 for identification. This estimation strategy is implemented
using comprehensive, high-frequency transaction-level data for a large panel of
individuals. The estimated marginal propensity to consume (MPC)out of
unanticipated, permanent shocks to income is approximately one. This estimate
takes into account the elasticity of demand for gasoline and potential slow
adjustment to changes in prices. The high MPC implies that changes in gasoline
prices have large aggregate effects
-
Rational Illiquidity and Consumption: Theory and Evidence from
Income Tax Withholding and Refunds,
with Michael Gelman, Claremont
McKenna, Matthew Shapiro,
University of Michigan, and Dan Silverman, Arizona State University. American Economic
Review, September 2022, 112(9), pp. 2959-91.
Abstract. Low liquidity and a high marginal propensity to consume are tightly
linked. This paper analyzes this link in the context of income tax withholding
and refunds. A theory of rational cash management with income uncertainty
endogenizes the relationship between illiquidity and the MPC, and can explain
the finding that households tend to
spend tax refunds as if they valued liquidity, yet do not act to increase
liquidity by reducing their withholding. The theory is supported by
individual-level evidence based on
financial account records, including a positive correlation between the
size of tax refunds and the MPC out of those refunds.
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Experimental
Evidence of Physician Social Preference with
Jing Li, Cornell, Larry
Casalino, Cornell, Ray Fisman,
Boston University, and Daniel
Markovits, Yale Law School. Proceedings
of the National Academy of Sciences, July 2022, 119(28), pp. 1-11.
Abstract. Physicians’ professional ethics require that they put
patients’ interests ahead of their own and that they should allocate
limited medical resources efficiently. Understanding physicians’ extent
of adherence to these principles requires understanding the social preferences
that lie behind them. These social preferences may be divided into two
qualitatively different tradeoffs: the tradeoff between self and other
(altruism) and the tradeoff between reducing differences in payoffs (equality)
versus increasing total payoffs (efficiency). We experimentally measure social
preferences among a nationwide sample of U.S. practicing physicians. Our design
allows us to distinguish empirically between altruism and equality-efficiency
orientation and to accurately measure both tradeoffs at the level of the
individual subject. We further compare the experimentally measured social
preferences of physicians to those of a representative sample of Americans, an
“elite” subsample of Americans, and a nationwide sample of medical
students. We find that physicians’ altruism stands out. Although most
physicians place a greater weight on self than on other, the share of
physicians who place a greater weight on other than on self is twice as large
as for all other samples—32% as compared to 15-17%. Subjects in the
general population are the closest to physicians in terms of altruism. The
higher altruism among physicians compared to the other samples cannot be
explained by income or age differences. By contrast, physicians’ preferences
regarding equality-efficiency orientation are not meaningfully different from
those of the general sample and elite subsample and are less
efficiency-oriented than medical students.
- How Individuals Smooth Spending: Evidence from the 2013
Government Shutdown Using Account Data
(with Michael Gelman, University of Michigan, Matthew Shapiro, University
of Michigan, Dan Silverman,
Arizona State University, and Steven Tadelis, UC
Berkeley). Journal of Public Economics,
September 2020, 189, pp. 103917. [Appendix]
Abstract. Using comprehensive account records, this paper examines how individuals
adjusted spending and saving in response to a temporary drop in liquidity due
to the 2013 U.S. government shutdown. The shutdown cut paychecks by 40% for
affected employees, which was recovered within 2 weeks. Because the shutdown
affected only the timing of payments, it provides a distinctive experiment
allowing estimates of the response to a liquidity shock holding income
constant. Spending dropped sharply, implying a naïve estimate of 58 cents
less spending for every dollar of lost liquidity. This estimate overstates the
consumption response. While many individuals had low liquid assets, they used
multiple sources of short-term liquidity to smooth consumption. Sources of
short-term liquidity include delaying recurring payments such as for mortgages
and credit card balances.
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Liquidity Risk in
Sequential Trading Networks
(with Maciej Kotowski,
Harvard University, and Matthew
Leister, Monash University). Games
and Economic Behavior, May 2018, 109, pp.565-581. [Appendix]
Abstract. This paper studies a model of intermediated exchange with
liquidity-constrained traders. Intermediaries are embedded in a trading network
and their financial capacities are private information. We characterize our
model's monotone, pure-strategy equilibrium. Agents earn positive
intermediation rents in equilibrium. An experimental investigation supports the
model's baseline predictions concerning agents' strategies, price dynamics, and
the division of surplus. While private financial constraints inject uncertainty
into the trading environment, our experiment suggests they are also a
behavioral speed-bump, preventing traders from experiencing excessive losses
due to overbidding.
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Social Preferences of
Future Physicians (with Jing Li, Cornell, and William Dow, UC Berkeley). Proceedings of the National Academy of
Sciences, November 2017, 114(48), pp. 10291-10300.
Abstract. This paper advances scientific understanding of social preference—a
topic of longstanding cross-disciplinary interest—by studying the
preferences of future physicians. In making treatment decisions, physicians
make fundamental tradeoffs between their own (financial) self-interest, patient
benefit, and stewardship of social resources. These tradeoffs affect patient
health, adoption of new scientific medical technologies, and the equity and
efficiency of our health care system. Understanding physicians’ decisions
about these tradeoffs requires understanding the social preferences that are
behind them. Our main finding that future physicians are substantially less
altruistic and more efficiency focused than the average American challenges
notions of physician altruism, the fundamental feature of medical
professionalism, and has potential implications for policy in a host of health
care areas.
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Distributional Preferences
and Political Behavior, with Ray Fisman, Columbia
B-School, and Pam Jakiela, University
of Maryland. Journal of Public Economics,
November 2017, 155, pp. 1-10.
Abstract. We document the relationship between distributional preferences and
voting decisions in a large and diverse sample of Americans. Using a
generalized dictator game, we generate individual-level measures of
fair-mindedness (weight on oneself versus others) and equality-efficiency
tradeoffs. Subjects' equality-efficiency tradeoffs predict their political
decisions: equality-focused subjects are more likely to have voted for Barack
Obama in 2012, and to be affiliated with the Democratic Party. Our findings
shed light on how American voters are motivated by their distributional
preferences.
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The
Distributional Preferences of an Elite (with
Ray Fisman, Boston
University, Pam Jakiela, University of
Maryland, and Daniel
Markovits, Yale Law School). Science,
September 2015, 349(6254), pp. 1300.
Abstract. We study the
distributional preferences of an elite cadre of J.D. students at Yale Law School
(YLS), a group that hold particular interest because they will assume future
positions of power and influence in American society. Our experimental design
provides a rigorous test of the rationality of redistributive decisions and
allows us to decompose the underlying distributional preferences into two
qualitatively different tradeoffs: the tradeoff between fair-mindedness and
self-interest, and the tradeoff between equality and efficiency. We find that
the YLS subjects are much more rational than subjects drawn from the American
Life Panel (ALP) – a large and diverse sample of Americans. The YLS
subjects are also less fair-minded than the ALP subjects, and, 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 the YLS students’ career
choices: equality-minded subjects are significantly more likely to be employed
at non-profit organizations. Finally, we show that two samples of
“intermediate” elites display distributional preferences that lie
between the YLS elite and the general population, providing further external
validation for the experimental results.
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How Did the Great Recession Impact Social Preferences? with Ray Fisman, Columbia
B-School, and Pam Jakiela, University
of Maryland. Journal of Public Economics.
August 2015, 128, pp. 84–95. [Appendix]
Abstract. To better
understand how support for redistributive policies is shaped by macroeconomic
shocks, we explore how distributional preferences changed during the recent
"Great Recession." We conducted identical modified dictator games
during both the recession and the preceding economic boom. The experiments
capture subjects' selfishness (the weight on one's own payoffs) and
equality-efficacy tradeoffs (concerns for reducing differences in payoffs
versus increasing total payoffs), which we then compare across economic
conditions. Subjects exposed to recession exhibit greater selfishness and
higher emphasis on efficacy relative to equality. Reproducing recessionary
conditions inside the laboratory by confronting subjects with possible negative
payoffs [weakly] intensifies selfishness and increases efficacy orientation,
bolstering the interpretation that differing economic circumstances drive our
results.
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Estimating Ambiguity Aversion in a Portfolio Choice
Experiment, with David Ahn,
Berkeley, Syngjoo Choi,
UCL, and Douglas Gale, NYU.
Version: September 25, 2013. Quantitative Economics, July 2014,
5(2), pp. 195–223. [Appendix I] [Appendix II] [Appendix III]
[Appendix IV] [Appendix V]
[Appendix VI] [Appendix
VII] [Appendix VIII] [Appendix IX] [Appendix X]
Abstract. We report a portfolio-choice experiment that enables us to estimate parametric
models of ambiguity aversion at the level of the individual subject. The assets
are Arrow securities corresponding to three states of nature, where one state
is risky with known probability and two states are ambiguous with unknown
probabilities. We estimate two specifications of ambiguity aversion, one kinked
and one smooth that encompass many of the theoretical models in the literature.
Each specification includes two parameters: one for ambiguity attitudes and
another for risk attitudes. We also estimate a three-parameter specification
that includes an additional parameter for pessimism/optimism
(underweighting/overweighting the probabilities of different payoffs). The
parameter estimates for individual subjects exhibit considerable heterogeneity.
We cannot reject the null hypothesis of Subjective Expected Utility for a
majority of subjects. Most of the remaining subjects exhibit statistically
significant ambiguity aversion or seeking and/or pessimism or optimism.
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Harnessing
Naturally Occurring Data to Measure the Response of Spending to Income, with Michael Gelman, University of Michigan, Matthew Shapiro, University
of Michigan, Dan Silverman,
Arizona State University, and Steven Tadelis, UC
Berkeley. Science, July 2014,
345(6193) pp. 212-215.
Abstract. This paper presents a new
data infrastructure for measuring economic activity. The infrastructure records
transactions and account balances, yielding measurements with scope and
accuracy that have little precedent in economics. The data are drawn from a diverse
population that overrepresents males and younger adults but contains large
numbers of underrepresented groups. The data infrastructure permits evaluation
of a benchmark theory in economics that predicts that individuals should use a
combination of cash management, saving, and borrowing to make the timing of
income irrelevant for the timing of spending. As in previous studies and in
contrast to the predictions of the theory, there is a response of spending to
the arrival of anticipated income. The data also show, however, that this
apparent excess sensitivity of spending results largely from the coincident
timing of regular income and regular spending. The remaining excess sensitivity
is concentrated among individuals with less liquidity.
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Who is (More) Rational? with Syngjoo Choi, UCL, Wieland Müller, Tilburg
University, and Dan Silverman,
Arizona State University. American
Economic Review, June 2014, 104(6), pp. 1518–1550. [Appendix I] [Appendix II]
[Appendix III] [Appendix IV]
[Appendix V] [Appendix VI]
Abstract. Revealed
preference theory offers a criterion for decision-making quality: if decisions
are high quality then there exists a utility function the choices maximize. We
conduct a large-scale experiment to test for consistency with utility
maximization. Consistency scores vary markedly within and across socioeconomic
groups. In particular, consistency is strongly related to wealth: a standard
deviation increase in consistency is associated with 15-19 percent more
household wealth. This association is quantitatively robust to conditioning on
correlates of unobserved constraints, preferences, and beliefs. Consistency
with utility maximization under laboratory conditions thus captures
decision-making ability that applies across domains and influences important
real-world outcomes.
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An Old Measurement of Decision-making Quality Sheds New Light
on Paternalism, with Dan Silverman, Arizona State
University. Journal of Institutional and Theoretical Economics, February 2013, 169(1), pp. 29-44.
Abstract. Definitive judgment about the quality of decision
making is made difficult by twin problems of measurement and identification. A
measure of decision-making quality is hard to formalize, to quantify, and to
make practical for use in a variety of choice environments; and it is difficult
to distinguish differences in decision-making quality from unobserved
differences in preferences, information, beliefs, or constraints. In this
paper, we describe a widely applicable set of tools for theoretical analysis
and experimental methods for addressing these problems. These tools and methods
can indicate a more targeted approach to “light paternalism”
polices aimed at improving decision-making quality.
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Social Learning in Networks: A Quantal Response Equilibrium
Analysis of Experimental Data, with
Syngjoo Choi, UCL, and Douglas Gale, NYU. Review of
Economic Design, September 2012, 16(2-3), pp. 93-118. [Appendix I] [Appendix II]
Abstract. Individuals living in society are bound together by a
social network and, in many social and economic situations, individuals learn
by observing the behavior of others in their local environment. This process is
called social learning. Learning in incomplete networks, where different
individuals have different information, is especially challenging: because of
the lack of common knowledge individuals must draw inferences about the actions
others have observed, as well as about their private information. This paper
reports an experimental investigation of learning in three-person networks and
uses the theoretical framework of Gale and Kariv (2003) to interpret the data
generated by the experiments. The family of three-person networks includes
several non-trivial architectures, each of which gives rise to its own
distinctive learning patterns. To test the usefulness of the theory in
interpreting the data, we adapt the Quantal Response Equilibrium (QRE) model of
McKelvey and Palfrey (1995, 1998). We find that the theory can account for the
behavior observed in the laboratory in a variety of networks and informational
settings. This provides important support for the use of QRE to interpret
experimental data.
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Network Architecture and Mutual Monitoring in Public Goods
Experiments, with Jeffrey Carpenter,
Middlebury College, and Andrew
Schotter, NYU. Review of Economic Design, September 2012, 16(2-3),
pp. 175-191. [Appendix I]
Abstract. Following Fehr and Gäechter (2000), a large and
growing number of experiments show that public goods can be provided at high
levels when mutual monitoring and costly punishment are allowed. Nearly all
experiments, however, study monitoring and punishment in a complete network
where all subjects can monitor and punish each other. The architecture of
social networks becomes important when subjects can only monitor and punish the
other subjects to whom they are connected by the network. We study several
incomplete networks and find that they give rise to their own distinctive
patterns of behavior. Nevertheless, a number of simple, yet fundamental,
properties in graph theory allow us to interpret the variation in the patterns
of behavior that arise in the laboratory and to explain the impact of network
architecture on the efficiency and dynamics of the experimental outcomes.
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Network Architecture, Salience and Coordination, with Syngjoo Choi, UCL, Douglas Gale, NYU, and Thomas Palfrey, Caltech.
Version: January 5, 2011. Games and Economic Behavior, September 2011,
73(1), pp. 76-90. [Appendix I] [Appendix II] [Appendix III]
Abstract. This paper reports the results of an experimental
investigation of dynamic games in networks. In each period, the subjects
simultaneously choose whether or not to make an irreversible contribution to
the provision of an indivisible public good. Subjects observe the past actions
of other subjects if and only if they are connected by the network. Networks
may be incomplete so subjects are asymmetrically informed about the actions of
other subjects in the same network, which is typically an obstacle to the attainment
of an efficient outcome. For all networks, the game has a large set of
(possibly inefficient) equilibrium outcomes. Nonetheless, the network
architecture makes certain strategies salient and this in turn facilitates
coordination on efficient outcomes. In particular, asymmetries in the network
architecture encourage two salient behaviors, strategic delay and strategic
commitment. By contrast, we find that symmetries in the network architecture
can lead to mis-coordination and inefficient outcomes.
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An Experimental Test of Advice and Social Learning, with Boğaçhan Çelen,
Columbia B-School, and Andrew
Schotter, NYU. Version: June 17, 2010. Management Science, October 2010, 56(10), pp. 1678-1701. [Appendix I]
Abstract. Social learning describes any situation in which
individuals learn by observing the behavior of others. In the real world,
however, individuals learn not just by observing the actions of others, but
also learn from advice. This paper introduces advice giving into the standard
social-learning experiment of Çelen and Kariv (2005). The experiments
are designed so that both pieces of information – action and advice - are
equally informative (in fact, identical) in equilibrium. Despite the informational
equivalence of advice and actions, we find that subjects in a laboratory
social-learning situation appear to be more willing to follow the advice given
to them by their predecessor than to copy their action, and that the presence
of advice increases subjects' welfare.
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Trading in Networks: A Normal Form Game Experiment, with Douglas
Gale, NYU. Version: September 30, 2008. American Economic Journal: Microeconomics, August 2009, 1(2), pp.
114-132. [Appendix I] [Appendix
II]
Abstract. This paper reports an experimental study of trading
networks. Networks are incomplete in the sense that each trader can only
exchange assets with a limited number of other traders. The greater the
incompleteness of the network, the more intermediation is required to transfer
the assets between initial and final owners. The uncertainty of trade in
networks constitutes a potentially important market friction. Nevertheless, we
find that the pricing behavior observed in the laboratory converges to
competitive equilibrium behavior in a variety of treatments. However, the rate
of convergence varies depending on the network, pricing rule, and payoff
function.
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Sequential Equilibrium in Monotone Games: Theory-Based
Analysis of Experimental Data, with Syngjoo
Choi, UCL, and Douglas Gale,
NYU. Journal of Economic Theory,
December 2008, 143(1), pp. 302–330. [Appendix]
Abstract. A monotone game
is an extensive-form game with complete information, simultaneous moves and an
irreversibility structure on strategies. It captures a variety of situations in
which players make partial commitments and allows us to characterize conditions
under which equilibria result in socially desirable outcomes. However, since
the game has many equilibrium outcomes, the theory lacks predictive power. To
produce stronger predictions, one can restrict attention to the set of
sequential equilibria, or Markov equilibria, or symmetric equilibria, or
pure-strategy equilibria. This paper explores the relationship between
equilibrium behavior in a class of monotone games, namely voluntary
contribution games, and the behavior of human subjects in an experimental
setting. Several key features of the symmetric Markov perfect equilibrium
(SMPE) are consistent with the data. To judge how well the SMPE fits the data,
we estimate a model of Quantal Response Equilibrium (QRE) (McKelvey and Palfrey
1995, 1998) and find that the decision rules of the QRE model are qualitatively
very similar to the empirical choice probabilities.
-
Consistency
and Heterogeneity of Individual Behavior under Uncertainty,
with Syngjoo Choi, UCL, Douglas Gale, NYU, and Ray Fisman, Columbia
B-School). American Economic Review, December 2007, 97(5), pp. 1921-1938. (Some of the results reported here
are also distributed in Substantive and Procedural
Rationality in Decisions under Uncertainty.) [Appendix I] [Appendix II]
[Appendix III] [Appendix
IV] [Appendix V] [Appendix
VI] [Appendix VII] [Appendix
VIII]
Abstract. By using
graphical representations of simple portfolio choice problems, we generate a
very rich data set to study behavior under uncertainty at the level of the
individual subject. We test the data for consistency with the maximization
hypothesis, and we estimate preferences using a two-parameter utility function
based on Faruk Gul (1991). This specification provides a good interpretation of
the data at the individual level and can account for the highly heterogeneous
behaviors observed in the laboratory. The parameter estimates jointly describe
attitudes toward risk and allow us to characterize the distribution of risk
preferences in the population.
-
Individual Preferences for Giving, with Ray Fisman, Columbia
B-School, and Daniel
Markovits, Yale Law School. American Economic Review, May 2007, 97(5), pp. 1858-1876.
(Previously distributed in three different papers titled Individual
Preferences for Giving, Pareto Damaging Behaviors
and Distinguishing Social Preferences from Preferences
for Altruism.) [Appendix I][Appendix II][Appendix III][Appendix IV][Appendix V][Appendix VI]
Abstract. We utilize
graphical representations of Dictator Games which generate rich
individual-level data. Our baseline experiment employs budget sets over
feasible payoff-pairs. We test these data for consistency with utility
maximization, and we recover the underlying preferences for giving (tradeoffs
between own payoffs and the payoffs of others). Two further experiments augment
the analysis. An extensive elaboration employs three-person budget sets to
distinguish preferences for giving from social preferences (tradeoffs between
the payoffs of others). And an intensive elaboration employs step-shaped sets
to distinguish between behaviors that are compatible with well-behaved
preferences and those that are compatible only with not well-behaved cases.
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Revealing
Preferences Graphically: An Old Method Gets a New Tool Kit, with Syngjoo Choi, UCL, Ray Fisman, Columbia
B-School, and Douglas Gale,
NYU. American Economic Review, Papers & Proceedings, May
2007, 97(2), pp.153-158.
Abstract. This paper describes the necessary tools, both methodological and
analytical, for providing a comprehensive individual-level analysis of decision-making
under risk. Two distinctive features of the paper are the new experimental
technique, and the application of the tools of the theory of consumer demand to
individual decision-making in the laboratory. To characterize an individual's
decision-making under risk, it is necessary to generate many observations per
subject over a wide range of choice sets. An innovative graphical interface was
developed for this purpose, where subjects see on a computer screen a
geometrical representation of a portfolio choice problem. Subjects choose
portfolios through a simple point-and-click. This intuitive and user-friendly
interface allows for the quick and efficient elicitation of many decisions per
subject under a wide range of choice scenarios. The experimental platform and
analytical techniques that have been developed can also be applied to many
types of individual choice problems.
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Financial Networks, with Douglas Gale, NYU. American
Economic Review, Papers & Proceedings, May 2007,
97(2), pp. 99-103.
Abstract. Apart from centralized
exchanges such as the NYSE, most financial transactions take place in networks
where one or more intermediaries link the initial seller and final buyer. This
paper presents a model of financial networks, in which financial exchange is
intermediated by traders who form a chain of links between the initial owner of
the assets and ultimate owner of the assets. Networks are incomplete in the
sense that each trader can only exchange assets with a limited number of other
traders. The greater the incompleteness of the network, the more intermediation
is required to transfer the assets between initial and final owners.
Intermediation takes time and time is costly, so incompleteness constitutes a
potentially important market imperfection. The cost and uncertainty of trade in
networks may give rise to other problems and, in extreme cases, lead to a
market breakdown. The results are applicable not just to financial networks but
to any model of exchange which shares the same basic network structure.
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An Experimental Test of Observational Learning under
Imperfect Information, with Boğaçhan
Çelen, Columbia B-School. Economic Theory, October 2005,
26(3), pp. 677-699 (NYU C.E.S.S. working paper).
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Abstract. To explore the
difference between social learning under perfect and imperfect information,
this paper takes an experimental look at a situation in which individuals learn
by observing the behavior of their immediate predecessors. Our experimental
design is based on the theory of Çelen and Kariv (Observational Learning
Under Imperfect Information) and uses the procedures of Çelen and Kariv
(Distinguishing Informational Cascades from herd Behavior in the Laboratory)
with the exception that the history of actions observed by subjects is
different. We find is that imitation is much less frequent when subjects have
imperfect information, even less frequent than the theory predicts. Further,
while we find strong evidence that under perfect information a form of
generalized Bayesian behavior adequately explains behavior in the laboratory,
under imperfect information behavior is not even consistent with this
generalization of Bayesian behavior. To reconcile this with the conclusions
under perfect information, we undertake a modification of the model that
abandons the assumption of common knowledge of rationality.
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Distinguishing Informational Cascades from Herd Behavior in
the Laboratory, with Boğaçhan
Çelen, Columbia B-School. American Economic Review, June
2004, 94(3), pp. 484-497.
Abstract. This paper reports an experimental test of how
individuals learn from the behavior of others. By using techniques only
available in the laboratory, we elicit subjects' beliefs. This allows us to
distinguish informational cascades (convergence of beliefs) from herd behavior
(convergence of actions). By adding a setup with continuous signal and discrete
action, we enrich the ball-and-urn observational learning experiments paradigm
of Anderson and Holt (1997). We test a model that explains subjects' behavior as
a form of generalized Bayesian behavior that incorporates limits on the
rationality of others. We find strong evidence that, in Bayesian terms,
subjects put too much weight on their own information and too little weight on
the public information. Put differently, subjects are overconfident in the
precision of their private information. To put the observed behavior into
perspective, we use a simple modification of the Bayesian model, which provides
a framework that enables us to understand individual behavior in the
laboratory.
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Observational
Learning Under Imperfect Information, with Boğaçhan Çelen, Columbia
B-School. Games and Economic Behavior, March 2004, 47(1), pp. 72-86.
Abstract. This paper explores Bayes-rational sequential
decision making in a game with pure information externalities, where each
decision maker observes only her predecessor's binary action. Under perfect
information, the martingale property of the stochastic learning process is used
to establish convergence of beliefs and actions. Under imperfect information,
in contrast, beliefs and actions cycle forever. However, despite the
instability, over time the private information is ignored and decision makers become
increasingly likely to imitate their predecessors. Consequently, we observe
longer and longer periods of uniform behavior, punctuated by increasingly rare
switches. These results suggest that the kind of episodic instability that is
characteristic of social behavior in the real world makes more sense in the
imperfect-information model, and that the imperfect information premise
provides a better theoretical description of fads and fashions.
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Bayesian
Learning in Social Networks, with Douglas
Gale, NYU. Games and Economic Behavior, November 2003
Abstract. In this paper, we extend the standard model of social
learning in two ways. First, we introduce a social network and assume that
agents can only observe the actions of agents to whom they are connected by
this network. Secondly, we allow agents to choose a different action at each
date. If the network satisfies a connectedness assumption, the initial
diversity resulting from diverse private information is eventually replaced by
uniformity of actions, though not necessarily of beliefs, in finite time with
probability one. We look at particular networks to illustrate the impact of
network architecture on speed of convergence and the optimality of absorbing
states. Convergence is remarkably rapid, so that asymptotic results are a good
approximation even in the medium run.