Tonight, Sunday, at 5:30pm California time, I'll be opening the Monday morning session in Hong Kong of the THE 18TH CONGRESS OF ASIAN SOCIETY OF TRANSPLANTATION 25 -28 August 2023.
Here's an update on the three scheduled workshops connected to the SLMath (formerly MSRI) semester focus on market and mechanism design. (There will be two in September and one in November.)
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SITE 2023 Session 5: Experimental Economics Thu, Aug 10 2023, 9:00am - Fri, Aug 11 2023, 5:00pm PDT
John A. and Cynthia Fry Gunn Building, 366 Galvez Street, Stanford, CA 94305
ORGANIZED BY Christine Exley, Harvard University Kirby Nielsen, California Institute of Technology Muriel Niederle, Stanford University Alvin Roth, Stanford University Lise Vesterlund, University of Pittsburgh
This session will be dedicated to advances in experimental economics combining laboratory and field-experimental methodologies with theoretical and psychological insights on decision-making, strategic interaction and policy. We are inviting papers in lab experiments, field experiments and their combination that test theory, demonstrate the importance of psychological phenomena, and explore social and policy issues. In addition to senior faculty members, invited presenters will include junior faculty as well as graduate students.
Thursday, August 10, 2023
9:00 AM - 9:30 AM PDT Breakfast and Welcome
AUG 10 9:30 AM - 10:00 AM PDT
Information Avoidance and Image Concerns
Presented by: Judd Kessler (The Wharton School)
Co-author(s): Christine L. Exley (Harvard University)
A rich literature finds that individuals avoid information and suggests that avoidance is driven by image concerns. This paper provides the first direct test of whether individuals avoid information because of image concerns. We build off of a classic paradigm, introducing control conditions that make minimal changes to eliminate the role of image concerns while keeping other key features of the environment unchanged. Data from 6,421 experimental subjects shows that image concerns play a role in driving information avoidance, but a role that is substantially smaller than one might have expected.
AUG 10 10:00 AM - 10:30 AM PDT
Transactional Preferences and the Minimum Wage
Presented by: Kristóf Madarász (London School of Economics)
Co-author(s): Anna Becker (Stockholm University), Attila Lindner (University College London), and Heather Sarsons (University of British Columbia)
A growing number of studies suggest that minimum wages have limited disemployment effects while at the same time increasing output prices. This finding contradicts the ”law of demand”, which states that output demand, and therefore employment, should fall whenever prices increase. We propose a simple framework to explain this fact and to highlight some aspects of ethical consumption more generally. Consumers derive extra utility when engaging in transactions that can be associated with positive moral attributes. In the context of the minimum wage, consumers derive a higher marginal utility when they know that the good they are consuming is produced by a worker earning a higher wage. Combined with firms’ inability to credibly commit to higher wages, a mandated minimum wage policy can lead to higher output and positive employment effects simultaneously. We implement an online survey experiment in the U.S. to test for the proposed mechanism. We use our findings to reassess the welfare implications of the policy.
AUG 10 10:30 AM - 11:00 AM PDT
Assessing Behavioral Incentive Compatibility
Presented by: Lise Vesterlund (University of Pittsburgh)
AUG 1011:00 AM - 11:30 AM PDT Break
AUG 10
11:30 AM - 12:00 PM PDT
Connecting Common Ratio and Common Consequence Preferences
Presented by: Charlie D. Sprenger (Caltech)
Co-author(s): Christina McGranaghan (University of Delaware), Kirby Nielsen (California Institute of Technology), Ted O’Donoghue (Cornell University), and Jason Somerville (Federal Reserve Bank of New York)
Many models of decision-making under uncertainty are motivated by two prominent deviations from expected utility (EU): the common consequence effect (CCE) and the common ratio effect (CRE). Both decision problems were originally proposed as thought experiments by Allais (1953), and later popularized by Kahneman & Tversky (1979). The apparent deviations from EU predictions in each problem have motivated a wide body of decision theories in risky choice.
Although the CRE and CCE both represent violations of the EU axiom of independence, they have been studied mostly independently, and using quite different experimental parameters. In fact, however, the two decision problems are closely related: If conducted at a common set of experimental parameters, the two problems would share three out of four possible options. Moreover, the connections between the two problems are relevant for assessing various non-EU models—i.e., different models predict specific patterns.
In this paper, we extend existing empirical tests by (i) explicitly recognizing the connection between the two decision problems; (ii) conducting a large number of experiments covering connected CRE and CCE problems at different experimental parameters; and (iii) implementing experiments using both paired choice tasks (for comparison to the prior literature) and paired valuation tasks (our preferred approach given the inferential challenges outlined in McGranaghan et al (2022)).
Our results provide important insights on the shape of risk preferences. We find small but significant CR preferences, but systematic reverse CC preferences. Through their connection, this pattern implies that individuals violate betweenness by preferring mixtures. These results are inconsistent with leading non-EU models, and we propose a model to rationalize these findings.
AUG 10 12:00 PM - 12:30 PM PDT
Beliefs in a High-Stakes Environment
Presented by: Stephanie Wang (University of Pittsburgh)
Co-author(s): Yiming Liu (Humboldt University of Berlin)
It has been well-documented that people tend to be overconfident. We investigate whether biased beliefs in performance persist in a high-stakes environment. Specifically, we ask whether students are overconfident when estimating their high school entrance exam performance. Students in our environment have strong incentives to accurately assess their exam scores because they need to submit their rank order list under an immediate acceptance mechanism before knowing their exam performance. Combining administrative and survey data on estimated performance and actual performance, we find no evidence for overconfidence in estimation in this high-stakes environment. However, when we remove the high stakes by eliciting students’ recall of their performance in a previous mock exam, they show a strong pattern of overconfidence. Consistent with Benabou and Tirole ́ (2002)’s theory of the supply of biased beliefs through biased memory, we find suggestive evidence that students rely on their potentially biased memory of past performance to construct their high-stakes estimation.
AUG 11 12:30 PM - 2:0
AUG 10 12:30 PM - 2:00 PM PDT Lunch/Discussion
AUG 10 2:00 PM - 2:15 PM PDT
Procedural Decision-Making in the Face of Complexity
Presented by: Gonzalo Arrieta (Stanford University)
Co-author(s): Kirby Nielsen (California Institute of Technology)
Individuals often change their decision-making in response to complexity, as has been discussed for decades in psychology and economics, but existing literature provides little evidence on the general characteristics of these processes. We introduce an experimental methodology to show that in the face of complexity, individuals resort to “procedural” decision-making, which we categorize as choice processes that are more describable. We elicit accuracy in replicating decision-makers’ choices to experimentally measure and incentivize the choice process’ describability. We show that procedural decision-making increases as we exogenously vary the complexity of the environment, defined by the choice set’s cardinality. This allows for procedural reinterpretations of existing findings in decision-making under complexity, such as in the use of heuristics.
AUG 10 2:15 PM - 2:30 PM PDT
What Drives Violations of the Independence Axiom? The Role of Decision Confidence
Presented by: Aldo Lucia (California Institute of Technology)
Recent theoretical work implicates decision confidence as a central component of decision-making under uncertainty, attributing failures of Expected Utility (EU) to a lack of confidence. We design an experiment testing EU’ central independence axiom and contemporaneously eliciting measures of decision confidence. We find that choices characterized by high self-reported levels of decision confidence and low response times are more likely to com-ply with the independence axiom. Contrary to the common certainty effect rationale for independence violations, we show that subjects predominantly violate EU by choosing risky lotteries over certain amounts when they are unconfident in their choices.
AUG 10 2:30 PM - 2:45 PM PDT
Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech
Presented by: Mallory Avery (Monash University)
Co-author(s): Andreas Leibbrandt (Monash University) and Joseph Vecci (University of Gothenburg)
The use of Artificial Intelligence (AI) in recruitment is rapidly increasing and drastically changing how people apply to jobs and how applications are reviewed. In this paper, we use two field experiments to study how AI in recruitment impacts gender diversity in the male-dominated technology sector, both overall and separately for labor supply and demand. We find that the use of AI in recruitment changes the gender distribution of potential hires, in some cases more than doubling the fraction of top applicants that are women.This change is generated by better outcomes for women in both supply and demand. On the supply side, we observe that the use of AI reduces the gender gap in application completion rates. Complementary survey evidence suggests that this is driven by female jobseekers believing that there is less bias in recruitment when assessed by AI instead of human evaluators. On the demand side, we find that providing evaluators with applicants’ AI scores closes the gender gap in assessments that otherwise disadvantage female applicants. Finally, we show that the AI tool would have to be substantially biased against women to result in a lower level of gender diversity than found without AI.
AUG 10 2:45 PM - 3:00 PM PDT
Regulation of Organ Transplantation and Procurement: A Market Design Lab Experiment
Presented by: Alex Chan (Harvard University)
Co-author(s): Alvin E. Roth (Stanford University)
We conduct a lab experiment that shows current rules regulating transplant centers (TCs) and organ procurement organizations (OPOs) create perverse incentives that inefficiently reduce both organ recovery and beneficial transplantations. We model the decision environment with a 2-player multi period game between an OPO and a TC. In the condition that simulates current rules, OPOs recover only highest-quality kidneys and forgo valuable recovery opportunities, and TCs decline some beneficial transplants and perform some unnecessary transplants. Alternative regulations that reward TCs and OPOs together for health outcomes in their entire patient pool lead to behaviors that increase organ recovery and appropriate transplants.
AUG 10 3:00 PM - 3:30 PM PDT Break
AUG 10 3:30 PM - 3:45 PM PDT
Memory and the Persistence of Gender Discrimination
Presented by: Francesca Miserocchi (Harvard University)
Standard models of discrimination assume that decision-makers use all the available information about candidates when making their decisions. Based on research in psychology, I test the hypothesis that when decision-makers have a lot of other information in their mind, they are less likely to remember how particular individuals performed and fall back on stereotypes, which disadvantages women in predominantly male-dominated fields. First, in years when teachers need to evaluate a larger number of students – amplifying memory constraints – girls are considerably less likely to be recommended for top-tier scientific high school tracks. On the contrary, the gender gap in students’ objective math ability does not expand during these years. Second, I conduct an experiment in which teachers assign track recommendations for hypothetical student profiles. Teachers are less likely to recommend girls to scientific tracks if they freely recall the information about them than when they can reference the information (proxying a perfect memory benchmark). Third, when asked to remember a candidate’s past performance on a series of trivia questions in sports and pop-culture, participants tend to remember a higher share of correct sports questions when they are answered by a boy than by an identical girl. The opposite is true for pop-culture questions. The results suggest that a significant portion of gender discrimination is driven by imperfect and selective memory of previously observed information, opening up the scope for policy interventions in the form of structured reminders.
AUG 10 3:45 PM - 4:00 PM PDT
Revealed Preference when Attention is Selective and Malleable
Presented by: John Conlon (Stanford University)
I show experimentally that information persuades not only by shifting beliefs but also by redirecting attention. Participants in my experiment decide whether to purchase a multi-attribute good. At baseline, selective attention generates large distortions in how responsive demand is to the values of these attributes. Randomly providing information about the value of one attribute, even when it is already known and transparently redundant, starkly increases responsiveness to that attribute and distracts attention from others. These forces can produce paradoxical responses to correcting beliefs: reducing overoptimism about an attribute can nonetheless boost demand for its associated good.
AUG 10 4:00 PM - 4:15 PM PDT
Interventionist Preferences and the Welfare state: The Case of In-Kind Nutrition Assistance
Presented by: Tony Q. Fan (Stanford University)
Co-author(s): Sandro Ambuehl (University of Zurich), B. Douglas Bernheim (Stanford University), and Zach Freitas-Groff (Stanford University)
Poverty assistance is often administered in-kind even though cash transfers might raise recipients’ welfare more effectively. We characterize the political economy constraint that paternalistic motives impose on the welfare system. In our experiment, a representative sample of U.S. citizens reveal their motives by deciding whether to constrain real U.S. food stamp recipients’ choices between in-kind donations and cash equivalents we disburse. The modal respondent (40%) imposes the strictest possible constraints, while 30% impose no constraints. Hence, the majority’s behavior is consistent with deontological motives rather than trade-off thinking. Yet, because of biased beliefs about recipient preferences, respondents underestimate the restrictiveness of their interventions, suggesting that they are partly misguided. Overall, respondents’ goal is not to ensure sufficient healthy nutrition, but to prevent consumption of items deemed inappropriate. While respondents reveal racial and gender stereotypes in various survey questions, neither donor nor recipient demographics have substantial effects on restriction decisions, though restrictions increase with respondents’ political conservatism. In-experiment behavior correlates strongly with views about government policy.
AUG 10 5:00 PM - 8:00 PM PDT Dinner at Muriel’s House
Friday, August 11, 2023
9:00 AM - 9:30 AM PDT Breakfast and Welcome
AUG 11 9:30 AM - 10:00 AM PDT
Sleep: Educational Impact and Habit Formation
Presented by: Silvia Saccardo (Carnegie Mellon University)
Co-author(s): Osea Giuntella (University of Pittsburgh) and Sally Sadoff (University of California San Diego)
In a field experiment among undergraduates, we test the impact of interventions to increase sleep on sleep habits and academic achievement. Offering incentives contingent on sleeping at least 7 hours per night increases sleep during both the four-week treatment period and the one to five-week post-treatment period. The intervention also significantly increases GPA at the end of the semester. Our estimates suggest that causally increasing sleep by an average of 6 - 16 minutes per night improves GPA by 0.12 - 0.14 standard deviations. We additionally examine the role of timing of rewards and reminders and feedback for improving sleep habits. We find that immediate incentives combined with reminders and feedback have the largest impact during treatment, but do not outperform delayed incentives or reminders and feedback alone during the post-intervention period. Our results suggest that interventions targeting sleep are a cost-effective tool for improving educational outcomes.
AUG 11 10:00 AM - 10:30 AM PDT
Describing Deferred Acceptance to Participants: Experimental Analysis
Presented by: Ori Heffetz (Cornell University and Hebrew University)
Co-author(s): Yannai Gonczarowski (Harvard University), Guy Ishai (Hebrew University of Jerusalem), and Clayton Thomas (Princeton University)
Designed markets often rely on carefully crafted descriptions of mechanisms. By and large, these descriptions attempt to convey as directly as possible what the outcome of the market will be. Are there principled, alternative theories of how to construct descriptions to expose different properties of mechanisms? Recently-proposed menu descriptions aim to provide such a theory towards exposing the strategyproofness of real-world mechanisms such as Deferred Acceptance. We design an incentivized experiment to test the ability of a menu description of Deferred Acceptance (compared to a traditional description) to affect participant behavior and their understanding of strategyproofness. We also design treatments conveying the definition of strategyproofness itself rather than the full details of the mechanism, with one treatment inspired by traditional definitions and one inspired by menu descriptions.
AUG 11 10:30 AM - 11:00 AM PDT
Decomposing the Winner’s Curse in Common-Value Auctions: What is the Role of Contingent Thinking?
Presented by: Muriel Niederle (Stanford University)
AUG 11 11:00 AM - 11:30 AM PDT Break
AUG 11 11:30 AM - 12:00 PM PDT
Stochastic Dominance and Preference for Randomization
Presented by: Séverine Toussaert (University of Oxford)
Decision theorists usually take a normative view on stochastic dominance: a decision maker who chooses a lottery that puts more weight on options he likes less must be making a mistake. In this paper, I argue that stochastic dominance violations may naturally occur in situations where anticipatory utility is high, such as going on a holiday trip. In such a situation, the decision maker may trade the certainty of going to his favorite destination for the excitement of not knowing where he will go. To document this phenomenon, I conduct an experiment in which participants make a series of binary choices between a sure destination and a lottery over holiday trips. The outcome of the lottery is revealed close to the date of travel. I vary the characteristics of the lotteries to understand when violations of stochastic dominance are most likely to occur and analyze their properties. I discuss the implications for the modelling of anticipatory utility.
AUG 11 12:00 PM - 12:30 PM PDT
Insensitive Investors
Presented by: Cary Frydman (University of Southern California)
Co-author(s): Constantin Charles (University of Southern California) and Mete Kilic (University of Southern California)
We experimentally study the transmission of subjective expectations into actions. Subjects in our experiment report valuations that are far too insensitive to their expectations, relative to the prediction from a frictionless model. We propose that the insensitivity is driven by a noisy cognitive process that prevents subjects from precisely computing asset valuations. The empirical link between subjective expectations and actions becomes stronger as subjective expectations approach rational expectations. Our results highlight the importance of incorporating weak transmission into belief-based asset pricing models. Finally, we discuss how cognitive noise can provide a microfoundation for inelastic demand in the stock market.
0 PM PDT Lunch/Discussion
AUG 11
2:00 PM - 2:30 PM PDT
The Experimenters' Dilemma: Inferential Preferences over Populations
Presented by: Alistair Wilson (University of Pittsburgh)
Co-author(s): Luca Rigotti (University of Pittsburgh) and Neeraja Gupta (University of Richmond)
We examine the experimenter’s preferences over different populations using statistical power under a fixed budget as the stand-in for the researcher’s utility. We consider five populations commonly used in experiments by economists: undergraduate students at a physical location, undergraduate students in a virtual setting, Amazon MTurk "workers", a filtered MTurk subset from CloudResearch, and Prolific. Focusing on noise due to inattention, observation costs dominate the comparisons, with the larger online population samples superior to the smaller lab samples. However, once we factor in responsiveness to treatment, the lab samples have greater power than either MTurk or Prolific.
AUG 11 2:30 PM - 3:00 PM PDT Break
AUG 11 3:00 PM - 3:30 PM PDT
Quantifying Lottery Choice Complexity
Presented by: Benjamin Enke (Harvard University)
Co-author(s): Cassidy Shubatt (Harvard University)
We develop indices of the objective and subjective complexity of lottery choice problems that can be computed for any standard dataset. These indices reflect which choice set features increase error rates and cognitive uncertainty in gauging expected values. Using these measures, we study behavioral responses to complexity across one million experimental decisions. In line with a model of heteroscedastic cognitive noise, complexity (i) makes choices more inconsistent and regressive to people’s prior; (ii) predicts when subjects accept unattractive gambles; and (iii) spuriously generates complexity aversion and small-stakes risk aversion. In structural estimations, complexity-dependent heteroscedasticity improves model fit considerably more than prospect theory does.
AUG 11 3:30 PM - 4:00 PM PDT
Competing Causal Interpretations: A Choice Experiment
Presented by: Sandro Ambuehl (University of Zurich)
Co-author(s): Heidi C. Thysen (Norwegian School of Economics)
A central factor when choosing an action is its causal effect on the outcome of interest. Yet, causal information is often lacking. People instead observe correlational or historical data, along with causal interpretations and action recommendations provided by experts who frequently disagree with each other. We use a laboratory experiment to study human choice in such settings. Roughly half of our subjects attempt to determine the fit of the causal interpretations to past data, as the literature on model persuasion assumes, and we outline the limits to their ability to do so. Half the subjects’ choices are co-determined by the interpretations’ promises of future payouts, as the literature on narrative competition assumes, or by the downside these choices entail if they are mistaken. Additionally, subjects commonly employ heuristics such as Occam’s razor, but they usually prefer more complex interpretations to more parsimonious ones. We also study the extent to which behavior is robust to framing and has out-of-sample predictive power, as well as the relation between subjects’ choices and their political attitudes and psychological characteristics. Finally, we will characterize the contexts in which subjects’ behavioral tendencies expose them to the greatest losses and render them most receptive to misleading interpretations.
AUG 11 4:00 PM - 4:30 PM PDT
Extracting Models From Data Sets: An Experiment Using Notes-to-Self
Presented by: Guillaume Fréchette (New York University)
Co-author(s): Emanuel Vespa (University of California, San Diego) and Sevgi Yuksel (University of California, Santa Barbara)
We report results from an experiment designed to study how people extract patterns from their observations. The novel experimental design asks subjects to organize different sets of observations (data) with the goal of making predictions in similar situations. We study whether the predictions subjects make in each environment are consistent with them using some “model” that posits specific statistical relationships between different variables. We find that the predictions of most subjects can be rationalized by some model. Importantly, we find the most commonly used model is the optimal one in that it maximizes prediction accuracy. Deviations from the optimal model often involve use of simpler models that fail to account for statistically relevant correlations in the data. Variation in the set of observations presented to subjects across environments allows us to test whether the way subjects learn from data display a key aspect of causal reasoning: identification of conditional independence between variables. While we find strong evidence for this, we also observe that failures of this increase with the noise in the data. Complemented with ancillary non-choice data that emerges as a by-product of our design, our results provide insights into how people form models of the world by studying data and how they use these models to make predictions.
AUG 11 5:00 PM - 7:00 PM PDT Dinner in Courtyard
SITE 2023 Session 4: Psychology and Economics Tue, Aug 8 2023, 9:00am - Wed, Aug 9 2023, 5:00pm PDT John A. and Cynthia Fry Gunn Building, 366 Galvez Street, Stanford, CA 94305
ORGANIZED BY B. Douglas Bernheim, Stanford University, John Beshears, Harvard University, Vincent Crawford, University of Oxford & University of California San Diego, David Laibson, Harvard University, Ulrike Malmendier, University of California Berkeley
This session brings together researchers working on issues at the intersection of psychology and economics. The segment will focus on evidence of and explanations for non-standard choice patterns, as well as the positive and normative implications of those patterns in a wide range of economic decision-making contexts, such as lifecycle consumption and savings, workplace productivity, health, and prosocial behavior. The presentations will frequently build upon insights from other disciplines, including psychology and sociology. Theoretical, empirical, and experimental studies will be included.
Tuesday, August 8, 2023
9:00 AM - 9:30 AM PDT Check-in & Breakfast
AUG 8 9:30 AM - 10:00 AM PDT
Sophisticated Consumers with Inertia: Long-Term Implications from a Large-Scale Field Experiment
Presented by: Navdeep S. Sahni (Stanford University)
Co-author(s): Klaus M. Miller (HEC Paris) and Avner Strulov-Shlain (University of Chicago)
Using a randomized field experiment with a leading European newspaper, we study both the inertia anticipated by consumers and the actual inertia they experience. Our experiment among two million readers varies promotional subscription terms, including whether or not the contract automatically renews to a full-price subscription by default. By analyzing their subscription behavior over two years, we study how consumers respond to inertia-inducing subscription contracts in the short- and long-run. We find strong inertia. Half of the auto-renewal contract takers continue to a full-price subscription while rarely using it. At the same time, consumers preempt their future inertia; 24%-36% of potential subscribers avoid subscribing when offered an auto renewal promo. Further, offering an auto-renewal contract decreases the share of subscribers over the two years after the promo by 10%. Even though auto-renewal generates higher revenue in the medium-run due to payments from inert subscribers, auto-renewal and auto-cancel are revenue equivalent after one year, but with fewer subscribers in auto-renewal. Using a mixed-types model, we estimate that while 70% of consumers are inert, a large majority of them (at least 58%) are aware of their inertia. Our results highlight the importance of sophistication about future biases in the market; sophisticated consumers avoid exploitation and are missed by researchers and firms analyzing only takers, since takers are selected on their na ̈ıvet ́e.
AUG 8 10:00 AM - 10:30 AM PDT
Hedging by Giving: Spiritual Insurance and Religious Donations
Presented by: Yu Zhang (Peking University)
Co-author(s): Yu-Jane Liu (Peking University), Juanjuan Meng (Peking University), and Dalin Sheng (Southwestern University of Finance and Economics)
This paper analyzes donation behaviors from the perspective of religious beliefs. Using a transaction-level dataset from an Asian economy, we show that higher income uncertainty predicts more donations, especially for religious donations, and after negative income uncertainty and health shock. This pattern is inconsistent with existing explanations of donation, but can be explained by a “spiritual insurance” channel, whereby donators believe that giving reduces the probability of the bad state. Indeed, we find that those who donate to non-local religious organizations reduce their insurance purchases, suggesting that “spiritual insurance” channel can be influential for donation and the insurance market.
AUG 8 10:30 AM - 11:00 AM PDT
The Creativity Premium: Exploring the Link Between Childhood Creativity and Life Outcomes
Presented by: Victoria Prowse (Purdue University)
Co-author(s): David Gill (Purdue University)
Success in life increasingly depends on key skills that allow people to thrive in education, the labor market, and their interactions with others. In this paper, we emphasize creativity as a key skill that is essential to open-ended problem solving and resistant to automation. We use rich longitudinal data to study the relationship between people’s creativity measured in childhood and their individual attributes and life outcomes. We find that childhood creativity predicts labor market and educational success: more creative individuals earn more during the course of their careers, work in higher occupational categories, and reach higher levels of educational attainment. Our analysis of attributes further suggests that creative individuals have a package of practical skills that allows them to thrive in work environments where learning from experience is important. We combine insights from our findings with evidence from psychology to propose creativity-improving interventions that could lead to substantial economic benefits.
AUG 8 11:00 AM - 11:30 AM PDT Break
AUG 8 11:30 AM - 12:00 PM PDT
The Dynamics of Networks and Homophily
Presented by: Leeat Yariv (Princeton University)
Co-author(s): Matthew O. Jackson (Stanford University), Stephen M. Nei (University of Exeter), and Erik Snowberg (University of Utah)
We examine friendships and study partnerships among university students over several years. At the aggregate level, connections increase over time, but homophily on gender and ethnicity is relatively constant across time, university residences, and different network layers. At the individual level, homophilous tendencies are persistent across time and network layers. Furthermore, we see assortativity in homophilous tendencies. There is weaker, albeit significant, homophily over malleable characteristics---risk preferences, altruism, study habits, and so on. We find little evidence of assimilation over those characteristics. We also document the nuanced impact of network connections on changes in Grade Point Average.
AUG 8 12:00 PM - 12:30 PM PDT
Strategic Behavior with Tight, Loose and Polarized Norms
Presented by: Eugen Dimant (University of Pennsylvania)
Co-author(s): Michele Gelfand (University of Maryland), Anna Hochleitner (University of Nottingham), and Silvia Sonderegger (University of Nottingham)
Descriptive norms - the behavior of other individuals in one's reference group - play a key role in shaping individual decisions. Organizations are increasingly using information about descriptive norms to nudge positive behavior change. When characterizing peer decisions, a standard approach in the literature is to focus on average behavior. In this paper, we argue both theoretically and empirically that not only averages but also the shape of the whole distribution of behavior can play a crucial role in how people react to descriptive norms. Using a representative sample of the U.S. population, we experimentally investigate how individuals react to strategic environments that are characterized by different distributions of behavior, focusing on the distinction between tight (i.e., characterized by low behavioral variance), loose (i.e., characterized by high behavioral variance), and polarized (i.e., characterized by u-shaped behavior) environments. We find that individuals indeed strongly respond to differences in the variance and shape of the descriptive norm they are facing: loose norms generate greater behavioral variance and polarization generates polarized responses. In polarized environments, most individuals prefer extreme actions -- which expose them to considerable strategic risk -- to intermediate actions that minimize such risk. Furthermore, in polarized and loose environments, personal traits and values play a larger role in determining actual behavior. This provides important insights into how individuals navigate environments that contain strategic uncertainty.
AUG 8 12:30 PM - 2:00 PM PDT Lunch
AUG 8 2:00 PM - 2:30 PM PDT
Empathy, Motivated Reasoning, And Redistribution
Presented by: Tingyan Jia (Stanford University)
I investigate both theoretically and experimentally the economics of empathy and its implications for redistribution. I first define empathy as an accurate simulation of how one would feel if they were in another’s position, distinguishing it from altruism.I propose a novel mechanism by which personal experience affects distributional motives through empathy: wealthy individuals have selfish motivation not to be empathetic towards the poor in order to justify less redistribution; in addition, more varied personal experience of consumption constrains such motivated reasoning, therefore increasing empathy and redistribution. I provide a test of the mechanism in a laboratory setting. I create exogenous variation in experiences and manipulate the timing of information to identify the role of motivated reasoning for subjects with different experiences. I find strong support for the validity of the mechanism: subjects with uniform experience are more susceptible to self-serving motivated reasoning in both their empathy beliefs and redistribution choices.
AUG 8 2:30 PM - 3:00 PM PDT
CEO Social Preferences and Layoffs
Presented by: Marius Guenzel (The Wharton School)
Co-author(s): Clint Hamilton (University of California, Berkeley), and Ulrike Malmendier (University of California, Berkeley)
We study whether CEO social preferences influence firm decision-making with respect to employees, using a new dataset on layoff announcements by U.S. public firms. We first document sizable frictions in firms’ layoff decisions: after exogenous CEO changes, new CEOs make more, and shareholder value-increasing, layoffs. Consistent with a mechanism of social preferences arising through social interactions, CEOs become more reluctant to make layoffs over their tenure as they form more connections inside the firm. This effect is amplified for “difficult-to-implement” layoffs during recessions, near company headquarters, and during the holiday season. Finally, we document a personal cost of firing for CEOs in the form of accelerated long-run mortality.
AUG 8 3:00 PM - 3:30 PM PDT
Understanding Markets with Socially Responsible Consumers
Presented by: Botond Koszegi (Central European University)
Co-author(s): Marc Kaufmann (Central European University)
Many consumers care about climate change and other broad externalities. We model and analyze the market behavior of such “socially responsible consumers,” derive properties of the resulting competitive equilibria, and study the effectiveness of different policies. In violation of price taking, a vanishingly small consumer cares about her impact on the behavior of the rest of the market to a non-vanishing extent. That impact on others endogenously dampens the consumer’s direct effect on the externality, undermining responsible behavior. Dampening implies that even if all consumers value the externality like the social planner, they mitigate too little in any equilibrium, and may coordinate on the worst of multiple equilibria. To motivate consumers to lower the externality in a closed economy, a unit tax is superior to a cap-and-trade system, but there are policies that are better than a tax. Furthermore, under trade with a large or very polluting partner, a cap is better than a tax. When there are two products that are perfect substitutes in consumption but generate different externalities, there is always an equilibrium in which the products have the same price and consumers are indifferent between them. Under conditions we identify, this selfish equilibrium is the unique equilibrium. In a selfish equilibrium, a cap and a unit tax on the dirty product can achieve the same outcomes. In non-selfish equilibria, a proportional subsidy on the clean product dominates both a unit tax and a cap.
AUG 8 3:30 PM - 4:00 PM PDT Break
AUG 8 4:00 PM - 4:30 PM PDT
Complexity and Time
Presented by: Benjamin Enke (Harvard University)
Co-author(s): Thomas Graeber (Harvard University) and Ryan Oprea (University of California, Santa Barbara)
We provide experimental evidence that core intertemporal choice anomalies – including extreme short-run impatience, structural estimates of present bias, hyperbolicity and transitivity violations – are driven by complexity rather than time or risk preferences. First, all anomalies also arise in structurally similar atemporal deci-sion problems involving valuation of iteratively discounted (but immediately paid) rewards. These computational errors are strongly predictive of intertemporal decisions. Second, intertemporal choice anomalies are highly correlated with indices of complexity responses including cognitive uncertainty and choice inconsistency. We show that model misspecification resulting from ignoring behavioral responses to complexity severely inflates structural estimates of present bias.
AUG 8 4:30 PM - 5:00 PM PDT
Cognitive Imprecision and Stake-Dependent Risk Attitudes
Presented by: Michael Woodford (Columbia University)
Co-author(s): Ziang Li (Princeton University) and Mel Win Khaw (Microsoft)
In an experiment that elicits subjects' willingness to pay (WTP) for the outcome of a lottery, we confirm the fourfold pattern of risk attitudes described by Kahneman and Tversky. In addition, we document a systematic effect of stake sizes on the magnitude and sign of the relative risk premium, holding fixed both the probability that a lottery pays off and the sign of its payoff (gain vs. loss). We further show that in our data, there is a log-linear relationship between the monetary payoff of the lottery and WTP, conditional on the probability of the payoff and its sign. We account quantitatively for this relationship, and the way in which it varies with both the probability and sign of the lottery payoff, in a model in which all departures from risk-neutral bidding are attributed to an optimal adaptation of bidding behavior to the presence of cognitive noise. Moreover, the cognitive noise required by our hypothesis is consistent with patterns of bias and variability in judgments about numerical magnitudes and probabilities that have been observed in other contexts.
AUG 8 5:30 PM - 7:30 PM PDT Dinner
Wednesday, August 9, 2023 9:00 AM - 9:30 AM PDT Check-in & Breakfast
AUG 9 9:30 AM - 10:00 AM PDT
Paternalistic Discrimination
Presented by: Nina Caroline Buchmann (Stanford University)
Co-author(s): Carl Meyer (Stanford University) and Colin D. Sullivan (Purdue University)
Women in Bangladesh struggle to access the labor market in general and male-dominated occupations in particular, despite recent progress in education and training. We use a two-sided field experiment to identify paternalistic discrimination: the preferential hiring of male workers to protect female workers from jobs perceived as harmful or difficult. We observe real application and hiring decisions for a night-shift job in Bangladesh and experimentally vary employers’ and candidates’ perceptions of the danger of the job. Improvements to worker safety increase both the supply of and demand for female labor, leading to a compounding increase in female workers. In a behavioral labor model, we demonstrate how other-regarding preferences affect hiring and wages in equilibrium, and we complement the experimental results with survey data to i) analyze the effect of paternalistic discrimination on horizontal and vertical gender segregation in different industries, ii) estimate the degree to which paternalistic preferences restrict women’s labor potential and work readiness, and iii) identify policies that can increase women’s employment across different industries in Bangladesh.
AUG 9 10:00 AM - 10:30 AM PDT
A Memory Model of Belief Formation
Presented by: Maxim Bakhtin (Stanford University)
Co-author(s): Muriel Niederle (Stanford University) and Markus M. Mobius (Microsoft Research)
We model a rational individual who forms beliefs on demand by retrieving observations from the memory database. While she can retrieve data only randomly, she has access to an index that divides the data into two parts, for example, women and men. We show that three effects — importance, variability, and rarity — determine which group is retrieved more under the optimal strategy. Hence although the agent uses Bayes rule to form beliefs, she is biased towards her prior among groups she rationally retrieves fewer data points from. We show that the optimal use of the index leads to rational beliefs that are best described as persistent stereotypes.
AUG 9 10:30 AM - 11:00 AM PDT
Selective Memory Equilibrium
Presented by: Drew Fudenberg (Massachusetts Institute of Technology)
Co-author(s): Giacomo Lanzani (Massachusetts Institute of Technology) and Philipp Strack (Yale University)
We study agents who are more likely to remember some experiences than others, but update beliefs as if the experiences they remember are the only ones that occurred. If the agent’s behavior converges, their limit strategy is a selective memory equilibrium. We illustrate how selective memory equilibrium can be used to understand the long-run effects of several well-documented memory biases. We then extend our analysis to cases where the expected number of recalled experiences is bounded and experiences that are recalled once are more likely to be recalled again. Here we characterize the long-run action frequencies that can arise.
AUG 9 11:00 AM - 11:30 AM PDT Break
AUG 9 11:30 AM - 12:00 PM PDT
Context-dependent Perceptions and Decision Making
Presented by: Keyu Wu (University of Zürich)
All choices are based on information about the available options. A large body of research documents, however, that the same information is often perceived and evaluated differently depending on the prevailing context. Moreover, seemingly identical contextual information, such as previously seen products or job applicants, have been shown to exert opposing influences on perceptions of the same information about a “target” product or job applicant. Inspired by insights from neuroscience and psychophysics, I propose a unifying framework that can parsimoniously reconcile the seemingly contradictory influences of contextual information. This framework generates a novel set of predictions for how properties of the contextual information and the target, such as the perceived uncertainty in both and the perceived discrepancy between them, can be manipulated to affect perceptions and decisions. Because of the generality of perceptual regularities, the framework yields testable implications for a wide range of decision domains, such as the perceived attractiveness of products and services, the evaluation of job applicants, the perceived acceptability of wages, or the perceived trustworthiness of politicians. In addition, based on an experiment on risky investment decisions, I document how decisions can be changed as predicted by the framework through appropriately manipulating several properties of tthe context and the target.
AUG 9
12:00 PM - 12:30 PM PDT
When Do “Nudges” Increase Welfare?
Presented by: Dmitry Taubinsky (University of California, Berkeley)
Co-author(s): Hunt Allcott (Stanford University), Daniel Cohen (Northwestern University), and William Morrison (University of California, Berkeley)
Policymakers are increasingly interested in non-standard policy instruments (NPIs), or “nudges,” such as simplified information disclosure and warning labels. We characterize the welfare effects of NPIs using public finance sufficient statistic approaches, allowing for endogenous prices, market power, and optimal or suboptimal taxes. While many empirical evaluations have focused on whether NPIs increase ostensibly beneficial behaviors on average, we show that this can be a poor guide to welfare. Welfare also depends on whether the NPI reduces the variance of distortions from heterogenous biases and externalities, and the average effect becomes irrelevant with zero pass-through or optimal taxes. We apply our framework to randomized experiments evaluating automotive fuel economy labels and sugary drink health labels. In both experiments, the labels increase ostensibly beneficial behaviors but also may decrease welfare in our model, because they increase the variance of distortions.
AUG 9 12:30 PM - 2:00 PM PDT Lunch
AUG 9 2:00 PM - 2:30 PM PDT
Communicating with Anecdotes
Presented by: Nicole Immorlica (Microsoft Research)
Co-author(s): Nika Haghtalab (University of California, Berkeley), Brendan Lucier (Microsoft Research), Markus Mobius (Microsoft Research), and Divyarthi Mohan (Tel Aviv University)
We study a communication game between a sender and receiver where the sender has access to a set of informative signals about a state of the world. The sender chooses one of her signals and communicates it to the receiver. We call this an “anecdote.” The receiver takes an action. The state of the world and the receiver action are payoff relevant for both the sender and receiver. The sender and receiver are also influenced by a personal preference so that, fixing the state of the world, their preferred receiver action differs. We characterize perfect Bayesian equilibria of this game. The sender faces a temptation to persuade: she is tempted to select a more biased anecdote to influence the receiver’s action. Anecdotes are still informative to the receiver (who will debias at equilibrium) but the attempt to persuade comes at the cost of precision. This gives rise to “informational homophily” where the receiver prefers to listen to like minded senders because they provide higher-precision signals. Furthermore, this leads to a cost of informedness – fixing the personal preferences of the sender, the receiver may prefer a less-informed sender to a more-informed one for certain anecdote distributions.
AUG 9 2:30 PM - 3:00 PM PDT
Complexity, Communication and Misrepresentation
Presented by: Junya Zhou (Purdue University)
Co-author(s): Collin Raymond (Cornell University)
We investigate how increasing the complexity of the message space, in the presence of limited memory, can reduce misrepresentation in strategic communication. We enrich a standard cheap talk game so that senders must communicate not just a payoff-relevant state, but also payoff-irrelevant attributes correlated with the state. We show that: i) increasing the set of attributes that may need to be reported (i.e., the complexity of the game) improves the amount of information transmitted in equilibrium, ii) too much of an increase in complexity leads to a reversal of those gains, iii) limited memory on the part of players, as well as the relative complexity faced by senders and receivers, drives these changes, and iv) individuals experience cognitive costs when dealing with complex environments that they are willing to pay to avoid. Our findings demonstrate that the reporting of redundant information may induce equilibria that feature improved outcomes compared to simpler, more direct reporting systems, and point out the importance of complexity when trying to induce truthful information revelation.
AUG 9 3:00 PM - 3:30 PM PDT
Sequential Cursed Equilibrium
Presented by: Shengwu Li (Harvard University)
Co-author(s): Shani Cohen (Harvard University)
Cursed equilibrium posits that players in a Bayesian game neglect the relationship between their opponent’s actions and their opponent’s type (Eyster and Rabin, 2005). Sequential cursed equilibrium generalizes this idea to extensive games, including those with endogenous private information. It predicts that players neglect the information content of hypothetical events, but make correct inferences from observed events—as is consistent with data from experiments on hypothetical thinking.
AUG 9 3:30 PM - 4:00 PM PDT Break
AUG 9 4:00 PM - 4:30 PM PDT
Evaluating the Evidence of Daily Income Targeting with Experimental and Observational Data
Presented by: Alec Brandon (Johns Hopkins University)
Co-author(s): Colin F. Camerer (California Institute of Technology), John A. List (University of Chicago), Ian Muir (Lyft, Inc.), and Jenny Wang (Massachusetts Institute of Technology)
We evaluate the evidence of daily income targeting by designing and analyzing a field experiment that randomly assigns financial windfalls across thousands of rideshare drivers. Over the year leading up to our windfall experiment, our sample replicates the observational finding that the faster a driver accumulates daily income the earlier they conclude their workdays. However, we find that our windfall treatment, which increases daily income by more than thirty percent, has no detectable effect on the labor supply of our sample. This null effect is estimated precisely enough to reject the effects predicted by the prior evidence and our replications. Heterogeneity analyses also fail to detect a statistically significant effect of the treatment windfall. Revisiting our replications, we find that a more complete measure of daily income and more flexible controls causes higher levels of daily income to no longer coincide with the early conclusion of workdays. The precision of our experimentally estimated nulls and the sensitivity of our replications to alternative specifications call into question much of the evidence of daily income targeting and provide guidance for future research.
AUG 9 4:30 PM - 5:00 PM PDT
Willingness to Accept, Willingness to Pay, and Loss Aversion
Presented by: Erik Snowberg (University of Utah)
Co-author(s): Colin Camerer (California Institute of Technology), Pietro Ortoleva (Princeton University), Mark Dean (Columbia University), and Jonathan Chapman (University of Bologna)
We use four incentivized representative surveys to study the endowment effect for lotteries in 4,000 U.S. adults. We replicate the standard finding of an endowment effect—the divergence between Willingness to Accept (WTA) and Willingness to Pay (WTP), but document three new findings. First, we find little evidence that the endowment effect is related to loss aversion for risky prospects, counter to predictions of popular theories in economics. Second, WTA and WTP not only diverge, but are, at best, weakly correlated. Third, WTA and WTP strongly relate to other aspects of risk preferences. The structure of these behaviors points to different theories of the endowment effect.
AUG 9 5:00 PM - 7:00 PM PDT Dinner
Here's the conference announcement from Marseille:
From matchings to markets. A tale of Mathematics, Economics and Computer Science. Des matchings aux marchés. Une histoire de mathématiques. 11 – 15 December 2023, at the CIRM center in Marseille, France.
"This conference aims at gathering researchers from the fields of mathematics, computer science and economics (broadly defined) sharing common interests in the study of matching problems and the design of their markets. The presentations can cover a wide variety of topics and methods: specific matching markets, general models, theory, empirical analysis. . . etc"
Nick Arnosti (University of Minnesota)
Michal Feldman (Tel Aviv University)
Alfred Galichon (Science Po & New York University)
Michael Jordan (University of Stanford)
Claire Mathieu (CNRS – Collège France)
Nick Arnosti (University of Minnesota)
Julien Combe (CREST & École Polytechnique)
Claire Mathieu (CNRS – Paris)
Vianney Perchet (ENSAE & Criteo AI lab)
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