Experimental Economics

Date
Mon, Aug 15 2022, 9:00am - Tue, Aug 16 2022, 4:30pm PDT
Location
SIEPR Koret-Taube Conference Center, Room 130
366 Galvez Street, Stanford
[In-person session]
Organized by
  • Christine Exley, Harvard Business School
  • Muriel Niederle, Stanford University
  • Kirby Nielsen, California Institute of Technology
  • Alvin Roth, Stanford University
  • Lise Vesterlund, University of Pittsburgh

This workshop 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 would invite 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.  

In This Session

Monday, August 15, 2022

Aug 15

8:30 am - 9:00 am PDT

Check-In and Breakfast

Aug 15

9:00 am - 9:30 am PDT

Welcome

Aug 15

9:00 am - 9:30 am PDT

Distinguishing Common Ratio Preferences from Common Ratio Effects Using Paired Valuation Task

Presented by: Jason Somerville (Federal Reserve Bank of New York)
Co-author(s): Christina McGranaghan (University of Delaware), Kirby Nielsen (California Institute of Technology), Ted O’Donoghue (Cornell University), and Charles D. Sprenger (California Institute of Technology)

The empirical observation of the common ratio effect (CRE) is often interpreted as evidence of an underlying common ratio preference (CRP). However, prior research has demonstrated that, in the presence of noise, expected utility can generate a CRE in standard paired choice tasks. We expand on that research to describe how the existence or absence of a CRE may reveal little about whether there exists an underlying CRP. We then propose an alternative approach to test for the existence of a CRP using paired valuation tasks that is robust to heterogeneity and noise. We implement this approach in an online experiment with 900 participants, and we find no evidence of a systematic CRP. To reconcile our findings with existing evidence, we present the same participants with standard paired choice tasks, and we demonstrate how appropriately chosen experimental parameters can generate a CRE even in our population that has no systematic CRP.

Aug 15

10:00 am - 10:30 am PDT

Expected But Not Accounted For: The Gender Gap in Confidence

Presented by: Christine Exley (Harvard Business School)

Women consistently believe their performance is lower than equally-performing men in domains such as math and science.  This gender gap in confidence contributes to many gender differences in decisions, such as those relating to competition and negotiation. This gender gap in confidence may also contribute to others (e.g., employers, colleagues, clients and peers) underestimating the performance of women relative to equally-performing men.  For instance, if women underestimate their performance when making self-assessments—and if employers fail to fully account for the gender gap in confidence when reviewing these self-assessments—employers may systematically underestimate the performance of women. Via a series of experiments, this paper finds that, when participants are directly asked about the gender gap in confidence, the gender gap in confidence is expected.  Nonetheless, the same participants fail to accurately account for the gender gap in confidence when reviewing self-assessments. The gender gap in self-assessments causes others—even others who expect the gender gap in confidence—to underestimate the performance of women relative to equally-performing men. 

Aug 15

10:30 am - 11:00 am PDT

Break

Aug 15

11:00 am - 11:30 am PDT

Moral Luck: Mechanisms, Robustness, and Prevalence

Presented by: David Huffman (University of Pittsburgh)
Co-author(s): Armin Falk (Institute for Behavior and Inequality) and Sven Heuser (University of Bonn)

In many types of decisions, individuals can influence the probabilities of good or bad outcomes by their actions, but there is still a role for chance in determining final outcomes. If punishment and rewards are conditioned on such random outcomes, this violates a property of optimal incentives. It has been posited since ancient times that humans do assign punishments and rewards based on factors outside of actors’ control, a tendency called “moral luck.” This paper provides new evidence on the prevalence and robustness of moral luck, and on a key open question of whether moral luck is a preference or a bias. The results are from controlled experiments that can cleanly identify moral luck, but also involve real, consequential moral choices that are a matter of life and death for a third party (a mouse). We find moral luck in punishment, and show that this is at least partly due to a bias. Our findings support a causal chain in which random outcomes lead to biased judgments and incentivized beliefs about the nature of the actor, even though they contain zero information, and this in turn causes punishments to vary with outcomes. We also show that the bias is strong enough to remain in the face of an intervention that encourages deliberation. The bias is prevalent, but not universal, it is unrelated to most demographics, and is present regardless of high or low cognitive ability or education. We also find evidence that actors exhibit internalized moral luck in how they evaluate themselves based on outcomes.

Aug 15

11:30 am - 12:00 pm PDT

Identity and Economic Incentives

Presented by: Kwabena Donkor (Stanford University)
Co-author(s): Eugen Dimant (University of Pennsylvania), Lorenz Goette (National University of Singapore), Michael Kurschilgen (Technical University of Munich), and Maximilian Mueller (UC Berkeley).

This paper theoretically and empirically analyzes how identity (one’s sense of self)affects consumption or investment decisions. We first present a model where identity distorts individuals’ beliefs about uncertain outcomes and imposes psychic costs on identity-incongruent actions. Then, using two large field experiments on soccer betting in the UK and Kenya, we experimentally varied material incentives for betting on matches where soccer fans are neutral or favor one of the teams playing. Finally, we combine the model with respondents’ portfolio allocations across different matches to disentangle biases in investment decisions due to over optimistic beliefs and those due to the psychic costs from identity-incongruent choices. We find that, on average, respondents misallocate 10% of their investment budget because of their over-optimistic beliefs and misallocate an additional 15% of their budget to avoid psychic costs. Our experimental findings also suggest that the impact of debiasing information campaigns that target biased beliefs is limited in contexts with identity concerns than otherwise.

Aug 15

12:00 pm - 1:30 pm PDT

Break – Discussion

Aug 15

1:30 pm - 2:00 pm PDT

Tell Me Now or Tell Me Gradually: The Resolution of Uncertainty in the Value and Probability Domains

Presented by: Kathleen Ngangoue (UCLA Anderson)
Co-author(s): Eungik Lee (New York University) and Andrew Schotter (New York University)

We compare preferences for resolution of uncertainty when the uncertainty is resolved about a probability rather than a value. In various existing frameworks–e.g., Kreps and Porteus (1978)–, preferences over gradual versus one-shot resolution do not depend on whether values or probabilities define the main object of uncertainty. Yet, in our experiment, a large majority of subjects preferred to resolve uncertain values gradually but uncertain probabilities all at once–both with uncertainty defined over gains and losses. Interestingly, we find this discrepancy to be history-dependent: it fades away when subjects learned that the best outcomes were no longer possible. Our analyses suggest that in our experiments subjects put larger decision weights on uncertain values–in particular, high values–relative to uncertain probabilities. We discuss the deviations from the expected utility framework that are needed to explain our data.

Aug 15

2:00 pm - 2:30 pm PDT

Biased Memory and Perceptions of Self-Control

Presented by: Dmitry Taubinsky (UC Berkeley)
Co-author(s): Afras Sial (UC Berkeley) and Justin Sydnor (University of Wisconsin–Madison)

Using data from a field experiment on exercise, we analyze the relationship between imperfect memory and people’s awareness of their limited self-control. We find that people overestimate past gym attendance, and that larger overestimation of past attendance is associated with (i) more overestimation of future attendance, (ii) a lower willingness to pay to motivate higher future gym attendance, and (iii) a smaller gap between goal and forecasted attendance. We organize these facts with a structural model of quasi-hyperbolic discounting and naivete, estimating that people with more biased memories are more naive about their time inconsistency, but not more time-inconsistent.

Aug 15

2:30 pm - 3:00 pm PDT

Break

Aug 15

3:00 pm - 3:15 pm PDT

The Inference-Forecast Gap in Belief Updating

Presented by: Tony Fan (Stanford University)
Co-author(s): Yucheng Liang (Carnegie Mellon University) and Cameron Peng (London School of Economics and Political Science)

Individual forecasts of economic variables show widespread overreaction to recent news, but laboratory experiments on belief updating typically find underinference from new signals. We provide new experimental evidence to connect these two seemingly inconsistent phenomena. Building on a classic experimental paradigm, we study how people make inferences and revise forecasts in the same information environment. Participants underreact to signals when inferring about underlying states, but overreact to signals when revising forecasts about future outcomes. This gap in belief updating is largely driven by the use of different simplifying heuristics for the two tasks. Additional treatments suggest that the choice of heuristics is affected by the similarity between cues in the information environment and the belief-updating question: when forming a posterior belief, participants are more likely to rely on cues that appear similar to the variable elicited by the question.

Aug 15

3:15 pm - 3:30 pm PDT

Understanding and Improving Policymakers' Sensitivity to Program Impact

Presented by: Mattie Toma (Harvard University)
Co-author(s): Elizabeth Bell (Florida State University)

Policymakers routinely make high-stakes decisions of which programs to fund. Assessing the value of a program is difficult and may be affected by bounded rationality. In an experiment with policymakers in the U.S. government, we find that respondents’ valuations of programs are inelastic with respect to the program’s impact. A complementary experiment among a representative sample of the general public reveals even more pronounced inelasticity in a population less familiar with making program funding decisions. We design and test two portable decision aids, one which presents two alternative programs side-by-side rather than in isolation and another which translates total program cost into an annual cost per person impacted. The decision aids increase elasticity by 0.20 on a base of 0.33 among policymakers and by 0.21 on a base of 0.21 among the general public. We provide evidence that cognitive noise—noisy assessments of complex inputs—is a mechanism that can help explain the observed inelasticity of program valuation with respect to impact.

Aug 15

3:30 pm - 3:45 pm PDT

Complexity, Communication and Misrepresentation

Presented by: Junya Zhou (Purdue University)
Co-author(s): Collin Raymond (Purdue University)

We investigate how increasing the complexity of the message space can reduce misrepresentation in strategic communication. We develop a theoretical model that extends the standard cheap talk approach by i) allowing for communication about both a payoff relevant state and non-payoff relevant attributes which are correlated with the state, and ii) supposing that agents are boundedly rational in understanding the relationship between the states and their attributes. We show that although babbling is the only equilibrium for perfectly rational agents, boundedly rational agents induce an equilibrium that features informative messages. We adopt a novel experimental design to test our predictions and explore mechanisms that drive changes in the informativeness of communication. We find that increasing the number of messages that could be sent, while keeping the number of messages sent fixed, can significantly reduce misrepresentation, particularly when the receiver can anticipate what questions the messages are in response to. We find that the informativeness of communication is dependent both on the complexity level and cognitive ability of agents. Our results shed light on why principals in mechanisms may not use a direct mechanisms, but instead use an indirect mechanism which elicits multi-dimensional information even when the additional information seems redundant, as in tax reporting or insurance claims.

Aug 15

3:45 pm - 4:00 pm PDT

Lowering the Playing Field: Discrimination through Contrast Effects

Presented by: Xiaoyue Shan (The Wharton School, University of Pennsylvania)
Co-author(s): Judd B. Kessler (The Wharton School, University of Pennsylvania) and Corinne Low (The Wharton School, University of Pennsylvania)

We document a new source of discrimination in hiring that arises through contrast effects. We analyze data from an incentivized resume rating experiment, where employers evaluate a sequence of randomly generated resumes to be matched with real job seekers. Candidates who follow white men are rated as significantly less desirable than those who follow women or minority candidates. Exploring the mechanisms, we find that employers in our data only display a direct bias in favor of white men when resumes are high-quality, and the contrast effect only arises when the prior resume is a low-quality white man. Our results thus suggest that the contrast effect only arises when employers do not show direct favoritism towards white men in ratings; in these cases, they indirectly favor white men through a contrast effect channel instead. Our findings highlight the power of implicit bias and provide evidence on how it may operate.

Aug 15

4:00 pm - 4:15 pm PDT

To Learn or Not to Learn: Can Temporary Affirmative Action Improve Representation?

Presented by: Neeraja Gupta (University of Pittsburgh)

In absence of policy interventions like affirmative action, employers’ biased beliefs about underrepresented groups may not correct on their own due to less hiring of and subsequent learning about those underrepresented. This paper explores whether temporary affirmative action can improve representation even after the policy is lifted in settings where employers hold biased beliefs about performance. I experimentally elicit employer hiring decisions and beliefs about potential employee performance in two between-subject experimental treatments: a control treatment without affirmative action and a temporary affirmative action treatment. While beliefs and hiring are biased against women in the control condition, I find in the temporary affirmative action treatment that representation improves even after affirmative action is lifted. Exposure substantially increases the likelihood that women are hired even beyond the policy instance. This increase is partially driven by employers gradually learning that their beliefs about women’s performance are biased downward where employers who are most likely to discriminate against women show the greatest reduction in gender bias in beliefs. The results shed new light on using a temporary affirmative action policy to fundamentally break a cycle of underrepresentation by correcting biased beliefs.

Aug 15

4:15 pm - 4:30 pm PDT

Intergenerational Transmission of Education: Internalized Aspirations versus Parent Pressure

Presented by: Maximilian W. Mueller (UC Berkeley)

High school graduates in Germany who lack parents with college experience are40 percentage points less likely to attend college than those with college-educated par-ents, despite the fact that in Germany college is free. This study provides evidence that parental influence explains a significant portion of this socio-economic gap through at least two channels: one, parental pressure and two, the intergenerational transmission of beliefs and preferences. To understand parental influence, I conduct a field experiment with 1,195 students and 819 parents in Germany. Importantly, I experimentally make students’ stated college plans visible to parents. In the first finding, visibility to parents doubles the socio-economic gap in college plans to 27 percentage points. This is mainly driven by a large increase in college plans among students with college-educated parents. To disentangle mechanisms, I collect detailed survey data on students’ and parents’ subjective expectations for various career tracks and estimate a structural model of career choice under uncertainty. Model simulations indicate that 40% ofthe socio-economic gap in college plans is explained by parental pressure and 44% by students internalizing family-specific beliefs.

Aug 15

5:00 pm - 8:00 pm PDT

Dinner at Muriel’s House

Tuesday, August 16, 2022

Aug 16

9:00 am - 9:30 am PDT

Check-In and Breakfast

Aug 16

9:30 am - 10:00 am PDT

Welcome

Aug 16

10:00 am - 10:30 am PDT

Flagging Suspicious Behavior Using Machine Learning Can Improve Human Predictions

Presented by: Marta Serra-Garcia (UC San Diego)
Co-author(s): Uri Gneezy (UC San Diego))

Can machine learning (ML) help people predict behavior in high-stakes prisoner’s dilemmas? We show participants videos from the TV show Golden Balls, in which contestants communicate before choosing whether to cooperate or defect. Participants show limited ability to predict contestants’ behavior; simple ML algorithms provide significantly more accurate predictions. We then flag contestants that ML predicts are highly likely to cooperate or defect. We find that flagging the extreme predictions helps participants improve their predictions. In addition, 54% of participants choose to fully delegate their predictions to the algorithm, improving their predictions as a result.

Aug 16

10:30 am - 11:00 am PDT

An Approach to Testing Reference Points

Presented by: Alex Rees-Jones (University of Pennsylvania)
Co-author(s): Ao Wang (UC Berkeley)

The application of reference-dependent models is often complicated by the modeler's uncertainty regarding the reference point (referent) that agents adopt. We develop a powerful and minimally parametric approach to testing whether decisions could be rationalized by a general reference-dependent model with a specic referent. Our approach builds from the observation that, when both payos and the true referent are randomly varied, a marginal increase in all payos will have an equivalent eect as a marginal decrease in the referent. The observation that this equivalence holds at all payo/referent combinations, when applied to decisions over properly constructed gambles, allows us to generate our test through modications to existing tools for rejecting single-index representations. We assess the performance of this test in a simulation study and nd that it is highly diagnostic even in the comparatively small sample sizes that are common in experimental economics. We then utilize this approach in an online experiment in which we randomly vary the salience of both goal-based and expectationsbased referents. In this experiment, we conrm the common assumption that salient goals could serve as reference points. Illustrating the importance of salience, we reject that either reference point is adopted when it is not salient. Perhaps surprisingly, we reject the adoption of expectations as a reference point even when they are salient.

Aug 16

11:00 am - 11:30 am PDT

Break

Aug 16

11:30 am - 12:00 pm PDT

Free to Fail? Paternalistic Preferences in the United States

Presented by: Bjorn Bartling (University of Zurich)
Co-author(s): Alexander W. Cappelen (NHH Norwegian School of Economics), Henning Hermes (Düsseldorf Institute for Competition Economics), Marit Skivenes (University of Bergen), and Bertil Tungodden (NHH Norwegian School of Economics)

We study paternalistic preferences in two large-scale, incentivized experiments with participants sampled from the general population in the United States. Participants, acting as third-party spectators, decide whether to intervene to prevent another individual, the stakeholder, from making a mistake. We find causal evidence for the nature of the intervention being of great importance for the willingness to intervene; only about a third of the spectators intervene by restricting the stakeholder’s choices set, while a large majority intervene by providing information. In contrast, the source of the stakeholder’s mistake does not have a substantial causal effect on the willingness to intervene. We introduce a theoretical framework which allows us to classify fifty percent of the spectators as libertarian paternalists and to explore the main reasons why people are libertarian paternalists. Our results shed light on attitudes to paternalistic policies in the general population and why the idea of libertarian paternalism has gained strong support in recent years.

Aug 16

12:00 pm - 12:30 pm PDT

Dynamic Coordination in Efficient and Fair outcomes: A Developmental Perspective

Presented by: Isabelle Brocas (University of Southern California)
Co-author(s): Juan D. Carrillo (University of Southern California)

We study in the laboratory the behavior of children and adolescents (ages 7 to 16) in two repeated coordination games, the stag hunt and battle of the sexes. Coordinating on the efficient and fair long run outcome (EFO) requires participants to share intentions and beliefs. This exercise is arguably complex in the battle of the sexes, as it requires taking turns between the two static Nash equilibria, hence coordinating the strategies. By contrast, in the stag hunt it only requires repeating the action that leads to the Pareto efficient outcome, hence coordinating the actions. We obtain four main findings. First, for both games, we show a significant and remarkably stable increase in the ability to coordinate on the EFO with age. Second, the majority of participants in all ages adhere to one of a small number of relatively simple strategies. Third, jointly profitable outcomes are more prevalent in the stag hunt than in the battle of the sexes. Last, behavior improves between the first and second supergame. This evidence suggests that we gradually learn how to share intentions and beliefs, an ability that we train rapidly and export to new interactions, but that is limited by game complexity.

Aug 16

12:30 pm - 2:00 pm PDT

Break – Discussion

Aug 16

2:00 pm - 2:30 pm PDT

A (Dynamic) Investigation of Stereotypes, Belief-updating, and Behavio

Presented by: Katherine Coffman (Harvard Business School)
Co-author(s): Maria Paola Ugalde Araya (Arizona State University) and Basit Zafar (University of Michigan)

Many decisions – such as what educational or career path to pursue – are dynamic in nature, with individuals receiving feedback at one point in time and making decisions later. Using a controlled experiment, with two sessions one week apart, we analyze the dynamic effects of feedback on beliefs about own performance and decision-making across two different domains (verbal skills and math). We find significant gender gaps in beliefs and choices before feedback: men are more optimistic about their performance and more willing to compete than women in both domains, but the gaps are significantly larger in math. Feedback significantly shifts individuals’ beliefs and choices. Despite this, we see substantial persistence of gender gaps over time. This is particularly true among the set of individuals who receive negative feedback. We find that, holding fixed performance and decisions before feedback, women update their beliefs and choices more negatively than men do after bad news. Our results highlight the challenges involved in overcoming gender gaps in dynamic settings.

Aug 16

2:30 pm - 3:00 pm PDT

Discrimination Without Reason: Contrast Effects in Statistical Discrimination

Presented by: Sevgi Yuksel (UC Santa Barbara)
Co-author(s): Ignacio Esponda (UC Santa Barbara) and Ryan Oprea (UC Santa Barbara)

We report experimental evidence that people have difficulty effectively engaging in statistical discrimination, leading to lower accuracy gains from discriminating than a rational model would predict. As a result, discrimination can be significantly reduced without lowering accuracy, simply by improving the way people use information. We show that this inefficiency stems from subjects putting excess weight on their subjective judgements while simultaneously applying crude contrast-driven group-level biases. A series of treatment interventions give us insight into the psychological drivers of these errors and guidance on policies likely to be effective at removing them.

Aug 16

3:00 pm - 3:30 pm PDT

Break

Aug 16

3:30 pm - 4:00 pm PDT

Not Too Early, Not Too Late: Encouraging Engagement in Education

Presented by: Ulrike Malmendier (UC Berkeley)
Co-author(s): Tracy X. Liu (Tsinghua University), Stephanie W.Wang (University of Pittsburg) and Shuhuai Zhang (Tsinghua University)

Declining engagement over time is a central obstacle to achieving long-term goals, especially in education. A common route to addressing the fall-off among students through the course of a semester is to schedule assignments and tests throughout the term. In this field experiment, we study how the timing of a potentially rewarding but cognitively taxing assignment, taking notes and posting them, affects students’ academic behavior and performance. We find that assigning such tasks to low-performing students in the middle of the term, compared to early or late in the semester, improves their performance more, e. g., in terms of higher attendance, homework grades, and exam grades. We argue that, rather than “early intervention,” possibly with the goal of habit formation in studying, or “crunch time intervention,” engagement interventions are most effective if they target the time when students start to fall off because of accumulating frictions and complications in their semester schedule.

Aug 16

4:00 pm - 4:30 pm PDT

Confidence, Self-Selection and Bias in the Aggregate

Presented by: Ryan Oprea (UC Santa Barbara)
Co-author(s): Benjamin Enke (Harvard University) and Thomas Graeber (Harvard Business School,)

Economics experiments have produced widespread evidence that people suffer from a range of cognitive biases. However, unlike experiments, real-world institutions often allow decision makers to self-select out, potentially filtering (or amplifying) the impact of biases on economic aggregates. We study the economic impacts of such self-selection and how they depend on people’s meta- cognitive awareness of their own errors. In a series of online experiments that cover a wide range of classical decision biases, we document large heterogeneity in how objective task performance is related to the intensity of bets in speculative markets, bids for property rights in auctions and contributions to collective decisions. In some tasks, rational subjects are more confident than their biased counterparts and bet, bid and vote more aggressively. As a result, self-selection tends to filter the effect of irrationalities on aggregate quantities. However, in other tasks, confidence and performance are unrelated or even negatively correlated, so that experimental institutions do not filter errors and sometimes even magnify them. As a methodological blueprint, we show that a simple measure of the relative calibration of confidence strongly predicts the degree to which institutional self-selection filters the effect of irrationalities.

Aug 16

5:00 pm - 8:00 pm PDT

Dinner at Landau Courtyard