We elicit social networks among students in an Italian high school either by measuring the complete network in an incentive-compatible way or by using a truncated elicitation of at most five links. We find that truncation undercounts weak links by up to 90% but only moderately undercounts the time spent with strong friends. We use simulations to demonstrate that the measurement error induced by censoring might be particularly significant when studying phenomena such as social learning which are often thought to operate along weak ties. We then discuss how a modified network elicitation protocol might be able to reduce measurement error.

Can informing people of high community support for social distancing encourage them to do more of it? We randomly assigned a treatment correcting individuals’ underestimates of community support for social distancing. In theory, informing people that more neighbors support social distancing than expected encourages free-riding and lowers the perceived benefits from social distancing. At the same time, the treatment induces people to revise their beliefs about the infectiousness of COVID-19 upwards; this perceived infectiousness effect as well as the norm adherence effect increase the perceived benefits from social distancing. We estimate impacts on social distancing, measured using a combination of self- reports and reports of others. While experts surveyed in advance expected the treatment to increase social distancing, we find that its average effect is close to zero and significantly lower than expert predictions.

However, the treatment’s effect is heterogeneous, as predicted by theory: it decreases social distancing where current COVID-19 cases are low (where free-riding dominates), but increases it where cases are high (where the perceived-infectiousness effect dominates). These findings highlight that correcting misperceptions may have heterogeneous effects depending on disease prevalence.

We use a series of experiments to understand whether and how people’s beliefs about their own abilities are biased relative to the Bayesian benchmark and how these beliefs then affect behavior. We find that subjects systematically and substantially overweight positive feedback relative to negative (asymmetry) and also update too little overall (conservatism). These biases are substantially less pronounced in an ego-free control experiment. Updating does retain enough of the structure of Bayes' rule to let us model it coherently in an optimizing framework, in which, interestingly, asymmetry and conservatism emerge as complementary biases. We also find that exogenous changes in beliefs affect subjects’ decisions to enter into a competition and do so similarly for more and less biased subjects, suggesting that people cannot "undo" their biases when the time comes to decide.

Interventions to promote learning are often categorized into supply- and demand-side approaches. In a randomized experiment to promote learning about COVID-19 among Mozambican adults, we study the interaction between a supply and a demand intervention, respectively: teaching via targeted feedback, and providing financial incentives to learners. In theory, teaching and learner-incentives may be substitutes (crowding out one another) or complements (enhancing one another). Experts surveyed in advance predicted a high degree of substitutability between the two treatments. In contrast, we find substantially more complementarity than experts predicted. Combining teaching and incentive treatments raises COVID-19 knowledge test scores by 0.5 standard deviations, though the standalone teaching treatment is the most cost-effective. The complementarity between teaching and incentives persists in the longer run, over nine months post-treatment.

The aim of this Handbook is twofold: to educate and to inspire. It is meant for researchers and graduate students who are interested in taking a data-based and behavioral approach to the study of game theory. Educators and students of economics will find the Handbook useful as a companion book to conventional upper-level game theory textbooks, enabling them to compare and contrast actual behavior with theoretical predictions. Researchers and non-specialists will find valuable examples of laboratory and field experiments that test game theoretic propositions and suggest new ways of modeling strategic behavior. Chapters are organized into several sections; each section concludes with an inspirational chapter, offering suggestions on new directions and cutting-edge topics of research in experimental game theory.

We investigate the stability of measured risk attitudes over time, using a 13-year longitudinal sample of individuals in the National Longitudinal Survey of Youth 1979. We find that an individual's risk aversion changes systematically in response to personal economic circumstances. Risk aversion increases with lengthening spells of employment and time out of labor force, and decreases with lengthening unemployment spells. However, the most important result is that the majority of the variation in risk aversion is due to changes in measured individual tastes over time and not to variation across individuals. These findings that measured risk preferences are endogenous and subject to substantial measurement errors suggest caution in interpreting coefficients in models relying on contemporaneous, one-time measures of risk preferences.

We study the role of ethnicity in experimental labor markets where “employers” determine wages of “workers” who perform a real effort task. This task requires a true skill which we show is not affected by minority status. In some treatments, we provide subtle priming to employers about minority status of workers as commonly depicted on Chinese “Hukou” identification system. We conduct our experiments at two sites located in provinces that differ by their historical shares of ethnic groups in the population. We find that: (1) Han and minority workers are equally productive in both provinces; (2) in the diverse province, there is no difference in the wages between Han and minority workers; (3) in the non-diverse province, minority workers receive 4%-7% lower wages than Han workers.

Social networks can facilitate informal lending and risk-sharing in situations where for-
mal institutions such as banks and insurance companies do not exist. The social collateral approach provides an analytically tractable framework that can be used to analyze a wide range of informal transfers. Moreover, the approach is easily amenable to empirical analysis.

Do corrupt people self select themselves in professions where the scope of corruption is high? We conduct a corruption experiment with private sector job aspirants and aspirants of Indian bureaucracy. The game models embezzlement of resources in which “supervisors” evaluate the performance of “workers” and then pay them. We find that aspirant bureaucrats indulge in more corruption than private sector aspirants but the likelihood of being corrupt is same across two sectors.

Social learning is a rapidly growing field for empirical and theoretical research in economics. We encounter social learning in many economically important phenomena, such as the adoption of new products and technologies or job search in labor markets. We review the existing empirical and theoretical literatures and argue that they have evolved largely independently of each other. This suggests several directions for future research that can help bridge the gap between both literatures. For example, the theory literature has come up with several models of social learning, ranging from na{\"ıve DeGroot models to sophisticated Bayesian models whose assumptions and predictions need to be empirically tested. Alternatively, empiricists have often observed that social learning is more localized than existing theory models assume, and that information can decay along a transmission path. Incorporating these findings into our models might require theorists to look beyond asymptotic convergence in social learning.

We conduct a field experiment in a large real-world social network to examine how subjects expect to be treated by their friends and by strangers who make allocation decisions in modified dictator games. While recipients’ beliefs accurately account for the extent to which friends will choose more generous allocations than strangers (i.e. directed altruism), recipients are not able to anticipate individual differences in the baseline altruism of allocators (measured by giving to an unnamed recipient, which is predictive of generosity towards named recipients). Recipients who are direct friends with the allocator, or even recipients with many common friends, are no more accurate in recognizing intrinsically altruistic allocators. Recipient beliefs are significantly less accurate than the predictions of an econometrician who knows the allocator’s demographic characteristics and social distance, suggesting recipients do not have information on unobservable characteristics of the allocator.

We conduct online field experiments in large real-world social networks in order to decompose prosocial giving into three components: (1) baseline altruism toward randomly selected strangers, (2) directed altruism that favors friends over random strangers, and (3) giving motivated by the prospect of future interaction. Directed altruism increases giving to friends by 52 percent relative to random strangers, while future interaction effects increase giving by an additional 24 percent when giving is socially efficient. This finding suggests that future interaction affects giving through a repeated game mechanism where agents can be rewarded for granting efficiency-enhancing favors. We also find that subjects with higher baseline altruism have friends with higher baseline altruism.

This paper builds a theory of trust based on informal contract enforcement in social networks. In our model, network connections between individuals can be used as social collateral to secure informal borrowing. We de…ne network-based trust as the highest amount one agent can borrow from another agent, and derive a reduced-form expression for this quantity which we then use in three applications. (1) We predict that dense networks generate bonding social capital that allows transacting valuable assets, while loose networks create bridging social capital that improves access to cheap favors like information. (2) For job recommendation networks, we show that strong ties between employers and trusted recommenders reduce asymmetric information about the qualityof job candidates. (3) Using data from Peru, we show empirically that network-based trust predicts informal borrowing, and we structurally estimate and test our model.

Program to visualize/calculate trust flow

This classroom experiment introduces students to the concept of double marginalization, i.e. the exercise of market power at successive vertical layers in a supply chain. By taking on roles of firms, students determine how the mark-ups are set at each successive production stage. They learn that final retail prices tend to be higher than if the firms were vertically integrated. Students compare the welfare implications of two potential solutions to the double marginalization problem: acquisition and franchise fees. The experiment also can stimulate a discussion of two-part tariffs, transfer pricing, contracting, and the Coase theorem. Veconlab website

Are beautiful people better negotiators? I present evidence from a simple bargaining game where players can listen to pre-recorded “speeches” and see the pictures of other players. I find that physically attractive players receive a greater share of the surplus if the partner can both listen to their speech and view their picture. This effect is strongest when the listening partner is female. These results suggest new directions for experimental and empirical research on the role of non-resume characteristics on labor market outcomes and give new perspectives to practitioners in negotiations involving extreme power imbalance.