nep-exp New Economics Papers
on Experimental Economics
Issue of 2021‒07‒19
eighteen papers chosen by

  1. The Roots of Cooperation By Zvonimir Basic; Parampreet Christopher Bindra; Daniela Glätzle-Rützler; Angelo Romano; Matthias Sutter; Claudia Zoller
  2. Learning versus Unlearning: An Experiment on Retractions By Duarte Gon\c{c}alves; Jonathan Libgober; Jack Willis
  3. Effects of incentive framing on performance and effort: evidence from a medically framed experiment By Lagarde, Mylène; Blaauw, Duane
  4. Countering Misinformation on Social Media Through Educational Interventions: Evidence from a Randomized Experiment in Pakistan By Ayesha Ali; Ihsan Ayyub Qazi
  5. Limited Self-knowledge and Survey Response Behavior By Armin Falk; Thomas Neuber; Philipp Strack
  6. Does Saving Cause Borrowing? By Paolina C. Medina; Michaela Pagel
  7. Non-Bayesian updating in a social learning experiment By Roberta De Filippis; Antonio Guarino; Philippe Jehiel; Toru Kitagawa
  8. Decreasing Incomes Increase Selfishness By Nickolas Gagnon; Riccardo D. Saulle; Henrik W. Zaunbrecher
  9. Healthy, nudged, and wise: Experimental evidence on the role of cost reminders in healthy decision-making By Adnan M. S. Fakir; Tushar Bharati
  10. Coordination and the poor maintenance trap: an experiment on public infrastructure in India By Alex Armand; Britta Augsburg; Antonella Bancalari
  11. Fostering the adoption of robo-advisors: A 3-weeks online stock-trading experiment By Alexia Gaudeul; Caterina Giannetti
  12. Framing and Social Information Nudges at Wikipedia By Maximilian Linek; Christian Traxler
  13. Expl(AI)ned: The impact of explainable artificial intelligence on cognitive processes By Bauer, Kevin; von Zahn, Moritz; Hinz, Oliver
  14. Why Do People Demand Rent Control? By Daniel Müller; Elisabeth Gsottbauer
  15. Using Predictive Analytics to Track Students: Evidence from a Seven-College Experiment By Peter Bergman; Elizabeth Kopko; Julio E. Rodriguez
  16. Fighting Climate Change: The Role of Norms, Preferences, and Moral Values By Peter Andre; Teodora Boneva; Felix Chopra; Armin Falk
  17. Institutions, competitiveness and cognitive ability By Syngjoo Choi; Byung-Yeon Kim; Jungmin Lee; Sokbae (Simon) Lee
  18. Employers’ willingness to invest in the training of temporary workers: a discrete choice experiment By Poulissen, Davey; de Grip, Andries; Fouarge, Didier; Künn, Annemarie

  1. By: Zvonimir Basic; Parampreet Christopher Bindra; Daniela Glätzle-Rützler; Angelo Romano; Matthias Sutter; Claudia Zoller
    Abstract: Understanding the roots of human cooperation among strangers is of great importance for solving pressing social dilemmas and maintening public goods in human societies. We study the development of cooperation in 929 young children, aged 3 to 6. In a unified experimental framework, we examine which of three fundamental pillars of human cooperation – direct and indirect reciprocity as well as third-party punishment – emerges earliest as an effective means to increase cooperation in a repeated prisoner’s dilemma game. We find that third-party punishment exhibits a strikingly positive effect on cooperation rates by doubling them in comparison to a control condition. It promotes cooperative behavior even before punishment of defectors is applied. Children also engage in reciprocating others, showing that reciprocity strategies are already prevalent at a very young age. However, direct and indirect reciprocity treatments do not increase overall cooperation rates, as young children fail to anticipate the benefits of reputation building. We also show that the cognitive skills of children and the socioeconomic background of parents play a vital role in the early development of human cooperation.
    Keywords: cooperation, reciprocity, third-party punishment, reputation, children, parents, cognitive abilities, socioeconomic status, prisoner’s dilemma game, experiment
    JEL: C91 C93 D01 D91 H41
    Date: 2021
  2. By: Duarte Gon\c{c}alves; Jonathan Libgober; Jack Willis
    Abstract: Widely discredited ideas nevertheless persist. Why do people fail to ``unlearn''? We study one explanation: beliefs are resistant to retractions (the revoking of earlier information). Our experimental design identifies unlearning -- i.e., updating from retractions -- and enables its comparison with learning from equivalent new information. Across different kinds of retractions -- for instance, those consistent or contradictory with the prior, or those occurring when prior beliefs are either extreme or moderate -- subjects do not fully unlearn from retractions and update less from them than from equivalent new information. This phenomenon is not explained by most of the well-studied violations of Bayesian updating, which yield differing predictions in our design. However, it is consistent with difficulties in conditional reasoning, which have been documented in other domains and circumstances.
    Date: 2021–06
  3. By: Lagarde, Mylène; Blaauw, Duane
    Abstract: We study the effects on performance of incentives framed as gains or losses, as well as the effort channels through which individuals increase performance. We also explore potential spill-over effects on a non-incentivised activity. Subjects participated in a medically framed real-effort task under one of the three contracts, varying the type of performance incentive received: (1) no incentive; (2) incentive framed as a gain; or (3) incentive framed as a loss. We find that performance improved similarly with incentives framed as losses or gains. However, individuals increase performance differently under the two frames: potential losses increase participants’ performance through a greater attention (fewer mistakes), while bonuses increase the time spent on the rewarded activity. There is no spill-over effect, either negative or positive, on the non-incentivised activity. We discuss the meaning and implications of our results for the design of performance contracts.
    Keywords: penalties; rewards; laboratory experiment; prosocial motivation; intrinsic motivation; Springer deal
    JEL: C91 D64 I11
    Date: 2021–06–20
  4. By: Ayesha Ali; Ihsan Ayyub Qazi
    Abstract: Fake news is a growing problem in developing countries with potentially far-reaching consequences. We conduct a randomized experiment in urban Pakistan to evaluate the effectiveness of two educational interventions to counter misinformation among low-digital literacy populations. We do not find a significant effect of video-based general educational messages about misinformation. However, when such messages are augmented with personalized feedback based on individuals' past engagement with fake news, we find an improvement of 0.14 standard deviations in identifying fake news. We also find negative but insignificant effects on identifying true news, driven by female respondents. Our results suggest that educational interventions can enable information discernment but their effectiveness critically depends on how well their features and delivery are customized for the population of interest.
    Date: 2021–07
  5. By: Armin Falk (briq and the University of Bonn); Thomas Neuber (University of Bonn); Philipp Strack (Yale University)
    Abstract: We study response behavior in surveys and show how the explanatory power of self-reports can be improved. First, we develop a choice model of survey response behavior under the assumption that the respondent has imperfect self-knowledge about her individual characteristics. In panel data, the model predicts that the variance in responses for different characteristics increases in self-knowledge and that the variance for a given characteristic over time is non-monotonic in self-knowledge. Importantly, the ratio of these variances identifies an individual's level of self-knowledge, i.e. the latter can be inferred from observed response patterns. Second, we develop a consistent and unbiased estimator for self-knowledge based on the model. Third, we run an experiment to test the model's main predictions in a context where the researcher knows the true underlying characteristics. The data confirm the model's predictions as well as the estimator's validity. Finally, we turn to a large panel data set, estimate individual levels of self-knowledge, and show that accounting for differences in self-knowledge significantly increases the explanatory power of regression models. Using a median split in self-knowledge and regressing risky behaviors on self-reported risk attitudes, we find that the R2 can be multiple times larger for above- than below-median subjects. Similarly, gender differences in risk attitudes are considerably larger when restricting samples to subjects with high self-knowledge. These examples illustrate how using the estimator may improve inference from survey data.
    Keywords: survey research, rational inattention, laboratory experiments, non-cognitive skills, preferences
    JEL: C83 D91 J24
    Date: 2021–07
  6. By: Paolina C. Medina; Michaela Pagel
    Abstract: We study whether savings nudges have the unintended consequence of additional borrowing in high-interest credit. We use data from a pre-registered experiment that encouraged 3.1 million bank customers to save via SMS messages and train a machine learning algorithm to predict individual-level treatment effects. We then focus on individuals who are predicted to save most in response to the intervention and hold credit card debt. We find that these individuals save 5.7% more (61.84 USD per month) but do not change their borrowing: for every additional dollar saved, we can rule out increases of more than two cents in interest expenses.
    JEL: D14 G5
    Date: 2021–06
  7. By: Roberta De Filippis (Institute for Fiscal Studies); Antonio Guarino (Institute for Fiscal Studies); Philippe Jehiel (Institute for Fiscal Studies); Toru Kitagawa (Institute for Fiscal Studies and cemmap and University College London)
    Abstract: In our laboratory experiment, subjects, in sequence, have to predict the value of a good. The second subject in the sequence makes his prediction twice: first (“first belief”), after he observes his predecessor’s prediction; second (“posterior belief”), after he observes his private signal. We find that the second subjects weigh their signal as a Bayesian agent would do when the signal confirms their first belief; they overweight the signal when it contradicts their first belief. This way of updating, incompatible with Bayesianism, can be explained by the Likelihood Ratio Test Updating (LRTU) model, a generalization of the Maximum Likelihood Updating rule. It is at odds with another family of updating, the Full Bayesian Updating. In another experiment, we directly test the LRTU model and find support for it.
    Date: 2020–12–14
  8. By: Nickolas Gagnon; Riccardo D. Saulle; Henrik W. Zaunbrecher
    Abstract: We use a controlled laboratory experiment to study the causal impact of income decreases within a time period on redistribution decisions at the end of that period, in an environment where we keep fixed the sum of incomes over the period. First, we investigate the effect of a negative income trend (intra-personal decrease), which means a decreasing income compared to one's recent past. Second, we investigate the effect ofa negative income trend relative to the income trend of another person (inter-personal decrease). If intra-personal or inter-personal decreases create dissatisfaction for an individual, that person may become more selfish to obtain compensation. We formal-ize both effects in a multi-period model augmenting a standard model of inequality aversion. Overall, conditional on exhibiting sufficiently-strong social preferences, we find that individuals indeed behave more selfishly when they experience decreasing incomes. While many studies examine the effect of income inequality on redistribution decisions, we delve into the history behind one's income to isolate the effect of income changes.
    Date: 2021–07
  9. By: Adnan M. S. Fakir (Business School, The University of Western Australia); Tushar Bharati (Business School, The University of Western Australia)
    Abstract: We evaluate the performance of two behavioral interventions aimed at reducing tobacco consumption in an ultra-poor, rural region of Bangladesh where conventional methods like taxes and warning labels are infeasible. The first intervention asked participants to daily log their tobacco consumption expenditure. The second intervention placed two graphic posters warning participating households of the harmful effects of tobacco consumption on their children and themselves in their sleeping quarters. While both interventions reduced household tobacco consumption expenditure, male participants who logged their expenditure substituted cigarettes with cheaper smokeless tobacco. Risk-averse males who spent relatively more on tobacco responded more to the logbook intervention. Relatively more educated, patient males with children below age five responded better to the poster intervention. The findings suggest extending policies that worked elsewhere to the rural poor in developing countries, where cheaper substitutes are readily available, might be unwise. Instead, policies can leverage something as universal as parents’ concern for their children’s health for promoting healthy decision-making.
    Keywords: tobacco; smoking; healthy decision-making; nudge; field experiment; Bangladesh
    JEL: C93 D9 I1 I12 I18 O1
    Date: 2021
  10. By: Alex Armand; Britta Augsburg; Antonella Bancalari
    Abstract: Poorly maintained public infrastructure is common in poorer countries, but very little is known about the obstacles leading to such equilibrium. By experimentally identifying the impact of incentives for maintenance for both providers and potential users, this paper provides one of the first economic analyses of provider–user dynamics in the presence of local coordination failure. We randomly allocate shared sanitation facilities in two major Indian cities to either a control or two treatments: the first incentivizes maintenance among providers, while the second adds a sensitization campaign about the returns of a well-maintained facility among potential users. Using a wide range of survey, behavioral and objective measurements, we show that maintenance does not favor collective action. The treatments raise the quality of facilities and reduce free riding, but at the cost of user selection, with consequences for public health. While potential users’ willingness to pay and cooperation are unaffected, their demand for public intervention increases. Sensitization raises awareness among potential users, but does not alter their behavior.
    Keywords: Infrastructure, maintenance, free riding, willingness to pay, basic services, water and sanitation, information, health.
    JEL: D12 C39 I15 I18 O18 Q53
    Date: 2021
  11. By: Alexia Gaudeul; Caterina Giannetti
    Abstract: We consider how to increase the take-up of robo-advisors to help investors cope with the disposition effect. In a 3-weeks online stock-trading experiment, participants traded freely in week 1, were assisted by trading algorithms in week 2, and chose whether to be assisted in week 3. Passive algorithms prevented trading, active ones traded according to Bayesian rules. Participants could override algorithm choices in some treatments. Only a minority adopted robo-advisors in week 3, with the worst performers being the least likely to do so. Algorithm aversion was reduced if the algorithm traded actively and could be overridden.
    Keywords: disposition effect, commitment devices, robo-advisors, sophisticated investors, trading, algorithm aversion
    JEL: G11 G40
    Date: 2021–07–01
  12. By: Maximilian Linek; Christian Traxler
    Abstract: We analyze a series of trials that randomly assigned Wikipedia users in Germany to different web banners soliciting donations. The trials varied framing or content of social information about how many other users are donating. Framing a given number of donors in a negative way increased donation rates. Variations in the communicated social information had no detectable effects. The findings are consistent with the results from a survey experiment. In line with donations being strategic substitutes, the survey documents that the negative framing lowers beliefs about others' donations. Varying the social information, in contrast, is ineffective in changing average beliefs.
    Date: 2021–06
  13. By: Bauer, Kevin; von Zahn, Moritz; Hinz, Oliver
    Abstract: This paper explores the interplay of feature-based explainable AI (XAI) techniques, information processing, and human beliefs. Using a novel experimental protocol, we study the impact of providing users with explanations about how an AI system weighs inputted information to produce individual predictions (LIME) on users' weighting of information and beliefs about the task-relevance of information. On the one hand, we find that feature-based explanations cause users to alter their mental weighting of available information according to observed explanations. On the other hand, explanations lead to asymmetric belief adjustments that we interpret as a manifestation of the confirmation bias. Trust in the prediction accuracy plays an important moderating role for XAI-enabled belief adjustments. Our results show that feature-based XAI does not only superficially influence decisions but really change internal cognitive processes, bearing the potential to manipulate human beliefs and reinforce stereotypes. Hence, the current regulatory efforts that aim at enhancing algorithmic transparency may benefit from going hand in hand with measures ensuring the exclusion of sensitive personal information in XAI systems. Overall, our findings put assertions that XAI is the silver bullet solving all of AI systems' (black box) problems into perspective.
    Keywords: XAI,explainable machine learning,Information Processing,Belief updating,algorithmic transparency
    Date: 2021
  14. By: Daniel Müller; Elisabeth Gsottbauer
    Abstract: We conduct a representative survey experiment in Germany to understand why people support inecient policies. In particular, we measure beliefs about and preferences for rent control - a policy that is widely regarded as harmful by experts. To tease out causal mechanisms, we provide randomly selected subsets of participants with empirical estimates about the e ects of rent control on rent prices and housing supply and with information about the consensus among economists against rent control. We find that people update their beliefs and that this leads to lower demand for rent control. Left-wingers update their beliefs more strongly, which reduces the ideological gap in support for rent control by about one-third. Providing information about economists' rejection of this policy leads to the largest reduction in support. However, the main drivers of support for rent control are fairness considerations and profit motives. Our study also highlights the importance of trust in expert advice since treatment effects are consistently larger among those who indicate trust in expert advice. Finally, an obfuscated follow-up survey conducted three weeks later reveals that the effects, both on support for rent control and on beliefs, persist only for those who trust.
    Keywords: beliefs, demand for bad policies, housing supply, rent control, survey experiment, trust in experts
    JEL: H10 H30 H31
    Date: 2021
  15. By: Peter Bergman; Elizabeth Kopko; Julio E. Rodriguez
    Abstract: Tracking is widespread in U.S. education. In post-secondary education alone, at least 71% of colleges use a test to track students. However, there are concerns that the most frequently used college placement exams lack validity and reliability, and unnecessarily place students from under-represented groups into remedial courses. While recent research has shown that tracking can have positive effects on student learning, inaccurate placement has consequences: students face misaligned curricula and must pay tuition for remedial courses that do not bear credits toward graduation. We develop an alternative system to place students that uses predictive analytics to combine multiple measures into a placement instrument. Compared to colleges’ existing placement tests, the algorithm is more predictive of future performance. We then conduct an experiment across seven colleges to evaluate the algorithm’s effects on students. Placement rates into college-level courses increased substantially without reducing pass rates. Adjusting for multiple testing, algorithmic placement generally, though not always, narrowed gaps in college placement rates and remedial course taking across demographic groups. A detailed cost analysis shows that the algorithmic placement system is socially efficient: it saves costs for students while increasing college credits earned, which more than offsets increased costs for colleges. Costs could be reduced with improved data digitization, as opposed to entering data by hand.
    JEL: I0 I20 I24
    Date: 2021–06
  16. By: Peter Andre (University of Bonn); Teodora Boneva (University of Bonn); Felix Chopra (University of Bonn); Armin Falk (briq and the University of Bonn)
    Abstract: We document individual willingness to fight climate change and its behavioral determinants in a large representative sample of US adults. Willingness to fight climate change - as measured through an incentivized donation decision - is highly heterogeneous across the population. Individual beliefs about social norms, economic preferences such as patience and altruism, as well as universal moral values positively predict climate preferences. Moreover, we document systematic misperceptions of prevalent social norms. Respondents vastly underestimate the prevalence of climate- friendly behaviors and norms among their fellow citizens. Providing respondents with correct information causally raises individual willingness to fight climate change as well as individual support for climate policies. The effects are strongest for individuals who are skeptical about the existence and threat of global warming.
    Keywords: climate change, climate behavior, climate policies, social norms, economic preferences, moral values, beliefs, survey experiments
    JEL: D64 D91 Q51
    Date: 2021–07
  17. By: Syngjoo Choi (Institute for Fiscal Studies); Byung-Yeon Kim (Institute for Fiscal Studies); Jungmin Lee (Institute for Fiscal Studies and University of Arkansas); Sokbae (Simon) Lee (Institute for Fiscal Studies and Columbia University and IFS)
    Abstract: We investigate whether growing up in a socialist country affects the development of competitiveness by comparing three Korean groups in South Korea, born and raised in three countries with distinct institutional environments: South Korea, North Korea, and China. We examine the effect of home country experiences on competitiveness using laboratory experiments. Results show that North Korean refugees are signi?cantly less competitive than South Koreans or Korean-Chinese immigrants. Ultimately, we ?nd that the lower cognitive ability of North Koreans is a crucial determinant for the de?ciency of competitiveness, while we fail to ?nd evidence for direct effects of social-ist institutions. Analysis through the lens of a choice model with probability weighting uncovers the effects of cognitive ability not only on expected performance but also on subject belief about winning and aversion for competition.
    Date: 2020–06–24
  18. By: Poulissen, Davey (RS: GSBE other - not theme-related research, ROA / Health, skills and inequality); de Grip, Andries (ROA / Health, skills and inequality, RS: GSBE Theme Learning and Work, RS: SBE - MACIMIDE); Fouarge, Didier (RS: GSBE Theme Learning and Work, RS: GSBE Theme Data-Driven Decision-Making, ROA / Labour market and training); Künn, Annemarie (RS: GSBE Theme Learning and Work, ROA / Labour market and training)
    Abstract: Various studies have shown that temporary workers participate less in training than those on permanent contracts. Human resources practices are considered to be an important explanation for this difference. We develop a theoretical framework for employers’ provision of training that explicitly incorporates the costs and benefits associated with training investments in employees with different types of employment contracts. Our framework not only predicts employers to be less willing to invest in temporary workers due to the shorter time horizon associated with such an investment, but it also provides insights into how this willingness depends on characteristics of the training that are related to the expected costs and benefits of the training investment. A discrete choice experiment is used to empirically test the predictions from our theoretical framework. In line with our theoretical framework, we find that employers are less likely to invest in the training of temporary workers. This particularly holds when temporary workers do not have the prospect of a permanent contract with their current employer. Furthermore, we show that employers’ likelihood of investing in temporary workers indeed depends on aspects related to the costs and benefits of training, that is, a financial contribution to the training costs made by employees, a repayment agreement that applies when workers leave the organisation prematurely, and the transferability of the skills being trained. Our findings can be used to increase employers’ willingness to invest in temporary workers. However, similar effects are observed when looking at employers’ willingness to invest in permanent workers, suggesting that it will be difficult to decrease the gap in employers’ willingness to invest between temporary and permanent workers.
    JEL: J24 J41 J62
    Date: 2021–05–27

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.