nep-exp New Economics Papers
on Experimental Economics
Issue of 2021‒02‒01
thirty papers chosen by

  1. Machine Learning and Perceived Age Stereotypes in Job Ads: Evidence from an Experiment By Ian Burn; Daniel Firoozi; Daniel Ladd; David Neumark
  2. Fines and progressive ideology promote social distancing By Edoardo Gallo; Darija Halatova; Alastair Langtry
  3. Nudges to Increase Completion of Welfare Applications: Experimental Evidence from Michigan By Christopher J. O'Leary; Dallas Oberlee; Gabrielle Pepin
  4. Promoting Platform Takeoff and Self-Fulfilling Expectations: Field Experimental Evidence By Kevin Boudreau
  5. Gender Differences in Performance under Competition: Is There a Stereotype Threat Shadow? By Diogo Geraldes; Arno Riedl; Martin Strobel
  6. Inducing perspective-taking for prosocial behaviour in natural resource management By Ortiz-Riomalo, Juan Felipe; Koessler, Ann-Kathrin; Engel, Stefanie
  7. Designing the Market for Job Vacancies: A Trust Experiment with Employment Centers Staff By Guglielmo Briscese; Andreas Leibbrandt
  8. Incentives for Conformity and Anticonformity By Fabian Dvorak; Urs Fischbacher; Katrin Schmelz
  9. The Endogenous Formation of Common Pool Resource Coalitions By Carlos A. Chávez; James J. Murphy; Felipe J. Quezada; John K. Stranlund
  10. Can technology improve the classroom experience in primary education? An African experiment on a worldwide program By Joana Cardim; Teresa Molina-Millán; Pedro C. Vicente
  11. Exploring Narrative Economics: An Agent-Based-Modeling Platform that Integrates Automated Traders with Opinion Dynamics By Kenneth Lomas; Dave Cliff
  12. Weighting-Based Treatment Effect Estimation via Distribution Learning By Dongcheng Zhang; Kunpeng Zhang
  13. Adaptive Correspondence Experiments By Hadar Avivi; Patrick M. Kline; Evan Rose; Christopher R. Walters
  14. When Bonuses Backfire: Evidence from the Workplace By Jakob Alfitian; Dirk Sliwka; Timo Vogelsang
  15. Job Search and Hiring with Two-sided Limited Information about Workseekers’ Skills By Eliana Carranza; Robert Garlick; Kate Orkin; Neil Rankin
  17. When Distrust Goes Viral: Causal Effects of Covid-19 on European Political Attitudes By Gianmarco Daniele; Andrea F.M. Mfartinangeli; Francesco Passarelli; Willem Sas; Lisa Windsteiger
  18. Narratives on COVID-19 and Policy Opinions: A Survey Experiment By Armenak Antinyan; Thomas Bassetti; Luca Corazzini; Filippo Pavesi
  19. Migration and Informal Insurance By Costas Meghir; Ahmed Mushfiq Mobarak; Ahmed Corina Mommaerts; Ahmed Melanie Morten
  20. Parental Paternalism and Patience By Lukas Kiessling; Shyamal Chowdhury; Hannah Schildberg-Hörisch; Matthias Sutter
  21. Algorithms for Learning Graphs in Financial Markets By Jos\'e Vin\'icius de Miranda Cardoso; Jiaxi Ying; Daniel Perez Palomar
  22. On Information and the Demand for Insurance By Gandhi, Amit; Samek, Anya; Serrano-Padia, Ricardo
  23. Limited tenure concessions for collective goods By Nicolas Quérou; Agnes Tomini; Christopher Costello
  24. Whose Advice Counts More – Man or Machine? An Experimental Investigation of AI-based Advice Utilization By Mesbah, Neda; Tauchert, Christoph; Buxmann, Peter
  25. Collusion in Quality-Segmented Markets By Iwan Bos; Marco A. Marini
  26. Using Nonexperimental Methods to Address Noncompliance By Daniel Litwok
  27. A Theory of Updating Ambiguous Information By Rui Tang
  28. Biased Beliefs and Entry into Scientific Careers By Ina Ganguli; Patrick Gaule; Danijela Vuletic Cugalj
  29. Using social recognition to address the gender difference in volunteering for low-promotability tasks By Ritwik Banerjee; Priyoma Mustafi
  30. The Value of Time in the United States: Estimates from Nationwide Natural Field Experiments By Ariel Goldszmidt; John A. List; Robert D. Metcalfe; Ian Muir; V. Kerry Smith; Jenny Wang

  1. By: Ian Burn; Daniel Firoozi; Daniel Ladd; David Neumark
    Abstract: We explore whether ageist stereotypes in job ads are detectable using machine learning methods measuring the linguistic similarity of job-ad language to ageist stereotypes identified by industrial psychologists. We then conduct an experiment to evaluate whether this language is perceived as biased against older workers. We find that language classified by the machine learning algorithm as closely related to ageist stereotypes is perceived as ageist by experimental subjects. The scores assigned to the language related to ageist stereotypes are larger when responses are incentivized by rewarding participants for guessing how other respondents rated the language. These methods could potentially help enforce anti-discrimination laws by using job ads to predict or identify employers more likely to be engaging in age discrimination.
    JEL: J14 J71 K31
    Date: 2021–01
  2. By: Edoardo Gallo; Darija Halatova; Alastair Langtry
    Abstract: Social distancing has been one of the core public policy measures used to mitigate the economic and health impacts of the COVID-19 pandemic. Such widespread adoption of social distancing measures is wholly unprecedented, and governments have implemented a variety of policies to encourage compliance. These typically rely on financial penalties (fines) and/or informational messages (nudges). There is, however, a lack of evidence on the impact of these policies. We examine the effectiveness of fines and nudges in promoting social distancing in a web-based interactive experiment. The study involves a nearrepresentative sample of 400 participants from the US population, and it was conducted in May 2020 at the height of the pandemic. Fines significantly promote distancing, but nudges only have a marginal impact. Political ideology also has a causal impact -- progressives are more likely to practice distancing, and are marginally more responsive to fines. Further, individuals do more social distancing when they know they may be a superspreader. Our results highlight the crucial role of web-based interactive experiments in informing governments on the causal impact of policies at a time when lab and/or field-based experimental research is not feasible.
    Date: 2020–12
  3. By: Christopher J. O'Leary (W.E. Upjohn Institute for Employment Research); Dallas Oberlee (W.E. Upjohn Institute for Employment Research); Gabrielle Pepin (W.E. Upjohn Institute for Employment Research)
    Abstract: The Temporary Assistance for Needy Families (TANF) program provides cash assistance to very-low-income families with children. Application procedures to receive TANF benefits, however, often involve substantial transaction costs likely to reduce take-up. We estimate, through a randomized controlled trial design, the effects of a detailed telephone-call reminder to increase TANF application completion in southwest Michigan, where applicants must visit a regional public employment office at least four times to be eligible for benefits. We do not find that personalizing reminder calls increased participation in the initial appointment at the public employment office. However, conditional on attending the initial session, applicants who received reminder calls before additional appointments were more likely to complete all application requirements, compared to those who did not receive reminders. Evidence suggests that reminder calls increase attendance at public employment office appointments but that personalizing such calls has limited impact.
    Keywords: Temporary Assistance for Needy Families, nudge, welfare-to-work, randomized controlled trial, application costs
    JEL: D90 I38 H75 H83
    Date: 2020–11
  4. By: Kevin Boudreau
    Abstract: The theoretical literature on platforms and network effects predicts that the initial growth and takeoff of a platform crucially depends on the market’s expectations of the future installed base. This paper tests this claim, reporting on a field experiment in which invitations to join a newly launched platform were sent to 16,349 individuals and included randomized statements regarding the future expected installed base (along with disclosures of the current installed base). I find evidence consistent with subjective expectations playing a crucial role in shaping early adoption and platform takeoff. Statements regarding expectations of the future installed base more significantly affected adoption than did disclosures of the current installed base. Statements of larger numbers of expected users caused more adoption than did smaller numbers. Statements of a smaller installed base of users (whether current or expected) led to lower demand than did stating nothing at all. The effect of stating subjective expectations by the platform became insignificant once the current installed base grew larger. The response of adoption to expected numbers of users reveals patterns consistent with the long-theorized chicken-and-egg problem and self-fulfilling expectations. The findings have significant implications for the effective promotion, marketing, and “evangelism” of new platform ventures.
    JEL: C93 D16 D26 D43 L1 L13 L86
    Date: 2021–01
  5. By: Diogo Geraldes; Arno Riedl; Martin Strobel
    Abstract: The gender gap in income and leadership positions in many domains of our society is an undisputed pervasive phenomenon. One explanation for the disadvantaged position of women put forward in the economic and psychology literature is the weaker response of women to competitive incentives. Despite the large amount of literature trying to explain this fact, the precise mechanisms behind the gender difference in competitive responsiveness are still not fully uncovered. In this paper, we use laboratory experiments to study the potential role of stereotype threat on the response of men and women to competitive incentives in mixed-gender competition. We use a real effort math task to induce an implicit stereotype threat against women in one treatment. In additional treatments we, respectively, reinforce this stereotype threat and induce a stereotype threat against men. In contrast to much of the literature we do not observe that women are less competitive than men, neither when there is an implicit nor when there is an explicit stereotype threat against women. We attribute this to two factors which differentiates our experiment from previous ones. We control, first, for inter-individual performance differences using a within-subject design, and, second, for risk differences between non-competitive and competitive environments by making the former risky. We do find an adverse stereotype threat effect on the performance of men when there is an explicit stereotype threat against them. In that case any positive performance effect of competition is nullified by the stereotype threat. Overall, our results indicate that a stereotype threat has negative competitive performance effects only if there is information contradicting an existing stereotype. This suggests that the appropriate intervention to prevent the adverse effect of stereotype threat in performance is to avoid any information referring to the stereotype.
    Keywords: competitiveness, gender gaps, stereotype threat, experiment
    JEL: C91 D01 J16
    Date: 2020
  6. By: Ortiz-Riomalo, Juan Felipe; Koessler, Ann-Kathrin; Engel, Stefanie
    Abstract: Natural resource management often involves social dilemmas. Institutional and behavioural economics have shown that other-regarding preferences and pro-social behaviour can help overcome such dilemmas. Interventions that induce resource users to consider a perspective broader than their own may then be useful to promote and strengthen pro-social behaviour. Such interventions are often applied in participatory resource management approaches. To the best of our knowledge, nonetheless, no previous study has systematically assessed the effect of induced perspective-taking on resource users’ prosocial behaviour in a controlled manner. In this study, we do so in the context of watershed management. We conducted a lab-in-the-field experiment with downstream farmers in a Peruvian watershed. In the experiment, farmers were induced to imagine the perspective of upstream farmers before deciding on a donation that can help these upstream farmers improve their wellbeing without compromising the water supply downstream. We find that induced perspective-taking increases prosocial behaviour. This effect cannot be explained by the additional information on the social and ecological characteristics of the watershed received during the perspective-taking experience, nor by an ‘experimenter demand effect’. Rather the effect of the perspective-taking intervention is likely to work via an activation or strengthening of other-regarding preferences. Our results contribute to the study of pro-social behaviour and the ways it could be induced by interventions targeting other-regarding preferences.
    Keywords: perspective-taking,prosocial behaviour,other-regarding preferences,social dilemmas,natural resource management,environmental policy,framed field experiment
    JEL: D01 D64 D91 C93 Q25 Q57
    Date: 2021
  7. By: Guglielmo Briscese; Andreas Leibbrandt
    Abstract: Trust is a key factor for the well-functioning of labor markets. We experimentally study the behavior of staff at competing employment agencies who serve as matchmakers between labor supply and demand. Employment agents can collaborate by sharing vacancies and job seekers at the risk of the other agent approaching the employer to place their own job seekers. In a framed field experiment with actual employment agents we test mechanisms to increase collaboration. We find that financial incentives to collaborate increase vacancy sharing but also increase the likelihood of the other provider approaching the employer to place their own job seekers. We also find that social incentives can backfire and decrease vacancy sharing unless employment agents have a perfect reputation. However, social incentives have a positive effect in increasing cooperative behavior. We discuss the implications for the design of incentives to increase trust in competitive markets like that of employment agencies.
    Keywords: trust game, labor market, framed field experiment
    JEL: D90 C92 J48
    Date: 2020
  8. By: Fabian Dvorak; Urs Fischbacher; Katrin Schmelz
    Abstract: We study how social evaluation affects conformity and anticonformity in theory and in an experiment. In theory, we show that negative social evaluation, i.e., potential punishment, creates incentives for conformity. Positive social evaluation, i.e., potential reward, creates incentives for anticonformity. In a laboratory experiment, we investigate the effect of these incentives in three domains: judgments in the knowledge domain, subjective arts preferences, and decisions in a creativity-related task. We rely on a new design in which we compare choices under social influence with predictions based on choices without social influence using transitivity. The experimental results confirm the theoretical predictions.
    Keywords: conformity, creativity, social learning, institutions
    Date: 2020
  9. By: Carlos A. Chávez (Universidad de Talca); James J. Murphy (Department of Economics, University of Alaska Anchorage); Felipe J. Quezada (University of Massachusetts Amherst); John K. Stranlund (University of Massachusetts Amherst)
    Abstract: We develop a theoretical model of endogenous CPR coalition formation in which the resource is co-defended with costly monitoring by coalition members and sanctions for encroachment imposed by the government. We demonstrate that CPR coalitions can form even when monitoring is so costly that coalition members choose not to monitor for encroachment, but the coalitions will be relatively small. Larger coalitions will form if monitoring costs are low enough to yield effective deterrence. We tested the results of the model using lab-in-field experiments with fishers who were members of Chile’s territorial use rights fisheries (TURFs) and in the lab with Chilean university students. We find that fishers frequently formed CPR coalitions, even when they could not deter outsider poaching. Fishers usually formed the grand coalition when the monitoring cost was low, but they formed smaller coalitions when monitoring was more costly. Fishers invested in monitoring frequently and these investments reduced poaching. Relative to open access, when coalitions formed, total harvest effort was curtailed and earnings for coalition members generally increased. Students formed coalitions less frequently, these coalitions tended to be small, and they infrequently invested in monitoring, even when it was profitable to do so. Consequently, student coalition member earnings were not better off on average than under open access.
    Keywords: experimental economics, Common pool resources; enforcement; field experiments; poaching; territorial use rights fisheries; social dilemma; fisheries management; development economics; co-enforcement; coalition formation; encroachment
    JEL: C72 C90 C93 D70 K42 Q22 Q28 Q56 H40
    Date: 2021–01
  10. By: Joana Cardim; Teresa Molina-Millán; Pedro C. Vicente
    Abstract: Primary school coverage has been increasing in most developing countries. Yet, it has not been accompanied by significant improvements in learning indicators. We implemented a randomized experiment in Angola around the introduction of ProFuturo, a worldwide educational program. The program includes a Computer-assisted Learning (CAL) software directed at improving the regular classroom experience. One year after the program started, we find higher familiarity with technology. Teachers miss fewer days of classes and implement better teaching practices. Students become more interested in learning and pro-social. Finally, the program improves students’ test scores in the most popular subject in the CAL platform.
    Keywords: Primary education, computer-assisted learning, CAL, field experiment, RCT, Africa, Angola
    JEL: O12 I21
    Date: 2021
  11. By: Kenneth Lomas; Dave Cliff
    Abstract: In seeking to explain aspects of real-world economies that defy easy understanding when analysed via conventional means, Nobel Laureate Robert Shiller has since 2017 introduced and developed the idea of Narrative Economics, where observable economic factors such as the dynamics of prices in asset markets are explained largely as a consequence of the narratives (i.e., the stories) heard, told, and believed by participants in those markets. Shiller argues that otherwise irrational and difficult-to-explain behaviors, such as investors participating in highly volatile cryptocurrency markets, are best explained and understood in narrative terms: people invest because they believe, because they have a heartfelt opinions, about the future prospects of the asset, and they tell to themselves and others stories (narratives) about those beliefs and opinions. In this paper we describe what is, to the best of our knowledge, the first ever agent-based modelling platform that allows for the study of issues in narrative economics. We have created this by integrating and synthesizing research in two previously separate fields: opinion dynamics (OD), and agent-based computational economics (ACE) in the form of minimally-intelligent trader-agents operating in accurately modelled financial markets. We show here for the first time how long-established models in OD and in ACE can be brought together to enable the experimental study of issues in narrative economics, and we present initial results from our system. The program-code for our simulation platform has been released as freely-available open-source software on GitHub, to enable other researchers to replicate and extend our work
    Date: 2020–12
  12. By: Dongcheng Zhang; Kunpeng Zhang
    Abstract: Existing weighting methods for treatment effect estimation are often built upon the idea of propensity scores or covariate balance. They usually impose strong assumptions on treatment assignment or outcome model to obtain unbiased estimation, such as linearity or specific functional forms, which easily leads to the major drawback of model mis-specification. In this paper, we aim to alleviate these issues by developing a distribution learning-based weighting method. We first learn the true underlying distribution of covariates conditioned on treatment assignment, then leverage the ratio of covariates' density in the treatment group to that of the control group as the weight for estimating treatment effects. Specifically, we propose to approximate the distribution of covariates in both treatment and control groups through invertible transformations via change of variables. To demonstrate the superiority, robustness, and generalizability of our method, we conduct extensive experiments using synthetic and real data. From the experiment results, we find that our method for estimating average treatment effect on treated (ATT) with observational data outperforms several cutting-edge weighting-only benchmarking methods, and it maintains its advantage under a doubly-robust estimation framework that combines weighting with some advanced outcome modeling methods.
    Date: 2020–12
  13. By: Hadar Avivi; Patrick M. Kline; Evan Rose; Christopher R. Walters
    Abstract: Correspondence experiments probe for discrimination by manipulating employer perceptions of applicant characteristics. We consider the gains from dynamically adapting the number and characteristics of fictitious applications to the sequence of employer responses received so far. Calibrating the employer callback process to data from a recent correspondence experiment by Nunley et al. (2015), we find it is possible to cut the number of applications required to detect a fixed number of discriminatory jobs roughly in half relative to the static benchmark design that sends the same number and mix of applications to all jobs. These gains are achieved primarily from abandoning jobs with very low callback probabilities and those that demonstrate a willingness to call black applicants.
    JEL: C9 J18 J71
    Date: 2021–01
  14. By: Jakob Alfitian; Dirk Sliwka; Timo Vogelsang
    Abstract: Monetary incentives are widely used to align employees' actions with the objectives of employers. We conduct a field experiment in a retail chain to evaluate whether an attendance bonus reduces employee absenteeism. The RCT assigned 346 apprentices for one year to either a monetary attendance bonus, a time-off bonus or a control group. We find that neither form of the bonus reduced absenteeism, but the monetary bonus increased absence by around 45%. This backfiring effect is persistent and driven by the most recently hired apprentices. Survey results reveal that the bonus shifted the perception of absenteeism as acceptable behavior.
    Date: 2021
  15. By: Eliana Carranza (World Bank); Robert Garlick (Duke University); Kate Orkin (University of Oxford); Neil Rankin (University of Stellenbosch)
    Abstract: We present field experimental evidence that limited information about workseekers’ skills distorts both firm and workseeker behavior. Assessing workseekers’ skills, giving workseekers their assessment results, and helping them to credibly share the results with firms increases workseekers’ employment and earnings. It also aligns their beliefs and search strategies more closely with their skills. Giving assessment results only to workseekers has similar effects on beliefs and search, but smaller effects on employment and earnings. Giving assessment results only to firms increases callbacks. These patterns are consistent with two-sided information frictions, a new finding that can inform design of information-provision mechanisms.
    Keywords: Job search, hiring, two-sided limited information, worker assessment, field experiment, employment, earnings
    JEL: J23 J24 J31 J41 O15 O17
    Date: 2020–06
  16. By: DeCaro, Daniel
    Abstract: This codebook provides concepts and methodologies for coding and quantifying the content and function of communication in group social dilemma experiments, specifically with a social and ecological component (e.g., common pool resource dilemma). The content that is coded pertains to such categories as small talk, humor, information exchange (e.g., ecological, social, institutional), enforcement (e.g., praise, warnings, threats), decision making (e.g., proposals, choosing). Functional categories pertain to key functions needed for group members to govern the dilemma: e.g., develop agreements, make group decisions (e.g., democratic decision making), resolve conflicts, and enforce compliance. This codebook provides guidance for metrics to associate coded communication content and function to observed cooperation.
    Date: 2021–01–13
  17. By: Gianmarco Daniele; Andrea F.M. Mfartinangeli; Francesco Passarelli; Willem Sas; Lisa Windsteiger
    Abstract: To investigate how Covid-19 is shaping the way Europeans think about institutions, we conducted a large online survey experiment during the first wave of the epidemic (June). With a randomised survey ow we varied whether respondents are given Covid-related treatment questions first, before answering the outcome questions. We find that the crisis has severely undermined trust in politicians, the media, the EU and social welfare spending financed by taxes. This is mainly due to economic insecurity, but also because of health concerns. We also uncover a rallying effect around (scientific) expertise combined with populist policies losing ground.
    Keywords: Covid-19, institutional trust, political attitudes, online survey experiment, European Union, welfare, taxation, populism
    JEL: D72 H51 H53 H55 O52 P52
    Date: 2020
  18. By: Armenak Antinyan (Wenlan School of Business, Zhongnan University of Economics and Law, China); Thomas Bassetti (Department of Economics and Management “Marco Fanno”, University of Padua, Italy); Luca Corazzini (Department of Economics and VERA, University Of Venice Cà Foscari); Filippo Pavesi (School of Economics and Management, LIUC (Carlo Cattaneo University), Italy)
    Abstract: Narratives impact people’s opinions on relevant policy issues, and their political context may influence these effects. Indeed, some specific contexts may be more easily swayed by certain stories that provide explanations for current social and economic phenomena. We explore this issue by considering the ongoing COVID-19 pandemic as a natural experiment that creates the ideal conditions for existing narratives to gain momentum and spread. In particular, we run a survey experiment in the US by exposing subjects to two media-based popular explanations on the causes of the COVID- 19 pandemic. The Lab narrative attributes the upstart of the pandemic to human error and scientific misconduct in a laboratory in China, while the Nature narrative describes the genetic and biological causes of the virus. We find evidence that subjects’ beliefs on the origins of the disease are influenced by the narrative they are presented with. Moreover, the Lab narrative leads subjects living in Republican leaning states to express less favorable opinions about trade openness and the relevance of climate change relative to those living in Democratic leaning states. Thus, our findings provide support for the idea that recalling stories that are part of larger narratives can lead to divergence of opinions on crucial issues leading to an increase in policy polarization. Finally, we explore the underlying features of social contexts associated with US states’ political orientation, that moderate the impact of narratives on policy opinions.
    Keywords: Economic Narratives, COVID-19, Policy Issues, Survey Experiment
    JEL: D72 D83 C83 C99 P16 Z18
    Date: 2021
  19. By: Costas Meghir (Cowles Foundation, Yale University, NBER, IZA, CEPR, and Institute for Fiscal Studies); Ahmed Mushfiq Mobarak (Cowles Foundation, Yale University); Ahmed Corina Mommaerts (University of Wisconsin – Madison); Ahmed Melanie Morten (Stanford University and NBER)
    Abstract: We document that an experimental intervention o?ering transport subsidies for poor rural households to migrate seasonally in Bangladesh improved risk sharing. A theoretical model of endogenous migration and risk sharing shows that the e?ect of subsidizing migration depends on the underlying economic environment. If migration is risky, a temporary subsidy can induce an improvement in risk sharing and enable pro?table migration. We estimate the model and ?nd that the migration experiment increased welfare by 12.9%. Counterfactual analysis suggests that a permanent, rather than temporary, decline in migration costs in the same environment would result in a reduction in risk sharing.
    Keywords: Informal Insurance, Migration, Bangladesh, RCT
    JEL: D12 D91 D52 O12 R23
    Date: 2019–07
  20. By: Lukas Kiessling (Max Planck Institute for Research on Collective Goods); Shyamal Chowdhury (University of Sydney and IZA); Hannah Schildberg-Hörisch (Institute for Competition Economics (DICE) and IZA); Matthias Sutter (Max Planck Institute for Research on Collective Goods, University of Cologne, University of Innsbruck, IZA, and CESifo)
    Abstract: We study whether and how parents interfere paternalistically in their children’s intertemporal decision-making. Based on experiments with over 2,000 members of 610 families, we find that parents anticipate their children’s present bias and aim to mitigate it. Using a novel method to measure parental interference, we show that more than half of all parents are willing to pay money to override their children’s choices. Parental interference predicts more intensive parenting styles and a lower intergenerational transmission of patience. The latter is driven by interfering parents not transmitting their own present bias, but molding their children’s preferences towards more time-consistent choices.
    Keywords: Parental paternalism, Time preferences, Convex time budgets, Present bias, Intergenerational transmission, Parenting styles, Experiment
    JEL: C90 D1 D91 D64 J13 J24 O12
    Date: 2021–01
  21. By: Jos\'e Vin\'icius de Miranda Cardoso; Jiaxi Ying; Daniel Perez Palomar
    Abstract: In the past two decades, the field of applied finance has tremendously benefited from graph theory. As a result, novel methods ranging from asset network estimation to hierarchical asset selection and portfolio allocation are now part of practitioners' toolboxes. In this paper, we investigate the fundamental problem of learning undirected graphical models under Laplacian structural constraints from the point of view of financial market times series data. In particular, we present natural justifications, supported by empirical evidence, for the usage of the Laplacian matrix as a model for the precision matrix of financial assets, while also establishing a direct link that reveals how Laplacian constraints are coupled to meaningful physical interpretations related to the market index factor and to conditional correlations between stocks. Those interpretations lead to a set of guidelines that practitioners should be aware of when estimating graphs in financial markets. In addition, we design numerical algorithms based on the alternating direction method of multipliers to learn undirected, weighted graphs that take into account stylized facts that are intrinsic to financial data such as heavy tails and modularity. We illustrate how to leverage the learned graphs into practical scenarios such as stock time series clustering and foreign exchange network estimation. The proposed graph learning algorithms outperform the state-of-the-art methods in an extensive set of practical experiments. Furthermore, we obtain theoretical and empirical convergence results for the proposed algorithms. Along with the developed methodologies for graph learning in financial markets, we release an R package, called fingraph, accommodating the code and data to obtain all the experimental results.
    Date: 2020–12
  22. By: Gandhi, Amit (University of Pennsylvania & Microsoft); Samek, Anya (University of California, San Diego); Serrano-Padia, Ricardo (School of Economics)
    Abstract: Technological advances in the insurance industry mean that insurers may be better informed about underlying risks than consumers. We evaluate the impact of these information frictions by combining demand elicitation surveys with insurance claim data. We find an ‘information premium’ - i.e., consumers are willing to pay more for insurance when risks are uncertain. Importantly, we find that the information premium is negatively correlated with risk aversion. This leads to a selection effect: individuals who purchase insurance are not necessarily the most risk averse. The resulting misallocation of insurance can lead to large welfare losses and biased risk preference estimates.
    Keywords: risk; uncertainty; ambiguity; insurance; compound risk; demand analysis; information disclosure; incentivized survey; laboratory experiment; frictions
    JEL: D12 D14 D81 G22 J33
    Date: 2021–01–11
  23. By: Nicolas Quérou (CEE-M - Centre d'Economie de l'Environnement - Montpellier - FRE2010 - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Agnes Tomini (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique - AMU - Aix Marseille Université); Christopher Costello (UCSB - University of California [Santa Barbara] - University of California)
    Abstract: This paper proposes and analyzes the consequences of a widely-used, but little-studied institution, limited-tenure concessions, for governing club goods and common-pool resources. We first show in a simple repeated game setting that such a system can incentivize socially-efficient provision of club goods. We then extend the model to account for spatially-connected resources, an arbitrary number of heterogeneous agents, and natural resource dynamics, and show that the basic ability of limited-tenure concessions to incentivize the first best private provision is preserved in this rich setting that is more representative of natural resources such as fish, water, and game. The duration of tenure and the dispersal of the resource then play pivotal roles in whether this limited-duration concession achieves the socially optimal outcome. Finally, in a setting with costly monitoring, we discuss the features of a concession contract that ensure first-best behavior, but at least cost to the implementing agency.
    Keywords: Concessions,club goods,cooperation,natural resources,spatial externalities,dynamic games
    Date: 2020–10–19
  24. By: Mesbah, Neda; Tauchert, Christoph; Buxmann, Peter
    Date: 2021–01–05
  25. By: Iwan Bos (Maastricht University); Marco A. Marini (University of Rome La Sapienza and CREI)
    Abstract: We appreciate the comments of and discussions with David Collie, Luis Corchón, Jean Gabszewicz, Andrey Minaev, Riccardo Saulle, Attila Tasnádi, Jacques-François Thisse and participants at the Oligo Workshop in Nottingham. All opinions and errors are ours alone.
    Keywords: Partial Cartels, Price Collusion, Market Segmentation, Vertical Di¤erentiation
    JEL: D4 L1
    Date: 2020–11
  26. By: Daniel Litwok (Abt Associates)
    Abstract: The analysis compares estimates of the incremental impact for those who receive HPOG with a program enhancement to the standard HPOG program. The experimental benchmark for the incremental impact comes from two-stage least squares with random assignment as an instrumental variable for enhancement take-up. Then, ignoring the randomly assigned conditions, the analysis estimates the counterfactual for those who “take up” the enhancement using ordinary least squares and inverse propensity weighting. The analysis also tests whether adding information that is only available due to the experiment—who complied with their randomization status and who did not—improves the nonexperimental estimates. The analysis compares these estimates using statistical tests recommended by the within-study comparison literature.
    Keywords: Treatment effects, Experimental methods, Nonexperimental methods, Within-study comparison
    JEL: C31 J24
    Date: 2020–04
  27. By: Rui Tang
    Abstract: We introduce a new updating rule, the conditional maximum likelihood rule (CML) for updating ambiguous information. The CML formula replaces the likelihood term in Bayes' rule with the maximal likelihood of the given signal conditional on the state. We show that CML satisfies a new axiom, increased sensitivity after updating, while other updating rules do not. With CML, a decision maker's posterior is unaffected by the order in which independent signals arrive. CML also accommodates recent experimental findings on updating signals of unknown accuracy and has simple predictions on learning with such signals. We show that an information designer can almost achieve her maximal payoff with a suitable ambiguous information structure whenever the agent updates according to CML.
    Date: 2020–12
  28. By: Ina Ganguli (University of Massachusetts - Amherst); Patrick Gaule (University of Bath); Danijela Vuletic Cugalj (CERGE-EI)
    Abstract: We investigate whether excessively optimistic beliefs play a role in the persistent demand for doctoral and postdoctoral training in science. We elicit the beliefs and career preferences of doctoral students through a novel survey and randomize the provision of structured information on the true state of the academic market and information through role models on nonacademic careers. One year later, both treatments lead students to update their beliefs about the academic market and impact career preferences. However, we do not find an effect on actual career outcomes two years postintervention.
    Keywords: higher education, information, biased beliefs, career preferences, science
    JEL: I23 D80 D84 J24
    Date: 2020–09
  29. By: Ritwik Banerjee; Priyoma Mustafi
    Abstract: Research shows that women volunteer significantly more for tasks that people prefer others to complete. Such tasks carry little monetary incentives because of their very nature. We use a modified version of the volunteer's dilemma game to examine if non-monetary interventions, particularly, social recognition can be used to change the gender norms associated with such tasks. We design three treatments, where a) a volunteer receives positive social recognition, b) a non-volunteer receives negative social recognition, and c) a volunteer receives positive, but a non-volunteer receives negative social recognition. Our results indicate that competition for social recognition increases the overall likelihood that someone in a group has volunteered. Positive social recognition closes the gender gap observed in the baseline treatment, so does the combination of positive and negative social recognition. Our results, consistent with the prior literature on gender differences in competition, suggest that public recognition of volunteering can change the default gender norms in organizations and increase efficiency at the same time.
    Date: 2020–12
  30. By: Ariel Goldszmidt; John A. List; Robert D. Metcalfe; Ian Muir; V. Kerry Smith; Jenny Wang
    Abstract: The value of time determines relative prices of goods and services, investments, productivity, economic growth, and measurements of income inequality. Economists in the 1960s began to focus on the value of non-work time, pioneering a deep literature exploring the optimal allocation and value of time. By leveraging key features of these classic time allocation theories, we use a novel approach to estimate the value of time (VOT) via two large-scale natural field experiments with the ridesharing company Lyft. We use random variation in both wait times and prices to estimate a consumer's VOT with a data set of more than 14 million observations across consumers in U.S. cities. We find that the VOT is roughly $19 per hour (or 75% (100%) of the after-tax mean (median) wage rate) and varies predictably with choice circumstances correlated with the opportunity cost of wait time. Our VOT estimate is larger than what is currently used by the U.S. Government, suggesting that society is under-valuing time improvements and subsequently under-investing public resources in time-saving infrastructure projects and technologies.
    JEL: D0 D1 R4
    Date: 2020–12

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.