Research

PEER-REVIEWED PUBLICATIONS:

WHY DON'T STRUGGLING STUDENTS DO THEIR HOMEWORK? DISENTANGLING MOTIVATION AND STUDY PRODUCTIVITY AS DRIVERS OF ADOLESCENT HUMAN CAPITAL FORMATION (2025): Accepted at Journal of Political Economy, with Christopher Cotton, John List, Joseph Price, and Sutanuka Roy

ONLINE SUPPLEMENTAL APPENDIX

RESOLVING FAILED BANKS: UNCERTAINTY, MULTIPLE BIDDING, AND AUCTION DESIGN (2024): Review of Economic Studies, vol. 91, May, pp. 1201-1242, with Jason Allen, Robert Clark, and Eric Richert

*Winner of the Public Utility Research Prize for best paper in regulatory economics, 2020, 18th Annual IIOC Conference

AFFIRMATIVE ACTION AND HUMAN CAPITAL INVESTMENT: EVIDENCE FROM A RANDOMIZED FIELD EXPERIMENT (2022): Journal of Labor Economics, vol. 40(1), pp. 157-185, with Christopher Cotton and Joseph Price

*Previous versions of this paper have circulated under the title, "Incentive Provision in Investment Contests: Theory and Evidence"

HOW EFFICIENT ARE DECENTRALIZED AUCTION PLATFORMS? (2021): Review of Economic Studies, vol. 88 (1), pp. 91-125, with Joern Boehnke and Aaron Bodoh-Creed.

COLLEGE ASSIGNMENT AS A LARGE CONTEST (2018): Journal of Economic Theory, vol. 175, May, pp. 88-126, with Aaron Bodoh-Creed.

IDENTIFICATION AND ESTIMATION OF A BIDDING MODEL FOR ELECTRONIC AUCTIONS (2017): Quantitative Economics, vol. 8 (2), July, pp. 505-551, with Timothy P. Hubbard and Harry J. Paarsch.

REPLACING SAMPLE TRIMMING WITH BOUNDARY CORRECTION IN NONPARAMETRIC ESTIMATION OF FIRST-PRICE AUCTIONS (2015): Journal of Applied Econometrics, vol. 30 (5), August, pp. 739-762, with Timothy P. Hubbard.

STRUCTURAL ECONOMETRIC METHODS IN AUCTIONS: A GUIDE TO THE LITERATURE (2012): Journal of Econometric Methods, vol. 1, August, pp. 67-106, with Timothy P. Hubbard and Yigit Saglam

ON THE PRICING RULE IN ELECTRONIC AUCTIONS (2010): International Journal of Industrial Organization, vol. 28, July, pp.423-578

*Winner of the 2011 Paul Geroski Award for being one of the two best paper s to appear in IJIO during 2010.

WORKING PAPERS:

STRESS TESTING STRUCTURAL MODELS OF UNOBSERVED HETEROGENEITY: ROBUST INFERENCE ON OPTIMAL NONLINEAR PRICING (current version: October 2024): under review, with Aaron Bodoh-Creed, John List, Ian Muir, and Gregory Sun

ABSTRACT: We propose methods for empirical market design in adverse-selection settings where identification based on exogenous price variation is hampered by multi-dimensional unobserved heterogeneity. We derive sharp bounds on counterfactual demand under out-of-sample prices. Bounds arise because plausible DGPs must respect the Law of Demand and observed shift(s) in aggregate demand following an exogenous price change(s). Our bounds use data available in many settings, including our application to rideshare demand. They enable viable, welfare-improving, nonlinear pricing design while achieving robustness against worst-case deviations from baseline model assumptions. Our framework provides novel insights for optimal experimental design of pricing RCTs. We also show that our CDF bounds can be re-interpreted as bounds on reduced-form treatment-effect heterogeneity.ONLINE SUPPLEMENTAL APPENDIX

BANKING FRAGILITY AND RESOLUTION COSTS (current version: May 2024): R&R at American Economic Review, with Jason Allen, Robert Clark, and Eric Richert

ABSTRACT: We develop a framework for stress-testing the FDIC’s ability to resolve bank-failure waves that allows macroeconomic conditions to endogenously influence costs by altering the composition of failures, eligible bidders, and actual bidders. Our entry model captures the fact that there are many eligible bidders, but only a subset seriously consider bidding, as in many procurement settings. We validate the model by forecasting resolution costs for recent failures whose FDIC-estimated costs are known. We apply it to predict costs of contemporary hypothetical crises (monetary tightening, commercial real estate), and to understand the competition/stability tradeoff of local-selling constraints.

THE RETURNS TO COLLEGE(S): ESTIMATING VALUE ADDED AND MATCH EFFECTS IN HIGHER EDUCATION (current version: August 2021): with Jack Mountjoy.

ABSTRACT: Students who attend different colleges in the U.S. end up with vastly different economic outcomes. We study the role of relative value-added across colleges within student choice sets in producing these outcome disparities. Linking administrative high school records, college applications, admissions decisions, enrollment spells, degree completions, and quarterly earnings spanning the Texas population, we identify relative college value-added by comparing the outcomes of students who apply to and are admitted by the same set of institutions, as this approach strikingly balances observable student potential across college treatments and renders our extensive set of covariates irrelevant as controls. Methodologically, we develop a framework for identifying and interpreting value-added under varying assumptions about match effects and sorting gains, generalizing the constant treatment effects assumption typically employed in the value-added literature. Empirically, we estimate a relatively tight, though non-degenerate, distribution of relative value-added across the wide diversity of Texas public universities. Selectivity poorly predicts value-added within student choice sets: a fleeting selectivity earnings premium fades to zero after a few years in the labor market, and more selective colleges tend to have lower value-added on STEM degree completion. Non-peer college inputs like instructional spending more strongly predict value-added, especially conditional on selectivity. Educational impacts predict labor market impacts: colleges with larger earnings value-added also tend to be colleges that boost persistence, BA completion, and STEM degrees along the way. Finally, we probe the potential for (mis)match effects by allowing each college's relative value-added to vary flexibly by student characteristics. At first glance, Black students appear to face small negative returns to choosing more selective colleges, but this pattern of modest "mismatch" is entirely driven by the availability of two large historically Black universities with low selectivity but above-average value-added. Across the non-HBCUs, Black students face similar returns to selectivity, and indistinguishable value-added schedules more generally, compared to their peers from other backgrounds.ONLINE SUPPLEMENTAL APPENDIX

TOWARD AN UNDERSTANDING OF CORPORATE SOCIAL RESPONSIBILITY: THEORY AND FIELD EXPERIMENTAL EVIDENCE (current version: January 2022): with Daniel Hedblom and John List

ABSTRACT: We develop theory and a tightly-linked field experiment to identify and estimate a model of worker selection on (multi-dimensional) unobservables in the presence of variation of pecuniary incentives (wage offer) and non-pecuniary incentives (CSR status of the firm). Our research design meticulously but noninvasively tracks the real-time activities of 170 data-entry workers performing paid productive tasks. The resulting data allow us to separately identify both selection and treatment effects of CSR and money in motivating effort and high-quality output. We find strong evidence that when a firm advertises its CSR pursuits during employee recruitment, it attracts substantially more applicants, and the overall applicant pool is comprised of candidates that (on average) produce output more quickly, produce higher-quality work requiring fewer costly quality controls, and have more valuable time. Our observed effects are roughly comparable to the impacts of a 36% wage increase. We also find that when a firm recruits workers with a $15/hr wage offer (as compared to a lower offer of $11/hr), its production costs may actually decrease due to selection of individuals who are more productive and produce higher quality work requiring fewer costly quality-control measures. We also find an economically important complementarity between CSR and wages. Beyond exploring the supply-side impact of CSR, our research design serves as a framework for causal inference on pecuniary and non-pecuniary incentives in the workplace more generally.ONLINE SUPPLEMENTAL APPENDIX

PRE-COLLEGE HUMAN CAPITAL INVESTMENT AND AFFIRMATIVE ACTION: A STRUCTURAL POLICY ANALYSIS OF US COLLEGE ADMISSIONS (current version: August 2024): under review, with Aaron Bodoh-Creed

ABSTRACT: We estimate a model of a college admissions contest with affirmative action (AA) where students compete for seats at better schools by choosing pre-college human capital (HC) investments. We are able to identify and flexibly estimate the contest structure in the college admissions market, including the tendency for AA to affect admissions profiles on different segments of the US college quality spectrum. We identify the effects of college quality, pre-college HC, and unobserved student characteristics on post-college income using a control function derived using methods from the auctions literature. College quality is the primary income determinant, while unobserved student characteristics play a secondary role. Pre-college HC affects income indirectly through its influence on graduation probability and enrollment. We also estimate the fraction of pre-college HC ``wasted'' by the rat-race nature of the admissions contest, and run counterfactuals of admissions, graduation rates, and post-college income race gaps under alternate admissions schemes not observed in the data.ONLINE SUPPLEMENTAL APPENDIX
FOR AN (ANCIENT, 2013) PREDECESSOR OF THIS PROJECT, CLICK HERE

SHIFTING COMPETITION, AFFIRMATIVE ACTION, AND HUMAN CAPITAL ACCUMULATION: A COMPARATIVE STATIC ANALYSIS OF INVESTMENT CONTESTS (current version: February 2025): R&R, Journal of Human Capital, with Christopher Cotton

ABSTRACT: We analyze a theoretical model in which many heterogeneous agents invest in productive human capital as they compete for better college seats or employment opportunities. We derive theoretical predictions about how intensity of market competition and/or preferential treatment allocation policies change the distribution of effort and human capital accumulation across different population groups. Our main results highlight how Spence-like incentives still play a significant role in many important market settings with dominant Beckerian incentives, where effort produces intrinsically valuable human capital. We show that the findings are robust to a range of assumptions, and discuss policy implications of these results. ONLINE SUPPLEMENTAL APPENDIX

HIGH-DIMENSIONAL SELLER SIGNALING IN E-COMMERCE: USING MACHINE LEARNING TO EXPLAIN VIOLATIONS OF THE LAW OF ONE PRICE (current version: July 2024): R&R, Quantitative Marketing and Economics, with Joern Boehnke and Aaron Bodoh-Creed

ABSTRACT: Significant price dispersion for homogeneous goods in e-commerce is a well-documented puzzle; we find robust empirical evidence that the puzzle is roughly half as large as previously thought. We use an approach motivated by economic theory, employing a rich new dataset encompassing a wealth of ``unstructured data’’ from 14 product categories, and flexible machine learning methods. We quantify sellers' marketing strategies through customization of content, layout, and appearance of their product-listing web-page. We find that marketing strategies play an important role in differentiating product listings for otherwise homogeneous goods, accounting for half of observed cross-sectional price dispersion. Our results place a bound on the role that market frictions play on e-commerce platforms. We also find a high degree of substitutability between content and listing style for signaling of value to potential buyers. This suggests that online platforms provide a wide array of avenues for sellers to create perceived product differentiation.ONLINE SUPPLEMENTAL APPENDIX

WORK IN PROGRESS

A CONVENIENT TEST OF INDEPENDENT PRIVATE VALUES AGAINST A COMPREHENSIVE ALTERNATE HYPOTHESES IN AUCTION DATA, with Timothy P. Hubbard and Eric Richert SLIDES (manuscript coming soon)

A FIELD EXPERIMENTAL ANALYSIS OF TEAMWORK DYNAMICS IN THE WORKPLACE: DEMOGRAPHICS, COMMUNICATION, AND WORKER PERFORMANCE, with Hillary Elfenbein, Jeffrey Flory, John List, and Amanda Pallais

A NEW METHOD FOR EFFICIENT COMPUTATION OF NON-STATIONARY DYNAMIC PROGRAMMING PROBLEMS WITH HISTORY DEPENDENCE, with Barton Hamilton and Rana Mohie Eldin

A MARKET DESIGN APPROACH TO REDUCING ACHIEVEMENT GAPS: INSIGHTS FOR ADDRESSING HETEROGENEOUS ACADEMIC PRODUCTIVITY AND MOTIVATION, with Chris Cotton, John List, and Greg Sun

IS MATH TUTORING A TREATMENT FOR LACK OF UNDERSTANDING OR LACK OF ENGAGEMENT? A FIELD EXPERIMENTAL INVESTIGATION OF RESPONSE TO INTERVENTION, with Christopher Cotton, John List, and Joseph Price

LESS PROFICIENT OR MORE METHODICAL: A FIELD EXPERIMENTAL INVESTIGATION OF MEASURED GENDER GAPS IN MATH SCORES, with Christopher Cotton and John List

HOW MALLEABLE ARE UNOBSERVED STUDENT CHARACTERISTICS DURING MIDDLE CHILDHOOD?, with Juanna Joensen, John List, and Anya Samek

STUDENTS, TEACHERS, AND ADMINISTRATORS: A HIERARCHICAL MODEL OF VALUE ADDED IN EDUCATION, with Faith Fatchen, Faisal Kattan, and John List

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