COMMENTS WELCOME

Contact: hickmanbr [AT] uchicago [DOT] edu

PUBLICATIONS:

ON THE PRICING RULE IN ELECTRONIC AUCTIONS (2010)

International Journal of Industrial Organization, 28(5), 423-433.
Winner of the 2011 Paul Geroski Award for being one of the two best papers to appear in the journal during the previous year.


ABSTRACT: Researchers and experts have typically viewed electronic auctions (such as those implemented by eBay, Amazon, and Yahoo!) as either oral, ascending-price (English) auctions or second-price, sealed-bid (Vickrey) auctions. I show that important theoretical differences exist between English and Vickrey pricing rules and those used in electronic auctions, due to the presence of bid increments. I also show, using data on eBay laptop sales, that these differences have practical significance. I explore the implications of bid increments for strategic bid selection in a static model within the symmetric independent private-values paradigm. I derive the unique symmetric equilibrium bid function, showing that the presence of bid increments can significantly alter bidder behavior. Using numerical methods, I also illustrate that these result in a highly non-linear bid function, in contrast to that predicted under either the English or the Vickrey formats.

MATLAB program files to accompany On the Pricing Rule in Electronic Auctions

Click the link above to download a compressed folder EA_MATLAB_Files.rar which contains a MATLAB program (with supporting files) to compute the equilibrium of an electronic auction. The folder contains a ReadMe file with instructions.

STRUCTURAL ECONOMETRIC METHODS IN AUCTIONS: A GUIDE TO THE LITERATURE (2012), with Timothy P. Hubbard and Yigit Saglam

Journal of Econometric Methods, 1(1), pp. 67-106. DOI: 10.1515/2156-6674.1019

ABSTRACT: Auction models have proved to be attractive to structural econometricians who, since the late 1980s, have made substantial progress in identifying and estimating these rich game-theoretic models of bidder behavior. We provide a guide to the literature in which we contrast the various informational structures (paradigms) commonly assumed by researchers and uncover the evolution of the field. We highlight major contributions within each paradigm and benchmark modifications and extensions to these core models. Lastly, we discuss special topics that have received substantial attention among auction researchers in recent years, including auctions for multiple objects, auctions with risk averse bidders, testing between common and private value paradigms, unobserved auction-specific heterogeneity, and accounting for an unobserved number of bidders as well as endogenous entry.

REPLACING SAMPLE TRIMMING WITH BOUNDARY CORRECTION IN NONPARAMETRIC ESTIMATION OF FIRST-PRICE AUCTIONS (2015), with Timothy P. Hubbard

Journal of Applied Econometrics Volume 30, Issue 5, pp. 739-762

ABSTRACT: Two-step nonparametric estimators have become standard in empirical auctions. A drawback concerns boundary effects which cause inconsistencies near the endpoints of the support and bias in finite samples. To cope, sample trimming is typically used which leads to non-random data loss. Monte Carlo experiments show this leads to poor performance near the support boundaries and on the interior due bandwidth-selection issues. We propose a modification which employs boundary-correction techniques, demonstrating substantial improvement in finite-sample performance. We implement the new estimator using oil lease auctions data and find that trimming masks a substantial degree of bidder asymmetry and inefficiency in allocations.

MATLAB program files to accompany Replacing Sample Trimming with Boundary Correction in Nonparametric Estimation of First-Price Auctions

Click the link above to download a MATLAB toolbox for boundary correction in kernel density estimation.

IDENTIFICATION AND ESTIMATION OF A BIDDING MODEL FOR ELECTRONIC AUCTIONS (2017), with Timothy P. Hubbard and Harry J. Paarsch

Quantitative Economics Volume 8, Issue 2, pp. 505-551

ABSTRACT: Because of bid increments bidders in electronic auctions engage in demand shading, in contrast to the commonly assumed second-price format. We use simulation methods to demonstrate that mis-specifying the pricing rule in this way can lead to significant bias in estimates of the latent valuation distribution and other related objects of interest such as expected revenue projections. We explore identification and estimation of a model with a correctly-specified pricing rule. A further challenge is that the econometrician only observes a lower bound on the number of participants in each auction. We are able to identify nonparametrically the form of an exogenous bidder arrival process, which matches potential buyers to auction listings from this observed lower bound. This then allows us to identify the private value distribution without functional form assumptions. We propose a computationally convenient sieve-type estimator of the private value distribution which involves B-splines. We also compare two parametric models of bidder participation and find that a generalized Poisson model cannot be rejected against the empirical distribution of the observables. Our structural estimates enable an exploration of information rents and optimal reserve prices on eBay. Note: previous versions of this paper circulated under the title " INVESTIGATING THE ECONOMIC IMPORTANCE OF PRICING-RULE MIS-SPECIFICATION IN EMPIRICAL MODELS OF ELECTRONIC AUCTIONS."

Online Supplemental Appendix to Accompany "IDENTIFICATION AND ESTIMATION OF A BIDDING MODEL FOR ELECTRONIC AUCTIONS"

MATLAB program files to accompany Identification and Estimation of a Bidding Model for Electronic Auctions

Click the link above to download a compressed folder QE_SUPPLEMENTAL_MATERIALS_hhp2016.zip which contains MATLAB programs (with supporting files) to perform our Monte Carlo analysis and execute our empirical estimator. We also provide a MATLAB toolbox for researchers who wish to use B-splines for general numerical work. The folder contains a ReadMe file with installation and useage instructions.

WORKING PAPERS:

COLLEGE ASSIGNMENT AS A LARGE CONTEST, with Aaron L. Bodoh-Creed

Latest version: August 2017
(revise and resubmit at Journal of Economic Theory)

NOTE: A previous version of the paper was circulated under the title "EFFORT, RACE GAPS AND AFFIRMATIVE ACTION: A GAME-THEORETIC ANALYSIS OF COLLEGE ADMISSIONS."

ABSTRACT: We develop a model of college assignment as a large contest wherein students with heterogeneous learning-costs compete for seats at vertically differentiated colleges through the acquisition of productive human capital. We use a continuum model to approximate the outcomes of a game with large, but finite, sets of colleges and students. The continuum approximation lends tractability to a rich model for studying investment incentives in rank-order competitions. By incorporating two common families of affirmative action mechanisms into our model, admissions preferences and quotas, we can show that (legal) admissions preference schemes and (illegal) quotas have the same sets of equilibria including identical outcomes and investment strategies. Finally, we explore the welfare costs of using human capital accumulation to compete for college admissions. We define the cost of competition as the welfare difference between a color-blind admissions contest and the first-best outcome chosen by an omniscient social planner. Using a calibrated version of our model, we find that the cost of competition is equivalent to a loss of $91,795 in NPV of lifetime earnings.

PRE-COLLEGE HUMAN CAPITAL INVESTMENT AND AFFIRMATIVE ACTION: A STRUCTURAL POLICY ANALYSIS OF US COLLEGE ADMISSIONS , with Aaron L. Bodoh-Creed

Latest version: July 2017
(currently under review)

NOTE: This version replaces a previous draft circulated under the title "Effort, Race Gaps, and Affirmative Action: A Structural Policy Analysis of US College Admissions"

ABSTRACT: We study a structural model of college admissions framed as a contest between a continuum of students for enrollment in a continuum of colleges where the contest outcome is decided by the students' choice of human capital (HC). Students have private information about their learning costs, and colleges have heterogeneous, observable qualities. Our econometric model is inspired by methods from the empirical auctions literature and allow us to separately identify the roles of school quality, HC, and unobserved learning costs on post-college household income. We use our estimates to conduct counterfactual experiments comparing different college admissions rules including color-blind admissions, a proportional quota for minority students, and means-tested affirmative action (AA). An AA ban would result in a large migration of minority students out of the best schools and into the lowest quality schools with a corresponding reduction in household income and mean graduation rates. However, the signs and magnitudes of changes to HC investment and individual graduation rate depend on the demographics and learning cost type of the particular student in question. We also argue that a means-tested AA plan does not significantly increase racial diversity. Finally, our estimates imply that the competitive incentive to accrue HC is stronger than the productive incentive for all but the top 4% achieving students.

Online Appendix to Accompany "HUMAN CAPITAL INVESTMENT AND AFFIRMATIVE ACTION"



INCENTIVE PROVISION IN INVESTMENT CONTESTS: THEORY AND EVIDENCE, with Christopher Cotton and Joseph P. Price

Current version: April 2017
(currently under review)

ABSTRACT: We build on recent models of large-scale contests–in which many heterogenous agents compete for heterogenous prizes–to develop novel theoretical predictions concerning incentive provision in scenarios where competitive human capital investment determines rank-order allocations of non-divisible resources such as college seats. We then conduct a field experiment in which hundreds of subjects compete for an array of prizes, and find empirical patterns in competitive learning behaviors that are highly-consistent with the theory. Our findings deliver two key insights. First, when human capital serves a dual role as an intrinsic asset and a rank-order index, investment behavior varies significantly with the strength of one’s competition, holding own ability and the set of prizes fixed. Second, if an observable noisy signal of ability is available, we find evidence of a counterintuitive role for preferential treatment in promoting overall investment.

Online Appendix to Accompany "INCENTIVE PROVISION IN INVESTMENT CONTESTS"



HOW EFFICIENT ARE DECENTRALIZED AUCTION PLATFORMS?, with Aaron L. Bodoh-Creed and Jorn Boehnke

Latest version: February 2017
(revise and resubmit at Review of Economic Studies)

ABSTRACT: We provide a model of a decentralized, dynamic auction market platform (e.g., eBay) in which a continuum of buyers and sellers participate in simultaneous, single-unit auctions each period. Our model accounts for the endogenous entry of agents and the impact of intertemporal optimization on bids. We estimate the structural primitives of our model using Kindle sales on eBay. We find that just over one third of Kindle auctions on eBay result in an inefficient allocation with deadweight loss amounting to 14% of total possible market surplus. We also find that partial centralization - for example, running half as many 2-unit, uniform price auctions each day - would eliminate a large fraction of the inefficiency, but yield slightly lower seller revenues. Our results also highlight the importance of understanding platform composition effects - selection of agents into the market - in assessing the implications of market design. We close by proving that the equilibrium of our model with a continuum of buyers and sellers is an approximate equilibrium of the analogous model with a finite number of agents.

ONLINE APPENDIX TO ACCOMPANY "How Efficient are Decentralized Auction Platforms?"



PRODUCTIVITY VERSUS MOTIVATION: COMBINING FIELD EXPERIMENTS WITH STRUCTURAL ECONOMETRICS TO STUDY ADOLESCENT HUMAN CAPITAL PRODUCTION, with Christopher Cotton, John List, and Joseph Price

Click on link above to access slides; manuscript coming in December 2016

ABSTRACT: Demographic achievement gaps are well documented, with females and minorities under-performing relative to males and non-minorities, respectively. However, little is known about the underlying factors driving these gaps. We formalize a model of 2-dimensional unobserved heterogeneity--learning productivity and motivation--to depict the process of producing new human capital during middle childhood. We propose a novel research design wherein field experiments are used to generate the requisite set of observables to identify the structural model of unobserved heterogeneity, rather than directly testing some treatment effect. This research design allows us to disentangle, at the individual level, a child's willingness to work at math (motivation) from his/her ability to accomplish a given learning task in a fixed amount of time. We are also able to estimate a compensating differential function which characterizes each individual's marginal cost (measured in $USD) of devoting one more hour to study from an arbitrary start point. Our structural results uncover several new insights. First, adolescent females and minorities are less productive with a unit of time than are males or non-minorities, respectively. However, females and minorities are also more motivated to learn, as measured by their willingness to substitute from leisure toward study.

TOWARD AN UNDERSTANDING OF CORPORATE SOCIAL RESPONSIBILITY: THEORY AND FIELD EXPERIMENTAL EVIDENCE, with Daniel Hedblom and John List

Latest version: March 2017

ABSTRACT: We develop a theory and a tightly-linked field experiment to explore the supply side impact of CSR. Our natural field experiment, in which we created our own firm and hired actual workers, generates a rich data set on worker behavior and responses to CSR incentives. We use these data to estimate a structural principal-agent model with three dimensions of worker heterogeneity: productivity, work quality, and value of time. This allows us to answer a variety of questions related to treatment effects (on existing employees behaviors) and selection effects on the pool of applicants from CSR. We find strong evidence that when a firm convinces its workers that their efforts make the world a better place (as opposed to just making money) it will attract workers that are more productive, produce higher quality work, and have more highly valued leisure time. We also find an economically significant treatment effect of CSR on improving work quality of existing employees as well. Our research design may serve as a framework for causal inference on more general forms of non-pecuniary incentives in the workplace.

USING MACHINE LEARNING TO EXPLAIN VIOLATIONS OF THE "LAW OF ONE PRICE", with Aaron L. Bodoh-Creed and Jorn Boehnke

Latest version: August 2017
(currently under review)


ABSTRACT: Substantial price variation for homogeneous goods in online markets is a well-known puzzle that has withstood attempts by empirical researchers to explain it. Economic theory suggests two possible sources of the dispersion: either market frictions are more important than previously thought, or there are subtle differences between product listings presented to e-commerce consumers that applied econometricians have failed to detect. We use a very detailed data set consisting of posted-price listings for new Kindle Fire tablets from eBay to determine if observable listing heterogeneity can explain the price dispersion of seemingly homogeneous products. By combining a richer set of variables than previous studies with more sophisticated machine learning techniques, we can explain 42% of the dispersion. We interpret this as a bound on the in uence of market frictions on price dispersion. Variables describing the amount of information in the listing are good predictors of the price, but variables describing the style of a listing's text are good predictors as well. We identify readily interpretable groups of words that are also good predictors of price. We find a high degree of heterogeneity of the marginal effects of seller reputation and including an image in the listing, but the patterns of heterogeneity largely conform to economic intuition. A smaller, but non-trivial, latitude for market frictions remains, and we discuss their possible sources.

WORK IN PROGRESS:

Is Math Tutoring a Treatment of Lack of Understanding or Lack of Engagement?, with Christopher Cotton, John List, and Joseph Price

Pecuniary and Non-Pecuniary impacts of Affirmative Action in College Admissions, with Jack Mountjoy

Macro-Level Market Design: Optimal Fee Schedules in Two-Sided Platform Selling Mechanisms, with Aaron Bodoh-Creed and Joern Boehnke

Information Processing versus Self-Control: Toward a More Complete Understanding of the Factors Driving Obesity, with Justin Holz and John List

On the Maleability of Cognitive and Non-Cognitive Characteristics in Adolescent Academic Development, with Anya Samek, Juanna Joensen, and John List