Brent Richard Hickman

On the Pricing Rule in Electronic Auctions

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-value 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.

College Assignment as a Large Contest

We develop a model of college assignment as a large contest wherein students with heterogeneous abilities 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. 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

Identification and estimation of a bidding model for electronic auctions

91,795 in NPV of lifetime earnings.

How Efficient are Decentralized Auction Platforms

Because of discrete bid increments, bidders at electronic auctions engage in shading instead of revealing their valuations, which would occur under the commonly assumed second-price rule. We demonstrate that misspecifying the pricing rule can lead to biased estimates of the latent valuation distribution, and then explore identification and estimation of a model with a correctly specified pricing rule. A further challenge to econometricians is that only a lower bound on the number of participants at each auction is observed. From this bound, however, we establish nonparametric identification of the arrival process of bidders—the process that matches potential buyers to auction listings—which then allows us to identify the latent valuation distribution without imposing functional-form assumptions. We propose a computationally tractable, sieve-type estimator of the latent valuation distribution based on B-splines, and then compare two parametric models of bidder participation, finding that a generalized Poisson model cannot be rejected by the empirical distribution of observables. Our structural estimates enable us to explore information rents and optimal reserve prices on eBay.

Using Machine Learning to Explain Violations of the 'Law of One Price'

We provide a model of a decentralized, dynamic auction market platform (e.g., eBay) in which a large number 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. Solving our model with a finite number of bidders is computationally intractable due to the curse of dimensionality, so we prove that a continuum version of our model provides a good approximation of an equilibrium in the finite model. We use the approximation to 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 13.5% 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 lower seller revenues. Our results highlight the importance of understanding platform composition effects - selection of agents into the market - in assessing the implications of market design.

Pre-College Human Capital Investments and Affirmative Action: A Structural Policy Analysis of US College Admissions

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 influence 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 listings 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.