Are Structural Estimates of Auction Models Reasonable? Evidence from Experimental Data

Recently, economists have developed methods for structural estimation of auction models. Many researchers object to these methods because they find the rationality assumptions used in these models to be implausible. In this paper, we explore whether structural auction models can generate reasonable estimates of bidders' private information. Using bid data from auction experiments, we estimate four alternative structural models of bidding in first-price sealed-bid auctions: 1) risk neutral Bayes-Nash, 2) risk averse Bayes-Nash, 3) a model of learning and 4) a quantal response model of bidding. For each model, we compare the estimated valuations and the valuations assigned to bidders in the experiments. We find that a slight modification of Guerre, Perrigne and Vuong's (2000) procedure for estimating the risk neutral Bayes-Nash model to allow for bidder asymmetries generates quite reasonable estimates of the structural parameters.

Procurement Contracting with Time Incentives: Theory and Evidence

In public sector procurement, social welfare often depends on the time taken to complete the contract. A leading example is highway construction, where slow completion times inflict a negative externality on commuters. Recently, highway departments have introduced innovative contracting methods based on scoring auctions that give contractors explicit time incentives. We characterize equilibrium bidding and efficient design of these contracts. We then gather an extensive data set of highway repair projects awarded by the California Department of Transportation between 2003 and 2008 that includes both innovative and standard contracts. Comparing similar con- tracts in which the innovative design was and was not used, we show that the welfare gains to commuters from quicker completion substantially exceeded the increase in the winning bid. Having argued that the current policy is effective, we then develop a structural econometric model that endogenizes participation and bidding to examine counterfactual policies. Our estimates suggest that while the current policy raised com- muter surplus relative to the contractor's costs by $359M (6.8$1.52B (29%).

Economic Insights from Internet Auctions: A Survey

This paper surveys recent studies of Internet auctions. Four main areas of research are summarized. First, economists have documented strategic bidding in these markets and attempted to understand why sniping, or bidding at the last second, occurs. Second, some researchers have measured distortions from asymmetric information due, for instance, to the winner's curse. Third, we explore research about the role of reputation in online auctions. Finally, we discuss what Internet auctions have to teach us about auction design.

Semiparametric Estimation of a Dynamic Game of Incomplete Information

Recently, empirical industrial organization economists have proposed estimators for dynamic games of incomplete information. In these models, agents choose from a finite number actions and maximize expected discounted utility in a Markov perfect equilibrium. Previous econometric methods estimate the probability distribution of agents%u2019 actions in a first stage. In a second step, a finite vector of parameters of the period return function are estimated. In this paper, we develop semiparametric estimators for dynamic games allowing for continuous state variables and a nonparametric first stage. The estimates of the structural parameters are T1/2 consistent (where T is the sample size) and asymptotically normal even though the first stage is estimated nonparametrically. We also propose sufficient conditions for identification of the model.

Complementarities and Collusion in an FCC Spectrum Auction

We empirically study bidding in the C Block of the US mobile phone spectrum auctions. Spectrum auctions are conducted using a simultaneous ascending auction design that allows bidders to assemble packages of licenses with geographic complementarities. While this auction design allows the market to find complementarities, the auction might also result in an inefficient equilibrium. In addition, these auctions have equilibria where implicit collusion is sustained through threats of bidding wars. We estimate a structural model in order to test for the presence of complementarities and implicit collusion. The estimation strategy is valid under a wide variety of alternative assumptions about equilibrium in these auctions and is robust to potentially important forms of unobserved heterogeneity. We make suggestions about the design of future spectrum auctions.Technology and Industry

An Empirical Model of Stock Analysts' Recommendations: Market Fundamentals, Conflicts of Interest, and Peer Effects

In this paper we develop an empirical model of equity analyst recommendations for firms in the NASDAQ 100 during 1998-2003. In the model we allow recommendations to depend on publicly observed information, measures of an analyst's beliefs about a stock's future earnings, investment banking activity, and peer group effects which determine industry norms. To address the reflection problem, we propose a new approach to identification and estimation of models with peer effects suggested by recent work on estimating games. Our empirical results suggest that recommendations depend most heavily on publicly observable information about the stocks and on industry norms. In most of our specifications, the existence of an investment banking deal does not have a statistically significant relationship with analysts' stock recommendations.

Moral Hazard, Incentive Contracts and Risk: Evidence from Procurement

Deadlines and penalties are widely used to incentivize effort. We model how these incentive contracts affect the work rate and time taken in a procurement setting, characterizing the efficient contract design. Using new micro-level data on Minnesota highway construction contracts that includes day-by-day information on work plans, hours actually worked and delays, we find evidence of moral hazard. As an application, we build an econometric model that endogenizes the work rate, and simulate how different incentive structures affect outcomes and the variance of contractor payments. Accounting for the traffic delays caused by construction, switching to a more efficient design would substantially increase welfare without substantially increasing the risk borne by contractors.

Measuring the Efficiency of an FCC Spectrum Auction

FCC spectrum auctions sell licenses to provide mobile phone service in designated geographic territories. We propose a method to structurally estimate the deterministic component of bidder valuations and apply it to the 1995–1996 C-block auction. We base our estimation of bidder values on a pairwise stability condition, which implies that two bidders cannot exchange licenses in a way that increases total surplus. Pairwise stability holds in many theoretical models of simultaneous ascending auctions, including some models of intimidatory collusion and demand reduction. Pairwise stability is also approximately satisfied in data that we examine from economic experiments. The lack of post-auction resale also suggests pairwise stability. Using our estimates of deterministic valuations, we measure the allocative efficiency of the C-block outcome.

Demand Estimation With Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach

We study the identification and estimation of preferences in hedonic discrete choice models of demand for differentiated products. In the hedonic discrete choice model, products are represented as a finite dimensional bundle of characteristics, and consumers maximize utility subject to a budget constraint. Our hedonic model also incorporates product characteristics that are observed by consumers but not by the economist. We demonstrate that, unlike the case where all product characteristics are observed, it is not in general possible to uniquely recover consumer preferences from data on a consumer's choices. However, we provide several sets of assumptions under which preferences can be recovered uniquely, that we think may be satisfied in many applications. Our identification and estimation strategy is a two stage approach in the spirit of Rosen (1974). In the first stage, we show under some weak conditions that price data can be used to nonparametrically recover the unobserved product characteristics and the hedonic pricing function. In the second stage, we show under some weak conditions that if the product space is continuous and the functional form of utility is known, then there exists an inversion between a consumer's choices and her preference parameters. If the product space is discrete, we propose a Gibbs sampling algorithm to simulate the population distribution of consumers' taste coefficients.

Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach

We study the identification and estimation of Gorman-Lancaster style hedonic models of demand for differentiated products for the case when one product characteristic is not observed. Our identification and estimation strategy is a two-step approach in the spirit of Rosen (1974). Relative to Rosen's approach, we generalize the first stage estimation to allow for a single dimensional unobserved product characteristic, and also allow the hedonic pricing function to have a general, non-additive structure. In the second stage, if the product space is continuous and the functional form of utility is known then there exists an inversion between the consumer's choices and her preference parameters. This inversion can be used to recover the distribution of random coefficients nonparametrically. For the more common case when the set of products is finite, we use the revealed preference conditions from the hedonic model to develop a Gibbs sampling estimator for the distribution of random coefficients. We apply our methods to estimating personal computer demand.