Recent Advances in Empirical Auctions
Friday, Jan. 6, 2017 3:15 PM – 5:15 PM
- Chair: Paulo Somaini, Stanford University
Simultaneous First-Price Auctions With Preferences Over Combinations: Identification, Estimation and Application
AbstractMotivated by the empirical prevalence of simultaneous bidding across a wide range of auction markets, we develop and estimate a structural model of strategic interaction in simultaneous first-price auctions when objects are heterogeneous and bidders have preferences over combinations. We begin by proposing a general theoretical model of bidding in simultaneous first price auctions, exploring properties of best responses and existence of equilibrium within this environment. We then specialize this model to an empirical framework in which bidders have stochastic private valuations for each object and stable incremental preferences over combinations; this immediately reduces to the standard separable model when incremental preferences over combinations are zero. We establish non-parametric identification of the resulting model under standard exclusion restrictions, thereby providing a basis for both testing on and estimation of preferences over combinations. We then apply our model to data on Michigan Department of Transportation highway procurement auctions, we quantify the magnitude of cost synergies and assess possible efficiency losses arising from simultaneous bidding in this market.
Nonparametric Estimation of First-Price Auctions With Risk-Averse Bidders
AbstractThis paper proposes nonparametric estimators for the bidders' utility function and density of private values in a first-price sealed-bid auction model with independent valuations. I study a setting with risk-averse bidders and adopt a fully nonparametric approach by not placing any restrictions on the shape of the utility function beyond regularity conditions. I propose a population criterion function that has a unique minimizer, which characterizes the utility function and density of private values. The resulting estimators emerge after replacing the population quantities by sample analogues. These estimators are uniformly consistent and their convergence rates are established. Monte Carlo experiments show that the proposed estimators perform well in practice.
Strategic Bidding and Contract Renegotiation
AbstractWhen firms bid in procurement auctions, they take into account the likelihood of future contract renegotiations. If they anticipate that certain input quantities will change ex post, they have an incentive to strategically skew their itemized bids, thereby increasing profits for themselves and costs for the procuring agency. We develop and estimate a structural model of strategic bidding using a dataset of road construction projects in Vermont. We find that firms engage in strategic bidding that increases profit margins by 3-4% at the project level, and 7-9% on the specific items that are renegotiated.
- C0 - General