industry structure.

We consider dynamic games that can have state variables that are partially observed, serially correlated, endogenous, and heterogeneous. We propose a Bayesian method that uses a particle filter to compute an unbiased estimate of the likelihood within a Metropolis chain. Unbiasedness guarantees...

Experience in one product market can potentially improve firm performance in a related product market in the future. Thus, entry into a market is determined not just by profits in that market but also by its future impact on profitability in other markets. We formulate and estimate a dynamic...

We discuss the identification and estimation of discrete games with complete information. Following Bresnahan and Reiss, a discrete game is defined to be a generalization of a standard discrete choice model in which utility depends on the actions of other players. Using recent algorithms that...

We develop econometric models of ascending (English) auctions which allow for both bidder asymmetries as well as common and/or private value components in bidders' underlying valuations We show that the equilibrium inverse bid functions in each round of the auction are implicitly defined...

We develop a new estimation methodology for dynamic optimization models with unobserved state variables Our approach is semiparametric in the sense of not requiring explicit parametric assumptions to be made concerning the distribution of these unobserved state variables We propose a two-step...

We empirically measure the effects of increasing competition on equilibrium bidding in procurement auctions In common-value auctions the winner's curse counsels more conservative bidding as the number of competitors increases First we estimate the structural parameters of an equilibrium bidding...

In this paper we study a statistical method of implementing quasi-Bayes estimators for nonlinear and nonseparable GMM models, that is motivated by the ideas proposed in Chernozhukov and Hong (2003) and Creel and Kristensen (2011) and that combines simulation with nonparametric regression in the...

Estimation of unknown parameters and functions involved in complex nonlinear econometric models is a very important issue. Existing estimation methods include generalised method of moments (GMM) by Hansen (1982) and others, efficient method of moments (EMM) by Gallant and Tauchen (1997), Markov...