This volume of Advances in Econometrics focuses on recent developments in the use of structural econometric models in empirical economics. The papers in this volume are divided in to three broad groups. The first part looks at recent developments in the estimation of dynamic discrete choice models. This includes using new estimation methods for these models based on Euler equations, estimation using sieve approximation of high dimensional state space, the identification of Markov dynamic games with persistent unobserved state variables and developing test of monotone comparative static in models of multiple equilibria. The second part looks at recent advances in the area empirical matching models. The papers in this section look at developing estimators for matching models based on stability conditions, estimating matching surplus functions using generalized entropy functions, solving for the fixed point in the Choo-Siow matching model using a contraction mapping formulation. While the issue of incomplete, or partial identification of model parameters is touched upon in some of the foregoing chapters, two chapters focus on this issue, in the context of testing for monotone comparative statics in models with multiple equilibria, and estimation of supermodular games under the restrictions that players' strategies be rationalizable. The last group of three papers looks at empirical applications using structural econometric models. Two applications applies matching models to solve endogenous matching to the loan spread equation and to endogenize marriage in the collective model of intrahousehold allocation. Another applications looks at market power of condominium developers in the Japanese housing market in the 1990s.

Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.

Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.