Dynamic Economics: Quantitative Methods and Applications (The MIT Press) - Tapa dura

"Paarsch is the 'founding father' of the rapidly growing literature on structural econometric analysis of auctions, and Hong compliments Paarsch's skills in the economics, theory, and computation of solutions to auction models with his own strongexpertise in semiparametric econometric methods. The result is an excellent book that is on the 'must read' list for anyone who is interested in this literature, including the frontiers of current research in both parametric and semiparametric methods of inferences that can be applied to a wide range of auction institutions."--John Rust, Professor of Economics, University of Maryland " Dynamic Economics is the sort of book I wish I had written. It provides a very accessible and interesting introduction to the literature on economic models based on dynamic programming methods that have been developed in the last several decades. Unlike other recent work in this area, Adda and Cooper"s book discusses econometric methods for estimating the unknown parameters of these models as well as summarizing some of the most promising computational methods for solving them. The book provides a range of interesting examples and is written at a level that is accessible for people who are new to the subject, but it also contains many deep ideas that will be appreciated by people who spend their careers researching in this area. I learned a lot from this book and recommend it as a text for graduate classes (possibly even advanced undergraduate classes) on dynamic economic methods." John Rust, Professor of Economics, University of Maryland "*Dynamic Economics* is the sort of book I wish I had written. It provides a very accessible and interesting introduction to the literature on economic models based on dynamic programming methods that have been developed in the last several decades. Unlike other recent work in this area, Adda and Cooper's book discusses econometric methods for estimating the unknown parameters of these models as well as summarizing some of the most promising computational methods for solving them. The book provides a range of interesting examples and is written at a level that is accessible for people who are new to the subject, but it also contains many deep ideas that will be appreciated by people who spend their careers researching in this area. I learned a lot from this book and recommend it as a text for graduate classes (possibly even advanced undergraduate classes) on dynamic economic methods."--John Rust, Professor of Economics, University of MarylandPlease note: Endorser gives permission to excerpt from quote.

An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers. This book is an effective, concise text for students and researchers that combines the tools of dynamic programming with numerical techniques and simulation-based econometric methods. Doing so, it bridges the traditional gap between theoretical and empirical research and offers an integrated framework for studying applied problems in macroeconomics and microeconomics. In part I the authors first review the formal theory of dynamic optimization; they then present the numerical tools and econometric techniques necessary to evaluate the theoretical models. In language accessible to a reader with a limited background in econometrics, they explain most of the methods used in applied dynamic research today, from the estimation of probability in a coin flip to a complicated nonlinear stochastic structural model. These econometric techniques provide the final link between the dynamic programming problem and data. Part II is devoted to the application of dynamic programming to specific areas of applied economics, including the study of business cycles, consumption, and investment behavior. In each instance the authors present the specific optimization problem as a dynamic programming problem, characterize the optimal policy functions, estimate the parameters, and use models for policy evaluation. The original contribution of Dynamic Economics: Quantitative Methods and Applications lies in the integrated approach to the empirical application of dynamic optimization programming models. This integration shows that empirical applications actually complement the underlying theory of optimization, while dynamic programming problems provide needed structure for estimation and policy evaluation.