Synopses & Reviews
andlt;Pandgt;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.andlt;/Pandgt;
Review
"This is an excellent text in applied dynamic macroeconomics for teachers, students, and researchers. It enables the research community to learn how to use dynamic economic theory to interpret economic data and quantify the theoretical implications. Any applied economist should have this book on his or her shelf as a quick guide for the available options of 'how to do it.'"--Zvi Eckstein, Tel Aviv University, University of Minnesota, and Centre for Economic Policy ResearchPlease note: Endorser gives permission to excerpt from quote.
Review
"This book is a welcome addition to the macroeconomics literature. It is both a very effective textbook and a welcome summary of developments and tools needed to do state-of-the-art research in the very dynamic, changing field."--Paul D. McNelis, Professor of Economics, Georgetown University
Review
"*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. The MIT Press
Review
"This book ties together numerical methods with state of the art mathematical tools in a user-friendly way. It should be part of the program in 'math camps' for incoming graduate students in Economics and Finance. The Matlab programs are a very useful resource for anyone doing applied research."--Paul D. McNelis, Professor of Economics, Georgetown University
Review
"This book is an important contribution to the rapidly growing literature on computational economics and finance. It provides an extremely well integrated presentation of dynamic economic models and some of the most effective numerical methods for solving them. It reinforces these ideas by providing illustrative solutions written in Matlab. This book should enable most people who do not have extensive prior background in computation to understand the key methods and ideas, and to actually begin applying these methods to their own problems. I think it will be an essential part of the toolkit of the applied practitioner in economics or finance."--John Rust, Professor of Economics, University of MarylandPlease note: The third sentence may, if necessary, be omitted for space reasons.
Review
Paarsch is the 'founding father' of the rapidly growing literature on structural econometric analysis of auctions, and Hong complements Paarsch's skills in the economics, theory, and computation of solutions to auction models with his own strong expertise 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. The MIT Press
Review
Russell Cooper is Professor in the Department of Economics at the University of Texas, Austin. He was formerly affiliated with Boston University and was a Visiting Scholar in the Research Department of the Federal Reserve Bank of Minneapolis.
"This book is a welcome addition to the macroeconomics literature. It is both a very effective textbook and a welcome summary of developments and tools needed to do state-of-the-art research in the very dynamic, changing field."--Paul D. McNelis, Professor of Economics, Georgetown University
"This is an excellent text in applied dynamic macroeconomics for teachers, students, and researchers. It enables the research community to learn how to use dynamic economic theory to interpret economic data and quantify the theoretical implications. Any applied economist should have this book on his or her shelf as a quick guide for the available options of 'how to do it.'"--Zvi Eckstein, Tel Aviv University, University of Minnesota, and Centre for Economic Policy ResearchPlease note: Endorser gives permission to excerpt from quote.
"*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.
"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
An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers.
Review
andlt;Pandgt;"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 Marylandandlt;/Pandgt; The MIT Press
Review
andlt;Pandgt;" andlt;Iandgt;Dynamic Economicsandlt;/Iandgt; 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 Marylandandlt;/Pandgt; The MIT Press The MIT Press
Review
andlt;Pandgt;"*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.andlt;/Pandgt; The MIT Press
Review
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Review
The MIT Press
Synopsis
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.
Synopsis
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.
Synopsis
An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers.
Synopsis
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.
Synopsis
optimization programming models, for students and researchers.
Synopsis
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.
Synopsis
andlt;Pandgt;An integrated approach to the empirical application of dynamic optimization programming models, for students and researchers. andlt;/Pandgt;
About the Author
Jérôme Adda is a Lecturer in the Department of Economics at University College, London, and a Research Associate at the Institute of Fiscal Studies.Russell Cooper is Professor in the Department of Economics at the University of Texas, Austin. He was formerly affiliated with Boston University and was a Visiting Scholar in the Research Department of the Federal Reserve Bank of Minneapolis.