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 | Economic Modeling and Inference |
Economic Modeling and Inference takes econometrics to a new level by demonstrating how to combine modern economic theory with the latest statistical inference methods to get the most out of economic data. This graduate-level textbook draws applications from both microeconomics and macroeconomics, paying special attention to financial and labor economics, with an emphasis throughout on what observations can tell us about stochastic dynamic models of rational optimizing behavior and equilibrium. Bent Jesper Christensen and Nicholas Kiefer show how parameters often thought estimable in applications are not identified even in simple dynamic programming models, and they investigate the roles of extensions, including measurement error, imperfect control, and random utility shocks for inference. When all implications of optimization and equilibrium are imposed in the empirical procedures, the resulting estimation problems are often nonstandard, with the estimators exhibiting nonregular asymptotic behavior such as short-ranked covariance, superconsistency, and non-Gaussianity. Christensen and Kiefer explore these properties in detail, covering areas including job search models of the labor market, asset pricing, option pricing, marketing, and retirement planning. Ideal for researchers and practitioners as well as students, Economic Modeling and Inference uses real-world data to illustrate how to derive the best results using a combination of theory and cutting-edge econometric techniques.
Bent Jesper Christensen is professor of economics and management at the University of Aarhus in Denmark. Nicholas M. Kiefer is the Ta-Chung Liu Professor in Economics and Statistical Science at Cornell University. "Christensen and Kiefer's excellent book shows how careful dynamic theory and econometrics go hand in hand, opening up new vistas in the areas of search theory, finance, and macroeconomics."--Tom Sargent, New York University and the Hoover Institution "There is no other book that mixes dynamic economic theory, statistical inference, and real quantitative applications like this one. Christensen and Kiefer will challenge the top tier of students and take them to the research frontier."--Robert Lucas, University of Chicago "Dynamic programming is an organizing framework that has enabled economists to integrate economic theory with empirical analysis. Few textbooks reflect the integrated nature of contemporary research, but Christensen and Kiefer reveal the power of the dynamic programming approach in a wide variety of applications from job search to portfolio choice. Their new book will be invaluable to students who wish to participate in this exciting enterprise."--John Y. Campbell, Harvard University "The authors do a splendid job of showing how to use stochastic dynamic optimization techniques to generate the implied distributions of observables needed for estimation. There are many interesting and useful examples included in the book, ranging from applications of the theory of job search to those of asset pricing theory. This book should be a reference for anyone interested in using dynamic economic models to make inferences about the world we observe."--Dale Mortensen, Aarhus University, Denmark, and Northwestern University "An extremely ambitious and thought-provoking book, one that combines state-of-the-art economic theory with sophisticated econometric techniques. The dynamic programming framework brings together important results and recent developments in a unique, unified way. The book is sure to inspire many PhD students and empirically oriented researchers for years to come."--Tim Bollerslev, Duke University Subject Areas:
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