Structural Macroeconometrics : : Second Edition / / David N. DeJong, Chetan Dave.

• VerfasserIn: DeJong, David N.,; Dave, Chetan,
• Place / Publishing House: Princeton, NJ : : Princeton University Press, , [2011]; ©2012
• Year of Publication: 2011
• Language: English
• Physical Description: 1 online resource (440 p.) :; 57 line illus. 21 tables.

The revised edition of the essential resource on macroeconometricsStructural Macroeconometrics provides a thorough overview and in-depth exploration of methodologies, models, and techniques used to analyze forces shaping national economies. In this thoroughly revised second edition, David DeJong and Chetan Dave emphasize time series econometrics and unite theoretical and empirical research, while taking into account important new advances in the field.The authors detail strategies for solving dynamic structural models and present the full range of methods for characterizing and evaluating empirical implications, including calibration exercises, method-of-moment procedures, and likelihood-based procedures, both classical and Bayesian. The authors look at recent strides that have been made to enhance numerical efficiency, consider the expanded applicability of dynamic factor models, and examine the use of alternative assumptions involving learning and rational inattention on the part of decision makers. The treatment of methodologies for obtaining nonlinear model representations has been expanded, and linear and nonlinear model representations are integrated throughout the text. The book offers a rich array of implementation algorithms, sample empirical applications, and supporting computer code.Structural Macroeconometrics is the ideal textbook for graduate students seeking an introduction to macroeconomics and econometrics, and for advanced students pursuing applied research in macroeconomics. The book's historical perspective, along with its broad presentation of alternative methodologies, makes it an indispensable resource for academics and professionals.

Table of Contents

Frontmatter -- Contents -- Preface -- Preface to the First Edition -- Part I Introduction -- Chapter 1 Background and Overview -- Chapter 2 Casting Models in Canonical Form -- Chapter 3 DSGE Models: Three Examples -- Part II Model Solution Techniques -- Chapter 4 Linear Solution Techniques -- Chapter 5 Nonlinear Solution Techniques -- Part III Data Preparation and Representation -- Chapter 6 Removing Trends and Isolating Cycles -- Chapter 7 Summarizing Time Series Behavior When All Variables Are Observable -- Chapter 8 State-Space Representations -- Part IV Monte Carlo Methods -- Chapter 9 Monte Carlo Integration: The Basics -- Chapter 10 Likelihood Evaluation and Filtering in State-Space Representations Using Sequential Monte Carlo Methods -- Chapter 11 Calibration -- Chapter 12 Matching Moments -- Chapter 13 Maximum Likelihood -- Chapter 14 Bayesian Methods -- References -- Index