The last twenty years have witnessed tremendous advances in the mathematical, statistical, and computational tools available to applied macroeconomists. This rapidly evolving field has redefined how researchers test models and validate theories. Yet until now there has been no textbook that unites the latest methods and bridges the divide between theoretical and applied work. Fabio Canova brings together dynamic equilibrium theory, data analysis, and advanced econometric and computational methods to provide the first comprehensive set of techniques for use by academic economists as well as professional macroeconomists in banking and finance, industry, and government. This graduate-level textbook is for readers knowledgeable in modern macroeconomic theory, econometrics, and computational programming using RATS, MATLAB, or Gauss. Inevitably a modern treatment of such a complex topic requires a quantitative perspective, a solid dynamic theory background, and the development of empirical and numerical methods--which is where Canova's book differs from typical graduate textbooks in macroeconomics and econometrics. Rather than list a series of estimators and their properties, Canova starts from a class of DSGE models, finds an approximate linear representation for the decision rules, and describes methods needed to estimate their parameters, examining their fit to the data. The book is complete with numerous examples and exercises. Today's economic analysts need a strong foundation in both theory and application. Methods for Applied Macroeconomic Research offers the essential tools for the next generation of macroeconomists.

Preface xi
Preliminaries 1
Stochastic Processes 2
Convergence Concepts 3
Time Series Concepts 8
Laws of Large Numbers 14
Central Limit Theorems 16
Elements of Spectral Analysis 18
DSGE Models, Solutions, and Approximations 26
A Few Useful Models 27
Approximation Methods 45
Extracting and Measuring Cyclical Information 70
Statistical Decompositions 72
Hybrid Decompositions 83
Economic Decompositions 100
Time Aggregation and Cycles 104
Collecting Cyclical Information 105
VAR Models 111
The Wold Theorem 112
Specification 118
Moments and Parameter Estimation of a VAR(q) 126
Reporting VAR Results 130
Identification 141
Problems 151
Validating DSGE Models with VARs 159
GMM and Simulation Estimators 165
Generalized Method of Moments and Other Standard Estimators 166
IV Estimation in a Linear Model 169
GMMEstimation; An Overview 176
GMM Estimation of...Preface xi
Preliminaries 1
Stochastic Processes 2
Convergence Concepts 3
Time Series Concepts 8
Laws of Large Numbers 14
Central Limit Theorems 16
Elements of Spectral Analysis 18
DSGE Models, Solutions, and Approximations 26
A Few Useful Models 27
Approximation Methods 45
Extracting and Measuring Cyclical Information 70
Statistical Decompositions 72
Hybrid Decompositions 83
Economic Decompositions 100
Time Aggregation and Cycles 104
Collecting Cyclical Information 105
VAR Models 111
The Wold Theorem 112
Specification 118
Moments and Parameter Estimation of a VAR(q) 126
Reporting VAR Results 130
Identification 141
Problems 151
Validating DSGE Models with VARs 159
GMM and Simulation Estimators 165
Generalized Method of Moments and Other Standard Estimators 166
IV Estimation in a Linear Model 169
GMMEstimation; An Overview 176
GMM Estimation of DSGE Models 191
Simulation Estimators 197
Likelihood Methods 212
The Kalman Filter 214
The Prediction Error Decomposition of Likelihood 221
Numerical Tips 228
ML Estimation of DSGE Models 230
Two Examples 240
Calibration 248
A Definition 249
The Uncontroversial Parts 250
Choosing Parameters and Stochastic Processes 252
Model Evaluation 259
The Sensitivity of the Measurement 279
Savings, Investments, and Tax Cuts: An Example 282
Dynamic Macro Panels 288
From Economic Theory to Dynamic Panels 289
Panels with Homogeneous Dynamics 291
Dynamic Heterogeneity 304
To Pool or Not to Pool? 315
Is Money Superneutral? 321
Introduction to Bayesian Methods 325
Preliminaries 326
Decision Theory 335
Inference 336
Hierarchical and Empirical Bayes Models 345
Posterior Simulators 353
Robustness 370
Estimating Returns to Scale in Spain 370
Bayesian VARs 373
The Likelihood Function of an m-Variable VAR(q) 374
Priors for VARs 376
Structural BVARs 390
Time-Varying-Coefficient BVARs 397
Panel VAR Models 404
Bayesian Time Series and DSGE Models 418
Factor Models 449
Stochastic Volatility Models 427
Markov Switching Models 433
Bayesian DSGE Models 440
A Statistical Distributions 463
References 469
Index 487