Real Business Cycles: A Reader

By James E. Hartley; Kevin D. Hoover et al. | Go to book overview

CHAPTER 19

INTERNATIONAL ECONOMIC REVIEW

Vol. 36, No. 2, May 1995

SENSITIVITY ANALYSIS AND MODEL EVALUATION IN SIMULATED DYNAMIC GENERAL EQUILIBRIUM ECONOMIES*

BY FABIO CANOVA 1

This paper describes a Monte Carlo procedure to evaluate dynamic nonlinear general equilibrium macro models. The procedure makes the choice of parameters and the evaluation of the model less subjective than standard calibration techniques, it provides more general restrictions than estimation by simulation approaches and provides a way to conduct global sensitivity analysis for reasonable perturbations of the parameters. As an illustration the technique is applied to three examples involving different models and statistics.


1. INTRODUCTION

A growing body of research in the applied macroeconomic literature uses simulation techniques to derive the time series properties of nonlinear stochastic general equilibrium models, to compare them to real world data and to evaluate policy options (see e.g. King, Plosser, and Rebelo 1988, or Cooley and Hansen 1990). In implementing numerical analyses of general equilibrium models, one has to overcome four hurdles. First, an economy must be specified and functional forms for its primitives selected. Second, a decision rule for the endogenous variables in terms of the exogenous (and predetermined) variables and of the parameters must be computed. Third, given the probability structure of the economy, values for the parameters must be chosen. Fourth, the closeness of functions of simulated and the actual data must be assessed in a metric which is relevant to the problem and policy conclusions, if any, should be drawn.

While models are often specified with an eye to analytical tractability and there has been progress in developing techniques to numerically approximate unknown decision rules for the endogenous variables (see e.g. Sims 1984, Coleman 1989, Novales 1990, Baxter 1991, Tauchen and Hussey 1991, Judd 1992, Marcet 1992 and the January 1990 issue of the Journal of Business and Economic Statistics), surprisingly little attention has been paid to the problems connected with the other two steps of the simulations. In particular, the selection of the parameters and the evaluation of the simulation results have been undertaken using procedures which

* Manuscript received October 1991; revised November 1994.

1 I would like to thank David Backus, Javier Diaz, Frank Diebold, John Geweke, Eric Ghysels, Gary Hansen, Bruce E. Hansen, Jane Marrinan, Yaw Nyarko, Adrian Pagan, Franco Peracchi, Victor Rios-Rull, Gregor Smith, Herman van Dijk, Randall Wright, two anonymous referees, and the participants of seminars at Brown University, European University Institute, New York University, University of Montreal, University of Rochester, University of Pennsylvania, University of Rome and Carlos III Madrid for comments and suggestions.

477

-355-

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Real Business Cycles: A Reader
Table of contents

Table of contents

  • Title Page iii
  • Contents vii
  • Acknowledgements xi
  • Part I - Introduction 1
  • Chapter 1 - The Limits of Business Cycle Research 3
  • Notes 34
  • Chapter 2 - A User's Guide to Solving Real Business Cycle Models 43
  • Part II - The Foundations of Real Business Cycle Modeling 55
  • Chapter 3 57
  • Chapter 4 83
  • References 96
  • Chapter 5 97
  • Chapter 6 102
  • Chapter 7 108
  • Part III - Some Extensions 147
  • Chapter 8 149
  • Chapter 9 168
  • References 178
  • Chapter 10 - Current Real-Business-Cycle Theories and Aggregate Labor-Market Fluctuations 179
  • Chapter 11 - The Inflation Tax in a Real Business Cycle Model 200
  • Part IV - The Methodology of Equilibrium Business Cycle Models 217
  • Chapter 12 219
  • Chapter 13 237
  • Chapter 14 254
  • Chapter 15 272
  • Part V - The Critique of Calibration Methods 293
  • Chapter 16 295
  • Chapter 17 - Measures of Fit for Calibrated Models 302
  • Chapter 18 333
  • Chapter 19 355
  • Part VI - Testing the Real Business Cycle Model 381
  • Chapter 20 - Business Cycles: Real Facts and a Monetary Myth 383
  • References 398
  • Chapter 21 399
  • Chapter 22 - Evaluating a Real Business Cycle Model 431
  • Chapter 23 462
  • Chapter 24 496
  • Chapter 25 513
  • Chapter 26 - Did Technology Shocks Cause the 1990-1991 Recession? 533
  • Part VII - The Solow Residual 541
  • Chapter 27 - Technical Change and the Aggregate Production Function 543
  • Chapter 28 552
  • Chapter 29 564
  • Chapter 30 - Output Dynamics in Real-Business-Cycle Models 571
  • Part VIII - Filtering and Detrending 591
  • Chapter 31 - Postwar U. S. Business Cycles: an Empirical Investigation 593
  • Chapter 32 609
  • Chapter 33 626
  • Index 652
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