Eo, Yunjong (2008): Bayesian Analysis of DSGE Models with Regime Switching.
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I estimate DSGE models with recurring regime changes in monetary policy (inflation target and reaction coefficients), technology (growth rate and volatility), and/or nominal price rigidities. In the models, agents are assumed to know deep parameter values but make probabilistic inference about prevailing and future regimes based on Bayes’ rule. I develop an estimation method that takes these probabilistic inferences into account when relating state variables to observed data. In an application to postwar U.S. data, I find stronger support for regime switching in monetary policy than in technology or nominal rigidities. In addition, a model with regime switching policy that conforms to the long-run Taylor principle given in Davig and Leeper (2007) is preferred to a determinacy-indeterminacy model motivated by Lubik and Schorfheide (2004). These empirical results indicate that, even though a passive policy regime produced more volatility in the economy from the early 1970s to the mid-1980s, the economy can be explained by determinacy over the entire postwar period, implying no role for sunspot shocks in explaining the changes in volatility.
|Item Type:||MPRA Paper|
|Original Title:||Bayesian Analysis of DSGE Models with Regime Switching|
|Keywords:||New Keynesian DSGE; Markov-switching; Monetary Policy; Indeterminacy; Long-run Taylor Principle; Bayesian Analysis;|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation
C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection
E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E52 - Monetary Policy
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General
|Depositing User:||Yunjong Eo|
|Date Deposited:||10 Mar 2009 10:00|
|Last Modified:||13 Feb 2014 18:05|
Ahmed, S., A. Levin, and B. A. Wilson (2004): “Recent U.S. Macroeconomic Stability: Good Policies, Good Practices, or Good Luck?,” The Review of Economics and Statistics, 86(3), 824–832.
An, S., and F. Schorfheide (2007): “Bayesian Analysis of DSGE Models,” Econometric Reviews, 26(2-4), 113–172.
Boivin, J., and M. P. Giannoni (2006): “Has Monetary Policy Become More Effective?,” The Review of Economics and Statistics, 88(3), 445–462.
Bullard, J., and K. Mitra (2007): “Determinacy, Learnability, and Monetary Policy Inertia,” Journal of Money, Credit and Banking, 39(5), 1177–1212.
Chib, S., and E. Greenberg (1995): “Understanding the Metropolis-Hastings Algorithm,” The American Statistician, 49(4), 327–335.
Chib, S., and S. Ramamurthy (2008): “MCMC Methods for Bayesian Estimation of DSGE Models,” Working Paper.
Clarida, R., J. Gali, and M. Gertler (2000): “Monetary Policy Rules And Macroeconomic Stability: Evidence And Some Theory,” The Quarterly Journal of Economics, 115(1), 147–180.
Davig, T., and E. M. Leeper (2007): “Generalizing the Taylor Principle,” American Economic Review, 97(3), 607–635.
Farmer, R. E., D. F. Waggoner, and T. Zha (2008): “Minimal state variable solutions to Markov-switching rational expectations models,” Working Paper 2008- 23, Federal Reserve Bank of Atlanta.
Hamilton, J. D. (1989): “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle,” Econometrica, 57(2), 357–84.
(1994): Time Series Analysis. Princeton University Press. Justiniano, A., and G. E. Primiceri (2008): “The Time-Varying Volatility of Macroeconomic Fluctuations,” The American Economic Review, 98(3), 604–641.
Kim, C.-J. (1994): “Dynamic linear models with Markov-switching,” Journal of Econometrics, 60(1-2), 1–22
Kim, C.-J., and C. R. Nelson (1999a): “Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle,” The Review of Economics and Statistics, 81(4), 608–616.
(1999b): State-Space Models with Regime Switching: Classical and Gibbs- Sampling Approaches with Applications. The MIT Press.
Lubik, T. A., and F. Schorfheide (2003): “Computing Sunspot Equilibria in Linear Rational Expectations Models,” Journal of Economic Dynamics and Control, 28(2), 273–285.
(2004): “Testing for Indeterminacy: An Application to U.S. Monetary Policy,” American Economic Review, 94(1), 190–217.
McConnell, M. M., and G. Perez-Quiros (2000): “Output Fluctuations in the United States: What Has Changed since the Early 1980’s?,” American Economic Review, 90(5), 1464–1476.
Schorfheide, F. (2005): “Learning and Monetary Policy Shifts,” Review of Economic Dynamics, 8(2), 392–419.
Sims, C. A. (2002): “Solving Linear Rational Expectations Models,” Computational Economics, 20(1-2), 1–20.
Sims, C. A., D. F. Waggoner, and T. Zha (2008): “Methods for inference in large multiple-equation Markov-switching models,” .
Stock, J. H., and M. W. Watson (1996): “Evidence on Structural Instability in Macroeconomic Time Series Relations,” Journal of Business & Economic Statistics, 14(1), 11–30.
(2002): “Has the Business Cycle Changed, and Why?,” NBER Macroeconomics Annual, 17, 159–218.
Woodford, M. (2003): Interest and Prices: Foundations of a Theory of Monetary Policy. Princeton University Press.
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