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Endogenous Monetary Policy Regimes and the Great Moderation

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  • Ana Beatriz Galvao
  • Massimiliano Marcellino

Abstract

This paper contributes to the literature on the changing transmission mechanism of monetary policy by introducing a model whose parameter evolution explicitly depends on the conduct of monetary policy. We find that the model fits the data well, in particular when complemented with an estimated break around 1985 that could be associated with the re-gained credibility of the central bank. The responses of output and inflation to policy shocks change not only because of the break in 1985 but also according to the monetary policy stance: policy shocks have stronger negative e¤ects when policy is tight. There is also evidence in favour of large changes in the volatility of the output equation, but not of inflation. A set of counterfactual experiments indicate that good policy and good luck contributed to the great moderation, but neither of them can fully explain it. A more general variation in the model dynamics underlying the shock transmission mechanism is required.

Suggested Citation

  • Ana Beatriz Galvao & Massimiliano Marcellino, 2010. "Endogenous Monetary Policy Regimes and the Great Moderation," Economics Working Papers ECO2010/22, European University Institute.
    • Handle: RePEc:eui:euiwps:eco2010/22
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    Cited by:

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    2. Ballarin, Giovanni & Dellaportas, Petros & Grigoryeva, Lyudmila & Hirt, Marcel & van Huellen, Sophie & Ortega, Juan-Pablo, 2024. "Reservoir computing for macroeconomic forecasting with mixed-frequency data," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1206-1237.
    3. Nakajima Jouchi, 2011. "Monetary Policy Transmission under Zero Interest Rates: An Extended Time-Varying Parameter Vector Autoregression Approach," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-24, October.
    4. Jouchi Nakajima & Mike West, 2013. "Bayesian Analysis of Latent Threshold Dynamic Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 151-164, April.
    5. Sergei Seleznev, 2019. "Truncated priors for tempered hierarchical Dirichlet process vector autoregression," Bank of Russia Working Paper Series wps47, Bank of Russia.
    6. Jolejole-Foreman, Maria Christina & Mallory, Mindy L. & Baylis, Katherine R., 2013. "Impact of Wheat and Rice Export Ban on Indian Market Integration," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150595, Agricultural and Applied Economics Association.
    7. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.
    8. Sandra Eickmeier & Wolfgang Lemke & Massimiliano Marcellino, 2015. "Classical time varying factor-augmented vector auto-regressive models—estimation, forecasting and structural analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 493-533, June.

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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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