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TIMING AND SIGNALS OF MONETARY REGIME SWITCHING

Published online by Cambridge University Press:  24 August 2020

Daniel Soques*
Affiliation:
University of North Carolina Wilmington
*
Address correspondence to: Daniel Soques, Department of Economics and Finance, University of North Carolina Wilmington, 601 South College Rd, Wilmington, NC28403-5945, USA. e-mail: [email protected]. Phone: +(919) 818-5575.

Abstract

This study investigates if the reaction function of the Federal Reserve switches between two distinct policy rules. Using a time-varying transition probability framework, we also determine if forward-looking macroeconomic or financial covariates signal an impending monetary regime switch. We find that US monetary policy is best described by a Markov-switching model with two regime processes, one of which controls for heteroskedasticity in the shocks to the policy rule. We find that the Fed switches between an aggressive regime with a relatively high weight on inflation and a dovish regime that is less responsive to inflationary pressures. We find that an increase in private forecasters’ expectations of an impending recession signals a switch from the more aggressive policy regime to the less aggressive regime. A recovery in equity returns signals a return back to the more aggressive regime.

Type
Articles
Copyright
© 2020 Cambridge University Press

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Footnotes

Jordan Fonville provided research assistance. The author benefitted from comments from two anonymous referees and conversations with Santiago Barraza, Yoosoon Chang, Adam Check, Taeyoung Doh, Andrew Foerster, Neville Francis, Ming Chien Lo, Michael Owyang, Laura Jackson Young, and seminar participants at the Federal Reserve Bank of Richmond, the 2017 Conference of the Society for Economic Measurement, the 2018 Symposium of the Society of Nonlinear Dynamics and Econometrics, the 2018 IAAE Annual Conference, the 2018 Midwestern Econometrics Group Conference, and the 2019 Annual Meeting of the Financial Management Association. The author is indebted to Athanasios Orphanides for providing data on the real-time output gap.

References

Adrian, T., Boyarchenko, N. and Giannone, D. (2019) Vulnerable growth. American Economic Review 109(4), 12631289.CrossRefGoogle Scholar
Ahmad, S. (2016) A multiple threshold analysis of the Fed’s balancing act during the great moderation. Economic Modelling 55, 343358.CrossRefGoogle Scholar
Alba, J. D. and Wang, P. (2017) Taylor rule and discretionary regimes in the united states: Evidence from a k-state Markov regime-switching model. Macroeconomic Dynamics 21(3), 817833.CrossRefGoogle Scholar
Alcidi, C., Flamini, A. and Fracasso, A. (2011) Policy regime changes, judgment and taylor rules in the greenspan era. Economica 78(309), 89107.CrossRefGoogle Scholar
Assenmacher-Wesche, K. (2006) Estimating central banks preferences from a time-varying empirical reaction function. European Economic Review 50(8), 19511974.CrossRefGoogle Scholar
Baetje, F. and Friedrici, K. (2016) Does cross-sectional forecast dispersion proxy for macroeconomic uncertainty? new empirical evidence. Economics Letters 143, 3843.CrossRefGoogle Scholar
Banaian, K. and Lo, M. C. (2010) Interpreting U.S. Monetary Policy using the Taylor Rule: A Regime-Switching Approach. Working Paper.Google Scholar
Barthélemy, J. and Marx, M. (2017) Solving endogenous regime switching models. Journal of Economic Dynamics and Control 77, 125.CrossRefGoogle Scholar
Baxa, J., Horváth, R. and Vašček, B. (2013) Time-varying monetary-policy rules and financial stress: Does financial instability matter for monetary policy? Journal of Financial Stability 9(1), 117138.CrossRefGoogle Scholar
Bennani, H., Kranz, T. and Neuenkirch, M. (2018) Disagreement between fomc members and the Fed’s staff: New insights based on a counterfactual interest rate. Journal of Macroeconomics 58, 139153.CrossRefGoogle Scholar
Best, G. and Hur, J. (2017) Bad Luck, Bad Policy, and Learning?A Markov-Switching Approach to Understanding Postwar U.S. Macroeconomic Dynamics. Working Paper.CrossRefGoogle Scholar
Bianchi, F. (2013) Regime switches, agents’ beliefs, and post-world war ii U.S. macroeconomic dynamics. The Review of Economic Studies 80(2), 463490.CrossRefGoogle Scholar
Bomberger, W. A. (1996) Disagreement as a measure of uncertainty. Journal of Money, Credit and Banking 28(3), 381392.CrossRefGoogle Scholar
Carter, C. K. and Kohn, R. (1994) On Gibbs sampling for state space models. Biometrika 81(3), 541553.CrossRefGoogle Scholar
Castro, V. (2011) Can central banks monetary policy be described by a linear (augmented) taylor rule or by a nonlinear rule? Journal of Financial Stability 7(4), 228246.CrossRefGoogle Scholar
Castro, V. and Sousa, R. M. (2012) How do central banks react to wealth composition and asset prices? Economic Modelling 29(3), 641653.CrossRefGoogle Scholar
Chang, Y. and Kwak, B. (2017) U.S. Monetary-Fiscal Regime Changes in the Presence of Endogenous Feedback in Policy Rules. CAEPR Working Paper: No. 2017-016.Google Scholar
Check, A. (2017) Estimating the FOMCs Interest Rate Rule: A Markov-Switching Stochastic Search Variable Selection Approach. Working Paper.Google Scholar
Chib, S. (1996) Calculating posterior distributions and modal estimates in Markov mixture models. Journal of Econometrics 75(1), 7997.CrossRefGoogle Scholar
Choi, J. and Foerster, A. (2016) Optimal Monetary Policy Regime Switches. Federal Reserve Bank of Kansas City Working Paper.Google Scholar
Creel, J. and Hubert, P. (2015) Has inflation targeting changed the conduct of monetary policy? Macroeconomic Dynamics 19(1), 121.CrossRefGoogle Scholar
Davig, T. and Doh, T. (2014) Monetary policy regime shifts and inflation persistence. The Review of Economics and Statistics 96(5), 862875.CrossRefGoogle Scholar
Diebold, F. X., Lee, J.-H. and Weinbach, G. C. (1994) Regime switching with time-varying transition probabilities. Business Cycles: Durations, Dynamics, and Forecasting 1, 144165.Google Scholar
Estrella, A. and Mishkin, F. S. (1998) Predicting us recessions: Financial variables as leading indicators. Review of Economics and Statistics 80(1), 4561.CrossRefGoogle Scholar
Filardo, A. J. (1994) Business-cycle phases and their transitional dynamics. Journal of Business & Economic Statistics 12(3), 299308.Google Scholar
Foerster, A. T. (2016) Monetary policy regime switches and macroeconomic dynamics*. International Economic Review 57(1), 211230.CrossRefGoogle Scholar
Francis, N. R., Jackson, L. E. and Owyang, M. T. (2020) How has empirical monetary policy analysis in the us changed after the financial crisis? Economic Modelling 84, 309321.CrossRefGoogle Scholar
Fuhrer, J. and Tootell, G. (2008) Eyes on the prize: How did the Fed respond to the stock market? Journal of Monetary Economics 55(4), 796805.CrossRefGoogle Scholar
Galí, J., Smets, F. and Wouters, R. (2012) Slow recoveries: A structural interpretation. Journal of Money, Credit and Banking 44(s2), 930.CrossRefGoogle Scholar
Giacomini, R. and Rossi, B. (2006) How stable is the forecasting performance of the yield curve for output growth? Oxford Bulletin of Economics and Statistics 68, 783795.CrossRefGoogle Scholar
Gnabo, J.-Y. and Moccero, D. N. (2015) Risk management, nonlinearity and aggressiveness in monetary policy: The case of the US Fed. Journal of Banking & Finance 55, 281294. Global Governance and Financial Stability.CrossRefGoogle Scholar
Gonzalez-Astudillo, M. (2018) Identifying the stance of monetary policy at the zero lower bound: A Markov-switching estimation exploiting monetary-fiscal policy interdependence. Journal of Money, Credit and Banking 50(1), 115154.CrossRefGoogle Scholar
Goodfriend, M. (1991) Interest rates and the conduct of monetary policy. Carnegie-Rochester Conference Series on Public Policy 34, 730.CrossRefGoogle Scholar
Hamilton, J. D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57(2), 357384.CrossRefGoogle Scholar
Jaimovich, N. and Siu, H. E. (2020) Job polarization and jobless recoveries. Review of Economics and Statistics, 102(1), 129147.CrossRefGoogle Scholar
Kaufmann, S. (2015) K-state switching models with time-varying transition distributions does loan growth signal stronger effects of variables on inflation? Journal of Econometrics 187(1), 8294.CrossRefGoogle Scholar
Kim, C.-J. and Nelson, C. R. (1999) State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications. MIT Press Books, Cambridge, MA.Google Scholar
Kim, C.-J. and Nelson, C. R. (2006) Estimation of a forward-looking monetary policy rule: A time-varying parameter model using ex post data. Journal of Monetary Economics 53(8), 19491966.CrossRefGoogle Scholar
Lahiri, K. and Sheng, X. (2010) Measuring forecast uncertainty by disagreement: The missing link. Journal of Applied Econometrics 25(4), 514538.CrossRefGoogle Scholar
Lakdawala, A. (2016) Changes in federal reserve preferences. Journal of Economic Dynamics and Control 70, 124143.CrossRefGoogle Scholar
Laubach, T. and Williams, J. C. (2003) Measuring the natural rate of interest. The Review of Economics and Statistics 85(4), 10631070.CrossRefGoogle Scholar
Lei, X. and Tseng, M. C. (2019) “Wait-and-see” monetary policy. Macroeconomic Dynamics 23(5), 17931814.CrossRefGoogle Scholar
Liu, Z., Waggoner, D. F. and Zha, T. (2009) Asymmetric expectation effects of regime shifts in monetary policy. Review of Economic Dynamics 12(2), 284303.CrossRefGoogle Scholar
Liu, Z., Waggoner, D. F. and Zha, T. (2011) Sources of macroeconomic fluctuations: A regime-switching DSGE approach. Quantitative Economics 2(2), 251301.CrossRefGoogle Scholar
Lo, M. C. and Piger, J. (2005) Is the response of output to monetary policy asymmetric? evidence from a regime-switching coefficients model. Journal of Money, Credit and Banking, 865886.CrossRefGoogle Scholar
Orphanides, A. (2004) Monetary policy rules, macroeconomic stability, and inflation: A view from the trenches. Journal of Money, Credit and Banking 36(2), 151175.CrossRefGoogle Scholar
Owyang, M. T. and Ramey, G. (2004) Regime switching and monetary policy measurement. Journal of Monetary Economics 51(8), 15771597.CrossRefGoogle Scholar
Pace, P. D. (2013) Gross domestic product growth predictions through the yield spread: Time-variation and structural breaks. International Journal of Finance & Economics 18(1), 124.CrossRefGoogle Scholar
Partouche, H. (2007) Time-Varying Coefficients in a GMM Framework: Estimation of a Forward Looking Taylor Rule for the Federal Reserve. Banque de France Working Paper: No. 177.CrossRefGoogle Scholar
Perruchoud, A. (2009) Estimating a taylor rule with Markov switching regimes for switzerland. Swiss Journal of Economics and Statistics (SJES) 145(II), 187220.CrossRefGoogle Scholar
Petersen, K. (2007) Does the Federal Reserve Follow a Non-Linear Taylor Rule? Economics Working Papers: No. 200737.Google Scholar
Qin, T. and Enders, W. (2008) In-sample and out-of-sample properties of linear and nonlinear taylor rules. Journal of Macroeconomics 30(1), 428443.CrossRefGoogle Scholar
Rabanal, P. (2004) Monetary Policy Rules and the U.S. Business Cycle; Evidence and Implications. IMF Working Papers: No. 04/164, International Monetary Fund, Sep.CrossRefGoogle Scholar
Rich, R. and Tracy, J. (2010) The relationships among expected inflation, disagreement, and uncertainty: Evidence from matched point and density forecasts. The Review of Economics and Statistics 92(1), 200207.CrossRefGoogle Scholar
Rigobon, R. and Sack, B. (2003) Measuring the reaction of monetary policy to the stock market. The Quarterly Journal of Economics 118(2), 639669.CrossRefGoogle Scholar
Rudebusch, G. D. (1995) Federal reserve interest rate targeting, rational expectations, and the term structure. Journal of Monetary Economics 35(2), 245274.CrossRefGoogle Scholar
Rudebusch, G. D. (2005) Monetary Policy and Asset Price Bubbles. FRBSF Economic Letter.Google Scholar
Schorfheide, F. (2005) Learning and monetary policy shifts. Review of Economic Dynamics 8(2), 392419. Monetary Policy and Learning.CrossRefGoogle Scholar
Sill, K. (2012) Measuring economic uncertainty using the survey of professional forecasters. Federal Reserve Bank of Philadelphia Business Review 92, 1627.Google Scholar
Sill, K. (2014) Forecast disagreement in the survey of professional forecasters. Business Review Q2, 1524.Google Scholar
Sims, C. A. and Zha, T. (2006) Were there regime switches in U.S. monetary policy? American Economic Review 96(1), 5481.CrossRefGoogle Scholar
Stock, J. H. and Watson, M. W. (1989) New indexes of coincident and leading economic indicators. NBER Macroeconomics Annual 4, 351394.CrossRefGoogle Scholar
Taylor, J. B. (1993) Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy 39, 195214.CrossRefGoogle Scholar
Taylor, J. B. (2011) Macroeconomic lessons from the great deviation. In: Acemoglu, D. and Woodford, M. (eds.), NBER Macroeconomics Annual 2010, vol. 25, pp. 387395. University of Chicago Press.Google Scholar
Woodford, M. (1999) Optimal monetary policy inertia. The Manchester School 67(s1), 135.CrossRefGoogle Scholar
Wu, J. C. and Xia, F. D. (2016) Measuring the macroeconomic impact of monetary policy at the zero lower bound. Journal of Money, Credit and Banking 48(2–3), 253291.CrossRefGoogle Scholar
Zarnowitz, V. and Lambros, L. A. (1987) Consensus and uncertainty in economic prediction. Journal of Political Economy 95(3), 591621.CrossRefGoogle Scholar