Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-10T07:59:37.997Z Has data issue: false hasContentIssue false
  • English
  • Français

Estimating the FOMC’s interest rate rule with variable selection and partial regime switching

Published online by Cambridge University Press:  24 August 2021

Adam Check
Adam Check*
Affiliation:
University of St. Thomas, St Paul, MN 55105, USA
*
Email: ajc@stthomas.edu.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

When studying the Federal Open Market Committee’s (FOMC’s) interest rate rule, some authors, such as Gonzalez-Astudillo [(2018) Journal of Monetary, Credit, and Banking 50(1), 115–154.], find evidence for changes in inflation and output gap responses. Others, such as Sims and Zha [(2006) American Economic Review 96(1), 54–81.], only find evidence for a change in the variance of the interest rate rule. In this paper, I develop a new two-regime Markov-switching model that probabilistically performs variable selection and identification of parameter change for each variable in the model. I find substantial evidence that there have been changes in the FOMC’s response to the unemployment gap and in the volatility of the rule. When the FOMC responds strongly to the unemployment gap, I find a bimodal density for the inflation response coefficient. Despite the bimodal density, there is a low probability that there have been changes in the FOMC’s response to inflation.

Keywords

Monetary policyinterest rate ruleMarkov switchingmodel averagingC22C24C51C52E52
Type
Articles
Information
Macroeconomic Dynamics , Volume 27 , Issue 2 , March 2023 , pp. 297 - 330
Copyright
© The Author(s), 2021. Published by Cambridge University Press

References

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(03), 817–833.CrossRefGoogle Scholar
Aruoba, B. S., Mlikota, M., Schorfheide, F. and Villalvazo, S. (2021a) Svars with Occasionally-Binding Constraints. NBER Working Papers w28571, National Bureau of Economic Research, Inc.CrossRefGoogle Scholar
Aruoba, S. B., Cuba-Borda, P., Higa-Flores, K., Schorfheide, F. and Villalvazo, S. (2021) Piecewise-linear approximations and filtering for DSGE models with occasionally binding constraints. Review of Economic Dynamics 41, 96–120.CrossRefGoogle Scholar
Bae, J., Kim, C.-J. and Kim, D. (2012) The evolution of the monetary policy regimes in the US. Empirical Economics 43(2), 617–649.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, 139–53.CrossRefGoogle Scholar
Bianchi, F. (2013) Regime switches, agents’ beliefs, and post-world war ii US macroeconomic dynamics. The Review of Economic Studies 80(2), 463–490.CrossRefGoogle Scholar
Bianchi, F. and Melosi, L. (2017) Escaping the great recession. American Economic Review 107(4), 1030–1058.CrossRefGoogle Scholar
Boivin, J. (2006) Has US monetary policy changed? Evidence from drifting coefficients and real-time data. Journal of Money, Credit and Banking 38(5), 1149–1173.CrossRefGoogle Scholar
Carvalho, C., Nechio, F. and Tristao, T. (2019) Taylor Rule Estimation by OLS. Federal Reserve Bank of San Francisco Working Paper 2018-11. Available at https://doi.org/10.24148/wp2018-11https://doi.org/10.24148/wp2018-11.CrossRefGoogle Scholar
Castelnuovo, E., Greco, L. and Raggi, D. (2014) Policy rules, regime switches, and trend inflation: An empirical investigation for the United States. Macroeconomic Dynamics 18(04), 920–942.CrossRefGoogle Scholar
Chan, J. C. C., Koop, G. and Potter, S. M. (2013) A new model of trend inflation. Journal of Business & Economic Statistics 31(1), 94–106.CrossRefGoogle Scholar
Check, A. (2016) Regime Switching and the Monetary Economy. PhD thesis, University of Oregon.Google Scholar
Chib, S. (1998) Estimation and comparison of multiple change-point models. Journal of Econometrics 86, 221–241.CrossRefGoogle Scholar
Clarida, R., Galí, J. and Gertler, M. (2000) Monetary policy rules and macroeconomic stability: Evidence and some theory. The Quarterly Journal of Economics 115(1), 147–180.CrossRefGoogle Scholar
Cogley, T. and Sargent, T. J. (2005) Drift and volatilities: Monetary policies and outcomes in the post WWII US. Review of Economic Dynamics 8(2), 262–302.CrossRefGoogle Scholar
Coibion, O. and Gorodnichenko, Y. (2011) Monetary policy, trend inflation, and the great moderation: An alternative interpretation. American Economic Review 101(1), 341–70.CrossRefGoogle Scholar
Davig, T. and Leeper, E. M. (2011) Monetary-fiscal policy interactions and fiscal stimulus. European Economic Review 55, 211–27.CrossRefGoogle Scholar
Del Negro, M., Giannoni, M. P. and Schorfheide, F. (2015) Inflation in the great recession and New Keynesian models. American Economic Journal: Macroeconomics 7(1), 168–196.Google Scholar
Frühwirth-Schnatter, S. (2006) Finite Mixture and Markov Switching Models , Spring Series in Statistics, vol. 1. New York: Springer Science & Business Media.Google Scholar
George, E. I. and McCulloch, R. E. (1993) Variable selection via Gibbs sampling. Journal of the American Statistical Association 88(423), 881–89.CrossRefGoogle Scholar
George, E. I., Sun, D. and Ni, S. (2008) Bayesian stochastic search for VAR model restrictions. Journal of Econometrics 142(1), 553–580.CrossRefGoogle Scholar
Giles, J. A. and Giles, D. E. A. (1993) Pre-test estimation and testing in econometrics: Recent developments. Journal of Economic Surveys 7(2), 145–197.CrossRefGoogle Scholar
Gonzalez-Astudillo, M. (2018) Indentifying the stance of monetary policy at the zero lower bound: A Markov-switching estimation exploiting Monetary-Fiscal policy interdependence. Journal of Monetary, Credit, and Banking 50(1), 115–154.CrossRefGoogle Scholar
Hamilton, J. D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57(2), 357–84.CrossRefGoogle Scholar
Jeffreys, H. (1939) Theory of Probability, 3rd ed. New York: Oxford University Press.Google Scholar
Johannsen, B. K. and E. Mertens (forthcoming) A time-series model of interest rates with the effective lower bound. Journal of Money, Credit and Banking. https://doi.org/10.1111/jmcb.12771 CrossRefGoogle Scholar
Kaya, A., Golub, S., Kuperberg, M. and Lin, F. (2019) The federal reserve’s dual mandate and the inflation-unemployment tradeoff. Contemporary Economic Policy 37(4), 641–651.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, vol. 1. Cambridge, Massachusetts: The MIT Press.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), 1949–1966.CrossRefGoogle Scholar
Kim, S., Shephard, N. and Chib, S. (1998) Stochastic volatility: Likelihood inference and comparison with ARCH models. Review of Economic Studies 65(3), 361–93.CrossRefGoogle Scholar
Koop, G. and Korobilis, D. (2010) Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends®in Econometrics 3(4), 267–358.CrossRefGoogle Scholar
Koop, G. and Korobilis, D. (2018) Variational bayes inference in high-dimensional time-varying parameter models. arXiv preprint arXiv:1809.03031.CrossRefGoogle Scholar
Kozicki, S. and Tinsley, P. (2006) Minding the gap: Central bank estimates of the unemployment natural rate. Computational Economics 27(2), 295–327.CrossRefGoogle Scholar
Kozicki, S. and Tinsley, P. (2009) Perhaps the 1970s FOMC did what it said it did. Journal of Monetary Economics 56(6), 842–855.CrossRefGoogle Scholar
Kruschke, J. K. (2015) Doing Bayesian Data Analysis, 2nd ed. London: Academic Press/Elsevier.Google Scholar
Lee, K., Morley, J. and Shields, K. (2015) The meta Taylor rule. Journal of Money, Credit and Banking 47(1), 73–98.CrossRefGoogle Scholar
Lindley, D. V. (1957) A statistical paradox. Biometrica 44(1–2), 187–192.CrossRefGoogle Scholar
Murray, C. J., Nikolsko-Rzhevskyy, A. and Papell, D. H. (2015) Markov switching and the Taylor principle. Macroeconomic Dynamics 19(04), 913–930.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), 151–75.CrossRefGoogle Scholar
Orphanides, A. and Williams, J. C. (2005) The decline of activist stabilization policy: Natural rate misperceptions, learning, and expectations. Journal of Economic Dynamics and Control 29(11), 1927–1950.CrossRefGoogle Scholar
Piger, J. (2009) Models of regime changes. In: Encyclopedia of Complexity and System Science.CrossRefGoogle Scholar
Primiceri, G. E. (2005) Time varying structural vector autoregressions and monetary policy. Review of Economic Studies 72(3), 821–852.CrossRefGoogle Scholar
Romer, C. D. and Romer, D. H., (2004) A new measure of monetary shocks: Derivation and implications. American Economic Review 94(4), 1055–1084.CrossRefGoogle Scholar
Sims, C. A. and Zha, T. (2006) Were there regime switches in US monetary policy? American Economic Review 96(1), 54–81.CrossRefGoogle Scholar
Smets, F. and Wouters, R. (2003) An estimated dynamic stochastic general equilibrium model of the Euro area. Journal of the European Economic Association 1(5), 1123–1175.CrossRefGoogle Scholar
Soques, D. (2020) Timing and signals of monetary regime switching. Macroeconomic Dynamics, 1–35.Google Scholar
Taylor, J. B. (1993) Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy 39(1), 195–214.CrossRefGoogle Scholar
Taylor, J. B. (2013) A Review of Recent Monetary Policy. Economics Working Papers 13103, Hoover Institution, Stanford University.Google 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), 253–291.CrossRefGoogle Scholar