Abstract
We study how model uncertainty affects the understanding of the interest rate persistence using a generalized Taylor-rule function covering numerous submodels via model average approach. The data-driven weights can be regarded as a measure of power-sharing across monetary policy committee members. We show that the model uncertainty is important in Canada, France, and Sweden, and the implied weights indicate that the U.K. and the U.S. have a lower model uncertainty caused either by an over-influential chairman or the consistent agreement of committee members. The importance of model uncertainty can be emphasized by sequential estimation during the 2008 financial crisis.
Funding source: National Science Council
Award Identifier / Grant number: NSC 102-2410-H-259-005-
Acknowledgments
The authors would like to thank Christina Gerberding and Anthony Garratt for sharing real-time data. We have benefited immensely from the insightful comments provided by Shiu-Sheng Chen, Kuo-Hsuan Chin, Tai-Kuang Ho and Zong-Shin Liu as well as seminar participants at Feng Chia University, National Yunlin University of Science and Technology, and National Tsing Hua University. We appreciate the feedback and comments received from colleagues at the 21st Macroeconometric Modelling Workshop, the Taiwan Economic Association 2015 Annual Meeting, and the Taiwan Econometric Association 2020 Annual Meeting. Ming-Jen Chang thanks the National Science Council of Taiwan for financial support (NSC 102-2410-H-259-005-).
-
Research funding: None declared.
-
Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
-
Conflict of interest: The authors declare that they have no conflict of interest.
-
Ethical approval: This article does not contain any studies with human participants performed by any of the authors.

Interest rate i
t
, forecasted inflation rate
References
Andrews, D. W., and B. Lu. 2001. “Consistent Model and Moment Selection Procedures for GMM Estimation with Application to Dynamic Panel Data Models.” Journal of Econometrics 101: 123–64. https://doi.org/10.1016/s0304-4076(00)00077-4.Search in Google Scholar
Apel, M., M. Blix Grimaldi, and I. Hull. 2022. “How Much Information do Monetary Policy Committees Disclose? Evidence from the FOMC’s Minutes and Transcripts.” Journal of Money, Credit, and Banking 54: 1459–90. https://doi.org/10.1111/jmcb.12885.Search in Google Scholar
Bai, J., and S. Ng. 2002. “Determining the Number of Factors in Approximate Factor Models.” Econometrica 70: 191–221. https://doi.org/10.1111/1468-0262.00273.Search in Google Scholar
Bai, J., and S. Ng. 2008. “Forecasting Economic Time Series Using Targeted Predictors.” Journal of Econometrics 146: 304–17. https://doi.org/10.1016/j.jeconom.2008.08.010.Search in Google Scholar
Bai, J., and S. Ng. 2009. “Boosting Diffusion Indices.” Journal of Applied Econometrics 24: 607–29. https://doi.org/10.1002/jae.1063.Search in Google Scholar
Brock, W. A., S. N. Durlauf, and K. D. West. 2007. “Model Uncertainty and Policy Evaluation: Some Theory and Empirics.” Journal of Econometrics 136: 629–64. https://doi.org/10.1016/j.jeconom.2005.11.009.Search in Google Scholar
Buckland, S. T., K. P. Burnham, and N. H. Augustin. 1997. “Model Selection: An Integral Part of Inference.” Biometrics 53: 603–18. https://doi.org/10.2307/2533961.Search in Google Scholar
Bullard, J., and K. Mitra. 2007. “Determinacy, Learnability, and Monetary Policy Inertia.” Journal of Money, Credit, and Banking 39: 1177–212. https://doi.org/10.1111/j.1538-4616.2007.00062.x.Search in Google Scholar
Burnham, K., and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach In Ecological Modelling. New York: Springer Science & Business Media.Search in Google Scholar
Caputo, R., and A. Díaz. 2018. “Now and Always, the Relevance of the Taylor Rule in Europe.” International Journal of Finance & Economics 23: 41–6. https://doi.org/10.1002/ijfe.1601.Search in Google Scholar
Carvalho, C., F. Nechio, and T. Tristao. 2021. “Taylor Rule Estimation by OLS.” Journal of Monetary Economics 124: 140–54. https://doi.org/10.1016/j.jmoneco.2021.10.010.Search in Google Scholar
Castelnuovo, E. 2007a. “Cost Channel and the Price Puzzle: The Role of Interest Rate Smoothing.” Unpublished manuscript.Search in Google Scholar
Castelnuovo, E. 2007. “Taylor Rules and Interest Rate Smoothing in the Euro Area.” The Manchester School 75 (1): 1–16. https://doi.org/10.1111/j.1467-9957.2007.01000.x Search in Google Scholar
Chappell, H. W., and R. R. McGregor. 2017. “The Lower Bound and the Causes of Monetary Policy Inertia: Evidence from Sweden.” Applied Economics 49: 1132–46. https://doi.org/10.1080/00036846.2016.1213360.Search in Google Scholar
Chappell, H. W.Jr, and R. R. McGregor. 2018. “Committee Decision-Making at Sweden’s Riksbank.” European Journal of Political Economy 53: 120–33. https://doi.org/10.1016/j.ejpoleco.2017.07.005.Search in Google Scholar
Chappell, H. W.Jr, R. R. McGregor, and T. A. Vermilyea. 2014. “Power-Sharing in Monetary Policy Committees: Evidence from the United Kingdom and Sweden.” Journal of Money, Credit, and Banking 46: 665–92. https://doi.org/10.1111/jmcb.12121.Search in Google Scholar
Chen, J.-e., and M. Kashiwagi. 2017. “The Japanese Taylor Rule Estimated Using Censored Quantile Regressions.” Empirical Economics 52: 357–71. https://doi.org/10.1007/s00181-016-1074-8.Search in Google Scholar
Clarida, R., J. Galí, and M. Gertler. 1998. “Monetary Policy Rules in Practice: Some International Evidence.” European Economic Review 42: 1033–67. https://doi.org/10.1016/s0014-2921(98)00016-6.Search in Google Scholar
Clarida, R., J. Galí, and M. Gertler. 2000. “Monetary Policy Rules and Stability: Evidence and Some Theory.” Quarterly Journal of Economics 115: 147–80. https://doi.org/10.1162/003355300554692.Search in Google Scholar
Coibion, O., and Y. Gorodnichenko. 2012. “Why are Target Interest Rate Changes so Persistent.” American Economic Journal: Macroeconomics 4: 126–62. https://doi.org/10.1257/mac.4.4.126.Search in Google Scholar
Consolo, A., and C. A. Favero. 2009. “Monetary Policy Inertia: More a Fiction Than a Fact?” Journal of Monetary Economics 56: 900–6. https://doi.org/10.1016/j.jmoneco.2009.06.007.Search in Google Scholar
Curtis, D. 2005. “Monetary Policy and Economic Activity in Canada in the 1990s.” Canadian Public Policy/Analyse de Politiques 31: 59–77. https://doi.org/10.2307/3552595.Search in Google Scholar
Durbin, J. 1970. “Testing for Serial Correlation in Least-Squares Regression when Some of the Regressors Are Lagged Dependent.” Econometrica 38: 410–21. https://doi.org/10.2307/1909547.Search in Google Scholar
English, W. B., W. R. Nelson, and B. P. Sack. 2003. “Interpreting the Significance of the Lagged Interest Rate in Estimated Monetary Policy Rules.” Contributions to Macroeconomics 3: 1073. https://doi.org/10.2202/1534-6005.1073.Search in Google Scholar
Fève, P., J. Matheron, and C. Poilly. 2007. “Monetary Policy Dynamics in the Euro Area.” Economics Letters 96: 97–102. https://doi.org/10.1016/j.econlet.2006.12.030.Search in Google Scholar
Garratt, A., G. Koop, E. Mise, and S. P. Vahey. 2009. “Real-Time Prediction with U.K. Monetary Aggregates in the Presence of Model Uncertainty.” Journal of Business & Economic Statistics 27: 480–91. https://doi.org/10.1198/jbes.2009.07208.Search in Google Scholar
Gerdesmeier, D., F. Mongelli, and B. Roffia. 2010. “Interest Rate Setting by the Fed, the ECB, the Bank of Japan and the Bank of England Compared.” Comparative Economic Studies 52: 549–74. https://doi.org/10.1057/ces.2010.15.Search in Google Scholar
Hayo, B., and P. G. Méon. 2013. “Behind Closed Doors: Revealing the ECB’s Decision Rule.” Journal of International Money and Finance 37: 135–60. https://doi.org/10.1016/j.jimonfin.2013.06.005.Search in Google Scholar
Hayo, B., and M. Neuenkirch. 2011. “Canadian Interest Rate Setting: The Information Content of Canadian and U.S. Central Bank Communication.” Southern Economic Journal 78: 131–48. https://doi.org/10.4284/0038-4038-78.1.131.Search in Google Scholar
Kam, T. 2007. “Interest-Rate Smoothing in a Two-Sector Small Open Economy.” Journal of Macroeconomics 29: 283–304. https://doi.org/10.1016/j.jmacro.2005.04.006.Search in Google Scholar
Kam, T., K. Lees, and P. Liu. 2009. “Uncovering the Hit List for Small Inflation Targeters: A Bayesian Structural Analysis.” Journal of Money, Credit, and Banking 41: 583–618. https://doi.org/10.1111/j.1538-4616.2009.00224.x.Search in Google Scholar
Kim, T. H., and P. Mizen. 2010. “Estimating Monetary Reaction Functions at Near Zero Interest Rates.” Economics Letters 106: 57–60. https://doi.org/10.1016/j.econlet.2009.09.025.Search in Google Scholar
Kuttner, K. N., and A. S. Posen. 2004. “The Difficulty of Discerning What’s Too Tight: Taylor Rules and Japanese Monetary Policy.” The North American Journal of Economics and Finance 15: 53–74. https://doi.org/10.1016/j.najef.2003.12.004.Search in Google Scholar
Lubik, T. A., and F. Schorfheide. 2007. “Do Central Banks Respond to Exchange Rate Movements? A Structural Investigation.” Journal of Monetary Economics 54: 1069–87. https://doi.org/10.1016/j.jmoneco.2006.01.009.Search in Google Scholar
Ng, S., and P. Perron. 2005. “A Note on the Selection of Time Series Models.” Oxford Bulletin of Economics & Statistics 67: 115–34. https://doi.org/10.1111/j.1468-0084.2005.00113.x.Search in Google Scholar
Nikolsko-rzhevskyy, A. 2011. “Monetary Policy Estimation in Real Time : Forward-Looking Taylor Rules without Forward- Looking Data Stable.” Journal of Money, Credit, and Banking 43: 871–97. https://doi.org/10.1111/j.1538-4616.2011.00400.x.Search in Google Scholar
Onatski, A., and J. H. Stock. 2002. “Robust Monetary Policy under Model Uncertainty in a Small Model of the U.S. Economy.” Macroeconomic Dynamics 6: 85–110. https://doi.org/10.1017/s1365100502027050.Search in Google Scholar
Orphanides, A. 2001. “Monetary Policy Rules Based on Real-Time Data.” The American Economic Review 91: 964–85. https://doi.org/10.1257/aer.91.4.964.Search in Google Scholar
Peersman, G., and F. Smets. 1999. “The Taylor Rule: A Useful Monetary Policy Benchmark for the Euro Area?” International Finance 2: 85–116. https://doi.org/10.1111/1468-2362.00020.Search in Google Scholar
Proïa, F. 2018. “Testing for Residual Correlation of Any Order in the Autoregressive Process.” Communications in Statistics - Theory and Methods 47: 628–54. https://doi.org/10.1080/03610926.2017.1310240.Search in Google Scholar
Riboni, A., and F. J. Ruge-Murcia. 2010. “Monetary Policy by Committee: Consensus, Chairman Dominance, or Simple Majority?” Quarterly Journal of Economics 125: 363–416. https://doi.org/10.1162/qjec.2010.125.1.363.Search in Google Scholar
Rudebusch, G. D. 2002. “Term Structure Evidence on Interest Rate Smoothing and Monetary Policy Inertia.” Journal of Monetary Economics 49: 1161–87. https://doi.org/10.1016/s0304-3932(02)00149-6.Search in Google Scholar
Rudebusch, G. D. 2006. “Monetary Policy Inertia: Fact or Fiction?” International Journal of Central Banking 2: 85–135.10.2139/ssrn.864484Search in Google Scholar
Smales, L. A., and N. Apergis. 2016. “The Influence of FOMC Member Characteristics on the Monetary Policy Decision-Making Process.” Journal of Banking & Finance 64: 216–31. https://doi.org/10.1016/j.jbankfin.2015.12.002.Search in Google Scholar
Stock, J. H., and M. W. Watson. 2002. “Forecasting Using Principal Components from a Large Number of Predictors.” Journal of the American Statistical Association 97: 1167–79. https://doi.org/10.1198/016214502388618960.Search in Google Scholar
Stocker, T. 2007. “On the Asymptotic Bias of OLS in Dynamic Regression Models with Autocorrelated Errors.” Statistical Papers 48: 81–93. https://doi.org/10.1007/s00362-006-0317-8.Search in Google Scholar
Taylor, J. B. 1993. “Discretion versus Policy Rules in Practice.” Carnegie-Rochester Conference Series On Public Policy 39: 195–214. https://doi.org/10.1016/0167-2231(93)90009-l.Search in Google Scholar
Taylor, M. P., and E. Davradakis. 2006. “Interest Rate Setting and Inflation Targeting: Evidence of a Nonlinear Taylor Rule for the United Kingdom.” Studies in Nonlinear Dynamics & Econometrics 10: 1359. https://doi.org/10.2202/1558-3708.1359.Search in Google Scholar
Tillmann, P. 2010. “Monetary Policy Committees and Model Uncertainty.” In Working Paper.Search in Google Scholar
Tura-Gawron, K. 2017. “The Forecasts-Based Instrument Rule and Decision Making. How Closely Interlinked? The Case of Sweden.” Equilibrium. Quarterly Journal of Economics and Economic Policy 12: 295–315. https://doi.org/10.24136/eq.v12i2.16.Search in Google Scholar
Vassalli, M., and C. Dalle Nogare. 2006. “A Pressure-Augmented Taylor Rule for Italy.” In Working Paper.Search in Google Scholar
Woodford, M. 2003. Interest and Prices: Foundations of A Theory of Monetary Policy. Princeton: Princeton University Press.10.1515/9781400830169Search in Google Scholar
© 2023 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Original Articles
- Extreme Weather Events and Economic Activity: The Case of Low Water Levels on the Rhine River
- Interest Rate Persistence and Monetary Policy Rule in Light of Model Uncertainty
- The Impact of the German Fuel Discount on Prices at the Petrol Pump
- The Instability of the Market for Government Bonds in the EMU
Articles in the same Issue
- Frontmatter
- Original Articles
- Extreme Weather Events and Economic Activity: The Case of Low Water Levels on the Rhine River
- Interest Rate Persistence and Monetary Policy Rule in Light of Model Uncertainty
- The Impact of the German Fuel Discount on Prices at the Petrol Pump
- The Instability of the Market for Government Bonds in the EMU