Wolters, Maik Hendrik (2010): Estimating Monetary Policy Reaction Functions Using Quantile Regressions.
Download (365kB) | Preview
Monetary policy rule parameters are usually estimated at the mean of the interest rate distribution conditional on inflation and an output gap. This is an incomplete description of monetary policy reactions when the parameters are not uniform over the conditional distribution of the interest rate. I use quantile regressions to estimate parameters over the whole conditional distribution of the Federal Funds Rate. Inverse quantile regressions are applied to deal with endogeneity. Realtime data of inflation forecasts and the output gap are used. I find significant and systematic variations of parameters over the conditional distribution of the interest rate.
|Item Type:||MPRA Paper|
|Original Title:||Estimating Monetary Policy Reaction Functions Using Quantile Regressions|
|Keywords:||monetary policy rules; IV quantile regression; real-time data|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General
E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E58 - Central Banks and Their Policies
E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E52 - Monetary Policy
|Depositing User:||Maik Hendrik Wolters|
|Date Deposited:||13. Jul 2010 12:14|
|Last Modified:||12. Feb 2013 19:59|
ADAM, K., AND R. M. BILLI (2006): “Optimal Monetary Policy under Commitment with a Zero Bound on Nominal Interest Rates,” Journal of Money, Credit, and Banking, 38(7), 1877–1905.
AMEMIYA, T. (1982): “Two Stage Least Absolute Deviations Estimators,” Econometrica, 50, 689–711.
BLINDER, A. S. (1998): Central Banking in Theory and Practice. Cambridge, MA: MIT Press.
CHEN, L.-A., AND S. PORTNOY (1996): “Two-Stage Regresson Quantiles and Two-Stage Trimmed Least Squares Estimators for Structural Equation Models,” Communications in Statistics. Theory and Methods, 25(5), 1005–1032.
CHERNOZHUKOV, V., AND C. HANSEN (2001): “An IV Model of Quantile Treatment Effects,”Massachusetts Institute of Technology, Department of Economics,Working Paper 02-06.
CHERNOZHUKOV, V., AND C. HANSEN (2005): “An IV Model of Quantile Treatment Effects,” Econometrica, 73(1), 245–261.
CHEVAPATRAKUL, T., T.-H. KIM, AND P. MIZEN (2009): “The Taylor Principle and Monetary Policy Approaching a Zero Bound on Nominal Rates: Quantile Regression Results for the United States and Japan,” Journal of Money, Credit and Banking, 41(8), 1705–1723.
CLARIDA, R., J. GAL´I, AND M. GERTLER (1998): “Monetary Policy Rules in Practice: Some International Evidence,” European Economic Review, 42, 1003–1067.
(2000): “Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory,” Quarterly Journal of Economics, 115(1), 147–180.
CUKIERMAN, A., AND A. MUSCATELLI (2008): “Nonlinear Taylor Rules and Asymmetric Preferences in Central Banking: Evidence from the United Kingdom and the United States,” The B.E. Journal of Macroeconomics, 8(1).
DOLADO, J. J., R. MARIA-DOLORES, AND M. NAVEIRA (2005): “Are monetary-policy reaction functions asymmetric?: The role of nonlinearity in the Phillips curve,” European Economic Review, 49, 485 503.
FITZENBERGER, B. (1997): “The Moving Blocks Bootstrap and Robust Inference for Linear Least Squares and Quantile Regressions,” Journal of Econometrics, 82, 235–287.
GERLACH, S. (2000): “Asymmetric Policy Reactions and Inflation,” Working paper, Bank for International Settlements.
GREENSPAN, A. (1997): “Rules vs. discretionary monetary policy,” Speech at the 15th Anniversary Conference of the Center for Economic Policy Research at Stanford University, Stanford, California.
KATO, R., AND S.-I. NISHIYAMA (2005): “Optimal monetary policy when interest rates are bounded at zero,” Journal of Economic Dynamics & Control, 29, 97–133.
KOENKER, R., AND G. W. BASSET (1978): “Regression Quantiles,” Econometrica, 46(1), 33–50.
LEE, S. (2004): “Endogeneity in Quantile Regression Models: A Control Function Approach,” CeMMAP Working Paper, University College London, 08/04.
MEYER, L. H., E. T. SWANSON, AND V. WIELAND (2001): “NAIRU Uncertainty and Nonlinear Policy Rules,” American Economic Review, 91(2), 226–231.
ORPHANIDES, A. (2001): “Monetary Policy Rules Based on Real-Time Data,” American Economic Review, 91, 964–985.
ORPHANIDES, A. (2004): “Monetary Policy Rules, Macroeconomic Stability, and Inflation: A View from the Trenches,” Journal of Money, Credit and Banking, 36(2), 151–175.
ORPHANIDES, A., AND V. WIELAND (2000): “Efficient Monetary Policy Design Near Price Stability,” Journal of the Japanese and International Economies, 14, 327–365.
ORPHANIDES, A., AND V. WIELAND (2008): “Economic Projections and Rules of Thumb for Monetary Policy,” Federal Reserve Bank of St. Louis Review, 90(4), 307–324.
POOLE, W. (2006): “Understanding the Fed,” Speech at the Dyer County Chamber of Commerce Annual Membership Luncheon, Dyersburg, Tenn.
POWELL, J. L. (1983): “The Asymptotic Normality of Two-Stage Least Absolute Deviations Estimators,” Econometrica, 51(5), 1569–1575.
SCHALING, E. (1999): “The nonlinear Phillips Curve and inflation forecast targeting,” Bank of England Working Paper No. 98.
SURICO, P. (2007): “The Feds monetary policy rule and U.S. inflation: The case of asymmetric preferences,” Journal of Economic Dynamics & Control, 31, 305–324.
TAYLOR, J. B. (1993): “Discretion versus Policy Rules in Practice,” Carnegie-Rochester Conference Series on Public Policy, 39, 195–214.
TILLMANN, P. (2010): “Parameter uncertainty and non-linear monetary policy rules,” Macroeconomic Dynamics, forthcoming
TOMOHIRO SUGO, Y. T. (2005): “The optimal monetary policy rule under the non-negativity constraint on nominal interest rates,” Economics Letters, 89, 95100.