Estimating Monetary Policy Reaction Functions Using Quantile Regressions

36 Pages Posted: 28 Jun 2010 Last revised: 28 Sep 2011

See all articles by Maik H. Wolters

Maik H. Wolters

Kiel Institute for the World Economy - IFW

Date Written: September 21, 2011

Abstract

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. Real-time data of inflation forecasts and the output gap are used. I find significant and systematic variations of parameters over the conditional interest rate distribution. Testing for structural changes in regression quantiles shows that these parameter variations cannot be explained by preference shifts of the Fed. Asymmetric interest rate responses can rather be related to expansions and recessions and are consistent with a recession avoidance preference of the Fed during the Volcker-Greenspan era.

Keywords: Monetary Policy Rules, IV Quantile Regression, Real-Time Data

JEL Classification: C14, E52, E58

Suggested Citation

Wolters, Maik H., Estimating Monetary Policy Reaction Functions Using Quantile Regressions (September 21, 2011). Available at SSRN: https://ssrn.com/abstract=1631788 or http://dx.doi.org/10.2139/ssrn.1631788

Maik H. Wolters (Contact Author)

Kiel Institute for the World Economy - IFW ( email )

United States

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