Asset price volatility and monetary policy rules: A dynamic model and empirical evidence

The issue of which measure of inflation ought to be targeted by policymakers has been extensively analysed, but the equally important issue of which inflation rate is actually targeted by policymakers in practice has been given much less attention. The paper addresses this question, using data for the UK, a country where differences among the alternative measures are especially marked. We estimate simple Taylor-like monetary policy rules, using several different measures of inflation. We find that plausible models can be obtained for each of the different measures, suggesting that it may not matter which is used in empirical analysis. Models using the RPI measure of inflation have a slight empirical advantage which reflects the ability better to explain monetary policy in more turbulent circumstances.

Download Full-text

Monetary policy rules under a fixed exchange rate regime: empirical evidence from China

Applied Financial Economics ◽

10.1080/09603100600749279 ◽

2007 ◽

Vol 17 (12) ◽

pp. 941-950 ◽

Cited By ~ 11

Author(s):

Shengzu Wang ◽

Jagdish Handa

Keyword(s):

Monetary Policy ◽

Exchange Rate ◽

Empirical Evidence ◽

Exchange Rate Regime ◽

Policy Rules ◽

Monetary Policy Rules ◽

Fixed Exchange Rate

Download Full-text

MONETARY POLICY RULES UNDER UNCERTAINTY: EMPIRICAL EVIDENCE, ADAPTIVE LEARNING, AND ROBUST CONTROL

Macroeconomic Dynamics ◽

10.1017/s1365100505040332 ◽

2005 ◽

Vol 9 (5) ◽

pp. 651-681 ◽

Cited By ~ 3

Author(s):

WENLANG ZHANG ◽

WILLI SEMMLER

Keyword(s):

Monetary Policy ◽

Robust Control ◽

Empirical Evidence ◽

Adaptive Learning ◽

Learning Algorithm ◽

Model Misspecification ◽

State Space Model ◽

State Variables ◽

Policy Rules ◽

Monetary Policy Rules

We first explore empirical evidence of parameter and shock uncertainties in a state-space model with Markov switching. The evidence indicates that uncertainties in the U.S. economy have been too great to accurately define monetary policy rules. We then explore monetary policy rules under uncertainty with two approaches: the RLS learning algorithm and robust control. The former allows the parameters to be learned for a given model. Yet, as our results of the RLS learning in a framework of optimal control indicate, the state variables do not necessarily converge even in a nonstochastic model. The latter, by permitting uncertainty with respect to model misspecification, allows for a broader framework. Our study on robust control shows that robust optimal monetary policy rules reveal a stronger response to fluctuations in inflation and output than when no uncertainty exists, implying that uncertainty does not necessarily require caution.

Download Full-text