THE PERFORMANCE OF FORECAST-BASED MONETARY POLICY RULES UNDER MODEL UNCERTAINTY
Andrew Levin (),
Volker Wieland and
John Williams
No 203, Computing in Economics and Finance 2000 from Society for Computational Economics
Abstract:
In recent years, a number of researchers have advocated monetary policy rules for setting the short-term nominal interest rate rules in response to forecasts of inflation, rather than recent outcomes of a limited set of macroeconomic variables such as the well-known Taylor rule. Furthermore, such inflation-forecast-based rules are considered to describe the policy strategies of several inflation- targeting central banks fairly well. While outcome-based rules express the interest rate as an explicit function of available information, forecast-based rules are equilibrium relations which require a forecasting model in order to generate an interest rate prescription. In this paper, we compare the performance of outcome- and forecast-based rules in four different macro-econometric models of the U.S. economy---the Fuhrer-Moore model, the MSR model of Orphanides and Wieland, Taylor's Multi-Country Model and the FRB/US staff model---and investigate directly how robust such rules are to model uncertainty. We start by looking at a set of rules taken from the literature and then turn to investigate the characteristics of forecast-based rules that are optimized in one of our four models more systematically.We find that forecast-based rules yield at best only small benefits in stabilizing inflation, output and interest rates relative to optimized outcome-based rules, which respond to inflation, the output gap and the lagged interest rate. While forecast-based rules have been recommended in the literature, because they can account for policy transmission lags and embody much information on the state of the economy, these potential advantages are quantitatively unimportant in our models. However, we find that even if output stabilization only receives a small weight in the policy objective, constraining the policy rule to respond to the inflation forecast alone and not also directly to output causes a significant deterioration in performance. As to the choice of forecast horizon, for rules optimized in our models it is fairly short, typically between one- and four-quarters-ahead for a four-quarter moving average of inflation. Regarding the robustness properties of forecast-based rules, we obtain mixed results. Rules that are optimized in one of our models and use forecasts less than a year ahead usually also perform reasonably well in the other three models. However, rules that respond to expectations of inflation of more than a year into the future, which includes many rules proposed in the literature, generally are not robust to model uncertainty, owing to the sharp differences in output and inflation persistence in the four models. In fact, many of these rules may not even be associated with a stable unique rational expectations equilibrium in some of our models.We conclude that proposals that advocate interest rate rules which respond to inflation forecasts alone with a forecast horizon of more than one year should be treated with significant caution.
Date: 2000-07-05
References: Add references at CitEc
Citations: View citations in EconPapers (6)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
Journal Article: The Performance of Forecast-Based Monetary Policy Rules Under Model Uncertainty (2003) 
Working Paper: The performance of forecast-based monetary policy rules under model uncertainty (2003) 
Working Paper: The performance of forecast-based monetary policy rules under model uncertainty (2001) 
Working Paper: The performance of forecast-based monetary policy rules under model uncertainty (2001) 
Working Paper: The Performance of Forecast-Based Monetary Policy Rules under Model Uncertainty (2000) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf0:203
Access Statistics for this paper
More papers in Computing in Economics and Finance 2000 from Society for Computational Economics CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().