An econometric specification of monetary policy dark art

Ielpo, Florian and Guégan, Dominique (2006): An econometric specification of monetary policy dark art.

Abstract

The classical Taylor rules usually do not yield the same estimation error when working in a monthly or a quarterly framework. This brings us to the conclusion that there must be something that monthly Taylor rules can capture and that the quarterly one cannot: we postulate that it simply boils down to the fact that the target rate’s changes are irregularly spaced in time. So as to tackle this issue, we propose to split the target rate chronicle between changes in the target and the associated durations, that is the time spending between two changes in the target rate. In this framework, we propose to consider that changes in rate can be regarded as a real monetary policy decision, whereas the duration period between two changes can be related to a ”wait and see” position or some fine tuning problematic. To show that both these features of monetary policy do not react to the same fundamentals, we propose an econometric understanding of the Fed’s reaction function using a new model derived from financial econometrics that has been proposed by Engle and Russell (2005). We propose to model the changes in target rates with a classical ordered probit and the durations with an autoregressive conditional duration model. We extracted the Fed anticipations regarding inflation and activity using some factor based method, and used these factors as explanatory variables for the changes in rates and the related durations. We show that the target rate level, the scale of the change in target rate and the associated duration do not necessarily react to the same factors and if they do, the impact can be different. This empirical result supports the idea that durations and scale of the change in target rate deserve equal attention when modeling a Central Bank reaction function.

• Item Type: MPRA Paper
• Institution: Centre d'Economie de la Sorbonne
• Language: English
• Keywords: Taylor rule; duration models; probit models; Central Bank expectations; factor based methods
• Subjects: E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E52 - Monetary Policy; E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E58 - Central Banks and Their Policies

References

Aguiar-Conraria, L. (2003). Forecasting in data-rich environments. Department of Economics, Cornell University and Minho University.

Bauwens, L. and Giot, P. (1998). Asymmetric acd models: Introducing price information in acd models with a two state transition model. Technical Report 9844, Catholique de Louvain - Center for Operations Research and Economics.

Bernanke, B. S. and Boivin, J. (2001). Monetary policy in a data-rich environment. NBER working paper.

Berndt, E. K., Hall, R. E., Hall, B., and Hausman, J. A. (1974). Estimation and inference in nonlinear structural models. Annals of Economic and Social Mea- surement, 3:653–665.

Carstensen, K. (2005). Estimating the ECB policy reaction function. forthcoming in German Economic Review, (Issue 1).

Clarida, R., Galli, J., and Gertler, M. (1998). Monetary policy rules in practice : some international evidence. European Economic Review, (42):1033–1067.

Clarida, R., Galli, J., and Gertler, M. (1999). The science of monetary policy: a new keynesian perspective. Journal of Economic Literature, (37):1661–1707.

Clarida, R., Galli, J., and Gertler, M. (2000). Monetary policy rules and macroeconomic stability : evidence and some theory. Quarterly Journal of Economics, (115):147–180.

Engle, R. (2000). The econometrics of ultra-high frequency data. Econometrica, 68(1):1–22.

Engle, R. and Russell, J. (1994). Forecasting transaction rates: the autoregressive conditional duration model. NBER Working paper, (4966).

Engle, R. and Russell, J. (1995). Autoregressive conditional duration: A new model for irregularly spaced time series data. Department of Economics, UC San Diego, (94-27r).

Engle, R. and Russell, J. (2005). A discrete-state continuous-time model of financial transactions prices and times: The autoregressive conditional multinomialautoregressive conditional duration model. Journal of Business & Economic Sta- tistics, (23(2)).

Fischer, A. (2000). Do interventions smooth interest rate? Swiss National Bank paper.

Fischer, A. and Zurlinden, M. (2004). Are interventions self exciting? Open Economies Review, 15(3):223–237.

Forni, M., Hallin, M., Lippi, M., and Reichlin, L. (2000). The generalized dynamic factor model: Identification and estimation. Review of Economics and Statistics, (82):540–554.

Gerhard, F. (2001). Empirical models of the intra day process of price changes and liquidity - a transaction level approach. PhD Dissertation - Nuffield College, Oxford.

Goodfriend, M. (1990). Interest rates and the conduct of monetary policy. Working Paper 90-06, Federal Reserve Bank of Richmond.

Hamilton, J. D. and Jorda, O. (2000). A model for the federal funds rate target. NBER Working Papers 7847, National Bureau of Economic Research, Inc.

Hausman, J. A., Lo, A.W., and MacKinlay, A. C. (1992). An ordered probit analysis of transaction stock prices. Journal of Financial Economics, 31(3):319–379.

Kishor, N. and Koenig, E. (2005). VAR estimation and forecasting when data are subject to revision. Working Papers 05-01, Federal Reserve Bank of Dallas.

Meitz, M. and Ter¨asvirta, T. (2004). Evaluating models of autoregressive conditional duration. SSE/EFI Working Paper Series in Economics and Finance, (557).

Stock, J. and Watson, M. (1999). Diffusion indices. Unpublished, Harvard Univer- sity.

Taylor, J. (1993). Discretion versus policy rules in practice. Carnegie-Rochester Conference Series on Public Policy, 39(1):195–214.

Woodford, M. (1999). Optimal monetary policy inertia. Manchester School, 67(0):1– 35.

Woodford, M. (2003). Interest and Prices: Foundations of a Theory of Monetary Policy. Princeton University Press.