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An econometric specification of monetary policy dark art

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  • Ielpo, Florian
  • Guégan, Dominique

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.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 1004.

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Date of creation: 04 Mar 2006
Date of revision: 07 Oct 2006
Handle: RePEc:pra:mprapa:1004

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Keywords: Taylor rule; duration models; probit models; Central Bank expectations; factor based methods;

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References

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  1. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules And Macroeconomic Stability: Evidence And Some Theory," The Quarterly Journal of Economics, MIT Press, vol. 115(1), pages 147-180, February.
  2. Goodfriend, Marvin, 1991. "Interest rates and the conduct of monetary policy," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 34(1), pages 7-30, January.
  3. James D. Hamilton & Oscar Jorda, . "A model for the federal funds rate target," Department of Economics 99-07, California Davis - Department of Economics.
  4. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "The science of monetary policy: A new Keynesian perspective," Economics Working Papers 356, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 1999.
  5. Richard Clarida & Jordi Gali & Mark Gertler, 1997. "Monetary Policy Rules in Practice: Some International Evidence," NBER Working Papers 6254, National Bureau of Economic Research, Inc.
  6. Robert F. Engle & Jeffrey R. Russell, 1994. "Forecasting Transaction Rates: The Autoregressive Conditional Duration Model," NBER Working Papers 4966, National Bureau of Economic Research, Inc.
  7. N. Kundan Kishor & Evan F. Koenig, 2009. "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 181-190, July.
  8. Fischer, Andreas M & Zurlinden, Mathias, 1998. "Are Interventions Self-Exciting?," CEPR Discussion Papers 1964, C.E.P.R. Discussion Papers.
  9. Carstensen, Kai, 2006. "Estimating the ECB policy reaction function," Munich Reprints in Economics 19941, University of Munich, Department of Economics.
  10. BAUWENS, Luc & GIOT, Pierre, . "Asymmetric ACD models: Introducing price information in ACD models," CORE Discussion Papers RP -1670, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  11. Andreas M. Fischer, 2000. "Do Interventions Smooth Interest Rates?," Working Papers 00.04, Swiss National Bank, Study Center Gerzensee.
  12. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  13. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, Archie Craig, 1955-, 1990. "An ordered probit analysis of transaction stock prices," Working papers 3234-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  14. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 103-116 National Bureau of Economic Research, Inc.
  15. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
  16. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
  17. BAUWENS, Luc & GIOT, Pierre, 1998. "Asymmetric ACD models: introducing price information in ACD models with a two state transition model," CORE Discussion Papers 1998044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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Cited by:
  1. Dominique Guégan & Florian Ielpo, 2008. "Flexible time series models for subjective distribution estimation with monetary policy in view," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 51(1), pages 79-103.

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