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A model for the federal funds rate target

  • James D. Hamilton
  • Oscar Jorda

This paper is a statistical analysis of the manner in which the Federal Reserve determines the level of the Federal funds rate target, one of the most publicized and anticipated economic indicators in the financial world. The analysis presents two econometric challenges: (1) changes in the target are irregularly spaced in time; (2) the target is changed in discrete increments of 25 basis points. The contributions of this paper are: (1) to give a detailed account of the changing role of the target in the conduct of monetary policy; (2) to develop new econometric tools for analyzing time-series duration data; (3) to analyze empirically the determinants of the target. The paper introduces a new class of models termed autoregressive conditional hazard processes, which allow one to produce dynamic forecasts of the probability of a target change. Conditional on a target change, an ordered probit model produces predictions on the magnitude by which the Fed will raise or lower the Federal funds rate. By decomposing Federal funds rate innovations into target changes and nonchanges, we arrive at new estimates of the effects of a monetary policy "shock.''

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Paper provided by California Davis - Department of Economics in its series Department of Economics with number 99-07.

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Handle: RePEc:fth:caldec:99-07
Contact details of provider: Postal: University of California Davis - Department of Economics. One Shields Ave., California 95616-8578
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  1. Hausman, Jerry A. & Lo, Andrew W. & MacKinlay, A. Craig, 1992. "An ordered probit analysis of transaction stock prices," Journal of Financial Economics, Elsevier, vol. 31(3), pages 319-379, June.
  2. Bennett T. McCallum & Edward Nelson, 1999. "Performance of Operational Policy Rules in an Estimated Semiclassical Structural Model," NBER Chapters, in: Monetary Policy Rules, pages 15-56 National Bureau of Economic Research, Inc.
  3. Monika Piazzesi, 2001. "An Econometric Model of the Yield Curve with Macroeconomic Jump Effects," NBER Working Papers 8246, National Bureau of Economic Research, Inc.
  4. Feinman, Joshua N, 1993. "Estimating the Open Market Desk's Daily Reaction Function," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(2), pages 231-47, May.
  5. Thornton, Daniel L., 2001. "The Federal Reserve's operating procedure, nonborrowed reserves, borrowed reserves and the liquidity effect," Journal of Banking & Finance, Elsevier, vol. 25(9), pages 1717-1739, September.
  6. Strongin, Steven, 1995. "The identification of monetary policy disturbances explaining the liquidity puzzle," Journal of Monetary Economics, Elsevier, vol. 35(3), pages 463-497, June.
  7. Asger Lunde & Allan Timmermann, 2000. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Econometric Society World Congress 2000 Contributed Papers 1216, Econometric Society.
  8. Robert F. Engle, 1996. "The Econometrics of Ultra-High Frequency Data," NBER Working Papers 5816, National Bureau of Economic Research, Inc.
  9. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
  10. Glenn D. Rudebusch, 1995. "Federal Reserve interest rate targeting, rational expectations, and the term structure," Working Papers in Applied Economic Theory 95-02, Federal Reserve Bank of San Francisco.
  11. Clarida, R. & Gali, J. & Gertler, M., 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and some Theory," Working Papers 98-01, C.V. Starr Center for Applied Economics, New York University.
  12. Dueker, Michael, 1999. "Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 466-72, October.
  13. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
  14. Christopher A. Sims, 1992. "Interpreting the Macroeconomic Time Series Facts: The Effects of Monetary Policy," Cowles Foundation Discussion Papers 1011, Cowles Foundation for Research in Economics, Yale University.
  15. Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance icma-dp2000-05, Henley Business School, Reading University.
  16. Davutyan, Nurhan & Parke, William R, 1995. "The Operations of the Bank of England, 1890-1908: A Dynamic Probit Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 1099-1112, November.
  17. Charles L. Evans & David A. Marshall, 1997. "Monetary policy and the term structure of nominal interest rates: evidence and theory," Working Paper Series, Macroeconomic Issues WP-97-10, Federal Reserve Bank of Chicago.
  18. H. Robert Heller, 1988. "Implementing monetary policy," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Jul, pages 419-429.
  19. Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-45, September.
  20. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1, December.
  21. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
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