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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
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  1. Lunde, Asger & Timmermann, Allan G, 2003. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," CEPR Discussion Papers 4104, C.E.P.R. Discussion Papers.
  2. Monika Piazzesi, 2001. "An Econometric Model of the Yield Curve with Macroeconomic Jump Effects," NBER Working Papers 8246, National Bureau of Economic Research, Inc.
  3. Daniel L. Thornton, 1998. "The Federal Reserve's operating procedure, nonborrowed reserves, borrowed reserves and the liquidity effect," Working Papers 1998-009, Federal Reserve Bank of St. Louis.
  4. 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.
  5. 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.
  6. Evans, Charles L. & Marshall, David A., 1998. "Monetary policy and the term structure of nominal interest rates: Evidence and theory," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 53-111, December.
  7. 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.
  8. Hausman, J.A. & Lo, A.W. & MacKinlay, A.C., 1991. "An Ordered Probit Analysis of Transaction Stock Prices," Weiss Center Working Papers 26-91, Wharton School - Weiss Center for International Financial Research.
  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. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1.
  11. Rudebusch, Glenn D., 1995. "Federal Reserve interest rate targeting, rational expectations, and the term structure," Journal of Monetary Economics, Elsevier, vol. 35(2), pages 245-274, April.
  12. 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.
  13. 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.
  14. Michael Dueker, 1998. "Conditional heteroskedasticity in qualitative response models of time series: a Gibbs sampling approach to the bank prime rate," Working Papers 1998-011, Federal Reserve Bank of St. Louis.
  15. Bennett T. McCallum & Edward Nelson, 1998. "Performance of Operational Policy Rules in an Estimated Semi-Classical Structural Model," NBER Working Papers 6599, National Bureau of Economic Research, Inc.
  16. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
  17. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
  18. 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.
  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. 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.
  21. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
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