IDEAS home Printed from https://ideas.repec.org/p/fth/caldec/99-07.html
   My bibliography  Save this paper

A model for the federal funds rate target

Author

Listed:
  • James D. Hamilton
  • Oscar Jorda

Abstract

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.''

Suggested Citation

  • James D. Hamilton & Oscar Jorda, "undated". "A model for the federal funds rate target," Department of Economics 99-07, California Davis - Department of Economics.
    • Handle: RePEc:fth:caldec:99-07
    as

    Download full text from publisher

    File URL: http://www.econ.ucdavis.edu/working_papers/99-7.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
    3. David E. Runkle, 1998. "Revisionist history: how data revisions distort economic policy research," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 22(Fall), pages 3-12.
    4. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    5. 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.
    6. Kuttner, Kenneth N., 2001. "Monetary policy surprises and interest rates: Evidence from the Fed funds futures market," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 523-544, June.
    7. 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.
    8. 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.
    9. 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.
    10. 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 231-247, May.
    11. Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
    12. Robert F. Engle, 2000. "The Econometrics of Ultra-High Frequency Data," Econometrica, Econometric Society, vol. 68(1), pages 1-22, January.
    13. 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.
    14. Monika Piazzesi, 2001. "An Econometric Model of the Yield Curve with Macroeconomic Jump Effects," NBER Working Papers 8246, National Bureau of Economic Research, Inc.
    15. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
    16. 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 725-745, September.
    17. 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.
    18. 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.
    19. Piazzesi, Monika, 2001. "An Econometric Model of the Yield Curve With Macroeconomic Jump Effects," University of California at Los Angeles, Anderson Graduate School of Management qt5946p7hn, Anderson Graduate School of Management, UCLA.
    20. 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.
    21. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1.
    22. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
    23. 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 466-472, October.
    24. Cook, Timothy & Hahn, Thomas, 1989. "The effect of changes in the federal funds rate target on market interest rates in the 1970s," Journal of Monetary Economics, Elsevier, vol. 24(3), pages 331-351, November.
    25. 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.
    26. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James D. Hamilton & Oscar Jorda, 2002. "A Model of the Federal Funds Rate Target," Journal of Political Economy, University of Chicago Press, vol. 110(5), pages 1135-1167, October.
    2. George Monokroussos, 2011. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 519-534, March.
    3. Selva Demiralp & Oscar Jorda, "undated". "The Pavlovian Response of Term Rates to Fed Announcements," Department of Economics 99-06, California Davis - Department of Economics.
    4. Selva Demiralp & Oscar Jorda, "undated". "The Pavlovian Response of Term Rates to Fed Announcements," Department of Economics 99-06, California Davis - Department of Economics.
    5. Thornton, Daniel L., 2004. "The Fed and short-term rates: Is it open market operations, open mouth operations or interest rate smoothing?," Journal of Banking & Finance, Elsevier, vol. 28(3), pages 475-498, March.
    6. Monika Piazzesi, 2005. "Bond Yields and the Federal Reserve," Journal of Political Economy, University of Chicago Press, vol. 113(2), pages 311-344, April.
    7. Grammig, Joachim & Kehrle, Kerstin, 2008. "A new marked point process model for the federal funds rate target: Methodology and forecast evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2370-2396, July.
    8. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
    9. Brissimis, Sophocles N. & Magginas, Nicholas S., 2006. "Forward-looking information in VAR models and the price puzzle," Journal of Monetary Economics, Elsevier, vol. 53(6), pages 1225-1234, September.
    10. Lucio Sarno & Daniel L. Thornton & Yi Wen, 2007. "What's Unique About the Federal Funds Rate? Evidence from a Spectral Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 293-319, April.
    11. M. Marzo, 2001. "Evaluating Monetary Policy Regimes: the Role of Nominal Rigidities," Working Papers 411, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Sarno, Lucio & Thornton, Daniel L & Valente, Giorgio, 2005. "Federal Funds Rate Prediction," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 449-471, June.
    13. William H.Greene & Max Gillman & Mark N. Harris & Christopher Spencer, 2013. "The Tempered Ordered Probit (TOP) model with an application to monetary policy," Discussion Paper Series 2013_10, Department of Economics, Loughborough University, revised Sep 2013.
    14. Bouakez, Hafedh & Essid, Badye & Normandin, Michel, 2013. "Stock returns and monetary policy: Are there any ties?," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 33-50.
    15. Hibiki Ichiue, 2004. "Why Can the Yield Curve Predict Output Growth, Inflation, and Interest Rates? An Analysis with an Affine Term Structure Model," Bank of Japan Working Paper Series 04-E-11, Bank of Japan.
    16. Belderbos, Rene & Ikeuchi, Kenta & Fukao, Kyoji & Kim, Young Gak & Kwon, Hyeog Ug, 2013. "Plant Productivity Dynamics and Private and Public R&D Spillovers: Technological, Geographic and Relational Proximity," CEI Working Paper Series 2013-05, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    17. Brooks, Robert & Harris, Mark & Spencer, Christopher, 2007. "An Inflated Ordered Probit Model of Monetary Policy: Evidence from MPC Voting Data," MPRA Paper 8509, University Library of Munich, Germany.
    18. George Monokroussos, 2006. "A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function," Computing in Economics and Finance 2006 390, Society for Computational Economics.
    19. Berument, Hakan & Froyen, Richard T., 2006. "Monetary policy and long-term US interest rates," Journal of Macroeconomics, Elsevier, vol. 28(4), pages 737-751, December.
    20. Dungey, Mardi & Henry, Olan & McKenzie, Michael, 2010. "From Trade-to-Trade in US Treasuries," Working Papers 10446, University of Tasmania, Tasmanian School of Business and Economics, revised 01 May 2010.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fth:caldec:99-07. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/educdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.