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Improving Federal-Funds Rate Forecasts in VAR Models Used for Policy Analysis

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  • Robertson, John C
  • Tallman, Ellis W

Abstract

Federal-funds rate-forecast errors from vector autoregressive (VAR) models used for monetary policy analysis and fitted by ordinary least squares (OLS) are large relative to those from the futures market. Using three different structural VAR models, we show that forecasts based on a shrinkage estimator dominate the OLS-based forecasts--even after restricting the lag length and/or imposing exact unit-root restrictions--and are broadly comparable to the futures-market forecasts. Our results refute the perception that VAR models forecast the funds rate poorly in general and suggest that using stochastic prior restrictions can provide an effective way of improving forecast accuracy without sacrificing structural interpretation.

Suggested Citation

  • Robertson, John C & Tallman, Ellis W, 2001. "Improving Federal-Funds Rate Forecasts in VAR Models Used for Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 324-330, July.
  • Handle: RePEc:bes:jnlbes:v:19:y:2001:i:3:p:324-30
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    Citations

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    Cited by:

    1. Nason, James M. & Tallman, Ellis W., 2015. "Business Cycles And Financial Crises: The Roles Of Credit Supply And Demand Shocks," Macroeconomic Dynamics, Cambridge University Press, vol. 19(4), pages 836-882, June.
    2. Pär Österholm, 2008. "Can forecasting performance be improved by considering the steady state? An application to Swedish inflation and interest rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(1), pages 41-51.
    3. Gurkaynak, Refet S. & Sack, Brian T. & Swanson, Eric P., 2007. "Market-Based Measures of Monetary Policy Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 201-212, April.
    4. Chew Lian Chua & Sarantis Tsiaplias, 2009. "Can consumer sentiment and its components forecast Australian GDP and consumption?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 698-711.
    5. Michael Dueker & Katrin Assenmacher-Wesche, 2010. "Forecasting macro variables with a Qual VAR business cycle turning point index," Applied Economics, Taylor & Francis Journals, vol. 42(23), pages 2909-2920.
    6. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
    7. Robertson, John C & Tallman, Ellis W & Whiteman, Charles H, 2005. "Forecasting Using Relative Entropy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 383-401, June.
    8. Todd E. Clark & Michael W. McCracken, 2010. "Averaging forecasts from VARs with uncertain instabilities," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 5-29, January.
    9. P. Geoffrey Allen & Robert Fildes, 2005. "Levels, Differences and ECMs – Principles for Improved Econometric Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 881-904, December.
    10. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    11. Fabian Fink & Yves S. Schüler, 2013. "The Transmission of US Financial Stress: Evidence for Emerging Market Economies," Working Paper Series of the Department of Economics, University of Konstanz 2013-01, Department of Economics, University of Konstanz.
    12. Fabio Canova & Fernando J. Pérez Forero, 2012. "Estimating overidentified, nonrecursive, time-varying coefficients structural VARs," Economics Working Papers 1321, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Andrew Bauer & Robert A. Eisenbeis & Daniel F. Waggoner & Tao Zha, 2006. "Transparency, expectations and forecasts," Economic Review, Federal Reserve Bank of Atlanta, vol. 91(Q 1), pages 1-25.
    14. Faust, Jon & Swanson, Eric T. & Wright, Jonathan H., 2004. "Identifying VARS based on high frequency futures data," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1107-1131, September.
    15. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City, revised 2006.
    16. Sims, Christopher A. & Waggoner, Daniel F. & Zha, Tao, 2008. "Methods for inference in large multiple-equation Markov-switching models," Journal of Econometrics, Elsevier, vol. 146(2), pages 255-274, October.
    17. Erdem, Ergin & Shi, Jing, 2011. "ARMA based approaches for forecasting the tuple of wind speed and direction," Applied Energy, Elsevier, vol. 88(4), pages 1405-1414, April.
    18. John H. Huston & Roger W. Spencer, 2009. "Speculative excess and the Federal Reserve's response," Studies in Economics and Finance, Emerald Group Publishing, vol. 26(1), pages 46-61, March.
    19. John B. Carlson & Ben R. Craig & William R. Melick, 2005. "Recovering market expectations of FOMC rate changes with options on federal funds futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(12), pages 1203-1242, December.
    20. Fink, Fabian & Schüler, Yves S., 2015. "The transmission of US systemic financial stress: Evidence for emerging market economies," Journal of International Money and Finance, Elsevier, vol. 55(C), pages 6-26.
    21. Higgins, Patrick & Zha, Tao & Zhong, Wenna, 2016. "Forecasting China's economic growth and inflation," China Economic Review, Elsevier, vol. 41(C), pages 46-61.
    22. Eric M. Leeper & Tao Zha, 2002. "Empirical analysis of policy interventions," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    23. Kenneth B. Petersen & Vladimir Pozdnyakov, 2008. "Predicting the Fed," Working papers 2008-07, University of Connecticut, Department of Economics.
    24. Paul Viefers, 2011. "Bayesian Inference for the Mixed-Frequency VAR Model," Discussion Papers of DIW Berlin 1172, DIW Berlin, German Institute for Economic Research.
    25. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.

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