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Did the FED Surprise the Markets in 2001? A Case Study for Vars with Sign Restrictions

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  • Uhlig, H.F.H.V.S.

    (Tilburg University, Center For Economic Research)

Abstract

In 2001, the Fed has lowered interest rates in a series of cuts, starting from 6.5 % at the end of 2000 to 2.0 % by early November.This paper asks, whether the Federal Reserve Bank has been surprising the markets, taking as given the conventional view about the effect of monetary policy shocks.New econometric techniques turn out to be particularly suitable for answering this question: this paper can be viewed as a showcase and case study for their application.In order to concentrate on the Greenspan period, a vector autoregression is fitted to US data, starting in 1986 and ending in September 2001.Monetary policy shocks are identified, using the new sign restriction methodology of Uhlig (1999), imposing the "conventional view" that contractionary policy shocks lead to a rise in interest rates and declines in nonborrowed reserves, prices and output.We find that neither the Fed policy choices in 2001 nor those of 2000 were surprising.We provide a method to "explain" these interest rate movements by decomposing them into their sources. Finally, we argue that constant-interest-rate projections like those popular at many central banks are of limited informational value, can be highly misleading, and should instead be replaced by on-the-equilibrium-path projections.

Suggested Citation

  • Uhlig, H.F.H.V.S., 2001. "Did the FED Surprise the Markets in 2001? A Case Study for Vars with Sign Restrictions," Discussion Paper 2001-88, Tilburg University, Center for Economic Research.
  • Handle: RePEc:tiu:tiucen:83b97cda-fa7d-47db-8c40-d98d360bf13f
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    References listed on IDEAS

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    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
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    8. Eric M. Leeper & Tao Zha, 2002. "Empirical analysis of policy interventions," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    9. John H. Cochrane, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 109(1), pages 241-265.
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    Cited by:

    1. Chadha, J.S. & Corrado, L. & Sun, Q., 2008. "Money, Prices and Liquidity Effects: Separating Demand from Supply," Cambridge Working Papers in Economics 0855, Faculty of Economics, University of Cambridge.
    2. Mackowiak, Bartosz, 2006. "What does the Bank of Japan do to East Asia?," Journal of International Economics, Elsevier, vol. 70(1), pages 253-270, September.
    3. Michael T. Owyang, 2002. "Modeling Volcker as a non-absorbing state: agnostic identification of a Markov-switching VAR," Working Papers 2002-018, Federal Reserve Bank of St. Louis.
    4. Luc Bauwens & Dimitris Korobilis, 2013. "Bayesian methods," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 16, pages 363-380 Edward Elgar Publishing.
    5. Marco Del Negro & Christopher Otrok, 2005. "Monetary policy and the house price boom across U.S. states," FRB Atlanta Working Paper 2005-24, Federal Reserve Bank of Atlanta.
    6. Hristov, Nikolay & Hülsewig, Oliver & Wollmershäuser, Timo, 2012. "Loan supply shocks during the financial crisis: Evidence for the Euro area," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 569-592.
    7. Andrew Mountford, 2005. "Leaning into the Wind: A Structural VAR Investigation of UK Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 597-621, October.

    More about this item

    Keywords

    monetary policy; vector autoregressive models;

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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