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Identifying Monetary Policy Shocks via Changes in Volatility

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  • MARKKU LANNE
  • HELMUT LÜTKEPOHL

Abstract

A central issue of monetary policy analysis is the specification of monetary policy shocks. In a structural vector autoregressive setting there has been some controversy about which restrictions to use for identifying the shocks because standard theories do not provide enough information to fully identify monetary policy shocks. In fact, to compare different theories it would even be desirable to have over-identifying restrictions that would make statistical tests of different theories possible. It is pointed out that some progress toward over-identifying monetary policy shocks can be made by using specific data properties. In particular, it is shown that changes in the volatility of the shocks can be used for identification. Based on monthly U.S. data from 1965 to 1996 different theories are tested and it is found that associating monetary policy shocks with shocks to nonborrowed reserves leads to a particularly strong rejection of the model whereas assuming that the Fed accommodates demand shocks to total reserves cannot be rejected. Copyright (c) 2008 The Ohio State University.

Suggested Citation

  • Markku Lanne & Helmut Lütkepohl, 2008. "Identifying Monetary Policy Shocks via Changes in Volatility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1131-1149, September.
    • Handle: RePEc:mcb:jmoncb:v:40:y:2008:i:6:p:1131-1149
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    References listed on IDEAS

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    1. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics,in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148 Elsevier.
    2. Lawrence J. Christiano & Martin Eichenbaum, 1991. "Identification and the Liquidity Effect of a Monetary Policy Shock," NBER Working Papers 3920, National Bureau of Economic Research, Inc.
    3. Benkwitz, Alexander & L tkepohl, Helmut & Wolters, J rgen, 2001. "Comparison Of Bootstrap Confidence Intervals For Impulse Responses Of German Monetary Systems," Macroeconomic Dynamics, Cambridge University Press, vol. 5(01), pages 81-100, February.
    4. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, November.
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    JEL classification:

    • 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

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