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Monetary policy with signal extraction from the bond market

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Abstract

Monetary policy is conducted in an environment of uncertainty. This paper sets up a model where the central bank uses real-time data from the bond market together with standard macroeconomic indicators to estimate the current state of the economy more efficiently, while taking into account that its own actions influence what it observes. The timeliness of bond market data allows for quicker responses of monetary policy to disturbances compared to the case when the central bank has to rely solely on collected aggregate data. The information content of the term structure creates a link between the bond market and the macroeconomy that is novel to the literature. To quantify the importance of the bond market as a source of information, the model is estimated on data for the United States and Australia using Bayesian methods. The empirical exercise suggests that there is some information in the US term structure that helps the Federal Reserve to identify shocks to the economy on a timely basis. Australian bond prices seem to be less informative than their US counterparts, perhaps because Australia is a relatively small and open economy.

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Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 1181.

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Date of creation: Nov 2008
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Handle: RePEc:upf:upfgen:1181

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Keywords: Monetary policy; imperfect information; bond market; term structure of interest rates;

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  1. Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, Elsevier, vol. 44(2), pages 195-222, October.
  2. John Y. Campbell & John H. Cochrane, 1994. "By force of habit: a consumption-based explanation of aggregate stock market behavior," Working Papers 94-17, Federal Reserve Bank of Philadelphia.
  3. Antonio Moreno & Geert Bekaert & Seonghoon Cho, 2004. "New-Keynesian Macroeconomics and the Term Structure," 2004 Meeting Papers, Society for Economic Dynamics 388, Society for Economic Dynamics.
  4. Soderlind, Paul & Svensson, Lars, 1997. "New techniques to extract market expectations from financial instruments," Journal of Monetary Economics, Elsevier, Elsevier, vol. 40(2), pages 383-429, October.
  5. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Proceedings, Federal Reserve Bank of San Francisco, Federal Reserve Bank of San Francisco, issue Jun.
  6. Svensson, Lars E. O. & Woodford, Michael, 2001. "Indicator Variables for Optimal Policy under Asymmetric Information," Seminar Papers, Stockholm University, Institute for International Economic Studies 689, Stockholm University, Institute for International Economic Studies.
  7. Hördahl, Peter & Tristani, Oreste & Vestin, David, 2004. "A joint econometric model of macroeconomic and term structure dynamics," Working Paper Series, European Central Bank 0405, European Central Bank.
  8. Andrew Ang & Monika Piazzesi & Min Wei, 2003. "What does the yield curve tell us about GDP growth?," Proceedings, Federal Reserve Bank of San Francisco, Federal Reserve Bank of San Francisco, issue Mar.
  9. Refet S. Gürkaynak & Brian Sack & Eric Swanson, 2005. "The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models," American Economic Review, American Economic Association, American Economic Association, vol. 95(1), pages 425-436, March.
  10. Ben S. Bernanke & Michael Woodford, 1997. "Inflation forecasts and monetary policy," Proceedings, Federal Reserve Bank of Cleveland, Federal Reserve Bank of Cleveland, pages 653-686.
  11. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, Elsevier, vol. 22(2), pages 305-333, December.
  12. Andrew Ang & Monika Piazzesi, 2001. "A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables," NBER Working Papers 8363, National Bureau of Economic Research, Inc.
  13. Marvin Goodfriend, 1998. "Using the term structure of interest rates for monetary policy," Economic Quarterly, Federal Reserve Bank of Richmond, Federal Reserve Bank of Richmond, issue Sum, pages 13-30.
  14. Mishkin, Frederic S, 1990. "The Information in the Longer Maturity Term Structure about Future Inflation," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 105(3), pages 815-28, August.
  15. Arturo Estrella & Frederic S. Mishkin, 1996. "Predicting U.S. recessions: financial variables as leading indicators," Research Paper, Federal Reserve Bank of New York 9609, Federal Reserve Bank of New York.
  16. Jeffery D. Amato & Thomas Laubach, 2001. "Implications of habit formation for optimal monetary policy," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2001-58, Board of Governors of the Federal Reserve System (U.S.).
  17. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, Elsevier, vol. 12(3), pages 383-398, September.
  18. Tore Ellingsen & Ulf Soderstrom, 2001. "Monetary Policy and Market Interest Rates," American Economic Review, American Economic Association, American Economic Association, vol. 91(5), pages 1594-1607, December.
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Cited by:
  1. Vázquez, Jesús & María-Dolores, Ramón & Londoño, Juan-Miguel, 2013. "On the informational role of term structure in the US monetary policy rule," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 37(9), pages 1852-1871.
  2. Refet S. G�rkaynak & Jonathan H. Wright, 2012. "Macroeconomics and the Term Structure," Journal of Economic Literature, American Economic Association, vol. 50(2), pages 331-67, June.
  3. Mihaela NICOLAU, 2010. "Financial Markets Interactions between Economic Theory and Practice," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 27-36.

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