IDEAS home Printed from
   My bibliography  Save this paper

Optimal Monetary Policy with Real-time Signal Extraction from the Bond Market


  • Kristoffer Nimark

    (Reserve Bank of Australia)


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.

Suggested Citation

  • Kristoffer Nimark, 2006. "Optimal Monetary Policy with Real-time Signal Extraction from the Bond Market," RBA Research Discussion Papers rdp2006-05, Reserve Bank of Australia.
  • Handle: RePEc:rba:rbardp:rdp2006-05

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Hordahl, Peter & Tristani, Oreste & Vestin, David, 2006. "A joint econometric model of macroeconomic and term-structure dynamics," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 405-444.
    2. Amato, Jeffery D. & Laubach, Thomas, 2004. "Implications of habit formation for optimal monetary policy," Journal of Monetary Economics, Elsevier, vol. 51(2), pages 305-325, March.
    3. Marvin Goodfriend, 1998. "Using the term structure of interest rates for monetary policy," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 13-30.
    4. Ang, Andrew & Piazzesi, Monika & Wei, Min, 2006. "What does the yield curve tell us about GDP growth?," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 359-403.
    5. John Y. Campbell & John H. Cochrane, 1994. "By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," CRSP working papers 412, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    6. Lippi, Francesco & Neri, Stefano, 2003. "Information Variables for Monetary Policy in a Small Structural Model of the Euro Area," CEPR Discussion Papers 4125, C.E.P.R. Discussion Papers.
    7. Tore Ellingsen & Ulf Soderstrom, 2001. "Monetary Policy and Market Interest Rates," American Economic Review, American Economic Association, vol. 91(5), pages 1594-1607, December.
    8. Bartolini, Leonardo & Bertola, Giuseppe & Prati, Alessandro, 2002. "Day-to-Day Monetary Policy and the Volatility of the Federal Funds Interest Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 137-159, February.
    9. Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
    10. Lippi, Francesco & Neri, Stefano, 2007. "Information variables for monetary policy in an estimated structural model of the euro area," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1256-1270, May.
    11. Harvey, Campbell R., 1988. "The real term structure and consumption growth," Journal of Financial Economics, Elsevier, vol. 22(2), pages 305-333, December.
    12. Svensson, Lars E. O. & Woodford, Michael, 2004. "Indicator variables for optimal policy under asymmetric information," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 661-690, January.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Timothy Kam & Kirdan Lees & Philip Liu, 2009. "Uncovering the Hit List for Small Inflation Targeters: A Bayesian Structural Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 583-618, June.
    2. Gunji, Hiroshi & Miura, Kazuki & Yuan, Yuan, 2009. "Bank competition and monetary policy," Japan and the World Economy, Elsevier, vol. 21(1), pages 105-115, January.

    More about this item


    monetary policy; imperfect information; bond market; term structure of interest rates;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:rba:rbardp:rdp2006-05. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paula Drew). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.