IDEAS home Printed from https://ideas.repec.org/p/fip/fedlwp/2004-013.html
   My bibliography  Save this paper

A dynamic factor analysis of the response of U. S. interest rates to news

Author

Listed:
  • Marco Lippi
  • Daniel L. Thornton

Abstract

This paper uses a dynamic factor model recently studied by Forni, Hallin, Lippi and Reichlin (2000) and Forni, Giannone, Lippi and Reichlin (2004) to analyze the response of 21 U.S. interest rates to news. Using daily data, we find that the news that affects interest rates daily can be summarized by two common factors. This finding is robust to both the sample period and time aggregation. Each rate has an important idiosyncratic component; however, the relative importance of the idiosyncratic component declines as the frequency of the observations is reduced, and nearly vanishes when rates are observed at the monthly frequency. Using an identification scheme that allows for the fact that when policy actions are unknown to the market the funds rate should respond first to policy actions, we are unable to identify a unique effect of monetary policy in the funds rate at the daily frequency.

Suggested Citation

  • Marco Lippi & Daniel L. Thornton, 2004. "A dynamic factor analysis of the response of U. S. interest rates to news," Working Papers 2004-013, Federal Reserve Bank of St. Louis.
  • Handle: RePEc:fip:fedlwp:2004-013
    as

    Download full text from publisher

    File URL: http://research.stlouisfed.org/wp/2004/2004-013.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lucio Sarno & Daniel L. Thornton & Yi Wen, 2007. "What's Unique About the Federal Funds Rate? Evidence from a Spectral Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(2), pages 293-319, April.
    2. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1113-1141, December.
    3. Hamilton, James D, 1997. "Measuring the Liquidity Effect," American Economic Review, American Economic Association, vol. 87(1), pages 80-97, March.
    4. Daniel L. Thornton, 2001. "Identifying the liquidity effect at the daily frequency," Review, Federal Reserve Bank of St. Louis, vol. 83(Jul), pages 59-82.
    5. Duffee, Gregory R, 1996. "Idiosyncratic Variation of Treasury Bill Yields," Journal of Finance, American Finance Association, vol. 51(2), pages 527-551, June.
    6. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2009. "Opening The Black Box: Structural Factor Models With Large Cross Sections," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1319-1347, October.
    7. Sarno, Lucio & Thornton, Daniel L & Valente, Giorgio, 2005. "Federal Funds Rate Prediction," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 449-471, June.
    8. Lucio Sarno & Daniel L. Thornton, 2004. "The efficient market hypothesis and identification in structural VARs," Review, Federal Reserve Bank of St. Louis, vol. 86(Jan), pages 49-60.
    9. William Poole & Robert H. Rasche & Daniel L. Thornton, 2002. "Market anticipations of monetary policy actions," Review, Federal Reserve Bank of St. Louis, vol. 84(Jul), pages 65-94.
    10. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    11. John B. Taylor, 2001. "Expectations, open market operations, and changes in the federal funds rate," Review, Federal Reserve Bank of St. Louis, vol. 83(Jul), pages 33-58.
    12. Garfinkel, Michelle R & Thornton, Daniel L, 1995. "The Information Content of the Federal Funds Rate: Is It Unique?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(3), pages 838-847, August.
    13. Rudebusch, Glenn D, 1998. "Do Measures of Monetary Policy in a VAR Make Sense?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 907-931, November.
    14. Forni, Mario & Lippi, Marco & Reichlin, Lucrezia, 2003. "Opening the Black Box: Structural Factor Models versus Structural VARs," CEPR Discussion Papers 4133, C.E.P.R. Discussion Papers.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Moneta, Fabio & Rüffer, Rasmus, 2006. "Business cycle synchronisation in East Asia," Working Paper Series 671, European Central Bank.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sarno, Lucio & Thornton, Daniel L., 2003. "The dynamic relationship between the federal funds rate and the Treasury bill rate: An empirical investigation," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1079-1110, June.
    2. Ard H.J. den Reijer, 2005. "Forecasting Dutch GDP using Large Scale Factor Models," DNB Working Papers 028, Netherlands Central Bank, Research Department.
    3. Cipollini, A. & Kapetanios, G., 2009. "Forecasting financial crises and contagion in Asia using dynamic factor analysis," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 188-200, March.
    4. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    5. Di Bonaventura, Luca & Forni, Mario & Pattarin, Francesco, 2018. "The Forcasting Performance of Dynamic Factor Models with Vintage Data," CEPR Discussion Papers 13034, C.E.P.R. Discussion Papers.
    6. Eickmeier, Sandra, 2007. "Business cycle transmission from the US to Germany--A structural factor approach," European Economic Review, Elsevier, vol. 51(3), pages 521-551, April.
    7. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2014. "Dynamic Factor Models, Cointegration and Error Correction Mechanisms," Working Papers ECARES ECARES 2014-14, ULB -- Universite Libre de Bruxelles.
    8. Thornton, Daniel L., 2014. "Monetary policy: Why money matters (and interest rates don’t)," Journal of Macroeconomics, Elsevier, vol. 40(C), pages 202-213.
    9. Matteo Luciani, 2015. "Monetary Policy and the Housing Market: A Structural Factor Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 199-218, March.
    10. Daniel L. Thornton, 2007. "Open market operations and the federal funds rate," Review, Federal Reserve Bank of St. Louis, vol. 89(Nov), pages 549-570.
    11. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    12. Mario Forni & Luca Gambetti & Luca Sala, 2014. "No News in Business Cycles," Economic Journal, Royal Economic Society, vol. 124(581), pages 1168-1191, December.
    13. Domenico Giannone & Troy D. Matheson, 2007. "A New Core Inflation Indicator for New Zealand," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 145-180, December.
    14. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
    15. Belviso Francesco & Milani Fabio, 2006. "Structural Factor-Augmented VARs (SFAVARs) and the Effects of Monetary Policy," The B.E. Journal of Macroeconomics, De Gruyter, vol. 6(3), pages 1-46, December.
    16. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    17. Matteo Barigozzi & Marc Hallin, 2016. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 33-60, February.
    18. Barigozzi, Matteo & Trapani, Lorenzo, 2020. "Sequential testing for structural stability in approximate factor models," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 5149-5187.
    19. Selva Demiralp & Òscar Jordà, 2002. "The announcement effect: evidence from open market desk data," Economic Policy Review, Federal Reserve Bank of New York, vol. 8(May), pages 29-48.
    20. Romain Houssa & Lasse Bork & Hans Dewachter, 2008. "Identification of Macroeconomic Factors in Large Panels," Working Papers 1010, University of Namur, Department of Economics.

    More about this item

    Keywords

    Interest rates;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:fip:fedlwp:2004-013. 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: . General contact details of provider: https://edirc.repec.org/data/frbslus.html .

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (email available below). General contact details of provider: https://edirc.repec.org/data/frbslus.html .

    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.