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Do FOMC Members Herd?

Author

Listed:
  • Jan-Christoph Rülke

    () (WHU - Otto Beisheim School of Management,WHU - Otto Beisheim School of Management)

  • Peter Tillmann

    () (Justus-Liebig-University Giessen)

Abstract

Twice a year FOMC members submit forecasts for growth, unemplyoment and in ation to be published in the Humphrey-Hawkins Report to Congress. In this paper we use individual FOMC forecasts to assess whether these forecasts exhibit herding behavior, a pattern often found in private sector forecasts. While growth and unemployment forecast do not show herding behavior, the in ation forecasts show strong evidence of anti-herding, i.e. FOMC members intentionally scatter their forecasts around the consensus. Interestingly, anti-herding is more important for nonvoting members than for voters.

Suggested Citation

  • Jan-Christoph Rülke & Peter Tillmann, 2010. "Do FOMC Members Herd?," MAGKS Papers on Economics 201032, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Handle: RePEc:mar:magkse:201032
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    File URL: http://www.uni-marburg.de/fb02/makro/forschung/magkspapers/32-2010_ruelke.pdf
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    References listed on IDEAS

    as
    1. David Romer, 2010. "A New Data Set on Monetary Policy: The Economic Forecasts of Individual Members of the FOMC," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(5), pages 951-957, August.
    2. Gavin, William T. & Mandal, Rachel J., 2003. "Evaluating FOMC forecasts," International Journal of Forecasting, Elsevier, vol. 19(4), pages 655-667.
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    4. William T. Gavin, 2003. "FOMC forecast: is all the information in the central tendency?," Review, Federal Reserve Bank of St. Louis, issue May, pages 27-46.
    5. Tillmann, Peter, 2011. "Strategic forecasting on the FOMC," European Journal of Political Economy, Elsevier, vol. 27(3), pages 547-553, September.
    6. Christina D. Romer & David H. Romer, 2008. "The FOMC versus the Staff: Where Can Monetary Policymakers Add Value?," American Economic Review, American Economic Association, vol. 98(2), pages 230-235, May.
    7. Bernhardt, Dan & Campello, Murillo & Kutsoati, Edward, 2006. "Who herds?," Journal of Financial Economics, Elsevier, vol. 80(3), pages 657-675, June.
    8. William T. Gavin & Geetanjali Pande, 2008. "FOMC consensus forecasts," Review, Federal Reserve Bank of St. Louis, issue May, pages 149-164.
    9. Michael W. McCracken, 2010. "Using FOMC forecasts to forecast the economy," Economic Synopses, Federal Reserve Bank of St. Louis.
    10. Chanont Banternghansa & Michael W. McCracken, 2009. "Forecast disagreement among FOMC members," Working Papers 2009-059, Federal Reserve Bank of St. Louis.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. El-Shagi, Makram & Jung, Alexander, 2015. "Does the Greenspan era provide evidence on leadership in the FOMC?," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 173-190.
    3. Bohl, Martin T. & Klein, Arne C. & Siklos, Pierre L., 2014. "Short-selling bans and institutional investors' herding behaviour: Evidence from the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 262-269.
    4. Fendel, Ralf & Rülke, Jan-Christoph, 2012. "Are heterogeneous FOMC forecasts consistent with the Fed’s monetary policy?," Economics Letters, Elsevier, vol. 116(1), pages 5-7.
    5. Nakazono, Yoshiyuki, 2013. "Strategic behavior of Federal Open Market Committee board members: Evidence from members’ forecasts," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 62-70.
    6. Smales, Lee A. & Apergis, Nick, 2016. "The influence of FOMC member characteristics on the monetary policy decision-making process," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 216-231.
    7. Schultefrankenfeld, Guido, 2017. "Appropriate monetary policy and forecast disagreement at the FOMC," Discussion Papers 39/2017, Deutsche Bundesbank.
    8. Rülke Jan-Christoph, 2012. "Do Private Sector Forecasters Desire to Deviate From the German Council of Economic Experts?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(4), pages 414-428, August.
    9. Ellis, Michael A. & Liu, Dandan, 2016. "FOMC forecasts and monetary policy deliberations," Economics Letters, Elsevier, vol. 147(C), pages 131-134.
    10. Jan-Christoph Rülke, 2011. "Do private sector forecasters desire to deviate from the German council of economic experts?," WHU Working Paper Series - Economics Group 11-04, WHU - Otto Beisheim School of Management.
    11. Roman Horvath & Katerina Smidkova & Jan Zapal, 2012. "Is the U.S. Fed Voting Record Informative about Future Monetary Policy?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(6), pages 478-484, December.
    12. Peter Tillmann, 2011. "Reputation and Forecast Revisions: Evidence from the FOMC," MAGKS Papers on Economics 201128, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

    More about this item

    Keywords

    Central Federal Open Market Committee; monetary policy; forecasting; herding;

    JEL classification:

    • 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
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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