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Assessing the Evidence of Macro- Forecaster Herding: Forecasts of Inflation and Output Growth

Listed author(s):
  • Michael P Clements

    (ICMA Centre, Henley Business School, University of Reading)

We consider a number of ways of testing whether macroeconomic forecasters herd or anti-herd, i.e., whether they shade their forecasts towards those of others or purpose- fully exaggerate their differences. When applied to survey respondents expectations of inflation and output growth the tests indicate conflicting behaviour. We show that this can be explained in terms of a simple model in which differences between forecasters are primarily due to idiosyncratic factors or reporting errors rather than imitative behaviour. Models of forecaster heterogeneity that stress informational rigidities will also falsely indicate imitative behaviour.

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File URL: http://www.icmacentre.ac.uk/images/2014/10/ICM-2014-12-Clements.pdf
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Paper provided by Henley Business School, Reading University in its series ICMA Centre Discussion Papers in Finance with number icma-dp2014-12.

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Date of creation: Oct 2014
Handle: RePEc:rdg:icmadp:icma-dp2014-12
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Web page: http://www.henley.reading.ac.uk/

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  1. Giampiero M. Gallo & Clive W.J. Granger & Yongil Jeon, 2002. "Copycats and Common Swings: The Impact of the Use of Forecasts in Information Sets," IMF Staff Papers, Palgrave Macmillan, vol. 49(1), pages 1-2.
  2. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
  3. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  4. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
  5. Andrew J. Patton & Allan Timmermann, 2011. "Predictability of Output Growth and Inflation: A Multi-Horizon Survey Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 397-410, July.
  6. Pierdzioch, Christian & Rülke, Jan-Christoph, 2012. "Forecasting stock prices: Do forecasters herd?," Economics Letters, Elsevier, vol. 116(3), pages 326-329.
  7. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
  8. Victor Zarnowitz, 1969. "The New ASA–NBER Survey of Forecasts by Economic Statisticians," NBER Chapters,in: Supplement to NBER Report Four, pages 1-8 National Bureau of Economic Research, Inc.
  9. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
  10. David Laster & Paul Bennett & In Sun Geoum, 1999. "Rational Bias in Macroeconomic Forecasts," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 293-318.
  11. Patton, Andrew J. & Timmermann, Allan, 2007. "Testing Forecast Optimality Under Unknown Loss," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1172-1184, December.
  12. Pierdzioch, Christian & Rülke, Jan Christoph & Stadtmann, Georg, 2010. "New evidence of anti-herding of oil-price forecasters," Energy Economics, Elsevier, vol. 32(6), pages 1456-1459, November.
  13. Graham Elliott & Ivana Komunjer & Allan Timmermann, 2008. "Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?," Journal of the European Economic Association, MIT Press, vol. 6(1), pages 122-157, 03.
  14. Kajal Lahiri & Antony Davies & Xuguang Sheng, 2010. "Analyzing Three-Dimensional Panel Data of Forecasts," Discussion Papers 10-07, University at Albany, SUNY, Department of Economics.
  15. Bernhardt, Dan & Campello, Murillo & Kutsoati, Edward, 2006. "Who herds?," Journal of Financial Economics, Elsevier, vol. 80(3), pages 657-675, June.
  16. Zellner, Arnold, 1986. "Biased predictors, rationality and the evaluation of forecasts," Economics Letters, Elsevier, vol. 21(1), pages 45-48.
  17. J. Steven Landefeld & Eugene P. Seskin & Barbara M. Fraumeni, 2008. "Taking the Pulse of the Economy: Measuring GDP," Journal of Economic Perspectives, American Economic Association, vol. 22(2), pages 193-216, Spring.
  18. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
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