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Are Some Forecasters Really Better Than Others?

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Author Info

  • Antonello D’Agostino

    (Central Bank of Ireland)

  • Kieran McQuinn

    (Central Bank of Ireland)

  • Karl Whelan

    (University College Dublin)

Abstract

In any dataset with individual forecasts of economic variables, some forecasters will perform better than others. However, it is possible that these ex post differences reflect sampling variation and thus overstate the ex ante differences between forecasters. In this paper, we present a simple test of the null hypothesis that all forecasters in the US Survey of Professional Forecasters have equal ability. We construct a test statistic that reflects both the relative and absolute performance of the forecaster and use bootstrap techniques to compare the empirical results with the equivalents obtained under the null hypothesis of equal forecaster ability. Results suggests limited evidence for the idea that the best forecasters are actually innately better than others, though there is evidence that a relatively small group of forecasters perform very poorly.

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File URL: http://www.ucd.ie/t4cms/wp10_12.pdf
File Function: First version, 2010
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Bibliographic Info

Paper provided by School Of Economics, University College Dublin in its series Working Papers with number 201012.

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Length: 30 pages
Date of creation: 15 Apr 2010
Date of revision:
Handle: RePEc:ucn:wpaper:201012

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Keywords: Forecasting; Bootstrap;

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References

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  1. James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
  2. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  3. Antonello D'Agostino & Domenico Giannone & Paolo Surico, 2005. "(Un)Predictability and Macroeconomic Stability," Macroeconomics 0510024, EconWPA.
  4. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
  5. Carl S Bonham & Richard H Cohen, 2000. "Testing the Rational Expectations Hypothesis using Survey Data," Working Papers 200007, University of Hawaii at Manoa, Department of Economics.
  6. 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.
  7. Batchelor, R A, 1990. "All Forecasters Are Equal," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 143-44, January.
  8. Keane, Michael P & Runkle, David E, 1990. "Testing the Rationality of Price Forecasts: New Evidence from Panel Data," American Economic Review, American Economic Association, vol. 80(4), pages 714-35, September.
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Cited by:
  1. D’Agostino, Antonello & Schnatz, Bernd, 2012. "Survey-based nowcasting of US growth: a real-time forecast comparison over more than 40 years," Working Paper Series 1455, European Central Bank.
  2. Clements, Michael P, 2012. "Subjective and Ex Post Forecast Uncertainty : US Inflation and Output Growth," The Warwick Economics Research Paper Series (TWERPS) 995, University of Warwick, Department of Economics.
  3. Robert Rich & Joseph Song & Joseph Tracy, 2012. "The measurement and behavior of uncertainty: evidence from the ECB Survey of Professional Forecasters," Staff Reports 588, Federal Reserve Bank of New York.
  4. Kenny, Geoff & Kostka, Thomas & Masera, Federico, 2013. "Can macroeconomists forecast risk? Event-based evidence from the euro area SPF," Working Paper Series 1540, European Central Bank.
  5. Tito Nícias Teixeira da Silva Filho, 2013. "Banks, Asset Management or Consultancies' Inflation Forecasts: is there a better forecaster out there?," Working Papers Series 310, Central Bank of Brazil, Research Department.

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