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Are Some Forecasters Really Better Than Others?

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Author Info

  • ANTONELLO D’AGOSTINO
  • KIERAN MCQUINN
  • KARL WHELAN

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 suggest little support 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://hdl.handle.net/10.1111/j.1538-4616.2012.00507.x
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Bibliographic Info

Article provided by Blackwell Publishing in its journal Journal of Money, Credit and Banking.

Volume (Year): 44 (2012)
Issue (Month): 4 (06)
Pages: 715-732

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Handle: RePEc:mcb:jmoncb:v:44:y:2012:i:4:p:715-732

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0022-2879

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References

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  1. 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.
  2. D''Agostino, Antonello & Giannone, Domenico & Surico, Paolo, 2007. "(Un)Predictability and Macroeconomic Stability," CEPR Discussion Papers 6594, C.E.P.R. Discussion Papers.
  3. 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.
  4. 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.
  5. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, 02.
  6. 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.
  7. Batchelor, R A, 1990. "All Forecasters Are Equal," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 143-44, January.
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Citations

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Cited by:
  1. 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.
  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. 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.
  4. 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.
  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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