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Testing forecast optimality under unknown loss

Publication ,  Journal Article
Patton, AJ; Timmermann, A
Published in: Journal of the American Statistical Association
2007

Empirical tests of forecast optimality have traditionally been conducted under the assumption of mean squared error loss or some other known loss function. In this article we establish new testable properties that hold when the forecaster's loss function is unknown but testable restrictions can be imposed on the data-generating process, trading off conditions on the data-generating process against conditions on the loss function. We propose flexible estimation of the forecaster's loss function in situations where the loss depends not only on the forecast error, but also on other state variables, such as the level of the target variable. We apply our results to the problem of evaluating the Federal Reserve's forecasts of output growth. Forecast optimality is rejected if the Fed's loss depends only on the forecast error. However, the empirical findings are consistent with forecast optimality provided that overpredictions of output growth are costlier to the Fed than underpredictions, particularly during periods of low economic growth. © 2007 American Statistical Association.

Duke Scholars

Published In

Journal of the American Statistical Association

DOI

ISSN

0162-1459

Publication Date

2007

Volume

102

Issue

480

Start / End Page

1172 / 1184

Related Subject Headings

  • Statistics & Probability
  • 1603 Demography
  • 1403 Econometrics
  • 0104 Statistics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Patton, A. J., & Timmermann, A. (2007). Testing forecast optimality under unknown loss. Journal of the American Statistical Association, 102(480), 1172–1184. https://doi.org/10.1198/016214506000001176
Patton, A. J., and A. Timmermann. “Testing forecast optimality under unknown loss.” Journal of the American Statistical Association 102, no. 480 (2007): 1172–84. https://doi.org/10.1198/016214506000001176.
Patton AJ, Timmermann A. Testing forecast optimality under unknown loss. Journal of the American Statistical Association. 2007;102(480):1172–84.
Patton, A. J., and A. Timmermann. “Testing forecast optimality under unknown loss.” Journal of the American Statistical Association, vol. 102, no. 480, 2007, pp. 1172–84. Scival, doi:10.1198/016214506000001176.
Patton AJ, Timmermann A. Testing forecast optimality under unknown loss. Journal of the American Statistical Association. 2007;102(480):1172–1184.
Journal cover image

Published In

Journal of the American Statistical Association

DOI

ISSN

0162-1459

Publication Date

2007

Volume

102

Issue

480

Start / End Page

1172 / 1184

Related Subject Headings

  • Statistics & Probability
  • 1603 Demography
  • 1403 Econometrics
  • 0104 Statistics