Journal article
Testing Forecast Optimality under Unknown Loss.
- Abstract:
-
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 functio...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Accepted manuscript, pdf, 397.5KB)
-
- Publisher copy:
- 10.1198/016214506000001176
Authors
Bibliographic Details
- Publisher:
- American Statistical Association Publisher's website
- Journal:
- Journal of the American Statistical Association Journal website
- Volume:
- 102
- Issue:
- 480
- Pages:
- 1172 - 1184
- Publication date:
- 2007-01-01
- DOI:
- ISSN:
-
0162-1459
Item Description
- Language:
- English
- UUID:
-
uuid:cf321d44-28f2-4709-b937-7c0abbd9af17
- Local pid:
- oai:economics.ouls.ox.ac.uk:12743
- Deposit date:
- 2011-08-15
Related Items
Terms of use
- Copyright holder:
- American Statistical Association
- Copyright date:
- 2007
- Notes:
- This is an Author's Accepted Manuscript of an article published in Journal of the American Statistical Association, 102, 480, 1172-1184 (December 2007), © 2007 American Statistical Association, available online at: http://www.tandfonline.com/10.1198/016214506000001176.
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