Theoretical guidelines for a partially informed forecast examiner
MPRA Paper from University Library of Munich, Germany
The paper explores probability theory foundations behind evaluation of probabilistic forecasts. The emphasis is on a situation when the forecast examiner possesses only partially the information which was available and was used to produce a forecast. We argue that in such a situation forecasts should be judged by their conditional auto-calibration. Necessary and sufficient conditions of auto-calibration are discussed and expressed in the form of testable moment conditions. The paper also analyzes relationships between forecast calibration and forecast efficiency.
Keywords: probabilistic forecast; forecast calibration; moment condition; probability integral transform; orthogonality condition; scoring rule; forecast encompassing (search for similar items in EconPapers)
JEL-codes: C52 C53 (search for similar items in EconPapers)
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https://mpra.ub.uni-muenchen.de/67333/1/MPRA_paper_67333.pdf revised version (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:55017
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