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)
New Economics Papers: this item is included in nep-ecm and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (3) Track citations by RSS feed
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/55017/1/MPRA_paper_55017.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/67333/1/MPRA_paper_67333.pdf revised version (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:55017
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Series data maintained by Joachim Winter ().