Osband’s principle for identification functions

Timo Dimitriadis (), Tobias Fissler () and Johanna Ziegel ()
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Timo Dimitriadis: Heidelberg University
Tobias Fissler: Vienna University of Economics and Business (WU)
Johanna Ziegel: University of Bern

Statistical Papers, 2024, vol. 65, issue 2, No 23, 1125-1132

Abstract: Abstract Given a statistical functional of interest such as the mean or median, a (strict) identification function is zero in expectation at (and only at) the true functional value. Identification functions are key objects in forecast validation, statistical estimation and dynamic modelling. For a possibly vector-valued functional of interest, we fully characterise the class of (strict) identification functions subject to mild regularity conditions.

Keywords: Calibration; Characterisation; Identification function; Point forecasts; Z-estimation; 62C07; 62F10; 62J20 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00362-023-01428-x

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