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Interpretation of point forecasts with unknown directive

Schmidt, Patrick; Katzfuss, Matthias; Gneiting, Tilmann 1
1 Institut für Stochastik (STOCH), Karlsruher Institut für Technologie (KIT)


Point forecasts can be interpreted as functionals (i.e., point summaries) of predictive distributions. We extend methodology for the identification of the functional based on time series of point forecasts and associated realizations. Focusing on state-dependent quantiles and expectiles, we provide a generalized method of moments estimator for the functional, along with tests of optimality under general joint hypotheses of functional relationships and information bases. Our tests are more flexible, and in simulations better calibrated and more powerful than existing solutions. In empirical examples, economic growth forecasts and model output for precipitation are indicative of overstatement in anticipation of extreme events.

Verlagsausgabe §
DOI: 10.5445/IR/1000137053
Veröffentlicht am 12.09.2021
DOI: 10.1002/jae.2833
Zitationen: 3
Web of Science
Zitationen: 2
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Stochastik (STOCH)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 09.2021
Sprache Englisch
Identifikator ISSN: 0883-7252, 1099-1255
KITopen-ID: 1000137053
Erschienen in Journal of Applied Econometrics
Verlag John Wiley and Sons
Band 36
Heft 6
Seiten 728-743
Vorab online veröffentlicht am 05.07.2021
Nachgewiesen in Dimensions
Web of Science
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