Open Access
2021 Forecast evaluation of quantiles, prediction intervals, and other set-valued functionals
Tobias Fissler, Rafael Frongillo, Jana Hlavinová, Birgit Rudloff
Author Affiliations +
Electron. J. Statist. 15(1): 1034-1084 (2021). DOI: 10.1214/21-EJS1808


We introduce a theoretical framework of elicitability and identifiability of set-valued functionals, such as quantiles, prediction intervals, and systemic risk measures. A functional is elicitable if it is the unique minimiser of an expected scoring function, and identifiable if it is the unique zero of an expected identification function; both notions are essential for forecast ranking and validation, and M- and Z-estimation. Our framework distinguishes between exhaustive forecasts, being set-valued and aiming at correctly specifying the entire functional, and selective forecasts, content with solely specifying a single point in the correct functional. We establish a mutual exclusivity result: A set-valued functional can be either selectively elicitable or exhaustively elicitable or not elicitable at all. Notably, since quantiles are well known to be selectively elicitable, they fail to be exhaustively elicitable. We further show that the classes of prediction intervals and Vorob’ev quantiles turn out to be exhaustively elicitable, hence not selectively elicitable, but still selectively identifiable. In particular, we provide a mixture representation of elementary exhaustive scores, leading the way to Murphy diagrams. We establish that the shortest prediction interval and those specified by an endpoint or midpoint in general fail to be elicitable with respect to either notion, unless an endpoint is given via a quantile. We end with a comprehensive literature review on common practice in forecast evaluation of set-valued functionals.

Funding Statement

T. Fissler received financial support via his Chapman Fellowship from Imperial College London for parts of this work. R. Frongillo was supported in part by the U.S. National Science Foundation under Grant No. 1657598. B. Rudloff acknowledges support from the OeNB anniversary fund, project number 17793.


We would like to express our sincere gratitude to Tilmann Gneiting and Johanna Ziegel for insightful discussions about the topic, to Alexander Jordan who helped to coin the terminology of exhaustive versus selective elicitability in a joint discussion, to Dario Azzimonti, Zied Ben Bouallègue, Seamus Bradley, Jonas Brehmer, Timo Dimitriadis, David Ginsbourger, Claudio Heinrich, Kory Johnson, Xiaochun Meng, Ilya Molchanov, Ruodu Wang, and Dominic Wrazidlo for valuable discussions and helpful references, and to Yuan Li for a careful proofreading of an earlier version of this paper.


Download Citation

Tobias Fissler. Rafael Frongillo. Jana Hlavinová. Birgit Rudloff. "Forecast evaluation of quantiles, prediction intervals, and other set-valued functionals." Electron. J. Statist. 15 (1) 1034 - 1084, 2021.


Received: 1 August 2020; Published: 2021
First available in Project Euclid: 16 March 2021

Digital Object Identifier: 10.1214/21-EJS1808

Primary: 62C05 , 62F07 , 91B06
Secondary: 62H11

Keywords: consistency , convex level sets , elicitability , Identifiability , M-estimation , prediction intervals , random sets , Vorob’ev quantiles

Vol.15 • No. 1 • 2021
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