Publication Type
Journal Article
Version
acceptedVersion
Publication Date
1-2023
Abstract
In this article, we introduce a new command, cspa, that implements the conditional superior predictive ability test developed in Li, Liao, and Quaedvlieg (2022, Review of Economic Studies 89: 843–875). With the conditional performance of predictive methods measured nonparametrically by the conditional expectation functions of their predictive losses, we test the null hypothesis that a benchmark model weakly outperforms a collection of competitors uniformly across the conditioning space. The proposed command can implement this test for both independent cross-sectional data and serially dependent time-series data. Confidence sets for the most superior model can be obtained by inverting the test, for which the cspa command also offers a convenient implementation.
Keywords
cspa, conditional moment inequality, forecast evaluation, functional inference, series estimation
Discipline
Econometrics
Research Areas
Econometrics
Publication
The Stata Journal
Volume
22
Issue
4
First Page
924
Last Page
940
ISSN
1536-867X
Identifier
10.1177/1536867X221141014
Publisher
SAGE Publications
Citation
LI, Jia; LIAO, Zhipeng; QUAEDVLIEG, Rogier; and ZHOU, Wenyu.
Conditional evaluation of predictive models: The cspa command. (2023). The Stata Journal. 22, (4), 924-940.
Available at: https://ink.library.smu.edu.sg/soe_research/2700
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1177/1536867X221141014