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Conditional evaluation of predictive models: The cspa command

Jia Li (), Zhipeng Liao (), Rogier Quaedvlieg and Wenyu Zhou ()
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Jia Li: Singapore Management University
Zhipeng Liao: University of California–Los Angeles
Wenyu Zhou: Zhejiang University

Stata Journal, 2022, vol. 22, issue 4, 924-940

Abstract: In this article, we introduce a new command, cspa, that implements the conditional superior predictive ability test developed in Li, Liao, and Quaed- vlieg (2022, Review of Economic Studies 89: 843–875). With the conditional per- formance 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. Confi- dence 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 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1177/1536867X221141014

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