Conditional evaluation of predictive models: The cspa command

• Autores: Jia Li, Zhipeng Liao, Rogier Quaedvlieg, Wenyu Zhou
• Localización: The Stata journal, ISSN 1536-867X, Vol. 22, Nº. 4, 2022, págs. 924-940
• Idioma: inglés
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• Resumen

  • 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.