Resumen de Conditional evaluation of predictive models: The cspa command
Jia Li, Zhipeng Liao, Rogier Quaedvlieg, Wenyu Zhou
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.
