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Conditional evaluation of predictive models: The cspa command
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DOI：10.1177/1536867X221141014.png)
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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.
Keyword:
st0696
cspa
conditional moment inequality
forecast evaluation
functional inference
series estimation
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2.4
论文数:
1.2K
被引数:
8.4K
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Uniform nonparametric inference for time series using Stata基于Stata的时间序列统一非参数推断.png)
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