Econometric Theory· 2026Q1
A BOOTSTRAP SPECIFICATION TEST FOR SEMIPARAMETRIC MODELS WITH GENERATED REGRESSORS
- 1citations
- Q1SCImago
- 2026year
Short summary
A novel wild bootstrap test accurately validates semiparametric models containing nonparametrically generated regressors, showing good performance in simulations and a real-world application.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces a specification test for semiparametric models with nonparametrically generated regressors.
- Employs a novel wild bootstrap procedure for valid critical value calculation.
- The test is implementable with bias-corrected nonparametric estimators, avoiding undersmoothing.
- Demonstrates good small-sample performance in simulations.
- Applied successfully to women's labor force participation decisions.
AI-generated from the title and abstract; the full text is not read.
Abstract
This article provides a specification test for semiparametric models with nonparametrically generated regressors. Such regressors are not observed by the researcher but are nonparametrically identified and estimable. Applications of the test include models with endogenous regressors identified by control functions, semiparametric sample selection models, or binary games with incomplete information. The statistic is built from the residuals of the semiparametric model. A novel wild bootstrap procedure is shown to provide valid critical values. We consider nonparametric estimators with an automatic bias correction that makes the test implementable without undersmoothing. In simulations, the test exhibits good small sample performance, and an application to women’s labor force participation decisions shows its implementation in a real data context.
The authors' abstract, as published at the source. Econometric Theory, 2026 · DOI ↗
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Field: Statistics and Probability
Statistics and ProbabilityMathematics