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Inference In Nonparametric Series Estimation With Specification Searches For The Number Of Series Terms

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  • Kang, Byunghoon

Abstract

Nonparametric series regression often involves specification search over the tuning parameter, that is, evaluating estimates and confidence intervals with a different number of series terms. This paper develops pointwise and uniform inferences for conditional mean functions in nonparametric series estimations that are uniform in the number of series terms. As a result, this paper constructs confidence intervals and confidence bands with possibly data-dependent series terms that have valid asymptotic coverage probabilities. This paper also considers a partially linear model setup and develops inference methods for the parametric part uniform in the number of series terms. The finite sample performance of the proposed methods is investigated in various simulation setups as well as in an illustrative example, that is, the nonparametric estimation of the wage elasticity of the expected labor supply from Blomquist and Newey (2002, Econometrica 70, 2455–2480).

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  • Kang, Byunghoon, 2021. "Inference In Nonparametric Series Estimation With Specification Searches For The Number Of Series Terms," Econometric Theory, Cambridge University Press, vol. 37(2), pages 311-345, April.
    • Handle: RePEc:cup:etheor:v:37:y:2021:i:2:p:311-345_4
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    Cited by:

    1. Giovanni Ballarin, 2023. "Impulse Response Analysis of Structural Nonlinear Time Series Models," Papers 2305.19089, arXiv.org, revised Jun 2024.

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