Kang, David (2021) Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms. Econometric Theory, 37 (2). pp. 311-345. ISSN 0266-4666
ET_4015_manuscript_Final_modified.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.
Download (491kB)
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).