Logo image
Two-step series estimation and specification testing of (partially) linear models with generated regressors
期刊文章   同儕審查

Two-step series estimation and specification testing of (partially) linear models with generated regressors

Yu-Chin Hsu, Jen-Che LiaoEric S. Lin
Econometric Reviews
2022

摘要

Linear and nonlinear generated regressors partially linear model semiparametric linear model series estimation specification tests Economics and Econometrics
This paper studies three semiparametric models that are useful and frequently encountered in applied econometric work—a linear and two partially linear specifications with generated regressors, i.e., the regressors that are unobserved, but can be nonparametrically estimated from the data. Our framework allows for generated regressors to appear in linear or nonlinear components of partially linear models. We propose two-step series estimators for the finite-dimensional parameters, establish their (Formula presented.) -consistency (with sample size n) and asymptotic normality, and provide the asymptotic variance formulae that take into account the estimation error of generated regressors. Moreover, we develop a nonparametric specification test for the models considered. Numerical performances of the proposed estimators and test via simulation experiments and an empirical application illustrate the utility of our approach.

相關連結

指標

1 檢視次數

詳細資料

Logo image