Estimation in a semiparametric panel data model with nonstationarity. (14th September 2019)

• Record Type: Journal Article
• Authors: Dong, Chaohua; Gao, Jiti; Peng, Bin
• Is Part Of: Econometric reviews. Volume 38:Number 8(2019)
• Page Start: 961
• Page End: 977
• Publication Date: 2019-09-14
• Subjects: Asymptotic theory -- closed-form estimate -- orthogonal series method -- partially linear panel data model; C13 -- C14 -- C23 -- C51; Econometrics -- Periodicals; 330.015195
• DOI: 10.1080/07474938.2018.1514021
• Languages: English
• ISSNs: 0747-4938

Abstract

Abstract: In this paper, we consider a partially linear panel data model with nonstationarity and certain cross-sectional dependence. Accounting for the explosive feature of the nonstationary time series, we particularly employ Hermite orthogonal functions in this study. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the unknown functions for the cases where N and T go jointly to infinity. Rates of convergence and asymptotic normalities are established for the proposed estimators. Both the finite sample performance and the empirical applications show that the proposed estimation methods work well.