Estimation in a semiparametric panel data model with nonstationarity

被引:2
|
作者
Dong, Chaohua [1 ]
Gao, Jiti [2 ]
Peng, Bin [3 ]
机构
[1] Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan, Hubei, Peoples R China
[2] Monash Univ, Dept Econometr & Business Stat, Melbourne, Vic, Australia
[3] Univ Bath, Dept Econ, Bath BA2 7JP, Avon, England
基金
中国国家自然科学基金; 澳大利亚研究理事会;
关键词
Asymptotic theory; closed-form estimate; orthogonal series method; partially linear panel data model; UNIT-ROOT TESTS; TIME-SERIES; NONPARAMETRIC REGRESSION; DEPENDENCE; INFERENCE; TRENDS;
D O I
10.1080/07474938.2018.1514021
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:961 / 977
页数:17
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