Efcient Estimation of Varying Coefcient Seemly Unrelated Regression Model  

作　　者：Qun-fang XU Yang BAI 

机构地区：[1]School of Sciences,Zhejiang Agriculture and Forestry University [2]School of Statistics and Management,Shanghai University of Finance and Economics [3]Key Laboratory of Mathematical Economics (SUFE),Ministry of Education

出　　处：《Acta Mathematicae Applicatae Sinica》2014年第1期119-144,共26页应用数学学报（英文版）

基　　金：Xu’s research was supported by Key Academic Project from Bureau of Statistics of Zhejiang Province(201325);Research Project of the National Statistics(2013LY119);Bai’s work was partially supported by National Natural Science Funds for Young Scholar(No.11001162);Shanghai University of Finance and Economics through Project 211 Phase IV and Shanghai Leading Academic Discipline Project(No.B804)

摘　　要：In this paper, we propose a class of varying coefficient seemingly unrelated regression models, in which the errors are correlated across the equations. By applying the series approximation and taking the contemporaneous correlations into account, we propose an efficient generalized least squares series estimation for the unknown coefficient functions. The consistency and asymptotic normality of the resulting estimators are established. In comparison with the ordinary/east squares ones, the proposed estimators are more efficient with smaller asymptotical variances. Some simulgtlon＇studies and a real application are presented to demonstrate the finite sample performance of the proposed methods. In addition, based on a B-spline approximation, we deduce the asymptotic bias and variance of the proposed estimators.In this paper, we propose a class of varying coefficient seemingly unrelated regression models, in which the errors are correlated across the equations. By applying the series approximation and taking the contemporaneous correlations into account, we propose an efficient generalized least squares series estimation for the unknown coefficient functions. The consistency and asymptotic normality of the resulting estimators are established. In comparison with the ordinary/east squares ones, the proposed estimators are more efficient with smaller asymptotical variances. Some simulgtlon＇studies and a real application are presented to demonstrate the finite sample performance of the proposed methods. In addition, based on a B-spline approximation, we deduce the asymptotic bias and variance of the proposed estimators.

关 键 词：series approximation varying coefficient seemingly unrelated regression contemporaneous correlation asymptotic normality 

分 类 号：O212.1[理学—概率论与数理统计] TN911.73[理学—数学]