摘要
本文建立了一类变系数面板数据模型.此模型假设自变量的系数是某一平滑变量的未知函数,允许自变量,平滑变量和误差项存在通过共同因子结构引入的截面相关.由于一些共同因子的不可观测性,本文采用局部线性共同相关效应估计方法对未知的函数进行估计并给出了估计量的渐近性质.蒙特卡罗模拟结果表明该估计方法具有良好的小样本性质.利用1990-2012年中国省级面板数据,本文对我国外商直接投资与经济增长之间的关系进行了实证分析,结果表明:外商直接投资和经济增长之间存在明显非线性关系,各省份不同的初始经济水平会导致外商直接投资对经济增长的影响不同.
In this paper,we propose a varying-coefficient panel data model.This model assumes the coefficients of explanatory variables to be unknown functions of certain smooth variables and allows for cross-sectional dependence among explanatory,smooth variables and error terms through a common factors structure.The local linear common correlated effect estimation technique is applied to estimating the varying coefficients,and the asymptotic property for the proposed estimator is established.Meanwhile,Monte Carlo simulations demonstrate good finite sample performance for this estimator.Furthermore,we examine the relationship between foreign direct investment(FDI)and economic growth by using China’s provincial level data in the period from 1990 to 2012.Our empirical findings verify the existence of a significant nonlinear relationship,and show that the impact of FDI on economic growth depends on the level of initial economic conditions in different regions.
作者
徐秋华
张梓玚
XU Qiuhua;ZHANG Ziyang(School of Finance,Southwestern University of Finance and Economics,Chengdu 611130,China)
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2019年第4期817-828,共12页
Systems Engineering-Theory & Practice
基金
福建省统计科学重点实验室(厦门大学)开放课题(2016004)~~
关键词
面板数据模型
截面相关
变系数
局部线性估计
共同相关效应
panel data models
cross-sectional dependence
varying coefficient
local linear estimation
common correlated effects
