Estimation of Partially Specified Spatial Panel Data Models with Random-Effects

In this article, we study estimation of a partially specified spatial panel data linear regression with random-effects. Under the conditions of exogenous spatial weighting matrix and exogenous regressors, we give an instrumental variable estimation. Under certain sufficient assumptions, we show that...

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Bibliographic Details
Published in:Acta mathematica Sinica. English series 2015-03, Vol.31 (3), p.456-478
Main Authors: Zhang, Yuan Qing, Yang, Guang Ren
Format: Article
Language:English
Subjects:
Asymptotic methods
Asymptotic properties
Computer simulation
Data models
Estimators
Mathematical analysis
Mathematical models
Mathematics
Mathematics and Statistics
Monte Carlo methods
Monte Carlo simulation
Panels
Regression
Regression analysis
Studies
Variables
Weighting
估计量
数据模型
渐近正态分布
空间
线性回归
蒙特卡罗模拟
随机效应
面板
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Summary:In this article, we study estimation of a partially specified spatial panel data linear regression with random-effects. Under the conditions of exogenous spatial weighting matrix and exogenous regressors, we give an instrumental variable estimation. Under certain sufficient assumptions, we show that the proposed estimator for the finite dimensional parameter is root-N consistent and asymptotically normally distributed and the proposed estimator for the unknown function is consistent and asymptotically distributed. Consistent estimators for the asymptotic variance-covariance matrices of both the parametric and unknown components are provided. The Monte Carlo simulation results verify our theory and suggest that the approach has some practical value.
ISSN:1439-8516
1439-7617
DOI:10.1007/s10114-015-3569-1