Consistent estimation of linear panel data models with measurement error

被引：11

作者：

Meijer, Erik ^{[1
]}

Spierdijk, Laura ^{[2
]}

Wansbeek, Tom ^{[2
]}

机构：

[1] Univ Southern Calif, Los Angeles, CA USA

[2] Univ Groningen, Groningen, Netherlands

来源：

JOURNAL OF ECONOMETRICS | 2017年 / 200卷 / 02期

关键词：

Measurement error; Panel data; Third moments; Heteroskedasticity; GMM; INSTRUMENTAL VARIABLE ESTIMATION; GENERALIZED-METHOD; GMM ESTIMATION; REGRESSION-COEFFICIENTS; EFFICIENT ESTIMATION; MOMENT ESTIMATORS; SAMPLE PROPERTIES; IN-VARIABLES; SELECTION; BIAS;

D O I：

10.1016/j.jeconom.2017.06.003

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Measurement error causes a bias towards zero when estimating a panel data linear regression model. The panel data context offers various opportunities to derive instrumental variables allowing for consistent estimation. We consider three sources of moment conditions: (i) restrictions on the covariance matrix of the errors in the equations, (ii) nonzero third moments of the regressors, and (iii) heteroskedasticity and nonlinearity in the relation between the error-ridden regressor and another, error-free, regressor. In simulations, these approaches appear to work well. (C) 2017 Elsevier B.V. All rights reserved.

引用

页码：169 / 180

页数：12

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