Economics at your fingertips  

Consistent estimation of linear panel data models with measurement error

Erik Meijer (), Laura Spierdijk and Tom Wansbeek

Journal of Econometrics, 2017, vol. 200, issue 2, 169-180

Abstract: 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.

Keywords: Measurement error; Panel data; Third moments; Heteroskedasticity; GMM (search for similar items in EconPapers)
JEL-codes: C23 C26 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Consistent Estimation of Linear Panel Data Models with Measurement Error (2015) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-05-11
Handle: RePEc:eee:econom:v:200:y:2017:i:2:p:169-180