Consistent estimation of linear panel data models with measurement error

Erik Meijer, Laura Spierdijk*, Tom Wansbeek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)169-180
Number of pages12
JournalJournal of Econometrics
Volume200
Issue number2
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • GMM
  • Heteroskedasticity
  • Measurement error
  • Panel data
  • Third moments

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