Panel Regression with Random Noise
The paper explores the effect of measurement errors on the estimation of a linear panel data model. The conventional fixed effects estimator, which ignores measurement errors, is biased. By correcting for the bias one can construct consistent and asymptotically normal estimators. In addition, we find estimates for the asymptotic variances of these estimators. The paper focuses on multiplicative errors, which are often deliberately added to the data in order to minimize their disclosure risk. They can be analyzed in a similar way as additive errors, but with some important and consequential differences.
|Date of creation:||2009|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +49 (89) 9224-0
Fax: +49 (89) 985369
Web page: http://www.cesifo.de
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Griliches, Zvi & Hausman, Jerry A., 1986.
"Errors in variables in panel data,"
Journal of Econometrics,
Elsevier, vol. 31(1), pages 93-118, February.
- Lin, An-loh, 1989. "Estimation of multiplicative measurement-error models and some simulation results," Economics Letters, Elsevier, vol. 31(1), pages 13-20.
- Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_2608. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Julio Saavedra)
If references are entirely missing, you can add them using this form.