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Panel Regression with Random Noise


  • Gerd Ronning
  • Hans Schneeweiss


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.

Suggested Citation

  • Gerd Ronning & Hans Schneeweiss, 2009. "Panel Regression with Random Noise," CESifo Working Paper Series 2608, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_2608

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    References listed on IDEAS

    1. Lin, An-loh, 1989. "Estimation of multiplicative measurement-error models and some simulation results," Economics Letters, Elsevier, vol. 31(1), pages 13-20.
    2. Wansbeek, Tom, 2001. "GMM estimation in panel data models with measurement error," Journal of Econometrics, Elsevier, vol. 104(2), pages 259-268, September.
    3. Griliches, Zvi & Hausman, Jerry A., 1986. "Errors in variables in panel data," Journal of Econometrics, Elsevier, vol. 31(1), pages 93-118, February.
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    More about this item


    panel regression; multiplicative measurement errors; bias correction; asymptotic variance; disclosure control;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General


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