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Multiple Linear Panel Regression with Multiplicative Random Noise

In: Statistical Modelling and Regression Structures

Author

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  • Hans Schneeweiß

    (University of Munich, Department of Statistics)

  • Gerd Ronning

    (University of Tübingen, Department of Economics)

Abstract

The paper explores the effect of multiplicative measurement errors on the estimation of a multiple linear panel data model. The conventional fixed effects estimator of the slope parameter vector,which ignores measurement errors, is biased. By correcting for the bias one can construct a consistent and asymptotically normal estimator. In addition, we find a consistent estimate of the asymptotic covariance matrix of this estimator. Measurement errors are sometimes deliberately added to the data in order to minimize their disclosure risk, and then it is often multiplicative errors that are used instead of the more conventional additive errors. Multiplicative errors can be analyzed in a similar way as additive errors, but with some important and consequential differences.

Suggested Citation

  • Hans Schneeweiß & Gerd Ronning, 2010. "Multiple Linear Panel Regression with Multiplicative Random Noise," Springer Books, in: Thomas Kneib & Gerhard Tutz (ed.), Statistical Modelling and Regression Structures, pages 399-417, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2413-1_21
    DOI: 10.1007/978-3-7908-2413-1_21
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