Multiple Linear Panel Regression with Multiplicative Random Noise

Hans Schneeweiß () and Gerd Ronning ()
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Hans Schneeweiß: University of Munich, Department of Statistics
Gerd Ronning: University of Tübingen, Department of Economics

A chapter in Statistical Modelling and Regression Structures, 2010, pp 399-417 from Springer

Abstract: 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.

Keywords: Panel regression; multiplicative measurement errors; bias correction; asymptotic variance; disclosure control (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2413-1_21

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DOI: 10.1007/978-3-7908-2413-1_21

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