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Approximating the Bias of the LSDV Estimator for Dynamic Unbalanced Panel Data Models

Giovanni Bruno ()

No 159, KITeS Working Papers from KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy

Abstract: This paper extends the LSDV bias approximations in Bun and Kiviet (2003) to unbalanced panels. The approximations are obtained by modify-ing the within operator to accommodate the dynamic selection rule. They are accurate, with higher order terms bringing only decreasing improve-ments to the approximations. This removes an important cause for limited applicability of bias corrected LSDV estimators.

Keywords: Bias approximation; Unbalanced panels; Dynamic panel data; LSDV estimator; Monte Carlo experiment (search for similar items in EconPapers)
JEL-codes: C23 (search for similar items in EconPapers)
Date: 2004-07, Revised 2004-07
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ftp://ftp.unibocconi.it/pub/RePEc/cri/papers/WP159Bruno.pdf (application/pdf)

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Journal Article: Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models (2005) Downloads
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