Synthetic Estimation of Dynamic Panel Models When Either N or T or Both Are Not Large: Bias Decomposition in Systematic and Random Components

Carolina Carbajal-De-Nova and Francisco Venegas-Martínez
Authors registered in the RePEc Author Service: Carolina Carbajal De Nova

MPRA Paper from University Library of Munich, Germany

Abstract: By increasing the dimensions N or T, or both, in data panel analysis, bias can be reduced asymptotically to zero. This research deals with an econometric methodology to separate and measure bias through synthetic estimators without altering the data panel dimensions. This is done by recursively decomposing bias in systematic and random components. The methodology provides consistent synthetic estimators.

Keywords: panel data models; bias analysis; econometric modeling (search for similar items in EconPapers)
JEL-codes: C51 (search for similar items in EconPapers)
Date: 2019-06-09
New Economics Papers: this item is included in nep-ecm
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