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

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.

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Year of publication:	2019-06-09
Authors:	Carbajal-De-Nova, Carolina ; Venegas-Martínez, Francisco

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Type of publication:	Book / Working Paper
Language:	English
Notes:	Carbajal-De-Nova, Carolina and Venegas-Martínez, Francisco (2019): Synthetic Estimation of Dynamic Panel Models When Either N or T or Both Are Not Large: Bias Decomposition in Systematic and Random Components.
Classification:	C51 - Model Construction and Estimation
Source:	BASE

Persistent link: https://www.econbiz.de/10015264263