Castagnetti, Carolina and Rossi, Eduardo (2008): Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study.
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Abstract
Recently some new techniques have been proposed for the estimation of the slope coefficients in presence of unobserved components. Though, the presence of common observed and unobserved factors is neither considered or the estimation of their impacts is not taken into account. In this work a range of estimators is surveyed and their finite-sample properties are examined by means of Monte Carlo experiments. We consider both the properties of estimators for the individual specific components and for the observed common effects.
Item Type: | MPRA Paper |
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Original Title: | Estimation methods in panel data models with observed and unobserved components: a Monte Carlo study |
Language: | English |
Keywords: | factor error structure; principal component; common regressors; cross-section dependence; large panels, Monte Carlo simulations. |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models |
Item ID: | 26196 |
Depositing User: | carolina castagnetti |
Date Deposited: | 29 Oct 2010 11:33 |
Last Modified: | 28 Sep 2019 01:30 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/26196 |