One-step robust estimation of fixed-effects panel data models
The panel-data regression models are frequently applied to micro-level data, which often suffer from data contamination, erroneous observations, or unobserved heterogeneity. Despite the adverse effects of outliers on classical estimation methods, there are only a few robust estimation methods available for fixed-effects panel data. A new estimation approach based on two different data transformations is therefore proposed. Considering several robust estimation methods applied to the transformed data, the robust and asymptotic properties of the proposed estimators are derived, including their breakdown points and asymptotic distributions. The finite-sample performance of the existing and proposed methods is compared by means of Monte Carlo simulations.
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Volume (Year): 57 (2013)
Issue (Month): 1 ()
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- Badi H. Baltagi & Georges Bresson, 2012. "A Robust Hausman-Taylor Estimator," Center for Policy Research Working Papers 140, Center for Policy Research, Maxwell School, Syracuse University.
- Ronchetti, Elvezio & Trojani, Fabio, 2001. "Robust inference with GMM estimators," Journal of Econometrics, Elsevier, vol. 101(1), pages 37-69, March.
- Coakley, Jerry & Fuertes, Ana-Maria & Smith, Ron, 2006.
"Unobserved heterogeneity in panel time series models,"
Computational Statistics & Data Analysis,
Elsevier, vol. 50(9), pages 2361-2380, May.
- Jerry Coakley & Ana-Maria Fuertes & Ron Smith, 2004. "Unobserved Heterogeneity in Panel Time Series Models," Birkbeck Working Papers in Economics and Finance 0403, Birkbeck, Department of Economics, Mathematics & Statistics.
- Cízek, Pavel, 2011. "Semiparametrically weighted robust estimation of regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 774-788, January.
- Cizek, Pavel, 2008. "Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 687-696, June.
- Cizek, P., 2007. "Robust and Efficient Adaptive Estimation of Binary-Choice Regression Models," Discussion Paper 2007-12, Tilburg University, Center for Economic Research.
- Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
- Maria Caterina Bramati & Christophe Croux, 2007. "Robust estimators for the fixed effects panel data model," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 521-540, November.
- Wagenvoort, Rien & Waldmann, Robert, 2002. "On B-robust instrumental variable estimation of the linear model with panel data," Journal of Econometrics, Elsevier, vol. 106(2), pages 297-324, February.
- Cornwell, Christopher & Rupert, Peter, 1988. "Efficient Estimation with Panel Data: An Empirical Comparison of Instrumental Variables Estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(2), pages 149-155, April.
- Marc G. Genton & André Lucas, 2003. "Comprehensive definitions of breakdown points for independent and dependent observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 81-94.
- Marc G. Genton & André Lucas, 2000. "Comprehensive Definitions of Breakdown-Points for Independent and Dependent Observations," Tinbergen Institute Discussion Papers 00-040/2, Tinbergen Institute.