caa a22 4500 605519781 CHVBK 20210128100732.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11009-014-9432-5 doi (NATIONALLICENCE)springer-10.1007/s11009-014-9432-5 Víšek Jan Faculty of Social Sciences, Institute of Economic Studies, Charles University, Opletalova 26, Prague, The Czech Republic aut Estimating the Model with Fixed and Random Effects by a Robust Method [Elektronische Daten] [Jan Víšek] Regression model with fixed and random effects estimated by modified versions of the Ordinary Least Squares (OLS) is a standard tool of panel data analysis. However, it is vulnerable to the bad effects of influential observations (contamination and/or atypical observations). The paper offers robustified versions of the classical methods for this framework. The robustification is carried out by the same idea which was employed when robustifying OLS, it is the idea of weighting down the large order statistics of squared residuals. In contrast to the approach based on the M-estimators this approach does not need the studentization of residuals to reach the scale- and regression-equivariance of estimator in question. Moreover, such approach is not vulnerable with respect the inliers. The numerical study reveals the reliability of the respective algorithm. The results of this study were collected in a file which is possible to find on web, address is given below. Patterns of these results were included also into the paper. The possibility to reach nearly the full efficiency of estimation - due to the iteratively tailored weight function - in the case when there are no influential points is also demonstrated. Springer Science+Business Media New York, 2014 Linear regression model nationallicence The least weighted squares nationallicence Fixed and random effects nationallicence Numerical simulations nationallicence Methodology and Computing in Applied Probability Springer US; http://www.springer-ny.com 17/4(2015-12-01), 999-1014 1387-5841 17:4<999 2015 17 11009 https://doi.org/10.1007/s11009-014-9432-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11009-014-9432-5 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Víšek Jan Faculty of Social Sciences, Institute of Economic Studies, Charles University, Opletalova 26, Prague, The Czech Republic aut NATIONALLICENCE 773 0- Methodology and Computing in Applied Probability Springer US; http://www.springer-ny.com 17/4(2015-12-01), 999-1014 1387-5841 17:4<999 2015 17 11009