Robust Estimation for the Fixed Effect Panel Data Model
| Format: | Restricted Document |
|---|
| _version_ | 1860799511080730624 |
|---|---|
| building | INTELEK Repository |
| collection | Online Access |
| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 |
| date | 2018-01-18 13:00:12 |
| eventvenue | Bukit Tinggi, Sumatera |
| format | Restricted Document |
| id | 6283 |
| institution | UniSZA |
| originalfilename | 1117-01-FH03-FESP-18-12638.pdf |
| person | UniSZA Unisza unisza |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6283 |
| spelling | 6283 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6283 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 8 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in UniSZA Unisza unisza 2018-01-18 13:00:12 1117-01-FH03-FESP-18-12638.pdf UniSZA Private Access Robust Estimation for the Fixed Effect Panel Data Model Ordinary Least Square parameter estimation for the fixed effect regression suffers biasness in the presence of high leverage points. In this study, a robust alternative is proposed by incorporating new robust weights in Generalized M-estimator determined by a superior outlier detection method, Robust Diagnostic-F (RDF). The method helps to obtain new robust weights for Robust Within GM-estimator (RWGM). The performance of the newly proposed method, RWGM(RDF) is investigated using real and simulated data sets. The ratios of root mean square error are evaluated and compared with the existing RWGM under robust centering procedures. The newly proposed estimator is found to be more efficient and resilient towards high leverage points due to the success of the new robust weights. The results are confirmed through reanalyzing numerical examples. 8th International Conference on Numerical Optimization and Operation Research (ICNOOR-VIII) Bukit Tinggi, Sumatera |
| spellingShingle | Robust Estimation for the Fixed Effect Panel Data Model |
| summary | Ordinary Least Square parameter estimation for the fixed effect regression suffers biasness in the presence of high leverage points. In this study, a robust alternative is proposed by incorporating new robust weights in Generalized M-estimator determined by a superior outlier detection method, Robust Diagnostic-F (RDF). The method helps to obtain new robust weights for Robust Within GM-estimator (RWGM). The performance of the newly proposed method, RWGM(RDF) is investigated using real and simulated data sets. The ratios of root mean square error are evaluated and compared with the existing RWGM under robust centering procedures. The newly proposed estimator is found to be more efficient and resilient towards high leverage points due to the success of the new robust weights. The results are confirmed through reanalyzing numerical examples. |
| title | Robust Estimation for the Fixed Effect Panel Data Model |
| title_full | Robust Estimation for the Fixed Effect Panel Data Model |
| title_fullStr | Robust Estimation for the Fixed Effect Panel Data Model |
| title_full_unstemmed | Robust Estimation for the Fixed Effect Panel Data Model |
| title_short | Robust Estimation for the Fixed Effect Panel Data Model |
| title_sort | robust estimation for the fixed effect panel data model |