Robust Estimation Procedure in Panel Data Model
The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectiona...
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2015
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my.usim-89792015-08-05T04:43:45Z Robust Estimation Procedure in Panel Data Model Nurul Sima, Mohamad Shariff, Cross Sectional Dependence Outliers Robust Method Panel Data The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependence is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered. 2015-08-05T04:43:45Z 2015-08-05T04:43:45Z 2014-01-01 Conference Paper 978-0-7354-1236-1 0094-243X http://ddms.usim.edu.my/handle/123456789/8979 en_US Amer Inst Physics |
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Cross Sectional Dependence Outliers Robust Method Panel Data |
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Cross Sectional Dependence Outliers Robust Method Panel Data Nurul Sima, Mohamad Shariff, Robust Estimation Procedure in Panel Data Model |
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The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependence is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered. |
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Conference Paper |
author |
Nurul Sima, Mohamad Shariff, |
author_facet |
Nurul Sima, Mohamad Shariff, |
author_sort |
Nurul Sima, Mohamad Shariff, |
title |
Robust Estimation Procedure in Panel Data Model |
title_short |
Robust Estimation Procedure in Panel Data Model |
title_full |
Robust Estimation Procedure in Panel Data Model |
title_fullStr |
Robust Estimation Procedure in Panel Data Model |
title_full_unstemmed |
Robust Estimation Procedure in Panel Data Model |
title_sort |
robust estimation procedure in panel data model |
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Amer Inst Physics |
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2015 |
url |
http://ddms.usim.edu.my/handle/123456789/8979 |
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1645152512934674432 |
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13.222552 |