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New transformation methods in dynamic panel data models with heterogeneous time trends

机译:动态面板数据模型中具有不同时间趋势的新转换方法

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In this paper, we introduce new type of within groups transformations so called the double within groups (DWG) and the long within groups (LWG) transformations. Both transformations eliminate individual effects and heterogeneous deterministic time trends jointly. Asymptotic analysis shows that both the DWG and LWG estimators are consistent when T is large. Simulation results show that both estimators have smaller root mean squared errors than the modified within groups estimator.View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/13504850701735831
机译:在本文中,我们介绍了新型的组内转换,即组内双重转换(DWG)和组内较长转换(LWG)。两种转换共同消除了个体影响和异构确定性时间趋势。渐近分析表明,当T大时,DWG和LWG估计量都是一致的。仿真结果表明,两个估算器的均方根误差均小于修改组内估算器的均方根误差。查看全文下载全文相关变量linkedin,facebook,stumbleupon,digg,google,更多“,发布ID:” ra-4dff56cd6bb1830b“};添加到候选列表链接永久链接http://dx.doi.org/10.1080/13504850701735831

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