Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects
This paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data models with individual specific fixed effects and threshold effects simultaneously. We extend Hansen’s (Hansen, 1999) original setup to models including endogenous regressors, specifically, lagged depen...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2014/672610 |
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doaj-077eb519f0ca4883af1a65bec7da47292020-11-24T23:54:51ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/672610672610Estimation of Nonlinear Dynamic Panel Data Models with Individual EffectsYi Hu0Dongmei Guo1Ying Deng2Shouyang Wang3School of Management, University of Chinese Academy of Sciences, Beijing 100190, ChinaSchool of Economics, Central University of Finance and Economics, Beijing 100081, ChinaSchool of International Trade and Economics, University of International Business and Economics, Beijing 100029, ChinaAcademy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, ChinaThis paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data models with individual specific fixed effects and threshold effects simultaneously. We extend Hansen’s (Hansen, 1999) original setup to models including endogenous regressors, specifically, lagged dependent variables. To address the problem of endogeneity of these nonlinear dynamic panel data models, we prove that the orthogonality conditions proposed by Arellano and Bond (1991) are valid. The threshold and slope parameters are estimated by GMM, and asymptotic distribution of the slope parameters is derived. Finite sample performance of the estimation is investigated through Monte Carlo simulations. It shows that the threshold and slope parameter can be estimated accurately and also the finite sample distribution of slope parameters is well approximated by the asymptotic distribution.http://dx.doi.org/10.1155/2014/672610 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yi Hu Dongmei Guo Ying Deng Shouyang Wang |
spellingShingle |
Yi Hu Dongmei Guo Ying Deng Shouyang Wang Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects Mathematical Problems in Engineering |
author_facet |
Yi Hu Dongmei Guo Ying Deng Shouyang Wang |
author_sort |
Yi Hu |
title |
Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects |
title_short |
Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects |
title_full |
Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects |
title_fullStr |
Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects |
title_full_unstemmed |
Estimation of Nonlinear Dynamic Panel Data Models with Individual Effects |
title_sort |
estimation of nonlinear dynamic panel data models with individual effects |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2014-01-01 |
description |
This paper suggests a generalized method of moments (GMM) based estimation for dynamic panel data models with individual specific fixed effects and threshold effects simultaneously. We extend Hansen’s (Hansen, 1999) original setup to models including endogenous regressors, specifically, lagged dependent variables. To address the problem of endogeneity of these nonlinear dynamic panel data models, we prove that the orthogonality conditions proposed by Arellano and Bond (1991) are valid. The threshold and slope parameters are estimated by GMM, and asymptotic distribution of the slope parameters is derived. Finite sample performance of the estimation is investigated through Monte Carlo simulations. It shows that the threshold and slope parameter can be estimated accurately and also the finite sample distribution of slope parameters is well approximated by the asymptotic distribution. |
url |
http://dx.doi.org/10.1155/2014/672610 |
work_keys_str_mv |
AT yihu estimationofnonlineardynamicpaneldatamodelswithindividualeffects AT dongmeiguo estimationofnonlineardynamicpaneldatamodelswithindividualeffects AT yingdeng estimationofnonlineardynamicpaneldatamodelswithindividualeffects AT shouyangwang estimationofnonlineardynamicpaneldatamodelswithindividualeffects |
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1725464581414846464 |