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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Main Authors: Yi Hu, Dongmei Guo, Ying Deng, Shouyang Wang
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/672610
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spelling 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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