文献详情
Quantile Regression for Dynamic Panel Data Using Hausman-Taylor Instrumental Variables
文献类型：期刊
通讯作者：Tian, MZ (reprint author), Renmin Univ China, Sch Stat, Ctr Appl Stat, Beijing 100872, Peoples R China.; Tian, MZ (reprint author), Lanzhou Univ Finance & Econ, Sch Stat, Lanzhou 730101, Gansu, Peoples R China.; Tian, MZ (reprint author), Xinjiang Univ Finance & Econ, Sch Stat & Informat, Urumqi 830012, Xinjiang, Peoples R China.
期刊名称：COMPUTATIONAL ECONOMICS影响因子和分区
年：2019
卷：53
期：3
页码：1033-1069
ISSN：0927-7099
关键词：Dynamic panel data; Quantile regression; Fixed effects; Penalized regression; Hausman-Taylor instrumental variables
所属部门：统计学院
摘要：This paper considers quantile regression for dynamic fixed effects panel data models with Hausman-Taylor instrumental variables (HTIV). The fixed effects estimators of panel data are typically biased when there existing lagged dependent variables and endogenous covariates as regressors, so we suggest the use of the Hausman-Taylor instrumental variables to reduce the dynamic bias. HTIV can be used even if independent variables do not vary with time when the unobserved heterogeneity is related to ...More
This paper considers quantile regression for dynamic fixed effects panel data models with Hausman-Taylor instrumental variables (HTIV). The fixed effects estimators of panel data are typically biased when there existing lagged dependent variables and endogenous covariates as regressors, so we suggest the use of the Hausman-Taylor instrumental variables to reduce the dynamic bias. HTIV can be used even if independent variables do not vary with time when the unobserved heterogeneity is related to the independent variables. Besides, there is no need for HTIV to adapt instrumental variables beyond the model. In this paper, we consider Hausman-Taylor instrumental variables and propose two quantile regression estimators. We study the asymptotic properties of the proposed estimators. Monte Carlo simulation studies are conducted to examine the performance of the two proposed estimators. In addition, we illustrate the new approaches with an application to analyze the factors affecting price of commercialized residential buildings of 35 big and moderate cities in China, finding out that pre-price has a marked effect on current price. ...Hide

DOI：10.1007/s10614-017-9779-0
百度学术：Quantile Regression for Dynamic Panel Data Using Hausman-Taylor Instrumental Variables
语言：外文
基金：major research projects of philosophy and social science of the Chinese Ministry of Education [15JZD015]; Major Program of Beijing Philosophy and Social Science Foundation of China [15ZDA17]; Key Program of National Philosophy and Social Science Foundation [13AZD064]; Renmin University of China: the special developing and guiding fund for building world-class universities (disciplines) [15XNL008]; China Statistical Research Project [2016LD03]; Fund of the Key Research Center of Humanities and Social Sciences in the general Colleges and Universities of Xinjiang Uygur Autonomous Region
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Bayesian LASSO-Regularized quantile regression for linear regression models with autoregressive errors.Tian, Yuzhu, Shen, Silian, Lu, Ge, et al. .COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION. 2019, 48(3), 777-796.
Quantile Regression for Dynamic Panel Data Using Hausman-Taylor Instrumental Variables.Tao, Li, Zhang, Yuanjie, Tian, Maozai,.COMPUTATIONAL ECONOMICS. 2019, 53(3), 1033-1069.
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