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  • 标题:How to apply dynamic panel bootstrap-corrected fixed-effects (xtbcfe) and heterogeneous dynamics (panelhetero)
  • 本地全文:下载
  • 作者:Samuel Asumadu Sarkodie ; Phebe Asantewaa Owusu
  • 期刊名称:MethodsX
  • 印刷版ISSN:2215-0161
  • 电子版ISSN:2215-0161
  • 出版年度:2020
  • 卷号:7
  • 页码:1-14
  • DOI:10.1016/j.mex.2020.101045
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe characteristics of panel data namely, inter alia, missing values, cross-sectional dependence, serial correlation, small time period bias, omitted variable bias, country-specific fixed-effects, time effects, heterogeneous effects and convergence often lead to misspecification, and spurious regression, thus, affecting the consistency and robustness of the model. In this regard, a more sophisticated panel estimation technique that accounts for the attributes and challenges is worthwhile. The novel panel bootstrap-corrected fixed-effects estimator (xtbcfe) and heterogeneous dynamics (panelhetero) recommended in this study meets almost all the requirements for robust and consistent panel estimation with an interface for user modifications. We further demonstrate how to use empirical CDF, moments and kernel density estimation to investigate heterogeneous effects. Due to the complexities in the application ofxtbcfeandpanelheteroalgorithm, we provide a step-by-step procedure and guidelines for the estimation approach. We apply thextbcfeandpanelheteroalgorithm for global estimation of mortality, disability-adjusted life years and welfare cost from exposure to ambient air pollution. Importantly, thextbcfealgorithm can be applied to any panel data-based studies in social science, environmental science, environmental economics, health economics, energy economics, and among others.•Procedures useful for data imputation and transforming negative variables for time series, cross-sectional and panel data are presented.•Contrary to traditional models, we show how a novel approach can be modified and used to examine the degree of heterogeneous effects across cross-sectional units of panel data.•We demonstrate how the dynamic panel bootstrap-corrected fixed-effects estimator is useful in estimating higher-order panel data models and accounting for challenges such as omitted-variable bias, convergence, cross-section dependence and heterogeneous effects.•We apply the imputation technique,panelhetero, andxtbcfealgorithms to examine the nexus between ambient air pollution and health outcomes.Graphical abstractDisplay Omitted
  • 关键词:Bootstrap-corrected fixed-effects estimator;Treatment of Negative values;Bias correction;Within estimator;Dynamic panel modeling;Monte Carlo simulation;xtbcfe;panelhetero;Missing data imputation;Heterogeneous dynamics
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