How to apply dynamic panel bootstrap-corrected fixed-effects (xtbcfe) and heterogeneous dynamics (panelhetero)
| Autor: | Phebe Asantewaa Owusu, Samuel Asumadu Sarkodie |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Clinical Biochemistry
Kernel density estimation Bootstrap-corrected fixed-effects estimator 010501 environmental sciences Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420 [VDP] 01 natural sciences 03 medical and health sciences Robustness (computer science) Econometrics Imputation (statistics) Spurious relationship lcsh:Science Dynamic panel modeling Monte Carlo simulation 030304 developmental biology 0105 earth and related environmental sciences 0303 health sciences Treatment of Negative values Heterogeneous dynamics Samfunnsvitenskap: 200 [VDP] Missing data imputation Estimator xtbcfe Omitted-variable bias Method Article Missing data Matematikk og Naturvitenskap: 400::Geofag: 450 [VDP] Medical Laboratory Technology Within estimator panelhetero Bias correction lcsh:Q Dynamic panel bootstrap-corrected fixed-effects and Heterogeneous dynamics Samfunnsvitenskap: 200::Økonomi: 210 [VDP] Panel data |
| Zdroj: | MethodsX MethodsX, Vol 7, Iss, Pp 101045-(2020) |
| Popis: | The 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 of xtbcfe and panelhetero algorithm, we provide a step-by-step procedure and guidelines for the estimation approach. We apply the xtbcfe and panelhetero algorithm for global estimation of mortality, disability-adjusted life years and welfare cost from exposure to ambient air pollution. Importantly, the xtbcfe algorithm 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, and xtbcfe algorithms to examine the nexus between ambient air pollution and health outcomes. Graphical abstract Image, graphical abstract |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|