School of Management, Jiangsu University, Zhenjiang, China.
Front Public Health. 2022 Jun 17;10:903399. doi: 10.3389/fpubh.2022.903399. eCollection 2022.
This article explored the dynamic nexus among economic growth, industrialization, medical technology, and healthcare expenditure in West Africa while using urbanization and aged population as control variables. West African countries were sub-sectioned into low-income (LI) and lower-middle-income (LMI) countries. Panel data extracted from the World Development Indicators (WDI) from 2000 to 2019 were used for the study. More modern econometric techniques that are vigorous to cross-sectional dependence and slope heterogeneity were employed in the analytical process in order to provide accurate and trustworthy results. The homogeneity test and cross-sectional dependency test confirmed the studied panels to be heterogeneous and cross-sectionally dependent, respectively. Moreover, the CADF and CIPS unit root tests showed that the variables were not integrated in the same order. This, thus, leads to the employment of the PMG-ARDL estimation approach, which unveiled economic growth and urbanization as trivial determinants of healthcare expenditure in the LI and LMI panels. However, the results affirmed industrialization as a major determinant of healthcare expenditure in the LI and LMI panels. Additionally, medical technology was confirmed to decrease healthcare expenditure in the LMI panel, whereas in the LI panel, an insignificant impact was witnessed. Also, the aged population was found to intensify healthcare expenditure in both the LI and LMI panels. Lastly, on the causal connection between the series, the outcome revealed a mixture of causal paths among the variables in all the panels. Policy recommendations have therefore been proposed based on the study's findings.
本文探讨了西非经济增长、工业化、医疗技术和医疗支出之间的动态关系，同时将城市化和老年人口作为控制变量。西非国家分为低收入国家和中低收入国家。该研究使用了来自世界发展指标（WDI）的 2000 年至 2019 年的面板数据。为了提供准确和可靠的结果，在分析过程中使用了更现代的计量经济学技术，这些技术对横截面依赖性和斜率异质性具有强大的处理能力。同质性检验和横截面相关性检验分别证实了所研究的面板存在异质性和横截面相关性。此外，CADF 和 CIPS 单位根检验表明，变量没有以相同的顺序进行整合。因此，采用了 PMG-ARDL 估计方法，该方法表明经济增长和城市化是 LI 和 LMI 面板中医疗支出的微小决定因素。然而，结果证实工业化是 LI 和 LMI 面板中医疗支出的主要决定因素。此外，医疗技术被证实可以降低 LMI 面板中的医疗支出，而在 LI 面板中则没有显著影响。同样，老年人口被发现会加剧 LI 和 LMI 面板中医疗支出的增长。最后，在序列之间的因果关系方面，结果表明在所有面板中，变量之间存在多种因果关系。因此，根据研究结果提出了政策建议。
