School of Accounting, Zhejiang Gongshang University, Hangzhou, China.
Department of Insurance and Finance, National Taichung University of Science and Technology, Taichung, Taiwan.
Front Public Health. 2022 Sep 9;10:933728. doi: 10.3389/fpubh.2022.933728. eCollection 2022.
In this paper, we use the Fourier ARDL method (data from 2000 to 2019) to examine whether there is a correlation between economic fluctuation, health expenditure, and employment rate among BRICS countries. Fourier ARDL's model, the same as Bootstrap ARDL model, is to test the long-term cointegration relationship of variables; when there is cointegration, it will test whether there is a causal relationship. When there is no cointegration, short-term Granger causality between variables is tested. Our study shows that, in the long-term, whether South Africa takes economic fluctuation, employment rate or health expenditure as the dependent variable, there is a cointegration relationship with the other two independent variables, but the causal relationship is not significant. In short-term Granger causality tests, the effects of economic fluctuation in Brazil, China, and South Africa on health expenditure lag significantly by one period. Economic fluctuation in Brazil, India and China had a negative effect on employment rate, while South Africa had a positive effect. Health expenditure in Russia and India has a negative effect on employment rate, while China has a positive effect. Employment rates in China and South Africa have a significant positive effect on economic fluctuation, while Russia has a negative effect. India's employment rate has a negative effect on health expenditure, while South Africa's has a positive effect. In short-term causality tests, different countries will exhibit different phenomena. Except for economic fluctuation, where health spending is positive, everything else is negatively correlated, and all of them are positive in South Africa. Finally, we make policy recommendations for the BRICS countries on economic fluctuation, employment rates, and health expenditure.
在本文中,我们使用傅里叶 ARDL 方法(数据来自 2000 年至 2019 年)来检验金砖国家的经济波动、医疗支出和就业率之间是否存在相关性。傅里叶 ARDL 的模型与 Bootstrap ARDL 模型相同,用于检验变量的长期协整关系;当存在协整时,它将检验变量之间是否存在因果关系。当不存在协整时,将检验变量之间的短期格兰杰因果关系。我们的研究表明,从长期来看,无论是南非将经济波动、就业率还是医疗支出作为因变量,与其他两个自变量都存在协整关系,但因果关系并不显著。在短期格兰杰因果关系检验中,巴西、中国和南非的经济波动对滞后一期的医疗支出有显著影响。巴西、印度和中国的经济波动对就业率有负面影响,而南非则有正面影响。俄罗斯和印度的医疗支出对就业率有负面影响,而中国则有正面影响。中国和南非的就业率对经济波动有显著的正向影响,而俄罗斯则有负向影响。印度的就业率对医疗支出有负面影响,而南非的则有正向影响。在短期因果关系检验中,不同国家会表现出不同的现象。除了经济波动与医疗支出呈正相关外,其他都是负相关,而且南非所有情况都是正相关。最后,我们针对金砖国家的经济波动、就业率和医疗支出提出了政策建议。