Faculty of Economics and Administrative Sciences, Department of Econometrics, Usak University, Usak, Turkey.
Eur J Health Econ. 2020 Jul;21(5):801-811. doi: 10.1007/s10198-020-01174-z. Epub 2020 Mar 14.
The priority aim of this study is to investigate the effect of carbon footprint, which is an indicator of environmental degradation, on health expenditures for the USA. In the study, cointegration analysis was performed for the period 1970-2016 by using health expenditures, carbon footprint, gross domestic product per capita and life expectancy at birth variables. According to the results of standard cointegration analysis, only cointegration relationship between health expenditures and income was found. In the models with carbon footprint, no cointegration relationship was discovered between the original values of the variables. This result was approached with suspicion, and it was thought that there might be a hidden cointegration between healthcare expenditures and carbon footprint. For this purpose, the hidden cointegration analysis and crouching error correction model proposed by Granger and Yoon [18] were employed among the positive and negative components of the variables of healthcare expenditures and carbon footprint. The results of the hidden cointegration analysis revealed that there was a hidden cointegration relationship between the positive components of healthcare expenditures and the positive components of carbon footprint. Analysis results show that a 1% increase in carbon footprint will cause a 2.04% increase in healthcare expenditures in the long term in the USA. When the positive components of the variables were considered, it was concluded that there was a one-way long-term asymmetric causality relationship between carbon footprint and healthcare expenditures. As a result of the study, it was proposed that the carbon footprint should be diminished to prevent the increasing burden of the healthcare expenditures on the budget.
本研究的首要目标是探究碳足迹（环境污染程度的指标）对美国健康支出的影响。本研究采用 1970 年至 2016 年的健康支出、碳足迹、人均国内生产总值和出生时预期寿命等变量，通过协整分析进行了研究。根据标准协整分析的结果，仅发现健康支出与收入之间存在协整关系。在包含碳足迹的模型中，未发现变量原始值之间存在协整关系。对这一结果产生了怀疑，认为健康支出和碳足迹之间可能存在隐性协整关系。为此，采用了 Granger 和 Yoon [18] 提出的隐性协整分析和潜伏误差修正模型，对健康支出和碳足迹变量的正负分量进行了分析。隐性协整分析的结果表明，健康支出的正分量与碳足迹的正分量之间存在隐性协整关系。分析结果表明，在美国，碳足迹每增加 1%，长期来看将导致医疗支出增加 2.04%。当考虑变量的正分量时，碳足迹和医疗支出之间存在单向长期非对称因果关系。因此，研究建议减少碳足迹，以防止医疗支出对预算造成的负担不断增加。
