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mohamadi M, shahraki M. (2025). Dynamic relationship between health expenditure, carbon dioxide emission and human development index Evidence from OPEC countries. refahj. 25(96), : 1 doi:10.32598/refahj.25.96.1949.3
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URL: http://refahj.uswr.ac.ir/article-1-4280-en.html
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Extended Abstract
Introduction
One of the important economic variables in any society is the rate of growth and development, and in recent years, the Human Development Index (HDI) has been considered an important factor for development. The HDI is the average of life expectancy, education, and gross domestic product indices. In order to achieve development and raise the HDI, countries commit themselves to increasing economic growth, regardless of environmental considerations, which can lead to environmental pollution. Pollution can affect the economy and welfare, and in addition, it will pose serious risks to the survival of future generations and will jeopardize the development process of those countries. On the other hand, if a society views health care spending as an investment in human capital accumulation, then by considering human capital as a factor for economic growth, any increase in health care spending will lead to an increase in national production and income. It is clear that a healthier workforce is more motivated and productive, so health care spending, if it improves the health of individuals in society, can increase production and human development through improved productivity.
Countries usually support policies of rapid economic growth to reach a higher level of development, which have left many environmental impacts, especially for oil-exporting countries. On the other hand, environmental degradation also affects the health status and human development. Therefore, for policymaking, it is very necessary to examine the relationship between human development, environmental degradation, and health expenditures. Therefore, the aim of the present study is to examine the dynamic relationship between health expenditure, carbon dioxide emission and human development index Evidence from OPEC countries.
Method
This was a descriptive-analytical and applied study conducted at the international level using panel data from 12 OPEC member countries during the period 2000-2020 and using the econometric method of the vector error correction mechanism in the Eviews 10 software. To examine the stationery and absence of unit roots of the variables, panel data unit root tests; Im, Pesaran and Shin (IPS), Levin, Lin and Chu (LLC), and Fisher were used. In these tests, the null hypothesis indicates a unit root or non-stationery of the variables. To examine the cointegration between the variables, panel data cointegration tests such as Pedroni and Kao were used. In these tests, the null hypothesis is the absence of cointegration. The general form of the study models is as follows:
LHCit=α+β1 LCO2 it+β2 LHDIit+β3 POPit+β4 GOit+β5 LGDPPERit+β6 OPENit+β7 LIFEit+β8 SCHOOLit+μi+eit
LHDIit=α+β1 LCO2 it+β2 HLCit +β3 POP_GRit+β4 GOit+β5 LGDPPERit+β6 OPENit+β7 LIFEit+β8 LSCHOOLit+μi+eit
LCO2PC it=α+β1 LHDIit+β2 LHCPit +β3 POP_GRit+β4 GOit+β5 LGDPPERit+β6 OPENit+β7 LIFEit+β8 SCHOOLit+μi+eit
LCO2: Natural logarithm of carbon dioxide emissions (metric tons per capita)
LHDI: Natural logarithm of human development index
LHC: Natural logarithm of healthcare expenditure
GO: Government expenditure on education, total (% of GDP)
LGDPPER: Natural logarithm of GDP per capita (purchasing power parity)
OPEN: Trade openness
POP: Population growth rate (annual%)
LIFE: Life expectancy at birth (years)
SCHOOL: Tertiary enrolment rate (% gross)
Findings
The results of the unit root tests showed that some variables were stationary and some were non-stationary at the level. Variables that were non-stationary at the level, were stationary in the first difference. Panel data cointegration tests such as Pedroni and Kao were used. The results showed that the null hypothesis in the Kao and Pedroni tests is rejected at the 5% probability level; therefore, the lack of cointegration is rejected and the existence of a long-term relationship in the model is confirmed, and the model can be estimated using the VECM method. The results after estimation also showed that R2 for each of the main models was estimated to be 0.44, 0.66 and 0.46 percent for carbon dioxide emissions, human development index and health expenditures, respectively, which indicates that this estimate was able to explain more than 40 percent of the model in all three cases under study; Also, the normality tests of the error terms including Lotekpohl, Doornik-Hansen and Urzula showed that the error terms are normal. The LM autocorrelation test showed that there is no autocorrelation in the model and the stability tests also showed that all the roots of the VAR model are less than one, therefore model can be estimated using the VECM method. The results showed that there is a causal relationship between carbon dioxide emissions and the human development index. The increase in carbon dioxide emissions leads to an increase in health care expenditures and decrease in the human development index. Also, an increase in health expenditures led to an increase in the human development index.
Discussion
The model estimates showed that increasing health expenditures lead to increased carbon dioxide emissions and an increase in the human development index. The results of the causality test also showed that there is a one-way relationship between health expenditures and the human development index, which is that health expenditures are the causality of the human development index. This result is consistent with previous studies by Qureshi (2009), Alin and Marieta (2011), and Akbar et al. (2021) that increasing health expenditures can strengthen the human development index. Health expenditures may also be due to the emission of pollutants, which is the reason for energy consumption. With increasing energy consumption and the emission of pollutants such as carbon dioxide emissions and the expansion of greenhouse gas emissions caused by these substances, there will be a serious risk to the environmental situation and human health, which can increase health expenditures (Allin & Marietta, 2011). Also, increasing carbon dioxide emissions also lead to increased health expenditures. This result is consistent with studies such as Chaabouni and Saidi (2017), Apergis et al. (2018), and Akbar et al. (2021) that state that increased environmental degradation (CO2 emissions) increases health expenditures. In this study, a positive bidirectional relationship between health expenditures and CO2 emissions was confirmed at the 5% level, indicating that health activities may increase due to the emission of pollutants due to greater energy consumption and, consequently, increase health expenditures.
In general, in oil-exporting countries, the increase in carbon dioxide emissions leads to decrease in the human development index; Therefore, in order to reduce environmental effects in the path of development goals, it is necessary to use clean technologies in production processes. Also, countries should drastically reduce the use of carbon energy sources and increase the share of renewable sources in their energy mix to preserve the ecosystem and increase the quality of life.
Ethical Consideration:
Authors’ contributions
All authors have made substantial contributions to this study.
Funding
This study was not funded.
Conflicts of interest
The authors declared no conflict of interest.
Acknowledgments
In the present study, all ethical considerations, including the conditions of trustworthiness, honesty, and non-plagiarism, were observed, also we would like to thank all those who contributed to this study.
Refrence
Akbar, M., Hussain, A., Akbar, A., & Ullah, I. (2021). The dynamic association between healthcare spending, CO2 emissions, and human development index in OECD countries: Evidence from panel VAR model. Environment, development and sustainability, 23, 10470-10489. DOI:10.1007/s10668-020-01066-5.
Alin, O., & Marieta, M. D. (2011). Correlation analysis between the health system and human development level within the European :union:. International Journal of Trade, Economics and Finance, 2(2), 99. https://www.ijtef.com/papers/85-F00033.pdf
Apergis, N., Gupta, R., Lau, C. K. M., & Mukherjee, Z. (2018). US state-level carbon dioxide emissions: does it affect health care expenditure? Renewable and Sustainable Energy Reviews, 91, 521-530. https://doi.org/10.1016/j.rser.2018.03.035
Chaabouni, S., & Saidi, K. (2017). The dynamic links between carbon dioxide (CO2) emissions, health spending and GDP growth: A case study for 51 countries. Environmental research, 158, 137–144. https://doi.org/10.1016/j.envres.2017.05.041
Qureshi, M. A. (2009). Human development, public expenditure and economic growth: a system dynamics approach. International Journal of Social Economics, 36(1/2), 93–104. https://doi.org/10.1108/03068290910921217
Introduction
One of the important economic variables in any society is the rate of growth and development, and in recent years, the Human Development Index (HDI) has been considered an important factor for development. The HDI is the average of life expectancy, education, and gross domestic product indices. In order to achieve development and raise the HDI, countries commit themselves to increasing economic growth, regardless of environmental considerations, which can lead to environmental pollution. Pollution can affect the economy and welfare, and in addition, it will pose serious risks to the survival of future generations and will jeopardize the development process of those countries. On the other hand, if a society views health care spending as an investment in human capital accumulation, then by considering human capital as a factor for economic growth, any increase in health care spending will lead to an increase in national production and income. It is clear that a healthier workforce is more motivated and productive, so health care spending, if it improves the health of individuals in society, can increase production and human development through improved productivity.
Countries usually support policies of rapid economic growth to reach a higher level of development, which have left many environmental impacts, especially for oil-exporting countries. On the other hand, environmental degradation also affects the health status and human development. Therefore, for policymaking, it is very necessary to examine the relationship between human development, environmental degradation, and health expenditures. Therefore, the aim of the present study is to examine the dynamic relationship between health expenditure, carbon dioxide emission and human development index Evidence from OPEC countries.
Method
This was a descriptive-analytical and applied study conducted at the international level using panel data from 12 OPEC member countries during the period 2000-2020 and using the econometric method of the vector error correction mechanism in the Eviews 10 software. To examine the stationery and absence of unit roots of the variables, panel data unit root tests; Im, Pesaran and Shin (IPS), Levin, Lin and Chu (LLC), and Fisher were used. In these tests, the null hypothesis indicates a unit root or non-stationery of the variables. To examine the cointegration between the variables, panel data cointegration tests such as Pedroni and Kao were used. In these tests, the null hypothesis is the absence of cointegration. The general form of the study models is as follows:
LHCit=α+β1 LCO2 it+β2 LHDIit+β3 POPit+β4 GOit+β5 LGDPPERit+β6 OPENit+β7 LIFEit+β8 SCHOOLit+μi+eit
LHDIit=α+β1 LCO2 it+β2 HLCit +β3 POP_GRit+β4 GOit+β5 LGDPPERit+β6 OPENit+β7 LIFEit+β8 LSCHOOLit+μi+eit
LCO2PC it=α+β1 LHDIit+β2 LHCPit +β3 POP_GRit+β4 GOit+β5 LGDPPERit+β6 OPENit+β7 LIFEit+β8 SCHOOLit+μi+eit
LCO2: Natural logarithm of carbon dioxide emissions (metric tons per capita)
LHDI: Natural logarithm of human development index
LHC: Natural logarithm of healthcare expenditure
GO: Government expenditure on education, total (% of GDP)
LGDPPER: Natural logarithm of GDP per capita (purchasing power parity)
OPEN: Trade openness
POP: Population growth rate (annual%)
LIFE: Life expectancy at birth (years)
SCHOOL: Tertiary enrolment rate (% gross)
Findings
The results of the unit root tests showed that some variables were stationary and some were non-stationary at the level. Variables that were non-stationary at the level, were stationary in the first difference. Panel data cointegration tests such as Pedroni and Kao were used. The results showed that the null hypothesis in the Kao and Pedroni tests is rejected at the 5% probability level; therefore, the lack of cointegration is rejected and the existence of a long-term relationship in the model is confirmed, and the model can be estimated using the VECM method. The results after estimation also showed that R2 for each of the main models was estimated to be 0.44, 0.66 and 0.46 percent for carbon dioxide emissions, human development index and health expenditures, respectively, which indicates that this estimate was able to explain more than 40 percent of the model in all three cases under study; Also, the normality tests of the error terms including Lotekpohl, Doornik-Hansen and Urzula showed that the error terms are normal. The LM autocorrelation test showed that there is no autocorrelation in the model and the stability tests also showed that all the roots of the VAR model are less than one, therefore model can be estimated using the VECM method. The results showed that there is a causal relationship between carbon dioxide emissions and the human development index. The increase in carbon dioxide emissions leads to an increase in health care expenditures and decrease in the human development index. Also, an increase in health expenditures led to an increase in the human development index.
Discussion
The model estimates showed that increasing health expenditures lead to increased carbon dioxide emissions and an increase in the human development index. The results of the causality test also showed that there is a one-way relationship between health expenditures and the human development index, which is that health expenditures are the causality of the human development index. This result is consistent with previous studies by Qureshi (2009), Alin and Marieta (2011), and Akbar et al. (2021) that increasing health expenditures can strengthen the human development index. Health expenditures may also be due to the emission of pollutants, which is the reason for energy consumption. With increasing energy consumption and the emission of pollutants such as carbon dioxide emissions and the expansion of greenhouse gas emissions caused by these substances, there will be a serious risk to the environmental situation and human health, which can increase health expenditures (Allin & Marietta, 2011). Also, increasing carbon dioxide emissions also lead to increased health expenditures. This result is consistent with studies such as Chaabouni and Saidi (2017), Apergis et al. (2018), and Akbar et al. (2021) that state that increased environmental degradation (CO2 emissions) increases health expenditures. In this study, a positive bidirectional relationship between health expenditures and CO2 emissions was confirmed at the 5% level, indicating that health activities may increase due to the emission of pollutants due to greater energy consumption and, consequently, increase health expenditures.
In general, in oil-exporting countries, the increase in carbon dioxide emissions leads to decrease in the human development index; Therefore, in order to reduce environmental effects in the path of development goals, it is necessary to use clean technologies in production processes. Also, countries should drastically reduce the use of carbon energy sources and increase the share of renewable sources in their energy mix to preserve the ecosystem and increase the quality of life.
Ethical Consideration:
Authors’ contributions
All authors have made substantial contributions to this study.
Funding
This study was not funded.
Conflicts of interest
The authors declared no conflict of interest.
Acknowledgments
In the present study, all ethical considerations, including the conditions of trustworthiness, honesty, and non-plagiarism, were observed, also we would like to thank all those who contributed to this study.
Refrence
Akbar, M., Hussain, A., Akbar, A., & Ullah, I. (2021). The dynamic association between healthcare spending, CO2 emissions, and human development index in OECD countries: Evidence from panel VAR model. Environment, development and sustainability, 23, 10470-10489. DOI:10.1007/s10668-020-01066-5.
Alin, O., & Marieta, M. D. (2011). Correlation analysis between the health system and human development level within the European :union:. International Journal of Trade, Economics and Finance, 2(2), 99. https://www.ijtef.com/papers/85-F00033.pdf
Apergis, N., Gupta, R., Lau, C. K. M., & Mukherjee, Z. (2018). US state-level carbon dioxide emissions: does it affect health care expenditure? Renewable and Sustainable Energy Reviews, 91, 521-530. https://doi.org/10.1016/j.rser.2018.03.035
Chaabouni, S., & Saidi, K. (2017). The dynamic links between carbon dioxide (CO2) emissions, health spending and GDP growth: A case study for 51 countries. Environmental research, 158, 137–144. https://doi.org/10.1016/j.envres.2017.05.041
Qureshi, M. A. (2009). Human development, public expenditure and economic growth: a system dynamics approach. International Journal of Social Economics, 36(1/2), 93–104. https://doi.org/10.1108/03068290910921217
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Received: 2023/11/20 | Accepted: 2024/09/1 | Published: 2025/04/4
Received: 2023/11/20 | Accepted: 2024/09/1 | Published: 2025/04/4
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