Volume 31, Issue 7 (October 2020)
Studies in Medical Sciences 2020, 31(7): 568-575 |
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Babaie M. THE EFFECT OF HEALTH INDICATORS AND MACROECONOMIC VARIABLES ON THE LEVEL OF LIFE EXPECTANCY: COMPARISON OF DEVELOPING AND DEVELOPED COUNTRIES WITH THE PANEL DATA APPROACH. Studies in Medical Sciences 2020; 31 (7) :568-575
URL: http://umj.umsu.ac.ir/article-1-5282-en.html
URL: http://umj.umsu.ac.ir/article-1-5282-en.html
PhD in Economics, Allameh Tabataba'i University, Tehran, Iran , majid.eghtesad@gmail.com
Abstract: (4924 Views)
Background & Aims: Economic and social factors have a great impact on health and consequently on life expectancy. Health means having complete physical, mental, and social well-being, and it does not only refer to the absence of disease and disability. Health status depends on the factors affecting it, including economic, social, cultural, physical environment, genetic factors, and the level of access to health services. The health status of communities is measured by health indicators. The present study compares the effect of health indicators and macroeconomic variables on life expectancy.
Materials & Methods: This study first describes the factors affecting the life expectancy index, then estimates the impact of macroeconomic indicators (economic growth), inflation and unemployment , and health indicators (health expenditure, food poverty, mortality rate and level of education) on life expectancy (information from the countries surveyed from the World Bank website, the International Monetary Fund and the World Health Report) using the Panel Data method in the period 2010 to 2018 for developed and developing countries using Eviews software.
Results: Limer and Hausman F tests were used to determine the optimal model. Based on these tests in both categories of developed and developing countries, the width of the origin was not the same for all sections and the Panel Data method was used and model estimation in the case of fixed effects over model estimation has priority over other methods.
In developing countries, inflation, unemployment, mortality, and food poverty rates have a negative effect on life expectancy and the impact of economic growth, education, and health expenditures on this index are positive, but due to the level of significance of research variables is observed. The effect of education and health expenditures on life expectancy index is not considered significant. This may be due to the low level of education and spending on health in these countries.
Also, in developed countries, inflation, unemployment, mortality, and food poverty rates have a negative effect on life expectancy and the effect of economic growth, education, and health expenditures on this index is positive, but due to the significant level of research variables, the effect is observed. Inflation and mortality rates are not considered significant on the life expectancy index. This may be due to low inflation and mortality rates in these countries.
Conclusion: The results of comparing the panels of developed and developing countries show that in almost both categories of studied indicators, the impact of economic and health indicators on life expectancy index in developing countries is more than the developed countries. This can be due to the poor state of economic and health indicators in developing countries compared to developed countries, which with each change in these variables, the status of life expectancy index shows more changes than developed countries.
Materials & Methods: This study first describes the factors affecting the life expectancy index, then estimates the impact of macroeconomic indicators (economic growth), inflation and unemployment , and health indicators (health expenditure, food poverty, mortality rate and level of education) on life expectancy (information from the countries surveyed from the World Bank website, the International Monetary Fund and the World Health Report) using the Panel Data method in the period 2010 to 2018 for developed and developing countries using Eviews software.
Results: Limer and Hausman F tests were used to determine the optimal model. Based on these tests in both categories of developed and developing countries, the width of the origin was not the same for all sections and the Panel Data method was used and model estimation in the case of fixed effects over model estimation has priority over other methods.
In developing countries, inflation, unemployment, mortality, and food poverty rates have a negative effect on life expectancy and the impact of economic growth, education, and health expenditures on this index are positive, but due to the level of significance of research variables is observed. The effect of education and health expenditures on life expectancy index is not considered significant. This may be due to the low level of education and spending on health in these countries.
Also, in developed countries, inflation, unemployment, mortality, and food poverty rates have a negative effect on life expectancy and the effect of economic growth, education, and health expenditures on this index is positive, but due to the significant level of research variables, the effect is observed. Inflation and mortality rates are not considered significant on the life expectancy index. This may be due to low inflation and mortality rates in these countries.
Conclusion: The results of comparing the panels of developed and developing countries show that in almost both categories of studied indicators, the impact of economic and health indicators on life expectancy index in developing countries is more than the developed countries. This can be due to the poor state of economic and health indicators in developing countries compared to developed countries, which with each change in these variables, the status of life expectancy index shows more changes than developed countries.
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