- 1. INTRODUCTION
Life expectancy at birth indicates how many years an individual born in society will live on a particular year. Life expectancy at birth is one of the most important indicators of the health status and welfare level of society. It is frequently used in comparing health levels among countries and is one of the most important indicators of development. Increasing life expectancy accelerates economic growth and development by making significant contributions to human capital. Many economic, social, cultural, environmental and demographic factors affect life expectancy. In this respect, life expectancy at birth is of great importance for many countries today. Therefore, it becomes essential to know what factors affect life expectancy at birth in terms of health, social and economic policies to be implemented by countries.
2. LITERATURE REVIEW
While doing the literature review, it was paid attention to the studies that the life expectancy at birth was the dependent variable. When the related literature is analyzed, studies with economic, social, demographic, health and even political variables affecting life expectancy at birth are found. It has been observed that recent domestic and foreign studies are generally directed towards socio-economic variables. In this section, the literature on the subject is examined, and the related studies are tried to be summarized.
3. LIFE EXPECTANCY AT BIRTH AND AFFECTING FACTORS
Life expectancy at birth is frequently used in comparing the health levels of countries and while life expectancy increases in the societies where a healthy lifestyle is maintained, it is accepted that both the quality of life and health services are useful in these societies. Many economic, social, cultural, environmental and demographic factors affect life expectancy.
Due to the income increase of the countries and the improvements in health, life expectancy at birth increases. Increasing the resources allocated to health decreases diseases and deaths while increasing the quality of life and extending the average life.
Urbanization is seen as one of the factors affecting life expectancy. Urbanization makes life more comfortable with its proximity to the goods and services that individuals need. Urbanization can have positive effects on life expectancy by facilitating life with the increased educational opportunities, increased access to medicines, medicines, clean water and food when needed.
One of the factors that may affect the life expectancy at birth is the rate of crude birth. The fact that the births at very high rates in a country do not mean that the population growth rate will be very high. Increasing the health level of society and increasing the awareness of health decrease the fertility rate and positively affect the increase in the average life.
4. DATA, MODEL AND METHOD
In this section, the countries included in the study in order to determine the determinants of life expectancy at birth, data of these indicators and data sources of these countries are included.
Variable Description Source
Life Expectancy at Birth (LDYB) Total in Years WB Databank (WB, 2020)
GDP Per Capita (LGDP) Per Capita, Current US Dollar WB Databank (WB, 2020)
Urbanization (LURBAN) % of Total Population WB Databank (WB, 2020)
Crude Birth Rate (LKDO) Per 1000 People WB Databank (WB, 2020)
Carbon Dioxide Emission (LCO) Per Person in Tons OECD Database (OECD, 2020)
Countries included in the analysis; USA, UK, Turkey, Sweden, Spain, Portugal, Norway, New Zealand, Mexico, Ireland, Iceland, France, Germany, Finland, Greece, Denmark, Chile, Austria, Luxembourg, Australia, South Korea, Belgium, Japan, Canada, Israel Designated as the Netherlands, Italy and Switzerland
In order to determine the determinants of life expectancy at birth, the full logarithmic model created with variables whose logarithmic transformations are made is shown in Equation 1.
LDYBit=αi+ β1i LGDPit+ β2i LURBANit+ β3i LKDOit+ β4i LCOit + εit (1)
(i= 1,…39) and (t= 1980,…, 2018)
The letters i and t in Equation 1 show the cross-section size and time dimension of the mentioned variables, respectively. In this study, dynamic panel econometric forecasts are made with data sets from 28 countries. Long-term coefficients of the variables were estimated using the CommonCorelated Effects (CCE) method developed by Pesaran (2006), assuming horizontal cross-section dependency and heterogeneity.
When the co-integration estimator results are analyzed, in 28 OECD countries, the effect of per capita income and urbanization on life expectancy at birth is statistically significant; however, co-integration coefficients of coarse birth rate and carbon dioxide emissions were found to be statistically insignificant. The findings in these countries, which make up the panel, show that a 1% increase in per capita income reduces the life expectancy at birth by approximately 0.007%. This result is in parallel with the result obtained by Sede and Ohemang (2015). On the other hand, a 1% increase in urbanization increases life expectancy at birth by approximately 0.27%. This result is Ecevit (2013), and Shahbaz et al. (2015) support the results they obtained in their work.
The presence of a co-integration relationship between variables is analyzed by the test proposed by Westerlund (2006), which can be used in cases where horizontal cross-section dependency is present or not, taking into account structural breaks.
In this study, the effects of GDP per capita, crude birth rate, urbanization rate and carbon dioxide emission per capita in life expectancy were analyzed by dynamic panel econometric estimates with data from 1980-2018 in 28 OECD countries. Findings, in 28 OECD countries, the impact of per capita income and urbanization on life expectancy at birth was statistically significant; however, co-integration coefficients of crude birth rate and carbon dioxide emission are statistically insignificant. Across the panel, a 1% increase in per capita income reduces life expectancy at birth by about 0,007%, while a 1% increase in urbanization increases life expectancy at birth by about 0,27%. Also, the impact of the factor affecting life expectancy at birth in 28 OECD countries is estimated to differ from country to country.
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