Investigation of the Effects of Economic Indicators on Child Mortality: Panel Data Analysis

Year 2022, Volume: 8 Issue: 15, 12 - 21, 27.04.2022

Osman Şenol , İbrahim Hüseyin Cansever , Durmuş Gökkaya

https://doi.org/10.48121/jihsam.940188

Abstract

The health level of society is an indicator of the development as a whole, and it is monitored through various indicators. Among these indicators, infant and child mortality are followed by both countries and international organizations. The purpose of this study is to determine what effect economic variables have on child mortality. A Panel data analysis was used as a method in the study. Eviews 10.0 and Stata 15.0 package programs were used for data analysis. While the research universe is composed of 132 countries in the middle-upper income and high-income groups in the World Bank classification; The sample of the research consists of 49 countries whose data are taken. The time dimension of the study constitutes the 2000-2019 periods and the data types of the variables were used annually. While variables representing child mortality are used as dependent variables in the study; Gini index value representing income distribution, Gross Domestic Product, per capita income, public expenditure level, and the unemployment rate were used as independent variables. As a result of the research, it has been revealed that there is a positive relationship between the unemployment rate and income inequality and under-five mortality and neonatal deaths. Also, it has been observed that there is a negative relationship between the increase in public expenditure, per capita income and the level of Gross Domestic Product, and under-five mortality and neonatal deaths. It has been observed that the neonatal mortality rate is affected by economic variables more than the under-five mortality. In this context, it has been revealed that economic indicators are significantly related to child mortality.

Keywords

Child Mortality, Health Indicators, Health Expenditures, Income Inequality, Panel Data Analysis

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