Some Determinants of Infant Mortality Rate in SAARC Countries: an Empirical Assessment through Panel Data Analysis

2020 ◽  
Vol 13 (6) ◽  
pp. 2093-2116
Author(s):  
Ujjal Protim Dutta ◽  
Hemant Gupta ◽  
Asok Kumar Sarkar ◽  
Partha Pratim Sengupta
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Panel Data Analysis ◽  
Infant Mortality Rate ◽  
Empirical Assessment

Determinants of Infant Mortality Rate in Malaysia: Evidence from Dynamic Panel Data Study

2019 ◽  
Vol 21 (4) ◽  
pp. 443-450
Author(s):  
Chor Foon Tang
Keyword(s):  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Spending ◽  
Mortality Rates ◽  
Dynamic Panel Data ◽  
Infant Mortality Rate ◽  
Female Education ◽  
Dynamic Panel ◽  
Governance Quality

Understanding the factors associated with the infant mortality rate is essential as it may guide policymaking in efforts to alleviate the high incidence of infant mortality. The aim of this study is to explore the major determinants of the infant mortality rate with specific focus accorded to research and development (R&D) and governance quality. Our analysis utilizes unbalanced panel data from 122 countries from 2001 to 2013. Using the dynamic panel data generalized method of moments (GMM) estimator, we find that income, health spending, female education, technological progress and governance quality have significant negative impact on infant mortality rates. It can thus be surmised that policies to reduce infant mortality rates should focus upon improving the level of income, female education, health spending and governance quality, besides encouraging R&D activities.

scholarly journals PANEL DATA REGRESSION ANALYSIS FOR FACTORS AFFECTING INFANT MORTALITY RATE IN EAST JAVA 2013-2017

2021 ◽  
Vol 16 (3) ◽  
pp. 437
Author(s):  
Faishal Azhar Wardhana ◽  
Rachmah Indawati
Keyword(s):  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Data Availability ◽  
Infant Mortality Rate ◽  
Complete Coverage ◽  
Cross Sectional ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Government

ABSTRACTThe escalating infant mortality rate (IMR) in Indonesia has not been able to fulfill the target of Sustainable Development Goals (SDGs) that restrict the limit of IMR to just 12 of 1,000 live births. According to such fact, this research was designed as the application of panel data regression in an IMR case study of East Java from 2013–2017. Regression panel data enable research in describing cross-sectional and time series information. The variety of data availability in this method were capable of producing a high degree of freedom, allowing it to meet the prerequisites and statistical properties. This method was considered the most suitable one for analyzing the rising IMR. This research was classified as non-reactive research. All regencies/cities in East Java served as this study’s population. Data collection included K4 coverage, childbirth assistance, and KN complete coverage. The result of panel data regression showed a significant connection between K4 coverage (0.0230), childbirth assistance (p = 0.0105), and KN complete coverage (0.0205). Adjusted R-Square value was obtained with an amount of 80%, which means that all independent variables were able to explain the dependent one of that value, while the remaining were explained by other factors. This study can provide some suggestions to support IMR in East Java, including handling from the government or related pregnant families to support IMR on an ongoing basis. Keywords: panel data regression, IMR, K4, childbirth assistance, KN complete

Reflections on Microfinance

2019 ◽  
pp. 188-207
Author(s):  
Sovik Mukherjee ◽  
Ramesh Chandra Das
Keyword(s):  
Economic Development ◽  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Poverty Alleviation ◽  
Poverty Reduction ◽  
Poverty Line ◽  
Infant Mortality Rate ◽  
Self Sufficiency ◽  
Socio Economic Development

Microfinance has become the latest buzzword in the credit markets where it shoulders the responsibility of alleviating poverty coupled with socio-economic development. Dealing with microfinance coupled with the issue of poverty reduction, the first concern is to handle the twin objectives of poverty alleviation and achievement of financial self-sufficiency, which are often at loggerheads. To begin with, the present chapter constructs a five-dimensional human poverty index (HPI) in terms of the rate of unemployment, state wise illiteracy rate, state-wise infant mortality rate, state-wise percentage of population below the poverty line, and the percentage of population not having an access to electricity for the states across India. Thus, this will serve as an index for the extent of poverty. Consequently, a fall in the value of the index actually implies poverty alleviation. This empirical model does not justify the hypothesis that “microfinance reduces poverty” at the macro level using cross-state panel data for India.

scholarly journals Socioeconomic Determinants of Infant Mortality Rate in Asean: A Panel Data Analysis

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Vita Kartika Sari ◽  
Dwi Prasetyani
Keyword(s):  
Health Status ◽  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Health Expenditure ◽  
Strong Influence ◽  
Mortality Rates ◽  
Infant Mortality Rate ◽  
Gdp Per Capita ◽  
Per Capita

The infant mortality rate indicates the health status of a country. Previous studies have proven that socioeconomic factors have a significant influence on infant mortality rates in both developed and developing countries. Further studies on infant mortality rates are useful for public service strategic policy in the health sector. The main purpose of this study was to analyze the socioeconomic factors influencing infant mortality rates in ASEAN based on panel data estimates for 2000-2017. The dependent variable for this study was infant mortality rate, while the independent variables were health expenditure, female labor force, maternal fertility rate, and GDP per capita. The authors concluded that the main cause of infant mortality in ASEAN is care during delivery. Other influencing factors include family health status, maternal education level, and socio-economic inequality. This study found that the size of the female workforce has a strong influence on increasing the infant mortality rate in ASEAN. The fertility rate also had a strong influence on increasing infant mortality rate in ASEAN, while GDP per capita had a negative influence on infant mortality rate.  Health expenditure is proven to have no effect on the increase of infant mortality rates in ASEAN.

Major Determinants of Infant Mortality

2018 ◽  
Vol 20 (3) ◽  
pp. 345-362
Author(s):  
Subhanil Banerjee
Keyword(s):  
Panel Data ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Nutritional Status ◽  
Birth Spacing ◽  
Infant Mortality Rate ◽  
Development Indicators ◽  
Behavioural Factors ◽  
Health Programmes ◽  
Better Than

Infant mortality rate (IMR) is one of the most important development indicators. In India, there is a severe interstate disparity regarding IMR. Kerala registers a very low IMR; whereas in Odisha it is pretty high. It is somewhat paradoxical as Odisha fares substantially better than many other states with lower IMR regarding total fertility rate, antenatal care and in many other aspects. The present article attempts to investigate the applicability of usually perceived major determinants of IMR as evidenced in the existing literature for Odisha. The panel data multiple regression carried out with data of 30 districts of Odisha over three years indicates that physiological and behavioural factors together with maternal and demographic factors are perhaps more important than the health programmes for reduction of IMR in Odisha. Moreover, many of the usually perceived major determinants of IMR including economic betterment are statistically insignificant for Odisha. The policymakers should take into account these facts and instead of a series of health programmes, they might resort to awareness building regarding breastfeeding and birth spacing. Mother’s nutritional status should also be strengthened so that they can sustain exhaustive breastfeeding for first six months after the birth of the child.

scholarly journals Macroeconomic Determinants of Infant Mortality in WAEMU Countries: Evidence from Panel Data Analysis

2018 ◽  
Vol 5 (6) ◽  
pp. 52
Author(s):  
Edem K. Abbuy
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Data Model ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Infant Mortality Rate ◽  
Panel Data Model ◽  
Per Capita ◽  
Female Literacy ◽  
Macroeconomic Determinants

This paper investigates the macroeconomic determinants of infant mortality in WAEMU countries for the period 1980–2016. A panel data model from WAEMU countries was used to identify the macroeconomic determinants of infant mortality. We used fixed effects instrumental variables (FE-IV) estimator in panel data model. Our analysis using econometric estimations after correcting for endogeneity showed that female literacy, GDP per capita as a proxy for income, public health expenditure as a percentage of GDP and urbanization significantly affect infant mortality rate in a negative way.

scholarly journals Human Capital and Productivity: a Case Study of East Java

2020 ◽  
Vol 9 (2) ◽  
pp. 202-207
Author(s):  
Sugeng Setyadi ◽  
Rizal Syaifudin ◽  
Deris Desmawan
Keyword(s):  
Human Capital ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Panel Data Analysis ◽  
Fixed Effect Model ◽  
Infant Mortality Rate ◽  
Measured Variable ◽  
Literacy Rate ◽  
Level Of Education ◽  
Research Literacy

This research examines the influence of level of education and health rate as the measurement of human capital to productivity in East Java Provice, during 2009 to 2015. Variable of level of education is measured by literacy rate, while the variable of health rate is measured by infant mortality rate. The panel data analysis is used as research method, which is Fixed Effect Model is the best model than the other models. The research results show that the variable of level of education is not significant to productivity, whreas, the variable healt rate has negative and significant influence to productivity. The reason is because educated worker is not really nedded in East Java Province. Some workers with skills and experiences are preferred. Therefore, in this research literacy rate cannot be used as good proxy to measured variable of level of education. Moreover, a decrease in infant mortality rate is indicating that the health rate is good. Hence, productivity 

scholarly journals How does government spending on healthcare affects mortality rate in Italy? A panel data analysis

2016 ◽  
Vol 26 (suppl_1) ◽  
Author(s):  
D Golinelli ◽  
F Toscano ◽  
A Serafini ◽  
G Spataro ◽  
N Nante
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Mortality Rate ◽  
Government Spending ◽  
Panel Data Analysis
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