scholarly journals ANALISIS PENGARUH ANGKA KEMATIAN BAYI TERHADAP ANGKA HARAPAN HIDUP DI PROVINSI JAWA TIMUR BERDASARKAN ESTIMATOR LEAST SQUARE SPINE

2019 ◽  
Vol 1 (1) ◽  
pp. 56
Author(s):  
Anies Yulinda W ◽  
Trias Novia L. ◽  
Melati Tegarina ◽  
Nur Chamidah
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Health Sector ◽  
Parametric Model ◽  
Least Square ◽  
Infant Mortality Rate ◽  
Nonparametric Model ◽  
High Flexibility ◽  
Model Approach

Life expectancy can be used to evaluate the government's performance for improving the welfare of the population in the health sector. Life expectancy is closely related to infant mortality rate. Theoretically, decreasing of infant mortality rate will cause increasing of life expectancy. A statistical method that can be used to model life expectancy is nonparametric regression model based on least square spline estimator. This method provides high flexibility to accommodate pattern of data by using smoothing technique. The best estimated model is order one spline model with one knot based on minimum generalized cross validation (GCV) value of 0.607. Each increasing of one infant mortality rate unit will cause decreasing of life expectancy of  0.2314 for infant mortality rate less than 27, and of  0.0666 for infant mortality rate more than and equals to 27. In addition, based on mean square error (MSE) of 0.492 and R2value of 76.59% for nonparametric model approach compared with MSE of 0.634 and R2 value of 71.8%  for parametric model approach, we conclude that the use of nonparametric model approach based on least square spline estimator is better than that of parametric model approach.

scholarly journals The Impact of Health Indicators on Economic Growth In Pakistan

2013 ◽  
Vol 1 (1) ◽  
pp. 11-27
Author(s):  
Kashif Raza ◽  
Salman Majeed ◽  
Salman Majeed ◽  
Maryam Islam
Keyword(s):  
Economic Growth ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Health Sector ◽  
Health Indicators ◽  
Health Expenditures ◽  
Fertility Rate ◽  
Infant Mortality Rate ◽  
Series Data

This study aims at investigating the issues of health sector in Pakistan and highlights the important link between health indicators and economic growth. For this purpose, Ordinary least square method and Granger Causality technique are applied on time series data of Pakistan from 1980-2012. Health expenditures, fertility rate, life expectancy, and infant mortality rate have been used as health indicators. The basic objective of study is to enhance those issues in health sectors that directly or indirectly strike on economic growth of Pakistan so that effective policies can be chalked out to cop current as well future condition regarding health and an economic growth. The results showed that life expectancy, fertility rate, investment on health sectors has significantly influenced the per capita GDP. Health expenditures have also positive but insignificant impact on economic growth. Whereas there is negative relationship of infant mortality rate, population per bed on economic growth. The major policy implication of this study is that by increasing the health facilities through increase the investment on health sector that will improve the sustainable level of economic growth.

scholarly journals Features of machine learning in the study of the main factors of development of countries of the world

2021 ◽  
Vol 110 ◽  
pp. 02006
Author(s):  
Ludmila Borisova ◽  
Galina Zhukova ◽  
Anna Kuznetsova ◽  
Julie Martin
Keyword(s):  
Machine Learning ◽  
Regression Analysis ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Infant Mortality Rate ◽  
Live Births ◽  
Goods And Services ◽  
Machine Learning Methods ◽  
The World

The paper analyzes the socio-economic and demographic indicators of life expectancy in the countries of the world. Methods of regression analysis and machine learning are used. Statistically significant indicators that affect life expectancy around the world have been identified. When analyzing the data using machine learning methods, 13 of the 14 analyzed indicators were statistically significant. Significant indicators, in addition to those selected in the regression analysis, were 3: the under-five infant mortality rate (per 1,000 live births), the Net Barter Terms of Trade Index (2000 = 100), and Imports of goods and services (in % of GDP) (in the regression analysis, only the infant death rate was significant). In addition, it should be noted that there is a significant decrease in the under-five infant mortality rate (per 1,000 live births) for the EU, CIS and South-East Asian countries compared to the border set in the study for all countries: 4.65 vs. 34.9, a decrease in the birth rate from 2.785 to 1.85, a sharp increase in exports of goods and services: from 23.17 to 80.59, a halving in imports of goods and services, a drop in population growth from 2.105 to 0.85. The performed statistical analysis strongly supports the use of machine learning methods in identifying statistically significant relationships between various indicators that characterize the development of countries, if there are gaps in the data.

Does population health influence FDI inflows into Ghana?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustapha Immurana
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Population Health ◽  
Death Rate ◽  
Health Indicators ◽  
Least Square ◽  
Infant Mortality Rate ◽  
Fdi Inflows ◽  
Content Type ◽  
Under Five

PurposeGhana is one of the countries instituting several measures toward attracting more Foreign Direct Investment (FDI) inflows. This is because, FDI is largely viewed as essential to socioeconomic development. However, while population health can influence FDI inflows, it has received very little attention. This study, therefore, investigates empirically, as to focusing on population health could be a useful tool in Ghana’s attempt to attract more FDI inflows.Design/methodology/approachThe study uses time series data on Ghana from 1980 to 2018 to achieve its objective. Life expectancy, death rate, infant mortality rate, under-five mortality rate and incidence of malaria are used as proxies for population health, while the Ordinary Least Square (OLS) and the Instrumental Variable Two-Stage Least Square (IV2SLS) regressions are employed as empirical estimation techniques.FindingsUsing the OLS regression, except the incidence of malaria, the study finds all the other population health indicators to significantly influence FDI inflows. However, after controlling for endogeneity using the IV2SLS regression, all population health indicators are found to be significant as regards their effects on FDI inflows.Practical implicationsPaying attention to population health could be an effective strategy that can be employed by policymakers in the quest to get more FDI inflows into Ghana.Originality/valueThis study, to the best of our knowledge, is the first study solely devoted to Ghana, which doing so helps in devising country-specific policies with regard to the effect of population health on FDI inflows. Further, this study becomes the first to use death rate, infant mortality rate and under-five mortality rate in examining the effect of population health on FDI inflows. Thus, since there are various causes of deaths, using indicators that capture deaths from all factors helps in giving a much broader picture with regard to the FDI population health nexus. Also, this study is the first to use up to five different population health indicators in examining the effect of population health on FDI inflows, which aids in revealing whether FDI is sensitive to the population health indicator used.

scholarly journals Modelling Infant and Maternal Mortality Rate based on slum household uses Bivariate Spline Regression Method

2018 ◽  
Vol 73 ◽  
pp. 12002
Author(s):  
Alan Prahutama ◽  
Budi Warsito ◽  
MochAbdul Mukid
Keyword(s):  
Mortality Rate ◽  
Infant Mortality ◽  
Maternal Mortality ◽  
Spline Function ◽  
Predictor Variable ◽  
Regression Method ◽  
Infant Mortality Rate ◽  
Spline Regression ◽  
Maternal Mortality Rate ◽  
High Flexibility

Maternal mortality and infant mortality rate is an interrelated issue. Therefore, maternal and infant mortality modeling can be done bivariate. One method used to model the relationship between response variables and predictor variables is regression. The regression approach that does not use the assumption is spline regression. Spline regression is a regression method based on spline function. Spline function is a polynomial piece that has high flexibility. In this study the response variable used is bivariate, the maternal mortality rate and infant mortality rate, while the predictor variable used is the percentage of slum households. The weighting used is based on the value of the covariance variant. Determination of point knots using Mean Square Error (MSE). The results obtained modeling maternal and infant mortality rates based on the percentage of slum households resulted inMAPE 55.55%. Number of knots obtained as much as 5 point knots with linear order.

scholarly journals Empirical analysis of the push factors of human capital flight in Nigeria

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Oluwaseyi Popogbe ◽  
Oluyemi Theophilus Adeosun
Keyword(s):  
Human Capital ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Migration Rate ◽  
Infant Mortality Rate ◽  
Capital Flight ◽  
Push Factors ◽  
Content Type ◽  
Human Capital Flight

Purpose Human capital flight from Nigeria to developed countries has remained a topical issue. This paper aims to empirically analyze the push factors for the migrants who explore the various legal migrant schemes from a macro perspective. The authors examine human capital development and its role in contributing to human capital flight to more developed counties. Design/methodology/approach This paper is anchored on the push–pull model. Using secondary data from 1990 to 2019, the authors look at the relationship between human capital flight and variables such as life expectancy, infant mortality rate, population growth rate and Nigeria’s unemployment rate. The auto-regressive lag model (ARDL) was adopted to estimate the empirical relationship among these variables. Findings The results from the ARDL model suggest a positive relationship exists between population growth rate and migration rate. A negative relationship was, however, observed between life expectancy and migration rate. This study also found that an increase in the infant mortality rate negatively impacted migration significantly. Therefore, an increase in infant mortality rate lowered the migration rate. Finally, an increase in the unemployment rate increased migration; however, insignificantly. Research limitations/implications The findings from this study are limited to the push factors influencing migration out of Nigeria. These factors are also restricted to variables for which data can be derived under the study’s scope. The results of this study have far-reaching implications, especially for policymakers and citizens alike. Better human capital development through enhanced life expectancy and reduced population in Nigeria will reduce the migration rate. Therefore, this study calls for the doubling of developmental and infrastructural efforts at all levels of governance. Originality/value This paper’s importance lies in its ability to elucidate push factors that influenced migration out of Nigeria empirically. An empirical approach to the subject matter will explain these factors and the degree to which they influence migration. This will guide the policy-making process in curbing brain drain, which is a major challenge in Nigeria.

scholarly journals Analisis Angka Harapan Hidup di Jawa Timur Tahun 2015

2018 ◽  
Vol 6 (1) ◽  
pp. 17
Author(s):  
Lina Septi Danasari ◽  
Arief Wibowo
Keyword(s):  
Public Health ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Secondary Data ◽  
Infant Mortality Rate ◽  
North Coast ◽  
Health Improvement ◽  
Central Java ◽  
The Government

Life expectancy is one of the indicators to calculate the Human Development Index (HDI) which determined by infants’ health, toddlers’ health, frequency of liveborn children and death rate in the community. East Java Province has four dominant cultural areas such as Mataraman including the western part of the border of Central Java to Kediri, Madura including Bangkalan to Pamekasan, Arek including north coast of Surabaya to Malang and Tapal Kuda including Pasuruan, Probolinggo, Situbondo, Bondowoso, Lumajang and Jember. Those four cultural areas have different characteristic that can affect public health status especially life expectancy in East Java Province. The analysis aimed to know the correlation between infant mortality rate and life expectancy and to know the differences of life expectancy among four cultural areas in East Java year 2015. This analysis used secondary data obtained from Central Bureau of Statistic of East Java on May, 2017. The data were life expectancy as dependent variable, infant mortality rate as independent variable and cultural areas in East Java as grouping variables. The result showed that there was correlation between infant mortality rate with life expectancy (p=0.000) and there was different in life expectancy among four cultural areas in East Java year 2015 (p=0.000) such as cultural areas Mataraman-Madura, Mataraman-Tapal Kuda and Arek-Tapal Kuda. It suggested the government to continue improving the socio-economic welfare of the community and public health improvement in the Tapal Kuda area which had high infant mortality rate and low life expectancy.

scholarly journals Impact of Government Health Expenditure on Health Outcomes in the West African Sub-Region

2021 ◽  
Vol 21 (1) ◽  
pp. 48-59
Author(s):  
Rafiu Ayobanji Mustapha ◽  
Saidat Oluwatoyin Onikosi-Alliyu ◽  
Abdurrouf Babalola
Keyword(s):  
Health Outcome ◽  
Mortality Rate ◽  
Infant Mortality ◽  
West Africa ◽  
Public Expenditure ◽  
Least Square ◽  
Infant Mortality Rate ◽  
The West ◽  
Integration Test ◽  
The Impact

Abstract Research background: Health outcome such as infant mortality rate is an important measure of the standard of living. It is a part of Millennium Development Goals, which all countries of the World strive to achieve, by allocating enormous economic resources to the health sector respectively. Purpose: The study assessed the impact of government expenditure on health and on health outcome (infant mortality rate) in the West Africa Sub-region. Research methodology: Secondary data were collected from 2000 to 2015 on thirteen countries in the Sub-region. Owing to the fact that the nature of the data involved is macro-panel data, the study performed the pre-estimation test (such as panel unit-root test and co-integration test) to ascertain the time series properties of the series. Based on the results of the pre-estimation tests, the work employed the fully modified ordinary least square (FMOLS). Results: It is found in the study that public health spending has an indirect impact on infant mortality rate in the West Africa Sub-region. Novelty: No extant study examined the impact of public expenditure on health and on maternal mortality rate using the West Africa Sub-region as an area of coverage. This study employed a fully modified OLS (FMOLS) to assess the impact of public expenditure on health and on infant mortality rate in the West Africa Sub-region.

Health Status, Government Health Expenditure and Economic Growth Nexus in India: A Toda–Yamamoto Causality Approach

2020 ◽  
pp. 097674792096340
Author(s):  
Avinash Kaur
Keyword(s):  
Economic Growth ◽  
Health Status ◽  
Mortality Rate ◽  
Infant Mortality ◽  
Life Expectancy ◽  
Health Expenditure ◽  
Infant Mortality Rate ◽  
Government Health ◽  
The Government ◽  
Government Health Expenditure

This article attempts to examine the causal linkage among government health expenditure, health status and economic growth in India for the period from 1981–1982 to 2015–2016. The results of Johansen co-integration test indicate that government health expenditure, health status and economic growth have long-run relationship in India. The results of Toda–Yamamoto causality test showed that there existed unidirectional causal relationship running from government health expenditure to gross domestic product—GDP (economic growth); GDP (economic growth) to life expectancy; government health expenditure to infant mortality rate and infant mortality rate to life expectancy. On the other hand, there is no evidence showing causality in any direction between infant mortality rate to GDP (economic growth) and government health expenditure to life expectancy. The study strongly confirmed that the government health expenditure has an effect on GDP (economic growth) and infant mortality rate (which depicts health status) in India. The health outcomes, namely life expectancy and infant mortality rare, reveal unidirectional causality between them. Therefore, the study concludes that policymakers and the government should pay proper attention to the health sector in order to ultimately achieve economic growth in the country.

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