scholarly journals A Research on the Relationship between Environmental Sustainability Management and Human Development

2020 ◽  
Vol 12 (21) ◽  
pp. 9001
Author(s):  
Sue Ling Lai ◽  
Du-Nin Chen
Keyword(s):  
Life Expectancy ◽  
Environmental Health ◽  
Human Development ◽  
Environmental Performance ◽  
Human Development Index ◽  
Explanatory Power ◽  
Life Expectancy At Birth ◽  
Composite Indices ◽  
The Relationship ◽  
Years Of Schooling

The study explores the relationship between environmental performance and human development. A canonical correlation analysis was conducted to discover the maximum correlation between environmental performance and human development with the optimal estimated weights for indicators as constituting the composite indices. The results show that environmental health—being the most decisive—and ecosystem vitality are important indicators for representing the environmental performance. Other important indicators, in declining order, for constituting the human development index are mean years of schooling, expected years of schooling, and life expectancy at birth, with gross national income (GNI) being the last with relatively low weight. The canonical environmental performance index has utmost effect on mean years of schooling, then expected years of schooling, with explanatory power of more than 70% for both. Effect on life expectancy at birth is more than 60%, but only less than 30% on GNI. The canonical human development index has the highest explanatory power with nearly 80% for environmental health, but only 40% for ecosystem vitality. Both canonical composite indices reach a high correlation of 91% and the mutual explanatory power is 83%, confirming that environmental performance and human development are indeed positively and highly correlated.

scholarly journals Analysis of the Relationship between Human Development Index and Regional Development of West Sulawesi Province

2021 ◽  
Vol 2 (4) ◽  
pp. 31-38
Author(s):  
Muhammad Haekal Ansyar ◽  
Rusnadi Padjung ◽  
Muslim Salam
Keyword(s):  
Life Expectancy ◽  
Regional Development ◽  
Human Development ◽  
Human Development Index ◽  
Power Index ◽  
Regional Inequality ◽  
Purchasing Power ◽  
Development Index ◽  
The Relationship ◽  
Years Of Schooling

This study aims to analyze the relationship between the human development index and the regional development of West Sulawesi Province. This study uses panel data analysis that combines time series-cross section data and uses the Two Stage Least Square (2SLS) method. The type of data in this study is secondary data taken from the Central Statistics Agency (BPS) of West Sulawesi. The variables of the human development index are life expectancy, average length of schooling, expected length of schooling and purchasing power index. While the variables of regional development are poverty, unemployment, regional inequality and GRDP. The results of the analysis using the 2SLS method. In the HDI equation, the PW variable partially has a negative but not significant effect on the HDI for =5%. However, if for =20% PW has a negative and significant effect on HDI. While in the PW equation, the HDI variable partially has a negative but not significant effect on PW for = 5%. The R2 in the HDI equation is 97.5% and the remaining 2.5% which shows that the influence of PW, Life Expectancy, Average Years of Schooling, Expected Years of Schooling, and Purchasing Power Index together have an effect on HDI. While in the PW equation, the determination of R2 is 99.2% and the remaining 0.8% which shows HDI, Poverty Level, Unemployment Rate, Regional Inequality and Gross Regional Domestic Product together affect PW. So, there is a simultaneous relationship between the Human Development Index and Regional Development

scholarly journals The incidence and mortality of lip and oral cavity cancer and its relationship to the 2012 Human Development Index of Asia

2017 ◽  
Vol 4 (02) ◽  
pp. 1147 ◽  
Author(s):  
Amir Tiyuri ◽  
Abdollah Mohammadian-Hafshejani ◽  
Elham Iziy ◽  
Hamidreza Sadeghi Gandomani ◽  
Hamid Salehiniya
Keyword(s):  
Mortality Rate ◽  
Life Expectancy ◽  
Oral Cavity ◽  
Human Development ◽  
Human Development Index ◽  
Oral Cavity Cancer ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Incidence And Mortality ◽  
Years Of Schooling

Introduction: Lip and oral cavity cancer is one of the most prevalent cancers in Asia and considered to be a major public health problem due to the low survival rate. Because of the importance of access to information about this cancer (including incidence, mortality rate and relation to socioeconomic indicators), this study aims at investigating the incidence and mortality of lip and oral cavity cancer and its relationship with the Human Development Index (HDI) of Asia (from 2012). Method: This study was an ecological study in Asia for assessment of the correlation between age-specific incidence rate (ASIR) and age-specific mortality rate (ASMR) with the HDI and its components which include: life expectancy at birth, mean years of schooling and gross national income (GNI) per capita. Data on the standardized incidence ratio (SIR) and the standardized mortality ratio (SMR) for every Asian country for the year 2012 were obtained from the global cancer project and data on the HDI and its components were extracted from the World bank site.  We used a bivariate method for assessment of the correlation between the SIR and SMR with the HDI and its individual components. Statistical significance was assumed if P<0.05. All reported P-values were two-sided. Statistical analyses were performed using SPSS (Version 15.0, SPSS Inc.). Results: A total incidence of 162,506 cases and 95,005 deaths were recorded in Asian countries in 2012. Countries with the highest SIR (per 100,000) were the following: Maldives (11), Sri Lanka (10.3), Pakistan (9.8), Bangladesh (9.4), and India (7.2). The highest SMR was observed in the following countries: Pakistan (5.9), Bangladesh (5.6), Afghanistan (5.1), India (4.9), and Maldives (4.1). The correlation between SIR of lip and oral cavity cancer and HDI was -0.378 (p=0.010), with life expectancy at birth at -0.324 (p=0.028), mean years of schooling at -0.283 (p=0.057), and level of income per each person of the population at -0.279 (p=0.060). Moreover, the correlation was -0.664 (p≤0.001) between SMR and HDI. Conclusion: A significant reverse correlation was seen between the incidence and mortality rate of lip and oral cavity cancer and the HDI in Asia. The incidence and mortality of this type of cancer was high in developing or less developed countries.   

scholarly journals Comparative Study on Human Development Index (HDI): Indonesia and Bangladesh Context

2013 ◽  
Vol 3 (2) ◽  
Author(s):  
Soni Ahmad Nulhaqim ◽  
M D Kamrujjaman
Keyword(s):  
Comparative Study ◽  
Human Development ◽  
Human Development Index ◽  
Three Dimensions ◽  
Series Data ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Development Indicator ◽  
Clear Idea ◽  
Years Of Schooling

The Human Development Index (HDI) is a development indicator since 1990, operated by theUnited Nations Development Programme. Our entitled “Comparative Study on HumanDevelopment Index (HDI): Indonesia and Bangladesh Context” paper will focus oncomparison of both countries situation. In common scenes Indonesia is in advance thanBangladesh but what is the real situation are exist in both countries will be explained by ourstudy. Here we will compare series data (1980-2011) & its trends, value comparison (2011-2012), of two countries. In this paper we have analysis following segments of two countriesnamed Inequality-adjusted HDI(IHDI), Gender Inequality Index (GII), Multidimensional PovertyIndex (MPI) and Cross-Analysis of Indonesia & Bangladesh related to others relevant data like:Demographic Situation, Education Condition, Health Situation, Gender Observation etc. In ourpaper we have used New method for 2011 data onwards that Published on 4 November 2010(and updated on 10 June 2011), starting with the 2011 Human Development Report the HDIcombines three dimensions: A long and healthy life: Life expectancy at birth, Education index:Mean years of schooling and Expected years of schooling, A decent standard of living: GNI percapita (PPP US$). Hopefully this paper will give us a clear idea about two countries currentsocio-economic condition as well.

scholarly journals Estimates of global HIV/AIDS mortality, prevalence and incidence rates, and their association with the Human Development Index

2017 ◽  
Vol 4 (06) ◽  
pp. 1399
Author(s):  
Kamyar Mansori ◽  
Erfan Ayubi ◽  
Fatemeh Khosravi Shadmani ◽  
Shiva Mansouri Hanis ◽  
Somayeh Khazaei ◽  
...  
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Developed Countries ◽  
Incidence Rates ◽  
Global Public Health ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Global Age ◽  
Hiv Aids ◽  
Years Of Schooling

Background: HIV/AIDS is one of greatest global public health concerns today due to the high incidence, prevalence and mortality rates. The aim of this research was investigate and estimate the global HIV/AIDS mortality, prevalence and incidence rates, and explore their associations with the Human Development Index. Methods: The global age-standardized rates of mortality, prevalence and incidence of HIV/AIDS were obtained from the UNAIDS for different countries in 2015. The human development indexes (HDIs) were obtained from the World Bank database. The surveyed countries were divided into four groups according to the HDI distribution. The Spearman correlation coefficient and one-way ANOVA test were used for assessing the association of HIV/ AIDS indicators and HDI. Results: The highest rates of HIV/AIDS prevalence and incidence, and associated mortality in East and Southern Africa countries were 51.73%, 46.33% and 42.3%, respectively. Moreover, the highest and lowest global age-standardized rates of incidence and prevalence of HIV/AIDS was seen in adults ranging from 15-49 years of age for both low and high HDI countries. The prevalence and incidence rates of HIV/AIDS each had an inverse correlation with HDI and its four indicators (life expectancy at birth, mean years of schooling, expected years of schooling, and GNI per capita). Conclusion: Less developed countries with lower HDI show greater severity of the AIDS epidemic. Thus, it is essential to pay more attention to HIV/AIDS control and prevention programs in these countries. 

scholarly journals Classification of the Human Development Index in Indonesia Using the Bootstrap Aggregating Method

SinkrOn ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 100-106
Author(s):  
Noor Ell Goldameir ◽  
Anne Mudya Yolanda ◽  
Arisman Adnan ◽  
Lusi Febrianti
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Human Life ◽  
Classification Performance ◽  
Development Index ◽  
Life Expectancy At Birth ◽  
Bootstrap Aggregating ◽  
Bagging Method ◽  
Years Of Schooling

Successful development of the quality of human life in a region is determined by the Human Development Index (HDI). Human development performance based on the HDI can be measured: long and healthy life, knowledge, and a decent standard of living. The HDI is usually grouped into several categories to facilitate the classification of the HDI level of each region. This study aimed to determine the ability of the bootstrap aggregating (bagging) method to classify the HDI by district/city. Bagging is a stochastic machine learning approach that can eliminate the variance of the classifier by producing a bootstrap ensemble to obtain better accuracy results. The dependent variable in this study was the HDI by district/city in 2020. In contrast, life expectancy at birth, expected years of schooling, mean years of schooling, and real expenditure per capita are adjusted as independent variables. Bagging was applied to the high and low categories of HDI data. The bagging method demonstrated good classification performance due to only eight classification errors, namely the HDI data which should be in the high category but classified into the low category by the bagging method. Based on the results of calculations with 25 replications, it can be concluded that the bagging method has a very good performance, with an accuracy value of 92.3%, the sensitivity of 100%, and specificity of 83.33%. The bagging method is considered very good for the classifying the HDI by district/city in Indonesia in 2020 because it has a balanced accuracy of 91.67%.

scholarly journals ANALYSIS INDICATOR OF FACTORS AFFECTING HUMAN DEVELOPMENT INDEX (IPM)

2018 ◽  
Vol 2 (1) ◽  
pp. 11 ◽  
Author(s):  
Windya Wahyu Lestari ◽  
Victoria Efrida Sanar
Keyword(s):  
Life Expectancy ◽  
Human Resources ◽  
Human Development ◽  
Human Development Index ◽  
Estimation Result ◽  
Factors Affecting ◽  
Development Index ◽  
Relationship Of ◽  
The Relationship

The purpose of this study is to determine how big the influence of the indicators of factors that affect the Human Development Index. In addition, to determine the relationship of indicators of factors that affect the Human Development Index, to determine the development of human development of variables. That way can provide a standard against a State in improving the quality of human resources. Using the SPSS application method, this paper found that the variables that significantly influence the indicators of factors affecting the Human Development Index are life expectancy index, education index and income index. The estimation result using Correlasion Pearson shows that 14.788% is the variation of each observation is the same.   Keywords : Human Development Index, Life Expectancy Index, Education Index, Revenue Index.

scholarly journals Examining the Relationship Between Human Development Index and Socio-Economic Variables: A Panel Data Analysis

2018 ◽  
Vol 3 (2) ◽  
pp. 37
Author(s):  
Siti Ayu Jalil ◽  
Mohamad Nadzrul Kamaruddin
Keyword(s):  
Data Analysis ◽  
Life Expectancy ◽  
Human Development ◽  
Human Development Index ◽  
Health Expenditure ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Development Index ◽  
Socio Economic Variables ◽  
Years Of Schooling

Human Development Index (HDI) measures the average achievements from three basic dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. This study is to investigate the impact of socio-economic variables represented by the three dimensions i.e. mean years of schooling, expected years of schooling, gross domestic product, life expectancy and health expenditure on HDI in fifteen selected developing countries within a 5-year period (2010-2014). The panel data analysis tested the pooled regression model, fixed effects and random effects models. The findings indicated that the Panel Fixed Effects Model (FEM) has proven to be the best model to describe the study. From the FEM model, four predictors have shown significant positive effect on human development index which are, the mean years of schooling, expected years of schooling, life expectancy and GDP per capita whereas, health expenditure is the only variable that shows insignificant relationship. Hence, it can be stated that in these fifteen selected nations despite education and higher GDP are essential to achieve a higher level of HDI, life expectancy is also perceived as a vital indicator to imply a better level of HDI.

scholarly journals Multiple Dimensions of Human Development Index and Public Social Spending for Sustainable Development

2019 ◽  
Vol 19 (204) ◽  
Author(s):  
Iana Paliova ◽  
Robert McNown ◽  
Grant Nülle
Keyword(s):  
Sustainable Development ◽  
Life Expectancy ◽  
Human Development ◽  
Human Development Index ◽  
Well Being ◽  
Social Spending ◽  
Development Index ◽  
Educational Spending ◽  
Per Capita ◽  
Years Of Schooling

Multidimensional assessment of human development is increasingly recognized as playing an important role in assessing well-being. The focus of analysis is on the indicators measuring the three dimensions of Human Development Index (HDI) — standard of living, education and health, and their relationship with public social spending for achieving the 2030 Agenda for Sustainable Development. The study estimates the effects of public social spending on gross national income (GNI) per capita (in PPP in $), expected years of schooling and life expectancy for a sample of 68 countries. The relationship is robust to controlling for a variety of factors and the estimated magnitudes suggest a positive long-run effect of public educational spending on GNI per capita, public educational spending on expected years of schooling, and public health expenditures on life expectancy.

What Does Human Development Index Rating Mean in Terms of Individualism/Collectivism?

2003 ◽  
Vol 8 (2) ◽  
pp. 97-100 ◽  
Author(s):  
Maria José Sotelo ◽  
Luis Gimeno
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Principal Component ◽  
General Idea ◽  
Development Index ◽  
Low Levels ◽  
The Relationship

The authors explore an alternative way of analyzing the relationship between human development and individualism. The method is based on the first principal component of Hofstede's individualism index in the Human Development Index rating domain. Results suggest that the general idea that greater wealth brings more individualism is only true for countries with high levels of development, while for middle or low levels of development the inverse is true.

The Relationship between Human Development and Economic Growth

2018 ◽  
Author(s):  
Frances Stewart ◽  
Gustav Ranis ◽  
Emma Samman
Keyword(s):  
Economic Growth ◽  
Human Development ◽  
Human Development Index ◽  
Econometric Analysis ◽  
Complementary Relationship ◽  
Development Index ◽  
The Relationship ◽  
Intervening Variables

This chapter explores the interactions between economic growth and human development, as measured by the Human Development Index, theoretically and empirically. Drawing on many studies it explores the links in two chains, from economic growth to human development, and from human development to growth. Econometric analysis establishes strong links between economic growth and human development, and intervening variables influencing the strength of the chains. Because of the complementary relationship, putting emphasis on economic growth alone is not a long-term viable strategy, as growth is likely to be impeded by failure on human development. The chapter classifies country performance in four ways: virtuous cycles where both growth and human development are successful; vicious cycles where both are weak; and lopsided ones where the economy is strong but human development is weak, or conversely ones where human development is strong but the economy is weak.

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