Dimensions Of Human Development Index Research Articles

Does Islamic social finance promote the quality of human resources?

Purpose – This study aims to examine the contribution of Islamic Social Finance (ISF) distribution by sector (health, education, and economy) to the three dimensions of the Human Development Index (HDI) (health, education, and economy) and HDI aggregate in 34 provinces in Indonesia during the Covid-19 pandemic period (2020-2022).Methodology – A total of 102 panel data, a combination of data from 34 provinces in Indonesia (cross section) for a period of three years from to 2020-2022 (time series), were analyzed using a fixed effects panel model approach. Data were obtained from the National Board of Zakat (Badan Amil Zakat Nasional, BAZNAS) and the Central Statistics Agency (Badan Pusat Statistik, BPS).Findings – The main research results show that ISF channeled for human development purposes (in total) significantly increases the aggregate HDI by 0.008538%. However, the ISF distributed by sector (health, education, and economy) has a positive but insignificant impact on the three dimensions of HDI (health, education, and economy). This makes sense because the proportion of ISF distribution for these three fields tends to be small compared with other sectors.Implications – It is recommended that ISF fund allocation be more efficient, equitable, fair, and capable of reaching all aspects of human life. In addition, efforts must be made to collect ISF funds more effectively through technological integration.Originality – Most previous research has only tested Islamic social finance against HDI in aggregate, not by dimension, so the results were less specific.

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.

PENGARUH INDEKS PEMBANGUNAN MANUSIA DAN PDRB SEKTOR PERTANIAN TERHADAP KEMISKINAN DI KALIMANTAN TIMUR

The Human Development Index (HDI) is an indicator used to show the population's access to development outcomes and the development ranking of a region. The basic dimensions of HDI with the new method consist of a long and healthy life, knowledge, and a decent standard of living. The objectives of the study were to describe the HDI achievement, employment in the agricultural sector and its contribution to GRDP, and to analyze the effect of the HDI and GRDP of Agriculture on poverty in East Kalimantan. This study uses descriptive analysis and multiple linear regression analysis with variables Mean Length of School, Expenditure per capita (EXP), and Gross Regional Domestic Product of the agricultural sector (GDP). The data used are time series data for the period 2011-2020. The results showed an increase in HDI by 4.22, an increase in GRDP of 28.48 billion, and the percentage of poor people by an average during the 2011-2020 period of 6.25%. The variables of average length of schooling, per capita expenditure, and GRDP in the agricultural sector have a significant effect on the 5% level of poverty, while the variables of school year expectancy and life expectancy have no significant effect on poverty. RLS has a significant effect on increasing poverty, and EXP and GRDP in the agricultural sector have a significant effect on reducing poverty. The implication of the research is to increase the human development index by increasing the quality and quantity of providing education guarantees, social welfare guarantees to the community, as well as increasing income and creating job opportunities.

Aggregating Composite Indicators through the Geometric Mean: A Penalization Approach

In this paper, we introduce a penalized version of the geometric mean. In analogy with the Mazziotta Pareto Index, this composite indicator is derived as a product between the geometric mean and a penalization term to account for the unbalance among indicators. The unbalance is measured in terms of the (horizontal) variability of the normalized indicators opportunely scaled and transformed via the Box–Cox function of order zero. The penalized geometric mean is used to compute the penalized Human Development Index (HDI), and a comparison with the geometric mean approach is presented. Data come from the Human Development Data Center for 2019 and refer to the classical three dimensions of HDI. The results show that the new method does not upset the original ranking produced by the HDI but it impacts more on countries with poor performances. The paper has the merit of proposing a new reading of the Mazziotta Pareto Index in terms of the reliability of the arithmetic mean as well as of generalizing this reading to the geometric mean approach.

Urban Sustainable Development Index: a geospatial approach to add Tree Cover to HDI in São Paulo City

Human Development Index (HDI) has become an important tool to measure the basics aspects of human quality of living, being based on educational, economic and longevity dimensions. Over the years, criticism about the absence of an environmental dimension has emerged together with the need for knowledge about sustainable development at a local scale. For these reasons, this paper proposes a new approach for HDI, the Urban Sustainable Development Index (USDI), adding a Tree Cover indicator based on the most accepted criteria of 30% of tree cover to provide high quality of life and kept the balance between the other three dimensions of HDI. The normalized and weighted proposed index showed to be a promising alternative to complement existing sustainable indices impractical at local scale, mainly because they are based on carbon emission measurements. A Tree Cover indicator is more comprehensive, assessing greenhouse gases sequestration, heat islands attenuation, flora preservation, sustenance of fauna habitat, mitigation of extreme weather events and maintenance of water resources and soil stability. The case study in São Paulo city indicated that the transition from HDI to USDI resulted in a negative variation of almost 0.12, mostly in city central regions, and an increase up to 0.08 in peripherical regions - revealing how powerful can be geospatial analysis at a local scale, considering that USDI differs from the spatial distribution of HDI, valuing the importance of a sustainable urban index.

Classifying regencies and cities on human development index dimensions: Application of K-Means cluster analysis

The Human Development Index (HDI) is a measurement that analyzes a region's development in improving human development. The government's development plan aims to create a successful and peaceful life. The unbalanced development in every regency and city in Indonesia is a typical issue during the development process. It may also be shown that the HDI level changes across regencies and cities in Indonesia. This research aims to identify Indonesian regencies and cities based on HDI indices. K-Means clustering algorithm is the clustering method adopted. The results of the analysis formed 4 clusters. The first cluster consisted of 20 regencies with a low average HDI indicator. The second cluster consisted of 148 regencies and cities with an average HDI indicator is medium. The third cluster consisted of 88 regencies and cities with an average HDI indicator. The fourth cluster consists of 258 regencies and cities with high HDI indicators.

Soy Expansion, Environment, and Human Development: An Analysis across Brazilian Municipalities

In the last decades, Brazil has become one of the largest soybean producers and exporters in the world. Although dedicated policies have been implemented since the 1960s, the recent rapid transition towards an agricultural system largely based on soy has had a strong impact on the country’s socio-economic structure—not only in terms of land and labour markets but also on its diverse ecosystems. According to the extant literature, soy has had a beneficial impact on local human development, measured by the human development index (HDI) of the municipalities. However, there is a lack of empirical studies assessing the impact of soy expansion on the single dimensions of the HDI (longevity, education, and income) to disentangle the indirect effects of socio-environmental change while controlling for other local dynamics. To fill this gap, we applied econometric methods to a novel dataset combining municipal-level data on soy production with socio-economic and environmental data for the period 1991–2010. Our findings confirm the positive relation between soy expansion and the HDI at local level, but this relation differs between different HDI dimensions. The marginal benefits of soy expansion are increasing for the income dimension but decreasing for education and longevity. On the other hand, changes in soy productivity (a proxy for agricultural intensification) have a more complex impact on the HDI and its dimensions, but in general its marginal benefits are decreasing over time. Further research could expand the time series once more up-to-date information becomes available.

Choquet-Integral Aggregation Method to Aggregate Social Indicators to Account for Interactions: An Application to the Human Development Index

Composite well-being and sustainability indices are usually obtained as arithmetic and geometric means of sub-dimensions. However, the arithmetic mean does not consider potential interactions across the dimensions of the indices and the geometric mean does not penalize unbalanced achievements across dimensions strongly enough. This paper uses a flexible non-additive aggregation model—the Choquet integral—to account for potential synergies and redundancies of the dimensions that are used to obtain indices, and uses the Human development index (HDI) as an example to illustrate the flexibility of the aggregation procedure. This paper relies on multiple theoretical and empirical studies, which indicate mutually strengthening relationships (positive interactions) among the three HDI dimensions. To illustrate and show-case how positive interactions among the three HDI dimensions could be taken into account, this paper uses five hypothetical weight sets and simulates 500 weight sets that allow varying positive interactions among the three dimensions. The analyses with the HDI data suggest that both geometric and arithmetic mean HDI scores are roughly the same for most countries, even when variations across the three dimensions are relatively large. On the other hand, countries with balanced (unbalanced) achievements across dimensions rank in higher (lower) positions with the Choquet integral aggregation. The illustrations of this paper show-case how Choquet integral is a flexible aggregation method to take into account varying positive interactions across the HDI dimensions and able to detect unbalanced achievements.

THE RELATIONSHIP BETWEEN HDI VALUES AND ROAD TRAFFIC FATALITY RATES

Road traffic accidents are a serious but an avoidable problem that cause both life and economic loss worldwide. There are some common factors such as income, education and health that affect both socioeconomic development and road traffic fatality rates of countries. Examination of these factors separately during the analyze of road traffic fatality rates might cause misleading results due to the relationships between stated variables. Thus, using an inclusive parameter like Human Development Index (HDI), may provide more realistic results. In the current study, the relationship between HDI, its dimensions (GNI per capita, expected years of schooling, mean years of schooling and life expectancy at birth) and road traffic fatality rates are examined. Hierarchical regression analysis was conducted in order to obtain results about the effects of each dimension of HDI. Results showed that all dimensions of HDI negatively predicted road traffic fatalities. Results have been discussed according to related literature and suggestions have been made for further research and applications.

Can Revenue and Human Development Promote Happiness: Study on Provinces in Indonesia

This study seeks to see the relationship between the human development index (HDI) and gross regional domestic product (GRDP) variables on the happiness of economic growth data for provinces in Indonesia. The method used in this research is regression and path analysis. This study proves that happiness is not caused by the income (GRDP) of a region but rather significantly by one of the dimensions of HDI, namely the education dimension. The relationship through the variable between using path analysis through the indirect effect of the GRDP intermediary also significantly affects the education dimension. About 60% of the variable quality of education plays a role in happiness. If the effect is through an intermediary variable, the real influence of the variable quality of education on happiness is 65%. Other variables such as health and economy, directly or indirectly, do not significantly affect the level of happiness.JEL Classification: I3, E5, R10How to Cite:Rizal, S., & Fitrianto, A. (2021). Can Revenue and Human Development Promote Happiness: Study on Provinces in Indonesia. Signifikan: Jurnal Ilmu Ekonomi, 10(1), 113-128. https://doi.org/10.15408/sjie.v10i1.17600.

Education as an important aspect to determine human development index by province in Indonesia

The Human Development Index (HDI) is a comparative measure of life expectancy, education, and standard of living in all countries over the world to classify whether a country is a developed country, a developing country, or even an underdeveloped country. Currently, science and technology are developing rapidly. In order to compete with other countries, Indonesia needs to improve the quality of education, which is one of the dimensions of HDI. In this study, the HDI in Indonesia and several aspects of education are grouped by provinces then it is compared whether the cluster of HDI formed has the same members as the cluster of several variables related to education in Indonesia. The goal is to observe if the quality of education in Indonesia might represent HDI. The clustering method that will be used is k-means clustering with average silhouette method to determine the optimal number of cluster. The results show different cluster in two groups of dataset means that the high index of human development does not determine the high quality of education in Indonesia. It indicates that the assessment of the quality of education needs to be continued both for regions with high HDI conditions and vice versa because the quality of education does not appear to be reflected in the high HDI.

Identifying High-Potential Work Areas in Engineering for Global Development: Linking Industry Sectors to the Human Development Index

AbstractThose working in Engineering for Global Development seek to improve the conditions in developing countries. A common metric for understanding the development state of a given country is the Human Development Index (HDI), which focuses on three dimensions: health, education, and income. An engineer’s expertise does not always align with any of those dimensions directly, while they still hope to perform impactful work for human development. To discover other areas of expertise that are highly associated with the HDI, correlations and variable selection were performed between all World Development Indicators and the HDI. The resultant associations are presented according to industry sector for a straightforward connection to engineering expertise. The associated areas of expertise can be used during opportunity development as surrogates for focusing on the HDI dimensions themselves. The data analysis shows that work related to “Trade, Transportation, and Utilities,” such as electricity distribution, and exports or imports, “Natural Resources and Mining,” such as energy resources, agriculture, or access to clean water, and “Manufacturing,” in general, are most commonly associated with improvements in the HDI in developing countries. Also, because the associations were discovered at country-level, they direct where geographically particular areas of expertise have been historically associated with improving HDI.

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

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.

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

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

Towards a more ‘Sustainable’ Human Development Index: Integrating the environment and freedom

The Human Development Index (HDI) is one of the most widely used composite indicators of socio-economic development. However, the HDI is at the cross-roads. In order to retain its flagship role in the development arena, many scholars have called from the HDI to reinvent itself by adding sustainability dimensions.The aim of this paper is to introduce the Sustainable Human Development Index (SHDI), based on Multidimensional Synthesis of Indicators (MSI) – a new class of indexes that can be used for monitoring Sustainable Human Development (SHD). The approach we propose aims to address two primary issues regarding the HDI.The first issue involves the integration into the SHDI of two important sustainability-related dimensions that are missing in the HDI; namely, the environment and freedom (defined here in terms of political rights and civil liberties). The second issue focuses on the method of aggregation using the new class of indexes proposed. We aim to expand on the three standard HDI dimensions while avoiding problems associated with the geometric mean that tends to collapse to zero. In doing so, we manage to retain the same theoretical intuitions of the post-2010 HDI approach, i.e. to penalize the heterogeneity of outcomes.Moreover, we rely on the flexibility of the MSI approach to develop another index, the Environmentally-centered Sustainable Human Development Index (ESHDI), which puts the environmental dimension at the core of the analysis.In the first part of the paper we introduce the theoretical debate on the multidimensionality of the HDI, and consider the two new dimensions of sustainability, as well as the MSI aggregation approach. In the second part, the SHDI and the ESHDI are introduced, tested through a simulation analysis, and are compared with the HDI geometric mean using 2013 data.The simulations and the results of the empirical analysis show how the new class of indexes provide a more flexible approach to the procedure of aggregation, especially when the number of dimensions increases and/or when there is the need to stress the importance of one or more dimensions. The introduction of the two environmental and freedom sustainability dimensions greatly increases the potential of the HDI to address the SHD paradigm by capturing two core issues for the humanity and its common future.

Generación de bienestar social en México: un estudio DEA a partir del IDH

El presente documento aborda el estudio del uso eficiente de los recursos para generar bienestar social en México durante el período 1990-2010. Para ello se utilizó el Análisis de la Envolvente de Datos (DEA), tomando como referencia los indicadores socioeconómicos de las tres dimensiones del Índice de Desarrollo Humano (IDH). El análisis de resultados muestra que fueron Baja California Sur, Campeche, Colima, Chiapas, Distrito Federal, Estado de México, Quintana Roo, Tlaxcala y Zacatecas los más eficientes en la generación de bienestar social. Haciendo evidente que no son necesariamente las entidades que reciben más recursos las que mayor bienestar social generan.

Correlation Between Human Development Index and Infant Mortality Rate Worldwide

Background: Infant mortality rate (per 1000 live births) is a vital index to monitor the standard of health and social inequality which is related to human development dimensions worldwide. Human development index (HDI) includes basic social indicators such as life expectancy, education and income. Objectives: The current study aimed to find the correlation between human development index and infant mortality rate. Patients and Methods: This descriptive study that represents the relationship of infant mortality rate with human development index and human development index dimensions was performed on the profiles of 135 countries worldwide [Africa (35 countries), America (26 countries), Asia (30 countries), the Pacific (2 countries) and Europe (42 countries)]. Two databases were used in the study: the world health organization (WHO) database (2010) and human development database (2010). Data were analyzed using Pearson correlation test by SPSS software. Results: The study found that socio-economic factors or human development dimensions are significantly correlated with risk of chance mortality in the world. The per capita income (r = -0.625), life expectancy (r = -0.925) and education (r = -0.843) were negatively correlated with the infant mortality rate; human development index (r = -0.844) was also negatively correlated with the infant mortality rate (P < 0.01). Conclusions: Human development index is one of the best indicators and predictors to perceive healthcare inequities. Worldwide improvement of these indicators, especially the education level, might promote infant life expectancy and decrease infant mortality. Keywords: Infant Mortality Rate, Education, Income, Life Expectancy, Human Development Index

Albania vs. Balkan's Countries as Comparative Analysis of the Human Development Index

During the last decades, the central focus of economists was growth of incomes in the early 1990s, the focus shifted towards the quality of life and development strategies being oriented from production to welfare improvement. In recent years a large literature has been developed regarding indicators of welfare and life quality. The Human Development Index (HDI), elaborated by the United Nations Development Program in 1990, was an indicator of life quality and a good proxy indicator of welfare. Human Development Index provides a better alternative to measure countries overall achievements in their social and economic dimensions. In this paper, the theoretical literature review provides a brief history of the human evolution and development aspects. This paper examines the dimensions of Human Development Index like life expectancy, education and income index in Balkan countries. The aim of this paper is to found out the trend of human development in Balkan countries and to make a comparison of various human development aspects in Albania comparing it with other countries in the region. This paper is completed through qualitative methods. Finally the paper will be closed with some conclusions. DOI: 10.5901/mjss.2015.v6n4s3p311

Human Development Status and Regional Disparity in China

The 2010 United Nations Development Programme (UNDP) Global Human Development Report introduced a new methodology to calculate Human Development Index (HDI). Three dimensions of HDI i.e. income, education, and health are adjusted for inequalities in attainments across people. The paper uses the new methodology to estimate 2010 China's national and provincial HDI. Compared with UNDP global report, all the data used here are from China's domestic sources. The education indicator estimated here by referring to detailed local statistics and documents are higher than that in UNDP's global report, thus contributing a slight higher overall HDI estimate. Based on the estimation results here and UNDP's report, China is located in between high human development and low human development, in other words, placed around the half position among all 169 countries. To facilitate a cross-country comparison, the indices are normalized with reference to the goalposts outlined in the HDR 2010. When ranked according to global goalposts, Beijing's rank is 31 whereas the least developed Tibet only ranks 114. Most of the regional disparity is driven by their income differences. The findings of this paper try to shed light on the status of China's human development and also gain insights on China's regional disparity. Further research is required to explore the inter-linkages between inequalities across various dimensions and to examine the factors behind these inequalities.

Human development report 2010: Changes in parameters and perspectives

Human Development Report (HDR) 2010 in its 20 th year contains several significant changes. Indicators to measure the three dimensions of Human Development Index (HDI) have been changed: Gender-related Development Index (GDI) and Gender Empowerment Index have been replaced by Gender Inequality Index (GII) and Human Poverty Index has been replaced by Multi-dimensional Poverty Index. Inequality-adjusted HDI (IHDI) has been introduced for the first time. Between 1980 and 2010, India's HDI rose by 1.6% annually from 0.320 to 0.519. While India's HDI value has improved over time, the rank has not improved as much as compared to other developing countries. On GII, India ranked at 122 with a GII value of 0.748 (ranges between 0 and 1) in 2010 HDR (based on data of 2008), revealing considerable loss in achievements in three dimensions of human development - reproductive health, empowerment, and labor market - due to inequality between genders. Multi-dimensional Poverty Index was 0.296 (2000-2008) and IHDI was 0.365 (2000-2007).