scholarly journals Regional Development in Advanced Countries: a Within-Country Application of the Human Development Index for Austria

2015 ◽  
Vol 6 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Lukas Schrott ◽  
Martin Gächter ◽  
Engelbert Theurl
Keyword(s):  
Life Expectancy ◽  
Regional Development ◽  
Human Development ◽  
Human Development Index ◽  
Socioeconomic Development ◽  
Empirical Work ◽  
Substantial Part ◽  
Development Index ◽  
Country Level ◽  
Cross Country

Abstract Since its implementation in 1990, the human development index (HDI), the flagship indicator of multidimensional development, has attracted a great deal of attention and critics in academic, political and media circles. It initiated a new stage in the discussion of appropriate indicators to measure socioeconomic development. Until now, the vast majority of empirical work using the HDI concept has taken a cross-country perspective. The main aim of this paper is the application of the HDI at the sub-country level in small, highly developed and socioeconomically homogenous countries. For this undertaking we use a slightly modified version of the HDI, called the regional development index (RDI). For the components of the RDI - life expectancy, education and standard of living - we use recent cross section information for Austria at the level of districts. There exists considerable heterogeneity across districts in the RDI and its components. Our Theil-decomposition reveals that the overwhelming part of the observed heterogeneity is based on differences within provinces (96 percent), although the differences in life expectancy between the provinces explain a substantial part of the overall heterogeneity in this indicator (54 percent).

scholarly journals Country-Level Relationships of the Human Intake of N and P, Animal and Vegetable Food, and Alcoholic Beverages with Cancer and Life Expectancy

2020 ◽  
Vol 17 (19) ◽  
pp. 7240
Author(s):  
Josep Penuelas ◽  
Tamás Krisztin ◽  
Michael Obersteiner ◽  
Florian Huber ◽  
Hannes Winner ◽  
...  
Keyword(s):  
Life Expectancy ◽  
United Nations ◽  
Human Development ◽  
Human Development Index ◽  
Alcoholic Beverages ◽  
Cancer Prevalence ◽  
Development Index ◽  
Underdeveloped Countries ◽  
Country Level ◽  
Per Capita

Background: The quantity, quality, and type (e.g., animal and vegetable) of human food have been correlated with human health, although with some contradictory or neutral results. We aimed to shed light on this association by using the integrated data at country level. Methods: We correlated elemental (nitrogen (N) and phosphorus (P)) compositions and stoichiometries (N:P ratios), molecular (proteins) and energetic traits (kilocalories) of food of animal (terrestrial or aquatic) and vegetable origin, and alcoholic beverages with cancer prevalence and mortality and life expectancy (LE) at birth at the country level. We used the official databases of United Nations (UN), Food and Agriculture Organization of the United Nations (FAO), Organization for Economic Co-operation and Development (OECD), World Bank, World Health Organization (WHO), U.S. Department of Agriculture, U.S. Department of Health, and Eurobarometer, while also considering other possibly involved variables such as income, mean age, or human development index of each country. Results: The per capita intakes of N, P, protein, and total intake from terrestrial animals, and especially alcohol were significantly and positively associated with prevalence and mortality from total, colon, lung, breast, and prostate cancers. In contrast, high per capita intakes of vegetable N, P, N:P, protein, and total plant intake exhibited negative relationships with cancer prevalence and mortality. However, a high LE at birth, especially in underdeveloped countries was more strongly correlated with a higher intake of food, independent of its animal or vegetable origin, than with other variables, such as higher income or the human development index. Conclusions: Our analyses, thus, yielded four generally consistent conclusions. First, the excessive intake of terrestrial animal food, especially the levels of protein, N, and P, is associated with higher prevalence of cancer, whereas equivalent intake from vegetables is associated with lower prevalence. Second, no consistent relationship was found for food N:P ratio and cancer prevalence. Third, the consumption of alcoholic beverages correlates with prevalence and mortality by malignant neoplasms. Fourth, in underdeveloped countries, reducing famine has a greater positive impact on health and LE than a healthier diet.

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

Human Development

2018 ◽  
Author(s):  
Frances Stewart ◽  
Gustav Ranis ◽  
Emma Samman
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Empirical Work ◽  
Good Measure ◽  
Strong Correlations ◽  
Development Index ◽  
Form Part ◽  
Cross Country ◽  
Reductionist Approach

Human development is often identified with the Human Development Index (HDI), and this is how the empirical work in previous chapters has proceeded. But this is a very reductionist approach to human development. This chapter identifies eleven dimensions that form part of human development, beyond the three incorporated in the HDI, by drawing on the work of philosophers and others. It then explores empirically how far the HDI represents these other dimensions in cross-country comparisons, selecting several indicators for each dimension. It shows that the HDI is not a good measure of a broader concept of human development. Using the indicators adopted and excluding those with strong correlations with each other, or with the HDI, left an additional thirty-one indicators to get a comprehensive measure of human development. To get a comprehensive measure of human development requires many indicators besides the HDI.

scholarly journals Metode Analisis Diskriminan dalam Pengelompokan Kabupaten/Kota di Provinsi Sulawesi Selatan Berdasarkan Indikator Indeks Pembangunan Manusia

2020 ◽  
Vol 2 (1) ◽  
pp. 40
Author(s):  
Novi Afryanthi S. ◽  
Muhammad Arif Tiro ◽  
Ansari Saleh Ahmar
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Life Expectancy ◽  
Human Development ◽  
Human Development Index ◽  
Statistic Analysis ◽  
Development Index ◽  
South Sulawesi ◽  
Life Expectancy Increase

Abstract. Discriminant analysis is a method in multivariat statistic analysis that related with object which have separated into the defined group defined and see the accuracy  of the formed group. In this research, clustera analysis is used for the first grouping,  cluster  analysis is a statistical analysis which aims to classify some objects based on the characteristics similarity among the object. Data for this study is HDI (Human Development Index)  of indicator in south sulawesi in 2016. The result of this research are 1st cluster (lower  HDI indicator) which have 21 city/ distric and the 2nd cluster (higher  HDI indicator) which have 3 city/distric as the closeness value between the cluster that formed is 0.902 which shows the closeness between the cluster is high . Furthermore, the discriminant function that have formed explains that if the life expectancy increase, the HDI indicator in city/distric in south sulawesi province will decrease but if school  expectation duration in school , average of duration in school, and parity of pur hasing power is increasing, the HDI indicator in city/distric in aouth sulawesi will also increase.Keywords: Cluster analysis, Discriminant analysis , Human development index indicator.

scholarly journals Authoritarian Regimes and Economic Development: An Empirical Reflection

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 657-673
Author(s):  
Karim Khan ◽  
Saima Batool ◽  
Anwar Shah
Keyword(s):  
Economic Development ◽  
Human Development ◽  
Political Institutions ◽  
Human Development Index ◽  
Jel Classification ◽  
Authoritarian Regimes ◽  
Development Index ◽  
Alternative Measures ◽  
Cross Country ◽  
The Impact

Since the recent emphasis on institutions for overall economic development of the countries, the research in this strand has expanded enormously. In this study, we want to see the impact of political institutions on economic development in pure cross-country setting. We take the Human Development Index (HDI) as a measure of economic development and use two alternative measures of dictatorship. We find that dictatorship is adversely affecting economic development in our sample of 92 countries. For instance, transition from extreme dictatorship to ideal democracy would increase HDI by 17 percent. Moreover, our results are robust to alternative specifications and the problems of endogeneity and reverse causation as is shown by the results of 2 Stages Least Squares (2SLS). JEL Classification: P16, H11, H41, H42 Keywords: Economic Development, Human Development Index, Dictatorship

Time indicator of the Human Development Index

2017 ◽  
Vol 28 (1) ◽  
pp. 273-296
Author(s):  
R Ibar-Alonso ◽  
C Cosculluela-Martínez ◽  
GJD Hewings
Keyword(s):  
Life Expectancy ◽  
Gross Domestic Product ◽  
United Nations ◽  
Human Development ◽  
Human Development Index ◽  
Domestic Product ◽  
Discriminant Functions ◽  
Development Index ◽  
Fisher Discriminant ◽  
The United Nations

The Human Development Index, computed by the United Nations, has been challenged since it does not measure the real development of a country. It needs to be combined with other indexes and ratios (poverty, Gini index). Using the same data as the United Nations, an additional dimension (time) is added to create a Time Human Development Index (THDI) where the weights differ for each cluster of countries. Fisher discriminant functions classify countries in each period of time, allowing different weights of the variables for the same country each year. Results suggest that when the Literacy and gross enrolment rates decrease in the four countries occupying the lower positions in the THDI, the THDI falls. In those countries where the THDI increases, gross domestic product and life expectancy rates do not seem to be positively correlated to the THDI, while the gross enrolment rate also increases. Thus, gross enrolment and literacy rates are variables related to the evolution of THDI; while, surprisingly, gross domestic product and life expectancy has few influence in its evolution.

The global cancer burden and human development: A review

2017 ◽  
Vol 46 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Miranda M. Fidler ◽  
Freddie Bray ◽  
Isabelle Soerjomataram
Keyword(s):  
Risk Factors ◽  
Life Expectancy ◽  
Human Development ◽  
Cancer Incidence ◽  
Human Development Index ◽  
Developed Countries ◽  
Global Perspective ◽  
Cancer Burden ◽  
Development Index ◽  
Very High

Aims: This review examines the links between human development and cancer overall and for specific types of cancer, as well as cancer-related risk-factors and outcomes, such as disability and life expectancy. Methods: To assess human development, the Human Development Index was utilized continuously and according to four levels (low, medium, high, very high), where the low and very high categories include the least and most developed countries, respectively. All studies that assessed aspects of the global cancer burden using this measure were reviewed. Results: Although the present cancer incidence burden is greater in higher Human Development Index countries, a greater proportion of the global mortality burden is observed in less developed countries, with a higher mean fatality rate in the latter countries. Further, the future cancer burden is expected to disproportionally affect less developed regions; in particular, it has been estimated that low and medium Human Development Index countries will experience a 100% and 81% increase in cancer incidence from 2008 to 2030, respectively. Disparities were also observed in risk factors and average health outcomes, such as a greater number of years of life lost prematurely and fewer cancer-related gains in life expectancy observed in lower versus higher Human Development Index settings. Conclusions: From a global perspective, there remain clear disparities in the cancer burden according to national Human Development Index scores. International efforts are needed to aid countries in social and economic transition in order to efficiently plan, implement and evaluate cancer control initiatives as a means to reduce the widening gap in cancer occurrence and survival worldwide.

scholarly journals Global Discrepancies between Numbers of Available SARS-CoV-2 Genomes and Human Development Indexes at Country Scales

Viruses ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 775
Author(s):  
Philippe Colson ◽  
Didier Raoult
Keyword(s):  
Life Expectancy ◽  
Human Development ◽  
Human Development Index ◽  
Gdp Per Capita ◽  
Asian Countries ◽  
Genome Sequences ◽  
Microsoft Excel ◽  
Development Index ◽  
The World ◽  
Per Capita

It has now been over a year since SARS-CoV-2 first emerged in China, in December 2019, and it has spread rapidly around the world. Some variants are currently considered of great concern. We aimed to analyze the numbers of SARS-CoV-2 genome sequences obtained in different countries worldwide until January 2021. On 28 January 2021, we downloaded the deposited genome sequence origin from the GISAID database, and from the “Our world in data” website we downloaded numbers of SARS-CoV-2-diagnosed cases, numbers of SARS-CoV-2-associated deaths, population size, life expectancy, gross domestic product (GDP) per capita, and human development index per country. Files were merged and data were analyzed using Microsoft Excel software. A total of 450,968 SARS-CoV-2 genomes originating from 135 countries on the 5 continents were available. When considering the 19 countries for which the number of genomes per 100 deaths was >100, six were in Europe, while eight were in Asia, three were in Oceania and two were in Africa. Six (30%) of these countries are beyond rank 75, regarding the human development index and four (20%) are beyond rank 80 regarding GDP per capita. Moreover, the comparisons of the number of genomes sequenced per 100 deaths to the human development index by country show that some Western European countries have released similar or lower numbers of genomes than many African or Asian countries with a lower human development index. Previous data highlight great discrepancies between the numbers of available SARS-CoV-2 genomes per 100 cases and deaths and the ranking of countries regarding wealth and development.

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