In 2021, Massachusetts, Connecticut, and Minnesota had the highest Human Development Index (HDI) score of any other states at ****. Many more states had a score just below this at ****. Mississippi had the lowest HDI score at ****, and the U.S. average was ****.

******* had the highest level of the Human Development Index (HDI) worldwide in 2023 with a value of *****. With a score of ****, ****** followed closely behind *********** and had the second-highest level of human development in that year. The rise of the Asian tigers In the decades after the Cold War, the four so-called Asian tigers, South Korea, Singapore, Taiwan, and Hong Kong (now a Special Administrative Region of China) experienced rapid economic growth and increasing human development. At number eight and number 13 of the HDI, respectively, *********************** are the only Asian locations within the top-15 highest HDI scores. Both locations have experienced tremendous economic growth since the 1980’s and 1990’s. In 1980, the per capita GDP of Hong Kong was ***** U.S. dollars, increasing throughout the decades until reaching ****** in 2023, which is expected to continue to increase in the future. Meanwhile, in 1989, Singapore had a GDP of nearly ** billion U.S. dollars, which has risen to nearly *** billion U.S. dollars today and is also expected to keep increasing. Growth of the UAE The United Arab Emirates (UAE) is the only Middle Eastern country besides Israel within the highest ranking HDI scores globally. Within the Middle East and North Africa (MENA) region, the UAE has the third-largest GDP behind Saudi Arabia and Israel, reaching nearly *** billion U.S. dollars by 2022. Per capita, the UAE GDP was around ****** U.S. dollars in 1989, and has nearly doubled to ****** U.S. dollars by 2021. Moreover, this is expected to reach over ****** U.S. dollars by 2029. On top of being a major oil producer, the UAE has become a hub for finance and business and attracts millions of tourists annually.

The average for 2023 based on 184 countries was 0.744 points. The highest value was in Iceland: 0.972 points and the lowest value was in South Africa: 0.388 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

Context

The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions. The health dimension is assessed by life expectancy at birth, the education dimension is measured by mean of years of schooling for adults aged 25 years and more and expected years of schooling for children of school entering age. The standard of living dimension is measured by gross national income per capita. The HDI uses the logarithm of income, to reflect the diminishing importance of income with increasing GNI. The scores for the three HDI dimension indices are then aggregated into a composite index using geometric mean. Refer to Technical notes for more details. The HDI can be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The HDI simplifies and captures only part of what human development entails. It does not reflect on inequalities, poverty, human security, empowerment, etc. The HDRO provides other composite indices as a broader proxy on some of the key issues of human development, inequality, gender disparity, and poverty. A fuller picture of a country's level of human development requires analysis of other indicators and information presented in the HDR statistical annex.

Content

In this Dataset, we have Global, regional, and country/territory-level data on key dimensions of human development with various composite indices. The human development composite indices have been developed to capture broader dimensions of human development, identify groups falling behind in human progress and monitor the distribution of human development. In addition to the HDI, the indices include Multidimensional Poverty Index (MPI), Inequality-adjusted Human Development Index (IHDI), Gender Inequality Index (GII), Gender Development Index (GDI), Planetary pressures-adjusted HDI (PHDI) and Gender Social Norms Index (GSNI).

Dataset Glossary (Alphabetical Order)

• Adolescent Birth Rate - Births per 1000 Women Ages 15 to 19
• Carbon Dioxide Emissions per Capita Production in Tonnes
• Coefficient of Human Inequality
• Expected Years of Schooling - Female
• Expected Years of Schooling - Male
• Expected Years of Schooling
• Gender Development Index
• Gender Inequality Index
• Gross National Income Per Capita - Female
• Gross National Income Per Capita - Male
• Gross National Income Per Capita
• HDI Female
• HDI Male
• Human Development Index
• Inequality Adjusted Human Development Index
• Inequality in Education
• Inequality in Income
• Inequality in Life Expectancy
• Labour Force Participation Rate - Female Percentage Ages 15 and Older
• Labour Force Participation Rate - Male Percentage Ages 15 and Older
• Life Expectancy at Birth - Female
• Life Expectancy at Birth - Male
• Life Expectancy at Birth
• Material Footprint per Capita in Tonnes
• Maternal Mortality Ratio - Deaths per 100000 Live Births
• Mean Years of Schooling - Female
• Mean Years of Schooling - Male
• Mean Years of Schooling
• Planetary Pressures Adjusted Human Development Index

Cover Photo by: pch.vector on Freepik

Th e Human Development Index (HDI) is a composite index of outcome indicators in three dimensions: a. A long and healthy life, as reflected in life expectancy at birth. b. The acquisition of education and knowledge, as reflected in the mean years of schooling (adjusted for out of school children) and literacy rate (age 7 years and above). c. Th e standard of living and command over resources, as reflected in the monthly per capita expenditure adjusted for inflation and inequality.

The average for 2023 based on 27 countries was 0.915 points. The highest value was in Denmark: 0.962 points and the lowest value was in Bulgaria: 0.845 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

Context

The Gender Development Index (GDI) is a composite measure designed to assess gender disparities and inequalities in a society by considering factors related to human development. It is an extension of the Human Development Index (HDI) and focuses on three key dimensions: health, education, and income. In the GDI, these dimensions are assessed separately for males and females, allowing for a comparison of gender-based development gaps. Health indicators typically include life expectancy at birth for both genders. Education indicators encompass literacy rates and enrollment in primary, secondary, and tertiary education for both males and females. The income component typically examines income levels and workforce participation for both genders.

Content

This dataset provides comprehensive historical data on gender development indicators at a global level. It includes essential columns such as ISO3 (the ISO3 code for each country/territory), Country (the name of the country or territory), Continent (the continent where the country is located), Hemisphere (the hemisphere in which the country is situated), Human Development Groups, UNDP Developing Regions, HDI Rank (2021) representing the Human Development Index Rank for the year 2021, and Gender Development Index spanning from 1990 to 2021.

Dataset Glossary (Column-wise)

• ISO3 - ISO3 for the Country/Territory
• Country - Name of the Country/Territory
• Continent - Name of the Continent
• Hemisphere - Name of the Hemisphere
• Human Development Groups - Human Development Groups
• UNDP Developing Regions - UNDP Developing Regions
• HDI Rank (2021) - Human Development Index Rank for 2021
• Gender Development Index from 1990 to 2021 - Gender Development Index from 1990 to 2021

Data Dictionary

• UNDP Developing Regions:
  • SSA - Sub-Saharan Africa
  • LAC - Latin America and the Caribbean
  • EAP - East Asia and the Pacific
  • AS - Arab States
  • ECA - Europe and Central Asia
  • SA - South Asia

Structure of the Dataset

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Acknowledgement

This Dataset is created from Human Development Reports. This Dataset falls under the Creative Commons Attribution 3.0 IGO License. You can check the Terms of Use of this Data. If you want to learn more, visit the Website.

Cover Photo by: Freepik

Thumbnail by: Freepik

Compared to other African countries, Seychelles scored the highest in the Human Development Index (HDI) in 2022. The country also ranked 67th globally, as one of the countries with a very high human development. This was followed by Mauritius, Libya, Egypt, and Tunisia, with scores ranging from 0.80 to 0.73 points. On the other hand, Central African Republic, South Sudan, and Somalia were among the countries in the region with the lowest index scores, indicating a low level of human development.

Abstract: The aim of research was to analyze the level of human development of the 25 municipalities in the Administrative Region of Ribeirão Preto, São Paulo's State, Brazil, using Municipal Human Development Index, and to inform weaknesses and potentialities of the tool. The methodology has exploratory and descriptive characteristics, based on secondary data. The municipality of Serra Azul presented most of the critical indicators that compose the index.

Abstract Aim: This study aimed to examine the association between physical activity (PA) indicators and TV viewing as a function of the Human Development Index (HDI). Method: This cross-sectional study was based on data from the National School Health Survey, which was composed of 102,072 students (14.28±1.03; 51.3% girls). Total PA, active commuting to school (ACS) and TV viewing were assessed by questionnaires and classified through a gradual scale ranging from “F” (low) to “A+” (high). The correlation between total PA, ACS, TV viewing and HDI was verified by Spearman’s Correlation and presented in rs. Results: HDI was positively associated with total PA [girls: rs = 0.572 (p < 0.001); boys: rs = 0.843 (p < 0.001)] and ACS [girls: rs = 0.433 (p < 0.001); boys: rs = 0.554 (p < 0.001)]; while a negative correlation was found between HDI and TV viewing [girls: rs = -0.330 (p < 0.001); boys: rs = -0.348 (p < 0.001)]. Conclusions: Brazilian adolescents from states with higher HDI were more active and spent more time watching TV than their counterparts from states with lower HDI.

This dataset provides a country–year panel for OECD countries covering the period 2010–2024. It combines annual data on public, private and total social expenditure as a share of GDP with the World Happiness Index (WHI) and the Human Development Index (HDI).The data are constructed to analyze the relationships between social spending, subjective well-being and human development in OECD countries. The panel structure (one observation per country per year) makes the dataset suitable for descriptive analysis as well as regression-based empirical research.ContentsThe main Excel file contains a single data sheet:Sheet: data_setEach row corresponds to a specific country–year observation for an OECD member state.Variables:Country: Country name (OECD member; e.g., “Australia”, “Türkiye”, “United States”).iso3: ISO 3166-1 alpha-3 country code (e.g., “AUS”, “TUR”, “USA”).year: Calendar year (2010–2024).pub_socexp_gdp: Public social expenditure as a percentage of GDP (%).priv_socexp_gdp: Private (mandatory and voluntary) social expenditure as a percentage of GDP (%).tot_socexp_gdp: Total social expenditure (public + private) as a percentage of GDP (%).WHI: World Happiness Index; average national happiness score on a 0–10 scale based on the Cantril ladder question.HDI: Human Development Index; composite index of three basic dimensions of human development (health, education, and standard of living).income_group: Binary country income group indicator used in the analysis. High‑income OECD countries are coded as 1 (“High”), and all other OECD members (upper‑middle, lower‑middle and low income) are coded as 0 (“NonHigh”). Income groups were constructed using data from the OECD Data Explorer (2024) and the World Bank country income classification for 2024, based on PPP (purchasing power parity) income thresholds.Empty cells indicate that data for the corresponding country–year observation are not available in the original sources or were not included in the analytical sample due to missingness.Data sourcesSocial expenditure (pub_socexp_gdp, priv_socexp_gdp, tot_socexp_gdp)Data are taken from the OECD Social Expenditure Database (SOCX). SOCX provides reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at the program level for 38 OECD countries (and some accession countries), with coverage from 1980 and estimates for more recent years.Reference: OECD Social Expenditure Database (SOCX), https://www.oecd.org/en/data/datasets/social-expenditure-database-socx.html.World Happiness Index (WHI)Happiness data are drawn from the World Happiness Report, accessed via HumanProgress.org (World Happiness Report section). The index is based on average national values for answers to the Cantril ladder question, which asks respondents to evaluate their current life on a 0–10 scale, with the worst possible life as 0 and the best possible life as 10.Reference: World Happiness Report; HumanProgress.org, https://humanprogress.org.Human Development Index (HDI)HDI data are drawn from the Human Development Index series compiled by the United Nations Development Programme (UNDP), accessed via HumanProgress.org (Human Development Index section). The HDI measures three basic dimensions of human development: life expectancy at birth; an education component (adult literacy rate and school enrollment); and GDP per capita (purchasing power parity, PPP, in U.S. dollars), combined into a composite index.Reference: United Nations Development Programme (UNDP), Human Development Reports; HumanProgress.org, https://humanprogress.org.Data construction and coverageThe dataset is restricted to OECD member countries and the years 2010–2024.WHI and HDI series are matched to OECD social expenditure data using ISO3 country codes and calendar years.In addition, a binary income group variable (income_group) was created to distinguish high‑income OECD countries from other OECD members, using the World Bank’s 2024 income thresholds (PPP‑based) and country information from the OECD Data Explorer (2024).Some country–year combinations, particularly in later years (e.g., 2022–2024), contain missing values where the original sources do not provide data or only provide partial estimates. These are retained as empty cells.The empirical analyses in the associated study are conducted on subsets of the data restricted to complete cases for the relevant variables.Researchers can use this dataset to replicate the results of the associated study or to conduct additional analyses on the links between social expenditure, happiness and human development within the OECD context.If you use this dataset, please cite both this data file and the original data providers (OECD, World Happiness Report, UNDP, and HumanProgress.org).

The Human development index (HDI) for European countries in 2023 shows that although all the countries in this statistic have scores which imply high levels of development, Iceland score of ***** was the highest in this year. The HDI is a statistic that combines life-expectancy, education levels and GDP per capita. Countries with scores over ***** are considered to have very high levels of development, compared with countries that score lower.

Ranked bottom and top five states, HLI, 2016.

The Human Development Index (HDI) was developed by the United Nations Development Programme (UNDP) in the Human Development Report 1990 to measure the level of economic and social development of the United Nations member countries. The HDI is a composite indicator based on three basic variables: life expectancy, educational attainment and quality of life, and is calculated according to a certain methodology. "The One Belt One Road (OBOR) human development resilience dataset is a comprehensive indicator of human development resilience in each country. "The human development resilience dataset for countries along the Belt and Road is a comprehensive diagnosis based on sensitivity and adaptability analysis using year-by-year data of the Human Development Index for countries along the Belt and Road from 2000 to 2020. The Human Development Resilience Indicator (HDRI) data was prepared based on sensitivity and adaptation analysis. Please refer to the documentation for the methodology of preparing the dataset. "The Human Development Resilience Dataset for countries along the Belt and Road is an important reference for analysing and comparing the current state of human development resilience in each country.

Context

Every Politician lie but data doesn't. So I collected data of some of the important metrics of all the Indian States to check what is good and bad in all of them. The data is mostly scrapped from Wikipedia so it can be little bit inconsistent however, I will improve that in the subsequent versions.

Content

The contains the data about the metrics like HDI ( Human Development Index), Nominal GDP, Crime Rate, Percentage of population below poverty line and unemployment rate of all the states of India.

Acknowledgements

Most of the data is scrapped from Wikipedia so thanks to them for providing the data however I wish they improve their authenticity.

Inspiration

1. Feel free to play around the data, check where each state stands in all the metrics.
2. Try finding out why some states are top of some of the metrics, while at the bottom in others.
3. See if there's any correlation between different metrics. For example, One I am very interested to if there's any correlation between HDI and unemployment or HDI and nominal GDP or HDI and poverty.

In sub-Saharan Africa, a score of around 0.57 was achieved on the Human Development Index (HDI) in 2023. This represented a low level of human development. In 2018, the sub-region moved from being categorized as low human development to medium human development.

In 2023, Ukraine and Qatar topped the Gender Development Index (GDI) with index scores over ****. On the other hand, Yemen reported the lowest index, with only ****. The higher the value, the smaller the gap between women and men. The Gender Development Index (GDI) is basically a ratio of Human Development Index calculated separately for women and men.

This study explores the relationship between human development and market institutions and tests the performance of three alternative economic perspectives that each assign a different role to governments. Based on a sample of 34 OECD countries plus Russia across a time frame spanning 1990 to 2018, the results demonstrate that economic freedom and small size of government do not significantly affect human development as measured by the Human Development Index. Hence, we find no support for the free-market ideal. Conversely, it is found that human development is positively related to governmental interventions that aim to reduce externalities (public expenditure on education and environmental regulation). These results support the perfect-market perspective. With respect to the welfare-state perspective, the findings are mixed. On the one hand, we found that (some) labor market regulations (particularly hiring and firing regulations, hours regulations and mandated cost of worker dismissal) have a negative impact upon human development. On the other hand, human development is shown to be positively affected by governmental intervention seeking to reduce gender stratification in the labor market.

The average for 2023 based on 52 countries was 0.585 points. The highest value was in the Seychelles: 0.848 points and the lowest value was in South Africa: 0.388 points. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.