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.

Health Data Interactive (HDI) presents a broad range of important public health indicators through an interactive web-based application that provides access to pre-tabulated national and state data for the US. The primary objective is to provide national estimates of public health measures cross tabulated by a common set of variables. HDI tables contain national health statistics for infants, children, adolescents, adults, and older adults. The tables can be customized by age, gender, race/ethnicity, and geographic location to explore different trends and patterns.n

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.

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).

Ranked bottom and top five states, HLI, 2016.

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'.

Using micro-data on six surveys–the Gallup World Poll 2005–2023, the U.S. Behavioral Risk Factor Surveillance System, 1993–2022, Eurobarometer 1991–2022, the UK Covid Social Survey Panel, 2020–2022, the European Social Survey 2002–2020 and the IPSOS Happiness Survey 2018–2023 –we show individuals’ reports of subjective wellbeing in Europe declined in the Great Recession of 2008/9 and during the Covid pandemic of 2020–2021 on most measures. They also declined in four countries bordering Ukraine after the Russian invasion in 2022. However, the movements are not large and are not apparent everywhere. We also used data from the European Commission’s Business and Consumer Surveys on people’s expectations of life in general, their financial situation and the economic and employment situation in the country. All of these dropped markedly in the Great Recession and during Covid, but bounced back quickly, as did firms’ expectations of the economy and the labor market. Neither the annual data from the United Nation’s Human Development Index (HDI) nor data used in the World Happiness Report from the Gallup World Poll shifted much in response to negative shocks. The HDI has been rising in the last decade reflecting overall improvements in economic and social wellbeing, captured in part by real earnings growth, although it fell slightly after 2020 as life expectancy dipped. This secular improvement is mirrored in life satisfaction which has been rising in the last decade. However, so too have negative affect in Europe and despair in the United States.

General characteristics of elderly included in the EPIC-Elderly (Spain, the Netherlands, Greece, and Sweden), Rotterdam Study, SENECA (Northern Europe and Southern Europe), and the Zutphen Elderly Study across categories of alcoholic beverage preference.

Electroless Copper for HDI Build-Up Market Outlook

According to our latest research, the Global Electroless Copper for HDI Build-Up market size was valued at $1.2 billion in 2024 and is projected to reach $2.8 billion by 2033, expanding at a robust CAGR of 9.7% during 2024–2033. The primary factor driving this impressive growth trajectory is the surging demand for miniaturized and high-density interconnect (HDI) printed circuit boards (PCBs) in next-generation mobile devices, automotive electronics, and advanced industrial equipment. As the electronics industry pivots toward more compact, lightweight, and high-performance components, the adoption of electroless copper plating for HDI build-up layers has become indispensable, ensuring superior conductivity, reliability, and manufacturability in increasingly complex PCB architectures.

Regional Outlook

The Asia Pacific region commands the largest share of the Electroless Copper for HDI Build-Up market, accounting for over 55% of global revenue in 2024. This dominance is driven by the presence of major electronics manufacturing hubs such as China, Japan, South Korea, and Taiwan. These countries have established mature supply chains, advanced technological capabilities, and a robust ecosystem of PCB fabricators and component suppliers. Government incentives, favorable trade policies, and sustained investments in R&D further bolster the region’s leadership. The proliferation of consumer electronics, rapid adoption of 5G infrastructure, and the automotive sector’s transition to electric and autonomous vehicles continue to fuel demand for HDI PCBs, thereby accelerating the uptake of electroless copper solutions.

North America emerges as the fastest-growing regional market, forecasted to expand at a CAGR of 11.2% through 2033. This growth is underpinned by significant investments in advanced manufacturing, the resurgence of domestic electronics assembly, and the burgeoning demand for high-reliability PCBs in aerospace, defense, and automotive sectors. The region’s focus on technological innovation, coupled with stringent quality and environmental standards, drives the adoption of high-purity electroless copper solutions. Additionally, the presence of leading semiconductor and telecom equipment manufacturers, as well as increased government funding for R&D initiatives in advanced electronics, is catalyzing market expansion across the United States and Canada.

Emerging economies in Latin America and Middle East & Africa are gradually integrating electroless copper technologies into their electronics manufacturing sectors, though market penetration remains in its nascent stages. Challenges such as limited technical expertise, infrastructural constraints, and fluctuating regulatory environments can impede rapid adoption. However, growing investments in industrial automation, the localization of electronics assembly, and supportive policy frameworks are expected to create new opportunities. As these regions bridge the technology gap and develop skilled workforces, the demand for HDI build-up solutions, including electroless copper, is projected to rise steadily over the forecast period.

Report Scope

Adjusted a food group and nutrient intakes (mean (SE)) across categories of alcoholic beverage preference.

The data collected aim to test whether English proficiency levels in a country are positively associated with higher democratic values in that country. English proficiency is sourced from statistics by Education First’s "EF English Proficiency Index" which covers countries' scores for the calendar year 2022 and 2021. The EF English Proficiency Index ranks 111 countries in five different categories based on their English proficiency scores that were calculated from the test results of 2.1 million adults. While democratic values are operationalized through the liberal democracy index from the V-Dem Institute annual report for 2022 and 2021. Additionally, the data is utilized to test whether English language media consumption acts as a mediating variable between English proficiency and democracy levels in a country, while also looking at other possible regression variables. In order to conduct the linear regression analyses for the dats, the software that was utilized for this research was Microsoft Excel.The raw data set consists of 90 nation states in two years from 2022 and 2021. The raw data is utilized for two separate data sets the first of which is democracy indicators which has the regression variables of EPI, HDI, and GDP. For this table set there is a total of 360 data entries. HDI scores are a statistical summary measure that is developed by the United Nations Development Programme (UNDP) which measures the levels of human development in 190 countries. The data for nominal gross domestic product scores (GDP) are sourced from the World Bank. Having strong regression variables that have been proven to have a positive link with democracy in the data analysis such as GDP and HDI, would allow the regression analysis to identify whether there is a true relationship between English proficiency and democracy levels in a country. While the second data set has a total of 720 data entries and aims to identify English proficiency indicators the data set has 7 various regression variables which include, LDI scores, Years of Mandatory English Education, Heads of States Publicly speaking English, GDP PPP (2021USD), Common Wealth, BBC web traffic and CNN web traffic. The data for years of mandatory English education is sourced from research at the University of Winnipeg and is coded in the data set based on the number of years a country has English as a mandatory subject. The range of this data is from 0 to 13 years of English being mandatory. It is important to note that this data only concerns public schools and does not extend to the private school systems in each country. The data for heads of state publicly speaking English was done through a video data analysis of all heads of state. The data was only used for heads of state who had been in their position for at least a year to ensure the accuracy of the data collected; with a year in power, for heads of state that had not been in their position for a year, data was taken from the previous head of state. This data only takes into account speeches and interviews that were conducted during their incumbency. The data for each country’s GDP PPP scores are sourced from the World Bank, which was last updated for a majority of the countries in 2021 and is tied to the US dollar. Data for the commonwealth will only include members of the commonwealth that have been historically colonized by the United Kingdom. Any country that falls under that category will be coded as 1 and any country that does not will be coded as 0. For BBC and CNN web traffic that data is sourced by using tools in Semrush which provide a rough estimate of how much web traffic each news site generates in each country. Which will be utilized to identify the average number of web traffic for BBC News and CNN World News for both the 2021 and 2022 calendar. The traffic for each country will also be measured per capita, per 10 thousand people to ensure that the population density of a country does not influence the results. The population of each country for both 2021 and 2022 is sourced from the United Nations revision of World Population Prospects of both 2021 and 2022 respectively.

1) the Human Development Index (HDI - the Human Development Index) to measure the level of the member states of the United Nations economic and social Development indicators, is the result of the GNP Index challenge to traditional;2) this data comes from the United Nations development programme (UNDP) statistical data;3) from the dynamic human development index to reflect the development status of human, reveals the priority to the development of a country, the development policies for countries all over the world especially in developing countries have provided the certain basis, thereby helping to excavate a country's economic development potential;4) data covers all the way "area" 64 1 countries along the (Chinese), 1990-2019, a total of 29 data, in the heart of the "One Belt And One Road" related research application is very broad.

In 2024, Switzerland led the ranking of countries with the highest average wealth per adult, with approximately ******* U.S. dollars per person. The United States was ranked second with an average wealth of around ******* U.S. dollars per adult, followed by Hong Kong SAR. However, the figures do not show the actual distribution of wealth. The Gini index shows wealth disparities in countries worldwide. Does wealth guarantee a longer life? As the adage goes, “money can’t buy you happiness,” yet wealth and income are continuously correlated to the quality of life of individuals in different countries around the world. While greater levels of wealth may not guarantee a higher quality of life, it certainly increases an individual’s chances of having a longer one. Although they do not show the whole picture, life expectancy at birth is higher in the wealthier world regions. Does money bring happiness? A number of the world’s happiest nations also feature in the list of those countries for which average income was highest. Finland, however, which was the happiest country worldwide in 2022, is missing from the list of the top twenty countries with the highest wealth per adult. As such, the explanation for this may be the fact that a larger proportion of the population has access to a high-income relative to global levels. Measures of quality of life Criticism of the use of income or wealth as a proxy for quality of life led to the creation of the United Nations’ Human Development Index. Although income is included within the index, it also has other factors taken into account, such as health and education. As such, the countries with the highest human development index can be correlated to those with the highest income levels. That said, none of the above measures seek to assess the physical and mental environmental impact of a high quality of life sourced through high incomes. The happy planet index demonstrates that the inclusion of experienced well-being and ecological footprint in place of income and other proxies for quality of life results in many of the world’s materially poorer nations being included in the happiest.

Context

The Maternal Mortality Ratio (MMR) is a crucial indicator within the Gender Inequality Index (GII), an encompassing measure designed to assess gender disparities and inequities within a society. The GII, an extension of the Human Development Index (HDI), focuses on three primary dimensions: reproductive health, empowerment, and economic activity. Reproductive health, one of the key dimensions, sheds light on the challenges faced by individuals based on their gender. Within this context, the Maternal Mortality Ratio specifically gauges the number of maternal deaths per 100,000 live births, providing insight into the disparities in health outcomes experienced by women. This indicator reflects the state of maternal health and underscores the importance of addressing reproductive rights to mitigate gender inequalities.

Content

This dataset encompasses extensive historical information regarding gender development indicators on a global scale. Key columns include ISO3 (the ISO3 code assigned to each country/territory), Country (the name of the country or territory), Continent (the continent of the country's location), Hemisphere (the hemisphere in which the country is positioned), Human Development Groups, UNDP Developing Regions, HDI Rank (2021) representing the Human Development Index Rank for the year 2021, and Maternal Mortality Ratio (deaths per 100,000 live births) 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
• Maternal Mortality Ratio (deaths per 100,000 live births) from 1990 to 2021 - Maternal Mortality Ratio 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: Image by gstudioimagen1 on Freepik

Thumbnail by: Baby icons created by Victoruler - Flaticon

In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.

Context

The dataset extracted from the website of the Brazilian Institute of Geography and Statistics (IBGE) contains all demographic, economic, geographic and human development information on Brazilian cities.

Content

There was no complete dataset to download all this information. So, I did a webscrapping that entered all the pages of each Brazilian cities and got all the information available. After that, I consolidated everything into a single file and now share with you to serve as research and studies of Brazil's performance on development, economics, and other topics.

This file contains 14 columns and 5571 rows (with headers):

• IBGECode - ID of the cities
• LocalCidade - Name of the cities
• LocalUF - State initials of the cities
• LocalEstado - Full name of city states
• RegiaoBrasil - IBGE's Region for each city
• Latitude - city ​​latitude
• Longitude - city ​​longitude
• Gentilico - name given to people born in the city
• PopEstimada_2018 - Population estimated in 2018
• PopCenso 2010 - Population in 2010
• IDHM - HDI of each city
• ReceitasRealizadas_2014 - Revenues realized by cities
• DespesasEmpenhadas_2014 - Expenditure incurred by cities
• Pib_2014 - GDP by cities

Acknowledgements

I thank my co-workers who helped me develop web scrapping and distribute the consolidated information to all of you.

Inspiration

Questions to be answered about this dataset:

1. What is the forecast of the GDP of each city in Brazil?
2. Can we group the cities by some specific division related to HDI or GDP?
3. What will be the total population of the Brazilian in the South of the Country in 2020?

And so on.

Abstract Background Cerebrovascular diseases (CBVD) are the second major cause of death in the world. Objective To analyze the mortality trend of CBVD in Brazil (1996 to 2015) and its association with Human Development Index (HDI) and the Social Vulnerability Index (SVI). Methods This is an ecological study. We analyzed the mortality rate standardized by CBVD. Death data were obtained from the Mortality Information System (SIM) and populational data from the Brazilian Institute of Geography and Statistics (IBGE). The model of regression by inflection points (Joinpoint regression) was used to perform the temporal analysis, calculating the Annual Percent Change (APC) and Average Annual Percent Change (AAPC), with 95% of confidence interval and a significance of 5%. Trends were classified as increasing, decreasing or stationary. A multivariate regression model was used to analyze the association between mortality by CBVD, HDI and SVI. Results During this period, 1,850,811 deaths by CBVD were recorded. We observed a reduction in the national mortality rate (APC -2.4; p = 0.001). Twenty federation units showed a significant trend, of which 13 showed reduction, including all states in the Midwest (n=4), Southeast (n=4) and South (n=3). The HDI was positively associated and the SVI was negatively associated with mortality (p = 0.046 and p = 0.026, respectively). Conclusion An unequal epidemiological course of mortality was observed between the regions, being higher in the Southeast and South states, with a significative tendency of reduction, and lower in the North and Northeast states, but with a significative tendency of increase. HDI and SVI showed an association with mortality. (Arq Bras Cardiol. 2021; 116(1):89-99)