In 2023, Switzerland led the ranking of countries with the highest average wealth per adult, with approximately ******* U.S. dollars per person. Luxembourg 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 old 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 the 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.

Graph and download economic data for Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) (WFRBST01134) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.

Comparing the *** selected regions regarding the gini index , South Africa is leading the ranking (**** points) and is followed by Namibia with **** points. At the other end of the spectrum is Slovakia with **** points, indicating a difference of *** points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from * (=total equality of incomes) to *** (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

A high number of the countries with the highest income distribution levels are located in Eastern and Central Europe, with Slovakia topping the list, with an index of ****. On the other end of the scale, South Africa was the country with the lowest income distribution.

license: apache-2.0 tags: - africa - sustainable-development-goals - world-health-organization - development

  Average income of large-scale food producers, PPP (constant 2011 international $)





  Dataset Description

This dataset provides country-level data for the indicator "2.3.2 Average income of large-scale food producers, PPP (constant 2011 international $)" across African nations, sourced from the World Health Organization's (WHO) data portal on Sustainable… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/average-income-of-large-scale-food-producers-ppp-for-african-countries.

The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.

Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.

Small changes in estimates between years should be treated with caution as they may not be statistically significant.

Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

This dataset provides values for GDP PER CAPITA PPP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Gross National Income (GNI) per Capita based on purchasing power parity (current international $) by country for 2014. This is a filtered layer based on the "Gross National Income by country, 1990-2010 time series" layer.

Wealth inequality has been sharply rising in the United States and across many other high-income countries. Due to a lack of data, we know little about how this trend has unfolded across locations within countries. Investigating this subnational geography of wealth is crucial, as from one generation to the next, wealth powerfully shapes opportunity and disadvantage across individuals and communities. Using machine-learning-based imputation to link newly assembled national historical surveys conducted by the U.S. Federal Reserve to population survey microdata, the data presented in this paper addresses this gap. The Geographic Wealth Inequality Database ("GEOWEALTH-US") provides the first estimates of the level and distribution of wealth at various geographical scales within the United States from 1960 to 2020. The GEOWEALTH-US database enables new lines investigation into the contribution of inter-regional wealth patterns to major societal challenges including wealth concentration, spatial income inequality, equality of opportunity, housing unaffordability, and political polarization.

By 2030, the middle-class population in Asia-Pacific is expected to increase from 1.38 billion people in 2015 to 3.49 billion people. In comparison, the middle-class population of sub-Saharan Africa is expected to increase from 114 million in 2015 to 212 million in 2030.

Worldwide wealth

While the middle-class has been on the rise, there is still a huge disparity in global wealth and income. The United States had the highest number of individuals belonging to the top one percent of wealth holders, and the value of global wealth is only expected to increase over the coming years. Around 57 percent of the world’s population had assets valued at less than 10,000 U.S. dollars; while less than one percent had assets of more than million U.S. dollars. Asia had the highest percentage of investable assets in the world in 2018, whereas Oceania had the highest percent of non-investable assets.

The middle-class

The middle class is the group of people whose income falls in the middle of the scale. China accounted for over half of the global population for middle-class wealth in 2017. In the United States, the debate about the middle class “disappearing” has been a popular topic due to the increase in wealth to the top billionaires in the nation. Due to this, there have been arguments to increase taxes on the rich to help support the middle-class.

Vietnam and US trade data is in the sheet “VN US”. (XLSX)

Gross National Income (GNI) per Capita based on purchasing power parity (current international $) by country for 2014. This is a filtered layer based on the "Gross National Income by country, 1990-2010 time series" layer. GNI based on purchasing power parity rates allows for easier comparison of countries by taking into account price differences between countries. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current international dollars based on the 2011 ICP round.Data Sources: World Bank, International Comparison Program database; Country shapes from Natural Earth 50M scale data.

This report provides a systematic review and empirical evidence related to the experiences of middle-income countries and economies participating in the Programme for International Student Assessment (PISA), 2000 to 2015. PISA is a triennial survey that aims to evaluate education systems worldwide by testing the skills and knowledge of 15-year-old students. To date, students representing more than 70 countries and economies have participated in the assessment, including 44 middle-income countries, many of which are developing countries receiving foreign aid. This report provides answers to six important questions about these middle-income countries and their experiences of participating in PISA: What is the extent of developing country participation in PISA and other international learning assessments? Why do these countries join PISA? What are the financial, technical, and cultural challenges for their participation in PISA? What impact has participation had on their national assessment capacity? How have PISA results influenced their national policy discussions? And what does PISA data tell us about education in these countries and the policies and practices that influence student performance? The findings of this report are being used by the OECD to support its efforts to make PISA more relevant to a wider range of countries, and by the World Bank as part of its on-going dialogue with its client countries regarding participation in international large-scale assessments.

Introduction

Money Laundering Statistics: Money laundering is the process of concealing the origins of illegally obtained money. These are from illegal activities, such as drug cases, human trafficking, sex work, terrorism, corruption, etc, to generate money. Laundering activities present several challenges for financial institutions, governments, and law enforcement agencies.

The global nature of the economy, the increasing sophistication of financial transactions, and the involvement of anti-money laundering (AML) initiatives all contribute to making the fight against money laundering a complex and ongoing issue, with severe consequences for the integrity of financial systems and economies.

This article includes several statistical analysis from different current sources that explores the methods, implications, and legal frameworks designed to combat money laundering on a global scale.

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(Source: unodc.org)

The average for 2023 based on 183 countries was 26826 U.S. dollars. The highest value was in Luxembourg: 130491 U.S. dollars and the lowest value was in Burundi: 829 U.S. dollars. The indicator is available from 1990 to 2023. Below is a chart for all countries where data are available.

Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2023 about personal income, personal, median, income, real, and USA.

BackgroundViolence against women perpetrated by an intimate partner (IPV) is prevalent in low- and middle-income countries (LAMIC). The aim was to describe the attitudes of women and men towards perpetration of physical violence to women by an intimate partner, in a large group of low- and middle-income countries.Methods and FindingsWe used data from Round Four of the UNICEF Multiple Indicator Cluster Surveys. Attitudes towards IPV against women were assessed by a study-specific scale asking if ‘wife beating’ is justified in any of five circumstances.Overall, data from 39 countries (all had data from women and 13 countries also had data from men) were included in the analyses. The proportions of women who held attitudes that ‘wife-beating’ was justified in any of the five circumstances varied widely among countries from 2.0% (95% CI 1.7;2.3) in Argentina to 90.2% (95% CI 88.9;91.5) in Afghanistan. Similarly, among men it varied from 5.0% (95% CI 4.0;6.0) in Belarus to 74.5% (95% CI 72.5;76.4) in the Central African Republic. The belief that ‘wife-beating’ is acceptable was most common in Africa and South Asia, and least common in Central and Eastern Europe and Latin America and the Caribbean. In general this belief was more common among people in disadvantaged circumstances, including being a member of a family in the lowest household wealth quintile, living in a rural area and having limited formal education. Young adults were more likely to accept physical abuse by a man of his intimate partner than those who were older, but people who had never partnered were less likely to have these attitudes.ConclusionsViolence against women is an international priority and requires a multicomponent response. These data provide evidence that strategies should include major public education programs to change attitudes about the acceptability of IPV against women, and that these should be addressed to women and girls as well as to boys and men.

Prevalence of depression, pain and related factors among study participants (n = 390).

Introduction

Money Laundering Statistics: Indeed, money laundering remains a big social problem across most economies and their financial systems. Most criminals aim to conceal the illicit sources of their funds and present them as clean. It is in the year 2024 when the extent of money laundering is at a crisis level in several nations.

This piece will contain relevant money laundering statistics on a global scale in 2024, including the effects, financial repercussions, and politics surrounding the existing policies to curb the vice.

This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.