Distribution of wealth

[[File:World_distributionofwealth_GDP_and_population_by_region.gif|thumb|right|250px|World distribution of wealth, GDP, and population by region in the year 2000. Created with openoffice.org Calc. Data obtained from the UNU-WIDER report on worldwide distribution of household wealth: Press release. The World Distribution of Household Wealth. December 5, 2006. By James B. Davies, Susanna Sandstrom, Anthony Shorrocks, and Edward N. Wolff. Tables to the 2006 report in Excel (including Gini coefficients for 229 countries). UNU-WIDER.]]

The '''distribution of wealth''' is a comparison of the wealth of various members or groups in a society. It shows one aspect of economic inequality or economic heterogeneity.

The distribution of wealth differs from the income distribution in that it looks at the economic distribution of ownership of the assets in a society, rather than the current income of members of that society. According to the International Association for Research in Income and Wealth, "the world distribution of wealth is much more unequal than that of income."<ref>{{cite web |url=http://www.iariw.org/abstracts/2006/daviesa.pdf |title=Estimating the World Distribution of Household Wealth |first1=James B. |last1=Davies |first2=Susanna |last2=Sandström |first3=Anthony F. |last3=Shorrocks |author3-link=Anthony Shorrocks |first4=Edward N. |last4=Wolff |publisher=Institution/Country: University of Western Ontario, Canada; WIDER-UNU |access-date=September 10, 2016 |archive-date=December 2, 2020 |archive-url=https://web.archive.org/web/20201202083915/http://www.iariw.org/abstracts/2006/daviesa.pdf |url-status=dead }}</ref>

For rankings regarding wealth, see List of sovereign states by wealth inequality or list of countries by wealth per adult.

==Definition of wealth== {{Main|Wealth}} Wealth of an individual is defined as net worth, expressed as: wealth = assets − liabilities

A broader definition of wealth, which is rarely used in measuring wealth inequality, also includes human capital. For example, the United Nations definition of ''inclusive wealth'' is a monetary measure which includes the sum of natural, human, and physical assets.<ref name="wealth">{{cite news|url=https://www.economist.com/finance-and-economics/2012/06/30/the-real-wealth-of-nations |title=Free exchange: The real wealth of nations |magazine=The Economist |date=June 30, 2012 |access-date=July 14, 2012}}</ref><ref name="IHDP">{{cite web |url=http://www.ihdp.unu.edu/article/iwr |title=Inclusive Wealth Report – IHDP |publisher=Ihdp.unu.edu |date=July 9, 2012 |access-date=July 14, 2012 |archive-url=https://web.archive.org/web/20120630055324/http://www.ihdp.unu.edu/article/iwr/ |archive-date=June 30, 2012 |url-status=dead }}</ref>

The relation between wealth, income, and expenses is: change of wealth = saving = income − consumption (expenses). If an individual has a large income but also large expenses, the net effect of that income on their wealth could be small or even negative.

== Conceptual framework ==

There are many ways to analyze the distribution of wealth. One commonly used example is to compare an individual's wealth at the 99th percentile to the median (50th) percentile. This is P99/P50, one of the potential Kuznets ratios, which follows an inverted-U shape, indicating the relationship between inequality and income per capita. Another common measure is the ratio of the total wealth held by the top, say, 1% of the wealth distribution, to the total wealth in the economy. In many societies, the richest ten percent control more than half of the total wealth.

The ''Pareto Distribution'' has often been used to mathematically quantify the distribution of wealth at the right tail (the wealth of the very rich); stating that the upper 20% owns 80%, the upper 4% owns 64%, the upper 0.8% owns 51.2%, etc. In fact, the tail of wealth distributions, similar to that of income distribution, behaves like a Pareto distribution but with a thicker tail.

''Wealth over people (WOP) curves'' are a visually compelling way to show the distribution of wealth in a nation. WOP curves are modified distribution-of-wealth curves. The vertical and horizontal scales each show percentages from 0 to 100. We imagine all the households in a nation being sorted from richest to poorest. They are then shrunk down and lined up (richest at the left) along the horizontal scale. For any particular household, its point on the curve represents how its wealth compares (as a proportion) to the average wealth of the richest percentile. For any nation, the average wealth of the richest 1/100 of households is the topmost point on the curve (people, 1%; wealth, 100%) or (p=1, w=100) or (1, 100). In the real world, two points on the WOP curve are always known before any statistics are gathered. These are the topmost point (1, 100) by definition, and the rightmost point (poorest people, lowest wealth) or (p=100, w=0) or (100, 0). This unfortunate rightmost point is given because there is always at least one percent of households (incarcerated, long-term illness, etc.) with no wealth at all. Given that the topmost and rightmost points are fixed ... our interest lies in the form of the WOP curve between them. There are two extreme possible forms of the curve. The first is the "perfect communist" WOP. It is a straight line from the leftmost (maximum-wealth) point, horizontally across the people scale, to p=99. Then it drops vertically to wealth = 0 at (p=100, w=0).

The other extreme is the "perfect tyranny" form. It starts on the left at the tyrant's maximum wealth of 100%. It then immediately drops to zero at p=2 and remains zero horizontally across the rest of the people. That is, the tyrant and his friends (the top percentile) own all the nation's wealth. All other citizens are serfs or enslaved people. An obvious intermediate form is a straight line connecting the left/top point to the right/bottom point. In such a "Diagonal" society, a household in the richest percentile would have just twice the wealth of a family in the median (50th) percentile. Such a society is compelling to many (especially people with low incomes). In fact, it is a comparison to a diagonal society, which is the basis for the Gini values used to measure disequity in a particular economy. These Gini values (40.8 in 2007) indicate that the United States is the third most inequitable economy among developed nations (behind Denmark and Switzerland).

More sophisticated models have also been proposed.<ref>{{cite web|url=https://www.newscientist.com/article.ns?id=mg18524904.300 |title=Why it is hard to share the wealth |work=New Scientist |date=March 12, 2005 |access-date=March 26, 2012}}</ref>

== Theoretical approaches == To model aspects of the distribution and holdings of wealth, many different theories have been used. Before the 1960s, data on this were collected mostly from wealth and estate tax records, with additional evidence gathered from small, unrepresentative examinations and other sources. The results from these sources tended to show that the distribution of wealth was highly unequal. That material inheritance played a major role in wealth differences and in the transmission of wealth status from generation to generation. There was also reason to believe that wealth inequality was shrinking over time, and the distribution's shape exhibited statistical regularities that could not have arisen by chance. Thus, early theoretical work on the distribution of wealth sought to explain statistical regularities and to comprehend the relationships among basic forces that could explain the high concentration of wealth and its declining trend over time.<ref name=":1">{{Cite journal|last1=Davies|first1=J.B.|last2=Shorrocks|first2=A.F.|date=2000|title=The distribution of wealth|journal=Handbook of Income Distribution|volume=1|pages=605–675|doi=10.1016/S1574-0056(00)80014-7}}</ref> John Maynard Keynes explored the impact of monetary policy on wealth distribution in ''A Tract on Monetary Reform''.<ref>{{Cite book |last1=Kappes |first1=Sylvio |url=https://books.google.com/books?id=dD60EAAAQBAJ&dq=%22monetary+reform%22+%22wealth+distribution%22&pg=PA167 |title=Central Banking, Monetary Policy and Income Distribution |last2=Rochon |first2=Louis-Philippe |last3=Vallet |first3=Guillaume |date=2023-03-02 |publisher=Edward Elgar Publishing |isbn=978-1-80037-193-4 |language=en}}</ref>

More lately, the research about wealth distribution has moved away from the worry with overall distributional characteristics, and in its place focuses more on the grounds of individual differences in the holdings of wealth.<ref name=":1" /> This change was caused partly because the importance of saving for retirement increased, and it is reflected in the vital role now assigned to the model of lifecycle savings developed by Modigliani and Brumberg<ref>{{Cite book|last1=Modigliani|first1=Franco|last2=Brumberg|first2=Richard|date=1954|chapter=Utility analysis and the consumption function: an interpretation of cross-section data|title=Post-Keynesian Economics (1962)|editor-last=Kurihara |editor-first=Kenneth K. |publisher=Rutgers University Press |pages=388–436 }}</ref> (1954), and Ando and Modigliani<ref>{{Cite journal|last1=Ando|first1=A.|last2=Modigliani|first2=F.|date=1963|title=The" life cycle" hypothesis of saving: Aggregate implications and tests|journal=The American Economic Review|volume=53|pages=55–84}}</ref> (1963). Another important progress has been the increase in availability and finesse in sets of microdata, which offer not just estimations of individuals' asset holdings and savings but also a variety of other household and personal characteristics that can assist in explaining the differences in wealth.<ref name=":1" />

== Wealth inequality == {{See also|Criticism of capitalism}} [[File:Homeless in san francisco mission district California (6086987323).jpg|thumb|A homeless individual sleeping on the street, next to a limousine]] '''Wealth inequality''' refers to the uneven distribution of wealth among individuals and entities. Although most research depends on written sources, archaeologists and anthropologists often view large houses as occupied by wealthy households.<ref>{{Cite journal |last1=McGuire |first1=R. H. |last2=Netting |first2=R. M. |date=1982 |title=Leveling Peasants? The Maintenance of Equality in a Swiss Alpine Community. |journal=American Ethnologist |volume=9 |issue=2 |pages=269–290|doi=10.1525/ae.1982.9.2.02a00040 }}</ref> The distribution of contemporaneous house sizes in a society (perhaps analyzed using the Gini coefficient) then can be regarded as a measure of wealth inequality. This approach has been used at least since 2014<ref>{{Cite journal |last1=Smith |first1=M. E. |last2=Dennehy |first2=T. |last3=Kamp-Whittaker |first3=A. |last4=Colon |first4=E. |last5=Harkness |first5=R. |date=2014 |title=Quantitative measures of wealth inequality in ancient central Mexican communities |journal=Advances in Archaeological Practice |volume=2 |issue=4 |pages=311–323|doi=10.7183/2326-3768.2.4.XX }}</ref> and has shown, for example, that ancient wealth disparities in Eurasia were greater than those in North America and in Mesoamerica following the earliest Neolithic period.<ref>{{Cite journal |last1=Kohler |first1=Timothy |last2=Smith |first2=Michael |last3=Bogaard |first3=Amy |last4=Feinman |first4=Gary |last5=Peterson |first5=Christian |last6=Betzenhauser |first6=Alleen |date=2017 |title=Greater post-Neolithic wealth disparities in Eurasia than in North America and Mesoamerica |journal=Nature |volume=551 |issue=7682 |pages=619–622|doi=10.1038/nature24646 |pmid=29143817 |pmc=5714260 |bibcode=2017Natur.551..619K }}</ref>

=== Global inequality statistics === [[File:Share of wealth globally.png|thumb|Share of wealth globally by year, as seen by Oxfam,<ref name=":2">{{cite web |date=January 18, 2016 |title=62 people own same as half world – Oxfam | Press releases | Oxfam GB |url=https://www.oxfam.org/en/pressroom/pressreleases/2016-01-18/62-people-own-same-half-world-reveals-oxfam-davos-report |access-date=September 10, 2016 |website=Oxfam.org.uk}}</ref> based on the net worth<ref name="Time">{{cite news |last=Davidson |first=Jacob |date=January 21, 2015 |title=Yes, Oxfam, the Richest 1% Have Most of the Wealth. But That Means Less Than You Think |magazine=Money |url=https://money.com/oxfam-richest-1-wealth-flawed/ |url-status=live |archive-url=https://web.archive.org/web/20220427140631/https://money.com/oxfam-richest-1-wealth-flawed/ |archive-date=April 27, 2022}}</ref>]]A study by the World Institute for Development Economics Research at United Nations University reports that the richest 1% of adults alone owned 40% of global assets in the year 2000, and that the richest 10% of adults accounted for 85% of the world total. The bottom half of the world's adult population owned 1% of global wealth.<ref name="un-wider">''The World Distribution of Household Wealth''. James B. Davies, Susanna Sandstrom, Anthony Shorrocks, and Edward N. Wolff. December 5, 2006.</ref> A 2006 study found that the richest 2% own more than half of global household assets.<ref name="really">[https://www.theglobeandmail.com/servlet/story/RTGAM.20061205.wxrich05/BNStory/International/home The rich really do own the world] December 5, 2006</ref> The Pareto distribution gives 52.8% owned by the upper 1%.

According to the OECD in 2012, the top 0.6% of the world's population (consisting of adults with more than US$1 million in assets) or the 42 million richest people in the world held 39.3% of world wealth. The next 4.4% (311 million people) held 32.3% of world wealth. The bottom 95% held 28.4% of world wealth. The large gaps in the report are reflected in the Gini index of 0.893, which is higher than the global income inequality gap measured in 2009 at 0.38.<ref>{{cite web |title=The World Factbook – Central Intelligence Agency |url=https://www.cia.gov/library/publications/the-world-factbook/fields/2172.html |archive-url=https://web.archive.org/web/20170716055851/https://www.cia.gov/library/publications/the-world-factbook/fields/2172.html |archive-date=July 16, 2017 |access-date=September 10, 2016 |website=Cia.gov}}</ref> For example, in 2012 the bottom 60% of the world population held the same wealth in 2012 as the people on Forbes' Richest list consisting of 1,226 richest billionaires of the world.

A 2021 Oxfam report found that collectively, the 10 richest men in the world owned more than the combined wealth of the bottom 3.1 billion people, almost half of the entire world population. Their combined wealth doubled during the pandemic.<ref>{{Cite web |date=January 19, 2022 |title=Inequality kills |url=https://www.oxfam.org/en/research/inequality-kills |access-date=April 20, 2022 |website=Oxfam International |language=en}}</ref><ref>{{Cite web |date=January 17, 2022 |title=World's 10 richest men see their wealth double during Covid pandemic |url=https://www.theguardian.com/business/2022/jan/17/world-10-richest-men-see-their-wealth-double-during-covid-pandemic |access-date=April 24, 2022 |website=the Guardian |language=en}}</ref><ref>{{Cite news |date=January 17, 2022 |title=Wealth of world's 10 richest men doubled in pandemic, Oxfam says |language=en-GB |work=BBC News |url=https://www.bbc.com/news/business-60015294 |access-date=April 24, 2022}}</ref>

'Global Wealth Report 2021', published by Credit Suisse, shows a substantial worldwide increase in wealth inequality during 2020. According to Credit Suisse, the wealth distribution pyramid in 2020 shows that the richest group of the adult population (1.1%) owns 45.8% of the total wealth. Compared with the 2013 wealth distribution pyramid, an overall increase of 4.8% is evident. The bottom half of the world's total adult population, the bottom quartile in the pyramid, owns only 1.3% of the total wealth. Again, compared with the 2013 wealth distribution pyramid, there is a 1.7% decrease. In conclusion, this comparison shows a substantial worldwide increase in wealth inequality over these years.

One of the main explanations for the ongoing increase in wealth inequality is the repercussions of the COVID-19 pandemic. Credit Suisse claims that the economic impact of the pandemic on employment and incomes in 2020 is likely to negatively affect the lowest groups of wealth holders, forcing them to draw more from their savings or take on higher debt. On the other hand, the top wealth groups appeared to be relatively unaffected by this negative trend. Moreover, they seemed to benefit from the lower interest rates' impact on share and house prices.<ref name=":3">{{Cite web |title=Global wealth report |url=https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html |access-date=April 27, 2022 |website=Credit Suisse |language=en}}</ref><ref name="credit-suisse1">{{cite web |title=Global Wealth Report 2013 |url=https://publications.credit-suisse.com/tasks/render/file/?fileID=BCDB1364-A105-0560-1332EC9100FF5C83 |url-status=dead |archive-url=https://web.archive.org/web/20150214155424/https://publications.credit-suisse.com/tasks/render/file/?fileID=BCDB1364-A105-0560-1332EC9100FF5C83 |archive-date=February 14, 2015 |access-date=June 30, 2016 |publisher=credit-suisse.com}}</ref>

According to the 'Global Wealth Report 2021' published by Credit Suisse, there were 56 million millionaires in the world in 2020, increasing by 5.2 million from a year earlier. The biggest number of dollar millionaires is reported in the USA, with 22 million millionaires (approximately 39% of the world total). This is far ahead of China, which holds second place with 9.4% of all global millionaires. The third place is currently being held by Japan, with 6.6% of all global millionaires.<ref name=":3" />

The ''World Inequality Report 2026'' stated that the wealthiest 0.001% alone—fewer than 60,000 individuals—control three times more wealth than half of humanity combined.<ref name=WIR_20251210>{{cite web |title=''World Inequality Report 2026'' |url=https://wir2026.wid.world/www-site/uploads/2025/12/World_Inequality_Report_2026.pdf |publisher=World Inequality Lab |archive-url=https://web.archive.org/web/20251210204752/https://wir2026.wid.world/www-site/uploads/2025/12/World_Inequality_Report_2026.pdf |archive-date=10 December 2025 |pages=12, 14 |date=10 December 2025 |url-status=live}}</ref>

====Real estate==== {{See also|Redlining}} While sizable numbers of households own no land, few have no income. For example, the top 10% of land owners (all corporations) in Baltimore, Maryland own 58% of the taxable land value. The bottom 10% of those who own any land own less than 1% of the total land value.<ref>Kromkowski, "Who owns Baltimore", CSE/HGFA, 2007.</ref> This form of analysis as well as Gini coefficient analysis has been used to support land value taxation.

=== Wealth distribution pyramid === thumb|Pyramid of global wealth distribution in 2013<ref name="credit-suisse1" /> In 2013, Credit Suisse prepared a ''wealth pyramid'' infographic (shown right). Personal assets were calculated in net worth, meaning wealth would be negated by having any mortgages.<ref name="Time" /> It has a large base of low wealth holders, alongside upper tiers occupied by progressively fewer people. In 2013, Credit Suisse estimated that 3.2 billion individuals – more than two-thirds of adults worldwide – had wealth below US$10,000. A further one billion (adult population) fall within the 10,000 – US$100,000 range. While the average wealth holding is modest in the base and middle segments of the pyramid, their total wealth amounts to US$40 trillion, underscoring the potential for novel consumer products and innovative financial services targeted at this often-neglected segment.<ref name="credit-suisse1" />

The pyramid shows that: * Half of the world's net wealth belongs to the top 1%, * The top 10% of adults hold 85%, while the bottom 90% hold the remaining 15% of the world's total wealth, * The top 30% of adults hold 97% of the total wealth.

==== Wealth distribution pyramid in 2020 ==== In 2020, Credit Suisse created an updated version of its wealth pyramid infographic. The infographic was constructed similarly to the 2013 pyramid; thus, personal assets were included in net worth. In 2020, Credit Suisse estimated that approximately 2.88 billion people (55% of the adult population) had less than US$10,000 in wealth. Further, 1.7 billion individuals (38.2% of the adult population) have wealth in the range of US$ 10,000 –US$100,000. To continue, 583 million people have wealth within the range of 100,000 – US$1,000,000, and approximately 56 million people (1.1% of the adult population) have wealth over US$1,000,000.<ref name=":3" />

==== Comparison of 2013 and 2020 pyramids ==== Vast differences between the 2013 and 2020 infographics are evident. For the first time, more than 1% of all global adults have wealth over US$1,000,000. Credit Suisse explains in the 'Global Wealth Report 2021' that this increase reflects the economic disruption caused by the pandemic and the disconnect between improvements in households' financial and real assets. However, the biggest difference is in the US$10,000–US$100,000 segment. Since 2013, there has been an increase of almost 10% of total adult population. According to Credit Suisse, the number of adults in this segment tripled since 2000. Credit Suisse attributes this increase to the growing prosperity of emerging economies, especially China, and the expansion of the middle class in the developing world. The upper-middle segment, with wealth in the range of US$100,000–US$1,000,000, has increased by 3.4%. In the report, Credit Suisse states that the middle class in developed countries typically belongs to this group.<ref name=":3" />

=== Wealth outlook for 2020-2025 === According to the 'Global Wealth Report 2021', published by Credit Suisse, global wealth is projected to rise by 39% over the next five years, reaching US$583 trillion by 2025. Wealth per adult is also projected to increase by 31%, and so is the number of global millionaires. The wealth pyramid, an infographic used to determine wealth distribution, will also change. The bottom segment covering adults with a net worth below US$10,000 will likely decrease by approximately 108 million over the next five years. The lower-middle segment of the pyramid, comprising adults with a net worth between US$10,000 and US$100,000, is projected to increase by 237 million adults. Most of these new members are most likely to be from lower-income countries. The upper-middle segment, comprising adults with wealth between US$100,000 and US$1 million, is projected to grow by 178 million adults. Most of these new members (approximately 114 million) are likely to come from upper-middle-income countries. The number of global millionaires is also projected to increase. According to estimates from Credit Suisse, the number of global millionaires could exceed 84 million by 2025, an increase of almost 28 million from 2020. The number of millionaires will not only increase in developed countries such as the USA and other European countries, but it is also expected to rise rapidly in lower-income countries. The biggest increase is expected in China, with a 92.7% change, representing about 4.8 million new dollar-millionaires. As a consequence, the number of Ultra High Net Worth Individuals (UHNWI) with net worth exceeding US$50 million will also increase.<ref name=":3" />

=== Gini Coefficient === The Gini coefficient (or Gini index) is an indicator often used to measure wealth inequality. A Gini coefficient of 0 reflects perfect equality, where all income or wealth values are the same. In contrast, a Gini coefficient of 1 (or 100%) reflects maximal inequality among values, a situation where a single individual has all the income while all others have none.<ref>{{Cite web |title=United States Census Bureau |url=https://www.census.gov/population/www/cps/cpsdef.html}}</ref> According to the Credit Suisse 'Global Wealth Report 2021', Brunei had the highest Gini coefficient in 2021 (91.6%); therefore, the wealth distribution in Brunei is vastly unequal. Slovakia had the lowest Gini coefficient in 2021 (50.3%) among all countries, making it the most equal country in terms of wealth distribution. Compared with the 2019 Credit Suisse report, wealth inequality has increased. This may be the result of the COVID-19 pandemic's repercussions. The biggest increase was recorded in Brazil. The Gini coefficient was 88.2% in 2019 and 89% in 2021, an increase of 0.8 percentage points over this period.<ref name=":4">Source [https://www.credit-suisse.com/about-us/en/reports-research/global-wealth-report.html Credit Suisse, Research Institute – Global Wealth Databook 2021]</ref>

The following table was created from information provided by the Credit Suisse Research Institute's "Global Wealth Databook", Table 3-1, published in 2021.<ref name=":4" />

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{| class="wikitable sortable" style="text-align:right;" |- ! rowspan="2" | Country ! rowspan="2" | Adults (In 1,000) ! colspan="2" | Wealth per adult (USD) ! colspan="4" | Distribution of adults (%) by wealth range (USD) ! rowspan="2" | Gini (%) |- ! Mean ! Median ! Under 10k ! 10k – 100k ! 100k – 1M ! Over 1M |- | style="text-align:left" | {{flaglist|Afghanistan}}|| 18,356 || 1,744 || 734 || 97.6 || 2.4 || 0.1 || 0.0 || 72.8 |- | style="text-align:left" | {{flaglist|Albania}}|| 2,187 || 30,524 || 15,363 || 41.0 || 54.2 || 4.7 || 0.1 || 68.2 |- | style="text-align:left" | {{flaglist|Algeria}}|| 27,620 || 8,871 || 2,302 || 87.0 || 11.7 || 1.2 || 0.1 || 84.8 |- | style="text-align:left" | {{flaglist|Angola}}|| 14,339 || 3,529 || 1,131 || 93.5 || 6.2 || 0.2 || 0.0 || 80.6 |- | style="text-align:left" | {{flaglist|Argentina}}|| 30,799 || 7,224 || 2,157 || 88.2 || 11.2 || 0.6 || 0.0 || 81.2 |- | style="text-align:left" | {{flaglist|Armenia}}|| 2,176 || 22,573 || 9,411 || 52.3 || 44.0 || 3.5 || 0.1 || 73.0 |- | style="text-align:left" | {{flaglist|Australia}}|| 19,159 || 483,755 || 238,072 || 9.8 || 20.7 || 60.0 || 9.4 || 65.6 |- | style="text-align:left" | {{flaglist|Austria}}|| 7,271 || 290,348 || 91,833 || 14.2 || 36.9 || 44.1 || 4.8 || 73.5 |- | style="text-align:left" | {{flaglist|Azerbaijan}}|| 7,155 || 11,926 || 5,022 || 73.5 || 25.2 || 1.3 || 0.0 || 72.7 |- | style="text-align:left" | {{flaglist|Bahamas}}|| 278 || 56,737 || 7,507 || 54.0 || 39.7 || 5.7 || 0.6 || 91.4 |- | style="text-align:left" | {{flaglist|Bahrain}}|| 1,318 || 87,559 || 14,520 || 45.0 || 48.0 || 6.1 || 0.9 || 88.9 |- | style="text-align:left" | {{flaglist|Bangladesh}}|| 106,060 || 7,837 || 3,062 || 84.6 || 14.6 || 0.7 || 0.0 || 75.2 |- | style="text-align:left" | {{flaglist|Barbados}}|| 221 || 63,261 || 21,071 || 41.0 || 46.0 || 12.4 || 0.6 || 80.4 |- | style="text-align:left" | {{flaglist|Belarus}}|| 7,367 || 23,278 || 12,168 || 45.9 || 51.3 || 2.8 || 0.1 || 66.7 |- | style="text-align:left" | {{flaglist|Belgium}}|| 8,993 || 351,327 || 230,548 || 11.9 || 20.1 || 62.3 || 5.7 || 60.3 |- | style="text-align:left" | {{flaglist|Belize}}|| 245 || 10,364 || 3,015 || 82.0 || 16.6 || 1.4 || 0.0 || 83.4 |- | style="text-align:left" | {{flaglist|Benin}}|| 5,839 || 2,558 || 890 || 95.6 || 4.3 || 0.1 || 0.0 || 78.2 |- | style="text-align:left" | {{flaglist|Bolivia}}|| 7,088 || 12,286 || 3,804 || 78.1 || 20.5 || 1.3 || 0.1 || 81.0 |- | style="text-align:left" | {{flaglist|Bosnia and Herzegovina}}|| 2,637 || 30,597 || 15,283 || 41.0 || 54.1 || 4.8 || 0.1 || 68.6 |- | style="text-align:left" | {{flaglist|Botswana}}|| 1,358 || 15,598 || 3,680 || 80.0 || 16.8 || 3.1 || 0.1 || 87.3 |- | style="text-align:left" | {{flaglist|Brazil}}|| 153,307 || 18,272 || 3,469 || 79.5 || 17.5 || 2.8 || 0.1 || 89.0 |- | style="text-align:left" | {{flaglist|British Caribbean}}|| 567 || 45,109 || 14,684 || 44.0 || 47.7 || 7.9 || 0.4 || 80.8 |- | style="text-align:left" | {{flaglist|Brunei}}|| 309 || 39,098 || 5,122 || 64.0 || 32.1 || 3.5 || 0.4 || 91.6 |- | style="text-align:left" | {{flaglist|Bulgaria}}|| 5,586 || 36,443 || 17,403 || 38.7 || 54.9 || 6.2 || 0.2 || 70.1 |- | style="text-align:left" | {{flaglist|Burkina Faso}}|| 9,480 || 1,681 || 622 || 98.0 || 1.9 || 0.1 || 0.0 || 76.8 |- | style="text-align:left" | {{flaglist|Burundi}}|| 5,381 || 728 || 281 || 99.5 || 0.5 || 0.0 || 0.0 || 75.1 |- | style="text-align:left" | {{flaglist|Cambodia}}|| 10,180 || 5,895 || 2,031 || 90.7 || 8.7 || 0.6 || 0.0 || 78.7 |- | style="text-align:left" | {{flaglist|Cameroon}}|| 12,716 || 3,042 || 941 || 94.3 || 5.5 || 0.2 || 0.0 || 81.6 |- | style="text-align:left" | {{flaglist|Canada}}|| 29,934 || 332,323 || 125,688 || 20.7 || 25.1 || 48.6 || 5.6 || 71.9 |- | style="text-align:left" | {{flaglist|Central African Republic}}|| 2,161 || 840 || 212 || 98.8 || 1.2 || 0.0 || 0.0 || 85.9 |- | style="text-align:left" | {{flaglist|Chad}}|| 7,059 || 1,117 || 355 || 98.7 || 1.3 || 0.1 || 0.0 || 80.6 |- | style="text-align:left" | {{flaglist|Chile}}|| 14,259 || 53,591 || 17,747 || 39.1 || 51.6 || 8.8 || 0.5 || 79.7 |- | style="text-align:left" | {{flaglist|China}}|| 1,104,956 || 67,771 || 24,067 || 20.9 || 66.1 || 12.5 || 0.5 || 70.4 |- | style="text-align:left" | {{flaglist|Colombia}}|| 35,612 || 16,928 || 4,854 || 72.0 || 25.4 || 2.5 || 0.1 || 82.7 |- | style="text-align:left" | {{flaglist|Comoros}}|| 447 || 5,397 || 1,466 || 91.5 || 7.9 || 0.6 || 0.0 || 84.8 |- | style="text-align:left" | {{flaglist|Congo, Dem. Rep.}}|| 39,740 || 1,240 || 356 || 98.3 || 1.6 || 0.1 || 0.0 || 83.2 |- | style="text-align:left" | {{flaglist|Congo, Rep.}}|| 2,707 || 2,180 || 582 || 95.6 || 4.2 || 0.1 || 0.0 || 84.7 |- | style="text-align:left" | {{flaglist|Costa Rica}}|| 3,696 || 44,337 || 14,662 || 44.0 || 47.4 || 8.4 || 0.3 || 79.9 |- | style="text-align:left" | {{flaglist|Croatia}}|| 3,303 || 69,140 || 34,945 || 27.0 || 57.0 || 15.5 || 0.5 || 68.5 |- | style="text-align:left" | {{flaglist|Cyprus}}|| 679 || 142,304 || 35,300 || 23.0 || 57.0 || 18.3 || 1.7 || 80.7 |- | style="text-align:left" | {{flaglist|Czechia}}|| 8,528 || 78,103 || 23,794 || 29.6 || 55.7 || 14.0 || 0.7 || 77.7 |- | style="text-align:left" | {{flaglist|Denmark}}|| 4,557 || 376,069 || 165,622 || 15.4 || 25.4 || 52.5 || 6.7 || 73.6 |- | style="text-align:left" | {{flaglist|Djibouti}}|| 618 || 3,112 || 1,077 || 94.0 || 6.0 || 0.0 || 0.0 || 78.8 |- | style="text-align:left" | {{flaglist|Dutch Caribbean}}|| 258 || 40,909 || 16,810 || 40.0 || 52.7 || 7.1 || 0.2 || 69.1 |- | style="text-align:left" | {{flaglist|Ecuador}}|| 11,361 || 17,151 || 5,444 || 69.9 || 27.9 || 2.1 || 0.1 || 80.8 |- | style="text-align:left" | {{flaglist|Egypt}}|| 59,547 || 19,468 || 6,329 || 66.5 || 30.7 || 2.6 || 0.1 || 79.2 |- | style="text-align:left" | {{flaglist|El Salvador}}|| 4,201 || 34,003 || 11,372 || 47.6 || 46.0 || 6.2 || 0.2 || 79.1 |- | style="text-align:left" | {{flaglist|Equatorial Guinea}}|| 776 || 18,246 || 4,561 || 77.0 || 18.8 || 4.1 || 0.1 || 86.3 |- | style="text-align:left" | {{flaglist|Eritrea}}|| 1,728 || 2,846 || 1,086 || 95.2 || 4.7 || 0.1 || 0.0 || 75.7 |- | style="text-align:left" | {{flaglist|Estonia}}|| 1,044 || 77,817 || 38,901 || 30.5 || 53.5 || 15.3 || 0.7 || 73.8 |- | style="text-align:left" | {{flaglist|Ethiopia}}|| 57,104 || 3,540 || 1,527 || 94.4 || 5.4 || 0.2 || 0.0 || 71.1 |- | style="text-align:left" | {{flaglist|Fiji}}|| 564 || 15,708 || 5,764 || 69.0 || 28.3 || 2.6 || 0.1 || 77.4 |- | style="text-align:left" | {{flaglist|Finland}}|| 4,373 || 167,711 || 73,775 || 27.8 || 35.2 || 35.1 || 1.9 || 74.0 |- | style="text-align:left" | {{flaglist|France}}|| 49,967 || 299,355 || 133,559 || 14.8 || 27.0 || 53.3 || 4.9 || 70.0 |- | style="text-align:left" | {{flaglist|French Caribbean}}|| 631 || 68,443 || 23,740 || 36.0 || 44.0 || 19.5 || 0.5 || 73.8 |- | style="text-align:left" | {{flaglist|Gabon}}|| 1,216 || 13,696 || 4,685 || 74.0 || 24.5 || 1.4 || 0.1 || 79.3 |- | style="text-align:left" | {{flaglist|Gambia}}|| 1,115 || 2,500 || 658 || 94.9 || 4.9 || 0.2 || 0.0 || 84.9 |- | style="text-align:left" | {{flaglist|Georgia}}|| 2,959 || 14,162 || 4,223 || 77.7 || 20.7 || 1.5 || 0.1 || 81.3 |- | style="text-align:left" | {{flaglist|Germany}}|| 68,015 || 268,681 || 65,374 || 10.6 || 45.2 || 39.8 || 4.3 || 77.9 |- | style="text-align:left" | {{flaglist|Ghana}}|| 16,617 || 6,132 || 2,198 || 88.5 || 11.1 || 0.4 || 0.0 || 77.5 |- | style="text-align:left" | {{flaglist|Greece}}|| 8,462 || 104,603 || 57,595 || 22.1 || 49.3 || 27.7 || 0.9 || 65.7 |- | style="text-align:left" | {{flaglist|Guinea}}|| 6,078 || 2,942 || 938 || 94.5 || 5.4 || 0.2 || 0.0 || 80.8 |- | style="text-align:left" | {{flaglist|Guinea-Bissau}}|| 949 || 1,828 || 670 || 97.0 || 3.0 || 0.0 || 0.0 || 77.6 |- | style="text-align:left" | {{flaglist|Guyana}}|| 497 || 12,280 || 4,637 || 74.0 || 24.6 || 1.4 || 0.0 || 76.5 |- | style="text-align:left" | {{flaglist|Haiti}}|| 6,621 || 767 || 193 || 99.2 || 0.7 || 0.0 || 0.0 || 85.2 |- | style="text-align:left" | {{flaglist|Hong Kong}}|| 6,292 || 503,335 || 173,768 || 13.7 || 23.7 || 54.3 || 8.3 || 74.6 |- | style="text-align:left" | {{flaglist|Hungary}}|| 7,769 || 53,664 || 24,126 || 21.4 || 67.6 || 10.7 || 0.3 || 66.5 |- | style="text-align:left" | {{flaglist|Iceland}}|| 255 || 337,787 || 231,462 || 6.0 || 18.0 || 70.7 || 5.3 || 50.9 |- | style="text-align:left" | {{flaglist|India}}|| 900,443 || 14,252 || 3,194 || 77.2 || 21.1 || 1.7 || 0.1 || 82.3 |- | style="text-align:left" | {{flaglist|Indonesia}}|| 180,782 || 17,693 || 4,693 || 67.2 || 30.8 || 1.9 || 0.1 || 77.7 |- | style="text-align:left" | {{flaglist|Iran}}|| 57,987 || 22,249 || 7,621 || 59.1 || 37.1 || 3.7 || 0.1 || 78.6 |- | style="text-align:left" | {{flaglist|Iraq}}|| 21,247 || 14,506 || 6,378 || 68.3 || 30.1 || 1.6 || 0.1 || 71.0 |- | style="text-align:left" | {{flaglist|Ireland}}|| 3,619 || 266,153 || 99,028 || 30.8 || 19.7 || 44.5 || 5.0 || 80.0 |- | style="text-align:left" | {{flaglist|Israel}}|| 5,626 || 228,268 || 80,315 || 15.8 || 41.2 || 40.1 || 2.9 || 73.4 |- | style="text-align:left" | {{flaglist|Italy}}|| 49,746 || 239,244 || 118,885 || 15.5 || 30.1 || 51.4 || 3.0 || 66.5 |- | style="text-align:left" | {{flaglist|Jamaica}}|| 2,041 || 19,893 || 5,976 || 66.7 || 30.3 || 2.9 || 0.1 || 82.0 |- | style="text-align:left" | {{flaglist|Japan}}|| 104,953 || 256,596 || 122,980 || 11.0 || 32.6 || 52.9 || 3.5 || 64.4 |- | style="text-align:left" | {{flaglist|Jordan}}|| 5,866 || 28,316 || 10,842 || 48.3 || 47.1 || 4.5 || 0.2 || 75.9 |- | style="text-align:left" | {{flaglist|Kazakhstan}}|| 12,226 || 33,463 || 12,029 || 46.3 || 49.3 || 4.2 || 0.2 || 76.4 |- | style="text-align:left" | {{flaglist|Kenya}}|| 27,473 || 12,313 || 3,683 || 79.6 || 18.8 || 1.5 || 0.1 || 82.2 |- | style="text-align:left" | {{flaglist|Korea, South}}|| 42,490 || 211,369 || 89,671 || 14.8 || 38.3 || 44.4 || 2.5 || 67.6 |- | style="text-align:left" | {{flaglist|Kuwait}}|| 3,146 || 129,890 || 28,698 || 42.8 || 44.0 || 10.7 || 2.5 || 86.5 |- | style="text-align:left" | {{flaglist|Kyrgyzstan}}|| 3,927 || 5,816 || 2,238 || 89.7 || 9.8 || 0.5 || 0.0 || 75.7 |- | style="text-align:left" | {{flaglist|Laos}}|| 4,288 || 7,379 || 1,610 || 91.6 || 7.0 || 1.3 || 0.0 || 87.9 |- | style="text-align:left" | {{flaglist|Latvia}}|| 1,477 || 70,454 || 33,884 || 36.0 || 50.5 || 12.7 || 0.8 || 80.9 |- | style="text-align:left" | {{flaglist|Lebanon}}|| 4,548 || 55,007 || 18,159 || 40.6 || 50.5 || 8.4 || 0.5 || 79.7 |- | style="text-align:left" | {{flaglist|Lesotho}}|| 1,243 || 1,226 || 264 || 97.8 || 2.2 || 0.1 || 0.0 || 88.6 |- | style="text-align:left" | {{flaglist|Liberia}}|| 2,502 || 4,453 || 1,464 || 91.9 || 7.8 || 0.3 || 0.0 || 80.1 |- | style="text-align:left" | {{flaglist|Libya}}|| 4,440 || 17,198 || 6,512 || 67.0 || 31.0 || 1.9 || 0.1 || 76.0 |- | style="text-align:left" | {{flaglist|Lithuania}}|| 2,166 || 63,500 || 29,679 || 29.3 || 58.0 || 12.2 || 0.5 || 71.0 |- | style="text-align:left" | {{flaglist|Luxembourg}}|| 498 || 477,306 || 259,899 || 13.0 || 19.0 || 59.2 || 8.8 || 67.0 |- | style="text-align:left" | {{flaglist|Madagascar}}|| 13,812 || 1,962 || 666 || 96.9 || 3.0 || 0.1 || 0.0 || 79.3 |- | style="text-align:left" | {{flaglist|Malawi}}|| 8,887 || 2,045 || 606 || 96.2 || 3.7 || 0.1 || 0.0 || 82.4 |- | style="text-align:left" | {{flaglist|Malaysia}}|| 22,315 || 29,287 || 8,583 || 55.0 || 41.1 || 3.7 || 0.2 || 82.9 |- | style="text-align:left" | {{flaglist|Maldives}}|| 409 || 25,511 || 8,519 || 56.0 || 39.3 || 4.5 || 0.2 || 79.8 |- | style="text-align:left" | {{flaglist|Mali}}|| 8,625 || 2,424 || 869 || 96.0 || 3.9 || 0.1 || 0.0 || 77.6 |- | style="text-align:left" | {{flaglist|Malta}}|| 358 || 148,934 || 84,390 || 13.0 || 45.0 || 40.6 || 1.4 || 61.7 |- | style="text-align:left" | {{flaglist|Mauritania}}|| 2,370 || 2,788 || 1,037 || 95.2 || 4.7 || 0.1 || 0.0 || 76.3 |- | style="text-align:left" | {{flaglist|Mauritius}}|| 968 || 63,372 || 27,456 || 31.0 || 56.0 || 12.5 || 0.5 || 72.1 |- | style="text-align:left" | {{flaglist|Melanesia}}|| 711 || 31,106 || 12,183 || 46.0 || 48.6 || 5.2 || 0.2 || 75.8 |- | style="text-align:left" | {{flaglist|Mexico}}|| 85,136 || 42,689 || 13,752 || 44.7 || 46.9 || 8.1 || 0.3 || 80.5 |- | style="text-align:left" | {{flaglist|Micronesia}}|| 341 || 13,193 || 4,876 || 74.0 || 23.9 || 2.1 || 0.0 || 77.9 |- | style="text-align:left" | {{flaglist|Moldova}}|| 3,188 || 15,491 || 7,577 || 61.8 || 36.5 || 1.7 || 0.0 || 69.4 |- | style="text-align:left" | {{flaglist|Mongolia}}|| 2,053 || 6,324 || 2,546 || 88.0 || 11.5 || 0.5 || 0.0 || 74.4 |- | style="text-align:left" | {{flaglist|Montenegro}}|| 476 || 60,310 || 30,739 || 29.0 || 57.0 || 13.6 || 0.4 || 68.4 |- | style="text-align:left" | {{flaglist|Morocco}}|| 24,654 || 13,459 || 3,874 || 78.4 || 19.7 || 1.9 || 0.1 || 81.9 |- | style="text-align:left" | {{flaglist|Mozambique}}|| 14,186 || 1,003 || 345 || 98.9 || 1.0 || 0.1 || 0.0 || 79.1 |- | style="text-align:left" | {{flaglist|Myanmar}}|| 35,734 || 5,025 || 2,458 || 91.7 || 8.0 || 0.3 || 0.0 || 67.0 |- | style="text-align:left" | {{flaglist|Namibia}}|| 1,375 || 15,294 || 3,677 || 80.5 || 16.4 || 3.0 || 0.1 || 86.6 |- | style="text-align:left" | {{flaglist|Nepal}}|| 17,887 || 4,056 || 1,437 || 93.3 || 6.3 || 0.3 || 0.0 || 78.1 |- | style="text-align:left" | {{flaglist|Netherlands}}|| 13,462 || 377,092 || 136,105 || 13.6 || 29.4 || 49.3 || 7.7 || 75.3 |- | style="text-align:left" | {{flaglist|New Zealand}}|| 3,600 || 348,198 || 171,624 || 21.2 || 20.0 || 52.5 || 6.3 || 69.9 |- | style="text-align:left" | {{flaglist|Nicaragua}}|| 4,107 || 12,239 || 3,694 || 78.2 || 20.5 || 1.3 || 0.1 || 81.0 |- | style="text-align:left" | {{flaglist|Niger}}|| 9,739 || 1,287 || 492 || 98.7 || 1.3 || 0.1 || 0.0 || 75.6 |- | style="text-align:left" | {{flaglist|Nigeria}}|| 95,931 || 6,451 || 1,474 || 91.7 || 7.6 || 0.7 || 0.0 || 85.8 |- | style="text-align:left" | {{flaglist|Norway}}|| 4,184 || 275,880 || 117,798 || 28.0 || 19.0 || 48.8 || 4.2 || 78.5 |- | style="text-align:left" | {{flaglist|Oman}}|| 3,765 || 39,434 || 9,886 || 50.5 || 43.1 || 6.0 || 0.4 || 86.7 |- | style="text-align:left" | {{flaglist|Pakistan}}|| 123,522 || 5,258 || 2,187 || 90.5 || 9.2 || 0.4 || 0.0 || 73.2 |- | style="text-align:left" | {{flaglist|Panama}}|| 2,843 || 43,979 || 13,147 || 45.3 || 46.6 || 7.8 || 0.3 || 82.5 |- | style="text-align:left" | {{flaglist|Papua New Guinea}}|| 4,941 || 6,710 || 1,790 || 91.3 || 7.7 || 1.0 || 0.0 || 84.3 |- | style="text-align:left" | {{flaglist|Paraguay}}|| 4,454 || 11,962 || 3,644 || 78.8 || 19.9 || 1.2 || 0.1 || 81.6 |- | style="text-align:left" | {{flaglist|Peru}}|| 22,530 || 17,017 || 5,445 || 70.4 || 27.4 || 2.1 || 0.1 || 80.1 |- | style="text-align:left" | {{flaglist|Philippines}}|| 66,960 || 15,290 || 3,155 || 83.1 || 14.8 || 2.0 || 0.1 || 86.9 |- | style="text-align:left" | {{flaglist|Poland}}|| 30,315 || 67,477 || 23,550 || 19.8 || 64.8 || 14.9 || 0.5 || 70.7 |- | style="text-align:left" | {{flaglist|Polynesia}}|| 423 || 37,998 || 14,076 || 44.0 || 49.3 || 6.4 || 0.3 || 77.9 |- | style="text-align:left" | {{flaglist|Portugal}}|| 8,339 || 142,537 || 61,306 || 23.2 || 45.1 || 30.0 || 1.6 || 70.5 |- | style="text-align:left" | {{flaglist|Qatar}}|| 2,396 || 146,730 || 83,680 || 12.0 || 45.3 || 41.7 || 1.0 || 58.1 |- | style="text-align:left" | {{flaglist|Romania}}|| 15,208 || 50,009 || 23,675 || 32.1 || 58.5 || 9.1 || 0.3 || 70.1 |- | style="text-align:left" | {{flaglist|Russia}}|| 111,845 || 27,162 || 5,431 || 72.8 || 23.8 || 3.1 || 0.2 || 87.8 |- | style="text-align:left" | {{flaglist|Rwanda}}|| 6,581 || 4,188 || 1,266 || 92.8 || 6.9 || 0.3 || 0.0 || 81.9 |- | style="text-align:left" | {{flaglist|Sao Tome and Principe}}|| 104 || 4,029 || 1,702 || 92.4 || 7.3 || 0.2 || 0.0 || 73.1 |- | style="text-align:left" | {{flaglist|Saudi Arabia}}|| 24,186 || 68,697 || 15,495 || 46.4 || 44.4 || 8.2 || 1.0 || 86.7 |- | style="text-align:left" | {{flaglist|Senegal}}|| 7,975 || 4,702 || 1,570 || 91.4 || 8.3 || 0.3 || 0.0 || 79.7 |- | style="text-align:left" | {{flaglist|Serbia}}|| 5,480 || 31,705 || 14,954 || 41.7 || 52.9 || 5.3 || 0.1 || 70.6 |- | style="text-align:left" | {{flaglist|Seychelles}}|| 69 || 63,427 || 24,651 || 36.0 || 51.0 || 12.5 || 0.5 || 75.9 |- | style="text-align:left" | {{flaglist|Sierra Leone}}|| 3,937 || 995 || 370 || 99.0 || 0.9 || 0.0 || 0.0 || 76.7 |- | style="text-align:left" | {{flaglist|Singapore}}|| 4,887 || 332,995 || 86,717 || 16.2 || 38.6 || 39.7 || 5.5 || 78.3 |- | style="text-align:left" | {{flaglist|Slovakia}}|| 4,346 || 68,059 || 45,853 || 11.6 || 69.8 || 18.4 || 0.2 || 50.3 |- | style="text-align:left" | {{flaglist|Slovenia}}|| 1,672 || 120,173 || 67,961 || 18.0 || 53.0 || 28.2 || 0.8 || 67.1 |- | style="text-align:left" | {{flaglist|South Africa}}|| 37,590 || 20,308 || 4,523 || 75.8 || 20.2 || 3.9 || 0.2 || 88.0 |- | style="text-align:left" | {{flaglist|Spain}}|| 37,798 || 227,122 || 105,831 || 16.7 || 31.6 || 48.6 || 3.0 || 69.2 |- | style="text-align:left" | {{flaglist|Sri Lanka}}|| 14,732 || 23,832 || 8,802 || 54.3 || 42.0 || 3.7 || 0.1 || 76.8 |- | style="text-align:left" | {{flaglist|Sudan}}|| 21,941 || 1,014 || 383 || 99.0 || 0.9 || 0.1 || 0.0 || 75.9 |- | style="text-align:left" | {{flaglist|Suriname}}|| 382 || 5,644 || 1,349 || 91.2 || 8.1 || 0.7 || 0.0 || 87.1 |- | style="text-align:left" | {{flaglist|Sweden}}|| 7,794 || 336,166 || 89,846 || 34.0 || 18.4 || 40.3 || 7.3 || 87.2 |- | style="text-align:left" | {{flaglist|Switzerland}}|| 6,958 || 673,962 || 146,733 || 11.9 || 33.7 || 43.2 | 11.2 || 78.1 |- | style="text-align:left" | {{flaglist|Syria}}|| 10,811 || 2,197 || 807 || 96.3 || 3.6 || 0.1 || 0.0 || 77.2 |- | style="text-align:left" | {{flaglist|Taiwan}}|| 19,633 || 238,862 || 93,044 || 13.9 || 38.6 || 44.4 || 3.1 || 70.8 |- | style="text-align:left" | {{flaglist|Tajikistan}}|| 5,227 || 4,390 || 1,844 || 92.4 || 7.3 || 0.3 || 0.0 || 73.1 |- | style="text-align:left" | {{flaglist|Tanzania}}|| 27,744 || 3,647 || 1,433 || 93.7 || 6.1 || 0.2 || 0.0 || 74.5 |- | style="text-align:left" | {{flaglist|Thailand}}|| 54,054 || 25,292 || 8,036 || 55.5 || 41.9 || 2.5 || 0.2 || 77.1 |- | style="text-align:left" | {{flaglist|Timor-Leste}}|| 689 || 5,185 || 2,838 || 91.4 || 8.3 || 0.3 || 0.0 || 62.6 |- | style="text-align:left" | {{flaglist|Togo}}|| 4,084 || 1,484 || 468 || 98.0 || 2.0 || 0.1 || 0.0 || 81.2 |- | style="text-align:left" | {{flaglist|Trinidad and Tobago}}|| 1,032 || 44,182 || 15,649 || 42.5 || 49.0 || 8.2 || 0.3 || 78.0 |- | style="text-align:left" | {{flaglist|Tunisia}}|| 8,207 || 17,550 || 6,177 || 67.4 || 30.2 || 2.3 || 0.1 || 77.8 |- | style="text-align:left" | {{flaglist|Turkey}}|| 57,768 || 27,466 || 8,001 || 57.6 || 38.8 || 3.4 || 0.2 || 81.8 |- | style="text-align:left" | {{flaglist|Turkmenistan}}|| 3,722 || 20,328 || 9,030 || 54.0 || 43.2 || 2.7 || 0.1 || 70.6 |- | style="text-align:left" | {{flaglist|Uganda}}|| 19,830 || 1,994 || 646 || 96.6 || 3.3 || 0.1 || 0.0 || 80.4 |- | style="text-align:left" | {{flaglist|Ukraine}}|| 34,639 || 13,104 || 2,529 || 79.1 || 19.5 || 1.3 || 0.1 || 84.4 |- | style="text-align:left" | {{flaglist|United Arab Emirates}}|| 8,053 || 115,476 || 21,613 || 45.1 || 46.0 || 6.8 || 2.1 || 88.8 |- | style="text-align:left" | {{flaglist|United Kingdom}}|| 52,568 || 290,754 || 131,522 || 18.0 || 27.8 || 49.5 || 4.7 || 71.7 |- | style="text-align:left" | {{flaglist|United States}}|| 249,969 || 505,421 || 79,274 || 26.3 || 28.5 || 36.4 || 8.8 || 85.0 |- | style="text-align:left" | {{flaglist|Uruguay}}|| 2,530 || 60,914 || 22,088 || 37.0 || 51.3 || 11.2 || 0.4 || 77.2 |- | style="text-align:left" | {{flaglist|Venezuela}}|| 18,359 || 21,040 || 7,341 || 60.5 || 36.8 || 2.5 || 0.1 || 78.1 |- | style="text-align:left" | {{flaglist|Vietnam}}|| 68,565 || 14,075 || 4,559 || 76.3 || 21.9 || 1.8 || 0.1 || 80.2 |- | style="text-align:left" | {{flaglist|Yemen}}|| 15,281 || 5,581 || 1,223 || 93.0 || 6.2 || 0.8 || 0.0 || 88.0 |- | style="text-align:left" | {{flaglist|Zambia}}|| 8,331 || 3,068 || 692 || 94.3 || 5.5 || 0.2 || 0.0 || 87.7 |- | style="text-align:left" | {{flaglist|Zimbabwe}}|| 7,086 || 7,131 || 2,356 || 86.9 || 12.5 || 0.6 || 0.0 || 79.8 |}

===Geographical distribution=== {{Main|Wealth distribution by country|List of sovereign states by wealth inequality|List of countries by income inequality}}

Wealth is unevenly distributed across regions of the world. At the end of the 20th century, wealth was concentrated among the G8, Western industrialized nations, several Asian nations, and OPEC nations. In the 21st century, wealth remains concentrated among the G8, with the United States of America leading at 30.2%, along with other developed countries, several Asia-Pacific countries, and OPEC countries.[[File:Countries by total wealth (trillions USD), Credit Suisse.png|thumb|270px|Countries by total wealth (trillions USD), Credit Suisse]] <gallery> File:Wdpiechartppp2000.gif|World distribution of wealth by country (PPP) File:Worldwealthdistribution2000PPP.gif|World distribution of wealth by region (PPP) File:Wdpiechartexchangerates2000.gif|World distribution of wealth by country (exchange rates) File:Worldwealthdistributionexchangerates.gif|World distribution of wealth by region (exchange rates) </gallery>

====By region==== {| class="wikitable" |- ! rowspan=3 | Region ! colspan=5 | Proportion of world (%)<ref name="Domhoff" /><ref>Data for the following table obtained from [http://www.wider.unu.edu/events/past-events/2006-events/en_GB/05-12-2006/ UNU-WIDER World Distribution of Household Wealth Report] {{Webarchive|url=https://web.archive.org/web/20100716052041/http://www.wider.unu.edu/events/past-events/2006-events/en_GB/05-12-2006/ |date=July 16, 2010 }} ([http://repositories.cdlib.org/cgirs/mgi/mgi-5/ The University of California also hosts a copy of the report])</ref> |- ! rowspan=2 | Population ! colspan=2 | Net worth ! colspan=2 | GDP |- ! PPP ! Exchange rates ! PPP ! Exchange rates |- | North America | 5.2 | 27.1 | 34.4 | 23.9 | 33.7 |- | Central/South America | 8.5 | 6.5 | 4.3 | 8.5 | 6.4 |- | Europe | 9.6 | 26.4 | 29.2 | 22.8 | 32.4 |- | Africa | 10.7 | 1.5 | 0.5 | 2.4 | 1.0 |- | Middle East | 9.9 | 5.1 | 3.1 | 5.7 | 4.1 |- | Asia | 52.2 | 29.4 | 25.6 | 31.1 | 24.1 |- | Other | 3.2 | 3.7 | 2.6 | 5.4 | 3.4 |- | Totals (rounded) | 100% | 100% | 100% | 100% | 100% |}

World distribution of financial wealth. In 2007, 147 companies controlled nearly 40 percent of the monetary value of all transnational corporations.<ref name="sciencenews">[http://www.sciencenews.org/view/generic/id/333389/title/Financial_world_dominated_by_a_few_deep_pockets Financial world dominated by a few deep pockets]. By Rachel Ehrenberg. September 24, 2011; Vol. 180 #7 (p. 13). ''Science News''. Citation is in the right sidebar. Paper is here [https://arxiv.org/abs/1107.5728] with PDF here [https://arxiv.org/PS_cache/arxiv/pdf/1107/1107.5728v2.pdf].</ref>

=== In the United States === {{Globalize|section|date=October 2022|2=United States}} {{see also|Wealth inequality in the United States|Income inequality in the United States|Affluence in the United States}} {{ multiple image |total_width=675 |title=Net personal wealth in the U.S. since 1962, and across age groups | image1= 1962- Net personal wealth - average in percentile ranges - linear scale - US.svg | caption1= The average personal wealth of people in the top 1% is more than a thousand times that of people in the bottom 50%.<ref name=WID_through_2021/> | image2= 1962- Net personal wealth - average in percentile ranges - logarithmic scale - US.svg | caption2= The logarithmic scale shows how wealth has increased for all percentile groups, though more so for wealthier people.<ref name=WID_through_2021>{{cite web |title=Evolution of wealth indicators, USA, 1913-2019 |url=https://wid.world/country/usa/ |website=WID.world |publisher=World Inequality Database |access-date=September 6, 2023 |archive-url=https://web.archive.org/web/20230705011218/https://wid.world/country/usa/ |archive-date=July 5, 2023 |date=2022 |url-status=live }}</ref> | image3= 2022 Average and median family net worth, by age - US.svg | caption3= ''Average'' net worth—which heavily weights extremely high-wealth families—substantially exceeds ''median'' net worth (families in the fiftieth percentile).<ref name=FedReserveNetWorth_202312/> Further, average net worth outgrew median net worth from 2019 through 2022.<ref name=FedReserveNetWorth_202312>{{cite web |title=Changes in U.S. Family Finances from 2019 to 2022 |url=https://www.federalreserve.gov/publications/files/scf23.pdf |publisher=Board of Governors of the Federal Reserve System (US) |archive-url=https://web.archive.org/web/20231225163527/https://www.federalreserve.gov/publications/files/scf23.pdf |archive-date=December 25, 2023 |page=12 (Table 2) |date=October 2023 |url-status=live }}</ref> }} {{multiple image |total_width=675 | image1= 2021 Household wealth by percentile - United States.svg |caption1= Though the 10th percentile of American households have zero net worth, the 90th percentile has $1.8 million of household wealth.<ref>Fig. 2 of {{cite web |last1=Sullivan |first1=Briana |title=Wealth of Households: 2023 (P70BR-211) |url=https://www2.census.gov/library/publications/2025/demo/p70br-211.pdf |publisher=US Census Bureau |archive-url=https://web.archive.org/web/20250726021914/https://www2.census.gov/library/publications/2025/demo/p70br-211.pdf |archive-date=July 26, 2025 |date=July 2025 |url-status=dead}}</ref> | image2= 2021 Median household wealth, by highest educational attainment - US.svg |caption2= Higher educational attainment in the US correlates with higher household wealth.<ref name=WealthEducation_2021>{{cite web |title=The Wealth of Households: 2021 / Current Population Reports / P70BR-183 |url=https://www.census.gov/content/dam/Census/library/publications/2023/demo/p70br-183.pdf |last1=Sullivan |first1=Brianna |last2=Hays |first2=Donald |last3=Bennett |first3=Neil |page=5 (Figure 2) |publisher=United States Census Bureau |archive-url=https://web.archive.org/web/20240524023705/https://www.census.gov/content/dam/Census/library/publications/2023/demo/p70br-183.pdf |archive-date=May 24, 2024 |date=June 2023 |url-status=live }}</ref> | image3= 2021 Median wealth by marital status - US.svg |caption3= Median wealth of married couples is almost three times that of single individuals, regardless of gender and across all age categories.<ref>{{cite web |last1=Sullivan |first1=Briana |title=Wealth of Households: 2023 (P70BR-211) |url=https://www2.census.gov/library/publications/2025/demo/p70br-211.pdf |publisher=US Census Bureau |archive-url=https://web.archive.org/web/20250726021914/https://www2.census.gov/library/publications/2025/demo/p70br-211.pdf |archive-date=July 26, 2025 |date=July 2025 |url-status=dead}}</ref> }} [[File:2022 Median and average transaction account balance, by age.svg |thumb |Values of transaction accounts—those with immediate "on-demand" access—vary across age groups. ''Average'' account values are skewed upward by a small number of high-balance accounts. ''Median'' balances in transaction accounts better indicate readily available funds.<ref name=Bankrate_20260227>Federal Reserve’s 2022 ''Survey of Consumer Finances'' as reported by {{cite web |last1=Bennett |first1=Karen |last2=Subitch |first2=Rhys |last3=Brock |first3=Thomas |title=The average amount in U.S. savings accounts – how does your cash stack up? |url=https://www.bankrate.com/banking/savings/savings-account-average-balance/ |website=Bankrate.com |archive-url=https://web.archive.org/web/20260408053151/https://www.bankrate.com/banking/savings/savings-account-average-balance/#how-much-does-the-average-household-have-in-savings |archive-date=April 8, 2026 |date=February 27, 2026 |url-status=live}}</ref>]] According to PolitiFact, in 2011, the 400 wealthiest Americans "have more wealth than half of all Americans combined."<ref name="PF-20110311">{{cite news |last1=Kertscher |first1=Tom |last2=Borowski |first2=Greg |title=The Truth-O-Meter Says: ''True'' – Michael Moore says 400 Americans have more wealth than half of all Americans combined |url=https://www.politifact.com/wisconsin/statements/2011/mar/10/michael-moore/michael-moore-says-400-americans-have-more-wealth-/ |date=March 10, 2011 |work=PolitiFact |access-date=August 11, 2013 }}</ref><ref name="HP-20110306">{{cite news |last=Moore |first=Michael |author-link=Michael Moore |title=America Is Not Broke |url=http://www.huffingtonpost.com/michael-moore/america-is-not-broke_b_832006.html |date=March 6, 2011 |work=Huffington Post |access-date=August 11, 2013 }}</ref><ref name="MM-20110307">{{cite web |last=Moore |first=Michael |author-link=Michael Moore |title=The Forbes 400 vs. Everybody Else |url=http://www.michaelmoore.com/words/must-read/forbes-400-vs-everybody-else |date=March 7, 2011 |website=michaelmoore.com |access-date=August 11, 2013 |url-status=dead |archive-date=March 9, 2011 |archive-url=https://web.archive.org/web/20110309211959/http://www.michaelmoore.com/words/must-read/forbes-400-vs-everybody-else }}</ref><ref name=":5">{{Cite web |last=Pepitone |first=Julianne |title=Forbes 400: The super-rich get richer |url=https://money.cnn.com/2010/09/22/news/companies/forbes_400/index.htm |archive-url=https://web.archive.org/web/20130828114556/https://money.cnn.com/2010/09/22/news/companies/forbes_400/index.htm |archive-date=2013-08-28 |access-date=2026-05-22 |website=money.cnn.com}}</ref> Inherited wealth may help explain why many Americans who have become rich may have had a "substantial head start".<ref name="Salon-20140324">{{cite web |last=Bruenig |first=Matt |title=You call this a meritocracy? How rich inheritance is poisoning the American economy |url=https://www.salon.com/2014/03/24/death_of_meritocracy_how_inheritance_is_poisoning_the_american_economy/ |date=March 24, 2014 |work=Salon |access-date=August 24, 2014 }}</ref><ref name="ECO-20140318">{{cite news |author=Staff |title=Inequality – Inherited wealth |url=https://www.economist.com/blogs/buttonwood/2014/03/inequality |date=March 18, 2014 |newspaper=The Economist |access-date=August 24, 2014 }}</ref> In September 2012, according to the Institute for Policy Studies, "over 60 percent" of the Forbes richest 400 Americans "grew up in substantial privilege".<ref name="OW-20120924">{{cite web |last=Pizzigati |first=Sam |title=The 'Self-Made' Hallucination of America's Rich |url=http://inequality.org/selfmade-myth-hallucinating-rich/ |date=September 24, 2012 |work=Institute for Policy Studies |access-date=August 24, 2014 }}</ref>

In 2007, the richest 1% of the American population owned 34.6% of the country's total wealth (excluding human capital),{{clarify|date=December 2019}} and the next 19% owned 50.5%. The top 20% of Americans owned 85% of the country's wealth, while the bottom 80% owned 15%. From 1922 to 2010, the share of the top 1% ranged from 19.7% to 44.2%, with the largest decline associated with the late-1970s stock market downturn. Ignoring the period where the stock market was depressed (1976–1980) and the period when the stock market was overvalued (1929), the share of wealth of the richest 1% remained extremely stable, at about a third of the total wealth.<ref name="Domhoff" /> Financial inequality was greater than inequality in total wealth, with the top 1% of the population owning 42.7%, the next 19% of Americans owning 50.3%, and the bottom 80% owning 7%.<ref name="ForbesJacobs">[https://www.forbes.com/sites/deborahljacobs/2011/11/01/occupy-wall-street-and-the-rhetoric-of-equality/ Occupy Wall Street And The Rhetoric of Equality] ''Forbes'' November 1, 2011, by Deborah L. Jacobs</ref> However, following the Great Recession which started in 2007, the share of total wealth owned by the top 1% of the population grew from 34.6% to 37.1%, and that owned by the top 20% of Americans grew from 85% to 87.7%. The Great Recession also caused a 36.1% drop in median household wealth but only an 11.1% drop for the top 1%, further widening the gap between the 1% and the 99%.<ref name="levyinstitute.org">[http://www.levyinstitute.org/pubs/wp_589.pdf Working Paper No. 589 ''Recent Trends in Household Wealth in the United States: Rising Debt and the Middle-Class Squeeze – an Update to 2007''] by Edward N. Wolff, Levy Economics Institute of Bard College, March 2010</ref><ref name="Domhoff">[http://sociology.ucsc.edu/whorulesamerica/power/wealth.html Wealth, Income, and Power] {{Webarchive|url=https://web.archive.org/web/20111020134522/http://sociology.ucsc.edu/whorulesamerica/power/wealth.html |date=2011-10-20 }} by G. William Domhoff of the UC-Santa Barbara Sociology Department</ref><ref name="ForbesJacobs" />

Dan Ariely and Michael Norton show in a study (2011) that US citizens across the political spectrum significantly underestimate the current US wealth inequality and would prefer a more egalitarian distribution of wealth, raising questions about ideological disputes over issues like taxation and welfare.<ref>Norton, M. I., & Ariely, D., [https://www.hbs.edu/faculty/Pages/item.aspx?num=38500 "Building a Better America – One Wealth Quintile at a Time"], Perspectives on Psychological Science, January 2011 6: 9-12</ref>

{| class="wikitable" style="text-align:center;" |+ Wealth proportion by population by year (including homes)<ref name="Domhoff" /><ref>1922–1989 data from Wolff (1996), 1992–2010 data from Wolff (2012)</ref> |- ! style="text-align:left;" | Year ! Bottom 99% ! Top 1% |- | style="text-align:left;" | 1922 | 63.3% | 36.7% |- | style="text-align:left;" | 1929 | 55.8% | 44.2% |- | style="text-align:left;" | 1933 | 66.7% | 33.3% |- | style="text-align:left;" | 1939 | 63.6% | 36.4% |- | style="text-align:left;" | 1945 | 70.2% | 29.8% |- | style="text-align:left;" | 1949 | 72.9% | 27.1% |- | style="text-align:left;" | 1953 | 68.8% | 31.2% |- | style="text-align:left;" | 1962 | 68.2% | 31.8% |- | style="text-align:left;" | 1965 | 65.6% | 34.4% |- | style="text-align:left;" | 1969 | 68.9% | 31.1% |- | style="text-align:left;" | 1972 | 70.9% | 29.1% |- | style="text-align:left;" | 1976 | 80.1% | 19.9% |- | style="text-align:left;" | 1979 | 79.5% | 20.5% |- | style="text-align:left;" | 1981 | 75.2% | 24.8% |- | style="text-align:left;" | 1983 | 69.1% | 30.9% |- | style="text-align:left;" | 1986 | 68.1% | 31.9% |- | style="text-align:left;" | 1989 | 64.3% | 35.7% |- | style="text-align:left;" | 1992 | 62.8% | 37.2% |- | style="text-align:left;" | 1995 | 61.5% | 38.5% |- | style="text-align:left;" | 1998 | 61.9% | 38.1% |- | style="text-align:left;" | 2001 | 66.6% | 33.4% |- | style="text-align:left;" | 2004 | 65.7% | 34.3% |- | style="text-align:left;" | 2007 | 65.4% | 34.6% |- | style="text-align:left;" | 2010 | 64.6% | 35.4% |} [[File:Total US family wealth timeline by wealth group.png|thumb|upright=1.55|Trends in the distribution of family wealth, 1989 to 2022. Congressional Budget Office.<ref name=CBO-trends>{{cite web |title=Trends in the Distribution of Family Wealth, 1989 to 2022 |url=https://www.cbo.gov/publication/60807 |website=Congressional Budget Office |language=en |date=2 October 2024}}</ref>]]

== Wealth concentration == '''Wealth concentration''' is a process by which created wealth, under some conditions, can become concentrated within a small group of individuals or entities. Those who hold wealth have the means to invest in newly created sources and structures of wealth, or to leverage the accumulation of wealth otherwise, and are thus the beneficiaries of even greater wealth.

===Economic conditions=== {{See also|Economic inequality}}thumb|250px|Global share of wealth by wealth group The first necessary condition for wealth concentration is an unequal initial distribution of wealth. The distribution of wealth across the population is often well approximated by a Pareto distribution, with tails that decay as a power law in wealth. According to PolitiFact and others, the 400 wealthiest Americans had "more wealth than half of all Americans combined."<ref name="PF-20110311"/><ref name="HP-20110306"/><ref name="MM-20110307"/><ref name=":5" /> Inherited wealth may help explain why many Americans who have become rich may have had a "substantial head start".<ref name="Salon-20140324"/><ref name="ECO-20140318"/> In September 2012, according to the Institute for Policy Studies, "over 60 percent" of the ''Forbes'' 400 Richest Americans "grew up in substantial privilege".<ref name="OW-20120924"/>

The second condition is that a small initial inequality must widen over time into a larger one. This is an example of positive feedback in an economic system. A team from Jagiellonian University developed a statistical model of economies showing that wealth condensation can occur whether total wealth is growing or not (if not, it implies that some individuals are growing their wealth at the expense of others rather than creating new wealth; this could mean those experiencing poverty could become poorer).<ref name="arXiv-20010122">{{cite journal |author=Burdaa, Z. |title=Wealth Condensation in Pareto Macro-Economies |url=http://www.mathnet.or.kr/mathnet/paper_file/heriot/johns/j_10.pdf |date=January 22, 2001 |journal=Physical Review E |doi=10.1103/PhysRevE.65.026102 |arxiv=cond-mat/0101068 |access-date=September 11, 2013 |bibcode=2002PhRvE..65b6102B |display-authors=etal |volume=65 |issue=2 |article-number=026102 |pmid=11863582 |s2cid=8822002 |archive-date=January 18, 2021 |archive-url=https://web.archive.org/web/20210118062955/https://www.mathnet.or.kr/mathnet/paper_file/heriot/johns/j_10.pdf |url-status=dead }}</ref>

Joseph E. Fargione, Clarence Lehman, and Stephen Polasky demonstrated in 2011 that chance alone, combined with the deterministic effects of compounding returns, can lead to unlimited concentration of wealth, such that the percentage of all wealth owned by a few entrepreneurs eventually approaches 100%.<ref>Joseph E. Fargione et al.: [https://doi.org/10.1371/journal.pone.0020728 ''Entrepreneurs, Chance, and the Deterministic Concentration of Wealth.'']</ref><ref>[https://share.cocalc.com/share/91277c1f83bd1bd143ec1e2faf67b3057e26602c/fargione.ipynb?viewer=share Simulation of wealth concentration according to Fargione, Lehman, and Polasky]</ref>

====Correlation between being rich and earning more==== Given an initial condition in which wealth is unevenly distributed (i.e., a "wealth gap"<ref name="AP-20140127">{{cite news |last1=Rugaber |first1=Christopher S. |last2=Boak |first2=Josh |title=Wealth gap: A guide to what it is, why it matters |url=http://apnews.excite.com/article/20140127/DABJ40P00.html |date=January 27, 2014 |work=AP News |access-date=January 27, 2014 |archive-date=March 16, 2019 |archive-url=https://web.archive.org/web/20190316101311/http://apnews.excite.com/article/20140127/DABJ40P00.html |url-status=dead }}</ref>), several non-exclusive economic mechanisms for wealth concentration have been proposed: * A correlation between being rich and being given high-paid employment (oligarchy). * A marginal propensity to consume low enough that high incomes are correlated with people who have already made themselves rich (meritocracy). * The ability of the rich to influence government disproportionately to their favor, thereby increasing their wealth (plutocracy and regulatory capture).<ref>{{cite book|title=The New Golden Age: The Coming Revolution against Political Corruption and Economic Chaos|url=https://archive.org/details/newgoldenagecomi0000batr|url-access=registration|first=Ravi|last=Batra|publisher=Palgrave Macmillan |date=2007 |isbn=978-1-4039-7579-9|access-date=October 21, 2011}}</ref>

In the first case, being wealthy allows one to earn more through high-paying employment (e.g., by attending elite schools). In the second case, having high-paid employment allows one to become rich (by saving one's money, since a lower percentage of it is consumed on necessities). In the third case, the wealthy exert power over the legislative process, which enables them to increase the wealth disparity by—using their economic power—lobbying for policies that benefit them.<ref>{{cite web|url=http://channer.tv/monday.htm,%2007-25-11.htm|title=TV interview with Dr. Ravi Batra|first=Harold Hudson|last=Channer|date=July 25, 2011|access-date=October 21, 2011}}</ref> An example of this is the high cost of political campaigning in some countries, in particular in the US (more generally, see also plutocratic finance). The Center for American Progress warns that a "significant percentage" of money in politics is spent for the purpose of "capturing private favours". It also notes that "campaign contributions and lobbying often help shape policy outcomes" in ways consistent with rent seeking.<ref>{{Cite web |date=2014-05-02 |title=How Campaign Contributions and Lobbying Can Lead to Inefficient Economic Policy |url=https://www.americanprogress.org/article/how-campaign-contributions-and-lobbying-can-lead-to-inefficient-economic-policy/ |access-date=2026-05-09 |website=Center for American Progress |language=en}}</ref>

Because these mechanisms are non-exclusive, all three explanations could work together to compound the effect, further increasing wealth concentration. Obstacles to restoring wage growth might have more to do with the broader dysfunction of a dollar-dominated political system, particularly in the US, than with the role of the extremely wealthy.<ref name=":0">{{Cite book|title=Learning by Doing: The Real Connection between Innovation, Wages, and Wealth|last=Bessen|first=James|publisher=Yale University Press|year=2015|isbn=978-0300195668|pages=226–27|quote=The obstacles to restoring wage growth might have more to do with the broader dysfunction of our dollar- dominated political system than with the particular role of the extremely wealthy.}}</ref>

Counterbalances to wealth concentration include certain forms of taxation, in particular wealth tax, inheritance tax, and progressive taxation of income. However, concentrated wealth does not necessarily inhibit wage growth for ordinary workers with low wages.<ref>{{Cite book|title=Learning by Doing: The Real Connection between Innovation, Wages, and Wealth|last=Bessen|first=James|publisher=Yale University Press|year=2015|isbn=978-0300195668|pages=3|quote=However, concentrated wealth does not necessarily inhibit wage growth.}}</ref>

The investor, billionaire, and philanthropist Warren Buffett, one of the wealthiest people in the world,<ref>{{cite web |title=The World's Billionaires |url=https://www.forbes.com/billionaires/list/ |url-status=live |archive-url=https://web.archive.org/web/20130403013841/http://www.forbes.com/billionaires/list/ |archive-date=3 April 2013 |access-date=1 May 2018 |website=forbes.com}}</ref> voiced in 2005 and once more in 2006 his view that his class, the "rich class", is waging class warfare on the rest of society. In 2005, Buffett said to CNN, "It's class warfare, my class is winning, but they shouldn't be."<ref>[http://edition.cnn.com/2005/US/05/10/buffett/index.html Buffett: 'There are lots of loose nukes around the world'] {{webarchive|url=https://web.archive.org/web/20160430104340/http://edition.cnn.com/2005/US/05/10/buffett/index.html|date=30 April 2016}} CNN.com</ref> In a November 2006 interview in ''The New York Times'', Buffett stated that "[t]here's class warfare all right, but it's my class, the rich class, that's making war, and we're winning."<ref name="Buffett_warfare">{{cite news |last=Buffett |first=Warren |date=26 November 2006 |title=In Class Warfare, Guess Which Class is Winning |url=https://www.nytimes.com/2006/11/26/business/yourmoney/26every.html |url-status=live |archive-url=https://web.archive.org/web/20170103165340/http://www.nytimes.com/2006/11/26/business/yourmoney/26every.html |archive-date=3 January 2017 |newspaper=The New York Times}}</ref>

==Redistribution of wealth and public policy== {{see also|Redistribution of income and wealth|Wealth distribution by country}}

In many societies, attempts have been made, through property redistribution, taxation, or regulation, to redistribute wealth, sometimes in support of the upper class, and sometimes to diminish economic inequality.

Examples of this practice go back at least to the Roman Republic in the third century B.C.,<ref>Livy, Rome and Italy: Books VI-X of the History of Rome from its Foundation, Penguin Classics, {{ISBN|0-14-044388-6}}</ref> when laws were passed limiting the amount of wealth or land that any one family could own. Motivations for such limitations on wealth include the desire for equality of opportunity, a fear that great wealth leads to political corruption, the belief that limiting wealth will gain the political favor of a voting bloc, or fear that extreme concentration of wealth results in rebellion.<ref>"… A perceived sense of inequity is a common ingredient of rebellion in societies …", Amartya Sen, 1973</ref> Various forms of socialism attempt to diminish the unequal distribution of wealth and thus the conflicts and social problems arising from it.<ref>"The Spirit Level" by Richard Wilkinson and Kate Pickett;Bloomsbury Press 2009</ref>

During the Age of Reason, Francis Bacon wrote "Above all things good policy is to be used so that the treasures and monies in a state be not gathered into a few hands… Money is like fertilizer, not good except it be spread."<ref>Francis Bacon, ''Of Seditions and Troubles''</ref>

The rise of Communism as a political movement has partially been attributed to the distribution of wealth under capitalism, in which a few lived in luxury. In contrast, the masses lived in extreme poverty or deprivation. However, in the ''Critique of the Gotha Programme'', Marx and Engels criticized German Social Democrats for emphasizing issues of distribution instead of production and ownership of productive property.<ref>''Critique of the Gotha Program'', Karl Marx. Part I: "Quite apart from the analysis so far given, it was in general a mistake to make a fuss about so-called distribution and put the principal stress on it."</ref> While the ideas of Marx have nominally influenced various states in the 20th century, the Marxist notions of socialism and communism remain elusive.<ref>Archie Brown, ''The Rise and Fall of Communism'', Ecco, 2009, {{ISBN|978-0-06-113879-9}}</ref>{{vague|date=December 2019}}

On the other hand, the combination of Labour movement, technology, and social liberalism has diminished extreme poverty in the developed world today, though extremes of wealth and poverty continue in the Third World.<ref>Jeffrey D. Sachs, ''The End of Poverty'', Penguin, 2006, {{ISBN|978-0-14-303658-6}}</ref>

In the Outlook on the Global Agenda 2014 from the World Economic Forum, widening income disparities rank second among global risks.<ref>{{cite web|url=http://reports.weforum.org/outlook-14/top-ten-trends-category-page/2-widening-income-disparities/ |title=Outlook on the Global Agenda 2014 – Reports |publisher= World Economic Forum |website=Reports.weforum.org |access-date=September 10, 2016}}</ref><ref>{{cite web |url=http://www.oxfam.org/sites/www.oxfam.org/files/bp-working-for-few-political-capture-economic-inequality-200114-en.pdf |title=178 Oxfam Briefing Paoer |date=January 20, 2014 |website=Oxfam.org |access-date=September 10, 2016 |archive-date=October 8, 2019 |archive-url=https://web.archive.org/web/20191008051701/https://www.oxfam.org/sites/www.oxfam.org/files/bp-working-for-few-political-capture-economic-inequality-200114-en.pdf |url-status=dead }}</ref> According to a 2009 meta-analysis by Paul and Moser, countries with high income inequality and poor unemployment protections experience worse mental health outcomes among the unemployed.<ref>{{Cite web |title=The toll of job loss |url=https://www.apa.org/monitor/2020/10/toll-job-loss |access-date=November 26, 2023 |website=www.apa.org}}</ref>

==References== {{Reflist|30em}}

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==External links== {{Prone to spam|date=March 2012}}  * [https://unstats.un.org/unsd/demographic/sconcerns/income/default.htm U.N. statistics – Distribution of Income and Consumption; wealth and poverty] * [http://www.wider.unu.edu/research/projects-by-theme/poverty-inequality/en_GB/personal-assets-from-a-global-perspective/ Research on the World Distribution of Household Wealth (UNU-WIDER)] {{Webarchive|url=https://web.archive.org/web/20191221084609/https://www.wider.unu.edu/research/projects-by-theme/poverty-inequality/en_GB/personal-assets-from-a-global-perspective |date=December 21, 2019 }} * [https://web.archive.org/web/20070613005439/https://www.cia.gov/library/publications/the-world-factbook/fields/2172.html CIA World Factbook: Field Listing – Distribution of family income – Gini index] * [https://www.oxfam.org/en/pressroom/pressrelease/2013-01-19/annual-income-richest-100-people-enough-end-global-poverty-four-times Annual income of richest 100 people enough to end global poverty four times over]. ''Oxfam International,'' January 19, 2013.

===Wealth surveys=== Many countries have national wealth surveys, for example: * The British [http://www.ons.gov.uk/ons/guide-method/method-quality/specific/economy/wealth-and-assets-survey/wealth-and-assets-survey---user-guidance/index.html Wealth and Assets Survey] * The Italian Survey on Household Income and Wealth * The euro area [https://www.ecb.europa.eu/pub/economic-research/research-networks/html/researcher_hfcn.en.html Household Finance and Consumption Survey] * The US Survey of Consumer Finances * The Canadian [http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?lang=eng&catno=13F0026MIE2006001 Survey of Financial Security] * The German [http://www.armuts-und-reichtumsbericht.de/DE/Startseite/start.html Armuts- und Reichtumsbericht der Bundesregierung]

===Additional data, charts, and graphs=== * [https://www2.ucsc.edu/whorulesamerica/power/wealth.html Wealth, Income, and Power] by G. William Domhoff * [https://web.archive.org/web/20070627164747/http://www.gcad-cymru.org.uk/vtc/ngfl/geography/117/Master3/Lorenz.ppt PowerPoint presentation: Inequalities of Development] – Lorenz curve and Gini coefficient * [https://web.archive.org/web/20071016181500/http://mindfully.org/WTO/2006/Household-Wealth-Gap5dec06.htm Article on The World Distribution of Household Wealth report.] * [http://www.federalreserve.gov/pubs/oss/oss2/scfindex.html The Federal Reserve Board – Survey of Consumer Finances] * [http://www.federalreserve.gov/pubs/oss/oss2/2004/2004%20SCF%20Chartbook.zip Survey of Consumer Finances 1998–2004 charts – pdf] * [http://www.federalreserve.gov/pubs/oss/oss2/2004/bulletin.tables.int.xls Survey of Consumer Finances 1998–2004 data] and resulting Gini indices for mean incomes: 1989: [http://www.poorcity.richcity.org/cgi-bin/inequality.cgi?quantiles=20,*8.7|20,*21.5|20,*37.9|20,*59.9|10,*89.6|10,*249.2 51.1] {{Webarchive|url=https://web.archive.org/web/20210423141917/http://www.poorcity.richcity.org/cgi-bin/inequality.cgi%3Fquantiles=20,*8.7%7C20,*21.5%7C20,*37.9%7C20,*59.9%7C10,*89.6%7C10,*249.2 |date=April 23, 2021 }}, 1992: [http://www.poorcity.richcity.org/cgi-bin/inequality.cgi?quantiles=20,*8.9|20,*20.9|20,*35.8|20,*57.0|10,*84.6|10,*198.1 47.8] {{Webarchive|url=https://web.archive.org/web/20210423134752/http://www.poorcity.richcity.org/cgi-bin/inequality.cgi%3Fquantiles=20,*8.9%7C20,*20.9%7C20,*35.8%7C20,*57.0%7C10,*84.6%7C10,*198.1 |date=April 23, 2021 }}, 1995: [http://www.poorcity.richcity.org/cgi-bin/inequality.cgi?quantiles=20,*8.2|20,*21.6|20,*37.1|20,*57.0|10,*85.7|10,*215.8 49.0] {{Webarchive|url=https://web.archive.org/web/20210423140401/http://www.poorcity.richcity.org/cgi-bin/inequality.cgi%3Fquantiles=20,*8.2%7C20,*21.6%7C20,*37.1%7C20,*57.0%7C10,*85.7%7C10,*215.8 |date=April 23, 2021 }}, 1998: [http://www.poorcity.richcity.org/cgi-bin/inequality.cgi?quantiles=20,*9.2|20,*23.4|20,*39.4|20,*63.0|10,*92.2|10,*254.5 50.4] {{Webarchive|url=https://web.archive.org/web/20210423144923/http://www.poorcity.richcity.org/cgi-bin/inequality.cgi%3Fquantiles=20,*9.2%7C20,*23.4%7C20,*39.4%7C20,*63.0%7C10,*92.2%7C10,*254.5 |date=April 23, 2021 }}, 2001: [http://www.poorcity.richcity.org/cgi-bin/inequality.cgi?quantiles=20,*10.7|20,*25.7|20,*42.9|20,*69.4|10,*104.4|10,*322.4 52.6] {{Webarchive|url=https://web.archive.org/web/20210423143157/http://www.poorcity.richcity.org/cgi-bin/inequality.cgi%3Fquantiles=20,*10.7%7C20,*25.7%7C20,*42.9%7C20,*69.4%7C10,*104.4%7C10,*322.4 |date=April 23, 2021 }}, 2004: [http://www.poorcity.richcity.org/cgi-bin/inequality.cgi?quantiles=20,*10.8|20,*26.1|20,*43.4|20,*69.1|10,*106.5|10,*302.1 51.4] {{Webarchive|url=https://web.archive.org/web/20210423134602/http://www.poorcity.richcity.org/cgi-bin/inequality.cgi%3Fquantiles=20,*10.8%7C20,*26.1%7C20,*43.4%7C20,*69.1%7C10,*106.5%7C10,*302.1 |date=April 23, 2021 }} * [http://www.federalreserve.gov/pubs/oss/oss2/papers/concentration.2001.10.pdf Changes in the Distribution of Wealth in the U.S., 1989–2001] * [https://www.census.gov/prod/2003pubs/p70-88.pdf Report on Net Worth and Asset Ownership of Households] * [https://www.census.gov/prod/1/pop/p25-1129.pdf Projections of the Number of Households in the U.S. 1995–2010] * [https://web.archive.org/web/20180129141246/https://www.bea.gov/national/sna.htm The System of National Accounts (SNA): comparison of U.S. national accounts statistics with those of other countries] * [https://www.wto.org/english/res_e/res_e.htm World Trade Organization: Resources] * [https://thesocietypages.org/graphicsociology/2009/05/27/champagne-glass-distribution-of-wealth/ Champagne Glass infographic of global wealth distribution] from Dalton Conley's [https://www.amazon.com/dp/0393935175 You May Ask Yourself: An Introduction to Thinking Like a Sociologist] textbook, which was adapted from the 1992 UNDP original

Category:Distribution of wealth