dataesr/scientific-paragraphs-categorization huggingface dataset:
8 eductions in top ta rates can thus drive up ards not only post-ta income ine uality but pre-ta ine uality, as ell igher top ta rates may, ho ever, also discourage or e ort and business creation among the most talented In this scenario, higher top ta rates ould lead to less economic activity by the rich and hence less economic gro th In this case, top ta rates are not a desirable policy. in principle, there should be room to discuss these conflicting and legitimate claims on the basis o dispassionate analyses and sound data. piketty, saez, and stantcheva (2014) have developed a theoretical model and an empirical rame or ta ing into account these different effects. 9 By using a database on Ceo compensation and performance in developed countries, they conclude that bargaining elasticities are an important part of the story-in particular, to understand the high rise o s pay relative to their counterparts in Japan and europe (with comparability established by shared corporate sector, firm si e, and per ormance levels By calibrating the theoretical model, they sho top ta rates could rise up to and be el are-enhancing or everyone apart from the very top of the distribution.
As discussed earlier in this report, more work lies ahead to collect, harmonize, and analyze such information. The United Nations and other international organizations have a responsibility in this regard. WID. world will remain committed to working toward such results, with all its statistical contributors willing to dedicate resources to this task, to enlighten the public democratic debate. Bearing in mind these remarks, the SDG Target 10. 1 on inequality stands out as a very useful tool for stakeholders dedicated to tackling economic inequality. To be sure, an inequality metric based on sound data cannot in itself change policybut it is a necessary basis for doing so. The SDG framework can also lead to the establishment of a framework for collective learning on inequality reduction policies.
In art IV, e discussed ho increasing income ine uality, and the large trans ers o public wealth to private hands which have occurred over the past forty years, have led to a rise in ealth ine uality among individuals At the global level represented by China, europe, and the united states-the top 1% share of wealth increased from 28% in 1980 to 33% today, while the bottom 75% share oscillated around Large rises in top ealth shares have been e perienced in ConClusion the World Inequality Report 2018 draws from data available on the World Wealth and Income database (WId. world), which combines historical statistical sources in a consistent and fully transparent way to fill a gap in the democratic debate regarding inequality. our objective in this report has been to present inequality data that are consistent with macroeconomic statistics such as GdP and national income and that can be easily understood and used by the public, to help ground deliberations and decisions in facts.
to conclude, we must repeat that current no ledge o global income and ealth inequality remains limited and unsatisfactory. much more data collection work lies ahead of us to e pand the geographical coverage o our inequality data, as well as to provide more systematic representations of pre-and postta income and ealth ine uality ID orld, the World inequality lab, and their partner institutions are committed to pursuing these e orts in the coming years he ID orld database is currently being e panded to increase its coverage o emerging countries in Asia in particular, Malaysia and indonesia), africa (for instance, in south A rica , and Latin America hile and Me ico, among others e are also currently or ing to ards better integration o natural capital in national wealth estimates, as the importance of environmental degradation as a dimension o ine uality continues to gro ConClusIon More gender ine uality data are also being integrated to ID orld and e are developing estimates o ine uality at the regional (subnational) level, with the aim of further reducing the gap bet een individuals perceptions of inequality and what economic statistics are able to measure.
global income inequality is not inevitable in the future exeCutIve summary Figure e10 rising 30% … all countries follow US's 1980-2016 inequality 25% Global Top 1% income share trend = scenario 2 … all countries follow their own 1980-2016 inequality 20% trend = scenario 1 … all countries follow EU 15% Global inequality assuming … 1980-2016 inequality trend = scenario 3 scenario 3 10% scenario 1 5% Global Bottom 50% income share scenario 2 0% 1980 1990 2000 2010 2020 2030 2040 2050 Source: WID. world (2017). See wir2018. wid. world for data series and notes. World inequality report 2018.
See wir2018. wid. world for data series and notes. €10 000 €9 100 … all countries follow EU 1980-2016 Average income inequality trend €8 000 assuming … … all countries prolong their own 1980-2016 €6 300 inequality trend €6 000 … all countries follow Bottom 50% average income €4 500 US 1980-2016 inequality trend €4 000 €3 100 €2 000 €1 600 €0 1980 1990 2000 2010 2020 2030 2040 2050.
all Wid. world series, moreover, are Ne Yor : National Bureau o conomic esearch, accompanied ith a methodological paper 4 s. kuznets, Shares of Upper Income Groups in Income and Savings Chancelpiketty2015. pdf. of the Wid. world website with the objective 5 f. alvaredo, a. b. atkinson, l. Chancel, t. piketty, e. saez, and providing e tensive descriptions o the o reaching a ide audience o researchers G Zucman, Distributional National Accounts DINA Guidelines: Concepts and methods used in the World Wealth and income method and concepts used. Database, http:// id orld/document/dinaguidelines-v / ID orld or ing aper no and the general public ith a user-riendly / , December , interface. thanks to the work of over a hun-dred researchers located on five continents, tiglit , A en, and J itoussi, eport by the ommission on the Measurement o conomic er ormance and ocial rogress, 6 J raw data and the computer codes used to generate ine uality estimates are also the ID orld ebsite no gathers income ine uality data or more than aris, http://ec europa eu/eurostat/documents/ / / fitoussi+Commission+report.
1. 1a top 10% income shares across the world, 1980-2016: rising inequality almost everywhere, but at different speeds In 2016, 47% of national income was received by the top 10% in US-Canada, compared to 34% in 1980. Source: WID. world (2017). See wir2018. wid. world for data series and notes. t rends in Global inCome inequality Figure 2. Figure 2. Part II 60% 70% Share of national income (%) 30% 40% 50% 30% 40% 50% 60% Share of national income (%) Russia China India US-Canada Europe Europe China Middle East Sub-Saharan Africa India Russia US-Canada Brazil 20% 20% 1980 1980 1985 1985 1990 1990 1995 1995 2000 2000 2005 2005 2010 2010 2015 2015 In 2016, 55% of national income was received by the Top 10% earners in India, against 31% in 1980. Source: WID. world (2017). See wir2018. wid. world for data series and notes.
1. 1b top 10% income shares across the world, 1980-2016: Is world inequality moving toward the high-inequality frontier? 37% of national income was received by the Top 10% in Europe against 61% in the Middle-East. 70% 61% 60% 54% 55% 55% 50% 46% 47% 41% 40% 37% 30% 20% 10% 0% Europe China Russia US-Canada Sub- Brazil India Middle East Saharan Africa In 2016, Source: WID. world (2017). See wir2018. wid. world for data series and notes.
the geography of global income inequality was transformed over the past decades What is the share of african, asians, americans, and uropeans in each global incomeIn 1990, 33% of the population of the world's Top 0. 001% income group were residents of the US and Canada. Population share within each global income group (%) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1 10 20 30 40 50 60 70 80 90 99 99. 9 99. 99 99. 999 Source: WID. world (2017). See wir2018. wid. world for data series and notes.
1. 5 Geographic breakdown of global income groups in 1990 In 2016, 5% of the population of the world's Top 0. 001% income group were residents of Russia. t rends in Global inCome inequality groups and ho has this evolved over time Figures 2. 1. 5 and 2. 1. 6 answer these ques-tions by sho ing the geographical composi-tion o each income group in and in 2016. between 1980 and 1990, the geographic repartition o global incomes evolved only slightly, and our data allo or more precise geographic repartition in , so it is preferable to focus on this year. in a similar ay to ho igures through decomposed the data, igures and decompose the top into groups (see box 2. 1. 1 o be clear, all groups above percentile 99 are the decomposition of the richest o the global population in 1990, asians were almost not represented ithin top global income groups Indeed, the bulk of the population of india and China are found in the bottom half of the income distri-Figure 2.
1. 7 Global Bottom 50% and Top 1% income shares, 1980-2016 Source: WID. world (2017). See wir2018. wid. world for data series and notes. Figure 2. ParT II TRENdS IN globAl INComE INEqUAlITy level o global ine uality sustained throughout the entire period ith a top income group capturing t o times the total income captured by the bottom 50% of the population- implying a actor di erence in average per-adult income levels. second, it is apparent that high gro th in emerging countries since , in particular in hina, or the global financial crisis o as not su ficient to stop the rise in global income ine uality hen global ine uality is decomposed into a between-and within-country inequality component, it is apparent that within-country inequality continued to rise since 2000 whereas between-country inequality rose up to 2000 and decreased afterwards.
1. 8 Global top 10% income share, 1980-2016: between versus within country inequality Source: WID. world (2017). See wir2018. wid. world for data series and notes. Figure 2. trends in Global inCome inequality Part II Global Top 10% share … perfect equality Global Top 10% between countries share assuming … … perfect equality within countries currencies, so at first glance they should and reduces the bottom 50% share from reflect people s relative purchasing po er nearly 10% to 6% ( this makes them a natural conversion factor between currencies. the problem is that mar et e change rates reflect only the rela- tive purchasing po er o money in terms o tradable goods But non-tradable goods typi- cally services) are in fact cheaper relative to tradable ones in emerging economies given the so-called balassa-samuelson effect).
2. 1 and 2. 2. 2). 80% Average national income as a percentage of average global income (%) 40% 50% 60% 70% 30% 1950 1960 1970 1980 1990 2000 2010 Source: WID. world (2017). See wir2018. wid. world for data series and notes. In , average real income per adult in A rica as o the orld average income his figured decreased to in Income estimates account or di erences in the cost o living bet een countries Values are net o inflation.
Asia Africa Figure 2. 2. 1 average income in africa and asia relative to the global average, 1950-2016 trends in Global inCome inequality Part II 150% Average national income as a percentage of average global income (%) 30% 60% 90% 120% China Latin America 0% 1950 1960 1970 1980 1990 2000 2010 Source: WID. world (2017). See wir2018. wid. world for data series and notes. In , average real income per adult in Latin America as o the orld average income his figure decreased to in Income estimates account or di erences in the cost o living bet een countries Values are net o inflation World inequality report 2018 65.
-income groups were shut off from economic growth in the United States, while top incomes surged in the Anglo-Saxon world 25% Australia Canada Share of national income (%) 5% 10% 15% 20% UK Ireland US 0% 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Source: Novokmet, Piketty & Zucman (2017). See wir2018. wid. world for data series and notes. In 2014, 20% of national income was received by the Top 1% in the US. throughout the entire period around in a ter in the nited tates, shedding the early and rising to less than ne light on the process o une ual gro th also show a broadly similar pattern. 8 the generation impact o the financial crisis is visible on top- income shares, hich e hibit a mar ed our novel estimates also allow a better declined a ter Novel data suggest that understanding o the dynamics at the bottom top incomes have either recovered their of the distribution-at least for certain coun- shares or are progressively recovering them tries.
3. 6 top 10% national income share in brazil, the middle east, south africa and other countries, 2012-2016 0% 10% 20% 30% 40% 50% 60% 70% In 2016, 61% of national income was received by the Top 10% in the Middle East. 55 61 Middle East Brazil Source: WID. world (2017). See wir2018. wid. world for data series and notes. 410 million Population 210 million Share of national income (%) 61% 55% Figure 2. Part II t rends in Global inCome inequality even reached the most e treme levels In 1950, the richest 0. 1% of zambia commanded a bit more than 10% of total national income. Income ine uality as, ho ever, seemingly lower in West african countries such as Nigeria and Ghana, here the top aver-aged to o total income bet een and Interestingly, this pattern o geographical di erences in ine uality is still evident in survey data that has been collected in recent decades.
1b Pre-tax incomes of the top 1% and bottom 50% in the us, 1962-2014 2014: Top 1% = $1 337 000 1980: Top 1% = $439 000 Top 1% Bottom 50% 1980: Bottom 50% = $16 400 2014: Bottom 50% = $16 600 $30 000 $25 000 $20 000 $15 000 $10 000 $5 000 $0 1962 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 Source: Piketty, Saez and Zucman (2018). See wir2018. wid. world for data series and notes. Figure 2. 4.
See wir2018. wid. world for data series and notes. Between 1900 and 1950 , the share of national income growth captured by the Top 10% was 8%. PArT II TREndS In GLoBaL IncomE InEquaLITy large bonuses or stoc options some o hich have been largely mediati ed and then rom very high capital incomes derived rom improvements in the price of the stocks that they have come to own. top capital incomes have also been rising due to the rising share o macroeconomic capital in a conte t o declining labor bargaining po er and privatization policies.
the shares of the top 10% and bottom 50% diverged after the opening-up reforms In 2013, the Top 10% national income share was 40%. Source: Bartels (2017). See wir2018. wid. world for data series and notes. The share of income going to the Top 1% in 2013 grew by 35% relative to its 1983 value, while the share going to the Bottom 90% in 2013 fell by 13%. : Bartels (2017). See wir2018. wid. world for data series and notes. Part II Part II t rends in Global inCome inequality t rends in Global inCome inequality trends in Global inCome inequality trends in Global inCome inequality Part II Part II Figure 2. 6. 2 Figure 2. 6. 3 Chinese average incomes grew ninefold the orld s leading emerging economy Income shares in Germany, 1961-2013 Income inequality in Germany, 1983-2013 since 1978 despite the decline in its share of world popu- Share of national income (%) 15% 20% 25% 30% 35% 40% 45% the Communist party of China, then led by Top 10% Bottom 50% Middle 40% Top 1% Deng iaoping, implemented a series o poli-lation, China's share of world national income increased from less than 3% in 1978 to 19% in 2015, and real per-adult national income 2.
income per adult in russia and Western europe, 1870-2016 in communist russia, unemployment as virtually none istent ith only small age di erentials used to re ard differential inputs and to motivate effort. this In 2016, the national income per adult in Russia was 68% of the national income per adult in Western Europe. All values have been converted into 2016 Purchasing Power Parity (PPP) euros at a rate of €1 = $1. 3 = ₽ accounts or di erences in the cost o living bet een countries Values are net o inflationIn 2015, the Top 10% income share in Russia was 46%. Source: Novokmet, Piketty and Zucman (2017). See wir2018. wid. world for data series and notes. Figure 2. 8. 2 t rends in Global inCome inequality Figure 2. 8. 3 ratio between national Part II top 10% 80% 55% Top 10% (US) Ratio of Russian to Western Europe national income per adult (%) Share of national income (%) 25% 50% 40% 50% 60% 70% 30% 35% 40% 45% Ratio Russia / Western Europe (Germany-France-UK) Top 10% (France) Top 10% (Russia) 30% 20% 1870 1905 1890 1915 1880 1900 1925 1910 1935 1930 1945 1920 1940 1955 1950 1965 1970 1975 1960 1980 1985 2010 2005 2000 1995 1990 2015 ensured generally egalitarian ine uality price liberalization occurred on January 1, outcomes as compared to market economies.
income share in France, russia and the us, 1905-2015 In 2015, the Top 10% share of national income was 46%. Source: Novokmet, Piketty and Zucman (2017). See wir2018. wid. world for data series and notes. Part II t rends in Global inCome inequality trends in Global inCome inequality trends in Global inCome inequality Part II Part II mately pattern as those constructed by the euro-in his as a huge turn-precise estimation of top russian incomes. 37 national income ell by over in Figure 2. around in ust over seven years note that the pean bank for reconstruction and develop-econd, there are meaning ul di erences in be ore recovering rather lethargically income share o the bottom times greater than that o the top ment (ebrd). 36 they do, however, differ on t o points irst, they sho an even stronger 55% as five in , the income concepts employed.
8. 4 shows the annual and total gro th rates over the period or di erent groups o the population Interestingly, these igures sho the same up ard-sloping Between 1989 and 2016, the average income of the percentile group p99p99. 1 (the poorest 10% among the richest 1% of Russians) grew by 143%. Values are net o inflation Source: Novokmet, Piketty and Zucman (2017). See wir2018. wid. world for data series and notes.
average annual real growth by percentile in russia, 1905-2016 table 2. 8. 3 / average annual real growth rates Income group 1905-2016 1905-1956 1956-1989 1989-2016 Source: Novokmet, Piketty and Zucman (2017). See wir2018. wid. world for data series and notes. Part II t rends in Global inCome inequality TReNdS IN GloBAl INcome INequAlITy Part II prevent the oviet elite rom having access to been substantially higher than their annual superior goods, services, and opportunities incomes o our to five times the national his could ta e di erent orms, including access to special shops and vacation facilities, which allowed the soviet top 1% to enjoy living standards that in some cases might have 2. 9 average ould have suggested hese actors should be ept in mind hen ma ing historical and international comparisons-in russia or elsewhere.
9. 1, these reforms of national income, the bottom 50% earned were concomitant with a dramatic rise in 25% Share of national income (%) 10% 15% 20% Top 1% Bottom 50% 5% 1950 1960 1970 1980 1990 2000 2010 World inequality report 2018 125 Source: Chancel & Piketty (2017). See wir2018. wid. world for data series and notes. Figure 2.
1920 the private sector, incomes were constrained o ever, this dynamic changed dramatically 2010 by e tremely high ta rates: bet een and during the s and has remained as such , top marginal income ta rates rose rom ever since he s sa a much higher Source: Chancel & Piketty (2017). See wir2018. wid. world for data series and notes. Figure 2. e hibit a strong increase in the top wealth share in the recent period, in particular after 2002. 43   ighly une ual income gro th at the top mechanically drives wealth inequality across the population, which in returns fuels income concentration.
3a Income growth in India, 1951-2014: Full population vs. bottom 50% In the 2000s, the average income of the full population grew by 4. 5% per year on average, while the average income of the Top 1% grew by 8. 7% per year on average. Values are net o inflationSource: Chancel & Piketty (2017). See wir2018. wid. world for data series and notes. Part II t rends in Global inCome inequality Figure 2. 10% 8% Top 1% Average annual real growth (%) -2% 0% 2% 4% 6% Top 10 % Full population -4% -6% 1950 1960 1970 1980 1990 2000 2010 e perienced a significant reduction in their real at the opposite end of the distribution, the incomes, alling - , - and - respec- top 1% of indian earners captured as much tively over the 30-year period. the bottom gro th as the bottom group captured o total gro th between 1951 and 1980, while the middle table 2.
Inequality in the middle east is among the highest of any region worldwide argue that previous results, based on household survey data only, highly underestimate inequality and they offer novel estimates using the only fiscal data available in the region that has been recently released In 2012-2016 (latest year available), the Top 10% income share in the Middle East was 61%. Source: Alvaredo, Assouad and Piketty (2017). See wir2018. wid. world for data series and notes. income inequality in the middle east remains e tremely high over the period: the top income share fluctuated at around 60%-66% of total income, while the share of the bottom 50% and middle 40% varied between 8%-10% and 27%-30% of total income, respectively egional income has largely been concentrated among the top 1% of the adult population, which receives 27% of total income, that is three times more than the bottom , and appro imately the same as the middle 40% of the population.
10. 1 Inequality in the middle east, Western europe and the us, 2012-2016 tries. in the case of the middle east, they are largely due to the geography o oil o nership and the transformation of oil revenues into permanent financial endo ments, as e shall 2012-2016 (latest year available), the Top 10% income share in the Middle East was 61%. Source: Alvaredo, Assouad and Piketty (2017). See wir2018. wid. world for data series and notes. Part II t rends in Global inCome inequality omparing the Middle ast per ormance in While these results contradict the aforemen- terms of inequality with other countries in tioned studies, they are robust to different the orld is legitimate and in ormative at estimation techniques. When the income least as much as the usual inequality compar- distribution is computed using purchasing isons between nation-states.
5% 6. 6% 38. 2% 9. 1% 13. 9% 4. 2% Top 0. 001% 50. 2% 2. 9% 48. 0% 5. 7% 1. 5% 0. 2% Source: Morgan (2017). See wir2018. wid. world for data series and notes. Between 2001 and 2015, the Top 10% captured 57. 8% of total growth. Note to readers: During the twentieth century, the top 1% income share was halved between 1914 and 1993, falling from 20% to 10%. Even if these numbers must be qualified, as they are surrounded by a number of uncertainties, the trajectory is similar to that of other former dominions of the British Empire, and is partly explained by the country's economic and political instability during the 1970s and 1980s. During the early 1970s the previously constant racial shares of income started to change in favor of the blacks, at the expense of the whites, in a context of declining per capita incomes.
25% Share of national income (%) 10% 20% 15% Top 1% 5% 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 middle class is still very elusive. rather, two societies seem to coe ist in outh A rica, one en oying living standards close to the rich or upper middle class in advanced economies, the other left behind. (Figure 2. 12. 1) In 2014, the Top 1% share of national income was 21%. Source: Alvaredo & Atkinson (2010). See wir2018. wid. world for data series and notes.