dataesr/scientific-paragraphs-categorization huggingface dataset:
We should make clear, however, that a lot of progress needs to be made before we can present a fully integrated approach. The present report should be viewed as one step in this direction. For example, in Part IV of the report, we are able to fully analyze the joint evolution of inequality of income and wealth for a number of countries (in particular, the United States and France). Doing so requires careful measurement not only of the inequality of pre-tax and post-tax income, but also of the distribution of saving rates across the different deciles of the distribution of pre-tax income. This kind of analysis will gradually be extended to more and more countries, as more data become income It reflects a nation s income more closely than Gdp does. the Wid. world database combines macroeconomic data from different sources in order to produce national income series for about two hundred countries.
these national income estimates are consistent ith those o international organi ations, ith one important improvement: our series address the issue that some income is missing rom published national accounts In the o ficial data, oreign income paid is higher than oreign income received at the global level because some o the income received in ta havens is no here recorded e allocate this global missing income dra ing on methods first developed by zucman (2013). 7  otal fiscal income as measured by ta data is always less than national income (as measured in the national accounts). part of the di erence is due to ta -e empt income flo s such as imputed rent (the rental value of o ner-occupied housing and undistributed profits the profits o corporations not distributed to individuals but ultimately benefitting owners of corporations).
Share of household wealth (%) Between 2000-2009, the average wealth share of the Top 0. 01% in Scandinavia was 4. 8%. 0. 7 percentage points of this wealth was held offshore. Source: Alstadsaeter, Johannesen and Zucman (2017). See wir2018. wid. world for data series and notes. All wealth excluding offshore Offshore wealth  When measured using market exchange rates, the top 10% share reaches 60% today, instead of 53% when using purchasing power parity (PPP) exchange rates. Global income growth dynamics are driven by strong forces of convergence between countries and divergence within countries. Standard economic trade models fail to explain these dynamics properly-in particular, the rise of inequality at the very top and within emerging countries. Global dynamics are shaped by a variety of national institutional and political contexts, described and discussed in the following chapters of this report.
We stress at the outset that the production o global ine uality dynamics is in its in ancy and will still require much more work. it is critical that national statistical and ta institutions release income and wealth inequality data in many countries where data are not available currently-in particular, in developing and emerging countries esearchers also need to thoroughly harmoni e and analyze these data to produce consistent, comparable estimates. the World inequality lab and the Wid. world research consortium intend to continue contributing to these tas s in the coming years even if there are uncertainties involved, it is already possible to produce meaning ul global income inequality estimates. the Wid. world database contains internationally comparable income ine uality estimates covering the entire population, from the lowest to the highest income earners, or many countries: the united states, China, india, russia, brazil, the middle east, and the major european countries (such as france, Germany, and the nited Kingdom A great deal can already be in erred by comparing ine uality trends in these regions sing simple assumptions, e have estimated the evolution of incomes in the rest of the world so as to distribute 100% o global income every year since and that these are relatively low inequality levels by historical standards (piketty, 2014).
in europe, russia, and north america, income gro th as lo er than , , and , respectively Behind these heterogeneous average gro th tra ectories, the di erent regions all share a common, stri ing characteristic. In all these countries, income gro th is systematically higher or upper income groups In hina, the bottom earners gre at less than hile the top gre at more than he gap bet een the bottom 50% and the top 0. 001% is even more important in india (less than 110% versus more than 3 000%). in russia, the top o the distribution had e treme gro th rates this reflects the shi t rom a regime in hich top incomes were constrained by the commu-   In this chapter on global income inequality, we have ultimately distributed the totality of global income, to the totality of the world population. To achieve this, we had to distribute the quarter of global income to the third of the global population for which there is currently no consistent income inequality data available.
Sub-Saharan Africa is a particular case: we did not have any country with consistent income inequality data over the past decades (whereas in Asia we have consistent estimates for China and India, in Latin America, we have estimates for Brazil, etc. ). For Sub-Saharan Africa, we thus relied on household surveys available from the World Bank (these estimates cover 70% of Sub-Saharan Africa's population and yet a higher proportion of the region's income). These surveys were matc ed wit scal data a ailable from WID. world so as to provide a better representation of inequality at the top of the social pyramid (see Part I). Doing so then allowed us to produce a global distribution of income. The methodology we followed a is available on wir2018. wid. world, as well as all the computer codes we used, so as to allow anyone make alternative assumptions or contribute to extend this work.
Share of national income (%) In 2014, 13% of national income was received by the Bottom 50% in the US. Pre-tax national income is measured after the operation of pension and unemployment insurance systems (which cover the majority of cash transfers), but before direct income and wealth taxes. Source: Piketty, Saez and Zucman (2018). See wir2018. wid. world for data series and notes. Top 1% average pre-tax income (constant 2016 $) Bottom 50% average pre-tax income (constant 2016 $) In 2014, the average pre-tax income of the Top 1% was $ 1 337 000. Pre-tax national income is measured after the operation of pension and unemployment insurance systems (which cover the majority of cash transfers), but before direct income and wealth taxes.
Post-tax Source: Piketty, Saez and Zucman (2018). See wir2018. wid. world for data series and notes. Although post-ta ine uality has increased significantly since , it has risen at a slo er rate than pre-ta ine uality As can be seen in Figure  2. 4. 4, the share of total income attributable to the top 10% rose from to post-ta , and rom to pre-ta bet een and ignificant ta increases implemented in or those ith the largest incomes may have played a role in the slo er gro th o post-ta topincome shares relative to pre-ta income shares over the last few years. overall, redistributive policies have prevented post-ta ine uality rom returning all the ay to pre new deal levels (as discussed in more detail belo urther reducing ta es on top earners, as envisioned by the current administration and congress, could sharply increase post-ta income ine uality in coming years (box 2.
Bottom 50% Source: Piketty, Saez and Zucman (2018). See wir2018. wid. world for data series and notes. In this chapter, we present estimates of pre-and post-tax income inequality for the USA, which are two complementary concepts for the analysis of inequality. Comparing pre-and post-tax income inequality allows to better assessing the impact of personal taxes and in-kind transfers on the dynamics of income inequality. In the WID. world database, pre-tax income refers to incomes measured before personal income and wealth taxes and in-kind transfers (typically health transfers) but after the operation of the pension and employment insurance systems (as well as after Social security and disability transfers in the case of the United States). In contrast, post-tax income refers to incomes measured after all taxes (in particular, after direct personal and wealth taxes) and after all government transfers (cash and in-kind).
Post-tax income excluding transfers In 2014, the average pre-tax labor income of men aged 20-64 years old was 1. 76 times greater (76% higher) than the average pre-tax labor income of women aged -years old re-ta labor income is composed o ages as ell as pensions, social security, and unemployment insurance benefits, minus the corresponding contributions. Source: Piketty, Saez and Zucman (2018). See wir2018. wid. world for data series and notes.
4% average annual increase in their real income, while between 1983 and 2014 their real income increased by 0. 9% on average per year. 1983-2014   1950-1983   Income group (percentile) Source: Garbinti, Goupille-Lebret and Piketty (2017). See wir2018. wid. world for data series and notes. Why has there been a rise in top incomes over the recent period? In the case of France, top earners have experienced significant increases in their incomes from both labor and capital. Between 1983 and 2013, the labor income of the top 0. 01% rose 53%, while their capital income increased by 48%. It is di ficult or standard e planations based on technical change and the changing supply and demand of skills to explain rising income concentration at the very top, whether around the world or in rance specifically  19  The rise of labor incomes at the top is more likely to be the result of evolutions in institutional factors governing pay-setting pro-cesses for top managerial compensation, including changes in corporate governance and the decline of unions and collective bargaining processes.
Part II trends in Global inCome inequality Investigating the evolution o ine uality using German income ta data has a long tradition, as particularly russian and a on ta data are internationally praised or their accuracy. simon kuznets partly drew his amous hypothesis o rising ine uality in the early phase of industrialization from prussian income ta data he early introduction o modern income ta ation in German states at the end of the nineteenth century offers a special opportunity to compute inequality series from the industrialization phase until today the series presented in this chapter are based on pre-ta income data rom historical German income-ta statistics collected by Charlotte bartels. one should note, however, that the impressive length o the period covered in Germany comes with a price, in that changing territories are covered by the series.
Middle 40% Source: Chancel & Piketty (2017). See wir2018. wid. world for data series and notes. epitomized by the seventh plan (1985-1990)  led by prime minister rajiv Gandhi (1984hat plan promoted the rela ation o mar et regulation, ith increased e ternal borro ing and increased imports hese free-market policy themes were then further embedded in the conditions attached to the international monetary fund's assistance to india in its balance of payment crisis in the early 1990s, which pushed further structural re orms or deregulation and liberali ation his period also sa the ta system undergo gradual trans ormation, ith top marginal income ta rates alling rom as high as in the 1970s to 50% in the mid-1980s. he structural changes to the economy along ith changes in ta regulation, appear to have had significant impact on income ine uality  in.
Within-country inequality is likely to be high in middle east countries Income ta data is un ortunately e tremely limited in the middle east and therefore prevents a detailed and precise analysis of within-country inequality. it is unfortunate that the only country for which data is currently available is lebanon, as household surveys in the middle east appear to underestimate top incomes at least as much as in the rest of the world (and possibly more). the Lebanese data confirms the general finding that top income levels reported in ta data are much higher than in household surveys: top 1% incomes are typically two to three times higher, ith large variations across income levels and over years. he lac o good data is particularly acute in the case of the Gulf countries, where the low o ficial Gini coe ficient might indeed hide important aspects of their political economy, namely the gro ing share o the non-national population, a large ma ority o hich is composed o lo -paid or ers, living in di ficult conditions he substantial gro th o migrant or ers in Gul countries give incentives to nationals within Gulf countries to de end their numerous privileges, beginning by restraining naturali ation given that national citizens typically do not pay income ta , benefit rom significant social spending, including ree healthcare and education, receive subsidies for electricity and fuel, and o ten receive other benefits such as land grants urthermore, some citi ens also have e pectations that the state provides them ith a ob and housing, an idea enshrined in some Gulf country constitutions.
Value of net national wealth (% of national income) In 2015, the value of net national wealth in China was 487% of net national income, i. e. it was worth 4. 9 years of national income. Net national wealth is equal to net private wealth plus net public wealth. Net private wealth is equal to new private assets minus net private debt. Source: WID. world (2017). See wir2018. wid. world for data series and notes. to compare how these countries' wealthincome ratios have evolved. this is particularly interesting given the changes in political and economic regimes e perienced in the emerging orld over the period considered as depicted in Figure  3. 1. 2, China and russia both e perienced large rises in their private wealth-income ratios after their transitions a ay rom communism hile to some e tent these increases are to be e pected as a large proportion of public wealth is transferred to the private sector , the scale o change e perienced is particularly stri ing in hina he comparison with the trajectories observed in developed countries is also of particular interest (about which more will be said below).
Share of net public wealth in net national wealth (%) In 2015, the share of public wealth in national wealth in France was 3% against 17% in 1980. Net public wealth is equal to public assets minus net public debt. Net national wealth is equal to net private wealth plus net public wealth. Source: Piketty, Yang and Zucman (2017). See wir2018. wid. world for data series and notes. the accumulated fund for the uk would have been very considerable some billion , or about o the Nor egian und As the K is a larger country, the und ould have represented a smaller percentage o national income, but nevertheless, the fiscal cushion would have enabled the uk's net worth to be positive in rather than negative today recent evolutions in wealth-income ratios are likely the result of economic policy decisions and country-specific contexts he ollo ing chapters provide a more detailed analysis of why wealth-income ratios developed as described above in developed countries since the 1970s (chapter 3.
urthermore, because saving and gro th rates are largely determined by di erent orces, ealth-income ratios can vary a great deal between countries. this fact has important implications or financial regulation ith per ect capital mar ets, large variations in ealth-income ratios potentially imply large net oreign asset positions, hich can create political tensions between countries. With imperfect capital markets and home portfolios bias, structurally high ealth-income ratios can contribute to domestic asset price bubbles such as those seen in Japan and spain. ousing and financial bubbles are potentially more devastating hen the total stoc o ealth amounts to si to eight years o national income rather than only two to three years. the fact that the Japanese and spanish bubbles are easily identifiable in the dataset also suggests that monitoring ealth-income ratios may help designing appropriate financial and monetary policy.
Value of wealth (% of national income) In 2015, the value of net private wealth was equivalent to 487% of net national income, i. e. it was worth 4. 5 years of national income. Chinese public wealth was equal to 223% of national income. Net national wealth is equal to net private wealth plus net public wealth. Net private wealth is equal to private assets minus private debts. Net public wealth is equal to public assets minus public debts. Source: Piketty, Yang and Zucman (2017). See wir2018. wid. world for data series and notes. ParT III Public versus Private caPital dynamics regional development policies sometimes more e ficiently and sometimes less so It also has potentially considerable fiscal conseuences, as governments ith negative net public ealth typically have to pay large interest payments be ore they can finance public spending and el are trans ers, hile those ith large positive net public ealth can benefit rom substantial capital incomes, enabling them to finance more public spending than ould be possible through ta collection It is interesting to compare the evolution o the public share in national wealth in China and a resource-rich country ith a large sovereign ealth und such as Nor ay hese two countries have essentially switched positions: the public share in hinese national declined from 70% to 30% between 1978 and 2015, while it rose from 30% to 60% in norway over the same period (see Figure  3.
Net foreign assets Trade surplus (net exports) Source: Novokmet, Piketty and Zucman (2017). See wir2018. wid. world for data series and notes. Given the large trade surpluses (9. 8% of national income per year between 1993 and 2015, i. e. a cumulated trade surplus over 200% of national income), net foreign assets accumulated by Russia are surprisingly small (26% in 2015). urthermore, the capital gains and losses reali ed on the port olio o oreign assets and liabilities needs to be accounted for. these portfolio effects can be substantial if there are large di erences bet een annual surpluses and the observed evolution of net oreign assets his is partly hat happened in ussia as oreign investors bought ussian (about 70-80% of national income in both cases). that is, they own about 50% of their total financial ealth o shore hese results are similar to estimates obtained by Gabriel zucman's earlier research that used a di erent methodological approach 22 thus they can be vie ed as some hat reassuring But hile these magnitudes are believed to be broadly accurate, these estimations lack absolute precision given the general lac o international financial transparency and the di ficulties o identi ying by hom these missing assets are o ned and hat orm they ta e potentially pose even greater challenges even more uncertain is the location of the assets held offshore by russian citizens.
4. 2 ComParing trends in Personal wealth inequality aCross the world Available data on personal wealth inequality shows that it has been on the rise in most countries since the early or late eighties. Increasing income inequality and the large transfers of public to private wealth which occurred over the past forty years drive these dynamics. Large rises in top wealth shares have been experienced in China and Russia following their transition from communism towards a capitalist economy, though the different inequality dynamics experienced between these two countries highlights different economic and political transition strategies. In the United States, wealth inequality has increased dramatically over the last 30 years and was mostly driven by the rise of the top 0. 1% wealth owners. Growing inequality of income and saving rates created a snowballing effect of rising wealth concentration.
the publicly available information discussed in this report and published on Wid. world on the distribution of wealth and cross-border assets is still imper ect But e see it as a fist systematic attempt at generating data on ealth ine uality over the globe It combines in a consistent manner ta data, ealth surveys and data on cross-border assets. the construction of estimates presented in this report was carried out for China, france, ussia, pain, the nited Kingdom and the united states which are presented in this chapter and the subsequent ones.
Bottom 50% Source: Garbinti, Goupille-Lebret and Piketty (2017). See wir2018. wid. world for data series and notes. tive ta rates or top income and ealth groups quickly reached very substantial levels, for e ample , and sometimes even more. 15  in the likely scenario that top wealth holders reacted by reducing their consumption levels and living standards less than the increase in ta hich came in addition to a negative shoc to their pre-ta capital incomes , then in e ect, they had to reduce their saving rate after 1945, those at the bottom and in the middle of the wealth distribution saved at higher rates than be ore, during the highgro th post ar decades due to some orm o habit ormation e ect hereby individuals were prudent with their consumption and saved earnings in case o shoc s or crises.
Including housing wealth Source: Martínez-Toledano (2017). See wir2018. wid. world for data series and notes. But i housing concentration increased at the top during the bubble and decreased thereafter, why has total wealth concentration remained virtually unchanged ne plausible e planation is that individuals ithin the top substituted financial assets or property during the period o the housing boom, but then accumulated greater financial assets hen house prices began to all he raction o total financial assets held by the top decreased during the boom years his is consistent with the idea that wealthy individuals can better diversify their portfolios, and have the capabilities to invest more in ris y assets, hen prices are increasing and can more easily disinvest when prices fall, to then acquire other assets.
Middle 40% Source: Martínez-Toledano (2017). See wir2018. wid. world for data series and notes. o housing assets as acilitated through borro ing A ter the property bubble burst, the top sold some o their housing assets and started to accumulate more financial assets to compensate for the decrease in housing prices Nonetheless, the total savings rate or the top decreased during these years, likely because they needed to consume a larger raction o their income he middle 40% instead started to save more in order to repay their housing mortgages, and there ore the di erence in saving rates across the t o ealth groups as reduced hese t o trends thus contributed to neutrali ing ealth concentration during pain s tumultuous period o housing price s ings ealth ine uality has also been amplified by the variance in the rates of return on assets o ned by di erent ealth groups in pain over the 1986-2012 period.
Share of personal wealth (%) In 2013, the wealth share of the Top 1% was 20% of total wealth. However, when excluding housing wealth, the Top 1% share was 33%. Source: Alvaredo, Atkinson and Morelli (2017). See wir2018. wid. world for data series and notes. The future of global income inequality is likely to be shaped by both convergence forces (rapid growth in emerging countries) and divergence forces (rising inequality within countries). No one knows which of these forces will dominate and whether these evolutions are sustainable. However, our benchmark projections show that if within-country inequality continues to rise as it has since 1980, then global income inequality will rise steeply, even under fairly optimistic assumptions regarding growth in emerging countries. The global top 1% income share could increase from nearly 20% today to more than 24% in 2050, while the global bottom 50% share would fall from 10% to less than 9%.