The article illustrates the degree of wealth in various Latin American economies and the process of wealth concentration towards billionaires (super-rich) and the highest economic strata to the detriment of the affluent, the upper-middle classes, and the middle classes –with the exception of Chile, Peru, and several other economies. Although Latin America has a high concentration of wealth, its Gini coefficient is lower than that of other regions of the world. A clear upward trend in the concentration of wealth in the region and the world can be seen throughout the period analyzed.

High levels of economic inequality are currently a global challenge. Even the World Economic Forum (2018), which brings together major business leaders and governments of the world, has identified economic inequality as one of the major trends and risks the global economy faces. Given the economic, social, and political impacts in the short, medium, and long term, phenomena such as increasing disparities in wealth and income are universal concerns, as are climate change, an aging population, and the increasing polarization of societies, to name just a few. Put another way, economic inequality negatively affects the level and variability of economic activity (Ostry et al., 2014), intensifies social conflicts, and increases economically powerful groups’ capacity to shape policies according to their particular interests (OXFAM, 2016).

Within the debate surrounding this issue, there is some agreement on the evolution of global and internal economic inequality. Bourguignon [2017 (2012)] and Milanovic [2017 (2016)] argue that, since the 19^th century, there has been an upward trend in the concentration of income, with a slowdown and then decrease between the 1950s and 1970s, after which the upward trend resumed. This article focuses on the period from the 1990s onward, due to the heightened expansion of the middle classes in emerging economies in this period. However, when we review the data from these countries, it becomes clear that the functional income distribution in favor of capital increased its share of wages from the 1980s onwards. This favored the richest 10% of the population (ECLAC, 2018; OECD, 2008; Piketty, 2014; Piketty and Saez, 2003).

This dilemma is nothing new in Latin America.¹ Factorial income distribution shows a sinusoidal trajectory in terms of the share of wages and profits (Alarco, 2014 and 2017). Here, despite national particularities, the highest share of wages occurred during the golden age of capitalism (the 19960s). There have been improvements in recent years, but they are mainly the result of policy decisions, especially in Brazil and Argentina. However, according to scholars such as Lustig and López-Calva (2010), the Gini index of personal income distribution fell, meaning that the structural reforms implemented since the 1990s have been successful. Nevertheless, these authors forget that household income surveys omit high-income (and upper-middle-income) sectors, foreign capital gains, and the increasingly significant processes of mergers and acquisitions that concentrate capital ownership in a few hands.² Solimano (2016) also criticizes these optimistic assessments, using data on high-income groups, wealth distribution, and tax data that reflect higher levels of inequality.³ In classical economics, analyzing wealth distribution, particularly the ownership of the means of production or productive wealth, is crucial when seeking to understand functional income distribution between capital and labor. Wealth is defined as the sum of individually-owned productive and financial assets in any given economy; net wealth, meanwhile, is calculated by deducting individuals’ debts or liabilities from their assets. Ownership of productive assets determines the ratios between income or rent in favor of capital, on the one hand, and income from remuneration (wages and salaries) or mixed income (from self-employed work) on the other. In turn, personal income distribution is conditioned by a number of variables, which are themselves affected by a set of structural and economic (both national and international), social, political, institutional, and personal factors. Fiscal policy (tax and social spending) significantly impacts distributive outcomes (Baéz Melián, 2018).

This article evaluates the extent and concentration of productive wealth in Latin America, using data from the World Bank and estimates from independent sources such as Credit Suisse, Forbes, and Knight Frank. In contrast to studies focused on more developed economies, the present study employs data from independent sources as, unfortunately, in the Latin American region there are no official statistics derived from household asset and debt surveys, estate and inheritance tax records, and information on investment income.

This article seeks to answer the following questions: what is the value of productive wealth in the main Latin American economies? What is the importance of billionaires in the region? How is wealth distributed and concentrated according to different estimates? And; what happens to wealth inequality within the region, between regions, and over time? The article is structured in four sections, in addition to the introduction and conclusion. The first section outlines both the criteria for measuring wealth and the various data sources used. The second section describes various absolute measures of wealth for various Latin American economies. The third section then presents data from the Forbes billionaires list, followed by the more detailed wealth distribution structures of Credit Suisse and Knight Frank. Finally, we make some interregional and intraregional comparisons.

Measuring wealth is a complex task, as most statistical information systems do not keep track of the capital stock accounts for national economies. Goldsmith (1962) was among the first to attempt to measure wealth. He began by measuring the flows of gross investment, net investment, and depreciation expenses for each type of asset considered in the U.S. national wealth. These estimates factored in assets’ useful life, deducting this from assets’ value by the depreciation coefficient estimated for each of them using the perpetual inventory formula.

Davies and Shorrocks (2000) use a microeconomic approach to measure wealth and its distribution, using data obtained from individuals and households, citing various data sources. The first type of data comes from household surveys that record asset and debt holdings. However, such data is made less reliable by sampling or reporting errors (some households have low levels of education, refuse to respond, underreport ownership of certain assets, or undervalue assets). The second data source is wealth and property tax data obtained from wealth tax records or from constructing multipliers pertaining to estate tax. Potential problems with wealth tax data is that it may not include certain types of wealth (e.g., consumer durables), or may undervalue certain assets. Furthermore, property tax data may be undervalued, either as it does not include property below the tax collection threshold or because it omits wealth that is exempt from taxation.

The income capitalization method can be used to measure wealth using data on income (Giffen, 1913). If income tax data is available, the investment income data can be divided by the corresponding capital gains tax share. Finally, it is possible to use published statistics on certain individual’s or families’ wealth or asset holdings (information that can be found in databases, for example at Forbes or Fortune).

Davies et al. (2010) use a macroeconomic approach to construct balance sheets from data on households’ financial and non-financial wealth. They analyzed 19 countries, mainly high-income countries, as well as some upper-middle-income countries. This data was complemented with data from household surveys, so as to include statistics from regions such as Asia, Africa, and Latin America and the Caribbean. These authors found that these countries’ wealth predominantly consists of non-financial assets. They argue that assets such as land and farms are more common in less developed countries, while financial assets are more important in rich countries. In developing economies, financial assets are mainly savings accounts, while in rich countries such assets are mainly stock holdings.

Roine and Waldenström (2015) contribute to the debate on wealth by reviewing the empirical literature on long-term data series. Net wealth consists of the sum of real and financial assets minus debt. Real assets include property, land, consumer durables, and some luxury goods. Financial assets include cash, bank deposits, insurance accounts, pension deposits, stocks, bonds, and other types of stock holdings. Debts are the sum of mortgages and consumer, investment, and educational loans. When valued at market prices, the value of net wealth becomes very sensitive to everyday fluctuations. The calculations factor in pension accounts or values of durable consumer goods adjusted for reporting problems or valuation difficulties., for various European countries and the U.S. during the period 1740-2011.

Saez and Zucman (2016) reconstruct total household wealth in the U.S. in two steps: the post-1945 period is calculated using household balance sheets taken from U.S. financial accounts; the 1913-1945 period, meanwhile, is calculated using various reconstruction techniques based on the post-1945 figures. After obtaining this aggregate, the authors calculate capital income distribution using individuals’ tax records, which were obtained from official sources and various studies. Alvaredo et al. (2019) present their findings on wealth and its distribution for economies such as the United States, France, Spain, and the United Kingdom, using a combination of household wealth surveys, income taxes that use the income capitalization method, and inheritance tax data that also use an inheritance multiplier. Pitketty (2019) discusses the estimates also available for Germany and Sweden, as well as several other economies. De Rosa (2019), on the other hand, uses the previously mentioned methodologies to determine aggregate results for Uruguay.

This study primarily uses data obtained from four sources: the World Bank, Credit Suisse, Forbes, and Knight Frank. The first source contains data on the value of wealth, as well as other macroeconomic information. The World Bank (2018a) understands productive capital as manufactured or constructed assets such as machinery, equipment, and physical structures, including the value of urban land. Capital stock is estimated using the perpetual inventory method adopted by the majority of member states of the Organization for Economic Cooperation and Development (OECD). This international organization makes use of data from the Penn World Table 9.0 database, which estimates the capital stock in 172 countries for the period 1970 – 2014, using the perpetual inventory method to estimate. Credit Suisse defines wealth as net worth, which is the commercial value of financial and non-financial assets minus debt.

Financial assets consist of cash, bank deposits, and shares. One of the obstacles to calculating wealth is that no country has a single, comprehensive source of data on personal wealth. For example, low- and middle-income countries have little data. The methodology is, therefore, essentially a bottom-up approach, which begins by establishing the average wealth level in the various countries where the pattern of wealth holdings is derived from household surveys and other sources.⁴ Underestimation problems necessitate adjustments when constructing estimates on the number of wealthy individuals and the size of their holdings. The upper tail of the wealth distribution is usually estimated using the Pareto distribution.⁵ The Forbes list is also used to determine the precise shape of the upper wealth tail.

Knight Frank, on the other hand, is more concise. As with the previous source, it counts financial and non-financial assets minus debt. Furthermore, its main source of data is simple, being based on responses from nearly 900 of the world's leading private bankers and wealth advisors, representing more than 10,000 clients with a combined wealth of about $2 trillion. New World Wealth⁶ provides the data on wealth distribution, showing historical and projected growth in five ranges at the regional, national, and major city levels.

Various wealth estimates produced by both the World Bank and Credit Suisse will now be presented. These obtain different results, due to the respective methodologies and study periods adopted by each source: 2005 and 2014 in one estimate and 2010, 2012, and 2016 in the other, respectively. Table 1 also shows the GDP for 2014 and the capital-output ratio as the ratio of productive wealth from both statistical sources to output.

According to World Bank data for 2014, the economy with the highest levels of wealth was Brazil, followed by Mexico and Argentina. At an intermediate level were Venezuela, Colombia, Chile, and Peru; the remaining economies, meanwhile, had lower wealth values, reflecting their smaller size. On the other hand, it should be noted that the Credit Suisse estimates are, in all cases, lower than those made by the World Bank, with smaller differences in the cases of Chile, Costa Rica, El Salvador, and Peru. There will be multiple causes for these differences.

The number of billionaires in Latin America has grown over time. ⁷ Table 2 shows the data from Forbes for selected years. Between 2009 and 2016, the number of Latin American billionaires grew from 36 to 87. The economy with the most billionaires was Brazil, followed by Mexico, Chile, Argentina, Peru, Colombia, and Venezuela. The remaining economies in the region have no billionaires. It should be noted that, between 2014 and 2016, the number of billionaires in Brazil and Mexico decreased due to the increased depreciation of the local currency. In absolute terms, the country with the greatest level of wealth owned by the super-rich is Brazil, with US$172.1 billion, followed by Mexico with US$116.7 billion and Chile with US$41.4 billion. With lower levels of wealth are Venezuela with US$5.1 billion and Peru with US$8.4 billion. In Argentina, these net assets total US$12.4 billion.

As of 2016, the region’s 87 billionaires, have a net worth of US$373.2 billion, higher than the nominal GDP of Venezuela, Colombia, or Peru. In relative terms, Chile's super-rich have a net worth equivalent to 16.6% of Chile's GDP, followed by Mexico with 10.9% of the country's GDP, and then Brazil with 9.6% of the national GDP. The region's billionaires have a combined net worth equivalent to 8.3% of the regional GDP. When these net assets are expressed in relation to the productive wealth reported by the World Bank for 2014, the region's billionaires own 2.1% of total productive wealth, with higher values in Chile (5.2%), Brazil (2.6%), and Mexico (2.3%).

Figure 1 illustrates billionaires’ importance both at the global level and in Latin America, and shows the world's billionaires’ wealth as a percentage of global GDP and billionaires’ wealth in Latin American countries as a percentage of the region’s GDP for the period 1999-2016. Both ratios allow us to analyze the trend towards concentration of wealth in the hands of the super-rich in the two areas analyzed.

This trend of billionaires increasing their share of wealth is consistent with what Lanovic [2017 (2016)] proposed, in the sense that this trend intensifies over time. In 1999, billionaires’ wealth represented just under 4.3% of world GDP, while in 2016 their share was slightly over 10.1% of annual GDP. The same trend is evident at the regional level. In 1999, Latin America’s billionaires had wealth levels equivalent to 3.5% of regional GDP, growing to 8.3% by 2016. The 21^st century has so far witnessed an undeniable increase in wealth concentration in the hands of the world's richest people.

Tables 3 and 4 show wealth distribution in the region’s economies in the region; the difference is that Table 3 details 10 ranks for 6 economies in the region, while Table 4 only distinguishes between those with more than US$1 million and the lower ranks for 13 economies in the region. This graph presents the full extent of the details available in the data source. In absolute terms, the economies with the most millionaires are Brazil, Mexico, Chile, Peru, Colombia, and Argentina. The number of individuals owning wealth of more than US$100 million has grown from 1,108 in 2012 to 1,494 in 2016, at a rate of more than 7.8% per year, higher than the regional GDP growth rate of 0.8% per year. Furthermore, the number of people with a net worth between US$50 and 100 million has increased from 1,985 in 2016 to 1,667 in 2012, with an average annual growth rate of 4.5%. However, the number of those with US$5 to 50 million remained static in the countries analyzed; furthermore, the number of millionaires worth between US$1 and 5 million has fallen in Argentina, Brazil, Colombia, and Mexico due to the lower market value of their net worth. Only Chile and Peru saw a significant growth in the number of millionaires in the 1-5 million (US$) range.

Tables 3 and 4, detailing 6 and 13 economies, respectively, make it clear that the number of adults with a net worth between US$10,000 and 1 million has fallen in both groups, indicating a reduction in the middle and upper-middle classes’ net worth. In contrast, the number of adults with a net worth under US$10,000 has increased significantly across the region. The only economies where the number of adults with a net worth between US$100,000 and 1 million has increased are Bolivia, Ecuador, El Salvador, Nicaragua, Paraguay, and Peru. Additionally, the number of adults with a net worth of between US$10,000 and 100,000 has increased in Argentina, Bolivia, Colombia, Ecuador, El Salvador, Peru, and Uruguay.

Table 5, on the other hand, shows the percentage of wealth held by the richest sections of the population in four Latin American economies: Brazil, Chile, Colombia, and Mexico, in addition to the large regional groups. It details the share of total wealth held by the richest 10%, 5%, and 1%, respectively, of the population. The data used is from Credit Suisse for 2015 and 2016. There is no data on other economies in the region or for earlier periods. In this dimension, there is a greater concentration in Brazil and Chile, followed by Mexico and Colombia. In the regional average, the richest 1% have 42% of the wealth and the top 10% have 71.2% of the total wealth. With these results, Latin America is at an intermediate level in terms of wealth concentration, with levels higher than Europe and Asia Pacific and slightly above North America. However, Latin America has a lower concentration in the richest percentile than India, Africa, and China.⁸

The data from Knight Frank consists of just 10 economies, 3 ranges, and 1 year, similar to the Credit Suisse data (see Table 6). However, some common trends can be seen. First, the number of people with a net worth over US$100 million rose significantly between 2005 and 2016, from 588 to 1006 people. Second, there was also an increase in those with US$30 million to 100 million and, to a lesser extent, in those with a net worth between US$10 million and 30 million. Third, the number of people with a net worth of over US$1 million but less than 10 million increased compared to the base year, 2005. However, in Brazil, Colombia, Mexico, and Venezuela, total net worth values decreased between 2015 and 2016.

Table 7 shows the total number of millionaires in the respective economies as a percentage of the total population, as of 2016. The first column details those with a net worth over US$1 million and incorporates the two upper brackets presented in the table. There are overlaps between the two data sources, but also some differences. In any event, Chile has the highest percentage of millionaires of the total population, in all categories, followed by Peru, Brazil, Argentina, and Colombia, according to Credit Suisse data. However, when Knight Frank's data is used, the list is headed by Mexico, followed by Chile, Argentina, and Brazil. On the other hand, the biggest differences between Credit Suisse’s and Knight Frank’s statistical sources occur in the case of Peru. In the case of those with a net worth between US$1 and 100 million, the list is led by Chile, followed by Brazil and Mexico. Similarly, according to Credit Suisse data, Chile has the largest percentage of the population with more than US$100 million, followed by Peru and Brazil. Likewise, according to the Knight Frank data, Chile is first, followed by Mexico then Brazil.

Table 8 shows wealth concentration in the main Latin American economies. It also shows the Gini coefficient calculated by Credit Suisse for each particular economy. The regional Gini coefficient, meanwhile, is recalculated according to a weighted average of the purchasing power parity GDP for the period 210-2016, in constant US$ based on 2011 values as reported by the World Bank. In the case of Venezuela, the years 2015 and 2016 were adjusted for the drop in real output in 2015 and 2016, as reported by the International Monetary Fund (IMF).

The Gini coefficients are high in all cases, reflecting high wealth concentration. The economies with the highest wealth concentration for 2016 are Venezuela, Brazil, Peru, and Chile; those with the lowest concentration, meanwhile, are Uruguay, El Salvador, Costa Rica, Ecuador, Colombia, Panama, and Nicaragua. At an intermediate level are Argentina, Bolivia, Mexico, and Paraguay. A clear trend towards increase can be seen for Brazil and Chile across the series. There is a growing but fluctuating trend in Argentina, Peru, and Venezuela. In the remaining economies, such as Bolivia, Colombia, Costa Rica, Ecuador, El Salvador, Mexico, Nicaragua, Panama, Paraguay, and Uruguay, there is greater variability. The weighted average of the region's various economies shows a clear upward trend from a value of 0.77 in 2010 to almost 0.8 in 2016. A clear trend towards increased wealth concentration can be seen in the second five-year period of the 21^st century.

It is useful to compare data on concentration levels in Latin America with that of other regions, as well as the world average. To do so, we make use of regional data from Credit Suisse and the world average obtained according to each region’s weighting against the 2011 US$ purchasing power parity GDP. Table 9 shows the regions analyzed, using Credit Suisse's definition of Latin America and the Caribbean, which includes non-Spanish speaking nations and the Caribbean. It also shows the findings for Latin America, including the 15 economies considered. As in Table 5, all cases showed high levels of wealth concentration.

In 2010, the highest levels of concentration were found in the Asia Pacific region, followed by Africa. China and Latin America were among the regions with the lowest concentration levels. By 2016, the highest concentration levels in the world were in the Asia Pacific region followed by Africa, India, North America, and Europe. Latin America and China were the lowest. In general, wealth concentration is increasing in all regions, with Latin America, Asia Pacific, China, Europe, and India standing out, followed by Africa and North America. The world average Gini coefficient also has an upward trend, rising from almost 0.8 in 2010 to 0.86 in 2016. Wealth tends to become concentrated in fewer hands, as does income (Piketty, 2019).

Studying wealth levels and their concentration is a complicated task, given the lack of official data on the subject for most Latin American economies. There is, therefore, an urgent need for academia and civil society to put pressure on their respective governments to elaborate and make transparent the data on the subject. For the time being, an alternative method is to use independent sources. The problem with this, however, is that each source employs a particular methodology, therefore obtaining differentiated results. The World Bank estimates productive wealth using aggregate accounting values of gross capital formation. These results diverge from the independent sources’ market valuation criteria and, therefore, are subject to numerous economic, financial, social, and political variables.

Despite the differences between the data sources and the limited statistical series, several common trends can be identified. In the second decade of the 21^st century, there is an increasing trend towards higher levels of wealth concentration; this is consistent with what various international studies on this problem have pointed out, especially in regards to income concentration. However, there is no evidence available with which to analyze trends in the region before and during the golden age of capitalism.

The super-rich have increased in number and importance, both globally and regionally in Latin America. There is a clear upward trend in terms of their share of their respective GDPs so far in the 21st century. They have a greater absolute presence in Brazil, but greater in Chile in relative terms. Likewise, the number of people with wealth of over US$50 million has increased significantly for the region's economies as a whole; meanwhile, the number of those with between US$5 and 50 million remain stagnant and the number of millionaires owning between US$1 and 5 million has fallen due to the downturns in Argentina, Brazil, Colombia, and Mexico. According to Knight Frank data, the number of people in Latin America who own between US$1 and 10 million has fallen between 2005 and 2016. Only Chile and Peru show increases in this category of small millionaires.

In Latin America, the richest 1% of the population maintains 42% of the wealth. This share is higher than in Europe and Asia Pacific, and is slightly higher than in North America. On the other hand, the number of people with a net worth of less than US$10,000 increased significantly, while the number of people with a net worth between US$10,000 and 1 million decreased. This indicates a drop in the wealth of the middle and upper-middle sectors between 2012 and 2016, with some exceptions.

The Gini coefficients of wealth concentration in all of Latin America show a trend towards growth between 2010 and 2016. Within the region, Brazil, Argentina, Chile, Peru, and Venezuela have the same upward trend. In 2016, Venezuela, Brazil, Peru, and Chile were the economies with the highest levels of concentration. The world's Gini coefficient also shows an upward trend. According to the data obtained from Credit Suisse, Latin America has very high and growing levels of wealth concentration, but lower than other regions of the world.

The fact that Latin America is not the region with the highest levels of wealth concentration is no great consolation, given that the Gini coefficients are extremely high, which produces factorial and functional income distribution in favor of profits and high concentration of personal income distribution. Unlike in more developed economies, the redistributive role of fiscal policy is less significant in Latin America. Inheritance taxes are either non-existent, very small, or recent additions. For this reason, there are reduced possibilities for more equitable personal income distribution.

Alarco, G. (2014), “Participación salarial y crecimiento económico en América Latina 1950-2011”, Revista CEPAL, no. 113. Available at <https:// www.cepal.org/es/publicaciones/36958-participacion-salarial-crecimien- to-economico-america-latina-1950-2011>

______ (2017), “Ciclos distributivos y crecimiento económico en América Latina”, Cuadernos de Economía, vol. 36, no. 72, doi <10.15446/cuad. econ.v36n72.65819>

______ (2018), “Mergers and acquisitions in Latin America 1990-2014: factorial distribution and contractionary impacts”, Metroeconomica, vol. 69, no. 3, doi <https://doi.org/10.1111/meca.12208>

Alarco, G., Castillo, C. and Leiva, F. (2019), Riqueza y desigualdad en el Perú: visión panorámica, Lima, OXFAM.

Alvaredo, F. and Gasparini, L. (2015), “Recent trends in inequality and poverty in developing countries”, Handbook of Income Distribution, Amsterdam, Elsevier.

Alvaredo, F., Chancel, L., Piketty, T., Saez, E. and Zucman, G. (2019), Informe sobre la desigualdad global 2018, México, Libros Grano de Sal.

Báez Melián, J. (2018), “Los efectos de la política fiscal sobre la desigualdad”, Revista de Economía Mundial, no. 49, doi <http://dx.doi.org/10.33776/ rem.v0i49.3890>

Banco Mundial (2011), The changing wealth of nations 2011, Washington, D.C., The World Bank.

______ (2018a), The changing wealth of nations 2018: Building a sustainable future, Washington, D.C., The World Bank.

______ (2018b), World development indicators, <http://databank.banco- mundial.org/data/reports.aspx?source=2&country=PER>

Bourguignon, F. [2017 (2012)], La globalización de la desigualdad, México, Fondo de Cultura Económica.

CEPAL (2018), La ineficiencia de la desigualdad 2018. Trigésimo séptimo periodo de sesiones de la CEPAL, Santiago, United Nations.

Credit Suisse (2011-2017), Global Wealth Databook 2010, Zurich, Switzerland.

Davies, J. and Shorrocks, A. (2000), “The distribution of wealth”, in A. Atkinson and F. Bourguignon (eds.), Handbook of Income Distribution, vol. 1, Holand, North Holland.

______, Sandström, S., Shorrocks, A. and Wol, E. (2010), “The level and distribution of global household wealth”, The Economic Journal, vol. 121, no. 551, doi <https://doi.org/10.1111/j.1468-0297.2010.02391.x>

De Rosa, M. (2019), Wealth accumulation and its distribution in Uruguay: First estimates of the untold half of story. Public Policies and Development Master Thesis, Paris, Paris School of Economics.

Fondo Monetario Internacional (FMI) (2018), International Financial Statistics, International Monetary Fund. Available at <https://data.imf. org/?sk=4c514d48-b6ba-49ed-8ab9-52b0c1a0179b>

Forbes (2010-2017), The Forbes world’s billionaires list, Forbes, New York, Forbes.

Foro Económico Mundial (2018), The global risks report 2018, Geneva, FEM.

Giffen, R. (1913), Statistics, Macmillan, London. Goldsmith, R. (1962), The national wealth of the United States in the postwar period, New Jersey, Princeton University Press.

Jiménez, J. (2015), Desigualdad, concentración del ingreso y tributación sobre las altas rentas en América Latina, Santiago, CEPAL.

Knight, F. (2014-2017), The wealth report: The global perspective on prime property and investment, London, Knight Frank Research.

Lustig, N. and López-Calva, L. (2010), Declining inequality in Latin America, a decade of progress? Washington, D.C., Brookings Institute.

Milanovic, B. [2017 (2016)], Desigualdad mundial. Un nuevo enfoque para la era de la globalización, México, Fondo de Cultura Económica.

Organización para la Cooperación y el Desarrollo Económicos (OCDE) (2008), Growing unequal? Income distribution and poverty in OECD countries, Paris, OCDE.

Ostry, J., Berg, A. and Tsangarides, Ch. (2014), Redistribution, inequality, and growth (IMF Staff Discussion Note SDN/14/02). http://www.imf.org/external/ns/search.aspx?hdCountrypage=&NewQuery=ostry+berg+tsangar ides&search=Search& lter_val=N&col=SITENG&collection=SITENG &lan=eng&iso=&requestfrom=&countryname=&f=

OXFAM (2016), Una economía al servicio del 1%. OXFAM Report 210, Oxford.

Piketty, T. (2014), El capital en el siglo XXI, México, Fondo de Cultura Económica.

______ (2019), Capital e ideología, Colombia, Editorial Planeta.

Piketty, T. and Saez, E. (2003), “Income inequality in the United States 1913- 1998”, The Quarterly Journal of Economic, vol. 118, no. 1, Oxford Academic.

Roine, J. and Waldenström, D. (2015), “Long-run trends in the distribution of income and wealth”, in A. Atkinson and F. Bourguignon (eds.), Handbook of Income Distribution, vol. 2A, North Holland.

Saez, E. and Zucman, G. (2016), “Wealth inequality in the United States since 1913: Evidence from capitalized income tax data”, The Quarterly Journal of Economics, vol. 131, no. 2. Available at <http://qje.oxfordjournals. org/>

Solimano, A. (2016), “Is inequality really declining in Latin America? Evidence on income, wealth and the social structure”, Revista de Economía Mundial, no. 43, DOI <http://dx.doi.org/10.33776/rem.v0i43.3859>

Trueba, C. and Remuzgo, L. (2016), Evolution of inequality in Latin America (1980-2014), Revista de Economía Mundial, 45, Spain, Universidad de Huelva. Available at <http://rabida.uhu.es/dspace/bitstream/handle/10 272/13731/Evolution_of_inequality%20.pdf?sequence=2>