Criteria and general evolution

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.

Methodologies and information sources

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.

Latin American Billionaires

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.

Source: Compiled by the authors using data from ^{Forbes (2010-2017)} and the ^{World Bank (2018a} and ^2018b)

Figure 1 Billionaires’ income as a percentage of GDP, in Latin America and the world 

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.

Concentration by strata

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.