copy the linklink copied!11.2. Income inequality and redistribution
Income inequality may have a negative impact on economic growth and generate social unrest due to disparities in access to economic opportunities and basic services, such as education and health care. Although recent evidence shows that income redistribution has improved in the region since 1990, some LAC countries are among some of the most unequal in the world, both in terms of income and access to services (Brezzi and De Mello, 2016).
In LAC countries for which data are available, income inequality was lower in 2017 or the latest available year compared to 2000. Bolivia has reduced inequality the most (from a Gini coefficient of 0.59 in 2000 to 0.44 in 2014). Uruguay had the lowest inequality (with a Gini 0.40) and Paraguay the highest (0.52). However, income inequality is higher in all LAC than in the five most unequal OECD countries (which have an average Gini of 0.38).
Another way to look at inequality is to compare the share of income held by the top quintile of the population to that held by the bottom quintile (i.e., S80/S20). When such an indicator is considered, data show that most countries (with the exception of Paraguay) managed to reduce income inequality, when comparing 2000 or earliest available year with the latest available year. The largest improvements are observed in Bolivia, which in 2000 had an S80/S20 ratio more than three times higher than in 2014, and Ecuador, that more than halved its S80/S20 ratio over the same period.
Governments can reduce income inequality by applying a progressive tax policy, fighting policy capture of benefits by interest groups and redistributing income through transfers to poorer households. In LAC countries with available data, there are divergences regarding the role of government in reducing inequalities. For instance, in Brazil in 2013, the Gini after taxes and transfers was 0.47, down from 0.58 before taxes and transfers. This reduction was similar to that of the five most unequal OECD countries. The reduction is much smaller in Chile, where in 2017 the Gini before taxes and transfers was 0.50, only four points higher than after redistribution (0.46).
Although not comparable, recent evidence for a larger set of LAC countries shows that governments from the region play a much smaller role in reducing inequalities than in OECD countries (OECD, 2017). Additionally, vulnerable groups in LAC face the risk of falling back into poverty with a deterioration of economic conditions (Brezzi and De Mello, 2016).
Income refers to household disposable income (i.e. income after taxes and transfers) and household market income (i.e. income before taxes and social transfers). To account for economies of scale within the household (i.e. any additional household member needs a less than proportionate increase of household income in order to maintain a given level of welfare), household income is equivalised by diving it by the square root of the household size (i.e. used is that of household “equivalised”: the total household income is adjusted with an equivalence scale of 0.5 ). The Gini coefficient is the standard measure of inequality. It is 0 when all households have identical income and 1 when one household has all the income. Income redistribution is gauged here in terms of the difference between Gini at disposable and market income. Another measure of inequality is the income quintile share ratio (S80/S20), which is obtained by dividing the share of total income received by the 20 % of the population with the highest disposable income (top quintile) over that received by the 20 % with the lowest disposable income (lowest quintile). For more information see http://www.oecd.org/els/soc/IDD-ToR.pdf
Data for OECD countries, as well as Brazil and Costa Rica are from the OECD Income Distribution Database (IDD).Data for the rest of LAC comes from the 2015/16 OECD project “Monitoring Inequalities and Fostering Inclusive Growth in Emerging Economies” estimates based on micro-data from household surveys, available through CEDLAS (Centre for Distributive, Labor and Social Issues in Latin America, Universidad Nacional de La Plata, Argentina). Estimates are based on the same definitions and methodologies used for OECD countries. Data for Bolivia, the Dominican Republic, Ecuador, Panama, Paraguay, Peru and Uruguay are not fully comparable to the OECD countries due to diverging methodologies.
Further reading
Balestra, C. et al. (2018), “Inequalities in emerging economies: Informing the policy dialogue on inclusive growth”, OECD Statistics Working Papers, No. 2018/13, OECD Publishing, Paris, https://doi.org/10.1787/6c0db7fb-en.
Brezzi, M. and L. De Mello (2016), “Inequalities in Latin America: Trends and implications for growth”, Hacienda Pública Española, Vol. 219/4, pp. 93-120.
Figure notes
The five most unequal OECD countries (excluding Chile and Mexico) are the United Kingdom, Korea, Lithuania, Turkey and United States. Data for the latest year are 2013 for Brazil, 2016 for Mexico, 2017 for Chile and 2018 for Costa Rica are 2018. For all other countries data are 2014. Data for Brazil refer to 2006, for Chile to 2009, for Costa Rica to 2010 and for Mexico to 2012 instead of 2007. Only countries with the same colour bar should be compared.
11.7 Data only available for countries included in the IDD
Source: Balestra, C., et al. (2018), «Inequalities in emerging economies: Informing the policy dialogue on inclusive growth», OECD Statistics Working Papers, No. 2018/13, OECD Publishing, Paris, https://doi.org/10.1787/6c0db7fb-en.for Bolivia, the Dominican Republic, Ecuador, Panama, Paraguay, Peru, Uruguay and OECD Income Distribution Database, https://stats.oecd.org/Index.aspx?DataSetCode=IDD for all the other countries.
Source: Balestra, C., et al. (2018), «Inequalities in emerging economies: Informing the policy dialogue on inclusive growth», OECD Statistics Working Papers, No. 2018/13, OECD Publishing, Paris, https://doi.org/10.1787/6c0db7fb-en.for Bolivia, the Dominican Republic, Ecuador, Panama, Paraguay, Peru, Uruguay and OECD Income Distribution Database, https://stats.oecd.org/Index.aspx?DataSetCode=IDD for all the other countries.
Source: OECD Income Distribution Database, https://stats.oecd.org/Index.aspx?DataSetCode=IDD
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