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On Data and Trends in Income Inequality Around the World

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On Data and Trends in Income Inequality Around the World Research Report ON DATA AND TRENDS financial services. If inequality undermines individuals’ efforts, education choices and social mobility, however, IN INCOME INEQUALITY citizens may lose confidence in institutions and the AROUND THE WORLD political system. Political and social instability due to inequality, in turn, may reduce investments and subse- quently economic growth in the country (see Alesina and Perotti 1996). Apart from investments, research results suggest that FLORIAN DORN1 income distribution within countries matters for sus- tainable growth by affecting diverse growth drivers, such as human capital accumulation, innovation incen- The extent, drivers and consequences of income in- tives, labor productivity, and aggregate demand (for equality are one of the most hotly debated issues in an overview, see Dabla-Norris et al. 2015, 6ff.; OECD politics and research in recent years. In response to 2015, 60ff.). Theoretical predictions and empirical evi- the enormous interest in income inequality, a growing dence on the relationship of income inequality and eco- number of cross-national inequality databases are now nomic growth are ambiguous. available. This article discusses these databases and describes trends in income inequality (within selected On the one hand, higher inequality may shift the pref- countries) around the world. erences of the population and politicians towards more regulation and redistribution policies such as, for ex- ample, greater protectionism and redistribution (e.g. Causes and consequences – why do we care about via higher taxation), which may, in turn, hamper eco- income inequality? nomic growth (see Okun 1975; Bertola 1993; Alesina and Rodrik 1994; Persson and Tabellini 1994; Perotti In the discussion on inequality it is important to distin- 1996; Claessens and Perotti 2007). Higher income guish between inequality of outcomes, and inequality inequality may also negatively impact health and ed- of opportunities due to differences in circumstances ucation outcomes if access to education and health- that are beyond individuals’ control.2 However, oppor- care primarily depends on income.3 This would result tunities and outcomes are closely related to each oth- in lower growth rates due to the inefficient allocation er, especially in an intergenerational context. Parental of human capital and lower labor productivity in the income and wealth, for example, may result from the long run than in more equitable societies (see Galor parents’ own efforts on the one hand, and may influence and Zeira 1993; Perotti 1996; Aghion, Caroli and their children’s access to a good education, healthcare Garcia-Penalosa 1999; Galor and Moav 2004; Stiglitz services and the ability to earn a high income on the 2012; Cingano 2014; Ostry, Berg and Tsangarides 2014; other. OECD 2015). Income inequality itself arises from a combination of On the other hand, some degree of inequality may pro- an individual’s effort and talent and his/her opportuni- vide incentives for people to make efforts, to invest ties, for example socioeconomic background of his/her and to move ahead in life, which could, in turn, boost parents as well as access to education, healthcare and education and innovation outcomes, entrepreneurship, 3 Low income earners have a budget restriction, as there is a fixed 1 Ifo Institute. The author thanks the Hanns-Seidel-Foundation for amount of income they need for consumption. Under the assumption funding and Kristin Fischer for providing excellent research assistance. of financial market imperfections, it is reasonable to assume that low 2 Outcomes are, for example, income, wealth, expenditure, educa- income earners also have higher restrictions in their access to credits. tion, or health. Differences in circumstances beyond the individuals’ Therefore, they do have less money to invest in education, which im- control that may shape opportunities include, for example, ethnicity, pacts the long-term productivity of the economy when the share of low family background, gender, or location of birth. income earners is high. CESifo DICE Report 4/2016 (December) 54 Research Report labor productivity, and thus economic growth (see Measuring income inequality – concepts and pitfalls Lazear and Rosen 1981; Barro 2000; Baumol 2007).4 As richer income deciles have higher saving rates than Income inequality is typically measured by the income their poorer counterparts, income inequality is associ- shares of the population (for instance, by deciles or ated with higher aggregate saving (see Dynan, Skinner quintiles), the relation of income shares (for instance, and Zeldes 2004). Higher aggregate savings may in- (for instance, the income ratio of the top 10% to that of crease investment, production possibilities and in turn the median income, “P90/50”, to that of the lowest in- the output level for all individuals (see Kaldor 1955, come decile, “P90/10”, or to the income of the bottom Bourguignon 1981). Thus, income inequality is not 40%, “Palma Ratio”) or indices like the Atkinson index, necessarily bad. Instead, it could be a precondition for Theil index or Gini index. The Gini index is the most increasing everyone’s income in real terms. In theory, widely used measure of income inequality in cross-na- everyone could be better off, even if inequality rises. tional databases. The index coefficient is derived from Ultimately, this is an empirical question. the Lorenz curve and is produced by the seminal work of Corrado Gini (1921).6 For a completely egalitarian in- Empirics suggest a nonlinear relationship between in- come distribution, in which everyone in the population come inequality and growth that depends on the ine- has the same income, the coefficient takes a value of 0. quality level, the time dimension, as well as the devel- A Gini coefficient of 1 (or 100%) indicates that the total opment level in the country in question. Barro (2000), income of a country is concentrated in one person (or for example, describes that the relationship between household), and all others have none – so it is the value income inequality and economic growth is negative of maximum inequality. in less developed countries, but positive in advanced economies. Chen (2003) proposes an inverted-U rela- Gini coefficients are often non-comparable, because tionship between initial income distribution and long- they are based on different sources and welfare con- term growth. Halter, Oechslin and Zweimüller (2014) cepts. Thus, there are different combinations in which suggest that higher income inequality helps economic Gini coefficients can be constructed: performance in the short-run but reduces economic growth in the long-run. Kolev and Niehues (2016) de- Income or consumption/expenditure-based concepts scribe the relationship as positive for advanced econ- omies as long as the net income inequality level is not Gini measurements can be based on consumption and too high.5 expenditure or the income of the observed statistical units. According to Atkinson and Bourguignon (2000), Due to the potential consequences of income inequal- none of these concepts enjoys any clear advantage. On ity, the literature on this topic also discusses several the one hand, consumption is smoother and less varia- possible drivers of income inequality such as techno- ble over time than income. African and Asian surveys, logical change, globalization, financial deepening, out- for example, prefer to collect detailed consumption data. sourcing and offshoring-activities. These drivers may On the other hand, the use of consumption raises prob- all change relative demand for factors like capital, and lems of definition and observation. In the industrialized skilled and unskilled labor – and, in turn, the relative world, as well as Latin America, inequality is predomi- skill-premium (see i.a. Stolper and Samuelson 1941; nantly assessed with reference to income, not consump- Acemoglu 1998; Aghion, Caroli and Garcia-Penalosa tion (see Deaton and Zaidi 2002). 1999; Card and Dinardo 2002; Feenstra and Hanson 1996, 1999). Regional disparities, changing demo- Labor and capital income graphic and household composition, as well as policies like redistribution or de-regulation and changes in la- The total income of an economy can be allocated by la- bor market institutions, may also affect the income dis- bor and capital income – this reflects incomes based on tribution within countries (see i.a. OECD 2011; Peichl, wages or profits. Different datasets and studies use dif- Pestel and Schneider 2012; Dabla-Norris et al. 2015). ferent measures to analyze inequality – such as inequal- ity in wage incomes, overall labor incomes (including earnings by self-employment), or total incomes includ- 4 Incentives also depend on fairness perception of wages (see Akerlof ing capital gains (returns from investments). Scholars and Yellen 1990; Cohn, Fehr and Goette 2014). 5 The threshold is identified at a Gini net income inequality level of 6 Scholars have devised several variants of writing the Gini coeffi- around 0.35 (Kolev and Niehues 2016). cient (see Yitzhaki 1998). 55 CESifo DICE Report 4/2016 (December) Research Report should be aware of the data they are using. Inferences tries should be aware of the pitfalls if they combine var- can change by using different datasets and compositions ious data sources. of statistical units. Inequality in wages, for example, can rise if more people switch from unemployment into a low-wage-sector employment; simultaneously, overall Cross-national income
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