Global Income Distribution: From The Fall Of The Berlin Wall To The Great Recession by Christoph Lakner and Branko Milanovic,The World Bank Economic Review
Abstract
We present an improved panel database of national household surveys between 1988 and 2008. In 2008, the global Gini index is around 70.5%, having declined by approximately 2 Gini points. China graduated from the bottom ranks, changing a twin-peaked global income distribution to a single-peaked one and creating an important global “median” class. 90% of the fastest growing country-deciles are from Asia, while almost 90% of the worst performers are from mature economies. Another “winner” was the global top 1%. Hence the global growth incidence curve has a distinct supine S shape, with gains highest around the median and top.
Introduction
This paper provides new evidence on the evolution of global interpersonal income inequality between 1988 and 2008. We measure inequality among all individuals in the world irrespective of their country of residency thus implicitly assuming a “cosmopolitan” social welfare function (Atkinson and Brandolini 2010) and translating the concern for within-country inequality to the global level (Pogge 2002; Singer 2002). Over this period, the face of globalization changed dramatically with the end of the Soviet Union and the integration of many developing countries into the world economy. Our analysis of global interpersonal inequality captures the effects of these tectonic shifts on both within- and between-country inequality.
We find that the inequality in the global income distribution, as measured for example by a Gini index, is high (compared with within-country inequality) and does not change substantially over this period. However, this hides re-ranking of country-deciles as some have grown much faster than others over this period. Because our data set is a panel of country-deciles, we can directly compare the growth of say, the top 10% in urban China with that of the bottom 10% in the United States.We can thus go beyond country-level analyses and take changes in within-country inequality into account. For example, for the global interpersonal income distribution it matters both that the growth in China has been exceptionally high but also that this growth has been faster at the top of the Chinese distribution.
This paper offers three main contributions to the study of global income inequality (see the reviews by Anand and Segal [2008, 2014] for a very comprehensive summary of the literature on this topic). First, we compile a new and improved database of national household surveys in response to criticism of earlier data sets. An important part of the literature on global inequality anchors income distribution data to national accounts, typically to GDP per capita. However, we argue, following Anand and Segal (2008), that household surveys are the appropriate source of information if one is interested in comparing the (disposable) income of the world’s citizens. Second, this allows us to present more credible results on the level of global interpersonal income inequality between 1988 and 2008. Third, we create balanced and unbalanced panels of country-deciles for five benchmark years (in five-year intervals). Hence we can go further than the statements about which countries affected global inequality, by looking into a more disaggregated distribution of country-deciles.We can identify those country-deciles that have gained and lost most over this 20-year period, and most importantly, we derive global growth incidence curves (GICs) showing which parts of the global distribution benefited the most (and the least) during globalization. This allows us to put empirical content to the often discussed questions of the emergence of the “global middle class” or income gains of the global top 1%.
Our interest in global interpersonal inequality is founded upon a concern for individual well-being, which treats persons the same irrespective of their country of residence.1 This cosmopolitan view is not shared by everyone and there exists a large philosophical literature on this issue (e.g., Nagel 2005). However, it is important to recognize the increasing role played by international organizations, and that the cosmopolitan view is the only one consistent with their constitutions. One might also have an instrumental concern for global interpersonal inequality if extreme global inequality leads to increased international tension, conflict or large scale migration. Furthermore, changes in global inequality capture some of the effects of globalization (Anand and Segal 2008). Globalization supported fast economic growth in many populous developing countries (mainly in Asia), thus reducing between-country inequality. At the same time, it is blamed for increasing inequalities within both rich (Autor et al. 2013) and poor (Goldberg and Pavcnik 2007) countries. Global interpersonal inequality captures both these effects in a unified framework.
Measuring global inequality empirically is substantially more difficult compared with within-country inequality. In the absence of a global household survey, we need to resort to combining national surveys. Our database includes 565 household surveys across five benchmark years and each country-year observation is represented by the average income of 10 income decile groups.2 National surveys collect information in terms of local currencies, which we convert into a common currency using within-country inflation to correct for changes in the price level over time, expressing first everything in constant 2005 local currency units, and then using the 2005 purchasing power parity (PPP) exchange rates to adjust for cost of living differences across countries. 3,4 In constructing our global distribution we mix income and consumption surveys. We refer to them interchangeably, as is customary in this literature, although we are obviously fully aware of the important differences between the two concepts. However, we improve on earlier approaches by keeping the type of survey (income or consumption) constant over time for a particular country.
The remainder of this paper is structured in four parts. Section II summarizes our data construction and methodology. Section III provides summary statistics on our database and presents the main results regarding global inequality. We report a number of different inequality measures and derive global and regional GICs. Section IV moves from a cross-sectional focus to a panel analysis. Therefore, it lets us track the movement of individual country-deciles in the global distribution, and highlights what parts of the initial (1988) distribution gained most and least during the next 20 years. Section V presents conclusions. We report a number of robustness checks in the appendix.
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