The Chartbook of Economic Inequality Tony Atkinson, Joe Hasell, Salvatore Morelli, and Max Roser 2017 2 The Chartbook of Economic Inequality A B Atkinson, Nuffield College, Oxford, London School of Economics and Institute for New Economic Thinking at the Oxford Martin School Joe Hasell, University of Naples – Federico II Salvatore Morelli, Institute for New Economic Thinking at the Oxford Martin School and CSEF – University of Naples – Federico II Max Roser Institute for New Economic Thinking at the Oxford Martin School May 2017 Abstract The Chartbook summarizes the evidence about long-run changes in five different dimensions of economic inequality – overall and top income inequality, poverty, earnings dispersion, and wealth inequality – for 25 countries covering more than one hundred years. The evidence represents an update and extension of the work done by Atkinson and Morelli (2014). The results are presented in 25 charts, one for each country, together with a full description of the method and sources. Series, sources and graphs can be downloaded at chartbookofeconomicinequality. Purpose The purpose of this Chartbook is to present a summary of evidence about long-run changes in five different dimensions of economic inequality for 25 countries covering more than one hundred years. The evidence represents an update of the work done by Atkinson and Morelli (2014). There is a range of countries and they account for more than a third of the world’s population: Argentina, Australia, Brazil, Canada, Finland, France, Germany, Iceland, India, Indonesia, Italy, Japan, Malaysia, Mauritius, Netherlands, New Zealand, Norway, Portugal, Singapore, South Africa, Spain, Sweden, Switzerland, the UK and the US. The results are presented in 25 charts, one for each country, together with a description of the sources. The underlying figures and original sources are available at chartbookofeconomicinequality. We aim to provide for each country five indicators covering on an annual basis: 1. Overall income inequality 2. Top income shares 3. Income (or consumption) based poverty measures; 4. Dispersion of individual earnings; 5. Top wealth shares/ wealth inequality measures. Tony Atkinson sadly passed away in January 2017, before the new version of the paper was finalized. Tony was the primary driver of this project which would not exist without his commitment, passion, and contribution. The assembly of the data for this chartbook has formed part of the Inequality project at the Institute for New Economic Thinking at the Oxford Martin School and has had the financial support of the INET grant (IN01100021). SM acknowledges financial support from the “Guido Cazzavillan Fellowship” at Ca’ Foscari University. An earlier version of the Chartbook was circulated in March 2014 with the title “The Chartbook of Economic Inequality”, ECINEQ working paper - 324. In April 2017 a bound copy of this document was distributed at the INET-Oxford. We thank Anne Brunner-Ellis, Jo Kay, Susan Mousley, and Tanya Vale for their support. For their help and advice, we thank Rolf Aaberge, Facundo Alvaredo, Charlotte Bartels, Hans Baumann, Andrea Brandolini, Jon Epland, Leonardo Gasparini, Markus M. Grabka, Arthur B. Kennickell, Andrew Leigh, René Levy, Stefán lafsson, Wiemer Salverda, Moritz Schularick, Ulrike Steins, Giovanni Vecchi, and Daniel Waldenstrm, but they are not to be held in any way responsible for any errors or omissions. 3 This is ambitious and our charts fall a long way short of being complete, as is illustrated in Table 1, which shows the dates at which, for each country, the five indicators commence. In the past, more evidence was available about the upper part of the distribution, and our indicators cover the top income shares more fully. For the other indicators, coverage is more limited. In only five of the twenty five countries do the data on overall inequality start before 1945. In many cases data are not always available for every year and there are gaps in the series. These are joined within the graphs but it is worth noting that this may well miss important year-to-year variations. In some cases, particularly for wealth, we have located no time series at all. Our emphasis is on change over time. We have therefore concentrated on comparability over time, and for this reason presented the evidence country by country. What do the indicators show For each of the five indicators, we have a preferred or otherwise standard definition, but we have had to depart from this where no data are available on this basis. To aid the reader, we have in the charts marked by the symbol (*) the series based on the preferred (or standard) definition. In a number of countries, this includes cases where data are available on the preferred definition only for the later part of the period, but where we have nonetheless chosen to piece together a longer series from sources that make use of different definitions. In the case of overall income inequality , our preferred income concept is equivalised (using a scale to allow for differences in household size and composition) household disposable income, defined as income from all sources, including transfer payments, minus direct taxes and social security contributions. The equivalence scale used in most cases is the “modified OECD scale”, which gives a weight of 1 to the first adult, of 0.5 to each additional adult, and of 0.3 to each child. This means that the income of a family of 2 adults and 2 children is divided by 2.1. In some cases, other scales are employed, such as the square root scale, where income is divided by the square root of the household size (2 in the example just given). The distribution is among persons: each individual appears in the distribution with the equivalised income of the household. No allowance is made for within-household inequality. In a number of cases, the definitions in the available statistics depart from this preferred version. For example, income may not be adjusted for household size and composition, or the distribution may relate to gross income, before the deduction of income and social security taxes. Because the income tax is usually progressive, inequality is typically higher for gross income than for disposable income. The overall distribution is summarised in a single summary statistic, typically the Gini coefficient, most commonly published by statistical agencies. The explanation of the coefficient given by most agencies is made in terms of geometry, but we prefer to describe it in terms of the mean difference. A Gini coefficient of G per cent means that, if we take any two households from the population at random, the expected difference is 2G per cent of the mean. So that a rise in the Gini coefficient from 30 to 40 per cent implies that the expected difference has gone up from 60 to 80 per cent of the mean. Another useful way of thinking, suggested by Amartya Sen, is in terms of “distributionally adjusted” national income, which with the Gini coefficient is (100-G) per cent of national income. So that a rise 4 in the Gini coefficient from 30 to 40 per cent is equivalent to reducing national income by 14 per cent (1/7). Much of the evidence about top income shares is derived from tax records, and our standard – although not necessarily preferred – definition is gross income for tax purposes before deduction of allowable outgoings. Typically, but not exclusively, income here excludes capital gains and losses. Where both including and excluding capital gains data was available (as for the United States and Sweden) we have chosen the latter. Transfer income is covered to varying degrees in different countries. Because the tax system is typically progressive, the top shares in disposable income are smaller: for example, in the UK in 2000 the