About this Website

Authors and Supporting Institutions

The data for this website have been compiled by Anthony B Atkinson and Salvatore Morelli and are published as Atkinson and Morelli (2014).
The online version of the Chartbook and the online data visualisations have been designed and constructed by Max Roser.
Support from the following institutions is gratefully acknowledged: Programme for Economic Modelling · Institute for New Economic Thinking – Oxford · Oxford Martin School

Purpose

The purpose of this Chartbook is to present a summary of evidence about long-run changes in economic inequality – primarily income, earnings, and wealth – for 25 countries covering more than one hundred years. There is a range of countries and they account for more than a third of the world’s population: Argentina, Brazil, Australia, 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 are available for download here
We aim to provide for each country five indicators covering on an annual basis:

  • Overall income inequality;
  • Top income shares
  • Income (or consumption) based poverty measures;
  • Dispersion of individual earnings;
  • Top wealth shares.

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 about a quarter of the 125 cases, do the data 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. For the 125 cells in Table 1 there are 18 blanks.
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.

Findings:

The main aim of the Chartbook is to allow readers to draw their own conclusions, but we have included below each chart a table summarising our answers to the following questions:

  • Has the dispersion of earnings been increasing in recent decades?
  • Has overall income inequality increased in recent years?
  • Have there been periods when overall inequality fell in a sustained way?
  • Has poverty been rising or falling over the past decades?
  • The US and certain other countries have seen top income shares first fall and then rise, is there a U-shaped pattern of this kind?
  • Has the concentration of wealth moved in the same way as income inequality?
  • Are there other particularly note-worthy features?

These are only some of the questions that readers will want to ask, but they capture some of the issues in current debate. It is, for example, widely held that there is a general upward trend in income inequality. How far is this in fact the case? The answer will of course depend in part by our view as to what constitutes a “salient” rise. In the case of both the Gini coefficient and the share of the top 1 per cent, we take a 3 percentage point difference as salient.

Sources

The sources are described for each country on the page following the chart. We have tried in all cases to check the figures against the original sources. The importance of such checking may be illustrated by reference to South Africa. In seeking data on the overall distribution, we had identified a series for the Gini coefficient covering the years from 1960 to 1987 in the World Income Inequality Database (WIID). Given the problems of securing long-term distributional data for that country, this appeared too good to be true. This proved to be the case. Investigation of the original source (Lachmann and Bercuson, 1992, Table 2) revealed that the title was “Gini coefficients assuming income equality within racial groups”. The data showed the differences between races, which is an important part, but only part, of the story. These data do not measure overall inequality and are not used here.

In this exercise, we have made use of valuable building blocks. In particular the studies of top incomes, largely resulting from the project organised by Atkinson and Piketty (2007 and 2010), provide an anchor for the empirical analysis. This project gave rise to the World Top Incomes Database (referred to below as WTID), administered by Facundo Alvaredo. But we wish also to cover, as far as possible, the distribution as a whole, and to follow what happens to poverty as well as riches. The series that we present therefore show not only top income shares but also measures of overall inequality and measures of low incomes. Here we are able to draw on the collection of historical data assembled over the years by Atkinson and Brandolini (see for example, Brandolini, 2002).

The general sources on which we have drawn are:

  • Atkinson, A B, 2008, The changing distribution of earnings in OECD countries, Oxford University Press, Oxford.
  • Atkinson, A B and Piketty, T, editors, 2007, Top incomes over the twentieth century, Oxford University Press, Oxford.
  • Atkinson, A B and Piketty, T, editors, 2010, Top incomes: a global perspective, Oxford University Press, Oxford.
  • Brandolini, A, 2002, “A bird’s eye view of long-run changes in income inequality”, Bank of Italy Research Department, Rome.
  • Luxembourg Income Study (LIS) Key Figures, downloaded from LIS website 15 October 2010; it should be noted that the country coverage of LIS is being extended: in February 2014 the Key Figures covered 40 countries, including 17 of those included in this chartbook.
  • World Top Incomes Data-Base (WTID), created and administered by F. Alvaredo,

We owe a considerable debt to the many researchers who have contributed to these sources.

 

Table 1 – Coverage of data (first year of data)

CountryOverall inequalityTop income sharesPovertyEarningsWealth
Argentina195319321980--
Australia19421921198119751915
Brazil1960196019842002-
Canada1959192019761931-
Finland19201920197119711909 (1800)
France19561915197019501911
Germany19501911 (1891)196219291973
Iceland1992199219861986-
India1951192219831983-
Indonesia196419201976--
Italy1901 (1861)197419771973-
Japan19231900 (1886)198519801983
Malaysia195719471970--
Mauritius196219331996--
Netherlands19591914197719771905 (1894)
New Zealand19511921198219581956
Norway19731900 (1875)197919861912 (1789)
Portugal1967193619801982-
Singapore19661947-1965-
South Africa1960191319701997-
Spain1964195419732004-
Sweden19511911 (1903)197519751908 (1800)
Switzerland19501933198219911915
UK193819131196119541923 (1740)
US19181913194819391916 (1774)

Note: In a few cases the actual initial year of the series (within the original sources) precedes the year 1900 and this is indicated within the table in italics and parenthesis. Series are not always continuous.