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Global Inequality - Trends and Issues Finn Tarp Overview Introduction Earlier studies: background A WIDER study [Methodology] Data General results Counterfactual scenarios Concluding remarks


  1. Global Inequality - Trends and Issues Finn Tarp

  2. Overview • Introduction • Earlier studies: background • A WIDER study • [Methodology] • Data • General results • Counterfactual scenarios • Concluding remarks

  3. Introduction

  4. Back to economics 101 1. Any competitive equilibrium is Pareto efficient 2. Under certain conditions, every Pareto efficient allocation can be achieved as a competitive equilibrium ‘Under certain conditions’ …..

  5. The ‘mainstream’ view • Economic transactions mainly occur in free and competitive environments • Externalities and the political process of minor importance • Efficiency issues separate from issues of equity

  6. WDR 2006 (1) • The dichotomy between policies for growth and policies specifically aimed at equity is false • The distribution of opportunities and the growth process are jointly determined

  7. WDR 2006 (2) • Sound policy can involve redistributions of influence, advantage or subsidies away from dominant groups • ‘Good’ redistribution may not always be directly to the poor (trade-offs) • Recall debates around ‘redistribution with growth’ and ‘basic human needs’ and growth versus HDI

  8. A WIDER perspective • From classical economics to a more nuanced, wider position: – Many channels through which inequality may affect growth and development negatively – Equity both an end and a means – No rejection of the competitive market (and the need for incentives to work) • Recall the discussion about the inverted-U

  9. A UN position • The report of the UN System Task Team (2012) to support the preparation of the Post 2015 UN Development Agenda points out that: ‘inequality is a key concern, not just from the perspective of a future in which a decent and secure wellbeing is a prerogative of all citizens, but sustained development itself is impeded by high inequalities. Hence, redressing these trends will be a major challenge in the decades ahead’

  10. Background

  11. Background • Trends in within-country inequality (e.g. Cornia and Kiiski 2001) using countries as the unit of focus • Other studies (e.g. Firebaugh 1999, 2003, and Boltho and Toniolo 1999) look at between-country inequalities (analysing inequality among individuals who are assigned the average per capita income of their country) • Fewer studies (e.g. Xavier Sala-i-Martín 2006, Bhalla 2002; Bourguignon and Morrisson 2002) have measured global interpersonal inequality decomposing inequality into within- and between-country inequality (looking at the inequality among individuals in the world, with each individual assigned her/his own per capita income)

  12. Relative versus absolute • The predominant ‘relative’ inequality measures (such as the Gini Index and the Theil L index or Mean Log Deviation): values remain unchanged when every income in an income distribution is uniformly scaled up or down by the same proportionate factor. • The less commonly used ‘absolute’ inequality measures (such as the Variance): values remain unchanged when every income in an income distribution has the same income added to, or subtracted from, it. • ‘Centrist’ inequality measures (such as Krtscha): value increase when every income in an income distribution is uniformly scaled up or down by the same proportionate factor, and decline when every income in an income distribution has the same income added to, or subtracted from, it.

  13. An intuitive approach • From a normative perspective relative and absolute inequality measures have been described as respectively ‘rightist’ , and ‘leftist’ , measures. • In the presence of income-growth: – viewing interpersonal disparities in terms of the ratio of incomes can be construed as reflecting a conservative judgement – viewing disparities in terms of the absolute difference in incomes can be construed as reflecting a radical judgement (see Kolm 1976).

  14. A UNU-WIDER study (with Miguel Nino-Zarazua and Laurence Roope)

  15. Aims 1. What are the most recent trends in global inequality? Has global inequality increased or declined? 2. Have these trends been homogenous across regions? 3. Is the picture of global inequality trends using ‘absolute’ or ‘centrist’ measures of inequality consistent with the picture using ‘relative’ inequality measures?

  16. Results in a nutshell 1. Using standard ‘relative’ inequality measures, global inequality declined steadily over the past three decades 2. We find heterogeneity in inequality trends across regions (inequality recently declined in Latin America and in South Asia; increased steadily in North America driven, primarily, by increased within-country inequality). A quick word about Piketty. 3. When using ‘absolute’ (the Variance) and ‘centrist’ ( Krtscha) inequality measures, we find that global inequality has increased dramatically . A key policy question: Can we say more on the potential trade-offs between growth and equality. We use counterfactual analysis to start exploring.

  17. Data

  18. Data (1) • We employ quintile data from the latest version (V3.0B) of the UNU-WIDER World Income and Inequality Database (WIID) (the longest and most comprehensive database of income distributions) • WIID adopts the definitions and and procedures in the Canberra Group Handbook

  19. Data (2) • Definitions of income-based or consumption-based inequality – Deaton & Zaidi (2002) suggest to use consumption for welfare measures – Atkinson & Bourguignon (2000) argue that for distributional analysis, income is preferable – Deininger and Squire (1996) suggest adding 6.6 Gini points to Gini coefficients based on consumption to obtain the corresponding income Gini coefficients. We refine this approach by making this adjustments directly using quantile share data

  20. Data (3) The number of individuals per country-quantile calculated based on population data from the following sources: 1. United Nations Population Division. World Population Prospects 2. Census reports and other statistical publications from national statistical offices 3. Eurostat: Demographic Statistics 4. Secretariat of the Pacific Community: Statistics and Demography Programme 5. U.S. Census Bureau: International Database The income levels per capita, per country-quantile were calculated based on GDP for the various country-years in 2005 US$ at PPP from the World Bank's databank

  21. General results

  22. Relative global Inequality 1.400 1.200 1.000 0.800 0.600 0.400 0.200 0.000 1975 1985 1995 2000 2005 2010 Gini Theil L Theil L within-country component Theil L between-country component

  23. Relative regional Inequality Theil L index (MLD) 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1975 1985 1995 2000 2005 2010 East Asia & Pacific Europe & Central Asia Latin America & Caribbean Middle East & North Africa North America South Asia Sub-Saharan Africa

  24. Relative ‘within’ regional Inequality • Within each region we also observe important variations. In Europe, for example : • Some countries have experienced a steep rise in inequality since the 2000s: Denmark, Sweden, France and Bosnia and Herzegovina • Other countries have observed a decline in inequality throughout the 2000s: Belgium, Italy, Norway, and Ireland • Some countries have experienced a relatively flat trend in domestic inequality throughout the 2000s: United Kingdom, Finland, and Czech Republic • Some countries have experienced a decline in inequality during the 1990s and until the mid-2000s but then a clear increase in inequality after the 2008 financial crisis: Greece, Slovenia, Spain, Bulgaria, Malta, Slovak Republic • Other countries have experienced first a rise in inequality , and then a fall in inequality since the 2008 financial crisis: Netherlands, Switzerland, Iceland, Poland, Hungary, Romania

  25. ‘Absolute’ and ‘Centrist’ global Inequality estimates 35,000 30,000 25,000 20,000 15,000 10,000 5,000 - (US dollars at 2005 PPP) 1975 1985 1995 2000 2005 2010 Variance Krtscha

  26. Counterfactual scenarios

  27. Counterfactual Scenario I (relative) • Assumption A: in 2010, India’s and China’s incomes per capita, and distribution of incomes, had remained at 1975 levels Results • Global inequality would have instead increased during 1975-2010, from 0.739 to 0.757 according the Gini coefficient, and from 1.349 to 1.493 according to the MLD Inequality Measure 1975 2010 0.739 0.757 Gini 1.349 1.493 Theil L (MLD) 0.262 0.261 Theil L within-country component 1.087 1.232 Theil L between-country component

  28. Counterfactual Scenario II (relative) • Assumption B: India and China had grown their per capita incomes at the same rates as they actually did over 1975-2010, while maintaining the same quintile shares as in 1975 Results • Global inequality would have fallen even further by 2010; to 0.621 according to the Gini coefficient, and to 0.769 according to the MLD index Inequality Measure 1975 2010 0.739 0.621 Gini 1.349 0.769 Theil L (MLD) 0.262 0.261 Theil L within-country component 1.087 0.507 Theil L between-country component

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