Global Inequality - Trends and Issues Finn Tarp
Global Inequality -
Trends and IssuesFinn Tarp
Overview
• Introduction
• Earlier studies: background
• A WIDER study
• [Methodology]
• Data
• General results
• Counterfactual scenarios
• Concluding remarks
Introduction
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’ …..
The ‘mainstream’ view
• Economic transactions mainly occur in free and competitive environments
• Externalities and the political process of minorimportance
• Efficiency issues separate from issues of equity
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
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
A WIDER perspective
• From classical economics to a more nuanced, widerposition:
– 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
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’
Background
Background
• Trends in within-country inequality (e.g. Cornia and Kiiski2001) using countries as the unit of focus
• Other studies (e.g. Firebaugh 1999, 2003, and Boltho and Toniolo 1999) look at between-country inequalities (analysinginequality 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)
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.
An intuitive approach
• From a normative perspective relative and absoluteinequality 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).
A UNU-WIDER study(with Miguel Nino-Zarazua and
Laurence Roope)
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?
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.
Data
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
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
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
General results
Relative global Inequality
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
1975 1985 1995 2000 2005 2010
Gini
Theil L
Theil L within-country component
Theil L between-country component
Relative regional Inequality
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1975 1985 1995 2000 2005 2010
Theil L index (MLD)
East Asia & Pacific Europe & Central AsiaLatin America & Caribbean Middle East & North AfricaNorth America South AsiaSub-Saharan Africa
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
‘Absolute’ and ‘Centrist’ global Inequality
estimates
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
1975 1985 1995 2000 2005 2010
Variance Krtscha
(US dollars at 2005 PPP)
Counterfactual
scenarios
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
Gini 0.739 0.757
Theil L (MLD) 1.349 1.493
Theil L within-country component 0.262 0.261
Theil L between-country component 1.087 1.232
Inequality Measure 1975 2010
Gini 0.739 0.621
Theil L (MLD) 1.349 0.769
Theil L within-country component 0.262 0.261
Theil L between-country component 1.087 0.507
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
Counterfactual scenario I (absolute/centrist)
• Assumption A: India’s and China’s incomes per capita, and distribution of incomes remained at 1975 levels
Results
• Both the Variance and the Krtscha measures are consistent with the relative inequality estimates; however, the results are more pronounced
Inequality Measure 1975 2010
Variance 10,370 32,300
Krtscha 19,342 37,339
Counterfactual scenario II (absolute/centrist)
• Assumption B: India and China grew their per capita incomes at the same rate as they actually did over 1975-2010, while maintaining the same domestic income quantile shares as in 1975
Results
• In marked contrast to the judgment of our relative inequality measures, both the Variance and the Krtscha register a large increase in inequality during 1975 to 2010
Inequality Measure 1975 2010
Variance 10,370 30,380
Krtscha 19,342 28,615
Counterfactual scenario III
• Assumption C: all countries have their actual incomes per capita in 2010, but their quantile shares (and therefore domestic relative inequality levels) are the same as those of Sweden in 2010
Results
• Relative inequality measures observe a very substantial decline in inequality. The results are, however, very different for the Variance, which almost doubles. Considerable tension between absolute inequality and growth in mean incomes
Inequality Measure 1975 2010
Absolute and centrist measures
Variance 10,370 19,320
Krtscha 19,342 18,191
Relative measures
Gini 0.739 0.569
MLD 1.349 0.609
Concluding remarks
Comparing results to previous studies?
• The overwhelming majority of previous studies on global inequality have investigated only relative inequality
• Our relative global inequality estimates lie broadly in the same ball park as previous studies including Dowrick and Akmal (2005); Sala-i-Martin (2006); Bhalla (2002); Bourguignon and Morrisson (2002); Milanovic (2005; 2014)
• Our results are largely consistent with the very few studies which have employed relative, absolute and centrist inequality measures (e.g. Bosmans et al. 2014)
Discussion (1)
• Taken together, we echo Atkinson and Brandolini(2010) in emphasizing how central the choice of measure is to any discussion of what has happened to global inequality levels during recent decades.
• Relative global inequality while still staggeringly high, has fallen steadily and quite substantially over the decades. This was driven by a dramatic decline in inequality between countries.
Discussion (2)
• Absolute inequality measures show global inequality increased substantially during the period 1975-2010 – growth in income in India and China had only a very modest dampening impact on the increased absolute inequality.
• The centrist Krtscha measure confirms the results from absolute measures; yet shows that centrist inequality trends peaked around 2005, and then were substantially dampened.
• Over the past 35 years, hundreds of millions of people in the developing world have been lifted out of poverty. Would a different set of policies have managed this without the increase in absolute inequality?
Difficult policy challenges remain
• What to do when trade-offs exist?
• Need for country level research and analysis of options
• At global level:
– Developed countries need to do a lot more to reconcile policies that are in partial or direct conflict with generally accepted principles of development and international cooperation
– For example: Act on aid, trade, migration and capital flows
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