INEQUALITIES, UNCOUNTED: MEASUREMENT CHOICES AND POLICY

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INEQUALITIES, UNCOUNTED: MEASUREMENT CHOICES AND POLICY TARGETS @AlexCobham

Overview Overview of inequalities What do we know? Uncounted: Measurement and power Policy targets including the Palma

Dimensions Economic inequalities Vertical (between individuals) Horizontal and intersecting (between groups, e.g. by gender; ethnolinguistic; spatial; disability; age; HIV status) Aspects Income, including employment opportunities Wealth, including land Stability as well as levels in snapshot

Dimensions Social inequalities Vertical (between individuals) Horizontal and intersecting (between groups, e.g. by gender; ethnolinguistic; spatial; disability; age; HIV status) Aspects Outcomes (e.g. mortality, literacy) Access to services (health, education) Inclusion (e.g. community involvement/marginalisation => political )

Dimensions Political inequalities Vertical (between individuals) Horizontal and intersecting (between groups, e.g. by gender; ethnolinguistic; spatial; disability; age; HIV status) Aspects Access to (influence over) national resources Voice, access to process, representation Outcomes in terms of other inequalities, e.g. access to services

Intergenerational inequalities Dimensions Vertical (between individuals) Horizontal and intersecting (between groups, e.g. by gender; ethnolinguistic; spatial; disability; age; HIV status) Aspects Sustainability: economic, social, political, and environmental

Costs of inequalities Inherent and instrumental Shorter, less fulfilling lives Weaker cognitive development of children Lower economic growth Shorter economic growth periods Higher risk of political conflict and of violence

What do we know? (VI) Economic Social Political Intergen l Income Outcomes (e.g. mortality, literacy) Representation Employment Access to services (health, education) Outcomes in terms of other inequalities Environmental Wealth? Inclusion? Voice, access to process? Economic Land? Stability? Access to (influence over) national resources? Social Political

What do we know? (HI) Economic Social Political Intergen l Gender Ethnoling c Spatial Disability Age HIV status

What do we know? (Intersects) Gender Ethno c Spatial Disability Age HIV status Gender Ethno c Spatial Disability Age HIV status

What do we know? This That The other??

Uncounted: Why it matters 1 What is uncounted is not random, but reflects power inequalities 2 The power to count (to choose what is counted and reported) can exacerbate inequality

Patterns of uncounted Uncounted, through lack of power Bottom end of distributions Marginality Uncounted, through power Top end of distributions (countries, people) Criminality

Uncounted by reporting power 140 120 100 Development expenditure per capita, 1996-2000 (North=100) Female IMR, 1993 (North=100) 80 60 40 20 0 North Central, ex Kh East Darfur Kordofan

Uncounted targets Manipulation of data 1990 revisionism Manipulation of targets (Pogge) Language Baseline year 1996 Baseline, millions 1,656 World Food Summit Target 2015 reduction 50.0% Target for 2015, millions 828 Required annual reduction 3.58% Halve number MDG-1 as adopted Halve fraction of world population 2000 1,665 40.4% 993 3.39% MDG-1 as revised Halve fraction of dev g population 1990 1,813 27.0% 1,324 1.25%

The power to revise results can render targets meaningless The power to revise targets can eradicate ambition

Choices for policy targets Millennium Development Positive Goals: Decisions by Technocrats Pragmatism Inertia? Post-2015 HLP Negative MDGs Gender Inequality Disaggregation & Illicit flows Economic inequality

Technical Criteria: Choice of indicators Pigou-Dalton transfer principle: rules out counter-intuitive responses to transfers Technical accuracy Political accountability Income scale independence: should not respond to proportional changes to all (Cost?) Dalton s principle of population: measure shouldn t respond to merging of identical populations An example: Inequality Anonymity or symmetry: measure is independent of any non-income characteristic of individuals Policy Atkinson axiom: Are the value judgments of using this indicator sufficiently explicit? Policy-signal axiom: Is it clear what signal given to policymakers on direction of change? Clarity axiom: Is it clear to a non-technical audience what has changed? Policy-response axiom: Is the policy response sufficiently clear? Decomposability: overall ineq is related consistently to ineq among sub-groups A horizontal axiom: Can measure also capture horizontal inequality?

Accountable counting? The Palma Ratio of national income shares: top 10% to bottom 40% Rests on Gabriel Palma finding: stability of middle deciles (5-9) Basically, it seems that a schoolteacher, a junior or midlevel civil servant, a young professional (other than economics graduates working in financial markets), a skilled worker, middle-manager or a taxi driver who owns his or her own car, all tend to earn the same income across the world as long as their incomes are normalized by income per capita of respective country.

Middle stability across countries 35% 30% Highest 10% Lowest 40% Middle 50% 25% 20% 15% 10% 5% 0% 1990 2010 Combined

Middle stability across time UK Venezuela Peru Paraguay Panama Mexico Honduras El Salvador Ecuador Dominican Rep. Costa Rica Colombia Chile Brazil Argentina Top 10% Middle 50% Bottom 40% 0% 2% 4% 6% 8% 10% 12% 14%

Stability across income stages 100% 80% 60% Top 10% Bottom 40% Middle 50% 40% 20% 0% -20% Argentina Brazil Mexico Peru

The Palma (2010)

Palma vs Gini Decile Income shares (%) 1 6.25 4.17 3.13 2.50 2.08 1.79 1.56 1.39 1.25 1.14 2 6.25 4.17 3.13 2.50 2.08 1.79 1.56 1.39 1.25 1.14 3 6.25 4.17 3.13 2.50 2.08 1.79 1.56 1.39 1.25 1.14 4 6.25 4.17 3.13 2.50 2.08 1.79 1.56 1.39 1.25 1.14 5 10 10 10 10 10 10 10 10 10 10 6 10 10 10 10 10 10 10 10 10 10 7 10 10 10 10 10 10 10 10 10 10 8 10 10 10 10 10 10 10 10 10 10 9 10 10 10 10 10 10 10 10 10 10 10 25.00 33.33 37.50 40.00 41.67 42.86 43.75 44.44 45.00 45.45 Palma 1 2 3 4 5 6 7 8 9 10 Gini 0.23 0.35 0.41 0.45 0.48 0.49 0.51 0.52 0.53 0.53

Palma vs Gini Policy If Palma so closely related to Gini; and Palma ignores half the income distribution; why would you possibly want to use it? 1. Policy axioms 2. Gini flaws P = y/x G = 58.1y 119.5x + 41.86 Atkinson axiom: Are the value judgments of using this indicator sufficiently explicit? Policy-signal axiom: Is it clear what signal given to policymakers on direction of change? Clarity axiom: Is it clear to a non-technical audience what has changed? Policy-response axiom: Is the policy response sufficiently clear? A horizontal axiom: Can measure also capture horizontal inequality?

Pop quiz Which measure would you prefer? P = y/x G = 58.1y 119.5x + 41.86

3 Palma proposals for post- 2015 Engberg-Pedersen (2013) Halve the distance from a Palma of 1 Doyle & Stiglitz (2014) Palma of 1 Cobham (2014) Global agreement, national setting

Conclusions Economic, social, political and intergenerational inequalities are at the heart of transformation. Being uncounted reflects power: the excess or the lack thereof, & worsens inequalities. Post-2015 and national plans offer great opportunities for progress (not least disaggregation; but the political obstacles are also great.

Remember: counting is political power0

Thank you @AlexCobham

Income inequality: too political? High-Level Panel: We recognized that every country is wrestling with how to address income inequality, but felt that national policy in each country, not global goalsetting, must provide the answer. History also shows that countries tend to have cycles in their income inequality as conventionally measured; and countries differ widely both in their view of what levels of income inequality are acceptable and in the strategies they adopt to reduce it.

Income inequality: too political? Thought experiment: We recognized that every country is wrestling with how to address gender violence, but felt that national policy in each country, not global goalsetting, must provide the answer. History also shows that countries tend to have cycles in their gender violence as conventionally measured; and countries differ widely both in their view of what levels of gender violence are acceptable and in the strategies they adopt to reduce it.