UNCOUNTEDInequality, post-2015 and measurement as power

Alex Cobham, CGDInternational Parliamentary

Conference on the Post-2015 Development Agenda28 November 2013

Pop quiz

Which measure would you prefer?

P = y/x

G = 58.1y – 119.5x + 41.86

50 ways to be uncounted• Blatant ‘uncounting’– Choice of reporting–Manipulation of data and targets– Patterns of being uncounted

• Choices for Post-2015– Choice of ‘development’ priorities– Choice of indicators, e.g. the Palma –Modest proposals

Blatant 1: Choice of reporting

The power to choose what is reported

can exacerbate inequality

Blatant 2: Manipulation

The power to revise ‘results’can render targets meaningless

The power to revise targets can eradicate ambition

Blatant 3: Patterns of uncounted

Uncounted, through power• Top end of distributions (countries,

people); • Criminality

Uncounted, through lack of power• Bottom end of distributions; • Marginality

Millennium Development Goals: Decisions by…• Technocrats• Pragmatism • Inertia ?

Choice of ‘development’ aspects

Positive Negative

MDGs Gender(not $-a-day!)

Inequality

Post-2015 HLP Disaggregation & Illicit flows

Economic inequality

Choice of indicators• Criteria:– Technical accuracy– Political accountability– (Cost?)

• An example: Inequality

Technical

Pigou-Dalton transfer principle: rules out counter-intuitive responses to transfers

Income scale independence: should not respond to proportional changes to all

Dalton’s principle of population: measure shouldn’t respond to merging of identical populationsAnonymity or symmetry: measure is independent of any non-income characteristic of individuals

Decomposability: overall ineq is related consistently to ineq among sub-groups

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?

A horizontal axiom: Can measure also capture horizontal inequality?

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 mid-level 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

1990 2010 Combined0%

5%

10%

15%

20%

25%

30%

35%Highest 10%Lowest 40%Middle 50%

Middle stability across time

Argentina

Brazil

Chile

Colombia

Costa Rica

Dominican Rep.

Ecuador

El Salvador

Honduras

Mexico

Panama

Paraguay

Peru

Venezuela

UK

0% 2% 4% 6% 8% 10% 12% 14%

Top 10%

Middle 50%

Bottom 40%

Stability across income stages

Argentina Brazil Mexico Peru

-20%

0%

20%

40%

60%

80%

100%Top 10%

Bottom 40%

Middle 50%

Most and least equal income distributions, 2010

Country Palma GiniZambia 4.77 57.49Colombia 4.52 55.91Paraguay 3.73 52.42Panama 3.63 51.92Rwanda 3.22 50.82…    Serbia 1.08 29.62Montenegro 1.02 28.58Belarus 0.98 27.7Ukraine 0.89 25.62Romania 0.80 24.24

Palma vs GiniIf Palma so closely related to Gini; and Palma ignores half the income distribution; why would you possibly want to use it?

1. Policy axioms2. Gini flaws

P = y/x G = 58.1y – 119.5x + 41.86

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?

A horizontal axiom: Can measure also capture horizontal inequality?

Pop quiz

Which measure would you prefer?

Palma = top 10% share/bottom 40% share

Gini = 58.1(top 10% share) – 119.5(bottom 40% share) + 41.86

Alternative approach:

Global process defines (global) political priorities;

National (and local?) process sets targets

i.e. if it’s “too political” to impose targets, don’t;

instead, set targets through a political process.

Choice of ‘development’ aspects

Conclusions• Being uncounted reflects power

• Decisions on statistics are political

• Post-2015 offers great opportunities for progress (not least disaggregation, illicit flows); but not without recognising and confronting the (political) obstacles.

Proposals• Inclusive politics (as far as

possible)

• Indicators chosen for accountability

• Data to follow ambition (not v.v.)

• Funding now (NSOs <0.1% of aid)

@AlexCobham

Thank youcgdev.org/europe

Blatant 1: Choice of reporting

E.g. banking confidentiality

– Shadow banking: The Morning After the Night

Before

– Data provision: to BIS not public

Blatant 1: Choice of reporting

RANK Jurisdiction FSI 2013 -Value1 Switzerland 1,765.3 2 Luxembourg 1,454.5 3 Hong Kong 1,283.4 4 Cayman Islands 1,233.6 5 Singapore 1,216.9 6 USA 1,213.0 7 Lebanon 747.9 8 Germany 738.3 9 Jersey 591.7

10 Japan 513.1

Blatant 1: Choice of reporting

E.g. political suppression

– The Black Book of Sudan: Who holds power?

Blatant 1: Choice of reporting

North Central, ex Kh East Darfur Kordofan0

20

40

60

80

100

120

140

Development expenditure per capita, 1996-2000 (North=100)

Female IMR, 1993 (North=100)

Blatant 1: Choice of reporting

E.g. political suppression

– The Black Book of Sudan: Who holds power?

– Data provision: to IMF not citizens (then; now)

Blatant 2: Manipulation…• …of data– ‘1990 revisionism’

• …of targets (Thomas Pogge)

MDG-1 as adopted Halve fraction of world population2000

1,665

40.4%

993

3.39%

MDG-1 as revisedHalve fraction of dev’g population1990

1,813

27.0%

1,324

1.25%

World Food Summit

Language Halve number

Baseline year 1996

Baseline, millions 1,656

Target 2015 reduction 50.0%

Target for 2015, millions 828

Required annual reduction 3.58%

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.

Choice of ‘development’ aspects

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.

Choice of ‘development’ aspects

Palma vs GiniDecile 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