““ Economic development as Economic development as

equalization of equalization of

opportunitiesopportunities ””

John E. Roemer

Yale University

1

How to measure economic

development?

Classically, as GDP per capita

The normative justification:

Individual Welfare = income yi Social welfare is the sum or average of incomes: 1N

yi∑

Can be criticized in at least two ways:

o welfare is linear in income, which ignores the

urgency of some needs over others

o social welfare is utilitarian, and reflects no

concern for inequality

2

• A technological justification?

You might say: GDP per capita is not intended as a welfare

measure but as a measure of industrial capacity.

But economic development must mean the advance of

human

society; it cannot be a technological concept. A productive

technologyrun by slaves all of whose product goes to a

small elite shouldnot be considered a highly developed

economy.

So I insist the justification of an index of econ development

be corollary to a concept of social welfare

3

Various possibilities

4

Equality of opportunity

The distribution of the social objective (here

income) should be independent of

circumstances beyond the control of

individuals, but may reflect actions that are

within their control

‘Leveling the playing field’ metaphor means

compensating persons for the effect on their

achievments which reflect disadvantages

beyond their control. The ‘troughs’ in the

playing field are these disavantages

5

Language

• Circumstances are those aspects of a

person’s environment that influence

outcomes & are beyond his control

• The typology is the partition of the pop’n

into types, where all individuals of a type

have similar circumstances

• With a type, outcomes will differ because

of differential effort

6

Example: The distribution of income

by type, defined as level of

parent’s education in Austria

(2005)

7

Contrast with Denmark and Hungary:

8

Define ut (e) as the outcome for an individual of type t who

expends effort e. ut is monotone increasing in effort: so it is not a

classical utility function

Let the distribuition of the outcome in type at the status quo be

Ft (u). How can we compare the efforts of two individuals in

the same type? Easy.

In different types? Difficult. Observe that the distribution of effort

is itself a circumstance. So to properly define degree of effort, must

sterilize this distribution of the effect of circumstances upon it. I

propose: Measure the degree of effort of an individual by her rank

on the effort distribution of her type; but this is also her rank on the

outcome distribution of her type!

Thus the EOp prescription is: Design policy to minimize the

horizontal distances between the CDFs of the objectives of the types

9

Formally:

Define as the objective value of the folks in

type t at quantile of the distribution of the objective

when the policy is

Choose policy ϕ to

maximize .

If the policy is the status quo, I define:

.

This is the mean value of the objective for the most

disadvantaged type. It is the area to the left of the most

disadvantaged type’s CDF and bounded above by the line

at 1.

vt (π;ϕ )πϕ

mint

0

1

∫ vt (π;ϕ ) dπ

W EOp = mint

0

1

∫ vt (π;ϕ s.q. ) dπ

10

So the EOp prescription is : design policy to push the CDFs

to the right as far as possible.

11

To what extent is unequal

opportunity responsible for

inequality? Let C(F) be the coefficient of variation

squared of a distribution F. If we have a

partition of the pop’n into types, and F is the

aggregate distribution, we can decompose

C(F) into a sum of two pos numbers:

C(F) = C(ΦT )+ (ρ t∑ )2 ftC(F

t )

12

where ΦT is the counterfactual distribution of

income where every member of type t earns

exactly the average income of type t.

13

It’s therefore natural to think of C(ΦT )C(F)

as

a lower bound on the fraction of total

inequality due to circumstances. Therefore,

an upper bound on the degree of inequality

due to effort is:

ηupp bnd = 1− C(ΦT )

C(F).

14

We can also perform a ‘dual

decomposition.’ Partition the society into

tranches π where each tranche comprises the

set of individuals (of all types) who expended

effort of degree π . We have a

decomposition: C(F) = C(E)+ (ρπ )2∫ C(Eπ )dπ

where E is a hypothetical distribution in

which everyone who expended the same

degree of effort has the same income, and Eπ

is the distribution of income in tranche π .

In like manner, we can interpret

ηlwr bnd = C(E)C(F)

as a lower bound on the

degree to which effort accounts for inequality

15

I therefore propose as a measure of the

degree to which effort explains inequality as

η =12(ηupp bnd +ηlwr bnd ).

16

A two-dimensional index of

economic development (Wc

EOp ,ηc )

The first component measures how well the

most disadvantaged type is doing and the

second measures the degree to which effort

(as opposed to circumstances) explains total

inequality in the society

17

Application

Use the data set EU-SILC to compute the

index (W EOp ,η) for a set of 22 countries.

• Circumstance: Typology into three types

based upon level of parental education

• Objective: Income after taxes & transfers

in 2005. (note defect: does not include

the value of public goods)

18

AT

BE

CZ

DK

DE

EE

ES

FI

FR

GR

HU

IS

IT

LT

LU

LV

NL

PL

PT

SESI

UK

10000 20000 30000 40000level

0.80

0.85

0.95

degree

Levels & Degrees of development

19

Some comments:

0. Levels of η are high

1. Lowest levels W EOp are the east

European countries & Spain

2. The only undominated country is

Denmark

3. Iceland(IS) looks good: but this is pre-

crash

4. I don’t believe Greece’s value of η .

20

Country, UBE LBE average effort

AT 0.970434 0.92 0.945217

BE 0.982783 0.646 0.814392

CZ 0.919772 0.892 0.905886

DK 0.990947 0.976 0.983473

DE 0.995659 0.746 0.870829

EE 0.956504 0.831 0.893752

ES 0.953383 0.883 0.918191

FI 0.988751 0.954 0.971375

FR 0.971633 0.886 0.928817

GR 0.994 0.945 0.9695

HU 0.946974 0.604 0.775487

IS 0.984799 0.923 0.953899

IT 0.985046 0.777 0.881023

LT 0.965407 0.92 0.942704

LU 0.964373 0.747 0.855687

LV 0.964469 0.723 0.843734

NL 0.991502 0.878 0.934751

PL 0.983872 0.781 0.882436

PT 0.95876 0.834 0.89638

SE 0.984744 0.93 0.957372

SI 0.982 0.944 0.963

UK 0.991047 0.703 0.847023

21

All highly developed

countries

In LDCs, both indices (W EOp ,η) will be

much smaller. For Latin America, η will be

typically under 0.5.

22

Question: Is there value added

using this measure vs. GDP per

capita?

Let’s aggregate the two dims of development

as (W EOp )θη1−θ for various choices of

θ ∈[0,1] and ask: What’s the rank-

correlation between the numbers (W EOp )θη1−θ

by country and the order of GDP per capita

by country?

Answer: For θ > 0.3, Spearman coefficient

of rank correlation is over 0.95! Of course

we lose information by passing to a uni-dim

measure

23

Why? Two reasons:

(a) η > 0.80 for all countries in the

sample

(b) correlation of the order of WcEOp and

GDPc is very high

But in a panel of countries of the world, we

would see some more dramatic differences

between the two rankings – in the main

because values of η will be much smaller

countries at low levels of development

24

Economic development is equity

World Development Report 2006 : Equity

and Development . An excellent report.

But suffers confusion of implicitly assuming

that development is measured by GDP per

cap, and counterposing this with ‘equity’

conceived of as EOp

25

Some quotations from WDR 2006:

“Greater equity is thus doubly good for poverty reduction: through potential

beneficial effects on aggregate long-run development and through greater

opportunities for poorer groups within any society (p.2)”

“If the opportunities faced by children like N. are so much more limited than those

faced by children like P. or S., and if this hurts development progress in the aggregate,

then public action has a legitimate role in seeking to broaden opportunities….(p.3)”

“Third, the dichotomy between policies for growth and policies specifically aimed at

equity is false (p.10)”

26

Further discussion

• Choice of income as the objective and typology based

on parental education is suggested to enable us to

calculate (W EOp ,η) for a very broad set of countries

• Ideally include more circumstances: rural vs urban,

race/ethnicity, gender

• For Sweden, Bjorklund, Jantti and Roemer perform a

typology of 1152 types using a huge Swedish data set.

We compute (using a different method) that

circumstances are responsible for 33% of inequality –

as opposed to the measure here of ηSweden = 4.3%.

• Even in egalitarian Sweden, circumstances remain

important in the determination of income.

27

Treatment of children • Children are not responsible until an ‘age of consent’

–perhaps age 15. Nature and nurture are both

circumstances in the discussion of child achievement.

• So if we want to look at incomes at age 30 (say), we

should treat measures of accomplishment at age 15

(education, literacy, etc.) as circumstances. Not to do

so is to hold children responsible for what they

achieve below the age of responsible action.

• See World Bank, Measuring inequality of opportunity

in Latin America and the Caribbean for an excellent

analysis of that topic, and calculation of inequality of

opportunities with regard to child accomplishment

28

Are people responsible for

their preferences?

• No: not entirely. The child who grows up in a

home with parents who have not experienced

education should not be responsible for having a

preference against higher education

• To say such preferences are due only to ‘lack of

information’ is a cop-out

• My proposal compensates persons for the effect

of circumstances on the distribution of effort

choices in their type. Since, neo-classically,

effort choices result from preference-satisfaction

maximization, we do not hold persons

responsible entirely for their preferences, but

attempt to sterilize away the effect of

circumstances on choices. What variation in

29

choice remains after this sterilization is held to be

the person’s responsibility

• This is to some degree paternalistic. It is a liberal

fallacy that paternalism is an unmitigated evil

30

EOp versus Meritocracy • In a meritocracy, individuals receive incomes which

are monotonically related to their skill levels. In an

ideal EOp distribution, they receive incomes

montonically related to their effort. These are

different rules. A meritocracy rewards skills even if

they are due to circumstances, while EOp in principle

does not.

• Since markets rewards skills independently of their

cause (circumstance or effort), markets are meritocrats

are more friendly to markets than opportunity

egalitarians.

• E.g., In my view, a person should not be materially

deprived because he lacks native intelligence. But

implementing that kind of talent-blind income

distribution requires strong market intervention via

transfers, etc.

31

Scope

• But I do not propose including IQ as a circumstance in

the calculation of the indices of economic

development today. I propose limiting circumstances

to measures of socio-economic advantage (like

parent’s education & income), race, etc. Including

IQ as a circumstance is an ethical advance appropriate

for a future time

• A friendly amendment to my proposal is to meld the

human development index and EOp: Take the

measure of advantage as the HDI, but disaggregate

the distribution of individual human development by

type, and proceed as I have in this paper.

32

EOp is good policy • Equality of opportunity is an ethic endorsed by

billions of people. In many surveys, respondents

answer that the justice of the income dist’n depends on

the extent to which incomes are due to effort versus

luck. This is the distinction EOp captures.

• The utilitarian measure of GDP per cap is insensitive

to this distinction

• The HDI as it is currently measured is insensitive to

this distinction – even with its latest inequality-

sensitive variant

• Computing the two–dimensional index of economic

development described here is consonant with popular

views of justice, and will lead to different policy

proposals than the measure of GDP per capita.