Finance and Income Inequality: What Do the Data Tell ...

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Our results suggest that, in the long run, inequality is less when financial ..... Clarke, Xu, and Zou inequality-narrowing hypotheses might require long-run.
Southern Economic

2006, 72(3). 578-596

Journal

Finance and Income Inequality: What Do the Data Tell Us? and Heng-fu Zou{

George R. G. Clarke,* Lixin Colin Xu,|

there are distinct conjectures about the relationship Although their explanatory little empirical research compares power.

between

finance

and income

the relationship 1995. Because financial

We

examine

inequality, between

for 83 countries between 1960 and and income inequality develop we use instruments to be endogenous, from the literature on law, finance, and growth might is less when financial development control for this. Our results suggest that, in the long run, inequality and Newman is greater, consistent with Galor and Zeira the (1993) and Banerjee (1993). Although at very sector development that inequality might increase as financial increases results also suggest as suggested sector development, low levels of financial and Jovanovic this (1990), by Greenwood

finance ment

is not

result results

thus

robust. We suggest

that financial development reject the hypothesis to improving that in addition financial growth,

benefits

the rich. Our

only

also

development

reduces

inequality.

JEL Classification: D3, G2, Ol

1. Introduction Recent

have

studies

shown

Because

financial

are

markets

sector

that financial

fraught

with

adverse

selection

financial

as collateral

are well

markets might

as

benefit

In contrast,

developed.

sector

the financial

for the rich, but not the poor, itmight worsen But excluded

this might from with

people revolution

getting talents,

not

loans,

the

Department,

case.

markets

World

As gain

might

ambition,

in financial

* Research

be

and

Bank,

(Levine

growth

borrowers

problems,

who

If financial

do have

that can be used

property

development

access

improves

inequality. sector

to it. In this Rajan

persistence.

is "opening

hazard

and moral

the rich

develops.

the financial access

economic

benefits only the rich and powerful.

therefore, find it difficult to get loans even

need collateral. The poor, who do not have this, might, when

boosts

development

that financial development

1997b).1 But many people worry

the

gates

and of

grows, respect, Zingales the

1818 H Street, NW, Washington,

the poor, finance

DC

might

(2003,

aristocratic

20433;

were

who

p. clubs

E-mail

be 92) to

previously

an equalizer argue

that

for the

everyone,"

as

[email protected];

corresponding author. t Research Department, World

DC 20433; Guanghua School of Management, Bank, 1818 H Street, NW, Washington, Peking University, Beijing 100871, China; E-mail lxu 1(g)worldbank.org. DC 20433. E-mail [email protected]. | Research Department, World Bank, 1818 H Street, NW, Washington, We are grateful for suggestions of two anonymous referees. We thank Jerry Caprio, Robert Cull, Ross Levine, and Mattias Lundberg for comments. We are especially grateful to Thorsten Beck for early collaboration in this project, help in collecting and compiling data, and many useful discussions. The findings, interpretations, and conclusions expressed herein are those of and Development/The World the authors and do not necessarily reflect the views of the International Bank for Reconstruction Bank and its affiliated organizations, or those of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. Received October 2003; accepted June 2005. 1 For the relationship between financial development and growth see, among others, Beck, Levine, (2000). Loayza, and Beck (2000), and Rousseau and Wachtel

578

and Loayza

(2000), Levine,

Finance and Income Inequality

579

witnessed by the observation that, "in 1929, 70% of the income of the top 0.01% of income earners in the United

came

States

from

In 1998,

of capital....

holding

and

wages

income

entrepreneurial

made

up 80% of the income of the top 0.01% of income earners in the United States, and only 20% came from

capital."

the idea that financial development might benefit the poor, several theoret that income inequality will be lower when financial markets are better devel suggest show that when 1993; Galor and Zeira 1993). These models oped (Banerjee and Newman investments are indivisible, financial market imperfections perpetuate the initial wealth distribution, Consistent with

ical models

in a negative

resulting

between

relationship

financial

and

development

income

even

inequality

in the

run.

long

the relation between

Although that

possible

different

to a nonlinear

leading

at different

of

financial

development

and

levels

sector

financial

between

relationship

could be linear, it is also

inequality and financial development dominate

mechanisms

sector

development, Greenwood

inequality.

and Jovanovic (1990) show how financial and economic development might give rise to an inverted U-shaped relationship between income inequality and financial sector development. In their model, income inequality first rises as the financial sector develops but later declines as more people gain access

to the

system.

The relation between financial development makers?policy

growth. Although economic

want

makers

how

and income distribution affect

policies

is important for policy

as well

inequality

as how

they

affect

recent work has established a robust link between financial sector development and

and

less

1997b),

(Levine

growth

development

to know

inequality.

work

Understanding

on

has

focused

this

relationship

the

relation

will

allow

between

to assess

makers

policy

sector

financial

whether financial development will improve inequality and when it might be useful in doing so. Because different theoretical models give different predictions about the distributional impact of financial development on inequality, empirical investigation is needed to distinguish between the competing

conjectures.2

This paper analyzes the relation between the distributional impact of financial intermediary development and income distribution using data from developing and developed countries from between 1960 and 1995. Specifically, we analyze whether financial intermediary development affects income

inequality

different allow sector

and whether

mechanisms the

might to be

relationship to

development

endogeneity

using

results

impact

inequality

literature

(see,

show

that

inequality

for

level

of financial

levels causation

to financial

sector

example,

decreases

Zeira (1993) and Banerjee and Newman

2

because

inequality

financial

the

at different

Further,

or from for

on

depends

powerful

nonlinear.

instruments

development-growth Our

the be more

development

Levine as financial

(1993). Although

1997a, markets

could sector

Because

development.

of financial

sector run

in

from we

development,

suggested

development,

either

the

the we

financial control

financial

for sector

1999). deepen,

consistent

with

Galor

and

some weak evidence suggests that at low

in regressions looking at factors Li, Squire, and Zou (1998) and Li, Xu, and Zou (2000) include financial sector development that affect income inequality. This paper, however, differs from Li, Squire, and Zou (1998) and Li, Xu, and Zou (2000) in several ways. First, neither of these earlier papers is primarily concerned with the impact of financial sector development on inequality. Li, Squire, and Zou (1998) focus on explaining international and intertemporal variations in income inequality, whereas Li, Xu, and Zou (2000) focus on the relationship between corruption and inequality (and growth). They do not try to distinguish the various hypotheses as we do here; that is, they assume a linear relationship, and given their focus, they do not run a battery of specifications to examine the robustness of their results. In addition, they do not deal with the endogeneity of use a different measure of financial sector development financial development, that measures financial development less over and only include results from a pooled cross section. (M2 GDP), precisely

Clarke, Xu, and Zou

580

of financial

levels that

is, that

development is an

there

inequality

inverted

relation

U-shaped

as financial

increase

might

between

sector sector

financial

increases,

development

and

development

income

inequality, as suggested by Greenwood and Jovanovic (1990), this second result is not highly robust. We strongly reject the hypothesis that financial development benefits only the rich: We do not find a positive and significant relation between financial development In the next

we

section,

and

inequality

sector

of financial

the endogeneity

development. review

briefly

sector

financial

and inequality after controlling for

the

theoretical We

development.

on

literature

then

the

discuss

the

relation

between

that we

data

income

use

to

test

the

theoretical hypotheses in Section 3. After discussing the empirical specification and some estimation issues in Section 4, we present empirical results in Section 5 and conclude in Section 6.

2. Theoretical

on Finance

Perspectives

and

Inequality

Although most economists would not expect financial development in the long

the popular

run,

middlemen

serve

who

common

press,

of

the rich

a recent

of

chapter

and Marxist

literature,

interest

the

only

the first

that

some

book

theory

and well

to widen

often

depict

connected. the

defending

income inequality

system

are

views

these

Indeed,

free-market

as greedy

financiers

two

by

so

famous

economists, Rajan and Zingales (2003), is entitled "Does finance benefit only the rich?" One plausible reason why financial development might benefit the rich, especially when institutions are weak, is that the financial system might mainly channel money to the rich and well are

to offer

who

excluding

the poor.3 As financial sectors become more developed,

households

but

continue

sector

develops,

financial

able

collateral

to neglect

and who

be more

connected,

the poor

the poor

who

remain

might

are unable

to provide

to migrate

to urban

unable

to repay

likely

they might

while

to rich

even

as the or start

in education,

invest

areas,

loan,

a result,

As

collateral.

the

lend more

new businesses. This tendency might be reinforced if the rich are able to prevent new firms from getting access

to finance,

economic

income

and

development

the

Although

sector

financial

the

from

case,

and

entering,

we

would

see

to

expect

least at some

inequality?at

the ability

reducing

levels

of

a positive

of financial

to improve

the poor relation

development.

then

between

financial

We

this story

call

hypothesis of financial development.

the inequality-widening from

them

preventing If this were

lot.

arguments

previous

suggest

than

development

that

low-income

households

high-income

this

households,

is not

benefit

might

more

the case.

necessarily

As

financial markets become deeper, and access to finance improves, households that did not previously have access to finance might be the main beneficiaries. Because poor households cannot invest in human only

and their

households

physical own are

capital

resources, able

or bear they

to draw

on

will

the be

their

start-up

to do

unable

own

costs

resources

associated

with

so unless for

investment

they

starting can whatever

a new

business

the

using

In contrast,

borrow.

level

of

rich

financial

sector development. Therefore, capital constraints might be less binding for rich households at any level of financial sector development, and so they might gain less when these constraints are

loosened. Several

recent

market

theoretical

models

have

imperfections might and Newman (1993) and Galor and Zeira 3

This paragraph mainly

this

formalized

increase income

draws from Rajan and Zingales

intuition,

suggesting

that

capital

inequality during economic development. Banerjee (1993) suggest that capital market imperfections and

(2003), chapter

1.

581

Finance and Income Inequality

in investment in human or physical capital may lead to divergence of income for the rich and the poor even in the long run. Further, depending on the initial wealth distribution, these indivisibilities

imperfections

and Zeira

who

agents

given

inequality

persists

a two-sector

model

through

will

be

to the next

bequests

can

this

run.

long

between

bequests

capital

to make

able

in the

This

results

market imperfections and an initially unequal distribution of wealth will maintain more

grow

and Newman

larly, Banerjee indivisible

require

a similar

than

slowly

Because

of

inequal

with

capital

of wealth.

two

of

rich

only

imperfections,

invest

this inequality and

distribution

in which

model,

market

capital

initial

equitable

a three-sector

construct

(1993)

investment.

a more

with

economy

the

in income

an economy

In their model,

generation.

sector.

than

larger

bequests

investment.

where

generations,

in a skill-intensive

work

with

individuals

only

imperfections,

can borrow

even with

in human

investment

market

capital

is perpetuated

ity that

income

construct

indivisible

or who

amount

that

(1993)

an

make

However, ment

mean

might

Galor

the

Simi

technologies can

agents

borrow

enough to run these indivisible, higher-return technologies. Once again, the initial distribution of has

wealth

on

long-run

effects

With

all else

imperfections.

income

remaining

distribution

and

these

equal,

in

growth

models

the presence

of

suggest

market

capital

with

that countries

larger

capital

market imperfections, that is, higher hurdles to borrow funds to finance indivisible investment, should have

income

higher

financial thesis

inequality. and

development of financial

(1990)

but

a theoretical

present

should

We

inequality.

a

observe

relationship

between

inequality-narrowing

hypo

negative

this hypothesis

call

the

development.

a related,

Offering

we

Consequently,

income

different,

that has

model

on

perspective elements

these

of both

basic

ideas,

ideas.

In their model,

and

Greenwood

agents

Jovanovic the

operate

more profitable, but more risky, of two technologies only when they can diversify risk by investing in financial

coalitions.

intermediary

less

thus

and of

members

accumulate

intermediary

inequality.

However,

litions,

resulting

in

Jovanovic's ity and

(1990)

eventually

hypothesis

inverted

are,

thus,

and income

in or

hump with

in the

long

different

the

relationship first

as more of financial

among

coa

these

join

and

Greenwood

between

income

and

increasing

then

inequal decreasing

financial

coalitions.

We

relation

between

financial

intermediaries

these three hypotheses the access

improving

in

increase

call

this

development. the

about

and

join

people

eventually

Consequently,

inequality

predictions

in rich

trend.

upward

(high-income) in an

resulting

all agents

U-shaped

distinguishing

households

is fixed,

fee

with

that poor individuals

between

widen,

income run

is correct,

will

inverted

hypothesis

U-shaped

hypothesis

low-income

a

predicts

quite

(low-income)

reversal

differences

outsiders

associated

fees)

membership

income

slowly,

the entrance

development,

inequality. Yet

inequality-narrowing and benefit

eventual

stabilizing

the

There

and

because

model sector

financial

before

an

more

wealth

coalitions

income

(e.g.,

individuals from joining them. Assuming

these coalitions prevent low-income save

costs

the fixed

However,

in poor

countries

to finance alike.

is important. If the

would

reduce

In contrast,

if the

inequality inverted

U

shaped hypothesis

is correct, improving the access to finance might initially worsen income inequality

in poor

improving

countries,

it only

the

after

has

country

passed

a certain

stage

of

financial

sector

development. Finally, if the inequality-widening hypothesis is true, some countries might be trapped in a high-inequality world that would be only worsened by financial sector development. In what follows,

we

use

data

from

a broad

cross

section

of

countries

between

1960

and

1995

to assess

the

empirical validity of the different hypotheses. It is perhaps useful to note that the inverted U-shaped hypothesis concerns a situation in which the empiricist observes the evolution of income inequality and financial development during short-

the

development

or medium-run

process. time-series

Thus, or

panel

the

relationship

data.

In

would

contrast,

be testing

most the

likely

to

show

inequality-widening

up

in and

Clarke, Xu, and Zou

582

inequality-narrowing time

long

hypotheses

might

require

as cross-sectional

such

data,

long-run

data

on

based

series.

3. Data This section describes our indicators and data for financial intermediary development and income inequality as well as the set of conditioning information. Table 1 presents descriptive statistics and correlations.4 The income inequality data are based on a new data set of Gini coefficients compiled by Deininger and Squire (1996) and extended by Lundberg and Squire (2000). Although the original data set contained over 2600 observations, Deininger and Squire (1996) and Lundberg and Squire (2000) limited the data set by imposing several quality conditions. First, all observations had to be national

from

household

for

surveys

the national

of

sentative

population. own

accounted

for,

including

To

explore

whether

or

expenditure all

Third,

income.

sources

the

Second,

income

of

of

to be

had

coverage

uses

and

repre to be

had

expenditure

consumption.5 is an

there

inverted

U-shaped

between

relationship

economic

development

and income inequality, as proposed by Kuznets (1955), we regress the logarithm of the Gini coef ficient on the log of real per capita GDP and its square. Figure 1 shows the result for the panel sample. The

for alternative

of an

the existence

suggests

graph

income

of

explanations

inverted

curve.

U-shaped such

inequality,

this graph

However,

as financial

not

does

control

depth.

recent literature on the relationship between financial intermediary development and economic growth has developed several indicators to proxy for the ability of financial intermediaries to The

identify

profitable

resource

mobilization.

GDP banks ment

monitor

and

concentrate

on

projects, We

and nonbank

private

sector

access

to loans

a measure

intermediaries

enterprises have

agents

access

sector

of financial

of financial

sector

a good

seems intermediation

and

management, financial

by

development showing

on

central

facilitate over

intermediaries

economic

that growth

as

banks

proxy

and

growth

have

and

the extent

used

in countries

govern

or

1990)

that have

studies this

from

to which

Jovanovic

recent

1993). Many

is faster

lenders

for

variable

(as in Greenwood and Zeira

1993, Galor

development,

sector

excludes

(but which

to financial

risk

comprises credit to private firms and households

as borrowers),

and Newman

(as in Banerjee

at the effect

looked

financial

state-owned

ease

managers, to the private

credit

indicator, which

(private credit). This and

control

as

variable

where

private

credit is higher (see, for example, Beck, Levine, and Loayza 2000; Levine, Loayza, and Beck 2000). To

assess

the robustness

of results,

we

use

a second

measure

of financial

development:

claims

on

sector by deposit money banks divided by GDP (bank assets). In contrast to private credit, this measure excludes credits by nonbank financial intermediaries and includes the nonfinancial domestic

credit

4

to governments

and

state-owned

enterprises.

Australia, Austria, Belgium, Burkina Faso, the Bahamas, Bolivia, Botswana, Brazil, Cameroon, Canada, Chile, China, Colombia, Costa Rica, Cote d'Ivoire, Cyprus, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Finland, France, Gabon, Gambia, Germany, Ghana, Greece, Guatemala, Guinea Bissau, Guyana, Honduras, Hong

The sample includes Algeria, Argentina,

India, Ireland, Italy, Jamaica, Japan, Jordan, Kenya, Korea, Luxembourg, Madagascar, Malawi, Mali, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Pakistan, Panama, Paraguay, Peru, Philippines, Portugal, Senegal, Sierra Leone, Singapore, South Africa, Spain, Sri Lanka, Sudan, Sweden, Thailand, Trinidad and Tobago, Tunisia, Turkey, Uganda, United Kingdom, United States of America, Venezuela, Zambia, and Zimbabwe.

Kong

(China), Indonesia,

Malaysia, Mexico, Morocco,

5

sampling methods, we adjust the data using a method suggested by Deininger and Squire (1996) and also applied by Li, Squire, and Zou (1998) and Lundberg and Squire (2000). Specifically, Deininger and Squire (1996) find Gini coefficients. We, a systematic difference of 6.6 points between the means of income-based and expenditure-based therefore, add 6.6 points to the expenditure-based Gini coefficients.

To account for different

Finance and Income Inequality Table 1. Descriptive

Number

583

Statistics Gini Coef.

Private Credit

Bank Assets

205 38.4 22.4 61.1

205 44.9 1.6 202.8

205 42.4 2.5 132.1

Initial GDP per Capita

Risk of Ethno-linguistic Fract.

Gov't Cons.

Exprop.

Inflation Mod Sect. Rate Val. Add.

of

observations Mean Minimum Maximum Gini coefficient Private credit

1.00 -0.38

1.00

Bank assets

(0.00) -0.48

0.86

Initial GDP

(0.00) -0.59

(0.00) 0.69

0.61

per capita Risk of

(0.00) -0.59

(0.00) 0.64

(0.00) 0.66

205 5552 160 20,367

(0.15) -0.48

Inflation

(0.00) 0.33

0.32

rate

-0.28

0.78

(0.00) 0.37

(0.00) 0.61

sector

-0.25

0.55

1.00

(0.00) 0.50

-0.36

(0.00) (0.00) -0.22

-0.30

1.00

(0.00) -0.45 -0.50

(0.00) (0.00) (0.00)

Modern

205 205 1.15 86.0 1.00 43.3 3.22 99.6

1.00

(0.00) (0.00) (0.00)

consumption

205 14.3 5.6 27.9

1.00

(0.00) (0.00) (0.00) 0.11 -0.38 -0.35

expropriation Ethnolinguistic fractionalization Government

163 0.25 0.00 0.86

205 7.3 3.3 10

-0.21

0.54

0.68

-0.21

-0.03

(0.00) (0.00)

value added/GDP (0.00) (0.00) (0.00)

1.00

(0.00)

0.67

(0.72) -0.68

(0.00) (0.00)

1.00

(0.00) 0.47

(0.00)

-0.06

1.00

(0.00) (0.43)

Gini coefficient from Deininger and Squire (1996) and Lundberg and Squire (2003). Gini, measurement-adjusted GDP per capita, real per capita GDP; Source: Loayza et al. (1999). Private Credit, claims on the private sector by financial institutions divided by GDP. Source: Beck, Demirgii?-Kunt, and Levine (2000). Bank Assets, claims on domestic nonfinancial sector by deposit money banks divided by GDP. Source: Demirgii?-Kunt and Levine (2000). Risk of Expropriation, index indicating risk of expropriation through confiscation or forced nationalization. Higher values indicate that risk is lower. Source: PRS Group (2003). Fractionalization, average value of five indices of ethnolinguistic fractionalization, with values ranging Ethnolinguistic from 0 to 1, with higher values indicating greater fractionalization. Source: Levine, Loayza, and Beck (2000). Government Consumption, government consumption as share of GDP. Source: World Bank (2004). Inflation Rate, log difference of Consumer Price Index. Source: International Monetary Fund (2002). Modern Sector Value Added/GDP, value added of service and industrial sectors as share of GDP. Source: World Bank (2004).

use private credit rather than the ratio of money

We a measure

used

commonly

to measure

financial

sector

and quasimoney

development

(M2) to GDP

and Levine

(King

1993;

(M2), Levine

1998), for several reasons. First, the ratio of M2 to GDP includes the liabilities of central in addition to banks and other financial intermediaries. Second, it includes credit to

and Zervos banks

governments

and

development

than private

Our

sample

state-owned

shows

enterprises.

Because

of

this,

it is a less

clean

measure

of financial

sector

credit. a

large

variation

in financial

intermediary

development.

Private

credit

ranges

to over 200% in Japan (1990-1995). The indicators of (1990-1995) financial intermediary development are positively and significantly correlated (see Table 1). The pairwise correlations indicate that income inequality is lower in countries with deeper financial markets; financial sector development is significantly and negatively correlated with theGini coefficient. Plotting from 2% of GDP

in Uganda

the logarithm of the Gini coefficient and its fitted value (from the regression of the logarithm of the

Clarke, Xu, and Zou

584

o log(Gini)

A fitted

value

4.5

3.5 0oo0o%0?0?

o

3H "i-r~

6

4

8 per

log(GDP

10

capita)

and log(GDPper 1. Log(Gini) Figure capita) in a panel of 91 countries. The fitted line is from a regression of log(Gini) on the log of real per capita GDP and its square. All data are averaged over seven 5-year periods between 1960 and 1995.

Gini coefficient on the logarithm of private credit) against the logarithm of private credit, Figure 2 sug gests

a negative,

and possibly

4. Empirical To

we

explore estimate

the

between

relationship

the following

financial

intermediary

discussed

claims

previously,

on

sector

the private

by

(private credit) and claims on the nonfinancial domestic GDP

(bank

f(Financeit)

are

assets)

based

which,

the measures on

earlier

and

development

income

regression:

In (Gini Coef.it) = ^o + /(Financeit) As

two.

the

between

Framework

further

inequality,

relation

nonlinear,

of

sector

financial

discussions,

we

QL\iFinanceit

+

(i)

+ a2CV;, + e,-,.

financial

as percentage

institutions

sector by deposit money The

development.

assume

has

focus

the following

of GDP

banks divided by the

of

functional

is

analysis form:

a^Financel.

The inequality-narrowing hypothesis predicts an < 0 and oti2= 0, the inequality-widening hypothesis = 0, and the inverted predicts an > 0 and ai2 U-shape hypothesis predicts an > 0 and ai2 < 0. In addition

to the financial

sector

we

variables,

include

several

to control

variables

for other

factors

thatmight affect inequality. Specifically, we include linear and squared terms of the log of (initial) real per

capita

GDP

to control

for a direct

that is independent of financial f(Financeit) steady-state convergence.

captures

the effects

situations,

initial

However,

because

"Kuznets

per

would capita

on

steady-state

Once

capture GDP

is highly

has

correlated

controlling If the

inequality.

whatever

on

development

intermediary development.

of finance GDP

of economic

effect"

been with

real

achieved financial

income

inequality

for initial GDP, data by sector

do

not

the

reflect

force

development,

of

and Income Inequality

Finance o log(Gini)

a

fitted

585

value

4.5

Qd

?&A1

^

o O

?o

? O

oOdpo O,? _ fi

M|ftA

3.5

3H "i-r

4

2 log(PRIVATE CREDIT)

log(Private Credit) in a panel of 91 countries. The fitted line is from a regression of log(Gini) 1960 and 1995. and its square. All data are averaged over seven 5-year periods between

against Figure 2. Log(Gini) on the log of Private Credit

that our

sure

to make GDP

per

capita

to these

In addition inflation

rate,

than

the rich

their

exposure

latter

to inflation.6

We,

a measure

and

income

inequality

across

available

It is less

time,

income

decrease against

include

For by

inflation

of

government

consumption,

ethnic

of

ethnic

diversity

to the

same

although

it could

also have

rights

fractionaliza We

might

effect,

expect

if, for example,

This

was

variable

not

all periods. protection

of property

the opposite

to hedge

them

is greater

for

more

relatively

ethnolinguistic expropriation).

value

the protection

class

the

coefficient.

is greater.7

and property

include

We

that allow

fractionalization

where

consumption

the middle

a positive

to have

it is set equal

example,

the poor,

and

between variables.

these

variables.

instruments

(the risk

rights

where

in countries

government

inequality.

expropriation

expect

in countries

therefore,

and,

whether

to financial

of property

the protection

to redistribution

clear

therefore,

the poor

access

omitting

control

additional

hurts

to the multicollinearity

respect the model

estimate

several

instability better

measures

to be higher

are averse

people

rich

of

have

also

include

that monetary the

we

we

with

is robust

we

development,

measures,

conjecturing because

Additionally, tion,

test of the three hypotheses

and financial

rights

will

increase protect

might

that is, protecting

or the

the poor

against exploitation by the rich. Similarly, ifmost redistribution through the tax and transfer system is toward

low-income

groups,

government

consumption

might

result

in greater

equality.

However,

it

could also have the opposite effect if rich households use their political power to exploit the poor. 6 7

See, for example, Easterly and Fischer (2001). Consistent with this, Alesina, Baqir, and Easterly ( 1999) find that spending on productive public goods (e.g., on schools) is lower in fractionalization was unavailable for many of the countries in our U.S. cities where ethnic diversity is greater. Ethnolinguistic on the other regressors for countries with missing data. Results we values based To excessive avoid loss, imputed sample sample. were robust to using other imputation techniques, including hotdeck imputation (Mander and Clayton 1999) and multiple impu tation (Royston 2004). Although the hotdeck approach was used for all regressions, themultiple imputation approach could be used only for OLS regressions. Results were similar in terms of size and statistical significance for the coefficients on the finance variables. Results were also similar for those coefficients when we simply dropped ethnolinguistic

fractionalization

from the estimation.

Clarke, Xu, and Zou

586

Kuznets

income

a variable

include

inequality

The

might

correlation

on

depend

the share

representing

to agriculture).

(as opposed

industry

that

suggests

we

Thus,

economy. and

(1955)

of value

the

added

the modern,

of

sectoral

of

for by

services

accounted

that

an

structure

is, nonagricultural

sector,

share of GDP and GDP per capita indicates that richer countries have largermodern sectors. Although the simple this

correlation

After

entire

conduct

the

long-term

contrast, ity and,

the long-term

of most

the convention

Following

analysis

using and

cross-country

empirical

rather

shorter

than

for most

basis

time

because

spans in our

countries

financial

although

sample,

be

they might

The

panels.

between

finance U-shaped the panel

to business

of testing

and

inequal

analysis

splits

use 5-year periods on

a

yearly

that are

fluctuations

cycle

In

hypothesis.

are available

data

intermediary

the

hypotheses.

5-year periods. We

subject

a way

offering

studies,

over

cross-sectional

the inverted

panel

the sample period 1960 to 1995 into seven nonoverlapping

significant.

averaged

inequality-widening

to test

in which

setup

sectors.

agricultural

data

inequality,

is negative,

and

using

comovement

of

larger

five-year

and

coefficient

positive

analysis,

finance

the process

the Gini and

becomes

cross-sectional

between

appropriate

and

inequality

correlation

inequality-narrowing

examine

might

be a more

might

of GDP

greater

data

relationship in the

featured

analysis

therefore,

a pure

and a panel

1995,

share

have

the partial

in two ways:

and

relationship

the panel

sector's

countries income,

capita

1960

capture

might

the modern poorer

the analysis

between

period

analysis

because for per

controlling We

between

to be

appears

controlled for by averaging over longer time periods. All panel regressions include time dummies to account we

for

structural results

present

from

random

bias

OLS

because

To

periods.

effects

account

take

of

does

not

allow

for

the possibility

reverse

of

who

affects

income

financial

we

Because we

inequality, similar

development

to join financial

is able

sector.

the financial

use

an

are

variables

in Levine

development

approach,

(1997a,

on economic

and,

in the effect

interested

primarily

used

coalitions

intermediary

instrumental

to the ones

intermediary

of

the data,

affect

might sector

the size of on

development

for financial

the exogenous

sector of

impact

are a set of dummy

instruments

the

suggested in some of the the initial distribution of

instruments assesses

which

The

growth.

therefore,

of financial

adopting

1999),

is, for

causality?that

possibility that inequality affects the provision of financial services?something theoretical models. For example, inGreenwood and Jovanovic's (1990) model, wealth

structure

the panel

estimation.

1 using ordinary least squares (OLS) (or random effects) estimation might

Estimating Equation introduce

across

differences

variables

proposed by La Porta et al. (1998) that identify the origin of the country's legal system.8We use the legal because

(1998), differences

rather

variables,

dummy

origin

are

they

in legal

the measures

than

available are

origin

for

a wider

significantly

of

creditor

sample

of

to financial

related

also

rights,

proposed

Several

countries. sector

papers

development,

by La

Porta

have

et al.

shown

perhaps

that

because

different legal traditions put different levels of emphasis on the rights of property owners or because some

systems

examine

8

are more

the validity

of

adaptable the

to exogenous

instruments

using

than

changes Hansen's

J-test

others.9

to test

In the empirical

the overidentifying

analysis,

we

restrictions.10

The measures

of legal origin were taken from the Global Development Network Growth Database produced by William Sewadeh (see Easterly 2001). Easterly 9 and Levine (2001) provide an excellent summary of much of the empirical and theoretical literature on Beck, Demirgii?-Kunt, this topic. La Porta et al. (1998) show that protection for corporate shareholders and creditors are strongest in common law and Mirvat

in French Civil Law countries. La Porta et al. (1997) relate these variables to some measures of capital (external market capitalization over GDP, number of listed firms per capita, initial public offerings), development showing that they are generally lower in civil law (especially French Civil Law) countries than in common law countries. and Levine (2001) show that private credit is lower in French Civil law countries than inGerman Civil Beck, Demirgii?-Kunt, countries and weakest

market

Law and common law countries. 10 In similar regressions of financial sector development on economic restrictions are valid. hypothesis that the overidentifying

growth, Levine

(1997a,

1999) fails to reject the null

Finance and Income Inequality Results

5. Empirical

from Cross-Sectional

Relationship

Long-Term test

To

587

the

and

inequality-widening

the

Samples

inequality-narrowing

we

hypotheses,

the natural

regress

log of the Gini coefficient on linear terms for the measure of financial sector development (private credit) and the additional control variables. Before we control for the possible endogeneity of the measures

sector

of financial

statistically

significant,

on private

the coefficient

development,

that

indicating

in countries

is lower

inequality

credit

but

is negative

statistically

on banks assets is also negative but is

1 of Table 2). The coefficient

insignificant (see column

where

are greater

assets

bank

as

a share of GDP (see column 3 of Table 2). Results for both measures are qualitatively similar when we omit per capita GDP and per capita GDP squared from the regression (see Table 3). These results, as we

discussed

not

do

earlier,

take

account

into

the

issue

of

the endogeneity

the finance

of

variables.

After controlling for endogeneity using the indicators of legal origin as instruments, the coefficient on

credit

private

remains

are

5). Results

similar

but

negative when

in size

increases

and becomes

statistically

as the measure

are used

assets

bank

(see column

significant sector

of financial

(see

development

column 7). This suggests that financial sector development reduces income inequality, supporting the inequality-narrowing hypothesis and rejecting the inequality-widening hypothesis of financial development. favoring

as

development dummies

origin that

tests

Hypothesis the results

are

they

from

the null

reject

the 2SLS

regressions,

endogenous.11

In addition,

are uncorrelated

with

we

the error

instruments

appropriate

that

hypothesis consistent

with

are unable term

(see Hansen

after

the financial

to reject

for in the

J-Statistics

variables,

relevant

financial

that

hypothesis

the other

exogenous,

that view

papers

the null

controlling

are

variables

the theoretical

tables).

the

legal

suggesting on

Based

the

coefficient estimates in column 5, a 1% increase in private credit decreases the Gini coefficient by 0.31%. Results are similar when per capita GDP is omitted (see Table 3), with the point estimate of the parameter

the

the measures

at -0.27.

smaller

slightly

test

To

inverted

U-shape

of financial

sector

of financial

hypothesis

(see

development

we

development,

columns

6 and

include

8). Because

squared

terms

for

on

the

the coefficient

squared term is statistically insignificant in all model specifications, the results do not support this hypothesis. Although the coefficient on the linear term becomes statistically insignificant in both model the

when

specifications linear

and

development

squared is treated

development

does

the squared terms

are

jointly

as endogenous.

affect

term

inequality,

is included,

significant

to note

it is important at a

1%

level

Thus,

these

regressions

it appears

to do

so in a roughly

that

the coefficients

when

financial

that although

financial

or higher

suggest linear

fashion.

data might provide a better way of testing the inverted U-shape hypothesis or medium-run

short-

After

controlling

variations for

in the comovements

the endogeneity

of

of financial

the financial

sector

sector the panel

However,

if panel data better capture

development variables,

on sector

many

and of

inequality. the coefficients

on

the other control variables are statistically insignificant (see column 5 of the relevant tables). Although the coefficients on the linear and squared terms for initial GDP per capita are statistically insignificant, they are jointly significant inmost model and

the negative

11 When

coefficient

on

the

squared

specifications.12 The positive coefficient on the linear term term

suggest

an

inverted

U-shape,

with

income

inequality

we perform a Durbin-Wu-Hausman test using an auxiliary regression (see Davidson and MacKinnon 1993), the null that credit" is is rejected at a 1% significance level (p-value = 0.001). For "bank assets," the exogenous hypothesis "private null hypothesis that it is exogenous is rejected at a 5% significance level (/7-value = 0.043). 12 are a at 1% level or higher when bank assets are included, jointly significant at a 10% level when They jointly significant private credit is included linearly, and statistically insignificant when private credit is included linearly and in squared terms.

588

Clarke,

Xu,

and

Zou

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