ETHNIC DIVERSITY, POLITICAL STABILITY,

AND PRODUCTIVE EFFICIENCY:

EMPIRICAL EVIDENCE

FROM THE AFRICAN COUNTRIES

March 20, 2013

Alexandre Repkine

ETHNIC DIVERSITY AND ECONOMIC PERFORMANCE

The negative consequences of ethnic dive

rsity:

Poor economic policies (Easterly and Levine, 19

97)

Suboptimal social capital formation (Easterly, 20

01)

Poor infrastructure and underprovision of

public goods (Collier and Gunning, 1999)

Low economic growth, also due to inadequate

provision of public goods (Alesina and La Ferrar

a, 2005)

ETHNIC DIVERSITY AND ECONOMIC PERFORMANCE

The positive side of ethnic diversity:

Human capital created due to implicit contract enforcement (Bates, 2000)

Ethnic diversity fosters competition and survival by analogy with biodiversity (Nettle and Romaine, 2000)

Ethnically diverse countries grow faster (Cinyabuguma and Putterman, 2011)

Ethnic diversity leads to higher productivity in terms of a private (as opposed to public) good: Alesina and Ferrara, 2005

ETHNIC DIVERSITY, PUBLIC AND PRIVATE GOODS

Ethnically diverse societies should find

themselves closer to the best-practice frontie

r

The best-practice frontier may itself be

depressed or stagnating

Hence no contradiction between Africa being

ethnically diverse and economically depresse

d

WORLD DISTRIBUTION OF LANGUAGES

Area Living languages Number of speakers

Count Percent Total Percen

t

Mean Median

Africa 2,146 30.2 789,138,977 12.7 367,726 27,000

America

s

1,060 14.9 51,109,910 0.8 48,217 1,170

Asia 2,304 32.4 3,742,996,641 60.0 1,624,565 12,000

Europe 284 4.0 1,646,624,761 26.4 5,797,975 63,100

Pacific 1,311 18.5 6,551,278 0.1 4,997 950

Totals 7,105 100.0 6,236,421,567 100.0 877,751 7,000Source: Ethnologue.com

ETHNIC DIVERSITY: NIGERIA

Nigeria

522 living languages

3 major language families

:

--Afroasiatic

--Nilo-Saharan

--Niger-Congo

88% (or 57%) ethnically

diverse

Population: 140 mn peopl

e

ENDOGENEITY ISSUES

Institutional frameworks help alleviate ethnicit

y-based conflicts

Democracy (Bluedorn, 2001; Collier, 2000)

Ethniciy-based conflicts may worsen econom

ic environment

Rent-seeking behavior (Mauro, 1995)

Worse institutional quality (Alesina et al., 2003)

GENERAL CAUSALITY FRAMEWORK

Ethnic Diversit

y

Productive

Efficiency

Complementarity of skills

Demarginalizatio

n

policies

Social inclusion

Opportunity co

sts of ethnic co

nflict

Vested interests

Awareness of

oppression / rents

Political aspiration

s

ETHNICITY AND LANGUAGE

Ethnicity is not identical with language

Two ethnicities vs one language Irish and English

Flemish and Dutch

Same ethnicity vs two languagesThe murky world of dialects

Spanish vs Catalan

Japanese vs Ryukyu

Our assumption: ethnicity = languageData issues

MEASURING ETHNIC DIVERSITY

Greenberg (1956)

Monolingual nonweighted index

Minimum informational requirements

Assumption of mutual non-intelligibility

Portuguese and Spanish vs Hungarian and Spanish

Afrikaans and Dutch

Assumption of absence of polyglots

Split personality nonweighted index

Same idea, but each language speaker counted as a

separate personality:

n

i

isEDI1

21

is Share of people speaking language

i

MEASURING ETHNIC DIVERSITY

EDI varies between 0 and 1: from no diversit

y to very diverse

However, the nonweighted index misses the

fact of mutual intelligibility between the two la

nguages

Diversity may be overestimated

The weighted version of ethnic diversity inde

x: n

i

n

j

ijji rssEDIW1 1

1is the measure of mutual

intelligibility

1,0ijr

COMPUTING ETHNIC DIVERSITY INDICES

Ethnologue (Lewis, 2009) provides data on the number of speakers in different countries

Ethnologue.com

World Atlas of Language Structures: data on 142 language characteristics for

Wals.info

Dryer and Haspelmath (2011)

Linguistic similarity computed as share of similar characteristics

ijr

Mean Median St.Dev. Minimum Maximum

Unweighted 0.63 0.68 0.24 0.0007 0.95

Weighted 0.51 0.53 0.22 0.0003 0.88

ETHNIC DIVERSITY INDICES IN SAMPLE

Country Weighted Index of

Ethnic Diversity

(EDIW)

Unweighted Index of

Ethnic Diversity (EDI)

Algeria 30.00% 81.29%

Angola 30.86% 77.44%

Benin 84.39% 92.11%

Botswana 26.90% 56.41%

Burkina Faso 48.11% 60.05%

Burundi 32.12% 42.86%

Cameroon 47.15% 69.75%

Central African

Republic

55.43% 63.84%

Chad 40.42% 69.98%

Comoros 52.81% 70.08%

Congo, Democratic

Republic of

46.23% 58.54%

Congo, Republic of 58.73% 75.88%

Cote d’Ivoire 48.95% 59.72%

Djibouti 36.81% 53.25%

Egypt 35.21% 60.64%

Equatorial Guinea 65.15% 66.70%

Ethiopia 72.29% 86.08%

Gabon 64.83% 68.35%

Gambia 49.68% 61.54%

Ghana 62.97% 79.19%

Guinea 55.13% 58.84%

Country Weighted Index of

Ethnic Diversity

(EDIW)

Unweighted Index

of Ethnic

Diversity (EDI)

Guinea-Bissau 57.26% 70.67%

Kenya 43.98% 71.24%

Lesotho 8.88% 26.04%

Liberia 81.82% 91.45%

Madagascar 71.89% 71.94%

Malawi 40.20% 52.32%

Mali 78.02% 87.35%

Mauritius 15.09% 15.10%

Morocco 20.45% 46.26%

Mozambique 88.16% 93.19%

Namibia 68.62% 77.17%

Niger 55.19% 63.98%

Nigeria 57.23% 87.57%

Rwanda 0.03% 0.07%

Senegal 70.02% 76.68%

Seychelles 4.98% 6.67%

Sierra Leone 73.78% 82.12%

Somalia 33.81% 35.04%

South Africa 48.06% 86.83%

Sudan 36.63% 46.30%

Swaziland 11.80% 19.44%

Tanzania 75.07% 94.70%

Togo 82.56% 89.74%

Tunisia 49.86% 49.93%

Uganda 67.96% 92.78%

Zambia 78.66% 87.71%

Zimbabwe 49.88% 54.54%

EMPIRICAL FRAMEWORK

LAWPROPINCLHEDIWSTABLESTABLE ,,,,

Political stability affects productive efficiency

Ethnic diversity affects political stability in both direct and indirect ways:

STABLE = Political Stability

EDIW = weighted index of ethnic diversity

H = human capital

INCL = quality of policies for social inclusion

PROP = property rights protection

LAW = extent of the rule of law

STABLEEDIEffEff ,

QUANTITY AND QUALITY OF HUMAN CAPITAL

Fedderke and Luiz (2008) Quality of human capital: e.g. teachers to pupils

Political aspirations hypothesis: less stability

Vested interests hypothesis: more stability

Quantity of human capital: e.g. number of secondary school years Social inclusion hypothesis: more stability

Potential Endogeneity Stable environment might influence e.g. opportunity costs

of ethnic conflict Modernization hypothesis

Creative destruction hypothesis

Two-stage instrumental estimation

ETHNIC DIVERSITY AND POLITICAL STABILITY:

TWO-STAGE INSTRUMENTAL ESTIMATION

Political stability affects productive efficiency

Ethnic diversity affects political stability along

with the other factors

Two-way causality is possible, necessitating t

he two-stage estimation approach

itititit

itititit

XZY

XYSTABLE

210

210

exogenous controls: log initial GDP p

er capita, logs ethnic diversity and its s

quare

endogenous determinants of political

stability: educational variables, property

rights protection, rule of law, social inclusio

n policies

itX

itY

vector of instruments for itZ

itY

0ititZE 0itit STABLEZE 0itit ZYE

CHOOSING INSTRUMENTS

World development indicators database

Algorithm: Choose set of instruments (many)

Run 2SLS estimations instrumenting elements of Y Instrument one element at a time (collinearity)

Pick estimations satisfying the: Wu-Hausman exogeneity test

Sargan’s (1958) test for overidentifying restrictions

Run Cragg and Donald’s (1993) test of weak instruments on the remaining estimations Choose the one with the highest value of the minimum eigenvalue

statistic

Prefer LIML to 2SLS in case this statistic is lower than either 2SLS relative bias at 5%, or 2SLS nominal 5% Wald’s test statistic

LIST OF INSTRUMENTS

Public spending on education, % GDP, log

Share of public education expenditure in total education expenditure, log

Share of government expenditure channeled into education, log

Share of public education expenditure on primary education, log

Share of public education expenditure channeled into secondary education, log

Secondary school starting age

Expenditure per student in secondary education as % of GDP per capita,log

Poverty headcount ratio at $1.5 a day, log

Gini coefficient, log

Ratio of young literate females to males, log

Population density, log

Dummy=1 if one of official languages is English, French, or Portuguese

Expenditure per student in primary education as % of GDP per capita,log

Expenditure per student in tertiary education as % of GDP per capita,log

Poverty headcount ratio at $1.5 a day, log

Gini coefficient, log

Employment to population ratio, ages 15 to 24, log

Population density, log

Estimation Method LIML 2SLS LIML LIML

Dependent Variable

Primary

Education

Quantity

Political

Stability

Secondary

Education

Quantity

Political

Stability

Social

Inclusion

Political

Stability

Property

Rights

Protection

Political

Stability

-.07

(-1.24)

0.37*

(2.04)

0.08

(0.95)

0.47**

(2.64)

0.10***

(4.37)

0.36*

(2.36)

-0.041

(-0.80)

0.57***

(2.94)

-0.001

(-0.19)

0.03

(1.17)

0.007

(0.72)

0.05*

(2.15)

0.01***

(4.76)

0.02

(1.09)

-.02**

(-3.05)

0.07**

(2.72)

Initial GDP per capita,

log

0.08***

(3.97)

-0.47***

(-6.73)

0.02

(0.68)

-0.56***

(-7.5)

0.07***

(9.42)

-0.53***

(-7.67)

0.09***

(5.24)

-0.78***

(-6.89)

Ln Primary Quantity 1.14**

(2.99)

Ln Secondary

Quantity

0.69***

(3.82)

Ln Social Inclusion 4.37***

(5.10)

Ln Property Rights 4.73***

(3.59)

EDIWln2

ln EDIW

Political Stability and Its Determi

nants

1. Political stability positively associated with all determinants (naturally)

2. Vested interests : ethnic diversity positively associated with property rights

protection

3. Ethnic diversity is positively associated to political stability: evidence agains

t political aspirations, pro social inclusion and vested interests: causality is

NOT implied!

Political Stability and Its Determi

nantsEstimation Method LIML 2SLS 2SLS LIML

Dependent Variable

Rule

of Law

Political

Stability

Tertiary

Education

Quantity

Political

Stability

Primary

Education

Quality

Political

Stability

Secondary

Education

Quality

Political

Stability

0.37***

(8.55)

0.37**

(2.81)

0.13

(1.26)

0.22

(1.10)

0.19***

(4.93)

0.36

(1.92)

-0.12*

(-2.25)

0.93***

(4.63)

0.04***

(8.11)

0.04*

(2.36)

0.02

(1.49)

.009

(0.36)

0.02***

(4.38)

0.04

(1.54)

-0.01

(-1.74)

.09***

(3.98)

Initial GDP per capita,

log

-.01

(-0.61)

-0.42***

(-7.45)

0.10*

(2.06)

-0.68***

(-6.85)

0.03**

(2.38)

-0.56***

(-6.05)

0.09***

( 4.34)

-.66***

(-9.14)

Ln LAW 3.15***

(6.64)

Ln Primary Quality 1.44**

(2.69)

Ln Tertiary Quantity 0.61***

(3.70)

Ln Secondary Quality 3.07***

(5.05)

EDIWln

2ln EDIW

Ethnic diversity positively related to rule of law: vested interests hypothesis

Political aspirations hypothesis does not find support

Ethnic diversity negatively associated with quality of secondary education, bu

t this is the only negative effect we discover

STOCHASTIC FRONTIER FRAMEWORK

Ethnic diversity found positively associated w

ith political stability even after controlling for

potential endogeneity

Stability positively affects productive efficienc

y since it makes more certain investment

outcomes

Aigner et al. (1997) and Battese and Coelli

(1995)

MODELING PRODUCTION EFFICIENCY

Production is prone to inefficiency:

Y is output, X is vector of inputs

V is random deviation from best practice (e.g. bad weather)

U is always positive and measures inefficiency

Inefficiency of each decision-making unit measured as follows:

Penn World Table for data on output, population and investment flows

Perpetual inventory method to compute capital stocks

itit UV

itit eXY

itUe

EMPIRICAL ESTIMATION FRAMEWORK

Translog specification of production function:

Mean of inefficiency term U is a function of several determinants:

Estimation of the production function AND the inefficiency mean function is simultaneous Assumption of independent estimates of U not need

ed

Omitted variable bias avoided (Wang and Schmidt, 2002)

ititititititititit UVYearLKLKLKY 65

2

4

2

3210 lnlnlnlnlnlnln

ititZiiit wZEDED lnlnln2

210

MONOTONICITY OF PRODUCTION FUNCTION

A strong point is made in Henningsen and

Henning (2009):Firm B is on the estimated frontie

r (“efficient”)

Firm A is estimated to be less

efficient than B

However, it produces the same

amount of output as A

This problem will not happen if th

e estimated frontier is regionally

monotonic

PROCEDURE FOR MONOTONIC ESTIMATION

1) Obtain unrestricted parameters of the production function and efficiency mean parameters

2) Adjust unrestricted parameters by solving

where is covariance matrix from unrestricted estimation

3) Solve the stochastic frontier model

TtKiXY itit ..1,..1,0ˆ,

ˆˆˆminargˆ

0

000

0

ˆ

02

210

0

0

10

lnlnln

ˆ,ˆlnln

ititZii

itit

wZEDEDuE

XYY

ETHNIC DIVERSITY AND PRIMARY EDUCATION

Inefficiency Mean Unrestr. Adjusted Unrestr. Adjusted Unrestr. Adjusted Unrestr. Adjusted

-0.18

(-0.82)

-0.22

(-0.93)

-0.60

(-1.34)

-0.55

(-1.48)

-0.71

(-1.56)

-0.62

(-1.72)

-0.99*

(-2.06)

-0.89*

(-2.01)

-0.56**

(-3.02)

-0.57*

(-2.54)

-0.72**

(-2.80)

-0.67**

(-2.87)

-0.83**

(-2.88)

-0.78**

(-3.19)

-1.29***

(-3.38)

-1.23**

(-3.25)

-0.10

( -1.92)

-0.10

(-1.56)

-0.11*

(-2.21)

-0.10**

(-2.21)

-0.13*

(-2.27)

-0.12*

(-2.44)

-0.30**

(-2.81)

-0.29**

(-2.79)

-0.46*

(-2.31)

-0.46**

(-2.96)

-0.50**

(-2.62)

-0.48**

(-3.22)

-1.05*

(-2.09)

-0.98*

(-2.50)

-0.35

(-1.92)

-0.37*

(-2.36)

1.05

(1.87)

1.02

(1.93)

-0.57

(-1.27)

-0.53

(-1.54)

1.55*

(2.32)

1.52*

(2.38)

Mean efficiency 0.76 0.78 0.78 0.79 0.78 0.79 0.80

Log-likelihood -253.04 -257.57 -245.38 -247.96 -242.99 -234.22 -235.05

0.46**

( 3.04)

0.45***

(3.51)

0.66***

(5.32)

0.60***

(5.83)

0.68***

(5.46)

0.60***

(5.41)

0.71***

(8.41)

0.67***

(7.63)

0.16***

( 5.82)

0.16***

( 6.29)

0.22***

(3.29)

0.20***

(4.67)

0.23***

(3.36)

0.20***

(4.45)

0.25***

(4.15)

0.23***

(4.17)

Monotonicity, % obs 100% 100% 99.9% 100%

Quasi-concavity,

% obs

89.2% 88.8% 88.2% 87.8%

Observations 704 704 704 704 704 704 704 704

0

ln EDIW2

ln EDIW

PRIMQNln

PRIMQLlnEDIWPRIMQN lnln

EDIWPRIMQL lnln

1. The direct effect of ethnic diversity on productive efficiency is

positive: complementarity of skills

2. Quantity of primary education increases production efficiency:

social inclusion

3. Quality of primary education per se is not linked strongly to efficiency,

but its interaction term is, suggesting some room for

political aspirations hypothesis

ETHNIC DIVERSITY AND SECONDARY,

TERTIARY EDUCATIONInefficiency Mean Unrestr. Adjusted Unrestr. Adjusted Unrestr. Adjusted Unrestr. Adjusted

-0.49

(-1.60)

-0.42

(-1.60)

NA NA NA NA -0.36

(-1.52)

-0.27

(-1.41)

-0.72***

(-3.53)

-0.67***

(-3.75)

-0.26***

(-4.68)

-0.26***

(-5.15)

-0.18*

(-1.97)

-0.18

(-1.92)

-0.63***

(-4.06)

-0.57***

(-4.40)

-0.11**

(-2.78)

-0.10**

(-3.04)

-0.04***

(-3.72)

-0.04***

(-3.90)

-0.06***

(-3.74)

-0.06***

(-5.54)

-0.10**

(-3.16)

-0.09***

(-3.44)

-0.37***

(-3.46)

-0.35***

(-4.13)

-0.25***

(-5.59)

-0.25***

(-7.40)

-0.14

( -1.72)

-0.12

(-1.79)

0.69***

(6.08)

0.69***

(6.28)

0.26

(1.16)

0.34*

(2.00)

0.206*

(2.40)

0.22**

(2.80)

-0.79*

(-2.52)

-0.66*

(-2.39)

-0.23*

(-2.37)

-0.20*

(-2.41)

0.04

(0.50)

0.05

(0.68)

Mean efficiency 0.76 0.77 0.78 0.78 0.79 0.81 0.75 0.75

Log-likelihood -238.67 -239.46 -218.60 -218.752 -213.00 -216.93 -230.79 -232.68

0.67***

(6.21)

0.61***

(6.65)

0.33*

(2.46)

0.33**

(2.84)

0.37

(1.84)

0.26

(1.89)

0.69***

(6.88)

0.60***

(6.78)

0.21***

(4.38)

0.19***

(5.57)

0.13***

(10.41)

0.13***

(10.98)

0.13***

(6.79)

0.12***

(10.27)

0.20***

(4.71)

0.17***

(6.25)

Monotonicity, % obs 100% 100% 100% 100%

Quasi-concavity,

% obs

88.4% 88.8% 99.9% 86.8%

Observations 704 704 704 704 704 704 704 704

0

ln EDIW2

ln EDIW

SECQNln

SECQLln

EDIWSECQN lnln

EDIWSECQL lnln

TERTQNln

EDIWTERTQN lnln

1. Ethnic diversity positively associated with efficiency: complementarity

of skills

2. Quantity of secondary school education positively associated with

efficiency: social inclusion hypothesis

3. However, interaction SECQNxEDIW suggests political aspirations are at

work: more access to secondary education spurs political unrest

4. Quality of secondary education decreasing efficiency:

political aspirations again

5. Quantity of tertiary education increases efficiency: social inclusion

EFFICIENCY AND DETERMINANTS OF STABILITY

Inefficiency Mean (1) (2) (3) (4) (5) (6) (7)

-9.29*

(-1.97)

NA NA NA -1.57*

(-2.27)

NA -0.81*

(-2.25)

-18.9*

(-1.99)

-0.35***

(-6.32)

-0.34*** (-6.

06)

-0.32***

(-5.50)

-2.40**

(-2.7)

-0.34***

(-6.47)

-1.21**

(-2.73)

-9.9*

(-1.97)

-0.08***

(-6.02)

-0.07*** (-5.

92)

-0.07***

(-5.62)

-0.77*

(-2.4)

-0.06***

(-4.75)

-0.36*

(-2.22)

-0.30** (3.17)

-0.69***

(-6.40)

-0.67*** (-6.

09)

-0.64***

(-5.78)

-1.24***

(-3.74)

-0.66***

(-6.45)

-1.19*** (-4.

69)

-0.82***

(-3.96)

-0.71*** (-3.

41)

-0.73***

(-3.74)

0.51 (0.99) -0.33

(-1.07)

-1.20**

(-2.92)

0.60*** (2.98

)

0.61** (6.10

)

0.50* (2.35) 2.13***

(3.03)

0.65**

(3.28)

1.55** (3.17

)

-0.11*

(-2.43)

-0.13**

(-2.63)

-0.11

(-1.26)

-0.74*** (-3.

43)

-0.32***

(-3.87)

0.04

(0.44)

-0.36***

(-4.66)

Mean efficiency 0.89 0.75 0.76 0.76 0.84 0.76 0.83

Log-likelihood 39.55 29.60 31.70 32.58 49.43 37.09 64.17

0.84*** (11.69) 0.87*** (19.7

2)

0.87*** (19.

78)

0.86*** (18.9

7)

0.84***

(18.17)

0.85*** (15.3

3)

0.80***

(16.14)

Monotonicity, % obs 99.8% 100% 99.8% 99.8% 99.8% 99.8% 99.8%

Quasi-concavity,

% obs

94.8% 94.8% 94.8% 94.8% 94.8% 94.8% 94.8%

Observations 406 406 406 406 406 406 406

0

ln EDIW2

ln EDIW

STABLEln

LAWln

PROPln

INCLln

SECQNln

SECQLln

PRIMQNln

PRIMQLln

TERTQNln

1. The direct effect of ethnic diversity on efficiency is conspicuous

2. Political stability expectedly associated with more efficient production

3. Law enforcement and property rights protection are predominantly sig

nificant with expected signs

4. Social inclusion comes out negatively associated with efficiency: one e

xplanation is social inclusion policies are diverting resources from produ

ctive activities

5. Educational quantity positively affects efficiency, while effects of

quality are insignificant

CONCLUSIONS

Ethnic diversity affects productive performance in both direct and indirect ways

The indirect effects of ethnic diversity originate in its association with determinants of political stability and human capital formation

3 hypothesis on indirect effects

Social inclusion

Political aspirations

Vested interests

CONCLUSIONS

Robust positive direct association between ethni

c diversity and productive efficiency: complemen

tarity of skills

Robust positive association between ethnic dive

rsity and political stability

Social inclusion and vested interests corroborated

Political aspirations: some evidence, but mostly refut

ed

Quantity of education associated with increased

efficiency, but not quality

PUZZLES

Quality of social inclusion policies associated with increased stability, but less productive efficiency Political aspirations hypothesis inapplicable for expla

nation purposes

Provision of social inclusion policies crowds out productive resources (affirmative action, political correctness etc)

Direct effect of GDP per capita on stability is negative Creative destruction (Aghion and Howitt, 1992)

Modernization hypothesis (Fedderke and Luiz, 2008)

FUTURE RESEARCH

Organizing business along ethnic lines Complementarity of skills would be more pronounced in truly

mixed businesses

Agricultural sector provides a natural experiment environment to test whether direct effects of ethnic diversity on productivity are smaller there

Clustering and enclaves The stimulating effect of an ethnically diverse environment ma

y not be realized in case ethnicities form enclaves isolated from each other

Spatial econometrics approach is necessary to see whether clustering actually neutralizes the positive effects of diversity Moran’s I as a measure of clustering

Spatial regressions instead of conventional 2SLS or stochastic frontiers