divide and rule or the rule of the divided?elias/nber_idm.pdf · fayoum quena northern alexandria...

IntroductionData

Empirical AnalysisConclusionAppendix

Divide and Rule or the Rule of the Divided?

Stelios Michalopoulos and Elias Papaioannou

Tufts University and Dartmouth College and CEPR

July 2010

NBER SI - Income Distribution and Macroeconomics

Stelios Michalopoulos and Elias Papaioannou Divide and Rule or the Rule of the Divided?

IntroductionData


African History through MapsResearch QuestionLiteratureIdenti�cation

Ethnic Homelands before Colonization - Murdock 1959


IntroductionData



Pre-Colonial Institutions across Ethnicities


IntroductionData



Berlin Conference Partitioned Africa Among ColonizersStelios Michalopoulos and Elias Papaioannou Divide and Rule or the Rule of the Divided?

IntroductionData



The Design of African Borders

Berlin Conference 1884/1885 and subsequent treaties among Europeans in1890s

Colonizers had not even explored most of Africa when borders were agreed.

No ethnicity-speci�c measure predicts which ethnicities were partitioned (see

appendix)

Drawing involved protectorates, large (free-trade) areas, and spheres ofin�uence rather than potential states.


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Upon African independence these

borders were respected creating

the boundaries of African states


IntroductionData



Ü

Rule of Law Across African Countries 19962004

Rule of Law 199620041.912 1.459

1.459 0.877

0.877 0.294

0.294 0.287

0.287 0.708

Current National Institutions

across African Countries


IntroductionData



Questions

What are the Determinants of Regional Developmentwithin Africa?

1 Do contemporaneous nationwide institutions a¤ect regionaleconomic performance across African states?

2 Do pre-colonial local institutional arrangements a¤ectcontemporary regional economic performance within Africa?


IntroductionData



Related Literature

1 Importance of National Contemporary Institutions(Acemoglu et al. 2001, 2002; La Porta et al. 1998, 1999)

Colonization (type or/and identity)Persistence

2 Fundamental Role of Local Precolonial Institutions(Herbst (2000); Gennaioli and Rainer (2006, 2007))

Limited penetration of nationwide institutions (poor infrastructure)Colonization limited (in duration and regions)

Long-run persistence of historical features and inequality(e.g. Guiso et al. 2008; Huillery, 2009; Banerjee and Iyer, 2005; Iyer, 2010; Dell,

2010; Acemoglu et al. 2008)


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Other Explanations

Border Design - State Arti�ciality (Englebert, Tarrango, and Carter (2002);Alesina, Easterly, and Matuszeski (2010))

Slavery (Nunn, 2008)

Geography-Health (Je¤ Sachs)

Ethnic Fragmentation/Polarization (e.g. Easterly and Levine 1997, Alesina etal. 2003)

Human Capital (e.g. Glaeser et al. 2004)


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National Institutions and Development

1. Partitioning => identical cultures subjected to di¤erent countrywidearrangements

Documenting Partitioned Ethnicities (see appendix for a complete list):

2 countries: Anyi (Ghana (58%) and the Ivory Coast (42%);

3 countries: Chewa (Mozambique (50%), Malawi (34%), and Zimbabwe (16%))

Use partitioned ethnic groups to exploit within-ethnicityacross-country variation in institutional performance


IntroductionData



Ethnic Institutions and Development

2. Exploit within-country across-ethnicity variation in tribalpre-colonial institutional traits

Account for post-independence national characteristics and countrylevel unobservables

E¤ectively control for local geography


IntroductionData


How to Proxy for Regional African Development?Regional Data (Country-Ethnicity)Country Characteristics

Satelite Light Density Data: Merits

signi�cant problems on cross-country African GDP data(measurement; unvailability; shadow economy)

paucity of high resolution regional data on development

Satellite Light Density: available at a very �ne grid (around 0.8 kmx 0.8 km)

strong correlation with income and consumption both across andwithin countries (Henderson, Storeygard, and Weil, 2009)

light density => proxy for public goods provision


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Light Density and Income across Africa

MoroccoLibya

Angola

Botswana

Benin

Burundi

Chad

Congo (Democratic Republic of the)

Cameroon

ComorosCentral Af rican Republic

Djibouti

Egypt

Equatorial Guinea

Ethiopia

The Gambia

Gabon

GhanaCote D'Ivoire

KenyaLiberia

Lesotho

Madagascar Malawi

Mali

Mozambique

Niger

Nigeria

GuineaBissauRwanda

South Africa

Sierra Leone

SomaliaSudan

Togo

Tunisia

Tanzania

UgandaBurkina Faso

Swaziland

Zambia

Algeria

Republic of Congo

Guinea

Senegal

Mauritania

Zimbabwe

Namibia

56

78

9Lo

g (G

DP

per

Cap

ita in

200

0)

6 4 2 0 2Log (1 + Average Light Density in 20072008)

Unconditional RelationshipLight Density and Income Per Capita Across African Countries

Unconditional Correlation

Morocco

Libya

Angola

Botswana

Benin

Burundi

Chad

Congo (Democratic Republic of the)

Cameroon

Comoros

Central African Republic

Djibouti

Egypt

Equatorial Guinea

Ethiopia

The Gambia

Gabon

GhanaCote D'Ivoire

Kenya

Liberia

Lesotho

MadagascarMalawi

Mali

Mozambique

Niger

Nigeria

GuineaBissau

Rwanda

South Africa

Sierra Leone

SomaliaSudan

Togo

Tunisia

Tanzania

UgandaBurkina Faso

Swaziland

Zambia

Algeria

Republic of Congo

Guinea

Senegal

Mauritania

Zimbabwe

Namibia

21

01

2Lo

g (G

DP

per

Cap

ita in

200

0)2 1 0 1 2 3

Log (1 + Average Light Density in 20072008)

Conditional on Population Density

Light Density and Income Per Capita Across African Countries

Conditioning on Pop. Dens.


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Light Density and Infant Mortality Across African Regions

Central

Congo, Dem. Rep. Of

Região Capital

Região OesteRegião Centro SulRegião EsteNorthWestern

NortheastNorthwest

Região SulWestern

Região Norte

Congo

Cyangugu

Butare

Burundi

Kibungo

Kigali Rurale

Lake

Mono

Atlantique

Zou

Marities

Borgou

Central Tillaberi (inc. Niamey)

South West

AtacoraSavanes Dosso

Oueme

North West

CentralePlateauxKaraEast Mopti

Upper EastGao/Kidal/Tombouctou

Upper West Segou

North

Sikasso

Northern

Côte d'Ivoire

Central/South & OuagadougouWest

South EastSouthNorth EastNorthern Cape

Southern

KgalagadiNorth West

Ghanzi

Matabeleland North

Central Kweneng

Matabeleland South

Northern Province

KgatlengNorth WestSouthern

RS V

RS II

RS IS.Darfur

RS IV

Central, South, & East

Chad

RS III

North/ Extreme north/Adamaoua

Bangui

W. Darfur

Western

BrongAhafo

LiberiaUpper Guinea

Forest Guinea

Northwest & southwest

South East

North East

West & littoral

Equatorial Guinea

Nord

Luapula

Copperbelt

Central

Sud

Est

Anjouan

Grande Comore

Moheli

Cape Verde

North/West

Debubawi Keih Bahri

Djibouti

Affar

Tunisia

CentreEst

Sud

Zone Nord (G3)

Libya

OuestOriental

Tahoua/Agadez

SudCentreSud

Ismailia

Red Sea

New Valley

Assyout

PortSaid

North Sina

Giza

Red Sea

Kafr ElShKalyoubia

DamiettaDakahlia

QuenaFayoumNorthern

Alexandria

Aswan

Menoufia

Cairo

BeniSuet

South Sina

Nile River

MeniaGharbia

Suez

SharkiaSuhagBehera

Matrouh

Anseba

Maekel

Gadaref

Kassala

TigrayDebub

GashBarkaSemenawi Keih Bahri

Spain

NordOuest

Addis

Rift Valley

North EasternSomali

Oromiya

Harari

Gambela

Dire Dawa

Amhara

BenGumz

SNNPNorth/East

Blue Nile

Central/South

Eastern

Sinnar

Ouest (inc. Libreville)

CentralAshanti

Greater Accra

EasternVolta

GuineaBissau

Lower Guinea

Central Guinea

Koulikoro (inc. Bamako)

Sierra Leone

Conakry

Sud

NordEstKayes

MacCarthy Island

Brikama

Kerewan

Banjul

Mansakonko

Centre

Basse

Coastal

Nyanza

Nairobi

Northern

Northern Highlands

Central Coast

WesternEastern

N.Darfur

Eastern CapeKwaZulu Natal

Lesotho

Free State

CentreTensiftCentreNord

Antananarivo

Mahajanga

Antsiranana

Toliary

Fianarantsoa

ToamasinaZone Sud (G1)

Zone Centre (G4)

Zone Fleuve (G2)

Sofala

Cabo DelgadoZambezia

Mashonaland Central

Manicaland

SouthInhambane

Masvingo

Southern

Eastern

Central

Niassa

Mashonaland East

Swaziland

Gaza

Mpumalanga

Lusaka

TeteNampula

Maputo Cidade

Manica

Maputo province

North

NouakchottMauritius

Northern

Southern Highlands MaradiZinda/Diffa

Western

Umutara

Gitarama

Kibuye

Kigali Ville (PVK)

Gisenyi

Ruhengeri

Byumba

W. Kordofan

N.Kordofan

White Nile

KhartoumGazira

S.Kordofan

OuestSao Tome and Principe

Seychelles

Central

Central

Western Cape

Gauteng

Mashonaland West

Midlands

Harare

Bulawayo

64

20

24

Log

Ligh

t Den

sity

With

in a

n Af

rican

Reg

ion

100 50 0 50 100Infant Mortality per African Region

Conditional on Population Density

Infant Mortality and Light Density Across African Regions

Conditioning on Pop. Dens.


IntroductionData



Data on Geography

Distance of the centroid of each ethnic group (in each country forpartitioned ethnicities) to the capital city.

Distance of the centroid of each ethnic group to the sea coast

Land area of each ethnic region in each country

Land area under water (rivers, lakes, other streams)

Elevation (Ruggedness)

Land suitability for agriculture

Population density in 2000

Malaria Stability Index


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Other Controls

Natural resources

Diamond mine indicator

Petroleum/oil �eld indicator

Early development indicators

Major city in 1400

Also experiment with historical population density and the size ofprecolonial settlements

Border Indicator


IntroductionData



Measures of National Institutional Development

World Bank�s Governance Indicators

Rule of Law Composite Index

Control of Corruption Composite Index

Caveats

experiment with alternative measures (ICRG risk of expropriation; Polity�s

executive constraints index; legal formalism, etc.)

results similar; unbundling institutions outside the scope of the current analysis


IntroductionData


Contemporaneous Institutions and Regional DevelopmentPrecolonial Institutions and Regional Development

Current National Institutions and Regional Development

Do contemporaneous nationwide institutions a¤ect regionaleconomic performance across African states?


IntroductionData



Empirical Speci�cation

yi ;c = a0 + IQLc + X 0i ;c�+ �PDi ;c + f (GEOi ;c ) + [aj + ai ] + "i ;c (1)

yi ;c : log light density at night of ethnic group i in country c .

PDi ;c : log population density of ethnic group i in country c .

IQLc : institutional quality of country c .

f (GEOi ;c ) : (regression discontinuity type) cubic polynomial indistance to the capital city and distance to sea coast (Dell, 2009).Xi ;c : vector of control variables.

aj : ethnic family �xed-e¤ects (Murdock (1959); 96 ethnic clusters)


IntroductionData



Technical Remarks

Estimation:

Signi�cant fraction (around 30%) of the observations on regionaldevelopment takes on the value of zero.

Besides OLS we report Tobit estimates.

Inference:

"Standard" heteroskedasticity-adjusted standard errors unreliable.

Report double clustered s.e. with clustering at the country-level andat the ethnic family level (Cameron, Gelbach, and Miller (2006))

1 Account for repeated observations (Moulton, 1986); also correlation ofprecolonial institutions among ethnic families.

2 Account for spatial correlation.

Conley�s (1999) method yields similar (and if anything smaller) s.e.


IntroductionData



Cross-Ethnic Group Analysis

(1) (2) (3) (4)

Rule of Law 0.1169** 0.1321*** 0.0651*** 0.0596**(0.0465) (0.0500) (0.0214) (0.0270)

adjusted R 2 0.153 0.241 0.521 0.528

Log Population Density Yes Yes Yes YesRD Geographic Polynomial No Yes Yes YesEthnic Family Fixed-E¤ects No No Yes YesGeographic Controls No No No YesObservations 1190 1190 1190 1190


IntroductionData



Cross-Ethnic Group Analysis

Positive correlation between rule of law and regional development.

Correlation weakens when we control for culture and geography(mimics evidence of cross-country works)

Cleaner identi�cation:

Focus on areas of the same ethnic group subject to di¤erentnational institutions


IntroductionData



Example of a Partitioned Group - Ababda


IntroductionData



Example of a Partitioned Group - Ewe


IntroductionData



Within-Ethnic Group Analysis

(1) (2) (3) (4) (5) (6)

Rule of Law 0.1129**(0.0503)

Control of Corruption 0.1239**(0.0629)

adjusted R 2 0.212 0.207within ethnicity R 2 __ __

Log Population Dens. Yes YesRD Geo Polynomial Yes YesEthnicity FE No NoGeographic Controls No NoObservations 496 496


IntroductionData



Within-Ethnic Group Analysis

(1) (2) (3) (4) (5) (6)

Rule of Law 0.1129** 0.0263 0.0259(0.0503) (0.0481) (0.0511)

Control of Corruption 0.1239** 0.0453 0.0432(0.0629) (0.0660) (0.0745)

adjusted R 2 0.212 0.207 0.723 0.724 0.727 0.728within ethnicity R 2 __ __ 0.058 0.059 0.062 0.063

Log Population Dens. Yes Yes Yes Yes Yes YesRD Geo Polynomial Yes Yes Yes Yes Yes YesEthnicity FE No No Yes Yes Yes YesGeographic Controls No No No No Yes YesObservations 496 496 496 496 496 496


IntroductionData



BARABRA

BIDEYATNUSANNUKWEMBUKUSHU NSENGATAJAKANT

TAJAKANT

AZJER

NUKWE NUKWEBARGU

BABUKURSANGASANGADARI

KUNDA

NAMA

NUSANNUSAN

GADAMES

MBUNDA PANDESURI NDOGOKUNGDIDINGA KOBA

KWANGARENDEMBU

MBUKUSHU NUKWEDZEMBARGU

BARGUHOLONYANGIYATAJAKANT

TAJAKANTZAGHAWA AULLIMINDENDAZA KOTAMASHI BIDEYATDZEM

IMRAGEN

TLOKWAKARERUNGANGAMAGULALUVALE

HIECHWARE

FANGBONDJOUDALAN LUVALEIMRAGEN

GADAMES

GADAMES

KARA

KANEMBU

AZANDEAZANDE

SEKE DIALONKE

KOMONONDEMBU

NDEMBUCHOKWERESHIAT ANUAK

TONGA

BAJUN

GIL

TAMA

DUMA

FOUTADJALONLAKA (ADAMAWA

ABABDA

HLENGWEFOUTADJALON

AMBOYOMBE

YAO

YAO BARARETTAAZANDE TAWARASANGA

SUBIA

TUMBUKA

DIALONKE

AFAR

AFARHLENGWE

DIALONKEKANEMBU TABWAYAKOMA RESHIATRESHIAT BARARETTABARARETTA BANZIRIGURMAJIEMUNDUKUNDA NAFANAUDALANUDALAN

SUBIA

SUBIA

SUBIA TIENGAMASINAMASINABERTA

JERID

BAYAKOMANGUMBA

KONGOLAMBYA

LAMBYA

MANGA

RUANDA

NZANKARAMASALIT

GURMASONINKESONINKENDUKABIRIFONLIGBI, DEGHA (SE)BARGUHLENGWE BORANYAKA

MAMBILA

DIDINGADIDINGA NYASANYASA

DIOLA

MALINKEMALINKEMBERE

MBEREAFAR

MALINKEMALINKEFANG

SUBIA

SUBIA ESATOMA AUSHIBOKI

KARAMOJONG ISHAAKMASAI

GURMA AMERKONYANKEYALUNKAKORANKOSONGHAINALU EGBA

THONGA

SAHO

PUKU

ESA

MALINKEMALINKEMALINKE

NSENGA

KOTOKO

TEKEIWA

VAIEKOIYOMBE

YOMBEBONI TENDA

TEMTUKULOR

BUSA

CHEWA

CHEWA ANAGURMA SHUWANGERE

NGERE

NAUDEBASHUWA

DIGO

KGATLA

KAONDE

SHEBELLECHAKOSSI

MINIANKAMINIANKA

LOBIGRUNSHIMUSGU FUNGONSONGHAISUNDI WUM GREBOTIGON

FOUTADJALON

TIGRINYA

NGWAKETSE

RONGA SONINKEMOMBERALUNGU

LAMBA

BIRIFON

BWAKA LAKA (ADAMAWALAKA (ADAMAWABOBO

NYANJA

NSUNGLISAMO

ZEKARAKUNDA

BULOMKONKOMBAATYUTI

FANG

MADILUGBARA

LUGBARABIRIFON

ANYI

ADELE MPEZENIMANDARA

TIENGATIENGA DENDI MINIANKA

NDAU

KONGO

BATANGERE

LAMBYA

MANYIKADAGARITRIBU KISSI KISSIMENDEBRONG

SOTHO

KPELLEKPELLE

NYASA

ZIMBA

MUNDANG

MALINKE BALANTEKRAN

KABRE

RUNDI

GUDE

MAKONDE

BUEM

FON

KONO

ASSINI

GURENSI

ESA

AVATIME

BWAKABWAKA

SHAMBALA

WAKURA

TUBURITIGRINYA

TIGRINYA

CHAGA

MATAKAM KISSISABEINYAKYUSAMENDE

KONJOAMBA

CHEWA

GURENSI

EWE

TEKE

GUSII

GOMANI

HAUSA

ALURLUGBARABASHI

KAPSIKIRUNDIRUNDI

CHIGA CHIGA

BANYUNRUANDA

RUANDA

RUANDARUANDA

BASHIBASHI

WANGA

1.5

0.5

1D

iffer

ence

in L

ight

Den

sity

With

in P

artit

ione

d E

thni

citie

s

2 1 0 1 2

Differences in Rule of Law Within a Country Pair

Unconditional RelationshipEthnicities Partitioned Across Countries: Does Rule of Law Matter?


IntroductionData



BARABRA

BIDEYATNUSANNUKWEMBUKUSHU NSENGATAJAKANT

TAJAKANT

AZJER

NUKWE NUKWEBARGU

BABUKURSANGASANGADARI

KUNDA

NAMA

NUSANNUSAN

GADAMES

MBUNDA PANDESURI NDOGOKUNGDIDINGAKOBA

KWANGARENDEMBU

MBUKUSHU NUKWEDZEMBARGU

BARGUHOLONYANGIYATAJAKANT

TAJAKANTZAGHAWA AULLIMINDENDAZA KOTAMASHI BIDEYATDZEM

IMRAGEN

TLOKWAKARERUNGANGAMA GULALUVALE

HIECHWARE

FANGBONDJOUDALANLUVALEIMRAGEN

GADAMES

GADAMES

KARA

KANEMBU

AZANDEAZANDE

SEKE DIALONKE

KOMONONDEMBU

NDEMBUCHOKWERESHIAT ANUAK

TONGA

BAJUN

GIL

TAMA

DUMA

FOUTADJALONLAKA (ADAMAWA

ABABDA

HLENGWEFOUTADJALON

AMBOYOMBE

YAO

YAO BARARETTAAZANDETAWARASANGA

SUBIA

TUMBUKA

DIALONKE

AFAR

AFARHLENGWE

DIALONKEKANEMBU TABWAYAKOMA RESHIATRESHIATBARARETTABARARETTA BANZIRIGURMAJIE MUNDUKUNDANAFANA UDALANUDALAN

SUBIA

SUBIA

SUBIA TIENGAMASINAMASINABERTA

JERID

BAYAKOMANGUMBA

KONGOLAMBYA

LAMBYA

MANGA

RUANDA

NZANKARAMASALIT

GURMA SONINKESONINKE NDUKABIRIFONLIGBI, DEGHA (SE)BARGUHLENGWE BORANYAKA

MAMBILA

DIDINGADIDINGANYASA NYASA

DIOLA

MALINKEMALINKEMBERE

MBERE AFAR

MALINKEMALINKEFANG

SUBIA

SUBIA ESATOMA AUSHIBOKI

KARAMOJONG ISHAAKMASAI

GURMA AMERKONYANKE

YALUNKAKORANKOSONGHAINALU EGBA

THONGA

SAHO

PUKU

ESA

MALINKEMALINKEMALINKE

NSENGA

KOTOKO

TEKEIWA

VAIEKOIYOMBE

YOMBEBONI TENDA

TEMTUKULOR

BUSA

CHEWA

CHEWA ANAGURMA SHUWANGERENGERE

NAUDEBASHUWA

DIGO

KGATLA

KAONDE

SHEBELLECHAKOSSI

MINIANKAMINIANKA

LOBIGRUNSHIMUSGUFUNGONSONGHAISUNDI WUM GREBOTIGON

FOUTADJALON

TIGRINYA

NGWAKETSE

RONGA SONINKEMOMBERALUNGU

LAMBA

BIRIFON

BWAKA LAKA (ADAMAWALAKA (ADAMAWABOBO

NYANJA

NSUNGLISAMO

ZEKARAKUNDA

BULOMKONKOMBAATYUTI

FANG

MADILUGBARA

LUGBARABIRIFON

ANYI

ADELEMPEZENIMANDARA

TIENGATIENGA DENDI MINIANKA

NDAU

KONGO

BATANGERE

LAMBYA

MANYIKADAGARITRIBU KISSI KISSIMENDEBRONG

SOTHO

KPELLEKPELLE

NYASA

ZIMBA

MUNDANG

MALINKEBALANTEKRAN

KABRE

RUNDI

GUDE

MAKONDE

BUEM

FON

KONO

ASSINI

GURENSI

ESA

AVATIME

BWAKABWAKA

SHAMBALA

WAKURA

TUBURITIGRINYA

TIGRINYA

CHAGA

MATAKAMKISSISABEINYAKYUSAMENDE

KONJOAMBA

CHEWA

GURENSI

EWE

TEKE

GUSII

GOMANI

HAUSA

ALURLUGBARABASHI

KAPSIKIRUNDIRUNDI

CHIGA CHIGA

BANYUNRUANDA

RUANDA

RUANDARUANDA

BASHIBASHI

WANGA

1.5

0.5

1D

iffer

ence

in L

ight

Den

sity

With

in P

artit

ione

d E

thni

citie

s

2 1 0 1 2Differences in Corruption Within a Country Pair

Unconditional RelationshipEthnicities Partitioned Across Countries: Does Corruption Matter?


IntroductionData



Sensitivity Analysis

Migration towards the country with the better institutions (noevidence; Table 3).

Heterogeneous E¤ectsE¤ect close and far from the capital city (Herbst, 2000)

Natural - Arti�cial Borders

Other sensitivity checks

Exclude North Africa (focus on Sub-Saharan) areas.

Large di¤erences in institutional quality across the border (e.g.Kenya-Somalia, Congo-Zambia, Botswana-Zimbabwe, Ghana-Ivory Coast)

Within same colonizer

Focus on the intensive/extensive margin of satellite light density


IntroductionData



Heterogeneous E¤ects: Far - Close to the Capital

Distance to the Capital

Close Far Close Far(1) (2) (3) (4)

Rule of Law 0.2110** 0.0221*** -0.0056 0.0072(0.0852) (0.0068) (0.0904) (0.0219)

adjusted R 2 0.509 0.387 0.907 0.825within ethnicity R 2 __ __ 0.030 0.149

Log Population Density Yes Yes Yes YesRD Geographic Polynomial Yes Yes Yes YesEthnicity Fixed-E¤ects No No Yes YesGeographic Controls No No No YesObservations 90 90 90 90


IntroductionData



Heterogeneous E¤ects: Natural - Arti�cial Borders

Border Type

Natural Arti�cial Natural Arti�cial(1) (2) (3) (4)

Rule of Law 0.2029** 0.0493** 0.0510 -0.0410(0.0832) (0.0216) (0.1164) (0.0547)

adjusted R 2 0.455 0.327 0.887 0.730within ethnicity R 2 __ __ 0.0523 0.1854

Log Population Density Yes Yes Yes YesRD Geographic Polynomial Yes Yes Yes YesEthnicity Fixed-E¤ects No No Yes YesGeographic Controls No No No YesObservations 170 122 170 122


IntroductionData



Local Ethnic Institutions and Regional Development


IntroductionData



So what matters for regional development within Africa?


IntroductionData



Local Ethnic Institutions and Development: The Argument

African historians have stressed the importance of ethnic institutions(e.g. Herbst, 2000).

accountability of local chiefs; political centralizationproperty rights protection; communal societies vs. individualistic

Ethnic institutional structures persisted during colonization and postindependence

Cross-country correlation between local political centralization andeconomic development (Gennaioli and Rainer (2006, 2007))


IntroductionData



Ethnic Institutional and Cultural Traits

George Peter Murdock�s (1967) Ethnolinguistic Atlas

information on 534 groups in Africa before colonization

variables on ethnic cultural traits (monogamy, polygyny),institutions (political centralization, slavery), societal structure(class strati�cation), the economy (dependence on agriculture, sizeof settlements), etc.

focus on:

"Jurisdictional Hierarchy above the Local Community Level"

"Class Strati�cation"


IntroductionData



Jurisdictional Hierarchy above the Local Level

Ordered variable, ranging from 0 to 4 indicating the number ofpolitical jurisdictional hierarchies above the local community level(village) for each society.

0 : stateless societies.

1 : petty chiefdoms.

2 : larger-paramount chiefdoms.

3 and 4 : groups part of large states.

Based on the number of jurisdictional hierarchy construct a binary(0, 1) index of political centralization

centralized societies increase the accountability of localadministrators, restraining the arbitrariness of local elites, Bates (1983).


IntroductionData




IntroductionData



Class Strati�cation

Ordered variable, ranging from 0 to 4 indicating the complexity ofthe societal structure.

0 : absence of signi�cant class distinctions

1 : some wealth distinctions

2 : elite strati�cation

3 : dual strati�cation

4 : complex strati�cation

strati�ed societies are more likely to have some form of propertyrights protection (Rudmin (1995))

link between historical inequality and development through propertyrights (Acemoglu et al. 2008; Dell, 2010)


IntroductionData




IntroductionData



Empirical Speci�cation

yi ;c = ac + �LOCINSTi + X 0i ;c�+ �PDi ;c + f (GEOi ;c ) + "i ;c (2)

yi ;c : log light density at night of ethnic group i in country c

PDi ;c : log population density of ethnic group i in country c

f (GEOi ;c ) : (regression discontinuity type) cubic polynomial indistance to the capital city and distance to nearest sea coast

Xi ;c : vector of control variables

LOCINSTi : proxy measure of ethnic institutional/cultural traits

ac : country �xed-e¤ects


IntroductionData



Precolonial Local Institutions and Regional Development

Jurisdictional Hierarchy

(1) (2) (3) (4)

Ethnic Institutions 0.0631** 0.0444*** 0.0375*** 0.0366***(0.0284) (0.0151) (0.0138) (0.0138)

adjusted R 2 0.146 0.536 0.617 0.621within country R 2 __ 0.148 0.212 0.233

Log Population Density Yes Yes Yes YesCountry Fixed-E¤ects No Yes Yes YesRD Geographic Polynomial No No Yes YesGeographic Controls No No Yes YesAdditional Controls No No No YesObservations 655 655 655 655


IntroductionData



Precolonial Local Institutions and Regional Development


(5) (6) (7) (8)

Ethnic Institutions 0.0262* 0.0250** 0.0211*** 0.0209***(0.0136) (0.0101) (0.0081) (0.0075)




IntroductionData



The Rule of the Divided

Jurisdictional Hierarchy

(1) (2) (3) (4)

Ethnic Institutions 0.0800*** 0.0579*** 0.0558*** 0.0544***(0.0303) (0.0187) (0.0162) (0.0154)




IntroductionData



The Rule of the Divided (cont.)


(5) (6) (7) (8)

Ethnic Institutions 0.0284* 0.0239** 0.0164* 0.0174*(0.0157) (0.0118) (0.0091) (0.0089)




IntroductionData


Main Contribution

O¤ers a platform for testing standard cross-country correlates ofdevelopment

Exploit

within-ethnicity across-country variation in nationwide characteristics

within-country across-ethnicity variation in pre-colonial traits


IntroductionData


Results Summary

1 Current National Institutions and Regional Development

1 Positive correlation between institutional quality and regionaldevelopment;

2 BUT no e¤ect of national institutions on development withinethnicities.

2 Ethnic Institutions and Ethnic Traits and Regional Development

1 Signi�cant positive e¤ect of precolonial local institutions and regionaldevelopment.

2 The positive within country e¤ect of precolonial institutions isparticularly strong in ethnic group areas at the border.


IntroductionData


Results Summary

1 Evidence consistent with African scholars�view on the roots ofregional development.

2 Natural level of analysis within Africa is the ethnicity (rather thanthe country).


IntroductionData


Future Research

Other Applications:

Re-examine the e¤ect of slavery on contemporaneous development

Examine whether the fact that Europeans used di¤erent ethnicgroups during the colonial phase has lingering e¤ects on regionaldevelopment

Do partitioned ethnicities fare worse than other groups? PublicGood Provision etc.

Does the ethnic origin of the African ruler matter for regionaldevelopment?


IntroductionData


What Predicts Borders?Sensitivity AnalysisWhy National Institutions May Not Matter?Why Local Tribal Institutions Matter?

Are Borders Random?

(1) (2) (3) (4) (5) (6)

Land Area 0.079*** 0.083*** 0.081** 0.038** 0.039** 0.053*(0.021) (0.021) (0.032) (0.019) (0.018) (0.028)

Warer Area 0.161*** 0.156*** 0.142** 0.131*** 0.133*** 0.098**(0.048) (0.044) (0.055) (0.027) (0.025) (0.043)

Distance to Sea 0.004 0.007 0.003 0.006 0.015 0.032(0.038) (0.034) (0.044) (0.031) (0.028) (0.041)

Elevation 0.048 0.001 0.044 0.051 0.006 0.048(0.101) (0.106) (0.117) (0.083) (0.087) (0.108)

Agriculture Suitability 0.18 0.168 0.033 0.174 0.176 0.018(0.120) (0.119) (0.145) (0.120) (0.110) (0.159)

North Africa 0.014 0.038 0.098 0.162*(0.083) (0.064) (0.069) (0.098)

South Africa 0.150* 0.216* 0.118 0.106(0.087) (0.113) (0.080) (0.112)

West Africa 0.132 0.177 0.046 0.032(0.110) (0.119) (0.091) (0.099)

East Africa 0.018 0.035 0.096* 0.1(0.074) (0.100) (0.052) (0.085)

Hist. Popul. Density 0.008 0.006(0.021) (0.020)

Agriculture Depend 0.061 0.021(0.075) (0.062)

Political Centralization 0.047 0.07(0.063) (0.064)

Slavery 0.023 0.029(0.074) (0.090)

adjusted Rsquared 0.090 0.110 0.140 0.050 0.070 0.080Observations 834 834 330 834 834 330

Border Indicator Split Indicator (10%)


IntroductionData



Migration Within Partitioned Ethnicities

(1) (2) (3) (4) (5) (6)

Rule of Law -0.6487* -0.0249 -0.0122(0.3668) (0.2925) (0.3109)

Control of Corruption -0.8149** -0.0967 -0.1067(0.4019) (0.3427) (0.3731)

adjusted R 2 0.247 0.255 0.827 0.827 0.834 0.834within ethnicity R 2 __ __ 0.018 0.018 0.025 0.025

Log Population Dens Yes Yes Yes Yes Yes YesRD Geo Polynomial Yes Yes Yes Yes Yes YesEthnicity FE No No Yes Yes Yes YesGeographic Controls No No No No Yes YesObservations 496 496 496 496 496 496


IntroductionData



Sharp Discontinuities

cross-sectional within ethnicity(1) (2)

Rule of Law 0.1562** 0.0407(0.0669) (0.0669)

adjusted R 2 0.450 0.891within ethnicity R 2 __ 0.0485

Log Population Density Yes YesRD Geographic Polynomial Yes YesGeographic Controls Yes YesEthnicity Fixed-E¤ects No YesObservations 150 150


IntroductionData



Intensive and Extensive Margin

Intensive Margin Extensive Margincross-sectional within ethnicity cross-sectional within ethnicity

(1) (2) (3) (4)

Rule of Law 0.8422** -0.3889 0.1257*** -0.0293(0.3326) (0.7622) (0.0455) (0.1210)

adjusted R 2 0.443 0.825 0.416 0.733within ethnicity R 2 __ 0.0774 __ 0.0887

Log Population Dens Yes Yes Yes YesRD Geo Polynomial Yes Yes Yes YesGeographic Controls Yes Yes Yes YesEthnicity Fixed-E¤ects No Yes No YesObservations 144 144 292 292


IntroductionData



Why National Institutions May Not Matter?

Once cultural traits are accounted for then national institutions playa lesser role

Measurement error

look close and far from the capital city where enforcement agencies are mainly

located.

National institutions are less relevant for the activities withinpartitioned groups

Subnational variation of nationwide institutions makes the use of anational averages less informative

currently collecting data on local formal institutions

National institutions a¤ect ethnicities di¤erentially

currently looking at the role of patronage politics and foreign aid.


IntroductionData



Why Local Tribal Institutions Matter?

Tribal institutions were enginneered locally so are bound to re�ecte¢ cient ways of solving local problems

Degree of class strati�cation has been shown to correlate with localproperty rights

Centralized societies increase the accountability of localadministrators, restraining the arbitrariness of local elites, Bates(1983).


IntroductionData



Summary Table

obs mean st.dev. p25 p50 p75 min max

Light Densiy20072008

1269 0.13 0.27 0.00 0.02 0.11 0.00 1.73

Control ofCorruption

1264 0.78 0.49 1.05 0.87 0.47 1.59 0.72

Rule of Law 1264 0.85 0.58 1.27 0.89 0.46 1.91 0.71

Split10pcIndicator

1269 0.43 0.49 0.00 0.00 1.00 0.00 1.00

Distance to theCapital City

1269 0.64 0.62 0.27 0.43 0.74 0.01 3.17

PopulationDensity in 2000

1225 2.72 1.80 1.82 3.00 3.95 6.67 6.22

Area 1269 1.84 1.93 0.87 2.07 3.12 6.82 6.20Water Area 1269 0.26 0.42 0.00 0.09 0.32 0.00 3.12

Sea Distance 1269 0.66 0.45 0.27 0.61 0.99 0.01 1.81

Mean Elevation 1269 0.62 0.44 0.30 0.49 0.94 0.00 2.18

Suitability ForAgriculture

1269 0.40 0.24 0.25 0.42 0.57 0.00 0.98

CentralizationIndicator

702 0.35 0.48 0.00 0.00 1.00 0.00 1.00

JurisdictionalHierarchy

702 1.21 0.95 0.00 1.00 2.00 0.00 4.00

ClassStratification

623 1.37 1.41 0.00 1.00 3.00 0.00 4.00

Appendix Table 2a Summary Statistics for the Main Specifications


IntroductionData



Correlation TableLightDensity


RuleofLaw

Distanceto theCapital

PopulationDensity in2000

Area WaterArea

SeaDistance

MeanElevation

SuitabilityForAgriculture



ClassStratification

Light Densiy20072008

1.00


0.27 1.00

Rule of Law 0.24 0.91 1.00

Split10pcIndicator

0.06 0.10 0.09

Distance tothe CapitalCity

0.18 0.29 0.37 1.00

PopulationDensity in2000

0.29 0.07 0.05 0.29 1.00

Area 0.09 0.05 0.04 0.09 0.19 1.00

Water Area 0.08 0.10 0.08 0.02 0.21 0.43 1.00

Sea Distance 0.32 0.29 0.27 0.49 0.28 0.06 0.08 1.00

MeanElevation

0.08 0.06 0.15 0.06 0.05 0.03 0.10 0.26 1.00

Suitability ForAgriculture

0.05 0.12 0.01 0.07 0.34 0.28 0.39 0.08 0.25 1.00


0.21 0.18 0.19 0.06 0.07 0.11 0.13 0.00 0.12 0.12 1.00


0.23 0.16 0.15 0.07 0.08 0.10 0.13 0.04 0.13 0.10 0.86 1.00

ClassStratification

0.14 0.11 0.10 0.04 0.05 0.09 0.16 0.00 0.10 0.10 0.59 0.63 1.00Stelios Michalopoulos and Elias Papaioannou Divide and Rule or the Rule of the Divided?

divide and rule or the rule of the divided?elias/nber_idm.pdf · fayoum quena northern alexandria...

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