14.772 Development Economics: Macroeconomics · Table 1: Africa and the Rest of the World. Mean std. dev. Min Max N. Real per capita GDP in 2000. Rest of World 8,809 7,591 521 37,471

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14.772 Development Economics: Macroeconomics Spring 2009

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The Long-Term Effects of Africa’s Slave Trades

Nathan Nunn

Table 1: Africa and the Rest of the World.

Mean std. dev. Min Max N

Real per capita GDP in 2000

Rest of World 8,809 7,591 521 37,471 124

Africa 1,833 2,002 218 10,652 52

Growth in real per capita GDP, 1960–2000

Rest of World 2.00 1.71 −3.54 6.41 94

Africa 0.70 1.65 −3.11 5.94 52

Historic Causes of Africa’s Underdevelopment?

• Colonialism

There is no doubt that a large number of negative

structural features of the process of economic

underdevelopment have historical roots going back to

European colonization. – Paul Bairoch (1993).

• The slave trade

Slavery was corruption: it involved theft, bribery, and

exercise of brute forces as well as ruses. Slavery thus

may be seen as one source of precolonial origins for

modern corruption. – Patrick Manning (1990)

Empirical Questions

• Can Africa’s poor performance be partially explained by the

slave trade?

• If so, what are the channels?

Summary of Paper

• History of Africa’s slave trades.

• Construct country-level slave export figures.

• Estimate the relationship between slave exports and economic

development across countries within Africa.

• Deal with the econometric problems: causality and

measurement error.

• Examine the potential channels of causality.

Africa’s slave trades Figure by MIT OpenCourseWare.

Magnitude of the Slave Trades

Slave Trade 1400–1599 1600–1699 1700–1799 1800–1900 1400–1900

trans-Atlantic 230,516 861,936 5,687,051 3,528,694 10,308,197

trans-Saharan 675,000 450,000 900,000 1,099,400 3,124,400

Red Sea 400,000 200,000 200,000 505,400 1,305,400

Indian Ocean 200,000 100,000 260,000 379,500 939,500

Total 1,505,516 1,611,936 7,047,051 5,512,994 15,677,497

Channels of causality

• Ethnic fractionalization

– Ties between village federations deteriorate

– Villages raid one another

• Political fractionalization and weakening of states

– Intra-community slave raiding and kidnapping

– Kingdoms experience civil wars

• Break-down of traditional judicial systems

– Judicial system comes to be used as tool for enslavement

Data Sources: Shipping Records

• Atlantic slave trade.

– Know port of embarkation.

• Indian Ocean slave trade.

– Know region of embarkation.

• Saharan slave trade.

– Know slaves’ destinations.

– Know which caravan slaves arrived on.

• Red Sea slave trade.

– Know port of embarkation.

Data Sources: Ethnicity Data

• Atlantic slave trade.

– 53 samples, 80,656 slaves, 229 ethnicities

• Indian Ocean slave trade.


• Saharan slave trade.


• Red Sea slave trade.

– 2 samples, 67 slaves, 32 ethnicities

Table 2: Slave Ethnicity Data: Trans-Atlantic Slave Trade, 1450–1799

Num. Num. Region Years Ethnic. Obs. Record Type

Valencia, Spain 1482–1516 77 2,675 Crown Records Puebla, Mexico 1540-1556 14 115 Notarial Records Dominican Republic 1547–1591 26 22 Records of Sale Peru 1548–1560 16 202 Records of Sale Mexico 1549 12 80 Plantation Accounts Peru 1560–1650 30 6,754 Notarial Records Lima, Peru 1583–1589 15 288 Baptism Records Colombia 1589–1607 9 19 Various Records Mexico 1600–1699 28 102 Records of Sale Dominican Republic 1610–1696 33 55 Government Records Chile 1615 6 141 Sales Records Lima, Peru 1630–1702 33 411 Parish Records Peru (Rural) 1632 25 307 Parish Records Lima, Peru 1640–1680 33 936 Marriage Records Colombia 1635–1695 6 17 Slave Inventories Guyane (French Guiana) 1690 12 69 Plantation Records Colombia 1716–1725 33 59 Government Records French Louisiana 1717–1769 23 223 Notarial Records Dominican Republic 1717–1827 11 15 Government Records South Carolina 1732–1775 35 681 Runaway Notices Colombia 1738–1778 11 100 Various Records Spanish Louisiana 1770–1803 79 6,615 Notarial Records St. Dominique (Haiti) 1771–1791 25 5,413 Sugar Plantations Bahia, Brazil 1775–1815 14 581 Slave Lists St. Dominique (Haiti) 1778–1791 36 1,280 Coffee Plantations Guadeloupe 1788 8 45 Newspaper Reports St. Dominique (Haiti) 1788–1790 21 1,297 Fugitive Slave Lists Cuba 1791–1840 59 3,093 Slave Registers St. Dominique (Haiti) 1796–1797 56 5,632 Plantation Inventories

Table 3: Slave Ethnicity Data: Trans-Atlantic Slave Trade, 1800–1900

Num. Num. Region Years Ethnic. Obs. Record Type

American Louisiana 1804–1820 62 223 Notarial Records Salvador, Brazil 1808–1842 6 456 Records of Manumission Trinidad 1813 100 12,460 Slave Registers St. Lucia 1815 62 2,333 Slave Registers Bahia, Brazil 1816–1850 27 2,666 Slave Lists St. Kitts 1817 48 2,887 Slave Registers Senegal 1818 17 80 Captured Slave Ship Berbice (Guyana) 1819 66 1,127 Slave Registers Salvador, Brazil 1819–1836 12 871 Manumission Certificates Salvador, Brazil 1820–1835 11 1,106 Probate Records Sierra Leone 1821–1824 68 605 Child Registers Rio de Janeiro, Brazil 1826–1837 31 772 Prison Records Anguilla 1827 7 51 Slave Registers Rio de Janeiro, Brazil 1830–1852 190 2,921 Free Africans’ Records Rio de Janeiro, Brazil 1833–1849 35 476 Death Certificates Salvador, Brazil 1835 13 275 Court Records Salvador, Brazil 1838–1848 7 202 Slave Registers St. Louis/Goree, Senegal 1843–1848 21 189 Emancipated Slaves Bakel, Senegal 1846 16 73 Sales Records d’Agoue, Benin 1846–1885 11 70 Church Records Sierra Leone 1848 132 12,425 Linguistic and British Census Salvador, Brazil 1851–1884 8 363 Records of Manumission Salvador, Brazil 1852–1888 7 269 Slave Registers Cape Verde 1856 32 314 Slave Census Kikoneh Island, Sierra Leone 1896–1897 11 185 Fugitive Slave Records Total 80,656

Constructing Estimates

↑ AFRICA

Country A Country B

Country C

Country D

Country E

NAtlantic

Ocean 100, 000 ⇐

250, 000 ⇐

From the ethnicity data, I calculate:

A : B = 4 : 1

C : D : E = 3 : 1 : 1

Calculations

Atlantic

Ocean

100, 000 ⇐ 250, 000 ⇐

AFRICA

80,000 20,000

150,000

50,000

50,000

↑

N

A= 100, 000 × 4/5 = 80, 000

B= 100, 000 × 1/5 = 20, 000

C= 250, 000 × 3/5 = 150, 000

D= 250, 000 × 1/5 = 50, 000

E= 250, 000 × 1/5 = 50, 000

Complications

• Movement between coastal countries or ‘diagonal’ movements

from inland to coastal countries.

– Estimated upper-bound is 15%.

• Under-sampling of interior slaves.

– Direction of bias is known.

– Can use IV.

• Countries are not laid out on a grid.

Total Slave Exports from 1400 to 1900 by Country.

Trans- Indian Trans- Red All

Atlantic Ocean Saharan Sea Slave Share

Country Trade Trade Trade Trade Trades of Total

Angola 3,616,027 0 0 0 3,616,027 23.1%

Nigeria 1,411,758 0 555,796 59,337 2,026,891 12.9%

Ghana 1,603,335 0 0 0 1,603,335 10.2%

Ethiopia 0 0 813,899 633,357 1,447,256 9.2%

Mali 524,102 0 509,950 1,034,052 6.6%

Sudan 615 0 408,260 454,913 863,788 5.5%

Dem. Rep. of Congo 752,828 0 0 0 752,828 4.8%

Mozambique 382,337 274,024 0 0 656,402 4.2%

Chad 823 0 409,367 118,673 528,863 3.4%

Tanzania 10,834 507,595 0 0 518,429 3.3%

Benin 461,782 0 0 0 461,782 2.9%

Senegal 222,359 0 98,732 0 321,091 2.0%

Togo 280,842 0 0 0 280,842 1.8%

Guinea 242,691 0 0 0 242,691 1.5%

Baseline Estimating Equation

ln yi = β0 + β1 ln(exportsi/areai) + C ′ δ + Xi′ γ + εii

• ln yi is the natural log of real per capita GDP in country i in

2000

• ln(exportsi/areai) is the natural log of the total number of

slaves exported between 1400 and 1900 normalized by land

area.

• Ci is a vector of dummy variables that indicate the origin of

the colonizer prior to independence.

• Xi is a vector of control variables that are meant to capture

differences in countries’ geography and climate.

Angola

Burundi

Benin

Burkina Faso

Botswana

Central African Republic

Ivory Coast

Cameroon

Congo

Comoros

Cape Verde Islands

Djibouti

AlgeriaEgypt

Ethiopia

Gabon

Ghana

Guinea

Gambia

Guinea−Bissau

Equatorial Guinea

Kenya

Liberia

Libya

Lesotho

Morocco

Madagascar

Mali

Mozambique

Mauritania

Mauritius

Malawi

Namibia

Niger

Nigeria

Rwanda

Sudan

Senegal

Sierra Leone

Somalia

Sao Tome & Principe

Swaziland

Seychelles

Chad

Togo

Tunisia

Tanzania

Uganda

South Africa

Democratic Republic of Congo

Zambia

Zimbabwe

5

7.5

1

0

Av

erag

e in

com

e p

er p

erso

n i

n 2

00

0

−4 0 5 11 Slave exports normalized by land area

Relationship Between Current Income and Past Slave Exports

Angola

Burundi

Benin

Burkina Faso

Botswana


Ivory Coast

Cameroon

Congo

Comoros

Cape Verde Islands

Djibouti

AlgeriaEgypt

Ethiopia

Gabon

Ghana

Guinea

Gambia

Guinea−Bissau

Equatorial Guinea

Kenya

Liberia

Libya

Lesotho

Morocco

Madagascar

Mali

Mozambique

Mauritania

Mauritius

Malawi

Namibia

Niger

Nigeria

Rwanda

Sudan

Senegal

Sierra Leone

Somalia

Sao Tome & Principe

Swaziland

Seychelles

Chad

Togo

Tunisia

Tanzania

Uganda

South Africa


Zambia

Zimbabwe

5

7.5

1

0

ln 2

00

0 r

eal

per

cap

ita

GD

P

2 9 16 Log Total Slave Exports Normalized by average Population from 1400−−1900

Dependent variable is log real per capita GDP in 2000, ln y

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

ln(exports/area) −.112∗∗∗

−.076∗∗∗

−.108∗∗∗

−.085∗∗

−.103∗∗∗

−.128∗∗∗

(.024) (.029) (.037) (.035) (.034) (.034)

Distance from equator .016 −.005 .019 .023 .006

(.017) (.020) (.018) (.017) (.017)

Longitude .001 −.007 −.004 −.004 −.009

(.005) (.006) (.006) (.005) (.006)

Lowest monthly rainfall −.001 .008 .0001 −.001 −.002

(.007) (.008) (.007) (.006) (.008)

Avg max humidity .009 .008 .009 .015 .013

(.012) (.012) (.012) (.011) (.010)

Avg min temperature −.019 −.039 −.005 −.015 −.037

(.028) (.028) (.027) (.026) (.025)

ln(coastline/area) .085∗∗ .092∗∗ .095∗∗ .082∗∗ .083∗∗

(.039) (.042) (.042) (.040) (.037)

Island indicator −.398 −.150

(.529) (.516)

Percent Islamic −.008∗∗∗

−.006∗

−.003

(.003) (.003) (.003)

French legal origin .755 .643 −.141

(.503) (.470) (.734)

North Africa indicator .382 −.304

(.484) (.517)

ln(gold prod/pop) .011 .014

(.017) (.015)

ln(oil prod/pop) .078∗∗∗ .088∗∗∗

(.027) (.025)

ln(diamond prod/pop) −.039 −.048

(.043) (.041)

Colonizer fixed effects Yes Yes Yes Yes Yes Yes

Number obs. 52 52 42 52 52 42

R2 .51 .60 .63 .71 .77 .80

Sao Tome & PrincipeCape Verde Islands

Djibouti

Rwanda

Central African Republic Morocco

Liberia

Zimbabwe

Tunisia

Niger

Gabon

Uganda

Botswana

Congo

Mauritius

Lesotho

Egypt

Swaziland

Cameroon

Zambia

Comoros

Somalia

Burundi

Sudan

Seychelles

Equatorial GuineaNamibiaLibya

Burkina Faso

Mali

Mauritania

South Africa

Ivory CoastNigeria

Sierra Leone

KenyaAlgeria

Tanzania

Chad

Guinea

Benin

Angola

Gambia

Ghana

Senegal

Ethiopia

Guinea−Bissau

Malawi

Togo


Mozambique

Madagascar

−1

.5

0

1.1

A

ver

age

inco

me

per

per

son

in

20

00

−7 0 Slave exports normalized by land area

9

Robustness of Results

• Changes in the construction of the slave export estimates.

• Omitting influential observations.

• Changes in the sample of countries considered.

• Slave exports disaggregated by time period and by slave trade.

Robustness and Sensitivity Checks.

Specification: Coef Std Err N R2

Normalizing slave exports by average −.103∗∗∗ (.035) 52 .77

population from 1400 to 1900

Omitting zero slave export countries −.104∗∗ (.041) 41 .84

Omitting N. Africa, islands, −.140∗∗∗ (.040) 38 .70

GNQ, LSO, SWZ, and ZAF

Including five region fixed effects −.099∗∗ (.036) 52 .80

Omitting influential observations −.091∗∗∗ (.031) 42 .90

Econometric Issues

1. Unobserved/omitted country characteristics

• Areas that initially had poor institutions or domestic

slavery may have selected into the slave trade and these

characteristics persist today.

• The effect of slave exports may be overestimated: βols will

be biased away from zero.

2. Measurement error in slave export estimates

• Overall noise in the data, i.e. attenuation bias: βols will be

biased towards zero.

• Under-representation of slaves from the interior: βols will be

biased towards zero.

Strategies

• Control for observable characteristics.

• Examine the historical evidence on selection during the slave

trades.

• Instrumental variables.

Selection During the Slave Trades

• Initial prevalence of domestic slavery:

– Did internal slavery predate the external slave trades?

• Initial prosperity:

– Were the initially least prosperous societies targeted?

Angola

Burundi

Benin

Burkina Faso

Botswana


Ivory Coast Cameroon

Congo

ComorosCape Verde Islands

Djibouti

Algeria

Egypt

Ethiopia

Gabon

Ghana

Guinea Gambia

Guinea−Bissau

Equatorial Guinea

Kenya

Liberia

Libya

Lesotho Morocco

Madagascar

MaliMozambique

Mauritania

Mauritius

Malawi

Namibia

Niger

Nigeria

Rwanda

Sudan

Senegal

Sierra Leone

Somalia

Sao Tome & Principe SwazilandSeychelles

Chad

Togo

Tunisia

Tanzania

Uganda

South Africa


Zambia

Zimbabwe

0

5

10

S

lav

e ex

po

rts

no

rmal

ized

by

lan

d a

rea

−2.5 0 Population density in 1400

3.5

Angola

Burundi

Benin

Burkina Faso

Botswana


Ivory Coast

Cameroon

Congo

ComorosCape Verde Islands

Djibouti

Algeria

Egypt

Ethiopia

Gabon

Ghana

Guinea

Gambia

Guinea−Bissau

Equatorial Guinea

Kenya

Liberia

Libya

Lesotho Morocco

Madagascar

Mali

Mozambique Mauritania

Mauritius

Malawi

Namibia

Niger

Nigeria

Rwanda

Sudan

Senegal

Sierra Leone

Somalia

Sao Tome & Principe SwazilandSeychelles

Chad

Togo

Tunisia

Tanzania

Uganda

South Africa


Zambia

Zimbabwe

4

15

S

lav

e ex

po

rts

no

rmal

ized

by

av

erag

e h

isto

ric

po

pu

lati

on

−2.5 0 Population density in 1400

3.25

Instrumental Variables

• Instruments

– Must be uncorrelated with unobservable country

characteristics ε, but correlated with slave exports S.

– I use the distance from each country’s interior to the closest

major slave market in each of the four slave trades.

• Crucial Assumption

– Location of demand influenced the location of supply.

– Location of supply did not influence the location of demand.

What determined the location of demand?

• Climate and soil conditions suitable for plantation agriculture.

– West Indies and Mauritius

• Existence of natural resources.

– Gold and silver mines in Brazil

– Salt mines in the Northern Sahara, Arabia and Persia

– Pearls divers in the Red Sea

• Religion.

– In muslim societies slaves were used as servants eunuchs,

concubines, soldiers and government officials: Middle East

and North Africa

Instruments

1. Sailing distance to the closest market of the Atlantic slave

trade.

2. Sailing distance to the closest market of the Indian Ocean slave

trade.

3. Overland distance to the closest market of the Saharan slave

trade.

4. Overland distance the closest port of the Red Sea slave trade.

Virginia, USA

Havana, CubaKingston, Jamaica

Haiti

Martinique

Dominica

Salvador, Brazil

Djibouti

Massawa

Mascat, Oman

Suakin

Rio de Janeiro, Brazil

Guyana

Algires

Tripoli

Benghazi

Tunis

Cairo

Burkina Faso

Figure by MIT OpenCourseWare.

Instrumental Variables Estimates.

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

Second Stage. Dependent variable is log income in 2000, ln y

ln(exports/area) −.208∗∗∗

−.201∗∗∗

−.286∗

−.248∗∗∗

(.053) (.047) (.153) (.071)

[−.51, −.14] [−.42, −.13] [−∞, +∞] [−.62, −.12]

Colonizer fixed effects No Yes Yes Yes

Geography controls No No Yes Yes

Restricted sample No No No Yes

F -stat 15.4 4.32 1.73 2.17

Number obs. 52 52 52 42

First Stage. Dependent variable is slave exports, ln(exports/area)

Atlantic distance −1.31∗∗∗

−1.74∗∗∗

−1.32∗

−1.69∗∗

(.357) (.425) (.761) (.680)

Indian distance −1.10∗∗∗ −1.43∗∗∗

−1.08 −1.57∗

(.380) (.531) (.697) (.801)

Saharan distance −2.43∗∗∗

−3.00∗∗∗

−1.14 −4.08∗∗

(.823) (1.05) (1.59) (1.55)

Red Sea distance −.002 −.152 −1.22 2.13

(.710) (.813) (1.82) (2.40)

F -stat 4.55 2.38 1.82 4.01

Colonizer fixed effects No Yes Yes Yes

Geography controls No No Yes Yes

Restricted sample No No No Yes

Hausman test (p-value) .02 .01 .02 .04

Sargan test (p-value) .18 .30 .65 .51

Channels

• What are slave exports correlated with?

Angola

Burundi

Benin

Burkina Faso

Botswana

Central African Republic Ivory Coast

CameroonCongo

Comoros

Cape Verde Islands

Djibouti

Algeria

Egypt

Ethiopia

Gabon

Ghana

Guinea

Gambia Guinea−Bissau

Equatorial Guinea

Kenya

Liberia

Libya

Lesotho

Morocco

Madagascar

MaliMozambique

Mauritania

Mauritius

Malawi

Namibia Niger

Nigeria

Rwanda

Sudan Senegal

Sierra LeoneSomalia

Swaziland

Seychelles

Chad

Togo

Tunisia

Tanzania

Uganda

South Africa


Zambia

Zimbabwe

−.1

.5

1

.1

Eth

nic

Div

ersi

ty

−4 0 5 11 Slave exports normalized by land area

Angola

Burundi

Benin

Burkina Faso

Botswana


Ivory Coast

Cameroon

Congo

Comoros

Djibouti

AlgeriaEgypt

Ethiopia

Gabon

Ghana

Guinea Gambia

Guinea−BissauEquatorial Guinea

Kenya

Liberia

Libya

Lesotho

Morocco

Madagascar

Mali

MozambiqueMauritania Malawi

Namibia

Niger

Nigeria

Rwanda

Sudan

Senegal

Sierra Leone Somalia

Swaziland

Chad

Togo

Tunisia

Tanzania Uganda Democratic Republic of Congo

Zambia

Zimbabwe

−.1

.5

1

.1

19

th c

entu

ry s

tate

dev

elo

pm

ent

−3.5 0 5 11 ln(exports/area)

(beta coef = −.37, t−stat = −2.63, N = 47, R2 = .13)

Table 4: Testing potential channels of causality.

Without colonizer fixed effects With colonizer fixed effects

OLS IV OLS IV

coef s.e. coef s.e. coef s.e. coef s.e.

Dependent variable

Pre-colonial state dev. −.026∗∗ (.013) −.069∗∗∗ (.025) −.026∗ (.015) −.064∗∗ (.025)

Rule of law −.073∗∗∗ (.020) −.118∗∗∗ (.039) −.078∗∗∗ (.018) −.095∗∗∗ (.032)

Ethnic fractionalization .040∗∗∗ (.009) .065∗∗∗ (.018) .041∗∗∗ (.010) .066∗∗∗ (.019)

Cultural diversity .029∗∗∗ (.007) .050∗∗∗ (.014) .031∗∗∗ (.008) .051∗∗∗ (.014)

Conclusions

• Constructed country-level slave export estimates.

• Estimated a robust relationship between slave exports and

subsequent economic development.

• Used IV to establish causality and to correct for measurement

error.

• Initial evidence suggests that the relationship between the slave

trade and current development are through the same channels

that have been highlighted by historians.

14.772 Development Economics: Macroeconomics · Table 1: Africa and the Rest of the World. Mean std. dev. Min Max N. Real per capita GDP in 2000. Rest of World 8,809 7,591 521 37,471

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