The Biogeographical Roots of the Wealth of Nations …media.virbcdn.com/files/a0/82affe5ac0c70159-BerglasLecture-H.pdf · The Biogeographical Roots of the Wealth of Nations Oded Galor

The Biogeographical Roots of the Wealth ofNations

Oded Galor

Ther Berglas Lecture

Tel-Aviv University, June 2015

Oded Galor Biogeographical Roots 1 / 100

Introduction Comparative Development

Income per Capita across the Globe in 2010

0-1000

1000-3

000

3000-5

000

5000-1

0000

10000-

15000

15000-

20000

20000-

30000

30000-

40000

40000+



Divergence across Regions: 1820—2010

0

5,000

10,000

15,000

20,000

25,000

30,000

1820 1850 1880 1910 1940 1970 2000

GD

P P

er C

apit

a (1

99

0 In

t'l $

)

Western Europe Western Offshoots Eastern Europe

Latin America Asia Africa

Source: Maddison Project (2013)



Regional Income per Capita: 1—2010

0

5,000

10,000

15,000

20,000

25,000

30,000

0 500 1000 1500 2000

GD

P P

er C

apit

a (1

99

0 In

t'l $

)





Inferences from Growth Theory

Diminishing returns to physical and human capital accumulation

Diminishing effect of technological progress on productivity

=⇒ Reduction in inequality

=⇒ Convergence



Income Distribution in 1960

.05

.1.1

5.2

.25

Den

sity

of C

ount

ries

4 6 8 10 12Log Income per Capita

1960



Lack of Convergence across Nations: 1960—1980

file:///C|/Users/Oded_Galor/Dropbox/Files2007/BOOKS/PUP-Revised/new material for chapter 2/denstiyR-1960 1980.gif[12/15/2013 1:22:42 PM]



Lack of Convergence across Nations: 1960—2000

.05

.1.1

5.2

.25

Den

sity

of C

ount

ries

4 6 8 10 12Log Income per Capita

1960 1980 2000



Persistent Inequality across Nations: 1980—2010

ALB

AGO

ATGARG

AUSAUT

BHSBHR

BGD

BRB

BEL

BLZ

BEN

BMU

BTN

BOL

BWA

BRA

BGR

BFA

BDI

KHM

CMR

CAN

CPV

CAF

TCD

CHL

CHN COL

COM

COD

COG

CRI

CIV

CYP

DNK

DJI

DMA

DOM

ECU

EGY

SLV

GNQ

ETH

FJI

FIN FRA

GAB

GMB

DEU

GHA

GRC

GRD

GTM

GINGNB

HND

HKG

HUN

ISL

IND

IDN

IRN

IRQ

IRL

ISR

ITA

JAM

JPN

JOR

KEN

KOR

LAO

LBN

LSO

LBR

LUX

MAC

MDGMWI

MYS

MDV

MLI

MLT

MRT

MUS

MEX

MNG

MAR

MOZ

NAM

NPL

NLD

NZL

NER

NGA

NOR

OMN

PAK

PAN

PRY

PER

PHL

POL

PRT

ROU

RWA

STP

SAU

SEN

SLE

SGP

ZAF

ESP

LKA

KNA

LCAVCT

SDN

SUR

SWZ

SWE

CHE

SYR

TWN

TZA

THA

TGO

TTO

TUN

TUR

UGA

GBR

USA

URY

VEN

VNM

ZMB

ZWE

.6.7

.8.9

11.

1Ln

GD

P p

er C

apita

in 2

010

(rel

ativ

e to

the

US

)

.6 .7 .8 .9 1 1.1Ln GDP per Capita in 1980 (relative to the US)



Fundamental Research Questions

What is the origin of the vast inequality in income per capita acrosscountries and regions?

What accounts for the divergence in per-capita income across countriesin the past two centuries?

What are the factors that inhibited the convergence of poor economiestoward richer ones in the past decades?

What is the role of historical factors in explaining the observed patternsof comparative development?


Phases of Development


The Malthusian Epoch

The Post-Malthusian Regime

The Modern Growth Regime



Phases of Development: Timeline of the Most Developed Economies

Malthusian Epoch (99.8%)

200K BP 1750s





200K BP 1750s

Post-Malthusian (0.1%)

1750s 1870s 2014





200K BP 1750s

Post-Malthusian (0.1%)

1750s 1870s 2014

1870s 2014

Modern Growth (0.1%)


Phases of Development The Malthusian Epoch

The Malthusian Epoch

Characterized by stagnation and the absence of economic growth

Central characteristics of the period:

Positive effect of income (above subsistence) on population growthDiminishing returns to labor (reflecting the existence of fixed factor)

Technological progress over this period

(temporarily) increases the marginal productivity of laborIncome per capita increases (above subsistence)Population increases, as long as income remains above subsistenceMarginal productivity of labor declines towards its long-run levelIncome per capita returnes to the subsistence level in the long-run

Technologically advanced & land-rich economies:

Higher population densitySimilar levels of income per-capita in the long-run



Land Productivity and Population Density in 1500

Conditional on transition timing, geographical factors, and continental fixed effects.

Source: Ashraf-Galor (AER 2011)



Land Productivity and Income per Capita in 1500

Conditional on transition timing, geographical factors, and continental fixed effects.




Technology and Population Density in 1500

Years elapsed since the Neolithic Transition reflects the technological level in 1500.

Conditional on land productivity, geographical factors, and continental fixed effects.




Technology and Income per Capita in 1500

Years elapsed since the Neolithic Transition reflects the technological level in 1500.

Conditional on land productivity, geographical factors, and continental fixed effects.



Phases of Development The Post-Malthusian Regime

The Post-Malthusian Regime

Characterized by the onset of economic growth:

Technological progress accelerates

Income per capita still has a positive effect on population growth

Technological progress:

Increases output more than population=⇒ growth in income per capita


Phases of Development The Post-Malthusian Regime

Regional Variation in the Timing of the Take-off

0

5,000

10,000

15,000

20,000

25,000

30,000

1700 1750 1800 1850 1900 1950 2000

GD

P P

er C

apit

a (1

99

0 In

t'l $

)




Phases of Development The Modern Growth Regime

The Modern Growth Regime

Sustained economic growth

Acceleration in technological progress

=⇒ Industrial demand for human capital

Human capital formation

=⇒ Decline in fertility rates (substitution of quantity by quality)

The decline in population growth

=⇒ Freed the growth process from counterbalancing effects ofpopulation growth

Technological progress, human capital formation & decline in populationgrowth

=⇒ Sustained economic growth


Phases of Development The Demographic Transition

Years Elapsed since the Onset of the Fertility Decline

0-15

15-30

30-45

45-60

60-75

75-90 90+ N.A



Timing of the Demographic Transition and Current Income per Capita

NPL

BTN LAOMLI

AGO

GINNGATGO

LBR

NAM

MDG

SYR

ERI

IRN

BDILSOKHMCOM

PRY

HTI

RWA

ETH

MNGNER

CAF

GTM

HND

LBYSAU

BGDGMB

NICDJI

MRT

JOR

KWT

ZAF

DZASWZBENVNMCHNSDNZMB

CIV

GHA

BWA

SENGEO

MWI

ALB

KGZ

UZB

AZEARM

BHR

TUN

LBN

BOL

CMR

MAR

MEXKOR

ZWE

EGY

CHL

ISR

DOM

JPN

BLZMUS

IND

THASLV

ROM

ATGPAN

TZA

TTO

FINCANBRACRI

PER

BGR

ITA

PRT

DNKNORUSA

GBRAUTVENNLD

PHL

CHEBEL

IDN

DEUESPFRA

LKA

ARGGUYHUN

SYC

SWECOLSUR

JAMURY

KEN

ECU

MYS4

20

24

Log

Inco

me

Per C

apita

in 2

005

2 1 0 1 2Years Elapsed since the Demographic Transition

coef = 1.3462847, (robust) se = .10852591, t = 12.41

Conditional on absolute latitude.



Regional Variation in Growth of Income per Capita: 1950—2000

500

5,000

50,000

1950 1960 1970 1980 1990 2000

GD

P P

er C

apit

a (l

og

scal

e)

Western Europe Western Offshoots Africa

Asia Eastern Europe Latin America


Challenges for Growth Theory The Malthusian Epoch

Fundamental Research Questions: The Malthusian Epoch

What accounts for the epoch of stagnation that characterized most ofhuman history?

Why did episodes of technological progress in the pre-industrializationera fail to generate sustained economic growth?

Why did increased productivity generated population growth rather thangrowth in income per capita?


Challenges for Growth Theory The Transition from Stagnation to Growth

Fundamental Research Questions: Transition from Stagnation to Growth

What are the factors that generated the transition from stagnation togrowth of DCs?

What are the hurdles faced by LDCs in the transition from stagnationto growth?

What triggered the demographic transition?

Is the demographic transition a necessary condition for sustained eco-nomic growth?


Challenges for Growth Theory Comparative Development

Fundamental Research Questions: Comparative Development

What accounts for the transition from stagnation to growth in somecountries and the persistent stagnation in others?

What governs the differential timing of the demographic transitionacross nations?

What is the origin of the vast inequality that emerged across countriesin the past two centuries?

What is the contribution of deep rooted factors to the vast inequalityacross countries?


Challenges for Growth Theory Comparative Development

Non-Unified Growth Theory

Captures the role of factor accumulation and technological progress in themodern growth regime

Not designed to shed light on:

The forces that triggered the transition of DCs from stagnation to growth

The factors that hindered convergence across countries

The historical origins of vast and persistent inequality across countries


Unified Growth Theory





Captures the process of development in its entirety

Identifies the forces that generated the transition from stagnation to growth

Examines the origins of the uneven distribution of wealth across the globe

Underlines the role of deep-rooted factors in comparative development


Deep Roots of Comparative Development

Deep Roots of Comparative Development

Persistent effects of geographical and historical human characteristics

Biogeographical conditions (domesticable species, orientation of continent)

Variation in the onset of the Neolithic Revolution (Diamond, 1997)

=⇒ Comparative economic development

Migratory distance from Africa to indigenous settlements

Variation human composition (genetic diversity) across ethnic groups,countries, and regions (Ashraf-Galor, AER 2013)=⇒ Comparative economic development

Geographical characteristics (climate, soil quality, latitude, isolation, disease environment)

Variation in institutions conducive to development (AJR, AER 2001)Variation in productivity (Sachs et al, 1999), Andersen-Dalgaard-Seaya, RES 2016)

Variation in cultural characteristics conducive for development (Alesina-Giuliano-Nunn, QJE 2013, Galor-Ozak, AER 2016)


The Neolithic Revolution

The Neolithic Origins of Comparative Development

The transition from hunter-gatherer tribes to agricultural communities:

Emergence of a non-food-producing class:

=⇒ Knowledge creation (science, technology & written languages)

Technological head start and its persistent effect via:

Urbanization, nation states, colonization, culture and institutions

Cross continents variations in biogeographical characteristics conducive forthe NR :

=⇒ Origins of the observed patterns of comparative development



Variation in the Onset of the Neolithic Revolution

0-2000

2000-4

000

4000-6

000

6000-8

000

8000-1

0000

10000+



Biogeographical Origins of the Onset of the Neolithic Revolution

Geographical factors that maximized biodiversity (climate, latitude, landmass)

Availability of domesticable species of plants and animals

=⇒ Onset of domestication

Orientation of continents:

=⇒ Diffusion of agricultural practices along similar latitudes


The Neolithic Revolution Testable Predictions

The Diamond Hypothesis

The domination of Euro-Asia in the pre-colonial era reflects:

Larger number of domesticable species of plants and animals

East-West orientation

=⇒ Technological head start and its implications

The economic domination of Europeans and their offshoots in the post-colonial era reflects

Persistence of technological head startResistance to infectious diseases evolved in the aftermath of the NR

The Neolithic Revolution is at the origins comparative development in:

1491Contemporary period


Out of Africa

The "Out of Africa" Origins of Comparative Development

The migration of humans out of Africa 70,000-90,000 BP affected

The distribution of genetic diversity across the globe

Comparative economic development

Accounts for 16% of the variation in the income per capita acrosscountries


Foundations

Main Building Blocks of the Proposed Hypothesis

The Serial Founder Effect:

Lower genetic diversity among indigenous populations at greater migra-tory distances from East Africa

Existence of an optimal level of genetic diversity (for each stage of develop-ment)

Balances between:

The negative effect on the cohesiveness of societyThe positive effect on innovations


Foundations The Serial Founder Effect

The Serial Founder Effect

Exodus of modern humans from Africa (70-90K BP)

Departing populations carry only a subset of the genetic diversity of theirparental colonies

=⇒ Lower genetic diversity among indigenous populations at greatermigratory distances from East Africa



An Illustration of the Serial Founder Effect

3 Alleles

Original Population




3 Alleles

Original Population

2 Alleles

Founder Population

Increasing Migratory Distance




3 Alleles

Original Population

2 Alleles

Founder Population

1 Allele (each)

Sub-founder Populations

Increasing Migratory Distance


Foundations Genetic Diversity

Genetic Diversity —Measurement

Expected Heterozygosity

The probability that two individuals, selected at random from a givenpopulation, are different from one another in a given spectrum of genes



Human Genome Diversity Project (HGDP)

Consists of 53 ethnic groups (52 originally)

Resided in the same geographical location for a prolonged period of time

Isolated geographically

Display insignificant genetic admixture with other ethnic groups



HGDP Ethnic Groups



The Spatial Distribution of the HGDP Ethnic Groups

Prince Rupert

Anadyr

Phnom Penh

Addis Ababa

Cairo

Istanbul

Papuan Karitiana

Orcadian

+ Marks the location of an HGDP ethnic group.

o Marks an approximate critical juncture in the journey of humankind from Africa.



Migratory Distance from Africa and Genetic Diversity

.55

.6.6

5.7

.75

Exp

ecte

d he

tero

zygo

sity

0 5 10 15 20 25

Migratory distance from East Africa (in thousand km)

Africa Middle East Europe Asia Oceania Americas


Foundations Trade-offs: Human Diversity and Productivity

Trade-offs: Human Diversity and Productivity

Existence of an optimal level of genetic diversity (for each stage of develop-ment)

Balances between:

The negative effect on the cohesiveness of societyThe positive effect on innovations



The Costs of Diversity

Genetic diversity increases the incidence of:

Mistrust

Civil conflicts

=⇒ Ineffi ciency in the operation of the economy relative to its PPF



The Benefits of Diversity

Genetic diversity

Increases the likelihood for the existence of traits that are complementaryto the adoption of newly technologies

Generates complementary in the production process

Increases the upper tail of the ability distribution that matters for inno-vations

=⇒ Diversity fosters innovations & expands the production possibilities



Optimal Diversity

Positive but diminishing effects of:

Genetic diversity on innovations

Homogeneity on cohesiveness

=⇒ A hump-shaped relationship between diversity and develop-ment

=⇒ Optimal level of genetic diversity (for each stage of development)



The Optimal Level of Genetic Diversity

0 1

)(y

*



The Rise in the Optimal Diversity —Faster Technological Progress

0 1

);( gy

)(* Lg

);( Hgy

);( Lgy

)(* Hg


Empirical Analysis Comparative Development: 1500 CE

Comparative Development in the Pre-Colonial Era

Productivity

(Population Density)




Productivity


Human Genetic

Diversity




Productivity


Human Genetic

Diversity

Migratory Distance from

East Africa




Productivity


Human Genetic

Diversity


East Africa

Timing of the Neolithic

Revolution




Productivity


Human Genetic

Diversity


East Africa

Timing of the Neolithic

Revolution

Land Productivity • Percentage of Arable Land

• Suitability of Land for Agriculture

• Absolute Latitude


Empirical Analysis Analysis using Predicted Diversity

Projected Genetic Diversity across Countries in the Pre-Colonial Era

0,57-0

,62

0,62-0

,65

0,65-0

,71

0,71-0

,73

0,73-0

,74

0,74-0

,75

0,75-0

,760,7

6+



Predicted Diversity and Comparative Development in 1500

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

Dependent Variable is Log Population Density in 1500

Predicted Diversity 250.99*** 213.54*** 203.02*** 195.42*** 199.73**(68.26) (63.50) (61.05) (56.09) (80.51)

Predicted Diversity Sqr. -177.40*** -152.11*** -141.98*** -137.98*** -146.17***(50.22) (46.65) (44.83) (40.84) (56.26)

Log Years since NR 1.29*** 1.05*** 1.16*** 1.24***(0.18) (0.19) (0.15) (0.24)

Log % of Arable Land 0.52*** 0.40*** 0.39***(0.12) (0.09) (0.10)

Log Absolute Latitude -0.17* -0.34*** -0.42***(0.09) (0.09) (0.12)

Log Agri. Suitability 0.19 0.31*** 0.26***(0.12) (0.10) (0.10)

Optimal Diversity 0.707 0.702 0.715 0.708 0.683(0.021) (0.025) (0.110) (0.051) (0.110)

Continent Dummies No No No No No Yes

Observations 145 145 145 145 145 145

R-squared 0.22 0.26 0.38 0.50 0.67 0.69

Bootstrap standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.



Predicted Diversity and Comparative Development in 1500

AGO

BDI

BEN

BFA

BWA

CAF

CIV

CMR

COG DZA

EGY

ETH

GAB

GHA

GIN

GMB

GNB

KEN

LBR

LBYLSO

MARMDG

MLI

MOZ MRT

MWI

NAM

NER

NGA

RWA

SDN

SENSLESOM

SWZTCD TGO

TUN

TZA

UGAZAF

ZMB

ZWE

ALB

AUT

BEL

BGR

BIH

BLR

CHE

CZEDEU

DNK

ESP

EST

FIN

FRA

GBR

GRC

HRVHUN

IRLITA

LTU

LVA

MDA

MKD

NLD

NORPOL

PRT

ROM

RUS

SVN

SWE

UKR

AFG

ARE

ARMAZE

BGD

CHN

GEO

IDN

IND

IRN

IRQ

ISR

JOR

JPN

KAZ

KGZ

KHM

KOR

KWT

LAO

LBN

LKA

MMR

MNG

MYS

NPL

OMN

PAK

PHL

PRK

QATSAU

SYR

THA

TJK

TKM

TUR

UZB

VNM

YEM

AUS

NZL

PNG

ARG

BLZ

BOL

BRA

CAN

CHL

COL

CRI

CUB

DOM

ECU

GTM

GUY

HND

HTI

MEX

NIC

PAN

PER

PRY

SLV

SUR

URY

USA

VEN

1213

1415

1617

.2 .25 .3 .35 .4 .45

Africa Europe Asia Oceania Americas

(Con

trol

var

iabl

es h

eld

at z

ero)

Log

popu

latio

n de

nsity

in 1

500

(Predicted) Genetic homogeneity



Robustness: Distances from Placebo Origins

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

Dependent Variable: Log Population Density in 1500

Distance calculated from: Addis Ababa Addis Ababa London Tokyo Mexico City

Migratory Distance 0.138** -0.040 0.052 -0.063(0.061) (0.063) (0.145) (0.099)

Migratory Distance Sqr. -0.008*** -0.002 -0.006 0.005(0.002) (0.002) (0.007) (0.004)

Aerial Distance -0.008(0.106)

Aerial Distance Sqr. -0.005(0.006)

Log Years since NR 1.160*** 1.158*** 1.003*** 1.047*** 1.619***(0.144) (0.138) (0.164) (0.225) (0.277)

Log % of Arable Land 0.401*** 0.488*** 0.357*** 0.532*** 0.493***(0.091) (0.102) (0.092) (0.089) (0.094)

Log Absolute Latitude -0.342*** -0.263*** -0.358*** -0.334*** -0.239***(0.091) (0.097) (0.112) (0.099) (0.083)

Log Agri. Suitability 0.305*** 0.254** 0.344*** 0.178** 0.261***(0.091) (0.102) (0.092) (0.080) (0.092)

Observations 145 145 145 145 145

R-squared 0.67 0.59 0.67 0.59 0.63

Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.



Robustness to Distance from Regional Technological Frontiers

(1) (2) (3)

Log Population Density Log Population Density Log Population Density

1500 CE 1000 CE 1 CE

Predicted Diversity 156.74** 183.77** 215.86**(77.98) (91.20) (106.50)

Predicted Diversity Sqr. -114.63** -134.61** -157.72**(54.67) (63.65) (74.82)

Log Years since NR Yes Yes Yes

Land Prod. Controls Yes Yes Yes

Log Distance to -0.19***Frontier in 1500 CE (0.07)

Log Distance to -0.23**Frontier in 1000 CE (0.11)

Log Distance to -0.30***Frontier in 1 CE (0.10)

Optimal Diversity 0.684 0.683 0.684(0.169) (0.218) (0.266)

Continent Dummies Yes Yes Yes

Observations 145 140 126

R-squared 0.72 0.64 0.66




Genetic Diversity and Urbanization Rates in 1500

DZA

EGY

MAR

TUN

ALB

AUT

BEL

BGR

BLR

CHECZE

DEUDNK

ESP

EST

FINFRA

GBR

GRC

HRV

HUN

ITA

LTULVA

MDA

MKD

NLD

NOR

POL

PRT

ROM

RUS

SVN

SWE

UKR

BGD

CHN

IDN

IND

IRN

ISR

JPN

KAZ

KOR

LAO

LKA

MYS

PAK

PHL

SAU

SYR

THA

TUR

UZB

VNM

AUS

NZL

ARG

BLZ

BOL

BRA

CAN

CHL

COL

CRI

DOM

ECU

GTM

GUY

HND

HTI

MEX

NICPAN

PER

PRY

SLV

URY

USA

VEN

2728

2930

31

.25 .3 .35 .4 .45


(Con

trol

var

iabl

es h

eld

at z

ero)

Log

urba

niza

tion

rate

in 1

500

(Predicted) Genetic homogeneity


Contemporary Analysis

Genetic Diversity in Contemporary Countries

The index of genetic diversity reflects:

Proportional representation of each ethnic group within a country

GD within each the ancestral population of each ethnic group

Genetic distance between each pair of ethnic groups



Genetic Distance

0.0

5.1

.15

.2.2

5P

airw

ise

Fst

gen

etic

dis

tanc

e

0 10 20 30

Pairwise migratory distance (in thousand km)



Genetic Diversity across Countries in 2000

0,62-0

,66

0,66-0

,69

0,69-0

,72

0,72-0

,73

0,73-0

,74

0,74-0

,75

0,75-0

,760,7

6+


Contemporary Analysis Empirical Findings

Genetic Diversity and Economic Development in 2000 and 1500

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

Log Income per Capita Log Population Densityin 2000 in 1500

Adjusted Diversity 204.610** 237.238*** 244.960***(88.466) (86.278) (85.454)

Adjusted Diversity Sqr. -143.437** -166.507*** -171.364***(62.545) (61.363) (60.843)

Unadjusted. Diversity 198.587**(79.110)

Unadjusted. Diversity Sqr. -145.320***(55.472)

Log Adj. Years since NR 0.061 0.002(0.262) (0.305)

Log Years since NR -0.151 1.238***(0.186) (0.230)

Log % of Arable Land -0.110 -0.119 -0.137 0.378***(0.100) (0.107) (0.111) (0.100)

Log Absolute Latitude 0.164 0.172 0.192 -0.423***(0.125) (0.119) (0.143) (0.124)

Log Agri. Suitability -0.193** -0.177* -0.189* 0.264***(0.095) (0.102) (0.102) (0.096)

Log Population Density in 0.0471500 (0.097)

Optimal Diversity 0.713 0.712 0.715 0.683(0.100) (0.036) (0.118) (0.095)

Continent Dummies Yes Yes Yes YesObservations 143 143 143 143R-squared 0.57 0.57 0.57 0.68




Genetic Diversity and Comparative Development in 2000

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

Dependent Variable: Log Income per Capita in 2000

Adjusted Diversity 315.282*** 225.858*** 204.102*** 277.342*** 215.675***(84.215) (67.669) (66.984) (70.232) (63.954)

Adjusted Diversity Sqr. -220.980*** -155.826*** -140.850*** -192.386*** -150.871***(59.562) (47.962) (47.393) (49.675) (45.554)

Log Adj. Time from NR -0.273 -0.092 -0.062 0.396* -0.046(0.269) (0.200) (0.203) (0.233) (0.208)

Log % of Arable Land -0.218*** -0.159*** -0.163*** -0.183*** -0.084(0.061) (0.049) (0.050) (0.051) (0.056)

Log Absolute Latitude 0.123 0.083 0.080 0.009 -0.006(0.122) (0.100) (0.101) (0.108) (0.087)

Social Infrastructure 2.359*** 2.069*** 1.826*** 0.880**(0.269) (0.377) (0.417) (0.418)

Democracy 0.036(0.029)

Ethnic Fractionalization -0.333 -0.122(0.280) (0.265)

% Population at Risk -0.502 -0.723**of Contracting Malaria (0.351) (0.353)

Avg. Schooling 0.134***(0.042)


Continent Dummies Yes Yes Yes Yes YesLegal Origin Dummies No No No Yes YesMajor Religion Shares No No No Yes YesObservations 109 109 109 109 94R-squared 0.74 0.84 0.85 0.90 0.93




Genetic Diversity and Comparative Development in 2000

AGO

BDI

BEN

BFA

BWA

CAF

CIV

CMR

COG

DZA

EGY

ETH

GAB

GHA

GIN

GMB

GNB

KEN

LSO

MAR

MDG

MLI

MOZMRT

MWI

NAM

NER

NGA

RWA

SDN

SEN

SLE

SOM

SWZ

TCD

TGO

TUN

TZA

UGA

ZAF

ZMB

ZWE

AUT

BEL

BGR

CHECYPDEU

DNK

ESP

FIN

FRA

GBR

GRC

HUNIRL

ITA

NLD

NORPOL

PRT

ROMSWE

BGD

CHN

IDN

IND

IRN

IRQ

ISR

JOR

JPN

KOR

LKA

MYS

OMN

PAK

PHL

SAU

SYR

THA

TUR

AUS

NZL

PNG

ARG

BOL

BRA

CAN

CHL

COL

CRI

DOM

ECU

GTM

GUY

HND

HTI

JAM

MEX

NIC

PAN

PER

PRY

SLV

TTO

URY

USA

VEN

13.5

1414

.515

15.5

16

.2 .25 .3 .35 .4


(Con

trol

var

iabl

es h

eld

at z

ero)

Log

inco

me

per

capi

ta in

200

0

(Predicted) Ancestry−adjusted genetic homogeneity


Contemporary Analysis Interpretations

Interpretations —Diversity and Comparative Development in 2000

Optimal GD in 2000 = 0.7208 ≈ GD in US = 0.7206

Increasing GD of the most homogeneous country, Bolivia (0.63), by 0.09:

=⇒ 5.4-fold increase income per capita in 2000

From 8% to 40% of that of the US

Decreasing GD of the most heterogeneous country, Ethiopia (0.77), by 0.05:

=⇒ 1.7-fold increase in income per capita in 2000

From 2% to 4% of that of the US


Robustness Nightlight

Genetic Diversity and Light Intensity per Capita 1992-2012

DZA

AGO

BWA

BDI

CMR

CAF

TCD

COG

ZAR

BEN

ETH

GAB

GMBGHA

GIN

CIV

KEN

LSOMDG

MWI

MLIMRT

MAR

MOZ

NAM

NER

NGA

GNB

RWA

SEN

SLE

SOM

ZAFZWE

SDNSWZ

TGO

TUN

UGA

EGY

TZA

BFA

ZMB

AUT

BELBGR

CYP

DNK

FIN

FRA

DEU

GRCHUN IRL

ITA

NLD

NOR

POL

PRTROM

ESP

SWE

CHE

GBR BGD

MMR

LKA

CHN

INDIDN

IRN

IRQ

ISR

JPN

JOR

KOR

MYS

OMNPAK

PHL

SAU

SYR

THA

TURAUS

NZL

PNG

ARG

BOL

BRA

CAN

CHL

COL

CRIDOM

ECU

SLV

GTM

GUY

HTI

HND

JAM

MEX

NIC

PAN

PRY

PER

TTO

USA

URY

VEN

2324

2526

27

.2 .25 .3 .35 .4


(Con

trol

var

iabl

es h

eld

at z

ero)

Log

light

inte

nsity

per

cap

ita, 1

992−

2012

(Predicted) Ancestry−adjusted genetic homogeneity

Source: Ashraf-Galor-Klemp (2014)


Robustness Ethnic Groups

Observed Genetic Diversity - 232 Ethnic Groups



Migratory Distance from Africa and Genetic Diversity

DZA

TZAKEN

SDN

CMR

KEN CMR

TZA

CMRTZA

TCDTCD

ZAR

ERI

KEN

ZAR CIV

KEN

TZA

KENKEN

KEN

CMRGABTCD

KENCOG

NGACMRKEN

CMR

SDN

TCDKENKEN CMR

NGA

CMR

TZA

ZAFTZATZA

TZA

CMRTCD

CMRKEN NGA

CMR

ETH KEN

TZASEN

TZA

KENNGACMR

TZA

TCD

GABTZACMR

CMR

NGAKEN

CMR

CMRNGA

SSD

ZAFTZA

ZAF

KEN AGOCMRCMR

CMR

GAB

SSD

CAF

KEN

TCDRWA

KEN

NGA

TCD

KEN

CMRGHA

TCDKEN

TZAKENCMR

CMRNGA

CMR

NGA

ZARCMR

GHACMR

ETHKEN

NAM

KENCMR

TZA NGA

CMR

SSD

TZA

CHN CHN

CHN

CHN

CHN

TWN

CHN

CHN

TWN

CHN

MNG

JPN

CHN

CHN

KHM

CHN

CHN

CHN

CHN

RUS

RUS

RUS

RUSPSESYR

YEMSYR

INDPAK

IND

PAK

INDIND

INDAFG

PAKIND

INDIND

PAKIND

PAK IND

IND

PAK

IND

IND

PAK

PAK

GBR

FRA

ITA

RUS ITA

ITA

ESP

MEX

GTM

PAN

MEX

MEX

MEX

MEX

PAN

CANCAN

CAN

PNG

PNG

PNGPNGPNG

PNG

PNG

PNG

PNG

PNG

NZL

PNG

PNG

PNG

PNG

PNG

PNG

PNG

PNGPNGPNGPNG

PNG

PNG

PNG

PNG

WSM

PNG

PNG

PNG

PNGPNGPNG

PNG

PNG

PER

BRA

PER

BRA

COL

COL

BRA

COL

COL

BRA

PER

COL

COL BRACOL

ARG

0.56

0.77

0.0 2.5

South America North America Oceania Australia Asia Europe Africa

Gen

etic

Dive

rsity

Migratory Distance from East Africa (in 10,000 km)



Genetic Diversity and Productivity of Ethnic Group - (IV Regressions)

DZA

TZA

KEN

SDN

CMR

KENCMR

TZA

CMR

TZATCDTCD ZAR

ERI

KEN

ZAR

CIV

KENTZA

KEN

KEN

KEN

CMR

GAB

TCD

KEN

COG

NGACMR

KEN

CMR

SDN

TCD

KEN

KEN

CMR

NGACMR

TZA

ZAF

TZA

TZATZA

CMR

TCD

CMR

KEN

NGA

CMR

ETH

KENTZA

SEN

TZA KENNGACMR

TZA

TCD GAB

TZA

CMRCMR

NGA

KEN

CMR

CMR

NGA

SSD

ZAF

TZA

ZAF

KEN

AGO

CMRCMR

CMR

GAB

SSD

CAF

KEN

TCD

RWA

KEN

NGA

TCD

KEN

CMRGHA

TCD

KENTZA

KEN

CMR

CMR

NGA

CMR

NGA

ZAR

CMR

GHA

CMR

ETH

KEN

NAM

KEN

CMRTZANGA

CMR

SSD

TZA

CHN

CHN

CHN

CHN

CHNTWN

CHN

CHN

TWN

CHN

MNG

JPN

CHN

CHN

KHM

CHN CHN

CHN

CHNRUS

RUS

RUS

RUS

PSE

SYRYEM

SYR

IND

PAK

IND

PAKIND

IND

IND

AFG

PAK

INDIND

IND

PAK

IND

PAK

IND

IND

PAK

INDIND

PAK

PAK

GBR

FRA

ITARUS

ITA

ITA

ESP

MEX

GTM

PAN

MEX

MEXMEXMEX

PAN

CANCAN

CAN

PNG

PNG

PNG

PNGPNG

PNG

PNG

PNG

PNG

PNG

NZL PNG

PNG

PNG

PNGPNG

PNGPNG

PNG

PNG

PNG

PNG

PNG

PNG

PNG

PNG

WSM

PNG

PNG

PNG

PNG

PNG

PNG

PNGPNG

PER

BRA

PER

BRA

COL

COL

BRA

COL

COL

BRA

PER

COL

COL

BRA

COL

ARG

350

364

0.561 0.768


Cont

rol v

aria

bles

hel

d at

zer

oLo

g Lu

min

osity

Genetic Diversity




Predicted Genetic Diversity - 1331 Ethnic Groups



Predicted Genetic Diversity - 1331 Ethnic Groups

ESP

DZA

EGY

LBY

TUN

DZA

DZA

DZA

MAR

DZADZA

TUN

ESH

DZA

MAR

EGY

EGY

MAR

EGY

MAR

MAR

MAR

MAR

DZA

MAR

DZA

DZA

TUN

UGA

ZAR

ETH

TCD

KEN

SSD

MRT

MRT

ZAR

NGA

BENNGA TZA

AGO

SEN

CIV

MLI

TZA

GHA

SDN

GHA

TCD

NGA

NGA KEN

MLI

TZA

ZMB

ZAR

NGA

TCD

ZAR

ETH

ZAR

CAF

UGA

NGA

TZA

ZAR

TZA

ZAF

KEN

SDN

NGA

CMR

NGALBR

TZAUGAKEN

NGA

NGA

ZAR

CIV

NGA

NGA

TZA

TZA

CMRKEN

ZAR

TZA

TZA

CAF

LBR

NGA

SDN

CIV

ZAR

CMR

CAF

MDG

ZAR

ETH

TZA

NGA

NGA

ZAR

TZABFA

NGA

CMR

BEN

MLI

CMRMLI

BFAKEN

GHA

ZAR

SDN

SDN

NGANAM

NGA

AGO

TZA

SSD

NGA

KENZARSDNGINETH

CMR

NGA

GINAGO

ZAR

ZAR

TZA

ETH

ZARSDN

MWIZMB

CMR

ETH

ERINGA

GHA

ZAR

SEN

CMR

CMR

AGO

NGA

LBR

KENKEN

SSD

CIV

ETH

TZA

ZAR

ZMB

ETH

ZMB

SSD

ZAF NAM

ZAR

KEN

ZAR

GHA

CMR

NAM

ETHZAR

GIN

GIN

ZAR

KEN

ZAR

CIV

SDN

NGA

ZAF

UGA

MDG

ZMB

AGOGAB

ETH

GHA

ZAR

UGA

CMRTGO

TZANGA

TZA

TGO

NGAGHA

RWA

NGA

CIV

ETH

NGA

SSD

TZA

MOZ

SENCIV

GHA

ZAR

GIN

GAB

BDI

CMR

ETH

CIV

MLI

BFA TZA

TCD

SDN

KEN

GHA

SDN

COG

BFA

KENNER

CMRSDN

ZAR

NGA

NGA

ZAR

CMR

GNB

MLIMLI

TZA

SEN

ETH

COG

NAM

TZA

ETHUGA

TZA

TGO

NGA

SSDERI

AGO

NGA

MOZ

SSD

CIV

ZMB

MLI

NGA

ZMB MWISLE

CIV

CMR

ETH

GABBFA

ETH

KEN

TZA

TZA

ZAF

GHA

SSD

ETH

BFA

ZAF

KEN

SDN

KEN

UGASSD

ETH

NGA

SLE

ETH

ZAF

ERI

NER

NGA

UGA

NGA

CMR

ZARZMB

CMR

KEN

NGA

TZA

SSD

ZAF

ZAR

GHA

ZAFNGA

ETH

NGA

ZARCMR

TGO

KEN

TCD

CMR

TZA

SEN

ZAR

TZA

TGO

ZAF

UGANER

MRT

ZAR

TZA

TCD UGA

ETH

CMR

BFA

NGA

ZAR

UGAGHA

SSD

UGA

NGA

MOZ

LBR

NGA

TZAETH

KEN

ZAF

MDG

SDN

BFA

CMR

ZAR

NGACMR

TZA

ZAR

NGA

NGA

TCD

NGA

CIV BEN

ZAF

TCD

KEN

ZAR

CMR

CMR

ZAR

ERI

NGAMOZ TCD

TZA

BFA MWI

NGA

TCD

TZA

MLI

ETH

ZAR

SEN

ZAR

SDNKEN

SDN

AGO

TZAMLI

AGO TZA

LBRSLE

ETH

TGO

TZA

CAF

TCD

NGA

ETH

GHACMR

NGA

CMR

SWZ

MDG

SSD

ETH

MOZ

TZA

CMR

KEN

ZWEZAR

MRT

TZA

ZARZAR

GHA

ETH

CMR

NGA

NGA

MDG

NGA

NGA

TCD

AGOSDN

SHN

CMR

SDNCMR

ZAR

TZACMR

NGA

TZA

GNB

ETH

UGA

GHA

ETH

CMR

LBR

CMR

ZAR

MLI

SDN

ETH

ZMB

ZAR

KEN

CIV

TZA

ZAR

MOZ

CMR

NGA

KEN

ZAR

SDN

CMR

TCD

KEN

CMR

ZAR

NER

CIV

CMR

KEN

KEN

NGA

ZMB

GAB

MOZ

CMR

MOZ

NGA

TCD

NGA

NGA

NGA

NGA

NGA

NGA

TCD

BFAAGO

SDN

ETH

GNB

MLI

SEN

ZMB

BFA

BFA

BWA

GHA

COGNGA

NGA

CMR

ZMB

SSD

CMR

NGA

GHA

KEN

MOZ

CMR

ZAR

ZAR

GIN

SSD

KEN

SDN

MOZ

ZARKEN

UGA

KEN

CMR

NAM

CMR

UGA

UGA

SSD

ETH

CMR

KEN

GHA

ZAR

ZAR

ZAR

CMR

SSD

MDGCMR

CMRCIV

CMR

ZAR

SSD

GAB

TZA

SLE

ETH

GNB

TGO

ETH

ZAR

KEN

ZAR

SSD

CMR

NGA

MOZ

SDN

BFA

ERI

GHA

NGA

CMR

KEN

ZAR

MLI

LBR

KEN

NGA

PHL

IDN

CHN

CHN

PNG

IDN

PNG

MMR

PNG

CHN

PNG

PNGPNG

IDN

IDN

TWN

PHL

IDN

MYS

IDN

IDN

CHN

IDN

CHN

PNG THA

CHN

IDN

IDN

PNGPHL

JPN

CHN

PHL

PHL

IDN

PHL

MMR

PNG

IDN

VNM

PNG

PNG

PHL

MMR

VNM

IDN

VNM

CHN

MMR

IDN

JPN

CHN

PNG

CHN

TWN

IDN

THA

IDN

PNG

PNG

PNG

PHL

IDNIDN

MYS

PHL

MMR

TWN

CHN

CHN

IDN

CHN

CHN

MYS

PNG

IDN

CHN

PNG

MMR

IDN

IDNPNG

PNG

CHN

TWN

IDNJPN

IDN

LAO

PNG

VNM

MYS

CHN

IDN

MYS

KHM

PNG

PNG

PNG

THA

PHL

MMR

MMR

CHN

KHM

PNG

PNG

PNG

CHN

JPN

CHNTLS

PNG

PNG

TWNCHN

VNM

IDN

PNG

IDN

IDN

JPN

PNG

PNGPNG

IDNPHL

PNG

CHN

VNM

TWN

MNG

PNG

CHN

CHN

IDN

RUS

PSE

RUS

RUS

ARM

RUS

RUS

RUS

RUS

GEO

RUS

RUSGEO

RUS

GEO

RUS

TUR

GEO

RUS

KAZ

RUS

SYR

IRQ

SAU

YEM

IRN

SAU

SYR

IRN

ISR

IRN

IRN

ISR

LBN

IRN

IRQ

SYR

IND

PAK

PAK

IND

IND

IND

IND

IND

AFGINDIND

IND

PAK

IND

IND

IND

IND

IND

IND

IND

IND

PAK

PAK

IND

IND

IND

IND

NPL

IND

PAK

BGD

BGD

AFG

IND

IND

IND LKA

PAK

BGD

IND

IND

IND

AFG

AFG

PAK

IND

PAK

IND

IND

IND

INDIND

IND

IND

IND

IND

IND

IND

IND

AFG

IND

NPL

IND

IND

LKA

IND

IND

AUS

AUS

AUS

AUS

AUS

AUS

AUSAUS

AUS

AUS

AUS

AUS

AUS

AUS

ITA

GBR

RUS

ESP

FRA

UKR

LTU

HUN

CZE

RUS

RUS

RUS

ROU

ITA

RUS

GRC

ISL

UKR

ESP

ALB

NLD

PRT

RUSITA SRB

ITA

IRL

BEL

ESP

RUS

BLR

BGR

GRL

MEXHND

MEXMEX

MEX

GTM

MEX

MEX

GTM

GTM

MEX

MEX

MEX

MEX

MEX

PAN

MEX

HND

BLZ

MEX

MEX

MEX

MEX

MEX

MEX

PAN

GTMHND

BHS

MEX

MEX

MEX

GTM

HTI

MEX

MEX

DMA

MEX

MEX

MEX

GTM

MEX

USA

CAN

CANUSA

USA

CANCAN

USA

USA

USA

USA

USA

USAUSA

USA

USA

USA

USA

USA

USA

USAUSA

USA

USACAN

USA

USA

USA

USA

USA

USA

USACAN

USA

CAN

USA

USA

USA

CANCAN CAN

USA

USA

CAN

USA

USA

USA

USAUSAUSA

USA

USA

USA

USA

USA

CAN

USAUSA

USA

USA

USAUSA

USA

USA

USA

USA

USA

USA

CAN

USA

USA

USA USA

USA

USA

USA

USAUSAUSA USA

USAUSA

USA

CAN

USA

USA

USA

USA

USA

USA

USAUSAUSA

USA

CAN

USA

USA

USA

USA

USA USA

USAUSA

CAN

CAN

USACAN

CAN

USA

USA

CAN

CANUSA USA

USA

USAUSA

USA

USA

USA

USA

USA

USA

USA

USA

USAUSA

CAN

USA

USAUSA

CANUSA

CAN

USA

USA

USA

CAN

CANUSA

USA

USA

USA

USA

USA

USA

USA

USA

USACAN

USA

USA

USA

USA

USA

USA

USA

USAUSA

USA

USA

USA USA

CAN

USA

CAN

USAUSA

USA

USA

USA

USA

CAN

USA

USA

CAN

USA

CAN

USA

USA

USA

USA

USA

USA

CAN

USA

USA

USA

CAN

USA

USA

USA

USA

USAUSA

USAUSA

USA

USA

USA

USA

USACAN

CAN

USA

USA

USA

USA

USA

CAN

USA

CAN

USA

USA

USA

USA

USA

CANUSA

USA

USA

USA

USA

USA

USA

CAN

USA

USA

CAN

USACAN

USA CAN

USAUSA

USA

USA

USA USA

USA

USA

CAN

USA

USA

CAN

CAN

USA

USA

CAN

PNG

SLB

PNG

TKL

PNGPNG

MHL

PNG

PYF

WSM

PLW

NRU

PNG

VUT

VUT

SLB

WLF

WSM

PNG

TON

TUV

WLF

SLB PNG

PNG

SLB

PYF

PNG

PNGPNG

PNG

PNG

SLB

MHL

SLB

COK

SLB

PNG

PNG

FSM

VUT

VUT

PNG

NCL

PNG

PNG

PNG

PNG

KIR

PNG

FSM

KIR

MNPNCL

PNG

COK

FJI

PNG

FJI

PNG

SLB

PNG

PNG

NIU

PNG

FSM

PNG

PNG

PNG

FJI

VUT

PYF

COK FSM

FJI

SLB

PNG

PNGPNG

NZL

GUM

MHL

VUT

PNG

PNG

PNGPNG

FSM

PNG

BRABRA

ECU

PRY

BOL

PERARGBRA COL

BRA

COL

PER

VEN

COL

BOL

VEN

PAN

BRA

BRA

VEN

PER

BRA

VEN

COL

BRA

PER

VEN

PERBRA

BRA

COL

COL

COL

BRA

GUY

COL

BRA

VEN

SUR

BRA

VEN

GUF

BRA

COL

ECU

VEN

COL

BRA

PRY

ARG

COL

BRA

PER

BRA

ARG

SUR

COL

BRA

ARG

BRA

ARGVEN

BRA

ARG

BOL

BRA

PER

BRA

PRY

BRA

PERPER

GUF PAN

COL

ARG

COL

BRA

BRA

BOL

GUY

VEN

CHL

COL

BRA

VEN

VEN

BRA

BOL

VEN

BRA

BRA

BRACOL

BRA

BRA

BRA

BRA

COL

91

103

0.579 0.768


Cont

rol v

aria

bles

hel

d at

zer

oLo

g Av

erag

e Li

ght p

er C

apita

(Predicted) Expected Heterozygosity



Mechanisms Cost of Diversity

Cost of Diversity: Genetic Diversity & Cultural Fragmentation

AGO

BDI

BEN

BFA

BWA

CAF

CIV

CMR

COG

DZA

EGY

ETH

GAB

GHA

GIN

GMBGNB

KEN

LBR

LBYLSO

MAR

MDG

MLI

MOZ

MRT

MWI

NAM

NER

NGA

RWA

SDN

SEN

SLE

SOM

SWZ

TCD

TGO

TUN

TZA

UGA

ZAF

ZAR

ZMB

ZWE

ALB

AUT

BEL

BGR

BIH

BLR

CHE

CZE

DEU

DNK

ESP

EST

FIN

FRA

GBR

GRC

HRV

HUN

IRL

ITA

LTU

LVAMDA

MKD

NLD

NOR

POL

PRT

ROM

RUS

SVN

SWE

UKR

YUG

AFG

ARE ARM

AZE

BGD

BTN

CHN

GEO

IDNIND

IRN

IRQISR

JOR

JPN

KAZ

KGZ

KHM

KOR

KWT

LAO

LBN

LKA

MMR

MNG

MYS

NPL

OMN

PAK

PHL

PRK

SAU

SYR

THA

TJK

TKM

TUR UZB

VNMAUS

NZL

PNG

CAN CRI

CUB

DOM

GTM

HND

HTI

MEX

NIC

PAN

SLV

USA

ARG

BOL

BRA

CHL

COL

ECU GUY

PER

PRY

URY

VEN

−1

−.5

0.5

1

−.05 0 .05

Africa Europe Asia Oceania N. America S. America

(Con

trol

var

iabl

es h

eld

at z

ero)

Log

num

ber

of e

thni

c gr

oups

(Control variables held at zero)

Genetic diversity (ancestry adjusted)

Relationship conditional on historical and geographical controls, as well as continent fixed effectsSlope coefficient = 6.397; (robust) standard error = 1.973; t−statistic = 3.242; partial R−squared = 0.059; observations = 144

Source: Ashraf and Galor (2013b)

Source: Ashraf-Galor (AER, May 2013)



Cost of Diversity: Genetic Diversity & Trust

BFA

DZA

EGY

ETH

GHA

MAR

MLI

NGA

RWA

TZA

UGA

ZAF

ZMB

ZWE

ALBAUT

BELBGR

BIHBLR

CHE

CZE

DEU

DNK

ESP

EST

FIN

FRA

GBR

GRCHRV

HUN

IRL

ITA

LTU

LUX

LVA

MDA

MKD

NLD

NOR

POL

PRT

ROM

RUS

SVK

SVN

SWE

UKR

YUG

ARM

AZEBGD

CHN

GEO

IDN

INDIRN

IRQ

ISR

JOR

JPN

KGZ

KOR

MYS

PAK

SAUTHA

TUR

VNM

AUS

NZL

CAN

GTMMEX SLV

USA

ARG

BRA

CHL

COL

PER

URY

VEN

−.2

−.1

0.1

.2.3

−.04 −.02 0 .02 .04


(Con

trol

var

iabl

es h

eld

at z

ero)

Pre

vale

nce

of in

terp

erso

nal t

rust



Relationship conditional on geographical controls and region fixed effectsSlope coefficient = −2.151; (robust) standard error = 0.756; t−statistic = −2.845; partial R−squared = 0.105; observations = 84

Source: Arbatli, Ashraf, and Galor (2015)



Cost of Diversity: Genetic Diversity & Heterogeneity in Preferences

BFA

DZA

EGY

ETH

GHA

MAR

MLI

NGA

RWA

TZA

UGA

ZAF

ZMB

ZWE

ALB

AUT

BEL

BGR

BIH

BLRCHECZE

DEU

DNKESP

EST

FIN

FRA

GBR

GRC

HRVHUN

IRL

ITA

LTU

LUX

LVA

MDA

MKD

NLD

NOR

POL

PRT ROM

RUS

SVK

SVN

SWE

UKR

YUG

ARM

AZE

BGD

GEO

IDN

IND

IRN

IRQISR

JOR

JPN

KGZ

KOR

PAK

THA

TUR

VNM

AUS

NZL CAN

GTM

MEX

SLV

USA

ARG

BRA

CHL

COL

PER

URY

VEN

−2

−1

01

2

−.04 −.02 0 .02 .04


(Con

trol

var

iabl

es h

eld

at z

ero)

Het

erog

enei

ty in

pol

itica

l pre

fere

nces



Relationship conditional on geographical controls and region fixed effectsSlope coefficient = 16.963; (robust) standard error = 5.954; t−statistic = 2.849; partial R−squared = 0.111; observations = 81




Cost of Diversity: Genetic Diversity & Ethnic Civil Conflict

AGO

BDI

BEN

BFA

BWACAF

CIVCMR

COG

DZA

EGY

ERI

ETH

GABGHAGIN

GMBGNB

GNQKEN

LBR

LBY

LSO

MAR

MDGMLI

MOZMRT

MWI

NAM

NER

NGA

RWA

SDNSEN SLE

SOM

SWZ TCD

TGOTUN

TZA

UGA

ZAF

ZAR

ZMB

ZWE

ALBAUTBEL

BGR

BIH

BLR

CHE

CZEDEU

DNK

ESPESTFIN FRA

GBR

GRC

HRV

HUNIRL

ITA

LTULUX

LVA

MDAMKD

NLDNOR POL

PRT

ROM

RUS

SVKSVN

SWE

UKR

YUG

AFGARE

ARM

AZE

BGD

BTN

CHN

GEO

IDN

IND

IRN

IRQISR

JOR

JPN

KAZ

KGZ

KHM

KOR

KWT

LAOLBN

LKA

MMR

MNG

MYS

NPL

OMN

PAK

PHL

PRK

QAT

SAUSYR

THA

TJK

TKM

TURUZB

VNM

YEM

AUS

NZL

PNG

BLZ

CAN

CRICUB

DOM

GTMHND

HTIMEX

NIC PANSLV

USA

ARGBOLBRA

CHLCOL

ECU

GUYPERPRY

URY

VEN

−.0

50

.05

.1.1

5

−.1 −.05 0 .05


(Con

trol

var

iabl

es h

eld

at z

ero)

Log

annu

al fr

eque

ncy

of c

ivil

conf

licts

, 196

0−20

08



Relationship conditional on geographical controlsSlope coefficient = 0.445; (robust) standard error = 0.117; t−statistic = 3.790; partial R−squared = 0.112; observations = 151


Source: Arbatli-Ashraf-Galor-Klemp (2016)


Mechanisms The Benefit of Diversity

Benefits of Diversity —Genetic Diversity & Scientific Research

BDI

BEN

BWA

CAFCMR

COG

DZA

EGY

ETH

GHA

GMB

KEN

LSO

MLI

MOZ

MRT

MWI

NER

RWA

SDN

SEN

SLE

SWZ

TGOTUN

UGAZAF

ZAR

ZMB

ZWE

AUT

BEL

BGR

CHE

CYP

DEU

DNK

ESP

FIN

FRA

GBR

GRC

HUN

IRL

ITA

NLD

NOR

POLPRT ROM

SWE

BGD

CHN

IDN

IND

IRN

IRQ

JPN

KOR

LKA

MMR

MYS

PAK

PHL

SYR

THA

TUR

AUS

NZL

PNG

CAN

CRI

DOM

GTMHND

HTI

MEX

NIC

PAN

SLV

TTO

USA

ARG

BOL

BRA

CHL

COL

ECU

GUY

PER

PRY URYVEN

−.4

−.2

0.2

.4

−.05 0 .05


(Con

trol

var

iabl

es h

eld

at z

ero)

Ave

rage

ann

ual s

cien

tific

art

icle

s pe

r ca

pita

, 198

1−20

00



Relationship conditional on historical, geographical, and institutional controls, as well as continent fixed effectsSlope coefficient = 2.484; (robust) standard error = 0.511; t−statistic = 4.864; partial R−squared = 0.131; observations = 93

Source: Ashraf and Galor (2013a)


Conclusion

Conclusions: Roots of Comparative Development

The migration of humans out of Africa 70,000-90,000 BP affected

The distribution of genetic diversity across the globe

Comparative economic development

Accounts for 16% of the variation in the income per capita acrosscountries

Variation in the onset of the Neolithic Revolution

Affected comprative developmemt till around 1500

Has no persistent effect on comparative development in the modern era


Conclusion

Policy Implications

Education policy

In overly-diverse societies:

Education geared towards: social cohesiveness & tolerance=⇒ Mitigating the cost of diversity

In overly-homogeneous societies:

cultivation of cultural diversity=⇒ substitute for low genetic diversity

Optimal level of cultural assimilation


AppendixSelection: Distance from East Africa and

Phenotypes

Migratory Distance from East Africa and Height

Accounting for distance from the equator.



Phenotypes

Migratory Distance from East Africa and Weight




Phenotypes

Migratory Distance from East Africa and Skin Reflectance




Phenotypes

Migratory Distance from East Africa and IQ




Phenotypes

Expected Heterozygosity in Microsatellites

Expected heterozygosity calculated for the 53 ethnic groups in the HGDPusing allelic frequencies for 783 microsatellite loci

Advantage of using microsatellites — a class of non-protein-coding regions ofthe human genome:

Selectively neutral

Ensures that the observed cross-sectional variation in diversity isnot due to differential forces of natural selection

Expected heterozygosity in microsatellites is positively correlated withphenotypic and cultural diversity

Permitting an exploration of the effect of GD on economic outcomes



Phenotypes

Distance from Africa and Craniometric Diversity

Source: Manica et al. (Nature 2007)



Phenotypes

Distance from Africa and Linguistic Diversity

Source: Atkinson (Science 2011)



Phenotypes

Distance from Africa and Dental Diversity

Source: Hanihara (American Journal of Physical Anthropology, 2008)



Phenotypes

Distance from Africa and Height Diversity

Source: Galor and Klemp (2014)



Phenotypes

Distance from Africa and Pelvic Bone Diversity

Source: Betti et al. (Human Biology, 2012)



Phenotypes

Robustness to Microgeographic Factors

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


Predicted Diversity 159.92*** 153.20*** 157.07** 150.02*** 157.06**(56.00) (53.39) (78.82) (49.36) (68.61)

Predicted Diversity Sqr. -110.39*** -105.33*** -112.78** -102.76*** -114.99**(41.08) (39.11) (55.48) (36.23) (48.26)

Log Years since NR Yes Yes Yes Yes Yes

Land Prod. Controls Yes Yes Yes Yes Yes

Mean Elevation -0.48** 0.51* 0.50*(0.23) (0.27) (0.27)

Roughness 5.15*** 3.09* 4.08**(1.77) (1.74) (1.84)

Roughness Sqr. -7.05** -7.05** -7.63***(3.11) (2.96) (2.91)

Distance to Nearest -0.49*** -0.44** -0.47** -0.39**Waterway (0.18) (0.18) (0.18) (0.18)

% Land within 100 km 0.70** 0.73** 1.11*** 1.18***of Waterway (0.28) (0.31) (0.29) (0.29)


Continent Dummies No No Yes No Yes

Observations 145 145 145 145 145

R-squared 0.69 0.74 0.75 0.76 0.78




Phenotypes

Robustness to Biogeography

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

Dependent Variable is Log Population Density in 1500

Predicted Diversity 216.85*** 252.08*** 174.41*** 212.12*** 274.92***(62.06) (70.81) (62.75) (72.13) (72.12)

Predicted Diversity Sqr. -154.75*** -180.65*** -125.14*** -151.58*** -197.12***(45.19) (51.89) (45.72) (52.79) (52.40)

Log Years since NR 1.30*** 1.16***(0.16) (0.31)

Land Prod. Controls Yes Yes Yes Yes Yes

Climate 0.62*** 0.42 0.37*(0.14) (0.27) (0.22)

Orientation of Axis 0.28 0.04 -0.17(0.33) (0.30) (0.27)

Size of Continent -0.01 -0.01 -0.01(0.02) (0.01) (0.01)

Domesticable Plants 0.02 -0.01 0.00(0.02) (0.02) (0.02)

Domesticable Animals 0.15** 0.12 -0.01(0.06) (0.07) (0.07)


Observations 96 96 96 96 96

R-squared 0.74 0.70 0.70 0.72 0.78




Phenotypes

Income Per Capita and Nightlight Observed by Satellites: 1992-2012

DZA

AGO

BWA

BDI

CMR

CAF TCD

COG

ZAR

BEN

ETH

GAB

GMBGHA

GIN

CIV

KEN

LSO

MDG

MWI

MLI

MRT

MAR

MOZ NAM

NER

NGA

GNB

RWASEN

SLE

ZAF

SDN

SWZ

TGO

TUN

UGA

EGY

TZABFA

ZMB

AUT

BEL

BGR

CYPDNK

FIN

FRADEU

GRCHUN IRL

ITA

NLD

NOR

POLPRT

ROM

ESP

SWE

CHEGBR

BGD

LKA

CHN

IND

IDN

IRN

IRQ

ISRJPN

JOR

KOR

MYS

OMN

PAK

PHL SAU

SYRTHA

TUR

AUS

NZL

PNG

ARG

BOL

BRACANCHL

COL

CRIDOM

ECU

SLV

GTM

GUY

HTI

HND

JAM

MEX

NIC

PAN

PRYPER

TTO

USA

URY

VEN

-2.7

-1.8

-.9

0

.9

1.8

2.7

-2.7 -1.8 -.9 0 .9 1.8 2.7

Log

per-a

rea

light

inte

nsity

(sta

ndar

dize

d)

Log GDP per capita in 1992-2012 (standardized)A

DZA

AGO

BWA

BDI

CMR

CAFTCD

COG

ZAR

BEN

ETH

GAB

GMB

GHA

GIN

CIV

KEN

LSO

MDG

MWI MLI

MRT

MAR

MOZ

NAM

NER

NGA

GNBRWA

SEN

SLE

ZAF

SDN

SWZ

TGO

TUN

UGA

EGY

TZABFA

ZMB

AUTBEL

BGR

CYP DNK

FIN

FRA

DEUGRCHUN

IRL

ITANLD

NOR

POL PRT

ROM

ESP

SWE

CHEGBR

BGD

LKACHNIND

IDN

IRN

IRQ

ISR

JPNJORKOR

MYS

OMN

PAK

PHL

SAU

SYR

THA

TUR

AUSNZL

PNG

ARG

BOL

BRA

CAN

CHL

COL

CRI

DOM

ECU

SLVGTM

GUY

HTI

HND

JAM MEX

NIC

PANPRY

PER

TTO

USA

URYVEN

-2.7

-1.8

-.9

0

.9

1.8

2.7

-2.7 -1.8 -.9 0 .9 1.8 2.7

Log

per-c

apita

light

inte

nsity

(sta

ndar

dize

d)

Log GDP per capita in 1992-2012 (standardized)B





Phenotypes

Migratory Distance from East Africa vs. Genetic Diversity

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


Genetic Diversity 417.003*** 300.978*** 361.421**(90.909) (76.371) (121.429)

Genetic Diversity Sqr. -306.218*** -241.755*** -268.515***(68.308) (61.099) (87.342)

Migratory Distance 0.463*** -0.003(0.142) (0.178)

Migratory Distance Sqr. -0.021*** -0.010(0.006) (0.009)

Mobility Index 0.353** 0.051(0.127) (0.154)

Mobility Index Sqr. -0.012*** -0.003(0.004) (0.006)

Observations 18 18 18 18 18

R-squared 0.43 0.30 0.30 0.47 0.43

P-value for:Joint Sig. of Diversity and its Sqr. 0.006 0.027Joint Sig. of Distance and its Sqr. 0.320Joint Sig. of Mobility and its Sqr. 0.905

Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1.



Phenotypes

Addressing Endogenous Post-1500 Migrations

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

Full Non w/o Neo w/o Latin w/o Sub >0.97Sample OECD Europes America Sahara Indigenous

Dependent Variable is Log Income per Capita in 2000

Adjusted Diversity 277.342*** 271.979*** 261.367*** 412.222*** 264.805** 304.735**(70.232) (88.479) (70.533) (148.584) (111.365) (111.588)

Adjusted Diversity Sqr. -192.386*** -188.974*** -181.811*** -287.067*** -183.863** -213.389**(49.675) (62.096) (49.671) (101.906) (80.398) (77.255)

Log Adj. Time of NR 0.396* 0.390 0.355 0.518* 0.068 0.448*(0.233) (0.281) (0.231) (0.298) (0.442) (0.254)

Log % of Arable Land -0.183*** -0.236*** -0.201*** -0.189*** -0.211** -0.104(0.051) (0.060) (0.055) (0.050) (0.097) (0.061)

Log Absolute Latitude 0.009 -0.021 -0.025 -0.139 0.218 -0.074(0.108) (0.119) (0.111) (0.126) (0.242) (0.130)

Social Infrastructure 1.826*** 1.313** 1.416*** 2.044*** 1.585*** 1.311*(0.417) (0.579) (0.507) (0.545) (0.486) (0.716)

Ethnic Frac. -0.333 -0.437 -0.390 -0.752** 0.104 -0.044(0.280) (0.375) (0.300) (0.348) (0.408) (0.412)

% Population at Risk -0.502 -0.605 -0.591 -0.308 -0.425 -0.153of Malaria (0.351) (0.381) (0.370) (0.486) (0.581) (0.434)

% Population Living -0.319 -0.196 -0.302 -0.520** -0.528 -0.339in Tropical Zones (0.204) (0.239) (0.219) (0.252) (0.341) (0.312)

Optimal Diversity 0.721 0.720 0.719 0.718 0.720 0.714(0.083) (0.085) (0.015) (0.023) (0.180) (0.012)

Observations 109 83 105 87 71 37R-squared 0.90 0.82 0.89 0.93 0.86 0.98




Phenotypes

Regional Technological Frontiers

City & Modern Location Continent Sociopolitical Entity Period

Cairo, Egypt Africa Mamluk Sultanate 1500 CEFez, Morocco Africa Marinid Kingdom of Fez 1500 CELondon, UK Europe Tudor Dynasty 1500 CEParis, France Europe Valois-Orléans Dynasty 1500 CEConstantinople, Turkey Asia Ottoman Empire 1500 CEPeking, China Asia Ming Dynasty 1500 CETenochtitlan, Mexico Americas Aztec Civilization 1500 CECuzco, Peru Americas Inca Civilization 1500 CE

Cairo, Egypt Africa Fatimid Caliphate 1000 CEKairwan, Tunisia Africa Berber Zirite Dynasty 1000 CEConstantinople, Turkey Europe Byzantine Empire 1000 CECordoba, Spain Europe Caliphate of Cordoba 1000 CEBaghdad, Iraq Asia Abbasid Caliphate 1000 CEKaifeng, China Asia Song Dynasty 1000 CETollan, Mexico Americas Classic Maya Civilization 1000 CEHuari, Peru Americas Huari Culture 1000 CE

Alexandria, Egypt Africa Roman Empire 1 CECarthage, Tunisia Africa Roman Empire 1 CEAthens, Greece Europe Roman Empire 1 CERome, Italy Europe Roman Empire 1 CELuoyang, China Asia Han Dynasty 1 CESeleucia, Iraq Asia Seleucid Dynasty 1 CETeotihuacán, Mexico Americas Pre-classic Maya Civilization 1 CECahuachi, Peru Americas Nazca Culture 1 CE


Documents

The Biogeographical Roots of the Wealth of Nations …media.virbcdn.com/files/a0/82affe5ac0c70159-BerglasLecture-H.pdf · The Biogeographical Roots of the Wealth of Nations Oded Galor