University of Pittsburgh Out Of Africa Hypothesis Evolution Presentation

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The “Out of Africa” Hypothesis, Human Genetic Diversity, and Comparative Economic
Development
Authors Quamrul Ashraf and Oded Galor presented a research study that tries to explain
socio-economic differences between countries based on genetic diversity. They propose and test
two hypotheses that analyze two different periods: before 1500 CE and after 1500 CE. The data
used for evaluating the proposal before 1500 CE is limited to only 21 countries, while the data
used to test the second period includes more than 100. The authors claim that both extremes are
detrimental to economical development; too much diversity or too little diversity hinder income
per capita.
The Authors
Oded Galor is an Israeli American professor of economics in Brown University, and he
developed the Unified Growth Theory that tries to explain how economic development and
inequality are tied to human history and evolutionary processes (Galor, 2022). This article is part
of a broader study about how modern economic development has been influenced by historic and
genetic factors. It explains why some countries have been able to successful foster innovation
and economic development while others haven’t regardless of sharing similar natural resources.
His latest book summarizes his proposal and is titled The Journal of Humanity, The Origins of
Wealth and Inequality. Quamrul Ashraf is a professor at Williams University. He was a student
of Oded Galor at Brown University and has collaborated with him in several publications
regarding economic growth and development and economic demography (Williams University,
2022).
Proposed Hypothesis
The authors claim that prehistoric immigrations of Homo Sapiens out of Africa and the
migratory distance affected the diversity of populations and in diversity affected economic
development. From an empirical point of view, different continents and regions show dissimilar
economic development and a way to explain these differences is through genetic diversity. The
authors claim that genetic factors dating thousands of years ago significantly influence
contemporary economic development. When a society is extremely diverse, there are factors that
hinder economic development like mutual distrust between its members. On the other hand,
when a society is extremely homogenous from a genetic point of view, innovation is rare. The
two extremes are represented by populations in South America (low genetic diversity) and Africa
(high genetic diversity).
The two premises that serve as basis for this research are that longer migratory distances
from Africa reduce genetic diversity and that there is an optimal level of diversity that fosters
economic development. The first premise is based on the Human Genome Diversity Project that
show that there is a relationship between the degree of heterozygosity (genetic diversity) of
populations within a country and the migratory distance away from East Africa. The following
graph shows this relationship and was presented by the authors. We can notice that African
countries are extremely diverse while American countries are less diverse. The migratory
distance does not follow straight aerial distances but follow migratory patterns. Since Homo
Sapiens entered the Americas through the Bering Strait, the distance travelled is the longest.
Literature Background
I started this report by analyzing the work of the authors which is very extensive reading
this specific subject. This research is based on the Human Genome Diversity Project that shows
how genetic diversity decreases as human migrant populations got farther away from Africa.
These results were also provided by a genetic studied carried out by Ramachandran et al. in 2005
called “Support from the Relationship of Genetic and Geographic Distance in Human
Populations for a Serial Founder Effect Originating in Africa” which was published by the
Proceedings of the National Academy of Sciences. Research carried out by other genetics also
support this claim Prugnolle et al., 2005, and Wang et al., 2007). The authors also build upon
their previous research, since this was a topic that they have analyzed extensively over the years.
There is extensive research about how geography and strong institutions affect economic
development that have been carried out over the years and helped the authors identify adjusting
factors. Other adjusting factors that have been researched in the past are differences in
linguistics, sociocultural factors, and human capital formation. A paper that studied similar
relationships between genetic diversity affecting economic development was presented by
Spolaore and Wacziarg in 2009 and was titled “The Diffusion of Development” which was
published by the Quarterly Journal of Economics. This work proposes that genetic distance
between populations create barriers to technological innovations. This study includes more
factors than just technological innovations, since Spolaore and Wacziarg’s study was too narrow.
Another unicausal hypothesis was proposed by Jared Diamond in 1997 in Guns, Gems and Steel:
The Fates of Human Societies. Diamond’s research focused on factors that affect economic
development occurring thousands of years ago, but that cannot explain events after 1500 CE.
Research: up to 1500 CE
This research was divided into two parts, one covering a period before 1500 CE and the
second part covering the period after 1500 CE. Since the Americas were colonized by European
settlers after the arrival of Christopher Columbus, that changed the genetic diversity of the
region. There are two forces that conflict each other regarding genetic diversity within a
population, innovation vs reduced cooperation and efficiency. High diversity leads to higher
innovation and more economically productive technologies can be developed, but high diversity
also leads to lower cooperation and overall efficiency. This is the reason why regions that are
located in the middle of the graph developed more before 1500 CE.
If we look at the middle of the graph, we will find Asian countries and they were the
birthplace of human civilization and China was for centuries the richest and most prosperous
country in the world. From a historical point of view, this changed after European colonization
started to occur in the 16th century. Agricultural development was the major economic driving
force before 1500 CE and more agricultural productivity resulted in higher population density.
Higher population density is not necessarily linked to a richer population.
The authors developed a linear regression considering how genetic diversity affected
agricultural productivity and therefore affected population density. They established a statistical
relationship that claims that increasing genetic diversity by 1% to the least diverse populations
would increase population density by 58%. On the other hand, decreasing genetic diversity by
1% to the most diverse populations would have increased population density by 23%. The
research also considers how these factors change over time since some geographical regions
might have been very productive from an agricultural point of view, increasing diversity; but as
their economies grew, so did their military power, which eventually hindered future migration.
The problem with this part of the research is that there is limited accurate information about
genetic diversity and populations prior to 1500 CE. The authors were able to use information
from only 21 countries.
When the authors extended their research to a larger sample of countries using predictive
statistics, the results were similar, and they were able to identify an optimum index of
heterozygosity at 0.683. A 1% increase in diversity to the least diverse populations would have
increased population density by 36%, while a 1% decrease in diversity to the most diverse
populations would have increased population density by 29%. The authors also found statistical
evidence to claim that a 1% deviation form the optimal diversity of 0.683 would result in a
decrease in population density of 1.5%.
The statistical model behind this first part shows how agricultural productivity is affected
by genetic diversity. Since genetic diversity creates both favorable and unfavorable effects on
productivity, the possibility of new technologies increased the level of productivity while lack of
cooperation resulting from high diversity decreases productivity. Since extreme factors tend to
offset the other, the regions that had an intermediate level of diversity were able to maximize the
output per worker.
This sounds logical especially since history shows us that populations with an
intermediate level of diversity were able to form structured societies and civilizations before.
This is not only limited to Sumerian civilization but also applies to China, India, Greece, and
Rome. Later on, populations with an intermediate level of genetic diversity continued to develop
in Europe and Asia, which yielded favorable conditions for later economic development.
Even though this argument is backed by historical events, it has some flaws. Genetic
diversity was very low in the Americas, but two vast empires also developed there. The Aztec
Empire had a population of over 5 million people in Mexico before it was conquered by Spanish
conquistadors in 1519 (University of Idaho, 2022) and the Inca Empire had a population of more
than 12 million in 1532 before the Spanish conquistadors ravaged it (Encyclopedia Britannica,
2022). It is impossible to infer how the Aztec and Incan empires would have developed if they
hadn’t been destroyed by Spain, but the fact is that they existed and had large cities while having
a very low genetic diversity.
Research: after 1500 CE
The second part of this research analyzes modern economic development, especially
technological innovations that have allowed countries to have a robust and solid economy with
high GDP per capita without relying solely on the extraction of natural resources. Information
was available for 109 countries, and it covers the period after 1500 CE, but focuses mostly on
economic development of the last century. The following graph was presented by the authors,
and we can again find countries with higher GDP per capita near the middle of the graph. It is
not as clear as the previous graph, but some notable examples of countries with high economic
development that are located in the middle area are the United States, New Zealand, Austria, etc.
High degrees of genetic diversity again tend to foster innovation but also result in
negative effects of lack of cooperation and lower efficiency. Low degrees of genetic diversity
result in high cooperation but low technological innovations. This is why intermediate levels
yield the highest results from an economic point of view and increase GDP per capita. For
example, Bolivia is the most homogenous country regarding genetic diversity but also has a very
low GDP per capita. Statistical regression suggests that increasing genetic diversity by 1% in
Bolivia would raise GDP per capita by 41%. Ethiopia is located on the other extreme with the
degree of genetic diversity and an even lower GDP per capita. Decreasing genetic diversity in
Ethiopia by 1% should increase GDP per capita by 21%. The optimum level of diversity was
also calculated, and it is 0.721, which resembles the diversity level of the Untied States. The
United States is the largest economy in the world and the most innovative country. If Bolivia’s
degree of diversity increased to match the level of diversity of the United States, its GDP per
capita would increase by a factor of 5.4 (or 540%). This would reduce inequality between
Bolivia and the United States from the current ratio of 12:1 to 2.2:1. On the other hand,
decreasing Ethiopia’s degree of diversity so that it matches the level of the United States, then its
GDP per capita could increase by a factor of 1.7, reducing inequality for the current level of 47:
to 27:1. We can notice that the positive effects of increasing diversity in low diversity countries
results in proportionally higher benefits. Another result obtained from the regression analysis
shows that deviating the current level of diversity in the United States by 1% will result in a
decrease of 1.9% in the GDP per capita.
Statistical analysis was adjusted to reduce the effects of abundant natural resources like
oil which have resulted in high GDP per capita in Arab countries but at the same time economic
development is not high. Other factors that were adjusted are institutions, social infrastructure,
certain endemic diseases, etc. The regression formula used is more complex than the one used in
the first part since this time the number of countries including is much larger, resulting in a
stronger correlation. The factors used to forecast economic development include how genetic
diversity affects timing and land productivity (since countries with higher population density had
a head start after 1500 CE), institutional and cultural controls, geographic controls, and countryspecific disturbance factors.
Again, there are some notable cases that can be studied, and I want to focus on what
happened to Argentina. Argentina had the highest GDP per capita in 1895 when its European
population was increasing, and the native American population was virtually exterminated
(Etchebarne, 2020). This seems to support the theory proposed by the authors since increasing
genetic diversity in a population with a very low initial genetic diversity did foster economic
growth. Argentina continued to receive immigrants from different backgrounds, mostly Italians,
Spaniards, French, and German. It also hosts the largest Jewish population (as a percentage) after
Israel, and there is also a significant Muslim population. But starting approximately 70 years
ago, Argentina’s economy started to sink. Currently, the racial distribution is over 90% European
descendants, mostly from the previously stated countries (World Population Review, 2022). But
did the country become too genetically diverse? Is it possible that having too many different
European backgrounds plus certain Middle Eastern and native population pockets distanced the
country from the optimum diversity level? Argentina is a very strange case in economics since it
represents the only country that went from a developing nation to a rich nation (the richest
actually) and back to a developing nation. This doesn’t necessarily contradict the authors’ theory,
instead, I believe that it supports it. While Argentina’s population became more European, it
grew and hosted some of the most brilliant innovators. But as European diversity increased, there
is the possibility that institutional and cultural controls started to fail and that resulted in a
decrease of productivity and lower economic development.
Conclusions and Personal Remarks
This research provides evidence that genetic diversity is both beneficial and costly when
it comes to economic development. Too much or too little diversity tend to hinder GDP per
capita, while intermediate levels tend to improve it. It explains why a country like the United
States, which is diverse, but not too diverse, has been able to develop economically and it
became the world’s largest economy and most innovative country. While African countries with
a very high degree of genetic diversity have been constantly involved in internal disputes (lack of
cooperation) that have hurt them economically. Other countries with a low degree of genetic
diversity, like some Asian or Latin American countries, have failed to promote innovation and
technological breakthroughs. The authors adjusted several factors in their mathematical
calculations, and they yield constant results.
Personally, I think that this is a good starting point for a deeper understanding of how
genetic factors and diversity affect economic development. There are some notable exceptions to
this proposal like the Aztecs or the Incas, or Argentina in more modern times, but sometimes
exceptions make the rule. It is possible that a certain level of diversity is necessary to foster
innovation, and we can notice it in the United States by looking at some of the most brilliant
entrepreneurs of our time including Steve Jobs (born in Syria), Elon Musk (born in South
Africa), Sergei Brin (born in Russia), Jeff Bezos (Latin family), Mark Zuckerberg (Jewish
descendant), etc. I think that diversity fosters creativity, but in order for creativity to yield
significant innovations, certain society’s institutions must exist. American entrepreneurial spirit
has attracted immigrants for more than 100 years. Certain values of American society also
influence economic development positively, like tolerance for failure which is absolutely
necessary for success stories to exist. Another aspect to be considered is how certain cultural
values affect a country’s economy and why former British colonies became so wealthy. I believe
that this study should be extended to include other factors that combined with genetic diversity
help countries to develop economically.
References
Diamond, J.-. (2005). Guns, Germs & Steel. W W Norton & Company.
Encyclopedia Britannica. (2022). Inca | History, Achievements, Culture, & Geography.
https://www.britannica.com/topic/Inca
Etchebarne, C. (2020, April 16). In 1895 Argentina Had the World’s Highest GDP Per Capita:
What Went Wrong? Libertad y Progreso.
https://www.libertadyprogreso.org/en/2018/04/15/in-1895-argentina-had-the-worldshighest-gdp-per-capita-what-went-wrong/
Galor, O. (2022). Professor Oded Galor. Oded Galor. https://www.odedgalor.com/
Ramachandran, S., Deshpande, O., Roseman, C. C., Rosenberg, N. A., Feldman, M. W., &
Cavalli-Sforza, L. L. (2005). Support from the relationship of genetic and geographic
distance in human populations for a serial founder effect originating in Africa.
Proceedings of the National Academy of Sciences, 102(44), 15942–15947.
https://doi.org/10.1073/pnas.0507611102
Spolaore, E., & Wacziarg, R. (2009). The Diffusion of Development*. Quarterly Journal of
Economics, 124(2), 469–529. https://doi.org/10.1162/qjec.2009.124.2.469
University of Idaho. (2022). Aztec Empire in 1519.
https://webpages.uidaho.edu/engl257/Ren/aztec_empire_in_1519.htm#:%7E:text=Aztec
%20Empire%20in%201519%3A%20c,5%20Million%20people.
Williams University. (2022). Quamrul H. Ashraf. https://econ.williams.edu/profile/qha1/
World Population Review. (2022). Argentina Population 2022 (Demographics, Maps, Graphs).
https://worldpopulationreview.com/countries/argentina-population
American Economic Review 2013, 103(1): 1–46
http://dx.doi.org/10.1257/aer.103.1.1
The “Out of Africa” Hypothesis, Human Genetic Diversity,
and Comparative Economic Development†
By Quamrul Ashraf and Oded Galor*
This research advances and empirically establishes the hypothesis
that, in the course of the prehistoric exodus of Homo sapiens out of
Africa, variation in migratory distance to various settlements across
the globe affected genetic diversity and has had a persistent humpshaped effect on comparative economic development, reflecting the
trade-off between the beneficial and the detrimental effects of diversity
on productivity. While the low diversity of Native American populations and the high diversity of African populations have been detrimental for the development of these regions, the intermediate levels of
diversity associated with European and Asian populations have been
conducive for development. (JEL N10, N30, N50, O10, O50, Z10)
Prevailing hypotheses of comparative economic development highlight various
determinants of the remarkable inequality in income per capita across the globe. The
significance of geographical, institutional, and cultural factors, human capital, ethnolinguistic fractionalization, colonialism, and globalization has been at the heart of
a debate concerning the genesis of the astounding transformation in the pattern of
comparative development over the past few centuries. While early research focused
on the proximate forces that contributed to the divergence in living s­tandards in
the post–Industrial Revolution era, attention has shifted gradually toward some
* Ashraf: Department of Economics, Williams College, 24 Hopkins Hall Dr., Williamstown, MA 01267 (e-mail:
Quamrul.H.Ashraf@williams.edu); Galor: Department of Economics, Brown University, 64 Waterman St., Providence,
RI 02912 (e-mail: Oded_Galor@brown.edu). The authors are grateful to five anonymous referees, Alberto Alesina,
Kenneth Arrow, Alberto Bisin, Dror Brenner, John Campbell, Kenneth Chay, Steve Davis, Andrew Foster, David
Genesove, Douglas Gollin, Sergiu Hart, Saul Lach, Ross Levine, Anastasia Litina, Nathan Nunn, Ola Olsson, Mark
Rosenzweig, Antonio Spilimbergo, Enrico Spolaore, Alan Templeton, Romain Wacziarg, and David Weil; seminar
participants at Aix-Marseille, Bar-Ilan, Barcelona, Ben-Gurion, Brown, Boston College, Chicago GSB, Copenhagen,
Doshisha, Groningen, Haifa, Harvard, Hebrew U., Hitotsubashi, the IMF, Keio, Kyoto, Luxembourg, MIT, Osaka,
Porto, Princeton, St. Gallen, Sciences Po, Tel Aviv, Tokyo, Tufts, UCLA Anderson, UPF, Williams, the World Bank,
Yale, and Zurich; and conference participants of the CEPR EHRTN Summer Workshop on From Stagnation to Growth:
Unified Growth Theory in Florence, the second Annual Conference on Macroeconomics across Time and Space
at the Philadelphia Fed, the Korean Economic Association’s International Employment Forum in Seoul, the SED
Annual Meeting, the NBER Summer Institute, the NBER Political Economy Group Meeting, the fourth Migration
and Development Conference at Harvard, the ninth IZA Annual Migration Meeting, the MOVE Workshop on Social
Economics in Barcelona, the eighth BETA Workshop in Historical Economics in Strasbourg, and the International
Conference on Intergenerational Transmission of Entrepreneurship, Occupation, and Cultural Traits in the Process of
Long-Run Economic Growth in Naples for helpful comments and suggestions. The authors also thank attendees of the
Klein Lecture, the Kuznets Lecture, and the Maddison Lecture, and they are especially indebted to Yona Rubinstein
for numerous insightful discussions and to Sohini Ramachandran for sharing her data. Desislava Byanova and Daniel
Doran provided excellent research assistance. Financial support from the Watson Institute for International Studies
and the Population Studies and Training Center (PSTC) at Brown University is gratefully acknowledged. The PSTC
receives core support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development
(5R24HD041020). Ashraf’s research is supported by a Hellman Fellows Grant through Williams College. Galor’s
research is supported by National Science Foundation (SES-0921573).
†
To view additional materials, visit the article page at http://dx.doi.org/10.1257/aer.103.1.1.
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THE AMERICAN ECONOMIC REVIEW
february 2013
ultimate, deep-rooted, prehistoric factors that may have affected the course of comparative development since the emergence of human civilization.
This research argues that deep-rooted factors, determined tens of thousands of
years ago, have had a significant effect on the process of economic development
from the dawn of humankind to the contemporary era. It advances the hypothesis
that, in the course of the exodus of Homo sapiens out of Africa, variation in migratory distance from the cradle of humankind in East Africa to various settlements
across the globe affected genetic diversity and has had a long-lasting hump-shaped
effect on the pattern of comparative economic development that is not captured by
geographical, institutional, and cultural factors.
Consistent with the predictions of the theory, the empirical analysis finds that the level
of genetic diversity within a society has a hump-shaped effect on development outcomes
in the precolonial as well as in the modern era, reflecting the trade-off between the beneficial and the detrimental effects of diversity on productivity. While the low degree of
diversity among Native American populations and the high degree of diversity among
African populations have been detrimental forces in the development of these regions,
the intermediate levels of genetic diversity prevalent among European and Asian populations have been conducive for development. This research thus highlights one of the
deepest channels in comparative development, pertaining not to factors associated with
the onset of complex agricultural societies as in the influential hypothesis of Diamond
(1997), but to conditions innately related to the very dawn of humankind itself.
The hypothesis rests upon two fundamental building blocks. First, migratory distance from the cradle of humankind in East Africa had an adverse effect on the
degree of genetic diversity within ancient indigenous settlements across the globe.
Following the prevailing hypothesis, commonly known as the serial founder effect,
it is postulated that, in the course of human expansion over planet Earth, as subgroups of the populations of parental colonies left to establish new settlements further away, they carried with them only a subset of the overall genetic diversity of
their parental colonies. Indeed, as depicted in Figure 1, migratory distance from
East Africa has an adverse effect on genetic diversity in the 53 ethnic groups across
the globe that constitute the Human Genome Diversity Cell Line Panel, compiled
by the Human Genome Diversity Project (HGDP) in collaboration with the Centre
d’Etudes du Polymorphisme Humain (CEPH).
Second, there exists an optimal level of diversity for each stage of economic development, reflecting the interplay between the opposing effects of diversity on the development process. The adverse effect pertains to the detrimental impact of diversity on
the efficiency of the aggregate production process. Heterogeneity raises the likelihood of disarray and mistrust, reducing cooperation and disrupting the socioeconomic
order. Higher diversity is therefore associated with lower productivity, which inhibits
the capacity of the economy to operate efficiently relative to its production possibility frontier. The beneficial effect of diversity, on the other hand, concerns the positive
role of heterogeneity in the expansion of society’s production possibility frontier. A
wider spectrum of traits is more likely to contain those that are complementary to the
advancement and successful implementation of superior technological paradigms.1
1
The following two mechanisms further illustrate this argument. First, in an economy where the labor force is
characterized by heterogeneity in a wide array of traits, to the extent that some of these traits lead to specialization in
VOL. 103 NO. 1
Ashraf and Galor: Diversity and Development
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Expected heterozygosity
0.75
0.7
0.65
0.6
Africa
Middle East
Europe
Asia
Oceania
Americas
0.55
0
5
10
15
20
25
Migratory distance from East Africa (in thousand km)
Figure 1. Expected Heterozygosity and Migratory Distance from East Africa
Note: This figure depicts the negative impact of migratory distance from East Africa on expected heterozygosity
(genetic diversity) across the 53 ethnic groups that constitute the HGDP-CEPH Human Genome Diversity Cell
Line Panel.
Higher diversity t­herefore enhances society’s capability to integrate advanced and
more efficient production methods, expanding the economy’s production possibility
frontier and conferring the benefits of improved productivity.
Higher diversity in a society’s population can therefore have conflicting effects
on the level of its productivity. Aggregate productivity is enhanced on the one hand
by an increased capacity for technological advancement while diminished on the
other by reduced cooperation and efficiency.2 Further, if the beneficial effects of
population diversity dominate at lower levels of diversity and the detrimental effects
prevail at higher ones (i.e., if there are diminishing marginal returns to both diversity
and homogeneity), the theory would predict a hump-shaped effect of genetic diversity on productivity throughout the development process.
The hypothesized channels through which genetic diversity affects aggregate
productivity follow naturally from separate well-established mechanisms in the
field of evolutionary biology and experimental evidence from scientific studies on
organisms that display a relatively high degree of social behavior in nature (e.g.,
living in task-directed hierarchical societies and engaging in cooperative r­earing
task-oriented activities, higher diversity will increase productivity for society as a whole, given complementarities
across different tasks. Second, in an environment in which only individuals with sufficiently high levels of cognitive abilities can contribute to technological innovation, greater variance in the distribution of these traits across the
population will lead to higher productivity.
2
This hypothesis is consistent with evidence on the costs and benefits associated with intrapopulation heterogeneity, primarily in the context of ethnic diversity, as reviewed by Alesina and La Ferrara (2005).
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THE AMERICAN ECONOMIC REVIEW
february 2013
of offspring).3 The benefits of genetic diversity, for instance, are highlighted in the
Darwinian theory of evolution by natural selection, according to which diversity,
by permitting the forces of natural selection to operate over a wider spectrum of
traits, increases the adaptability and, hence, the survivability of a population under
changing environmental conditions.4 On the other hand, to the extent that genetic
diversity is associated with a lower average degree of relatedness among individuals in a population, kin selection theory, which emphasizes that cooperation among
genetically related individuals can indeed be collectively beneficial as it ultimately
facilitates the propagation of shared genes to the next generation, is suggestive of
the hypothesized mechanism through which diversity confers costs on aggregate
productivity.
Population geneticists typically measure the extent of diversity in genetic material across individuals within a given population (such as an ethnic group) using an
index called “expected heterozygosity.” Like most other measures of diversity, this
index may be interpreted simply as the probability that two individuals, selected
at random from the relevant population, differ genetically from one another with
respect to a given spectrum of traits. Specifically, the expected heterozygosity
measure for a given population is constructed by geneticists using sample data on
allelic frequencies; i.e., the frequency with which a gene variant or allele (e.g., the
brown versus blue variant for the eye color gene) occurs in the population sample.
Given allelic frequencies for a particular gene or DNA locus, it is possible to compute a gene-specific heterozygosity statistic (i.e., the probability that two randomly
selected individuals differ with respect to the gene in question), which when averaged over multiple genes or DNA loci yields the overall expected heterozygosity for
the relevant population.
The most reliable and consistent data for genetic diversity among indigenous populations across the globe consists of 53 ethnic groups from the HGDP-CEPH Human
Genome Diversity Cell Line Panel. According to anthropologists, these groups are
not only historically native to their current geographical locations but have also
been isolated from genetic flows from other ethnic groups. Empirical evidence provided by population geneticists (e.g., Ramachandran et al. 2005) for these 53 ethnic
groups suggests that, indeed, migratory distance from East Africa has an adverse
linear effect on genetic diversity as depicted in Figure 1. Migratory distance from
East Africa for each of the 53 ethnic groups was computed using the great circle (or
geodesic) distances from Addis Ababa, Ethiopia to the contemporary geographical
coordinates of these ethnic groups, subject to five obligatory intermediate waypoints
(i.e., Cairo, Egypt; Istanbul, Turkey; Phnom Penh, Cambodia; Anadyr, Russia; and
Prince Rupert, Canada) that capture paleontological and genetic evidence on prehistoric human migration patterns.
Nonetheless, while the existing data on genetic diversity pertain only to ethnic
groups, data for examining comparative development are ty