Exodus Of Homo Sapiens From Africa And Genetic Diversity May Explain Economic Growth Divergence Across Continents

Quamrul Ashraf, and Oded Galor.

Abstract.

This paper argues that deep-rooted factors, determined tens of thousands of years ago, had a significant effect on the course of economic development from the dawn of human civilization to the contemporary era. It advances and empirically establishes the hypothesis that, in the course of the exodus of Homo sapiens out of Africa, variation in migratory distance from the cradle of humankind to various settlements across the globe affected genetic diversity, and has had a long-lasting effect on the pattern of comparative economic development that is not captured by geographical, institutional, and cultural factors.

The level of genetic diversity within a society is found to have a hump-shaped effect on development outcomes in the pre-colonial era, reflecting the trade-off between the beneficial and the detrimental effects of diversity on productivity. Moreover, the level of genetic diversity in each country today (as determined by the genetic diversities and genetic distances amongst its ancestral populations), has a non-monotonic effect on income per capita in the modern world. While the intermediate level of genetic diversity prevalent among Asian and European populations has been conducive for development, the high degree of diversity among African populations and the low degree of diversity among Native American populations have been a detrimental force in the development of these regions.

Introduction

Existing theories of comparative development highlight a variety of proximate and ultimate factors underlying some of the vast inequities in living standards across the globe. The importance of geographical, cultural and institutional factors, human capital formation, ethnic, linguistic, and religious fractionalization, colonialism and globalization has been at the center of a debate regarding the origins of the differential timing of transitions from stagnation to growth and the remarkable transformation of the world income distribution in the last two centuries. While theoretical and empirical research has typically focused on the effects of such factors in giving rise to and sustaining the Great Divergence in income per capita in the pre-industrial era, attention has recently been drawn towards some deep-rooted factors that have been argued to affect the course of comparative economic development.

This paper thus highlights one of the deepest channels in comparative development, pertaining not to factors associated with the dawn of complex agricultural societies as in Diamond’s (1997) influential hypothesis, but to conditions innately related to the very dawn of mankind 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, 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.

Second, there exists an optimal level of diversity for economic development, reflecting the interplay between the conflicting 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 of an economy. Heterogeneity increases the likelihood of mis-coordination and distrust, reducing cooperation and disrupting the socioeconomic order. Greater population diversity is therefore associated with the social cost of a lower total factor productivity, which inhibits the ability of society to operate efficiently with respect to its production possibility frontier.

The beneficial effect of diversity, on the other hand, concerns the positive role of diversity in the expansion of society’s production possibility frontier. A wider spectrum of traits is more likely to be complementary to the development and successful implementation of advanced technological paradigms. Greater heterogeneity therefore fosters the ability of a society to incorporate more sophisticated and efficient modes of production, expanding the economy’s production possibility frontier and conferring the benefits of increased total factor productivity.

Higher diversity in a society’s population can therefore have conflicting effects on the level of its total factor productivity. Aggregate productivity is enhanced on the one hand by an increased capacity for technological advancement, while simultaneously diminished on the other by reduced cooperation and efficiency. However, if the beneficial effects of population diversity dominate at lower levels of diversity and the detrimental effects dominate at higher levels (i.e., if there are diminishing marginal returns to both diversity and homogeneity), the theory would predict an inverted-U relationship between genetic diversity and development outcomes over the course of the development process.

In estimating the impact on economic development of migratory distance from East Africa via its effect on genetic diversity, this research overcomes limitations and potential concerns that are presented by the existing data on genetic diversity across the globe (i.e., measurement error, data limitations, and potential endogeneity). 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, are genetically different from one another. 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 vs. 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, however, of only 53 ethnic groups from the Human Genome Diversity Cell Line Panel. According to anthropologists, these groups are not only historically native to their current geographical location 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 suggest that, indeed, migratory distance from East Africa has an adverse linear effect on genetic diversity. 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 geographic coordinates of these ethnic groups, subject to 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 prehistorical human migration patterns.

Nonetheless, while the existing data on genetic diversity pertain only to ethnic groups, data for examining comparative development are typically available at the country level. Moreover, many national populations today are composed of multiple ethnicities, some of which may not be indigenous to their current geographical locations. This raises two complex tasks. First, one needs to construct a measure of genetic diversity for national populations, based on genetic diversity data at the ethnic group level, accounting for diversity not only within each component group but for diversity due to differences between ethnic groups as well. Second, it is necessary to account for the potential inducement for members of distinct ethnic groups to relocate to relatively more lucrative geographical locations.

To tackle these difficulties, this study adopts two distinct strategies. The first restricts attention to development outcomes in the pre-colonial era when, arguably, regional populations were indigenous to their current geographical location and largely homogenous in terms of their ethnic compositions, with the presence of multiple indigenous ethnicities in a given region having a negligible effect on the diversity of the regional population. The second, more complex strategy involves the construction ofan index of genetic diversity for contemporary national populations that accounts for the expected heterozygosity within each sub-national group as well as the additional component of diversity at the country level that arises from the genetic distances between its pre-colonial ancestral populations. The examination of comparative development under this second strategy would have to additionally account for the potential inducement for members of distinct ethnic groups to relocate to relatively more lucrative geographical locations.

The examination of comparative development in the pre-colonial era, when societies were in their agricultural stage of development, requires the interpretation of outcomes from a Malthusian equilibrium point of view. Improvements in the technological environment during the Malthusian epoch generated only temporary gains in income per capita, eventually leading to a larger, but not richer, population (Ashraf and Galor, 2010). Thus the relevant variable gauging comparative economic development during this era is population density as opposed to income per capita. In light of this argument, this study employs cross-country historical data on population density as the outcome variable of interest in the historical analysis and examines the hypothesized effect of human genetic diversity within societies on their population densities in the year 1500 CE.

Using data on genetic diversity observed at the ethnic group level, the historical analysis reveals, consistently with the proposed hypothesis, a highly significant hump-shaped effect of genetic diversity on log population density in the year 1500 CE. In particular, accounting for the influence of the timing of the Neolithic Revolution, the natural productivity of land for agriculture, as well as other geographical characteristics that may affect population density in the pre-industrial era, the estimated linear and quadratic coefficients associated with genetic diversity imply that a 1 percentage point increase in diversity for the least diverse society in the regression sample would raise its population density by 58%, whereas a 1 percentage point decrease in diversity for the most diverse society would raise its population density by 23%. Despite the statistical significance and robustness of these effects, however, the analysis is subsequently expanded upon to lend further credence to these findings by alleviating concerns regarding sample size limitations and potential endogeneity bias.

The issue of data limitations encountered by the analysis stems from the fact that diversity data at the ethnic group level currently spans only a modest subset of the sample of countries for which historical population estimates are available. The potential endogeneity issue, on the other hand, arises from the possibility that genetic diversity within populations could partly reflect historical processes such as interregional migrations that were, in turn, determined by historical patterns of comparative development. Furthermore, the direction of the potential endogeneity bias is a priori ambiguous. For example, while historically better developed regions may have been attractive destinations to potential migrants, serving to increase genetic diversity in relatively wealthier societies, the more advanced technologies in these societies may also have conferred the necessary military prowess to prevent or minimize foreign invasions, thereby reducing the likelihood of greater genetic diversity in their populations.

In surmounting the aforementioned data limitations and potential endogeneity issues, this research appeals to the “out of Africa” theory regarding the origins of Homo sapiens. According to this well-established hypothesis, the human species, having evolved to its modern form in East Africa some 150,000 years ago, thereafter embarked on populating the entire globe in a stepwise migration process beginning about 70,000–90,000 BP. Using archeological data combined with mitochondrial and Y-chromosomal DNA analysis to identify the most recent common ancestors of contemporary human populations, geneticists are able to not only offer evidence supporting the origin of humans in East Africa but also trace the prehistorical migration routes of the subsequent human expansion into the rest of the world. In addition, population geneticists studying human genetic diversity have argued that the contemporary distribution of diversity across populations should reflect a serial- founder effect originating in East Africa. Accordingly, since the populating of the world occurred in a series of stages where subgroups left initial colonies to create new colonies further away, carrying with them only a portion of the overall genetic diversity of their parental colonies, contemporary genetic diversity in human populations should be expected to decrease with increasing distance along prehistorical migratory paths from East Africa. Indeed, several studies in population genetics (e.g., Prugnolle et al., 2005; Ramachandran et al., 2005; Wang et al., 2007) have found strong empirical evidence in support of this prediction.

The present study exploits the explanatory power of migratory distance from East Africa for genetic diversity within ethnic groups in order to overcome the data limitations and potential endogeneity issues encountered by the initial analysis discussed above. In particular, the strong ability of prehistorical migratory distance from East Africa in explaining observed genetic diversity permits the analysis to generate predicted values of genetic diversity using migratory distance for countries for which diversity data are currently unavailable. This enables a subsequent analysis to estimate the e¤ects of genetic diversity, as predicted by migratory distance from East Africa, in a much larger sample of countries. Moreover, given the obvious exogeneity of migratory distance from East Africa with respect to development outcomes in the Common Era, the use of migratory distance to project genetic diversity alleviates concerns regarding the potential endogeneity between observed genetic diversity and economic development.

The main results from the historical analysis, employing predicted genetic diversity in the extended sample of countries, indicate that, controlling for the influence of land productivity, the timing of the Neolithic Revolution, and continental fixed effects, a 1 percentage point increase in diversity for the most homogenous society in the sample would raise its population density in 1500 CE by 36%, whereas a 1 percentage point decrease in diversity for the most diverse society would raise its population density by 29%. Further, a 1 percentage point change in diversity in either direction at the predicted optimum of 0.683 would lower population density by 1.5%.7

Moving to the contemporary period, the analysis, as discussed earlier, constructs an index of genetic diversity at the country level that not only incorporates the expected heterozygosities of the pre-Columbian ancestral populations of contemporary sub-national groups, as predicted by the migratory distances of the ancestral populations from East Africa, but also incorporates the pairwise genetic distances between these ancestral populations, as predicted by their pairwise migratory distances. Indeed, the serial-founder effect studied by population geneticists not only predicts that expected heterozygosity declines with increasing distance along migratory paths from East Africa, but also that the genetic distance between any two populations will be larger the greater the migratory distance between them.

The baseline results from the contemporary analysis indicate that the genetic diversity of contemporary national populations has an economically and statistically significant hump-shaped effect on income per capita. This hump-shaped impact of diversity on income per capita is robust to continental fixed effects, and to controls for ethnic fractionalization and various measures of institutional quality, including social infrastructure, an index gauging the extent of democracy, constraints on the power of chief executives, legal origins, major religion shares, and the share of the population of European descent, as well as to controls for years of schooling, disease environments, and other geographical factors that have received attention in the literature on cross-country comparative development.

The direct effect of genetic diversity on contemporary income per capita, once institutional, cultural, and geographical factors are accounted for, indicates that: (i) increasing the diversity of the most homogenous country in the sample (Bolivia) by 1 percentage point would raise its income per capita in the year 2000 CE by 39%, (ii) decreasing the diversity of the most diverse country in the sample (Ethiopia) by 1 percentage point would raise its income per capita by 21%, (iii) a 1 percentage point change in genetic diversity (in either direction) at the optimum level of 0.721 (that most closely resembles the diversity level of the U.S.) would lower income per capita by 1.9%, (iv) increasing Bolivia’s diversity to the optimum level prevalent in the U.S. would increase Bolivia’s per capita income by a factor of 4.7, closing the income gap between the U.S. and Bolivia from 12:1 to 2.5:1, and (v) decreasing Ethiopia’s diversity to the optimum level of the U.S. would increase Ethiopia’s per capita income by a factor of 1.7 and, thus, close the income gap between the U.S. and Ethiopia from 47:1 to 27:1.

Reassuringly, the highly significant and stable hump-shaped effect of genetic diversity on income per capita in the year 2000 CE is not an artifact of post-colonial migrations towards prosperous countries and the concomitant increase in ethnic diversity in these economies. The hump-shaped effect of genetic diversity remains highly significant and the optimal diversity estimate remains virtually intact if the regression sample is restricted to (a) non-OECD economies (i.e., economies that were less attractive to migrants), (b) non Neo-European countries (i.e., excluding the U.S., Canada, New Zealand and Australia), (c) non-Latin American countries, (d) non Sub-Saharan African countries, and perhaps most importantly (e) to countries whose indigenous population is larger than 97% of the entire population (i.e., under conditions that virtually eliminate the role of migration in the creation of diversity).

Related Literature

The existing literature on comparative development has emphasized a variety of factors underlying some of the vast differences in living standards across the globe. The influence of geography, for instance, has been stressed from a historical perspective by Jones (1981), Diamond (1997), and Pomeranz (2000), and is highlighted empirically by Gallup et al. (1999) and Olsson and Hibbs (2005), amongst others. Institutions, on the other hand, are given historical precedence by North and Thomas (1973), Mokyr (1990), and Greif (1993), and are emphasized empirically by Hall and Jones (1999), La Porta et al. (1999), Rodrik et al. (2004), and Acemoglu et al. (2005). In related strands of the literature on institutions, Engerman and Sokolof (2000) and Acemoglu et al. (2005) have stressed the role of colonialism, while the e¤ects of ethno-linguistic fractionalization are examined by Easterly and Levine (1997), Alesina et al. (2003), and others. Meanwhile, the historical impact of sociocultural factors has been highlighted by Weber (1905) and Landes (1998), with empirical support coming from Barro and McCleary (2003), Tabellini (2008), as well as Guiso et al. (2009). Finally, the importance of human capital formation has been underlined in unified growth theory (e.g., Galor, 2010), and has been demonstrated empirically by Glaeser et al. (2004).

This research is the first to argue that the variation in prehistorical migratory distance from the cradle of humankind to various settlements across the globe has had a persistent effect on the process of development and on the contemporary variation in income per capita across the globe. The paper is also unique in its attempt to establish the role of genetic (rather than ethnic) diversity within a nation.

The employment of data and empirical results from the field of population genetics places this research in the neighborhood of a recent insightful paper in the economic literature by Spolaore and Wacziarg (2009) who have appealed to data on genetic distance between human populations to proxy for the effect of sociocultural differences between societies on the diffusion of economic development. Specifically, the authors argue that genetic distance between populations, which captures their divergence in biological and cultural characteristics over time, has been a barrier to the horizontal diffusion of technological innovations across populations. They show that Fst genetic distance, a measure that reflects the time elapsed since two populations shared a common ancestor, confers a statistically significant positive effect on both historical and contemporary pairwise income differences. In contrast, the genetic diversity metric within populations exploited by this paper facilitates the analysis of the effect of the variation in traits across individuals within a society on its development process.

Unlike Spolaore and Wacziarg (2009) where genetic distance between populations diminishes the rate of technological diffusion and reduces productivity, the hypothesis advanced and tested in this paper suggests that genetic diversity within a population confers both social costs, in the form of lower social capital arising from differences amongst individual members, and social benefits in the form of diversity-driven knowledge accumulation. Hence, the overall effect of genetic diversity on developmental outcomes would be hump-shaped, rather than monotonically negative. The results of the empirical analysis conducted in this study suggest that the previously unexamined beneficial effect of genetic differences is indeed a significant factor in the overall influence of the genetic channel on comparative development.

The examination of the effects of genetic diversity along with the influence of the timing of agricultural transitions also places this paper in an emerging strand of the literature that has focused on empirically testing Diamond’s (1997) assertion regarding the long-standing impact of the Neolithic Revolution.10 Diamond (1997) has stressed the role of biogeographical factors in determining the timing of the Neolithic Revolution, which conferred a developmental head-start to societies that experienced an earlier transition from primitive hunting and gathering techniques to the more technologically advanced agricultural mode of production. According to this hypothesis, the luck of being dealt a favorable hand thousands of years ago with respect to biogeographic endowments, particularly exogenous factors contributing to the emergence of agriculture and facili- tating the subsequent diffusion of agricultural techniques, is the single most important driving force behind the divergent development paths of societies throughout history that ultimately led to the contemporary global differences in standards of living. Specifically, an earlier transition to agriculture due to favorable environmental conditions gave some societies an early advantage by conferring the benefits of a production technology that generated resource surpluses and enabled the rise of a non-food-producing class whose members were crucial for the development of written language and science, and for the formation of cities, technology-based military powers and nation states. The early technological dominance of these societies subsequently persisted throughout history, being further sustained by the subjugation of less-developed societies through exploitative geopolitical and historical processes such as colonization.

While the long-standing influence of the Neolithic Revolution on comparative development remains a compelling argument, this research demonstrates that, contrary to Diamond’s (1997) uni- causal hypothesis, the composition of human populations with respect to their genetic diversity has been a significant and persistent factor that affected the course of economic development from the dawn of human civilization to the present. In estimating the economic impact of human genetic diversity while controlling for the channel emphasized by Diamond (1997), the current research additionally establishes the historical significance of the timing of agricultural transitions for pre- colonial population density, which, as already argued, is the relevant variable capturing comparative economic development during the Malthusian epoch of stagnation in income per capita.

The focus of the historical analysis on economic development in the pre-colonial Malthusian era also necessitates controls for the natural productivity of land for agriculture. Given that in a Malthusian environment resource surpluses are primarily channeled into population growth with per capita incomes largely remaining at or near subsistence, regions characterized by natural factors generating higher agricultural crop yields should, ceteris paribus, also exhibit higher population densities (Ashraf and Galor, 2010). If diversity in a society influences its development through total factor productivity (comprised of both social capital and technological know-how), then controlling for the natural productivity of land would constitute a more accurate test of the effect of diversity on the Malthusian development outcome – i.e., population density.

Concluding Remarks

**This paper is part of a broader research by Quamrul Ashraf Oded Galo entitled “THE “OUT OF AFRICA” HYPOTHESIS, HUMAN GENETIC DIVERSITY, AND COMPARATIVE ECONOMIC DEVELOPMENT.”

References

Acemoglu, Daron, Simon Johnson, and James A. Robinson, “Institutions as a Fundamental Cause of Long-Run Growth,” in Philippe Aghion and Steven N. Durlauf, eds., Handbook of Economic Growth, Vol IA, Amsterdam, The Netherlands: Elsevier North-Holland, 2005.

Alesina, Alberto and Eliana La Ferrara, “Ethnic Diversity and Economic Performance,” Journal of Economic Literature, September 2005, 43 (3), 762–800.

, Arnaud Devleeschauwer, William Easterly, Sergio Kurlat, and Romain Wacziarg, “Fractionalization,” Journal of Economic Growth, June 2003, 8 (2), 155–194.

Ashraf, Quamrul and Oded Galor, “Dynamics and Stagnation in the Malthusian Epoch,” 2010.

Working Paper, Department of Economics, Williams College.

, , and Ömer Özak, “Isolation and Development,” Journal of the European Economic Association, April-May 2010, 8 (2-3), 401–412.

Bairoch, Paul, Cities and Economic Development: From the Dawn of History to the Present, Trans. by Christopher Braider. Chicago, IL: The University of Chicago Press, 1988.

Barbujani, Guido, Arianna Magagni, Eric Minch, and L. Luca Cavalli-Sforza, “An Apportionment of Human DNA Diversity,” Proceedings of the National Academy of Sciences, April 1997, 94 (9), 4516–4519.

Barro, Robert J. and Rachel M. McCleary, “Religion and Economic Growth across Countries,”

American Sociological Review, October 2003, 68 (5), 760–781.

Cann, Howard M., Claudia de Toma, Lucien Cazes, Marie-Fernande Legrand, Valerie Morel, Laurence Piou¤re et al., “A Human Genome Diversity Cell Line Panel,” Science, April 2002, 296 (5566), 261–262.

Cavalli-Sforza, L. Luca, “The Human Genome Diversity Project: Past, Present and Future,”

Nature Reviews Genetics, April 2005, 6 (4), 333–340.

Conley, Timothy G., “GMM Estimation with Cross Sectional Dependence,” Journal of Econometrics, September 1999, 92 (1), 1–45.

Dalgaard, Carl-Johan and Holger Strulik, “The Physiological Foundations of the Wealth of Nations,” 2010. Discussion Paper No. 10-05, University of Copenhagen.

Desmet, Klaus, Michel Le Breton, Ignacio Ortuño-Ortín, and Shlomo Weber, “Nation Formation and Genetic Diversity,” 2006. CEPR Discussion Paper No. 5918.

Diamond, Jared, Guns, Germs and Steel: The Fates of Human Societies, New York, NY: W. W. Norton & Co., 1997.

, “Evolution, Consequences and Future of Plant and Animal Domestication,” Nature, August 2002, 418 (6898), 700–707.

Easterly, William and Ross Levine, “Africa’s Growth Tragedy: Policies and Ethnic Divisions,”

Quarterly Journal of Economics, November 1997, 112 (4), 1203–1250.

Engerman, Stanley L. and Kenneth L. Sokolo¤, “History Lessons: Institutions, Factor Endowments, and Paths of Development in the New World,” Journal of Economic Perspectives, Summer 2000, 14 (3), 217–232.

Gallup, John L. and Je¤rey D. Sachs, “The Economic Burden of Malaria,” The American

Journal of Tropical Medicine and Hygiene, January 2001, 64 (1-2), 85–96.

, , and Andrew D. Mellinger, “Geography and Economic Development,” International Regional Science Review, August 1999, 22 (2), 179–232.

Galor, Oded, “The 2008 Lawrence R. Klein Lecture–Comparative Economic Development: Insights from Uni…ed Growth Theory,” International Economic Review, February 2010, 51 (1), 1–44.

and Omer Moav, “Natural Selection and the Origin of Economic Growth,” Quarterly Journal of Economics, November 2002, 117 (4), 1133–1191.

and , “The Neolithic Revolution and Contemporary Variations in Life Expectancy,” 2007.

Working Paper, Department of Economics, Brown University.

Glaeser, Edward L., Rafael La Porta, Florencio Lopez-de-Silanes, and Andrei Shleifer, “Do Institutions Cause Growth?,” Journal of Economic Growth, September 2004, 9 (3), 271–

303.

Greif, Avner, “Contract Enforceability and Economic Institutions in Early Trade: The Maghribi Traders’ Coalition,” American Economic Review, June 1993, 83 (3), 525–548.

Gri¢ths, Anthony J. F., Je¤rey H. Miller, David T. Suzuki, Richard C. Lewontin, and William M. Gelbart, An Introduction to Genetic Analysis, New York, NY: W. H. Freeman

& Co., 2000.

Guiso, Luigi, Paola Sapienza, and Luigi Zingales, “Cultural Biases in Economic Exchange?,”

Quarterly Journal of Economics, August 2009, 124 (3), 1095–1131.

Hall, Robert E. and Charles I. Jones, “Why Do Some Countries Produce So Much More Output Per Worker Than Others?,” Quarterly Journal of Economics, February 1999, 114 (1), 83–116.

Jones, Eric L., The European Miracle: Environments, Economies and Geopolitics in the History of Europe and Asia, Cambridge, UK: Cambridge University Press, 1981.

La Porta, Rafael, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert W. Vishny, “The Quality of Government,” Journal of Law, Economics, and Organization, March 1999, 15 (1), 222–279.

Lagerlöf, Nils-Petter, “Long-Run Trends in Human Body Mass,” Macroeconomic Dynamics, June 2007, 11 (3), 367–387.

Landes, David S., The Wealth and Poverty of Nations: Why Some Are So Rich and Some So Poor, New York, NY: W. W. Norton & Co., 1998.

Macaulay, Vincent, Catherine Hill, Alessandro Achilli, Chiara Rengo, Douglas Clarke, William Meehan et al., “Single, Rapid Coastal Settlement of Asia Revealed by Analysis of Complete Mitochondrial Genomes,” Science, May 2005, 308 (5724), 1034–1036.

McEvedy, Colin and Richard Jones, Atlas of World Population History, New York, NY: Penguin Books Ltd., 1978.

Michalopoulos, Stelios, “The Origins of Ethnolinguistic Diversity: Theory and Evidence,” 2008.

Working Paper, Department of Economics, Tufts University.

Mokyr, Joel, The Lever of Riches: Technological Creativity and Economic Progress, New York, NY: Oxford University Press, 1990.

Murphy, Kevin M. and Robert H. Topel, “Estimation and Inference in Two-Step Econometric Models,” Journal of Business and Economic Statistics, October 1985, 3 (4), 370–379.