Students of comparative development have turned their focus to factors rooted deeper and deeper in history.

  • There is growing agreement that human and geographic factors inherited from eras as far removed as the Neolithic period still influence the wealth of nations today.
  • An early example of this hypothesis was Jared Diamond’s book Guns, Germs and Steel (1997), where he argued that geographic advantages from early human history still affect prosperity today.

Economists no longer focus exclusively on the proximate determinants of growth, such as capital accumulation or technology – they now study deeper causes rooted in long-term history. The debate today is not whether deep history matters, but why and through which mechanisms it operates to affect current outcomes.

Ancestors matter, but why?

An important insight from the recent empirical literature is that the history of populations is a much stronger predictor of current economic outcomes than the history of geographical locations. For example:

  • A long familiarity with organised modes of government and a long exposure to agriculture are good for economic development. But it is the history of a population that matters – more than the population’s location. The US is rich today because of the historical heritage of its European colonisers.

The deep history of North America matters much less (Putterman and Weil 2010; Comin, Easterly and Gong 2010).

  • The reversal of fortune – documented by Acemoglu, Johnson and Robinson (2002) at the level of geographic locations for former colonies – disappears when correcting for ancestry and expanding the sample beyond former colonies (Spolaore and Wacziarg 2013a; Chanda, Cook and Putterman 2013).

This once more suggests that development can be accounted for by factors that are transmitted from generation to generation.

  • A closely related literature argues that geography and biology affect current development because of long-term indirect effects, transmitted from one generation to the next, and going back to prehistoric times (Diamond 1997; Olsson and Hibbs 2005; Ashraf and Galor 2011, 2013).

Even though Jared Diamond’s well-known book Guns, Germs and Steel is often presented as a purely ‘geographic’ interpretation of comparative development, at its core is the historical transmission of biogeographic advantage – such as agricultural knowledge and resistance to germs – across generations. According to Diamond, early inhabitants of Eurasia passed those advantages on to their descendants, who then moved to dominate large parts of the rest of the world.

In sum, a central message of the recent research on comparative economic development is that history matters because historical factors that are more or less conducive to development are passed on from generation to generation along lines of ancestry.

But why does ancestry matter?

This is an old and still open question. In the past, much of the debate was focused on whether ancestors matter because of nature (the inheritance of biological traits) or nurture (for instance, the cultural transmission of work ethic or trust). The scientific community, however, has come to recognise that the dichotomy between nature and nurture is obsolete and reductive. As we pointed out in a recent discussion of this literature, people and societies inherit traits from their ancestors through a complex interaction of biological and cultural channels, with an essential role played by environmental factors (Spolaore and Wacziarg 2013a).

Relatedness and barriers to the spread of technologies

Much of the debate on the effects of inherited traits has been about modes of transmission (biological, cultural, or both), while less attention has been given to different modes of operation. How do inherited traits affect development? Most scholars in this literature have focused on direct effects – people in some societies inherit traits – say, work ethic or fertility preferences – that directly make them richer. Such direct effects, however, are only one possible channel, and not necessarily the most important one. Another key mechanism is that long-term divergence in inherited traits can create barriers to the diffusion of technologies and innovations. This is the focus of our own work.

In a series of papers, we argue that the intergenerational transmission of human traits – particularly culturally transmitted traits – has led to divergence between populations over the course of history (Spolaore and Wacziarg 2009, 2012, 2013a, 2013b). In turn, divergence has introduced barriers to the diffusion of technologies across societies. Such barriers impede the flow of technologies in proportion to how genealogically distant populations are from each other.

To measure the degree of relatedness between populations, we used genetic distance. Data on genetic distance was gathered by population geneticists specifically to trace genealogical linkages between world populations. Measures of average differences between vectors of allele frequencies (different genes) across any two populations provide a measure of genetic distance. Genetic distance has been shown to correlate with other measures of cultural differences such as linguistic distance and differences in answers to questions from the World Values Survey.

The goal of this approach is not to study any genetic characteristics that may confer any advantage in development. By design, the genes used to construct our measures of genealogical distance do not capture any such traits. On the contrary, they are neutral: their spread results from random factors and not from natural selection. For instance, neutral genes include those coding for different blood types, which did not confer a particular advantage or disadvantage to individuals carrying them during human evolutionary history. In general, the neutral genes on which genetic distance is based do not capture traits that are important for fitness and survival. Instead, genetic distance is like a molecular clock – it measures average separation times between populations. Therefore, genetic distance can be used as a summary statistic for divergence in all the traits that are transmitted with variation from one generation to the next over the long run, including divergence in cultural traits.

Our hypothesis

Our hypothesis is that, at a later stage, when populations enter into contact with each other, differences in those traits create barriers to exchange, communication, and imitation. These differences could indeed reflect traits that are mostly transmitted culturally and not biologically – such as styles of communication, norms of behaviour, values, and preferences.

We use these measures of genetic distance to test our model of technological diffusion (Spolaore and Wacziarg 2009, 2013b). Our barriers model implies that different development patterns across societies should depend not so much on the absolute genetic distance between them, but more on their relative genetic distance from the world’s technological frontier. For example, when studying the spread of the Industrial Revolution in Europe in the 19th century, what matters is not so much the absolute distance between the Greeks and the Italians, but rather how much closer Italians were to the English than the Greeks were. Indeed, we show that the magnitude of the effect of genetic distance relative to the technological frontier is about three times as large as that of absolute genetic distance. When including both measures in the regression, genetic distance relative to the frontier remains significant while absolute genetic distance becomes insignificantly different from zero. The effects are large in magnitude – a one-standard-deviation increase in genetic distance relative to the technological frontier (the US in the 20th century) is associated with an increase in the absolute difference in log income per capita of almost 29% of that variable’s standard deviation.

Our model implies that after a major innovation, such as the Industrial Revolution, the effect of genealogical distance should be pronounced, but that it should decline as more and more societies adopt the innovations of the technological frontier (which, in the 19th century, was the UK). These predictions are supported by the historical evidence. The figure below shows the standardised effects of genetic distance relative to the frontier for a common sample of 41 countries, for which data are available at all dates. The figure is consistent with our barriers model. As predicted, the effect of genetic distance – which is initially modest in 1820 – rises by around 75% to reach a peak in 1913, and declines thereafter.

Figure 1. Standardised effect of genetic distance over time, 1820-2005

Finally, our model implies that genetic distance should have predictive power at the level of disaggregated technologies. We find this to be the case both historically – when measuring technological usage on the extensive margin – and for more recent technological developments – measuring technological usage along the intensive margin. In sum, we find considerable evidence that barriers introduced by historical separation between populations are central to account for the world distribution of income.

Policy implications

These results have substantial policy implications. A common concern when studying the persistent effect of long-term history is that not much can be done today. But if a major effect of long-term historical divergence is due to barriers, there is much room and scope for policy action. Populations that are historically farther from the frontier can benefit from policies that specifically aim at reducing barriers to exchange and communication. Moreover, our findings suggest that the effects of long-term divergence in inherited traits – captured by genetic distance – are not fixed and immutable, but depend on dynamic factors (e.g. where the frontier is located), and do change (and decline) over time.

Ancestors matter, but they are not eternal destiny.


Acemoglu, Daron, Simon Johnson, and James A Robinson (2002), “Reversal of Fortune: Geography and Institutions in the Making of the Modern World Income Distribution”, Quarterly Journal of Economics 117(4): 1231–1294.

Ashraf, Quamrul and Oded Galor (2011), “Dynamics and Stagnation in the Malthusian Epoch”, The American Economic Review 101(5): 2003–2041.

Ashraf, Quamrul and Oded Galor (2013), “The ‘Out-of-Africa’ Hypothesis, Human Genetic Diversity, and Comparative Economic Development”, The American Economic Review 103(1): 1–46.

Putterman, Louis and David N Weil (2010), “Post-1500 Population Flows and the Long-Run Determinants of Economic Growth and Inequality”, Quarterly Journal of Economics 125(4): 1627–1682.

Chanda, Areendam, C Justin Cook, and Louis Putterman (2013), “Persistence of Fortune: Accounting for Population Movements, There Was No Post-Columbian Reversal”, Working paper, Brown University, February.

Comin, Diego, William Easterly and Erick Gong (2010), “Was the Wealth of Nations Determined in 1000 B.C.?”, American Economic Journal: Macroeconomics 2(3): 65–97.

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Olsson, Ola and Douglas A Hibbs, Jr (2005), “Biogeography and Long-Run Economic Development”, European Economic Review 49(4): 909–38.

Spolaore, Enrico and Romain Wacziarg (2009), “The Diffusion of Development”, Quarterly Journal of Economics 124(2): 469–529.

Spolaore, Enrico and Romain Wacziarg (2012), “Long-Term Barriers to the International Diffusion of Innovations”, in Jeffrey Frankel and Christopher Pissarides, eds., NBER International Seminar on Macroeconomics 2011, Chapter 1: 11-46, Chicago: University of Chicago Press.

Spolaore, Enrico and Romain Wacziarg (2013a), “How Deep Are the Roots of Economic Development?”, Journal of Economic Literature 51(2): 1–45.

Spolaore, Enrico and Romain Wacziarg (2013b), “Long-Term Barriers to Economic Development”, CEPR Discussion Paper 9638, September, forthcoming in Handbook of Economic Growth, Volume 2, edited by Philippe Aghion and Steven Durlauf, Amsterdam: Elsevier, 2014.

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