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Ancestry and culture

Cultural transmission occurs both vertically – from one generation to the next – and, increasingly in modern times, horizontally – within generations and across populations. Using novel data for 74 countries, this column explores how genetic relatedness between populations affects the transmission of cultural traits. A pattern of positive and significant relationships is found between genetic distance and various measures of cultural distance, including language, religion, values, and norms. This implies that populations that are ancestrally closer face lower barriers to learning new ideas and behaviours from each other.

The impact of cultural factors on economic and political outcomes is becoming a central focus of the social sciences. Within this growing literature, scholars have pursued two distinct but connected lines of research. One line is about the economic and political effects of cultural variables, such as language, religion, values and norms – an approach with a distinguished intellectual pedigree that has undergone a recent resurgence.1 The other line of research explores how ancestry and genetic relatedness between populations affect development, conflict and other outcomes.2

Vertical vs. horizontal transmission of culture

It is intuitive that these two lines of research should be linked, as cultural traits are typically transmitted with variation from one generation to the next, and most people learn their language and religious beliefs from their parents or other close relatives. Thus, we should expect a relationship between ancestry and culture. However, people sometimes do change their language, convert to a new religion, and adopt new norms and values because of migration, conquest, or the peaceful diffusion of cultural innovations. Anthropologists and scholars of evolution (for instance, Richerson and Boyd 2005) refer to the spread of new cultural traits within generations as horizontal transmission, to be distinguished from vertical transmission, which takes place across related generations.

Horizontal transmission and cultural change have always been important in human history, but they have become especially prominent in modern times, with the spread of new transportation and communication technologies across once isolated groups. Horizontal learning and change may weaken the links between a population’s current culture and the culture of its ancestors. Nonetheless, even in the presence of extensive horizontal exchanges, genealogical relatedness between different populations may still matter, because societies that share ancestral cultures and a common history face lower barriers to learn from each other and adopt each other's new ideas and novel patterns of behaviour. This is a theme that we discussed in a previous Vox column (see Spolaore and Wacziarg 2013b).

An important empirical question then is – to what extent do ancestry, language, and culture remain connected in contemporary times? Obtaining evidence on the connections between ancestry and culture sheds light on the extent of historical persistence over time and space. Perhaps more importantly, this research can help illuminate the mechanisms and channels through which vertical and horizontal transmission continue to interact and affect the spread of new technologies and modern behaviours – from industrialisation (Spolaore and Wacziarg 2009 and 2013b) to fertility decline (Spolaore and Wacziarg 2014).

Surprisingly, there has been little systematic research on this issue.3 In a recent paper we explored the interrelationships between various measures of ancestral relatedness, language, and culture across contemporary societies (Spolaore and Wacziarg 2015).

Genetic and memetic distances

Even more than in other empirical areas, a fundamental obstacle to the study of ancestry and culture is measurement. The issue is not only data availability, but, even more importantly, the conceptual definition of the key variables. How does one define and measure complex and multidimensional concepts such as relatedness, language, and culture?

In our work, we use two sets of measures. To measure the extent of common ancestry and relatedness between countries, we use genetic distance, which captures differences in gene distributions across populations. This measure is based on neutral genes that change randomly over time, and therefore work as a molecular clock, reflecting the time since different populations were separated – that is, since they were the same population. The idea is analogous to relatedness between individuals, whereby two sisters are more closely related than two first cousins because they share more recent common ancestors – their parents rather than their grandparents.

To measure differences in culturally transmitted traits, we consider a broad range of linguistic, religious, and other cultural distances between countries, which we refer to as ‘memetic distances.’ Memetic distance refers to differences in memes – a terminology introduced by Dawkins (1976). A meme is the cultural equivalent of a gene – it is a trait transmitted culturally, rather than biologically. We focus on three categories of memetic distances: linguistic distance; religious distance; and distance in a broad array of values, norms, and attitudes. The latter are obtained by looking at differences, across pairs of countries, in average responses to questions asked in the World Values Survey (WVS).4

How correlated are genetic and memetic distances?

Our empirical approach is to examine the correlation between ancestral distance, measured using genetic distance, and our various measures of memetic distances. We examine both the simple correlation and the correlation conditional on geographic distance (due to ancient migratory paths, genetic and geographic distances are positively correlated, so it is important to control for a wide range of measures of geographic distance when assessing the relationship between ancestral distance and cultural distance). We expect to find different patterns of correlations across different categories of measures of memetic distance. Indeed, both the extent of horizontal transmission and the frequency of innovation – i.e. the rate of cultural drift – differ whether we are talking about language, religion or values. We do find that there is heterogeneity in the extent to which genetic and memetic distances are correlated.

For linguistic distance, we find some of the largest correlations. Using measures of distance based on counting the number of common nodes between two languages on a linguistic tree (the subject of the field of cladistics), we find that a one standard deviation increase in genetic distance is associated with a 0.15 to 0.22 standard deviation increase in linguistic distance, depending on the measure and specification. These correlations are stronger when focusing on the Old World only. Indeed the population movements that followed the discovery of the New World were important factors breaking the link between genetic and linguistic distance. For instance large parts of Latin America are composed of Spanish speakers who are nonetheless descended from Amerindian populations.

For religious distance, we find that genetic distance comes out with a positive statistically significant coefficient in most specifications, but that the magnitude of the effect is generally a bit smaller than for linguistic distance. In fact, the emergence of major monotheistic religions is a recent phenomenon and religious ‘innovation’ (the entry of new religions) occurs at a faster rate than both genetic and linguistic drift. Moreover, religious conversions are a more widespread phenomenon than the wholesale replacement of a language. Historical examples abound of entire populations switching religions as a result of an innovation (such as the Protestant Reformation) or as a result of colonisation and the forced conversions that it often implied.

Our most novel results concern distance in values, attitudes, and norms. We computed a wide range of measures of distances between countries in the way an average respondent would answer questions from the WVS. For each question in that survey we calculated several measures of distance, including FST distance, which is the same functional form as that applied by population geneticists to the study of genetic distance (we applied it instead, of course, to compute memetic distance). We start with an analysis of the relationship between genetic distance and question-specific memetic distances, for 740 questions from the WVS. If there were no relationship between genetic and cultural distances we would expect 2.5% of the correlations to be positive and significant at the 5% significance level. Yet Figure 1, a histogram of the standardised effect of genetic distance, representing the effect of a one standard deviation change in genetic distance as a share of a standard deviation in the dependent variable, shows that 66.9% of the effects are positive, and 47.2% are both positive and significant at the 5% level – far in excess of the shares we would expect out of randomness. We also find a number of large effects, with 20% of the effects greater than 0.20. In sum, across a wide range of questions, having recent common ancestors is associated with answering more similarly on questions relating to values, norms and attitudes.

Figure 1. Distribution of beta coefficients on genetic distance (740 questions, with geodesic distance control)

While these results are informative, they conflate questions on very different subjects. To further examine the patterns of correlations, we calculated summary indices of memetic distance based on categorical groupings of the questions in the World Values Survey, as well as on the average of all available questions. The analysis is now limited to 98 questions available for all 74 countries in our sample. We found that genetic distance is positively correlated with all but one of these summary indices of cultural distance. We found a large, statistically significant positive relationship between genetic distance and our overall index of cultural distance based on all 98 questions – the standardised effect of genetic distance was 25.5%. Breaking things down by question category, we found positive and significant effects of genetic distance on cultural distance for all but category D (Family). The largest effects, quantitatively, are for categories A (Perceptions of Life), E (Politics and Society) and F (Religion and Morale).

Concluding remarks

Across a wide range of measures of memetic distance, we found a general pattern of positive and significant correlations between ancestral distance and cultural distance in contemporary populations. In other words, ancestry and culture go hand in hand. This is consistent with a conceptual framework in which a broad range of cultural traits are transmitted with variation across generations over time, so that a lower degree of genealogical relatedness is associated with greater cultural differences.

Of course, this does not mean that one’s culture is completely determined by one’s ancestors. Clearly, cultural traits do change over time within societies, and diffuse horizontally across societies. However, cultural change and horizontal learning themselves are not unconnected to ancestry, as populations that are ancestrally closer are more likely to face lower barriers to learning new ideas and behaviours from each other. Measures of ancestral, linguistic, and cultural distances can help us understand exchanges and interactions across different individuals and populations.

As we obtain a better understanding of the complex links between long-term relatedness and cultural similarities and differences across populations, we can also gain important insights on the scope and limits of policies aimed at reducing barriers to the spread of innovations and modern patterns of behaviour across societies – for example, by facilitating economic and cultural exchanges as well as movement of people across cultural borders. In this respect, this line of study is a first step towards addressing the fundamental dilemma of modern development – to figure out how populations that differ in inherited cultural traits and historical legacies can more effectively manage to learn from each other, and adopt each other’s best ideas and innovations, while maintaining the benefits associated with deeply-rooted cultural diversity.       


Banfield, E C (1958), The moral basis of a backward society, New York, NY: The Free Press,

Dawkins, R (1976), The selfish gene, Oxford: Oxford University Press.

Desmet, K, M Le Breton, I Ortuño-Ortín and S Weber (2011), “The stability and breakup of nations: A quantitative analysis”, Journal of Economic Growth, 16(3), 183-213.

Richerson, P J and R Boyd (2004), Not by genes alone: How culture transformed human evolution, Chicago: University of Chicago Press.

Spolaore, E, ed. (2014), Culture and economic growth, The International Library of Critical Writings in Economics, two volumes, Cheltenham, UK: Edward Elgar.

Spolaore, E and R Wacziarg (2009), "The diffusion of development", Quarterly Journal of Economics, 124(2): 469-529.

Spolaore, E and R Wacziarg (2013a), “How deep are the roots of economic development?”, Journal of Economic Literature, 51(2): 1-45.

Spolaore, E and R Wacziarg (2013b), “Long-term barriers to growth”, VoxEU.org, October 3.

Spolaore, E and R Wacziarg (2014), “Fertility and modernity”, Tufts University and UCLA Anderson School of Management.

Spolaore, E and R Wacziarg (2015), “Ancestry, language and culture”, prepared for the forthcoming Palgrave Handbook of Economics and Language, V Ginsburgh and S Weber (eds), CEPR Discussion Paper 10644.

Weber, M (1905), The Protestant ethic and the spirit of capitalism, (translated from German by T Parsons), London and New York: Routledge, 1930 (reprinted 2005).


1 Classic references are Weber (1905) and Banfield (1958). For the recent theoretical and empirical literature see, for example, the contributions in Spolaore (2014).

2  For an overview, see Spolaore and Wacziarg (2013a).

3 An interesting exception is Desmet et al (2011), who however only focused on European countries.

4 All these measures are available at http://www.anderson.ucla.edu/faculty_pages/romain.wacziarg/papersum.html

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