Barriers to the spread of prosperity

Barriers to the spread of prosperity

Enrico Spolaore, Romain Wacziarg 10 February 2017

Because the Industrial Revolution, modern prosperity has spread from its European birthplace to numerous corners of the world. The diffusion of technologies, institutions and behaviours connected with this technique of economic modernisation has been unequal both over space and time. This column, extracted from a recently available Vox eBook, argues that the divergent historical paths accompanied by distinct populations resulted in barriers between them. Although these barriers are deeply rooted, their effect isn’t permanent and immutable.

Related

Editor’s note: This column first appeared as a chapter in the Vox eBook, The Long Economic and Political Shadow of History, Volume 1, open to download here.

A recently available literature has documented the important role played by deeply-rooted factors as predictors of the existing world distribution of income and other economic outcomes. These factors include geographic conditions and historical events that sent different societies on different economic trajectories – the consequences of bio-geographic endowments (Olsson and Hibbs 2005, Ashraf and Galor 2011), the legacy of colonialism (Acemoglu et al. 2001), the persistent aftereffect of pre-colonial traits and institutions (Michalopoulos and Papaioannou 2013), the durable cultural impact of traditional agricultural practices (Alesina et al. 2013), and the consequences of long-term history and movements of populations around the world (Spolaore and Wacziarg 2009, Putterman and Weil 2010, Ashraf and Galor 2013), to mention but a few. Several historical determinants are summarised in the brand new VoxEU eBook where this column features (Michalopoulos and Papaioannou 2017). However, the mechanisms where deeply-rooted factors influence current prosperity remain elusive. Moreover, studies that emphasise the persistence of historical legacies and long-term determinants raise questions about the scope for change. As described, for instance, within an excellent discussion by Banerjee and Duflo (2014), there can be an inherent tension between historical determinism and the power of policy to affect outcomes. If days gone by casts such an extended shadow, can contemporary societies escape from factors and constraints that may have historically limited their economic development?

In this column, we argue that the divergent historical paths accompanied by distinct populations resulted in barriers between them. The more divergent the historical paths of different populations, the higher the barriers. And the higher the barriers, the more challenging it had been for innovations, institutions and behaviours to spread from society to society. Hence, typically, countries that are richer today are those more closely linked to the frontier society where modern technologies, institutions and behaviours first arose. As a way to prosper, more distantly related societies have to overcome the barriers that separate them from societies that are nearer to the frontier. However, while such barriers are deeply-rooted, their effect isn’t permanent and immutable. Historical factors usually do not constitute permanent limits to the growth potential of these with disadvantageous historical legacies. Instead, barriers caused by distinct historical trajectories could be gradually overcome, suggesting a considerable role to use it and positive change.

Measuring human barriers

In principle, barriers to the transmission of prosperity can arise from numerous sources. Geographic barriers will tend to be very important to several outcomes, plus they are perhaps easiest to measure and control for in empirical focus on the diffusion of development. Measuring human barriers – the ones that prevent, at confirmed geographic distance, the spread of innovations, institutions and behaviours – is a lot more challenging. Inside our past work, you start with Spolaore and Wacziarg (2009), we employed a number of measures of historical separation among populations to fully capture human barriers. Chief included in this was FST genetic distance, a measure that captures separation times between populations: when humans migrated out of Africa, groups splintered because they moved across continents, and the groups that separated earlier had additional time to drift apart genetically than groups that separated recently. Hence, genetic distance is correlated with how long populations experienced a common history. Pairs of societies with smaller genetic distance are anticipated to have lower human barriers to the spread of development. 2

The theory behind the usage of genetic distance as an over-all proxy for human barriers is that human traits – not merely biological but also cultural – are mostly transmitted, with variation, from generation to generation (i.e. vertically). Thus, the longer two societies have drifted apart, the higher the differences in traits between them, and the higher the barriers that separate them. Of course, genetic distance is in no way the only way of measuring intergenerational separation times. Linguistic distance is a closely related class of measures, again predicated on a trait that’s mostly transmitted vertically (language). Another possibility is to look directly at differences in culture, as revealed by surveys: values, norms, and attitudes (including however, not limited by religion). Cultural values could be transmitted in several ways – vertically, from generation to generation; obliquely, across biologically unrelated members of the same society; or horizontally, i.e. across societies (Richerson and Boyd 2005). The vertical dimension of transmission is a common feature of genetic traits and language, and of norms and values. Thus, metrics of distance between societies that derive from these three classes of measures, while distinct from one another, ought to be positively correlated. That is indeed what we find in Spolaore and Wacziarg (2016a), where we further discuss and document empirically the complex links between various measures of human relatedness. The bottom line is, the vertical transmission of genes, language and culture makes up about the positive correlations between human distance metrics predicated on each one of these traits. Yet these measures aren’t perfectly correlated because: i) there are differential rates of drift in genes, language and values, ii) a few of these traits are transmitted horizontally, and iii) different methodologies are accustomed to compute distances over the three classes. Inside our ongoing research on the diffusion of development, we use all three classes of measures.

Three examples

What is the data these measures of human relatedness matter when predicting differences in prosperity? In recent work we’ve found such evidence in a number of contexts. Here we will discuss three: technology, institutional quality, and fertility behaviour.

The diffusion of development

In Spolaore and Wacziarg (2009, 2014a), we documented a solid correlation between genetic distance between countries in accordance with the technological frontier and their differences in degrees of development: two societies are predicted to have similar degrees of development if they are actually at relatively similar distances from the global technological frontier (inside our applications, either the united states or northwestern Europe). We interpreted this correlation as indicative of barriers to the spread of the Industrial Revolution. We showed specifically that the result of barriers was largest soon after the Industrial Revolution, when some however, not all countries had transitioned to economic modernity. The result declined as increasingly more societies, at successively greater genetic distances from the innovation frontier, became rich. In age globalisation, when barriers became better to overcome, the result fell further (Figure 1).

Further, in Spolaore and Wacziarg (2012, 2014a) we discovered that this pattern held true not only for the overall degree of prosperity, measured by per capita income, also for specific technologies (cell phones, computers, etc.). In sum, societies that are historically distant from the technological frontier have a harder time adopting better technologies, and therefore take longer to be prosperous.

Figure 1 Standardised aftereffect of genetic distance in accordance with the united kingdom on bilateral differences in per capita income as time passes, 1820-2005

Source: Spolaore and Wacziarg (2014a)

The diffusion of institutions

In Spolaore and Wacziarg (2016b), we conducted an identical exercise to comprehend the worldwide diffusion of democracy through the Third Wave of Democratisation that became popular in the 1970s. The way in which of the diffusion process was like the spread of the Industrial Revolution: genetic distance in accordance with the institutional frontier (the united states) matters increasingly following the onset of the 3rd wave, and declines gradually as more countries, at greater distances from the institutional frontier, become democratic (Figure 2). What deserves further research may be the precise mechanism whereby institutional change spreads in one country to another.

Figure 2 Standardised aftereffect of genetic distance in accordance with the united states on bilateral differences in Polity 2 Democracy scores, 1960-2005

Source: Spolaore and Wacziarg (2016b)

The diffusion of the fertility transition in Europe

In both examples above, the result of distance from the frontier fades away over time, but will not disappear entirely. Yet a prediction of our diffusion model is that the result of ancestral distance should disappear following the most distant societies have finally overcome the barriers and adopted modern technologies, institutions and behaviours. The case of the European fertility transition, starting in the first 19th century in France, affords a good example where in fact the entire diffusion process could be observed in your sample. In Spolaore and Wacziarg (2014b), we analysed this technique in a panel of European regions from 1831 to 1970. We measured ancestral distance using linguistic distance, since this is more designed for the parts of Europe than genetic distance. Initially, only regions that spoke a language near French adopted the fertility behaviour first seen in France in the late 18th to early 19th centuries. Later, regions at successively greater distances from France adopted the brand new behaviour. By the finish of our sample period, just about any region in Europe had adopted modern behaviours regarding fertility (i.e. 2-3 children per household). The interpretation of the particular diffusion process differs than for our other examples for just two reasons. First, the frontier society in this instance had not been England, but France. This fact highlights how different innovations may begin at different frontiers – implying different barriers with their diffusion. Second, fertility behaviours likely diffused as the consequence of an activity of social influence regarding appropriate norms of fertility, as opposed to the diffusion of specific technologies (although the diffusion of contraceptive methods – broadly defined – may have played a complementary role). Whatever the complete mechanism, the lesson is clear: ancestral barriers, measured by relative linguistic distance from French, predicted the diffusion of modern fertility behaviours across Europe.

Figure 3 Standardised aftereffect of linguistic distance to French on marital fertility through time

Note: Overlapping samples of 30 years centred on the date displayed in the x-axis.The sample is a balanced sample of 519 European regions
Source: Spolaore and Wacziarg (2014b)

Conclusion: Barriers and the scope for policy

As we’ve argued in this column, populations that are historically and culturally more distant face higher barriers to adopting each other’s technologies, institutions, and behavioural innovations. Such barriers – measured by genetic, linguistic and cultural distance – stem from long-term historical divergence, and therefore capture the result of deeply-rooted historical factors that sent different populations on different historical trajectories. However, we’ve also seen that the result of barriers isn’t permanent and immutable, but changes as time passes, as societies that are farther from the frontier also learn and adopt novel technologies and innovations.

Moreover, the frontier itself isn’t immutable, but changes as time passes, and may differ based on the specific innovation – for instance, the frontier was originally England for the Industrial Revolution, but France for the societal changes in norms and behaviour connected with Europe’s demographic transition.

If such historical barriers could be overcome – plus they have indeed been overcome by many societies as time passes – there is room for optimism regarding the scope for change and progress, even though coping with persistent historical factors. 3 While distances themselves could be deeply-rooted ever sold, their effect on contemporary outcomes can, in principle, be suffering from current actions and policies. For example, policy can reduce obstacles to interactions and communication between folks from different cultural and linguistic backgrounds. Our research shows that the result of barriers to the spread of prosperity has diminished in age globalisation. The ease with which ideas, people, goods and capital can flow across societal borders really helps to decrease the ancestral barriers that kept populations from learning from one another. Facilitating these flows, therefore, supplies the promise of lower barriers to the spread of prosperity.

References

Acemoglu, D, S Johnson and J Robinson (2001), “The Colonial Origins of Comparative Development”, American Economic Review 91(5): 1369-1401.

Alesina, A, P Giuliano and N Nunn (2013), “On the Origins of Gender Roles: Women and the Plough”, Quarterly Journal of Economics 128(2): 469-530.

Ashraf, Q and O Galor (2011), “Dynamics and Stagnation in the Malthusian Epoch”, American Economic Review 101(5): 2003-41.

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

Banerjee, A and E Duflo (2014), “Beneath the Thumb of History? Political Institutions and the Scope to use it”, Annual Overview of Economics 6: 951-971.

Galor, O (2011), Unified Growth Theory, Princeton: Princeton University Press.

Michalopoulos, S and E Papaioannou (2013), “Pre-colonial Ethnic Institutions and Contemporary African Development”, Econometrica 81(1): 113-152,

Mokyr, J. (2005), “Long-Term Economic Growth and the annals of Technology”, in P Aghion and S N Durlauf (eds), Handbook of Economic Growth, Volume 1B, Amsterdam: Elsevier, North-Holland.

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

Putterman, L and D N Weil (2010), “Post-1500 Population Flows and the Long-Run Determinants of Economic Growth and Inequality”, Quarterly Journal of Economics 125(4): 1627-82.

Richerson, P. J. and R. Boyd (2005), Not By Genes Alone: How Culture Transformed Human Evolution, Chicago: University of Chicago Press.

Spolaore, E and R Wacziarg (2009), “The Diffusion of Development”, Quarterly Journal of Economics 124(2): 469-529.

Endnotes

1 For instance, see Mokyr (2005) for an insightful historical discussion and Galor (2011) for a unified account of the growth take-off.

2 Of course, since geographic and genetic distances are correlated – because groups splintered gradually because they moved farther and farther from East Africa, while conquering other territories – it really is vital to control for geographic distance in virtually any work that uses genetic distance as a way of measuring human barriers.

3 Having said that, we have to add that inter-population barriers usually do not always play a poor role in history. They may also avoid the spread of deleterious innovations, such as for example hateful ideologies or disruptive behaviors, and could reduce international conflict over territories and resources (see Spolaore and Wacziarg 2016c).

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