Yesterday I looked at urbanization vs income per capita across Asian countries. Today I want to get into more detail and extend my analysis to the regions of America, Europe, Africa and Asia (revisited). The data comes from the World Development Indicators database and I have included my cleaned-up dataset at the end of the post. I have chosen GDP per capita in PPP at constant 2011 international dollar and urban population as a percentage of total population. For the year 2014 the indicators are available for 179 countries.
Urbanization is an indicator for structural transformation because the relative decline of the agricultural sector compared to the industrial and services sector implies a substantial migration of labour from rural to urban areas in a country (Perkins et al., 2013). Based on this, there should be a positive correlation between a country’s level of urbanization and its standard of living. This is of interest to policy makers because a high urban population rate despite low GDP per capita is a hint towards inefficiencies in for example the labour market or urban policies. As there is enough urban labour available for expanding the industrial and services economy there must be a weakening in the link of recruitment of rural labour into the cities and their productivity in the urban sector thereafter.
The first diagram summarizes the association between urbanization and GDP per capita for the entire dataset. Thereby the y-axis is measured on a log2 scale in order to transform the correlation between GDP per capita and urbanization into a linear trend. Overall it can be inferred that a rise in urban population tends to be accompanied by an increase in income per capita in the dataset. In general, urbanization ranges from just unter 10 percent (Trinidad and Tobago) to 100 percent (Hong Kong, Macau and Singapore). Meanwhile GDP per capita ranges from 567 Dollar (Central African Republic) to 134,182 Dollar (Qatar). I have also chosen to give certain datapoints as an example. In global comparison it can be observed that outliers tend to be developing countries, small island countries (Trinidad and Tobago), city-states (Singapore, Hong Kong and Macau) and oil-rich countries such as Qatar. Furthermore conflict and violence seem to weaken the transmission link between urbanization and a country’s standard of living (Congo, Palestine). It can be concluded that countries suffering from negative externalities are signficantly below the trend line whereas countries suffering from positive environmental influences or other factors are significantly above the trend line.
The second diagram looks at the North and South American continent in depth. The United States and Canada are major positive outliers in regional comparison. The remainder is relatively closely scattered around the trend line. The sub-regional trend for South America is somewhat flatter where high urban population rates have not resulted in standards of living comparable to high income countries. Uruguay is the best example in these regards with an urban population of around 95 percent but a GDP per capita of only circa 19,924 Dollar. This observation for the complete South American region might indicate regional conflicts that weaken the transmission mechanism between migration to cities and increases in GDP per capita.
The next continent I want to look at is Europe. The lowest European GDP per capita in the dataset has Moldova at 4,754 Dollar with an urban population of almost 45 percent. The highest GDP per capita can be found in Luxembourg at around 91,408 Dollar. The lowest urban population share has Bosnia and Herzegovina at just under 40 percent whereas the highest urban population share of almost 98 percent can be found in Belgium. There are considerable regional differences across the continent. Western and Northern Europe are closely scattered around the trend on the right whereas Eastern European countries are more loosely scattered around the trend line on the left. Southern Europe remains diverse in terms of urbanization rates. It can be seen that outliers tend to occur in sections of lower GDP per capita below the trend line (Moldova and Ukraine). Especially Ukraine serves as an example of conflict offsetting the link between urbanization and increases in standard of living.
The next regional diagram deals with Africa. For simplicity, only Western African countries are labelled as I want to focus on the significant lower GDP per capita in this region at the same urban population shares compared to the rest of Africa, especially Southern Africa (yellow trend line). Here again, the considerable regional differences suggest that there are regional conflicts or other negative environmental influences regarding West Africa and positive external factors for Southern Africa shifting its trend line significantly upwards. The lowest GDP per capita in this region has the Central African Republic (also the global minimum as mentioned before). The highest GDP per capita has Equatorial Guinea at around 33,142 Dollar. What is more, the minimum and maximum regional GDP per capita occur both in Central Africa. This suggests that there are considerable differences in Central Africa causing this divergence. Equatorial Guinea and Central African Republic have an identical urban population share of 39.8 percent. Hence the gap in their standard of living is likely influenced by country-specific and not regional-specific factors. The lowest share in urban population has Burundi at around 12 percent. This is the second lowest global rate after Trinidad and Tobago (Caribbean). Gabon has the highest African urban population of circa 87 percent.
Finally, I want to revisit my analysis of urbanization and GDP per capita across Asian countries with an improved diagram. The smallest urban population have Sri Lanka and Nepal (only 18 percent). In comparison the regional maximum can be found in Singapore, Macao and Hong Kong of 100 percent due to their city-state status. However, they are closely followed by the countries Qatar (99), Kuwait (98), Japan (93) Israel (92). The most densely urban populations are found in Western Asia (yellow) and Eastern Asia (red). The smallest urban populations are in the areas of Southern (green) and Central Asia (lilac). Southeastern Asia is more diverse in terms of urban population shares. However, Acemoglu, Johnson and Robinson (2001) point out that South-East Asia in fact has a history of high population density and urbanization but that intervention of Europe has reversed this to a certain extent. This might explain the diversity of urbanization rates in Southeastern Asia. Also, Southeastern Asia’s neigbouring regions may have some influence, i.e. mainly urban from Eastern and mainly rural from Southern Asia. In Asia the lowest GDP per capita has Afghanistan of only 1,844 Dollar. Given its urban population share of 26 percent it is below the trend line. Again, this is an indicator for conflict and negative environmental factors dampening the correlation between urbanization and GDP per capita. The highest GDP per capita has Qatar at 134182 Dollar followed by Macau (133,341 Dollar). These are also the highest GDP per capita in global comparison. Macau’s GDP for example is equivalent to 754 percent of the world’s average (Tradingeconomics, 2016). Finally, it can be seen that Asia has the greatest divergence in urbanization rates and GDP per capita compared to America, Europe and Africa. This, certainly, is a major challenge for the Asian continent.
Thanks for reading and feel free to comment my analysis!
My dataset can be found here: Urbanisation vs GDP per capita WDI 2014
Acemoglu, D., Johnson, S., and Robinson, J.A. (2001). Reversal Of Fortune: Geography And Institutions In The Making Of The Modern World Income Distribution, Quarterly Journal of Economics, 2002, v107(4,Nov), pp.1231-1294.
Perkins, D.H., Radelet, S., Lindauer, D.L., and Block, S.A. (2013). Economics of Development, Seventh Edition. New York, NY: W.W. Norton & Company.
Tradingeconomics (2016). Macau: GDP per Capita PPP. [online ] Available at: http://www.tradingeconomics.com/macau/gdp-per-capita-ppp [Accessed 11/04/2016].
World Bank (2016). World Development Indicators. [Data] Retrieved from World Development Indicators (WDI) database: http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators&preview=on [Accessed 11/04/2016].