Seite - (000074) - in Disrupted Development and the Future of Inequality in the Age of Automation

5 AUTOMATION AND STRUCTURAL TRANSFORMATION … 67 It is interesting to note that the McKinsey Global Institute assigns the lowest automatability estimates to Kuwait and South Africa, the for- mer an entirely oil-fueled Organization of the Petroleum Exporting Countries (OPEC) economy with practically no unemployment, and the latter having one of the highest unemployment rates and most seg- regated labor markets in the world. Overall, the median estimates of the McKinsey Global Institute for HICs (n = 27) is 47, whereas the median for low-income countries (LICs) and lower middle-income countries (LMICs) (n = 13) is 51. It is worth at this point considering the structural characteristics of economies. Figure 5.3 reproduces the familiar cross-country pattern across three sectors, showing that rich countries generally have very low levels of employment in agriculture and high levels of service sector employment, with the reverse being the case for developing countries. The industry share of employment is uncorrelated with GNI per capita (p > 0.05) from a cross-country perspective. Given this overall structural pattern, what then is the relationship between automatability and sectoral characteristics? Figure 5.4 shows that the pattern is similar, though somewhat less pronounced, to the pattern of GNI per capita and automatability. The service sector share, in particular, is a strong predictor of both McKinsey’s and the World Bank’s automatability estimates. The more agrarian an economy is, the larger the population performing tasks that machines could theoretically perform. We can thus say, assuming the automatability estimates are reasonable, that the labor force of more service sector-based, richer economies tends to be less replaceable compared to more agriculture-based, poorer econ- omies. This pattern is intuitive and is explained by the complexity and creativity of service-sector work and the amount of face-to-face human interaction involved in it. If we break down the relationship of sectoral employment by level of GNI per capita (Fig. 5.5), the above-mentioned pattern largely holds. Among HICs, there is no relationship between agriculture and automatability simply because there is almost no employ- ment in agriculture. Industrial work is more automatable and service-sec- tor work less automatable across both country groupings, so the level of economic development does not moderate that sectoral relationship.13 Generally, we can say the APS is (much) larger in countries with lower income per capita. If countries have to decide how to reallocate employ- ment during structural change and the described cross-country pattern