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74 L. SCHLOGL AND A. SUMNER 9. Lewis believed in contrast to Asia that Africa had a labor shortage due to agricultural land availability. The constraint to growth in Africa was low agriculture productivity rather than manufacturing growth and required government intervention in agriculture (See Kanbur, 2016, p. 7). 10. A second MGI report (MGI, 2017b) released later the same year was much less pessimistic. It estimated labor displacement at 400 m jobs glob- ally which would be offset by 555 million jobs created by increased labor demand. 11. There are further data sets of IMF (2017) and UNCTAD (2017) which we do not have access to at time of writing. 12. We may overemphasize the technical feasibility angle in this section given the data we use which leads us to an inverse relationship between autom- atability and per capita income. At the current cost of automation, there is a positive relationship and the curve may turn into an inverted U as costs keeps falling and all jobs in developed countries have been automated, before eventually becoming negative; the question of course is how long away “eventually” is. Thus our assessment may be too pessimistic. 13. There is a significant (p < 0.05) positive correlation of industrial employ- ment shares and automatability in HICs. This pattern is also found using the data of Arntz et al. (2016). It can similarly be observed in develop- ing countries (non-HICs) in the McKinsey Global Institute (2017b) data where it is though not significant as data coverage is too limited. references Acemoglu, D., & Autor, D. (2011). Skills, tasks and technologies: Implications for employment and earnings. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics (Vol. 4B, pp. 1043–1171). Amsterdam: Elsevier. Acemoglu, D., & Restrepo, P. (2015). The race between machine and man: Implications of technology for growth, factor shares and employment. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2781320. Acemoglu, D., & Restrepo, P. (2017). Robots and jobs: Evidence from US labor markets (NBER Working Paper Series No. 23285). Cambridge, MA: NBER. Retrieved from http://www.nber.org/papers/w23285. ADB (Asian Development Bank). (2018). Asian development outlook 2018: How technology affects jobs. Manila: ADB. Arntz, M., Gregory, T., & Zierahn, U. (2016). The risk of automation for jobs in OECD countries: A comparative analysis. OECD Social, Employment and Migration Working Papers, 2(189), 47–54. Atkinson, A. B., & Bourguignon, F. (2014). Introduction: Income distribution today. In A. B. Atkinson & F. Bourguignon (Eds.), Handbook of income distri- bution, volume 2A (pp. xvii–lxiv). Oxford and Amsterdam: Elsevier.