4. The following regression was estimated: ln(V AP W )f,c = αc + βs + γ ∗ Tf,c + ρ ∗ Xf,c + vf,c, where αc and βs are country and sector fixed effects, Tf,c is a vector of firm-level technology measures, and Xf,c is a vector of controls that includes the observable variables discussed plus 12 dummies for the sectors for which the sample includes data on sector-specific technologies and other services. 5. Caselli (2005) uses purchasing power parity (PPP) adjustments to compute sectoral productivity. This may induce additional discrepancies in cross-country productivity gaps across sectors if the PPP price index differs more across countries in agriculture than in nonagricultural sectors. 6. This does not necessarily mean that these technologies are biased toward unskilled workers, given that the results could be driven by the growth effect. Yet, evidence in the literature suggests that technologies such as online platforms used for export sales can lead to reduction in the wage skill premium (Cruz, Milet, and Olarreaga 2020). 7. There is, however, significant heterogeneity across countries. In Senegal, for example, there is a positive and strong correlation between technology sophistication and changes in the share of low-skilled workers. 8. The results do not claim any causal relationship, given that the analysis is unable to control for unobservable characteristics for workers and firms and the fact that more productive or higherability workers self-select into firms that use more advanced technologies.
References Acemoglu, D., and D. Autor. 2011. “Skills, Tasks and Technologies: Implications for Employment and Earnings.” Chapter 12 in Handbook of Labor Economics, Vol. 4, edited by David Card and Orley Ashenfelter, 1043–171. Elsevier. Aghion, P., U. Akcigit, A. Hyytinen, and O. Toivanen. 2018. “On the Returns to Invention within Firms: Evidence from Finland.” AEA Papers and Proceedings 108: 208–12. Aghion, P., A. Bergeaud, R. Blundell, and R. Griffith. 2019. “The Innovation Premium to Soft Skills in Low-Skilled Occupations.” CEPR Discussion Paper 14102, Center for Economic and Policy Research, Washington, DC. Alvarez, J., F. Benguria, N. Engbom, and C. Moser. 2018. “Firms and the Decline in Earnings Inequality in Brazil.” American Economic Journal: Macroeconomics 10 (1): 149–89. Autor, D. A. 2015. “Why Are There Still So Many Jobs? The History and Future of Workplace Automation.” Journal of Economic Perspectives 29 (3): 3–30. Bloom, N., F. Guvenen, B. S. Smith, J. Song, and T. von Wachter. 2018. “The Disappearing Large-Firm Wage Premium.” AEA Papers and Proceedings 108: 317–22. Caselli, F. 2005. “Accounting for Cross-Country Income Differences.” Chapter 9 in Handbook of Economic Growth, Vol. 1, Part A, 679–741. Elsevier. Cirera, X., and A. S. Martins-Neto. 2020. “Do Innovative Firms Pay Higher Wages? Micro-Level Evidence from Brazil.” Policy Research Working Paper 9442, World Bank, Washington, DC. Comin, D., and B. Hobijn. 2010. “An Exploration of Technology Diffusion.” American Economic Review 100 (5): 2031–59. Comin, D., D. Lashkari, and M. Mestieri. 2021. “Structural Change with Long-Run Income and Price Effects.” Econometrica 89 (1): 311–74. Cruz, M., E. Milet, and M. Olarreaga. 2020. “Online Exports and the Skilled-Unskilled Wage Gap.” PLOS one 15 (5): e0232396. Cusolito, A. P., and W. F. Maloney. 2018. Productivity Revisited: Shifting Paradigms in Analysis and Policy. World Bank Productivity Project series. Washington, DC: World Bank.
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