technologies can affect jobs and wages is a useful starting point (Acemoglu and Restrepo (2019).<sup>9</sup> First, computerization and other digital automation replaces labor with capital in completing routine, codifiable tasks, thus eliminating jobs (the “displacement” effect). Automation can also allow for more flexible allocation of tasks, thereby raising labor productivity and the demand for labor in non-automated tasks (the “productivity” effect). Finally, new technologies can also create new tasks that complement digital technologies, potentially creating jobs (the “reinstatement” effect).<sup>10</sup> On net, the negative displacement effect of automation may be outweighed by productivity gains that increase the demand for labor, including in complementary tasks.

Evidence suggests that the adoption of ICT associated with the first wave of digitalization has not reduced aggregate employment in advanced economies. Based on data for the 2000s from 19 advanced economies, including those of the European Union, Australia, Canada, Japan, the Republic of Korea, and the United States, Autor and Salomons (2018) find that own-industry employment losses attributable to ICT-related automation were reversed by indirect gains in customer-facing industries and induced increases in aggregate demand.<sup>11</sup> In the United States, the expansion of automated teller machines (ATMs) is a much-cited example. Despite the number of ATMs quadrupling between 1995 and 2010, the number of bank tellers increased by about 10 percent between 1980 and 2010. By reducing the cost of operating a bank branch, ATMs indirectly increased the demand for tellers. Further, as routine cash-handling tasks receded, computerization enabled tellers to become involved in new “relationship banking” tasks (Autor 2015).

The few empirical studies on developing economies broadly find that the net effect of the first wave of digitalization on jobs has been positive, albeit with differences according to type of employment. Hjort and Poulsen (2019), for example, conclude that the reinstatement effect outweighs the substitution effect of automation associated with faster internet access in SubSaharan African countries. Studies of the impacts of ICT adoption on jobs have also investigated location-based differences. In Tanzania and Nigeria, working-age individuals living in areas covered by mobile internet experienced an increase in wage employment (Bahia et al. 2020, 2021).

Evidence about the effects of robots on jobs in advanced economies has not coalesced around a definitive narrative. In an analysis considering both the displacement and productivity effects, Acemoglu and Restrepo (2020) show that the introduction of one industrial robot per 1,000 workers has reduced the employment-to-population ratio in the United States by 0.2 percentage point and wages by 0.4 percent. A similar study on EU countries using the same density of industrial robots estimates a reduction in the employment-to-population ratio of about 0.2 percent (Chiacchio, Petropoulos, and Pichler 2018). The adverse effect of robots on employment in the EU is echoed in the findings of Carbonero, Ernst, and Weber (2020). Yet a study of seven European countries using firm-level data concludes that industrial robots have no direct effect on employment (Jäger, Moll, and Lerch 2016). Antón et al. (2022) caution against drawing clear conclusions about how employment was impacted by robot adoption in Europe between 1995 and 2015, showing that the effect is sensitive to the time period, country sample, and model specification.

> 9 The “task-based” framework followed previous investigations of “skill-biased technological change.”

> 10 Acemoglu and Restrepo (2018) use data from Lin (2011) to show that about half of the employment growth over 1980-2015 took place in occupations in which job titles or tasks changed.

> 11 However, own-industry labor share losses are not outweighed by gains elsewhere.

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