Mariya Brussevich, Ms. Era Dabla-Norris, Christine Kamunge, Pooja Karnane, Salma Khalid, and Ms. Kalpana Kochhar
New technologies?digitalization, artificial intelligence, and machine learning?are changing the way work gets done at an unprecedented rate. Helping people adapt to a fast-changing world of work and ameliorating its deleterious impacts will be the defining challenge of our time. What are the gender implications of this changing nature of work? How vulnerable are women’s jobs to risk of displacement by technology? What policies are needed to ensure that technological change supports a closing, and not a widening, of gender gaps? This SDN finds that women, on average, perform more routine tasks than men across all sectors and occupations?tasks that are most prone to automation. Given the current state of technology, we estimate that 26 million female jobs in 30 countries (28 OECD member countries, Cyprus, and Singapore) are at a high risk of being displaced by technology (i.e., facing higher than 70 percent likelihood of being automated) within the next two decades. Female workers face a higher risk of automation compared to male workers (11 percent of the female workforce, relative to 9 percent of the male workforce), albeit with significant heterogeneity across sectors and countries. Less well-educated and older female workers (aged 40 and above), as well as those in low-skill clerical, service, and sales positions are disproportionately exposed to automation. Extrapolating our results, we find that around 180 million female jobs are at high risk of being displaced globally. Policies are needed to endow women with required skills; close gender gaps in leadership positions; bridge digital gender divide (as ongoing digital transformation could confer greater flexibility in work, benefiting women); ease transitions for older and low-skilled female workers.
Ms. Andrea De Michelis, Mr. Marcello M. Estevão, and Ms. Beth Anne Wilson
Traditionally, shocks to total factor productivity (TFP) are considered exogenous and the employment response depends on their effect on aggregate demand. We raise the possibility that in response to labor supply shocks firms adjust efficiency, rendering TFP endogenous to firms’ production decisions. We present robust cross-country evidence of a strong negative correlation between growth in TFP and labor inputs over the medium to long run. In addition, when using instruments to capture changes in hours worked that are independent of TFP shocks, we find that cross-country increases in labor input cause reductions in TFP growth. These results have important policy implications, including that low productivity growth in some countries may partly be a side effect of strong labor market performance. By the same token, countries facing a declining workforce, say, because of aging, may see accelerating TFP as firms find better ways of employing workers.