working papers

This paper develops a task-adjusted, country-specific measure of workers’ exposure to artificial intelligence (AI) in 108 countries, covering approx. 89% of global employment. Accounting for within-occupation task differences significantly amplifies the development gradient in AI exposure. We attribute these differences primarily to cross-country differences in ICT use intensity, followed by occupational composition, human capital and globalisation-related firm characteristics.

Measuring worker-level job tasks of Ukrainian war refugees in Poland, we find substantial task degradation, namely performing more routine-intensive jobs in Poland after displacement than in Ukraine before the full-scale war. People who experience a greater task degradation were more likely to plan to return to Ukraine by 2023, particularly those who initially, in 2022, did not plan to return.

Using a a discrete choice experiment with 10,000 people in Poland, we examine public preferences for policies to achieve energy security and climate change mitigation goals in the context of the energy crisis caused by Russia’s invasion of Ukraine. We find a strong aversion to carbon tax, only slightly mitigated by redistribution. Income, trust, and age shape preferences for climate and energy policies, and for redistribution mechanisms.

We study the effects of robot penetration on household income inequality in 14 European countries between 2006–2018. Automation reduced relative hourly wages and employment of directly affected European demographic groups. We use the estimated wage and employment shocks as input to the EUROMOD microsimulation model to assess how robot-driven shocks affected household income inequality. Automation had tiny effects on income inequality. Transfers played a key role in cushioning the transmission of these shocks to household incomes.

Job polarization can pose serious problems for emerging economies that rely on worker reallocation from low-skilled to middle-skilled jobs to converge toward advanced economies. Evidence from Central and Eastern European (CEE) countries shows that structural change and education expansion can prevent polarization, as they enable a shift from manual to cognitive work and prevent the “hollowing out” of middle-skilled jobs. However, in CEE countries they have also led to a high routine cognitive content of jobs, which makes such jobs susceptible to automation and computerization in the future.