The Impact of Robots on Labour Market Transitions in Europe

Bachmann, Ronald; Gonschor, Myrielle; Lewandowski, Piotr; Madoń, Karol

doi:10.2139/ssrn.4114890

Cited by 4 publications

(6 citation statements)

References 14 publications

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“…In a very recent work, Bachmann et al (2022) studied the impact of robot adoption on workers' transitions (from employment to unemployment and viceversa) in Europe. They found small negative effects on job separations and small positive effects on job findings, with these effects being stronger for intensive routine manual or routine cognitive tasks occupations.…”

Section: Related Literaturementioning

confidence: 99%

Can Machines Learn Creativity Needs? An Approach Based on Matrix Completion

2022

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Technological progress has been recently associated with a crowding-out of cognitive-skill intensive jobs in favour of jobs requiring soft skills, such as ones related to social intelligence, flexibility and creativity. The nature of soft skills makes them hardly replaceable by machine work and among subsets of soft skills, creativity is one of the hardest to define and codify. Therefore, creativity-intensive occupations have been shielded from automation. Given this framework, our study contributes to a nascent field on interdisciplinary research to predict the impact of artificial intelligence on work activities and future jobs using machine learning. In our work, we focus on creativity, starting from its possible definitions, then we get significant insights on creativity patterns and dynamics in the Italian labour market, using a machine learning approach. We make use of the INAPP-ISTAT Survey on Occupations (ICP), where we identify 25 skills associated with creativity. Then, we apply matrix completion—a machine learning technique which is often used by recommender systems—to predict the average importance levels of various creative skills for each profession, showing its excellent prediction capability for the specific problem. We also find that matrix completion typically underestimates the average importance levels of soft skills associated with creativity, especially in the case of professions belonging to the major group of legislators, senior officials and managers, as well as intellectual professionals. Conversely, overestimates are typically obtained for other professions, which may be associated with a higher risk of being automated.

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Section: Related Literaturementioning

confidence: 99%

Can Machines Learn Creativity Needs? An Approach Based on Matrix Completion

2022

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“…The relationship between investment in automation technology and employment and wage outcomes is endogenous. The decision to invest in automation technologies is influenced by the labor cost and availability (Bachmann et al 2022) including labor market institutional factors (Presidente 2023). Also, some common industry-region level determinants of automation and labor such as labor institutions are not directly observable.…”

Section: Identification and IV Strategymentioning

confidence: 99%

“…Some studies use data from other European countries(Aghion et al 2019, Dauth et al 2021, Bachmann et al 2022. However, compared to employment trends between EU countries and the U.S. employment trends in EU countries are more closely correlated due in particular to global value chains and human capital flows.…”

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confidence: 99%

Automation and Employment Over the Technology Life Cycle: Evidence from European Regions

Jaccoud,

Petit,

Ciarli

et al. 2024

SSRN Journal

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“…We instrument exposure to both robots and ICT capital. In each case, we follow Bachmann et al (2022), and generalise the "technology frontier" instrument previously applied by and Dauth et al (2021). We instrument the robot (ICT) exposure in sector 𝑠, country 𝑐, and year 𝑡 with the average robot (ICT) exposure in other European countries.…”

Section: Estimation Framework and Instrumentsmentioning

confidence: 99%

“…We use the average exposure to ICT or robots in comparable countries as an instrument. This method has been previously applied to measure the effects of robots by, e.g., , Dauth et al (2021), and Bachmann et al (2022). We also control for globalisation, in line with the literature that identifies technological progress as a critical driver of labour market developments and trade as a mediating factor (Gregory et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The impact of ICT and robots on labour market outcomes of demographic groups in Europe

Albinowski,

Lewandowski

2024

Labour Economics

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The Impact of Robots on Labour Market Transitions in Europe

Cited by 4 publications

References 14 publications

Can Machines Learn Creativity Needs? An Approach Based on Matrix Completion

Can Machines Learn Creativity Needs? An Approach Based on Matrix Completion

Automation and Employment Over the Technology Life Cycle: Evidence from European Regions

The impact of ICT and robots on labour market outcomes of demographic groups in Europe

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