New Evidence on the Effect of Technology on Employment and Skill Demand

Hirvonen, Johannes; Stenhammar, Aapo; Tuhkuri, Joonas

doi:10.2139/ssrn.4081625

Cited by 15 publications

(10 citation statements)

References 112 publications

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“…If these types of arrangements do play an important role in negotiating negative short‐term by‐products of automation, then we would see this positively reflected in the labour share. For example, collective agreements might push employers to invest in reskilling employees as opposed to laying them off, while strong works councils or employee representation on boards could lead to compromises over cuts (see Hirvonen et al., 2022). As such, I predict that the negative relation between robotization and the labour share is less pronounced in cooperative settings (H2).…”

Section: Theory and Argumentmentioning

confidence: 99%

Conflict or cooperation? Exploring the relationship between cooperative institutions and robotisation

Overbeke

2022

Brit J Industrial Rel

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Robotization of production challenges the status‐quo in the economy, some win, while others lose out. Literature has argued that automation causes redistribution, both between capital and labour as within either category. We also know that many economies have chosen to adopt cooperative institutions to negotiate the negative by‐products of such economic changes. What is, however, less clear is how such institutions influence rates of automation themselves. This article contributes to this debate by conducting a panel analysis of sectoral robotization rates and cooperative institutions in 25 OECD countries between 1993 and 2017 using an original institutional indicator. The findings suggest that aside from simply redistributing the costs and benefits of automation throughout the productive sector, cooperative institutions also meaningfully predict higher levels of robot density, showing that more institutionalized economies do not lag behind in terms of automation. What is more, these institutions also seem to co‐determine the rates of robotization occurring during recessions.

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Section: Theory and Argumentmentioning

confidence: 99%

Conflict or cooperation? Exploring the relationship between cooperative institutions and robotisation

Overbeke

2022

Brit J Industrial Rel

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“…Similarly Hirvonen, Stenhammar, and Tuhkuri (2022) present evidence of the effects of advanced technologies on employment. Their study focuses on a technology subsidy program in Finland and demonstrates that advanced technologies led to increases in employment and no change in skill composition.…”

Section: Literature Reviewmentioning

confidence: 93%

Economics of ChatGPT: a labor market view on the occupational impact of artificial intelligence

Zarifhonarvar

2023

JEBDE

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PurposeThe study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.Design/methodology/approachAn analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.FindingsThe study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.Research limitations/implicationsWhile this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.Originality/valueThis paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

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“…This includes investments in transport, ICT equipment, cultivated biological resources, intellectual property products, etc. A similar method was used by Hirvonen et al (2022), who measured technological progress in Finland from 1994 to 2018 through financial firms' data. This approach was selected because, first, it provides a relatively direct measure of how much companies invest into new technologies, though it also includes some non-technological investments.…”

Section: Estimating Technological Upgradingmentioning

confidence: 99%

From Socialism to Capitalism: Low-Skill-Biased Change in the Baltics during the Transition and Beyond

Christenko

Martinaitis

Krūminas

2023

TalTech Journal of European Studies

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How did technological upgrading in the Baltics during the transition from planned to market economy affect labour? Existing academic literature would imply a skill-biased or polarising effect. However, we find that the opposite is likely true—technological upgrading predominantly benefited lower skilled workers. This is explained by an abundance of lower skilled labour, which fostered the usage of less advanced technologies that such workers could utilise. This article contributes to the discussion on the relationship between technology and labour by highlighting that technological upgrading may lead to low-skill-biased change.

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New Evidence on the Effect of Technology on Employment and Skill Demand

Cited by 15 publications

References 112 publications

Conflict or cooperation? Exploring the relationship between cooperative institutions and robotisation

Conflict or cooperation? Exploring the relationship between cooperative institutions and robotisation

Economics of ChatGPT: a labor market view on the occupational impact of artificial intelligence

From Socialism to Capitalism: Low-Skill-Biased Change in the Baltics during the Transition and Beyond

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