Ongoing Research

Abstract: We investigate the diffusion of frontier technologies across German firms before and during the Covid-19 crisis. Our analysis tracks the nature, timing, and pandemic-related motivations behind technology investments, using tailor-made longitudinal survey data linked to administrative worker-firm records. Technologies adopted after the onset of the pandemic increasingly facilitated remote work and mitigated the negative employment effects of the crisis. Overall, however, investments in frontier technologies declined sharply, equivalent to a loss of 1.4 years of pre-pandemic investment activity. This procyclical adoption pattern is particularly striking since the pandemic created clear incentives to experiment with new technologies. Our findings highlight how short-run fluctuations may influence medium-run economic growth through their impact on technology diffusion. 

Press: Der Spiegel, t3n, Heise Online, ZEW press release, Mannheimer Morgen, Markenartikel, IZA Newsroom.

Versions: Published as ZEW Discussion Paper No 24-057. See also ZEW Policy Brief No. 24-14.

Abstract: Within a quasi-experimental setting, we show that the first-time adoption of industry-specific minimum wages led to a doubling in the share of solo self-employment in areas with a strong bite. We explain this with the minimum wage-driven cost shock, which led to reduced labor demand and wages for dependent employment while creating incentives for independent employment. Our results suggest that dependent workers have been involuntarily pushed into more precarious alternative work arrangements, with poorer social security and lower incomes. Such unintended side effects are likely to occur when the minimum wage is set extraordinarily high, especially during an economic downturn. 

Press: IZA Newsroom, ZEW News.

Versions: Earlier versions published as IZA Discussion Paper No. 15283 as well as ZEW Discussion Paper No. 22-024 .

Abstract: This paper highlights the nuanced relationship between firms' technology adoption and the employment structure of the economy. Leveraging a novel firm survey that we link to German administrative employment records, we categorize firms based on their technology adoption status. We find that frontier technology adopters significantly contribute to the economy-wide decline in routine and rise of non-routine cognitive jobs, primarily through firms with complementary workforce skills. Our results suggest (1) a continued de-routinization with frontier technology adoption, (2) the importance of complementary skills for the decline of routine jobs, and (3) a fallacy of drawing economy-wide conclusions from within-firm workforce adjustments.

Press: IZA Newsroom

Awards: Best Poster Award 2018 of the European Association of Labour Economics (EALE) .

Versions: Earlier version published as IZA Discussion Paper No 16740 and ZEW Discussion Paper.

Abstract: We develop a novel firm-level indicator of Artificial Intelligence (AI) adoption in Europe by applying a Large Language Model to more than three million firm websites from Belgium, France, Germany, and Luxembourg (2016–2024). The method detects not only whether firms adopt AI, but also their role in the AI ecosystem and the type of AI technology they employ. The share of AI-active firms grew from 1\% in 2016 to 12\% in 2024, with acceleration after 2022. We document a structural transformation: the ecosystem is shifting from specialized AI core technology providers toward broader AI adopters, signaling widespread diffusion. While adoption is concentrated among larger, younger, knowledge-intensive firms in urban innovation clusters, workforce skills emerge as a key factor associated with AI adoption. Our skill-level analysis suggests that foundational Data skills form the necessary base for adoption, while specialized AI skills act as strong complements.

Versions: IZA Discussion Paper No 18434

Data: https://github.com/MAP-AI-data/data

Abstract: The capabilities of AI have expanded rapidly in recent years; yet, our understanding how AI affects labor demand remains very limited. We use 31 million online job ads from four European countries to investigate how the demand for skills and occupations has shifted in response to AI. Our analysis relies on advanced ML models to extract and classify skills from job ads in multiple languages. We document a significant growth in the demand for AI, data and prediction skills in exposed occupations, but a decline in social skills since 2018. We also observe significant shifts in the skill sets of exposed occupations pointing towards greater skill specialization. Finally, we show that there is some indication that there is exposed occupations become less labor-intensive, but that employers demand more workers in these occupations.  

Abstract: We study how firm-level technology adoption affects worker outcomes using linked employer–employee data for Germany that combine administrative records with a survey of 2,032 establishments (2011–2016). We classify technologies into established digital and frontier technologies (e.g., AI, AR, 3D printing) and estimate their causal effects using an instrumental-variables strategy that exploits firms’ pre-adoption technological readiness, measured by the historical share of workers with technology-related skills. Technology adoption increases employment stability and wages, with substantially larger gains from established digital technologies. Effects are highly heterogeneous: workers in occupations undergoing task restructuring and those performing complex tasks benefit most. Crucially, returns depend on firms’ deployment strategies. Technologies that augment labor generate sizable gains, whereas substitutive adoption yields limited benefits. These results highlight that the effects of technological change depend on how technologies are integrated into production.

Press (based on older version): IZA Newsroom, NBC

Versions: earlier version published as IZA Discussion Paper No 14626 and ZEW Discussion Paper No. 21-073.