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PublicationArticle (with peer review)

Direct and indirect effects of private- and government-sponsored venture capital

Abstract

Starting from the discourse on the impact of private and governmental venture capital investments, we examine the effects of different types of venture capital on firms’ sales, employment and investment. Our results show that both private and governmental venture capital investments boost firm sales with a delay of 2–3 years. The results suggest that VC impacts sales primarily through efficiency gains and to some extent, investments in physical capital investments, whereas no employment effects can be traced. Finally, we find indications of governmental VC investors being more prone to make follow-up investments in stagnating, non-growing firms than private investors.

Engberg, E., Gustavsson Tingvall, P. & Halvarsson, D. (2021). Direct and indirect effects of private- and government-sponsored venture capital. Empirical Economics, 60, 701-735. DOI: 10.1007/s00181-019-01770-w

Details

Author: Engberg, E., Gustavsson Tingvall, P. & Halvarsson, D.
Publication year: 2021
Published in: Empirical Economics

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Ph.D.
Daniel Halvarsson
+460760184541daniel.halvarsson@ratio.se

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Working Paper No. 380. Artificial Intelligence, hiring and employment: Job postings evidence from Sweden.

Engberg, E., Hellsten, M., Javed, F., Lodefalk, M., Sabolová, R., Schroeder, S.

Publication year

2024

Published in

Ratio Working Paper Series.

Abstract

This paper investigates the impact of artificial intelligence (AI) on hiring and employment, using the universe of job postings published by the Swedish Public Employment Service from 2014-2022 and universal register data for Sweden. We construct a detailed measure of AI exposure according to occupational content and find that establishments exposed to AI are more likely to hire AI workers. Survey data further indicate that AI exposure aligns with greater use of AI services. Importantly, rather than displacing non-AI workers, AI exposure is positively associated with increased hiring for both AI and non-AI roles. In the absence of substantial productivity gains that might account for this increase, we interpret the positive link between AI exposure and non-AI hiring as evidence that establishments are using AI to augment existing roles and expand task capabilities, rather than to replace non-AI workers.

Article (with peer review)

Artificial intelligence, tasks, skills and wages: Worker-level evidence from Germany

Engberg, E., Koch, M., Lodefalk, M., & Schroeder, S.

Publication year

2025

Published in

Research Policy

Abstract

As a first step, the study documents novel evidence on changes in tasks and skills within occupations in Germany over the past two decades. It further identifies a distinct relationship between ex ante occupational work content and ex post exposure to artificial intelligence (AI) and automation through robots. Workers in occupations with high AI exposure perform different activities and face different skill requirements than workers in occupations primarily exposed to robots, suggesting that AI and robots substitute for different types of tasks and skills. The study also shows that changes in the task and skill content of occupations are related to their initial exposure to these technologies. Finally, using individual labour market biographies, the analysis investigates the relationship between AI exposure and wages. By examining the dynamic effects of AI exposure over time, the study finds positive associations with wages, with nuanced differences across occupational groups, thereby providing further insight into the substitutability and augmentability of AI.

Artificial Intelligence for Public Use

Lodefalk, M.; Engberg, E.; Lidskog, R.; Tang, A.

Publication year

2025

Published in

Örebro University School of Business Working Paper

Abstract

This paper investigates the economic and societal impacts of Artificial Intelligence (AI) in the public sector, focusing on its potential to enhance productivity and mitigate labour shortages. Employing detailed administrative data and novel occupational exposure measures, we simulate future scenarios over a 20-year horizon, using Sweden as an illustrative case. Our findings indicate that advances in AI development and uptake could significantly alleviate projected labour shortages and enhance productivity. However, outcomes vary substantially across sectors and organisational types, driven by differing workforce compositions. Complementing the economic analysis, we identify key challenges that hinder AI’s effective deployment, including technical limitations, organisational barriers, regulatory ambiguity, and ethical risks such as algorithmic bias and lack of transparency. Drawing from an interdisciplinary conceptual framework, we argue that AI’s integration in the public sector must address these socio-technical and institutional factors comprehensively. To unlock AI’s full potential, substantial investments in technological infrastructure, human capital development, regulatory clarity, and robust governance mechanisms are essential. Our study thus contributes both novel economic evidence and an integrated societal perspective, informing strategies for sustainable and equitable public-sector digitalisation.