The Employment Impact of Emerging Digital Technologies

Abstract

This paper measures the exposure of industries and occupations to a broad set of emerging digital technologies and estimates their impact on European employment. Using a novel approach that leverages sentence transformers, we calculate exposure scores based on the semantic similarity between patents and international standard classifications, creating the open–access ‘TechXposure’ database. Through a shift–share design, we instrument regional exposure to estimate the effects of these technologies on employment across European regions. We find a net positive impact, with growth in low- and high-skilled employment at the expense of middleskilled jobs, suggesting ongoing job polarization. At the technology level, we observe significant heterogeneity: robots and machine learning negatively impact employment (except for highskilled workers), while workflow management and information processing systems have positive effects. Our results suggest that focusing narrowly on specific technologies like AI and robots may overlook broader positive employment impacts stemming from complementarities among diverse digital technologies.

Keywords: occupation exposure, industry exposure, text as data, natural language processing, sentence transformers, emerging digital technologies, automation, employment

JEL Classification: C810, O310, O330, O340, J240, O520, R230