Does the matching between workers and jobs help explain productivity differentials across firms? To address this question we develop a job-worker allocation quality measure (JAQ) by combining employer-employee administrative data with machine learning techniques. The proposed measure is...

The Greek economy has so far failed to shift its production structure towards more complex, high value-added activities incorporating knowledge-intensive practices. Greece lacks a systemic “activating knowledge” dimension. Given the country’s low performance in innovation and knowledge...

Politicians, the media, and the public express concern that immigrants depress wages by competing with native workers, but 30 years of empirical research provide little supporting evidence to this claim. Most studies for industrialized countries have found no effect on wages, on average, and...

This study examines the causal influence of digital technologies, specifically operational (ODT) and information digital technologies (IDT), on firms’ employment structure using Italian firm-level data. It employs a unique empirical approach, constructing instrumental variables based on...

We analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive...

We investigate the impact of product market competition on firms’ automation investments. We use a rich combination of micro-data on Portuguese exporters and exploit a novel source of variation in the degree of competition they face – a tariff liberalization between the European Union and...

Which types of human capital influence the adoption of advanced technologies? We study the skill-biased adoption of information and communication technologies (ICT) across two waves in the UK. Specifically, we compare the "new wave" of cloud and machine learning / AI technologies during the...