What are the reasons behind the global trends in corporate margins and market concentration?
This article wishes to provide guidance on how the new vertical restraints linked to e-commerce should be treated and recommendations over the priorities and challenges that need to be addressed.
Empirical trends in markups and market power: their implications for productivity and growth
How can Europe catch up on the global electric vehicle race?
The electrification of vehicles has become a key trend in the automotive sector, driven by clean energy and climate-change concerns. In a scenario of further proliferation of electric vehicles, the authors here consider how Europe might best attempt to catch and overtake other countries’ manufacturers and suppliers in the development race.
Bruegel fellows Reinhilde Veugelers and Simone Tagliapietra elaborate on the recent Policy Contribution they co-authored on the European automotive industry in the light of the global electric vehicle revolution.
Machine learning and artificial intelligence (AI) systems are rapidly being adopted across the economy and society. Early excitement about the benefits of these systems has begun to be tempered by concerns about the risks that they introduce.
With 2018 drawing to a close, and the dawn of 2019 imminent, Bruegel's scholars reflect on the economic policy developments we can expect in the new year – one that brings with it the additional uncertainty of European elections.
This Policy Contribution investigates the position of the European automotive industry in a scenario in which electrification substantially progresses. Europe cannot follow China in the adoption of centrally-planned industrial policy measures. But it certainly can and should do more to stimulate the transformation of its automotive industry through more ambitious policies.
How is global competition policy evolving given the challenges of the digital era?
What is the place of civil society in the digital age as well as the role of technology in society?
Machine learning (ML), together with artificial intelligence (AI), is a hot topic. Economists have been looking into machine learning applications not only to obtain better prediction, but also for policy targeting. We review some of the contributions.