November 20th, Yassine Lefouili's HDR Defense

November 20, 2020 Research

Yassine LEFOUILI, assistant professor at Toulouse Capitole 1 University will defend his thesis (Habilitation à diriger des recherches) on Friday 20th November at 2:00 pm, by zoom meeting.

Title : « Essais en économie industrielle et économie du droit »

Memberships are :

  • Marie-Laure Allain (Senior researcher CNRS, CREST)
  • Vincenzo Denicolo (Professor University of Bologna)
  • Thierry Pénard (Professor University of Rennes I)
  • Bruno Jullien (Senior researcher CNRS, TSE)
  • Doh-Shin Jeon (Professor at TSE)

Abstract:

The research presented in this HDR application is organized in five parts. The first part includes three papers dealing with competition policy in two-sided markets. Specifically, these papers analyze the competitive effects of collusion, horizontal mergers, and tying in these markets. The second part studies various aspects of the relationship between competition and investment. More precisely, it includes three papers that investigate the impact of mergers and yardstick competition on innovation and one paper that deals with the way merger policy should be designed to account for firms’ incentives to enter the market. The third part studies cross-licensing agreements, as well as other upstream bilateral agreements, among firms interacting in downstream markets. The fourth part includes two papers on the economics of privacy. The first one investigates firms’ incentives to protect customer data and the welfare effects of regulations improving transparency and consumer control. The second one studies the impact of a regulation that restricts a dominant firm’s ability to disclose personal data on its incentives to improve quality and social welfare. Finally, the fifth part pertains to litigation and settlement. It includes papers on the determinants of forum shopping in patent litigation, the impact of fee shifting and bifurcation on litigation and settlement, and the optimal mechanism to license uncertain patents.non-exclusively) as a function of (the distribution of) that sufficient statistic.