• Graduate program
  • Research
  • News
  • Events
    • Summer School
      • Climate Change
      • Gender in Society
      • Inequalities in Health and Healthcare
      • Business Data Science Summer School Program
      • Receive updates
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Conference: Consumer Search and Markets
    • Annual Tinbergen Institute Conference
  • Summer School
    • Climate Change
    • Gender in Society
    • Inequalities in Health and Healthcare
    • Business Data Science Summer School Program
    • Receive updates
  • Alumni
  • Magazine
Home | Events Archive | Optimal transportation through saddlepoints and some robustness issues
Seminar

Optimal transportation through saddlepoints and some robustness issues


  • Series
    Erasmus Econometric Institute Series
  • Speaker(s)
    Elvezio Ronchetti (University of Geneva, Switzerland)
  • Field
    Econometrics
  • Location
    Erasmus University Rotterdam, E building, room ET-14
    Rotterdam
  • Date and time

    November 16, 2023
    12:00 - 13:00

Abstract
We showcase some unexplored connections between saddlepoint approximations, measure transportation, and some key topics in information theory by reviewing selectively some fundamental results available in the literature. We start with the link between Esscher's tilting (which is a result rooted in information theory and that lies at the heart of saddlepoint approximations) and the solution of the dual Kantorovich problem (which lies at the heart of measure transportation theory) via the Legendre transform of the cumulant generating function. We then investigate these links in the framework of M-estimators and quantile regression. The unveiled connections offer the possibility to view saddlepoint approximations from different angles, putting under the spotlight the links to e.g. convex analysis (via the notion of duality) or differential geometry (via the notion of geodesic). Finally, we discuss some robustness issues of optimal transportation and their connections to penalization methods. Joint work with Davide La Vecchia and Andrej Ilievski.