• 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 | Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters
Seminar

Robust Tests of Model Incompleteness in the Presence of Nuisance Parameters


  • Location
    Erasmus University Rotterdam, E building, room ET-18
    Rotterdam
  • Date and time

    October 12, 2023
    12:00 - 13:00

Abstract

We develop a novel test of model incompleteness and analyze its asymptotic properties. A key observation is that one can define a least-favorable parametric model along which detecting local alternatives without knowing the selection mechanism is the hardest. The test builds on a score function constructed from such a model. The proposed procedure remains computationally tractable even in the presence of nuisance parameters because it suffices to estimate them only under the null hypothesis of model completeness.

We illustrate the test by applying it to a market entry model and a triangular model with a set-valued control function. Joint paper with Shuowen Chen.

Registration and more info about this seminar series here.