• 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 | Identification in a Binary Choice Panel Data Model with a Predetermined Covariate
Seminar

Identification in a Binary Choice Panel Data Model with a Predetermined Covariate


  • Series
    Erasmus Econometric Institute Series
  • Speaker(s)
    Bryan Graham (University of California, Berkeley, United States)
  • Field
    Econometrics
  • Location
    Erasmus University Rotterdam, Campus Woudestein, Langeveld room 2.14
    Rotterdam
  • Date and time

    October 05, 2023
    12:00 - 13:00

Abstract

We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter θ, whereas the distribution of unit-specific heterogeneity, as well as the feedback process that maps lagged outcomes into future covariate realizations, are left unrestricted. We provide a simple condition under which θ is never point-identified, no matter the number of time periods available. This condition is satisfied in most models, including the logit one. We also characterize the identified set of θ and show how to compute it using linear programming techniques. While θ is not generally point-identified, its identified set is informative in the examples we analyze numerically, suggesting that meaningful learning about θ may be possible even in short panels with feedback. As a complement, we report calculations of identified sets for an average partial effect, and find informative sets in this case as well. Joint paper with Stéphane Bonhomme, and Kevin Dano.