Seminar

Counterfactual Identification and Latent Space Enumeration in Discrete Outcome Models

Speaker

Jiaying Gu (Toronto)

Date & Time

25 October 2022

Type

Seminar

Venue

The Institute for Fiscal Studies
7 Ridgmount Street,
Fitzrovia,
London,
WC1E 7AE

Abstract: This paper provides a unified framework for partial identification of counterfactual parameters in a general class of discrete outcome models allowing for endogenous regressors and multidimensional latent variables, all without parametric distributional assumptions. Our main theoretical result is that, when the covariates are discrete, the infinite-dimensional latent variable distribution can be replaced with a finite-
dimensional version that is equivalent from an identification perspective. The finite-dimensional latent variable distribution is constructed in practice by enumerating regions of the latent variable space with a
new and efficient cell enumeration algorithm for hyperplane arrangements. We then show that bounds on a certain class of counterfactual parameters can be computed by solving a sequence of linear programming
problems, and show how the researcher can introduce additional assumptions as constraints in the linear programs. Finally, we apply the method to a mobile phone choice example with heterogeneous choice
sets, as well as an airline entry game example.

Click here for papers.

Venue address:

The Institute for Fiscal Studies 
7 Ridgmount Street  London WC1E 7AE

*Please use the IFS Conference entrance, to the left of the car parking area, and not the glass CILIP entrance.