Deconvoluting Preferences and Errors: A Model for Binomial Panel Data

In many stated choice experiments researchers observe the random variables Vt, Xt, and Yt = 1{U + δ⊤Xt + εt < Vt}, t ≤ T, where δ is an unknown parameter and U and εt are unobservable random variables. We show that under weak assumptions the distributions of U and εt and also the unknown parameter δ can be consistently estimated using a sieved maximum likelihood estimation procedure.