We propose a framework for doing sharp nonparametric welfare analysis in discrete choice models with unobserved variation in choice sets. We recover jointly the distribution of choice sets and the distribution of preferences. To achieve this we use panel data on choices and assume nestedness of the latent choice sets. Nestedness means that choice sets of different decision makers are ordered by inclusion. It may be satisfied, for instance, when it is the result of either a search process or unobserved feasibility. Using variation of the uncovered choice sets we show how to do ordinal (nonparametric) welfare comparisons. When one is willing to make additional assumptions about preferences, we show how to nonparametrically identify the ranking over average utilities in the standard multinomial choice setting.
We propose a framework for doing sharp nonparametric welfare analysis in discrete choice models with unobserved variation in choice sets. We recover jointly the distribution of choice sets and the distribution of preferences. To achieve this we use panel data on choices and assume nestedness of the latent choice sets. Nestedness means that choice sets of different decision makers are ordered by inclusion. It is satisfied, for instance, when the choice set variation is the result of either a search process or unobserved feasibility. Using variation of the uncovered choice sets we show how to do ordinal (nonparametric) welfare comparisons. When one is willing to make additional assumptions about preferences, we show how to nonparametrically identify the ranking over average utilities in the standard multinomial choice setting.
R
may be
is
R
it
the choice set variation