To build Discrete Choice Models, we collect and analyse either historical data (revealed preference) or experimental data (stated preference).

Discrete Choice Modelling

The bread-and-butter of our analysis toolkit. Includes any of the family of models explaining the choice behaviour of individuals and groups who face discrete economic alternatives. Depending on the project, we may use Multinomial Logit (MNL), Nested Logit, Mixed Logit (Random Parameters Logit), Probit, or an EBA model.