The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors with large supports used in related papers. One of our two identification arguments is constructive. Both approaches may be applied to other choice models with random coefficients.
Authors: Patrick Bajari, Jeremy Fox, Kyoo-il Kim, and Stephen P. Ryan
Journal of Econometrics, February 2012, Vol. 166, No. 2, pp. 204–212 (link)