The recently derived Logit-Mixed Logit (LML) model captures unobserved preference heterogeneity seminonparametrically as a function of polynomials, step functions, and splines. This study contributes twofold in exploring and extending the usefulness of the LML specification. First, we conduct a...

This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox, Kim, Ryan, and Bajari (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its sparse nature observed in many applications. Recognizing...

This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox, Kim, Ryan, and Bajari (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its sparse nature observed in many applications. Recognizing...