Nonparametric Estimation in Random Coefficients Binary Choice Models
Nonparametric Estimation in Random Coefficients Binary Choice Models
This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for the random coefficients is developed, utilizing Fourier-Laplace series on spheres. This approach offers …