Optimal linear discriminators for the discrete choice model in growing dimensions
维度增长下离散选择模型的最优线性判别器
Manski’s celebrated maximum score estimator for the discrete choice model, which is an optimal linear discriminator, has been the focus of much investigation in both the econometrics and statistics literatures, but its behavior under growing dimension scenarios largely remains unknown. This paper addresses that gap. Two different cases are considered: p grows with n but at a slow rate, that is, p/n→0; and p≫n (fast growth). In the binary response model, we recast Manski’s…