A Note on Additive Separability and Latent Index Models of Binary Choice: Representation Results*
证明了一类非可分的潜指数函数可以等价表示为加性可分或线性指数函数，说明在二元选择模型中假设加性可分或线性潜指数函数比以往认为的限制更少。
Abstract The standard binary choice model in econometrics has the choice determined by a latent index crossing a threshold. The latent index is almost always assumed to be additively separable in observable and unobservable regressors, and most commonly linear in all regressors. This note provides a class of non‐separable latent index functions which will have equivalent representations as additively separable or linear index functions. These results demonstrate that assuming a linear or additively separable latent index function is less restrictive than previously recognized.