Semiparametric estimation of the Box–Cox transformation model

In this paper, I propose a semiparametric estimation procedure for the Box–Cox transformation model. I show a global identification result under mild conditions that allow conditional heteroskedastic error terms. The proposed estimator minimizes a second order U‐process and does not require any user‐chosen values such as a smoothing parameter that sometimes induces unstable inference result. With a slight modification, it can also be applied to …