文章基本信息

标题：Local M-estimation with discontinuous criterion for dependent and limited observations
本地全文：下载
作者：Myung Hwan Seo ; Taisuke Otsu
期刊名称：Econometrics Publications
印刷版ISSN：0969-4366
出版年度：2016
出版社：Suntory Toyota International Centre for Economics and Related Disciplines
摘要：This paper examines asymptotic properties of local M-estimators under three sets of high-level conditions. These conditions are sufficiently general to cover the minimum volume predictive region, conditional maximum score estimator for a panel data discrete choice model, and many other widely used estimators in statistics and econometrics. Specifically, they allow for discontinuous criterion functions of weakly dependent observations, which may be localized by kernel smoothing and contain nuisance parameters whose dimension may grow to infinity. Furthermore, the localization can occur around parameter values rather than around a fixed point and the observation may take limited values, which leads to set estimators. Our theory produces three different nonparametric cube root rates and enables valid inference for the local M-estimators, building on novel maximal inequalities for weakly dependent data. Our results include the standard cube root asymptotics as a special case. To illustrate the usefulness of our results, we verify our conditions for various examples such as the Hough transform estimator with diminishing bandwidth, maximum score-type set estimator, and many others.
关键词：cube root asymptotics ; maximal inequality ; mixing process ; partial identification ; parameter-dependent localization