暨南IESR郑立助理教授的合作论文被数量经济学著名期刊JBES接受发表

近日，暨南大学经济与社会研究院助理教授郑立的合作论文“Optimal Model Averaging of Mixed-Data Kernel-Weighted Spline Regressions”（合作者：Jeffrey S. Racine, Qi Li, Dalei Yu）被数量经济学著名期刊Journal of Business and Economic Statistics 接受发表。

Abstract

Model averaging has a rich history dating from its use for combining forecasts from time-series models (Bates and Granger) and presents a compelling alternative to model selection methods. We propose a frequentist model averaging procedure defined over categorical regression splines (Ma, Racine, and Yang) that allows for mixed-data predictors, as well as nonnested and heteroscedastic candidate models. We demonstrate the asymptotic optimality of the proposed model averaging estimator, and develop a post-averaging inference theory for it. Theoretical underpinnings are provided, finite-sample performance is evaluated, and an empirical illustration reveals that the method is capable of outperforming a range of popular model selection criteria in applied settings. An R package is available for practitioners (Racine).

个人简介

郑立，现任暨南大学经济与社会研究院助理教授，于美国德州农工大学获得博士学位，研究领域为计量经济学、实证产业组织。研究成果发表于Journal of Business and Economic Statistics等国际权威期刊，主持国家自然科学基金青年项目。

来源：暨南大学经济与社会研究院

转自：“医科研”微信公众号

如有侵权，请联系本站删除！