统计与管理学院2015年学术报告第61期
【主 题】LASSO estimation of threshold autoregressive models
【报告人】张荣茂
浙江大学
【时 间】 2015年12月31日（星期四）10:00－11:00
【地 点】 上海财经大学统计与管理学院大楼1208室
【语 言】 英文
【摘 要】This talk will give a novel approach for estimating a threshold autoregressive (TAR) model with multiple-regimes and its large sample properties. By reframing the problem in a regression variable selection context, a least absolute shrinkage and selection operator (LASSO) procedure is proposed to estimate a TAR model with an unknown number of thresholds, where the computation can be performed efficiently. It is further shown that the number and the location of the thresholds can be consistently estimated. A near optimal convergence rate of the threshold parameters is also established. Simulation studies are conducted to assess the performance in finite samples. The results are illustrated with an application to the quarterly U.S. real GNP data over the period 1947-2009.
【邀请人】黄涛
