A smoothed least squares estimator for threshold regression models
A smoothed least squares estimator for threshold regression models
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DOI：
10.1016/j.jeconom.2006.11.002
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发表时间：
2007-12-01
影响因子：
6.3
通讯作者：
Linton, Oliver
中科院分区：
文献类型：
--
作者：
Seo, Myung Hwan;Linton, Oliver
本文提出了门限回归模型参数的一种平滑最小二乘估计。我们的模型概括了汉森[2000]中考虑的情况。样本分割和阈值估计。Econometrica 68，575-603]允许阈值取决于观察到的回归变量的线性指数，从而允许离散变量进入。我们也不认为阈值效应小到可以忽略不计。我们的估计被证明是一致的，渐近正态的，从而促进标准的推断技术的基础上估计的标准误差或标准的引导的斜率和阈值参数。(c)2006 Elsevier B. V.保留所有权利。
We propose a smoothed least squares estimator of the parameters of a threshold regression model. Our model generalizes that considered in Hansen [2000. Sample splitting and threshold estimation. Econometrica 68, 575-603] to allow the thresholding to depend on a linear index of observed regressors, thus allowing discrete variables to enter. We also do not assume that the threshold effect is vanishingly small. Our estimator is shown to be consistent and asymptotically normal thus facilitating standard inference techniques based on estimated standard errors or standard bootstrap for the slope and threshold parameters. (c) 2006 Elsevier B.V. All rights reserved.