Threshold Regression with Endogeneity for Short Panels

被引：2

作者：

Gorgens, Tue ^{[1
]}

Wurtz, Allan H. ^{[2
,3
]}

机构：

[1] Australian Natl Univ, Res Sch Econ, Acton, ACT 2601, Australia

[2] Aarhus Univ, CREATES, Fuglesangs Alle 4, DK-8210 Aarhus V, Denmark

[3] Aarhus Univ, Dept Econ & Business Econ, Fuglesangs Alle 4, DK-8210 Aarhus V, Denmark

来源：

ECONOMETRICS | 2019年 / 7卷 / 02期

基金：

澳大利亚研究理事会;

关键词：

threshold regression; dynamic models; endogeneity; panel data; GMM estimation; integrated difference kernel IDK estimator; superconsistency; DYNAMIC PANELS; MODELS;

D O I：

10.3390/econometrics7020023

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper considers the estimation of dynamic threshold regression models with fixed effects using short panel data. We examine a two-step method, where the threshold parameter is estimated nonparametrically at the N-rate and the remaining parameters are estimated by GMM at the -rate. We provide simulation results that illustrate advantages of the new method in comparison with pure GMM estimation. The simulations also highlight the importance of the choice of instruments in GMM estimation.

引用

页数：8

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