Weak identification in probit models with endogenous covariates

被引:1
|
作者
Dufour, Jean-Marie [1 ,2 ]
Wilde, Joachim [3 ]
机构
[1] McGill Univ, Dept Econ, Ctr Interuniv Rech Anal Org CIRANO, Leacock Bldg,Room 414,855 Sherbrooke St West, Montreal, PQ H3A 2T7, Canada
[2] McGill Univ, CIREQ, Leacock Bldg,Room 414,855 Sherbrooke St West, Montreal, PQ H3A 2T7, Canada
[3] Fachbereich Wirtschaftswissensch, Rolandstr 8, D-49069 Osnabruck, Germany
基金
加拿大自然科学与工程研究理事会;
关键词
Probit model; Weak identification; z-test; GENERALIZED-METHOD; GMM ESTIMATION; INFERENCE; ECONOMETRICS; INSTRUMENTS; RECESSIONS; PARAMETERS; LIKELIHOOD; FAILURE; MOMENTS;
D O I
10.1007/s10182-018-0325-8
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Weak identification is a well-known issue in the context of linear structural models. However, for probit models with endogenous explanatory variables, this problem has been little explored. In this paper, we study by simulating the behavior of the usual z-test and the LR test in the presence of weak identification. We find that the usual asymptotic z-test exhibits large level distortions (over-rejections under the null hypothesis). The magnitude of the level distortions depends heavily on the parameter value tested. In contrast, asymptotic LR tests do not over-reject and appear to be robust to weak identification.
引用
收藏
页码:611 / 631
页数:21
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