Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models

Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models
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检验半参数双变量概率模型中不存在未观察到的混杂因素的假设

DOI:
10.1007/s00180-013-0458-x
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发表时间:
2013
影响因子:
1.3
通讯作者:
Marra G
Marra G
中科院分区:
数学4区
文献类型:
--
作者:
Marra G

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拉格朗日乘数和瓦尔德检验的假设没有未观察到的混杂推广到半参数递归和样本选择的二元概率模型的背景下。通过蒙特卡罗研究,使用几种情况检查了测试的有限样本量特性:正确的模型规格,分布和功能错误规格,有和没有排除限制。模拟结果为实证分析提供了一些重要的指导。测试使用两个数据集进行说明,其中出现了未观察到的混淆问题。
Lagrange multiplier and Wald tests for the hypothesis of absence of unobserved confounding are extended to the context of semiparametric recursive and sample selection bivariate probit models. The finite sample size properties of the tests are examined through a Monte Carlo study using several scenarios: correct model specification, distributional and functional misspecification, with and without an exclusion restriction. The simulation results provide some guidelines which may be important for empirical analysis. The tests are illustrated using two datasets in which the issue of unobserved confounding arises.
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