Sheikhi Ayyub, Bahador Fatemeh, Arashi Mohammad
Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University, Kerman, Iran.
Department of Statistics, Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran.
J Appl Stat. 2020 Oct 26;49(3):709-721. doi: 10.1080/02664763.2020.1837084. eCollection 2022.
In situations that the predictors are correlated with the error term, we propose a bridge estimator in the two-stage least squares estimation. We apply this estimator to overcome the multicollinearity and sparsity of the explanatory variables, when the endogeneity problem is present.The proposed estimator was applied to modify the Durbin-Wu-Hausman (DWH) test of endogeneity in the presence of multicollinearity. To compare our modified test with the existing DWH for detection of an endogenous problem in multi-collinear data, some numerical assessments are carried out. The numerical results showed that the proposed estimators and the suggested test perform better for the multi-collinear data. Finally, a genetical data set is applied for illustration the our results by estimating the coefficients parameters in the presence of endogeneity and multicollinearity.
在预测变量与误差项相关的情况下，我们在两阶段最小二乘估计中提出了一种桥梁估计量。当存在内生性问题时，我们应用此估计量来克服解释变量的多重共线性和稀疏性。所提出的估计量被用于修正存在多重共线性时的内生性的杜宾 - 吴 - 豪斯曼（DWH）检验。为了将我们修正后的检验与现有的用于检测多重共线数据中内生性问题的DWH检验进行比较，我们进行了一些数值评估。数值结果表明，所提出的估计量和建议的检验对于多重共线数据表现更好。最后，通过在存在内生性和多重共线性的情况下估计系数参数，应用一个遗传数据集来说明我们的结果。
