We extend the instrumental variable method for the mean regression models to linear quantile regression models with errors-in-variables.The proposed estimator is consistent and asymptotically normally distributed under some fairly general conditions.Moreover,this approach is practical and easy to implement.Simulation studies show that the finite sample performance of the estimator is satisfactory.The method is applied to a real data study of education and wages.
errors in variablesinstrumental variablesleast absolute deviationmeasurement errorquantile regression
关静、王力群
展开 >
天津大学数学学院,天津,300350
曼尼托巴大学统计系,加拿大,R3T 2N2
变量误差 工具变量 最小绝对偏差 测量误差 分位数回归
project was supported by the Natural Sciences and Engineering Research Council of Canada
NETL
NSTL
万方数据
维普
