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The Numerical Simulation of Improving Parameter Estimation by Instrumental Variable Method

机译:工具变量法改进参数估计的数值模拟

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In this paper the stochastic explanatory variables problem is studied using Monte-Carlo method.Taking a linear regression model with intercept of 3, slope of 4 as an example, whose random error in standard normal distribution, it is verified that parameter estimators are biased, especially the average relative error of estimator of slope is significantly large, as more than 10%, when random explanatory variables are in different contemporaneously correlated with random error item.When the instrumental variables, independent with random error item and in varying degrees related to random explanatory variable, is used, the estimation accuracy of the slope are significantly improved and the relative error dropped to less than 4%, but the estimation accuracy of the intercept term no significant improvement using the instrumental variable method.
机译:本文采用蒙特卡洛方法研究了随机解释变量问题。以线性截距为3,斜率为4的线性回归模型为例,该模型的标准正态分布具有随机误差,证明参数估计量存在偏差。特别是当随机解释变量与随机误差项同时相关时,斜率估计量的平均相对误差非常大,超过10%。当工具变量与随机误差项独立且在不同程度上与随机误差相关时使用解释变量,斜率的估计精度显着提高,相对误差降至4%以下,但是使用工具变量法对截距项的估计精度没有显着提高。

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