论文标题
CSA2SLS：使用Stata的许多乐器的完整子集方法
csa2sls: A complete subset approach for many instruments using Stata
论文作者
论文摘要
我们开发一个stata命令$ \ texttt {csa2sls} $，该{CSA2SLS} $在Lee and Shin（2021）中实现完整子集的平均两个阶段最小二乘（CSA2SLS）估算器。 CSA2SLS估计器是两阶段最小二乘估计器的替代方案，该估计值可以补救由许多相关仪器引起的偏差问题。我们进行蒙特卡洛模拟，并确认CSA2SL估计量同时减少了平方误差和估计偏差，而估计偏置则大大减少了仪器相关时。我们通过经验应用程序说明了Stata中$ \ texttt {csa2sls} $的用法。
We develop a Stata command $\texttt{csa2sls}$ that implements the complete subset averaging two-stage least squares (CSA2SLS) estimator in Lee and Shin (2021). The CSA2SLS estimator is an alternative to the two-stage least squares estimator that remedies the bias issue caused by many correlated instruments. We conduct Monte Carlo simulations and confirm that the CSA2SLS estimator reduces both the mean squared error and the estimation bias substantially when instruments are correlated. We illustrate the usage of $\texttt{csa2sls}$ in Stata by an empirical application.
