csa2sls: A Complete Subset Approach for Many Instruments Using Stata
with Siha Lee (McMaster U), Julius Owusu (McMaster U), and Youngki Shin (McMaster U)
We develop a Stata command 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 squares error and the estimation bias substantially when instruments are correlated. We illustrate the usage of csa2sls in Stata by two empirical applications.Â