Averaged estimator, many weak instruments, class estimator, k-class estimator
Analysis | Econometrics | Economics | Mathematics
We develop averaged instrumental variables estimators as a way to deal with many weak instruments. We propose a weighted average of the preliminary k-class estimators, where each estimator is obtained using different subsets of the available instrumental variables. The averaged estimators are shown to be consistent and to satisfy asymptotic normality. Furthermore, its approximate mean squared error reveals that using a small number of instruments for each preliminary k-class estimator reduces the finite sample bias, while averaging prevents the variance from inflating. Monte Carlo simulations find that the averaged estimators compare favorably with alternative instrumental-variable-selection approaches when the strength levels of individual IV are similar with each other.
Lee, Yoonseok and Zhou, Yu, "Averaged Instrumental Variables Estimators" (2015). Center for Policy Research. 212.
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.