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Are you a BA or MA student interested in our Master in Economic Research or PhD in Economy programs?
Would you like to learn more about the curriculum or the admission process?

Let us invite you to Gaudeamus Brno educational fair on November 1-2, 2022.
You will find as at the Charles University´s stand.

Let us invite you to a Brown Bag Seminar by Alena Skolkova (CERGE-EI PhD student)
on November 2, 2022, at 13:00 in room 402

You can join also online: 
Lifesize link: https://call.lifesizecloud.com/16176658, Passcode: 5594

Presenter: Alena Skolkova

Title: "Elastic-Net for Instrumental Variables Regression"

Abstract: Instrumental variables (IV) are commonly applied for identification of treatment effects and policy evaluation. The use of many informative instruments improves the estimate accuracy. However, dealing with high-dimensional sets of instrumental variables of unknown strength may be complicated and requires instrument selection or regularization of the first-stage regression. Currently, lasso is established as one of the most popular regularization techniques relying on the assumption of approximate sparsity. I investigate the relative performance of the lasso and elastic-net estimators for fitting the first stage as part of IV estimation. As elastic-net involves ridge-type regularization, it generally improves upon lasso in finite samples when correlations among the instrumental variables are significant. In addition, by attaining a balance between lasso and ridge penalties, elastic-net accommodates deviations of the first-stage equation from a sparse structure, thus being a robust alternative to lasso that heavily relies on the sparsity assumption. I show the asymptotic equivalence of the IV estimators that employ the lasso and elastic-net first-stage estimates under sparsity. Via a Monte Carlo study I demonstrate the robustness of the IV estimator based on the elastic-net first-stage estimates to correlation among the instruments, and deviations from sparsity. Finally, I provide an empirical example that employs the elastic-net IV estimator for estimation of return to schooling.

This project is co-financed by the European Union.