doctoral student in Economics and Statistics
Current Research Projects
Synthetic Controls in Action (with Alberto Abadie) (Link)
Synthetic instruments in DiD designs with unmeasured confounding (with Ahmet Gulek) (Link)
Bayesian and Frequentist Inference for Synthetic Controls (with Ignacio Martinez) (Link) (R-Package)
Predictor Selection for Synthetic Controls (arxiv)
Bagged Polynomial Regression and Neural Networks (with Sylvia Klosin) (arxiv)
Published Work
Stretching the Net: Multidimensional Regularization (Econometric Theory, 2021)
In the paper I derive asymptotic risk (expected loss) results for shrinkage estimators with multidimensional regularization in high-dimensional settings.
I show that as the number of parameters to estimate grows the empirical loss converges to the oracle-optimal risk.
New Research!
"Predictor selection for synthetic controls." arxiv
This paper proposes the use of a sparse synthetic control procedure that penalizes the number of predictors used in generating the counterfactual to select the most important predictors. We derive, in a linear factor model framework, a new model selection consistency result and show that the penalized procedure has a faster mean squared error convergence rate.