3 papers
econ.EM2025
Semiparametric inference for impulse response functions using double/debiased machine learning
Daniele Ballinari, Alexander Wehrli
We introduce a double/debiased machine learning estimator for the impulse response function in settings where a time series of interest is subjected to multiple discrete treatments…
econ.EM2025
Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration
Daniele Ballinari, Nora Bearth
In the last decade, machine learning techniques have gained popularity for estimating causal effects. One machine learning approach that can be used for estimating an average treat…
econ.EM2024
Calibrating doubly-robust estimators with unbalanced treatment assignment
Daniele Ballinari
Machine learning methods, particularly the double machine learning (DML) estimator (Chernozhukov et al., 2018), are increasingly popular for the estimation of the average treatment…