48 citations · 61 across the 6 of their papers we have counts for
3 papers · 1 filter
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India
Victor Chernozhukov, Mert Demirer, Esther Duflo +1
We propose strategies to estimate and make inference on key features of heterogeneous effects in randomized experiments. These key features include best linear predictors of the ef…
Double/Debiased/Neyman Machine Learning of Treatment Effects
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +3
Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016) provide a generic double/de-biased machine learning (DML) approach for obtaining valid inferential statements ab…
Double/Debiased Machine Learning for Treatment and Causal Parameters
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +4
Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well. Achieving this goal does not imply that these metho…