11 citations · 23 across the 7 of their papers we have counts for
7 papers
Fast Learning of Optimal Policy Trees
James Cussens, Julia Hatamyar, Vishalie Shah +1
We develop and implement a version of the popular "policytree" method (Athey and Wager, 2021) using discrete optimisation techniques. We test the performance of our algorithm in fi…
Exploring the heterogeneous impacts of Indonesia's conditional cash transfer scheme (PKH) on maternal health care utilisation using instrumental causal forests
Vishalie Shah, Julia Hatamyar, Taufik Hidayat +1
This paper uses instrumental causal forests, a novel machine learning method, to explore the treatment effect heterogeneity of Indonesia's conditional cash transfer scheme on mater…
Machine Learning for Staggered Difference-in-Differences and Dynamic Treatment Effect Heterogeneity
Julia Hatamyar, Noemi Kreif, Rudi Rocha +1
We combine two recently proposed nonparametric difference-in-differences methods, extending them to enable the examination of treatment effect heterogeneity in the staggered adopti…
Policy Learning with Rare Outcomes
Julia Hatamyar, Noemi Kreif
Machine learning (ML) estimates of conditional average treatment effects (CATE) can guide policy decisions, either by allowing targeting of individuals with beneficial CATE estimat…
Machine learning in policy evaluation: new tools for causal inference
Noemi Kreif, Karla DiazOrdaz
While machine learning (ML) methods have received a lot of attention in recent years, these methods are primarily for prediction. Empirical researchers conducting policy evaluation…
Evaluation of adaptive treatment strategies in an observational study where time-varying covariates are not monitored systematically
Noémi Kreif, Oleg Sofrygin, Julie Schmittdiel +5
In studies based on electronic health records (EHR), the frequency of covariate monitoring can vary by covariate type, across patients, and over time. This can lead to major challe…
Data-adaptive doubly robust instrumental variable methods for treatment effect heterogeneity
Karla DiazOrdaz, Rhian Daniel, Noemi Kreif
We consider the estimation of the average treatment effect in the treated as a function of baseline covariates, where there is a valid (conditional) instrument. We describe two dou…