2 citations · 2 across the 3 of their papers we have counts for
3 papers
econ.EM2026
Reevaluating Causal Estimation Methods with Data from a Product Release
Justin Young, Eleanor Wiske Dillon
Recent developments in causal machine learning methods have made it easier to estimate flexible relationships between confounders, treatments and outcomes, making unconfoundedness…
stat.ML2025
A Meta-learner for Heterogeneous Effects in Difference-in-Differences
Hui Lan, Haoge Chang, Eleanor Dillon +1
We address the problem of estimating heterogeneous treatment effects in panel data, adopting the popular Difference-in-Differences (DiD) framework under the conditional parallel tr…
econ.EM2021★ 2 cited
Estimating the Long-Term Effects of Novel Treatments
Keith Battocchi, Eleanor Dillon, Maggie Hei +3
Policy makers typically face the problem of wanting to estimate the long-term effects of novel treatments, while only having historical data of older treatment options. We assume a…