1 code implementation • 18 Oct 2023 • Julia Hatamyar, Noemi Kreif, Rudi Rocha, Martin Huber
We combine two recently proposed nonparametric difference-in-differences methods, extending them to enable the examination of treatment effect heterogeneity in the staggered adoption setting using machine learning.
no code implementations • 1 Jul 2023 • Julia Hatamyar, Christopher F. Parmeter
Our ASCM results also suggest that the lifting of eviction moratoria had little to no impact on COVID-19 cases and deaths.
no code implementations • 10 Feb 2023 • 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 estimates, or as inputs to decision trees that optimise overall outcomes.
no code implementations • 13 Sep 2022 • Julia Hatamyar
I find that workplace breastfeeding legislation increases the likelihood of female labor force participation by 4. 2 percentage points in the two years directly following implementation.
