1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
From Average Effects to Targeted Assignment: A Causal Machine Learning Analysis of Swiss Active Labor Market Policies
Federica Mascolo, Nora Bearth, Fabian Muny +2
Active labor market policies are widely used by the Swiss government, enrolling over half of all unemployed individuals. This paper evaluates the effectiveness of Swiss programs in…
Beyond Baby Blues: The Child Penalty in Mental Health in Switzerland
Nora Bearth
This paper investigates the mental health penalty for women after childbirth in Switzerland. Leveraging insurance data, we employ a staggered difference-in-difference research desi…
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…
Causal Machine Learning for Moderation Effects
Nora Bearth, Michael Lechner
It is valuable for any decision maker to know the impact of decisions (treatments) on average and for subgroups. The causal machine learning literature has recently provided tools…