106 citations · 280 across the 5 of their papers we have counts for
5 papers
On the Role of the Zero Conditional Mean Assumption for Causal Inference in Linear Models
Federico Crudu, Michael C. Knaus, Giovanni Mellace +1
Many econometrics textbooks imply that under mean independence of the regressors and the error term, the OLS parameters have a causal interpretation. We show that even when this as…
Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments
Phillip Heiler, Michael C. Knaus
Binary treatments are often ex-post aggregates of multiple treatments or can be disaggregated into multiple treatment versions. Thus, effects can be heterogeneous due to either eff…
Double Machine Learning based Program Evaluation under Unconfoundedness
Michael C. Knaus
This paper reviews, applies and extends recently proposed methods based on Double Machine Learning (DML) with a focus on program evaluation under unconfoundedness. DML based method…
Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence
Michael C. Knaus, Michael Lechner, Anthony Strittmatter
We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Ca…
Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach
Michael Knaus, Michael Lechner, Anthony Strittmatter
We systematically investigate the effect heterogeneity of job search programmes for unemployed workers. To investigate possibly heterogeneous employment effects, we combine non-exp…