2 citations · 3 across the 7 of their papers we have counts for
8 papers · 1 filter
Sharp Bounds and Inference in Sample Selection Models with Treatment Endogeneity
Yingying Dong, Phillip Heiler
This paper provides partial identification and inference for treatment effects in nonparametric sample selection models with endogenous treatment and (weak) sample selection monoto…
Heterogeneity Analysis with Heterogeneous Treatments
Phillip Heiler, Michael C. Knaus
Analysis of effect heterogeneity at the group level is standard practice in empirical treatment evaluation. However, treatments analyzed are often aggregates of multiple underlying…
Treatment Evaluation at the Intensive and Extensive Margins
Phillip Heiler, Asbjørn Kaufmann, Bezirgen Veliyev
This paper provides a solution to the evaluation of treatment effects in selective samples when neither instruments nor parametric assumptions are available. We provide sharp bound…
A Guide to Impact Evaluation under Sample Selection and Missing Data: Teacher's Aides and Adolescent Mental Health
Simon Calmar Andersen, Louise Beuchert, Phillip Heiler +1
This paper is concerned with identification, estimation, and specification testing in causal evaluation problems when data is selective and/or missing. We leverage recent advances…
Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization
Phillip Heiler
We propose a method for estimation and inference for bounds for heterogeneous causal effect parameters in general sample selection models where the treatment can affect whether an…
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…
Efficient Covariate Balancing for the Local Average Treatment Effect
Phillip Heiler
This paper develops an empirical balancing approach for the estimation of treatment effects under two-sided noncompliance using a binary conditionally independent instrumental vari…
Shrinkage for Categorical Regressors
Phillip Heiler, Jana Mareckova
This paper introduces a flexible regularization approach that reduces point estimation risk of group means stemming from e.g. categorical regressors, (quasi-)experimental data or p…