Mediation analysis
M Huber - Handbook of labor, human resources and population …, 2020 - Springer
Mediation analysis aims at evaluating the causal mechanisms through which a treatment or
intervention affects an outcome of interest. The goal is to disentangle the total treatment …
intervention affects an outcome of interest. The goal is to disentangle the total treatment …
A review of causal mediation analysis for assessing direct and indirect treatment effects
M Huber - 2019 - folia.unifr.ch
Mediation analysis aims at evaluating the causal mechanisms through which a treatment or
intervention affects an outcome of interest. The goal is to disentangle the total treatment …
intervention affects an outcome of interest. The goal is to disentangle the total treatment …
Identifying causal mechanisms (primarily) based on inverse probability weighting
M Huber - Journal of Applied Econometrics, 2014 - Wiley Online Library
This paper demonstrates the identification of causal mechanisms of a binary treatment under
selection on observables,(primarily) based on inverse probability weighting; ie we consider …
selection on observables,(primarily) based on inverse probability weighting; ie we consider …
Identifying mechanisms behind policy interventions via causal mediation analysis
Causal analysis in program evaluation has primarily focused on the question about whether
or not a program, or package of policies, has an impact on the targeted outcome of interest …
or not a program, or package of policies, has an impact on the targeted outcome of interest …
Testing instrument validity for LATE identification based on inequality moment constraints
We derive testable implications of instrument validity in just identified treatment effect models
with endogeneity and consider several tests. The identifying assumptions of the local …
with endogeneity and consider several tests. The identifying assumptions of the local …
Dynamic regression discontinuity under treatment effect heterogeneity
YC Hsu, S Shen - Quantitative Economics, 2024 - Wiley Online Library
Regression discontinuity is a popular tool for analyzing economic policies or treatment
interventions. This research extends the classic static RD model to a dynamic framework …
interventions. This research extends the classic static RD model to a dynamic framework …
Evaluating (weighted) dynamic treatment effects by double machine learning
We consider evaluating the causal effects of dynamic treatments, ie, of mul-tiple treatment
sequences in various periods, based on double machine learning to control for observed …
sequences in various periods, based on double machine learning to control for observed …
Partial identification of local average treatment effects with an invalid instrument
CA Flores, A Flores-Lagunes - Journal of Business & Economic …, 2013 - Taylor & Francis
We derive nonparametric bounds for local average treatment effects (LATE) without
imposing the exclusion restriction assumption or requiring an outcome with bounded …
imposing the exclusion restriction assumption or requiring an outcome with bounded …
Why do tougher caseworkers increase employment? The role of program assignment as a causal mechanism
Previous research found that less accommodating caseworkers are more successful in
placing unemployed workers into employment. This paper explores the causal mechanisms …
placing unemployed workers into employment. This paper explores the causal mechanisms …
Causal pitfalls in the decomposition of wage gaps
M Huber - Journal of Business & Economic Statistics, 2015 - Taylor & Francis
The decomposition of gender or ethnic wage gaps into explained and unexplained
components (often with the aim to assess labor market discrimination) has been a major …
components (often with the aim to assess labor market discrimination) has been a major …