Similar Search Results

Nonparametric Bounds on Treatment Effects with Imperfect Instruments

Ban, Kyunghoon; Kédagni, Désiré - 2020

bounds on the average treatment effect when an imperfect instrument is available. As in Nevo and Rosen (2012), we assume that … the correlation between the imperfect instrument and the unobserved latent variables has the same sign as the correlation … the imperfect instrument is less endogenous than the treatment variable can help tighten the bounds. We also use the …

Persistent link: https://www.econbiz.de/10014092605

Treatment evaluation with multiple outcome periods under endogeneity and attrition

Frölich, Markus; Huber, Martin - 2014

Persistent link: https://www.econbiz.de/10010242778

Direct and indirect treatment effects : causal chains and mediation analysis with instrumental variables

Frölich, Markus; Huber, Martin - 2014

This paper discusses the nonparametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the...

Persistent link: https://www.econbiz.de/10010379279

Direct and indirect treatment effects : causal chains and mediation analysis with instrumental variables

Frölich, Markus; Huber, Martin - 2014

This paper discusses the nonparametric identi.cation of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the...

Persistent link: https://www.econbiz.de/10010382130

Bounding program benefits when participation is misreported

Tommasi, Denni; Zhang, Lina - 2020

In empirical research, measuring correctly the benefits of welfare interventions is incredibly relevant for policymakers as well as academic researchers. Unfortunately, the endogenous program participation is often misreported in survey data and standard instrumental variable techniques are not...

Persistent link: https://www.econbiz.de/10012243324

"Randomisation bias" in the medical literature : a review

Sianesi, Barbara - 2016

causal model. This ‘no randomisation bias’ assumption is generally untestable but if violated would undermine the causal …

Persistent link: https://www.econbiz.de/10011580011

Nonparametric instrumental variable methods for dynamic treatment evaluation

Berg, Gerard J. van den; Bonev, Petyo; Mammen, Enno - 2016

We develop a nonparametric instrumental variable approach for the estimation of average treatment effects on hazard rates and conditional survival probabilities, without model structure. We derive constructive identification proofs for average treatment effects under noncompliance and dynamic...

Persistent link: https://www.econbiz.de/10011453442

Nonparametric instrumental variable methods for dynamic treatment evaluation

Berg, Gerard J. van den; Bonev, Petyo; Mammen, Enno - 2016

We develop a nonparametric instrumental variable approach for the estimation of average treatment effects on hazard rates and conditional survival probabilities, without model structure.We derive constructive identification proofs for average treatment effects under noncompliance and dynamic...

Persistent link: https://www.econbiz.de/10011492188

Direct and indirect effects under sample selection and outcome attrition

Huber, Martin; Solovyeva, Anna - In: Econometrics : open access journal 8 (2020) 4/44, pp. 1-25

outcomes are only partially observed due to sample selection or outcome attrition. We assume sequential conditional … missing at random or instrumental variable assumptions on the outcome attrition process. Under these conditions, we derive … identification results for the effects of interest that are based on inverse probability weighting by specific treatment, mediator …

Persistent link: https://www.econbiz.de/10012404583

Local quantile treatment effects

Melly, Blaise; Wüthrich, Kaspar - 2016

This chapter reviews instrumental variable models of quantile treatment effects. We focus on models that achieve identification through a monotonicity assumption in the treatment choice equation. We discuss the key conditions, the role of control variables as well as the estimands in detail and...

Persistent link: https://www.econbiz.de/10011442004