1 citations · 1 across the 3 of their papers we have counts for
3 papers
econ.EM2024
Partial Identification of Distributional Treatment Effects in Panel Data using Copula Equality Assumptions
Heshani Madigasekara, D. S. Poskitt, Lina Zhang +1
This paper aims to partially identify the distributional treatment effects (DTEs) that depend on the unknown joint distribution of treated and untreated potential outcomes. We cons…
econ.EM2024
Partially Identified Heterogeneous Treatment Effect with Selection: An Application to Gender Gaps
Xiaolin Sun, Xueyan Zhao, D. S. Poskitt
This paper addresses the sample selection model within the context of the gender gap problem, where even random treatment assignment is affected by selection bias. By offering a ro…
econ.EM2020★ 1 cited
Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects
Lina Zhang, David T. Frazier, D. S. Poskitt +1
This paper examines the identification power of instrumental variables (IVs) for average treatment effect (ATE) in partially identified models. We decompose the ATE identification…