7 papers
Graph-Laplacian Variance Estimators for Finely Stratified Experiments
Yuehao Bai, Xun Huang, Joseph P. Romano +2
This paper considers design-based inference on the average treatment effect in finely stratified experiments, where uncertainty arises only from the randomized treatment assignment…
Inference for Linear Systems with Unknown Coefficients
Yuehao Bai, Kirill Ponomarev, Andres Santos +3
This paper considers the problem of testing whether there exists a solution satisfying certain non-negativity constraints to a linear system of equations. Importantly and in contra…
Inference for Treatment Effects Conditional on Generalized Principal Strata using Instrumental Variables
Yuehao Bai, Shunzhuang Huang, Sarah Moon +3
We propose a general approach for inference for a broad class of treatment effect parameters in a setting of a discrete valued treatment and instrument with a general outcome varia…
On the Identifying Power of Generalized Monotonicity for Average Treatment Effects
Yuehao Bai, Shunzhuang Huang, Sarah Moon +2
In the context of a binary outcome, treatment, and instrument, Balke and Pearl (1993, 1997) es- tablish that the monotonicity condition of Imbens and Angrist (1994) has no identify…
Reasonable uncertainty: Confidence intervals in empirical Bayes discrimination detection
Jiaying Gu, Nikolaos Ignatiadis, Azeem M. Shaikh
We revisit empirical Bayes discrimination detection, focusing on uncertainty arising from both partial identification and sampling variability. While prior work has mostly focused…
A New Design-Based Variance Estimator for Finely Stratified Experiments
Yuehao Bai, Xun Huang, Joseph P. Romano +2
This paper considers the problem of design-based inference for the average treatment effect in finely stratified experiments. Here, by "design-based'' we mean that the only source…