58 citations · 96 across the 8 of their papers we have counts for
4 papers · 1 filter
Bayesian Double Machine Learning for Causal Inference
Francis J. DiTraglia, Laura Liu
This paper proposes a simple, novel, and fully-Bayesian approach for causal inference in partially linear models with high-dimensional control variables. Off-the-shelf machine lear…
A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models
Francis J. DiTraglia, Camilo Garcia-Jimeno
To estimate causal effects from observational data, an applied researcher must impose beliefs. The instrumental variables exclusion restriction, for example, represents the belief…
Identifying the effect of a mis-classified, binary, endogenous regressor
Francis J. DiTraglia, Camilo Garcia-Jimeno
This paper studies identification of the effect of a mis-classified, binary, endogenous regressor when a discrete-valued instrumental variable is available. We begin by showing tha…
Identifying Causal Effects in Experiments with Spillovers and Non-compliance
Francis J. DiTraglia, Camilo Garcia-Jimeno, Rossa O'Keeffe-O'Donovan +1
This paper shows how to use a randomized saturation experimental design to identify and estimate causal effects in the presence of spillovers--one person's treatment may affect ano…