"regsensitivity: A Stata Package for Regression Sensitivity Analysis," with Matthew Masten and Alexandre Poirier
Description: This package implements the regression sensitivity analyses developed in Diegert, Masten, and Poirier (2022) and Oster (2019). The source code is available on the github repo. See the package vignette for a walk through of the package which reproduces part of the empirical analysis in Diegert, Masten, and Poirier (2022). To install the package from Stata, type ssc install regsensitivity. Type help regensitivity for syntax and instructions.
"tesensitivity: A Stata Package for Assessing Sensitivity to the Unconfoundedness Assumption," with Linqi Zhang, Matthew Masten and Alexandre Poirier
Description: This package implements the sensitivity analyses developed Masten and Poirier (2018). See the package vignette for a walk through of the package which reproduces part of the empirical analysis in Masten and Poirier (2018). To install the package from Stata, type ssc install tesensitivity. Type help tesensitivity for syntax and instructions.
"spmlex: Semi-parametric Maximum Likelihood Estimation," with Jackson Bunting and Arnaud Maurel
Description:Â A Python package for semi-parametric maximum likelihood estimation with jax. It provides a computationally efficient method for estimating economic models with permanent unobserved heterogeneity. We use it in the empirical illustration in Bunting, Diegert, and Maurel (2025).