A crash course in good and bad controls
Many students of statistics and econometrics express frustration with the way a problem
known as “bad control” is treated in the traditional literature. The issue arises when the …
known as “bad control” is treated in the traditional literature. The issue arises when the …
Handle with care: a sociologist's guide to causal inference with instrumental variables
Instrumental variables (IV) analysis is a powerful, but fragile, tool for drawing causal
inferences from observational data. Sociologists increasingly turn to this strategy in settings …
inferences from observational data. Sociologists increasingly turn to this strategy in settings …
sensemakr: Sensitivity analysis tools for OLS in R and Stata
This tutorial introduces the package sensemakr for R and Stata, which implements a suite of
sensitivity analysis tools for regression models developed in Cinelli and Hazlett (2020 …
sensitivity analysis tools for regression models developed in Cinelli and Hazlett (2020 …
Rain, rain, go away: 194 potential exclusion‐restriction violations for studies using weather as an instrumental variable
J Mellon - American Journal of Political Science, 2021 - Wiley Online Library
Instrumental variable (IV) analysis relies on the exclusion restriction—that the instrument
only affects the dependent variable via its relationship with the independent variable and not …
only affects the dependent variable via its relationship with the independent variable and not …
Ecological community logics, identifiable business ownership, and green innovation as a company response
We investigate which companies are more inclined to respond with green innovation to
ecological community logics. We propose that the noneconomic utility of doing so–in the …
ecological community logics. We propose that the noneconomic utility of doing so–in the …
Long story short: Omitted variable bias in causal machine learning
We derive general, yet simple, sharp bounds on the size of the omitted variable bias for a
broad class of causal parameters that can be identified as linear functionals of the …
broad class of causal parameters that can be identified as linear functionals of the …
Scalable sensitivity and uncertainty analyses for causal-effect estimates of continuous-valued interventions
Estimating the effects of continuous-valued interventions from observational data is a
critically important task for climate science, healthcare, and economics. Recent work focuses …
critically important task for climate science, healthcare, and economics. Recent work focuses …
Higher education and cultural liberalism: Regression discontinuity evidence from romania
Some studies suggest that university attendance exerts a liberalizing effect on attitudes
toward cultural issues such as sexuality and sexual identity, prostitution, drug addiction …
toward cultural issues such as sexuality and sexual identity, prostitution, drug addiction …
Robust Mendelian randomization in the presence of residual population stratification, batch effects and horizontal pleiotropy
Mendelian Randomization (MR) studies are threatened by population stratification, batch
effects, and horizontal pleiotropy. Although a variety of methods have been proposed to …
effects, and horizontal pleiotropy. Although a variety of methods have been proposed to …
Omitted variable bias in machine learned causal models
We derive general, yet simple, sharp bounds on the size of the omitted variable bias for a
broad class of causal parameters that can be identified as linear functionals of the …
broad class of causal parameters that can be identified as linear functionals of the …