20 citations · 41 across the 14 of their papers we have counts for
17 papers
Discussion of "Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models"
Eli Ben-Michael, Avi Feller
Choi and Yuan (2025) propose a novel approach to applying matrix completion to the problem of estimating causal effects in panel data. The key insight is that even in the presence…
Partial identification via conditional linear programs: estimation and policy learning
Eli Ben-Michael
Many important quantities of interest are only partially identified from observable data: the data can limit them to a set of plausible values, but not uniquely determine them. Thi…
Statistical methods to estimate the impact of gun policy on gun violence
Eli Ben-Michael, Mitchell L. Doucette, Avi Feller +2
Gun violence is a critical public health and safety concern in the United States. There is considerable variability in policy proposals meant to curb gun violence, ranging from inc…
Temporal Aggregation for the Synthetic Control Method
Liyang Sun, Eli Ben-Michael, Avi Feller
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data…
Using Multiple Outcomes to Improve the Synthetic Control Method
Liyang Sun, Eli Ben-Michael, Avi Feller
When there are multiple outcome series of interest, Synthetic Control analyses typically proceed by estimating separate weights for each outcome. In this paper, we instead propose…
Estimating Racial Disparities in Emergency General Surgery
Eli Ben-Michael, Avi Feller, Rachel Kelz +1
Research documents that Black patients experience worse general surgery outcomes than white patients in the United States. In this paper, we focus on an important but less-examined…
Policy Learning with Asymmetric Counterfactual Utilities
Eli Ben-Michael, Kosuke Imai, Zhichao Jiang
Data-driven decision making plays an important role even in high stakes settings like medicine and public policy. Learning optimal policies from observed data requires a careful fo…
The Balancing Act in Causal Inference
Eli Ben-Michael, Avi Feller, David A. Hirshberg +1
The idea of covariate balance is at the core of causal inference. Inverse propensity weights play a central role because they are the unique set of weights that balance the covaria…
Estimating the effects of a California gun control program with Multitask Gaussian Processes
Eli Ben-Michael, David Arbour, Avi Feller +2
Gun violence is a critical public safety concern in the United States. In 2006 California implemented a unique firearm monitoring program, the Armed and Prohibited Persons System (…
Is it who you are or where you are? Accounting for compositional differences in cross-site treatment variation
Benjamin Lu, Eli Ben-Michael, Avi Feller +1
Multisite trials, in which treatment is randomized separately in multiple sites, offer a unique opportunity to disentangle treatment effect variation due to "compositional" differe…
Interpretable Sensitivity Analysis for Balancing Weights
Dan Soriano, Eli Ben-Michael, Peter J. Bickel +2
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measur…
Multilevel calibration weighting for survey data
Eli Ben-Michael, Avi Feller, Erin Hartman
In the November 2016 U.S. presidential election, many state level public opinion polls, particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading…
A trial emulation approach for policy evaluations with group-level longitudinal data
Eli Ben-Michael, Avi Feller, Elizabeth A. Stuart
To limit the spread of the novel coronavirus, governments across the world implemented extraordinary physical distancing policies, such as stay-at-home orders, and numerous studies…
Varying impacts of letters of recommendation on college admissions: Approximate balancing weights for subgroup effects in observational studies
Eli Ben-Michael, Avi Feller, Jesse Rothstein
In a pilot program during the 2016-17 admissions cycle, the University of California, Berkeley invited many applicants for freshman admission to submit letters of recommendation. W…
Hospital Quality Risk Standardization via Approximate Balancing Weights
Luke Keele, Eli Ben-Michael, Avi Feller +2
Comparing outcomes across hospitals, often to identify underperforming hospitals, is a critical task in health services research. However, naive comparisons of average outcomes, su…
Synthetic Controls with Staggered Adoption
Eli Ben-Michael, Avi Feller, Jesse Rothstein
Staggered adoption of policies by different units at different times creates promising opportunities for observational causal inference. Estimation remains challenging, however, an…
The Augmented Synthetic Control Method
Eli Ben-Michael, Avi Feller, Jesse Rothstein
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The "synthetic control" is a weighted ave…