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20222025
most citedUncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption

3 citations · 5 across the 6 of their papers we have counts for

collaborators

7 papers

econ.EM2025

Sequential Decision Problems with Missing Feedback

Filippo Palomba

This paper investigates the challenges of optimal online policy learning under missing data. State-of-the-art algorithms implicitly assume that rewards are always observable. I sho…

econ.EM2025

Leveraging Covariates in Regression Discontinuity Designs

Matias D. Cattaneo, Filippo Palomba

It is common practice to incorporate additional covariates in empirical economics. In the context of Regression Discontinuity (RD) designs, covariate adjustment plays multiple role…

econ.EM2025

rdhte: Conditional Average Treatment Effects in RD Designs

Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell +2

Understanding causal heterogeneous treatment effects based on pretreatment covariates is a crucial aspect of empirical work. Building on Calonico, Cattaneo, Farrell, Palomba, and T…

econ.EM2025

Treatment Effect Heterogeneity in Regression Discontinuity Designs

Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell +2

Empirical studies using Regression Discontinuity (RD) designs often explore heterogeneous treatment effects based on pretreatment covariates, even though no formal statistical meth…

cs.LG2024

A Causal Framework for Evaluating Deferring Systems

Filippo Palomba, Andrea Pugnana, José Manuel Alvarez +1

Deferring systems extend supervised Machine Learning (ML) models with the possibility to defer predictions to human experts. However, evaluating the impact of a deferring strategy…

econ.EM2022★ 3 cited

Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption

Matias D. Cattaneo, Yingjie Feng, Filippo Palomba +1

We propose principled prediction intervals to quantify the uncertainty of a large class of synthetic control predictions (or estimators) in settings with staggered treatment adopti…

stat.ME2022★ 2 cited

scpi: Uncertainty Quantification for Synthetic Control Methods

Matias D. Cattaneo, Yingjie Feng, Filippo Palomba +1

The synthetic control method offers a way to quantify the effect of an intervention using weighted averages of untreated units to approximate the counterfactual outcome that the tr…