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Regression Discontinuity Designs Using Covariates

Abstract We study regression discontinuity designs when covariates are included in the estimation. We examine local polynomial estimators that include discrete or continuous covariates in an additive…
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Rdrobust: Software for Regression-discontinuity Designs

A major upgrade to the Stata (and R) rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regression-discontinuity designs, has superior performance because of several numerical and implementation improvements.
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Robust Inference on Average Treatment Effects with Possibly More Covariates than Observations

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On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference

ABSTRACT Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite…
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Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs

This work establishes valid coverage error expansions for RBC confidence interval estimators and establishes that RBC inference yields higher-order refinements (relative to traditional undersmoothing) in the context of RD designs.
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Prevalence of Urinary Tract Infection in Childhood: A Meta-Analysis

A meta-analysis to determine the pooled prevalence of urinary tract infection in children by age, gender, race, and circumcision status found uncircumcised male infants less than 3 months of age and females less than 12 months ofAge had the highest baseline prevalence of UTI.
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Deep Neural Networks for Estimation and Inference

This work studies deep neural networks and their use in semiparametric inference, and establishes novel nonasymptotic high probability bounds for deep feedforward neural nets for a general class of nonparametric regression‐type loss functions.
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Deep Neural Networks for Estimation and Inference: Application to Causal Effects and Other Semiparametric Estimands

This work provides new rates of convergence for deep feedforward neural nets and obtains valid semiparametric inference, and proves valid inference after first-step estimation with deep learning, a result new to the literature.
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Is Survival Better at Hospitals With Higher “End-of-Life” Treatment Intensity?

There was a nonlinear negative relationship between hospital EOL treatment intensity and 30-day mortality among all admissions, although patients with higher PPD derived the greatest benefit, and admission to higher E OL treatment intensity hospitals is associated with small gains in postadmission survival.
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Large sample properties of partitioning-based series estimators

We present large sample results for partitioning-based least squares nonparametric regression, a popular method for approximating conditional expectation functions in statistics, econometrics, and…
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