11 papers
Placebo Discontinuity Design
Rahul Singh, Moses Stewart
Standard regression discontinuity design (RDD) models rely on the continuity of expected potential outcomes at the cutoff. The standard continuity assumption can be violated by str…
Uniform inference for kernel instrumental variable regression
Marvin Lob, Rahul Singh, Suhas Vijaykumar
Instrumental variable regression is a foundational tool for causal analysis across the social and biomedical sciences. Recent advances use kernel methods to estimate nonparametric…
Generated outcomes as generated regressors: Equivalences in recursive causal estimation
Wisse Rutgers, Rahul Singh
Time-varying treatment effects, surrogate-identified treatment effects, and mediation effects can all be written as recursive regressions, in which each regression's predicted valu…
Program Evaluation with Remotely Sensed Outcomes
Ashesh Rambachan, Rahul Singh, Davide Viviano
We study causal inference in experiments and quasi-experiments, where the economic outcome is imperfectly measured by a remotely sensed variable. The remotely sensed variable is lo…
Testing for lack of fit in paired comparison data
Rahul Singh, Ori Davidov
Linear stochastic transitivity is a central assumption in paired comparison models that is rarely verified in practice. Empirical violations, however, are common and can substantia…
Canonical correlation regression with noisy data
Isaac Meza, Rahul Singh
We study instrumental variable regression in data rich environments. The goal is to estimate a linear model from many noisy covariates and many noisy instruments. Our key assumptio…