The fast growing statistical literatures on matching methods in several disciplines offer the promise of causal inference without resort to the difficult-to-justify functional form assumptions inherent in commonly used parametric methods. However, these literatures also suffer from many diverse...

The recent literature has underscored the importance of properly accounting for nonstationarity in the application of the synthetic control methods and proposed inference methods to do so. This note studies the size properties of the method proposed by Masini and Medeiros (2022) through...

In instrumental variable studies, missing instrument data are very common. For example, in the Wisconsin Longitudinal Study, one can use genotype data as a Mendelian randomization–style instrument, but this information is often missing when subjects do not contribute saliva samples or when the...

Nonparametric identification strategy is employed to capture causal relationships without imposing any variant of monotonicity existing in the nonseparable nonlinear error model literature. This is important as when monotonicity is applied to the instrumental variables it limits their...

Difference-in-differences (DID) is commonly used for causal inference in time-series cross-section data. It requires the assumption that the average outcomes of treated and control units would have followed parallel paths in the absence of treatment. In this paper, I propose a method that not...

Across the social sciences, lagged explanatory variables are a common strategy to confront challenges to causal identification using observational data. We show that “lag identification” — the use of lagged explanatory variables to solve endogeneity problems — is an illusion: lagging...

The Internet Appendix collects the proofs and additional results that support the main text. We show in simulations that our estimators perform well relative to alternative estimators and can be improved even further with an iterative approach. We also confirm that the distribution results,...