Connor Dowd | Searcharxiv

arXiv2020

A New ECDF Two-Sample Test Statistic

Empirical cumulative distribution functions (ECDFs) have been used to test the hypothesis that two samples come from the same distribution since the seminal contribution by Kolmogorov and Smirnov. This paper describes a statistic which is usable under the same conditions as Kolmogorov-Smirnov, but provides more power than other extant tests in that vein. I demonstrate a valid (conservative) procedure for producing finite-sample p-values. I outline the close relationship between this statistic and its two main predecessors. I also provide a public R package (CRAN: twosamples [2018]) implementing the testing procedure in $O(N\log(N))$ time with $O(N)$ memory. Using the package's functions, I perform several simulation studies showing the power improvements.

stat.ME↗

arXiv2019

Estimation and Inference for Synthetic Control Methods with Spillover Effects

Estimation and inference procedures for synthetic control methods often do not allow for the existence of spillover effects, which are plausible in many applications. In this paper, we consider estimation and inference for synthetic control methods, allowing for spillover effects. We propose estimators for both direct treatment effects and spillover effects and show that they are asymptotically unbiased. In addition, we propose an inferential procedure and show that it is asymptotically unbiased. Our estimation and inference procedure applies to cases with multiple treated units and/or multiple post-treatment periods, and to ones where the underlying factor model is either stationary or cointegrated. We discuss the bias from misspecified spillover structures and propose a test for correct specification. We apply our method to a classic empirical example that investigates the effect of California's tobacco control program as in Abadie et al. (2010) and find evidence of spillovers. We contrast our method with the pure-donor approach through a sensitivity analysis.

econ.EM↗