6 citations · 8 across the 7 of their papers we have counts for
7 papers
On the Rates of Convergence of Induced Ordered Statistics and their Applications
Federico A. Bugni, Ivan A. Canay, Deborah Kim
Induced order statistics (IOS) arise when sample units are reordered according to the value of an auxiliary variable, and the associated responses are analyzed in that induced orde…
Testing Conditional Stochastic Dominance at Target Points
Federico A. Bugni, Ivan A. Canay, Deborah Kim
This paper introduces a test for conditional stochastic dominance between two distributions at prespecified values of a conditioning covariate, referred to as target points. The te…
Decomposition and Interpretation of Treatment Effects in Settings with Delayed Outcomes
Federico A. Bugni, Ivan A. Canay, Steve McBride
This paper studies settings where the analyst is interested in identifying and estimating the average \emph{direct} causal effect of a binary treatment on an outcome. We consider a…
Inference for Cluster Randomized Experiments with Non-ignorable Cluster Sizes
Federico Bugni, Ivan Canay, Azeem Shaikh +1
This paper considers the problem of inference in cluster randomized experiments when cluster sizes are non-ignorable. Here, by a cluster randomized experiment, we mean one in which…
On the implementation of Approximate Randomization Tests in Linear Models with a Small Number of Clusters
Yong Cai, Ivan A. Canay, Deborah Kim +1
This paper provides a user's guide to the general theory of approximate randomization tests developed in Canay, Romano, and Shaikh (2017) when specialized to linear regressions wit…
Inference under Covariate-Adaptive Randomization with Multiple Treatments
Federico A. Bugni, Ivan A. Canay, Azeem M. Shaikh
This paper studies inference in randomized controlled trials with covariate-adaptive randomization when there are multiple treatments. More specifically, we study inference about t…
Testing Continuity of a Density via g-order statistics in the Regression Discontinuity Design
Federico A. Bugni, Ivan A. Canay
In the regression discontinuity design (RDD), it is common practice to assess the credibility of the design by testing the continuity of the density of the running variable at the…