4 papers · 1 filter
Valid Inference when Testing Violations of Parallel Trends for Difference-in-Differences
Jonas M. Mikhaeil, Christopher Harshaw
The difference-in-differences (DID) research design is a key identification strategy which allows researchers to estimate causal effects under the parallel trends assumption. While…
The Conflict Graph Design: Estimating Causal Effects under Arbitrary Neighborhood Interference
Vardis Kandiros, Charilaos Pipis, Constantinos Daskalakis +1
A fundamental problem in network experiments is selecting an appropriate experimental design in order to precisely estimate a given causal effect of interest. In this work, we prop…
A General Design-Based Framework and Estimator for Randomized Experiments
Christopher Harshaw, Fredrik Sävje, Yitan Wang
We describe a design-based framework for drawing causal inference in general randomized experiments. Causal effects are defined as linear functionals evaluated at unit-level potent…
Optimized variance estimation under interference and complex experimental designs
Christopher Harshaw, Joel A. Middleton, Fredrik Sävje
Unbiased and consistent variance estimators generally do not exist for design-based treatment effect estimators because experimenters never observe more than one potential outcome…