Design-based Estimation Theory for Complex Experiments
Author:
Haoge Chang
Keyword:
Economics, Econometrics, Econometrics (econ.EM)
journal:
--
date:
2023-11-11 16:00:00
Abstract
This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units. We develop a design-based estimation theory for arbitrary experimental designs. Our theory facilitates the analysis of many design-estimator pairs that researchers commonly employ in practice and provide procedures to consistently estimate asymptotic variance bounds. We propose new classes of estimators with favorable asymptotic properties from a design-based point of view. In addition, we propose a scalar measure of experimental complexity which can be linked to the design-based variance of the estimators. We demonstrate the performance of our estimators using simulated datasets based on an actual network experiment studying the effect of social networks on insurance adoptions.PDF: Design-based Estimation Theory for Complex Experiments.pdf
