Synthetic Difference in Differences for Repeated Cross-Sectional Data
Abstract
The synthetic difference-in-differences method provides an efficient method to estimate a causal effect with a latent factor model. However, it relies on the use of panel data. This paper presents an adaptation of the synthetic difference-in-differences method for repeated cross-sectional data. The treatment is considered to be at the group level so that it is possible to aggregate data by group to compute the two types of synthetic difference-in-differences weights on these aggregated data. Then, I develop and compute a third type of weight that accounts for the different number of observations in each cross-section. Simulation results show that the performance of the synthetic difference-in-differences estimator is improved when using the third type of weights on repeated cross-sectional data.
Keywords
Cite
@article{arxiv.2409.20199,
title = {Synthetic Difference in Differences for Repeated Cross-Sectional Data},
author = {Yoann Morin},
journal= {arXiv preprint arXiv:2409.20199},
year = {2024}
}