DiD with one treated unit and a substantial number of zeroes in the dataset

External question — Cross Validated Stack Exchange Author: Sunniva Original post: https://stats.stackexchange.com/questions/654119 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. This may be a very basic question, but as I have yet to find a solution to it I'll give it a go: I wish to run a DiD on time series trade data. I have only one unit in my treatment group, which represents export from state A to state B over 100 months. My control group consists of exports from state A to a minimum of 10 other countries in the same time period. To my understanding, this research design poses at least two challenges: The presence of a substantial number of zeroes in the dataset. Possible breach of the homoskedasticity assumption due to the difference in the number of treated vs untreated units. My question is: Would it be sufficient to run a DiD with a PPML (Poisson pseudo maximum likelihood) to deal with these issues? Or, would it be better to run a synthetic control, which is suitable for instances with only one treated unit? If the latter option is recommended, would you recommend combining the approach with a PPML in order to deal with the large amount of zeroes in my data? I am very grateful for any feedback<3