Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/272534 
Year of Publication: 
2023
Series/Report no.: 
IZA Discussion Papers No. 15907
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
In this paper, we describe a computational implementation of the Synthetic difference-in-differences (SDID) estimator of Arkhangelsky et al. (2021) for Stata. Synthetic difference-in-differences can be used in a wide class of circumstances where treatment effects on some particular policy or event are desired, and repeated observations on treated and untreated units are available over time. We lay out the theory underlying SDID, both when there is a single treatment adoption date and when adoption is staggered over time, and discuss estimation and inference in each of these cases. We introduce the sdid command which implements these methods in Stata, and provide a number of examples of use, discussing estimation, inference, and visualization of results.
Subjects: 
difference-in-differences
synthetic control
synthetic difference-in-differences
estimation
inference
visualization
JEL: 
C13
C87
C23
C52
C63
Document Type: 
Working Paper

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