pronounced 'sassy' or 'SAS-C'
Run with:
python main_SASC.py
Based on Non-parametric identifiability and sensitivity analysis of synthetic control models, published in CLeaR (Causal Learning and Reasoning) 2023 (https://www.cclear.cc/2023)
pandas, scitkit-learn, matplotlib, tabulate
Install from requirements.txt:
conda create --name SASC --file requirements.txt
See code Shi et al.'s paper On the Assumptions of Synthetic Control Methods: https://github.com/claudiashi57/fine-grained-SC
See code from Shi et al.'s code from "Theory for identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework"
In line 73 of "Application_GermanReunification.R" run:
' export <- data.frame(data.all$Y,data.all$W,data.all$X) write.csv(export, "GermanReunificationGDP.csv", row.names = FALSE) '