Quasi-Stationary Dynamics of CPG Promotions: Simulated Data and Code

This record contains the simulated data and Python source code supporting the paper“Quasi-Stationary Dynamics of CPG Promotions.” Contents include:- Simulated 104-week retailer–UPC–level promotion dataset (promo_data.csv)- Python code to simulate promotion dynamics, estimate transition matrices, compute quasi-stationary distributions and decay rates- Generated outputs used to produce manuscript figures, including survival curves, transition heatmaps, and decision matrices All data are simulated and contain no proprietary, confidential, or third-partycommercial information. The deposit is intended for methodological demonstrationand reproducibility.