Replication package for the paper "Strategic coarseness in enforcement communication". The package contains all Python code, calibration data (JSON), result files, and PDF figures necessary to reproduce all results and figures in the paper. Running "python run_all.py" from the repository root reproduces everything in approximately 60-120 seconds. Random seeds are fixed for full determinism. Contents:- run_all.py: master script to reproduce all results- code/01_calibration.py: validates parameters- code/02_lp_solver.py: solves the LP, saves lp_results.json- code/03_robustness.py: robustness checks- code/04_figures.py: generates all five PDF figures- data/calibration_parameters.json: calibration parameters (input)- data/lp_results.json: LP solution (output)- data/robustness_results.json: robustness results (output)- figures/: five PDF figures Requirements: Python 3.11+, numpy>=1.26, scipy>=1.13, matplotlib>=3.8, pandas>=2.2 The calibration parameters are synthetic but policy-plausible, constructed to be consistent with publicly available EU WEEE enforcement data (Eurostat 2025, European Commission 2025, Forti et al. 2020, WEEE Forum 2024). They are not econometrically estimated from microdata. AI use declaration: the author used Claude (Anthropic) to assist with drafting prose and generating initial code versions. All content was reviewed and validated by the author.