1# Data audit (P1)2| file | sha256 | rows | cols |3|---|---|---|---|4| data/endowments.csv | fc130a2f54c750a5834ec7314060d91f7984769c7c006ad04b98582a016ba74b | 2 | 3 (agent, good1, good2) |5| data/parameters.csv | 717807e75337fbf4aff8e4d74e0fc0b83b799f78fa689172be0d501cb3e43983 | 4 | 3 (parameter, value, description) |67- Units: endowments in units of each good; alphas dimensionless. No dates (theoretical exercise).8- No missing values, no duplicate agents/parameters. Agents A (8,2), B (4,8): all strictly positive.9- alpha_A=0.4, alpha_B=0.6, both in (0,1) -> interior Cobb-Douglas demands.10- **Anomaly:** parameters.csv records aggregate_endowment_good1 = 14.0, but the sum of individual endowments of good 1 is 8+4 = 12.0. aggregate_endowment_good2 = 10.0 matches 2+8 = 10.0.11- **Decision:** endowments.csv is declared the primary data; agents' budgets are determined by their individual endowments, so the only internally consistent aggregate is the sum (12). Using 14 in market clearing while budgets use 12 would break Walras' law (no consistent equilibrium). We use 12 and 10, report the discrepancy in data_issues, and show a sensitivity calculation with 14 in the report.12- Information-availability: both inputs allowed; no violations.13