Data audit (P1)
data/model.csv: SHA-256 098123961451e4f9a2e76afdbc83aec78066fc713d0645659c09b77b1636195b (matches bundle.json). 10 data rows x 3 columns (parameter, value, description). No missing values, no duplicate parameter names.- Parameters: alpha=0.36, beta=0.95, y_min=0.05, y_max=5.0, grid_points=400, grid_spacing=log, vfi_tolerance=1e-8, eval points 0.5, 1.0, 2.0.
valuecolumn mixes numeric and the string "log" (grid_spacing) -> parsed per row; not an anomaly.- Checks: 0<alpha<1, 0<beta<1, y_min<y_max, eval points inside grid. Steady state y* = (alpha*beta)^(alpha/(1-alpha)) ~ 0.547 lies inside grid; optimal next-period output from any y in [0.05,5] lies in [~0.23, ~1.21], inside grid, so truncation does not bind.
- Eval points 0.5, 1.0, 2.0 are not grid nodes on the 400-point log grid -> linear interpolation (in ln y) of the VFI policy, as allowed by TASK.md.
- No information-availability violations: the file contains only theoretical parameters.
- Exclusions: none (out/exclusions.csv records the single "parse" step with 0 removed).