{
  "citation": "statsmodels 0.15.0: the reference specification of wooldridge_jtrain ex14_1_grant_1 (infer.ols, figure 'coef.grant_1') on an independent code path",
  "deviation_evidence": null,
  "doi": null,
  "excerpt": null,
  "independent": true,
  "item_set": null,
  "kind": "software",
  "known_deviation": null,
  "licence": null,
  "locator": "wooldridge_jtrain: Example 14.1 / Table 14.1 (edition not confirmed; fixed effects estimation, dependent variable log(scrap)), row 'grant_1'",
  "metric": null,
  "n_items": null,
  "page": null,
  "read_copy_sha256": null,
  "retrieved_at": "2026-10-15",
  "se": 0.21019996441849426,
  "se_as_published": null,
  "source_id": "wooldridge_jtrain.ex14_1_grant_1.software",
  "tolerance_reason": null,
  "units": null,
  "url": "https://pypi.org/project/statsmodels/0.15.0/",
  "value": -0.4215895085292114,
  "value_as_published": null,
  "verified_by": "software_run",
  "verified_note": "sm.OLS(lscrap, add_constant(['grant_1', 'grant', 'd88', 'd89']), fe dummies ['fcode']; 58 independent columns).fit(cov_type='nonrobust') on jtrain (the file pinned at sha256 2820079b04c953a3555a3722e4b14430bc9efedfd6870715a863717de8177383); n_obs = 162. The tool infer.ols (magi_infer, numpy) does not call statsmodels. Written by scripts/paper_repro_reference.py."
}