{
  "task_id": "F3-conf-01",
  "model_name": "ardl_emp_direct",
  "model_description": "Direct OLS per horizon h: gdp_yoy(s) = a + b*gdp_yoy(s-h-2) + c*emp_yoy(s-h-1), expanding window from 1998 using only targets observed at the origin (s <= t-2), dropping training rows whose target or regressor month lies in 2020-03..2021-12 (COVID); forecast plugs in gdp_yoy(t-2) and emp_yoy(t-1).",
  "n_origins": 48,
  "first_origin": "2022-05-01",
  "last_origin": "2026-04-01",
  "last_target_date_available": "2026-02-01",
  "last_predictor_date_available": "2026-03-01",
  "rmse_naive_h1": 0.813620914876824,
  "mae_naive_h1": 0.6421395833333333,
  "rmse_naive_h3": 1.1399827160604965,
  "mae_naive_h3": 0.8715583333333333,
  "rmse_model_h1": 0.7429391431496228,
  "mae_model_h1": 0.6039917291666668,
  "rmse_model_h3": 0.9023000300820814,
  "mae_model_h3": 0.7534547083333333,
  "rel_improvement_rmse_h1": 0.08687310077064803,
  "rel_improvement_rmse_h3": 0.20849674528381346,
  "feasibility": "complete",
  "feasibility_reason": null,
  "data_issues": [
    {
      "issue": "COVID-19 outliers in 2020-2021 (gdp_yoy from -16.2% to +18.5%, emp_yoy similar) would dominate OLS fits.",
      "handling": "Training rows with target or regressor month in 2020-03..2021-12 excluded from model estimation; evaluation sample (targets 2022-06..2026-07) unaffected; naive unaffected."
    },
    {
      "issue": "Data are the current (final) vintage, not first releases; yoy columns match levels to rounding (max abs diff ~5e-5).",
      "handling": "Used as given; results simulate publication timing only, no real-time validity claimed."
    },
    {
      "issue": "GDP columns empty for 2026-08 and 2026-09.",
      "handling": "Not needed: latest target month is 2026-07; GDP never used beyond t-2."
    }
  ],
  "n_input_rows": {
    "canada_gdp_employment.csv": 345
  },
  "n_analysed": 310,
  "n_analysed_note": "training rows at last origin: h=1 310, h=3 306 (n_analysed reports h=1)",
  "random_seed": null,
  "supplementary_dm_test": {
    "h1": {
      "dm_stat": -2.0256616311210522,
      "p_two_sided": 0.04849813720717646
    },
    "h3": {
      "dm_stat": -1.6522374059203309,
      "p_two_sided": 0.10515234905747618
    }
  }
}