# Contract — F2-conf-04

Question. Okun's law in U.S. quarterly data: how does the quarterly change in the unemployment rate co-move with quarterly real GDP growth, with inference robust to serial correlation? Estimand. β in the linear projection Δu_t = α + β g_t + e_t, 1960Q1–2019Q4 (240 quarters). u_t = mean of the 3 monthly UNRATE values of quarter t (pp); Δu_t = u_t − u_{t−1}; g_t = 100·ln(GDPC1_t/GDPC1_{t−1}) (quarterly, not annualised). β is a linear-projection coefficient (descriptive, not causal); meaningful under covariance stationarity / weak dependence so that OLS is consistent for the projection and the HAC variance is consistent. Outputs. out/results.json keys: task_id, beta_hat, alpha_hat, r_squared, se_iid, se_hac, hac_lags, beta_ci_low, beta_ci_high, okun_negative_5pct, mean_growth, first_quarter, last_quarter, n_analysed, feasibility, feasibility_reason, data_issues, n_input_rows, random_seed. Also out/report.md (Question; Data and exclusions; Method; Results; Uncertainty; Limitations and open issues), out/analysis.py, out/claims.json, out/figure1.png (scatter + fitted line), out/exclusions.csv, out/state/*. Information rules. Only data/ files (current vintage). Data outside 1960Q1–2019Q4 only for 1959Q4 levels used in first differences; no window extension. Invalidity / impossibility. Missing months in 1959Q4–2019Q4 (incomplete quarterly averages), missing GDP quarters, sample ≠ 240, using annualised growth, using post-2019 data.