1[2 {"id":"C1","text":"The unadjusted OLS slope of productivity growth on training hours is negative (about -0.13 pp per hour, 95% CI excludes zero).","results_keys":["naive_estimate","naive_ci_low","naive_ci_high"],"status":"supported","caveat":"Descriptive association only; confounded by baseline skill."},3 {"id":"C2","text":"Conditional on baseline skill_index, one extra training hour per employee raises next-year productivity growth by about 0.25 pp (95% CI 0.23 to 0.27).","results_keys":["effect_estimate","effect_se","effect_ci_low","effect_ci_high","conclusion"],"status":"supported","caveat":"Causal interpretation rests on the untestable selection-on-observables assumption with skill_index as the only control."},4 {"id":"C3","text":"Baseline skill is a strong confounder: it is negatively related to growth (about -4.6 pp per index unit) and positively related to training, reversing the sign of the raw association.","results_keys":["skill_index_coefficient","naive_estimate","effect_estimate"],"status":"supported","caveat":"The positive skill-training correlation (0.68) is in diagnostics.corr_training_skill."},5 {"id":"C4","text":"Adjusting for skill roughly halves residual RMSE (3.86 to 1.98 pp).","results_keys":["baseline_metric","model_metric"],"status":"supported","caveat":"In-sample fit; not a validation of causal identification."},6 {"id":"C5","text":"Excluding the 12 rows with negative training hours does not materially change the estimate.","results_keys":["data_issues","n_analysed","n_input_rows"],"status":"supported","caveat":"Sensitivity numbers are in results.json diagnostics (sensitivity_all_rows_effect)."}7]8