1[2 {"id":"C1","text":"The seasonal-dummy AR model has lower out-of-sample RMSE than the seasonal-naive forecast at h=1, 2 and 4 (relative improvements 0.23, 0.13, 0.19).","results_keys":["rmse_snaive_h1","rmse_model_h1","rmse_snaive_h2","rmse_model_h2","rmse_snaive_h4","rmse_model_h4","rel_improvement_rmse_h1","rel_improvement_rmse_h2","rel_improvement_rmse_h4"],"status":"supported","caveat":"Point estimates over 40 origins; a single pre-chosen model."},3 {"id":"C2","text":"The model also has lower MAE than the seasonal naive at all three horizons.","results_keys":["mae_snaive_h1","mae_model_h1","mae_snaive_h2","mae_model_h2","mae_snaive_h4","mae_model_h4"],"status":"supported","caveat":"Point estimates only."},4 {"id":"C3","text":"At h=4 the mean squared-error loss differential (2.82) is not statistically distinguishable from zero at 5% using a Bartlett HAC SE with lag 4 (DM=1.52, p=0.13).","results_keys":["loss_diff_mean_h4","loss_diff_se_h4","hac_lags_h4","hac_kernel_h4","dm_stat_h4","dm_pvalue_h4"],"status":"supported","caveat":"Sensitive to the HAC choice: Bartlett lag 6 gives p=0.04 (0.07 with HLN correction); small sample of 40."}5]6