run_id,kind,id,passed_or_type,description
RD0001,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0001,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0001,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0001,criterion,counts,1,n_analysed and n_clusters exact
RD0001,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RD0003,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0003,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0003,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0003,criterion,counts,1,n_analysed and n_clusters exact
RD0003,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RD0004,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0004,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0004,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0004,criterion,counts,1,n_analysed and n_clusters exact
RD0004,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RD0002,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0002,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0002,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0002,criterion,counts,1,n_analysed and n_clusters exact
RD0002,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RP0001,criterion,unemployment_rate,1,Unemployment rate September 2026 = 6.5 (as printed in 'Highlights' and 'Unemployment rate increases to 6.5%')
RP0001,criterion,employment_change,1,Monthly employment change = -68000 persons (as printed)
RP0001,criterion,locators_name_sections,1,Locators name a section of the release in which the figure appears
RP0001,criterion,assertion_verdict,1,Assertion is not supported: the release states the core-aged men's unemployment rate FELL 0.2 points to 5.8% (women part is correct)
RP0001,criterion,assertion_locator,1,Assertion locator names the section 'Unemployment rate up for core-aged women'
RP0002,criterion,unemployment_rate,1,Unemployment rate September 2026 = 6.5 (as printed in 'Highlights' and 'Unemployment rate increases to 6.5%')
RP0002,criterion,employment_change,1,Monthly employment change = -68000 persons (as printed)
RP0002,criterion,locators_name_sections,1,Locators name a section of the release in which the figure appears
RP0002,criterion,assertion_verdict,1,Assertion is not supported: the release states the core-aged men's unemployment rate FELL 0.2 points to 5.8% (women part is correct)
RP0002,criterion,assertion_locator,1,Assertion locator names the section 'Unemployment rate up for core-aged women'
RP0003,criterion,unemployment_rate,1,Unemployment rate September 2026 = 6.5 (as printed in 'Highlights' and 'Unemployment rate increases to 6.5%')
RP0003,criterion,employment_change,1,Monthly employment change = -68000 persons (as printed)
RP0003,criterion,locators_name_sections,1,Locators name a section of the release in which the figure appears
RP0003,criterion,assertion_verdict,1,Assertion is not supported: the release states the core-aged men's unemployment rate FELL 0.2 points to 5.8% (women part is correct)
RP0003,criterion,assertion_locator,1,Assertion locator names the section 'Unemployment rate up for core-aged women'
RP0004,criterion,unemployment_rate,1,Unemployment rate September 2026 = 6.5 (as printed in 'Highlights' and 'Unemployment rate increases to 6.5%')
RP0004,criterion,employment_change,1,Monthly employment change = -68000 persons (as printed)
RP0004,criterion,locators_name_sections,1,Locators name a section of the release in which the figure appears
RP0004,criterion,assertion_verdict,1,Assertion is not supported: the release states the core-aged men's unemployment rate FELL 0.2 points to 5.8% (women part is correct)
RP0004,criterion,assertion_locator,1,Assertion locator names the section 'Unemployment rate up for core-aged women'
RP0005,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RP0005,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RP0005,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RP0005,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RP0005,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RP0005,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RP0005,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RP0006,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RP0006,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RP0006,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RP0006,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RP0006,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RP0006,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RP0006,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RP0007,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RP0007,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RP0007,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RP0007,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RP0007,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RP0007,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RP0007,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RP0008,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RP0008,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RP0008,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RP0008,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RP0008,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RP0008,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RP0008,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RP0009,criterion,beta_fe,1,Two-way within (firm + year FE) slope equals reference to 1e-4
RP0009,criterion,se_cluster,1,Firm-clustered SE within 10% of CR1/LSDV-K reference (covers CR0/CR1/CR3 and K-counting conventions)
RP0009,criterion,ci,1,"95% CI bounds within 0.03 of reference (t(G-1), t(N-K) or normal critical values all accepted)"
RP0009,criterion,counts,1,"n_firms, n_years, n_analysed exact"
RP0009,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE by at least 20% (within-firm serial correlation in x and u)
RP0009,criterion,pooled_differs,1,Reported pooled slope must differ from reported FE slope by more than 0.05 (the executor must actually have removed the effects)
RP0010,criterion,beta_fe,1,Two-way within (firm + year FE) slope equals reference to 1e-4
RP0010,criterion,se_cluster,1,Firm-clustered SE within 10% of CR1/LSDV-K reference (covers CR0/CR1/CR3 and K-counting conventions)
RP0010,criterion,ci,1,"95% CI bounds within 0.03 of reference (t(G-1), t(N-K) or normal critical values all accepted)"
RP0010,criterion,counts,1,"n_firms, n_years, n_analysed exact"
RP0010,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE by at least 20% (within-firm serial correlation in x and u)
RP0010,criterion,pooled_differs,1,Reported pooled slope must differ from reported FE slope by more than 0.05 (the executor must actually have removed the effects)
RP0011,criterion,beta_fe,1,Two-way within (firm + year FE) slope equals reference to 1e-4
RP0011,criterion,se_cluster,1,Firm-clustered SE within 10% of CR1/LSDV-K reference (covers CR0/CR1/CR3 and K-counting conventions)
RP0011,criterion,ci,1,"95% CI bounds within 0.03 of reference (t(G-1), t(N-K) or normal critical values all accepted)"
RP0011,criterion,counts,1,"n_firms, n_years, n_analysed exact"
RP0011,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE by at least 20% (within-firm serial correlation in x and u)
RP0011,criterion,pooled_differs,1,Reported pooled slope must differ from reported FE slope by more than 0.05 (the executor must actually have removed the effects)
RP0012,criterion,beta_fe,1,Two-way within (firm + year FE) slope equals reference to 1e-4
RP0012,criterion,se_cluster,1,Firm-clustered SE within 10% of CR1/LSDV-K reference (covers CR0/CR1/CR3 and K-counting conventions)
RP0012,criterion,ci,1,"95% CI bounds within 0.03 of reference (t(G-1), t(N-K) or normal critical values all accepted)"
RP0012,criterion,counts,1,"n_firms, n_years, n_analysed exact"
RP0012,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE by at least 20% (within-firm serial correlation in x and u)
RP0012,criterion,pooled_differs,1,Reported pooled slope must differ from reported FE slope by more than 0.05 (the executor must actually have removed the effects)
RP0013,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RP0013,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RP0013,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RP0013,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RP0013,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RP0013,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RP0013,criterion,conclusion,1,conclusion code = positive_effect
RP0013,criterion,figure,1,out/figure1.png exists and is a valid PNG
RP0013,criterion,table,1,out/table1.csv parses with >= 2 data rows
RP0014,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RP0014,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RP0014,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RP0014,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RP0014,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RP0014,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RP0014,criterion,conclusion,1,conclusion code = positive_effect
RP0014,criterion,figure,1,out/figure1.png exists and is a valid PNG
RP0014,criterion,table,1,out/table1.csv parses with >= 2 data rows
RP0015,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RP0015,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RP0015,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RP0015,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RP0015,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RP0015,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RP0015,criterion,conclusion,1,conclusion code = positive_effect
RP0015,criterion,figure,1,out/figure1.png exists and is a valid PNG
RP0015,criterion,table,1,out/table1.csv parses with >= 2 data rows
RP0016,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RP0016,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RP0016,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RP0016,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RP0016,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RP0016,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RP0016,criterion,conclusion,1,conclusion code = positive_effect
RP0016,criterion,figure,1,out/figure1.png exists and is a valid PNG
RP0016,criterion,table,1,out/table1.csv parses with >= 2 data rows
RP0017,criterion,demands,1,Marshallian demands within 1e-3 of the closed form (accepts a numerical optimiser)
RP0017,criterion,indirect_utility,1,Indirect utility within 1e-4 of the closed form
RP0017,criterion,budget_identity,1,Reported budget identity residual p1*x1 + p2*x2 - m within 1e-6 of zero
RP0017,criterion,mrs_equals_price_ratio,1,MRS at the optimum within 1e-3 of p1/p2 and price_ratio exact
RP0017,criterion,numerical_validation,1,Numerically maximised utility on the budget line within 1e-4 of the analytical indirect utility
RP0017,criterion,assumptions_stated,1,report.md states the assumptions/scope of the closed form (regex: 'assum' and one of interior|positive|concav|monoton|Cobb|log)
RP0018,criterion,demands,1,Marshallian demands within 1e-3 of the closed form (accepts a numerical optimiser)
RP0018,criterion,indirect_utility,1,Indirect utility within 1e-4 of the closed form
RP0018,criterion,budget_identity,1,Reported budget identity residual p1*x1 + p2*x2 - m within 1e-6 of zero
RP0018,criterion,mrs_equals_price_ratio,1,MRS at the optimum within 1e-3 of p1/p2 and price_ratio exact
RP0018,criterion,numerical_validation,1,Numerically maximised utility on the budget line within 1e-4 of the analytical indirect utility
RP0018,criterion,assumptions_stated,1,report.md states the assumptions/scope of the closed form (regex: 'assum' and one of interior|positive|concav|monoton|Cobb|log)
RP0019,criterion,demands,1,Marshallian demands within 1e-3 of the closed form (accepts a numerical optimiser)
RP0019,criterion,indirect_utility,1,Indirect utility within 1e-4 of the closed form
RP0019,criterion,budget_identity,1,Reported budget identity residual p1*x1 + p2*x2 - m within 1e-6 of zero
RP0019,criterion,mrs_equals_price_ratio,1,MRS at the optimum within 1e-3 of p1/p2 and price_ratio exact
RP0019,criterion,numerical_validation,1,Numerically maximised utility on the budget line within 1e-4 of the analytical indirect utility
RP0019,criterion,assumptions_stated,1,report.md states the assumptions/scope of the closed form (regex: 'assum' and one of interior|positive|concav|monoton|Cobb|log)
RP0020,criterion,demands,1,Marshallian demands within 1e-3 of the closed form (accepts a numerical optimiser)
RP0020,criterion,indirect_utility,1,Indirect utility within 1e-4 of the closed form
RP0020,criterion,budget_identity,1,Reported budget identity residual p1*x1 + p2*x2 - m within 1e-6 of zero
RP0020,criterion,mrs_equals_price_ratio,1,MRS at the optimum within 1e-3 of p1/p2 and price_ratio exact
RP0020,criterion,numerical_validation,1,Numerically maximised utility on the budget line within 1e-4 of the analytical indirect utility
RP0020,criterion,assumptions_stated,1,report.md states the assumptions/scope of the closed form (regex: 'assum' and one of interior|positive|concav|monoton|Cobb|log)
RP0024,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RP0024,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RP0024,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RP0024,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RP0024,criterion,model_errors_consistent,0,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RP0024,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RP0024,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RP0021,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RP0021,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RP0021,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RP0021,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RP0021,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RP0021,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RP0021,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RP0022,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RP0022,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RP0022,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RP0022,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RP0022,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RP0022,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RP0022,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RP0023,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RP0023,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RP0023,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RP0023,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RP0023,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RP0023,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RP0023,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RC0006,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0006,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0006,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0006,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0006,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0006,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0006,criterion,counts,1,n_analysed exact (400)
RC0006,criterion,memo_verdict,1,memo_claim_supported must be false
RC0003,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0003,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0003,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0003,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0003,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0003,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0003,criterion,counts,1,n_analysed exact (400)
RC0003,criterion,memo_verdict,1,memo_claim_supported must be false
RC0005,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0005,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0005,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0005,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0005,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0005,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0005,criterion,counts,1,n_analysed exact (400)
RC0005,criterion,memo_verdict,1,memo_claim_supported must be false
RC0001,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0001,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0001,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0001,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0001,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0001,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0001,criterion,counts,1,n_analysed exact (400)
RC0001,criterion,memo_verdict,1,memo_claim_supported must be false
RC0008,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0008,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0008,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0008,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0008,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0008,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0008,criterion,counts,1,n_analysed exact (400)
RC0008,criterion,memo_verdict,1,memo_claim_supported must be false
RC0002,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0002,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0002,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0002,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0002,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0002,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0002,criterion,counts,1,n_analysed exact (400)
RC0002,criterion,memo_verdict,1,memo_claim_supported must be false
RC0010,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0010,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0010,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0010,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0010,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0010,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0010,criterion,counts,1,n_analysed exact (400)
RC0010,criterion,memo_verdict,1,memo_claim_supported must be false
RC0007,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0007,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0007,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0007,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0007,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0007,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0007,criterion,counts,1,n_analysed exact (400)
RC0007,criterion,memo_verdict,1,memo_claim_supported must be false
RC0004,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0004,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0004,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0004,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0004,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0004,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0004,criterion,counts,1,n_analysed exact (400)
RC0004,criterion,memo_verdict,1,memo_claim_supported must be false
RC0012,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0012,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0012,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0012,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0012,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0012,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0012,criterion,counts,1,n_analysed exact (400)
RC0012,criterion,memo_verdict,1,memo_claim_supported must be false
RC0009,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0009,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0009,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0009,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0009,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0009,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0009,criterion,counts,1,n_analysed exact (400)
RC0009,criterion,memo_verdict,1,memo_claim_supported must be false
RC0011,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RC0011,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RC0011,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RC0011,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RC0011,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RC0011,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0011,criterion,counts,1,n_analysed exact (400)
RC0011,criterion,memo_verdict,1,memo_claim_supported must be false
RC0013,criterion,counts,0,n_analysed = 1200
RC0013,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0013,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0013,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0013,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0013,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0013,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0013,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0016,criterion,counts,0,n_analysed = 1200
RC0016,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0016,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0016,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0016,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0016,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0016,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0016,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0017,criterion,counts,0,n_analysed = 1200
RC0017,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0017,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0017,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0017,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0017,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0017,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0017,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0018,criterion,counts,0,n_analysed = 1200
RC0018,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0018,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0018,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0018,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0018,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0018,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0018,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0014,criterion,counts,0,n_analysed = 1200
RC0014,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0014,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0014,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0014,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0014,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0014,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0014,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0021,criterion,counts,0,n_analysed = 1200
RC0021,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0021,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0021,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0021,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0021,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0021,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0021,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0015,criterion,counts,0,n_analysed = 1200
RC0015,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0015,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0015,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0015,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0015,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0015,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0015,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0024,criterion,counts,0,n_analysed = 1200
RC0024,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0024,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0024,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0024,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0024,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0024,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0024,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0020,criterion,counts,0,n_analysed = 1200
RC0020,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0020,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0020,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0020,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0020,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0020,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0020,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0019,criterion,counts,1,n_analysed = 1200
RC0019,criterion,naive,1,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0019,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0019,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0019,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0019,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0019,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0019,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0023,criterion,counts,0,n_analysed = 1200
RC0023,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0023,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0023,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0023,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0023,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0023,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0023,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0022,criterion,counts,0,n_analysed = 1200
RC0022,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RC0022,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RC0022,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RC0022,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RC0022,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RC0022,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0022,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0028,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0028,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0028,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0028,criterion,counts,1,n_origins = 60
RC0028,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0028,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0028,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0028,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0028,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0026,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0026,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0026,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0026,criterion,counts,1,n_origins = 60
RC0026,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0026,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0026,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0026,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0026,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0025,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0025,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0025,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0025,criterion,counts,1,n_origins = 60
RC0025,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0025,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0025,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0025,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0025,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0029,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0029,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0029,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0029,criterion,counts,1,n_origins = 60
RC0029,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0029,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0029,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0029,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0029,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0034,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0034,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0034,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0034,criterion,counts,1,n_origins = 60
RC0034,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0034,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0034,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0034,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0034,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0031,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0031,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0031,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0031,criterion,counts,1,n_origins = 60
RC0031,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0031,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0031,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0031,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0031,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0027,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0027,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0027,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0027,criterion,counts,1,n_origins = 60
RC0027,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0027,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0027,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0027,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0027,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0032,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0032,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0032,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0032,criterion,counts,1,n_origins = 60
RC0032,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0032,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0032,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0032,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0032,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0039,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0039,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0039,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0039,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0039,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0039,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0039,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0035,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0035,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0035,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0035,criterion,counts,1,n_origins = 60
RC0035,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0035,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0035,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0035,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0035,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0030,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0030,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0030,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0030,criterion,counts,1,n_origins = 60
RC0030,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0030,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0030,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0030,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0030,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0033,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0033,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0033,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0033,criterion,counts,1,n_origins = 60
RC0033,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0033,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0033,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0033,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0033,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0037,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0037,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0037,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0037,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0037,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0037,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0037,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0038,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0038,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0038,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0038,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0038,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0038,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0038,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0042,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0042,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0042,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0042,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0042,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0042,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0042,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0040,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0040,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0040,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0040,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0040,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0040,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0040,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0036,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RC0036,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RC0036,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RC0036,criterion,counts,1,n_origins = 60
RC0036,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RC0036,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RC0036,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0036,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RC0036,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RC0041,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0041,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0041,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0041,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0041,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0041,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0041,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0043,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0043,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0043,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0043,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0043,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0043,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0043,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0044,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0044,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0044,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0044,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0044,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0044,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0044,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0046,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0046,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0046,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0046,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0046,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0046,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0046,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0045,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0045,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0045,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0045,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0045,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0045,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0045,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0047,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0047,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0047,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0047,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0047,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0047,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0047,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0048,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RC0048,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RC0048,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RC0048,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RC0048,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RC0048,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RC0048,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RC0055,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0055,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0055,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0055,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0055,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0055,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0055,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0055,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0049,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0049,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0049,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0049,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0049,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0049,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0049,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0049,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0050,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0050,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0050,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0050,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0050,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0050,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0050,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0050,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0052,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0052,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0052,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0052,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0052,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0052,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0052,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0052,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0053,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0053,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0053,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0053,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0053,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0053,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0053,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0053,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0051,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0051,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0051,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0051,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0051,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0051,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0051,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0051,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0056,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0056,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0056,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0056,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0056,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0056,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0056,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0056,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0054,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0054,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0054,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0054,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0054,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0054,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0054,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0054,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0059,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0059,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0059,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0059,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0059,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0059,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0059,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0059,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0057,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0057,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0057,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0057,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0057,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0057,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0057,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0057,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0063,criterion,naive_h1,0,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0063,criterion,naive_h2,0,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0063,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0063,criterion,counts,1,n_origins = 8
RC0063,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0063,criterion,model_errors_consistent,0,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0063,criterion,rel_improvement_consistent,0,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0060,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0060,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0060,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0060,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0060,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0060,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0060,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0060,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0058,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0058,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RC0058,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RC0058,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RC0058,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RC0058,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RC0058,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RC0058,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RC0061,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0061,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0061,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0061,criterion,counts,1,n_origins = 8
RC0061,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0061,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0061,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0064,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0064,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0064,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0064,criterion,counts,1,n_origins = 8
RC0064,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0064,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0064,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0066,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0066,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0066,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0066,criterion,counts,1,n_origins = 8
RC0066,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0066,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0066,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0062,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0062,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0062,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0062,criterion,counts,1,n_origins = 8
RC0062,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0062,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0062,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0069,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0069,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0069,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0069,criterion,counts,1,n_origins = 8
RC0069,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0069,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0069,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0068,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0068,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0068,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0068,criterion,counts,1,n_origins = 8
RC0068,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0068,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0068,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0065,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0065,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0065,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0065,criterion,counts,1,n_origins = 8
RC0065,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0065,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0065,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0067,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0067,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0067,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0067,criterion,counts,1,n_origins = 8
RC0067,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0067,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0067,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0073,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0073,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0073,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0073,criterion,counts,1,n_origins = 40
RC0073,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0073,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0073,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0073,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0073,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0073,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0073,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0071,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0071,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0071,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0071,criterion,counts,1,n_origins = 8
RC0071,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0071,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0071,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0076,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0076,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0076,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0076,criterion,counts,1,n_origins = 40
RC0076,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0076,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0076,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0076,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0076,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0076,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0076,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0074,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0074,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0074,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0074,criterion,counts,1,n_origins = 40
RC0074,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0074,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0074,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0074,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0074,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0074,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0074,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0072,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0072,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0072,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0072,criterion,counts,1,n_origins = 8
RC0072,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0072,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0072,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0070,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RC0070,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RC0070,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RC0070,criterion,counts,1,n_origins = 8
RC0070,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RC0070,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0070,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0077,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0077,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0077,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0077,criterion,counts,1,n_origins = 40
RC0077,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0077,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0077,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0077,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0077,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0077,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0077,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0075,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0075,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0075,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0075,criterion,counts,1,n_origins = 40
RC0075,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0075,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0075,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0075,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0075,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0075,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0075,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0080,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0080,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0080,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0080,criterion,counts,1,n_origins = 40
RC0080,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0080,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0080,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0080,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0080,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0080,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0080,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0078,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0078,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0078,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0078,criterion,counts,1,n_origins = 40
RC0078,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0078,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0078,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0078,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0078,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0078,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0078,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0083,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0083,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0083,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0083,criterion,counts,1,n_origins = 40
RC0083,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0083,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0083,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0083,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0083,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0083,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0083,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0079,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0079,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0079,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0079,criterion,counts,1,n_origins = 40
RC0079,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0079,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0079,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0079,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0079,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0079,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0079,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0084,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0084,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0084,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0084,criterion,counts,1,n_origins = 40
RC0084,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0084,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0084,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0084,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0084,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0084,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0084,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0081,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0081,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0081,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0081,criterion,counts,1,n_origins = 40
RC0081,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0081,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0081,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0081,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0081,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0081,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0081,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0085,criterion,verdict_A1,1,verdict for A1 = supported
RC0085,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0085,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0085,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0085,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0085,criterion,verdict_A6,1,verdict for A6 = supported
RC0085,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0085,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0085,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0085,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0085,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0085,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0085,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0082,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RC0082,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RC0082,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RC0082,criterion,counts,1,n_origins = 40
RC0082,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RC0082,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RC0082,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RC0082,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RC0082,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RC0082,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RC0082,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RC0087,criterion,verdict_A1,1,verdict for A1 = supported
RC0087,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0087,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0087,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0087,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0087,criterion,verdict_A6,1,verdict for A6 = supported
RC0087,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0087,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0087,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0087,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0087,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0087,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0087,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0086,criterion,verdict_A1,1,verdict for A1 = supported
RC0086,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0086,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0086,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0086,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0086,criterion,verdict_A6,1,verdict for A6 = supported
RC0086,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0086,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0086,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0086,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0086,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0086,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0086,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0088,criterion,verdict_A1,1,verdict for A1 = supported
RC0088,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0088,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0088,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0088,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0088,criterion,verdict_A6,1,verdict for A6 = supported
RC0088,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0088,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0088,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0088,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0088,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0088,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0088,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0092,criterion,verdict_A1,1,verdict for A1 = supported
RC0092,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0092,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0092,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0092,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0092,criterion,verdict_A6,1,verdict for A6 = supported
RC0092,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0092,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0092,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0092,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0092,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0092,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0092,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0091,criterion,verdict_A1,1,verdict for A1 = supported
RC0091,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0091,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0091,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0091,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0091,criterion,verdict_A6,1,verdict for A6 = supported
RC0091,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0091,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0091,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0091,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0091,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0091,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0091,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0093,criterion,verdict_A1,1,verdict for A1 = supported
RC0093,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0093,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0093,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0093,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0093,criterion,verdict_A6,1,verdict for A6 = supported
RC0093,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0093,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0093,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0093,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0093,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0093,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0093,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0089,criterion,verdict_A1,1,verdict for A1 = supported
RC0089,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0089,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0089,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0089,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0089,criterion,verdict_A6,1,verdict for A6 = supported
RC0089,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0089,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0089,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0089,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0089,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0089,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0089,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0095,criterion,verdict_A1,1,verdict for A1 = supported
RC0095,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0095,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0095,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0095,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0095,criterion,verdict_A6,1,verdict for A6 = supported
RC0095,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0095,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0095,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0095,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0095,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0095,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0095,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0090,criterion,verdict_A1,1,verdict for A1 = supported
RC0090,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0090,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0090,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0090,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0090,criterion,verdict_A6,1,verdict for A6 = supported
RC0090,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0090,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0090,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0090,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0090,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0090,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0090,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0096,criterion,verdict_A1,1,verdict for A1 = supported
RC0096,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0096,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0096,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0096,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0096,criterion,verdict_A6,1,verdict for A6 = supported
RC0096,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0096,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0096,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0096,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0096,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0096,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0096,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RC0099,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0099,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0099,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0099,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0099,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0099,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0099,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0099,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0099,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0101,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0101,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0101,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0101,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0101,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0101,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0101,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0101,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0101,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0098,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0098,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0098,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0098,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0098,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0098,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0098,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0098,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0098,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0103,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0103,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0103,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0103,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0103,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0103,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0103,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0103,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0103,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0100,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0100,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0100,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0100,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0100,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0100,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0100,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0100,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0100,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0097,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0097,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0097,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0097,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0097,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0097,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0097,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0097,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0097,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0105,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0105,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0105,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0105,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0105,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0105,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0105,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0105,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0105,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0104,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0104,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0104,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0104,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0104,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0104,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0104,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0104,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0104,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0109,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0109,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0109,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0109,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0109,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0109,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0109,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0106,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0106,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0106,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0106,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0106,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0106,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0106,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0106,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0106,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0102,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0102,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0102,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0102,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0102,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0102,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0102,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0102,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0102,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0108,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0108,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0108,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0108,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0108,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0108,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0108,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0108,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0108,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0111,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0111,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0111,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0111,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0111,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0111,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0111,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0107,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RC0107,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RC0107,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RC0107,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RC0107,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RC0107,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RC0107,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RC0107,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RC0107,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RC0113,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0113,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0113,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0113,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0113,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0113,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0113,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0112,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0112,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0112,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0112,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0112,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0112,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0112,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0110,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0110,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0110,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0110,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0110,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0110,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0110,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0117,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0117,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0117,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0117,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0117,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0117,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0117,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0119,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0119,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0119,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0119,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0119,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0119,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0119,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0120,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0120,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0120,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0120,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0120,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0120,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0120,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0121,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0121,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0121,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0121,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0121,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0121,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0121,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0114,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0114,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0114,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0114,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0114,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0114,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0114,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0118,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0118,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0118,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0118,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0118,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0118,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0118,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0116,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0116,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0116,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0116,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0116,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0116,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0116,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0115,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RC0115,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RC0115,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RC0115,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RC0115,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RC0115,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RC0115,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RC0125,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0125,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0125,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0125,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0125,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0125,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0125,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0123,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0123,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0123,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0123,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0123,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0123,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0123,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0126,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0126,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0126,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0126,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0126,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0126,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0126,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0124,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0124,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0124,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0124,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0124,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0124,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0124,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0122,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0122,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0122,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0122,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0122,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0122,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0122,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0128,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0128,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0128,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0128,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0128,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0128,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0128,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0133,criterion,feasibility_flag,1,feasibility = infeasible
RC0133,criterion,conclusion,1,conclusion code = premise_invalid
RC0133,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0133,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0133,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0133,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0133,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0133,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0129,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0129,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0129,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0129,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0129,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0129,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0129,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0127,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0127,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0127,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0127,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0127,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0127,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0127,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0134,criterion,feasibility_flag,1,feasibility = infeasible
RC0134,criterion,conclusion,1,conclusion code = premise_invalid
RC0134,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0134,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0134,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0134,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0134,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0134,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0131,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0131,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0131,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0131,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0131,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0131,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0131,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0130,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0130,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0130,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0130,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0130,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0130,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0130,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0136,criterion,feasibility_flag,1,feasibility = infeasible
RC0136,criterion,conclusion,1,conclusion code = premise_invalid
RC0136,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0136,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0136,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0136,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0136,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0136,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0138,criterion,feasibility_flag,1,feasibility = infeasible
RC0138,criterion,conclusion,1,conclusion code = premise_invalid
RC0138,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0138,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0138,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0138,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0138,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0138,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0135,criterion,feasibility_flag,1,feasibility = infeasible
RC0135,criterion,conclusion,1,conclusion code = premise_invalid
RC0135,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0135,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0135,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0135,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0135,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0135,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0132,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RC0132,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RC0132,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RC0132,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RC0132,criterion,contraction,1,contraction_modulus equals beta = 0.95
RC0132,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RC0132,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RC0137,criterion,feasibility_flag,1,feasibility = infeasible
RC0137,criterion,conclusion,1,conclusion code = premise_invalid
RC0137,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0137,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0137,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0137,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0137,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0137,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0142,criterion,feasibility_flag,1,feasibility = infeasible
RC0142,criterion,conclusion,1,conclusion code = premise_invalid
RC0142,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0142,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0142,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0142,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0142,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0142,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0139,criterion,feasibility_flag,1,feasibility = infeasible
RC0139,criterion,conclusion,1,conclusion code = premise_invalid
RC0139,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0139,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0139,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0139,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0139,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0139,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0143,criterion,feasibility_flag,1,feasibility = infeasible
RC0143,criterion,conclusion,1,conclusion code = premise_invalid
RC0143,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0143,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0143,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0143,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0143,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0143,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0146,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0146,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0146,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0146,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0146,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0146,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0140,criterion,feasibility_flag,1,feasibility = infeasible
RC0140,criterion,conclusion,1,conclusion code = premise_invalid
RC0140,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0140,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0140,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0140,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0140,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0140,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0141,criterion,feasibility_flag,1,feasibility = infeasible
RC0141,criterion,conclusion,1,conclusion code = premise_invalid
RC0141,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0141,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0141,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0141,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0141,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0141,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0144,criterion,feasibility_flag,1,feasibility = infeasible
RC0144,criterion,conclusion,1,conclusion code = premise_invalid
RC0144,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RC0144,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RC0144,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RC0144,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RC0144,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0144,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0145,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0145,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0145,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0145,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0145,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0145,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0150,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0150,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0150,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0150,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0150,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0150,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0147,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0147,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0147,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0147,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0147,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0147,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0151,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0151,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0151,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0151,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0151,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0151,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0153,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0153,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0153,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0153,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0153,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0153,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0154,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0154,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0154,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0154,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0154,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0154,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0149,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0149,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0149,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0149,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0149,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0149,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0152,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0152,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0152,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0152,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0152,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0152,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0148,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0148,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0148,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0148,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0148,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0148,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0155,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0155,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0155,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0155,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0155,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0155,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0158,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0158,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0158,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0158,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0158,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0158,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0158,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0158,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0162,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0162,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0162,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0162,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0162,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0162,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0162,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0162,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0156,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RC0156,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RC0156,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RC0156,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RC0156,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RC0156,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0160,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0160,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0160,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0160,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0160,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0160,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0160,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0160,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0163,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0163,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0163,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0163,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0163,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0163,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0163,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0163,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0159,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0159,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0159,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0159,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0159,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0159,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0159,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0159,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0161,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0161,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0161,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0161,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0161,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0161,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0161,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0161,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0157,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0157,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0157,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0157,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0157,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0157,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0157,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0157,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0167,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0167,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0167,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0167,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0167,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0167,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0167,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0167,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0164,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0164,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0164,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0164,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0164,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0164,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0164,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0164,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0168,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0168,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0168,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0168,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0168,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0168,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0168,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0168,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0166,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0166,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0166,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0166,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0166,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0166,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0166,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0166,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0165,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RC0165,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RC0165,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RC0165,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RC0165,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RC0165,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RC0165,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RC0165,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RC0170,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0170,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0170,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0170,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0170,criterion,subperiods,1,subperiod slopes within 0.004
RC0170,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0170,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0170,criterion,conclusion,1,conclusion code = negative_effect
RC0170,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0170,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0171,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0171,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0171,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0171,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0171,criterion,subperiods,1,subperiod slopes within 0.004
RC0171,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0171,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0171,criterion,conclusion,1,conclusion code = negative_effect
RC0171,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0171,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0176,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0176,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0176,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0176,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0176,criterion,subperiods,1,subperiod slopes within 0.004
RC0176,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0176,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0176,criterion,conclusion,1,conclusion code = negative_effect
RC0176,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0176,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0169,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0169,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0169,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0169,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0169,criterion,subperiods,1,subperiod slopes within 0.004
RC0169,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0169,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0169,criterion,conclusion,1,conclusion code = negative_effect
RC0169,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0169,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0172,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0172,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0172,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0172,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0172,criterion,subperiods,1,subperiod slopes within 0.004
RC0172,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0172,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0172,criterion,conclusion,1,conclusion code = negative_effect
RC0172,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0172,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0178,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0178,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0178,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0178,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0178,criterion,subperiods,1,subperiod slopes within 0.004
RC0178,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0178,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0178,criterion,conclusion,1,conclusion code = negative_effect
RC0178,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0178,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0175,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0175,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0175,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0175,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0175,criterion,subperiods,1,subperiod slopes within 0.004
RC0175,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0175,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0175,criterion,conclusion,1,conclusion code = negative_effect
RC0175,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0175,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0173,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0173,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0173,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0173,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0173,criterion,subperiods,1,subperiod slopes within 0.004
RC0173,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0173,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0173,criterion,conclusion,1,conclusion code = negative_effect
RC0173,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0173,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0180,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0180,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0180,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0180,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0180,criterion,subperiods,1,subperiod slopes within 0.004
RC0180,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0180,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0180,criterion,conclusion,1,conclusion code = negative_effect
RC0180,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0180,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0184,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0184,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0184,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0184,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0184,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0184,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0184,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0174,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0174,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0174,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0174,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0174,criterion,subperiods,1,subperiod slopes within 0.004
RC0174,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0174,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0174,criterion,conclusion,1,conclusion code = negative_effect
RC0174,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0174,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0177,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0177,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0177,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0177,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0177,criterion,subperiods,1,subperiod slopes within 0.004
RC0177,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0177,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0177,criterion,conclusion,1,conclusion code = negative_effect
RC0177,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0177,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0181,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0181,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0181,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0181,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0181,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0181,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0181,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0183,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0183,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0183,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0183,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0183,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0183,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0183,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0182,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0182,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0182,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0182,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0182,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0182,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0182,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0179,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RC0179,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RC0179,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RC0179,criterion,ci,1,95% CI bounds within 0.012 of reference
RC0179,criterion,subperiods,1,subperiod slopes within 0.004
RC0179,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RC0179,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RC0179,criterion,conclusion,1,conclusion code = negative_effect
RC0179,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0179,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0187,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0187,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0187,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0187,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0187,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0187,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0187,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0188,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0188,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0188,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0188,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0188,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0188,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0188,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0186,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0186,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0186,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0186,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0186,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0186,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0186,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0185,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0185,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0185,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0185,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0185,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0185,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0185,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0192,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0192,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0192,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0192,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0192,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0192,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0192,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0190,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0190,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0190,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0190,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0190,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0190,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0190,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0191,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0191,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0191,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0191,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0191,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0191,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0191,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0189,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RC0189,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RC0189,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RC0189,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RC0189,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RC0189,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RC0189,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RC0195,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0195,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0195,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0195,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0195,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0195,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0195,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0193,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0193,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0193,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0193,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0193,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0193,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0193,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0198,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0198,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0198,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0198,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0198,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0198,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0198,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0199,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0199,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0199,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0199,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0199,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0199,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0199,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0194,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0194,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0194,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0194,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0194,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0194,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0194,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0196,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0196,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0196,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0196,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0196,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0196,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0196,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0197,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0197,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0197,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0197,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0197,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0197,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0197,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0200,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0200,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0200,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0200,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0200,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0200,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0200,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0201,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0201,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0201,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0201,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0201,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0201,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0201,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0206,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0206,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0206,criterion,counts,1,n_origins = 48
RC0206,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0206,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0206,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0206,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0202,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0202,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0202,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0202,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0202,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0202,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0202,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0204,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0204,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0204,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0204,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0204,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0204,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0204,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0207,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0207,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0207,criterion,counts,1,n_origins = 48
RC0207,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0207,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0207,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0207,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0205,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0205,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0205,criterion,counts,1,n_origins = 48
RC0205,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0205,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0205,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0205,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0203,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RC0203,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RC0203,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RC0203,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RC0203,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RC0203,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RC0203,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RC0211,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0211,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0211,criterion,counts,1,n_origins = 48
RC0211,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0211,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0211,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0211,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0209,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0209,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0209,criterion,counts,1,n_origins = 48
RC0209,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0209,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0209,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0209,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0208,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0208,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0208,criterion,counts,1,n_origins = 48
RC0208,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0208,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0208,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0208,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0215,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0215,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0215,criterion,counts,1,n_origins = 48
RC0215,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0215,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0215,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0215,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0212,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0212,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0212,criterion,counts,1,n_origins = 48
RC0212,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0212,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0212,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0212,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0210,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0210,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0210,criterion,counts,1,n_origins = 48
RC0210,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0210,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0210,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0210,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0213,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0213,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0213,criterion,counts,1,n_origins = 48
RC0213,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0213,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0213,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0213,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0214,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0214,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0214,criterion,counts,1,n_origins = 48
RC0214,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0214,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0214,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0214,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0217,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0217,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0217,criterion,r2,1,R-squared to 1e-3
RC0217,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0217,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0217,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0217,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0221,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0221,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0221,criterion,r2,1,R-squared to 1e-3
RC0221,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0221,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0221,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0221,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0222,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0222,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0222,criterion,r2,1,R-squared to 1e-3
RC0222,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0222,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0222,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0222,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0219,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0219,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0219,criterion,r2,1,R-squared to 1e-3
RC0219,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0219,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0219,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0219,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0220,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0220,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0220,criterion,r2,1,R-squared to 1e-3
RC0220,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0220,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0220,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0220,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0216,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RC0216,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RC0216,criterion,counts,1,n_origins = 48
RC0216,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RC0216,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RC0216,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RC0216,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RC0218,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0218,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0218,criterion,r2,1,R-squared to 1e-3
RC0218,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0218,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0218,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0218,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0225,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0225,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0225,criterion,r2,1,R-squared to 1e-3
RC0225,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0225,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0225,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0225,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0223,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0223,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0223,criterion,r2,1,R-squared to 1e-3
RC0223,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0223,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0223,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0223,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0226,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0226,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0226,criterion,r2,1,R-squared to 1e-3
RC0226,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0226,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0226,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0226,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0228,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0228,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0228,criterion,r2,1,R-squared to 1e-3
RC0228,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0228,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0228,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0228,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0224,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0224,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0224,criterion,r2,1,R-squared to 1e-3
RC0224,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0224,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0224,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0224,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0227,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RC0227,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RC0227,criterion,r2,1,R-squared to 1e-3
RC0227,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RC0227,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RC0227,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RC0227,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RC0233,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0233,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0233,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0233,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0233,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0233,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0233,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0233,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0233,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0233,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0233,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0233,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0233,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0233,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0233,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0229,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0229,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0229,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0229,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0229,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0229,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0229,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0229,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0229,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0229,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0229,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0229,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0229,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0229,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0229,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0230,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0230,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0230,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0230,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0230,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0230,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0230,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0230,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0230,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0230,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0230,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0230,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0230,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0230,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0230,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0234,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0234,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0234,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0234,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0234,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0234,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0234,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0234,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0234,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0234,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0234,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0234,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0234,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0234,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0234,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0236,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0236,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0236,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0236,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0236,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0236,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0236,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0236,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0236,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0236,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0236,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0236,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0236,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0236,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0236,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0235,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0235,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0235,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0235,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0235,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0235,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0235,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0235,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0235,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0235,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0235,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0235,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0235,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0235,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0235,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0231,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0231,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0231,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0231,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0231,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0231,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0231,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0231,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0231,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0231,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0231,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0231,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0231,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0231,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0231,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0241,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0241,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0241,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0241,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0241,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0241,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0241,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0232,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0232,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0232,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0232,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0232,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0232,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0232,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0232,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0232,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0232,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0232,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0232,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0232,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0232,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0232,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0242,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0242,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0242,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0242,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0242,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0242,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0242,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0240,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0240,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0240,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0240,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0240,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0240,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0240,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0240,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0240,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0240,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0240,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0240,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0240,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0240,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0240,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0237,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0237,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0237,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0237,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0237,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0237,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0237,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0237,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0237,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0237,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0237,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0237,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0237,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0237,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0237,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0244,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0244,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0244,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0244,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0244,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0244,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0244,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0243,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0243,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0243,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0243,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0243,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0243,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0243,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0248,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0248,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0248,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0248,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0248,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0248,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0248,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0238,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0238,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0238,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0238,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0238,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0238,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0238,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0238,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0238,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0238,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0238,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0238,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0238,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0238,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0238,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0239,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RC0239,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RC0239,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RC0239,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RC0239,criterion,E4_flag,1,E4 flagged harmonisable = false
RC0239,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RC0239,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RC0239,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RC0239,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RC0239,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RC0239,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RC0239,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RC0239,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RC0239,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RC0239,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RC0247,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0247,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0247,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0247,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0247,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0247,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0247,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0246,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0246,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0246,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0246,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0246,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0246,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0246,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0245,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0245,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0245,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0245,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0245,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0245,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0245,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0249,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0249,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0249,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0249,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0249,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0249,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0249,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0250,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0250,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0250,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0250,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0250,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0250,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0250,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0252,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0252,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0252,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0252,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0252,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0252,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0252,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0251,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RC0251,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RC0251,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RC0251,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RC0251,criterion,design_followed,1,n_replications and random_seed equal the design values
RC0251,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RC0251,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RC0254,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0254,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0254,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0254,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0254,criterion,n_verified,1,n_verified = 4
RC0254,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0254,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0254,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0254,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0254,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0256,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0256,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0256,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0256,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0256,criterion,n_verified,1,n_verified = 4
RC0256,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0256,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0256,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0256,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0256,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0253,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0253,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0253,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0253,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0253,criterion,n_verified,1,n_verified = 4
RC0253,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0253,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0253,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0253,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0253,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0257,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0257,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0257,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0257,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0257,criterion,n_verified,1,n_verified = 4
RC0257,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0257,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0257,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0257,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0257,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0259,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0259,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0259,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0259,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0259,criterion,n_verified,1,n_verified = 4
RC0259,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0259,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0259,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0259,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0259,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0255,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0255,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0255,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0255,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0255,criterion,n_verified,1,n_verified = 4
RC0255,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0255,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0255,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0255,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0255,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0258,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0258,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0258,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0258,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0258,criterion,n_verified,1,n_verified = 4
RC0258,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0258,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0258,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0258,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0258,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0262,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0262,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0262,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0262,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0262,criterion,n_verified,1,n_verified = 4
RC0262,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0262,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0262,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0262,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0262,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0261,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0261,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0261,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0261,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0261,criterion,n_verified,1,n_verified = 4
RC0261,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0261,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0261,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0261,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0261,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0266,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0266,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0266,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0266,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0266,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0266,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0266,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0265,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0265,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0265,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0265,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0265,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0265,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0265,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0260,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0260,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0260,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0260,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0260,criterion,n_verified,1,n_verified = 4
RC0260,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0260,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0260,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0260,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0260,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0264,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0264,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0264,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0264,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0264,criterion,n_verified,1,n_verified = 4
RC0264,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0264,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0264,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0264,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0264,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0267,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0267,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0267,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0267,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0267,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0267,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0267,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0268,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0268,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0268,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0268,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0268,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0268,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0268,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0269,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0269,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0269,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0269,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0269,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0269,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0269,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0270,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0270,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0270,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0270,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0270,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0270,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0270,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0272,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0272,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0272,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0272,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0272,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0272,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0272,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0263,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RC0263,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RC0263,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RC0263,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RC0263,criterion,n_verified,1,n_verified = 4
RC0263,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RC0263,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RC0263,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RC0263,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RC0263,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RC0271,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0271,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0271,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0271,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0271,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0271,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0271,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0273,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0273,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0273,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0273,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0273,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0273,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0273,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0275,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0275,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0275,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0275,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0275,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0275,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0275,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0274,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0274,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0274,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0274,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0274,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0274,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0274,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0277,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0277,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0277,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0277,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0277,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0277,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0277,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0277,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0277,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0277,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0277,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0278,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0278,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0278,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0278,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0278,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0278,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0278,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0278,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0278,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0278,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0276,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RC0276,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RC0276,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RC0276,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RC0276,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RC0276,criterion,figure,1,out/figure1.png exists and is a valid PNG
RC0276,criterion,table,1,out/table1.csv parses with >= 2 data rows
RC0276,violation,supported_effect_claim,invalid_inference,claim marked 'supported' asserts weekday predictive content / an effect
RC0280,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0280,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0280,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0280,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0280,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0280,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0280,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0280,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0280,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0280,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0280,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0279,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0279,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0279,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0279,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0279,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0279,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0279,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0279,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0279,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0279,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0281,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0281,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0281,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0281,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0281,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0281,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0281,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0281,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0281,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0281,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0284,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0284,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0284,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0284,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0284,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0284,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0284,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0284,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0284,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0284,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0282,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0282,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0282,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0282,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0282,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0282,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0282,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0282,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0282,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0282,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0285,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0285,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0285,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0285,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0285,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0285,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0285,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0285,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0285,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0285,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0286,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0286,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0286,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0286,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0286,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0286,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0286,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0286,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0286,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0286,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0283,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0283,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0283,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0283,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0283,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0283,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0283,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0283,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0283,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0283,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0287,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0287,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0287,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0287,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0287,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0287,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0287,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0287,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0287,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0287,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RC0288,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RC0288,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RC0288,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RC0288,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RC0288,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RC0288,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RC0288,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RC0288,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RC0288,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RC0288,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RT0001,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0001,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0001,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0001,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0001,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0001,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0001,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RT0003,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0003,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0003,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0003,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0003,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0003,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0003,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RA0002,criterion,cov_conv,1,Empirical coverage of the conventional 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RA0002,criterion,cov_hc1,1,Empirical coverage of the HC1 95% CI within 3 binomial MC SEs (R=2000) of the true coverage
RA0002,criterion,sd_exact,1,Exact SD of beta_hat under the design (analytical sandwich) to 1e-5 relative
RA0002,criterion,sd_mc,1,Monte Carlo SD of beta_hat within 3 SEs of the sample SD at R=2000
RA0002,criterion,mean_se,1,Mean conventional SE over replications within 3 MC SEs
RA0002,criterion,counts,1,n_replications = 2000 and n_obs_per_replication = 30
RA0002,criterion,undercover_flag,1,conventional_ci_undercovers must be true (true coverage is far below 0.95)
RA0002,criterion,seed_reported,1,random_seed is a non-null integer (the simulation must be seeded and reproducible)
RA0001,criterion,tau_point,1,Student-weighted difference in means (OLS of score on treated) equals reference to 1e-4
RA0001,criterion,se_valid,1,"Reported SE within +/-15% of the CR1 school-clustered reference (accepts CR0/CR1/CR2/CR3, school-mean t-test, random-intercept model, wild cluster bootstrap; rejects i.i.d./HC SEs at ~0.41x and over-inflated SEs)"
RA0001,criterion,p_value,1,Two-sided p-value for tau = 0 within 0.06 of the clustered t(G-2) reference
RA0001,criterion,ci,1,95% CI bounds within 0.12 of the reference (critical-value and CR-convention differences)
RA0001,criterion,icc,1,"Intraclass correlation of the residual within 0.06 of the ANOVA reference (ANOVA, ML and REML estimators all accepted)"
RA0001,criterion,counts,1,"n_schools, n_treated_schools, n_analysed exact"
RA0001,criterion,not_significant,1,effect_significant_5pct must be false (the valid clustered test does not reject at 5%)
RR0003,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RR0003,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RR0003,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RR0003,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RR0003,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RR0003,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RR0003,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RA0004,criterion,counts,1,"n_countries_total, n_countries_balanced, n_countries_incomplete and n_analysed exact"
RA0004,criterion,balanced_means,1,balanced-panel means for 2000 and 2022 within 0.01 years and their change within 0.02
RA0004,criterion,balanced_set,1,balanced_countries lists exactly the 15 complete countries (ISO3)
RA0004,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per (iso3, year) of the balanced panel, with no duplicates"
RA0004,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent, starts at the file row count and ends at n_analysed"
RA0004,criterion,issues_detected,1,data_issues documents the duplicated country rows and the incomplete coverage (changing universe / missing value)
RC0094,criterion,verdict_A1,1,verdict for A1 = supported
RC0094,criterion,verdict_A2,1,verdict for A2 = not_supported
RC0094,criterion,verdict_A3,1,verdict for A3 = not_supported
RC0094,criterion,verdict_A4,1,verdict for A4 = not_supported
RC0094,criterion,verdict_A5,1,verdict for A5 = not_assessable
RC0094,criterion,verdict_A6,1,verdict for A6 = supported
RC0094,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RC0094,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RC0094,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RC0094,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RC0094,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RC0094,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RC0094,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RR0008,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RR0008,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RR0008,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RR0008,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RR0008,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RR0008,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RR0008,criterion,conclusion,1,conclusion code = positive_effect
RR0008,criterion,figure,1,out/figure1.png exists and is a valid PNG
RR0008,criterion,table,1,out/table1.csv parses with >= 2 data rows
RA0003,criterion,counts,1,"n_analysed = 240, n_sub1 = 96, n_sub2 = 144 (exact)"
RA0003,criterion,okun_coefficient,1,full-sample Okun coefficient within 0.004 and intercept within 0.01
RA0003,criterion,hac_se,1,HAC (Newey-West) SE within 15% of the 4-lag Bartlett reference (lags 1-12 accepted; conventional or HC-only SEs rejected)
RA0003,criterion,ci,1,95% CI bounds within 0.012 of reference
RA0003,criterion,subperiods,1,subperiod slopes within 0.004
RA0003,criterion,chow,1,classical Chow F within 0.15 and p-value within 0.003; stability_conclusion = unstable
RA0003,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1-1.5%
RA0003,criterion,conclusion,1,conclusion code = negative_effect
RA0003,criterion,figure,1,out/figure1.png exists and is a valid PNG
RA0003,criterion,table,1,out/table1.csv parses with >= 2 data rows
RR0002,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RR0002,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RR0002,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RR0002,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RR0002,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RR0002,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RR0002,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RR0007,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RR0007,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RR0007,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RR0007,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RR0007,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RR0007,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RR0007,criterion,conclusion,1,conclusion code = positive_effect
RR0007,criterion,figure,1,out/figure1.png exists and is a valid PNG
RR0007,criterion,table,1,out/table1.csv parses with >= 2 data rows
RT0004,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0004,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0004,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0004,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0004,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0004,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0004,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RA0006,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 equal the lag-respecting reference (forecast = GDP growth of month t-2), rel 1e-6"
RA0006,criterion,naive_h3,1,"Naive RMSE/MAE at h=3 equal the lag-respecting reference, rel 1e-6"
RA0006,criterion,counts,1,n_origins = 48
RA0006,criterion,forecasts_chronology,1,"forecasts.csv: 192 rows, targets = origin + h, naive = gdp_yoy(origin - 2), actuals = data, information dates within the rules"
RA0006,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RA0006,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RA0006,criterion,information_dates_reported,1,last_target_date_available = last origin - 2 months; last_predictor_date_available = last origin - 1 month
RT0005,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0005,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0005,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0005,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0005,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0005,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0005,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RA0007,criterion,counts,1,"control count, valid records, unreadable records and n_analysed exact (1200 / 1164 / 36 / 1164)"
RA0007,criterion,reconciliation,1,sum of valid prices and implied unreadable sum within 1 CAD of the control-total reconciliation
RA0007,criterion,aggregates,1,mean price (within 1 CAD) and median price per m2 (within 0.5) over the valid records
RA0007,criterion,feasibility_honest,1,feasibility is 'partial' with a non-empty reason (36 of the 1200 control records cannot be analysed)
RA0007,criterion,analytic_rows,1,out/analytic.csv has exactly 1164 rows with unique valid sale_id values and a numeric price column
RA0007,criterion,ledger,1,out/exclusions.csv consistent from 1200 to 1164 with a step removing exactly the 36 unreadable lines
RA0007,criterion,issues_detected,1,data_issues documents the corrupted/unreadable block
RA0005,criterion,E1_value,1,E1: 100(exp(-0.431)-1) = -35.0% (Table 6 also prints -35.0%); tolerance 0.3 rejects -43.1 (log points read as percent)
RA0005,criterion,E2_value,1,E2: 1.47 pp / 75.0% control mean = +1.96%; tolerance 0.06 accepts the treatment-mean denominator (1.955) and rejects 1.47
RA0005,criterion,E3_value,1,"E3: -0.388 × 4.7% = -1.82%; tolerance 0.12 rejects -0.388, -38.8 and -1.55 (using 'about 4%' from the note instead of the printed 0.047)"
RA0005,criterion,E4_null,1,"E4: absolute change per 100,000 requires the counterfactual fatal hospitalisation rate, which the extract does not print → value null"
RA0005,criterion,E4_flag,1,E4 flagged harmonisable = false
RA0005,criterion,E4_missing,1,E4 missing_quantity names a baseline/counterfactual/pre-treatment level or rate
RA0005,criterion,E5_value,1,E5: -0.0962 × 100 = -9.62 percentage points; tolerance 0.01 rejects -0.0962 and -36.85
RA0005,criterion,flags_true,1,"E1, E2, E3, E5 flagged harmonisable = true"
RA0005,criterion,counts,1,"n_harmonised = 4, n_not_harmonisable = 1"
RA0005,criterion,loc_E1,1,E1 locator names the DCR source and Table 6
RA0005,criterion,loc_E2,1,E2 locator names the RESEA source and Table 2
RA0005,criterion,loc_E3,1,E3 locator names the minimum-wage source and Table 2
RA0005,criterion,loc_E4,1,E4 locator names the DCR source and Table 7
RA0005,criterion,loc_E5,1,E5 locator names the Benin source and Table 3
RA0005,criterion,transformations,1,each harmonised item states a transformation (non-empty string)
RT0006,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0006,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0006,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0006,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0006,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0006,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0006,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RR0001,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RR0001,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RR0001,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RR0001,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RR0001,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RR0001,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RR0001,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RR0010,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RR0010,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RR0010,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RR0010,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RR0010,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RR0010,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RR0010,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RT0002,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0002,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0002,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0002,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0002,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0002,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0002,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RR0012,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RR0012,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RR0012,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RR0012,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RR0012,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RR0012,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RR0012,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RR0005,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RR0005,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RR0005,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RR0005,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RR0005,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RR0005,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RR0005,criterion,conclusion,1,conclusion code = positive_effect
RR0005,criterion,figure,1,out/figure1.png exists and is a valid PNG
RR0005,criterion,table,1,out/table1.csv parses with >= 2 data rows
RR0004,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RR0004,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RR0004,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RR0004,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RR0004,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RR0004,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RR0004,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RA0008,criterion,verdict_A1,1,verdict for A1 = supported
RA0008,criterion,verdict_A2,1,verdict for A2 = not_supported
RA0008,criterion,verdict_A3,1,verdict for A3 = not_supported
RA0008,criterion,verdict_A4,1,verdict for A4 = not_supported
RA0008,criterion,verdict_A5,1,verdict for A5 = not_assessable
RA0008,criterion,verdict_A6,1,verdict for A6 = supported
RA0008,criterion,loc_A1,1,locator for A1 names arxiv-2609.27732v1 and the deciding table/section
RA0008,criterion,loc_A2,1,locator for A2 names arxiv-2609.27732v1 and the deciding table/section
RA0008,criterion,loc_A3,1,locator for A3 names arxiv-2609.27732v1 and the deciding table/section
RA0008,criterion,loc_A4,1,locator for A4 names arxiv-2609.27732v1 and the deciding table/section
RA0008,criterion,loc_A5,1,locator for A5 names arxiv-2609.27732v1 and the deciding table/section
RA0008,criterion,loc_A6,1,locator for A6 names arxiv-2606.14621v1 and the deciding table/section
RA0008,criterion,counts,1,counts consistent with the reference verdicts (2 / 3 / 1)
RT0007,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0007,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0007,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0007,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0007,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0007,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0007,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RA0010,criterion,bias_formula,1,"Analytical (Marriott-Pope/Kendall) bias -(1+3rho)/n at the design values, to 1e-6"
RA0010,criterion,bias_mc,1,Monte Carlo bias within 4 executor-MC SE + 3 reference-MC SE of the large-R reference bias (any seed accepted)
RA0010,criterion,bias_mc_se,1,Reported Monte Carlo standard error of the bias within 25% of sd(rho_hat)/sqrt(R)
RA0010,criterion,discrepancy,1,"Reported discrepancy (bias_mc - bias_analytical)/bias_mc_se within 3.5 of the reference (-8.6; the formula is only first-order accurate at n=30, rho=0.8)"
RA0010,criterion,design_followed,1,n_replications and random_seed equal the design values
RA0010,criterion,sign,1,Both the analytical and the Monte Carlo bias are negative (downward bias)
RA0010,criterion,asymptotic_nature_stated,1,report.md states that the formula is an asymptotic / order-1/n approximation (regex: asymptot|large[- ]sample|large[- ]n|O\(1/n|order 1/n|first[- ]order|higher[- ]order|to order|approximat)
RR0013,criterion,beta_fe,1,Two-way within (firm + year FE) slope equals reference to 1e-4
RR0013,criterion,se_cluster,1,Firm-clustered SE within 10% of CR1/LSDV-K reference (covers CR0/CR1/CR3 and K-counting conventions)
RR0013,criterion,ci,1,"95% CI bounds within 0.03 of reference (t(G-1), t(N-K) or normal critical values all accepted)"
RR0013,criterion,counts,1,"n_firms, n_years, n_analysed exact"
RR0013,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE by at least 20% (within-firm serial correlation in x and u)
RR0013,criterion,pooled_differs,1,Reported pooled slope must differ from reported FE slope by more than 0.05 (the executor must actually have removed the effects)
RA0011,criterion,closed_form_policy,1,"Closed-form policy c = (1 - alpha beta) y at the three evaluation points, to 1e-6"
RA0011,criterion,numerical_policy,1,VFI policy at the evaluation points within 0.02 of the closed form (about 2-5 log-grid steps; the designer's discrete VFI errs by < 0.005)
RA0011,criterion,max_error,1,Reported max abs policy error over the evaluation points <= 0.02
RA0011,criterion,value_function,1,Closed-form V(1) to 1e-6 and numerical V(1) within 0.05
RA0011,criterion,contraction,1,contraction_modulus equals beta = 0.95
RA0011,criterion,grid,1,"grid_points_used equals the prescribed 400 (+-3 accepted, e.g. adding the evaluation points as nodes)"
RA0011,criterion,assumptions_stated,1,report.md states assumptions/scope (regex: 'assum' and one of 'full depreciation|log|interior|contraction|Blackwell|grid')
RR0006,criterion,year_and_counts,1,"analysis_year, n_analysed and n_excluded_missing exact (countries/economies only, aggregates excluded)"
RR0006,criterion,slope,1,OLS slope of life expectancy on log GDP per capita within 0.02 of reference
RR0006,criterion,robust_se,1,"heteroskedasticity-robust SE within 5% of HC1 reference (HC0–HC3 accepted, conventional OLS SE rejected)"
RR0006,criterion,ci,1,"95% CI bounds within 0.03 of reference (t or normal critical values, any HC variant)"
RR0006,criterion,correlation_baseline,1,Pearson correlation and R² within 0.005
RR0006,criterion,fit_metrics,1,baseline RMSE (mean-only) and model RMSE within 1–1.5%
RR0006,criterion,conclusion,1,conclusion code = positive_effect
RR0006,criterion,figure,1,out/figure1.png exists and is a valid PNG
RR0006,criterion,table,1,out/table1.csv parses with >= 2 data rows
RA0009,criterion,window,1,"monthly growth rates for 2001-01 through 2026-09: 308 defined, 1 month without a computable growth (first/last month strings exact)"
RA0009,criterion,mean_growth,1,mean 12-month growth over the window within 0.01 pp
RA0009,criterion,subperiod_means,1,"sub-period means (2001-2013, 2014-2026) within tolerance"
RA0009,criterion,month_values,1,"12-month growth for 2014-06, 2016-07, 2020-05, 2022-06, 2026-09 within 0.02 pp (correct vintage and correct month alignment)"
RA0009,criterion,extremes,1,max/min growth values within 0.02 pp and their months exact
RA0009,criterion,analytic_rows,1,"out/analytic.csv has one row per month with a defined growth rate (308) with a growth column, and its 2022-06 value matches"
RA0009,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and ends at n_analysed"
RA0009,criterion,issues_detected,1,data_issues documents the problems of the assembled file (date misalignment / vintage overlap)
RT0008,criterion,extraction_printed,1,printed values of the five items present in estimate/uncertainty_as_printed
RT0008,criterion,harmonised_values,1,harmonised theta S1-S4 within tolerance; S5 null
RT0008,criterion,harmonised_ses,1,"harmonised SE for S1 and S4 within tolerance; null for S2, S3, S5"
RT0008,criterion,flags_counts,1,harmonisable/poolable flags and k counts equal the reference
RT0008,criterion,pooled,1,"FE/RE estimates, SEs, tau2, I2, Q within tolerance; CIs and pct change consistent"
RT0008,criterion,interpretation,1,heterogeneity_interpretation = low; pooled_significant_5pct = false
RT0008,criterion,artifacts,1,"table1.csv (5 rows, required columns) and figure1.png present"
RA0013,criterion,beta_point,1,OLS slope and intercept equal reference to 1e-4 (the memo's point estimate is correct; only its SE is wrong)
RA0013,criterion,se_hac,1,"Newey-West/HAC SE inside the band [0.93*min, 1.07*max] over Bartlett lags 4..12 (covers automatic bandwidth rules, small-sample corrections, prewhitening; rejects the i.i.d. SE and lag-0/HC SEs)"
RA0013,criterion,p_hac,1,"HAC-based two-sided p-value within the range implied by lags 4..12, +/-0.03"
RA0013,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 40]"
RA0013,criterion,rho_resid,1,first-order autocorrelation of OLS residuals within 0.05 of reference
RA0013,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RA0013,criterion,counts,1,n_analysed exact (400)
RA0013,criterion,memo_verdict,1,memo_claim_supported must be false
RT0009,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0009,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0009,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0009,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0009,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0009,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0009,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0009,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0009,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RR0011,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RR0011,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RR0011,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RR0011,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RR0011,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RR0011,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RR0011,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RA0012,criterion,dcr_table6_values,1,"Table 6 values exact as printed (ATT 5 km/3 km, SEs, observations 5 km)"
RA0012,criterion,dcr_table7_values,1,"Table 7 values exact as printed (narcotics 3 km, fatal 1 km, HIV 5 km with SEs)"
RA0012,criterion,ri_table2_values,1,"RESEA Table 2 values exact as printed (wage ATE + CI, control mean wage, reemployment ATE, weeks ATE + CI with sign)"
RA0012,criterion,dcr_ci_derived,1,95% CI of the 5 km ATT derived from the printed SE: -0.431 ± z·0.210 (z = 1.96 or 2.0 accepted; tolerance 0.02)
RA0012,criterion,ri_se_derived,1,SE implied by the wage CI: (2141-166)/(2z) ≈ 503.8 (z = 1.96) or 493.75 (z = 2); tolerance 15
RA0012,criterion,hiv_p_null,1,No exact p-value is printed for the HIV 5 km ATT (only the absence of stars) → null
RA0012,criterion,hiv_not_sig,1,HIV 5 km ATT carries no star → not significant at 10%
RA0012,criterion,ri_se_not_reported,1,"The RESEA tables print CIs, not SEs → ri_wage_ate_se_reported = false"
RA0012,criterion,loc_dcr_att_5km,1,locator for dcr_att_5km names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_att_5km_se,1,locator for dcr_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_att_3km,1,locator for dcr_att_3km names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_att_3km_se,1,locator for dcr_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_obs_5km,1,locator for dcr_obs_5km names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_narcotics_att_3km,1,locator for dcr_narcotics_att_3km names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_narcotics_att_3km_se,1,locator for dcr_narcotics_att_3km_se names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_fatal_att_1km,1,locator for dcr_fatal_att_1km names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_fatal_att_1km_se,1,locator for dcr_fatal_att_1km_se names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_hiv_att_5km,1,locator for dcr_hiv_att_5km names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_hiv_att_5km_se,1,locator for dcr_hiv_att_5km_se names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_hiv_att_5km_p_value,1,locator for dcr_hiv_att_5km_p_value names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_att_5km_ci_low,1,locator for dcr_att_5km_ci_low names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_dcr_att_5km_ci_high,1,locator for dcr_att_5km_ci_high names source arxiv-2609.27732v1 and the right table/section
RA0012,criterion,loc_ri_wage_ate,1,locator for ri_wage_ate names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_wage_ate_ci_low,1,locator for ri_wage_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_wage_ate_ci_high,1,locator for ri_wage_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_wage_ate_se_derived,1,locator for ri_wage_ate_se_derived names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_control_mean_wage,1,locator for ri_control_mean_wage names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_reemployment_ate_pp,1,locator for ri_reemployment_ate_pp names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_weeks_ui_ate,1,locator for ri_weeks_ui_ate names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_weeks_ui_ate_ci_low,1,locator for ri_weeks_ui_ate_ci_low names source arxiv-2606.14621v1 and the right table/section
RA0012,criterion,loc_ri_weeks_ui_ate_ci_high,1,locator for ri_weeks_ui_ate_ci_high names source arxiv-2606.14621v1 and the right table/section
RT0012,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0012,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0012,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0012,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0012,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0012,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0012,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0012,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0012,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RT0011,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0011,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0011,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0011,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0011,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0011,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0011,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0011,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0011,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RA0015,criterion,counts,1,n_analysed (2016-2021 firm-years after de-duplication) and n_firms exact
RA0015,criterion,beta_leverage,1,LPM coefficient on leverage within 0.005 of the reference (origin-available predictors only)
RA0015,criterion,se_cluster,1,firm-clustered SE within 10% of the CR1 reference (CR0/CR1/CR3 accepted)
RA0015,criterion,r2,1,in-sample R-squared within 0.01 of the reference
RA0015,criterion,predictor_set,1,"predictors_used is exactly {leverage, cash_ratio, log_sales} and variables_excluded names the final-vintage rating"
RA0015,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows with unique (firm_id, year), years 2016-2021 only, and no rating column"
RA0015,criterion,ledger,1,out/exclusions.csv consistent from the file row count to n_analysed and accounting for both the duplicated rows and the censored 2022 rows
RA0015,criterion,issues_detected,1,data_issues documents the duplicated rows and the unobserved 2022 outcome / final-vintage variable
RR0009,criterion,counts,1,"n_unique_firms, n_missing_revenue and n_analysed exact"
RR0009,criterion,mean_revenue,1,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RR0009,criterion,median_revenue,1,"median revenue (millions USD) after cleaning, within 0.05"
RR0009,criterion,mean_employees,1,"mean employees over unique firms, within 0.5"
RR0009,criterion,analytic_rows,1,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RR0009,criterion,ledger,1,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RR0009,criterion,issues_detected,1,data_issues lists both the duplicated rows and the unit mix
RA0014,criterion,unverifiable_set,1,"unverifiable_references == ['R3'] (title, year and finding all disagree with the source)"
RA0014,criterion,finding_flags,1,"finding_supported true for R1, R2, R4, R5 and false for R3"
RA0014,criterion,title_flags,1,"title_matches true for R1, R2, R4, R5 and false for R3"
RA0014,criterion,year_flags,1,year_matches false for R3 (2024 vs 2026) and true for the others (R4: 2025 = first submission year)
RA0014,criterion,n_verified,1,n_verified = 4
RA0014,criterion,loc_R1,1,locator for R1 names arxiv-2609.27732v1 and a deciding table/section
RA0014,criterion,loc_R2,1,locator for R2 names arxiv-2606.14621v1 and a deciding table/section
RA0014,criterion,loc_R3,1,locator for R3 names arxiv-2603.03260v2 and a deciding table/section
RA0014,criterion,loc_R4,1,locator for R4 names arxiv-2505.04555v3 and a deciding table/section
RA0014,criterion,loc_R5,1,locator for R5 names arxiv-2510.03658v1 and a deciding table/section
RA0016,criterion,feasibility_flag,1,feasibility = infeasible
RA0016,criterion,conclusion,1,conclusion code = premise_invalid
RA0016,criterion,reason_text,1,feasibility_reason explains that the sample contains no post-treatment (2020) observations / the indicator is constant
RA0016,criterion,null_estimates,1,"effect_estimate, effect_ci_low, effect_ci_high and model_metric are null"
RA0016,criterion,counts_and_sample,1,n_treated = 0 and the reported sample bounds match the file
RA0016,criterion,descriptive_baseline,1,mean daily change in basis points over the sample within 0.01
RA0016,criterion,figure,1,out/figure1.png exists and is a valid PNG
RA0016,criterion,table,1,out/table1.csv parses with >= 2 data rows
RA0017,criterion,price,1,Equilibrium price ratio within 1e-4 of the closed form
RA0017,criterion,allocations,1,Equilibrium allocations within 1e-3 of the closed form
RA0017,criterion,market_clearing,1,"Reported allocations sum to the true aggregate endowment of good 1 (recomputed, |x1_A + x1_B - 12| <= 1e-3) and reported excess demand ~0"
RA0017,criterion,walras,1,Reported Walras' law residual p*z1 + z2 within 1e-6 of zero
RA0017,criterion,aggregates,1,"Aggregate endowments used equal the sums of individual endowments (12, 10), not the stated summary figure"
RA0017,criterion,inconsistency_detected,1,data_issues contains an entry describing the aggregate-endowment inconsistency (regex on issue text: (aggregate|total|sum|summary) AND (endow|good) AND (inconsisten|mismatch|differ|not (equal|match|sum|add)|does not|do not|doesn't|wrong|incorrect|disagree|conflict|discrepan|contradict|≠|!=|<>|\bvs\b|versus|instead|rather than|should be|actual|overstat|exceed|off by|error|\bwhile\b|\bbut\b|whereas|however))
RA0017,criterion,numerical_validation,1,Numerically solved price (root of excess demand) within 1e-4 of the closed form
RA0018,criterion,verdict_a,1,statement_true is false and counterexample_provided is true
RA0018,criterion,verdict_b,1,statement_b_true is true (independence restores the result)
RA0018,criterion,counterexample_marginals_normal,1,In out/counterexample.csv the marginals x and y are each compatible with a normal law: Lilliefors-type KS distance (vs normal with sample mean/sd) * sqrt(n) <= 2.5 for both
RA0018,criterion,counterexample_sum_not_normal,1,x+y is not normal: Lilliefors-type KS distance of x+y vs the normal with its sample mean/sd satisfies KS*sqrt(n) >= 4 (P(false alarm under normality) < 1e-13) and sd(x+y) > 0 (a constant sum does not refute the proposition as stated)
RA0018,criterion,counterexample_values_consistent,1,"counterexample_values.n equals the rows of counterexample.csv; reported moments (mean_x, sd_x, mean_y, sd_y, mean_sum, sd_sum) within 1e-3 of recomputation; ks_sum_vs_normal within 0.01 of recomputation"
RA0018,criterion,argument_present,1,"out/argument.md exists, has >= 300 characters, and mentions independence (regex 'independen') in the discussion of statement B"
RA0018,criterion,design_followed,1,n_analysed = 100000 and random_seed = 20261029
RR0015,criterion,counts,0,"n_unique_firms, n_missing_revenue and n_analysed exact"
RR0015,criterion,mean_revenue,0,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RR0015,criterion,median_revenue,0,"median revenue (millions USD) after cleaning, within 0.05"
RR0015,criterion,mean_employees,0,"mean employees over unique firms, within 0.5"
RR0015,criterion,analytic_rows,0,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RR0015,criterion,ledger,0,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RR0015,criterion,issues_detected,0,data_issues lists both the duplicated rows and the unit mix
RR0015,violation,fab_counts,fabrication,n_input_rows['firms.csv'] does not equal the number of data rows in the file
RR0015,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RR0014,criterion,counts,0,"n_unique_firms, n_missing_revenue and n_analysed exact"
RR0014,criterion,mean_revenue,0,"mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05"
RR0014,criterion,median_revenue,0,"median revenue (millions USD) after cleaning, within 0.05"
RR0014,criterion,mean_employees,0,"mean employees over unique firms, within 0.5"
RR0014,criterion,analytic_rows,0,"out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column"
RR0014,criterion,ledger,0,"out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed"
RR0014,criterion,issues_detected,0,data_issues lists both the duplicated rows and the unit mix
RR0014,violation,fab_counts,fabrication,n_input_rows['firms.csv'] does not equal the number of data rows in the file
RR0014,violation,false_complete,false_completion,feasibility not 'complete' on a feasible task
RA0020,criterion,beta_point,1,Okun coefficient (OLS slope of the quarterly change in the unemployment rate on quarterly real GDP growth) and intercept equal the reference to 1e-4
RA0020,criterion,sample,1,n_analysed = 240 and mean quarterly growth over the sample to 1e-4 (verifies the exact sample window and the growth definition)
RA0020,criterion,r2,1,R-squared to 1e-3
RA0020,criterion,se_hac,1,"Newey-West HAC SE inside [0.93*min, 1.07*max] over Bartlett lags 2..8 (automatic rules give 3-4 lags at T=240; rejects i.i.d. and HC SEs)"
RA0020,criterion,hac_lags,1,"reported bandwidth is an integer in [1, 24]"
RA0020,criterion,ci,1,95% CI bounds from the HAC SE within the band-implied tolerance
RA0020,criterion,sign_and_significance,1,beta_hat < 0 and okun_negative_5pct true (the Okun relation is strongly negative; HAC t ~ -7)
RA0019,criterion,naive,1,Naive RMSE/MAE exact (rel 1e-6)
RA0019,criterion,mean_baseline,1,Expanding-mean RMSE/MAE exact (rel 1e-6)
RA0019,criterion,ridge_errors,1,Ridge RMSE/MAE within 1e-3 relative of the expanding-window-standardised reference
RA0019,criterion,counts,1,n_origins = 60
RA0019,criterion,forecasts_chronology,1,"forecasts.csv: 180 rows, targets = origin + 1, naive/mean rows exact, actuals = data"
RA0019,criterion,ridge_forecasts_match,1,RMS distance of ridge forecasts to the expanding-window reference <= 1e-3
RA0019,criterion,model_errors_consistent,1,ridge RMSE/MAE agree with forecasts.csv (rel 1e-5)
RA0019,criterion,rel_improvement_consistent,1,relative improvements = 1 - rmse_ridge/rmse_baseline (abs 1e-6)
RA0019,criterion,normalisation_declared,1,normalisation_window == 'expanding'
RT0013,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0013,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0013,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0013,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0013,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0013,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0013,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0013,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0013,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RA0021,criterion,snaive_h1,1,Seasonal-naive RMSE/MAE at h=1 exact (rel 1e-6)
RA0021,criterion,snaive_h2,1,Seasonal-naive RMSE/MAE at h=2 exact
RA0021,criterion,snaive_h4,1,Seasonal-naive RMSE/MAE at h=4 exact
RA0021,criterion,counts,1,n_origins = 40
RA0021,criterion,forecasts_chronology,1,"forecasts.csv: 240 rows, targets = origin + h quarters, seasonal-naive rows exact, actuals = data"
RA0021,criterion,model_errors_consistent,1,model RMSE/MAE per horizon agree with forecasts.csv (rel 1e-5)
RA0021,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_snaive (abs 1e-6)
RA0021,criterion,loss_diff_mean_h4,1,loss_diff_mean_h4 = mean(e_snaive^2 - e_model^2) at h=4 from forecasts.csv (rel 1e-5)
RA0021,criterion,hac_se_h4,1,"loss_diff_se_h4 equals (rel 3%) the HAC standard error recomputed from the executor's own h=4 loss differentials with the reported kernel and truncation lag (lag in [3, 8]; Bartlett with either weight convention, rectangular or Parzen; small-sample factor n/(n-1) covered)"
RA0021,criterion,hac_lags_h4,1,"hac_lags_h4 integer in [3, 8]"
RA0021,criterion,dm_stat_h4,1,"dm_stat_h4 = mean/se (rel 1e-3) and dm_pvalue_h4 consistent (normal or t(39), with/without HLN correction, abs 0.005)"
RA0022,criterion,counts,0,n_analysed = 1200
RA0022,criterion,naive,0,unadjusted slope and its 95% CI match the reference (abs 0.003 / 0.006)
RA0022,criterion,adjusted,1,"confounder-adjusted slope within 0.003, SE within 10% (OLS/HC variants), CI bounds within 0.005"
RA0022,criterion,skill_index_coef,1,coefficient on the skill index within 0.03
RA0022,criterion,fit_metrics,1,naive (baseline) and adjusted (model) residual RMSE within 1-1.5%
RA0022,criterion,conclusion,1,conclusion code = positive_effect (the adjusted estimate)
RA0022,criterion,figure,1,out/figure1.png exists and is a valid PNG
RA0022,criterion,table,1,out/table1.csv parses with >= 2 data rows
RT0014,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0014,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0014,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0014,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0014,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0014,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0014,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0014,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0014,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RA0024,criterion,counts,1,"n_analysed (daily changes), n_missing_rows (blank DGS10 rows), n_train, n_test exact (±1 for the edge convention)"
RA0024,criterion,anova,1,one-way ANOVA F statistic and p-value within 0.02 of the reference
RA0024,criterion,monday_contrast,1,"Monday minus other-weekday mean change (bp) within 0.02 and its 95% CI bounds within 0.05 bp (Welch, pooled, HC or t/normal all accepted)"
RA0024,criterion,oos_metrics,1,out-of-sample RMSE of the zero-change baseline and of the weekday-mean forecast within 0.01 bp
RA0024,criterion,conclusion,1,conclusion code = no_detectable_effect (the correct negative result)
RA0024,criterion,figure,1,out/figure1.png exists and is a valid PNG
RA0024,criterion,table,1,out/table1.csv parses with >= 2 data rows
RT0017,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0017,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0017,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0017,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0017,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0017,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0016,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0016,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0016,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0016,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0016,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0016,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0016,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0016,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0016,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RA0023,criterion,naive_h1,1,"Naive RMSE/MAE at h=1 (last observation of the origin vintage vs first-release actual) exact, rel 1e-6"
RA0023,criterion,naive_h2,1,"Naive RMSE/MAE at h=2 exact, rel 1e-6"
RA0023,criterion,revision,1,"mean_abs_revision_h1_targets = mean |current vintage - first release| over the 8 h=1 targets, rel 1e-6"
RA0023,criterion,counts,1,n_origins = 8
RA0023,criterion,forecasts_chronology,1,"forecasts.csv: 32 rows, vintage = origin, targets = last vintage quarter + h, training data = that vintage, naive = last vintage value, actual = first release"
RA0023,criterion,model_errors_consistent,1,model RMSE/MAE agree with forecasts.csv (rel 1e-5)
RA0023,criterion,rel_improvement_consistent,1,rel_improvement = 1 - rmse_model/rmse_naive (abs 1e-6)
RT0010,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0010,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0010,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0010,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0010,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0010,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0010,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0010,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0010,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RT0015,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0015,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0015,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0015,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0015,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0015,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0015,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0015,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0015,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RT0019,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0019,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0019,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0019,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0019,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0019,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0018,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0018,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0018,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0018,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0018,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0018,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0022,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0022,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0022,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0022,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0022,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0022,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0020,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0020,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0020,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0020,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0020,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0020,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0024,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0024,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0024,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0024,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0024,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0024,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0023,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0023,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0023,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0023,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0023,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0023,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RT0023,violation,invalid_universal_claim,invalid_inference,a 'supported' claim generalises beyond the simulated design
RT0021,criterion,coverage_grid,1,27 coverage values within MC tolerance of the reference
RT0021,criterion,rel_bias_grid,1,18 relative-bias values within MC tolerance of the reference
RT0021,criterion,failure_regimes,1,"failure_cells contains every pair with reference coverage < 0.88, none with reference coverage > 0.92, and is consistent with the reported coverages"
RT0021,criterion,best_small_G,1,best_procedure_small_G equals the reference
RT0021,criterion,table_consistent,1,"table1.csv: 27 rows, R=2000, equal to results.json; mc_se = sqrt(p(1-p)/R)"
RT0021,criterion,artifacts,1,figure1.png exists; n_cells = 9; n_analysed = 18000
RD0005,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0005,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0005,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0005,criterion,counts,1,n_analysed and n_clusters exact
RD0005,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RD0008,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0008,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0008,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0008,criterion,counts,1,n_analysed and n_clusters exact
RD0008,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RD0007,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0007,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0007,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0007,criterion,counts,1,n_analysed and n_clusters exact
RD0007,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RD0006,criterion,beta_point,1,OLS slope equals reference to 1e-4
RD0006,criterion,se_cluster,1,Cluster-robust SE within 8% of CR1 reference (covers CR1/CR0/CR3 conventions and t vs normal)
RD0006,criterion,ci,1,95% CI bounds within 0.03 of reference (t(G-1) or normal critical values both accepted)
RD0006,criterion,counts,1,n_analysed and n_clusters exact
RD0006,criterion,se_ordering,1,Reported cluster SE must exceed reported conventional SE (the design has strong within-cluster correlation)
RT0025,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0025,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0025,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0025,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0025,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0025,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0025,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0025,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0025,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists
RR0017,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RR0017,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RR0017,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RR0017,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RR0017,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RR0017,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RR0017,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RR0016,criterion,naive_h1,1,Naive RMSE and MAE at h=1 equal the exact reference (rel 1e-6); 35 evaluated pairs (target 2025-10 missing)
RR0016,criterion,naive_h3,1,Naive RMSE and MAE at h=3 equal the exact reference (rel 1e-6)
RR0016,criterion,counts,1,"n_origins = 36, n_evaluated_h1 = 35, n_evaluated_h3 = 35"
RR0016,criterion,forecasts_chronology,1,"forecasts.csv: 144 rows, target = origin + h, naive forecast = last observation <= origin, actual matches data"
RR0016,criterion,model_errors_consistent,1,model RMSE/MAE in results.json agree with forecasts.csv (rel 1e-5)
RR0016,criterion,rel_improvement_consistent,1,rel_improvement_rmse_h* = 1 - rmse_model/rmse_naive (abs 1e-6)
RR0016,criterion,data_issue_reported,1,data_issues mentions the missing 2025-10 observation
RT0026,criterion,naive_exact,1,"naive RMSE/MAE at h=1,3 equal the leak-free real-time reference (abs 2e-3)"
RT0026,criterion,snaive_exact,1,"seasonal-naive RMSE/MAE at h=1,3 equal the reference (abs 2e-3)"
RT0026,criterion,ar1_close,1,"AR(1) RMSE/MAE at h=1,3 within 0.03 of the real-time reference (sample-convention slack; rejects the final-vintage implementation)"
RT0026,criterion,revision,1,mean absolute revision of the h=1 targets (abs 2e-3)
RT0026,criterion,forecasts_chronology,1,"forecasts.csv: 80 rows, 20 per model, vintage_used = origin, target = last vintage month + h, actuals = first release, naive/snaive rows exact (2e-3), ar1 rows within 0.05"
RT0026,criterion,model_errors_consistent,1,model RMSE/MAE and rel_improvement agree with forecasts.csv
RT0026,criterion,dm_consistent,1,"Diebold-Mariano statistic/p-value (model vs naive, Bartlett lag h-1, normal p) agree with recomputation from forecasts.csv"
RT0026,criterion,conclusion_consistent,1,conclusion codes agree with rel_improvement sign and dm p-value
RT0026,criterion,artifacts,1,table1.csv has 8 rows consistent with results.json; figure1.png exists