{ "spec": { "name": "Regional Sports and Events Complex \u2014 Economic Impact", "client": "Illustrative County Board of Commissioners", "region": "Illustrative Region", "analysis_type": "impact", "analysis_type_label": "Impact analysis - prospective change", "dollar_year": 2024, "closure": "type_ii", "closure_label": "Type II (closed on households at the accounts-implied rate)", "leakages": null, "household_income_distribution": null, "effective_leakages": null, "regionalization": null, "discount_rate": 0.04, "horizon_years": 12, "analyst": "Project Red Team", "purpose": "Whether a $4.0M county contribution is recovered through the revenue the facility generates." }, "regionalization": null, "absorption": null, "imports": null, "sourcing": [], "peers": [], "suppression_bound": null, "peer_subject": "", "fiscal_balance": null, "price_level": null, "tier": "illustrative", "publishable": false, "headline": { "tier": "illustrative", "publishable": false, "annual:Annual Operations": { 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annual figure" } } }, "phases": { "Construction": { "label": "Construction", "region": "Illustrative Region", "closure": "type_ii", "closure_label": "Type II (closed on households at the accounts-implied rate)", "dollar_year": 2024, "tier": "illustrative", "summary": { "output": { "direct": 5915000.0, "indirect": 2263686.1167949853, "induced": 2883644.861513781, "total": 11062330.978308765 }, "labor_income": { "direct": 2001500.0000000002, "indirect": 756621.7597697268, "induced": 1070914.1338956696, "total": 3829035.893665396 }, "employment": { "direct": 43.6925, "indirect": 21.121471053181637, "induced": 28.13406685584536, "total": 92.948037909027 }, "value_added": { "direct": 4193149.999999999, "indirect": 1721849.9999999993, "induced": 2220839.508053544, "total": 8135839.508053541 } }, "output_multiplier": 1.87021656438018, "by_sector": { "output": { "AGR": { "direct": 0.0, "indirect": 169962.3970934614, "induced": 97808.41048871007, "total": 267770.80758217146 }, "MIN": { 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"total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } } }, "notes": [ "Tax revenue is derived from average effective rates applied to modeled tax bases. It is not a jurisdiction-specific tax calculation and should not be used as a revenue forecast without reconciliation against actual collections.", "Tax structure: Illustrative County (Project Red Team illustrative rates \u2014 replace with jurisdiction actuals)" ] } }, "Annual Operations": { "label": "Annual Operations", "region": "Illustrative Region", "closure": "type_ii", "closure_label": "Type II (closed on households at the accounts-implied rate)", "dollar_year": 2024, "tier": "illustrative", "summary": { "output": { "direct": 3510171.105882353, "indirect": 1107885.1923494618, "induced": 1754224.1589553226, "total": 6372280.457187138 }, "labor_income": { "direct": 1311189.0522352941, "indirect": 366674.9208576025, "induced": 651475.3154659647, "total": 2329339.2885588617 }, "employment": { "direct": 36.8586688, "indirect": 10.060456786947686, "induced": 17.1149576797331, "total": 64.03408326668078 }, "value_added": { "direct": 2672306.970352941, "indirect": 837864.1355294118, 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"induced": 11908.980448011156, "total": 43102.17707661886 }, "personal_income": { "direct": 111582.18834522353, "indirect": 31204.035764981974, "induced": 55440.5493461536, "total": 198226.7734563591 }, "social_insurance": { "direct": 163426.60347060708, "indirect": 45702.362135691576, "induced": 81199.88331967786, "total": 290328.8489259765 }, "corporate_profits": { "direct": 105840.52931282826, "indirect": 36639.67333287989, "induced": 54396.2828734344, "total": 196876.48551914256 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "state": { "sales_and_excise": { "direct": 115782.13458675952, "indirect": 40081.23935684277, "induced": 59505.72796226627, "total": 215369.10190586856 }, "property": { "direct": 70963.24377898165, "indirect": 24565.920896129443, "induced": 36471.25262203416, "total": 132000.41729714526 }, "personal_income": { "direct": 36188.817841694115, "indirect": 10120.227815669828, "induced": 17980.718706860625, "total": 64289.76436422457 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 26460.132328207066, "indirect": 9159.918333219972, "induced": 13599.0707183586, "total": 49219.12137978564 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "local": { "sales_and_excise": { "direct": 82701.52470482822, "indirect": 28629.456683459124, "induced": 42504.09140161876, "total": 153835.07278990612 }, "property": { "direct": 50688.03127070117, "indirect": 17547.086354378174, "induced": 26050.894730024404, "total": 94286.01235510375 }, "personal_income": { "direct": 3015.7348201411764, "indirect": 843.3523179724858, "induced": 1498.3932255717189, "total": 5357.480363685381 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "tribal": { "sales_and_excise": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "property": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "personal_income": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } } }, "notes": [ "Tax revenue is derived from average effective rates applied to modeled tax bases. It is not a jurisdiction-specific tax calculation and should not be used as a revenue forecast without reconciliation against actual collections.", "Tax structure: Illustrative County (Project Red Team illustrative rates \u2014 replace with jurisdiction actuals)" ] } } }, "timeline": { "years": [ 2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037 ], "base_year": 2026, "discount_rate": 0.04, "horizon_note": "Timeline covers 2026-2037. Annual activities are held at their final ramp level through the horizon; one-time activities occur only in their scheduled years.", "series": { "output": { "2026": 5531165.489154383, "2027": 5531165.489154383, "2028": 3823368.274312283, "2029": 5097824.36574971, "2030": 6372280.457187138, "2031": 6372280.457187138, "2032": 6372280.457187138, "2033": 6372280.457187138, "2034": 6372280.457187138, "2035": 6372280.457187138, "2036": 6372280.457187138, "2037": 6372280.457187138 }, "labor_income": { "2026": 1914517.946832698, "2027": 1914517.946832698, "2028": 1397603.5731353168, "2029": 1863471.4308470895, "2030": 2329339.2885588617, "2031": 2329339.2885588617, "2032": 2329339.2885588617, "2033": 2329339.2885588617, "2034": 2329339.2885588617, "2035": 2329339.2885588617, "2036": 2329339.2885588617, "2037": 2329339.2885588617 }, "employment": { "2026": 46.4740189545135, "2027": 46.4740189545135, "2028": 38.42044996000847, "2029": 51.227266613344625, "2030": 64.03408326668078, "2031": 64.03408326668078, "2032": 64.03408326668078, "2033": 64.03408326668078, "2034": 64.03408326668078, "2035": 64.03408326668078, "2036": 64.03408326668078, "2037": 64.03408326668078 }, "value_added": { "2026": 4067919.7540267706, "2027": 4067919.7540267706, "2028": 2916712.2576966016, "2029": 3888949.676928803, "2030": 4861187.096161003, "2031": 4861187.096161003, "2032": 4861187.096161003, "2033": 4861187.096161003, "2034": 4861187.096161003, "2035": 4861187.096161003, "2036": 4861187.096161003, "2037": 4861187.096161003 } }, "undiscounted_total": { "output": 70961767.27586786, "labor_income": 25724825.206118695, "value_added": 53830998.21196697 }, "present_value": { "output": 57057016.217755474, "labor_income": 20646176.98762994, "value_added": 43229387.21919733 }, "steady_state_employment": 64.03408326668078, "peak_output": { "year": 2030, "value": 6372280.457187138 } }, "taxes": { "Construction": { "structure": "Illustrative County", "tier": "illustrative", "total": 2542116.4849051842, "subnational_total": 1211172.6455883929, "by_institution": { "federal": 1330943.8393167914, "state": 780299.1088229241, "local": 430873.53676546866, "tribal": 0.0 }, "by_type": { "sales_and_excise": 747661.1074577821, "property": 458243.90457089874, "personal_income": 440339.12777152064, "social_insurance": 477251.03378645494, "corporate_profits": 418621.3113185278, "other_taxes_and_fees": 0.0 }, "by_effect": { "direct": 1306329.8399999996, "indirect": 545400.930726076, "induced": 690385.7141791085, "total": 2542116.484905184 }, "detail": { "federal": { "sales_and_excise": { "direct": 60875.27039999998, "indirect": 26810.179600636046, "induced": 31940.327192609126, "total": 119625.77719324514 }, "property": { "direct": 37310.64959999999, "indirect": 16432.045561680156, "induced": 19576.329569663656, "total": 73319.0247313438 }, "personal_income": { "direct": 170327.65000000002, "indirect": 64388.51175640375, "induced": 91134.79279452149, "total": 325850.9545509253 }, "social_insurance": { "direct": 249466.96, "indirect": 94305.33613769872, "induced": 133478.73764875624, "total": 477251.03378645494 }, "corporate_profits": { "direct": 170422.70399999994, "indirect": 75056.14796030599, "induced": 89418.19709451632, "total": 334897.04905482224 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "state": { "sales_and_excise": { "direct": 186430.51559999993, "indirect": 82106.17502694788, "induced": 97817.25202736544, "total": 366353.9426543132 }, "property": { "direct": 114263.86439999996, "indirect": 50323.13953264548, "induced": 59952.509307094944, "total": 224539.51323974036 }, "personal_income": { "direct": 55241.4, "indirect": 20882.76056964446, "induced": 29557.23009552048, "total": 105681.39066516494 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 42605.675999999985, "indirect": 18764.036990076496, "induced": 22354.54927362908, "total": 83724.26226370556 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "local": { "sales_and_excise": { "direct": 133164.65399999992, "indirect": 58647.267876391335, "induced": 69869.46573383246, "total": 261681.38761022373 }, "property": { "direct": 81617.04599999996, "indirect": 35945.09966617534, "induced": 42823.22093363925, "total": 160385.36659981453 }, "personal_income": { "direct": 4603.450000000001, "indirect": 1740.2300474703716, "induced": 2463.1025079600404, "total": 8806.782555430413 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "tribal": { "sales_and_excise": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "property": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "personal_income": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } } }, "notes": [ "Tax revenue is derived from average effective rates applied to modeled tax bases. It is not a jurisdiction-specific tax calculation and should not be used as a revenue forecast without reconciliation against actual collections.", "Tax structure: Illustrative County (Project Red Team illustrative rates \u2014 replace with jurisdiction actuals)" ] }, "Annual Operations": { "structure": "Illustrative County", "tier": "illustrative", "total": 1513215.8601377732, "subnational_total": 714356.9704557193, "by_institution": { "federal": 798858.889682054, "state": 460878.404947024, "local": 253478.56550869526, "tribal": 0.0 }, "by_type": { "sales_and_excise": 439528.7793997318, "property": 269388.60672886786, "personal_income": 267874.0181842691, "social_insurance": 290328.8489259765, "corporate_profits": 246095.6068989282, "other_taxes_and_fees": 0.0 }, "by_effect": { "direct": 827627.0231916425, "indirect": 265602.5498085222, "induced": 419986.28713760874, "total": 1513215.8601377737 }, "detail": { "federal": { "sales_and_excise": { "direct": 37806.41129363576, "indirect": 13087.751626724172, "induced": 19430.441783597147, "total": 70324.60470395708 }, "property": { "direct": 23171.671438034824, "indirect": 8021.525190572879, "induced": 11908.980448011156, "total": 43102.17707661886 }, "personal_income": { "direct": 111582.18834522353, "indirect": 31204.035764981974, "induced": 55440.5493461536, "total": 198226.7734563591 }, "social_insurance": { "direct": 163426.60347060708, "indirect": 45702.362135691576, "induced": 81199.88331967786, "total": 290328.8489259765 }, "corporate_profits": { "direct": 105840.52931282826, "indirect": 36639.67333287989, "induced": 54396.2828734344, "total": 196876.48551914256 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "state": { "sales_and_excise": { "direct": 115782.13458675952, "indirect": 40081.23935684277, "induced": 59505.72796226627, "total": 215369.10190586856 }, "property": { "direct": 70963.24377898165, "indirect": 24565.920896129443, "induced": 36471.25262203416, "total": 132000.41729714526 }, "personal_income": { "direct": 36188.817841694115, "indirect": 10120.227815669828, "induced": 17980.718706860625, "total": 64289.76436422457 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 26460.132328207066, "indirect": 9159.918333219972, "induced": 13599.0707183586, "total": 49219.12137978564 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "local": { "sales_and_excise": { "direct": 82701.52470482822, "indirect": 28629.456683459124, "induced": 42504.09140161876, "total": 153835.07278990612 }, "property": { "direct": 50688.03127070117, "indirect": 17547.086354378174, "induced": 26050.894730024404, "total": 94286.01235510375 }, "personal_income": { "direct": 3015.7348201411764, "indirect": 843.3523179724858, "induced": 1498.3932255717189, "total": 5357.480363685381 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } }, "tribal": { "sales_and_excise": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "property": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "personal_income": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "social_insurance": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "corporate_profits": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 }, "other_taxes_and_fees": { "direct": 0.0, "indirect": 0.0, "induced": 0.0, "total": 0.0 } } }, "notes": [ "Tax revenue is derived from average effective rates applied to modeled tax bases. It is not a jurisdiction-specific tax calculation and should not be used as a revenue forecast without reconciliation against actual collections.", "Tax structure: Illustrative County (Project Red Team illustrative rates \u2014 replace with jurisdiction actuals)" ] } }, "multipliers": { "AGR": { "output_final_demand": 1.6569893384471106, "labor_income_final_demand": 0.45193979665948, "employment_final_demand_per_million": 15.757016018913927, "value_added_final_demand": 1.2621249274114967, "output_ratio": 1.6569893384471106, "labor_income_ratio": 2.0542718029976363, "employment_ratio": 1.6586332651488342 }, "MIN": { "output_final_demand": 1.6591823858430135, "labor_income_final_demand": 0.45358657406941505, "employment_final_demand_per_million": 15.731419614168722, "value_added_final_demand": 1.2630800577457424, "output_ratio": 1.6591823858430135, "labor_income_ratio": 2.0617571548609774, "employment_ratio": 1.6559389067546022 }, "UTL": { "output_final_demand": 1.889343382852404, "labor_income_final_demand": 0.6543512199387487, "employment_final_demand_per_million": 15.409464914973622, "value_added_final_demand": 1.379523483649536, "output_ratio": 1.889343382852404, "labor_income_ratio": 1.924562411584555, "employment_ratio": 2.2013521307105175 }, "CON": { "output_final_demand": 1.8873771609180054, "labor_income_final_demand": 0.6548145279088221, "employment_final_demand_per_million": 15.497932509169388, "value_added_final_demand": 1.3797922021136375, "output_ratio": 1.8873771609180054, "labor_income_ratio": 1.9259250820847709, "employment_ratio": 2.2139903584527696 }, "MFG": { "output_final_demand": 1.8586267097804423, "labor_income_final_demand": 0.5643545976966767, "employment_final_demand_per_million": 12.709165078866619, "value_added_final_demand": 1.3273254735454219, "output_ratio": 1.8586267097804423, "labor_income_ratio": 2.17059460652568, "employment_ratio": 2.8242589064148045 }, "WHL": { "output_final_demand": 1.7209502882526393, "labor_income_final_demand": 0.5875973745212786, "employment_final_demand_per_million": 17.831049315507364, "value_added_final_demand": 1.340806276150156, "output_ratio": 1.7209502882526393, "labor_income_ratio": 1.780598104609935, "employment_ratio": 1.6210044832279424 }, "RET": { "output_final_demand": 1.7201631382038314, "labor_income_final_demand": 0.5879412977704744, "employment_final_demand_per_million": 17.841432687036914, "value_added_final_demand": 1.3410057515170017, "output_ratio": 1.7201631382038314, "labor_income_ratio": 1.7816402962741649, "employment_ratio": 1.621948426094265 }, "TRN": { "output_final_demand": 1.7209366699382613, "labor_income_final_demand": 0.5885004497654079, "employment_final_demand_per_million": 17.809700159883814, "value_added_final_demand": 1.3413300594827247, "output_ratio": 1.7209366699382613, "labor_income_ratio": 1.783334696258812, "employment_ratio": 1.6190636508985283 }, "FIN": { "output_final_demand": 1.8274656411267456, "labor_income_final_demand": 0.7453153878183281, "employment_final_demand_per_million": 16.84246655120952, "value_added_final_demand": 1.432282669892317, "output_ratio": 1.8274656411267456, "labor_income_ratio": 1.6562564173740624, "employment_ratio": 1.8713851723566133 }, "PRO": { "output_final_demand": 1.8253557259568178, "labor_income_final_demand": 0.7464166766434936, "employment_final_demand_per_million": 16.937772617324626, "value_added_final_demand": 1.432921417034059, "output_ratio": 1.8253557259568178, "labor_income_ratio": 1.6587037258744306, "employment_ratio": 1.8819747352582916 }, "HLT": { "output_final_demand": 1.8263314597108833, "labor_income_final_demand": 0.7440213649932519, "employment_final_demand_per_million": 16.849956129596016, "value_added_final_demand": 1.4315321370965794, "output_ratio": 1.8263314597108833, "labor_income_ratio": 1.6533808110961155, "employment_ratio": 1.8722173477328907 }, "ACC": { "output_final_demand": 1.8593993638637665, "labor_income_final_demand": 0.6845357452207789, "employment_final_demand_per_million": 25.15195522494983, "value_added_final_demand": 1.397030497984156, "output_ratio": 1.8593993638637665, "labor_income_ratio": 1.801409855844155, "employment_ratio": 1.4795267779382253 } }, "provenance": { "study": "Regional Sports and Events Complex \u2014 Economic Impact", "base_tier": "illustrative", "overall_tier": "illustrative", "publishable": false, "sources": [ "Project Red Team synthetic region generator \u2014 structural placeholder, not an observed economy (2024)", "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "Project Red Team illustrative rates \u2014 replace with jurisdiction actuals", "Project Red Team illustrative staffing patterns \u2014 replace with BLS OES industry-occupation matrix for the study region" ], "assumptions": [ "Fixed production technology: input proportions do not change with the scale of the shock.", "No supply constraints: the region can meet added demand without price effects or capacity limits.", "Linearity: effects scale proportionally with the shock.", "Local consumption per $1 of local labor income = $0.580, taken from the household column of the regional accounts rather than assumed.", "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region.", "Local purchase percentage for the commodity: 62%.", "Share of margin activity occurring locally: 100%.", "Local purchase percentage for the commodity: 5%.", "Taxes on production and imports are treated as revenue and allocated across levels of government rather than re-rated.", "Effective rates are jurisdiction averages, not a modeled tax code.", "Tax bases are recomputed per effect round so the fiscal table reconciles to the impact table.", "Local purchase percentage for the commodity: 100%.", "Local purchase percentage for the commodity: 4%.", "Spending profile covers 6 commodities and sums to 100% of the stated total.", "The 22 stated jobs have the same output per worker as the regional average for ACC.", "Stated employment replaces the coefficient-derived direct job count; indirect and induced jobs still come from the model.", "28% of this activity's demand is spending that would have occurred elsewhere in the region anyway, and is therefore displacement rather than new economic activity.", "The adjustment nets demand and household income. A stated direct job count is preserved rather than fractionally reduced; any offsetting regional jobs must be modeled as a separate displaced activity.", "Basis: Intercept surveys at three comparable facilities.", "Timeline covers 2026-2037. Annual activities are held at their final ramp level through the horizon; one-time activities occur only in their scheduled years.", "Present values use 2026 as the base year at 4.0%; the price level remains the study's declared dollar year, and undiscounted sums are reported alongside them.", "The model is static: it assumes regional production technology and trade patterns do not change over the horizon. For horizons beyond roughly ten years that assumption weakens materially.", "Sources compose multiplicatively, which treats each as a proportional perturbation of the level rather than an additive one. That is right for a multiplier and for output, and would be wrong for a figure that can cross zero.", "INDEPENDENT resamples each source separately and is the conventional combination; it understates the tail whenever the optimistic ends of two sources tend to occur together, which they do when the same analyst chooses both.", "ALIGNED pairs equal percentiles across sources and is the widest defensible reading. The truth lies between the two and neither is a forecast.", "The closure is an analyst's choice, not a property of the region. Reporting one closure's result without the others' range overstates the precision of the finding.", "Coefficients carry a 15% coefficient of variation, stated rather than measured.", "Perturbations are independent across cells, which understates spread where errors are correlated \u2014 as they are when a whole table comes from one source.", "0 of 200 draws were discarded as non-productive rather than clamped.", "New jobs follow the sector's existing occupational mix.", "A facility with an unusual staffing model will not match this; where the operator has a staffing plan, use it instead.", "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "entries": [ { "quantity": "regional accounts", "method": "industry-by-industry social accounting matrix", "formula": "", "source": "Project Red Team synthetic region generator \u2014 structural placeholder, not an observed economy", "vintage": "2024", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [], "inputs": { "region": "Illustrative Region", "n_sectors": 12, "coverage": "regional", "total_output": 2400000000.0 }, "notes": [] }, { "quantity": "Leontief total requirements", "method": "Leontief inverse of the regional direct-requirements matrix", "formula": "L = (I - A)^-1, A = Z diag(x)^-1", "source": "", "vintage": "", "citation": "Miller & Blair, Input-Output Analysis: Foundations and Extensions, 3rd ed., ch. 2", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Fixed production 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"Tax bases are recomputed per effect round so the fiscal table reconciles to the impact table." ], "inputs": { "structure": "Illustrative County", "personal_income_rate": 0.115, "social_insurance_rate": 0.152, "corporate_profits_rate": 0.135 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: ACC", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "ACC", "purchaser_value": 1596000.0, "local_final_demand": 1596000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: RET", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "RET", "purchaser_value": 912000.0, "local_final_demand": 912000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: MFG", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 4%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "MFG", "purchaser_value": 380000.0, "local_final_demand": 161120.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: TRN", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "TRN", "purchaser_value": 342000.0, "local_final_demand": 342000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: PRO", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "PRO", "purchaser_value": 304000.0, "local_final_demand": 304000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: HLT", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "HLT", "purchaser_value": 266000.0, "local_final_demand": 266000.0 }, "notes": [] }, { "quantity": "spending pattern: Visitor spending", "method": "expenditure profile allocated across commodities", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Spending profile covers 6 commodities and sums to 100% of the stated total." ], "inputs": { "total": 3800000, "commodities": 6 }, "notes": [] }, { "quantity": "employment event: Facility staff", "method": "job count converted to industry output", "formula": "output = jobs / (jobs per $1 of output)", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "The 22 stated jobs have the same output per worker as the regional average for ACC.", "Stated employment replaces the coefficient-derived direct job count; indirect and induced jobs still come from the model." ], "inputs": { "sector": "ACC", "jobs": 22, "implied_output": 1294117.6470588236 }, "notes": [] }, { "quantity": "displacement adjustment: Annual Operations", "method": "net-new demand adjustment", "formula": "net new = gross x (1 - 0.28)", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "base", "assumptions": [ "28% of this activity's demand is spending that would have occurred elsewhere in the region anyway, and is therefore displacement rather than new economic activity.", "The adjustment nets demand and household income. A stated direct job count is preserved rather than fractionally reduced; any offsetting regional jobs must be modeled as a separate displaced activity.", "Basis: Intercept surveys at three comparable facilities." ], "inputs": { "displacement_share": 0.28 }, "notes": [] }, { "quantity": "tax revenue", "method": "effective rates applied to modeled value-added tax bases", "formula": "revenue = base x effective rate x institutional share", "source": "Project Red Team illustrative rates \u2014 replace with jurisdiction actuals", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Taxes on production and imports are treated as revenue and allocated across levels of government rather than re-rated.", "Effective rates are jurisdiction averages, not a modeled tax code.", "Tax bases are recomputed per effect round so the fiscal table reconciles to the impact table." ], "inputs": { "structure": "Illustrative County", "personal_income_rate": 0.115, "social_insurance_rate": 0.152, "corporate_profits_rate": 0.135 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Sitework and structures", "method": "purchaser-price 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the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Equipment", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 5%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "MFG", "purchaser_value": 1500000, "local_final_demand": 645000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: ACC", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "ACC", "purchaser_value": 1596000.0, "local_final_demand": 1596000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: RET", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "RET", "purchaser_value": 912000.0, "local_final_demand": 912000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: MFG", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 4%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "MFG", "purchaser_value": 380000.0, "local_final_demand": 161120.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: TRN", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "TRN", "purchaser_value": 342000.0, "local_final_demand": 342000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: PRO", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "PRO", "purchaser_value": 304000.0, "local_final_demand": 304000.0 }, "notes": [] }, { "quantity": "purchaser-to-producer price conversion", "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "source": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Retail and wholesale margins are recorded as output of the trade sectors, not of the sector that produced the good.", "Only the margin portion of a retail purchase is local unless the good itself is produced in the region." ], "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "notes": [] }, { "quantity": "spending event: Visitor spending: HLT", "method": "purchaser-price spending converted to local producer-price demand", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Local purchase percentage for the commodity: 100%.", "Share of margin activity occurring locally: 100%." ], "inputs": { "commodity": "HLT", "purchaser_value": 266000.0, "local_final_demand": 266000.0 }, "notes": [] }, { "quantity": "spending pattern: Visitor spending", "method": "expenditure profile allocated across commodities", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "estimated", "tier_label": "Modeled estimate", "layer": "base", "assumptions": [ "Spending profile covers 6 commodities and sums to 100% of the stated total." ], "inputs": { "total": 3800000, "commodities": 6 }, "notes": [] }, { "quantity": "employment event: Facility staff", "method": "job count converted to 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household income. A stated direct job count is preserved rather than fractionally reduced; any offsetting regional jobs must be modeled as a separate displaced activity.", "Basis: Intercept surveys at three comparable facilities." ], "inputs": { "displacement_share": 0.28 }, "notes": [] }, { "quantity": "multi-year impact stream", "method": "phased timeline with ramped activity levels", "formula": "NPV = sum_t effect_t / (1 + 0.040)^(t - 2026)", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "base", "assumptions": [ "Timeline covers 2026-2037. Annual activities are held at their final ramp level through the horizon; one-time activities occur only in their scheduled years.", "Present values use 2026 as the base year at 4.0%; the price level remains the study's declared dollar year, and undiscounted sums are reported alongside them.", "The model is static: it assumes regional production technology and trade patterns do not change over the horizon. For horizons beyond roughly ten years that assumption weakens materially." ], "inputs": { "years": 12, "discount_rate": 0.04, "base_year": 2026 }, "notes": [] }, { "quantity": "predictive interval for output-weighted average multiplier", "method": "1 uncertainty source combined multiplicatively in relative space under sources vary independently", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "base", "assumptions": [ "Sources compose multiplicatively, which treats each as a proportional perturbation of the level rather than an additive one. That is right for a multiplier and for output, and would be wrong for a figure that can cross zero.", "INDEPENDENT resamples each source separately and is the conventional combination; it understates the tail whenever the optimistic ends of two sources tend to occur together, which they do when the same analyst chooses both.", "ALIGNED pairs equal percentiles across sources and is the widest defensible reading. The truth lies between the two and neither is a forecast." ], "inputs": {}, "notes": [] }, { "quantity": "predictive interval for output-weighted average multiplier", "method": "1 uncertainty source combined multiplicatively in relative space under sources move together", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "base", "assumptions": [ "Sources compose multiplicatively, which treats each as a proportional perturbation of the level rather than an additive one. That is right for a multiplier and for output, and would be wrong for a figure that can cross zero.", "INDEPENDENT resamples each source separately and is the conventional combination; it understates the tail whenever the optimistic ends of two sources tend to occur together, which they do when the same analyst chooses both.", "ALIGNED pairs equal percentiles across sources and is the widest defensible reading. The truth lies between the two and neither is a forecast." ], "inputs": {}, "notes": [] }, { "quantity": "closure sensitivity", "method": "the same accounts run under every closure the study could have chosen", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "base", "assumptions": [ "The closure is an analyst's choice, not a property of the region. Reporting one closure's result without the others' range overstates the precision of the finding." ], "inputs": {}, "notes": [] }, { "quantity": "coefficient uncertainty", "method": "multiplicative lognormal perturbation of the technical-coefficients matrix", "formula": "a_ij' = a_ij * L, L ~ lognormal(mean 1, CV 15%)", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "base", "assumptions": [ "Coefficients carry a 15% coefficient of variation, stated rather than measured.", "Perturbations are independent across cells, which understates spread where errors are correlated \u2014 as they are when a whole table comes from one source.", "0 of 200 draws were discarded as non-productive rather than clamped." ], "inputs": {}, "notes": [] }, { "quantity": "occupational composition", "method": "sector staffing patterns applied to modeled employment", "formula": "", "source": "Project Red Team illustrative staffing patterns \u2014 replace with BLS OES industry-occupation matrix for the study region", "vintage": "", "citation": "", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "New jobs follow the sector's existing occupational mix.", "A facility with an unusual staffing model will not match this; where the operator has a staffing plan, use it instead." ], "inputs": {}, "notes": [] }, { "quantity": "belief over rival theses", "method": "Bayesian update over five competing explanations, weighted by source", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "epistemic quality", "method": "how well evidenced the study is, scored over the governed evidence base from source independence, contamination and how contested the leading explanation is \u2014 internally the information crystal, in manifold/information.py", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "forecast accuracy of the practice", "method": "this practice's closed forecasts scored against their outcomes, over the closed-study register \u2014 internally the reality crystal, in manifold/reality.py", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "recommendation strength", "method": "recommendation authority opened at what the evidence supports, then reduced once per project-level governance layer and never added back \u2014 internally the throttle cascade, in manifold/synthesis.py", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "stakeholder lens verdicts", "method": "the cascade re-read under each stakeholder's weighting of the case", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "what would change the verdict", "method": "inverse cascade priced against the collection plan", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "case geometry", "method": "the case read twice, once as what argues for it and once as what argues against it, with the transport between the two readings measured \u2014 internally the dual tetrahedron, in manifold/tetrahedron.py", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] }, { "quantity": "flat evidence observation view", "method": "every governed observation, absence and consequence flattened into one typed stream a renderer can print without re-deciding anything \u2014 the flat evidence-surface contract, version 1, in manifold/surface.py", "formula": "", "source": "", "vintage": "", "citation": "", "tier": "derived", "tier_label": "Derived by standard method", "layer": "decision", "assumptions": [ "Project Red Team decision layer applied to the base analysis, not standard input-output output. A reviewer reproducing the federal method will not reproduce it." ], "inputs": {}, "notes": [] } ] }, "validation": { "subject": "study: Regional Sports and Events Complex \u2014 Economic Impact", "passed": true, "checks": [ { "name": "non_negative", "severity": "info", "message": "intermediate flows Z is non-negative", "detail": {} }, { "name": "non_negative", "severity": "info", "message": "industry output is non-negative", "detail": {} }, { "name": "non_negative", "severity": "info", "message": "employment is non-negative", "detail": {} }, { "name": "balance", "severity": "info", "message": "industry AGR row/column balance balances within tolerance", "detail": { "gap": 0.0 } }, { "name": "balance", "severity": "info", "message": "industry MIN row/column balance balances within tolerance", "detail": { "gap": 0.0 } }, { "name": "balance", "severity": "info", "message": "industry UTL row/column balance balances within tolerance", "detail": { "gap": 0.0 } }, { "name": "balance", "severity": "info", "message": "industry CON row/column balance balances within tolerance", "detail": { "gap": 0.0 } }, { "name": "balance", "severity": "info", "message": "industry MFG row/column balance balances within tolerance", "detail": { "gap": 0.0 } }, { "name": "balance", "severity": "info", "message": "industry WHL row/column balance balances within tolerance", "detail": { "gap": 2.9802322387695312e-08 } }, { "name": "balance", "severity": "info", "message": "industry RET row/column balance balances within tolerance", "detail": { "gap": 5.960464477539063e-08 } }, { "name": "balance", "severity": "info", "message": "industry TRN row/column balance balances within tolerance", "detail": { "gap": 2.9802322387695312e-08 } }, { "name": "balance", "severity": "info", "message": "industry FIN row/column balance balances within tolerance", "detail": { "gap": 2.9802322387695312e-08 } }, { "name": "balance", "severity": "info", "message": "industry PRO row/column balance balances within tolerance", "detail": { "gap": 2.9802322387695312e-08 } }, { "name": "balance", "severity": "info", "message": "industry HLT row/column balance balances within tolerance", "detail": { "gap": 2.9802322387695312e-08 } }, { "name": "balance", "severity": "info", "message": "industry ACC row/column balance balances within tolerance", "detail": { "gap": 0.0 } }, { "name": "balance", "severity": "info", "message": "total output vs total sales balances within tolerance", "detail": { "gap": 4.76837158203125e-07 } }, { "name": "consumption_rate", "severity": "info", "message": "local consumption per $1 labor income = 0.580", "detail": { "rate": 0.5799996578061883 } }, { "name": "productive", "severity": "info", "message": "spectral radius 0.2429 < 1", "detail": { "spectral_radius": 0.24290098133831614 } }, { "name": "diagonal", "severity": "info", "message": "minimum diagonal 1.0093 >= 1", "detail": {} }, { "name": "productive", "severity": "info", "message": "spectral radius 0.5898 < 1", "detail": { "spectral_radius": 0.5897952033091378 } }, { "name": "diagonal", "severity": "info", "message": "minimum diagonal 1.0210 >= 1", "detail": {} }, { "name": "plausible", "severity": "info", "message": "Type II output multiplier 1.791 within published range", "detail": { "value": 1.791158595256476 } }, { "name": "ordering", "severity": "info", "message": "Type I 1.3208 <= Type II 1.7912", "detail": {} }, { "name": "margins", "severity": "info", "message": "12 commodity margin structures defined", "detail": {} }, { "name": "illustrative_rates", "severity": "warn", "message": "tax rates are illustrative placeholders; fiscal tables built on them cannot be published as findings", "detail": {} }, { "name": "rates", "severity": "info", "message": "effective rates within a plausible range", "detail": {} }, { "name": "resolved", "severity": "info", "message": "2 events -> $5,915,000 local final demand", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: ACC: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: RET: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: TRN: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: PRO: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: HLT: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "resolved", "severity": "info", "message": "2 events -> $3,510,171 local final demand", "detail": {} }, { "name": "resolved", "severity": "info", "message": "2 events -> $5,915,000 local final demand", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: ACC: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: RET: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: TRN: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: PRO: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "assumption", "severity": "warn", "message": "Visitor spending: HLT: local purchase percentage is 100%. Verify this \u2014 it assumes nothing was bought from outside the region.", "detail": {} }, { "name": "resolved", "severity": "info", "message": "2 events -> $3,510,171 local final demand", "detail": {} }, { "name": "illustrative_study", "severity": "warn", "message": "this study rests on at least one illustrative input, so its numbers are structural placeholders rather than findings. The contaminating inputs are listed in the provenance appendix.", "detail": {} } ] }, "decision": null, "study": { "contribution": [ { "sector": "Manufacturing", "sector_index": 4, "closure": "type_ii", "direct_output": 260061066.52809066, "total_output": 360708733.66839963, "total_labor_income": 102282474.414513, "total_employment": 2154.4062132975355, "output_share": 0.15029530569516653, "employment_share": 0.09520797125517909, "impact_total_output": 372826553.1918977, "overstatement": 0.03359447219439393, "narrative": "Manufacturing accounts for 15.0% of regional output and 9.5% of employment once its supply chain is included \u2014 $360,708,734 of output against $260,061,067 produced directly. Run as an impact instead of a contribution the same figure would have come out 3.4% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Health, education, and social services", "sector_index": 10, "closure": "type_ii", "direct_output": 259770114.83498073, "total_output": 325239485.6146091, "total_labor_income": 137681550.67579666, "total_employment": 2924.3631000051237, "output_share": 0.13551645233942047, "employment_share": 0.12923406748759805, "impact_total_output": 328871399.9356957, "overstatement": 0.011166892341571977, "narrative": "Health, education, and social services accounts for 13.6% of regional output and 12.9% of employment once its supply chain is included \u2014 $325,239,486 of output against $259,770,115 produced directly. Run as an impact instead of a contribution the same figure would have come out 1.1% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Construction", "sector_index": 3, "closure": "type_ii", "direct_output": 216749963.21089178, "total_output": 294358087.8945682, "total_labor_income": 99582211.79448435, "total_employment": 2256.216724571509, "output_share": 0.12264920328940342, "employment_share": 0.09970720272370108, "impact_total_output": 302200752.12040365, "overstatement": 0.02664327751933393, "narrative": "Construction accounts for 12.3% of regional output and 10.0% of employment once its supply chain is included \u2014 $294,358,088 of output against $216,749,963 produced directly. Run as an impact instead of a contribution the same figure would have come out 2.7% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Retail trade", "sector_index": 6, "closure": "type_ii", "direct_output": 234872012.43189207, "total_output": 293590196.76987296, "total_labor_income": 97336953.14198714, "total_employment": 3107.7397005133726, "output_share": 0.12232924865411374, "employment_share": 0.13733788467968605, "impact_total_output": 300021953.82174844, "overstatement": 0.02190726094617168, "narrative": "Retail trade accounts for 12.2% of regional output and 13.7% of employment once its supply chain is included \u2014 $293,590,197 of output against $234,872,012 produced directly. Run as an impact instead of a contribution the same figure would have come out 2.2% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Finance, insurance, and real estate", "sector_index": 8, "closure": "type_ii", "direct_output": 223614957.36514005, "total_output": 279929826.86472476, "total_labor_income": 118692034.82708181, "total_employment": 2512.88992447074, "output_share": 0.11663742786030198, "employment_share": 0.11105015860971156, "impact_total_output": 283134332.65063703, "overstatement": 0.011447532482706357, "narrative": "Finance, insurance, and real estate accounts for 11.7% of regional output and 11.1% of employment once its supply chain is included \u2014 $279,929,827 of output against $223,614,957 produced directly. Run as an impact instead of a contribution the same figure would have come out 1.1% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Accommodation, food service, and recreation", "sector_index": 11, "closure": "type_ii", "direct_output": 201420470.604635, "total_output": 268191112.2369278, "total_labor_income": 98402324.01130632, "total_employment": 4015.7123715364423, "output_share": 0.11174629676538658, "employment_share": 0.17746320340077254, "impact_total_output": 270684109.0020141, "overstatement": 0.009295597994626759, "narrative": "Accommodation, food service, and recreation accounts for 11.2% of regional output and 17.7% of employment once its supply chain is included \u2014 $268,191,112 of output against $201,420,471 produced directly. Run as an impact instead of a contribution the same figure would have come out 0.9% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Agriculture, forestry, and fishing", "sector_index": 0, "closure": "type_ii", "direct_output": 186673741.0765867, "total_output": 241530803.49578148, "total_labor_income": 59718946.11746077, "total_employment": 2281.3971659575477, "output_share": 0.10063783478990895, "employment_share": 0.10081998207091865, "impact_total_output": 245780942.4955803, "overstatement": 0.017596674785512523, "narrative": "Agriculture, forestry, and fishing accounts for 10.1% of regional output and 10.1% of employment once its supply chain is included \u2014 $241,530,803 of output against $186,673,741 produced directly. Run as an impact instead of a contribution the same figure would have come out 1.8% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Mining and resource extraction", "sector_index": 1, "closure": "type_ii", "direct_output": 184055773.8541315, "total_output": 239118364.01399076, "total_labor_income": 59294983.90729804, "total_employment": 2250.1357091385753, "output_share": 0.09963265167249614, "employment_share": 0.09943846921422289, "impact_total_output": 242509417.9925894, "overstatement": 0.0141814870329251, "narrative": "Mining and resource extraction accounts for 10.0% of regional output and 9.9% of employment once its supply chain is included \u2014 $239,118,364 of output against $184,055,774 produced directly. Run as an impact instead of a contribution the same figure would have come out 1.4% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Transportation and warehousing", "sector_index": 7, "closure": "type_ii", "direct_output": 166227863.03312075, "total_output": 207940617.56844634, "total_labor_income": 68987205.46185659, "total_employment": 2194.6734615575997, "output_share": 0.08664192398685264, "employment_share": 0.09698746993616433, "impact_total_output": 212395540.79160467, "overstatement": 0.02142401650650072, "narrative": "Transportation and warehousing accounts for 8.7% of regional output and 9.7% of employment once its supply chain is included \u2014 $207,940,618 of output against $166,227,863 produced directly. Run as an impact instead of a contribution the same figure would have come out 2.1% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Wholesale trade", "sector_index": 5, "closure": "type_ii", "direct_output": 163487505.12178433, "total_output": 204554827.64223912, "total_labor_income": 67723013.7426528, "total_employment": 2162.2448617826153, "output_share": 0.0852311781842663, "employment_share": 0.09555437845315344, "impact_total_output": 209007498.44675592, "overstatement": 0.021767615342251467, "narrative": "Wholesale trade accounts for 8.5% of regional output and 9.6% of employment once its supply chain is included \u2014 $204,554,828 of output against $163,487,505 produced directly. Run as an impact instead of a contribution the same figure would have come out 2.2% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Utilities", "sector_index": 2, "closure": "type_ii", "direct_output": 146852953.38574487, "total_output": 200433783.401268, "total_labor_income": 67647036.97842427, "total_employment": 1521.5439151527773, "output_share": 0.08351407641719501, "employment_share": 0.06724038783550977, "impact_total_output": 205087761.2123136, "overstatement": 0.023219527826445985, "narrative": "Utilities accounts for 8.4% of regional output and 6.7% of employment once its supply chain is included \u2014 $200,433,783 of output against $146,852,953 produced directly. Run as an impact instead of a contribution the same figure would have come out 2.3% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." }, { "sector": "Professional and business services", "sector_index": 9, "closure": "type_ii", "direct_output": 156213578.55300164, "total_output": 194730329.6844493, "total_labor_income": 82881307.15702957, "total_employment": 1765.5779910163221, "output_share": 0.08113763736852053, "employment_share": 0.07802479290113508, "impact_total_output": 197333636.70393714, "overstatement": 0.013368780424222404, "narrative": "Professional and business services accounts for 8.1% of regional output and 7.8% of employment once its supply chain is included \u2014 $194,730,330 of output against $156,213,579 produced directly. Run as an impact instead of a contribution the same figure would have come out 1.3% higher, because the industry would have been counted re-supplying itself. This is a share of what exists, not a forecast of what would be lost if it left." } ], "structural": { "linkages": [ { "code": "AGR", "name": "Agriculture, forestry, and fishing", "backward": 0.9269, "forward": 0.8286, "backward_raw": 1.657, "forward_raw": 1.4813, "backward_dispersion": 1.9512, "forward_dispersion": 2.2127, "output_share": 0.077781, "employment_share": 0.07837, "classification": "weakly linked" }, { "code": "MIN", "name": "Mining and resource extraction", "backward": 0.9281, "forward": 0.8016, "backward_raw": 1.6592, "forward_raw": 1.433, "backward_dispersion": 1.9293, "forward_dispersion": 2.2772, "output_share": 0.07669, "employment_share": 0.077271, "classification": "weakly linked" }, { "code": "UTL", "name": "Utilities", "backward": 1.0569, "forward": 0.9266, "backward_raw": 1.8893, "forward_raw": 1.6564, "backward_dispersion": 1.722, "forward_dispersion": 1.9969, "output_share": 0.061189, "employment_share": 0.045428, "classification": "pulls strongly (buys local)" }, { "code": "CON", "name": "Construction", "backward": 1.0558, "forward": 0.8786, "backward_raw": 1.8874, "forward_raw": 1.5707, "backward_dispersion": 1.718, "forward_dispersion": 2.1147, "output_share": 0.090312, "employment_share": 0.067051, "classification": "pulls strongly (buys local)" }, { "code": "MFG", "name": "Manufacturing", "backward": 1.0397, "forward": 1.0274, "backward_raw": 1.8586, "forward_raw": 1.8367, "backward_dispersion": 1.7789, "forward_dispersion": 1.7962, "output_share": 0.108359, "employment_share": 0.051717, "classification": "key sector" }, { "code": "WHL", "name": "Wholesale trade", "backward": 0.9627, "forward": 0.9139, "backward_raw": 1.721, "forward_raw": 1.6337, "backward_dispersion": 1.8964, "forward_dispersion": 2.0059, "output_share": 0.06812, "employment_share": 0.079474, "classification": "weakly linked" }, { "code": "RET", "name": "Retail trade", "backward": 0.9622, "forward": 1.3993, "backward_raw": 1.7202, "forward_raw": 2.5014, "backward_dispersion": 2.0319, "forward_dispersion": 1.3022, "output_share": 0.097863, "employment_share": 0.114175, "classification": "supplies strongly (others depend on it)" }, { "code": "TRN", "name": "Transportation and warehousing", "backward": 0.9627, "forward": 0.9665, "backward_raw": 1.7209, "forward_raw": 1.7277, "backward_dispersion": 1.9075, "forward_dispersion": 1.8905, "output_share": 0.069262, "employment_share": 0.080806, "classification": "weakly linked" }, { "code": "FIN", "name": "Finance, insurance, and real estate", "backward": 1.0223, "forward": 1.2412, "backward_raw": 1.8275, "forward_raw": 2.2189, "backward_dispersion": 1.8977, "forward_dispersion": 1.5038, "output_share": 0.093173, "employment_share": 0.088938, "classification": "key sector" }, { "code": "PRO", "name": "Professional and business services", "backward": 1.0211, "forward": 0.907, "backward_raw": 1.8254, "forward_raw": 1.6214, "backward_dispersion": 1.7896, "forward_dispersion": 2.0393, "output_share": 0.065089, "employment_share": 0.062131, "classification": "pulls strongly (buys local)" }, { "code": "HLT", "name": "Health, education, and social services", "backward": 1.0216, "forward": 1.2119, "backward_raw": 1.8263, "forward_raw": 2.1665, "backward_dispersion": 1.8907, "forward_dispersion": 1.5392, "output_share": 0.108238, "employment_share": 0.103318, "classification": "key sector" }, { "code": "ACC", "name": "Accommodation, food service, and recreation", "backward": 1.0401, "forward": 0.8976, "backward_raw": 1.8594, "forward_raw": 1.6046, "backward_dispersion": 1.7549, "forward_dispersion": 2.0727, "output_share": 0.083925, "employment_share": 0.151321, "classification": "pulls strongly (buys local)" } ], "key_sectors": [ { "code": "HLT", "name": "Health, education, and social services", "backward": 1.0216, "forward": 1.2119, "backward_raw": 1.8263, "forward_raw": 2.1665, "backward_dispersion": 1.8907, "forward_dispersion": 1.5392, "output_share": 0.108238, "employment_share": 0.103318, "classification": "key sector" }, { "code": "MFG", "name": "Manufacturing", "backward": 1.0397, "forward": 1.0274, "backward_raw": 1.8586, "forward_raw": 1.8367, "backward_dispersion": 1.7789, "forward_dispersion": 1.7962, "output_share": 0.108359, "employment_share": 0.051717, "classification": "key sector" }, { "code": "FIN", "name": "Finance, insurance, and real estate", "backward": 1.0223, "forward": 1.2412, "backward_raw": 1.8275, "forward_raw": 2.2189, "backward_dispersion": 1.8977, "forward_dispersion": 1.5038, "output_share": 0.093173, "employment_share": 0.088938, "classification": "key sector" } ], "important_coefficients": [ { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "MFG", "buyer_name": "Manufacturing", "coefficient": 0.04217729278337893, "influence": 0.19609123242063542, "influence_share": 0.020887113547328716 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "CON", "buyer_name": "Construction", "coefficient": 0.033524743786806435, "influence": 0.1582746874017985, "influence_share": 0.01685899632849383 }, { "supplier": "MFG", "supplier_name": "Manufacturing", "buyer": "UTL", "buyer_name": "Utilities", "coefficient": 0.042567752220008144, "influence": 0.14771367496258447, "influence_share": 0.015734065533426825 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "AGR", "buyer_name": "Agriculture, forestry, and fishing", "coefficient": 0.03342796540297741, "influence": 0.1385533273218187, "influence_share": 0.014758329806011687 }, { "supplier": "TRN", "supplier_name": "Transportation and warehousing", "buyer": "UTL", "buyer_name": "Utilities", "coefficient": 0.04061389991830646, "influence": 0.13257309638913234, "influence_share": 0.014121331603754875 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "TRN", "buyer_name": "Transportation and warehousing", "coefficient": 0.029727657389076973, "influence": 0.1279713871251832, "influence_share": 0.01363116984220441 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "HLT", "buyer_name": "Health, education, and social services", "coefficient": 0.027152292915431253, "influence": 0.12404332868012957, "influence_share": 0.01321276356391461 }, { "supplier": "HLT", "supplier_name": "Health, education, and social services", "buyer": "MFG", "buyer_name": "Manufacturing", "coefficient": 0.03065100597775338, "influence": 0.12342195380042437, "influence_share": 0.013146576373862075 }, { "supplier": "WHL", "supplier_name": "Wholesale trade", "buyer": "MFG", "buyer_name": "Manufacturing", "coefficient": 0.04035029381584969, "influence": 0.1225219313795869, "influence_share": 0.013050708393090511 }, { "supplier": "TRN", "supplier_name": "Transportation and warehousing", "buyer": "ACC", "buyer_name": "Accommodation, food service, and recreation", "coefficient": 0.03731930201799434, "influence": 0.11988807839320273, "influence_share": 0.012770157418350511 } ], "extraction": [ { "sector": "MFG", "name": "Manufacturing", "output_loss": 505038690.08637, "output_loss_share": 0.154875, "employment_loss": 3259.7555450227787, "employment_loss_share": 0.144056, "labor_income_loss": 148855543.04342872, "direct_output": 260061066.52809066, "ripple_multiple": 1.942 }, { "sector": "HLT", "name": "Health, education, and social services", "output_loss": 492664057.63695574, "output_loss_share": 0.15108, "employment_loss": 4423.875386741771, "employment_loss_share": 0.195501, "labor_income_loss": 208955028.8509856, "direct_output": 259770114.83498073, "ripple_multiple": 1.8965 }, { "sector": "CON", "name": "Construction", "output_loss": 429515706.94787836, "output_loss_share": 0.131715, "employment_loss": 3477.198510540792, "employment_loss_share": 0.153665, "labor_income_loss": 148231957.9260283, "direct_output": 216749963.21089178, "ripple_multiple": 1.9816 }, { "sector": "FIN", "name": "Finance, insurance, and real estate", "output_loss": 428753320.7270746, "output_loss_share": 0.131481, "employment_loss": 3816.0999767706635, "employment_loss_share": 0.168642, "labor_income_loss": 184005684.86475188, "direct_output": 223614957.36514005, "ripple_multiple": 1.9174 }, { "sector": "RET", "name": "Retail trade", "output_loss": 415053300.7489495, "output_loss_share": 0.12728, "employment_loss": 4488.260995420256, "employment_loss_share": 0.198346, "labor_income_loss": 133050926.78847192, "direct_output": 234872012.43189207, "ripple_multiple": 1.7671 } ], "decomposition": [ { "sector": "MFG", "initial": 1.0, "first_round": 0.33, "industrial_support": 0.1036, "consumption_induced": 0.425, "total": 1.8586, "induced_share": 0.2287 }, { "sector": "HLT", "initial": 1.0, "first_round": 0.2, "industrial_support": 0.066, "consumption_induced": 0.5603, "total": 1.8263, "induced_share": 0.3068 }, { "sector": "RET", "initial": 1.0, "first_round": 0.21, "industrial_support": 0.0674, "consumption_induced": 0.4428, "total": 1.7202, "induced_share": 0.2574 }, { "sector": "FIN", "initial": 1.0, "first_round": 0.2, "industrial_support": 0.0662, "consumption_induced": 0.5613, "total": 1.8275, "induced_share": 0.3071 }, { "sector": "CON", "initial": 1.0, "first_round": 0.3, "industrial_support": 0.0942, "consumption_induced": 0.4931, "total": 1.8874, "induced_share": 0.2613 } ], "provenance": { "quantity": "linkage indices", "method": "Hirschman-Rasmussen backward and forward linkage analysis", "formula": "BL_j = (sum_i L_ij) / (mean of L); FL_i = (sum_j L_ij) / (mean of L)", "source": "", "vintage": "", "citation": "Miller & Blair, Input-Output Analysis, 3rd ed., ch. 12; Rasmussen (1956); Hirschman (1958)", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Linkages are computed on the same Leontief inverse as the impact tables, under the study's stated closure.", "An index above 1.0 means the sector is above the regional average in that direction; it is not a statement about absolute size." ], "inputs": {}, "notes": [] } }, "incidence": { "jobs_by_tier": { "below 0.75x median": 38.02, "0.75x - 1.25x median": 15.01, "above 1.25x median": 11.0 }, "income_by_bracket": { "under_25k": 694439.6, "25k_50k": 726023.14, "50k_75k": 469829.03, "75k_100k": 272968.86, "over_100k": 166078.66 }, "jobs_by_sector": { "ACC": 25.03, "RET": 12.99, "TRN": 5.46, "HLT": 4.88, "PRO": 3.74, "FIN": 3.29, "WHL": 2.07, "AGR": 1.47, "CON": 1.38, "UTL": 1.31, "MIN": 1.27, "MFG": 1.12 }, "average_wage_of_new_jobs": 41198.86, "regional_median_wage": 46000.0, "wage_ratio": 0.8956, "share_to_bottom_two_brackets": 0.6098, "baseline_share_bottom_two": 0.49, "improves_distribution": true, "total_jobs": 64.03, "total_labor_income": 2329339.29, "headline": "The modeled job mix for 64 jobs averages 10% below the regional median wage ($41,199 job-weighted average wage against a $46,000 median). 61% of new labor income reaches the two lowest household brackets, against 49% of households in the region 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The recommendation is withheld until it is replaced \u2014 not because the answer would be unfavorable, but because no answer derived from this evidence would mean anything.", "diagnostics": { "information_state": "contaminated", "action_state": "adverse", "reality_state": "unearned", "epistemic_quality": 0.14, "leading_hypothesis": "", "decision_readiness": 0.366 } }, "proof": { "proof_confidence": 0.14, "methods": { "supplied table": { "method": "supplied table", "closed_count": 0, "open_count": 0, "regions_covered": 0, "mean_accuracy": 0.0, "worst_accuracy": 0.0, "optimism_bias": 0.5, "confidence": 0.14, "status": "provisional", "rationale": "needs 4 more closed forecasts, 2 more regions", "may_use_unqualified": false, "caveat": "The supplied table method has no completed forecast-versus-outcome record yet. Results carry the uncertainty of an unvalidated method.", "retirement_pressure": 0.0 } }, "proven": [], "provisional": [ "supplied table" ], "suspended": [], "retirement_candidates": [], "diagnostics": { "method_count": 1, "closed_total": 0, "open_total": 0 } }, "retirement": { "retirement_pressure": 0.0, "simplification_pressure": 0.312, "candidates": [], "retire_now": [], "watch": [], "recommended_action": "no retirement pressure: the toolkit is earning its place", "diagnostics": { "method_count": 1, "checked_count": 0, "best_accuracy": 0.0 } }, "collection": { "tasks": [], "budget": null, "selected": [], "deferred": [], "rejected": [], "total_cost": 0.0, "total_expected_value": 0.0, "net_value": 0.0, "summary": "No measurement is worth commissioning: nothing on the list would change the decision by more than it costs to find out.", "diagnostics": { "task_count": 0, "thesis_contested": true, "belief_margin": 0.0, "thesis_entropy": 1.0, "contamination_risk": 1.0, "decision_stake": 0.0 } }, "negative_space": null }, "evidence_view": { "contract_version": "evidence_surface.v1", "observation_contract": { "contract_version": "evidence_surface.v1", "observation_fields": [ "observation_id", "kind", "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics", "unit", "source_type" ], "stable_contract_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ], "compatibility_fields": [ "unit", "source_type" ], "trend_state_fields": [ "metric", "state", "level", "slope", "acceleration", "volatility", "peer_percentile", "structural_break", "capacity_distance", "revision_risk", "suppression_risk", "freshness_decay", "contradiction_index" ], "impact_hypotheses": [ "genuine_expansion", "displacement", "substitution", "leakage_dominant", "non_materialization" ], "viability_hypotheses": [ "financeable_as_scoped", "undercapitalized_or_scope_mismatch", "permitting_delay", "operating_shortfall", "fiscal_mismatch", "community_capacity_binding" ], "observation_kinds": { "base_model_input": { "purpose": "Solved model input or provenance fact that sets the evidence floor.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] }, "decision_uncertainty_parameter": { "purpose": "Decision-layer uncertainty parameter and its evidence standing.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] }, "hypothesis_evidence_atom": { "purpose": "Governed evidence atom that moves competing hypotheses.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] }, "data_quality_penalty": { "purpose": "Weakness in public/API or validation evidence that affects confidence.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] }, "trend_early_warning_indicator": { "purpose": "Time-series or practice-state warning before the client claim travels.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] }, "disclosed_but_not_used_fact": { "purpose": "Relevant fact disclosed but intentionally not used in the model.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] }, "missing_expected_evidence": { "purpose": "Expected evidence absent under a live hypothesis or claim gate.", "required_fields": [ "claim", "consequence", "authority", "value", "provenance", "vintage", "checksum", "supports", "contradicts", "missing", "used", "signal_family", "direction", "weight", "diagnostics" ] } } }, "observation_count": 19, "missing_count": 13, "by_kind": { "base_model_input": 6, "missing_expected_evidence": 13 }, "observations": [ { "observation_id": "base:0:regional_accounts", "kind": "base_model_input", "claim": "regional accounts rests on ILLUSTRATIVE \u2014 not a finding.", "consequence": "Sets the headline evidence tier floor; the gate cannot publish the affected numbers as findings.", "authority": "ILLUSTRATIVE \u2014 not a finding", "value": "", "provenance": "Project Red Team synthetic region generator \u2014 structural placeholder, not an observed economy", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": false, "used": true, "signal_family": "regional accounts", "direction": "adverse", "weight": 1.0, "diagnostics": { "method": "industry-by-industry social accounting matrix", "formula": "", "citation": "", "inputs": { "region": "Illustrative Region", "n_sectors": 12, "coverage": "regional", "total_output": 2400000000.0 }, "ledger_entries": 1 }, "unit": "", "source_type": "illustrative" }, { "observation_id": "base:1:leontief_total_requirements", "kind": "base_model_input", "claim": "Leontief total requirements rests on ILLUSTRATIVE \u2014 not a finding.", "consequence": "Sets the headline evidence tier floor; the gate cannot publish the affected numbers as findings.", "authority": "ILLUSTRATIVE \u2014 not a finding", "value": "", "provenance": "Leontief inverse of the regional direct-requirements matrix", "vintage": "", "checksum": "", "supports": {}, "contradicts": {}, "missing": false, "used": true, "signal_family": "Leontief total requirements", "direction": "adverse", "weight": 1.0, "diagnostics": { "method": "Leontief inverse of the regional direct-requirements matrix", "formula": "L = (I - A)^-1, A = Z diag(x)^-1", "citation": "Miller & Blair, Input-Output Analysis: Foundations and Extensions, 3rd ed., ch. 2", "inputs": {}, "ledger_entries": 1 }, "unit": "", "source_type": "illustrative" }, { "observation_id": "base:2:induced_effects", "kind": "base_model_input", "claim": "induced effects rests on ILLUSTRATIVE \u2014 not a finding.", "consequence": "Sets the headline evidence tier floor; the gate cannot publish the affected numbers as findings.", "authority": "ILLUSTRATIVE \u2014 not a finding", "value": "", "provenance": "household closure at the accounts-implied consumption rate", "vintage": "", "checksum": "", "supports": {}, "contradicts": {}, "missing": false, "used": true, "signal_family": "induced effects", "direction": "adverse", "weight": 1.0, "diagnostics": { "method": "household closure at the accounts-implied consumption rate", "formula": "Lbar = (I - Abar)^-1 with a household row and column", "citation": "", "inputs": { "consumption_rate": 0.5799996578061883, "closure": "type_ii" }, "ledger_entries": 1 }, "unit": "", "source_type": "illustrative" }, { "observation_id": "base:3:purchaser_to_producer_price_conversion", "kind": "base_model_input", "claim": "16 model inputs for purchaser-to-producer price conversion rest on ILLUSTRATIVE \u2014 not a finding.", "consequence": "Sets the headline evidence tier floor; the gate cannot publish the affected numbers as findings.", "authority": "ILLUSTRATIVE \u2014 not a finding", "value": "", "provenance": "Project Red Team illustrative margin rates \u2014 replace with BEA supply-table margins before publication", "vintage": "", "checksum": "", "supports": {}, "contradicts": {}, "missing": false, "used": true, "signal_family": "purchaser-to-producer price conversion", "direction": "adverse", "weight": 1.0, "diagnostics": { "method": "margin allocation", "formula": "local FD = purchaser value x margin share x local share, allocated to producer / wholesale / retail / transport", "citation": "", "inputs": { "n_commodities_with_margins": 12, "default_producer_share": 1.0 }, "ledger_entries": 16 }, "unit": "", "source_type": "illustrative" }, { "observation_id": "base:4:tax_revenue", "kind": "base_model_input", "claim": "2 model inputs for tax revenue rest on ILLUSTRATIVE \u2014 not a finding.", "consequence": "Sets the headline evidence tier floor; the gate cannot publish the affected numbers as findings.", "authority": "ILLUSTRATIVE \u2014 not a finding", "value": "", "provenance": "Project Red Team illustrative rates \u2014 replace with jurisdiction actuals", "vintage": "", "checksum": "", "supports": {}, "contradicts": {}, "missing": false, "used": true, "signal_family": "tax revenue", "direction": "adverse", "weight": 1.0, "diagnostics": { "method": "effective rates applied to modeled value-added tax bases", "formula": "revenue = base x effective rate x institutional share", "citation": "", "inputs": { "structure": "Illustrative County", "personal_income_rate": 0.115, "social_insurance_rate": 0.152, "corporate_profits_rate": 0.135 }, "ledger_entries": 2 }, "unit": "", "source_type": "illustrative" }, { "observation_id": "base:5:occupational_composition", "kind": "base_model_input", "claim": "occupational composition rests on ILLUSTRATIVE \u2014 not a finding.", "consequence": "Sets the headline evidence tier floor; the gate cannot publish the affected numbers as findings.", "authority": "ILLUSTRATIVE \u2014 not a finding", "value": "", "provenance": "Project Red Team illustrative staffing patterns \u2014 replace with BLS OES industry-occupation matrix for the study region", "vintage": "", "checksum": "", "supports": {}, "contradicts": {}, "missing": false, "used": true, "signal_family": "occupational composition", "direction": "adverse", "weight": 1.0, "diagnostics": { "method": "sector staffing patterns applied to modeled employment", "formula": "", "citation": "", "inputs": {}, "ledger_entries": 1 }, "unit": "", "source_type": "illustrative" }, { "observation_id": "regional_sensor:missing:qcew_employment_coverage", "kind": "missing_expected_evidence", "claim": "The BLS Quarterly Census of Employment and Wages (QCEW) employment coverage produced no reading for Illustrative Region 2024, and this sensor cannot separate a source that answered badly from a precondition that stopped it before it was asked, so which of the two happened here is not established. Neither one is a finding that the source had nothing to show. It is one of this study's default regional sensors.", "consequence": "The regional employment coverage and suppression check did not run, so sector coverage is not established by QCEW.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "BLS QCEW annual CSV", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": true, "used": false, "signal_family": "employment_source_quality", "direction": "adverse", "weight": 0.55, "diagnostics": { "trend_index": 0, "metric": "qcew_employment_coverage", "state": "missing", "sensor": "qcew_employment_coverage", "source_status": "missing", "reason": "no shipped QCEW annual file was found for the region and no county FIPS was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:usaspending_federal_award_flow", "kind": "missing_expected_evidence", "claim": "The USAspending.gov federal award flow was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The federal-award sensor cannot test the funding environment without county geography. Grant, match, and federal-support claims still need award-level evidence.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "USAspending.gov API", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": true, "used": false, "signal_family": "funding_reality", "direction": "adverse", "weight": 0.42, "diagnostics": { "trend_index": 1, "metric": "usaspending_federal_award_flow", "state": "missing", "sensor": "usaspending_federal_award_flow", "source_status": "missing", "reason": "no county FIPS was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:sam_gov_opportunity_pipeline", "kind": "missing_expected_evidence", "claim": "The SAM.gov contract-opportunity pipeline was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The SAM.gov opportunity sensor cannot test the federal procurement pipeline without a state or ZIP. Contract, solicitation, set-aside, and procurement-notice claims still need notice-level evidence.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "SAM.gov Opportunities API", "vintage": "2024", "checksum": "", "supports": { "non_materialization": 0.42 }, "contradicts": { "genuine_expansion": 0.42 }, "missing": true, "used": false, "signal_family": "market_demand", "direction": "adverse", "weight": 0.42, "diagnostics": { "trend_index": 2, "metric": "sam_gov_opportunity_pipeline", "state": "missing", "sensor": "sam_gov_opportunity_pipeline", "source_status": "missing", "reason": "no state or ZIP place-of-performance filter was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:epa_tri_facility_context", "kind": "missing_expected_evidence", "claim": "The EPA Toxics Release Inventory (TRI) facility context was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The EPA TRI facility sensor cannot check regional environmental-regulatory context without county geography. Site, emissions, cleanup, and permitting claims still need project-specific records.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "EPA Envirofacts DMAP REST service", "vintage": "2024", "checksum": "", "supports": { "permitting_delay": 0.44 }, "contradicts": { "financeable_as_scoped": 0.4 }, "missing": true, "used": false, "signal_family": "environmental_regulatory_context", "direction": "adverse", "weight": 0.44, "diagnostics": { "trend_index": 3, "metric": "epa_tri_facility_context", "state": "missing", "sensor": "epa_tri_facility_context", "source_status": "missing", "reason": "no county FIPS was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:eia_electricity_cost_pressure", "kind": "missing_expected_evidence", "claim": "The EIA electricity price series was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The EIA electricity sensor is state-level, so it cannot test power-cost exposure without a resolved state. Energy-sensitive operating claims still need a tariff or utility bill.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "EIA Open Data API", "vintage": "2024", "checksum": "", "supports": { "undercapitalized_or_scope_mismatch": 0.4 }, "contradicts": { "financeable_as_scoped": 0.4 }, "missing": true, "used": false, "signal_family": "energy_cost", "direction": "adverse", "weight": 0.4, "diagnostics": { "trend_index": 4, "metric": "eia_electricity_cost_pressure", "state": "missing", "sensor": "eia_electricity_cost_pressure", "source_status": "missing", "reason": "no single-state geography was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:noaa_climate_weather_context", "kind": "missing_expected_evidence", "claim": "The NOAA Climate Data Online weather record was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The NOAA climate sensor could not form a location query. Weather, heat, precipitation, resilience, insurance, and seasonality claims still need dated climate or engineering support.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "NOAA Climate Data Online API", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": true, "used": false, "signal_family": "climate_weather_context", "direction": "adverse", "weight": 0.4, "diagnostics": { "trend_index": 5, "metric": "noaa_climate_weather_context", "state": "missing", "sensor": "noaa_climate_weather_context", "source_status": "missing", "reason": "no county FIPS or state geography was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:fred_macro_financing_conditions", "kind": "missing_expected_evidence", "claim": "The FRED macro financing series was asked for Illustrative Region 2024 and did not come back with a checkable answer, so what it would have shown is unknown rather than nothing. It is one of this study's default regional sensors.", "consequence": "The FRED macro financing sensor did not produce a checkable result. Interest-rate, inflation, escalation, and capital-stack claims still need dated source support.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "FRED API", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": true, "used": false, "signal_family": "financing_conditions", "direction": "adverse", "weight": 0.46, "diagnostics": { "trend_index": 6, "metric": "fred_macro_financing_conditions", "state": "missing", "sensor": "fred_macro_financing_conditions", "source_status": "missing", "reason": "published() missing 1 required positional argument: 'source'", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:nass_agricultural_land_value_context", "kind": "missing_expected_evidence", "claim": "The USDA NASS Quick Stats agricultural land-value series was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The NASS land-value sensor cannot form a county query. Parcel value, acquisition downside, alternative land use, and highest-and-best-use claims still need appraisal or project-specific land evidence.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "USDA NASS Quick Stats API", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": true, "used": false, "signal_family": "land_use_downside", "direction": "adverse", "weight": 0.38, "diagnostics": { "trend_index": 7, "metric": "nass_agricultural_land_value_context", "state": "missing", "sensor": "nass_agricultural_land_value_context", "source_status": "missing", "reason": "no county FIPS was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:laus_labour_capacity", "kind": "missing_expected_evidence", "claim": "The BLS Local Area Unemployment Statistics (LAUS) series was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The labor-market sensor cannot test whether the jobs claim lands in a tightening or seasonal labor market.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "BLS LAUS API", "vintage": "2024", "checksum": "", "supports": { "community_capacity_binding": 0.5 }, "contradicts": { "financeable_as_scoped": 0.35 }, "missing": true, "used": false, "signal_family": "labor_capacity", "direction": "adverse", "weight": 0.5, "diagnostics": { "trend_index": 8, "metric": "laus_labour_capacity", "state": "missing", "sensor": "laus_labour_capacity", "source_status": "missing", "reason": "no county FIPS was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:bea_transfer_dependence", "kind": "missing_expected_evidence", "claim": "The BEA transfer-receipt share of personal income was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The regional-income sensor cannot test transfer dependence or commuting leakage without county geography.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "BEA Regional API", "vintage": "2024", "checksum": "", "supports": {}, "contradicts": {}, "missing": true, "used": false, "signal_family": "household_closure", "direction": "adverse", "weight": 0.5, "diagnostics": { "trend_index": 9, "metric": "bea_transfer_dependence", "state": "missing", "sensor": "bea_transfer_dependence", "source_status": "missing", "reason": "no county FIPS was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:acs_county_poverty_rate", "kind": "missing_expected_evidence", "claim": "The American Community Survey county poverty rate was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The ACS profile sensor could not form one county query from the supplied geography; a multi-state regional profile needs an explicit aggregation policy.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "Census ACS API", "vintage": "2024", "checksum": "", "supports": { "community_capacity_binding": 0.42 }, "contradicts": { "financeable_as_scoped": 0.35 }, "missing": true, "used": false, "signal_family": "community_capacity", "direction": "adverse", "weight": 0.42, "diagnostics": { "trend_index": 10, "metric": "acs_county_poverty_rate", "state": "missing", "sensor": "acs_county_poverty_rate", "source_status": "missing", "reason": "ACS default v0 needs counties in one state", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:acs_housing_available_rate", "kind": "missing_expected_evidence", "claim": "The American Community Survey share of housing units available was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The housing sensor could not form one county query from the supplied geography; multi-state housing capacity needs an explicit aggregation policy.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "Census ACS API", "vintage": "2024", "checksum": "", "supports": { "community_capacity_binding": 0.42 }, "contradicts": { "financeable_as_scoped": 0.35 }, "missing": true, "used": false, "signal_family": "housing_capacity", "direction": "adverse", "weight": 0.42, "diagnostics": { "trend_index": 11, "metric": "acs_housing_available_rate", "state": "missing", "sensor": "acs_housing_available_rate", "source_status": "missing", "reason": "ACS default v0 needs counties in one state", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" }, { "observation_id": "regional_sensor:missing:hud_user_housing_market_context", "kind": "missing_expected_evidence", "claim": "The HUD USER housing-market data was not read for Illustrative Region 2024: this study did not supply the geography or identifier the source needs, so it was never asked. It is one of this study's default regional sensors.", "consequence": "The HUD User sensor could not form a FMR, Income Limits, HUD-USPS crosswalk, or USPS NCWM query. Rent, income-limit, affordability, ZIP-geography, and address-vacancy claims still need dated public support.", "authority": "Project Red Team default regional sensor guard", "value": "", "provenance": "HUD User dataset APIs", "vintage": "2024", "checksum": "", "supports": { "community_capacity_binding": 0.44 }, "contradicts": { "financeable_as_scoped": 0.35 }, "missing": true, "used": false, "signal_family": "housing_capacity", "direction": "adverse", "weight": 0.44, "diagnostics": { "trend_index": 12, "metric": "hud_user_housing_market_context", "state": "missing", "sensor": "hud_user_housing_market_context", "source_status": "missing", "reason": "no county FIPS, ZIP, or census tract was available", "region": "Illustrative Region", "year": 2024, "fips": [], "level": "" }, "unit": "", "source_type": "public_api" } ] }, "synthesis": { "convergence": { "evidence": 0.243528, "delivery": 0.486279, "governance": 0.261095, "weakest_group": "evidence", "max_contradiction": 0.344, "contested": [], "couplings": [ { "name": "evidence x forecast record", "group": "evidence", "left": { "name": "the evidence base", "meta": [ 0.14, 0.0, 1.0, 0.3 ], "quality": 0.14, "hazard": 1.0, "trust": 0.0, "family": "adverse" }, "right": { "name": "the firm's forecast record", "meta": [ 0.0, 1.0, 0.0, 0.0 ], "quality": 0.0, "hazard": 0.32, "trust": 0.0, "family": "neutral" }, "overlap_mass": 0.214441, "alignment": 0.5, "persistence": 0.136, "contradiction": 0.0, "survivability": 0.118, "consensus": 0.243528, "contested": false, "transport": { "compatibility": 0.350328, "distance": 0.726223, "radius": 0.42, "resonant_transfer": 0.012636, "direct_transfer": 0.032063, "contradiction_load": 0.60412, "insulation": 0.22624, "attenuation": 1.0, "net_transfer": 0.0, "resistance": 1.0 }, "reading": "Very little of what the evidence base and the firm's forecast record establish reaches the conclusion (0.00 of it arrives). They are too far apart for one to carry the other, so a claim resting on the pairing is weaker than either looks alone." }, { "name": "recommendation x case structure", "group": "delivery", "left": { "name": "the recommendation", "meta": [ 0.036, 0.0, 0.0, 1.0 ], "quality": 0.036, "hazard": 0.3, "trust": 0.2, "family": "neutral" }, "right": { "name": "the case structure", "meta": [ 0.004055, 0.312912, 0.030583, 0.578098 ], "quality": 0.159077, "hazard": 0.421902, "trust": 0.8, "family": "neutral" }, "overlap_mass": 0.468239, "alignment": 0.93906, "persistence": 0.289602, "contradiction": 0.132871, "survivability": 0.312912, "consensus": 0.486279, "contested": false, "transport": { "compatibility": 0.586497, "distance": 0.263568, "radius": 0.36, "resonant_transfer": 0.508227, "direct_transfer": 0.067495, "contradiction_load": 0.445441, "insulation": 0.426811, "attenuation": 0.657629, "net_transfer": 0.064927, "resistance": 0.935073 }, "reading": "Very little of what the recommendation and the case structure establish reaches the conclusion (0.06 of it arrives). They are too far apart for one to carry the other, so a claim resting on the pairing is weaker than either looks alone." }, { "name": "method proof x forecast record", "group": "governance", "left": { "name": "the method's proof", "meta": [ 0.14, 0.14, 1.0, 0.0 ], "quality": 0.14, "hazard": 0.0, "trust": 0.14, "family": "neutral" }, "right": { "name": "the firm's forecast record", "meta": [ 0.0, 1.0, 0.0, 0.0 ], "quality": 0.0, "hazard": 0.32, "trust": 0.0, "family": "neutral" }, "overlap_mass": 0.228503, "alignment": 0.568667, "persistence": 0.226, "contradiction": 0.344, "survivability": 0.1, "consensus": 0.211759, "contested": false, "transport": { "compatibility": 0.392661, "distance": 0.663174, "radius": 0.32, "resonant_transfer": 0.004894, "direct_transfer": 0.021664, "contradiction_load": 0.55564, "insulation": 0.21772, "attenuation": 1.0, "net_transfer": 0.0, "resistance": 1.0 }, "reading": "Very little of what the method's proof and the firm's forecast record establish reaches the conclusion (0.00 of it arrives). They are too far apart for one to carry the other, so a claim resting on the pairing is weaker than either looks alone." }, { "name": "arbitration x evidence", "group": "governance", "left": { "name": "the arbitration across views", "meta": [ 0.09603, 0.032, 0.14, 0.8664 ], "quality": 0.09603, "hazard": 0.545104, "trust": 0.383872, "family": "neutral" }, "right": { "name": "the evidence base", "meta": [ 0.14, 0.0, 1.0, 0.3 ], "quality": 0.14, "hazard": 1.0, "trust": 0.0, "family": "adverse" }, "overlap_mass": 0.283337, "alignment": 0.722093, "persistence": 0.223688, "contradiction": 0.298202, "survivability": 0.383872, "consensus": 0.31043, "contested": false, "transport": { "compatibility": 0.430747, "distance": 0.515598, "radius": 0.32, "resonant_transfer": 0.023287, "direct_transfer": 0.039155, "contradiction_load": 0.627725, "insulation": 0.309341, "attenuation": 1.0, "net_transfer": 0.0, "resistance": 1.0 }, "reading": "Very little of what the arbitration across views and the evidence base establish reaches the conclusion (0.00 of it arrives). They are too far apart for one to carry the other, so a claim resting on the pairing is weaker than either looks alone." } ] }, "opening_strength": 0.330982, "recommendation_strength": 0.300873, "total_cost": 0.030109, "dominant_throttle": "evidence quality", "throttles": [ { "layer": "evidence quality", "finding": 0.45, "scored": true, "before": 0.330982, "after": 0.315498, "cost": 0.015484, "multiplier": 0.953219, "assessed": true, "reason": "evidence carries 100% contamination or internal contradiction; the leading explanation is undetermined" }, { "layer": "forecast record", "finding": 0.88, "scored": false, "before": 0.315498, "after": 0.315498, "cost": 0.0, "multiplier": 1.0, "assessed": false, "reason": "no closed studies in the register yet, so this practice has no measured accuracy to discount by. That is not the same as no expected bias: across 210 transport projects the published record is systematic overestimation that did not improve over thirty years (Flyvbjerg et al. 2005). Unmeasured is not unbiased." }, { "layer": "case structure", "finding": 0.751201, "scored": true, "before": 0.315498, "after": 0.310129, "cost": 0.005369, "multiplier": 0.982982, "assessed": true, "reason": "structure holds; weakest leg is delivery" }, { "layer": "regional absorption", "finding": 0.88, "scored": true, "before": 0.310129, "after": 0.307759, "cost": 0.00237, "multiplier": 0.992359, "assessed": false, "reason": "regional labor and capacity conditions were not supplied, so the model's no-supply-constraint assumption stands unchallenged" }, { "layer": "method proof", "finding": 0.6646, "scored": false, "before": 0.307759, "after": 0.307759, "cost": 0.0, "multiplier": 1.0, "assessed": true, "reason": "proof confidence for this method is 0.14 of 1.00, where 1.00 is a method checked against its own recorded outcomes and 0.00 is one never checked; no baseline recorded, so drift could not be checked" }, { "layer": "cross-view arbitration", "finding": 0.779317, "scored": true, "before": 0.307759, "after": 0.30319, "cost": 0.00457, "multiplier": 0.985151, "assessed": true, "reason": "the information, reality and action views arbitrate to 'quarantine narrative'" }, { "layer": "lens disagreement", "finding": 0.88, "scored": true, "before": 0.30319, "after": 0.300873, "cost": 0.002317, "multiplier": 0.992359, "assessed": false, "reason": "stakeholder lenses were not run, so it is unknown whether this verdict survives a lender's weighting or only the sponsor's" }, { "layer": "practice capacity", "finding": 0.88, "scored": false, "before": 0.300873, "after": 0.300873, "cost": 0.0, "multiplier": 1.0, "assessed": false, "reason": "the rest of the firm's book was not federated into this study" }, { "layer": "claim strength", "finding": 0.88, "scored": false, "before": 0.300873, "after": 0.300873, "cost": 0.0, "multiplier": 1.0, "assessed": false, "reason": "the claim-strength check was not run, so nothing capped how strongly this study states its conclusions" }, { "layer": "assessment coverage", "finding": 0.6, "scored": true, "before": 0.300873, "after": 0.300873, "cost": 0.0, "multiplier": 1.0, "assessed": true, "reason": "3 of 5 scoring layers were assessed, so confidence is capped at 60%. Examining fewer layers cannot produce a stronger recommendation." } ], "vetoes": [ "arbitration says quarantine narrative" ], "unassessed_layers": [ "forecast record", "regional absorption", "lens disagreement", "practice capacity", "claim strength" ], "may_recommend": false, "percentile": 0.1, "bands": { "source": "a synthetic reference population (provisional)", "n": 0, "recommend_at": 0.69622, "conditions_at": 0.61381 }, "verdict": "withhold", "headline": "Opened at 0.33 and closed at 0.30. The layer that found most against this case was evidence quality (finding 0.45). 5 layers were not assessed (forecast record, regional absorption, lens disagreement, practice capacity, claim strength); an unassessed layer is not a layer that passed. A recommendation is withheld regardless of strength: arbitration says quarantine narrative. Publish the analysis and say plainly what would have to change.", "waterfall": [ { "layer": "opening position", "value": 0.330982, "cost": 0.0, "assessed": true, "scored": true, "finding": 1.0, "reason": "what the three convergence scores support before any governance layer is applied" }, { "layer": "evidence quality", "finding": 0.45, "scored": true, "before": 0.330982, "after": 0.315498, "cost": 0.015484, "multiplier": 0.953219, "assessed": true, "reason": "evidence carries 100% contamination or internal contradiction; the leading explanation is undetermined", "value": 0.315498 }, { "layer": "forecast record", "finding": 0.88, "scored": false, "before": 0.315498, "after": 0.315498, "cost": 0.0, "multiplier": 1.0, "assessed": false, "reason": "no closed studies in the register yet, so this practice has no measured accuracy to discount by. That is not the same as no expected bias: across 210 transport projects the published record is systematic overestimation that did not improve over thirty years (Flyvbjerg et al. 2005). Unmeasured is not unbiased.", "value": 0.315498 }, { "layer": "case structure", "finding": 0.751201, "scored": true, "before": 0.315498, "after": 0.310129, "cost": 0.005369, "multiplier": 0.982982, "assessed": true, "reason": "structure holds; weakest leg is delivery", "value": 0.310129 }, { "layer": "regional absorption", "finding": 0.88, "scored": true, "before": 0.310129, "after": 0.307759, "cost": 0.00237, "multiplier": 0.992359, "assessed": false, "reason": "regional labor and capacity conditions were not supplied, so the model's no-supply-constraint assumption stands unchallenged", "value": 0.307759 }, { "layer": "method proof", "finding": 0.6646, "scored": false, "before": 0.307759, "after": 0.307759, "cost": 0.0, "multiplier": 1.0, "assessed": true, "reason": "proof confidence for this method is 0.14 of 1.00, where 1.00 is a method checked against its own recorded outcomes and 0.00 is one never checked; no baseline recorded, so drift could not be checked", "value": 0.307759 }, { "layer": "cross-view arbitration", "finding": 0.779317, "scored": true, "before": 0.307759, "after": 0.30319, "cost": 0.00457, "multiplier": 0.985151, "assessed": true, "reason": "the information, reality and action views arbitrate to 'quarantine narrative'", "value": 0.30319 }, { "layer": "lens disagreement", "finding": 0.88, "scored": true, "before": 0.30319, "after": 0.300873, "cost": 0.002317, "multiplier": 0.992359, "assessed": false, "reason": "stakeholder lenses were not run, so it is unknown whether this verdict survives a lender's weighting or only the sponsor's", "value": 0.300873 }, { "layer": "practice capacity", "finding": 0.88, "scored": false, "before": 0.300873, "after": 0.300873, "cost": 0.0, "multiplier": 1.0, "assessed": false, "reason": "the rest of the firm's book was not federated into this study", "value": 0.300873 }, { "layer": "claim strength", "finding": 0.88, "scored": false, "before": 0.300873, "after": 0.300873, "cost": 0.0, "multiplier": 1.0, "assessed": false, "reason": "the claim-strength check was not run, so nothing capped how strongly this study states its conclusions", "value": 0.300873 }, { "layer": "assessment coverage", "finding": 0.6, "scored": true, "before": 0.300873, "after": 0.300873, "cost": 0.0, "multiplier": 1.0, "assessed": true, "reason": "3 of 5 scoring layers were assessed, so confidence is capped at 60%. Examining fewer layers cannot produce a stronger recommendation.", "value": 0.300873 } ] }, "inverse": { "current": "withhold", "current_strength": 0.300873, "next_rung": "recommend with conditions", "required_strength": 0.61381, "shortfall": 0.312937, "reachable": false, "cheapest_flip": null, "levers": [ { "name": "better evidence", "kind": "evidence", "ceiling": 1.0, "gain": 0.699127, "flips_to": "", "cost": null, "purchasable": false, "actionable": true, "method": "", "gain_per_thousand": 0.0, "note": "The evidence convergence would need to rise from 0.24 to 1.00. No collection plan was supplied, so this is unpriced \u2014 run `build_collection_plan` with an EVPPI table to cost it." }, { "name": "evidence quality", "kind": "sensitivity", "ceiling": 0.310123, "gain": 0.00925, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Even resolved perfectly this layer moves the recommendation by 0.009, short of the 0.313 needed. Governance layers are deliberately given little authority; evidence is what decides." }, { "name": "assessment coverage", "kind": "sensitivity", "ceiling": 0.305694, "gain": 0.004821, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Even resolved perfectly this layer moves the recommendation by 0.005, short of the 0.313 needed. Governance layers are deliberately given little authority; evidence is what decides." }, { "name": "case structure", "kind": "sensitivity", "ceiling": 0.302278, "gain": 0.001405, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Even resolved perfectly this layer moves the recommendation by 0.001, short of the 0.313 needed. Governance layers are deliberately given little authority; evidence is what decides." }, { "name": "cross-view arbitration", "kind": "sensitivity", "ceiling": 0.301723, "gain": 0.00085, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Even resolved perfectly this layer moves the recommendation by 0.001, short of the 0.313 needed. Governance layers are deliberately given little authority; evidence is what decides." }, { "name": "regional absorption", "kind": "sensitivity", "ceiling": 0.299896, "gain": 0.0, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Even resolved perfectly this layer moves the recommendation by 0.000, short of the 0.313 needed. Governance layers are deliberately given little authority; evidence is what decides." }, { "name": "lens disagreement", "kind": "sensitivity", "ceiling": 0.299896, "gain": 0.0, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Even resolved perfectly this layer moves the recommendation by 0.000, short of the 0.313 needed. Governance layers are deliberately given little authority; evidence is what decides." }, { "name": "forecast record", "kind": "unpurchasable", "ceiling": 0.300873, "gain": 0.0, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Publish corrections on the studies that missed and let new forecasts close. A register improves by being kept honestly over years; no engagement budget shortens that." }, { "name": "method proof", "kind": "unpurchasable", "ceiling": 0.300873, "gain": 0.0, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Run the method against outcomes until it has earned unqualified use, or state the caveat in the report. Proof is accumulated, not bought." }, { "name": "practice capacity", "kind": "unpurchasable", "ceiling": 0.300873, "gain": 0.0, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "Close or resource the other engagements before accepting more work. This is a decision about the firm's book, not about this project." }, { "name": "claim strength", "kind": "unpurchasable", "ceiling": 0.300873, "gain": 0.0, "flips_to": "", "cost": null, "purchasable": false, "actionable": false, "method": "", "gain_per_thousand": 0.0, "note": "How strongly this practice may speak is set by the other layers, so it lifts on its own once the evidence and the case structure improve. It is a consequence, not a target." } ], "headline": "No purchase changes this while the recommendation is withheld. Arbitration says quarantine narrative. Those are categorical: clear them first, and only then is it worth asking what evidence would cost." }, "horizon_curves": { "curves": [ { "bucket": "near", "label": "0-3 years", "count": 0, "mean_accuracy": 0.0, "optimism_bias": 0.5, "worst_accuracy": 0.0, "evidenced": false }, { "bucket": "mid", "label": "4-7 years", "count": 0, "mean_accuracy": 0.0, "optimism_bias": 0.5, "worst_accuracy": 0.0, "evidenced": false }, { "bucket": "long", "label": "8+ years", "count": 0, "mean_accuracy": 0.0, "optimism_bias": 0.5, "worst_accuracy": 0.0, "evidenced": false } ], "horizon_decay": 0.0, "supported_horizon_years": 0, "note": "No horizon bucket has enough closed forecasts to describe accuracy by horizon. Any projection length is unvalidated." }, "thesis_value": { "modeled_value": 6372280.457187138, "expected_value": 2039129.746299884, "favorable_value": 6372280.457187138, "adverse_value": 318614.0228593569, "thesis_discount": 0.68, "beliefs": { "genuine_expansion": 0.2, "displacement": 0.2, "substitution": 0.2, "leakage_dominant": 0.2, "non_materialization": 0.2 }, "realization": { "genuine_expansion": 1.0, "displacement": 0.15, "substitution": 0.1, "leakage_dominant": 0.3, "non_materialization": 0.05 }, "headline": "Taken at face value the project delivers $6,372,280. Weighted across the competing explanations the evidence actually supports, the expected figure is $2,039,130 \u2014 a 68% discount that comes from the evidence not having settled which explanation applies, not from anything about the project's execution." }, "robustness": { "metric": "output-weighted average multiplier", "base_label": "Type II (closed on households at the accounts-implied rate)", "base_metric": 1.791158595256476, "spread": { "low": 1.3207724576521573, "high": 1.8091006335120667, "range": 0.4883281758599094, "relative": 0.27263257265612806 }, "spread_by_family": { "closure": { "low": 1.3207724576521573, "high": 1.791158595256476, "range": 0.4703861376043186, "relative": 0.2626155712006976 }, "coefficients": { "low": 1.7718817415746257, "high": 1.8091006335120667, "range": 0.03721889193744099, "relative": 0.020779227498898063 } }, "conservative": 1.3207724576521573, "variants": [ { "label": "Type I (open model \u2014 direct and indirect only)", "family": "closure", "description": "Open model. No induced effects claimed at all \u2014 the conservative floor and the hardest number to argue with.", "metric": 1.3207724576521573, "delta": -0.262616, "valid": true, "note": "" }, { "label": "Coefficients low (5th percentile, 15% CV)", "family": "coefficients", "description": "The coefficient matrix is itself an estimate; this is the low end of its plausible range.", "metric": 1.7718817415746257, "delta": -0.010762, "valid": true, "note": "" }, { "label": "Coefficients high (95th percentile, 15% CV)", "family": "coefficients", "description": "The high end of the coefficient matrix's plausible range.", "metric": 1.8091006335120667, "delta": 0.010017, "valid": true, "note": "" } ], "headline": "Across defensible methodological choices the output-weighted average multiplier ranges 1.321 to 1.809 \u2014 a 27% spread that owes to the analyst's choice of method rather than to anything about the project. Of that spread, the closure alone accounts for 26 of the 27 percentage points." } }, "robustness": { "metric": "output-weighted average multiplier", "base_label": "Type II (closed on households at the accounts-implied rate)", "base_metric": 1.791158595256476, "spread": { "low": 1.3207724576521573, "high": 1.8091006335120667, "range": 0.4883281758599094, "relative": 0.27263257265612806 }, "spread_by_family": { "closure": { "low": 1.3207724576521573, "high": 1.791158595256476, "range": 0.4703861376043186, "relative": 0.2626155712006976 }, "coefficients": { "low": 1.7718817415746257, "high": 1.8091006335120667, "range": 0.03721889193744099, "relative": 0.020779227498898063 } }, "conservative": 1.3207724576521573, "variants": [ { "label": "Type I (open model \u2014 direct and indirect only)", "family": "closure", "description": "Open model. No induced effects claimed at all \u2014 the conservative floor and the hardest number to argue with.", "metric": 1.3207724576521573, "delta": -0.262616, "valid": true, "note": "" }, { "label": "Coefficients low (5th percentile, 15% CV)", "family": "coefficients", "description": "The coefficient matrix is itself an estimate; this is the low end of its plausible range.", "metric": 1.7718817415746257, "delta": -0.010762, "valid": true, "note": "" }, { "label": "Coefficients high (95th percentile, 15% CV)", "family": "coefficients", "description": "The high end of the coefficient matrix's plausible range.", "metric": 1.8091006335120667, "delta": 0.010017, "valid": true, "note": "" } ], "headline": "Across defensible methodological choices the output-weighted average multiplier ranges 1.321 to 1.809 \u2014 a 27% spread that owes to the analyst's choice of method rather than to anything about the project. Of that spread, the closure alone accounts for 26 of the 27 percentage points." }, "structural": { "linkages": [ { "code": "AGR", "name": "Agriculture, forestry, and fishing", "backward": 0.9269, "forward": 0.8286, "backward_raw": 1.657, "forward_raw": 1.4813, "backward_dispersion": 1.9512, "forward_dispersion": 2.2127, "output_share": 0.077781, "employment_share": 0.07837, "classification": "weakly linked" }, { "code": "MIN", "name": "Mining and resource extraction", "backward": 0.9281, "forward": 0.8016, "backward_raw": 1.6592, "forward_raw": 1.433, "backward_dispersion": 1.9293, "forward_dispersion": 2.2772, "output_share": 0.07669, "employment_share": 0.077271, "classification": "weakly linked" }, { "code": "UTL", "name": "Utilities", "backward": 1.0569, "forward": 0.9266, "backward_raw": 1.8893, "forward_raw": 1.6564, "backward_dispersion": 1.722, "forward_dispersion": 1.9969, "output_share": 0.061189, "employment_share": 0.045428, "classification": "pulls strongly (buys local)" }, { "code": "CON", "name": "Construction", "backward": 1.0558, "forward": 0.8786, "backward_raw": 1.8874, "forward_raw": 1.5707, "backward_dispersion": 1.718, "forward_dispersion": 2.1147, "output_share": 0.090312, "employment_share": 0.067051, "classification": "pulls strongly (buys local)" }, { "code": "MFG", "name": "Manufacturing", "backward": 1.0397, "forward": 1.0274, "backward_raw": 1.8586, "forward_raw": 1.8367, "backward_dispersion": 1.7789, "forward_dispersion": 1.7962, "output_share": 0.108359, "employment_share": 0.051717, "classification": "key sector" }, { "code": "WHL", "name": "Wholesale trade", "backward": 0.9627, "forward": 0.9139, "backward_raw": 1.721, "forward_raw": 1.6337, "backward_dispersion": 1.8964, "forward_dispersion": 2.0059, "output_share": 0.06812, "employment_share": 0.079474, "classification": "weakly linked" }, { "code": "RET", "name": "Retail trade", "backward": 0.9622, "forward": 1.3993, "backward_raw": 1.7202, "forward_raw": 2.5014, "backward_dispersion": 2.0319, "forward_dispersion": 1.3022, "output_share": 0.097863, "employment_share": 0.114175, "classification": "supplies strongly (others depend on it)" }, { "code": "TRN", "name": "Transportation and warehousing", "backward": 0.9627, "forward": 0.9665, "backward_raw": 1.7209, "forward_raw": 1.7277, "backward_dispersion": 1.9075, "forward_dispersion": 1.8905, "output_share": 0.069262, "employment_share": 0.080806, "classification": "weakly linked" }, { "code": "FIN", "name": "Finance, insurance, and real estate", "backward": 1.0223, "forward": 1.2412, "backward_raw": 1.8275, "forward_raw": 2.2189, "backward_dispersion": 1.8977, "forward_dispersion": 1.5038, "output_share": 0.093173, "employment_share": 0.088938, "classification": "key sector" }, { "code": "PRO", "name": "Professional and business services", "backward": 1.0211, "forward": 0.907, "backward_raw": 1.8254, "forward_raw": 1.6214, "backward_dispersion": 1.7896, "forward_dispersion": 2.0393, "output_share": 0.065089, "employment_share": 0.062131, "classification": "pulls strongly (buys local)" }, { "code": "HLT", "name": "Health, education, and social services", "backward": 1.0216, "forward": 1.2119, "backward_raw": 1.8263, "forward_raw": 2.1665, "backward_dispersion": 1.8907, "forward_dispersion": 1.5392, "output_share": 0.108238, "employment_share": 0.103318, "classification": "key sector" }, { "code": "ACC", "name": "Accommodation, food service, and recreation", "backward": 1.0401, "forward": 0.8976, "backward_raw": 1.8594, "forward_raw": 1.6046, "backward_dispersion": 1.7549, "forward_dispersion": 2.0727, "output_share": 0.083925, "employment_share": 0.151321, "classification": "pulls strongly (buys local)" } ], "key_sectors": [ { "code": "HLT", "name": "Health, education, and social services", "backward": 1.0216, "forward": 1.2119, "backward_raw": 1.8263, "forward_raw": 2.1665, "backward_dispersion": 1.8907, "forward_dispersion": 1.5392, "output_share": 0.108238, "employment_share": 0.103318, "classification": "key sector" }, { "code": "MFG", "name": "Manufacturing", "backward": 1.0397, "forward": 1.0274, "backward_raw": 1.8586, "forward_raw": 1.8367, "backward_dispersion": 1.7789, "forward_dispersion": 1.7962, "output_share": 0.108359, "employment_share": 0.051717, "classification": "key sector" }, { "code": "FIN", "name": "Finance, insurance, and real estate", "backward": 1.0223, "forward": 1.2412, "backward_raw": 1.8275, "forward_raw": 2.2189, "backward_dispersion": 1.8977, "forward_dispersion": 1.5038, "output_share": 0.093173, "employment_share": 0.088938, "classification": "key sector" } ], "important_coefficients": [ { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "MFG", "buyer_name": "Manufacturing", "coefficient": 0.04217729278337893, "influence": 0.19609123242063542, "influence_share": 0.020887113547328716 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "CON", "buyer_name": "Construction", "coefficient": 0.033524743786806435, "influence": 0.1582746874017985, "influence_share": 0.01685899632849383 }, { "supplier": "MFG", "supplier_name": "Manufacturing", "buyer": "UTL", "buyer_name": "Utilities", "coefficient": 0.042567752220008144, "influence": 0.14771367496258447, "influence_share": 0.015734065533426825 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "AGR", "buyer_name": "Agriculture, forestry, and fishing", "coefficient": 0.03342796540297741, "influence": 0.1385533273218187, "influence_share": 0.014758329806011687 }, { "supplier": "TRN", "supplier_name": "Transportation and warehousing", "buyer": "UTL", "buyer_name": "Utilities", "coefficient": 0.04061389991830646, "influence": 0.13257309638913234, "influence_share": 0.014121331603754875 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "TRN", "buyer_name": "Transportation and warehousing", "coefficient": 0.029727657389076973, "influence": 0.1279713871251832, "influence_share": 0.01363116984220441 }, { "supplier": "RET", "supplier_name": "Retail trade", "buyer": "HLT", "buyer_name": "Health, education, and social services", "coefficient": 0.027152292915431253, "influence": 0.12404332868012957, "influence_share": 0.01321276356391461 }, { "supplier": "HLT", "supplier_name": "Health, education, and social services", "buyer": "MFG", "buyer_name": "Manufacturing", "coefficient": 0.03065100597775338, "influence": 0.12342195380042437, "influence_share": 0.013146576373862075 }, { "supplier": "WHL", "supplier_name": "Wholesale trade", "buyer": "MFG", "buyer_name": "Manufacturing", "coefficient": 0.04035029381584969, "influence": 0.1225219313795869, "influence_share": 0.013050708393090511 }, { "supplier": "TRN", "supplier_name": "Transportation and warehousing", "buyer": "ACC", "buyer_name": "Accommodation, food service, and recreation", "coefficient": 0.03731930201799434, "influence": 0.11988807839320273, "influence_share": 0.012770157418350511 } ], "extraction": [ { "sector": "MFG", "name": "Manufacturing", "output_loss": 505038690.08637, "output_loss_share": 0.154875, "employment_loss": 3259.7555450227787, "employment_loss_share": 0.144056, "labor_income_loss": 148855543.04342872, "direct_output": 260061066.52809066, "ripple_multiple": 1.942 }, { "sector": "HLT", "name": "Health, education, and social services", "output_loss": 492664057.63695574, "output_loss_share": 0.15108, "employment_loss": 4423.875386741771, "employment_loss_share": 0.195501, "labor_income_loss": 208955028.8509856, "direct_output": 259770114.83498073, "ripple_multiple": 1.8965 }, { "sector": "CON", "name": "Construction", "output_loss": 429515706.94787836, "output_loss_share": 0.131715, "employment_loss": 3477.198510540792, "employment_loss_share": 0.153665, "labor_income_loss": 148231957.9260283, "direct_output": 216749963.21089178, "ripple_multiple": 1.9816 }, { "sector": "FIN", "name": "Finance, insurance, and real estate", "output_loss": 428753320.7270746, "output_loss_share": 0.131481, "employment_loss": 3816.0999767706635, "employment_loss_share": 0.168642, "labor_income_loss": 184005684.86475188, "direct_output": 223614957.36514005, "ripple_multiple": 1.9174 }, { "sector": "RET", "name": "Retail trade", "output_loss": 415053300.7489495, "output_loss_share": 0.12728, "employment_loss": 4488.260995420256, "employment_loss_share": 0.198346, "labor_income_loss": 133050926.78847192, "direct_output": 234872012.43189207, "ripple_multiple": 1.7671 } ], "decomposition": [ { "sector": "MFG", "initial": 1.0, "first_round": 0.33, "industrial_support": 0.1036, "consumption_induced": 0.425, "total": 1.8586, "induced_share": 0.2287 }, { "sector": "HLT", "initial": 1.0, "first_round": 0.2, "industrial_support": 0.066, "consumption_induced": 0.5603, "total": 1.8263, "induced_share": 0.3068 }, { "sector": "RET", "initial": 1.0, "first_round": 0.21, "industrial_support": 0.0674, "consumption_induced": 0.4428, "total": 1.7202, "induced_share": 0.2574 }, { "sector": "FIN", "initial": 1.0, "first_round": 0.2, "industrial_support": 0.0662, "consumption_induced": 0.5613, "total": 1.8275, "induced_share": 0.3071 }, { "sector": "CON", "initial": 1.0, "first_round": 0.3, "industrial_support": 0.0942, "consumption_induced": 0.4931, "total": 1.8874, "induced_share": 0.2613 } ], "provenance": { "quantity": "linkage indices", "method": "Hirschman-Rasmussen backward and forward linkage analysis", "formula": "BL_j = (sum_i L_ij) / (mean of L); FL_i = (sum_j L_ij) / (mean of L)", "source": "", "vintage": "", "citation": "Miller & Blair, Input-Output Analysis, 3rd ed., ch. 12; Rasmussen (1956); Hirschman (1958)", "tier": "illustrative", "tier_label": "ILLUSTRATIVE \u2014 not a finding", "layer": "base", "assumptions": [ "Linkages are computed on the same Leontief inverse as the impact tables, under the study's stated closure.", "An index above 1.0 means the sector is above the regional average in that direction; it is not a statement about absolute size." ], "inputs": {}, "notes": [] } }, "incidence": { "jobs_by_tier": { "below 0.75x median": 38.02, "0.75x - 1.25x median": 15.01, "above 1.25x median": 11.0 }, "income_by_bracket": { "under_25k": 694439.6, "25k_50k": 726023.14, "50k_75k": 469829.03, "75k_100k": 272968.86, "over_100k": 166078.66 }, "jobs_by_sector": { "ACC": 25.03, "RET": 12.99, "TRN": 5.46, "HLT": 4.88, "PRO": 3.74, "FIN": 3.29, "WHL": 2.07, "AGR": 1.47, "CON": 1.38, "UTL": 1.31, "MIN": 1.27, "MFG": 1.12 }, "average_wage_of_new_jobs": 41198.86, "regional_median_wage": 46000.0, "wage_ratio": 0.8956, "share_to_bottom_two_brackets": 0.6098, "baseline_share_bottom_two": 0.49, "improves_distribution": true, "total_jobs": 64.03, "total_labor_income": 2329339.29, "headline": "The modeled job mix for 64 jobs averages 10% below the regional median wage ($41,199 job-weighted average wage against a $46,000 median). 61% of new labor income reaches the two lowest household brackets, against 49% of households in the region \u2014 more broadly distributed than the status quo.", "tier": "illustrative" }, "occupations": { "occupations": [ { "occupation": "Food service workers", "jobs": 9.511469156377037, "share": 0.1485376017138391, "average_wage": 24500.0 }, { "occupation": "Retail salespersons", "jobs": 5.716682172041857, "share": 0.0892756151163087, "average_wage": 31000.0 }, { "occupation": "Housekeeping and cleaning", "jobs": 4.255130938379201, "share": 0.06645103234566485, "average_wage": 26000.0 }, { "occupation": "Supervisors and managers", "jobs": 4.22766698785196, "share": 0.0660221365275915, "average_wage": 48582.73069693182 }, { "occupation": "Recreation and fitness workers", "jobs": 3.754527298569883, "share": 0.05863326383441016, "average_wage": 29000.0 }, { "occupation": "Front-desk and clerks", "jobs": 3.5042254786652247, "share": 0.054724379578782824, "average_wage": 30500.0 }, { "occupation": "Cashiers", "jobs": 2.8583410860209284, "share": 0.04463780755815435, "average_wage": 26500.0 }, { "occupation": "Stock and material movers", "jobs": 2.07879351710613, "share": 0.032463860042294075, "average_wage": 33000.0 }, { "occupation": "Maintenance", "jobs": 1.5018109194279532, "share": 0.023453305533764065, "average_wage": 38000.0 }, { "occupation": "Nursing assistants and aides", "jobs": 1.3670489388261635, "share": 0.02134877035926097, "average_wage": 33000.0 }, { "occupation": "Registered nurses", "jobs": 0.9764635277329738, "share": 0.015249121685186405, "average_wage": 78000.0 }, { "occupation": "Office and administrative", "jobs": 0.8899166695653147, "share": 0.013897546808925272, "average_wage": 39620.1091878885 } ], "occupations_shown": 12, "occupations_total": 21, "shown_share": 0.6346944411041823, "coverage": 0.6915781504163169, "tier": "illustrative", "source": "Project Red Team illustrative staffing patterns \u2014 replace with BLS OES industry-occupation matrix for the study region" } }