Monitor an experimental US market-condition index and explore a simulated estimate of sensitivity to a borrowing-rate shock. The market index uses a 0–1 scale and offers conditional future scenarios. The shock-response chart combines observed inflation-adjusted GDP with explicitly assumed model paths. Quarterly GDP and daily market inputs retain their own cadence. Each has its own units and limits. Neither is a recession probability.
US market fragility index — experimental · sealed record
What it cannot see: the reading
says nothing about exogenous shocks — a war, a pandemic, a policy accident —
that arrive from outside its four market drivers. Its retrospective record on credit-cycle
drawdowns is mixed: elevated ahead of the dot-com peak, only watch before the
2008 crisis, and no elevated lead before the 2020 drawdown. Read it as a monitor, not a
proven leading indicator.
Historical index and conditional future paths
Solid line: historical index. Dashed paths: conditional on authored future inputs, with no assigned probabilities. They are separate from the sealed prediction.
Retained scenario snapshot: 2026-09-20; market inputs through 2026-09-18. The static diagram belongs to this dated snapshot. JavaScript checks its identity against the reading above before enabling comparison.
At 2027Q3: Optimistic · easing market stress 0.132; Reference · unchanged drivers 0.240; Pessimistic · higher market stress 0.894. These are conditional calculations with no assigned probabilities.
History alone uses a 0–0.66 frame (extending if needed). With future scenarios visible, the frame is 0–1 so stress paths are not clipped.
The line steps at quarter ends by construction — daily movement enters
only through quarter-to-date driver means. Historical points are replays computed from
today’s source vintages, not an archive of values published on those dates.
Conditional index values; no assigned probabilities. Current quarter assumed to settle unchanged.
Quarter
Optimistic · easing market stress
Reference · unchanged drivers
Pessimistic · higher market stress
2026Q4
0.205703
0.263113
0.611791
2027Q1
0.163763
0.249879
0.772895
2027Q2
0.142794
0.243262
0.853448
2027Q3
0.132309
0.239954
0.893724
Scenario assumptions and how to read the paths
Optimistic means lower index stress, pessimistic means higher stress, and reference holds the current drivers unchanged. None is a most-probable forecast; no probabilities or confidence intervals have been established.
Authored inputs held in each future quarter; no probability ranking
Scenario
10y–2y yield spread (pp)
Baa–10y credit spread (pp)
VIX
CAPE
Optimistic · easing market stress
1
1.5
14
30
Pessimistic · higher market stress
-0.5
4
35
40
Reference
Hold all four origin driver inputs unchanged. The index may still move as smoothing and retained history evolve.
The provisional quarter is assumed to close unchanged. The model then processes the stated inputs once per future quarter. Its retained inversion memory and smoothing can change the reference index even when drivers stay constant. The 0–1 scale accommodates all scenarios; its values are not recession probabilities. “Optimistic” does not imply an investment return.
Compare observed US real GDP with the model’s no-shock and higher-borrowing-rate paths on one calendar. GDP is already adjusted for inflation. These conditional paths illustrate how a shock changes output; they are not a calibrated US GDP forecast or a recession probability.
Latest observation: 2026Q2, $24.271 trillion in chained 2017 dollars, annualized. Showing ten years of observed history plus the selected 3-year model experiment. Observations after the assumed start remain visible for comparison.
US real GDP: observed history and conditional model paths
trillion chained 2017 USD, annual rate — CONDITIONAL ON AN ASSUMED STATE — not a measurement, not a forecast, and no probability attaches
Y axis: US real GDP · trillions of inflation-adjusted 2017 dollars (annual rate)
X axis: calendar dates; each series retains its own observation or simulation cadence.
2025Q4 GDP level used as the assumed model starting scale
Shaded historical context; it does not assign a cause to every movement.
Quarterly observed GDP and GDP-scaled model nodes. Scenario rates are conditional model output under an assumed state — not a GDP forecast of any kind, official or otherwise, and no probability attaches; missing cells are not zero. Units: trillion chained 2017 USD, annual rate.
Date / observation period
Observed US real GDP · quarterly
D_A/R_LOW · no-shock model
D_A/R_LOW · +2pp rate scenario
D_A/R_HIGH · no-shock model
D_A/R_HIGH · +2pp rate scenario
D_B/R_LOW · no-shock model
D_B/R_LOW · +2pp rate scenario
D_B/R_HIGH · no-shock model
D_B/R_HIGH · +2pp rate scenario
2016Q2 · observed quarter
19.0627
—
—
—
—
—
—
—
—
2016Q3 · observed quarter
19.1979
—
—
—
—
—
—
—
—
2016Q4 · observed quarter
19.3044
—
—
—
—
—
—
—
—
2017Q1 · observed quarter
19.3983
—
—
—
—
—
—
—
—
2017Q2 · observed quarter
19.5069
—
—
—
—
—
—
—
—
2017Q3 · observed quarter
19.6608
—
—
—
—
—
—
—
—
2017Q4 · observed quarter
19.8824
—
—
—
—
—
—
—
—
2018Q1 · observed quarter
20.0441
—
—
—
—
—
—
—
—
2018Q2 · observed quarter
20.1505
—
—
—
—
—
—
—
—
2018Q3 · observed quarter
20.2762
—
—
—
—
—
—
—
—
2018Q4 · observed quarter
20.3049
—
—
—
—
—
—
—
—
2019Q1 · observed quarter
20.4316
—
—
—
—
—
—
—
—
2019Q2 · observed quarter
20.6023
—
—
—
—
—
—
—
—
2019Q3 · observed quarter
20.8433
—
—
—
—
—
—
—
—
2019Q4 · observed quarter
20.9854
—
—
—
—
—
—
—
—
2020Q1 · observed quarter
20.7092
—
—
—
—
—
—
—
—
2020Q2 · observed quarter
19.078
—
—
—
—
—
—
—
—
2020Q3 · observed quarter
20.5589
—
—
—
—
—
—
—
—
2020Q4 · observed quarter
20.7919
—
—
—
—
—
—
—
—
2021Q1 · observed quarter
21.0821
—
—
—
—
—
—
—
—
2021Q2 · observed quarter
21.4409
—
—
—
—
—
—
—
—
2021Q3 · observed quarter
21.6178
—
—
—
—
—
—
—
—
2021Q4 · observed quarter
21.9887
—
—
—
—
—
—
—
—
2022Q1 · observed quarter
21.9327
—
—
—
—
—
—
—
—
2022Q2 · observed quarter
21.967
—
—
—
—
—
—
—
—
2022Q3 · observed quarter
22.1256
—
—
—
—
—
—
—
—
2022Q4 · observed quarter
22.2783
—
—
—
—
—
—
—
—
2023Q1 · observed quarter
22.4396
—
—
—
—
—
—
—
—
2023Q2 · observed quarter
22.5805
—
—
—
—
—
—
—
—
2023Q3 · observed quarter
22.841
—
—
—
—
—
—
—
—
2023Q4 · observed quarter
23.0338
—
—
—
—
—
—
—
—
2024Q1 · observed quarter
23.0821
—
—
—
—
—
—
—
—
2024Q2 · observed quarter
23.2865
—
—
—
—
—
—
—
—
2024Q3 · observed quarter
23.4786
—
—
—
—
—
—
—
—
2024Q4 · observed quarter
23.5865
—
—
—
—
—
—
—
—
2025Q1 · observed quarter
23.5482
—
—
—
—
—
—
—
—
2025Q2 · observed quarter
23.771
—
—
—
—
—
—
—
—
2025Q3 · observed quarter
24.0268
—
—
—
—
—
—
—
—
2025Q4 · observed quarter
24.0557
—
—
—
—
—
—
—
—
2026-01-01 · model year 0.000000
—
24.0557
24.0557
24.0557
24.0557
24.0557
24.0557
24.0557
24.0557
2026-01-06 · model year 0.015625
—
24.0797
24.0788
24.0783
24.0775
24.0795
24.0781
24.0774
24.076
2026-01-12 · model year 0.031250
—
24.1031
24.1012
24.1004
24.0986
24.1027
24.0999
24.0985
24.0958
2026-01-18 · model year 0.046875
—
24.1259
24.1232
24.1219
24.1193
24.1254
24.1211
24.1191
24.115
2026-01-23 · model year 0.062500
—
24.1482
24.1446
24.1429
24.1394
24.1475
24.1419
24.1392
24.1338
2026-01-29 · model year 0.078125
—
24.1699
24.1655
24.1634
24.1591
24.1691
24.1621
24.1587
24.152
2026-02-04 · model year 0.093750
—
24.191
24.1858
24.1833
24.1781
24.1901
24.1817
24.1778
24.1697
2026-02-09 · model year 0.109375
—
24.2116
24.2055
24.2026
24.1967
24.2105
24.2008
24.1963
24.187
2026-02-15 · model year 0.125000
—
24.2317
24.2247
24.2215
24.2147
24.2304
24.2194
24.2142
24.2037
2026-02-21 · model year 0.140625
—
24.2511
24.2434
24.2397
24.2322
24.2497
24.2375
24.2317
24.2199
2026-02-27 · model year 0.156250
—
24.27
24.2615
24.2575
24.2492
24.2684
24.255
24.2486
24.2356
2026-03-04 · model year 0.171875
—
24.2883
24.279
24.2746
24.2656
24.2866
24.2719
24.265
24.2508
2026-03-10 · model year 0.187500
—
24.306
24.296
24.2913
24.2816
24.3042
24.2884
24.2809
24.2656
2026-03-16 · model year 0.203125
—
24.3232
24.3125
24.3074
24.297
24.3213
24.3043
24.2962
24.2798
2026-03-21 · model year 0.218750
—
24.3398
24.3284
24.323
24.3119
24.3377
24.3196
24.3111
24.2936
2026-03-27 · model year 0.234375
—
24.3558
24.3438
24.338
24.3262
24.3537
24.3345
24.3254
24.3069
2026Q1 · observed quarter
24.1804
—
—
—
—
—
—
—
—
2026-04-02 · model year 0.250000
—
24.3713
24.3586
24.3526
24.3401
24.369
24.3488
24.3392
24.3197
2026-04-07 · model year 0.265625
—
24.3862
24.3729
24.3666
24.3535
24.3838
24.3626
24.3526
24.3321
2026-04-13 · model year 0.281250
—
24.4006
24.3867
24.3801
24.3664
24.3981
24.376
24.3655
24.344
2026-04-19 · model year 0.296875
—
24.4145
24.4
24.393
24.3788
24.4119
24.3888
24.3778
24.3555
2026-04-25 · model year 0.312500
—
24.4278
24.4127
24.4055
24.3908
24.4251
24.4011
24.3898
24.3665
2026-04-30 · model year 0.328125
—
24.4406
24.425
24.4176
24.4022
24.4378
24.413
24.4012
24.3771
2026-05-06 · model year 0.343750
—
24.4528
24.4368
24.4291
24.4133
24.4499
24.4244
24.4122
24.3873
2026-05-12 · model year 0.359375
—
24.4646
24.4481
24.4401
24.4238
24.4616
24.4353
24.4228
24.3971
2026-05-17 · model year 0.375000
—
24.4759
24.4589
24.4507
24.434
24.4728
24.4458
24.4329
24.4065
2026-05-23 · model year 0.390625
—
24.4866
24.4692
24.4609
24.4437
24.4835
24.4558
24.4426
24.4155
2026-05-29 · model year 0.406250
—
24.497
24.4791
24.4706
24.453
24.4938
24.4654
24.4519
24.4241
2026-06-03 · model year 0.421875
—
24.5068
24.4886
24.4799
24.4619
24.5035
24.4746
24.4608
24.4323
2026-06-09 · model year 0.437500
—
24.5162
24.4977
24.4888
24.4704
24.5129
24.4834
24.4693
24.4402
2026-06-15 · model year 0.453125
—
24.5252
24.5063
24.4972
24.4785
24.5218
24.4917
24.4774
24.4478
2026-06-21 · model year 0.468750
—
24.5337
24.5145
24.5053
24.4863
24.5303
24.4997
24.4851
24.455
2026-06-26 · model year 0.484375
—
24.5418
24.5224
24.513
24.4937
24.5383
24.5074
24.4925
24.4619
2026Q2 · observed quarter
24.2706
—
—
—
—
—
—
—
—
2026-07-02 · model year 0.500000
—
24.5495
24.5298
24.5204
24.5007
24.546
24.5146
24.4996
24.4684
2026-07-08 · model year 0.515625
—
24.5569
24.5369
24.5273
24.5074
24.5533
24.5215
24.5063
24.4747
2026-07-13 · model year 0.531250
—
24.5638
24.5437
24.534
24.5138
24.5602
24.5281
24.5127
24.4807
2026-07-19 · model year 0.546875
—
24.5704
24.5501
24.5403
24.5199
24.5668
24.5344
24.5188
24.4864
2026-07-25 · model year 0.562500
—
24.5767
24.5562
24.5463
24.5257
24.573
24.5403
24.5246
24.4918
2026-07-31 · model year 0.578125
—
24.5826
24.5619
24.5519
24.5312
24.5789
24.546
24.5301
24.497
2026-08-05 · model year 0.593750
—
24.5882
24.5674
24.5573
24.5364
24.5845
24.5513
24.5353
24.5019
2026-08-11 · model year 0.609375
—
24.5935
24.5726
24.5624
24.5413
24.5898
24.5564
24.5403
24.5066
2026-08-17 · model year 0.625000
—
24.5985
24.5775
24.5673
24.546
24.5948
24.5612
24.545
24.5111
2026-08-22 · model year 0.640625
—
24.6032
24.5821
24.5719
24.5505
24.5995
24.5658
24.5495
24.5153
2026-08-28 · model year 0.656250
—
24.6076
24.5865
24.5762
24.5547
24.6039
24.5702
24.5537
24.5193
2026-09-03 · model year 0.671875
—
24.6118
24.5906
24.5803
24.5587
24.6081
24.5743
24.5578
24.5232
2026-09-08 · model year 0.687500
—
24.6158
24.5945
24.5842
24.5625
24.6121
24.5781
24.5616
24.5268
2026-09-14 · model year 0.703125
—
24.6195
24.5982
24.5878
24.5661
24.6158
24.5818
24.5652
24.5303
2026-09-20 · model year 0.718750
—
24.623
24.6017
24.5913
24.5695
24.6193
24.5853
24.5687
24.5336
2026-09-26 · model year 0.734375
—
24.6263
24.605
24.5946
24.5728
24.6226
24.5886
24.5719
24.5368
2026-10-01 · model year 0.750000
—
24.6294
24.6081
24.5977
24.5758
24.6257
24.5917
24.575
24.5398
2026-10-07 · model year 0.765625
—
24.6323
24.611
24.6006
24.5787
24.6287
24.5947
24.578
24.5427
2026-10-13 · model year 0.781250
—
24.6351
24.6138
24.6034
24.5815
24.6314
24.5975
24.5808
24.5454
2026-10-18 · model year 0.796875
—
24.6377
24.6165
24.6061
24.5841
24.634
24.6002
24.5835
24.548
2026-10-24 · model year 0.812500
—
24.6401
24.6189
24.6086
24.5866
24.6365
24.6027
24.586
24.5505
2026-10-30 · model year 0.828125
—
24.6424
24.6213
24.6109
24.589
24.6388
24.6051
24.5884
24.5529
2026-11-04 · model year 0.843750
—
24.6445
24.6235
24.6132
24.5913
24.641
24.6074
24.5907
24.5552
2026-11-10 · model year 0.859375
—
24.6466
24.6256
24.6153
24.5934
24.643
24.6096
24.593
24.5574
2026-11-16 · model year 0.875000
—
24.6485
24.6276
24.6173
24.5955
24.645
24.6117
24.5951
24.5596
2026-11-22 · model year 0.890625
—
24.6504
24.6295
24.6193
24.5974
24.6469
24.6137
24.5971
24.5616
2026-11-27 · model year 0.906250
—
24.6521
24.6314
24.6211
24.5993
24.6486
24.6156
24.5991
24.5636
2026-12-03 · model year 0.921875
—
24.6537
24.6331
24.6229
24.6012
24.6503
24.6174
24.6009
24.5655
2026-12-09 · model year 0.937500
—
24.6553
24.6348
24.6246
24.6029
24.6519
24.6192
24.6028
24.5674
2026-12-14 · model year 0.953125
—
24.6568
24.6364
24.6263
24.6046
24.6535
24.6209
24.6045
24.5692
2026-12-20 · model year 0.968750
—
24.6583
24.638
24.6279
24.6063
24.6549
24.6226
24.6062
24.5709
2026-12-26 · model year 0.984375
—
24.6597
24.6395
24.6294
24.6079
24.6564
24.6242
24.6079
24.5727
2027-01-01 · model year 1.000000
—
24.661
24.6409
24.6309
24.6094
24.6577
24.6257
24.6095
24.5744
2027-01-06 · model year 1.015625
—
24.6623
24.6429
24.6324
24.6115
24.6591
24.6281
24.6111
24.5769
2027-01-12 · model year 1.031250
—
24.6636
24.6448
24.6338
24.6135
24.6604
24.6304
24.6127
24.5794
2027-01-18 · model year 1.046875
—
24.6649
24.6467
24.6352
24.6156
24.6617
24.6327
24.6142
24.5818
2027-01-23 · model year 1.062500
—
24.6661
24.6486
24.6366
24.6176
24.663
24.635
24.6158
24.5843
2027-01-29 · model year 1.078125
—
24.6674
24.6505
24.638
24.6196
24.6642
24.6373
24.6173
24.5867
2027-02-04 · model year 1.093750
—
24.6686
24.6524
24.6394
24.6216
24.6655
24.6396
24.6188
24.5892
2027-02-09 · model year 1.109375
—
24.6698
24.6542
24.6407
24.6235
24.6667
24.6419
24.6204
24.5916
2027-02-15 · model year 1.125000
—
24.671
24.6561
24.6421
24.6255
24.668
24.6441
24.6219
24.5941
2027-02-21 · model year 1.140625
—
24.6722
24.658
24.6435
24.6275
24.6693
24.6464
24.6234
24.5966
2027-02-27 · model year 1.156250
—
24.6735
24.6599
24.6449
24.6296
24.6706
24.6487
24.625
24.599
2027-03-04 · model year 1.171875
—
24.6748
24.6618
24.6463
24.6316
24.6719
24.651
24.6266
24.6015
2027-03-10 · model year 1.187500
—
24.6761
24.6637
24.6478
24.6336
24.6732
24.6534
24.6282
24.6041
2027-03-16 · model year 1.203125
—
24.6774
24.6657
24.6493
24.6357
24.6745
24.6557
24.6298
24.6066
2027-03-21 · model year 1.218750
—
24.6787
24.6677
24.6508
24.6378
24.6759
24.6581
24.6315
24.6092
2027-03-27 · model year 1.234375
—
24.6801
24.6697
24.6523
24.64
24.6774
24.6606
24.6331
24.6118
2027-04-02 · model year 1.250000
—
24.6816
24.6718
24.6539
24.6421
24.6788
24.663
24.6349
24.6144
2027-04-07 · model year 1.265625
—
24.6831
24.6739
24.6555
24.6444
24.6804
24.6655
24.6366
24.6171
2027-04-13 · model year 1.281250
—
24.6846
24.676
24.6572
24.6466
24.6819
24.6681
24.6385
24.6198
2027-04-19 · model year 1.296875
—
24.6862
24.6782
24.6589
24.6489
24.6835
24.6706
24.6403
24.6226
2027-04-25 · model year 1.312500
—
24.6878
24.6805
24.6606
24.6513
24.6852
24.6733
24.6422
24.6254
2027-04-30 · model year 1.328125
—
24.6895
24.6828
24.6624
24.6537
24.6869
24.676
24.6442
24.6282
2027-05-06 · model year 1.343750
—
24.6913
24.6851
24.6643
24.6561
24.6887
24.6787
24.6462
24.6311
2027-05-12 · model year 1.359375
—
24.6931
24.6876
24.6662
24.6586
24.6906
24.6815
24.6483
24.6341
2027-05-17 · model year 1.375000
—
24.695
24.6901
24.6682
24.6612
24.6925
24.6844
24.6504
24.6371
2027-05-23 · model year 1.390625
—
24.6969
24.6926
24.6703
24.6638
24.6945
24.6873
24.6526
24.6401
2027-05-29 · model year 1.406250
—
24.699
24.6952
24.6724
24.6665
24.6966
24.6903
24.6549
24.6433
2027-06-03 · model year 1.421875
—
24.7011
24.6979
24.6746
24.6693
24.6987
24.6934
24.6572
24.6465
2027-06-09 · model year 1.437500
—
24.7033
24.7007
24.6769
24.6721
24.7009
24.6965
24.6596
24.6497
2027-06-15 · model year 1.453125
—
24.7055
24.7035
24.6792
24.675
24.7032
24.6997
24.6621
24.653
2027-06-21 · model year 1.468750
—
24.7079
24.7065
24.6817
24.678
24.7056
24.703
24.6646
24.6564
2027-06-26 · model year 1.484375
—
24.7103
24.7095
24.6842
24.681
24.7081
24.7063
24.6673
24.6599
2027-07-02 · model year 1.500000
—
24.7128
24.7125
24.6867
24.6841
24.7106
24.7098
24.67
24.6634
2027-07-08 · model year 1.515625
—
24.7154
24.7157
24.6894
24.6873
24.7132
24.7133
24.6727
24.667
2027-07-13 · model year 1.531250
—
24.7181
24.719
24.6921
24.6906
24.716
24.7169
24.6756
24.6707
2027-07-19 · model year 1.546875
—
24.7209
24.7223
24.6949
24.6939
24.7188
24.7205
24.6785
24.6744
2027-07-25 · model year 1.562500
—
24.7238
24.7257
24.6979
24.6974
24.7217
24.7243
24.6816
24.6783
2027-07-31 · model year 1.578125
—
24.7268
24.7292
24.7009
24.7009
24.7247
24.7281
24.6847
24.6822
2027-08-05 · model year 1.593750
—
24.7299
24.7328
24.7039
24.7045
24.7278
24.7321
24.6879
24.6861
2027-08-11 · model year 1.609375
—
24.733
24.7365
24.7071
24.7082
24.731
24.7361
24.6911
24.6902
2027-08-17 · model year 1.625000
—
24.7363
24.7403
24.7104
24.7119
24.7343
24.7402
24.6945
24.6943
2027-08-22 · model year 1.640625
—
24.7397
24.7442
24.7137
24.7158
24.7377
24.7444
24.698
24.6986
2027-08-28 · model year 1.656250
—
24.7431
24.7482
24.7172
24.7198
24.7412
24.7487
24.7015
24.7029
2027-09-03 · model year 1.671875
—
24.7467
24.7522
24.7207
24.7238
24.7447
24.7531
24.7052
24.7073
2027-09-08 · model year 1.687500
—
24.7504
24.7564
24.7244
24.7279
24.7484
24.7576
24.7089
24.7118
2027-09-14 · model year 1.703125
—
24.7542
24.7607
24.7281
24.7321
24.7522
24.7621
24.7127
24.7163
2027-09-20 · model year 1.718750
—
24.758
24.7651
24.732
24.7365
24.7561
24.7668
24.7166
24.721
2027-09-26 · model year 1.734375
—
24.762
24.7695
24.7359
24.7409
24.7601
24.7716
24.7206
24.7257
2027-10-01 · model year 1.750000
—
24.7661
24.7741
24.7399
24.7454
24.7643
24.7764
24.7247
24.7305
2027-10-07 · model year 1.765625
—
24.7703
24.7788
24.7441
24.75
24.7685
24.7814
24.7289
24.7355
2027-10-13 · model year 1.781250
—
24.7746
24.7836
24.7483
24.7547
24.7728
24.7865
24.7332
24.7405
2027-10-18 · model year 1.796875
—
24.779
24.7884
24.7526
24.7594
24.7772
24.7916
24.7376
24.7456
2027-10-24 · model year 1.812500
—
24.7836
24.7934
24.7571
24.7643
24.7818
24.7969
24.7421
24.7507
2027-10-30 · model year 1.828125
—
24.7882
24.7985
24.7616
24.7693
24.7864
24.8023
24.7467
24.756
2027-11-04 · model year 1.843750
—
24.793
24.8037
24.7662
24.7744
24.7912
24.8077
24.7514
24.7614
2027-11-10 · model year 1.859375
—
24.7978
24.809
24.771
24.7796
24.7961
24.8133
24.7562
24.7668
2027-11-16 · model year 1.875000
—
24.8028
24.8144
24.7758
24.7848
24.801
24.819
24.7611
24.7724
2027-11-22 · model year 1.890625
—
24.8079
24.8199
24.7808
24.7902
24.8061
24.8247
24.7661
24.7781
2027-11-27 · model year 1.906250
—
24.8131
24.8255
24.7858
24.7957
24.8113
24.8306
24.7712
24.7838
2027-12-03 · model year 1.921875
—
24.8184
24.8313
24.791
24.8013
24.8167
24.8366
24.7764
24.7896
2027-12-09 · model year 1.937500
—
24.8238
24.8371
24.7962
24.8069
24.8221
24.8427
24.7816
24.7956
2027-12-14 · model year 1.953125
—
24.8293
24.843
24.8016
24.8127
24.8276
24.8489
24.787
24.8016
2027-12-20 · model year 1.968750
—
24.8349
24.8491
24.8071
24.8186
24.8333
24.8552
24.7925
24.8077
2027-12-26 · model year 1.984375
—
24.8407
24.8552
24.8127
24.8246
24.839
24.8616
24.7981
24.8139
2028-01-01 · model year 2.000000
—
24.8466
24.8615
24.8183
24.8306
24.8449
24.8681
24.8038
24.8202
2028-01-06 · model year 2.015625
—
24.8525
24.8679
24.8241
24.8368
24.8509
24.8747
24.8096
24.8266
2028-01-12 · model year 2.031250
—
24.8586
24.8744
24.83
24.8431
24.857
24.8814
24.8155
24.8331
2028-01-18 · model year 2.046875
—
24.8648
24.881
24.836
24.8495
24.8632
24.8882
24.8215
24.8397
2028-01-23 · model year 2.062500
—
24.8712
24.8877
24.8421
24.856
24.8695
24.8951
24.8276
24.8464
2028-01-29 · model year 2.078125
—
24.8776
24.8945
24.8483
24.8625
24.876
24.9022
24.8338
24.8532
2028-02-04 · model year 2.093750
—
24.8842
24.9014
24.8546
24.8692
24.8825
24.9093
24.8401
24.8601
2028-02-10 · model year 2.109375
—
24.8908
24.9084
24.8611
24.876
24.8892
24.9165
24.8465
24.8671
2028-02-15 · model year 2.125000
—
24.8976
24.9156
24.8676
24.8829
24.896
24.9239
24.8531
24.8741
2028-02-21 · model year 2.140625
—
24.9045
24.9228
24.8742
24.8899
24.9029
24.9313
24.8597
24.8813
2028-02-27 · model year 2.156250
—
24.9115
24.9302
24.881
24.897
24.9099
24.9389
24.8664
24.8886
2028-03-03 · model year 2.171875
—
24.9186
24.9376
24.8878
24.9042
24.917
24.9466
24.8732
24.8959
2028-03-09 · model year 2.187500
—
24.9258
24.9452
24.8948
24.9115
24.9242
24.9543
24.8801
24.9034
2028-03-15 · model year 2.203125
—
24.9332
24.9529
24.9018
24.9189
24.9315
24.9622
24.8872
24.9109
2028-03-21 · model year 2.218750
—
24.9406
24.9607
24.909
24.9264
24.939
24.9702
24.8943
24.9186
2028-03-26 · model year 2.234375
—
24.9482
24.9686
24.9163
24.934
24.9466
24.9783
24.9015
24.9263
2028-04-01 · model year 2.250000
—
24.9559
24.9766
24.9236
24.9417
24.9542
24.9865
24.9088
24.9342
2028-04-07 · model year 2.265625
—
24.9637
24.9847
24.9311
24.9495
24.962
24.9948
24.9163
24.9421
2028-04-12 · model year 2.281250
—
24.9716
24.9929
24.9387
24.9574
24.9699
25.0032
24.9238
24.9502
2028-04-18 · model year 2.296875
—
24.9796
25.0013
24.9464
24.9654
24.978
25.0117
24.9314
24.9583
2028-04-24 · model year 2.312500
—
24.9877
25.0097
24.9542
24.9735
24.9861
25.0203
24.9392
24.9665
2028-04-30 · model year 2.328125
—
24.996
25.0182
24.9621
24.9817
24.9943
25.029
24.947
24.9748
2028-05-05 · model year 2.343750
—
25.0043
25.0269
24.9701
24.99
25.0027
25.0379
24.9549
24.9832
2028-05-11 · model year 2.359375
—
25.0128
25.0357
24.9782
24.9984
25.0111
25.0468
24.963
24.9918
2028-05-17 · model year 2.375000
—
25.0214
25.0445
24.9864
25.007
25.0197
25.0558
24.9711
25.0004
2028-05-22 · model year 2.390625
—
25.0301
25.0535
24.9947
25.0156
25.0284
25.065
24.9794
25.0091
2028-05-28 · model year 2.406250
—
25.0389
25.0626
25.0031
25.0243
25.0372
25.0742
24.9877
25.0178
2028-06-03 · model year 2.421875
—
25.0478
25.0718
25.0116
25.0331
25.0461
25.0836
24.9961
25.0267
2028-06-09 · model year 2.437500
—
25.0568
25.0811
25.0203
25.042
25.0551
25.093
25.0047
25.0357
2028-06-14 · model year 2.453125
—
25.0659
25.0905
25.029
25.051
25.0642
25.1026
25.0133
25.0448
2028-06-20 · model year 2.468750
—
25.0752
25.1
25.0378
25.0601
25.0734
25.1122
25.022
25.054
2028-06-26 · model year 2.484375
—
25.0845
25.1096
25.0467
25.0693
25.0828
25.122
25.0309
25.0632
2028-07-02 · model year 2.500000
—
25.094
25.1194
25.0558
25.0786
25.0922
25.1318
25.0398
25.0726
2028-07-07 · model year 2.515625
—
25.1035
25.1292
25.0649
25.088
25.1018
25.1418
25.0488
25.082
2028-07-13 · model year 2.531250
—
25.1132
25.1391
25.0741
25.0975
25.1114
25.1519
25.058
25.0916
2028-07-19 · model year 2.546875
—
25.123
25.1491
25.0835
25.1071
25.1212
25.162
25.0672
25.1012
2028-07-24 · model year 2.562500
—
25.1329
25.1593
25.0929
25.1168
25.1311
25.1723
25.0765
25.1109
2028-07-30 · model year 2.578125
—
25.1429
25.1695
25.1025
25.1266
25.141
25.1827
25.0859
25.1208
2028-08-05 · model year 2.593750
—
25.153
25.1799
25.1121
25.1365
25.1511
25.1931
25.0954
25.1307
2028-08-11 · model year 2.609375
—
25.1632
25.1903
25.1218
25.1465
25.1613
25.2037
25.1051
25.1407
2028-08-16 · model year 2.625000
—
25.1735
25.2009
25.1317
25.1566
25.1716
25.2144
25.1148
25.1508
2028-08-22 · model year 2.640625
—
25.1839
25.2115
25.1416
25.1667
25.182
25.2252
25.1246
25.1609
2028-08-28 · model year 2.656250
—
25.1945
25.2223
25.1516
25.177
25.1925
25.236
25.1345
25.1712
2028-09-02 · model year 2.671875
—
25.2051
25.2331
25.1618
25.1874
25.2031
25.247
25.1445
25.1816
2028-09-08 · model year 2.687500
—
25.2158
25.2441
25.172
25.1978
25.2138
25.2581
25.1545
25.192
2028-09-14 · model year 2.703125
—
25.2267
25.2552
25.1823
25.2084
25.2247
25.2692
25.1647
25.2026
2028-09-20 · model year 2.718750
—
25.2376
25.2663
25.1928
25.2191
25.2356
25.2805
25.175
25.2132
2028-09-25 · model year 2.734375
—
25.2486
25.2776
25.2033
25.2298
25.2466
25.2919
25.1854
25.224
2028-10-01 · model year 2.750000
—
25.2598
25.2889
25.2139
25.2406
25.2577
25.3033
25.1958
25.2348
2028-10-07 · model year 2.765625
—
25.2711
25.3004
25.2246
25.2516
25.269
25.3149
25.2064
25.2457
2028-10-12 · model year 2.781250
—
25.2824
25.312
25.2354
25.2626
25.2803
25.3265
25.2171
25.2567
2028-10-18 · model year 2.796875
—
25.2939
25.3236
25.2463
25.2737
25.2917
25.3383
25.2278
25.2677
2028-10-24 · model year 2.812500
—
25.3054
25.3354
25.2573
25.2849
25.3033
25.3501
25.2386
25.2789
2028-10-30 · model year 2.828125
—
25.3171
25.3472
25.2684
25.2962
25.3149
25.3621
25.2496
25.2902
2028-11-04 · model year 2.843750
—
25.3288
25.3592
25.2796
25.3076
25.3266
25.3741
25.2606
25.3015
2028-11-10 · model year 2.859375
—
25.3407
25.3712
25.2909
25.3191
25.3385
25.3862
25.2717
25.3129
2028-11-16 · model year 2.875000
—
25.3527
25.3834
25.3023
25.3307
25.3504
25.3985
25.2829
25.3244
2028-11-21 · model year 2.890625
—
25.3647
25.3956
25.3137
25.3424
25.3624
25.4108
25.2942
25.336
2028-11-27 · model year 2.906250
—
25.3769
25.408
25.3253
25.3541
25.3746
25.4232
25.3056
25.3477
2028-12-03 · model year 2.921875
—
25.3891
25.4204
25.337
25.366
25.3868
25.4357
25.317
25.3595
2028-12-09 · model year 2.937500
—
25.4015
25.4329
25.3487
25.3779
25.3991
25.4483
25.3286
25.3714
2028-12-14 · model year 2.953125
—
25.4139
25.4455
25.3606
25.3899
25.4115
25.461
25.3403
25.3833
2028-12-20 · model year 2.968750
—
25.4265
25.4583
25.3725
25.4021
25.4241
25.4738
25.352
25.3953
2028-12-26 · model year 2.984375
—
25.4391
25.4711
25.3845
25.4143
25.4367
25.4867
25.3638
25.4074
2029-01-01 · model year 3.000000
—
25.4519
25.484
25.3966
25.4265
25.4494
25.4996
25.3757
25.4196
See the differences in output, employment and debt
The GDP-level paths nearly overlap because this rate pulse has a small incremental effect in this particular model. Use the percentage view below to inspect that effect without changing the scenario. State-level views also show what happens in the no-shock baseline.
Uses the shock, horizon and starting-state controls above. This close-up shows the experiment period only. Each metric keeps its own labeled axis; percentage points and percent changes have different meanings.
Assumed +2 percentage-point real borrowing-rate pulse for one year. Across 4 selected assumed states, the modeled range over 3 years is -0.1445 to +0.1974 % of the paired no-shock output. At 2029-01-01: +0.1178 to +0.1974. Negative means output is below its own no-shock path; positive means above. This is the difference at each date, not accumulated lost GDP. The range compares assumptions; it is not a confidence interval.
Modeled output difference from the paired baseline
% of the paired no-shock output — CONDITIONAL ON AN ASSUMED STATE - retained 2025Q4 inputs; not a current measurement or forecast, and no probability attaches.
Y axis: Output difference from paired baseline (%) - negative means lower output
X axis: calendar dates; each series retains its own observation or simulation cadence.
Exact paired native solver nodes; no fabricated historical observations. Negative means output is below its own no-shock path; positive means above. This is the difference at each date, not accumulated lost GDP. Units: % of the paired no-shock output.
Date / observation period
No-shock difference = 0
D_A/R_LOW - shock effect
D_A/R_HIGH - shock effect
D_B/R_LOW - shock effect
D_B/R_HIGH - shock effect
2026-01-01 - model year 0.000000
0
0
0
0
0
2026-01-06 - model year 0.015625
0
-0.0038
-0.0037
-0.006
-0.0057
2026-01-12 - model year 0.031250
0
-0.0075
-0.0073
-0.0119
-0.0114
2026-01-18 - model year 0.046875
0
-0.0111
-0.0108
-0.0177
-0.017
2026-01-23 - model year 0.062500
0
-0.0147
-0.0144
-0.0234
-0.0225
2026-01-29 - model year 0.078125
0
-0.0183
-0.0178
-0.0291
-0.0279
2026-02-04 - model year 0.093750
0
-0.0218
-0.0212
-0.0346
-0.0332
2026-02-09 - model year 0.109375
0
-0.0252
-0.0246
-0.04
-0.0384
2026-02-15 - model year 0.125000
0
-0.0285
-0.0278
-0.0454
-0.0436
2026-02-21 - model year 0.140625
0
-0.0318
-0.031
-0.0505
-0.0486
2026-02-27 - model year 0.156250
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2026-03-04 - model year 0.171875
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2026-03-10 - model year 0.187500
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2026-03-16 - model year 0.203125
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2026-03-21 - model year 0.218750
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2026-03-27 - model year 0.234375
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2026-04-02 - model year 0.250000
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2026-04-07 - model year 0.265625
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2026-04-13 - model year 0.281250
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2026-04-19 - model year 0.296875
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2026-04-25 - model year 0.312500
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2026-04-30 - model year 0.328125
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2026-05-06 - model year 0.343750
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2026-05-12 - model year 0.359375
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2026-05-17 - model year 0.375000
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2026-05-23 - model year 0.390625
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2026-05-29 - model year 0.406250
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2026-06-03 - model year 0.421875
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2026-06-09 - model year 0.437500
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2026-06-15 - model year 0.453125
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2026-06-21 - model year 0.468750
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2026-06-26 - model year 0.484375
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2026-07-02 - model year 0.500000
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2026-07-08 - model year 0.515625
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2026-07-13 - model year 0.531250
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2026-07-19 - model year 0.546875
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2026-07-25 - model year 0.562500
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2026-07-31 - model year 0.578125
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2026-08-05 - model year 0.593750
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2026-08-11 - model year 0.609375
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2026-08-17 - model year 0.625000
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2026-08-22 - model year 0.640625
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2026-08-28 - model year 0.656250
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2026-09-03 - model year 0.671875
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2026-09-08 - model year 0.687500
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2026-09-14 - model year 0.703125
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2026-09-20 - model year 0.718750
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2026-09-26 - model year 0.734375
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2026-10-01 - model year 0.750000
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2026-10-07 - model year 0.765625
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2026-10-13 - model year 0.781250
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2026-10-18 - model year 0.796875
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2026-10-24 - model year 0.812500
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2026-10-30 - model year 0.828125
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2026-11-04 - model year 0.843750
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2026-11-10 - model year 0.859375
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2026-11-16 - model year 0.875000
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2026-11-22 - model year 0.890625
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2026-11-27 - model year 0.906250
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2026-12-03 - model year 0.921875
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2026-12-09 - model year 0.937500
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2026-12-14 - model year 0.953125
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2026-12-20 - model year 0.968750
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2026-12-26 - model year 0.984375
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2027-01-01 - model year 1.000000
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2027-01-06 - model year 1.015625
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2027-01-12 - model year 1.031250
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2027-01-18 - model year 1.046875
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2027-01-23 - model year 1.062500
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2027-01-29 - model year 1.078125
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2027-02-04 - model year 1.093750
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2027-02-09 - model year 1.109375
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2027-02-15 - model year 1.125000
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2027-02-21 - model year 1.140625
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2027-02-27 - model year 1.156250
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2027-03-04 - model year 1.171875
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2027-03-10 - model year 1.187500
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2027-03-16 - model year 1.203125
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2027-03-21 - model year 1.218750
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2027-03-27 - model year 1.234375
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2027-04-02 - model year 1.250000
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2027-04-07 - model year 1.265625
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2027-04-13 - model year 1.281250
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2027-04-19 - model year 1.296875
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2027-04-25 - model year 1.312500
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2027-04-30 - model year 1.328125
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2027-05-06 - model year 1.343750
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2027-05-12 - model year 1.359375
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2027-05-17 - model year 1.375000
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2027-05-23 - model year 1.390625
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2027-05-29 - model year 1.406250
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2027-06-03 - model year 1.421875
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2027-06-09 - model year 1.437500
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2027-06-15 - model year 1.453125
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2027-06-21 - model year 1.468750
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2027-06-26 - model year 1.484375
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2027-07-02 - model year 1.500000
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2027-07-08 - model year 1.515625
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0.0011
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2027-07-13 - model year 1.531250
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0.0033
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0.0036
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2027-07-19 - model year 1.546875
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0.0055
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2027-07-25 - model year 1.562500
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0.0077
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0.0106
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2027-07-31 - model year 1.578125
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0.014
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2027-08-05 - model year 1.593750
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0.012
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2027-08-11 - model year 1.609375
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0.0141
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0.0207
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2027-08-17 - model year 1.625000
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0.0162
0.0063
0.024
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2027-08-22 - model year 1.640625
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0.0183
0.0083
0.0273
0.0025
2027-08-28 - model year 1.656250
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0.0204
0.0103
0.0305
0.0055
2027-09-03 - model year 1.671875
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0.0224
0.0123
0.0337
0.0086
2027-09-08 - model year 1.687500
0
0.0244
0.0143
0.0369
0.0116
2027-09-14 - model year 1.703125
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0.0264
0.0162
0.04
0.0146
2027-09-20 - model year 1.718750
0
0.0284
0.0182
0.0431
0.0176
2027-09-26 - model year 1.734375
0
0.0303
0.0201
0.0462
0.0205
2027-10-01 - model year 1.750000
0
0.0322
0.022
0.0492
0.0234
2027-10-07 - model year 1.765625
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0.0341
0.0238
0.0522
0.0263
2027-10-13 - model year 1.781250
0
0.036
0.0257
0.0552
0.0292
2027-10-18 - model year 1.796875
0
0.0379
0.0275
0.0581
0.032
2027-10-24 - model year 1.812500
0
0.0397
0.0293
0.061
0.0348
2027-10-30 - model year 1.828125
0
0.0415
0.0311
0.0639
0.0376
2027-11-04 - model year 1.843750
0
0.0433
0.0329
0.0667
0.0403
2027-11-10 - model year 1.859375
0
0.0451
0.0346
0.0695
0.043
2027-11-16 - model year 1.875000
0
0.0469
0.0364
0.0723
0.0457
2027-11-22 - model year 1.890625
0
0.0486
0.0381
0.075
0.0483
2027-11-27 - model year 1.906250
0
0.0503
0.0398
0.0777
0.051
2027-12-03 - model year 1.921875
0
0.052
0.0415
0.0804
0.0536
2027-12-09 - model year 1.937500
0
0.0537
0.0431
0.083
0.0561
2027-12-14 - model year 1.953125
0
0.0553
0.0448
0.0856
0.0587
2027-12-20 - model year 1.968750
0
0.0569
0.0464
0.0882
0.0612
2027-12-26 - model year 1.984375
0
0.0586
0.048
0.0907
0.0637
2028-01-01 - model year 2.000000
0
0.0601
0.0496
0.0932
0.0661
2028-01-06 - model year 2.015625
0
0.0617
0.0511
0.0957
0.0685
2028-01-12 - model year 2.031250
0
0.0633
0.0527
0.0981
0.0709
2028-01-18 - model year 2.046875
0
0.0648
0.0542
0.1006
0.0733
2028-01-23 - model year 2.062500
0
0.0663
0.0557
0.1029
0.0757
2028-01-29 - model year 2.078125
0
0.0678
0.0572
0.1053
0.078
2028-02-04 - model year 2.093750
0
0.0693
0.0587
0.1076
0.0803
2028-02-10 - model year 2.109375
0
0.0707
0.0601
0.1099
0.0825
2028-02-15 - model year 2.125000
0
0.0721
0.0616
0.1122
0.0848
2028-02-21 - model year 2.140625
0
0.0736
0.063
0.1144
0.087
2028-02-27 - model year 2.156250
0
0.0749
0.0644
0.1166
0.0892
2028-03-03 - model year 2.171875
0
0.0763
0.0658
0.1188
0.0913
2028-03-09 - model year 2.187500
0
0.0777
0.0672
0.1209
0.0935
2028-03-15 - model year 2.203125
0
0.079
0.0685
0.123
0.0956
2028-03-21 - model year 2.218750
0
0.0803
0.0698
0.1251
0.0977
2028-03-26 - model year 2.234375
0
0.0816
0.0712
0.1272
0.0997
2028-04-01 - model year 2.250000
0
0.0829
0.0725
0.1292
0.1017
2028-04-07 - model year 2.265625
0
0.0842
0.0738
0.1312
0.1037
2028-04-12 - model year 2.281250
0
0.0854
0.075
0.1332
0.1057
2028-04-18 - model year 2.296875
0
0.0867
0.0763
0.1351
0.1077
2028-04-24 - model year 2.312500
0
0.0879
0.0775
0.137
0.1096
2028-04-30 - model year 2.328125
0
0.0891
0.0787
0.1389
0.1115
2028-05-05 - model year 2.343750
0
0.0903
0.0799
0.1408
0.1134
2028-05-11 - model year 2.359375
0
0.0914
0.0811
0.1426
0.1153
2028-05-17 - model year 2.375000
0
0.0926
0.0823
0.1444
0.1171
2028-05-22 - model year 2.390625
0
0.0937
0.0835
0.1462
0.1189
2028-05-28 - model year 2.406250
0
0.0948
0.0846
0.1479
0.1207
2028-06-03 - model year 2.421875
0
0.0959
0.0857
0.1497
0.1225
2028-06-09 - model year 2.437500
0
0.097
0.0868
0.1514
0.1242
2028-06-14 - model year 2.453125
0
0.0981
0.0879
0.1531
0.1259
2028-06-20 - model year 2.468750
0
0.0991
0.089
0.1547
0.1276
2028-06-26 - model year 2.484375
0
0.1001
0.0901
0.1563
0.1293
2028-07-02 - model year 2.500000
0
0.1011
0.0911
0.1579
0.1309
2028-07-07 - model year 2.515625
0
0.1021
0.0922
0.1595
0.1326
2028-07-13 - model year 2.531250
0
0.1031
0.0932
0.1611
0.1342
2028-07-19 - model year 2.546875
0
0.1041
0.0942
0.1626
0.1358
2028-07-24 - model year 2.562500
0
0.1051
0.0952
0.1641
0.1373
2028-07-30 - model year 2.578125
0
0.106
0.0962
0.1656
0.1389
2028-08-05 - model year 2.593750
0
0.1069
0.0972
0.1671
0.1404
2028-08-11 - model year 2.609375
0
0.1078
0.0981
0.1685
0.1419
2028-08-16 - model year 2.625000
0
0.1087
0.099
0.1699
0.1434
2028-08-22 - model year 2.640625
0
0.1096
0.1
0.1713
0.1448
2028-08-28 - model year 2.656250
0
0.1105
0.1009
0.1727
0.1463
2028-09-02 - model year 2.671875
0
0.1113
0.1018
0.174
0.1477
2028-09-08 - model year 2.687500
0
0.1122
0.1027
0.1753
0.1491
2028-09-14 - model year 2.703125
0
0.113
0.1036
0.1766
0.1505
2028-09-20 - model year 2.718750
0
0.1138
0.1044
0.1779
0.1518
2028-09-25 - model year 2.734375
0
0.1146
0.1053
0.1792
0.1531
2028-10-01 - model year 2.750000
0
0.1154
0.1061
0.1804
0.1545
2028-10-07 - model year 2.765625
0
0.1162
0.1069
0.1816
0.1558
2028-10-12 - model year 2.781250
0
0.1169
0.1077
0.1828
0.157
2028-10-18 - model year 2.796875
0
0.1177
0.1085
0.184
0.1583
2028-10-24 - model year 2.812500
0
0.1184
0.1093
0.1852
0.1595
2028-10-30 - model year 2.828125
0
0.1191
0.1101
0.1863
0.1608
2028-11-04 - model year 2.843750
0
0.1198
0.1108
0.1874
0.162
2028-11-10 - model year 2.859375
0
0.1205
0.1116
0.1885
0.1632
2028-11-16 - model year 2.875000
0
0.1212
0.1123
0.1896
0.1643
2028-11-21 - model year 2.890625
0
0.1219
0.1131
0.1906
0.1655
2028-11-27 - model year 2.906250
0
0.1225
0.1138
0.1916
0.1666
2028-12-03 - model year 2.921875
0
0.1232
0.1145
0.1927
0.1677
2028-12-09 - model year 2.937500
0
0.1238
0.1152
0.1937
0.1688
2028-12-14 - model year 2.953125
0
0.1244
0.1158
0.1946
0.1699
2028-12-20 - model year 2.968750
0
0.125
0.1165
0.1956
0.171
2028-12-26 - model year 2.984375
0
0.1256
0.1172
0.1965
0.172
2029-01-01 - model year 3.000000
0
0.1262
0.1178
0.1974
0.173
Baseline matters: with these authored assumptions, even the no-shock employment paths fall from 95.55% to about 89.4–89.7% over three years. A small extra shock effect does not mean the modeled baseline is stable or an accurate US forecast. Historical recession shading belongs to the observed GDP record; shading here marks only the assumed one-year rate pulse.
Why does the model start from 2025Q4 when observed GDP reaches 2026Q2?
The experiment fixes its debt and employment assumptions at 2025Q4. Newer real GDP is available, but its other inputs have not been refreshed as one consistent state: the retained BIS debt series ends in 2025Q4, the older nominal-GDP pack ends in 2026Q1, and wage share uses a 2023 mapping. Relabeling this path as a 2026Q2 forecast would change the claim without updating the experiment.
A new 2026Q2 experiment needs an updated nominal-output denominator, a declared debt perimeter, employment and borrowing-rate mappings, and a new baseline/shock run. Fed-based debt totals offer a possible route, with their own coverage limits. The current chart keeps actual 2026 GDP visible and labels the older assumed model start.
How the levels are connected: each model path starts at the 2025Q4 observed annualized GDP level ($24.056 trillion), then follows its native real-output growth. This is an illustrative scale mapping, not a fit to subsequent US GDP. Solid dots show quarterly observations; dashed paths are scenarios. Quarterly GDP is an annualized flow, not a stock of wealth. Model nodes are output rates, not independently estimated official quarterly GDP.
Assumed states, not confidence bounds: D_A / D_B use different debt constructions; R_LOW / R_HIGH use alternative borrowing-rate mappings. All four have equal status. The model also uses a 2023 wage-share mapping and partial November–December 2025 employment (October is missing). The assumed rate pulse begins 1 January 2026 for one year; assigning these dates does not mean that it actually happened. Observed 2026 quarters remain visible. The full record is the retained 2000–2026 GDP series, not the entire official history.
Inspect output shortfalls, employment effects and earlier context
How does the modeled economy respond after borrowing rates rise? Each line compares one assumed starting state with its own no-shock baseline. Higher positive shortfall means more damage; a negative value means activity has moved above that baseline.
Peak modeled shortfall: 0.087–0.144 % output, across four assumed states. Each is compared with its own no-shock baseline.
Conditional on assumed states: retained 2025Q4 debt constructions and a 2023 wage-share mapping. This figure is a dated experiment, not a current US measurement or recession probability. The four lines are separate assumptions, not confidence-band edges. Starting employment uses November–December 2025 only because October is missing; it is not a complete-quarter observation.
0.1 means output is 0.1% below the same model’s no-shock output at that date. For example, baseline output of 100 and shocked output of 99.9 give 0.1%. Formula: 100 × (baseline − shocked output) / baseline. It is neither a 10% loss nor a recession probability. Zero = no difference; positive = below baseline; negative = above baseline. This shows the difference at each time, not accumulated loss.
Output shortfall versus the paired baseline
%; positive = below baseline — CONDITIONAL ON AN ASSUMED STATE — not a measurement, not a forecast, and no probability attaches
Y axis: Output below no-shock baseline (%)
X axis: Years since the assumed shock
Shaded: Assumed rate increase during model years 0–1..
Calendar placement: the assumed shock starts 1 January 2026, immediately after the 2025Q4 reference quarter, and the experiment ends 1 January 2029. These are illustrative dates assigned to the unchanged model path, not a forecast issued in 2025 or a claim that a shock happened in 2026. Within each model year, dates are interpolated between calendar anniversaries; the exact elapsed time is retained in the table. For nonzero shock choices, the shaded first year represents the chosen rate increase. The vertical scale is fixed across shock choices within each response.
Reading the four lines: D_A and D_B are different debt constructions; R_LOW and R_HIGH are lower and higher assumed borrowing-rate mappings. They have equal status, not statistical weights.
What happened before the assumed shock?
The observed history below changes with your response selection. It shows actual output or employment levels, with its own units. It is separate from the simulated difference above; a historical no-shock alternative cannot be observed.
Observed US real output before the assumed shock
Real GDP index; 2025Q4 = 100 — Observed context from retained source vintages; separate from the conditional model experiment
Y axis: Observed real GDP (2025Q4 = 100)
X axis: Observation quarters · retained source vintages, not real-time forecast records
Shaded historical context; these dates do not attribute the movement of this series to a single cause.
BEA real GDP, rebased (Real GDP index; 2025Q4 = 100)
2000Q1
57.692
2000Q2
58.742
2000Q3
58.802
2000Q4
59.153
2001Q1
58.959
2001Q2
59.328
2001Q3
59.090
2001Q4
59.252
2002Q1
59.748
2002Q2
60.114
2002Q3
60.358
2002Q4
60.433
2003Q1
60.751
2003Q2
61.289
2003Q3
62.309
2003Q4
63.032
2004Q1
63.389
2004Q2
63.880
2004Q3
64.486
2004Q4
65.144
2005Q1
65.867
2005Q2
66.191
2005Q3
66.710
2005Q4
67.081
2006Q1
67.983
2006Q2
68.159
2006Q3
68.261
2006Q4
68.848
2007Q1
69.055
2007Q2
69.477
2007Q3
69.878
2007Q4
70.317
2008Q1
70.017
2008Q2
70.433
2008Q3
70.063
2008Q4
68.530
2009Q1
67.752
2009Q2
67.631
2009Q3
67.869
2009Q4
68.602
2010Q1
68.934
2010Q2
69.601
2010Q3
70.138
2010Q4
70.506
2011Q1
70.339
2011Q2
70.815
2011Q3
70.799
2011Q4
71.594
2012Q1
72.195
2012Q2
72.517
2012Q3
72.622
2012Q4
72.705
2013Q1
73.423
2013Q2
73.619
2013Q3
74.246
2013Q4
74.893
2014Q1
74.635
2014Q2
75.599
2014Q3
76.518
2014Q4
76.905
2015Q1
77.597
2015Q2
78.078
2015Q3
78.390
2015Q4
78.535
2016Q1
78.990
2016Q2
79.244
2016Q3
79.806
2016Q4
80.248
2017Q1
80.639
2017Q2
81.091
2017Q3
81.730
2017Q4
82.651
2018Q1
83.323
2018Q2
83.766
2018Q3
84.288
2018Q4
84.408
2019Q1
84.935
2019Q2
85.644
2019Q3
86.646
2019Q4
87.237
2020Q1
86.088
2020Q2
79.307
2020Q3
85.463
2020Q4
86.432
2021Q1
87.639
2021Q2
89.130
2021Q3
89.866
2021Q4
91.407
2022Q1
91.175
2022Q2
91.317
2022Q3
91.976
2022Q4
92.611
2023Q1
93.282
2023Q2
93.867
2023Q3
94.950
2023Q4
95.752
2024Q1
95.953
2024Q2
96.802
2024Q3
97.601
2024Q4
98.050
2025Q1
97.890
2025Q2
98.816
2025Q3
99.880
2025Q4
100.000
The index is rebased for context only. Real GDP is not the model’s calibrated output history. No historical counterfactual shortfall is inferred. Recession areas provide historical context, not a claim that this model predicted those crises.
How could this become a historical fragility trend?
Estimate the response to the same standard shock from each past quarter’s starting conditions, then plot the resulting peak shortfall against that quarter’s date. That requires consistent debt, income and borrowing-rate definitions and explicit data vintages. No such calendar-quarter series is published in this chart. A daily website refresh does not create daily balance-sheet observations.
D_A and D_B are different debt constructions; R_LOW and R_HIGH are alternative assumed starting rates. No state is preferred. Rebounds remain visible in these paths; they do not cancel the separately reported accumulated-positive-shortfall measure.
The country comparison chart is exploratory. Each country line
is built from declared proxy inputs, normalised to that country’s own history, with
its own measurement period — so the lines are not comparable to the US instrument
or to each other, and none of this is a safety ranking. Countries are listed
alphabetically, which carries no meaning.
Approximate comparison indicators — quarterly
Not a ranking. The United States line is the sealed
instrument; the grey lines are approximate indicators built from different,
weaker inputs. A lower number on one line does not mean that economy is safer
than another - the two are not the same measurement.
Hover a name to pick its line out of the grey; click to
hide it.Pick one comparison line above; tap the chart to read
any quarter.Window: 2023Q3 onward - the earliest quarter every comparison leg
has data, so no line is drawn over a gap. Each line’s date is its own newest
complete quarter — shown per line, because the gaps differ.
There is deliberately no threshold line on
this chart. The 0.40 criterion belongs to the sealed US instrument, where it is
explained; the comparison lines have never been calibrated against it, so drawing it here
would only invite a reading none of these lines can support.
Historical context: grey areas mark US recession peak-to-trough months; violet areas and dashed markers identify selected international, banking and policy events. Names appear in lanes above the plots. These annotations do not enter the index or establish what caused its movement.
Read the crisis dates, definitions and sources
Selected context, not an exhaustive crisis catalogue. Monthly recession shading includes the peak month through the trough month; NBER’s recession-duration count begins in the month after the peak. Boundaries are month precision, not official day-level dates. Recessions were dated retrospectively. A US interval does not classify every country as being in recession.
Label
Dates
Type
Interpretation / source
Asian financial crisis
Jul 1997–Dec 1998
Selected stress window
Selected international crisis; not a US recession band. Source
Dot-com / 2001 downturn
Mar–Nov 2001
US recession context
US peak-to-trough months. The technology-stock decline began before this interval. Source
Global financial crisis
Dec 2007–Jun 2009
US recession context
US peak-to-trough months; the wider financial crisis has different boundaries. Source
COVID-19 downturn
Feb–Apr 2020
US recession context
US peak-to-trough months, dated retrospectively. Source
Ukraine invasion
24 Feb 2022
Dated event
Start of Russia’s full-scale invasion; a dated event, not a crisis-duration estimate. Source
SVB failure
10 Mar 2023
Dated event
A bank failure marker; not the duration of all 2023 banking stress. Source
2025 tariff shock
2–11 Apr 2025
Selected stress window
Selected trade-policy market-stress window discussed in the Fed’s April report; not a designated US recession. Source
Latest readings
Economy
Reading
Category
As of
Basis
The range on the US row is not a confidence
interval. It is the settling range of an open quarter: given the daily extremes already
observed, that is where the quarter could still end up when it closes. It says nothing about
how uncertain the model is. Comparison rows carry no range and no category label - not
because they are more certain, but because their uncertainty (proxy substitution,
publication lag, missing legs) is not quantified and the US model’s categories have
never been calibrated to them. Each row’s as-of column is its newest complete
quarter; it can sit several quarters behind the US row, so compare dates before comparing
values.
United States · beyond market prices
Financial vulnerability: evidence by dimension
Inspect debt payments, liquid buffers, modeled transmission, freight activity and federal finances. These measures answer different questions and retain their own dates and units. They are not five interchangeable risk scores.
Static view: all five dimensions. JavaScript enables selection and history controls.
Published household estimate
Debt-service / solvency
How much household income is committed to required debt payments?
11.16%
2026Q1 · quarterly · latest retained evidence
Published household statistics: quarterly estimated payment-burden history. Business payment coverage and aggregate solvency remain separate questions.
How to read it: Higher means more household income committed to required debt payments; lower means less. There is no universal safe cutoff.
Latest retained reading: 2026Q1: about $11.16 in required debt payments per $100 of household disposable income. This aggregate does not identify which households are in distress.
Household payment burden
Y axis: Required household payments / disposable income (%)
X axis: calendar dates; each series retains its own observation or simulation cadence.
Named US recession intervals provide historical context. They do not identify the cause of each change.
Household required debt payments / disposable income
Read values as a table
Retained-vintage observations, plotted at period end. Connecting points does not create daily observations. Fiscal years end September 30. Units: % of disposable personal income.
Date / observation period
Household required debt payments / disposable income
2016Q1
11.76
2016Q2
11.77
2016Q3
11.77
2016Q4
11.87
2017Q1
11.72
2017Q2
11.76
2017Q3
11.82
2017Q4
11.82
2018Q1
11.64
2018Q2
11.6
2018Q3
11.62
2018Q4
11.67
2019Q1
11.5
2019Q2
11.63
2019Q3
11.65
2019Q4
11.73
2020Q1
11.59
2020Q2
9.74
2020Q3
10.06
2020Q4
10.39
2021Q1
9.05
2021Q2
9.84
2021Q3
10.01
2021Q4
10.23
2022Q1
10.47
2022Q2
10.68
2022Q3
10.57
2022Q4
10.74
2023Q1
10.56
2023Q2
10.58
2023Q3
10.75
2023Q4
11.1
2024Q1
11.06
2024Q2
11.02
2024Q3
11.14
2024Q4
11.12
2025Q1
11.11
2025Q2
11.12
2025Q3
11.23
2025Q4
11.32
2026Q1
11.16
How to use it: Publisher estimate of the aggregate household payment burden. Required payments differ from payments actually made and from business debt service.
Definition, coverage and source dates
Household required debt payments / disposable income: Zero means no required payments in this ratio, not a safe-economy threshold. There is no calibrated risk cutoff. A larger aggregate share of household disposable income is committed to required payments. Units: % of disposable personal income; cadence: quarterly.
Households only; not corporate debt service or all private borrowers.
An aggregate ratio conceals unequal income, debt and liquid buffers.
No pre-2005 method splice or daily interpolation.
OUR RETRIEVAL RETURNED TEXT STATING that quarterly values computed with the current methodology are available FROM 2005 FORWARD. This matches the pack exactly: 85 quarterly observations, 2005-01-01 through 2026-01-01
OUR RETRIEVAL RETURNED NO STATEMENT of when the current methodology was introduced, revised or first applied - only of when values computed with it are available. A CONVERSION THAT CAN DROP CONTENT CANNOT DISTINGUISH AN ABSENCE AT THE SOURCE FROM AN ABSENCE IN THE RENDERING, so this is NOT evidence that the page is silent; it is evidence that what reached us was. No method-vintage is recorded here either way
Historical values use the retained current vintage; they are not an archive of the values known or published at each historical date.
How do corporate broad liquid assets compare with short-term liabilities?
95.33%
2026Q2 · quarterly · latest retained evidence
Published balance-sheet statistics: a quarterly sector ratio gives funding context, without claiming a measured maturity wall.
How to read it: Higher means more broad liquid assets per dollar of short-term liabilities; lower means less coverage. This is not all immediately available cash.
Latest retained reading: 2026Q2: about $95.33 in broad liquid assets per $100 of short-term corporate liabilities. Below 100% alone does not establish a funding shortfall.
Corporate liquidity coverage
Y axis: Broad liquid assets / short-term liabilities (%)
X axis: calendar dates; each series retains its own observation or simulation cadence.
Named US recession intervals provide historical context. They do not identify the cause of each change.
Retained-vintage observations, plotted at period end. Connecting points does not create daily observations. Fiscal years end September 30. Units: % of short-term liabilities.
How to use it: A ratio for the nonfinancial corporate sector. Broad liquid assets are not all immediately available cash, and aggregation can hide individual funding gaps.
Definition, coverage and source dates
Corporate broad liquid assets / short-term liabilities: 100% means equal aggregate broad liquid assets and short-term liabilities; it is not a solvency or liquidity pass/fail cutoff. More broad liquid assets relative to the sector's short-term liabilities; accessibility and payment timing remain unknown. Units: % of short-term liabilities; cadence: quarterly.
Broad liquid assets are not cash and may not be accessible at a common price under stress.
No borrower-level maturities, credit-line availability, collateral calls or near-term cash-flow gap are established.
How does a 30% assumed distress seed spread through a 25-sector network with capital assumed at 8% of network assets?
Withheld
Pending rights determination
Conditional model experiment: 25 measured sectors, a 30% initial distress seed and assumed 8% capital buffers; three statistical-discrepancy treatments.
This dimension is withheld from public evidence. the primary input to this dimension, `fed-sector-exposures`, has UNESTABLISHED redistribution rights, and this dimension is held until they are confirmed
This is not a data gap or an unmeasured factor — it is a deliberate withholding decision, distinct from this page's own "unavailable" state for an absent calibrated score. It will be published once an actual determination is made, not once this note is simply removed.
Is measured freight activity expanding or contracting?
-1.75% YoY
2026-06 · monthly · latest retained evidence
Observed activity context: monthly freight-volume growth is a supporting supply-and-demand condition, not a direct foreign-dependency estimate.
How to read it: Higher means faster freight-volume growth, not safer supply chains. Lower growth can reflect demand or supply changes.
Latest retained reading: 2026-06: freight volume was 1.75% lower than the same month a year earlier. This alone cannot distinguish weaker demand from disrupted supply.
Freight volume change
% change from the same month one year earlier — Observed freight activity: lower volume can reflect demand or supply. This does not measure missing supplies or a disruption probability.
Y axis: Freight volume change from the same month a year earlier (%)
X axis: calendar dates; each series retains its own observation or simulation cadence.
Named US recession intervals provide historical context. They do not identify the cause of each change.
US freight transportation volume: year-over-year change
Read values as a table
Retained-vintage observations, plotted at period end. Connecting points does not create daily observations. Fiscal years end September 30. Units: % change from the same month one year earlier.
Date / observation period
US freight transportation volume: year-over-year change
2016-06
1.24
2016-07
2.29
2016-08
0.24
2016-09
-0.89
2016-10
0.24
2016-11
1.99
2016-12
3.24
2017-01
1.39
2017-02
2.64
2017-03
3.74
2017-04
2.04
2017-05
3.2
2017-06
2.36
2017-07
2.4
2017-08
4.63
2017-09
5.57
2017-10
5.86
2017-11
6.99
2017-12
7.33
2018-01
6.06
2018-02
7.3
2018-03
8.33
2018-04
7.9
2018-05
8.18
2018-06
8.82
2018-07
5.77
2018-08
5.66
2018-09
7.14
2018-10
6.92
2018-11
5.69
2018-12
2.93
2019-01
4.72
2019-02
1.94
2019-03
0.81
2019-04
1.78
2019-05
0.88
2019-06
-0.22
2019-07
2.21
2019-08
3.23
2019-09
-0.72
2019-10
-1.44
2019-11
-1.8
2019-12
-1.31
2020-01
-1.38
2020-02
-0.88
2020-03
-1.83
2020-04
-10.03
2020-05
-8.66
2020-06
-5.93
2020-07
-4.4
2020-08
-6.97
2020-09
-4.31
2020-10
-3.72
2020-11
-3.22
2020-12
-1.11
2021-01
0.44
2021-02
-2.52
2021-03
0.52
2021-04
10.02
2021-05
7.65
2021-06
4.28
2021-07
0.3
2021-08
0.69
2021-09
1.3
2021-10
1.89
2021-11
2.42
2021-12
1.64
2022-01
0.88
2022-02
4.33
2022-03
3.34
2022-04
1.54
2022-05
2.15
2022-06
3.21
2022-07
3.09
2022-08
4.63
2022-09
4.14
2022-10
1.86
2022-11
-0.59
2022-12
-0.59
2023-01
0.51
2023-02
1.16
2023-03
-1.01
2023-04
-1.01
2023-05
-0.87
2023-06
-0.87
2023-07
0.51
2023-08
-0.58
2023-09
-0.58
2023-10
0.51
2023-11
2.08
2023-12
2.37
2024-01
-2.1
2024-02
-1.73
2024-03
-0.73
2024-04
-1.31
2024-05
1.32
2024-06
0.73
2024-07
-0.29
2024-08
1.17
2024-09
-0.15
2024-10
0.44
2024-11
-0.29
2024-12
-0.79
2025-01
1.92
2025-02
0.07
2025-03
0.66
2025-04
1.7
2025-05
-1.15
2025-06
-0.58
2025-07
0.87
2025-08
0.14
2025-09
0.51
2025-10
-1.16
2025-11
0.07
2025-12
-0.29
2026-01
-1.09
2026-02
1.1
2026-03
1.24
2026-04
0.51
2026-05
-1.24
2026-06
-1.75
How to use it: BTS Freight Transportation Services Index volume growth. Lower volumes can reflect weaker demand or a disruption; this series alone cannot separate them.
Definition, coverage and source dates
US freight transportation volume: year-over-year change: Zero means unchanged measured freight volume versus the same month one year earlier, not absence of supply vulnerability. Faster freight-volume growth; it does not establish safer supply chains. Units: % change from the same month one year earlier; cadence: monthly.
This is US freight activity, not foreign supplier concentration, available inventory, delivery delay or interruption probability.
Demand weakness and supply constraints can both lower freight volume; no cause is inferred from this series alone.
How do annual federal receipts, spending and the budget balance compare?
$5.24tn / $7.01tn
FY2025 · annual fiscal year · latest retained evidence
Observed fiscal context: compatible fiscal-year cash-flow histories show the federal financing position.
How to read it: With receipts unchanged, higher outlays widen the deficit; with outlays unchanged, higher receipts narrow it. Neither alone measures policy capacity.
Latest retained reading: FY2025: outlays exceeded receipts by $1.77 trillion in current dollars. This balance is not a default probability or a measure of remaining fiscal room.
Balance: $-1.77 trillion (receipts minus outlays; a negative value is a deficit).
Federal receipts / outlays
trillion current USD per fiscal year — Federal fiscal flows: a deficit is not a measure of sovereign default risk or remaining policy capacity.
Y axis: Federal fiscal-year flows (trillion US dollars, nominal)
X axis: calendar dates; each series retains its own observation or simulation cadence.
Named US recession intervals provide historical context. They do not identify the cause of each change.
Retained-vintage observations, plotted at period end. Connecting points does not create daily observations. Fiscal years end September 30. Units: trillion current USD per fiscal year.
Date / observation period
Federal receipts
Federal outlays
FY2015
3.25
3.69
FY2016
3.27
3.85
FY2017
3.32
3.98
FY2018
3.33
4.11
FY2019
3.46
4.45
FY2020
3.42
6.52
FY2021
4.05
6.82
FY2022
4.9
6.27
FY2023
4.44
6.13
FY2024
4.92
6.74
FY2025
5.24
7.01
How to use it: US federal budget cash flows, aligned to the same fiscal year; not all levels of government. Nominal values are not inflation-adjusted.
Definition, coverage and source dates
Federal receipts: Balance zero means receipts equal outlays. Positive is surplus, negative is deficit. Neither is a calibrated measure of fiscal capacity. A larger nominal annual flow; the sign of the balance distinguishes surplus from deficit. Units: trillion current USD per fiscal year; cadence: annual fiscal year.
Federal outlays: Balance zero means receipts equal outlays. Positive is surplus, negative is deficit. Neither is a calibrated measure of fiscal capacity. A larger nominal annual flow; the sign of the balance distinguishes surplus from deficit. Units: trillion current USD per fiscal year; cadence: annual fiscal year.
Federal budget balance (receipts minus outlays): Balance zero means receipts equal outlays. Positive is surplus, negative is deficit. Neither is a calibrated measure of fiscal capacity. A larger nominal annual flow; the sign of the balance distinguishes surplus from deficit. Units: trillion current USD per fiscal year; cadence: annual fiscal year.
Nominal fiscal-year federal flows; not a complete national balance sheet or all levels of government.
Debt maturity, currency, market access, inflation and institutional capacity remain outside this factor panel.
No quarterly NIPA interest is divided by fiscal-year cash receipts.
Refresh: this is a retained-data release. Automated source checking is not connected to this panel. A new page build does not mean its quarterly or annual observations changed. It may omit newer releases; source dates and vintages are available above and in the JSON.
Overall fragility: not estimated. Missing maturity schedules, institution-level counterparty exposures, supply dependencies and policy constraints remain unknown. There is no combined probability or confidence percentage.
The market index monitors four public market signals. The five-dimension evidence panel adds dated household debt-service and corporate liquidity ratios, a conditional contagion experiment, and observed freight and fiscal context. The Shock-response paths show sensitivity to an assumed rate shock. These are different measurements and experiments, not a common set of calibrated risk scores. Structural factors do not feed the market index. The explanations below describe the mechanisms and the evidence still missing.
Market conditions / yield-curve signals
What do current market prices say about near-term financial stress?Implemented · experimental
Mechanism
Four public market drivers observed daily: the 10y−2y Treasury
yield-curve spread, a corporate credit spread, equity volatility and an equity-valuation
measure. Each reflects investors’ forward-looking pricing of risk, not a direct
measurement of any borrower’s balance sheet.
Causal chain
When investors expect weaker growth or tighter credit conditions,
they demand more compensation for holding longer-dated or riskier assets; that
repricing shows up first in the yield curve, credit spreads, volatility and valuations,
often before the structural stress those conditions may eventually cause becomes
visible in slower-moving data.
Assessment status
Implemented, experimental. A daily composite reading is
published below, on this same page. Its retrospective record against past drawdowns is
mixed — see “what it cannot see” above the chart.
Supporting evidence
The current reading and its full daily and quarterly history are
below. The yield-curve leg specifically — what upward, flat, inverted and
higher-rate settings mean — is explained in the
yield-curve guide.
Useful for
A daily monitoring question: have market prices moved to reflect
more financial-system stress since yesterday?
Limit
A market-price composite is not a recession probability and does not
measure any of the five structural vulnerabilities below directly — it is a
separate, narrower signal.
Debt-service / solvency
Can households and businesses meet payments and absorb losses?Published household estimate
Mechanism
Separate required-payment burden from balance-sheet solvency. Debt
outstanding, required payments relative to income, interest coverage and liquid
buffers answer different parts of the question. Household and business evidence stays
separate — they are not one figure.
Causal chain
A shock that cuts income or raises borrowing costs increases the
payments due relative to what a borrower has on hand to pay them; if liquid buffers
cannot absorb that gap, missed payments and impaired solvency follow.
Assessment status
Published household estimate available above. A calibrated current score for the whole dimension is not estimated.
Supporting evidence
The household required-payment ratio is now charted by quarter. Corporate payment burdens, distribution and balance-sheet solvency remain separate gaps. Inspect the dated evidence.
Useful for
A monitoring question: what changes if income falls or
borrowing costs reset?
Limit
An aggregate payment ratio does not reveal every borrower’s
distress or establish a default probability.
Refinancing / liquidity
Can obligations be paid or refinanced when they fall due?Observed corporate factor
Mechanism
Maturity dates, repricing exposure, cash and committed credit
lines, and financing terms. Higher market credit spreads are funding context,
not a measured maturity wall.
Causal chain
When debt falls due it must be repaid or replaced with new
financing; if funding tightens or a lender pulls back at exactly that moment, an
otherwise solvent borrower can be forced into default or a forced sale for lack of
cash, not lack of net worth.
Assessment status
Observed corporate factor available above. A calibrated current score for the whole dimension is not estimated.
Supporting evidence
The nonfinancial corporate broad-liquid-assets / short-term-liabilities ratio is now charted. A ratio below 100% is not a measured funding shortfall; maturities and immediately accessible cash are not supplied. Inspect the dated evidence.
Useful for
A monitoring question: what happens if funding is unavailable
for three months?
Limit
A solvent borrower can still be illiquid; the market-conditions
index below does not measure this separately.
Financial contagion
How could losses spread between institutions or sectors?Conditional model result
Mechanism
Counterparty exposures, leverage, collateral, common asset holdings,
and withdrawal or redemption terms. Existing mechanism models are separate from a
measured current network of exposures.
Causal chain
A loss at one institution can force asset sales or funding
withdrawals that transmit stress to its counterparties and to others holding similar
assets, so an initially contained loss can widen into a broader event through exposure
and correlation, not through the size of the first loss alone.
Assessment status
Conditional model result available above. A calibrated current score for the whole dimension is not estimated.
Supporting evidence
The existing sector-network experiment now shows conditional amplification under three allocation treatments. Its assumed shock and capital buffers are explicit; it is not a current distress observation. Inspect the dated evidence.
Useful for
A scenario question: which counterparties and common assets
would amplify an initial loss?
Limit
A scenario drawn on assumed links is not an observed probability
or a complete financial-system exposure map.
External / supply dependencies
Which inputs or routes could interrupt production?Observed freight context
Mechanism
Product-specific import/supplier concentration, substitutability,
inventories, and route dependencies. Freight cost is context, not a disruption
probability.
Causal chain
If a concentrated input, supplier, or transport route is disrupted,
production that depends on it slows or stops until a substitute, inventory buffer, or
alternate route is found; the economic cost depends on substitutability and lead time,
not on the disrupted input's trade value.
Assessment status
Observed freight context available above. A calibrated current score for the whole dimension is not estimated.
Supporting evidence
Monthly US freight-volume growth is now charted as activity context. It cannot identify foreign dependencies or distinguish weaker demand from a supply interruption. Inspect the dated evidence.
Useful for
A monitoring question: what changes if a critical supplier or
route is unavailable?
Limit
Trade value alone cannot identify physical bottlenecks, spare
capacity, or replacement time.
Fiscal / policy buffers
What constrains the response to a shock?Observed fiscal context
Mechanism
Interest burden, revenue, debt maturity and currency composition,
monetary arrangements, and institutional constraints.
Causal chain
A revenue shortfall or a rise in borrowing costs increases
financing needs just as a shock may demand more spending; the ability to respond is
constrained by how quickly debt must be rolled at the new terms and by institutional
limits on borrowing or monetary support, not by the public debt/GDP ratio alone.
Assessment status
Observed fiscal context available above. A calibrated current score for the whole dimension is not estimated.
Supporting evidence
Annual federal receipts, outlays and their balance are now presented on the same fiscal-year basis. These are financing context, not a measure of remaining policy capacity. Inspect the dated evidence.
Useful for
A monitoring question: what happens to financing needs and
response options under a revenue or interest-cost shock?
Limit
Public debt/GDP alone does not measure policy capacity; budget cash
flows and national-accounts accruals answer different questions.
An unavailable mechanism is unknown, not zero or benign. A populated factor or scenario does not mean that the whole vulnerability dimension is measured.
How to read the fragility view
What the number is
A single 0–1 score summarising market conditions associated
with credit-cycle stress — an experimental index, not a measurement of every private
balance-sheet exposure. It combines four families of public market driver:
the term structure of interest rates, a credit spread, equity
volatility, and an equity valuation level. Higher means a higher combined
market-conditions score under this method — not a higher probability of any
event, and not a reading of the debt-service, refinancing, contagion, external or
fiscal buffers dimensions named above, which this index does not feed and do not feed
it. It does not directly observe household debt service, corporate refinancing needs,
cash buffers or bank positions; those belong to separate, separately named models.
The model recomputes the score daily and publishes it to cloud
storage; this page reads that published copy (with a baked fallback that is labelled
when stale). The inputs have different cadences: the market legs publish daily,
usually a day or two apart, while the valuation leg is an annual curated value held
constant through the year — so a daily publication is not four daily observations.
Daily movement enters only through quarter-to-date driver means — a single day cannot
swing the reading on its own, which is why the line is smooth and why a still-open
quarter is marked provisional.
Input
Plain explanation
Limitation to retain
Treasury yield curve
The difference between long- and shorter-term Treasury
yields; recent flat/inverted conditions raise this component.
Retained history can keep it elevated after the current
curve changes.
Corporate credit spread
The extra yield on Baa corporate debt relative to
Treasuries.
A market financing indicator, not the amount of debt or a
measure of total balance-sheet losses.
Equity volatility
The VIX measure of expected equity-market volatility.
Often responds during a sell-off; it does not necessarily
lead the shock.
Equity valuation
Share prices relative to long-run earnings, using CAPE.
Annual input in this implementation; high valuation alone
does not identify when a decline will occur.
The yield-curve input is the 10-year Treasury yield minus the
2-year yield. See the rates, their spread and the market index together in our
yield-curve guide.
What the regimes mean
The four regime names are bands of the combined score, not a
count of stretched legs — a weighted composite does not enforce a fixed number of
drivers being stretched at any given band. Elevated is the one precisely
defined boundary: the reading is above 0.40, the sealed tripwire's own public
criterion. Benign, Watch and Fragile are authored categories
on either side of it: the thresholds were chosen by this model's authors, and crossing
one is a statement about the combined index, not a calibrated probability of any
event and not a tally of how many of the four inputs are individually stretched.
What it is not
It is not a market call, not a recession probability, not a
timing signal, and not a demonstrated forecasting record. It is model-conditional:
it says what this model reads from these drivers. Its retrospective record on
credit-cycle drawdowns is mixed (stated above), and it says nothing about exogenous
shocks — a war, a pandemic, a policy accident — that arrive from outside its
market drivers.
Why the US line is different
The US reading is the sealed
instrument: all four legs are the United States' own published series — three at
daily frequency, the valuation leg an annual curated value — and the same instrument
stands behind a sealed, dated, scoreable prediction in the ledger. When it is wrong,
it will be scored in public like any other entry. Sealing makes the record checkable;
it does not, by itself, make the model right.
Why the other lines are approximate
No other economy has four keyless daily drivers of its own. The
comparison lines fill the gaps with declared proxies — a regional credit spread instead
of a national one, a global volatility index, market capitalisation over GDP as the
valuation leg, normalised against that country's own history. Each substitution is
listed on the country card on the home page.
That makes each of them useful for watching its own economy's
direction of travel. It does not make them the same instrument as the US index,
and it does not support ranking economies against each other — the same numeric value
need not represent the same exposure in two countries. They are
approximate: not sealed, not scored, and never
published as predictions.
Where we publish nothing. A country reading is not
the US instrument pointed at other data: with legs missing, and monthly, lagged inputs,
it would be a different model with a different calibration — and it would need its own
sealed lanes before it deserved to be called a prediction. Showing one under the same
name is exactly the failure this ledger exists to prevent.