HUMANITYVECTOR

US electricity net generation · United States · 12 months ahead

2027-05: the model assigns an 80 percent probability to 350,484 to 374,292 million kilowatthours

Point estimate 360,015 million kilowatthours from Drift, against 354,691 million kilowatthours observed in 2026-05. drift beats last_value on out-of-sample MAE by 13.6 percent over 36 cutoffs (minimum 24, margin 5 percent).

Distribution over the history

Fan chart

60 observed points to 2026-05, then 4 forecasts with 80 percent intervals301,903374,111446,3202021-062022-022022-102023-062024-022024-102025-062026-022027-05
Solid: observed (million kilowatthours). Dashed and shaded: model point estimates and 80 percent intervals from empirical residual quantiles. Filled dot: the record on this page. Green or red dot: the realised value, inside or outside its interval.
Quantiles
p5 346,161 · p10 350,484 · p25 354,798 · p50 363,917 · p75 368,582 · p90 374,292 · p95 379,828
Source
empirical quantiles of 36 in-window 12-step residuals, in log space; no normality assumed
The record

Immutable fields

Key
us-electricity-net-generation:USA:12
Id
0bb7e322-b171-4379-a926-2bbe1f1fb4a8
Created
2026-09-07 22:16 UTC
Data cutoff
2026-09-07 22:16 UTC
Origin
2026-05 = 354,691 (obs 245396)
Target period
2027-05 (365 days)
Point
360,015 million kilowatthours
Interval
350,484 to 374,292 at 80 percent
Model
drift models_v1.targets_v1
Baseline
last_value
Snapshot
4d454002289e02078827926c6c3b8d6d13800a4943d3db41e9aabcbd54e742c2
Data mode
ingested_at
Status
active
Drivers

Statistical association, not causal

Drift uses only the target's own history; there are no driver contributions.

Outcome

Not yet realised

The observation for 2027-05 has not been ingested. The weekly forecast.evaluate job attaches it when it arrives; the record above does not change.

Scenario assumptions

What the forecast takes for granted

  • No structural break in us-electricity-net-generation between the data cutoff and the target period.
  • The source keeps publishing the series on the same definition; a rebasing or redefinition invalidates the comparison.
  • The average historical change per period continues.
Falsifiers

What would show this forecast wrong

  • If the first published value of us-electricity-net-generation (USA) for 2027-05 is below 350,484 million kilowatthours or above 374,292 million kilowatthours, the 80 percent interval is falsified.
  • The model assigns a 10 percent probability to a value below 350,484 million kilowatthours and a 10 percent probability to a value above 374,292 million kilowatthours; interval misses should occur about one time in five over many forecasts, and a run of misses well above that rate falsifies the calibration.
  • The point forecast is above the last observed value (354,691 million kilowatthours); a realised value at or below that level falsifies the direction call.
Competing models

Scorecard for this target and horizon

ModelStatusCutoffsMAERMSEDirection80% coverageSkill vs last value
Drift
models_v1.targets_v1
champion369,31211,45278%89%13.6%
Holt (exponential smoothing with additive trend)
models_v1.targets_v1
challenger3624,56528,64642%89%-128.0%
Last value
models_v1.targets_v1
baseline3610,77613,4340%89%0.0%
Linear trend
models_v1.targets_v1
challenger3630,89136,40967%83%-186.7%
Ridge regression on lags and drivers
models_v1.targets_v1
challenger369,73812,46272%92%9.6%
Seasonal naive
models_v1.targets_v1
challenger3610,77613,4340%89%0.0%
Champion: Drift. drift beats last_value on out-of-sample MAE by 13.6 percent over 36 cutoffs (minimum 24, margin 5 percent).
Model card

Drift

Drift

Purpose. Point and 80 percent interval forecasts of us-electricity-net-generation (USA) 1, 3, 6, 12 months ahead. Owner: Forecast Lab (HV 3.0).

Method

The forecast extends the mean first difference of the whole training window from the last value: last value plus horizon times the average change. The series is modelled in natural logarithms and transformed back, so intervals are asymmetric in level terms.

Uncertainty

Intervals are empirical: the model is refitted at earlier origins inside the training window, the realised errors at the same horizon are collected, and the interval is the 10th to 90th percentile of those errors around the point forecast. No normality is assumed.

Training and evaluation

Training window: 641 periods, 1973-01-01 to 2026-05-01. Evaluation: rolling-origin backtest over 36 cutoffs using pseudo real-time data (the earliest ingested value per period; no vintage archive exists for this series, so revisions between the cutoff and today are not reproduced).

Known limitations

  • Structural breaks after the cutoff are not modelled.
  • Driver contributions are statistical associations, not causal effects.
  • Promotion to champion requires beating the last-value baseline on out-of-sample MAE by at least 5 percent over the minimum number of cutoffs; otherwise the baseline stays champion.
  • Retraining: every scheduled forecast.run refits on the data then available; backtests re-run from /admin/forecasts.
Version chain

Supersedes

This is the first record for its key.