Forecast
Forward projections from the prediction engine — baseline plus an optimistic/pessimistic band and a confidence interval, per macro indicator. These are PROJECTIONS, not observations: generated from observed history, never a guarantee. A country we hold no projections for is shown honestly.
Forecast
Need it as JSON? GET /api/v1/forecast/country/{iso3}.
SEQ: forward projections across 7 macro indicators, horizons 2026, 2028, 2030, 2035. These are projections, not observations — each carries an optimistic/pessimistic band and a confidence interval, anchored against the latest observed value where one is held.
Nowcast
Each indicator nowcast from its strongest leading series — inferable from observations already in hand.
For each indicator, SEQ's strongest leading series is fit by ordinary least squares over their shared observed history, then the leader's already-observed recent values project the target — so the next year or two is inferable from data already in hand. These are nowcasts from a leading correlation: correlation, not causation, and not a guaranteed forecast.
Led by CPI inflation by 3 years (it moves inversely tothe target; r = -0.685 over 43 obs).
| Year | Nowcast | Implied by CPI inflation in |
|---|---|---|
| 2026 | 2.2T | 2023 (4.1) |
Latest observed1.5(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 3.53 | 5.29 | 1.78 | 3.12 – 3.95 |
| 2028 | 3.8 | 6.84 | 0.76 | 3 – 4.6 |
| 2030 | 4.07 | 7.99 | 0.14 | 2.94 – 5.19 |
| 2035 | 4.73 | 10.28 | -0.82 | 2.84 – 6.62 |
Blended 1-yr-ahead1.21· skill-weighted across models
Track record±2.03typical miss · 1 realized · 136% MAPE
Method: linear_trend; lookback 8y; horizon 1y; confidence 80%
Latest observed4.5T(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 4.4T | 4.7T | 4.1T | 4.2T – 4.5T |
| 2028 | 4.7T | 5.3T | 4.3T | 4.4T – 5.1T |
| 2030 | 5.1T | 5.8T | 4.5T | 4.5T – 5.7T |
| 2035 | 6T | 7T | 5.2T | 4.8T – 7.2T |
Blended 1-yr-ahead4.7T· skill-weighted across models
Track record±128.7bntypical miss · 1 realized · 3% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed4.9(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 5.54 | 11.76 | 0.15 | 4.42 – 6.67 |
| 2028 | 7.01 | 12 | -2.33 | 4.88 – 9.14 |
| 2030 | 8.48 | 12 | -3.58 | 5.48 – 11.48 |
| 2035 | 12 | 12 | -5.05 | 6.8 – 12 |
Blended 1-yr-ahead4.97· skill-weighted across models
Track record±0.64typical miss · 1 realized · 13% MAPE
Method: weighted_composite; lookback 6y; horizon 1y; confidence 80%
Latest observed6.4k(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 6.3k | 6.7k | 5.9k | 6.1k – 6.5k |
| 2028 | 6.7k | 7.5k | 6k | 6.2k – 7.2k |
| 2030 | 7.1k | 8.2k | 6.2k | 6.3k – 7.9k |
| 2035 | 8.2k | 9.7k | 6.9k | 6.5k – 9.9k |
Blended 1-yr-ahead6.7k· skill-weighted across models
Track record±172.51typical miss · 1 realized · 3% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed67.5(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 69.15 | 74.39 | 63.1 | 67 – 71.29 |
| 2028 | 74.64 | 83.71 | 64.16 | 69.11 – 80.16 |
| 2030 | 80.13 | 91.85 | 66.61 | 71.03 – 89.23 |
| 2035 | 93.85 | 110.43 | 74.73 | 74.39 – 113.32 |
Blended 1-yr-ahead69.14· skill-weighted across models
Track record±1.65typical miss · 1 realized · 2% MAPE
Method: linear_trend; lookback 10y; horizon 1y; confidence 80%
Latest observed3.8(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 1.89 | 5.16 | -1.61 | 1.14 – 2.65 |
| 2028 | 0.77 | 6.43 | -5 | -0.53 – 2.07 |
| 2030 | -0.35 | 6.96 | -5 | -2.05 – 1.35 |
| 2035 | -3.15 | 7.19 | -5 | -5 – -0.35 |
Blended 1-yr-ahead4.03· skill-weighted across models
Track record±1.91typical miss · 1 realized · 50% MAPE
Method: exponential_smoothing; lookback 6y; horizon 1y; confidence 80%
Latest observed700.3m(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 693.1m | 725.9m | 662.7m | 671.6m – 714.6m |
| 2028 | 699.8m | 732.9m | 669.1m | 648.1m – 751.6m |
| 2030 | 706.6m | 739.9m | 675.6m | 626.3m – 786.8m |
| 2035 | 723.4m | 757.5m | 691.6m | 573.3m – 873.4m |
Blended 1-yr-ahead705.8m· skill-weighted across models
Track record±7.2mtypical miss · 1 realized · 1% MAPE
Method: exponential_smoothing; lookback 10y; horizon 1y; confidence 80%
Reliability badges show each indicator's best model skill— how much it beats a naive last-value forecast, measured out-of-sample on that series' own observed history (backtested one-step-ahead). A track record, not a guarantee of future accuracy.
Generated by the prediction engine (model prediction-engine-v1) on 2026-10-31 from observed history. Projections, not observations — never a guarantee of future values.
Machine-readable: GET /api/v1/forecast/country/SEQ · Country page → · Full brief → · API docs
| 2027 | 2.4T | 2024 (2.9) |
| 2028 | 2.5T | 2025 (2.1) |
Fit: GDP (current US$) ≈ 2800330510043.244 + -151264457501.0208·CPI inflation. Correlation, not causation.
Led by GDP (current US$) by 1 year (it moves inversely tothe target; r = -0.648 over 45 obs).
| Year | Nowcast | Implied by GDP (current US$) in |
|---|---|---|
| 2026 | -0.81 | 2025 (4.2T) |
Fit: CPI inflation ≈ 11.8512 + 0·GDP (current US$). Correlation, not causation.
Machine-readable: GET /api/v1/nowcast/country/SEQ?indicator= · API docs
