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}.
SSQ: 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, SSQ'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 1 year (it moves withthe target; r = 0.8 over 26 obs).
| Year | Nowcast | Implied by CPI inflation in |
|---|---|---|
| 2026 | 44.63 | 2025 (13.4) |
Fit: Govt debt / GDP ≈ . Correlation, not causation.
Latest observed-0.7(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | -0.84 | 0.99 | -2.67 | -1.23 – -0.45 |
| 2028 | -0.52 | 2.64 | -3.68 | -1.21 – 0.17 |
| 2030 | -0.2 | 3.88 | -4.29 | -1.12 – 0.71 |
| 2035 | 0.6 | 6.37 | -5.18 | -0.74 – 1.93 |
Blended 1-yr-ahead-0.81· skill-weighted across models
Track record±0.14typical miss · 1 realized · 20% MAPE
Method: linear_trend; lookback 8y; horizon 1y; confidence 80%
Latest observed2.5T(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 2.2T | 2.5T | 1.9T | 2.1T – 2.2T |
| 2028 | 2.1T | 2.7T | 1.6T | 2T – 2.3T |
| 2030 | 2.1T | 2.8T | 1.4T | 1.8T – 2.3T |
| 2035 | 2T | 3.1T | 1.1T | 1.6T – 2.4T |
Blended 1-yr-ahead2.5T· skill-weighted across models
Track record±337.7bntypical miss · 1 realized · 14% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed4.3(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 5.2 | 11.02 | 0.16 | 4.15 – 6.25 |
| 2028 | 6.8 | 12 | -1.94 | 4.79 – 8.81 |
| 2030 | 8.4 | 12 | -2.88 | 5.56 – 11.24 |
| 2035 | 12 | 12 | -3.95 | 7.01 – 12 |
Blended 1-yr-ahead4.36· skill-weighted across models
Track record±0.9typical miss · 1 realized · 21% MAPE
Method: weighted_composite; lookback 6y; horizon 1y; confidence 80%
Latest observed1.9k(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 1.7k | 2k | 1.4k | 1.6k – 1.7k |
| 2028 | 1.6k | 2.1k | 1.1k | 1.4k – 1.7k |
| 2030 | 1.5k | 2.1k | 900.74 | 1.3k – 1.6k |
| 2035 | 1.2k | 2.1k | 380.49 | 870.94 – 1.5k |
Blended 1-yr-ahead2k· skill-weighted across models
Track record±255.38typical miss · 1 realized · 13% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed57.9(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 61.61 | 67.68 | 54.6 | 59.69 – 63.53 |
| 2028 | 66.42 | 76.94 | 54.28 | 61.51 – 71.33 |
| 2030 | 71.23 | 84.81 | 55.57 | 63.15 – 79.32 |
| 2035 | 83.27 | 102.47 | 61.11 | 65.99 – 100.54 |
Blended 1-yr-ahead58.89· skill-weighted across models
Track record±3.71typical miss · 1 realized · 6% MAPE
Method: linear_trend; lookback 10y; horizon 1y; confidence 80%
Latest observed9.5(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 9.6 | 18.13 | 0.45 | 7.55 – 11.64 |
| 2028 | -2.86 | 11.92 | -5 | -5 – 0.55 |
| 2030 | -5 | 14.08 | -5 | -5 – -0.37 |
| 2035 | -5 | 21.98 | -5 | -5 – 1.78 |
Blended 1-yr-ahead8.67· skill-weighted across models
Track record±0.1typical miss · 1 realized · 1% MAPE
Method: exponential_smoothing; lookback 6y; horizon 1y; confidence 80%
Latest observed1.3bn(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 1.2bn | 1.3bn | 1.2bn | 1.2bn – 1.3bn |
| 2028 | 1.3bn | 1.3bn | 1.2bn | 1.2bn – 1.4bn |
| 2030 | 1.3bn | 1.4bn | 1.3bn | 1.2bn – 1.5bn |
| 2035 | 1.4bn | 1.5bn | 1.3bn | 1.1bn – 1.7bn |
Blended 1-yr-ahead1.3bn· skill-weighted across models
Track record±38.7mtypical miss · 1 realized · 3% 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 2026-09-17 from observed history. Projections, not observations — never a guarantee of future values.
Machine-readable: GET /api/v1/forecast/country/SSQ · Country page → · Full brief → · API docs
Led by Govt debt / GDP by 1 year (it moves withthe target; r = 0.746 over 25 obs).
| Year | Nowcast | Implied by Govt debt / GDP in |
|---|---|---|
| 2026 | 16.26 | 2025 (59.2) |
Fit: CPI inflation ≈ 2.4851 + 0.2326·Govt debt / GDP. Correlation, not causation.
Machine-readable: GET /api/v1/nowcast/country/SSQ?indicator= · API docs
