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 2027, 2029, 2031, 2036. 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 = 0.79 over 27 obs).
| Year | Nowcast | Implied by CPI inflation in |
|---|---|---|
| 2027 | 34.96 | 2026 (9.5) |
Fit: Govt debt / GDP ≈ . Correlation, not causation.
Latest observed-0.7(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | -0.46 | 1.24 | -2.15 | -0.82 – -0.09 |
| 2029 | 0.03 | 2.97 | -2.91 | -0.62 – 0.68 |
| 2031 | 0.52 | 4.32 | -3.27 | -0.33 – 1.37 |
| 2036 | 1.74 | 7.11 | -3.63 | 0.37 – 3.11 |
Blended 1-yr-ahead-0.81· skill-weighted across models
Track record±2.36typical miss · 20 realized · 200% MAPE
Method: linear_trend; lookback 8y; horizon 1y; confidence 80%
Latest observed2.5T(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 2.6T | 3T | 2.2T | 2.5T – 2.7T |
| 2029 | 2.8T | 3.5T | 2.2T | 2.5T – 3T |
| 2031 | 3T | 3.8T | 2.2T | 2.6T – 3.3T |
| 2036 | 3.4T | 4.7T | 2.3T | 2.7T – 4.1T |
Blended 1-yr-ahead2.5T· skill-weighted across models
Track record±447bntypical miss · 20 realized · 20% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed4.3(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 4.51 | 5.94 | 3.26 | 4.19 – 4.82 |
| 2029 | 4.96 | 7.44 | 2.8 | 4.3 – 5.61 |
| 2031 | 5.41 | 8.62 | 2.62 | 4.44 – 6.37 |
| 2036 | 6.53 | 11.07 | 2.59 | 4.73 – 8.33 |
Blended 1-yr-ahead4.36· skill-weighted across models
Track record±4.45typical miss · 20 realized · 111% MAPE
Method: weighted_composite; lookback 6y; horizon 1y; confidence 80%
Latest observed1.9k(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 2k | 2.3k | 1.7k | 1.9k – 2k |
| 2029 | 2k | 2.6k | 1.5k | 1.9k – 2.2k |
| 2031 | 2.1k | 2.8k | 1.4k | 1.8k – 2.3k |
| 2036 | 2.2k | 3.3k | 1.3k | 1.8k – 2.7k |
Blended 1-yr-ahead2k· skill-weighted across models
Track record±442.13typical miss · 20 realized · 24% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed57.9(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 59.85 | 66.21 | 52.5 | 57.91 – 61.78 |
| 2029 | 63.74 | 74.77 | 51.02 | 58.99 – 68.5 |
| 2031 | 67.64 | 81.87 | 51.21 | 59.96 – 75.32 |
| 2036 | 77.37 | 97.51 | 54.14 | 61.32 – 93.42 |
Blended 1-yr-ahead58.89· skill-weighted across models
Track record±10.41typical miss · 20 realized · 18% MAPE
Method: linear_trend; lookback 10y; horizon 1y; confidence 80%
Latest observed9.5(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 8.67 | 17.36 | -0.64 | 6.6 – 10.73 |
| 2029 | 3.21 | 18.26 | -5 | -0.28 – 6.7 |
| 2031 | -2.25 | 17.18 | -5 | -5 – 2.24 |
| 2036 | -5 | 22.48 | -5 | -5 – 1.89 |
Blended 1-yr-ahead8.67· skill-weighted across models
Track record±9.61typical miss · 20 realized · 67% MAPE
Method: exponential_smoothing; lookback 6y; horizon 1y; confidence 80%
Latest observed1.3bn(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 1.3bn | 1.3bn | 1.2bn | 1.2bn – 1.3bn |
| 2029 | 1.3bn | 1.4bn | 1.3bn | 1.2bn – 1.4bn |
| 2031 | 1.3bn | 1.4bn | 1.3bn | 1.2bn – 1.5bn |
| 2036 | 1.4bn | 1.5bn | 1.4bn | 1.1bn – 1.7bn |
Blended 1-yr-ahead1.3bn· skill-weighted across models
Track record±85mtypical miss · 20 realized · 7% 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 2026-08-01 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 = 0.683 over 26 obs).
| Year | Nowcast | Implied by Govt debt / GDP in |
|---|---|---|
| 2027 | 15.28 | 2026 (57.9) |
Fit: CPI inflation ≈ 3.2875 + 0.2071·Govt debt / GDP. Correlation, not causation.
Machine-readable: GET /api/v1/nowcast/country/SSQ?indicator= · API docs
