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}.
SAQ: 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, SAQ'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 Current account / GDP by 1 year (it moves inversely tothe target; r = -0.57 over 46 obs).
| Year | Nowcast | Implied by Current account / GDP in |
|---|---|---|
| 2027 | 7.64 | 2026 (-1.7) |
Latest observed-1.7(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | -1.73 | 0.73 | -4.2 | -2.27 – -1.2 |
| 2029 | -1.8 | 2.46 | -6.07 | -2.76 – -0.85 |
| 2031 | -1.87 | 3.64 | -7.38 | -3.15 – -0.6 |
| 2036 | -2.05 | 5.74 | -9.84 | -3.96 – -0.13 |
Blended 1-yr-ahead-1.88· skill-weighted across models
Method: linear_trend; lookback 8y; horizon 1y; confidence 80%
Latest observed5.3T(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 5.5T | 5.9T | 5.1T | 5.3T – 5.7T |
| 2029 | 6T | 6.8T | 5.4T | 5.6T – 6.5T |
| 2031 | 6.6T | 7.5T | 5.8T | 5.8T – 7.3T |
| 2036 | 7.9T | 9.3T | 6.8T | 6.3T – 9.6T |
Blended 1-yr-ahead5.5T· skill-weighted across models
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed6(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 5.76 | 7.44 | 4.3 | 5.39 – 6.13 |
| 2029 | 5.18 | 8.1 | 2.66 | 4.45 – 5.92 |
| 2031 | 4.61 | 8.37 | 1.35 | 3.61 – 5.6 |
| 2036 | 3.16 | 8.48 | -1.45 | 1.77 – 4.55 |
Blended 1-yr-ahead5.67· skill-weighted across models
Method: weighted_composite; lookback 6y; horizon 1y; confidence 80%
Latest observed2.7k(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 2.8k | 3k | 2.6k | 2.7k – 2.9k |
| 2029 | 3k | 3.4k | 2.7k | 2.8k – 3.3k |
| 2031 | 3.3k | 3.8k | 2.8k | 2.9k – 3.6k |
| 2036 | 3.9k | 4.6k | 3.2k | 3.1k – 4.7k |
Blended 1-yr-ahead2.8k· skill-weighted across models
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed78.3(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 79.65 | 87.07 | 71.1 | 77.18 – 82.12 |
| 2029 | 82.36 | 95.2 | 67.54 | 76.26 – 88.45 |
| 2031 | 85.06 | 101.64 | 65.93 | 75.4 – 94.72 |
| 2036 | 91.82 | 115.27 | 64.76 | 72.77 – 110.87 |
Blended 1-yr-ahead79.09· skill-weighted across models
Method: linear_trend; lookback 10y; horizon 1y; confidence 80%
Latest observed5.2(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 6.47 | 10.83 | 1.8 | 5.4 – 7.54 |
| 2029 | 9.69 | 17.24 | 1.6 | 7.55 – 11.83 |
| 2031 | 12.91 | 22.65 | 2.47 | 9.71 – 16.1 |
| 2036 | 20.96 | 34.74 | 6.19 | 14.55 – 27.37 |
Blended 1-yr-ahead5.11· skill-weighted across models
Method: exponential_smoothing; lookback 6y; horizon 1y; confidence 80%
Latest observed1.9bn(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 1.9bn | 2bn | 1.9bn | 1.9bn – 2bn |
| 2029 | 2bn | 2.1bn | 1.9bn | 1.8bn – 2.1bn |
| 2031 | 2bn | 2.1bn | 1.9bn | 1.8bn – 2.2bn |
| 2036 | 2bn | 2.1bn | 2bn | 1.6bn – 2.5bn |
Blended 1-yr-ahead2bn· skill-weighted across models
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 2026-08-02 from observed history. Projections, not observations — never a guarantee of future values.
Machine-readable: GET /api/v1/forecast/country/SAQ · Country page → · Full brief → · API docs
Fit: CPI inflation ≈ 5.3996 + -1.3166·Current account / GDP. Correlation, not causation.
Led by CPI inflation by 2 years (it moves inversely tothe target; r = -0.569 over 32 obs).
| Year | Nowcast | Implied by CPI inflation in |
|---|---|---|
| 2027 | 77.29 | 2025 (2.9) |
| 2028 | 73.83 | 2026 (5.2) |
Fit: Govt debt / GDP ≈ 81.6576 + -1.5056·CPI inflation. Correlation, not causation.
Machine-readable: GET /api/v1/nowcast/country/SAQ?indicator= · API docs
