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}.
APQ: 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, APQ'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 = -0.635 over 43 obs).
| Year | Nowcast | Implied by CPI inflation in |
|---|---|---|
| 2026 | 20.2T | 2023 (4.8) |
Latest observed2.6(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 3.31 | 4.29 | 2.32 | 3.05 – 3.56 |
| 2028 | 3.72 | 5.42 | 2.01 | 3.19 – 4.24 |
| 2030 | 4.13 | 6.33 | 1.93 | 3.35 – 4.91 |
| 2035 | 5.16 | 8.27 | 2.04 | 3.7 – 6.62 |
Blended 1-yr-ahead2.33· skill-weighted across models
Track record±0.71typical miss · 1 realized · 27% MAPE
Method: linear_trend; lookback 8y; horizon 1y; confidence 80%
Latest observed43.3T(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 42T | 45.2T | 39.2T | 40.7T – 43.3T |
| 2028 | 44.7T | 50.2T | 39.9T | 41.4T – 48T |
| 2030 | 47.3T | 54.5T | 41.1T | 42T – 52.7T |
| 2035 | 54T | 64.1T | 45.2T | 42.8T – 65.2T |
Blended 1-yr-ahead44.8T· skill-weighted across models
Track record±1.3Ttypical miss · 1 realized · 3% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed4.4(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 5.15 | 12 | -1.58 | 3.77 – 6.52 |
| 2028 | 5.72 | 12 | -5.94 | 3.21 – 8.24 |
| 2030 | 6.3 | 12 | -8.75 | 2.9 – 9.7 |
| 2035 | 7.74 | 12 | -10 | 2.41 – 12 |
Blended 1-yr-ahead4.14· skill-weighted across models
Track record±0.75typical miss · 1 realized · 17% MAPE
Method: weighted_composite; lookback 6y; horizon 1y; confidence 80%
Latest observed9.6k(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 9.3k | 10k | 8.6k | 9k – 9.5k |
| 2028 | 9.8k | 11k | 8.7k | 9k – 10.5k |
| 2030 | 10.3k | 11.9k | 8.8k | 9.1k – 11.4k |
| 2035 | 11.5k | 13.8k | 9.5k | 9.1k – 13.9k |
Blended 1-yr-ahead9.9k· skill-weighted across models
Track record±373.85typical miss · 1 realized · 4% MAPE
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed96.3(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 95.53 | 102.46 | 87.54 | 92.57 – 98.49 |
| 2028 | 99.6 | 111.6 | 85.75 | 92.23 – 106.97 |
| 2030 | 103.66 | 119.16 | 85.78 | 91.89 – 115.43 |
| 2035 | 113.83 | 135.74 | 88.54 | 90.22 – 137.44 |
Blended 1-yr-ahead97.43· skill-weighted across models
Track record±0.77typical miss · 1 realized · 1% MAPE
Method: linear_trend; lookback 10y; horizon 1y; confidence 80%
Latest observed3.7(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 2.12 | 5.74 | -1.76 | 1.28 – 2.96 |
| 2028 | -0.12 | 6.16 | -5 | -1.56 – 1.32 |
| 2030 | -2.36 | 5.74 | -5 | -4.35 – -0.38 |
| 2035 | -5 | 6.46 | -5 | -5 – -1.66 |
Blended 1-yr-ahead3.66· skill-weighted across models
Track record±1.58typical miss · 1 realized · 43% MAPE
Method: exponential_smoothing; lookback 6y; horizon 1y; confidence 80%
Latest observed4.5bn(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2026 | 4.5bn | 4.7bn | 4.3bn | 4.4bn – 4.7bn |
| 2028 | 4.5bn | 4.8bn | 4.3bn | 4.2bn – 4.9bn |
| 2030 | 4.6bn | 4.8bn | 4.4bn | 4bn – 5.1bn |
| 2035 | 4.6bn | 4.9bn | 4.4bn | 3.7bn – 5.6bn |
Blended 1-yr-ahead4.5bn· skill-weighted across models
Track record±12.8mtypical miss · 1 realized · 0% 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/APQ · Country page → · Full brief → · API docs
| 2027 | 21.2T | 2024 (4.3) |
| 2028 | 24.4T | 2025 (2.7) |
Fit: GDP (current US$) ≈ 29829985058469.992 + -1995975777077.5603·CPI inflation. Correlation, not causation.
Led by GDP (current US$) by 1 year (it moves inversely tothe target; r = -0.573 over 45 obs).
| Year | Nowcast | Implied by GDP (current US$) in |
|---|---|---|
| 2026 | 1.75 | 2025 (41T) |
Fit: CPI inflation ≈ 8.7692 + 0·GDP (current US$). Correlation, not causation.
Machine-readable: GET /api/v1/nowcast/country/APQ?indicator= · API docs
