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}.
AZQ: 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, AZQ'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 withthe target; r = 0.791 over 38 obs).
| Year | Nowcast | Implied by Current account / GDP in |
|---|---|---|
| 2027 | 36.54 | 2026 (-2.5) |
Latest observed-2.5(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | -3.04 | -0.83 | -5.26 | -3.54 – -2.54 |
| 2029 | -4.13 | -0.3 | -7.96 | -5.11 – -3.15 |
| 2031 | -5.22 | -0.28 | -10.16 | -6.65 – -3.79 |
| 2036 | -7.94 | -0.95 | -14.93 | -10.64 – -5.24 |
Blended 1-yr-ahead-2.26· skill-weighted across models
Method: linear_trend; lookback 8y; horizon 1y; confidence 80%
Latest observed2.4T(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 2.5T | 2.8T | 2.3T | 2.4T – 2.6T |
| 2029 | 2.7T | 3.2T | 2.3T | 2.5T – 2.9T |
| 2031 | 3T | 3.6T | 2.4T | 2.6T – 3.3T |
| 2036 | 3.5T | 4.4T | 2.8T | 2.8T – 4.3T |
Blended 1-yr-ahead2.5T· skill-weighted across models
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed2(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 2.14 | 4.41 | 0.17 | 1.72 – 2.55 |
| 2029 | 2.33 | 6.27 | -1.08 | 1.57 – 3.1 |
| 2031 | 2.53 | 7.61 | -1.87 | 1.48 – 3.58 |
| 2036 | 3.02 | 10.2 | -3.2 | 1.34 – 4.7 |
Blended 1-yr-ahead1.69· skill-weighted across models
Method: weighted_composite; lookback 6y; horizon 1y; confidence 80%
Latest observed71.9k(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 73.9k | 83k | 66k | 71.6k – 76.2k |
| 2029 | 79.3k | 95k | 65.6k | 73.4k – 85.1k |
| 2031 | 84.7k | 105k | 67.1k | 75k – 94.3k |
| 2036 | 98.1k | 126.8k | 73.2k | 77.8k – 118.5k |
Blended 1-yr-ahead73k· skill-weighted across models
Method: weighted_composite; lookback 8y; horizon 1y; confidence 80%
Latest observed51.3(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 52.47 | 59.72 | 44.09 | 50.51 – 54.42 |
| 2029 | 54.8 | 67.37 | 40.3 | 50.24 – 59.37 |
| 2031 | 57.14 | 73.36 | 38.42 | 50.07 – 64.2 |
| 2036 | 62.97 | 85.92 | 36.5 | 49.37 – 76.58 |
Blended 1-yr-ahead51.96· skill-weighted across models
Method: linear_trend; lookback 10y; horizon 1y; confidence 80%
Latest observed3.9(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 4.39 | 8.65 | -0.18 | 3.37 – 5.4 |
| 2029 | 5.79 | 13.17 | -2.12 | 3.87 – 7.7 |
| 2031 | 7.19 | 16.71 | -3.02 | 4.5 – 9.87 |
| 2036 | 10.69 | 24.16 | -3.75 | 5.99 – 15.38 |
Blended 1-yr-ahead3.94· skill-weighted across models
Method: exponential_smoothing; lookback 6y; horizon 1y; confidence 80%
Latest observed33.4m(2026)· IMF DataMapper API
| Year | Baseline | Optimistic | Pessimistic | Conf. band |
|---|---|---|---|---|
| 2027 | 33.3m | 34.9m | 31.8m | 32.3m – 34.3m |
| 2029 | 33.7m | 35.3m | 32.2m | 31.2m – 36.2m |
| 2031 | 34.1m | 35.8m | 32.6m | 30.3m – 38m |
| 2036 | 35.2m | 36.8m | 33.6m | 27.9m – 42.5m |
Blended 1-yr-ahead33.8m· 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/AZQ · Country page → · Full brief → · API docs
Fit: Govt debt / GDP ≈ 51.2481 + 5.8813·Current account / GDP. Correlation, not causation.
Led by Govt debt / GDP by 1 year (it moves withthe target; r = 0.754 over 37 obs).
| Year | Nowcast | Implied by Govt debt / GDP in |
|---|---|---|
| 2027 | -1.25 | 2026 (51.3) |
Fit: Current account / GDP ≈ -6.5511 + 0.1034·Govt debt / GDP. Correlation, not causation.
Led by Govt debt / GDP by 1 year (it moves withthe target; r = 0.611 over 37 obs).
| Year | Nowcast | Implied by Govt debt / GDP in |
|---|---|---|
| 2027 | 1.8T | 2026 (51.3) |
Fit: GDP (current US$) ≈ 244964937328.5729 + 29871898885.3262·Govt debt / GDP. Correlation, not causation.
Machine-readable: GET /api/v1/nowcast/country/AZQ?indicator= · API docs
