Global government-debt signals (sovereign debt-stress gauges)
Annual sovereign-debt signals derived from the IMF DataMapper (general government gross debt, % of GDP, ~190 economies, 1980 ->): 1-year and 3-year changes, 30-year change volatility, 3-sigma anomaly flags vs a trailing-10-year baseline, naive-drift 1-year forecasts, per-year cross-country volatility ranks, 10-year debt z-scores, 5-year debt-accumulation changes, and high-debt (>90% of GDP) and rapid-accumulation flags. The fiscal-sustainability companion to the WEO growth-momentum signals. Country codes normalized to verified ISO alpha-3. Raw data: International Monetary Fund (DataMapper, keyless API).
Qualité
Attribution
International Monetary Fund, DataMapper (derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Reference year (January 1). The DataMapper publishes WEO-vintage annual data. (unit: ISO date) |
| country | string | Country name (canonical English short name). |
| country_code | string | ISO 3166-1 alpha-3 country code. |
| series_id | string | IMF DataMapper indicator code (GGXWDG_NGDP). |
| series_label | string | IMF DataMapper indicator label: 'General government gross debt, percent of GDP'. |
| value | float | General government gross debt, percent of GDP (IMF DataMapper indicator GGXWDG_NGDP). (unit: percent of GDP) |
| change_1y | float | |
| volatility_30d | float | |
| momentum_3m | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| debt_z_10y | float | |
| debt_change_5y_pp | float | |
| high_debt_flag | integer | |
| rising_fast_flag | integer |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | change_1y | volatility_30d | momentum_3m | anomaly_flag | forecast_1m | rank | debt_z_10y | debt_change_5y_pp | high_debt_flag | rising_fast_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1980-01-01 | Belgium | BEL | GGXWDG_NGDP | General government gross debt, percent of GDP | 76.8 | — | — | — | 0 | — | — | — | — | 0 | 0 |
| 1980-01-01 | Canada | CAN | GGXWDG_NGDP | General government gross debt, percent of GDP | 44.6 | — | — | — | 0 | — | — | — | — | 0 | 0 |
| 1980-01-01 | Spain | ESP | GGXWDG_NGDP | General government gross debt, percent of GDP | 16.1 | — | — | — | 0 | — | — | — | — | 0 | 0 |
| 1980-01-01 | Finland | FIN | GGXWDG_NGDP | General government gross debt, percent of GDP | 10.9 | — | — | — | 0 | — | — | — | — | 0 | 0 |
| 1980-01-01 | France | FRA | GGXWDG_NGDP | General government gross debt, percent of GDP | 21.3 | — | — | — | 0 | — | — | — | — | 0 | 0 |
Télécharger un échantillon
Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).
Utiliser avec un LLM
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/global_debt_signals/global_government_debt_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/global_debt_signals/global_government_debt_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API: https://datazimuts.com/v1/datasets/global_debt_signals/global_government_debt_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.