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).
Quality
Attribution
International Monetary Fund, DataMapper (derived signals by Frontier Data Hub)
Schema
| Column | 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 |
Sample rows
| 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 |
Download sample data
Download the full sample snapshot for this dataset (sample rows, not the complete dataset).
Use with an LLM
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (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)API endpoint: https://datazimuts.com/v1/datasets/global_debt_signals/global_government_debt_signals
Tip: fetch /llms.txt for the full machine-readable catalog.