Global poverty & inequality signals (Gini and poverty headcount trajectories, anomaly flags)
Country-level signals derived from World Bank poverty and inequality indicators (Gini index, poverty headcount at $3.00 and $4.20 a day, 2021 PPP): 10-year point changes, OLS trend slopes over trailing survey years, 3-sigma anomaly flags, 5-year linear-extrapolation forecasts, per-year cross-country ranks, a poverty-improvement flag and a high-inequality flag. All rows are normalized to ISO alpha-3 country_code so they join cleanly with country macro data. Raw data: World Bank Poverty and Inequality Platform (keyless API, non-commercial terms).
Quality
Attribution
World Bank Poverty and Inequality Platform (derived signals by Frontier Data Hub)
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Survey year, reported as January 1 of the year (World Bank API field date). |
| country | string | |
| country_code | string | |
| series_id | string | World Bank indicator code: SI.POV.GINI (Gini index), SI.POV.DDAY (poverty headcount ratio at $3.00 a day, 2021 PPP), SI.POV.LMIC (poverty headcount ratio at $4.20 a day, 2021 PPP). |
| series_label | string | Official World Bank indicator name as published in the indicator metadata. |
| value | float | Indicator value for the survey year: Gini index (0 = perfect equality, 100 = perfect inequality) or poverty headcount ratio as a percentage of the population. See the World Bank indicator metadata for full methodology. |
| change_10y_pp | float | |
| trend_slope | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| improvement_flag | integer | |
| high_inequality_flag | integer |
Sample rows
| date | country | country_code | series_id | series_label | value | change_10y_pp | trend_slope | anomaly_flag | forecast_1m | rank | improvement_flag | high_inequality_flag |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1963-01-01 | United States | USA | SI.POV.DDAY | Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population) | 1.6 | — | — | 0 | — | 1 | — | — |
| 1963-01-01 | United States | USA | SI.POV.GINI | Gini index | 36.7 | — | — | 0 | — | 1 | — | 0 |
| 1963-01-01 | United States | USA | SI.POV.LMIC | Poverty headcount ratio at $4.20 a day (2021 PPP) (% of population) | 2.1 | — | — | 0 | — | 1 | — | — |
| 1964-01-01 | United States | USA | SI.POV.DDAY | Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population) | 1.5 | — | — | 0 | — | 1 | — | — |
| 1964-01-01 | United States | USA | SI.POV.GINI | Gini index | 37.4 | — | — | 0 | — | 1 | — | 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/poverty_inequality_signals/global_poverty_inequality_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/poverty_inequality_signals/global_poverty_inequality_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/poverty_inequality_signals/global_poverty_inequality_signals
Tip: fetch /llms.txt for the full machine-readable catalog.