Global harmonized-unemployment signals (OECD, 20 economies)
Monthly harmonized-unemployment signals for 20 major economies from the OECD's Infra-Annual Labor Statistics (ILO-harmonized definition, ages 15+, seasonally adjusted; redistributed by FRED): 3-month momentum, 30-month change volatility, 3-sigma anomaly flags vs a trailing 12-month baseline, drift forecasts, per-month cross-country ranks, a 3-year labor-stress z-score, an elevated-labor-market flag, and a cross-country dispersion gauge for global labor-divergence. The cross-country companion to us-labor-market-signals (US depth) and euro-area-unemployment-signals (euro breadth): one comparable measure for spotting which labor markets crack first. All rows normalized to ISO alpha-3 country codes so they join cleanly with every other global dataset. Raw series: OECD via FRED (commercial re-use of OECD data requires prior permission — flagged in the UI).
Quality
Attribution
OECD Infra-Annual Labor Statistics via FRED; commercial re-use of OECD data requires prior written permission (rights@oecd.org); derived signals by Frontier Data Hub
Schema
| Column | Type | Description |
|---|---|---|
| date | string | Observation date (FRED API field date; YYYY-MM-DD, monthly). |
| country | string | |
| country_code | string | |
| series_id | string | FRED series ID: LRHUTTTT{CC}M156S — Infra-Annual Labor Statistics: Monthly Unemployment Rate, Total, ages 15+, seasonally adjusted, for the 2-letter OECD country code CC (OECD, via FRED). |
| series_label | string | Official FRED series title as published for the series. |
| value | float | Harmonized monthly unemployment rate in percent (ILO definition, ages 15 and over, seasonally adjusted; OECD Infra-Annual Labor Statistics, via FRED). |
| momentum_3m | float | |
| volatility_30d | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| unemp_z_3y | float | |
| elevated_flag | integer | |
| dispersion_std | float |
Sample rows
| date | country | country_code | series_id | series_label | value | momentum_3m | volatility_30d | anomaly_flag | forecast_1m | rank | unemp_z_3y | elevated_flag | dispersion_std |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1993-01-01 | Austria | AUT | LRHUTTTTATM156S | Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria | 3.8 | — | — | 0 | — | 17 | — | 0 | 4.256898420741938 |
| 1993-02-01 | Austria | AUT | LRHUTTTTATM156S | Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria | 3.8 | — | — | 0 | — | 17 | — | 0 | 4.28449933028851 |
| 1993-03-01 | Austria | AUT | LRHUTTTTATM156S | Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria | 3.9 | — | — | 0 | — | 17 | — | 0 | 4.361000955976313 |
| 1993-04-01 | Austria | AUT | LRHUTTTTATM156S | Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria | 3.9 | 0.10000000000000009 | — | 0 | — | 17 | — | 0 | 4.433534304166689 |
| 1993-05-01 | Austria | AUT | LRHUTTTTATM156S | Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria | 4 | 0.20000000000000018 | — | 0 | — | 17 | — | 0 | 4.469890000287695 |
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_unemp_signals/global_harmonized_unemployment_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/global_unemp_signals/global_harmonized_unemployment_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_unemp_signals/global_harmonized_unemployment_signals
Tip: fetch /llms.txt for the full machine-readable catalog.