Global harmonized-unemployment signals (OECD, 20 economies)

Name: Global harmonized-unemployment signals (OECD, 20 economies)
Creator: Harmonized-Unemployment Signals (derived)
License: https://www.oecd.org/en/about/terms-and-conditions.html
Keywords: unemployment, labor-market, oecd, harmonized, cross-country, macroeconomics, business-cycle, momentum, anomaly-detection, forecasting, signals, fred

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).

Source: Harmonized-Unemployment Signals (derived)10,478 lignesMis à jour: 22/09/2026

unemploymentlabor-marketoecdharmonizedcross-countrymacroeconomicsbusiness-cyclemomentumanomaly-detectionforecastingsignalsfred

Qualité

96.7

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

Schéma

Colonne	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

Exemple de lignes

date	country	country_code	series_id	series_label	value	momentum_3m	volatility_30d	forecast_1m	rank	unemp_z_3y	dispersion_std
1993-01-01	Austria	AUT	LRHUTTTTATM156S	Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria	3.8	—	—	—	17	—	4.256898420741938
1993-02-01	Austria	AUT	LRHUTTTTATM156S	Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria	3.8	—	—	—	17	—	4.28449933028851
1993-03-01	Austria	AUT	LRHUTTTTATM156S	Infra-Annual Labor Statistics: Monthly Unemployment Rate Total: 15 Years or over for Austria	3.9	—	—	—	17	—	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	—	—	17	—	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	—	—	17	—	4.469890000287695

Télécharger un échantillon

Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).

Télécharger l'exemple CSV Télécharger l'exemple JSON

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_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)

Point d’accès API: https://datazimuts.com/v1/datasets/global_unemp_signals/global_harmonized_unemployment_signals

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.