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OECD Economic Outlook: unemployment rate

Unemployment as a percentage of the labour force (OECD measure UNR: "Unemployment rate"), for OECD members, G20 non-members and major aggregates. Includes the Outlook's two-year projections. Unit: percent of labour force (UNIT_MEASURE=PT_LF).

Source: OECD2,213 rowsUpdated: 9/21/2026
unemploymentlabourmacrooecdforecast

Quality

92.5

Attribution

OECD

Schema

ColumnTypeDescription
datestringObservation year (the TIME_PERIOD column of the OECD SDMX-CSV response), stored as the first day of the year.
series_idstringSDMX series key (<REF_AREA>.<MEASURE>), e.g. 'USA.GDPV_ANNPCT': the unique identifier of the series in the OECD Economic Outlook dataflow.
series_labelstringEconomy name from the OECD CL_AREA codelist, e.g. 'United States'.
valuefloatUnemployment as a percentage of the labour force (OECD measure UNR: "Unemployment rate"), for OECD members, G20 non-members and major aggregates. Includes the Outlook's two-year projections. Unit: percent of labour force (UNIT_MEASURE=PT_LF).

Sample rows

dateseries_idseries_labelvalue
1964-01-01AUS.UNRAustralia1.38532629813771
1965-01-01AUS.UNRAustralia1.25951796069311
1966-01-01AUS.UNRAustralia1.55550066825146
1967-01-01AUS.UNRAustralia1.87023617613434
1968-01-01AUS.UNRAustralia1.81318966160194

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/oecd/unemployment_rate_annual" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/oecd/unemployment_rate_annual").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/oecd/unemployment_rate_annual

Tip: fetch /llms.txt for the full machine-readable catalog.