Labor QC clean AI-training-safe

Global Average Wages (OECD)

What a full-time job actually pays, comparably, across the OECD: the average annual wage per country in current and constant purchasing-power-parity USD (and current USD), one row per country × measure × year since 2000. The cross-country real-wage series behind every cost-of-labour, living-standards and competitiveness comparison - the US, Japan, Germany, Korea and every member. Licence-clean and AI-training-safe.

1K
rows
38
zones
2000-2025
coverage
0.1 MB
download
Source
OECD
Licence
Redistributable open data
Updates
Annual
Data through
2025-01-01
Quality
QC clean · 0 failures
Format
Apache Parquet + dictionary

Safe to train on

Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.

What's included

  • Average annual wage - current USD PPP, constant USD PPP, and current USD
  • Every OECD country, annual, since 2000 - cross-country comparable
  • The real-wage / cost-of-labour benchmark for living-standards & competitiveness
  • One row per country × measure × year; joins to unemployment/inflation on ISO-3
  • Licence-clean & AI-training-safe - OECD (CC-BY-4.0)

Schema

ColumnTypeDescriptionFilledDistinct
zone str ISO-3 country code (USA, DEU, JPN, …) 100.0% 38
ts timestamp (UTC) Year 100.0% 26
series str Avg annual wage: current USD PPP / constant USD PPP / current USD 100.0% 2
value float Average annual wage 100.0% 993
unit str Unit 100.0% 2
res_min int Native resolution (annual) 100.0% 1

Sample & preview

Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: OECD (redistributable open data; attribution passes through - see our Licence).

Don't trust screenshots - drop the sample into your notebook right now.

import pandas as pd
df = pd.read_parquet("global-wages-oecd_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join
⬇ Download free Parquet sample or CSV for Excel
Coverage: 38 zones

AUS · AUT · BEL · CAN · CHE · CHL · COL · CRI · CZE · DEU · DNK · ESP · EST · FIN · FRA · GBR · GRC · HUN · IRL · ISL · ISR · ITA · JPN · KOR · LTU · LUX · LVA · MEX · NLD · NOR · NZL · POL · PRT · SVK · SVN · SWE · TUR · USA

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