📊 OECD Statistics Scraper

🚀 Export OECD economic and social statistics in seconds. Pull observations from 1,500+ OECD datasets including Quarterly National Accounts, Economic Outlook, Main Economic Indicators, and the Better Life Index. No sign-up needed.

The OECD Statistics Scraper pulls flat, row-per-observation data from the official OECD statistics catalogue. Every observation row carries the dataset identifier, series key, full set of dimension codes plus their human-readable labels, the time period, the value, and any series- or observation-level attributes. The underlying catalogue is the gold-standard source for cross-country economic and social comparisons and is cited by central banks, finance ministries, and academic researchers worldwide.

Coverage spans 1,500+ datasets across national accounts, prices, productivity, labour, education, health, environment, R&D, and well-being. Use the catalogue mode to enumerate every dataset (id, agency, version, name) in a single run, then switch to data mode with a dataset id and series key to pull observations. Download as CSV, Excel, JSON, or XML in under three minutes.

🎯 Target Audience	💡 Primary Use Cases
Macro economists, central-bank researchers, finance ministries, ESG analysts, academics, data journalists, policy think tanks	Cross-country GDP comparisons, inflation tracking, productivity benchmarks, well-being index dashboards, time-series forecasting inputs

📋 What the OECD Statistics Scraper does

Two operating modes share a single input form:

• 📚 Catalogue mode. Enumerate every OECD dataset (id, agency, version, English name) so you can discover what's available before drilling into the data.
• 📈 Data mode. Supply a dataset id (QNA, EO, MEI, KEI, SNA_TABLE1, BLI, EMP_LF, PPP, PRICES_CPI, GBARD, MSTI_PUB and more) plus an optional series key, start time, and end time to pull observations.

Each observation row carries the dataset id, series key, time identifier and label, derived year/quarter/month, the numeric value, plus every dimension as a code+label pair, and any series or observation attributes (status, unit multiplier, base year). One row per observation, ready to load straight into a dataframe.

💡 Why it matters: OECD data is the standard reference for cross-country macro and social comparisons. Building your own pipeline means parsing complex hierarchical envelopes, joining dimension lookups, and refreshing manually. This Actor flattens everything into a plain table on every run.

⚠️ Good to Know: series keys are positional and dot-separated. Each dataset has its own dimension order, so if you're unsure of the structure, run a small unfiltered query first (empty seriesKey) and inspect the dimension code/label fields in the result. Some legacy dataset ids have been retired or renamed in newer OECD releases.

🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the OECD Statistics Scraper page on the Apify Store.
3. 🎯 Set input. Pick a mode, supply a dataset id and optional series key plus time range.
4. 🚀 Run it. Click Start and let the Actor collect your observations.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from sign-up to downloaded dataset: 3-5 minutes. No coding required.

🔗 Recommended Actors

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• 📈 Indexmundi Scraper - Global demographic and economic indicators
• 📊 World Bank Open Data Scraper - Cross-country development indicators
• 🌍 Eurostat Scraper - European Union official statistics
• 🏛️ FRED Economic Data Scraper - U.S. Federal Reserve economic time series

💡 Pro Tip: browse the complete ParseForge collection for more reference-data scrapers.

⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by the OECD. All trademarks mentioned are the property of their respective owners. Only publicly available open OECD statistics are collected.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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