Labor market data: 9 sources and APIs compared (2026)

Labor market data comes in two fundamentally different shapes. Official statistics - government surveys like the BLS jobs report - are rigorous, free, and one to two months behind reality. Postings-derived data - built from the job ads companies publish - is real-time, granular to a single company, and either expensive or do-it-yourself. Most confusion about “where do I get labor market data” dissolves once you know which shape your problem needs.

Here are the nine sources that cover the field in 2026, what each actually measures, and which one fits which job.

Official statistics: the survey-based sources

• BLS Current Population Survey (CPS) - the monthly household survey behind the unemployment rate. The benchmark for labor-force participation and employment levels. Free, monthly, aggregated to demographics and geography.
• BLS JOLTS - the Job Openings and Labor Turnover Survey: openings, hires, quits, and layoffs by industry. The official measure of labor demand. Free, monthly, with roughly a one-month publication lag and industry-level granularity only.
• BLS OEWS - Occupational Employment and Wage Statistics: employment and wage distributions for 800+ occupations. The wage benchmark. Free, but annual - useless for anything moving quarter to quarter.
• FRED - the St. Louis Fed’s aggregator. Not a primary source, but the most convenient API for official series: one key, thousands of labor series, clean JSON.

Use these when you need methodological rigor, long time series, or numbers a policy or research audience will accept. Their structural limits: publication lag measured in months, aggregation that stops at industry or occupation level, and no visibility into any individual company.

Postings-derived data: the real-time sources

• Indeed Hiring Lab - free published indexes of posting volume by sector and country, built from Indeed’s own listings. Great for trend charts; you get their aggregates, not the underlying postings.
• LinkedIn Economic Graph - published workforce reports and hiring-rate data from LinkedIn’s network. Similar deal: useful aggregates, no raw data access for most organizations.
• Lightcast - the enterprise standard for postings analytics (formed from Emsi and Burning Glass). Deep occupation and skill taxonomies over decades of collected postings. Sales-led, typically five-to-six-figure annual contracts.
• LinkUp and Revelio Labs - postings and workforce datasets sold primarily to investors and corporate strategy teams. LinkUp indexes jobs directly from employer sites; Revelio models workforce flows from public profiles and postings. Both sales-led.
• Raw job-postings APIs - the build-your-own tier. Instead of buying someone’s aggregates, you pull the postings themselves - per company, per role, per day - and compute exactly the metric your product needs.

Which source for which job

• Academic or policy research - BLS and FRED. The lag is acceptable; the methodology is the point.
• Market sizing and skills taxonomy work - Lightcast if the budget exists; OEWS for the free wage baseline.
• Investment signals - LinkUp or Revelio, which are shaped (and priced) for that buyer.
• Trend content and dashboards - Indeed Hiring Lab and Economic Graph aggregates are free and citable.
• Products and GTM workflows - anything that needs company-level, current-week data (who is hiring, for what, right now) needs raw postings. Aggregates cannot answer per-company questions, and official statistics are structurally too slow.

Building on raw postings data

The raw-postings tier used to mean running your own scrapers across thousands of career sites. That is the layer JobsPipe’s jobs API replaces: postings from 30+ ATS and job-board sources - Workday, Greenhouse, Lever, Ashby, and the rest - normalized into one schema, refreshed within 24 hours, with structured salary, resolved locations, cross-source dedup, and webhooks on new postings. It is the same upstream data the commercial analytics vendors collect, exposed as an API you can build on directly. Our job posting API post covers the data model in detail.