Lightcast uses labor market data to connect and inform people, education, and employers. Lightcast gathers and integrates economic, labor market, demographic, and education data from dozens of government and private-sector sources, creating a comprehensive and current database that includes both published data and detailed estimates with full coverage of the United States.

With Lightcast Global we work to marry the different countries data sets across geographies so we lose some granularity in the process. If you’re interested in extremely granular skill sets, compensation and zip code type detail, please check out our US focused tool called Analyst.

The following is a list of Lightcast's data sources.

Bureau of Labor Statistics

• Current Employment Statistics (CES)

• Local Area Unemployment Statistics (LAUS)

• National Employment Projections

• Occupational Employment Statistics (OES)

• Quarterly Census of Employment and Wages (QCEW)

• National Industry-Occupation Employment Matrix (NIOEM)

• Occupational Education and Training Projections

Census Bureau

• American Community Survey (ACS)

• County Business Patterns (CBP)

• Current Population Survey (CPS)

• Non-Employer Statistics (NES)

• Quarterly Workforce Indicators (QWI)

• TIGER/Line Map File

• ZIP Code Business Patterns (ZBP)

• LEHD Origin-Destination Employment Statistics (LODES)

• Population Estimates

• U.S. National and State Population Projections

• Census 2000 & 2010 Summary Files

• Census of Government-State and Local

Department of Labor, Education and Training Administration

• Characteristics of the Insured Unemployed (CIU)

• O*NET Database

Occupation data in the United States is generally less complete and reliable than industry data. Accordingly, Lightcast occupation data are built by applying staffing patterns to industry data. Staffing patterns show the percentage occupational makeup of jobs within each industry. The primary sources for the staffing patterns Lightcast uses to create occupation data are Occupational Employment Statistics (OES) from the BLS, and the Census Bureau’s American Community Survey.

Creating Staffing Patterns for QCEW/Non-QCEW Employee Jobs: First, we obtain the most recent available OES staffing pattern and OES metro-level occupation data, and unsuppress them. Next, we use metro-level QCEW-based industry data (made compatible with OES coverage), the national OES staffing pattern, and OES metro-level occupation totals to “regionalize” the national staffing pattern, which means adjusting its percentages to match the local industry/occupation totals. Next, we add in national staffing patterns from ACS microdata for industries that OES does not cover. Due to differences in definitions and coverage, Lightcast's final national staffing pattern does differ from both OES and NIOEM.

Finally, staffing patterns for each historical year are created by back-chaining and adjusting the staffing pattern from the following year. The latest available staffing pattern is not adjusted to any other year’s staffing pattern but is the ultimate origin for all prior years’ staffing patterns. Due to changes in the structure of OES data, Lightcast does not use OES data prior to 2005. The staffing patterns for 2001-2004 are created by back-projecting the 2005 staffing pattern.

Creating Staffing Patterns for Self-Employed: For self-employment, Lightcast creates a national staffing pattern using ACS microdata. Certain aggregated occupation categories are broken out to more detailed levels using ratios from OES. This national staffing pattern is used for all counties, due to lack of geographically detailed information for the self-employed (ACSbased state staffing patterns generally have too small of sample size). The ACS staffing pattern is also back-projected from 2004 to 2001, and forward projected to the standard Lightcast projection year (typically 10 years beyond the present).

In the United States, occupational labor market data are classified using the Standard Occupation Classification (SOC). Like NAICS, SOC is hierarchical. It uses hyphenated six-digit codes to divide occupations into four levels: major groups, minor groups, broad occupations, and detailed occupations. We map the SOC’s to to Global Occupations.

O*NET is another resource for occupation data in the United States. It extends the SOC hierarchy to an additional level of detail and adds information about knowledge, skills, and abilities (KSAs), and education levels by occupation. O*NET is maintained under the sponsorship of the U.S. Department of Labor/Employment and Training.