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Industry by Occupation Earnings Data

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Ready to use this data? See the Core LMI reference documentation to get started.

Description

The dataset shows employment and percentile earnings by year, industry, and occupation for QCEW and Non-QCEW employees (excludes self-employed).

Use Cases

Questions answered by this dataset:

  • Which industry employs the most special effects animators?
  • What is the earnings difference for general contractors employed in residential vs nonresidential building construction?
  • What are the median earnings for purchasing managers working at nursing care facilities? How about the 75th percentile earnings?

Metrics

  • Jobs: The number of occupied positions. This is not quite the same as workers because one worker might fill more than one position.
  • Earnings
    • Average: Average hourly earnings per job.
    • Median: 50th percentile (median) hourly earnings per job.
    • Percentile10: 10th percentile hourly earnings per job.
    • Percentile25: 25th percentile hourly earnings per job.
    • Percentile50: 50th percentile (median) hourly earnings per job.
    • Percentile75: 75th percentile hourly earnings per job.
    • Percentile90: 90th percentile hourly earnings per job.
    • Average.Annual: Average annual earnings per job.
    • Median.Annual: 50th percentile (median) annual earnings per job.
    • Percentile10.Annual: 10th percentile annual earnings per job.
    • Percentile25.Annual: 25th percentile annual earnings per job.
    • Percentile50.Annual: 50th percentile (median) annual earnings per job.
    • Percentile75.Annual: 75th percentile annual earnings per job.
    • Percentile90.Annual: 90th percentile annual earnings per job.

Filters

  • Class of Worker (QCEW and Non-QCEW employees only)
  • Industry (6-digit NAICS)
  • Occupation (5-digit SOC)
  • Year

Core LMI Metadata

This dataset is offered via the Core LMI API. The metadata for this Core LMI API dataset is below.

AttributeDescription
Dataset IDEMSI.us.Staffing.Earn
Dataset URLhttps://agnitio.emsicloud.com/meta/dataset/EMSI.us.Staffing.Earn/{version}
Area Aggregation Path

The area aggregation path refers to the hierarchy that shows how data is aggregated, starting from the lowest-level geography and progressing to the highest-level geography.

The levels in the aggregation path include:

Aggregation Path
1234
Level 1NationMetropolitan USNationMetropolitan US
2 State MSA State MSA
3 County County County County
4 Zip Code Zip Code Census Tract Census Tract

Datasets with lower granularity aggregates only up to Level 1

Versions

http://agnitio.emsicloud.com/meta/dataset/EMSI.us.Staffing.Earn/2026.3

Metrics

  {
"name": "<Metric>.<Year>"
  }

Valid Values for Metrics

  {"Metric": [
        "Jobs",
        "Earnings.Average",
        "Earnings.Median",
        "Earnings.Percentile10",
        "Earnings.Percentile25",
        "Earnings.Percentile50",
        "Earnings.Percentile75",
        "Earnings.Percentile90",
        "Earnings.Average.Annual",
        "Earnings.Percentile10.Annual",
        "Earnings.Percentile25.Annual",
        "Earnings.Percentile50.Annual",
        "Earnings.Percentile75.Annual",
        "Earnings.Percentile90.Annual"
]
"Year": "2005-2025",
}

Dimensions

[
{
  "name": "ClassOfWorker",
  "levelsStored": [
     "2"
  ]
},
{
  "name": "Industry",
  "levelsStored": [
     "1",
     "2",
     "3",
     "4",
     "5",
     "6"
  ]
},
{
  "name": "Occupation",
  "levelsStored": [
     "1",
     "2",
     "3",
     "4",
     "5"
  ]
}
]

Attributes

{
"name": "Staffing.Earn",
"path": "Staffing.Earn",
"type": "dataset",
"countryCode": "us",
"description": "XXXXXXXXXXXXXXX",
"displayName": "US Industry by Occupation Earnings",
"minYearInclusive": "2005",
"maxYearInclusive": "2025",
"currentYear": "2025",
"releaseDate": "2026-06-04 02:19:12.1738593Z",
"datarun": "2026.3"
}

Updated about 4 hours ago

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