Unique ID: 2015106
| Division: | Office of Information and Regulatory Affairs |
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| Issue Date: | February 13th 2019 |
| Last modified: | February 22nd 2019 |
Autocoding: using payroll systems data for labor market statistics
Using payroll systems data for labor market statistics
Autocoding job titles to allow receipt of electronic files with job titles and wage levels for each employee that can be converted to the US Standard Occupational Classification system. The goal is for firms to provide data in their format from their payroll / HR records and significantly reduce response burden
Project Objective:
Pilot intended to go to production to supplement existing data, Pilot intended to go to production to improve timeliness, Pilot intended to go to production to replace existing data
Project Outcomes:
Improve response rates, increase the quality of input data on wages (replace wage ranges with point estimates), and provide a basis for converting the sampling design from supporting representative estimates based on 3 years of data to an annual time series.
Publications Comments:
We are working closely with another U.S. Bureau of Labor Statistics office that currently does autocoding
Statistical Area
Project Sources
| Type Of Institution: | National statistical office |
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| Big Data Source: | Other |
| Region: | North America |
| Country Area: | United States |
| Id Country Regional: | country |
Partnerships
| Other Partners: | Other |
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| Partnership Comments: | Data are collected in partnership with State Labor Market Information offices. |
Accessing Data
| Data Access Rights: | Broader access rights |
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Data Coverage
| Data Coverage: | All available data |
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| Coverage Geo Pop: | Whole country / high % of market |
| Cost Comments: | These are survey costs that are being paid for by reducing paper form printing costs. |
| Coverage Period: | On going, starting in 2016 |
Data Quality
| Quality Framework: | Quality of output statistics |
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| Quality Aspects Evaluated: | Privacy and Security, Accessibility, Relevance, Institutional/Business Environment, Validity, Accuracy, including selectivity, Coherence, including linkability to other sources, Other |
| Validation Comments: | We use standard edit reconciliation processes. Autocoding occupations will use large data bases of prior job title / standard occupational classification matches to determine the efficacy of matches from current data. |
| Quality Framework Comments: | All quality aspects apply. We have a variety of statistical measures on quality for the program, inputs, process and outputs. |
| Data Quality Concerns Comments: | We are always concerned and we plan to examine the quality of our job title matches very closely |
| Quality Assessment Comments: | In addition to these traditional measures, we also have a number of process measures and measures related to the reduction of total survey error. |
Methodology
| Methods Used: | Machine learning (Random forest, etc.) |
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Technologies
| Technologies: | Other |
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| Technologies Comments: | We are developing the code for autocoding job titles in house |
Other
| Income Level: | High-income |
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| Iso: | US |
| Timeframe To Produce Indicator: | NA |