Unique ID: 2015113

Division: Office of Information and Regulatory Affairs
Issue Date: February 13th 2019
Last modified: February 22nd 2019
Collaborative

Using administrative data to augment compensation surveys

Using administrative data to augment compensation surveys

This project matches national compensation survey (NCS) data with publicly available Form 5500 filings to augment information not collected as part of the NCS, to compare information collected in both sources, and to evaluate whether respondent burden can be reduced through the use of Form 5500 records. Additionally, we are now in the initial stages of trying to apply the matching approaches we have developed to new NCS Survey data as it is collected.

Project Objective:

Pilot intended to go to production to supplement existing data

Project Outcomes:

Improved data quality; reduced respondent burden; more efficient use of program resources.

Statistical Area

Demographic and social

Project Sources
Project Sources
Type Of Institution: National statistical office
Big Data Source: Other
Region: North America
Country Area: United States
Id Country Regional: country
Partnerships
Partnerships
Other Partners: Government institute
Accessing Data
Accessing Data
Data Access Rights: Broader access rights
Intermediary Comments: Currently our partner is funding a contractor to support the matching effort. Going forward we anticipate future matching can be performed internally using the algorithms being developed by the contractor.
Data Access Comments: The confidential data under this project is held by U.S. Bureau of Labor Statistics. Because we are matching with publicly available data, we can use the matched product very broadly.
Data Coverage
Data Coverage
Data Coverage: Only a portion of all data
Coverage Geo Pop: Whole country / high % of market
Cost Implication: Free
Coverage Geo Comments: Coverage limited only by match rate.
Coverage Period: 2010
Project Details
Project Details
Frequency Comments: There is not complete matching available.
Data Quality
Data Quality
Quality Framework: Quality of processing/throughput
Quality Aspects Evaluated: Privacy and Security, Completeness, Usability, Time Factors, Accuracy, including selectivity
Validation Comments: As the matched data are used in production, they will be exposed to the data validation processes that are part of the national compensation survey's design.
Quality Framework Comments: Our research in this project has been focused on the extent and quality of the matches between the data sources.
Methodology
Methodology
Methods Used: Traditional statistical methods
Technologies
Technologies
Technologies: Other
Technologies Comments: Algorithms developed using traditional statistical software
Other
Other
Income Level: High-income
Iso: US
Timeframe To Produce Indicator: NA
Frequency Comments: There is not complete matching available.
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