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Adjusting for Non-response in the Occupational Employment Statistics Survey
*Nicholas J. Horton, Smith College 
Polly A Phipps, Bureau Labor Statistics 
Daniell Toth, Bureau of Labor Statistics 

Keywords: administrative records data, propensity model, establishment survey, missing data, imputation

Past research indicates that employment size, industry sector, multi-establishment status, and metropolitan area size, along with important interactions, have a significant impact on an establishment’s propensity to respond to the Bureau of Labor Statistics Occupational Employment Statistics survey (OES). Using administrative wage data linked to the sample, we find that these establishment characteristics are related to wages; wage estimates are a major OES outcome variable. In this paper, we investigate the use of the administrative data for imputing missing data due to nonresponse. This imputation method focuses on adjusting the OES wage estimates with this auxiliary data to reduce potential bias.