A Prediction/Pseudo-Empirical Likelihood Raking Approach to Estimating Small-Area Occupational Employment Change Over Time

• Activity Number: 409
• Type: Contributed
• Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Section on Government Statistics
• Author(s): Jane Osburn*+
• Companies: Bureau of Labor Statistics
• Keywords: pseudo empirical likelihood ; small area estimation

Abstract

The Bureau of Labor Statistics Occupational Employment Statistics Survey produces estimates of occupational wages and employment for domains including all US MSAs and balance-of-State areas. Although the OES is designed as a cross-sectional survey, its size together with recent innovations in statistical/ computing methods make feasible estimators of the change in small area occupational employment over time on the scale of a large survey. The analyses use a zero-inflated binomial logistic-normal model to obtain, for each year separately, the best empirical prediction estimate of the proportion of total area /industry cell employment in each occupation. The Pseudo Empirical Likelihood alternative to raking is then used to constrain the marginal sums of the estimates to equal 1) relatively accurate estimates of occupational employment shares estimated at more aggregated levels, and 2) known population quantities at the area level. Two modifications of this estimator are also examined, including one that incorporates a size-adjustment weighting scheme, and another that uses a single average variance component in the composite estimators, obviating the need for raking.