Symmetric Coefficients of Variation for Binomial Estimates

Thomas M. Menino Convention & Exhibition Center 

Dating back decades, the U.S. Bureau of Labor Statistics (BLS) determines the publishability of Current Population Survey (CPS) labor force statistics by the weighted size of the estimation base. Recently, the effectiveness of this publication rule has attenuated as response rates have declined from around 95 percent to less than 70 percent, leading the BLS to seek more robust data quality standards based on coefficients of variation (CVs), as recommended in U.S. Census Bureau Statistical Quality Standards. However, CVs for binomial data, like labor force participation or unemployment rates, are inherently asymmetric, as the CV of a rate p and its complement 1-p can be quite different despite having equal variances. In this paper, we propose the geometric mean of CV(p) and CV(1-p) as a symmetric coefficient of variation for binomial estimates, resulting in publication standards that only depend on design effects and response counts, and demonstrate its relative stability compared to CV(p).

Current Population Survey

coefficient of variation

symmetric CV

binomial

geometric mean

design effect 

Survey Research Methods Section