Labour Force Status Estimates under a Bivariate Random Components Model

摘要

Models for a multi-category response data, labour force status, based on a generalized linear model specification typically assume that the regression coefficients to be varied with the response category. However, they can be extended to random components by allowing the area random effects to be depended on response category. In this paper, we describe a multinomial linear mixed model with a bivariate random component in estimating totals of the inactive, unemployed and employed people at Local Authority District (LAD) level. The random effects are assumed to follow a bivariate normal distribution. The model parameters including variance components and correlation coefficient are estimated by maximum and residual maximum likelihood methods. The estimated parameters and predicted values of the LAD (area) random effects are then used in calculating the empirical best linear unbiased-type estimates. The mean squared error estimates are obtained by using an analytical approximation approach. The application is the UK LFS data in Molina et al. (2007) and estimates are compared with the results in that paper. A simulation study demonstrates a good performance of the proposed model.