Reconciling reports: modelling employment earnings and measurement errors using linked survey and administrative data

Abstract We develop and apply new statistical models for linked survey and administrative data on employment earnings, incorporating 4 types of measurement error. In addition, we allow error distributions to differ with individual characteristics, which improves model fit and allows us to investigate substantive hypotheses about factors associated with error bias and variance. Contributing the first UK evidence to a field dominated by findings about the USA, we show that measurement errors are pervasive, but the 4 types are quite different in nature. We also document substantial heterogeneity in each of the error distributions.