Nonresponse and Measurement Error in Employment Research: Making Use of Administrative Data

Linking paradata from a survey on labor market participation to administrative data, this article has a unique opportunity to examine nonresponse and measurement error jointly and provide estimates for bias, variance, and mean square error. We find that increased contact attempts resulted in significant reductions in nonresponse bias. Measurement error increased somewhat with increased effort, though total bias was nevertheless reduced. One of the key survey indicators revealed an interesting case of counteracting effects of nonresponse and measurement error whereby increased effort to recruit nonrespondents led to an increase in mean square error with increased level of effort despite a reduction in nonresponse bias and constant measurement error.