Jenkins, Stephen P. Cappellari, Lorenzo Lynn, Peter Jäckle, Annette Sala, Emanuela
Year of Publication:
DIW Discussion Papers No. 490
We analyse consent patterns and consent bias in the context of a large general household survey, the ?Improving survey measurement of income and employment? (ISMIE) survey, also addressing issues that arise when there are multiple consent questions. Using a multivariate probit regression model for four binary outcomes with two incidental truncations, we show that there are biases in consent to data linkage with benefit and tax credit administrative records held by the Department for Work and Pensions, and with wage and employment data held by employers, and also in respondents? willingness and ability to supply their National Insurance Number. The biases differ according to the question considered, however. We also show that modelling consent questions independently rather than jointly may lead to misleading inferences about consent bias. A positive correlation between unobservable individual factors affecting consent to DWP record linkage and consent to employer record linkage is suggestive of a latent individual consent propensity.