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An Application of Non–Ignorable Non–Response Models for Gross Flows Estimation in the British Labour Force Survey

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  • Paul S. Clarke
  • P. F. Tate

Abstract

In previous work, non–response adjustments based on calibration weighting have been proposed for estimating gross flows in economic activity status from the quarterly Labour Force Survey. However, even after adjustment there may be residual non–response bias. The weighting is based on estimates of cross–sectional distributions and so cannot adjust for bias if non–response is associated with individual flows between quarters. To investigate this possibility, it was decided to apply models for estimating gross flows when non–response depends on the flows. This paper has two aims: first to describe the many problems encountered when attempting to implement these models; and second to outline a solution to the major problem that arose, namely, that comparing the model results directly with the weighting results was not possible. A simulation study was used to compare the results indirectly and it was tentatively concluded that non–response is not strongly associated with the flows and that the weighting provides an adequate adjustment.

Suggested Citation

  • Paul S. Clarke & P. F. Tate, 2002. "An Application of Non–Ignorable Non–Response Models for Gross Flows Estimation in the British Labour Force Survey," Australian & New Zealand Journal of Statistics, Australian Statistical Publishing Association Inc., vol. 44(4), pages 413-425, December.
  • Handle: RePEc:bla:anzsta:v:44:y:2002:i:4:p:413-425
    DOI: 10.1111/1467-842X.00243
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    Cited by:

    1. Rendtel, Ulrich & Basic, Edin, 2007. "Assessing the bias due to non-coverage of residential movers in the German microcensus panel: an evaluation using data from the socio-economic panel," Discussion Papers 2007/6, Free University Berlin, School of Business & Economics.
    2. Edin Basic & Ulrich Rendtel, 2007. "Assessing the bias due to non-coverage of residential movers in the German Microcensus Panel: an evaluation using data from the Socio-Economic Panel," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 91(3), pages 311-334, October.

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