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A Heap of Trouble? Accounting for Mismatch Bias in Retrospectively Collected Data on Smoking

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  • Bar, H
  • Lillard, D

Abstract

When event data are retrospectively reported, more temporally distal events tend to get “heaped” on even multiples of reporting units. Heaping may introduce a type of attenuation bias because it causes researchers to mismatch time-varying right-hand side variables. We develop a model-based approach to estimate the extent of heaping in the data, and how it affects regression parameter estimates. We use smoking cessation data as a motivating example to describe our approach, but the method more generally facilitates the use of retrospective data from the multitude of cross-sectional and longitudinal studies worldwide that already have and potentially could collect event data.

Suggested Citation

  • Bar, H & Lillard, D, 2010. "A Heap of Trouble? Accounting for Mismatch Bias in Retrospectively Collected Data on Smoking," Health, Econometrics and Data Group (HEDG) Working Papers 10/20, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:10/20
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    File URL: https://www.york.ac.uk/media/economics/documents/herc/wp/10_20.pdf
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    1. Julio Del Corral & Carlos Pestana Barros & Juan Prieto-Rodríguez, 2008. "The Determinants of Soccer Player Substitutions," Journal of Sports Economics, , vol. 9(2), pages 160-172, April.
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    Keywords

    count data; drinking; endogenous participation; maximum simulated likelihood; sample selection; treatment effects;

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