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

H Bar and D Lillard

Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York

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.

Keywords: count data; drinking; endogenous participation; maximum simulated likelihood; sample selection; treatment effects (search for similar items in EconPapers)
Date: 2010-07
New Economics Papers: this item is included in nep-ecm and nep-hea
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Persistent link: https://EconPapers.repec.org/RePEc:yor:hectdg:10/20

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