Abstract

Summary Duration data derived from retrospective surveys often show an abnormal concentration of responses at certain durations. This common kind of measurement error is known as “heaping” in the statistical literature. We show how heaping effects can be modelled within a maximum likelihood framework using external validation information and demonstrate how parameter estimates in discrete-time proportional hazard models are affected by alternative specifications of the heaping mechanism. The model is applied to unemployment duration data derived from the retrospective calendar information in the German Socio-Economic Panel. Our main result is that parameter estimates are generally rather insensitive to whether or not heaping is explicitly taken into account and to different assumptions about the heaping mechanism.

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