Heap: A Command for Estimating Discrete Outcome Variable Models in the Presence of Heaping at Known Points
Posted: 31 Aug 2018
Date Written: July 25, 2018
Self-reported survey data are often plagued by the presence of heaping. Accounting for this measurement error is crucial for the identification and consistent estimation of the underlying model (parameters) from such data. This paper introduces two Stata commands. The first command, heapmph, estimates the parameters of a discrete-time mixed proportional hazard model with gamma unobserved heterogeneity, allowing for fixed and random right censoring, and different sized heap points. The second command, heapop, extends the framework to ordered probability models, subject to heaping. Suitable specification tests are also provided.
Keywords: st0001, heap, heapmph, heapop, Discrete Time Duration Model, Heaping, Measurement Error, Ordered Probability Model
JEL Classification: C25, C41, C87
Suggested Citation: Suggested Citation