Heap: A Command for Estimating Discrete Outcome Variable Models in the Presence of Heaping at Known Points

Posted: 31 Aug 2018

See all articles by Wiji Arulampalam

Wiji Arulampalam

University of Warwick - Department of Economics; IZA Institute of Labor Economics

Valentina Corradi

University of Surrey - School of Economics

Daniel Gutknecht

Goethe University Frankfurt

Zizhong Yan

Jinan University - Institute for Economic and Social Research

Date Written: July 25, 2018

Abstract

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

Arulampalam, Wiji and Corradi, Valentina and Gutknecht, Daniel and Yan, Zizhong, Heap: A Command for Estimating Discrete Outcome Variable Models in the Presence of Heaping at Known Points (July 25, 2018). Available at SSRN: https://ssrn.com/abstract=3219651

Wiji Arulampalam

University of Warwick - Department of Economics ( email )

Coventry CV4 7AL
United Kingdom
01203 523471 (Phone)
01203 523032 (Fax)

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Valentina Corradi

University of Surrey - School of Economics ( email )

Guildford
Guildford, Surrey GU2 5XH
United Kingdom

Daniel Gutknecht

Goethe University Frankfurt ( email )

Frankfurt am Main, 60629
Germany

Zizhong Yan (Contact Author)

Jinan University - Institute for Economic and Social Research ( email )

601 West Whampoa Road
Tianhe District
Guangzhou, 510632
China

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