Diagnostic Analysis and Computational Strategies for Estimating Single Spell Discrete Time Duration Models – A Monte Carlo Study

53 Pages Posted: 2 Dec 2009 Last revised: 5 Dec 2009

See all articles by Xianghong Li

Xianghong Li

York University - Department of Economics

J. Barry Smith

York University - Department of Economics

Date Written: June 1, 2009

Abstract

This extensive Monte Carlo study re-examines properties of the nonparametric maximum likelihood estimator of discrete duration models with unobserved heterogeneity and unknown duration dependence. Alternative specifications and computation strategies are compared. We find: i) The inherent complexity of mixture models poses the major estimation hurdle. ii) It is important to choose a flexible specification for duration dependence. Polynomial specifications with a fixed number of terms can lead to systematically biased estimates of the hazard. iii) In estimation, simulated annealing is found to dominate all other optimization algorithms. Common applied research problems, such as near-boundary false optima are eliminated. iv) A bootstrap procedure is suggested to help choose the number of support points of unobserved heterogeneity. v) Likelihood ratio tests may still be appropriate especially when there are many common parameters in the components of the model. vi) Gateaux derivatives do not appear to help optimize the likelihood function.

Keywords: NPMLE, Discrete duration model

JEL Classification: C41, C14, C15

Suggested Citation

Li, Xianghong and Smith, J. Barry, Diagnostic Analysis and Computational Strategies for Estimating Single Spell Discrete Time Duration Models – A Monte Carlo Study (June 1, 2009). Available at SSRN: https://ssrn.com/abstract=1515271 or http://dx.doi.org/10.2139/ssrn.1515271

Xianghong Li (Contact Author)

York University - Department of Economics ( email )

4700 Keele St.
Toronto, Ontario M3J 1P3
Canada

J. Barry Smith

York University - Department of Economics ( email )

4700 Keele St.
Toronto, Ontario M3J 1P3
Canada

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