Diagnostic analysis and computational strategies for estimating discrete time duration models—A Monte Carlo study

Xianghong Li and Barry Smith

Journal of Econometrics, 2015, vol. 187, issue 1, 275-292

Abstract: This paper uses Monte Carlo analysis to study important and contentious issues in estimating single-spell discrete time duration models. We find simulated annealing dominates gradient methods for recovering true models. We recommend a partially flexible step function for duration dependence combined with likelihood ratio tests for determining support points of unobserved heterogeneity. We find that ignoring time-changing features of explanatory variables introduces substantial biases in model coefficient and average partial effect estimates. These biases do not diminish as sample size increases.

Keywords: Discrete time duration model; Monte Carlo; Simulated annealing; Duration dependence; Unobserved heterogeneity (search for similar items in EconPapers)
JEL-codes: C14 C15 C41 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:187:y:2015:i:1:p:275-292

DOI: 10.1016/j.jeconom.2015.02.024

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