A dual frailty model for lifetime analysis in maritime transportation

Robin Henderson (), Ralitsa Mihaylova () and Paul Oman ()
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Robin Henderson: Newcastle University
Ralitsa Mihaylova: Newcastle University
Paul Oman: Northumbria University

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2019, vol. 25, issue 4, No 9, 739-756

Abstract: Abstract We consider changes in ownership of commercial shipping vessels from an event history perspective. Each change in ownership can be influenced by the properties of the vessel itself, its age and history to date, the characteristics of both the seller and the buyer, and time-varying market conditions. Similar factors can affect the process of deciding when to scrap the vessel as no longer being economically viable. We consider a multi-state approach in which states are defined by the owning companies, a sale marks a transition, and scrapping of the vessel corresponds to moving to an absorbing state. We propose a dual frailty model that attempts to capture unexplained heterogeneity in the data, with one frailty term for the seller and one for the buyer. We describe a Monte Carlo Markov chain estimation procedure and verify its accuracy through simulations. We investigate the consequences of mistakenly ignoring frailty in these circumstances. We compare results with and without the inclusion of frailty.

Keywords: Bayes; Clarksea index; Ownership duration; Partial likelihood; Proportional intensity; Random effects; Sentiment (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10985-019-09463-3

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