Exploratory analysis of motorcycle holding time heterogeneity using a split-population duration model
This study integrated the samples taken in 2000 for motorcycle usage and their corresponding records registered in the Taiwan's Vehicle Registration System to observe the survival process of motorcycle ownership. The specific heterogeneity of censored observations that failed to demonstrate actual ownership status in the registration system was corrected by employing a split-population duration model with a Weibull hazard function. The results indicated that around 11% of all observations would never experience an eventual registration termination and that the hazard rates of terminating motorcycle ownership grew at a slightly increasing rate as the holding time increased. Ways of enhancing the accuracy of the motorcycle registration system and accelerating the elimination mechanisms for old motorcycles should be carefully examined.
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Volume (Year): 41 (2007)
Issue (Month): 6 (July)
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References listed on IDEAS
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- Peter Schmidt & Ann Dryden Witte, 1987.
"Predicting Criminal Recidivism Using "Split Population" Survival Time Models,"
NBER Working Papers
2445, National Bureau of Economic Research, Inc.
- Schmidt, Peter & Witte, Ann Dryden, 1989. "Predicting criminal recidivism using 'split population' survival time models," Journal of Econometrics, Elsevier, vol. 40(1), pages 141-159, January.
- Bandopadhyaya, Arindam & Jaggia, Sanjiv, 2001. "An analysis of second time around bankruptcies using a split-population duration model," Journal of Empirical Finance, Elsevier, vol. 8(2), pages 201-218, May.
- Jong, Gerard De, 1996. "A disaggregate model system of vehicle holding duration, type choice and use," Transportation Research Part B: Methodological, Elsevier, vol. 30(4), pages 263-276, August.
- Yamamoto, Toshiyuki & Kitamura, Ryuichi, 2000. "An analysis of household vehicle holding durations considering intended holding durations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 339-351, June.
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