Factors influencing the severity of damage in bus accidents in Turkey during 2002: An application of the ordered probit model

This paper presents an application of the ordered probit model to bus accident data to reveal the most significance factors that affect the severity of vehicle damage. Data recorded by The Department of Traffic Training and Research of the General Directorate of Security Affairs of Turkey for the year 2002 was used. The dependent variable was determined as the severity of damage, and was classified according to four levels: "No damage", "Little damage", "Medium damage" and "High damage". In view of the ordinality of the dependent variable, the use of the ordered probit model was preferred. The results suggest that, all variables indicating specific locations of the accident, having an accident at night or in bad weather conditions increase the severity of damage. On the contrary, travelling in the same direction in two-vehicle accidents, bumping into another vehicle from one side and those accidents classified as "other types of accident" lead to non-severe damage. Additionally, the severity of damage decreases for drivers graduated from high school.

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[1] Borooah, V. K. Logit and Probit (Ordered and Multinomial Models) (Sage University Papers,London, 07-138, 2002).
[2] Greene, W.H. LIMDEP Version 7.0 User's Manual (Bellport: Econometric Software Inc,1995).
[3] Greene, W. H. Econometric Analysis (New York University, Prince Hall, Upper Saddle River,New Jersey 07458, ISBN: 0-13-013297 7, 2000).
[4] Khattak, A. J., Schneider, R. J. and Targa, F. Risk factors in large truck rollovers and injury severity: Analysis of single-vehicle collisions, Transportation Research Board 82nd Annual Meeting, Washington, D.C., 2002.
[5] Kockelman, K. M. and Kweon, Y. J. Driver injury severity: An application of ordered probit models, Accident Analysis and Prevention 34, 313-321, 2002.
[6] Long, J. S. Regression Models for Categorical and Limited Dependent Variables (Sage Publications, Advance Qualitative Techniques in the Social Sciences Series; No:7, Thousand Oaks, London, 1997).
[7] Maddala, G. S. Limited-Dependent and Qualitative Variables in Econometrics, Econometric Society Monographs 3 (Cambridge University Press, 1983).
[8] O'Donnell, C. J. and Connor, D. H. Predicting the severity of motor vehicle accident injuries using models of ordered multiple choice, Accident Analysis and Prevention, 28(6), 739-753,1996.
[9] Powers, D. A. and Xie, Y. Statistical Methods for Categorical Data Analysis (Academic Press, 2000).
[10] Quddus, M.A., Noland, R. B. and Chin, H. C. An analysis of motorcycle injury and vehicle damage severity using ordered probit models, Journal of Safety Research 33, 445-462, 2002.