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Modelling Road Traffic Crashes Using Spatial Autoregressive Model With Additional Endogenous Variable

Author

Listed:
  • Olubusoye Olusanya Elisa

    (Department of Statistics, University of Ibadan, Oyo State, Nigeria)

  • Korter Grace Oluwatoyin

    (Department of Statistics, University of Ibadan, Oyo State, Nigeria)

  • Salisu Afees Adebare

    (Department of Economics, University of Ibadan, Oyo State, Nigeria)

Abstract

Road traffic crashes have become a global issue of concern because of the number of deaths and injuries. The model of interest is a linear cross sectional Spatial Autoregressive (SAR) model with additional endogenous variables, exogenous variables and SAR disturbances. The focus is on RTC in Oyo state, Nigeria. The number of RTC in each LGA of the state is the dependent variable. A 33×33 weights matrix; travel density; land area and major road length of each LGA were used as exogenous variables and population was the IV. The objective is to determine the hotspots and examine whether the number of RTC cases in a given LGA is affected by the number of RTC cases of neighbouring LGAs and an instrumental variable. The hotspots include Oluyole, Ido, Akinyele, Egbeda, Atiba, Oyo East, and Ogbomosho South LGAs. The study concludes that the number of RTC in a given LGA is affected by the number of RTC in contiguous LGAs. The policy implication is that road safety and security measures must be administered simultaneously to LGAs with high concentration of RTC and their neighbours to achieve significant remedial effect.

Suggested Citation

  • Olubusoye Olusanya Elisa & Korter Grace Oluwatoyin & Salisu Afees Adebare, 2016. "Modelling Road Traffic Crashes Using Spatial Autoregressive Model With Additional Endogenous Variable," Statistics in Transition New Series, Polish Statistical Association, vol. 17(4), pages 659-670, December.
    • Handle: RePEc:vrs:stintr:v:17:y:2016:i:4:p:659-670:n:9
    DOI: 10.21307/stattrans-2016-045
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    1. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
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    Cited by:

    1. Tingting Huang & Gilbert Saporta & Huiwen Wang & Shanshan Wang, 2021. "A robust spatial autoregressive scalar-on-function regression with t-distribution," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(1), pages 57-81, March.

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