IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v118y2018icp594-607.html
   My bibliography  Save this article

Evaluating the effects of the road safety system approach in Brunei

Author

Listed:
  • Haque, M. Ohidul
  • Haque, Tariq H.

Abstract

The main objective of this study is to evaluate the effects of the Road Safety System Approach on serious road casualties: fatalities and serious injuries in Brunei (target group), using the Auto Regressive Integrated Moving Average (ARIMA) and Intervention Time Series Analysis methods with control group. Control group is used to consider the influences of other factors which have been eliminated prior to estimating the net effect of the Road Safety System Approach for the target group relative to the control group. It is found that a significant reduction in serious road casualties of 30% was achieved for the first 12-months after the introduction of the Road Safety System Approach through the reformed road safety initiatives in Brunei. This shows that Brunei’s road safety record is now similar to other high road safety performing countries. Brunei can also now be considered as a model for the trajectory of road safety in the entire South East Asian region.

Suggested Citation

  • Haque, M. Ohidul & Haque, Tariq H., 2018. "Evaluating the effects of the road safety system approach in Brunei," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 594-607.
  • Handle: RePEc:eee:transa:v:118:y:2018:i:c:p:594-607
    DOI: 10.1016/j.tra.2018.08.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856418303793
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2018.08.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jung, Soyoung & Qin, Xiao & Oh, Cheol, 2016. "Improving strategic policies for pedestrian safety enhancement using classification tree modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 53-64.
    2. Taylor, A M Robert, 2003. "Robust Stationarity Tests in Seasonal Time Series Processes," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 156-163, January.
    3. Bu, Ruijun & McCabe, Brendan, 2008. "Model selection, estimation and forecasting in INAR(p) models: A likelihood-based Markov Chain approach," International Journal of Forecasting, Elsevier, vol. 24(1), pages 151-162.
    4. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
    5. Law, Teik Hua & Noland, Robert B. & Evans, Andrew W., 2011. "The sources of the Kuznets relationship between road fatalities and economic growth," Journal of Transport Geography, Elsevier, vol. 19(2), pages 355-365.
    6. Canova, Fabio & Hansen, Bruce E, 1995. "Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 237-252, July.
    7. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178, Decembrie.
    8. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    9. Frits Bijleveld & Jacques Commandeur & Siem Jan Koopman & Kees van Montfort, 2010. "Multivariate non‐linear time series modelling of exposure and risk in road safety research," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(1), pages 145-161, January.
    10. A. M. Robert Taylor, 1998. "Testing for Unit Roots in Monthly Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(3), pages 349-368, May.
    11. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    12. Osborn, Denise R. & Heravi, Saeed & Birchenhall, C. R., 1999. "Seasonal unit roots and forecasts of two-digit European industrial production," International Journal of Forecasting, Elsevier, vol. 15(1), pages 27-47, February.
    13. Hylleberg, Svend, 1995. "Tests for seasonal unit roots general to specific or specific to general?," Journal of Econometrics, Elsevier, vol. 69(1), pages 5-25, September.
    14. Aruna Chandran & Ricardo Pérez-Núñez & Abdulgafoor M Bachani & Martha Híjar & Aarón Salinas-Rodríguez & Adnan A Hyder, 2014. "Early Impact of a National Multi-Faceted Road Safety Intervention Program in Mexico: Results of a Time-Series Analysis," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-7, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Paulo Rodrigues & Denise Osborn, 1999. "Performance of seasonal unit root tests for monthly data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 985-1004.
    2. Gabriel Pons Rotger, 2004. "Seasonal Unit Root Testing Based on the Temporal Aggregation of Seasonal Cycles," Economics Working Papers 2004-1, Department of Economics and Business Economics, Aarhus University.
    3. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    4. CÁCERES HERNÁNDEZ, José Juan & CANO FERNÁNDEZ, Víctor J. & MARTÍN ÁLVAREZ, Francisco J., 2001. "Observaciones anómalas y contrastes de raíz unitaria en datos semanales," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 17, pages 85-105, Abril.
    5. Ikerne Valle & Kepa Astorkiza & Ignacio Díaz-Emparanza, 2017. "Measuring species concentration, diversification and dependency in a macro-fishery," Empirical Economics, Springer, vol. 52(4), pages 1689-1713, June.
    6. del Barrio Castro Tomás & Osborn Denise R, 2011. "Nonparametric Tests for Periodic Integration," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-35, February.
    7. Evren Erdoğan Cosar, 2006. "Seasonal behaviour of the consumer price index of Turkey," Applied Economics Letters, Taylor & Francis Journals, vol. 13(7), pages 449-455.
    8. Guglielmo M. Caporale & Luis A. Gil‐Alana, 2004. "Testing for Seasonal Fractional Roots in German Real Output," German Economic Review, Verein für Socialpolitik, vol. 5(3), pages 319-333, August.
    9. Rodrigues, Paulo M. M. & Taylor, A. M. Robert, 2004. "Alternative estimators and unit root tests for seasonal autoregressive processes," Journal of Econometrics, Elsevier, vol. 120(1), pages 35-73, May.
    10. Ghassen El Montasser, 2015. "The Seasonal KPSS Test: Examining Possible Applications with Monthly Data and Additional Deterministic Terms," Econometrics, MDPI, vol. 3(2), pages 1-16, May.
    11. L. A. Gil-Alana & P. M. Robinson, 2001. "Testing of seasonal fractional integration in UK and Japanese consumption and income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 95-114.
    12. Gianluca Cubadda, 2001. "Common Features In Time Series With Both Deterministic And Stochastic Seasonality," Econometric Reviews, Taylor & Francis Journals, vol. 20(2), pages 201-216.
    13. Smith, Richard J. & Taylor, A.M. Robert & del Barrio Castro, Tomas, 2009. "Regression-Based Seasonal Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 25(2), pages 527-560, April.
    14. Sheng-Hung Chen & Song-Zan Chiou-Wei & Zhen Zhu, 2022. "Stochastic seasonality in commodity prices: the case of US natural gas," Empirical Economics, Springer, vol. 62(5), pages 2263-2284, May.
    15. Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    16. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, Department of Economics and Business Economics, Aarhus University.
    17. Eric Ghysels & Denise R. Osborn & Paulo M. M. Rodrigues, 1999. "Seasonal Nonstationarity and Near-Nonstationarity," CIRANO Working Papers 99s-05, CIRANO.
    18. Smith, Richard J. & Robert Taylor, A. M., 2001. "Recursive and rolling regression-based tests of the seasonal unit root hypothesis," Journal of Econometrics, Elsevier, vol. 105(2), pages 309-336, December.
    19. Haldrup, Niels & Montanes, Antonio & Sanso, Andreu, 2005. "Measurement errors and outliers in seasonal unit root testing," Journal of Econometrics, Elsevier, vol. 127(1), pages 103-128, July.
    20. Rotger, Gabriel Pons, "undated". "Testing for Seasonal Unit Roots with Temporally Aggregated Time Series," Economics Working Papers 2003-16, Department of Economics and Business Economics, Aarhus University.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:118:y:2018:i:c:p:594-607. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.