IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa06p223.html

A Geo-Statistical Analysis of Road Mortality in the Enlarged EU

Author

Listed:
  • Isabelle Thomas

  • Vojtech Eksler

  • Sylvain Lassarre

Abstract

This paper aims at showing and understanding the spatial regional disparities hidden behind average national statistics on road fatalities in Europe; special attention is given on the EU last enlargement. The work is not limited on differences descriptions, but unveils what is hidden behind the observed infra-national heterogeneity in terms of road risk. It is indeed common practice to compare countries in terms of road safety performance and to rank them in terms of a risk indicator such as the mortality rate, which is often expressed by the number of fatalities due to road accidents per 100,000 inhabitants. Some countries are known for their very bad risk records and are often pointed out by national or international authorities, without any understanding of the regional differences hidden behind a national mean value. The data analysis shows that changes in the level of spatial aggregation of the data produce significant differences in the variables describing the level of road safety, and hence in operational recommendation and conclusions. Beside the differences in national conditions and polices, the regional differences in road environment characteristics, traffic performance, road user mix, travel speeds, seat-belt use, and availability of emergency care have been major contributors to these variations. Road safety professionals and decision makers should be aware of the differences existing when trying to reduce road toll of the country in sustainable and cost-effective way.

Suggested Citation

  • Isabelle Thomas & Vojtech Eksler & Sylvain Lassarre, 2006. "A Geo-Statistical Analysis of Road Mortality in the Enlarged EU," ERSA conference papers ersa06p223, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa06p223
    as

    Download full text from publisher

    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa06/papers/223.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    2. Claire Dujardin & Isabelle Thomas & Henry Tulkens, 2007. "Quelles frontières pour Bruxelles ? Une mise à jour," Reflets et perspectives de la vie économique, De Boeck Université, vol. 0(2), pages 155-176.
    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. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    2. Mumtaz, Haroon & Theodoridis, Konstantinos, 2017. "Common and country specific economic uncertainty," Journal of International Economics, Elsevier, vol. 105(C), pages 205-216.
    3. Christina Leuker & Thorsten Pachur & Ralph Hertwig & Timothy J. Pleskac, 2019. "Do people exploit risk–reward structures to simplify information processing in risky choice?," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 76-94, August.
    4. Rubio, F.J. & Steel, M.F.J., 2011. "Inference for grouped data with a truncated skew-Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3218-3231, December.
    5. Cristian David Correa-Álvarez & Juan Carlos Salazar-Uribe & Luis Raúl Pericchi-Guerra, 2023. "Bayesian multilevel logistic regression models: a case study applied to the results of two questionnaires administered to university students," Computational Statistics, Springer, vol. 38(4), pages 1791-1810, December.
    6. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    7. Svetlana V. Tishkovskaya & Paul G. Blackwell, 2021. "Bayesian estimation of heterogeneous environments from animal movement data," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
    8. Leonardo Oliveira Martins & Hirohisa Kishino, 2010. "Distribution of distances between topologies and its effect on detection of phylogenetic recombination," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(1), pages 145-159, February.
    9. Tamal Ghosh & Malay Ghosh & Jerry J. Maples & Xueying Tang, 2022. "Multivariate Global-Local Priors for Small Area Estimation," Stats, MDPI, vol. 5(3), pages 1-16, July.
    10. Eibich, Peter & Ziebarth, Nicolas R., 2014. "Examining the structure of spatial health effects in Germany using Hierarchical Bayes Models," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 305-320.
    11. Wu, Ji & Guo, Mengmeng & Chen, Minghua & Jeon, Bang Nam, 2019. "Market power and risk-taking of banks: Some semiparametric evidence from emerging economies," Emerging Markets Review, Elsevier, vol. 41(C).
    12. repec:jss:jstsof:21:i08 is not listed on IDEAS
    13. Deng, Yaguo & Veiga, Helena & Wiper, Michael Peter, 2016. "Efficiency evaluation of Spanish hotel chains," DES - Working Papers. Statistics and Econometrics. WS 23897, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Cathy W. S. Chen & Sangyeol Lee, 2017. "Bayesian causality test for integer-valued time series models with applications to climate and crime data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 797-814, August.
    15. Makoto Chikaraishi & Akimasa Fujiwara & Junyi Zhang & Kay Axhausen, 2011. "Identifying variations and co-variations in discrete choice models," Transportation, Springer, vol. 38(6), pages 993-1016, November.
    16. Galatia Cleanthous & Emilio Porcu & Philip White, 2021. "Regularity and approximation of Gaussian random fields evolving temporally over compact two-point homogeneous spaces," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 836-860, December.
    17. Baños-Pino, José F. & Boto-García, David & Zapico, Emma, 2021. "Persistence and dynamics in the efficiency of toll motorways: The Spanish case," Efficiency Series Papers 2021/03, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    18. Xing Ju Lee & Christopher C. Drovandi & Anthony N. Pettitt, 2015. "Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets," Biometrics, The International Biometric Society, vol. 71(1), pages 198-207, March.
    19. Vandenbulcke, Grégory & Dujardin, Claire & Thomas, Isabelle & Geus, Bas de & Degraeuwe, Bart & Meeusen, Romain & Panis, Luc Int, 2011. "Cycle commuting in Belgium: Spatial determinants and 're-cycling' strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 118-137, February.
    20. Chaix, Basile & Jouven, Xavier & Thomas, Frédérique & Leal, Cinira & Billaudeau, Nathalie & Bean, Kathy & Kestens, Yan & Jëgo, Bertrand & Pannier, Bruno & Danchin, Nicolas, 2011. "Why socially deprived populations have a faster resting heart rate: Impact of behaviour, life course anthropometry, and biology – the RECORD Cohort Study," Social Science & Medicine, Elsevier, vol. 73(10), pages 1543-1550.
    21. Emilio Augusto Coelho-Barros & Jorge Alberto Achcar & Josmar Mazucheli, 2010. "Longitudinal Poisson modeling: an application for CD4 counting in HIV-infected patients," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 865-880.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:wiw:wiwrsa:ersa06p223. 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: Gunther Maier (email available below). General contact details of provider: http://www.ersa.org .

    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.