ISSN (print) - 0131-7652

ISSN (online) - 2686-7605

Vol. 53 No. 2 (2023)
ECONOMY SECTORS AND MARKETS

Assessment of the Effectiveness of Regulation of Road Conditions Affecting Fatalities in Traffic Accidents

PDF (Русский)
  • N.S. Antonenko,
  • E.A. Ponomareva,
  • A.D. Savina
N.S. Antonenko
Institute of Control and Supervision; Russian Presidential Academy of National Economy and Public Administration, Moscow
E.A. Ponomareva
Institute of Control and Supervision; Russian Presidential Academy of National Economy and Public Administration, Moscow
A.D. Savina
Institute of Control and Supervision; Russian Presidential Academy of National Economy and Public Administration, Moscow
DOI: https://doi.org/10.30680/ECO0131-7652-2023-2-103-122

Published 2023-02-02

Keywords

  • road safety; traffic safety improvement; road accidents; traffic fatalities; statistical life cost (VSL); cost-benefit analysis (CBA); road infrastructure; logistic regression

How to Cite

1.
Antonenko Н, Ponomareva Е, Savina А. Assessment of the Effectiveness of Regulation of Road Conditions Affecting Fatalities in Traffic Accidents. ECO [Internet]. 2023 Feb. 2 [cited 2025 Jun. 13];53(2):103-22. Available from: https://ecotrends.ru/index.php/eco/article/view/4569

Abstract

The purpose of the study is to develop practical recommendations for prioritizing work to eliminate violations of the regulatory requirements for roads. It takes into account the impact of these violations on mortality in accidents, on the one hand, and the timing and cost of work to eliminate them, on the other. Calculations of the cost-benefit ratio for road construction works are made on the basis of the data on government contracts for road reconstruction and repair, the most common methods of estimating the cost of statistical life and quantitative estimates of the impact of poor road conditions on traffic fatalities for the period from 2015 to 2019. A total of 16 regulatory violations and 14 corrective actions were analyzed. Some of them are effective only if certain conditions are met.
PDF (Русский)

References

  1. Колесникова Д. М., Карабчук Т. С., Сальникова Д. В., Фаттахов Т. А. Оценка социально-экономических общественных потерь от ДТП в России // Вопросы экономики. 2016. № 6. С. 1–16.
  2. Пономарева Е. А., Савина А. Д. Факторы, влияющие на смертность в ДТП // Экономическая политика. 2022. Т. 17. № 4. С. 128–153.
  3. Alberini, A., & Ščasný, M. (2011). Context and the VSL: Evidence from a Stated Preference Study in Italy and the Czech Republic. Environmental and Resource Economics. No. 49(4). Pp. 511–538.
  4. Andersson, H. (2020). Chapter Three – The value of a statistical life. Advances in Transport Policy and Planning, 6.
  5. Antoniou, C., & Kostovasilis, K. (2016). How may external information affect traffic risk perception? Journal of Transportation Safety & Security. No. 9(3). Pp. 347–368.
  6. Ara Aksoy, S. (2020). On the benefit transfer of the value of a statistical life. Turkish Journal of Public Health. No. 18(2). Pp. 113–128.
  7. Bahamonde-Birke, F. J., Kunert, U., & Link, H. (2015). The Value of a Statistical Life in a Road Safety Context – A Review of the Current Literature. Transport Reviews. No. 35(4). Pp. 488–511.
  8. Carlsson, F., Daruvala, D., & Jaldell, H. (2010). Value of Statistical Life and Cause of Accident: A Choice Experiment. Risk Analysis. No. 30(6). Pp. 975–986.
  9. Daniels, S., Martensen, H., Schoeters, A., Van den Berghe, W., Papadimitriou, E., Ziakopoulos, A., … Perez, O. M. (2019). A systematic cost-benefit analysis of 29 road safety measures. Accident Analysis & Prevention, No.133(105292).
  10. Flügel, S., Veisten, K., Rizzi, L. I., de Dios Ortúzar, J., & Elvik, R. (2019). A comparison of bus passengers’ and car drivers’ valuation of casualty risk reductions in their routes. Accident Analysis & Prevention. No. 122. Pp. 63–75.
  11. Hammitt, J. K., & Robinson, L. A. (2011). The Income Elasticity of the Value per Statistical Life: Transferring Estimates between High and Low Income Populations. Journal of Benefit-Cost Analysis. No. 2(01). Pp. 1–29.
  12. Jaździk-Osmólska, A. (2021). Willingness to Pay for Road Safety Improvements in Poland. European Research Studies Journal. No. 3B, 91–112.
  13. Le, H., van Geldermalsen, T., Lim, W. L., & Murphy, P. (2011). Deriving accident costs using willingness-to-pay approaches-A case study for Singapore. Australasian Transport Research Forum (ATRF), 34th.
  14. Li, S. (2010). Traffic safety and vehicle choice: quantifying the effects of the “arms race” on American roads. Journal of Applied Econometrics. No. 27(1). Pp. 34–62.
  15. Liu, W., & Zhao, S. (2013). The Value of Statistical Life in Road Traffic Based on Logit Model. Journal of Transportation Systems Engineering and Information Technology. No. 13(1), Pp. 137–141.
  16. Lord, D., F. Mannering. (2010). The Statistical Analysis of Crash-Frequency Data: A Review and Assessment of Methodological Alternatives. Transportation Research Part A: Policy and Practice, No. 44(5). Pp. 291–305.
  17. Lyon, C., Persaud, B., Eccles, K. (2015). Safety Evaluation of Centerline Plus Shoulder Rumble Strips.
  18. Mannering, F.L., Shankar, V., & Bhat, C.R. (2016). Unobserved heterogeneity and the statistical analysis of highway accident data. Analytic Methods in Accident Research. No. 11. Pp. 1–16.
  19. Milligan, C., Kopp, A., Dahdah, S., & Montufar, J. (2014). Value of a statistical life in road safety: A benefit-transfer function with risk-analysis guidance based on developing country data. Accident Analysis & Prevention. No. 71. Pp. 236–247.
  20. Mon, E.E., Jomnonkwao, S., Khampirat, B., Satiennam, W., & Ratanavaraha, V. (2018). Willingness to pay for mortality risk reduction for traffic accidents in Myanmar. Accident Analysis & Prevention. No. 118. Pp. 18–28.
  21. Narain, U, Sall, C. (2016). Methodology for valuing the health impacts of air pollution: discussion of challenges and proposed solutions. World Bank Group.
  22. O’Brien, J. (2018). Age, autos, and the value of a statistical life. Journal of Risk and Uncertainty, No. 57(1). Pp. 51–79.
  23. Robinson, L., Hammitt, J., & O’Keeffe, L. (2019). Valuing Mortality Risk Reductions in Global Benefit-Cost Analysis. Journal of Benefit-Cost Analysis. No. 10(S1). Pp. 15–50.
  24. Sánchez-Martínez, F.I., Martínez-Pérez, J.E., Abellán-Perpiñán, J.M., & Pinto-Prades, J.L. (2021). The value of statistical life in the context of road safety: new evidence on the contingent valuation/standard gamble chained approach. Journal of Risk and Uncertainty. No. 63. Pp. 203–228.
  25. Savolainen, P.T., Mannering, F.L., Lord, D., Quddus, M.A. (2011). The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. Accident Analysis & Prevention. No. 43. Pp. 1666–1676.
  26. Svensson, M. (2009). Precautionary behavior and willingness to pay for a mortality risk reduction: Searching for the expected relationship. Journal of Risk and Uncertainty. No. 39(1). Pp. 65–85.
  27. Viscusi, W., & Masterman, C. (2017). Income Elasticities and Global Values of a Statistical Life. Journal of Benefit-Cost Analysis. No. 8(2). Pp. 226–250.
  28. Wijnen, W. (2021). Socio-economic costs of road crashes in middle-income countries: Applying a hybrid approach to Kazakhstan. IATSS Research. No. 45(3). Pp. 293–302.
  29. Wijnen, W., Weijermars, W., Schoeters, A., van den Berghe, W., Bauer, R., Carnis, L., … Martensen, H. (2019). An analysis of official road crash cost estimates in European countries. Safety Science. No. 113. Pp. 318–327.
  30. Yang, Z., Liu, P., & Xu, X. (2016). Estimation of social value of statistical life using willingness-to-pay method in Nanjing, China. Accident Analysis & Prevention. No. 95. Pp. 308–316.
  31. Ye, F., & Lord, D. (2014). Comparing three commonly used crash severity models on sample size requirements: Multinomial logit, ordered probit and mixed logit models. Analytic methods in accident research. No. 1. Pp. 72–85.