Estimating the Value of Statistical Life in Road Safety Improvement: The Case Study of Tabriz

Document Type : Research Paper

Authors

1 Ph.D. Candidate in Economics, Razi University, Kermanshah, Iran

2 Associate Professor of Economics, Razi University, Kermanshah, Iran

3 Assistant professor of Pharmacoeconomics and Pharmaceutical Administration, Road Traffic Injury Research Center, Tabriz University of Medical Sciences

Abstract

With respect to the rapid development of the road transport industry, improving safety and valuing accidents have become an essential issue in public policy. Over the past few decades, studies based on the estimation of valuing statistical life have played a unique role in the cost-benefit estimations of investment in the transport sector. In this regard, this study has been conducted using the stated choice method and the mixed logit model to examine the willingness to pay and the value of statistical life among the Tabriz drivers. The research data were collected through a questionnaire from 300 people who travel daily in the city for various reasons. The statistical value of life and injury for Tabriz city was 18663384 and 135005 Tomans respectively. According to the results, investing in road safety improvement projects is necessary to reduce casualties and injuries.

Keywords

Main Subjects

References

  1. Mohamed, H. (2015). Estimation of socio-economic cost of road accidents in Saudi Arabia: Willingness to pay approach. Advances in Management and Applied Economics, 5(3), 43-61.
  2. Ainy, E., Soori, H., Ganjali M., & Baghfalaki, T. (2014). Road traffic injury cost estimation by willingness to pay method. Safety Promotion and Injury Prevention, 2(3), 215-225 (In Persian).
  3. Anderson, H., & Treich, N. (2011). The value of statistical life. Transport Economics, 1-36.
  4. Antonion, C. (2014). A stated preference study of the willingness to pay to reduce traffic risk in urban vs rural roads. EUR.Transp.Res.Rev, 6, 31-42.
  5. Ashenfelter, O. (2006). Measuring the value of statistical life: Problems and prospects. Institute for the Study, of Labor, IZA Discussion Paper, No.1911, 1-32.
  6. Ayati, E., & Vahedi, J.R. (2006). Developing bridge safety index model for Iran. Journal of Engineering College, 37(1), 135-152 (In Persian).
  7. Bahamonde, F., Kunert, U., & Link, H. (2015). The value of statistical life in road safety context: A review current literature. Article in Transport Reviews, 1-27.
  8. Bamsal, P., Daziano, RA., & Achtnicht, M. (2018). Extending the mixed logit model for combination of random and fixed parameters. Journal of Choice Modeling, 27, 88-96.
  9. Birol, E., & Villalba, ER. (2006). Estimating Mexican farmer's valuation of Milpa diversity and genetically modified maize: A choice experiment approach. Environmental Economy and Policy Research, Working Paper, University of Cambridge, Department of Land Economics, 1-27.
  10. Elvik, R., Hoye, A., Vaa, T., & Sorensen, M. (2009). The handbook of road safety measures (2nd ed). Emerald, Bingley, UK.
  11. Flugel, S., Elvik, R., Veisten, K., Rizzi, L., Meyer, S., Rajmerdi, F., & Ortuzar, J. (2015). Asymetric preferences for road safety: Evidence from a stated choice experiment among car drivers. Transportation Research, 112-123.
  12. Gopalakarishnan, S. (2012). A public health perspective of road traffic accidents.  J. Fam. Med. Prim. Care, 1(2), 144-150.
  13. Haddak, M., Havet, N., & Lefevre, M. (2014). Willingness to pay for road safety improvement. Gate. Working Paper, 6, 1-18.
  14. Hajizadeh, E., & Asghari, M. (2011). Statistical methods and Analysis by looking at research methods in biological and health sciences, Jahad Daneshgahi Publications, Tehran, Iran (In Persian).
  15. Hanley, N., Mourat, S., & Wright, R.E. (2001). Choice modeling approaches: As superior alternatives for environmental valuation. Journal of Economic Surveys, 15(3), 435-462.
  16. Hensher, DA., & Greene, WH. (2001). The mixed logit model: The state of practice and warnings for the unwary. Institute of Transport Studies, 1-39.
  17. Hensher, DA., Rose, JM., & Greene, WH. (2005). Applied choice analysis: A primer, Cambridge University Press, Cambridge.
  18. Hensher, DA., Rose, JM., Ortuzar, JD., & Rizzi, L. (2009). Estimating the willingness to pay and value of risk reduction for car occupants in the road environment. Institute of Transport and Logistics Studies. Working Paper, 1-22.
  19. Hensher, DA., Rose, JM., Ortuzar, JD., & Rizzi, L. (2011). Estimating the value of risk reduction for pedestrains in the road environment: An exploratory analysis. Journal of Choice Modeling, 4(2), 70-94.
  20. Hojman, P., Ortuzar, J., & Rizzi, L. (2005). On the joint valuation of averting fatal and serve injuries in highway accidents. Journal of Safety Research, 36, 377-388.
  21. Isazadeh, S., Jalili Kamjoo, P., Madadi, S., & Mahmoodiniya, D. (2011). Choice experiment: Non market commodity (environmental) valuating based on the stated preference and choice modeling. Economics of Natural Resources, 1, 21-36 (In Persian).
  22. Jafari, A.M., Saleh, I., Yazdani, S., & Hoseini, S.S. (2013). The economics- environmental impacts analysis of the promotion of the wall of Ekbatan dam in Hamedan, Agricultural Economics, 7(2), 69-92 (In Persian).
  23. Jones-Lee, M.W., & Loomis, G. (1995). Scale and context effects in the valuation of transport safety. Journal of Risk and Uncertainty, 11(3), 183-203.
  24. Jones-Lee, M.W., Hammerton, M., & Phillips, P.R. (1995). Valuing the prevention of non-fatal road injuries: Contingent valuation vs standard gambles. Oxford Economic Papers, 47, 676-795.
  25. Louviere, J.J., Hensher, DA., & Swait, S. (2000). Stated choice methods: Analysis and applications. Cambridge University Press.
  26. McFadden, D. (1998). Measuring willingness to pay for transportation improvements. Theoretical Foundation of Time Choice Modeling, 339-364.
  27. Mishan, E.J. (1971). Evaluation of life and limb: A theoretical approach. Journal of Political Economy, 79, 687-745.
  28. Mitchel, R.C., & Carson, R.T. (2010). Using survey to value public goods. Resources for the Future, Washington D.C, 1-11.
  29. Mofadal, A., Kanitpong, K., & Jiwattanakulpaisarn, P. (2015). Analysis of pedestrian accident costs in Sudan using the willingness to pay method. Accident Analysis and Prevention, 78, 201-211
  30. Niroomand, N., & Jenkins, G.P. (2016). Estimating the value of life, injury and travel time saved: Using a stated preferences frame work. Accident Analysis and Prevention, 91, 216-225.
  31. Niroomand, N., & Jenkins, G.P. (2017). Estimating the value of life and injury for pedestrians using a stated preferences framework. Journal of Safety Research, 1-7.
  32. Rizzi, L.I., & Ortuzar, J.D. (2003). Stated preference in the valuation of interurban road safety. Accident Analysis and Prevention, 35, 9-22.
  33. SWOV Fact Sheet. (2012). The valuation of human losses of road deaths. WHO, 1-5.
  34. Train, K. (2003). Discrete choice methods with simulation. Cambridge UK, Cambridge University Press.
  35. Varian, H.R. (1992). Microeconomic analysis (3rd edition). Norton and Company INC, New York.
  36. Veisten, K., Flugel, S., Rizzi, L., Ortuzar, J., & Elvik, R. (2013). Valuing casualty risk reductions from estimated baseline risk. Research in Transportation Economics, 43, 50-61.
  37. Wenge, L., & Shongchuan, Z. (2013). The value of statistical life in road traffic: Based on logit model. Journal of Transportation Systems Engineering and Information Technology, 13(1), 137-141.
  38. Yang, Z., Liu, P., & Xu, X. (2016). Estimation of social value of statistical life using willingness to pay method in Nanjing China. Accident Analysis and Prevention, 1, 1-9.
Quarterly Journal of Applied Theories of Economics
Volume 5, Issue 4 - Serial Number 19
February 2019
Pages 107-142

Files

Share

How to cite

Statistics