National road casualties and economic development

Health Econ. 2006 Jan;15(1):65-81. doi: 10.1002/hec.1020.

Abstract

Objective: This paper explores why traffic fatalities increase with GDP per capita in lower income countries and decrease with GDP per capita in wealthy countries.

Methods: Data from 41 countries for the period 1992-1996 were obtained on road transport crashes, injuries, and fatalities as well as numbers of vehicles, kilometers of roadway, oil consumption, population, and GDP. Fixed effects regression was used to control for unobservable heterogeneity among countries.

Results: A 10% increase in GDP in a lower income country (GDP/Capita <1600) is expected to raise the number of crashes by 7.9%, the number of traffic injuries by 4.7%, and the number of deaths by 3.1% through a mechanism that is independent of population size, vehicle counts, oil use, and roadway availability. Increases in GDP in richer countries appear to reduce the number of traffic deaths, but do not reduce the number of crashes or injuries, all else equal. Greater petrol use and alcohol use are related to more traffic fatalities in rich countries, all else equal.

Conclusion: In lower income countries a rise in traffic-related crashes, injuries, and deaths accompanies economic growth. At a threshold of around 1,500 dollars-8,000 dollars per capita economic growth no longer leads to additional traffic deaths, although crashes and traffic injuries continue to increase with growth. The negative association between GDP and traffic deaths in rich countries may be mediated by lower injury severity and post-injury ambulance transport and medical care.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / economics*
  • Accidents, Traffic / mortality*
  • Accidents, Traffic / statistics & numerical data
  • Alcoholism / economics
  • Cross-Cultural Comparison
  • Developed Countries / economics*
  • Developing Countries / economics*
  • Gasoline / economics
  • Health Expenditures / statistics & numerical data
  • Humans
  • Income
  • Models, Econometric
  • Motor Vehicles / classification
  • Motor Vehicles / economics
  • Regression Analysis
  • Safety
  • Transportation / economics*

Substances

  • Gasoline