Identifying the Social Costs of Road Traffic Crashes in India through Quantitative and Quantile Regression Analysis

Despite recent advances in addressing road safety, especially in developed countries, road traffic crashes still result in 1.65 million fatalities annually and impose costs exceeding $95 billion. This paper reviews the literature on socio-economic costs, identifies key research gaps, and underscores the lack of analysis focused on developing countries, which experience 90% of global fatalities. Using both descriptive and econometric analyses, we observe an upward trend in road safety studies in high- and middle-income countries. We calculated the components of hospitalization costs and examined the relationship between these costs and patient characteristics using quantile regression models. The paper examines two primary methodologies for estimating socio-economic costs: willingness-to-pay (WTP) and human capital (HC). Our econometric findings show that studies using the WTP method typically estimate the impact on GDP to be approximately 1% higher than those using the HC approach. Furthermore, the HC method tends to underestimate total socio-economic costs by a factor of two compared to WTP-based estimates, although this gap narrows significantly when adjusting for factors like population density, income levels, and road safety conditions. Additionally, the paper highlights challenges with underreporting and the lack of a systematic method to account for it in cost estimations. We conclude with a call for more research in low- and middle-income countries that combines WTP, HC, and alternative valuation methods to provide a more comprehensive understanding of the socio-economic costs of road crashes.