Investigating the nature and impact of reporting bias in road crash data

Kibrom Abay

Transportation Research Part A: Policy and Practice, 2015, vol. 71, issue C, 31-45

Abstract: This paper investigates the nature, and impact of the reporting bias associated with the police-reported crash data on inferences made using this data. In doing so, we merge a detailed emergency room data and police-reported crash data for a specific region in Denmark. To disentangle potentially common observable and unobservable factors that affect drivers’ injury severity risk and their crash reporting behavior, we formulate a bivariate ordered-response probit model of injury severity risk and crash reporting propensity. To empirically identify the reporting bias in this joint model, we exploit an exogenous police reform that particularly affects some specific municipalities of the region under consideration. The empirical analysis reveals substantial reporting bias in the commonly used police-reported road crash data. This non-random sample selection associated with the police-reported crash data leads to biased estimates on the effect of some of the explanatory variables in injury severity analysis. For instance, estimates based on the police-reported crash data substantially underestimate the effectiveness of seat belt use in reducing drivers’ injury severity risk.

Keywords: Reporting bias; Under-reporting; Injury severity modeling; Random coefficients bivariate ordered-response probit; Maximum simulated likelihood (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.tra.2014.11.002

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