Academic journal article Journal of Risk and Insurance

Heterogeneity of the Accident Externality from Driving

Academic journal article Journal of Risk and Insurance

Heterogeneity of the Accident Externality from Driving

Article excerpt

ABSTRACT

This article examines the accident externality from driving in terms of loss probability and severity by using a unique individual-level data set with more than 3 million observations from Taiwan. Two types of accident externality are, respectively, measured: the average number of kilometers driven per month per vehicle and the total number of speeding tickets per month. For both variables, we find significant evidence to support the existence of the accident externality. Moreover, we find that the accident externality is heterogeneous in terms of the vehicles' characteristics.

INTRODUCTION

The risk of a specific driver is affected by other drivers' driving behavior. This is referred to as the accident externality from driving. Such an externality could be very costly to a society and has received much attention in the literature. For example, by using aggregate panel data for the United States, Edlin and Karaca-Mandic (2006) provide intriguing evidence to support the existence of an accident externality from driving. They find that to correct the substantial accident externalities, a Pigouvian tax could raise over $220 billion per year nationally. By adopting Edlin and Karaca-Mandic's methodology, Saito, Kato, and Shimane (2007) also find evidence of a positive and significant externality in Japan. The estimated nationwide Pigouvian tax is about $16-$51 billion in Japan.

In complementing the above literature that estimates the total size of the accident externality, this article studies two important questions that have so far not been explored to any significant extent in the literature. First, how does the externality affect the individual's loss probability and loss severity? Second, who suffers more due to other people's driving? In other words, this article seeks to examine the heterogeneity of the accident externality. The answers to these two questions can guide a social-welfare maximizing government in delicately coping with the externality. It is because information on the accident externality both in terms of frequency and severity is necessary for the government to push the private optimum to the social optimum when drivers are risk averse. (1) In addition, the government could directly compensate the identified victims to improve the social welfare.

Since the heterogeneity of the accident externality from driving cannot be analyzed through aggregate data, we adopt individual-level data. We hand-collect our data by integrating data from a vehicle manufacturer with data from an insurance company in Taiwan. Our insurance data include both the occurrence and the amount of money involved in the accident. (2) We are therefore in a position to investigate the impact of the accident externality on the frequency and severity separately. Our insurance data also contain the individuals' demographic variables that can be used to analyze the heterogeneity of the accident externality.

We use two variables to measure the accident externality. (3) One is the average number of kilometers driven per vehicle since the more kilometers that other drivers cover, the greater the potential for each driver to risk causing an accident. Our data from the vehicle manufacturer contain the kilometers driven for each vehicle. Thus, we could estimate the accident externality conditional on the individual's own driving. Furthermore, even if the average number of kilometers driven per vehicle is high, it might not necessarily mean that the risk is higher if others drive at a reasonable speed. (4) Since speed is one of the major risk factors associated with driving, we further adopt the total speeding tickets per month in Taiwan as another variable for the accident externality.

The major findings are as follows. First, we confirm the existence of the accident externality arising from driving in Taiwan both on the average number of kilometers driven per month per vehicle and on the total number of speeding tickets per month. …

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