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1. Target risk 2: a new psychology of safety and health citation install#
2. Target risk 2: a new psychology of safety and health citation drivers#

To do so, two separate Weibull regression models were estimated for men and women. We next analyze the impact of driving patterns and driving intensity on the risk of accidents for both genders in more detail. Weibull Regression Model for the Time to the First Accident at Fault Therefore, we conclude that men, in general, present riskier driving patterns than women. In the case of Age, the differences are not statistically significant ( p-value = 0.4724). The results of these tests indicate that the differences between men and women are statistically significant for Age vehicle, Experience, Km/day, Urban, Night and Speed ( p-values < 0.01). We conducted a Kruskal-Wallis test to determine whether the above differences between men and women are statistically significant or not (note that the normality hypothesis for the variables in Table 2 is rejected when using the Kolmogorov-Smirnov test). Finally, men present a higher percentage of nighttime driving, on average, than women (8.41% vs. On average, more men exceed the speed limit than women (9.08% vs. The average percentage of urban driving is around 27.5% when considering all drivers, and there is very little difference between men and women in this regard. The average number of kilometers traveled per day is higher for men than for women (34.02 vs. All these factors have been shown to account for the risk of accidents. Speed is normally considered in terms of violation of the limits time is normally established in terms of day/nighttime driving (with nights being more expensive) and location distinguishes between urban and non-urban driving (with the former being more expensive). This is the PAYD pricing option that most insurance companies offer today. In this case, the price can then be fixed in relation not only to the number of kilometers driven, but also to such factors as vehicle speed, the time of day the vehicle is driven and the main locations in which it is driven.

Target risk 2: a new psychology of safety and health citation install#

Today’s technology, though, makes it possible to measure the use of the car more objectively by employing a GPS system, on the basis of which sophisticated PAYD pricing systems can be proposed (having first obtained, of course, the permission of the driver to install the GPS equipment). The easiest way to measure the distance driven by a vehicle is by using an odometer auditing system however, this is open to fraudulent practices.

Target risk 2: a new psychology of safety and health citation drivers#

We present estimations of the time to the first accident for different types of drivers and also estimate the probability of the first crash occurring during the first year of coverage for each driver type. This suggests that gender differences in relation to the risk of accidents are, to a large extent, attributable to the fact that men present a higher driving intensity than women and, as such, are more exposed to the risk of accidents. However, if driving intensity (measured by the number of kilometers traveled per day) is introduced in the model, then gender no longer has a significant effect. Additionally, gender has a significant effect in explaining the time to the first crash, with men being involved in their first crash sooner than women. Our results show gender differences in vehicle usage, with male drivers being more exposed to the risk of accidents than female drivers (as men are less respectful of speed limits, drive more kilometers per day and also drive more during the night). We present an empirical application with real data from a major Spanish insurance company. We conclude that no gender discrimination is necessary if telematics provides enough information on driving habits. Estimates of the time to the first accident for different driver risk types are presented. This suggests that gender differences in the risk of accidents are, to a large extent, attributable to the fact that men drive more often than women.

Indeed, although gender has a significant effect in explaining the time to the first crash, this effect is no longer significant when the average distance traveled per day is introduced in the model. Our empirical application with real data is presented and shows that gender differences are mainly attributable to the intensity of use. We use regression models for survival data to estimate how long it takes them to have their first accident at fault during the coverage period. In this paper we analyze the effect of the distance traveled on the risk of accidents among young drivers with a PAYD policy. Pay-as-you-drive ( PAYD), or usage-based automobile insurance (UBI), is a policy agreement tied to vehicle usage.