Perception of the Risks Associated with Impaired Driving and Effects on Driving Behavior

This research studies the perception of the risks associated with impaired driving-probability of being apprehended or of having an accident-and the relation between the perception of risks and driving behavior. The most important determinants of perceptual biases are age, an accumulation of violations in the year preceding the survey, being a non-drinker, knowledge of the legal alcohol limit for driving, opinion about zero tolerance for impaired driving, and family income. Perceptual biases are shown to influence driving behavior, as captured by drivers' accumulated violations, demerit points and bodily injury accidents, in the years preceding and in the year following the survey. In conclusion, we analyze the results in terms of public policy for road safety.Risk perception, impaired driving, driving behavior, traffic violation, road accident, regulation, public policy

Poisson Models with Employer-Employee Unobserved Heterogeneity: An Application to Absence Data

We propose a parametric model based on the Poisson distribution that permits to take into account both unobserved worker and workplace heterogeneity as long as both effects are nested. By assuming that workplace and worker unobserved heterogeneity components follow a gamma and a Dirichlet distribution respectively, we obtain a closed form the unconditional density function. We estimate the model to obtain the determinants of absenteeism using linked employer-employee Canadian data from the Workplace and Employee Survey (2003). Coefficient estimates are interpreted in the framework of the typical labor-leisure model. We show that omitting unobserved heterogeneity on either side of the employment relationship leads to notable biases in the estimated coefficients. In particular, the impact of wages on absences is underestimated in simpler models.Absenteeism, Linked Employer-Employee Data, Employer-Employee Unobserved Heterogeneity, Count Data Models, Dirichlet Distribution

Modèle Bayésien de tarification de l’assurance des flottes de véhicules

Nous proposons un modèle paramétrique de tarification de l’assurance de véhicules routiers appartenant à une flotte. Les tables de primes qui y sont présentées tiennent compte des accidents passés des véhicules, des caractéristiques observables des véhicules et des flottes et des infractions au Code de la sécurité routière des conducteurs et des transporteurs. De plus, les primes sont ajustées en fonction des accidents accumulés par les flottes dans le temps. Il s’agit d’un modèle qui prend directement en compte des changements explicites des différentes composantes des probabilités d’accidents. Il représente une extension aux modèles d’assurance automobile de type bonus-malus pour les primes individuelles (Lemaire, 1985 ; Dionne et Vanasse, 1989 et 1992 ; Pinquet, 1997 et 1998 ; Frangos et Vrontos, 2001 ; Purcaru et Denuit, 2003). L’extension ajoute un effet flotte à l’effet véhicule pour tenir compte des caractéristiques ou des actions non observables des transporteurs sur les taux d’accidents des camions. Cette forme de tarification comporte plusieurs avantages. Elle permet de visualiser l’impact des comportements des propriétaires des flottes et des conducteurs des véhicules sur les taux d’accidents prédits et, par conséquent, sur les primes. Elle mesure l’influence des infractions et des accidents accumulés sur les primes d’assurance mais d’une façon différente. En effet, les effets des infractions sont obtenus via la composante de régression, alors que les effets des accidents proviennent des résidus non expliqués de la régression sur les accidents des camions via un modèle bayésien de tarification.We are proposing a parametric model to rate insurance for vehicles belonging to a fleet. The tables of premiums presented take into account past vehicle accidents, observable characteristics of the vehicles and fleets, and violations of the road-safety code committed by drivers and carriers. The premiums are also adjusted according to accidents accumulated by the fleets over time. The model proposed accounts directly for explicit changes in the various components of the probability of accidents. It represents an extension of bonus-malus-type automobile insurance models for individual premiums (Lemaire, 1985; Dionne and Vanasse, 1989 and 1992; Pinquet, 1997 and 1998; Frangos and Vrontos, 2001; Purcaru and Denuit, 2003). The extension adds a fleet effect to the vehicle effect so as to account for the impact that the unobservable characteristics or actions of carriers can have on truck accident rates. This form of rating makes it possible to visualize what impact the behaviors of owners and drivers can have on the predicted rate of accidents and, consequently, on premiums

Poisson Models with Employer-Employee Unobserved Heterogeneity: An Application to Absence Data

We propose a parametric model based on the Poisson distribution that permits to take into account both unobserved worker and workplace heterogeneity as long as both effects are nested. By assuming that workplace and worker unobserved heterogeneity components follow a gamma and a Dirichlet distribution respectively, we obtain a closed form for the unconditional density function. We estimate the model to obtain the determinants of absenteeism using linked employer-employee Canadian data from the Workplace and Employee Survey (2003). Coefficient estimates are interpreted in the framework of the typical labor-leisure model. We show that omitting unobserved heterogeneity on either side of the employement relationship leads to notable biases in the estimated coefficients. In particular, the impact of wages on absences is underestimated in simpler models.Absenteeism; Linked Employer-Employee Data; Employer- Employee Unobserved Heterogeneity; Count Data Models; Dirichlet Distribution

Road safety for fleets of vehicles

Road safety for fleets of vehicles has been neglected in the insurance literature, mainly because appropriate data and methodology were not available. This article makes a threefold contribution: 1) Produce statistics on current fleets’ road safety offences and accidents using a panel of 20 years of data on truck fleets; 2) relate fleets’ offences to accidents; and 3) identify and classify the riskiest fleets for insurance ratemaking based on past experience in managing road safety. Our main technical innovation to the insurance literature is in the estimation of fleets’ distributions of accidents. For each fleet size (or group of sizes), we estimate the parameters of the negative binomial (NB) distribution of the annual number of accidents according to the characteristics of the fleets, the years, and the number of driver (DRV) and carrier (CAR) road safety violations accumulated in the previous year. When the NB model does not accurately predict the mathematical expectation of the number of accidents of larger fleets, we proceed in two steps. First, we estimate the probability of having zero accidents in a year, and then estimate the negative binomial distribution using the estimated probability of having zero accidents, to weight the zeros of each fleet. To achieve our third objective, we construct risk classes for the vehicle fleets using the predicted accident probabilities obtained from the estimated models. Our results show a substantial heterogeneity between fleets in terms of road safety. This information should be very useful for optimal insurance pricing and better incentives for road safety

Étude des comportements de sécurité routière des propriétaires, exploitants et conducteurs des véhicules lourds au Québec

Le contenu de notre rapport consiste à : 1) Identifier les effets de l’application de la « Politique d’évaluation des PEVLs » sur la sécurité routière. 2) Inventorier les infractions commises par les conducteurs de véhicules lourds et par les PEVLs les plus courantes et leurs récurrences. Établir un lien statistique entre les types d’infraction des conducteurs de VLs et des PEVLs et les types d’accident. 3) Identifier et catégoriser les profils des conducteurs des VLs et des PEVLs et déterminer ceux qui sont les plus à risque sur le plan de la sécurité routière

Modèle Bayésien de tarification de l’assurance des flottes de véhicules*

We are proposing a parametric model to rate insurance for vehicles belonging to a fleet. The tables of premiums presented take into account past vehicle accidents, observable characteristics of the vehicles and fleets, and violations of the road-safety code committed by drivers and carriers. The premiums are also adjusted according to accidents accumulated by the fleets over time. The model proposed accounts directly for explicit changes in the various components of the probability of accidents. It represents an extension of bonus-malus-type automobile insurance models for individual premiums (Lemaire, 1985; Dionne and Vanasse, 1989 and 1992; Pinquet, 1997 and 1998; Frangos and Vrontos, 2001; Purcaru and Denuit, 2003). The extension adds a fleet effect to the vehicle effect so as to account for the impact that the unobservable characteristics or actions of carriers can have on truck accident rates. This form of rating makes it possible to visualize what impact the behaviors of owners and drivers can have on the predicted rate of accidents and, consequently, on premiums. Nous proposons un modèle paramétrique de tarification de l’assurance de véhicules routiers appartenant à une flotte. Les tables de primes qui y sont présentées tiennent compte des accidents passés des véhicules, des caractéristiques observables des véhicules et des flottes et des infractions au Code de la sécurité routière des conducteurs et des transporteurs. De plus, les primes sont ajustées en fonction des accidents accumulés par les flottes dans le temps. Il s’agit d’un modèle qui prend directement en compte des changements explicites des différentes composantes des probabilités d’accidents. Il représente une extension aux modèles d’assurance automobile de type bonus-malus pour les primes individuelles (Lemaire, 1985 ; Dionne et Vanasse, 1989 et 1992 ; Pinquet, 1997 et 1998 ; Frangos et Vrontos, 2001 ; Purcaru et Denuit, 2003). L’extension ajoute un effet flotte à l’effet véhicule pour tenir compte des caractéristiques ou des actions non observables des transporteurs sur les taux d’accidents des camions. Cette forme de tarification comporte plusieurs avantages. Elle permet de visualiser l’impact des comportements des propriétaires des flottes et des conducteurs des véhicules sur les taux d’accidents prédits et, par conséquent, sur les primes. Elle mesure l’influence des infractions et des accidents accumulés sur les primes d’assurance mais d’une façon différente. En effet, les effets des infractions sont obtenus via la composante de régression, alors que les effets des accidents proviennent des résidus non expliqués de la régression sur les accidents des camions via un modèle bayésien de tarification.

Health Care Workers' Risk Perceptions of Personal and Work Activities and Willingness to Report for Work During an Influenza Pandemic

The ability and willingness of health care workers to report for work during a pandemic are essential to pandemic response. The main contribution of this article is to examine the relationship between risk perception of personal and work activities and willingness to report for work during an influenza pandemic. Data were collected through a quantitative Web-based survey sent to health care workers on the island of Montreal. Respondents were asked about their perception of various risks to obtain index measures of risk perception. A multinomial logit model was applied for the probability estimations, and a factor analysis was conducted to compute risk perception indexes (scores). Risk perception associated with personal and work activities is a significant predictor of intended presence at work during an influenza pandemic. The average predicted probability of being at work during the worst scenario of an influenza pandemic is 46% for all workers in the sample, 36% for those overestimating risk in personal and work activities (95% CI: 35%-37%), 53% for those underestimating risk in work activities (95% CI: 52%-54%), and 49% for those underestimating risk of personal activities (95% CI: 48%-50%). When given an opportunity to change their intentions, 45% of those who initially did not intend to report for work in the worst scenario would do so if the pandemic resulted in a severe manpower shortage. These results have not been previously reported in the literature. Many organizational variables are also significant

Analyse de l’effet des règles d’obtention d’un permis de conduire au Québec (1991) sur la sécurité routière

La réglementation de la sécurité routière a été l’objet de plusieurs études. Sa principale motivation est reliée aux externalités que certains conducteurs peuvent générer à d’autres individus (conducteurs, piétons) et qui ne peuvent être tarifées directement par différents marchés privés. L’objectif de notre recherche est d’évaluer l’effet des règles d’obtention d’un permis de conduire au Québec (1991) sur les taux d’accidents des nouveaux conducteurs. Il n’est pas toujours évident qu’un changement de réglementation affectera le niveau d’équilibre de prévention routière dans une société. Dans cette recherche, nous vérifions que l’effet de la réforme n’est pas significatif sur les taux d’accidents et ce, ni pour l’ensemble des nouveaux conducteurs, ni pour l’ensemble des nouvelles conductrices, et ni pour chaque groupe d’âge analysé séparément. Par contre, il y a clairement des effets d’âge sur les taux d’accidents. Les nouveaux conducteurs comme les nouvelles conductrices âgés de 20 ans et plus, sont moins à risque d’avoir un accident que ceux et celles âgés de 16 ans à l’obtention du permis. Les nouveaux conducteurs âgés de 17 ans et ceux âgés de 18-19 ans enregistrent des risques semblables aux 16 ans. Ces variations entre les groupes d’âges montrent une grande hétérogénéité des nouveaux conducteurs et conductrices même durant leur première année de conduite alors que la réglementation de 1991 des nouveaux conducteurs et conductrices les considérait comme homogènes. Nous avons également vérifié si l’expérience accumulée durant la première année affecte les taux d’accidents. Nous obtenons que les taux moyens d’accidents observés durant les trois premiers mois chez les femmes et les quatre premiers mois chez les hommes, sont plus élevés que ceux des périodes subséquentes de 30 jours.Road safety regulation has been the object of many studies. Its main motivation is related to externalities between individuals (drivers, pedestrians) that cannot be priced directly in different private markets. The object of this research is to evaluate the effects of the change in the regulation (Quebec 1991) on access to the driving permit on crash rates. It is not always evident that a regulation change will affect the equilibrium level of safety in a given society. We found that the 1991 reform had no significant effect on crash rates, be it for all new drivers, male drivers, female drivers, or any age group taken separately. However, there is an age effect on accidents. New drivers, male and female who are at least 20 years old, are at a lower risk than those 16 years old when obtaining the permit. Male drivers who are 17 or 18-19 years old have similar risks as the 16 year old. These differences between age groups show a great heterogeneity among the new drivers even in their first year, but the 1991 regulation treated all new drivers uniformly. We have also investigated the effect of experience during the first year on crash rates. Average rates for the first three months for women and for the first four months for men are higher than the rates for the subsequent months

Perception of the Risks Associated with Impaired Driving and Effects on Driving Behavior

This research studies the perception of the risks associated with impaired driving - probability of being apprehended or of having an accident - and the relation between the perception of risks and driving behavior. The most important determinants of perceptual biases are age, an accumulation of violations in the year preceding the survey, being a non-drinker, knowledge of the legal alcohol limit for driving, opinion about zero tolerance for impaired driving, and family income. Perceptual biases are shown to influence driving behavior, as captured by drivers' accumulated violations, demerit points and bodily injury accidents, in the years preceding and in the year following the survey. In conclusion, we analyze the results in terms of public policy for road safety