Denise Desjardins

Neck injuries among belted and unbelted occupants of the front seat of cars

This article, part of a recently completed research project on safety belts, presents results on neck injuries. A total of 3927 injured front-seat occupants (drivers and passengers) involved in two-car crashes were studied. Among them, 725 sustained neck sprains (ICD-9 code 847.0); some of them may have sustained other injuries as well. The more serious injuries to the cervical spine were more prevalent among the unbelted occupants. Neck sprains were relatively more numerous among belted occupants compared with unbelted ones, with a relative risk estimate of 1.68. Similar results hold also for subsets of the data on different types of collisions; the relative risks ranged from 1.39 to 2.42. A log linear model was constructed for the odds ratio (neck sprain vs. no neck sprain) taking into account the following factors: (1) seatbelt use, (2) direction of impact, (3) authorized speed limit, and (4) vehicle weight. The resulting relative risk estimate (belted vs. unbelted) became 1.58. The results raise questions about seatbelts and their protection against neck sprains.

Experience rating schemes for fleets of vehicles

This paper proposes bonus-malus systems for fleets of vehicles, by using the individual characteristics of both the vehicles and the carriers. Bonus-malus coefficients are computed from the history of claims or from the history of safety offences of the carriers and the drivers. The empirical results are derived from a data set obtained from the Societe de l’Assurance Automobile du Quebec, the public insurer for bodily injuries and the regulator of road safety.

Exposure for different license categories through a phone survey: Validity and feasibility studies☆

This paper presents: (i) an operational definition of risk exposure, (ii) a questionnaire developed to measure exposure, (iii) validity studies of estimates of the distance traveled and time spent driving for different permit holder categories, and (iv) a feasibility study for a telephone survey on exposure. Results show that long-distance truck drivers from one company studied estimated accurately their distance driven on the last worked day; Montreal Urban Community Transport Commission bus drivers estimated well their time behind the wheel; while a convenience sample of private car drivers (coworkers and friends) estimated well their previous week distance and time on the road. Phone surveys appear to be an efficient and cost-effective method for risk exposure data collection.

Analysis of the Economic Impact of Medical and Optometric Driving Standards on Costs Incured by Trucking Firms and on the Social Costs of Traffic Accidents

Recent studies do not agree on the possible relationship between medical conditions and traffic safety; most of them do not control for exposure factors. In this study, we estimate the effect of different medical conditions (namely diabetes, high blood pressure, coronary disease and monocular vision) on the distribution of accidents of truck drivers. Our data and our model permit the simultaneous control for age, medical conditions and other characteristics of the truck drivers; exposure factors measured by hours, kilometers, and qualitative factors; and of the circumstances surrounding accidents described in police reports.

Reinsurance Demand and Liquidity Creation

This paper analyzes the relation between insurers’ liquidity creation and reinsurance demand. The empirical measure of liquidity creation was developed for banks by Berger and Bouwman (2009), who distinguished two important bank activities: liquidity creation and risk transformation. Insurers also actively transform risk, but the extent of their engagement in liquidity creation is less clear. Because liquidity creation is a risky activity, it may affect the demand for reinsurance. The goal of this study is to analyze how liquidity creation affects demand for reinsurance.

Modelling and Estimating Individual and Firm Effects with Count Panel Data

In this article, we propose a new parametric model for the modelling and estimation of accident distributions for drivers working in fleets of vehicles. The analysis uses panel data and takes into account individual and fleet effects in a non-linear model. Our sample contains more than 456,000 observations of vehicles and 87,000 observations of fleets. Non-observable factors are treated as random effects. The distribution of accidents is affected by both observable and non-observable factors from drivers, vehicles and fleets. Past experience of both individual drivers and individual fleets is very significant to explain road accidents. Unobservable factors are also significant, which means that insurance pricing should take into account both observable and unobservable factors in predicting the rate of road accidents under asymmetric information.

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.

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 employment relationship leads to notable biases in the estimated coefficients. In particular, the impact of wages on absences is underestimated in simpler models.

An Evaluation of the Effects on Crashes of the 1991 Legislative Reform on New Licensees in Quebec

Any learning task, particularly a complex one such as driving an automobile, needs time and experience to arrive at a good performance.