Factors Associated with the Enactment of Safety Belt and Motorcycle Helmet Laws

It has been shown that road safety laws, such as motorcycle helmet and safety belt laws, have a significant effect in reducing road fatalities. Although an expanding body of literature has documented the effects of these laws on road safety, it remains unclear which factors influence the likelihood that these laws are enacted. This study attempts to identify the factors that influence the decision to enact safety belt and motorcycle helmet laws. Using panel data from 31 countries between 1963 and 2002, our results reveal that increased democracy, education level, per capita income, political stability, and more equitable income distribution within a country are associated with the enactment of road safety laws.     

Risk Compensation and Bicycle Helmets

This study investigated risk compensation by cyclists in response to bicycle helmet wearing by observing changes in cycling behavior, reported experience of risk, and a possible objective measure of experienced risk. The suitability of heart rate variability (HRV) as an objective measure of experienced risk was assessed beforehand by recording HRV measures in nine participants watching a thriller film. We observed a significant decrease in HRV in line with expected increases in psychological challenge presented by the film. HRV was then used along with cycling pace and self‐reported risk in a field experiment in which 35 cyclist volunteers cycled 0.4 km downhill, once with and once without a helmet. Routine helmet users reported higher experienced risk and cycled slower when they did not wear their helmet in the experiment than when they did wear their helmet, although there was no corresponding change in HRV. For cyclists not accustomed to helmets, there were no changes in speed, perceived risk, or any other measures when cycling with versus without a helmet. The findings are consistent with the notion that those who use helmets routinely perceive reduced risk when wearing a helmet, and compensate by cycling faster. They thus give some support to those urging caution in the use of helmet laws.     

Real-World Personal Conversations Using a Hands-Free Embedded Wireless Device While Driving: Effect on Airbag-Deployment Crash Rates

A wireless device embedded in the vehicle allowed the user to engage in a personal hands-free conversation (HFC), and automatically placed an emergency notification call to an OnStar call center if the vehicle was involved in a crash in which its airbag deployed. A database stored the exact counts, start timestamps, and billed durations of all HFC and airbag notification calls. In 30 months of naturalistic driving, there were 91 million HFC calls from an average of 323,994 drivers per month who made calls. There were 14 airbag deployments in 276 million driver-minutes of HFC conversation for an exposed incidence rate of 5.08 airbag crashes per 100 million driver-minutes. There were 2,023 airbag deployments in an estimated 24.7 billion driver-minutes of no HFC conversation for a not-exposed incidence rate of 8.18 airbag crashes per 100 million driver-minutes. The crash incidence rate ratio (IRR) is the ratio of these two rates or 0.62 (95% C.I. 0.37 to 1.05). Sensitivity analyses controlled for the impact on the crash IRR of estimated time spent driving per day and calls by passengers. Counting all crashes as much as 20 minutes later than a call as related to that call gave similar results. We conclude that for personal conversations using a hands-free embedded device the risk of an airbag crash is somewhere in a range from a moderately lower risk to a risk near that of driving without a recent personal conversation. These results are not consistent with the large increase in crash risk reported in epidemiological studies using the case-crossover method.     

Safety Impacts of SUVs, Vans, and Pickup Trucks in Two-Vehicle Crashes

Policy makers, vehicle manufacturers, and consumers have shown growing concern about the relative safety of sport utility vehicles (SUVs), vans, pickups, and cars. Empirical analysis of real-world crashes is complicated by the possibility that apparent relationships between vehicle type and safety may be confounded by other factors, such as driver behavior and crash circumstances. This study compares different vehicle types with respect to their crashworthiness (self-protection) and aggressivity (risk to others) in crashes between two passenger vehicles. The U.S. Crashworthiness Data System is used to analyze detailed information on 6,481 drivers involved in crashes during 1993-1999. Logistic regression analysis is used to model the risk of serious injury or death to a driver, conditional on a crash occurring. Covariates include the body type of each vehicle in the crash; the driver's age, gender, and restraint use; and the configuration of the crash. A unique feature of this study is the use of "delta-v" to represent the joint effects of vehicle mass and crash severity. While estimated effects are somewhat sensitive to the injury severity level used as the outcome variable, SUVs, vans, and pickups appear to be more aggressive and may be more crashworthy than cars. Effects of pickups are most pronounced. Drivers in pickups face less risk of serious injury than car drivers (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.20-0.60), and drivers who collide with pickups experience more than twice the risk than those who collide with a car (OR, 2.18; 95% CI, 1.03-4.62). While vehicle mass and crash severity contribute to the apparent crashworthiness and aggressivity of passenger vehicles, other vehicle characteristics associated with body type (e.g., the stiffness and height of the underlying structure of the vehicle) also influence safety risks.     

Trait Predictors of Aggression and Crash‐Related Behaviors Across Drivers from the United Kingdom and the Irish Republic

Aggressive driving is acknowledged as a contributor to motor vehicle crashes. This study explored a theoretical model of aggressive expression and crash‐related outcomes using self‐report data collected, using an online questionnaire, from drivers in the United Kingdom and the Republic of Ireland. The proposed model tested whether the personality traits of boredom proneness, sensation seeking, and impulsivity, coupled with trait driving anger, predicted aggressive driving; and whether aggressive driving predicted crash‐related outcomes (loss of concentration and control, near misses, and moving violations). The structural model was confirmed, with aggressive expressions of anger being found to mediate the relationships driving anger and impulsivity had with the crash‐related outcomes. Multigroup invariance analysis showed that the model remained invariant across drivers from the United Kingdom and Ireland, suggesting that the contributing factors for aggressive expression and crash involvement are similar across both countries. When self‐reported crash‐related conditions were compared between drivers in the United Kingdom and Ireland, drivers in the United Kingdom reported more aggressive driving, more minor crashes, more incidents of road rage, and more frequent losses of concentration and vehicle control.     

The Health Impact of Mandatory Bicycle Helmet Laws

This article seeks to answer the question whether mandatory bicycle helmet laws deliver a net societal health benefit. The question is addressed using a simple model. The model recognizes a single health benefit—reduced head injuries—and a single health cost—increased morbidity due to foregone exercise from reduced cycling. Using estimates suggested in the literature on the effectiveness of helmets, the health benefits of cycling, head injury rates, and reductions in cycling leads to the following conclusions. In jurisdictions where cycling is safe, a helmet law is likely to have a large unintended negative health impact. In jurisdictions where cycling is relatively unsafe, helmets will do little to make it safer and a helmet law, under relatively extreme assumptions, may make a small positive contribution to net societal health. The model serves to focus the mandatory bicycle helmet law debate on overall health.     

Extension of the Application of Conway‐Maxwell‐Poisson Models: Analyzing Traffic Crash Data Exhibiting Underdispersion

The objective of this article is to evaluate the performance of the COM‐Poisson GLM for analyzing crash data exhibiting underdispersion (when conditional on the mean). The COM‐Poisson distribution, originally developed in 1962, has recently been reintroduced by statisticians for analyzing count data subjected to either over‐ or underdispersion. Over the last year, the COM‐Poisson GLM has been evaluated in the context of crash data analysis and it has been shown that the model performs as well as the Poisson‐gamma model for crash data exhibiting overdispersion. To accomplish the objective of this study, several COM‐Poisson models were estimated using crash data collected at 162 railway‐highway crossings in South Korea between 1998 and 2002. This data set has been shown to exhibit underdispersion when models linking crash data to various explanatory variables are estimated. The modeling results were compared to those produced from the Poisson and gamma probability models documented in a previous published study. The results of this research show that the COM‐Poisson GLM can handle crash data when the modeling output shows signs of underdispersion. Finally, they also show that the model proposed in this study provides better statistical performance than the gamma probability and the traditional Poisson models, at least for this data set.     

Redesigning the Downtown of an Expansive Sunbelt City: The Phoenix Case

ABSTRACT

Non-motorized traffic safety is a major public health concern, especially in the sprawling sunbelt cities of the United States. Phoenix is ranked quite high on the number of pedestrian and cyclist crashes in North American cities. This article analyses non-motorist safety incidents in downtown Phoenix. Non-motorist safety concerns were addressed by examining crash types in order to suggest adequate safety treatments. We also demonstrated the use of a countermeasure framework for higher crash locations denominated hotspots. Our findings indicate that it is important to implement a combination of countermeasures to reduce the high number of non-motorist crashes in city centers.     

Child Passenger Safety: Decisions about Seating Location, Airbag Exposure, and Restraint Use

The installation of passenger-side airbags in new vehicles complicates efforts to maximize child safety in motor vehicle crashes. It has been recommended by both public and private organizations that children sit in the rear seat with proper restraint to achieve maximum safety. Drivers now need to decide whether a child should be restrained, where the child should be seated (front versus rear), and whether the child should be seated in front of a passenger-side airbag. This research was undertaken to determine which choice minimizes the risk of fatality to children. Using data from the U.S. Fatality Analysis Reporting System for calendar years 1989 to 1998, fatal vehicle crashes with child passengers younger than 13 years were analyzed. The effectiveness of passenger-side airbags and rear seating for children, by age category and restraint use, was estimated using the double-pair comparison method. For each of four age categories, the fatality risk of each possible combination of restraint use, seating location, and airbag presence was also estimated using logistic regression. Passenger airbags were associated with an increase in child fatality risk of 31% for restrained children, and 84% for unrestrained children. Passenger airbags did appear to offer protection to restrained 9- to 12-year-old children. Restraint use and rear seating were associated with statistically significant reductions in the odds of a child dying in a crash. In order to minimize child fatality risk, parents should seat children in the rear of the vehicle while using the proper child restraint system, especially in vehicles with passenger airbags. These findings support current public education efforts in the United States.     

Technical Note – Pricing Below Cost Under Exchange‐Rate Risk

Pricing below cost is often classified as “dumping” in international trade and as “predatory pricing” in local markets. It is legally prohibited from practice because of earlier findings that it leads to predatory behavior by either eliminating competition or stealing market share. This study shows that a stochastic exchange rate can create incentives for a profit‐minded monopoly firm to set price below marginal cost. Our result departs from earlier findings because the optimal pricing decision is based on a rational behavior that does not exhibit any malicious intent against the competition to be considered as violating anti‐trust laws. The finding is a robust result, because our analysis demonstrates that this behavior occurs under various settings such as when the firm (i) is risk‐averse, (ii) can postpone prices until after exchange rates are realized, (iii) is capable of manufacturing in multiple countries, and (iv) operates under demand uncertainty in addition to the random exchange rate.     

Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk‐cost‐benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right‐of‐way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.     

Should Persons with Diabetes Be Licensed to Drive Trucks?—Risk Management

How should a regulatory agency interpret a risk analysis that concludes there is a small increase in risk? The agency must decide on behalf of society whether the increased risk is large enough to justify banning the risky activity or taking some other step to lessen the risks. In a companion paper (Songer et al.), we conclude that licensing insulin using persons to drive commercial motor vehicles in interstate commerce would result in 42 additional crashes each year. Here we address risk management issues by interpreting the number of additional crashes and the relative risks of the prospective handicapped drivers. Are the number of additional crashes (42) significant? Is the increase in the annual crash risk (from 0.00785 to 0.032 for non-insulin dependent and 0.048 for insulin dependent persons) significant? Are the relative risks significant for all insulin using drivers (4.7)? For drivers with a history of severe hypoglycemic reactions (19.8)? How should society tradeoff risk increases for increases in opportunity for these handicapped persons? We review other social decisions concerning highway safety: Accepting the increasing risks of letting 16 year olds drive, allowing extremely light cars, allowing some unsafe highways, and allowing extremely unsafe driving conditions at some times of day. We conclude that the additional risks from insulin using persons are well within the current accepted range of risks. Currently, 70% of states permit insulin using persons to drive trucks within their state. Nonetheless, the social cost, due to fatalities, injuries, and property damage from allowing a person with a history of severe hypoglycemic reactions to drive is more than $19,700 per year.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.     

Physical injury risks associated with drinking water arsenic treatment.

We estimated the number of transportation deaths that would be associated with water treatment in Albuquerque to meet the EPA's recently proposed revisions of the Maximum Contaminant Level (MCL) for arsenic. Vehicle mileage was estimated for ion exchange, activated alumina, and iron coagulation/microfiltration water treatment processes to meet an MCL of 0.020 mg/L, 0.010 mg/L, 0.005 mg/L, and 0.003 mg/L. Local crash, injury, and death rates per million vehicle miles were used to estimate the number of injuries and deaths. Depending on the water treatment options chosen, we estimate that meeting an arsenic MCL of 0.005 mg/L will result in 143 to 237 crashes, 58 to 98 injuries, and 0.6 to 2.6 deaths in Albuquerque over a 70-year period, resulting in 26 to 113 years of life lost. The anticipated health benefits for Albuquerque residents from a 0.005 mg/L arsenic MCL, estimated using either a multistage Weibull or Poisson model, ranged from 3 to 80 arsenic-related bladder and lung cancer deaths prevented over a 70-year period, adding between 43 and 1,123 years of life. Whether a revised arsenic MCL increases or reduces overall loss of life in Albuquerque depends on the accuracy of EPA's cancer risk assessment. If the multistage Weibull model accurately estimates the benefits, the years of life added is comparable or lower than the anticipated years lost due to transportation associated with the delivery of chemicals, disposal of treatment waste, and operation of the water treatment system. Coagulation/microfiltration treatment will result in substantially fewer transportation deaths than either ion exchange or activated alumina.     

Insurance,Public Assistance,and Household Flood Risk Reduction: A Comparative Study of Austria,England, and Romania

In light of increasing losses from floods, many researchers and policymakers are looking for ways to encourage flood risk reduction among communities, business, and households. In this study, we investigate risk‐reduction behavior at the household level in three European Union Member States with fundamentally different insurance and compensation schemes. We try to understand if and how insurance and public assistance influence private risk‐reduction behavior. Data were collected using a telephone survey (n = 1,849) of household decisionmakers in flood‐prone areas. We show that insurance overall is positively associated with private risk‐reduction behavior. Warranties, premium discounts, and information provision with respect to risk reduction may be an explanation for this positive relationship in the case of structural measures. Public incentives for risk‐reduction measures by means of financial and in‐kind support, and particularly through the provision of information, are also associated with enhancing risk reduction. In this study, public compensation is not negatively associated with private risk‐reduction behavior. This does not disprove such a relationship, but the negative effect may be mitigated by factors related to respondents' capacity to implement measures or social norms that were not included in the analysis. The data suggest that large‐scale flood protection infrastructure creates a sense of security that is associated with a lower level of preparedness. Across the board there is ample room to improve both public and private policies to provide effective incentives for household‐level risk reduction.     

Nonspeculative Bubbles in Experimental Asset Markets: Lack of Common Knowledge of Rationality vs. Actual Irrationality

We report the results of an experiment designed to study the role of speculation in the formation of bubbles and crashes in laboratory asset markets. In a setting in which speculation is not possible, bubbles and crashes are observed. The results suggest that the departures from fundamental values are not caused by the lack of common knowledge of rationality leading to speculation, but rather by behavior that itself exhibits elements of irrationality. Much of the trading activity that accompanies bubble formation, in markets where speculation is possible, is due to the fact that there is no other activity available for participants in the experiment.     

Estimated Rate of Fatal Automobile Accidents Attributable to Acute Solvent Exposure at Low Inhaled Concentrations

Acute solvent exposures may contribute to automobile accidents because they increase reaction time and decrease attention, in addition to impairing other behaviors. These effects resemble those of ethanol consumption, both with respect to behavioral effects and neurological mechanisms. These observations, along with the extensive data on the relationship between ethanol consumption and fatal automobile accidents, suggested a way to estimate the probability of fatal automobile accidents from solvent inhalation. The problem can be approached using the logic of the algebraic transitive postulate of equality: if A=B and B=C, then A=C. We first calculated a function describing the internal doses of solvent vapors that cause the same magnitude of behavioral impairment as ingestion of ethanol (A=B). Next, we fit a function to data from the literature describing the probability of fatal car crashes for a given internal dose of ethanol (B=C). Finally, we used these two functions to generate a third function to estimate the probability of a fatal car crash for any internal dose of organic solvent vapor (A=C). This latter function showed quantitatively (1) that the likelihood of a fatal car crash is increased by acute exposure to organic solvent vapors at concentrations less than 1.0 ppm, and (2) that this likelihood is similar in magnitude to the probability of developing leukemia from exposure to benzene. This approach could also be applied to other potentially adverse consequences of acute exposure to solvents (e.g., nonfatal car crashes, property damage, and workplace accidents), if appropriate data were available.     

Equitable Taxation and the Provision of Health Insurance Subsidies

Current U.S. income tax laws allow many taxpayers to exclude from taxable income part or all of the cost of acquiring health insurance through an employer‐sponsored benefit plan. This favorable tax treatment generally applies regardless of whether the employer or employee actually pays the health insurance premiums. We describe the effects of this tax policy on the U.S. tax system's horizontal and vertical equity. We also explain how taxpayers covered by employer‐sponsored plans are significantly subsidized by the government in acquiring health insurance, whereas taxpayers who acquire health insurance by other means or who are not covered by health insurance at all receive no such government assistance. We conclude that any prospective health‐care policy initiatives, including modifications to the 2010 health‐care reforms, should contemplate both the horizontal and vertical equity of the tax treatment of health insurance premiums.     

On the Size Distribution of Macroeconomic Disasters

The coefficient of relative risk aversion is a key parameter for analyses of behavior toward risk, but good estimates of this parameter do not exist. A promising place for reliable estimation is rare macroeconomic disasters, which have a major influence on the equity premium. The premium depends on the probability and size distribution of disasters, gauged by proportionate declines in per capita consumption or gross domestic product. Long‐term national‐accounts data for 36 countries provide a large sample of disasters of magnitude 10% or more. A power‐law density provides a good fit to the size distribution, and the upper‐tail exponent, α, is estimated to be around 4. A higher α signifies a thinner tail and, therefore, a lower equity premium, whereas a higher coefficient of relative risk aversion, γ, implies a higher premium. The premium is finite if α > γ. The observed premium of 5% generates an estimated γ close to 3, with a 95% confidence interval of 2 to 4. The results are robust to uncertainty about the values of the disaster probability and the equity premium, and can accommodate seemingly paradoxical situations in which the equity premium may appear to be infinite.     

家族董事席位超额控制与股价崩盘风险——基于关联交易的视角

本文基于关联交易的视角,以2008-2017年沪深A股上市家族企业为研究对象,考察了家族董事席位超额控制程度与股价崩盘风险之间的关系。研究发现,家族董事席位超额控制程度与企业的股价崩盘风险、控股家族的关联交易行为正相关;同时,控股家族的关联交易行为对企业股价崩盘风险有显著的正向影响,并且这种影响在家族董事席位超额控程度较高的公司中更为明显。进一步分析发现,机构持股比例较低、两职合一、董事会规模较小时,家族董事席位超额控制程度与企业的股价崩盘风险、控股家族的关联交易规模之间的正相关性更强;控股家族的关联交易规模对企业股价崩盘风险的正向影响更显著,其与家族董事席位超额控制程度的交互关系对股价崩盘风险的正向影响更明显。最后,控制潜在的内生性问题,并进行一系列的稳健性检验后,研究结论依然成立。本文不仅从关联交易的视角探讨了家族董事席位超额控制对资本市场的影响,也为家族企业股价崩盘风险的成因提供了更多的理论解释。