Target Level Of Risk Research Articles

Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management

An agricultural producer's crop yield and the subsequent farming revenues are affected by many complex factors, including price fluctuations, government policy and climate (e.g., rainfall and temperature) extremes. Geographical diversification is identified as a potential farmer adaptation and decision support tool that could assist producers to reduce unfavourable financial impacts due to the variabilities in crop price and yield, associated with climate variations. There has been limited research performed on the effectiveness of this strategy. This paper proposes a new statistical approach to investigate whether the geographical spread of wheat farm portfolios across three climate broad-acre (i.e., rain-fed) zones could potentially reduce financial risks for producers in the Australian agro-ecological zones. A suite of popular and statistically robust tools applied in the financial sector based on the well-established statistical theories, comprised of the Conditional Value-at-Risk (CVaR) and the joint copula models were employed to evaluate the effectiveness geographical diversification. CVaR is utilised to benchmark the losses (i.e., the downside risk), while the copula function is employed to model the joint distribution among marginal returns (i.e., profit in each zone). The mean-CVaR optimisations indicate that geographical diversification could be a feasible agricultural risk management approach for wheat farm portfolio managers in achieving their optimised expected returns while controlling the risks (i.e., target levels of risk). Further, in this study, the copula-based mean-CVaR model is seen to better simulate extreme losses compared to the conventional multivariate-normal models, which underestimate the minimum risk levels at a given target of expected return. Among the suite of tested copula-based models, the vine copula in this study is found to be a superior in capturing the tail dependencies compared to the other multivariate copula models investigated. The present study provides innovative solutions to agricultural risk management with advanced statistical models using Australia as a case study region, also with broader implications to other regions where farming revenues may be optimized through copula-statistical models.

Chosen risk level during car-following in adverse weather conditions

This study examines how precipitation, light conditions and surface conditions affect the drivers’ risk perception. An indicator CRI (Chosen Risk Index) is defined, which describes the chosen risk level for drivers in a car-following situation. The dataset contains about 70 000 observations of driver behaviour and weather status on a rural road. Based on the theory of risk homeostasis and an assumption that driving behaviour in situations with daylight, dry road and no precipitation reflects drivers’ target level of risk, generalised linear models (GLM) were estimated for cars and trucks separately to reveal the effect of adverse weather conditions on risk perception. The analyses show that both car and truck drivers perceive the highest risk when driving on snow covered roads. For car drivers, a snow covered road in combination with moderate rain or light snow are the factors which lowers the CRI the most. For trucks, snow cover and partially covered roads significantly lowers the CRI, while precipitation did not seem to impose any higher risk. Interaction effects were found for car drivers only.

The Human Element in Shipping Casualties as a Process of Risk Homeostasis of the Shipping Business

Evidence for the existence of risk compensation behaviour in the operation of vessels is shown in the paper The Risk Homeostasis Theory (Baniela and Ríos, 2010). In that analysis, it is concluded that the people engaged in the commercial affairs of ships tend to exchange the level of safety standard of vessels for a more profitable and riskier activity, which makes the rate of shipping accidents fluctuate within certain limits. Since the different levels of power and motivation of those involved in the risk-taking process were not considered in that research, it is the aim of this paper to analyse, on the one hand, how the pressure of the shipping market influences the risk behaviour of shipping business decision-makers and to show, on the other hand, how this influence makes them alter their target level of risk and introduce risks related to low operating cost strategies on vessels. This behavioural adaptation to the shipping market demand has led the human element to be regarded as a factor of risk in the activity of commercial vessels. In this context, the increasing incidence of human errors has arisen as a consequence of practices and manning policies established by the managers of shipping companies.

Risk Compensation-Can Improved Safety Degrade Performances?

In Brief The management and control of risk are a priority activity in both the design and utilization of medical devices. An important but often overlooked aspect of risk management is how people and organizations respond to changes in risk. Such changes, although they may be small, might have important safety considerations. The hypothesis of risk compensation is that people experiencing a real or perceived change in the riskiness of an activity will deliberately or subconsciously alter their behavior to obtain a new combination of risk and reward. In other words, risk compensation is the achievement of a new balance between behavior and the perceived risk. This is in contrast to the typical albeit tacit assumption that risk will always go down as a result of a technical or system risk-reducing improvement. Instead of the risk actually going down, the behavioral result of risk compensation can be to maintain a level of risk that is relatively constant. This level, known as the target level of risk, is different for everyone because it is based on the perception of the risk and the level at which the individual feels safe. Individuals will compensate for risk reduction with different actions and to different degrees, depending in part on the particular situation. The ultimate risk may become reduced but not as reduced as was theoretically possible. The worst scenario is when the change in behavior is so inappropriate that the risk actually goes up. This can occur in particular when the user's perception of the degree of risk improvement is more than the actual improvement, that is, the systematic change has not reduced the risk as much as the users of the system think is the case. If there is risk compensation, then the compensation can more than offset the improvement. The concept of risk compensation is important because it means that the risk reduction that could theoretically be obtained by a system change will not be fully achieved in the absence of strict controls because the users of the system will alter their behavior in a way that seems favorable to them but that is adverse to overall safety. The management and control of risk are a priority activity in both the design and utilization of medical devices. An important but often overlooked aspect of risk management is how people and organizations respond to changes in risk. Such changes, although they may be small, might have important safety considerations. The hypothesis of risk compensation is that people experiencing a real or perceived change in the riskiness of an activity will deliberately or subconsciously alter their behavior to obtain a new combination of risk and reward. In other words, risk compensation is the achievement of a new balance between behavior and the perceived risk. This is in contrast to the typical albeit tacit assumption that risk will always go down as a result of a technical or system risk-reducing improvement. Instead of the risk actually going down, the behavioral result of risk compensation can be to maintain a level of risk that is relatively constant. This level, known as the target level of risk, is different for everyone because it is based on the perception of the risk and the level at which the individual feels safe. Individuals will compensate for risk reduction with different actions and to different degrees, depending in part on the particular situation. The ultimate risk may become reduced but not as reduced as was theoretically possible. The worst scenario is when the change in behavior is so inappropriate that the risk actually goes up. This can occur in particular when the user's perception of the degree of risk improvement is more than the actual improvement, that is, the systematic change has not reduced the risk as much as the users of the system think is the case. If there is risk compensation, then the compensation can more than offset the improvement. The concept of risk compensation is important because it means that the risk reduction that could theoretically be obtained by a system change will not be fully achieved in the absence of strict controls because the users of the system will alter their behavior in a way that seems favorable to them but that is adverse to overall safety.

Risky health and safety habits related to perceived value of the future

Risk homeostasis theory postulates that people accept a specific level (target level) of risk in a given activity in return for benefits accruing from that activity. It follows that, if people expect a great deal from the future, the less likely they are to jeopardise it by taking risks in respect of their health and safety. One effective method for reducing target level of risk are incentives, and the available literature contains ample evidence of the effectiveness of incentives programmes in accident prevention. As incentives essentially imply an enhanced quality of life in the future, the question arises as to how expectations of the future may be related to health and safety habits. In order to explore the relationship between perceived value of the future and health and safety habits, an analysis of the psychological literature on individual differences in future time orientation/perspective is presented. Four factors are identified: (1) clear ideation of the future, (2) active planning for the future, (3) time pressure, and (4) optimistic expectations about events outside one's own control. It is hypothesised that factors (1) and (2) are associated with positive health and safety habits, while factors (3) and (4) may characterise individuals with relatively high target levels of physical risk. Research questions and procedures for the study of these relationships are discussed.

Risk homeostasis and the purpose of safety regulation

Abstract The risk homeostasis theory suggests that safety measures will not reduce accident loss unless they lower ‘target levels of risk’. The theory is plausible but untestable—target levels of risk are unmeasurable, and no all-embracing index of accident loss exists. Risk compensation effects are frequently underestimated. If danger is defined as the potential of some thing or activity to cause harm, then accident statistics are a worthless measure of it. Because people react to perceived changes in safety, situations can be rendered safer or more dangerous without altering the numbers of accidents that they cause. Legislators and regulators who seek to promote safety, and measure their achievements with accident statistics are likely to be either chronically frustrated or deceived. The ‘road safety community’ needs a new agenda. It should be less concerned about protecting people from themselves, probably an impossible task, and more concerned about achieving a fairer distribution of road traffic risk.

Goals, Risks, and Choices

Prof. Wilde tells us that the effect of a non-motivational change in the safety environment on the expected accident rate is nil. I suppose that the cautious thing to do is to note that this result is a hypothesis wrapped in an interesting, and perhaps plausible model of behavioral dynamics. We should call for additional empirical and theoretical work, but the major purpose of my comment is to suggest directions for X tracting additional insight from existing literature. An interesting revelation from Wilde's own perusal of the literature is that some of the most recent research was performed without explicit guidance from a risk compensation hypothesis. Risk compensation concepts appear to have developed along independent but parallel paths in at least three social disciplines. The work in psychology, sociology, and economics is faithful to the usual modes of thought in each of these areas, yet what is common among these approaches is much more important than their differences. Prof. Wilde makes statements about underlying variables that determine the risk target at an individual level. This is where his work as a psychologist is most closely linked to that of other disciplines; however, his emphasis on the behavioral dynamics at the individual level -- the perception, decision, and controlled skilled used by the individual in adapting to a target level of risk. This behavior dynamic is been aggregated over individuals and time to obtain a model relating risk targets to accident rates.... Language: en

Incentive systems for accident-free and violation-free driving in the general population.

A comprehensive model of driver behaviour and accident causation shows four central variables: (a) perceptual skills relative to accident risk, (b) judgemental (decisional) skills relevant to risk-reducing and risk-enhancing actions, (c) psychomotor control skills related to vehicle handling and (d) the target level of risk, that is the degree of risk the driver wishes to accept. It can be shown on both theoretical and empirical grounds that safety promotion efforts which attempt to alter the first three of these variables can only have a temporary influence on accident frequency. Long-term effects, on the other hand, may be obtained through policy actions upon the level of desired risk in the driver population. From a utility model of the factors that control desired risk, the potential beneficial effect of instituting incentives for accident-free driving may be derived. The available literature on this point is reviewed in an attempt to identify the critical features of effective incentive programmes.