Type of paper:Â | Essay |
Categories:Â | Risk Statistics |
Pages: | 6 |
Wordcount: | 1585 words |
The Value of a Statistical Life Concept
The need to reduce risks is a collective undertaking for many people everywhere in the world. In any project or business, risk assessment is the standard issue put into consideration. There are many programs aimed at reducing the risk of death. For instance, People in the market pay for goods and services on willing to pay (WTP) basis and the same case should apply when it comes to reducing death risks (Freeman, 2003). There are regulatory measures put in place to reducerisk that may cause harm. For example, programs on safety of the environment are aimed at reducing the health risks. These programs contribute significantly to the health benefit of the society. The reason people invest in purchasing a safety belt is that they judge that the reduction in risk associated with a car accident is worth the cost of the safety belt.
In the concept value statistical life, risks are observed as the possible cause of death and the cost that people are willing to pay in order to reduce mortality risk. For example, suppose the municipality decides to come up with a project to build a bridge for crossing the road where it is known an average of 5 people die every year from an accident. The plan will reduce the fatalities by 2 in a city with 100, 000 people. Suppose people are willing to pay an amount of $100 per year in support of the project, VSL would be 100*100000/2 = $5 million. The value of statistics life would be $ 5million.
The values of statistical life are measured by establishing the amount of money the society is readyto pay willingly to reduce death risks. The society's will to pay can be measured by conducting surveys on the amount an individual is willing to pay in order to live more. Compared to goods, the ready to pay study is overestimated (Brown et al. 1996; Bishop and Heberlein 1979). WTP is also measured by observing what people are WTP for goods aimed at reducing risks of injury such as work gear such as protective clothing in construction works. It can also be done by observing how much workers in an organisation are willing to pay for improvement of work living conditions regarding ensuring safety at the workplace.
Making the VSL concept acceptable to people requires people to know the importance of reducing any risks that might be mortal.
Estimating the Value Statistical Life (VSL)
Methods of determining the VSL can be categorised into Revealed preferences and stated preferences. Revealed preferences are got from some situations where observations are made on an individual's behaviours in making a tradeoff decisions between money and physical risk. In a revealed preference, the researcher will observe how an individual make tradeoffs between giving something of value like cash to cut down the probability of dying or having an injury (Blomquist, 2004). For instance,a person willing to pay for a smoke detector for alerting in case of fire in a house. Consumer decisions on transport like buying a bicycle helmet (Jerkins et al., 2001) or purchase specific car models for safety (Atkinson and Halvorsen, 1990) have been used in estimating the VSL.
Stated preference methods use non-market techniques to measure the amount people would be willing to pay for services or goods that are not exchanged in the market economy. The contingent valuation method (CVM) is the one that prevails in traffic in terms of evaluation on VSL ( Mitchell and Carson, 1989 ; Bateman et al., 2002). In Contigent Valuation Method, enquiries are made on how much people woulb be willing to pay for different types of risk reduction types of risk reduction. Or the amount of money they would demand in terms of compensation for the risks.
All the techniques for estimating VSL have limitations. For instance, Risk perception is a limitation where people have bases in estimating small risk probabilities. This is because estimations are given according to a willingness to pay for reduced risks. Estimates that are based on how risk is perceived are either inaccurate or biased. People have a tendancy to overestimate risks that are small and under estimate considerable dangers according to cognitive bias, and this could lead to fewer resources being used to mitigate significant risks.
Making Value statistical life palatable to the general public can only involve providing more information on the importance of VSL. It has been developed and used in the US by policymakers to analyse and reduce death risks. The people need awareness on the role of VSL in estimating risks and overcoming them. One way the VSL minimise death risks is through ensuring traffic safety policies and projects. Different VSL models can be used for various populations in a way that suits that particular population.
(Gayer et al., 2000, Bleichrodt and Eeckhoudt, 2006) argues that if individuals perceive risks to be high than they are, their will to pay for reduction of the risks is expected to be high than if the individuals were informed better. This means that VSL depends on how people perceive their mortality risks.
Some factors complicate the VSL estimates. This is because people with specific characteristics and risk type vary regarding their WTP FOR the risks. Therefore, some factors are to be considered when it comes to VSL. Such element includes; income, wealth, health and age.
Certain things matter in age. The age concept suggests that reducing the probability of death for an old person have different benefits to lowering likelihood of death for a younger person. In this, reducing death risk for a more youthful person would mean that the young person gets a chance to be productive to the nation, unlike the old people who are not of great value to the country since their productivity is reduced. We expect a 20-year-old with more than 50 years to live to derive more welfare than a 60-year-old person with less than 20 years to live. According to intuition, for a person who dies at 20 years that is seen as a tragedy, unlike a person who dies at 60 years. With that in mind, it is expected that a person who is 20 years have a whole life to live and risk reduction should be high. However, this is not reflected in the WTP for risk reductions for the young. Instead, the amount one is willing to pay for reduction of risks of dying is high for the elderly than the young people
Health also affects the VSL in that people prefer non-fatal diseases and injuries. People who have terminal diseases pay more for VSL to reduce the probability of dying than people with non-fatal illnesses. Willing to pay for risks in future is also low than willing to pay for risks which are current. Pain and disability also are determining factors for VSL since those who have mortal dangers with intense pain are willing to pay more to lower the risks. The government advice is that in analysis, any analysis method should use high values for the elderly in their willingness to pay for their risks.
In conclusion, the willingness to pay model in VSL makes a lot of sense though controversial in some ways. People should always pay what they are eager to get rid of risks and especially death risks. However, the estimation methods for Value statistical life are still in question on their accuracy and also biasness depending on peoples' different needs and characteristics. There is need to support VSL with more reliable and accurate criteria for estimations.
References
Aldy, Joseph E. and W. Kip Viscusi (2007), Age differences in the value of statistical life, Review of Environmental Economics and Policy 1: 241-260.
Anna A., Maureen, C., Alan, K., and Nathalie B.S., (2004) Does the value of a statistical life vary with age and health status? Evidence from the US and Canada. Journal of Environmental Economics and Management 48 769-792. [online] Available at: https://www.econ.umd.edu/sites/www.econ.umd.edu/files/pubs/jc49.pdf [accessed 3rd May 2018.].
Azimatun, N., Aizuddin, Saperi, S., and Syed, M.A. Methods and tools for measuring willingness to pay for healthcare: what is suitable for developing countries?
Bishop, R. and Heberlein T. 1979, 'Measuring Values of Extra-Market Goods: Are Direct Measures Biased?' American Journal of Agricultural Economics, vol. 61, pp. 926-930.
Cameron, Trudy Ann (2010), Euthanizing the value of a statistical life, Review of Environmental Economics and Policy 4: 161-178.
Hammitt, James K. (2007), Valuing changes in mortality risk: Lives saved versus life years saved, Review of Environmental Economics and Policy 1: 228-240.
Krupnick, A., Alberini, M., Cropper, N., Simon, B., O'Brien, R., Goeree, M., and Heintzelman, (2002). Age, health and the willingness to pay for mortality risk reductions: a contingent valuation study of Ontario residents, J. Risk Uncertainty24 161-186
Krupnick, Alan (2007), Mortality-risk estimate and age: Stated preference evidence, Review of Environmental Economics and Policy 1: 261-282.
Moore, M.J., and Viscusi, W.K. (1988) The quantity-adjusted value of life, Econ. Inq. 26 369 388.
Robinson, L.A. and Hammitt, J.K. (2011). Valuing Health and Longevity in RegulatoryAnalysis: Current Issues and Challenges, (In the Handbook on the Politics of Regulation (D. Levi-Faur, ed.). Cheltenham and Northampton: Edward Elgar. [online] Available at www.regulatory-analysis.com. [accessed 3rd May 2018.].
Ryan, C. B., Alecia, H., and Ahsan, K, (2017)The value of a statistical life: economics and politics. [online] Available at: https://strata.org/pdf/2017/vsl-full-report.pdf [accessed 3rd May 2018.].
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Sunstein, and Cass, R. (2013). "The Value of a Statistical Life: Some Clarifications and Puzzles." Regulatory Policy Program Working Paper RPP-2013-18.
Viscusi, K.W. (2013). The Benefits of Mortality Risk Reduction. The Duke Law Journal, 62, 1735-1745.
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