The Value of the Risk to Life in the Context of Crime

2019 ◽  
Vol 10 (2) ◽  
pp. 178-205 ◽  
Author(s):  
Emilio Picasso ◽  
Mariana Conte Grand
Keyword(s):  
Negative Impact ◽  
Stated Preference ◽  
Positive Influence ◽  
Income Risk ◽  
Benefit Cost Analysis ◽  
Developed Economies ◽  
Statistical Life ◽  
Victimization Experience ◽  
Public Policy Decisions ◽  
Benefit Cost

AbstractThe value of the risk to life is a key element for benefit-cost analysis, enabling more rational public policy decisions in diverse areas as environmental, health, and crime. We value the risk to life in the context of crime using a discrete choice experiment (CE). The method has clear advantages in that it applies to the whole population and does not require vast data from labor markets, for example. Such data are not always available even in developed economies. Combining the stated preference approach with contingent valuation (CV), CE offer advantages yet to be explored in the context of crime. We demonstrate the application in a developing economy, where similar valuations are not available. The best estimate obtained for Argentina is an average of 1.5 million in 2015 US dollars per statistical life with a confidence interval ($1.1–$2.3). This result is consistent with estimates for the developed world, after appropriate transfer. We also analyze demographic factors in the risk to life, finding a positive influence of income, risk aversion, previous victimization experience and family size on the value of a statistical life, as well as a negative impact of individualism.

scholarly journals What is the meaning of (statistical) life? Benefit–cost analysis in the time of COVID-19

2020 ◽  
Vol 36 (Supplement_1) ◽  
pp. S56-S63 ◽  
Author(s):  
Jonathan Colmer
Keyword(s):  
Social Benefits ◽  
Current Crisis ◽  
Mortality And Morbidity ◽  
Benefit Cost Analysis ◽  
Mortality Risks ◽  
Statistical Life ◽  
The Social ◽  
Morbidity Risks ◽  
Public Policy Decisions ◽  
Benefit Cost

Abstract Efforts to support public policy decisions need to be conducted carefully and thoughtfully. Recent efforts to estimate the social benefits of reductions in mortality risks associated with COVID-19 interventions are likely understated. There are large uncertainties over how much larger the social benefits could be. This raises questions about how helpful conventional approaches to valuing mortality and morbidity risks for benefit–cost analyses can be in contexts such as the current crisis.

Publication Selection Biases in Stated Preference Estimates of the Value of a Statistical Life

2020 ◽  
Vol 11 (3) ◽  
pp. 357-379
Author(s):  
Clayton J. Masterman ◽  
W. Kip Viscusi
Keyword(s):  
Labor Market ◽  
Occupational Injuries ◽  
Stated Preference ◽  
Meta Analysis ◽  
Mean Value ◽  
Benefit Cost Analysis ◽  
Statistical Life ◽  
The Usa ◽  
Benefit Cost ◽  
Lower Income Countries

AbstractThis article presents the first meta-analysis documenting the extent of publication selection biases in stated preference estimates of the value of a statistical life (VSL). Stated preference studies fail to overcome the publication biases that affect much of the VSL literature. Such biases account for approximately 90% of the mean value of published VSL estimates in this subset of the literature. The bias is greatest for the largest estimates, possibly because the high-income labor market and stated preference estimates from the USA serve as an anchor for the VSL in other higher income countries. Estimates from lower-income countries exhibit less bias but remain unreliable for benefit-cost analysis. Unlike labor market estimates of the VSL, there is no evidence that any subsample of VSL estimates is free of significant publication selection biases. Although stated preference studies often provide the most readily accessible country-specific VSL estimates, a preferable approach to monetizing mortality risk benefits is to draw on income-adjusted estimates from labor market studies in the USA that use Census of Fatal Occupational Injuries risk data. These estimates lack publication selection effects as well as the limitations that are endemic to stated preference methods.

scholarly journals Comparing the Application of CEA and BCA to Tuberculosis Control Interventions in South Africa

2019 ◽  
Vol 10 (S1) ◽  
pp. 132-153 ◽  
Author(s):  
Thomas Wilkinson ◽  
Fiammetta Bozzani ◽  
Anna Vassall ◽  
Michelle Remme ◽  
Edina Sinanovic
Keyword(s):  
South Africa ◽  
South African ◽  
Methodological Approach ◽  
Value Of Statistical Life ◽  
Policy Recommendations ◽  
Benefit Cost Analysis ◽  
Tb Control ◽  
Statistical Life ◽  
Benefit Cost ◽  
The Impact

Achieving ambitious targets to address the global tuberculosis (TB) epidemic requires consideration of the impact of competing interventions for improved identification of patients with TB. Cost-effectiveness analysis (CEA) and benefit-cost analysis (BCA) are two approaches to economic evaluation that assess the costs and effects of competing alternatives. However, the differing theoretical basis and methodological approach to CEA and BCA is likely to result in alternative analytical outputs and potentially different policy interpretations. A BCA was conducted by converting an existing CEA on various combinations of TB control interventions in South Africa using a benefits transfer approach to estimate the value of statistical life (VSL) and value of statistical life year (VSLY). All combinations of interventions reduced untreated active disease compared to current TB control, reducing deaths by between 5,000 and 75,000 and resulting in net benefits of Int$3.2–Int$137 billion (ZAR18.1 billion to ZAR764 billion) over a 20-year period. This analysis contributes to development and application of BCA methods for health interventions and demonstrates that further investment in TB control in South Africa is expected to yield significant benefits. Further work is required to guide the appropriate analytical approach, interpretation and policy recommendations in the South African policy perspective and context.

Is Existence Value Appropriate for Regulatory Benefit–Cost Analysis?

2020 ◽  
Vol 11 (3) ◽  
pp. 441-456
Author(s):  
Seth Binder
Keyword(s):  
Cost Analysis ◽  
Cognitive Biases ◽  
Stated Preference ◽  
Natural Resource Economics ◽  
Cost Analyses ◽  
Existence Value ◽  
Benefit Cost Analysis ◽  
Ethical Frameworks ◽  
Existence Values ◽  
Benefit Cost

AbstractSince its introduction to the field of environmental and natural resource economics in the late 1960s, existence value has faced several critiques from economists, psychologists, and philosophers. Critics have taken aim at the notion’s conceptual ambiguity and lack of connection to observable behavior, its incompatibility with cognitive processes and its sensitivity to cognitive biases, and ethical shortcomings in applying existence values to environmental decisionmaking. Unlike some critiques of existence value that draw on cognitive and ethical frameworks for decisionmaking fundamentally at odds with stated preference methods and benefit–cost analysis (BCA), this paper takes as given the use and adequacy of both. It focuses on challenges to existence value per se, with respect to the ability of existence value estimates to contribute to benefit–cost analyses in a way that is consistent with qualities of BCA that its proponents value: the objectivity, commensurability, and moral salience of the values analyzed. In light of the challenges, inclusion of existence value in benefit–cost analyses is found to inevitably compromise the quality of the BCA with respect to each criterion.

scholarly journals Valuing Mortality Risk Reductions in Global Benefit-Cost Analysis

2019 ◽  
Vol 10 (S1) ◽  
pp. 15-50 ◽  
Author(s):  
Lisa A. Robinson ◽  
James K. Hammitt ◽  
Lucy O’Keeffe
Keyword(s):  
Mortality Risk ◽  
Income Elasticity ◽  
Lower Income ◽  
Middle Income ◽  
Income Differences ◽  
Benefit Cost Analysis ◽  
Middle Income Countries ◽  
Statistical Life ◽  
The Past ◽  
Benefit Cost

The estimates used to value mortality risk reductions are a major determinant of the benefits of many public health and environmental policies. These estimates (typically expressed as the value per statistical life, VSL) describe the willingness of those affected by a policy to exchange their own income for the risk reductions they experience. While these values are relatively well studied in high-income countries, less is known about the values held by lower-income populations. We identify 26 studies conducted in the 172 countries considered low- or middle-income in any of the past 20 years; several have significant limitations. Thus there are few or no direct estimates of VSL for most such countries. Instead, analysts typically extrapolate values from wealthier countries, adjusting only for income differences. This extrapolation requires selecting a base value and an income elasticity that summarizes the rate at which VSL changes with income. Because any such approach depends on assumptions of uncertain validity, we recommend that analysts conduct a standardized sensitivity analysis to assess the extent to which their conclusions change depending on these estimates. In the longer term, more research on the value of mortality risk reductions in low- and middle-income countries is essential.

scholarly journals Benefit–Cost Analysis of Community-Led Total Sanitation: Incorporating Results from Recent Evaluations

2020 ◽  
Vol 11 (3) ◽  
pp. 380-417 ◽  
Author(s):  
Mark Radin ◽  
Marc Jeuland ◽  
Hua Wang ◽  
Dale Whittington
Keyword(s):  
Case Fatality ◽  
Sub Saharan Africa ◽  
Positive Health ◽  
Benefit Cost Analysis ◽  
Statistical Life ◽  
Diarrhea Incidence ◽  
Sub Saharan ◽  
Benefit Cost ◽  
Additional Reduction ◽  
Rate Case

AbstractWe analyze the economic costs and benefits of “community-led total sanitation” (CLTS), a sanitation intervention that relies on community-level behavioral change, in a hypothetical rural region in sub-Saharan Africa with 200 villages and 100,000 people. The analysis incorporates data on the effectiveness of CLTS from recent randomized controlled trials and other evaluations. The net benefits of this intervention are estimated both with and without the inclusion of a positive health externality, that is, the additional reduction in diarrhea for an individual when a sufficient proportion of other individuals in the community construct and use latrines and thereby decrease the overall load of waterborne pathogens and fecal bacteria in the environment. We find that CLTS interventions would pass a benefit–cost test in many situations, but that outcomes are not as favorable as some previous studies suggest. The model results are sensitive to baseline conditions, including the value of time, income level used to calculate the value of a statistical life, discount rate, case fatality rate, diarrhea incidence, and time spent traveling to defecation sites. We conclude that many communities likely have economic investment opportunities that are more attractive than CLTS, and recommend careful economic analysis of CLTS in specific locations.

scholarly journals Benefit-Cost Analysis with Local Residents’ Stated Preference Information: A Study of Non-Motorized Transport Investments in Pune, India

2011 ◽  
Vol 2 (3) ◽  
pp. 1-37 ◽  
Author(s):  
Hua Wang ◽  
Ke Fang ◽  
Yuyan Shi
Keyword(s):  
Willingness To Pay ◽  
Stated Preference ◽  
Contingent Valuation Method ◽  
Economic Value ◽  
Development Project ◽  
Benefit Cost Analysis ◽  
Local Residents ◽  
The Government ◽  
Benefit Cost ◽  
Motorized Transport

One of the major difficulties in doing benefit-cost analyses of a development project is to estimate a total economic value of the project benefits, which are usually multi-dimensional and include goods and services that are not traded in the market, and challenges also arise in aggregating the values of different benefits, which may not be mutually exclusive. This paper presents an analysis of a non-motorized transport project in Pune, India, which uses the contingent valuation method to estimate the total value of the project benefits across beneficiaries. A sample of the project beneficiaries are presented with a detailed description of the project and then are asked to vote on whether such a project should be undertaken given different specifications of costs to their households. A function of willingness-to-pay for the project is then derived from the survey answers and the key determinants are found to include household income, distance to the project streets, current use of the transportation modes, future use of the project streets, predicted impacts of the project, and level of trust in the government. The total willingness-to-pay of the local residents is found to be smaller than the total cost of an initial design of the project. Heteroskedasticity is also found to present in the willingness-to-pay models.

scholarly journals The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19

2020 ◽  
Vol 11 (2) ◽  
pp. 179-195 ◽  
Author(s):  
Linda Thunström ◽  
Stephen C. Newbold ◽  
David Finnoff ◽  
Madison Ashworth ◽  
Jason F. Shogren
Keyword(s):  
Economic Activity ◽  
Critical Parameters ◽  
Social Distancing ◽  
Benefit Cost Analysis ◽  
Statistical Life ◽  
Unknown Factor ◽  
Net Benefits ◽  
Benefit Cost ◽  
Benefits And Costs

AbstractWe examine the net benefits of social distancing to slow the spread of COVID-19 in USA. Social distancing saves lives but imposes large costs on society due to reduced economic activity. We use epidemiological and economic forecasting to perform a rapid benefit–cost analysis of controlling the COVID-19 outbreak. Assuming that social distancing measures can substantially reduce contacts among individuals, we find net benefits of about $5.2 trillion in our benchmark case. We examine the magnitude of the critical parameters that might imply negative net benefits, including the value of statistical life and the discount rate. A key unknown factor is the speed of economic recovery with and without social distancing measures in place. A series of robustness checks also highlight the key role of the value of mortality risk reductions and discounting in the analysis and point to a need for effective economic stimulus when the outbreak has passed.

Applying Benefit/Cost Analysis To Identify and Measure the Benefits of Intelligent Transportation Systems

1998 ◽  
Vol 1651 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Daniel Brand
Keyword(s):  
Data Collection ◽  
Customer Satisfaction ◽  
Cost Analysis ◽  
Intelligent Transportation Systems ◽  
Stated Preference ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Benefit Cost Analysis ◽  
Benefit Cost ◽  
Model Chain

The guidance provided by benefit/cost analysis (BCA) is used to identify the measures appropriate for assessing the benefits of intelligent transportation systems (ITS) investments using BCA. Proper recognition of how ITS differs from conventional transportation improvements can avoid expensive data collection, serious underestimates of the benefits of ITS, and mistakes in our planning and investment policies. The steps in BCA are described, including its strict rules governing the inclusion of benefit measures. An ITS causal model chain is presented that links the five traditional ITS goals (efficiency, mobility, safety, productivity, and energy/environment). The model chain varies from the conventional planning model because the ITS mobility and productivity benefit measures do not vary directly with its safety, energy, and environmental impacts. Recommendations are given for avoiding double counting ITS mobility and productivity benefits, and for identifying them correctly. Errors in valuing the mobility benefit using observed data on travel and ITS product and service buying behavior are described, as is the potential for serious underestimates of ITS mobility benefits from using observed or predicted travel time savings as the primary mobility benefit measure. Instead, direct measurement and valuation of the ITS mobility benefit using customer satisfaction (stated preference) survey methods avoid the problems of ( a) how exactly to measure the utility-generating features of ITS user benefits, and ( b) observing the behavioral responses to ITS information, which involve expensive data collection. Measuring customer satisfaction directly can also simplify other areas of ITS evaluation, including avoiding traditional transportation modeling in some instances.

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