What is the value of a statistical life (VSL)? How does one calculate such a value? Does everyone’s life have a different value? These questions are among the most provocative and delicate topics in economics. The VSL is defined as the "tradeoff between money and small risks of death." It is not to be confused with the amount of compensation one would receive for a wrongful death. It has important policy implications as economic estimates of the VSL amounts have included evidence from market decisions that reveal the implicit values reflected in behavior as well as the use of survey approaches to elicit these money-risk tradeoffs directly. Therefore, the following paper will look at the value of a statistical life, focusing on two things: the age-VSL relationship and the relationship between income and the VSL. It will then talk about some of the factors that affect the VSL and how the VSL itself affects policies and regulations.

The value of statistical life is an estimate of the monetary benefits of preventing an anonymous death. Society's willingness to pay to eliminate private health risks determines agencies' value-of-statistical-life estimates. Most estimates ignore society's willingness to pay to eliminate others' health risks. There are two possible reasons. First, altruism does not exist: Peter is not willing to pay to save Paul's life. The second possible reason is a bit more complicated. Certain economists argue that increasing benefit estimates to account for altruism involves double-counting. The purpose of this thesis is to evaluate these possibilities. Accounting for altruism, it turns out, is not double-counting if altruism is paternalistic. Furthermore, I empirically demonstrate that people are willing to pay to reduce others' health risks. Thus, the two justifications for ignoring altruism are, seemingly, unfounded, which indicates that analysts should increase the value of statistical life to account for altruism.

abstract: My dissertation combines the notion of residential sorting from Tiebout (1956) with Grossman’s (1972) concept of a health production function to develop a new empirical framework for investigating what individuals’ residential location choices reveal about their valuation of amenities, the welfare effects of climate change, the forces underlying environmental justice, and the value of a statistical life. Location choices are affected by age, health, and financial constraints, and by exposure to local amenities that affect people’s health and longevity. Chapter 1 previews how I formalize this idea and investigate its empirical implications in three interrelated essays. Chapter 2 investigates interactions between health, the environment, and income. Seniors tend to move at higher rates after being diagnosed with new chronic medical conditions. While seniors generally tend to move to locations with less polluted air, those who have been diagnosed with respiratory conditions move to relatively more polluted locations. This counterintuitive pattern is reconciled by documenting that new diagnoses bring about increases in medical expenditures, thereby limiting disposable income that can be spent on housing. Relatively cheaper places tend to be more polluted, and higher exposure to pollution leaves seniors more vulnerable to future health shocks. In Chapter 3, I combine information about housing prices with estimates of location-specific effects on mortality to estimate the Value of a Statistical Life (VSL) for seniors - one of the most important statistics used to evaluate policies affecting mortality. Since local amenities correlate with causal mortality effects, but also provide utility independently, the difficulty in controlling for local amenities implies that my VSL estimates are best interpreted as bounds. Chapter 4 builds a new structural framework for evaluating spatially heterogeneous changes to local amenities. I estimate a dynamic model of location choice with a sample of 5.5 million seniors from 2001-2013. Their average annual willingness-to-pay to avoid future climate change in the United States under a “business as usual” scenario ranges from $962 for older, sicker groups who are more vulnerable to climate change’s negative effects on health to -$1,894 for younger, healthier groups, who value warmer winters and are relatively resilient. / Dissertation/Thesis / Doctoral Dissertation Economics 2020

Construction is increasing due to increased demand and degradation of existing infrastructure. This construction often results in a reduced number of traffic lanes or lane width during construction, which often creates queue at the entrance to work zones. Variable Advisory Speed Systems (VASS) provide drivers with advanced warning regarding traffic speeds downstream to help them make better decisions in advance of problems that may exist downstream. The purpose of this study was to evaluate the effectiveness of a VASS at mitigating queues in work zone entrances during peak hour conditions. It was anticipated that by implementing a VASS queues would be reduced and vehicle flow increased in work zone areas. Three objectives of this study were: (1) research VASS systems that are available to be tested, (2) select and deploy a VASS in Utah at a long-term work zone, and (3) perform a statistical analysis on traffic flow characteristic data to evaluate the effectiveness of the VASS on queue mitigation. A literature review on the use of VASS for work zones returned minimal studies on advisory speeds in work zones. Most of the advanced speed notification systems, found during the literature review, used variable speed limit (VSL) applications. A VASS was selected and deployed at the northbound approach to the I-15 Beck St. widening project in North Salt Lake City. In this study the VASS consisted of five sensors and two variable message signs (VMSs). To determine if the system was effective at reducing queue the speed data were analyzed in detail to come to statistical conclusions. The collected data shows that the VASS investigated was effective on weekends during evening peak hours when there was a slow down. No consistent significance was seen on week days during the evening peak. There was no statistical difference between before and after speed data on any day of the week when there was no slow down. This study is valuable because it is unique in studying an advisory speed using VMSs and other ITS technology. This study recommends that further studies be conducted without a movable median barrier system, as was used in this construction project, to evaluate further about the effectiveness of VASSs. It is recommended that, if a VASS is considered, studies be done to see whether queues are expected to form at the work zone entrance, as VASSs will not be effective if queues do not form.

Air pollution—both indoor and outdoor—results in more deaths and diseases in India than in any other country in the world. The first chapter in this dissertation explores why despite profoundly negative health consequences of indoor air pollution, most rural Indian households cook using traditional biomass fuel. Among many factors that contribute to households’ continued use of solid fuels, we focus on one: women’s intra-household status. We exploit Indian son preference: having a girl first child lowers women’s status relative to having a boy first child, and is therefore associated with lower likelihood of using clean fuel. This effect is found throughout the wealth distribution, and is not concentrated among households in states with a high child sex ratio or households where women have some education. The second chapter focuses on outdoor air pollution in India. We use a general equilibrium model of Indian economy to quantify the spillovers from a carbon tax on fossil fuels to local air quality and the health outcomes in urban India. We estimate that a $10/ton of Carbon tax on all fossil fuels will reduce CO2 emission by 10.7% from business-as-usual and save nearly 0.3 million urban lives from pollution related deaths while adding 0.2 percent to the GDP over the three decades from 2003 to 2030. We get this double dividend from carbon tax if the tax revenue is used to reduce existing distortionary taxes. Carbon tax is more progressive if the revenue is repatriated to households, but the GDP is slightly smaller than the base case under this regime. In the third chapter, we present the first VSL estimates from India using hedonic wage method with worker and job characteristics data from Employment and Unemployment Survey of India (EUS)—a large nationally representative survey that has not been used in this literature before. We estimate VSL of an average low-skilled urban Indian worker to be about $85,000 in 2004-05 (about 65 times the annual wage) at 2010 constant prices. Our estimates of VSL and VSL-to-income ratio are much lower than all previous estimates from India. Comparisons with estimates from other developing countries like China and Taiwan, however, suggest that our estimates are more reasonable. Our VSL estimate, if reliable, sets a lower threshold for investment in environment and public safety projects that can be justified using cost-benefit criteria.

Researchers at the University of Central Florida (UCF) have been working during the past few years on different strategies to improve freeway safety in real-time. An ongoing research at UCF has investigated crash patterns that occurred on a stretch of Interstate-4 located in Orlando, FL and created statistical models to predict in real-time the likelihood of a crash in terms of time and space. The models were then tested using PARAMICS micro-simulation and different strategies that would reduce the risk of crashes were suggested. One of the main recommended strategies was the use of Variable Speed Limits (VSL) which intervenes by reducing the speed upstream the segment of high risk and increasing the speed downstream. The purpose of this study is to examine the recommendations reached by the micro-simulation using the UCF driving simulator. Drivers' speed behavior in response to changes in speed limits and different information messages are observed. Different scenarios that represent the recommendations from the earlier micro-simulation study and three different messages displayed using Variable Message Signs (VMS) as an added measure to advice drivers about changes in the speed limit were created. In addition, abrupt and gradual changes in speed were tested against the scenarios that maintained the speed limit constant or did include a VSL or VMS in the scenarios' design (base case). Dynamic congestion was also added to the scenarios' design to observe drivers' reactions and speed reductions once drivers approached congestion. A total of 85 subjects were recruited. Gender and age were the controlling variables for the subjects' recruitment. Each of the subjects drove 3 out of a total of 24 scenarios. In addition, a survey was conducted and involved hypothetical questions, including knowledge about VMS and VSL, and questions about their driving behavior. The survey data were useful in identifying the subjects' compliance with the speed limit and VSL/VMS acceptance. Two statistical analytical techniques were performed on the data that were collected from the simulator: ANOVA and PROC MIXED. The ANOVA test was used to investigate if the differences in speed and reaction distances between subjects were statistically significant for each sign compared to the base case. The PROC MIXED analysis was used to investigate the differences of all scenarios (24x24) based on the spot speed data collected for each driver. It was found from the analyses that drivers follow better the message displayed on VMS that informs them that the speed is changing, whether it is or not, strictly enforced as opposed to providing the reason for change or no information. Moreover, an abrupt change in speed produced immediate results; however both abrupt and gradual changes in speed produced the same reduction in speed at the target zone. It was also noticed that most drivers usually drive 5 mph above the speed limit, even though in the survey analysis the majority of them stated that they drive in compliance with the speed limit or with the flow of traffic. This means that if a modest speed reduction of 5 mph is requested they will ignore it, but if a 10 mph reduction is recommended they will reduce the speed by at least 5 mph. Consequently, it was noticed that drivers arrived at the congestion zone with a slower speed than the base speed limit due to the combination of VMS and VSL signage. By having drivers approaching congestion with a slower speed, potential rear-end crashes could be avoided. Comparing the two genders indicated that females are more likely to follow the VMS's recommendations to reduce the speed. Also females in general drive above the speed limit between 2 mph and 3 mph, while males drive above the speed limit between 5 mph and 8 mph. From the analysis of the age factor, it was concluded that drivers from the 16-19 age group drive faster and drivers from the 45 and above age group drive slower, than the drivers from the other groups. In general, all drivers reduced and/or increased their speed accordingly when a VMS and/or VSL was present in the scenario advising for this change in the speed limit. The investigations conducted for this thesis proved that the recommendations suggested previously based on the crash risk model and micro-simulation (Abdel-Aty et al., 2006) aid drivers in reducing their speed before they approach a segment of high risk and by doing so reduce the likelihood of a crash. Finally, the real-time safety benefits of VMS and VSL should be continuously evaluated in future studies.

This thesis focuses on evaluating the appropriate speed at which vehicles should travel under different traffic conditions on freeways and its impact on crash frequency. The common belief is that the lower speed results in fewer crashes as reduced speed provides drivers with more time to react effectively and avoid collisions. However, this perspective overlooks the interplay among traffic speed, average spacing between consecutive vehicles, and the distance available for stopping a vehicle. Hence, we propose a safety parameter termed ‘Safety Correlate' (SCORE), which is defined as the proportion of average spacing relative to the stopping distance. To determine the relationship between SCORE and crash frequency, data from 366 4-lane urban freeway segments located in Virginia was analyzed and a Random-effects Poisson Lognormal model was developed. The obtained result indicated that the safety parameter SCORE is negatively associated with the annual hourly crash frequency, implying that the lesser the average spacing as a proportion of the stopping distance while traffic flow remains constant, the more frequent will be the crashes. Additionally, this research presents an application of SCORE in setting variable speed limits under various traffic flows. Overall, the study results provide valuable insights by investigating SCORE to improve traffic safety. Also, this research would help practitioners and policymakers to incorporate safety aspects while setting variable speed limits on freeways.

To resolve the wage-risk trade off relationship on the labor market in Czech Republic, we introduce multiple hedonic wage regressions. Empirical theory ad- mits an income and age heterogeneity in value of a statistical life (VSL). This thesis employs a quantile regression along with age-dependent non-fatal and fa- tal on-the-job risk rates to estimate the age and income variation in VSL within a unified framework. Our results, based on EU-SILC 2018 data, implicate an inverted-V-shaped development of VSL with respect to age. The estimates of age-VSL peak for workers within the age cohort 42-47 across most real wage quantile levels and once reaching the maximum point the VSL proceeds to de- cline with age. In order to infer any effects of the global pandemic on VSL, we propose a set of novel COVID-19 control variables. Additionally, we annuitize the VSL estimates, which yields the value of a statistical life year (VSLY). The measures of VSLY correspond to the age and income varying trend of VSL. In conclusion, this thesis offers applicable varying VSL estimates across cohorts and wage distribution to policy-makers and respective authorities. JEL Classification J17, J24, J28, J31, J33 Keywords hedonic wage, compensating wage differential, quantile regression, VSL, income elasticity Title Measuring the...

This research evaluates Intelligent Transportation System (ITS) implementation strategies to improve the safety of a freeway once a potential of a crash is detected. Among these strategies are Variable Speed Limit (VSL) and ramp metering. VSL are ITS devices that are commonly used to calm traffic in an attempt to relieve congestion and enhance throughput. With proper use, VSL can be more cost effective than adding more lanes. In addition to maximizing the capacity of a roadway, a different aspect of VSL can be realized by the potential of improving traffic safety. Through the use of multiple microscopic traffic simulations, best practices can be determined, and a final recommendation can be made. Ramp metering is a method to control the amount of traffic flow entering from on-ramps to achieve a better efficiency of the freeway. It can also have a potential benefit in improving the safety of the freeway. This thesis pursues the goal of a best-case implementation of VSL. Two loading scenarios, a fully loaded case (90% of ramp maximums) and an off-peak loading case (60% of ramp maximums), at multiple stations with multiple implementation methods are strategically attempted until a best-case implementation is found. The final recommendation for the off-peak loading is a 15 mph speed reduction for 2 miles upstream and a 15 mph increase in speed for the 2 miles downstream of the detector that shows a high crash potential. The speed change is to be implemented in 5 mph increments every 10 minutes. The recommended case is found to reduce relative crash potential from .065 to -.292, as measured by a high-speed crash prediction algorithm (Abdel-Aty et al. 2005). A possibility of crash migration to downstream and upstream locations was observed, however, the safety and efficiency benefits far outweigh the crash migration potential. No final recommendation is made for the use of VSL in the fully loaded case (low-speed case); however, ramp metering indicated a promising potential for safety improvement.

Traditional crash frequency prediction models cannot capture the temporal effects of traffic characteristics due to the high level of data aggregation. Also, this approach is less suitable to address the crash risk for active traffic management strategies that typically operate for short-time intervals. Hence, this research proposes short-term crash prediction models for traffic management strategies such as Variable Speed Limit (VSL)/Variable Advisory Speed (VAS), and Part-time Shoulder Use (PTSU). By using high-resolution traffic detectors and VSL/VAS operational data, short-term Safety Performance Functions (SPFs) are estimated at weekday hourly and peak period aggregation levels. The results indicate that the short-term SPFs could capture various crash contributing factors and safety aspects of VSL/VAS more effectively than the traditional highly aggregated Average Annual Daily Traffic (AADT)-based approach. The study also investigates the safety effectiveness of VSL/VAS for different types and severity levels of traffic crashes. The results specify that the VSL/VAS system is effective in reducing rear-end crashes in the Multivariate Poisson Lognormal (MVPLN) crash type model as well as Property Damage Only (PDO) and C (non-incapacitating) crashes in the MVPLN crash severity model. Recommendations include deploying the VSL/VAS system combined with other traffic management strategies, strong enforcement policies, and drivers' compliance to increase the effectiveness of this strategy. Further, this research estimates the Random Parameters Negative Binomial-Lindley (RPNB-L) model for PTSU sections and provides valuable insights on potential crash contributing factors related to PTSU operation, design elements, and high-risk areas. Last, the study proposes a novel integrated crash prediction approach for freeway sections with combined traffic management strategies. By incorporating historical safety conditions from SPFs, real-time crash prediction performance could be improved as a part of proactive traffic management systems. The findings could assist transportation agencies, policymakers, and practitioners in taking appropriate countermeasures for preventing and reducing crash occurrence by incorporating safety aspects while implementing traffic management strategies on freeways.