Identifying the True Willingness-To-Pay of Bayesian Respondents in a Dichotomous Choice Contingent Valuation Methodology

This paper develops a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. We demonstrate by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrate that a simple extension of current DB-DC identifications derived explicitly from our Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provide some caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirms the simulation outcomes.Bayesian updating, contingent valuation, double-bound dichotomous choice, strategic behavior, willingness-to-pay

Economic analysis of the Florida Everglades restoration

An economic valuation methodology was developed in order to monetarily quantify the benefits resulting from the Indian River Lagoon - South (IRLS) $995 million Everglades restoration project. Service flows of the IRLS were identified and their associated economic baseline values were estimated utilizing existing research. A water quality baseline for the IRLS was also established and compared with the best available standards. Benefits accruing beyond the baseline values given the completion of the IRLS restoration were estimated via benefit transfer to be approximately$159 million annually, importantly factoring in the established IRLS water quality baseline. Given these benefit results of a lower bound estimate, the project was determined not to be economically feasible, i.e., NPV \u3c $0, via a cost-benefit analysis. However, Monte Carlo analyses provided further insights into the probability of an economically feasible restoration (36%) given the uncertainty surrounding the benefit estimation, as well as specific variables to focus on to improve this probability. This research highlights the potential significant economic value of the IRLS and the importance of properly estimating this value given the magnitude of costs

Could Flood Insurance be Privatised in the United States? A Primer

Since 1968, homeowners’ flood insurance in the United States has been mainly provided through the federally-run National Flood Insurance Program (NFIP). The Flood Insurance Reform Act of 2012 raises the possibility of moving coverage to the private sector, assuming the market can price this risk effectively and that premiums reflect risk. This paper provides the first large-scale quantification of risk-based premiums for over 300,000 residences prone to either storm surge or inland flooding using commercially developed probabilistic catastrophe models, and compares these premiums with those currently charged by the NFIP. Our findings reveal significant differences between the two. In some areas, the NFIP charges prices that are more than 15 times the pure premium, while other areas are charged up to three times less than the pure premium. The paper discusses the market and policy implications of these findings

Policy Options for Improving the Resilience of US Transportation Infrastructure

Despite the vulnerability of America’s aging infrastructure to costly disruptions from man-made and natural disasters, infrastructure insurance under-utilized. On average, only 30% of catastrophic losses in the past 10 years have been covered by insurance. Most infrastructure project managers have relied instead on taxpayer-funded federal aid when disaster strikes. But it doesn’t need to be this way. In this brief, Gina Tonn, Jeffrey Czajkowski, and Howard Kunreuther use technical reports and input from infrastructure managers to outline steps that policymakers can take to help maximize the use of infrastructure insurance for providing financial protection, encouraging investment in loss mitigation measures, and limiting the current reliance on taxpayer dollars.https://repository.upenn.edu/pennwhartonppi/1058/thumbnail.jp

Essays in Environmental Economic Valuation and Decision Making in the Presence of an Environmental Disaster

The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household’s evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household’s optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved

Individual hurricane evacuation intentions during the COVID-19 pandemic: insights for risk communication and emergency management policies

The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual hurricane preparedness is influenced by the additional risk stemming from a pandemic, which turns out to be a combination of perceptions of flood and pandemic risks that have opposite effects on preparedness behavior. We conducted a survey in early June 2020 of 600 respondents in flood-prone areas in Florida to obtain insights into households’ risk perceptions and preparedness for the upcoming hurricane season under COVID-19. The results show that concerns over COVID-19 dominated flood risk perceptions and negatively impacted people’s evacuation intentions. Whereas hotel costs were the main obstacle to evacuating during Hurricane Dorian in 2019 in the same geographic study area, the main evacuation obstacle identified in the 2020 hurricane season is COVID-19. Our statistical analyses investigating the factors influencing evacuation intentions show that older individuals are less likely to evacuate under a voluntary order, because they are more concerned about the consequences of becoming infected by COVID-19. We observe similar findings based on a real-time survey we conducted in Florida with another group of respondents under the threat of Hurricane Eta at the end of the hurricane season in November 2020. We discuss the implications of our findings for risk communication and emergency management policies that aim to improve hurricane preparedness when dealing with additional health risks such as a pandemic, a situation that may be exacerbated under the future climate

Housing Price Response to the Interaction of Positive Coastal Amenities and Negative Flood Risks

Since 1968 homeowners’ flood insurance in the United States has been mainly provided through the federally-run National Flood Insurance Program (NFIP), which as of December 2012 had 5.55 million NFIP policies-in-force nationwide with a total of $1.28 trillion of insured coverage (Michel-Kerjan et al, 2014). In 2012, Congress passed the Biggert-Waters Flood Insurance Reform Act (BW-12) in order to address a number of the well-documented structural and fiscal issues of the program, including key provisions of the bill that would increase existing discounted premiums to full-risk levels. However, BW-12 was itself reformed in March 2014 with the passage of Homeowner Flood Insurance Affordability Act (HFIAA-14) that importantly curbed many of the planned BW-12 rate increases. Realtors, homebuilders, and lenders had provided steep opposition to BW-12 (WSJ, 2013) decrying the movement toward risk-based premiums as causing “property values to steeply decline and made many homes unsellable, hurting the real estate market” (Insurance Journal, March 2014). In this paper we aim to shed some further light on this depressed property value assertion through a hedonic property analysis that accounts for the potential negative housing price effects of higher flood risk (and thus higher risk-based flood insurance rates), as well as the potential positive housing price effects of living close to the water, acting together on housing sales prices in a coastal community in Texas