Society For Risk Analysis Annual Meeting 2012
Session Schedule & Abstracts
* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.
|Chair(s): Matteo Convertino, Nik Sawe|
Sponsored by DARSG & ERASG
W2-E.1 10:30 A Conditional Weibull Approach to Modeling the Impacts of Technology, Weather, and Sample Selection on Crop Yield Distributions: Implications for Federal Crop Insurance. Woodard JD*; Cornell University firstname.lastname@example.org|
Abstract: A longstanding question in the crop insurance and yield risk literatures is to what extent the time horizon of a given sample impacts estimates of production risk, and what the appropriate sample period length â€śshouldâ€ť be for determining crop insurance rates. Simple answers to these questions have remained elusive though. First, the catastrophic nature of adverse weather events can result in high year-to-year variability in crop production. Second, these questions are confounded by the dynamic nature of production technology through time, which arguably has led to crops that are more resistant to adverse weather and other perils. Addressing these questions is of paramount importance in the current debate regarding the appropriateness of crop insurance rates in the Federal Crop Insurance Program (FCIP), as sample period selection, technology effects, and model assumptions can have large impacts on the rating of insurance. The objective of this study is to assess the impacts that sample period length, technology, and sampling variability in weather have on yield risk estimation. The application employs a rich farm-level dataset for Midwest corn in a high premium volume region of over 40,000 observations. A conditional Weibull distribution approach is developed which allows for assessment of yield risk under various sets of weather events and technology regimes by explicitly modeling the impacts of weather and technology change on probabilistic yield outcomes. The results indicate that relative yield risk for Midwest corn has declined significantly through time. Of particular importance, the results also demonstrate that expected insurance loss cost rates have fallen through time, after adjusting for weather, presumably due to improvements in management and biotechnology. Finally, the results provide evidence that FCIP insurance rates in the Midwest are likely severely inflated.
W2-E.2 10:50 Neuroimaging of Environmental Valuation. Sawe N*, Knutson B; Stanford University (SN, KB) email@example.com|
Abstract: Environmental economists have often employed contingent valuation as a method of deriving individual willingness-to-pay (WTP) for intrinsic, nonmarket services of environmental resources. Affective response plays a large role in generating this WTP, at times confounding contingent valuation measures, and is potentially driven by the perceived risk and destructiveness of land uses that impact natural resources. Using functional magnetic resonance imaging (FMRI) and a novel WTP task, we examined neural activation during environmental valuation in order to establish potential neural correlates of the decision process. This study was performed both in FMRI (n=9) and behaviorally (n=17) on healthy volunteers using a GE 3.0 T scanner (32 channel head coil, echoplanar pulse sequence, voxel size = 2.9 mm cubic, TR = 2000 msec). In 72 incentive-compatible trials, subjects were shown park land under threat of various new developmental land uses, and asked if they would donate from their endowed $24 to avert the use. From survey data (n=66), parks were classified as iconic (e.g., archetypal) or non-iconic, and proposed uses as destructive or conservative. Subjects showed increased activity in the nucleus accumbens, a region recruited in incentive processing, with both increasing iconicness of the park and increasingly conservative land uses (for both: p<0.001, uncorrected). Additionally, the integration of both the iconicness and destructiveness of the use led to greater activity in the medial prefrontal cortex (p<0.001, uncorrected), commonly characterized as an information integration region for incentive processing. These findings implicate reward/incentive circuitry for the processing of environmental valuation information during WTP tasks. With further study, FMRI may be a useful complement to surveys in assessing nonmarket valuation and risk assessment with regards to environmental resources.
W2-E.3 11:10 Energy efficient lighting: Results form three pieces to understand the engineer-economics aspects, consumer perceptions of light and color and consumer decision-making models. Azevedo I*; Carnegie Mellon University firstname.lastname@example.org|
Abstract: (1) Lighting constitutes more than 20% of total U.S. electricity consumption. We start by estimating the annualized costs of lighting technologies, showing that white LEDs will be lower than that of the most efficient fluorescent bulbs by the end of this decade. We compare the electricity consumption, carbon emissions, and cost-effectiveness of current lighting technologies, accounting for expected performance evolution through 2015. (2) Since consumersâ€™ adoption of energy-efficient lighting alternatives has been relatively slow, highlighting the need to better understand consumersâ€™ preferences for lighting conditions including brightness and color. Using a consumer research laboratory, we exposed one hundred participants to six lighting conditions, examining their preferences and their perceptions of lighting attributes. All participants read a newspaper under each lighting condition. Overall, lighting conditions that were perceived as more bright and cooler were rated as more pleasant. These findings suggest that lighting engineers and policy makers should consider consumersâ€™ perceptions in addition to the technical attributes when designing communications and energy efficiency-related performance standards (3) To quantify the influence of factors that drive consumer choices for light bulbs, we conducted a choice-based conjoint field experiment with 183 participants and estimated several discrete choice models from the data. We find that environmentally minded consumers have a stronger preference for compact fluorescent lighting technology, all else being equal, while politically liberal consumers have a stronger preference for low energy consumption. Perceived personal experiences of health issues, previous use or purchase of CFLs, awareness on climate change, income, and education levels were not significant in explaining choices. Greater willingness to pay for lower energy consumption and longer life was observed in conditions where estimated operating cost information was provided.
W2-E.4 11:30 A Mental Modeling Approach for Designing and Implementing USACEâ€™s Engineering With Nature Initiative. Bridges T*, Thorne S, Butte G, Kovacs D; United States Army Corps of Engineers (TB), Decision Partners LLC (ST, GB, DK) Todd.S.Bridges@erdc.usace.army.mil|
Abstract: Sustainable development of water resources infrastructure is supported by solutions that beneficially integrate engineering and natural systems. With recent advances in the fields of engineering and ecology, there is an opportunity to combine these fields of practice into a single collaborative and cost- effective approach for infrastructure development and environmental management. The U.S. Army Corps of Engineersâ€™ (USACE) Engineering With Nature (EWN) initiative is being developed to enable more sustainable delivery of economic, social and environmental benefits associated with water resources infrastructure. EWN directly supports USACEâ€™s â€śSustainable Solutions to Americaâ€™s Water Resources Needs: Civil Works Strategic Plan 2011 â€“ 2015â€ť. EWN is defined as the intentional alignment of natural and engineering processes to efficiently and sustainably deliver economic, environmental and social benefits through collaborative processes. A key EWN focus is on creating new ways of conducting business and expanding the benefits of USACE infrastructure projects through effective partner and stakeholder collaboration. It proposes a paradigm shift from the current decision making model, perceived by some as confrontational, to one of more effective decision making through early and ongoing collaboration with partners and stakeholders. One product of this new collaborative approach will be obtaining the statutorily required approvals faster and more efficiently, with less social friction , while meeting budget objectives and other priorities. To develop and implement this multi-year initiative, the USACE has undertaken a Mental Modeling approach. Current efforts are focused on: systematically engaging and collaborating with key stakeholders; identifying influences on adoption of EWN within both USACE and key partner organizations; and developing strategic communications practices to support and promote EWN.
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