Howard Kunreuther - US grants

This project continues research involving a series of experiments designed to test whether decision-making biases of individuals persist in a market environment. The investigator has completed a set of experiments and found that decision-making biases do persist to some extent in simple-market situations. The purpose of this project is to undertake a set of experiments in more complex market environments to determine whether or not the market can correct for these biases. This research is important for two reasons. First, it is often asserted that markets are efficient and, in the aggregate, eliminate irrational decisions of individuals. This research is aimed at testing this basic assumption. Secondly, the research has the potential to expand our understanding of how, in fact, markets operate to mitigate or eliminate irrational decisions by examining the significance of different market features. The results of this study should yield important insights into the nature of decision making under conditions of uncertainty, and to spur the development of new models and hypotheses and to set the standards for empirical work in this area of research.

This research is concerned with the role that regulations and insurance can play in reducing losses from earthquakes, hurricanes and windstorms while at the same time alleviating the financial burden to victims from these types of disasters. The project is timely as there is a concern by both the insurance industry and federal agencies such as the Federal Emergency Management Agency (FEMA) about these issues. The research will specifically focus on the effects of a catastrophic loss on insurers and reinsurers. The behavior of firms in the industry will be modeled to derive a set of testable hypotheses regarding their future actions. A set of empirical studies will then be undertaken through case studies, surveys, and interviews with key decision makers in insurance and reinsurance firms. Hurricane Andrew, the single most costly natural disaster in the insurance industry s history, offers an opportunity to examine the hypotheses by looking at its impact on surplus, future premiums, available coverage, and ability to obtain reinsurance coverage. The prescriptive analysis will contrast the implications of dealing with earthquake, hurricanes, and windstorms where private insurers and reinsurers are responsible for covering all insured losses with a policy that incorporates some type of federal reinsurance for covering catastrophic losses.

9714401 Kunreuther The project will examine the role of the private and public sectors in managing catastrophe risks from natural hazards. The goal is to develop a feasible program for minimizing future losses from natural hazards through mitigation while enhancing the availability and reliability of financial protection against damage from natural hazards. Alternative incentive programs for encouraging property owners to adopt cost-effective mitigation measures will be designed and evaluated. Also, new private capital market initiatives, as well as the public sector as sources of funds when large-scale earthquakes or hurricanes occur, will be examined. The aggregate impact of both loss reduction initiatives and risk bearing and pooling policies will be evaluated using science-based micro-modeling approaches. This research will further the understanding of decision making processes and strategies related to risk reduction. ***

Seismologists have predicted that a severe earthquake in the
Istanbul region is highly likely in the next 30 years. This
forecast has drawn much attention in the media and raises
challenges as to how potential losses may be reduced by
protective measures. Decisions made by private individuals,
by officials, and by engineers and builders are all relevant
to this question. The principles underlying protective decision
making need to be better understood, for the sake of this and
many other applications.

We investigate how people determine whether to purchase insurance
and/or invest in loss-reduction measures against risks from fire, theft,
accidents or natural disasters. We examine the effects of different
ways in which risks can be communicated and different frames in which
information and choices can be presented; we also examine how
protective decisions are affected by instructional modules that aid
understanding of probability and that suggest useful general strategies
for framing decisions. To estimate these effects, controlled laboratory
experiments, field surveys and interviews will be conducted both in
the United States and in Turkey.

DRU: Network Structure, Behavioral Considerations and Risk Management in Interdependent Security Games

Michael Kearns Howard Kunreuther
Computer and Information Science Operations and Information Management
University of Pennsylvania Wharton School
University of Pennsylvania


ABSTRACT

Interdependent security (IDS) games model situations where each player has to determine whether or not to invest in protection or security against an uncertain event knowing that there is some chance s/he will be negatively impacted by others who do not follow suit. IDS games capture a wide variety of collective risk and decision-making problems that include airline security, corporate governance, computer network security and vaccinations against diseases. This research project will investigate the marriage of IDS models with network formation models developed from social network theory and apply these models to problems in network security. Behavioral and controlled experiments will examine how human participants actually make choices under uncertainty in IDS settings. Computational aspects of IDS models will also be examined. To encourage and induce individuals to invest in cost-effective protection measures for IDS problems, we will examine several risk management strategies designed to foster cooperative behavior that include providing risk information, communication with others, economic incentives, and tipping strategies.

The proposed research is interdisciplinary in nature and should serve as an exciting focal point for researchers in computer science, decision and management sciences, economics, psychology, risk management, and policy analysis. It promises to advance our understanding of decision-making under risk and uncertainty for problems that are commonly faced by individuals, organizations, and nations. Through advances in computational methods one should be able to apply IDS models to large-scale problems. The research will also focus on weak links in an interdependent system and suggest risk management strategies for reducing individual and societal losses in the interconnected world in which we live.

The need for more accurate and detailed regional climate predictions is widely recognized; industry, local government and society increasingly require sufficient understanding and warning to enable proper planning and adaptation to mitigate future costs and disruptions arising from climate variability and change. This project is addressing critical research and model development issues aimed at improving such regional predictions in a three-phase approach. The Nested Regional Climate Model from the National Center for Atmospheric Research is being further developed with the inclusion of ocean and land coupling, atmospheric chemistry, and decision support tools for societal and industry users. This model also forms a test bed for the next generation Model for Prediction Across Scales (MPAS), a next-generation regional weather-climate-ocean prediction system with sophisticated atmospheric chemistry components. A number of statistical and related downscaling techniques will also be developed to enable improved assessment of extreme weather systems and their impacts.
Broader Impacts. A feature of the program is the wide, cross-disciplinary community approach and novel collaboration amongst experts in regional climate, severe weather, numerical modeling, data assimilation, atmospheric chemistry, industry, and societal applications. Coordinating the development of the new prediction systems and downscaling approaches directly with societal applications and development of decision tools will enable each to influence the other to their mutual benefit. Thus, the program entails both substantial intellectual merit and societal and scientific benefit. For example, it will enable earlier societal and industry use of the developing predictive capacity and lead to an improved, tightly-coupled predictive and decision system. This will feature novel societal approaches, such as the role that long-term contracts like multi-year insurance policies coupled with long-term loans can play in encouraging investments in cost-effective adaptation measures in the presence of climate change.

Vulnerability to property loss and societal disruption is increasing as society becomes more complex and interconnected, and as private, industrial and commercial development expands in high risk areas.
Understanding and predicting variations and changes in weather extremes is thus a major societal issue, encompassing urban, commercial and industrial planning, watershed maintenance, agricultural practices and the development of insurance solutions designed to encourage investment in cost-effective adaptation measures. Current climate models do not have the capacity to resolve the intensity, damage potential, and other important characteristics of extreme weather, e.g. extended droughts, heat waves, major hurricanes and resulting storm surge, severe local storms and tornadoes, extreme local rainfall and snowfall, ice storms, and wind storms.

The broader impacts of this activity are high. This collaborative project will bring together an international group of regional climate, societal, statistical, risk analysis, and insurance/reinsurance experts. The group will examine the potential for using high-level extreme value statistics to assess weather extremes through a combination of pilot projects and expert workshops. A feature of the program will be colloquia and funding to enable young scientists to develop careers in this cross-disciplinary area.