Biases in inferences about representatives’ motives may reinforce political acrimony

American politics is characterized by a high degree of partisan rancor, with seemingly little common ground between Democrats and Republicans at the state or national level. But why is compromise now so difficult to achieve? In new research which examines how people perceive politicians’ motives, David Doherty finds that factors such whether or not they agree with a representative’s position or their party affiliation can have a large influence. He writes that if people’s perceptions lead them to conclude that politicians are acting in bad faith, despite them agreeing on policy positions, then this will make political compromises even more difficult

Can Insurers Pay for the "Big One"? Measuring the Capacity of an Insurance Market to Respond to Catastrophic Losses

This paper presents a theoretical and empirical analysis of the capacity of the U.S. property-liability insurance industry to finance major catastrophic property losses. The topic is important because catastrophic events such as the Northridge earthquake and Hurricane Andrew have raised questions about the ability of the insurance industry to respond to the "Big One," usually defined as a hurricane or earthquake in the $100 billion range. At first glance, the U.S. property-liability insurance industry, with equity capital of more than$300 billion, should be able to sustain a loss of this magnitude. However, the reality could be different; depending on the distribution of damage and the spread of coverage as well as the correlations between insurer losses and industry losses. Thus, the prospect of a mega catastrophe brings the real threat of widespread insurance failures and unpaid insurance claims. Our theoretical analysis takes as its starting point the well-known article by Borch (1962), which shows that the Pareto optimal result in a market characterized by risk averse insurers is for each insurer to hold a proportion of the "market portfolio" of insurance contracts. Each insurer pays a proportion of total industry losses; and the industry behaves as a single firm, paying 100 percent of losses up to the point where industry net premiums and equity are exhausted. Borch's theorem gives rise to a natural definition of industry capacity as the amount of industry resources that are deliverable conditional on an industry loss of a given size. In our theoretical analysis, we show that the necessary condition for industry capacity to be maximized is that all insurers hold a proportionate share of the industry underwriting portfolio. The sufficient condition for capacity maximization, given a level of total resources in the industry, is for all insurers to hold a net of reinsurance underwriting portfolio which is perfectly correlated with aggregate industry losses. Based on these theoretical results, we derive an option-like model of insurer responses to catastrophes, leading to an insurer response-function where the total payout, conditional on total industry losses, is a function of the industry and company expected losses, industry and company standard deviation of losses, company net worth, and the correlation between industry and company losses. The industry response function is obtained by summing the company response functions, giving the capacity of the industry to respond to losses of various magnitudes. We utilize 1997 insurer financial statement data to estimate the capacity of the industry to respond to catastrophic losses. Two samples of insurers are utilized - a national sample, to measure the capacity of the industry as a whole to respond to a national event, and a Florida sample, to measure the capacity of the industry to respond to a Florida hurricane. The empirical analysis estimates the capacity of the industry to bear losses ranging from the expected value of loss up to a loss equal to total company resources. We develop a measure of industry efficiency equal to the difference between the loss that would be paid if the industry acts as a single firm and the actual estimated payment based on our option model. The results indicate that national industry efficiency ranges from about 78 to 85 percent, based on catastrophe losses ranging from zero to $300 billion, and from 70 to 77 percent, based on catastrophe losses ranging from$200 to $300 billion. The industry has more than adequate capacity to pay for catastrophes of moderate size. E.g., based on both the national and Florida samples, the industry could pay at least 98.6 percent of a$20 billion catastrophe. For a catastrophe of $100 billion, the industry could pay at least 92.8 percent. However, even if most losses would be paid for an event of this magnitude, a significant number of insolvencies would occur, disrupting the normal functioning of the insurance market, not only for property insurance but also for other coverages. We also compare the capacity of the industry to respond to catastrophic losses based on 1997 capitalization levels with its capacity based on 1991 capitalization levels. The comparison is motivated by the sharp increase in capitalizaiton following Hurricane Andrew and the Northridge earthquake. In 1991, the industry had$.88 in equity capital per dollar of incurred losses, whereas in 1997 this ratio had increased to $1.56. Capacity results based on our model indicate a dramatic increase in capacity between 1991 and 1997. For a catastrophe of$100 billion, our lower bound estimate of industry capacity in 1991 is only 79.6 percent, based on the national sample, compared to 92.8 percent in 1997. For the Florida sample, we estimate that insurers could have paid at least 72.2 percent of a $100 billion catastrophe in 1991 and 89.7 percent in 1997. Thus, the industry is clearly much better capitalized now than it was prior to Andrew. The results suggest that the gaps in catastrophic risk financing are presently not sufficient to justify Federal government intervention in private insurance markets in the form of Federally sponsored catastrophe reinsurance. However, even though the industry could adequately fund the "Big One," doing so would disrupt the functioning of insurance markets and cause price increases for all types of property-liability insurance. Thus, it appears that there is still a gap in capacity that provides a role for privately and publicly traded catastrophic loss derivative contracts.

Basking shark movement ecology in the north-east Atlantic

Large marine vertebrate species can exhibit vast movements, both horizontally and vertically, which challenges our ability to observe their behaviours at extended time-scales. There is a growing need to understand the intra- and inter-annual movements of mobile marine species of conservation concern in order to develop effective management strategies. The basking shark (Cetorhinus maximus) is the world's second largest fish species, however, a comprehensive understanding of this species’ ecology, biology and spatial behaviour in the north-east Atlantic is currently lacking. This thesis seeks to investigate the movement ecology of basking sharks using a suite of technologies to integrate biologging, biotelemetry, remotely sensed data, and ecological modelling techniques. I use satellite telemetry data from basking sharks tracked in 2012, 2013 and 2014 to quantify movements in coastal waters off the west coast of Scotland within the Sea of the Hebrides proposed MPA. Sharks exhibited seasonal residency to the proposed MPA, with three long-term tracked basking sharks demonstrating inter-annual site fidelity, returning to the same coastal waters in the year following tag deployment (Chapter 2). I reveal that sharks tracked into winter months exhibit one of three migration strategies spanning nine geo-political zones and the High Seas, demonstrating the need for multi-national cooperation in the management of this species across its range (Chapter 3). I examine the vertical space-use of basking sharks to improve an understanding of the processes that influence movements in all dimensions. Basking sharks exhibit seasonality in depth-use, conduct deep dives to over 1000 m, and alter their depth-use behaviour in order to remain within thermal niche of between 8 and 16 oC (Chapter 4). Finally, I combine contemporaneous data recorded by deployed satellite tags with remotely sensed environmental data to employ novel ecological modelling techniques to predict suitable habitat for basking sharks throughout the Atlantic Ocean (Chapter 5).Natural Environment Research Council (NERC