Workers' Compensation Insurance In North America: Lessons for Victoria?

Among the issues we will consider here are the following. Who carries the underwriting(insurance) risk for workers' compensation benefits? How is workers' compensation insuranceprices, and by whom? What fundamental principles guide the insurance pricing system? Whomonitors benefits for compliance with statutory requirements? Are the availability of coverageand the payment of insurers' claims obligations guaranteed? Is self-insurance allowed and, if so, for whom? How are incentives for prevention of accidents, and resulting workers' compensation claims, maintained? What is the performance of the overall system? In summary, how are these questions answered and what so the answers reveal about how these responsibilities are allocated among government agencies, other public entities and private firms

Learning from the Past and Looking to the Future: A Conversation between Pamela Tate and Robert Deahl about the Past 35 Years in Adult Learning

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The Supply of Catastrophe Insurance Under Regulatory Constraints

Klein and Kleindorfer provide a brief overview of the current extent of their research on this topic. The intent of this research is to empirically address interactions across the multiple stakeholders in the Catastrophe Insurance Business, i.e. homeowners, businesses, insurers, reinsurers, the construction and real estate sector, and regulatory institutions. Their analysis is aimed at addressing three questions: What is the structure and performance of the catastrophe insurance market? How do factors such as, interdependencies, profits, risk exposures, and distribution impact the performance of the market? What is the impact of regulation of this market on pricing adequacy, pricing precision, and financial risk? What is the current state of the market, and what future sustainable states of the market are possible? This paper is primarily devoted to describing what authors consider to be the structural drivers of supply and demand and the impact of regulatory controls. These drivers are: "Demand structure" (i.e. why consumers buy what they do) obviously contains several components. Items such as location, demography, price, policy features such as the presence of absence of bundling, "quality" effects such as perceived solvency and claims processes, and finally, how products are distributed, all impact consumer choice. In addition, consumers have other risk management options open to them, the most obvious being where to live, what type of construction to choose and what type of "mitigation", if any to employ. "Supply Structure" describes how the consumer business of insurance is conducted. Salient features would be the degree of competition, geography, profitability, solvency, exposure, loss costs, marketing costs, organizational form, financial structure, and regulatory/solvency constraints. Obviously, insurance companies attempt to maximize profits in the face of these variables "Regulatory Impact" on such things as pricing adequacy, pricing precision, and financial risk has important effects on all parties. In particular the freedom to manage ones risk exposure is critical to everyone from the individual consumer to the largest company, and regulation may produce. In an analysis to come later, the researchers will utilize detailed premium record data obtained from ISO on insurance transactions, supplemented by information on expected costs for different policies and risk characteristics. The data will, for the first time, provide and empirically grounded understanding of the supply and demand for CAT-related coverage provided in residential insurance policies. The study will seek to identify the factors that most affect supply and demand and the magnitudes of their relative effects, including the pricing of CAT coverage and alternative policy provisions.

The demand for homeowners insurance with bundled catastrophe coverages : Wharton project on managing catastrophic risks

In this paper, we estimate the demand for homeowner insurance in Florida. Since we are interested in a number of factors influencing demand, we approach the problem from two directions. We first estimate two hedonic equations representing the premium per contract and the price mark-up. We analyze how the contracts are bundled and how contract provisions, insurer characteristics and insured risk characteristics and demographics influence the premium per contract and the price mark-up. Second, we estimate the demand for homeowners insurance using two-stage least squares regression. We employ ISO's indicated loss costs as our proxy for real insurance services demanded. We assume that the demand for coverage is essentially a joint demand and thus we can estimate the demand for catastrophe coverage separately from the demand for noncatastrophe coverage. We determine that price elasticities are less elastic for catastrophic coverage than for non-catastrophic coverage. Further estimated income elasticities suggest that homeowners insurance is an inferior good. Finally, we conclude based on the results of a selection model that our sample of ISO reporting companies well represents the demand for insurance in the Florida market as a whole

Time-Encoded Raman: Fiber-based, hyperspectral, broadband stimulated Raman microscopy

Raman sensing and Raman microscopy are amongst the most specific optical technologies to identify the chemical compounds of unknown samples, and to enable label-free biomedical imaging with molecular contrast. However, the high cost and complexity, low speed, and incomplete spectral information provided by current technology are major challenges preventing more widespread application of Raman systems. To overcome these limitations, we developed a new method for stimulated Raman spectroscopy and Raman imaging using continuous wave (CW), rapidly wavelength swept lasers. Our all-fiber, time-encoded Raman (TICO-Raman) setup uses a Fourier Domain Mode Locked (FDML) laser source to achieve a unique combination of high speed, broad spectral coverage (750 cm-1 - 3150 cm-1) and high resolution (0.5 cm-1). The Raman information is directly encoded and acquired in time. We demonstrate quantitative chemical analysis of a solvent mixture and hyperspectral Raman microscopy with molecular contrast of plant cells.Comment: 9 pages, 4 figure

nsolvency Experience, Risk-Based Capital, and Prompt Corrective Action in Property-Liability Insurance

In December 1992, the National Association of Insurance Commissioners (NAIC) adopted a life-health insurer risk-based capital (RBC) formula and model law that became effective with the 1993 annual statement filed in March 1994. In principle, well-designed RBC requirements can help achieve an efficient reduction in the expected costs of insolvencies. They can provide incentives for insurers to operate safely in cases where market incentives are weak due to government mandated guarantees of insurer obligations or asymmetries regarding solvency between insurers and buyers. RBC requirements also may facilitate or encourage prompt corrective action by solvency regulators by helping regulators to identify weak insurers and giving regulators legal authority to intervene when capital falls below specified levels. RBC requirements may force regulators to act in amore timely manner when confronted with external pressure to delay action. However, RBC capital requirements have a number ofpotential limitations. Unavoidable imperfections in any meaningful RBC system will likely distort some insurer decisions in undesirable and unintended ways. RBC requirements by themselves will do little or nothing to help regulators determine when an insurer s reported capital (surplus) is overstated due to understatement of liabilities or overstatement of assets. A well-designed RBC system should minimize costs associated with misclassification of insurers. The system should be able to identify a high proportion of troubled companies early enough to permit regulators to take prompt corrective action and should identify as troubled only a minimal proportion of financially sound insurers. This study analyzes data on solvent and insolvent property-liability insurers to determine whether modifications in the NAIC s RBC formula can improve its ability to predict firms that subsequently fail without substantially increasing the proportion of surviving insurers that are incorrectly predicted to fail. It uses logistic regression models to investigate whether changes in the weight for the major components in the RBC formula and incorporation of information on company size and organizational form improve the tradeoff between Type I error rates (the percentage of insurers that later failed that are incorrectly predicted not to fail) and the Type II error rates (the percentage of surviving insurers that are incorrectly predicted to fail). The data analyzed were for 1989-91 for firms that subsequently failed and for firms that survived through the first nine months of 1993. The authors make four main conclusions. First, less than half of the companies that later failed had RBC ratios within the proposed ranges for regulatory and company action. Second, total and component RBC ratios generally are significantly different for failed and surviving firms based on univariate tests. Third, estimation of multiple logistic regression models of insolvency risk indicated that allowing the weights of the RBC component to vary and including firm size and organizational form variables generally produce a material improvement in the tradeoff between sample Type I and Type II error rates. And, fourth,the RBC models are noticeably less successful in predicting large firm insolvencies than in predicting smaller insolvencies. Regarding the estimated weights in the logistic regression models, a major conclusion is the reserve component of the NAIC risk-based capital formula, which accounts for half of industry risk-based capital, has virtually no predictive power in any of the tests conducted. Given the high costs associated with large failures and the inferior performance of the models in predicting large insolvencies, a higher payoff in terms of reduced insolvency costs is likely to be achieved by developing models that perform better for large firms.