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The book brings together academics, regulators, and industry experts to provide a multifaceted array of research and perspectives on insurance, its role and functioning, and the potential systemic risk it could create.
Over the past two decades, the United States has successfully deregulated prices and restrictions on most previously-regulated industries, including airlines, trucking, railroads, telecommunications, and banking. Only a few industries remain regulated, the largest being the property-liability insurance business. In light of recent sweeping financial modernization legislation in other sectors of the insurance industry, this timely volume examines the basis for continued regulation of rates and forms of the U.S. property-liability insurance market. The book focuses on private passenger automobile insurance—the most important personal line of property-liability coverage, with annual premiums of about $120 billion. The authors analyze five state case studies: California, Massachusetts, and New Jersey—three of the most heavily regulated states—as well as Illinois, which has been deregulated for about 30 years, and South Carolina, which began to deregulate in 1997. The study also includes an econometric analysis based on all fifty states over a 25-year period that gauges the impact of regulation on insurance price levels, price volatility, and the proportion of automobiles insured in residual markets. The authors conclude that regulation does not significantly reduce long-run prices for consumers, and generally limits availability of coverage, reduces the quality and variety of services available in the market, inhibits productivity growth, and increases price volatility. Contributors include Dwight Jaffee (University of California, Berkeley), Thomas Russell (Santa Clara University ), Laureen Regan (Temple University), Sharon Tennyson (Cornell University), Mary Weiss (Temple University), John Worrall (Rutgers University), Stephen D'Arcy (University of Illinois, Urbana-Champaign), Martin Grace (Georgia State University), Robert Klein (Georgia State University), Richard Phillips (Georgia State University), Georges Dionne (University of Montreal), and Richard Butler (Brigham Young University).
This paper explores insurance as a source of financial system vulnerability. It provides a brief overview of the insurance industry and reviews the risks it faces, as well as several recent failures of insurance companies that had systemic implications. Assimilation of banking-type activities by life insurers appears to be the key systemic vulnerability. Building on this experience and the experience gained under the FSAP, the paper proposes key indicators that should be compiled and used for surveillance of financial soundness of insurance companies and the insurance sector as a whole.
PRICING INSURANCE RISK A comprehensive framework for measuring, valuing, and managing risk Pricing Insurance Risk: Theory and Practice delivers an accessible and authoritative account of how to determine the premium for a portfolio of non-hedgeable insurance risks and how to allocate it fairly to each portfolio component. The authors synthesize hundreds of academic research papers, bringing to light little-appreciated answers to fundamental questions about the relationships between insurance risk, capital, and premium. They lean on their industry experience throughout to connect the theory to real-world practice, such as assessing the performance of business units, evaluating risk transfer options, and optimizing portfolio mix. Readers will discover: Definitions, classifications, and specifications of risk An in-depth treatment of classical risk measures and premium calculation principles Properties of risk measures and their visualization A logical framework for spectral and coherent risk measures How risk measures for capital and pricing are distinct but interact Why the cost of capital, not capital itself, should be allocated The natural allocation method and how it unifies marginal and risk-adjusted probability approaches Applications to reserve risk, reinsurance, asset risk, franchise value, and portfolio optimization Perfect for actuaries working in the non-life or general insurance and reinsurance sectors, Pricing Insurance Risk: Theory and Practice is also an indispensable resource for banking and finance professionals, as well as risk management professionals seeking insight into measuring the value of their efforts to mitigate, transfer, or bear nonsystematic risk.
Risk and Return for Regulated Industries provides a much-needed, comprehensive review of how cost of capital risk arises and can be measured, how the special risks regulated industries face affect fair return, and the challenges that regulated industries are likely to face in the future. Rather than following the trend of broad industry introductions or textbook style reviews of utility finance, it covers the topics of most interest to regulators, regulated companies, regulatory lawyers, and rate-of-return analysts in all countries. Accordingly, the book also includes case studies about various countries and discussions of the lessons international regulatory procedures can offer. - Presents a unified treatment of the regulatory principles and practices used to assess the required return on capital - Addresses current practices before exploring the ways methods play out in practice, including irregularities, shortcomings, and concerns for the future - Focuses on developed economies instead of providing a comprehensive global reviews - Foreword by Stewart C. Myers
In the aftermath of the recent financial crisis, the federal government has pursued significant regulatory reforms, including proposals to measure and monitor systemic risk. However, there is much debate about how this might be accomplished quantitatively and objectively—or whether this is even possible. A key issue is determining the appropriate trade-offs between risk and reward from a policy and social welfare perspective given the potential negative impact of crises. One of the first books to address the challenges of measuring statistical risk from a system-wide persepective, Quantifying Systemic Risk looks at the means of measuring systemic risk and explores alternative approaches. Among the topics discussed are the challenges of tying regulations to specific quantitative measures, the effects of learning and adaptation on the evolution of the market, and the distinction between the shocks that start a crisis and the mechanisms that enable it to grow.
The recent global financial crisis has forced a re-examination of risk transmission in the financial sector and how it affects financial stability. Current macroprudential policy and surveillance (MPS) efforts are aimed establishing a regulatory framework that helps mitigate the risk from systemic linkages with a view towards enhancing the resilience of the financial sector. This paper presents a forward-looking framework ("Systemic CCA") to measure systemic solvency risk based on market-implied expected losses of financial institutions with practical applications for the financial sector risk management and the system-wide capital assessment in top-down stress testing. The suggested approach uses advanced contingent claims analysis (CCA) to generate aggregate estimates of the joint default risk of multiple institutions as a conditional tail expectation using multivariate extreme value theory (EVT). In addition, the framework also helps quantify the individual contributions to systemic risk and contingent liabilities of the financial sector during times of stress.
Gini's mean difference (GMD) was first introduced by Corrado Gini in 1912 as an alternative measure of variability. GMD and the parameters which are derived from it (such as the Gini coefficient or the concentration ratio) have been in use in the area of income distribution for almost a century. In practice, the use of GMD as a measure of variability is justified whenever the investigator is not ready to impose, without questioning, the convenient world of normality. This makes the GMD of critical importance in the complex research of statisticians, economists, econometricians, and policy makers. This book focuses on imitating analyses that are based on variance by replacing variance with the GMD and its variants. In this way, the text showcases how almost everything that can be done with the variance as a measure of variability, can be replicated by using Gini. Beyond this, there are marked benefits to utilizing Gini as opposed to other methods. One of the advantages of using Gini methodology is that it provides a unified system that enables the user to learn about various aspects of the underlying distribution. It also provides a systematic method and a unified terminology. Using Gini methodology can reduce the risk of imposing assumptions that are not supported by the data on the model. With these benefits in mind the text uses the covariance-based approach, though applications to other approaches are mentioned as well.
The United States is unique among economically advanced nations in its reliance on employers to provide health benefits voluntarily for workers and their families. Although it is well known that this system fails to reach millions of these individuals as well as others who have no connection to the work place, the system has other weaknesses. It also has many advantages. Because most proposals for health care reform assume some continued role for employers, this book makes an important contribution by describing the strength and limitations of the current system of employment-based health benefits. It provides the data and analysis needed to understand the historical, social, and economic dynamics that have shaped present-day arrangements and outlines what might be done to overcome some of the access, value, and equity problems associated with current employer, insurer, and government policies and practices. Health insurance terminology is often perplexing, and this volume defines essential concepts clearly and carefully. Using an array of primary sources, it provides a store of information on who is covered for what services at what costs, on how programs vary by employer size and industry, and on what governments doâ€"and do not doâ€"to oversee employment-based health programs. A case study adapted from real organizations' experiences illustrates some of the practical challenges in designing, managing, and revising benefit programs. The sometimes unintended and unwanted consequences of employer practices for workers and health care providers are explored. Understanding the concepts of risk, biased risk selection, and risk segmentation is fundamental to sound health care reform. This volume thoroughly examines these key concepts and how they complicate efforts to achieve efficiency and equity in health coverage and health care. With health care reform at the forefront of public attention, this volume will be important to policymakers and regulators, employee benefit managers and other executives, trade associations, and decisionmakers in the health insurance industry, as well as analysts, researchers, and students of health policy.