• Selected
• Entire List

Abstract:
After Hurricane Andrew the U.S. Congress entertained proposals to allow insurers to employ tax-deferred loss reserves. Interest was strong at first, but as the events receded interest waned. After the most recent hurricane seasons, interest in the proposals has rejuvenated. We examine the use of catastrophic loss reserves in a stylized one period model of insurance. Taking account of the potential changes in consumer behavior due to the institution of catastrophe reserves, we discover large social welfare gains are possible under certain circumstances. The benefits, however, depend on the actuarial assumptions underlying the expected loss distribution.

Tax-Deferred Loss Reserves, Catastrophe Financing and Pricing, Extreme Value Theory, Mixture model, Insurance, Reinsurance

Abstract:
We use a unique dataset of bond downgrades from a niche rating company that has been found to be reacting faster to publicly available information than its competitors. Using regime-switching models we propose risk measures to quantify stock return disturbances (distress costs) associated with the timing of downgrades. These risk measures are based on the Capital Asset Pricing Model (CAPM) and use the estimated parameters of the regime-switching models in a method that resembles a dynamic event study. We observe a noticeable switch from a low-volatility to a high-volatility regime one day before the day of downgrades. On average the volatility in stock returns triples around the time of downgrades and the stock return process remains in the high-volatility regime for about three days. Using our proposed risk measure we find that stock returns are associated with distress costs of about twenty-two*d percent (where "d" is the daily market price of risk) over a window of ten days before and after downgrades. These costs can be further separated between bond rating companies that are designated by the SEC as nationally recognized to rate debt and those which are not.

NRSRO Ratings, Markov Regime-Switching, CAPM

Abstract:
Mortality dynamics are characterized by changes in mortality regimes. This paper describes a Markov regime switching model which incorporates mortality state switches into mortality dynamics. Using the 1901-2005 US population mortality data, we illustrate that regime switching models perform better than well-known models in the literature. Furthermore, we extend the Lee-Carter (1992) model in such a way that the error term of the time-series common factor has distinct mortality regimes with different means and volatilities. Finally, we show how to price mortality securities with this model.

Lee-Cater model, regime switching mortality model, mortality-linked securities

Abstract:
Using the unique dataset of the five major UK insurance sectors, we adopt a novel approach in the insurance literature and model the evolution of underwriting returns as Regime Switching processes. This produces estimates of time-varying conditional regime probabilities and captures non-normality characteristics present in the data. Using Dynamic Panel and Panel Vector Auto-Regressions we study the joint dynamics of underwriting regime probabilities and their attribution to economic factors. Our evidence uncovers high/low volatility switching for all sectors, where their joint evolution is mainly attributed to industry-specific factors. High volatility is linked with low profitability while impulse response functions and variance decompositions identify a negative association of changes in premiums and a positive association of changes in claims and interest rates with the likelihood of the low-profitability regime.

Insurance, Reinsurance, Business Cycles, Regime Switching, Panel VAR

Abstract:
In a market where consumers can observe their risk characteristics, price regulation may spur moral hazard on behalf of high-risk consumers. Several empirical studies have demonstrated a static cross-subsidization effect from low-risk to high-risk consumers in price regulated insurance markets. In a competitive market, the riskiest of the low-risk consumers enter the residual market since cross-subsidization surcharges make their premiums higher than premium ceilings. In this paper we develop a dynamic model of cross-subsidization that examines changes in risk classification of consumers, as a result of the institution of premium ceilings and subsequent potential changes in consumer behavior. The model can be applied in similar price-regulated markets to make inferences about population movements between risk-classification groups, expected increases in low-risk premiums and the time or level of the next action by the regulator.