The benefits associated with mortality risk reductions are a critical input for the benefit-cost analysis of economically significant federal regulations that affect health and safety. The dominant method of estimating the benefits of reducing mortality risks relies on labor markets to estimate the tradeoffs between workers’ wages and occupational risk. The past literature considers all labor market risks to be equivalent, failing to recognize the inherent heterogeneity in occupational hazards. In this research, heterogeneity in the value of reducing risks is explored within the labor market context. Unique location-specific risk data are developed for over 300 U.S. cities to separately identify the wage premiums for facing two disparate occupational risks: violent assault and motor vehicle accident risks. We find that ignoring the underlying heterogeneity in risks can lead to substantial over/under-statements of the benefits of reducing any one particular risk by up to 350%. As such, caution is urged for benefits transfer exercises that apply estimates of the marginal willingness to pay for reducing labor market accident risks to policies affecting very different risks, such as public safety or environmental risks.

We introduce a class of Bayesian infinite mixture models first introduced by Lo (1984) to determine the credibility premium for a non-homogeneous insurance portfolio. The Bayesian infinite mixture models provide us with much flexibility in the specification of the claim distribution. We employ the sampling scheme based on a weighted Chinese restaurant process introduced in Lo et al. (1996) to estimate a Bayesian infinite mixture model from the claim data. The Bayesian sampling scheme also provides a systematic way to cluster the claim data. This can provide some insights into the risk characteristics of the policyholders. The estimated credibility premium from the Bayesian infinite mixture model can be written as a linear combination of the prior estimate and the sample mean of the claim data. Estimation results for the Bayesian mixture credibility premiums will be presented.

This review identifies similarities between behavioural indicators of children with future schizophrenia-spectrum disorders and prodromal symptoms in the first episode of schizophrenia. An alternative concept of prodrome is described with implications for early recognition, monitoring and intervention of individuals at risk of future schizophrenia spectrum disorders.