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Few theoretically-consistent empirical models addressing the relationship between ambiguity, risk, and preferences for health and safety exist. To fill this gap, we propose a theoretical non-expected-utility model (NEUM) that is relatively easy to estimate using an interval-data model. The NEUM we develop hinges upon two sources of variability, one over risk and the other over ambiguity about the risk. Using data from a survey of Nevada residents concerning risks from nuclear-waste transport, we provide individual-specific welfare estimate for a risk increase. Our findings suggest that negative externalities from nuclear-waste transport perceived risks and ambiguity may be substantial. Copyright Springer Science + Business Media, LLC 2006Expected utility, Risk and uncertainty, Ambiguity, Nuclear-waste transport,

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Recent housing-market studies have modeled slow stock and price adjustment with some success. However, the empirical procedures used in these models break down if housing stocks or prices are driven by stochastic growth. In this paper I suggest an error-correction model for analyzing housing supply and demand under conditions of stochastic growth for a regional housing market. The model is applied to the housing market in Boulder, Colorado from 1981 through 1995—a period of rapid growth in housing values in the area. Long-run housing supply and demand are shown to be inelastic with respect to changes in the price of housing. The results indicate that developers respond more accurately to housing-market disequilibrium attributable to supply-side disturbances than to disturbances generated by changes in the demand for housing. On the other hand, price appreciation is driven primarily by demand disturbances. Copyright 2000 Blackwell Publishers