Contributions in Merlin

Kreps–Porteus preferences constitute a widely used alternative to time separability. We showin this paper that with these preferences utility maximization does not impose any observable restrictions on a household’s savings decisions or on choices in good markets over time. The additional assumption of a weakly separable aggregator is needed to ensure that the assumption of utility maximization restricts intertemporal choices. Under this assumption, choices in spot marketsare characterized by a strong axiom of revealed preferences (SSARP).Under uncertainty Kreps–Porteus preferences impose observable restrictions on portfolio choice if one observes the last period of an individual’s planning horizon. Otherwise there are no restrictions.

At a stationary Markov equilibrium of a Markovian economy of overlapping generations, prices at a date-event are determined by the realization of the shock, the distribution of wealth and, with production, the stock of capital. Stationary Markov equilibria may not exist; this is the case with intra-generational heterogeneity and multiple commodities or long life spans. Generalized Markov equilibria exist if prices are allowed to vary also with the realization of the shock, prices and the allocation of consumption and production at the predecessor date-event. (Stationary) Markov $ \epsilon $ -equilibria always exist; as $ \epsilon \rightarrow 0, $ allocations and prices converge to equilibrium prices and allocations that, however, need not be stationary.

The vision of Pervasive Computing is built on the assumption that computers will become part of everyday objects, augmenting them with information services and enhanced functionality. This article reports on the approach we have used to assess potential side effects of this development on human health and the environment, and the major risks we identified. Social risks such as the risk of conflicts between users and non-users of the technology were also included because of their potential indirect adverse health effects. Assessing a technological vision before it has materialized makes it necessary to deal with two types of uncertainty: first, the uncertainty of how fast and to what extent the technology will be taken up and how it will be used; second, the uncertainty of causal models connecting technology-related causes with potential health or environmental effects. Due to these uncertainties, quantitative methods to evaluate expected risks are inadequate, Instead, we developed a "risk filter" that makes it possible to rank risks according to a set of qualitative criteria based on the Precautionary Principle. As the overall result, it turned out that Pervasive Computing bears potential risks to health, society, and/or the environment in the following fields: Non-ionizing radiation, stress imposed on the user, restriction of consumers' and patients' freedom of choice, threats to ecological sustainability, and dissipation of responsibility in computer-controlled environments.

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The Amsterdam auction has been used to sell real estate in the Dutch capital for centuries. By awarding a premium to the highest losing bidder, the Amsterdam auction favors weak bidders without having the implementation difficulties of Myerson's (1981) optimal auction. In a series of experiments, we compare the standard first-price and English auctions, the optimal auction, and two variants of the Amsterdam auction. With strongly asymmetric bidders, the second-price Amsterdam auction raises substantially more revenues than standard formats and only slightly less than the optimal auction.

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The use of Markov-switching models to capture the volatility dynamics of financial time series has grown considerably during past years, in part because they give rise to a plausible interpretation of nonlinearities. Nevertheless, GARCH-type models remain ubiquitous in order to allow for nonlinearities associated with time-varying volatility. Existing methods of combining the two approaches are unsatisfactory, as they either suffer from severe estimation difficulties or else their dynamic properties are not well understood. In this article we present a new Markov-switching GARCH model that overcomes both of these problems. Dynamic properties are derived and their implications for the volatility process discussed. We argue that the disaggregation of the variance process offered by the new model is more plausible than in the existing variants. The approach is illustrated with several exchange rate return series. The results suggest that a promising volatility model is an independent switching GARCH process with a possibly skewed conditional mixture density