Poverty trapping refers to the fact that poor people in developing countries cannot escape their poverty without help from outside. This is worsened by extreme events, for example, floods or hurricanes, sending people to poverty who have not been poor before. Often, insurance is seen as a way out. This article studies poverty trapping in the context of catastrophic risk and introduces a ruin-type model, combining deterministic growth with a stochastic loss model. We analyze the properties of the resulting piecewise deterministic Markov process, especially its trapping risk, and discuss for which groups of people insurance can reduce trapping probability.

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We demonstrate how the problem of determining the ask price for electricity swing options can be considered as a stochastic bilevel program with asymmetric information. Unlike as for nancial options, there is no way for basing the pricing method on no-arbitrage arguments. Two main situations are analyzed: if the seller has strong market power he/she might be able to maximize his/her utility, while in fully competitive situations he/she will just look for a price which makes prot and has acceptable risk. In both cases the seller has to consider the decision problem of a potential buyer the valuation problem of determining a fair value for a specic option contract and anticipate the buyer's optimal reaction to any proposed strike price. We also discuss some methods for nding numerical solutions of stochastic bilevel problems with a special emphasis on using duality gap penalizations.