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A quantification of present and future mean annual losses due to extreme coastal events can be crucial for adequate decision making on adaptation to climate change in coastal areas around the globe. However, this approach is limited when uncertainty needs to be accounted for. In this paper, we assess coastal flood risk from sea-level rise and extreme events in 120 major cities around the world using an alternative stochastic approach that accounts for uncertainty. Probability distributions of future relative (local) sea-level rise have been used for each city, under three IPPC emission scenarios, RCP 2.6, 4.5 and 8.5. The approach allows a continuous stochastic function to be built to assess yearly evolution of damages from 2030 to 2100. Additionally, we present two risk measures that put low-probability, high-damage events in the spotlight: the Value at Risk (VaR) and the Expected Shortfall (ES), which enable the damages to be estimated when a certain risk level is exceeded. This level of acceptable risk can be defined involving different stakeholders to guide progressive adaptation strategies. The method presented here is new in the field of economics of adaptation and offers a much broader picture of the challenges related to dealing with climate impacts. Furthermore, it can be applied to assess not only adaptation needs but also to put adaptation into a timeframe in each city.

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In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant.First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel price and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained.Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type.Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively.Numerical computations involve the use of one-and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.

Abstract:The West Texas Intermediate (WTI) spot price shows high volatility and in 2014 and 2015 when quoted prices declined sharply, long-term prices in future markets were less volatile. These prices are different and diverge depending on how they process fundamental and transitory factors. US tight oil production has been a major innovation with significant macroeconomic effects. In this paper we use WTI spot prices and long-term futures prices, the latter calculated as the expected value with a stochastic model calibrated with the futures quotes of each sample day. These long-term prices are the long-term equilibrium value under risk neutral measurement. In order to analyze potential time-scale relationships between spots and future, we perform a wavelet cross-correlation analysis using a novel wavelet graphical tool recently proposed. To check the direction of the causality, we apply non-linear causality tests to raw data and log returns as well as to the wavelet transform of the spot and futures prices. Our results show that in the spot and futures markets for the period 24 February 2006-2 April 2016 there is a bi-directional causality effect for most time scales (from intra-week to biannual). This suggests that spot and futures prices react simultaneously to new information.