Superstorm Sandy is merely the most recent high-impact weather event to raise concerns about extreme weather events becoming more frequent or more severe. Previous examples include the western European heatwave of 2003, the Russian heatwave and the Pakistan floods of 2010, and the Texas heatwave of 2011. However, it remains an open question to what extent such events may be “attributed” to human influences such as increasing greenhouse gases. One way to answer this question is to run climate models under two scenarios, one including all the anthropogenic forcing factors (in particular, greenhouse gases) while the other is run only including the natural forcings (e.g. solar fluctuations) or control runs with no forcings at all. Based on the climate model runs, probabilities of the extreme event of interest may be computed under both scenarios, followed by the risk ratio or the “fraction of attributable risk”, which has become popular in the climatology community as a measure of the human influence on extreme events. This talk will discuss statistical approaches to these quantities, including the use of extreme value theory as a method of quantifying the risk of extreme events, and Bayesian hierarchical models for combining the results of different climate models. This is joint work with Xuan Li (UNC) and Michael Wehner (Lawrence Berkeley Lab). Event flyer.
Dr. Daniel Huppmann studied Mathematics at the Vienna University of Technology, where he earned an MSc degree in 2010. He joined the German Institute for Economic Research (DIW Berlin) as a student research assistant in 2008, started in DIW’s graduate (PhD) program in October 2011 and successfully defended his dissertation at the TU Berlin in June 2014. He is currently a Research Associate in the department Energy-Transportation-Environment at DIW Berlin. In his research, Daniel works at the intersection of Operations Research, game theory, and energy economics, with a focus on multi-stage games in the global crude oil and natural gas markets, and strategic investment in electricity networks.
Modeling Strategic Behavior in Global Energy Markets- the Role of OPEC and the Impact of US Climate Policy (abstract)
The first part of the talk focuses on the global crude oil market, in particular the role of OPEC, and the difficulty of properly capturing strategic behavior in real-world applications using equilibrium modeling. This article proposes a two-stage oligopoly model: in a game of several Stackelberg leaders, market power increases endogenously as the spare capacity of the competitive fringe goes down. This effect is due to the specific cost function characteristics of extractive industries. The model captures the increase of OPEC market power before the financial crisis and its drastic reduction in the subsequent turmoil at the onset of the global recession.The two-stage model better replicates the price path over the years 2003-2011 compared to a standard simultaneous-move, one-stage Nash-Cournot model with a fringe. This article also discusses how most large-scale numerical equilibrium models, widely applied in the energy sector, over-simplify and potentially misinterpret market power exertion.
The second part of the talk presents a large-scale global dynamic energy system and resource market equilibrium model (“MultiMod”). It combines endogenous fuel substitution within demand sectors and in power generation, detailed infrastructure capacity constraints and investment, as well as strategic behavior and market power aspects by suppliers in a unified framework. This model is the first-of-its-kind in which market power is exerted across several fuels. It bridges the divide between energy system models, focusing on fuel substitution and technology options, and sector specific models that have a detailed representation of infrastructure constraints and are able to capture strategic behavior. The model allows assessing and quantifying the impact of national or global climate policy and emission reduction targets on the global energy mix over the next decades. In the talk, Daniel will present current results from the Energy Modeling Forum, Round 31 (“North American Natural Gas and Energy Markets in Transition”), focusing on the impact of US shale gas scenarios and domestic energy policy (such as Technology Portfolio Standards) on global energy consumption patterns and the resulting import dependency and trade flows.