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Humboldt-Universität zu Berlin - IRI THESys

Humboldt-Universität zu Berlin | Projects | IRI THESys | Research | Research Projects | A Multi-method Analyis of Peak-Oil

A Multi-method Analyis of the Phenomenon of Peak-Oil

The idea of this project is to combine several approaches within this methodology and visualize the results in order to create what could be called a multimethod vulnerability indicator of reduced fossil fuel availability (in our case focused on oil).

The economic system is highly complex and individual sectors are interrelated and interdependent. Hence it is not an easy task and some even say it’s impossible (Giampietro and Mayumi 2008), to design a plan to adapt our economies to significantly lower levels of fossil fuel use. However too urgent and too high are the stakes for not taking action as soon as possible. Policies are needed to design a smooth transition towards a low-carbon society, for both of the above reasons. For this purpose we need to study the nature of the systemic dependence on these resources (in particular oil) and the resulting vulnerability of our economies (Turner, Kasperson et al. 2003). Economic modelling for this purpose is challenging too, but those Models, such as Input Output analysis, which work with sectorially disaggregated data have been named as best suited for this task (Jones, Leiby et al. 2004). The idea of this project is to combine several approaches within this methodology and visualize the results in order to create what could be called a multimethod vulnerability indicator of reduced fossil fuel availability (in our case focused on oil). This research would build on the pioneering work of Kerschner and colleagues (Arto-Oliazola and Kerschner 2009; Kerschner and Hubacek 2009; Kerschner, Prell et al. forthcoming). Figure 1 below shows the most important result of this research afford. This figure shows two measures of relative sector importance (structural and monetary) and the expected affectedness by oil price increases of individual sectors. The rationale behind this approach is that if sectors with high potential impacts (large circles) are moreover very important for that economy (Quadrant 4), then this increases that economies vulnerability e.g. sector 120, fertilizer production.

Vulnerability map of Kerschner et

Figure 1: Vulnerability map of Kerschner et.al. (forthcoming)

Following a similar logic the goal is to integrate, adapt and revise the results of a regional study by Arto-Oliazola and Kerschner (2009), who used (among other calculus) a Multiregional IO model in order to measure the distance of products travelled from and to that region. Yet again it can be asserted that regions which depend on exports to and imports from places which are far away, will be more vulnerable to reduced oil availability. This analysis can be expanded with employment data i.e. how many jobs depend on energy intensive industry or on sectors exporting products over long distances. Moreover one can use mobility data, to check how dependent the economy is from transport by car or lorry instead of by train for example. All these data and results would be combined and visually processed into a proper visual figure.

 

 

The researcher behind the project

Liviu Mantescu Foto: Liviu Mantescu

Christian Kerschner

I am a trained Ecological Economist, with a Masters and PhD Degree from the Autonomous University of Barcelona. My undergraduate degree is in international business administration from the University of Vienna. The research I am engaged in is coined by my concern for the environment in general and economic scale and resource scarcity issues. Privately I usually live with my fiancée Angela in a small house in the middle of an Austrian forest. I love animals, am a hobby bee-keeper (they 'sleep' while I am in Berlin) and mini-scale silviculturist.

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