Browsing by Subject "Uncertainty"

Now showing 1 - 4 of 4
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    Assessing uncertainty in Europe and the US : is there a common factor?
    (2012) Sauter, Oliver
    This paper aims an empirical investigation of uncertainty in the Euro Zone as well as the US. For this purpose I conduct a factor analysis of uncertainty measures starting in 2001 until the end of 2011. I use survey-based data provided by the ECB and the Federal Reserve Bank of Philadelphia as well as the stock market indices VSTOXX and VIX, both measures of implied volatility of stock market movements. Each measure shows an increase in uncertainty during the last years marked by the financial turmoil. Given the rise in uncertainty, the question arises whether this uncertainty is driven by the same underlying factors. For the Euro Zone, I show that uncertainty can be separated into factors of short and long-term uncertainty. In the US there is a sharp distinction between uncertainty that drives stock market and ?real? variables on the one hand and inflation (short and long-term) on the other hand. Combining both data sets, factor analysis delivers (1) an international stock market factor, (2) a common European uncertainty factor and (3) an US-inflation uncertainty factor.
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    Avoiding evolutionary inefficiencies in innovation networks
    (2011) Pyka, Andreas
    Innovation policy is in need for a rational which allows the design and evaluation of policy instruments. In economic policy traditionally the focus is on market failures and efficiency measures are used to decide whether policy should intervene and which instrument should be applied. In innovation policy this rational cannot meaningfully be applied because of the uncertain and open character of innovation processes. Uncertainty is not a market failure and cannot be repaired. Inevitably policy makers are subject to failure and their goals are to be considered as much more modest compared to the achievement of a social optimum. Instead of optimal innovation, the avoidance of evolutionary inefficiencies becomes the centrepiece of innovation policy making. Superimposed to the several sources of evolutionary inefficiencies are socalled network inefficiencies. Because of the widespread organisation of innovation in innovation networks, the network structures and dynamics give useful hints for innovation policy, where and when to intervene.
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    Comprehensive assessment of climate extremes in high-resolution CMIP6 projections for Ethiopia
    (2023) Rettie, Fasil M.; Gayler, Sebastian; Weber, Tobias K. D.; Tesfaye, Kindie; Streck, Thilo
    Climate extremes have more far-reaching and devastating effects than the mean climate shift, particularly on the most vulnerable societies. Ethiopia, with its low economic adaptive capacity, has been experiencing recurrent climate extremes for an extended period, leading to devastating impacts and acute food shortages affecting millions of people. In face of ongoing climate change, the frequency and intensity of climate extreme events are expected to increase further in the foreseeable future. This study provides an overview of projected changes in climate extremes indices based on downscaled high-resolution (i.e., 10 × 10 km2) daily climate data derived from global climate models (GCMs). The magnitude and spatial patterns of trends in the projected climate extreme indices were explored under a range of emission scenarios called Shared Socioeconomic Pathways (SSPs). The performance of the GCMs to reproduce the observed climate extreme trends in the base period (1983–2012) was evaluated, the changes in the climate projections (2020–2100) were assessed and the associated uncertainties were quantified. Overall, results show largely significant and spatially consistent trends in the projected temperature-derived extreme indices with acceptable model performance in the base period. The projected changes are dominated by the uncertainties in the GCMs at the beginning of the projection period while by the end of the century proportional uncertainties arise both from the GCMs and SSPs. The results for precipitation-related extreme indices are heterogeneous in terms of spatial distribution, magnitude, and statistical significance coverage. Unlike the temperature-related indices, the uncertainty from internal climate variability constitutes a considerable proportion of the total uncertainty in the projected trends. Our work provides a comprehensive insight into the projected changes in climate extremes at relatively high spatial resolution and the related sources of projection uncertainties.
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    Strategic network planning in biomass-based supply chains
    (2021) Fichtner, Stephan; Meyr, Herbert
    Fossil resources are limited and will run short. Moreover, the extensive usage of fossil resources is discussed as a key driver for climate change which means that a changeover in basic economic and ecological thinking is necessary. Especially for energy production, there has to be a movement away from the usage of fossil resources and towards renewable resources like wind, water, sun, or biomass. Within the first part of this work a structured review of recent literature on the long-term, strategic planning of biomass-based supply chains is provided. Therefore, in the first step, the overall research field “bioeconomy” by means of the various utilization pathways of biomass is structured and the demand-oriented view of supply chain management models and the supply-oriented view of bioeconomy are combined. In the second step, a literature review of operations research models and methods for strategic supply chain planning in biomass-based industries are provided. Thirdly, trends are identified and conclusions about research gaps are drawn. One of the identified research gaps is to make biomass-based supply chains profitable on their own, i.e., without governmental subsidies. Therefore, new optimization models are necessary, which should be as close to reality as possible, by for example considering risks and actual surrounding constraints concerning the legal framework. Within the second part of this work, an approach for strategic optimization of biogas plants considering increased flexibility is developed. Biogas plants can produce their energy flexibly and on-demand if their design is adjusted adequately. In order to achieve a flexibly schedulable biogas plant, the design of this plant has to be adapted to decouple the biogas and electricity production. Therefore, biogas storage possibilities and additional electrical capacity are necessary. The investment decision about the size of the biogas storage and the additional electrical capacity depends on the fluctuation of energy market prices and the availability of governmental subsidies. This work presents an approach supporting investment decisions to increase the flexibility of a biogas plant by installing gas storages and additional electrical capacities under consideration of revenues out of direct marketing at the day-ahead market. In order to support the strategic, long-term investment decisions, an operative plant schedule for the future, considering different plant designs given as investment strategies, using a mixed-integer linear programming (MILP) model in an uncertain environment is optimized. The different designs can be evaluated by calculating the net present value (NPV). Moreover, an analysis concerning current dynamics and uncertainties within spot market prices is executed. Furthermore, the influences concerning the variation of spot market prices compared to the influence of governmental subsidies, in particular, the flexibility premium, are revealed by computational results. Besides, the robustness of the determined solution is analyzed concerning uncertainties. The focus of the third part of the work is to consider variable substrate feeding in the mentioned optimization approach because it is expected that variable substrate feeding and thus a demand-oriented biogas production can influence the optimized plant design. In order to support this extension, an operative plant schedule for the future, considering (non-) linear technical characteristics of the biogas plant and the legal framework is optimized. Therefore, mixed-integer linear programming models with integrated approximation approaches of non-linear parts, representing the biogas production rates, are constructed. Furthermore, the influences of fluctuating spot market prices, governmental subsidies, and biomass feedstock prices on the decisions are analyzed for a fictional case example, which is based on a biogas plant in southern Germany. These numerical experiments show that variable substrate feeding can play a decisive role during the optimization of a biogas plant schedule as part of a long-term design optimization. However, the size of the strategic optimization problem makes the use of a heuristic solution algorithm necessary.