Analysis of Spatial Impacts on Investments and Economic Behavior
Project duration: 7/2010 - 10/2012
Funded by E.ON ERC
Many economic and business decisions are affected by geography and location. For example, spatial factors that affect power plant location include resource availability, distance to the grid and key electricity demand nodes, as well as the location of competitors. However, current mainstream methodologies for economic and business analysis do not model the type and scale of these spatial impacts in a systematic, scientific way. Concurrently, there have been exciting developments in Geographical Information Systems (GIS) and in the statistical tools needed to analyze how spatial factors may affect estimation analyses. Adapting and applying these innovative techniques adds significant insights to the evaluation of specific business and economic problems.
This report summarizes the research within a project conducted at the FCN where we study the impacts of spatial dynamics on decision-making in the energy sector. In the first part, we review the current literature and existing methodologies for the spatial analysis of economic and energy-related research questions. In particular, we briefly introduce key concepts and provide an overview of the theoretical frameworks adopted in spatial economic analysis.
In the second part, we apply these tools in a variety of contexts related to the energy sector. We implement and discuss three estimation techniques associated with hedonic price modeling. Then, we analyze the impact of wind farms on property values, study the economic feasibility of small-scale wind turbines (SWT) under varying urban conditions, and evaluate the local PV potentials in a GIS-based case study for the city of Aachen. The case studies illustrate the broad scope of analysis and the heterogeneous field of applications associated with the toolbox acquired through this research grant, a toolbox that we plan to put to use and enrich further in future projects.
Madlener R., Ghosh G., Oberst C., Sorda G., Sunak Y. (2012). Analysis of Spatial Impacts on Investment and Economic Behavior, E.ON Energy Research Center Series, Vol. 4, Issue 7, December (ISSN: 1868-7415).
Grieser B., Sunak Y., Madlener R. (2015). Economics of small wind turbines in urban settings: An empirical investigation for Germany, Renewable energy, 78: 334-350.
Madlener R., Sorda G. (2013). Intensivere Holzenergienutzung in Europa : Politik- und Forschungsaspekte, Schweizerische Zeitschrift für Forstwesen, 164 (12): 428-435.
Sorda G., Sunak Y., Madlener R. (2013). An Agent-Based Spatial Simulation to Evaluate the Promotion of Electricity from Agricultural Biogas Plants in Germany, Ecological economics, 89 (May): 43-60.
Grieser B., Madlener R., Sunak Y. (2013). Economics of Small Wind Power Plants in Urban Settings: An Empirical Investigation for Germany, FCN Working Paper No. 1/2013, Institute for Future Energy Consumer Needs and Behavior, RWTH Aachen University, January.
Sorda G., Madlener R. (2012). Cost-Effectiveness of Lignocellulose Biorefineries and their Impact on the Deciduous Wood Markets in Germany, FCN Working Paper No. 8/2012, Institute for Future Energy Consumer Needs and Behavior, RWTH Aachen University, September.
Sunak Y., Madlener R. (2012). The Impact of Wind Farms on Property Values: A Geographically Weighted Hedonic Pricing Model, FCN Working Paper No. 3/2012, Institute for Future Energy Consumer Needs and Behavior, RWTH Aachen University, May (revised March 2013).
Sorda G., Sunak Y., Madlener R. (2011). A Spatial MAS Simulation to Evaluate the Promotion of Electricity from Agricultural Biogas Plants in Germany, FCN Working Paper No. 1/2011, Institute for Future Energy Consumer Needs and Behavior, RWTH Aachen University, January (revised October 2012).
Ghosh G., Carriazo F. (2009): A Comparison of Three Methods of Estimation in the Context of Spatial Modeling. FCN Working Paper No. 9/2009, Institute for Future Energy Consumer Needs and Behavior, RWTH Aachen University, November.
Sorda G. (2014). The diffusion of selected renewable energy technologies : modeling, economic impacts, and policy implications, E.ON Energy Research Center, RWTH Aachen University
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