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This paper brings together the debate on economic impacts of renewable energy (RE) deployment and the discussion on modelling endogenous technological change on the global markets for the different renewable power generation technologies. Economic impacts of RE deployment are still mostly discussed on national level, where different effects have been identified. Recent research for Germany shows positive effects on the macro level and different distributional impacts. High investment in solar photovoltaics (PV) from 2010 to 2012 and induced increases in the RE surcharge are the main drivers. At the same time, cost reductions for wind and solar PV take place on global markets, with global learning curves explaining the cost reductions very well. This calls for better including the international dimension into the modelling. The complex feedback loops between global cost curves and national policies, which react to global learning with some time lags, are not yet integrated into quite complex economic models. These models have to capture different RE technologies, different industries, either delivering the RE technologies or strongly depending on electricity prices, which are influenced by national support policies and macroeconomic development. As a first step to better understand the role of international markets, assumptions on RE exports based on global scenarios can be used. Results show the importance of global markets at least for the German RE industries. If the international dimension is taken into account, mainly positive economic impacts of further RE deployment can be observed.

INFORGE (Interindustry Forecasting Germany) ist ein seit Anfang der 90er Jahre fortlaufend aktualisiertes und weiterentwickeltes makroökonometrisches Modell, das basierend auf den amtlichen Volkswirtschaftlichen Gesamtrechnungen (VGR) des Statistischen Bundesamtes (StBA) die wirtschaftliche Entwicklung Deutschlands abbildet. Das Modell ist vollständig dokumentiert (z.B. Meyer et al. 1999, Distelkamp et al. 2003, Ahlert et al. 2009) und wird in vielen Projekten verschiedener Auftraggeber (z.B. Deutscher Sparkassen- und Giroverband, Bundesministerium für Wirtschaft und Energie, Bundesagentur für Arbeit) eingesetzt. INFORGE bildet die komplexen ökonomischen Strukturen zwischen den Branchen und Marktteilnehmern ab und erlaubt somit eine detaillierte Beschreibung der Entwicklung des Wirtschaftswachstums nach Branchen und der Beschäftigung in Deutschland. Für nationale Modelle ist die Exportnachfrage für gewöhnlich eine exogen vorgegebene Größe. Da der Außenbeitrag für Deutschland – im Jahr 2012 lag er bei fast 160 Mrd. € – signifikant an Bedeutung gewonnen hat, sind damit auch die Anforderungen an INFORGE gewachsen, eine möglichst detaillierte Abbildung des Außenhandels zu integrieren. Entscheidend ist dabei die Dynamik des Welthandels insgesamt, aber auch nach Handelspartnern möglichst genau zu erfassen sowie den Weltmarktanteil Deutschlands an dieser Entwicklung abzubilden.

The BMBF project 'The impact of the German policy mix on technological and structural change in renewable power generation technologies' analyzes the impact of a renewable energy policy mix on technological change, welfare (economic development, employment), trade and structural change using a global macro-economic input-output model. The analysis requires several steps: 1. Identifying the effect of the policy mix on innovation and technological change. 2. Quantifying the effect of technological change on the model parameters and variables. 3. Analyzing the resulting effect on the economy. In this paper a renewable power generation (RPG) module for the INFORUM type econometric input-output models (see Eurostat, 2008) such as GINFORS (Lutz & Wiebe, 2012) or PANTA RHEI (Lehr et al., 2012) is developed. The RPG technologies that we have selected for further analysis are wind (on- and off-shore) and solar PV.

Science-based policy analysis becomes increasingly important in the globalised world. Complex economic and social structures need to be thoroughly analysed and direct and indirect effects of policy measures should be identified and, if possible, quantified. Economic policy modelling has a long tradition (Almon, 1991) and economic models have over the past decades become more detailed regarding the economic structure and more extensive regarding the non-economic aspects represented in these models. There exist detailed structural economic models for most OECD countries. For newly emerging economies and developing countries only few such models exist. A global database and model environment is provided by the GTAP project, which is frequently used to develop computable general equilibrium (CGE) models. These models use a unique database, which often is not compatible to datasets of national statistic offices. Still, there are countries for which no such structural economic models exist. The macro-economic PRESIMO model for Morocco for example does not include the industry structure of the Moroccan economy. However, analyses at the industry level are important when analysing the development of for example labour markets or energy demand. The economic opportunities from international projects such as DESERTEC (Concentrating Solar Power in the Saharan Region) could be evaluated identifying sectors, which benefit the most. Using the example of Morocco this paper outlines the prerequisites for developing structural economic models and shows application possibilities of these models for simulating the effects of policy measures.

We increasingly need to rely on demand side changes to complement technological improvements to mitigate environmental impacts such as global warming and loss of biodiversity. To do so we must better understand how different types of consumers vary in their impact on the environment and to understand the role of consumer behavior in impact mitigation. The drivers-pressures-states-impact-response (DPSIR) framework describes the interactions between the human and natural systems. As the pressures, states, and impacts components of DPSIR are used to inform environmental policy making, it is crucial to both accurately account for, and to understand the linkages between these components and the underlying drivers. This thesis contributes to better understating of drivers (D), pressures (P) and impacts (I). The first contribution is made by estimating how changes in household income affect greenhouse gas emissions across a range of regions (drivers). By linking a demand system to the multiregional input-output model EXIOBASE 3, results show that by 2030 changing consumer preferences triggered by changes in household income lead to a 1% decrease in global warming from greenhouse gas (GHG) emissions globally compared to static consumer preferences. The largest contributors to this relative decrease in emissions are developing regions driven by lower preference of certain emission intensive food products, while the income effect on emissions of developed regions remain relatively unchanged. However, large expected population and affluence increases in developing regions more than cancel out the small negative effect of a modified consumption structure. Secondly, accuracy of environmental footprint studies is improved by increasing the regional resolution in a multiregional input-output (MRIO) model (pressures). Using a regionally extended version of EXIOBASE with detailed land use extensions, results show that regional aggregation errors are introduced when countries are aggregated to rest-of-the-world regions in the MRIO. Aggregate land use embodied in imports of regions differs by up to 68%, while individual sector-level flows differ by up to 600% when using rest-of-the world regions compared to treating countries explicit. Finally, by linking biodiversity characterization factors of land use to the new EXIOBASE version, biodiversity footprints for numerous new regions are estimated (impacts). Biodiversity footprints have globally increased by 5-6% between 1995 and 2015. Countries rich in biodiversity, and not necessarily affluence, have the highest footprint per capita. However, looking at trends over time, a one percent increase in income leads to a more than one percent increase in biodiversity footprint across all consumption categories for the average consumer in the most affluent countries, while this is not found for developing countries. The subsequent discussion shows that the potential is large for extending on the work in this thesis by further developing the database for understanding how demand-side changes and consumer behavior can contribute to reaching environmental mitigation goals.