Name | Herr Prof. Dr. Tobias Schmidt |
Lehrgebiet | Energiepolitik |
Adresse | Energie- und Technologiepolitik ETH Zürich, CLD C 12.1 Clausiusstrasse 37 8092 Zürich SWITZERLAND |
Telefon | +41 44 632 04 86 |
tobiasschmidt@ethz.ch | |
URL | http://www.epg.ethz.ch |
Departement | Geistes-, Sozial- und Staatswissenschaften |
Beziehung | Ordentlicher Professor |
Nummer | Titel | ECTS | Umfang | Dozierende | |
---|---|---|---|---|---|
851-0609-06L | Governing the Energy Transition Number of participants limited to 30. Primarily suited for Master and PhD level | 2 KP | 2V | T. Schmidt | |
Kurzbeschreibung | This course addresses the role of policy and its underlying politics in the transformation of the energy sector. It covers historical, socio-economic, and political perspectives and applies various theoretical concepts to specific aspects of governing the energy transition. | ||||
Lernziel | - To gain an overview of the history of the transition of large technical systems - To recognize current challenges in the energy system to understand the theoretical frameworks and concepts for studying transitions - To demonstrate knowledge on the role of policy and politics in energy transitions | ||||
Inhalt | Climate change, access to energy and other societal challenges are directly linked to the way we use and create energy. Both the recent United Nations Paris climate change agreement and the UN Sustainable Development Goals make a fast and extensive transition of the energy system necessary. This course introduces the social and environmental challenges involved in the energy sector and discusses the implications of these challenges for the rate and direction of technical change in the energy sector. It compares the current situation with historical socio-technical transitions and derives the consequences for policy-making. It then introduces theoretical frameworks and concepts for studying innovation and transitions. It then focuses on the role of policy and policy change in governing the energy transition, considering the role of political actors, institutions and policy feedback. The course has a highly interactive (seminar-like) character. Students are expected to actively engage in the weekly discussions and to give a presentation (15-20 minutes) on one of the weekly topics during that particular session. The presentation (30%) and participation in the discussions (20%) will form one part of the final grade, the remaining 50% of the final grade will be formed by a final exam. | ||||
Skript | Slides and reading material will be made available via moodle.ethz.ch (only for registered students). | ||||
Literatur | A reading list will be provided via moodle.ethz.ch at the beginning of the semester. | ||||
Voraussetzungen / Besonderes | This course is particularly suited for students of the following programmes: MA Comparative International Studies; MSc Energy Science & Technology; MSc Environmental Sciences; MSc Management, Technology & Economics; MSc Science, Technology & Policy; ETH & UZH PhD programmes. | ||||
851-0609-09L | Mixed-Methods Research | 1 KP | 1S | T. Schmidt | |
Kurzbeschreibung | This course is designed to reflect how researchers can combine two or more methodological approaches in empirical projects — so-called mixed-methods research (MMR) — in order to strengthen the validity of their conclusions and demonstrate generalizability of their findings. The course is aiming at PhD students who are working on their theses in the context of ETH/UZH’s CIS | ||||
Lernziel | Mixed-methods research (MMR) comes with the promise of generating broader, deeper and more valid insights than single-method research using only a qualitative or a quantitative technique. In our workshop, we will review this promise by discussing advantages and disadvantages of MMR and challenges in applying it. On the first half of day 1, we start with briefly sorting the field of mixed-methods research that originated in the 1960s and 1970s. This demonstrates the variety of research that qualifies as “mixed” and the different strategies for combining qualitative and quantitative tools. Each type is illustrated with an empirical example. For the rest of the workshop, we focus on nested analysis as a recent innovation in the social sciences. We situate nested analysis in the broader framework of mixed-methods research and discuss it with regard to its potential for integrated theorizing about macro relationships and causal effects on the one hand, and lower-level (meso, micro) relationships and causal mechanisms on the other hand. We continue with discussing the choice of cases based on large-n results as the key feature of nested analysis. Finally, we discuss how to integrate the results derived with two different methods. Again, we use empirical examples from the social sciences to illustrate these points. | ||||
860-0002-00L | Quantitative Policy Analysis and Modeling | 6 KP | 4G | A. Patt, T. Schmidt, E. Trutnevyte, O. van Vliet | |
Kurzbeschreibung | The lectures will introduce students to the principles of quantitative policy analysis, namely the methods to predict and evaluate the social, economic, and environmental effects of alternative strategies to achieve public objectives. A series of graded assignments will give students an opportunity for students to apply those methods to a set of case studies | ||||
Lernziel | The objectives of this course are to develop the following key skills necessary for policy analysts: - Identifying the critical quantitative factors that are of importance to policy makers in a range of decision-making situations. - Developing conceptual models of the types of processes and relationships governing these quantitative factors, including stock-flow dynamics, feedback loops, optimization, sources and effects of uncertainty, and agent coordination problems. - Develop and program numerical models to simulate the processes and relationships, in order to identify policy problems and the effects of policy interventions. - Communicate the findings from these simulations and associated analysis in a manner that makes transparent their theoretical foundation, the level and sources of uncertainty, and ultimately their applicability to the policy problem. The course will proceed through a series of policy analysis and modeling exercises, involving real-world or hypothetical problems. The specific examples around which work will be done will concern the environment, energy, health, and natural hazards management. |