| Description |
Mitigating climate change (CC) is a complex policy problem. Sources of harmful greenhouse gas (GHG) emissions can be found in almost all societal and economic sectors. Likewise, the group of polluters is diverse, ranging from the industry enterprise to the individual. Effective climate policies must be designed to cope with this diversity in target groups. Hence, when formulating and implementing climate policy, the responsible decision-makers necessarily coordinate with a wide range of stakeholders like administrative entities from different sectors, political parties, interest groups, civil society organization, or science institutions. In addition, tackling CC is a multi-level game, since representatives of national governments negotiate at international conferences to coordinate international climate protection action. Decisions made at the international level must then be translated into national and subnational policies.
In this class, we aim to disentangle this complexity, by identifying the stakeholders, analysing their beliefs and interests, and studying factors that influence their coordination behaviour at the different arenas of policymaking. Studying these factors across a range of selected case studies, we also try to shed light on the question of why some countries enact more ambitious climate change policies than others. Macro level economic and political structures, such as the economic weight of fossil fuel industries, play an important role in shaping national policies. But, the process by which such macro-structural factors translate into political power and national climate change policies can be analysed through focussing on policy networks, i.e. various kinds of relationships (coordination, collaboration, resource exchange, shared opinions, etc.) between policy actors. In this course, we study and compare such climate policy across a number of selected case countries.
The objective of this course is therefore threefold: Firstly, we attempt to comprehend the socio-economic and political determinants of mitigating CC in different countries. Secondly, we use policy networks as an analytical tool to operationalise key concepts of relevant public policy theories. Third, we use network analysis as method to analyse various types of relational data (e.g. coordination, collaboration, shared opinions, etc.). For this purpose, students will able to analyse real, scientific data.
The course is organised in a flipped classroom format, i.e. class time is devoted to the discussion of readings and screencasts, concepts, student presentations, and exercises.
Requirements:
At least good knowledge of R; alternatively attendance of the R introductory course, offered in the first week of the semester
Inscription:
from August 15th 2020, 08.00 pm (20.00 Uhr) onwards via ILIAS
Form of implementation:
This class takes place in a mixed format of self-determined learning at home and interactive session in class. The sessions take place in the class room or via Zoom depending on the current Corona regulations and the number of participants. Podcasts, reading materials, and exercises are provided on a weekly bases and to be prepared before the sessions. During the interactive sessions, students will present policy network research, learn to analyse policy networks using R, and discuss typical research questions and challenges. |
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