Bjarne Steffen: Katalogdaten im Herbstsemester 2022
|Herr Prof. Dr. Bjarne Steffen
|Klimafinanzierung und -politik
Klimafinanzierung und -politik
ETH Zürich, CLD C 4
|+41 44 633 85 45
|Geistes-, Sozial- und Staatswissenschaften
Only for Science, Technology, and Policy MSc.
|B. Steffen, F. M. Egli, T. Schmidt
|The course Policy Analysis 1 will introduce important concepts and methods for ex-ante policy analysis. It will mostly focus on the policy content (vis-à-vis the policy process). We will primarily discuss quantitative methods. The course will contain several practical assignments in which students have to apply the concepts and methods studied.
|Students should gain the skill to perform policy analyses independently. To this end, students will be enabled to understand a policy problem and the rationale for policy intervention; to select appropriate impact categories and methods to address a policy problem through policy analysis; to assess policy alternatives, using various ex-ante policy analysis methods; and to communicate the results of the analysis.
|The course has four major topics:
•Rationales for public policy in Science and Technology
•Impact of policies on firms and investors
•Impacts of policies on socio-technical systems
•Impact of policies on society at large
|Doctoral Colloquium in Public Policy
Only PhD students. Permission from lecturers is required.
|M. Krauser, T. Bernauer, R. Garrett, T. Schmidt, B. Steffen
|In this colloquium, doctoral students present their research plan within the first year of their doctorate, which is reviewed by three professors affiliated with the ISTP and commented on by the peer students registered in the colloquium. We recommend attending the colloquium for two semesters and present the research plan in the second semester.
|Obtain feedback on research ideas the doctoral research plan and have the research plan approved by three faculty, as required by ETH Zurich.
|Doctoral students (typically affiliated with the ISTP or groups of ISTP members) attend this colloquium for one to two semesters. During the first (voluntary) semester they present their preliminary research ideas. During the second (obligatory) semester, they present their research plan, which is reviewed by three professors affiliated with the ISTP. The research plan should not be longer than 20 pages (references excluded). The second semester will be credited with 1 ECTS. All students are supposed to read and comment on their peers’ research ideas and plans throughout both semesters. The results of the review are submitted to the doctoral committee of D-GESS or other ETH departments where ISTP-affiliated doctoral students intend to graduate.
|Technology and Policy Analysis
|T. Schmidt, E. Ash, F. M. Egli, R. Garrett, M. Leese, A. Rom, B. Steffen
|Technologies substantially affect the way we live and how our societies function. Technological change, i.e. the innovation and diffusion of new technologies, is a fundamental driver of economic growth but can also have detrimental side effects. This module introduces methods to assess technology-related policy alternatives and to analyse how policies affect technological changes and society.
Participants understand (1) what ex ante and ex post policy impact analysis is, (2) in what forms and with what methods they can be undertaken, (3) why they are important for evidence-based policy-making.
Analysis of Policy and Technology Options:
Participants understand (1) how to perform policy analyses related to technology; (2) a policy problem and the rationale for policy intervention; (3) how to select appropriate impact categories and methods to address a policy problem through policy analysis; (4) how to assess policy alternatives, using various ex ante policy analysis methods; (5) and how to communicate the results of the analysis.
Evaluation of Policy Outcomes:
Participants understand (1) when and why policy outcomes can be evaluated based on observational or experimental methods, (2) basic methods for evaluating policy outcomes (e.g. causal inference methods and field experiments), (3) how to apply concepts and methods of policy outcome evaluation to specific cases of interest.
Big Data Approaches to Policy Analysis:
Participants understand (1) why "big data" techniques for making policy-relevant assessments and predictions are useful, and under what conditions, (2) key techniques in this area, such as procuring big datasets; pre-processing and dimension reduction of massive datasets for tractable computation; machine learning for predicting outcomes; interpreting machine learning model predictions to understand what is going on inside the black box; data visualization including interactive web apps.
|Course materials can be found on Moodle.