Search result: Catalogue data in Spring Semester 2021

Science, Technology, and Policy Master Information
Social Sciences
NumberTitleTypeECTSHoursLecturers
860-0005-01LColloquium Science, Technology, and Policy (FS) Information Restricted registration - show details
Only for Science, Technology, and Policy MSc.
O1 credit2KT. Schmidt
AbstractPresentations by invited guest speakers from academia and practice/policy. Students are assigned to play a leading role in the discussion and write a report on the respective event.
ObjectivePresentations by invited guest speakers from academia and practice/policy. Students are assigned to play a leading role in the discussion and write a report on the respective event.
ContentSee program on the ISTP website: Link
860-0001-00LPublic Institutions and Policy-Making Processes Restricted registration - show details
Number of participants limited to 25.

Priority for Science, Technology, and Policy MSc.
O3 credits2GE. K. Smith, S. Bechtold, F. Schimmelfennig
AbstractStudents acquire the contextual knowledge for analyzing public policies. They learn why and how public policies and laws are developed, designed, and implemented at national and international levels, and what challenges arise in this regard.
ObjectivePublic policies result from decision-making processes that take place within formal institutions of the state (parliament, government, public administration, courts). That is, policies are shaped by the characteristics of decision-making processes and the characteristics of public institutions and related actors (e.g. interest groups). In this course, students acquire the contextual knowledge for analyzing public policies. They learn why and how public policies and laws are developed, designed, and implemented at national and international levels, and what challenges arise in this regard. The course is organized in three modules. The first module (Stefan Bechtold) examines basic concepts and the role of law, law-making, and law enforcement in modern societies. The second module (Thomas Bernauer) deals with the functioning of legislatures, governments, and interest groups. The third module (Frank Schimmelfennig) focuses on the European Union and international organisations.
ContentPublic policies result from decision-making processes that take place within formal institutions of the state (parliament, government, public administration, courts). That is, policies are shaped by the characteristics of decision-making processes and the characteristics of public institutions and related actors (e.g. interest groups). In this course, students acquire the contextual knowledge for analyzing public policies. They learn why and how public policies and laws are developed, designed, and implemented at national and international levels, and what challenges arise in this regard. The course is organized in three modules. The first module (Stefan Bechtold) examines basic concepts and the role of law, law-making, and law enforcement in modern societies. The second module (Thomas Bernauer) deals with the functioning of legislatures, governments, and interest groups. The third module (Frank Schimmelfennig) focuses on the European Union and international organisations.
Lecture notesReading materials will be distributed electronically to the students when the semester starts.
LiteratureBaylis, John, Steve Smith, and Patricia Owens (2014): The Globalization of World Politics. An Introduction to International Relations. Oxford: Oxford University Press.

Caramani, Daniele (ed.) (2014): Comparative Politics. Oxford: Oxford University Press.

Gilardi, Fabrizio (2012): Transnational Diffusion: Norms, Ideas, and Policies, in Carlsnaes, Walter, Thomas Risse and Beth Simmons, Handbook of International Relations, 2nd Edition, London: Sage, pp. 453-477.

Hage, Jaap and Bram Akkermans (eds.) (2nd edition 2017): Introduction to Law, Heidelberg: Springer.

Jolls, Christine (2013): Product Warnings, Debiasing, and Free Speech: The Case of Tobacco Regulation, Journal of Institutional and Theoretical Economics 169: 53-78.

Lelieveldt, Herman and Sebastiaan Princen (2011): The Politics of European Union. Cambridge: Cambridge University Press.

Lessig, Lawrence (2006): Code and Other Laws of Cyberspace, Version 2.0, New York: Basic Books. Available at Link.

Schimmelfennig, Frank and Ulrich Sedelmeier (2004): Governance by Conditionality: EU Rule Transfer to the Candidate Countries of Central and Eastern Europe, in: Journal of European Public Policy 11(4): 669-687.

Shipan, Charles V. and Craig Volden (2012): Policy Diffusion: Seven Lessons for Scholars and Practitioners. Public Administration Review 72(6): 788-796.

Sunstein, Cass R. (2014): The Limits of Quantification, California Law Review 102: 1369-1422.

Thaler, Richard H. and Cass R. Sunstein (2003): Libertarian Paternalism. American Economic Review: Papers & Proceedings 93: 175-179.
Prerequisites / NoticeThis is a Master level course. The course is capped at 25 students, with ISTP Master students having priority.
860-0042-00LStatistics 2 Restricted registration - show details
Only for Science, Technology and Policy MSc.
O4 credits1GK. Harttgen
AbstractThis course introduces students to key statistical methods for analyzing social science data with a special emphasis on causal inference and policy evaluation.
ObjectiveStudents
- have a sound understanding of standard regression techniques
- know strategies to test causal hypotheses using regression analysis and/or experimental methods
- are able to formulate and implement a regression model for a particular policy question and a particular type of data
- are able to critically interpret results of applied statistics, in particular, regarding causal inference
- are able to critically read and assess published studies on policy evaluation
- are able to use the statistical software Stata for data analysis
ContentThe topics covered in the first part of the course are a revision and linear regression and non-linear regression techniques such as probit and logit regression analysis. The second part of the course focuses on causal inference and introduces methods such as panel data analysis, difference-in-difference methods, instrumental variable estimation, regression discontinuity design, and randomized controlled trials used for policy evaluation. The course shows how the various methods differ in terms of the required identifying assumptions to infer causality as well as the data needs.

Students will apply the methods from the lectures by solving bi-weekly assignments using statistical software and data sets provided by the instructors. These data sets will cover topics at the interface of policy, technology and society. Solving the assignments contributes to the final grade with a weight of 30%.
860-0032-00LIntroductory Macroeconomics Restricted registration - show details
Number of participants is limited to 30.
Prerequisite: An introductory course in Economics is required to sign up for this course.

Priority for Science, Technology, and Policy MSc.
O3 credits2VR. Pleninger
AbstractThis course examines the behaviour of macroeconomic variables, such as gross domestic product, unemployment and inflation rates. It tries to answer questions like: How can we explain fluctuations of national economic activity? What can economic policy do against unemployment and inflation?
ObjectiveThis lecture will introduce the fundamentals of macroeconomic theory and explain their relevance to every-day economic problems.
ContentThis course helps you understand the world in which you live. There are many questions about the macroeconomy that might spark your curiosity. Why are living standards so meagre in many African countries? Why do some countries have high rates of inflation while others have stable prices? Why have some European countries adopted a common currency? These are just a few of the questions that this course will help you answer. Furthermore, this course will give you a better understanding of the potential and limits of economic policy. As a voter, you help choose the policies that guide the allocation of society's resources. When deciding which policies to support, you may find yourself asking various questions about economics. What are the burdens associated with alternative forms of taxation? What are the effects of free trade with other countries? How does the government budget deficit affect the economy? These and similar questions are always on the minds of policy makers.
860-0033-00LBig Data for Public Policy Information Restricted registration - show details
Only for Master students and PhD students.
O3 credits2GE. Ash, M. Guillot
AbstractThis course provides an introduction to big data methods for public policy analysis. Students will put these techniques to work on a course project using real-world data, to be designed and implemented in consultation with the instructors.
ObjectiveMany policy problems involve prediction. For example, a budget office might want to predict the number of applications for benefits payments next month, based on labor market conditions this month. This course provides a hands-on introduction to the "big data" techniques for making such predictions.
ContentMany policy problems involve prediction. For example, a budget office might want to predict the number of applications for benefits payments next month, based on labor market conditions this month. This course provides a hands-on introduction to the "big data" techniques for making such predictions. These techniques include:

-- procuring big datasets, especially through web scraping or API interfaces, including social media data;
-- pre-processing and dimension reduction of massive datasets for tractable computation;
-- machine learning for predicting outcomes, including how to select and tune the model, evaluate model performance using held-out test data, and report results;
-- interpreting machine learning model predictions to understand what is going on inside the black box;
-- data visualization including interactive web apps.

Students will put these techniques to work on a course project using real-world data, to be designed and implemented in consultation with the instructors.
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