Bachelor
Lectures
The lecture provides the students with the necessary tools in order to analyze the short-run and medium-term impact of economic policy in closed and small open economies. The students acquire a comprehensive knowledge of the functioning of goods, money, financial and labor markets from a macroeconomic perspective. The effectiveness of monetary and fiscal policy measures is assessed with respect to its success in reducing unemployment and inflation, and in stabilizing the economy. The course also addresses the long-run perspective by discussing determinants of economic growth.
Contents:
- Introduction
- National Accounts
- Goods Market
- Money and Financial Markets
- Taylor Rule
- Time inconsistency of Monetary politics
- Labor Market
- Phillips Curve
- Expectations
- IS-LM-PC-Model
- Financial and Economic Crises
The lecture provides the students with the necessary tools in order to analyze policy related endeavors
based on behavioral models, where emotions, fairness and altruism plays a role. Moreover, the lecture
also tackles growth related topics. Inter alia, students learn that ideas are an essential ingredient for
understanding growth.
Contents:
Learning content:
1. Principles of Behavioral Macroeconomics
• Emotions and economic desicions
• Fariness and Altruismn
• Related examples from environmental economics and finance
2. Growth
• The simpled and extendet Solow-Model
• Automatization, Employment, Growth and Inequality
• Ideas, Innovations and endogenous Growth
The lecture provides the students with necessary tools in order to analyze the long-run consequences of resource depletion, pollution and climate change within (endogenous) growth models. Further, the students are encouraged to discuss relevant economic policy measures. We require general knowledge of the course “Technology and Growth”.
Contents:
- Hartwick Rule
- Green Solow Model
- Endogenous Growth and the Environment
- Endogenous Growth, the Environment and Health
- Limits of Growth
Starting this winter semester, we offer the course Datascience in Economics. This application-oriented course is designed to provide an insight into the world of Data Science. The course provides a first approach to topics like Data Scraping, Data Visualization, Machine Learning. In particular, we address Deep Learning, Decision Trees and Unsupervised Learning. For all topics there will be case studies which will be worked on directly in the lecture using Python.
This course enables students to validate basic economic theories with available data. The students learn to verify these theories with simple statistical methods. Furthermore, the students will be encouraged to conduct data research independently and purposefully.
Contents:
- Demand for Money
- Fisher Effect
- Inflation and Unemployment: Phillips Curve
- Okun’s Law
- Taylor Rule
- J-Curve Effect
- Easterlin Paradox
- Environmental Kuznets Curve
- Kuznets Curve: Inequality and Growth
The lecture provides the students with the necessary tools to analyze the long-run development of an economy based on growth models. The lecture complements the neoclassic growth theory with evolutionary and behavioral concepts. Where appropriate, the derived models will be tested empirically. This course mediates the necessary tools for the lecture "Environmental Macroeconomics".
Contents:
- Solow Model
- Endogenous Growth Theory
- Automation and Growth
- Overlapping Generations (OLG)
- Unified Growth Theory
The lecture gives an insight into environmental and resource economics. It mainly deals with microeconomic models in order to work out reasons for market failure and to analyze various environmental policy instruments, such as limit values, environmental certificates and emission taxes. The lecture also focuses on the topics energy supply and climate change. Not only can energy be generated from finite resources, such as coal, but it can also be generated from renewable resources, such as wind.
Students have a sound knowledge of state-of-the-art empirical methods addressing empirical questions.
Students can create their own data set, select appropriate econometric techniques, and can critically
present their findings.
Contents:
This course builds on the course “Introductory Econometrics”. The course introduces and applies advanced
methods for analyzing data both in the time series as well as in the panel dimension. These methods can
be directly applied for working on empirical projects in Finance, Marketing, and Accounting as well as in the
micro- and macro-econometric sphere. The following topics are addressed:
• ML-Estimation of Linear and Nonlinear models
• Limited Dependent Variable Models and Goodness of Fit Measures
• Time Series Econometrics
• Analysis of Panel Data
• Introduction to Bayesian Econometrics