Basic mathematical knowledge
The course consists of four chapters:
Requirements for the assignment of ECTS Credits and Grades
Exam (120 min)
The exam takes place on October 2 2019, 3:30–5:30 pm in EW242 Otto Mann Hörsaal (Schloss Ehrenhof West).
The students know basic mathematical concepts of analysis and linear algebra. They can interpret mathematical formulas that are written in the condensed mathematical syntax. The students understand the concept of a proof and can develop rigorous mathematical proofs in a elementary level. They understand abstract mathematical concepts like metric spaces and linear spaces and are able to comprehend argumentation on basis of abstract mathematical concepts. They are able to apply their knowledge; especially they are familiar with the calculation of limits and derivatives, the methods of linear algebra, and they can solve nonlinear optimization problems. The students are able to communicate their mathematical knowledge in English.
Teaching Assistants
Exercise Group 1 & 3: Can Çelebi (CDSE)
Exercise Group 2 & 4: Giovanni Ballarin (CDSE)
Download supplemental material >>
Lecture | |||||||
Lecture | 02.09.19 – 23.09.19 | Monday | 10:15 – 11:45 | A5, 6, C015 | |||
Lecture | 03.09.19 – 24.09.19 | Tuesday | 10:15 – 11:45 | A5, 6, C015 | |||
Lecture | 04.09.19 – 25.09.19 | Wednesday | 10:15 – 11:45 | A5, 6, C014 | |||
Lecture | 05.09.19 – 26.09.19 | Thursday | 10:15 – 11:45 | B6, 30–32, E-F, 308 | |||
Written exam | 02.10.19 | Wednesday | 15:30 – 17:30 | EW242 Otto Mann Hörsaal (Schloss Ehrenhof West) | |||
Retake Exam | 11.12.19 | Wednesday | 15:30 – 17:30 | A 5, 6, C 012 | |||
Tutorial | |||||||
Group 1 | 02.09.19 – 23.09.19 | Monday | 13:45 – 15:15 | B6, 23–25, A 304 | |||
Group 2 | 02.09.19 – 23.09.19 | Monday | 13:45 – 15:15 | B6, 23–25, A 303 | |||
Group 3 | 02.09.19 – 23.09.19 | Monday | 15:30 – 17:00 | B6, 23–25, A 304 | |||
Group 4 | 02.09.19 – 23.09.19 | Monday | 15:30 – 17:00 | B6, 23–25, A 303 | |||
Group 1 | 03.09.19 – 24.09.19 | Tuesday | 13:45 – 15:15 | B6, 23–25, A 304 | |||
Group 2 | 03.09.19 – 24.09.19 | Tuesday | 13:45 – 15:15 | B6, 23–25, A 301 | |||
Group 3 | 03.09.19 – 24.09.19 | Tuesday | 15:30 – 17:00 | B6, 23–25, A 304 | |||
Group 4 | 03.09.19 – 24.09.19 | Tuesday | 15:30 – 17:00 | B6, 23–25, A 301 | |||
Group 1 | 04.09.19 – 25.09.19 | Wednesday | 13:45 – 15:15 | B6, 23–25, A 304 | |||
Group 2 | 04.09.19 – 25.09.19 | Wednesday | 13:45 – 15:15 | B6, 23–25, A 303 | |||
Group 3 | 04.09.19 – 25.09.19 | Wednesday | 15:30 – 17:00 | B6, 23–25, A 304 | |||
Group 4 | 04.09.19 – 25.09.19 | Wednesday | 15:30 – 17:00 | B6, 23–25, A 305 | |||
Group 1 | 05.09.19 – 26.09.19 | Thursday | 13:45 – 15:15 | B6, 23–25, A 301 | |||
Group 2 | 05.09.19 – 26.09.19 | Thursday | 13:45 – 15:15 | B6, 23–25, A 302 | |||
Group 3 | 05.09.19 – 26.09.19 | Thursday | 15:30 – 17:00 | B6, 23–25, A 304 | |||
Group 4 | 05.09.19 – 26.09.19 | Thursday | 15:30 – 17:00 | B6, 23–25, A 302 | |||
Prerequisites
E700
Requirements for the assignment of ECTS-Credits and Grades
The course gives a foundation for studies in microeconomics at the Ph.D. level. The first part is devoted to decision theory. It is organized as follows:
1. Choice, preferences and utility
2. Choice under uncertainty: Expected utility
3. Utility for money
4. Behavioral models of choice under uncertainty
The second part covers game theory and is organized as follows:
5. Static games of complete information: Rationalizability and iterated strict dominance
6. Static games of complete information: Nash equilibrium
7. Static games of incomplete information
8. Dynamic games: The extensive form
9. Dynamic games: Equilibrium concepts
The students will acquire the basic tools for graduate-level microeconomic analysis. They will learn how to model decision-making and strategic interactions. They will acquire important mathematical skills used in decision theory and game theory. They will be able to apply that theory to their own research and to read recent developments in the field. The concepts learned in the course serve as building blocks for more advanced topics such as the ones covered in Advanced Microeconomics II and III, and also for macroeconomics and empirical economics. Students also learn how to write rigorous formal proofs to address microeconomic questions.
Textbook references
Contact Information
Nicolas Schutz; Phone: (0621) 181 1872; email: schutz@uni-mannheim.de, Office: 3–10, Office hours: by appointment.
Teaching Assistant
Lecture | |||||||
Lecture | 07.10.19 – 02.12.19 | Monday | 10:15 – 11:45 | L9, 1–2, 004 | |||
Lecture | 09.10.19 – 04.12.19 | Wednesday | 10:15 – 11:45 | L7, 3–5, 001 | |||
Written Exam | 09.12.19 | Monday | 10:15 – 12:15 | Schloss O 129 | |||
Retake Exam | 27.01.20 | Monday | 10:15 – 12:15 | B6, 30–32, 211 | |||
Tutorial | |||||||
Tutorial | 09.10.19 – 04.12.19 | Wednesday | 12:00 – 13:30 | B6,30–32, 110 | |||
Tutorial | 10.10.19 – 05.12.19 | Thursday | 12:00 – 13:30 | B6, 30–32, 309 | |||
E700
Goals and Contents of the Module:
This course provides an introduction to the foundations of modern macroeconomic analysis. The main object of this course will be structural dynamic models where households' preference, firms' technology, and market structure are explicitly specified. The behaviors of agents in the model economy are derived based on microeconomic foundations. The macroeconomic aggregates are then determined by aggregating individuals' micro-founded decisions. We will consider some applications as well.
Requirements for the assignment of ECTS credits and grades:
Literature:
Expected Competences acquired after Completion of the Module:
At the end of the semester, students are expected to be familiar with the basic methodology such as recursive methods and dynamic programming as well as the basic macroeconomic models.
Teaching Assistant
Lecture | |||||||
Lecture | 08.10.19 – 03.12.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, S031 | |||
Lecture | 09.10.19 – 04.12.19 | Wednesday | 15:30 – 17:00 | L7, 3–5, P044 | |||
Written Exam | 12.12.19 | Thursday | 10:15 – 12:15 | Schloss O 129 | |||
Retake exam | 30.01.20 | Thursday | 10:15 – 12:15 | B6, 30–32, 211 | |||
Tutorial | |||||||
Tutorial 1 | 09.10.19 – 04.12.19 | Wednesday | 13:45 – 15:15 | L7, 3–5, P 043 | |||
Tutorial 2 | 10.10.19 – 05.12.19 | Thursday | 13:45 – 15:15 | L7, 3–5, P 043 | |||
E700
The goal of the module is to offer advanced treatment to econometric theory and to serve as the gateway to further advanced theoretical and applied econometric modules offered in the economics graduate program at the Department of Economics in Mannheim.
In the module an introduction will be given to the probabilistic framework of econometric theory.
In the first part, basic notions of probability theory with their measure theoretical background are explained: probability measure, random variables, expectations, conditional expectations, notions of convergence and basic limit theorems.
The second part will be devoted to the formal derivation of theoretical foundations of linear regression models. The theory of the first part is then applied to obtain asymptotic properties of parameter estimators and to set up statistical tests in this framework.
The module gives training in the use of mathematical arguments in the theory of asymptotic econometrics.
Requirements for the Assignment of ECTS Credits and Grades:
written exam, 120 min,
regular attendance required
Literature:
On successful completion of the module, students are expected to attain the following competences:
Teaching Assistant
Lecture | |||||||
Lecture | 08.10.19 – 03.12.19 | Tuesday | 10:15 – 11:45 | L7, 3–5, 001 | |||
Lecture | 10.10.19 – 05.12.19 | Thursday | 10:15 – 11:45 | L7, 3–5, 001 | |||
Written Exam | 17.12.19 | Tuesday | 10:15 – 12:15 | Schloss O 129 | |||
Retake Exam | 03.02.20 | Monday | 10:15 – 12:15 | B6, 30–32, 211 | |||
Tutorial | |||||||
Exercise 1 | 08.10.19 – 03.12.19 | Tuesday | 13:45 – 15:15 | L7, 3–5, P 043 | |||
Exercise 2 | 08.10.19 – 03.12.19 | Tuesday | 17:15 – 18:45 | L7, 3–5, P 043 | |||
2nd and higher year Ph.D. students from the Center for Doctoral Studies in Economics (CDSE)
2nd year students from the Master of Economic Research
Method (hours per week): Colloquium (2 h)
Duration of the module: 4 semesters
ECTs awarded after each semester: 3 ECTs
Seminar | |||||||
Seminar | 03.09.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, S031 | |||
Seminar | 10.09.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 17.09.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 01.10.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 08.10.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 22.10.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, 001 | |||
Seminar | 05.11.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 12.11.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 26.11.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 | |||
Seminar | 03.12.19 | Tuesday | 15:30 – 17:00 | L7, 3–5, P 044 |
Presentations
Students will read, present and discuss papers in environmental economics.
Lecture | |||||||
Lecture | 12.09.19 – 05.12.19 | Thursday, every 14 days | 15:30 – 17:00 | L7, 3–5, 410 | |||
This seminar provides a forum for internal and external speakers to discuss their recent research in econometrics. Students working on either econometrics or an empirical project with a substantive econometric component are welcome to present. Please contact the instructor to set up a date.
Seminar | |||||||
Seminar | 05.09.19 – 05.12.19 | Thursday | 15:30 – 17:00 | L7, 3–5, S031 |
Formal: 2nd and higher year Ph.D. students from the Center for Doctoral Studies in Economics (CDSE).
2nd year students from the Master of Economic Research.
Course Content
Students are expected to gain knowledge on the frontier of modern quantitative macroeconomic research on growth and business cycles.
Requirements for the assignment of ECTS Credits and Grades
Students are expected to gain knowledge on the frontier of modern quantitative macroeconomic research on growth and business cycles.
Lecture | |||||||
Lecture | 02.09.19 – 14.10.19 | Monday | 13:45 – 15:15 | L7, 3–5, P044 | |||
Lecture | 02.09.19 – 14.10.19 | Monday | 15:30 – 17:00 | L7, 3–5, P044 | |||
E700–703, E801–806
Course Content
This course covers both methods and applications in empirical macroeconomics. On the methodological side, we cover structural vector autoregressive (SVAR) models. The focus will be on various identification strategies (e.g., short-run/long-run restrictions, sign restrictions, external instruments), but also inference, factor models, nonlinear models. In addition, we discuss narrative approaches to identify structural shocks and univariate methods to study their propagation. The lectures and assignments introduce a range of applications. Those include the analysis of technology shocks, monetary policy shocks, and fiscal policy shocks.
Teaching Method
Lecture (2 SWS) and Exercise (1 SWS)
Requirements for the Assignment of ECTS Credits and Grades
A research paper and regular assignments.
Literature
Ramey (Handbook of Macroeconomics, 2016, Volume 2A, Chapter 2: Macroeconomic Shocks and Their Propagation)
Kilian and Lütkepohl (Structural Vector Autoregressive Analysis, 2017; see www-personal.umich.edu/~lkilian/book.html)
Lütkepohl (New Introduction to Multiple Time Series Analysis, 2005)
The course introduces students to econometric methods and macroeconomic applications with a focus on business cycles.
Lecture | |||||||
Lecture | 02.09.19 – 14.10.19 | Monday | 10:15 – 11:45 | L7, 3–5, P043 | |||
Lecture | 02.09.19 – 14.10.19 | Monday | 17:15 – 18:45 | L7, 3–5, P043 | |||
Lecture | 21.10.19 | Monday | 10:15 – 11:45 | L7, 3–5, P044 | |||
Lecture | 21.10.19 | Monday | 17:15 – 18:45 | L9,1–2, 003 | |||
Lecture | 10.12.19 | Tuesday | 13:00 – 16:00 | L7, 3–5, P044 | |||
E601–603
The digital economy led to many new services where supply is matched with demand for various types of goods and services. More and more people and organizations are now in a position to design market rules that are being implemented in software. The design of markets is challenging as it needs to consider strategic behavior of market participants, psychological factors, and computational problems in order to implement the objectives of a designer. The recent years have led to many new insights and principles for the design of markets, which are beyond traditional economic theory. This course introduces the fundamentals of market design, an engineering field concerned with the design of real-world markets.
Syllabus
A. Matching Algorithms
1. Introduction
2. The basic matching model
3. The medical match
4. Assignment markets
5. School choice
6. Course allocation
7. Kidney exchange
B. Auctions
1. Private Value Auctions
2. The Revenue Equivalence Principle
3. Risk-Averse Bidders
4. Budget Constraints
5. Asymmetry
6. Auctions with Interdependent Values
7. Mechanism Design
Grading and ECTS credits
Exam + Assignments
After participating in the course, the participants understand methods and game-theoretical models of auctions as well as the fundamental problems in the design of matching markets. They are able to assess the properties of different auction formats and matching algorithms, and the results of theoretical and experimental analyses.
Lecture | |||||||
Lecture | 04.09.19 – 04.12.19 | Wednesday | 13:45 – 15:15 | L7, 3–5, P 044 | |||
Advanced Microeconomics I – III
Requirements for the assignment of ECTS-Credits and Grades: One homework (40%), one research paper about a set of articles (40%), and a presentation (60 minutes) of this paper (20%).
The course teaches contract theory at the level of the research frontier. It reviews a number of classic topics in contract theory and puts them in an abstract general framework that makes it possible to understand the underlying common structure of these topics. All topics are from finance, but there are many links to other fields of economics. The course therefore also benefits doctoral students in finance and serves as a bridge between the two fields.
The main topics are:
1. Contracts and contingent markets, 2. Debt Contracts, 3. Hidden actions, 4. Incomplete contracts and renegotiation.
Students are supposed to understand the deep structure of hidden information, hidden actions, and unverifiability problems and the common features shared by these problems. They are able to master the complex technical difficulties arising in the formulation and solution of such problems and can use the tools of contract theory in their own research.
Students are able to read publications at the research frontier in information economics and contract theory in the fields of finance and related areas and to judge the conceptual value of the approaches taken in these papers. They can communicate their findings to other students and researchers by means of full academic presentation and in research-type articles. They can evaluate the relevance and correctness of technical arguments made in the literature and identify mistakes in publications. They are capable of assessing which arguments are novel and likely to generate intellectual progress, and which ones are just technical firework.
Lecture | |||||||
Lecture | 04.09.19 – 11.09.19 | Wednesday | 10:30 – 12:00 | L9,1–2, 002 | |||
Lecture | 17.09.19 – 04.12.19 | Wednesday | 10:30 – 12:00 | L7,3–5, 410 | |||
This course reviews the implications of relaxing the rational expectations assumption in dynamic
macroeconomic models. It replaces the rational expectations hypothesis by the view that agents are
learning and constantly trying to improve their forecasts about payoff‐relevant variables beyond
their control. The course introduces the decision‐theoretic foundations of learning models, reviews
the basic theoretical results about the asymptotic behavior of learning models, and presents
applications of learning models for understanding business cycles and asset price behavior.
The course illustrates how the introduction of learning into otherwise standard dynamic economic
models generates additional propagation and can significantly enhance their empirical performance.
The learning approach was initially used to assess the plausibility of rational expectations (RE)
equilibria by studying whether or not learning convergence towards RE. Recently, more work focuses
on empirical applications and on policy implications.
Lecture | |||||||
Lecture | 10.10.19 | Thursday | 13:45 – 15:15 | L7, 3–5, S 031 | |||
Lecture | 17.10.19 | Thursday | 13:45 – 17:00 | L9, 1–2, 210 | |||
Lecture | 24.10.19 | Thursday | 13:45 – 17:00 | B6, 30–32, 211 | |||
Lecture | 07.11.19 | Thursday | 13:45 – 17:00 | B6, 30–32, 211 | |||
Exam | 21.11.19 | Thursday | 13:45 – 15:15 | B6, 30–32, 211 | |||
The course is intended as a forum to discuss and critically examine current research in the field of Empirical Political Economy. More specifically, the papers discussed in this class deal with the effects of institutions (electoral system, timing of elections, etc.) on the incentives that policymakers have while in office and on the type of politicians that decide to run for office and that are selected into office. Methodologically, the emphasis is on research designs that allow for a causal interpretation and that analyze the effect of political and fiscal institutions on policy outcomes.
Grading: 50% presentation + 50% referee report
Relevant literature for referee reports
www.andersonfrey.com/uploads/5/9/0/0/59009301/paper_may19.pdf
Relevant literature for presentations
Seminar | |||||||
Kick-off meeting | 02.09.19 | Monday | 15:30 – 17:00 | L7,3–5, 410 | |||
Individuall presentations | 12.11.19 | Tuesday | 08:30 – 18:30 | L9, 1–2, 409 |
E700 – E703, E801 – E806
Requirement for the assignment of ECTS-Credits and Grades
Presentations and seminar paper.
This block seminar is intended to discuss topics around theoretical as well as applied research in the area of causal inference as well as randomized experiments and experimental design. Students are encouraged to review literature on a topic within this field, and explore if such research field may reflect or support their development of their own PhD project. Seminar topics normally refer to either Econometric Theory, i.e. identification or design development as well as estimators and their properties, or the applicability of methods that are linked to causal identification.
Contact Person: Prof. Dr. Markus Frölich, froelich
uni-mannheim.deLecture | |||||||
04.09.19 – 04.12.19 | Wednesday | 12:00 – 13:30 | L7,3–5, P 043 | ||||
PhD program in economics: E700-E703 and E801-E806.
Other programs: E700, E703, E803, and E806 or equivalent courses.
The lecture will focus on multivariate time series models. After reviewing a few issues on (non)stationary univariate time series models discussed in Advanced Econometrics III, we will first deal with stable VAR models and their use for forecasting, Granger causality and impulse response analysis. To this end, we will also discuss important issues on asymptotic- and bootstrap-based inference. Afterwards, we discuss stable VARMA processes and infinite-order VARs. Finally, we consider integrated multivariate processes, i.e. will we deal with unit root econometrics as well as cointegration, including VEC modelling. The course both addresses asymptotic analyses as well as implementation issues. Accordingly, tutorial sessions are also devoted to coding and empirical problems besides addressing theoretical problems. In the last part of the course, participants introduce or discuss in more details (further) model classes by giving presentations and writing a paper. We may cover e.g. Bayesian VARs, structural VARs, factor-augmented VARs, VARMA models, etc.. This course is complementary to the course Structural Vector Autoregessive Analysis offered by Matthias Meier. While the latter course focus on structural modelling approaches from an applied macro perspective, we take an econometric approach and deal with multivariate I(1) approaches, VECM and VARMA models in more detail.
Grading and assignment of ECTS-credits
Paper (40 %), presentation (30 %), assignments (30 %)
Literature
The students have acquired the necessary demanding econometric, statistical and mathematical techniques to understand and solve theoretical problems in uni-variate and multiple, time series analysis, i.e. in special fields of Econometrics. They are able to understand methodologically demanding specialist literature and, based on that, can extend their methodological knowledge independently. They are able to sort out relevant literature for problem solving, i.e. they can analyze and synthesise the special literature. The students have acquired basic tools for empirical time series analysis and can understand empirical time series literature. Based on their methodological expertise, they are able to independently extend their knowledge in order to conduct own empirical analyses. The students can formulate research questions, are able to analyze and address them, and and can present, discuss, and defend research results in written and oral form.
Lecture | |||||||
Lecture | 02.09.19 – 02.12.19 | Monday | 15:30 – 17:00 | L7, 3–5, P043 | |||
Lecture | 05.09.19 – 05.09.19 | Thursday | 10:15 – 11:45 | L7, 3–5, P043 | |||
First and second year PhD courses.
Requirements for the assignment: Presenting of Research Projects
Research seminar where Ph.D. students, who have completed their course work, present their own research and receive feedback. Occasionally we will also have an outside speaker.
Lecture | |||||||
05.09.19 – 05.12.19 | Thursday | 12:00 – 13:30 | L7, 3–5, P044 | ||||
All first-year PhD courses
Goals and Contents of the module: PhD-level course of the modern theory of industrial organization. Topics include monopoly pricing, static and dynamic oligopoly, collusion, mergers, industry dynamics, vertical relations.
Requirements for the Assignment of ECTS Credits and Grades
Written exam (100 %)
Acquisition of a deep understanding of the key topics, seminal models, and frontiers of research in theoretical industrial organization.
Lecture | |||||||
03.09.19 – 03.12.19 | Tuesday | 10:15 – 13:30 | L7, 3–5, P043 | ||||
E700-E703, E801-E806
Requirements for the Assignment of ECTS Credits and Grades
Presentation (100 %).
This seminar is aimed at PhD students writing their dissertation in Industrial Organization. It is intended to guide students at all stages of dissertation research. The emphasis be on presentation and discussion of material by students.
Doctoral Students will know how to
Lecture | |||||||
04.09.19 – 04.12.19 | Wednesday | 12:00 – 13:30 | L7, 3–5, P044 | ||||
First-year sequence in the Economics PhD program
Students will read, present and discuss current research concerning the optimal design of mechanisms.
Grading and assignment of ECTS-credits: Presentations
On successful completion of the module, students are expected to attain the following competences:
Lecture | |||||||
05.09.19 – 24.10.19 | Thursday | 12:00 – 13:30 | L7, 3–5, P043 | ||||
06.11.19 | Wednesday | 10:15 – 11:45 | L9,1–2, 002 | ||||
07.11.19 – 05.12.19 | Thursday | 12:00 – 13:30 | L7, 3–5, P043 | ||||
E700-E703, E801-E806
Students present and discuss policy related economic research.
Requirements for the assignment of ECTS-Credits and Grades
At least one presentation. Students who wish to obtain ECTS credits should sign up for the course, students who do not wish to obtain credits should not sign up for the course.
Students learn to apply economic theory and quantitative methods to policy problems.
Further information: Students who would like to participate should contact Hans Grüner before the beginning of the semester
Contact Information: Prof. Dr. Grüner, Phone: (0621) 181-1886, email: gruener@uni-mannheim.de, Office: L7, 3–5, room 2–06
Seminar | |||||||
02.09.19 – 03.12.19 | Monday | 17:20 – 18:50 | L7, 3–5, P 044 |
E700-E703, E801-E806
Goals and Contents of the module:
Presentation and discussion of current research in public economics (external and internal speakers)
Requirements for the assignment of ECTS-Credits and Grades: Oral presentation of own reserach, contribution to discussion of other perticipants' reserach; only pass/
Improve presentations skills, obtain feedback to improve research paper.
Seminar | |||||||
03.09.19 – 03.12.19 | Tuesday | 12:00 – 13:30 | L9, 1–2, 003 |
First year courses
The course introduces the recent literature on behavioural game theory and learning:
Information Cascades
Quantal- response equilibrium
Level- k theories
Fictious Play
Reinforcement Learning
Experience weighted attraction learning
Imitation
Grading and assignment of ECTS credits
Written exam (90 min)
Literature
Fudenberg, D. and D. Levine (1998) “The Theory of Learning in Games”, Cambridge, Mass.: MIT- Press
Colin Camerer (2003) “Behavioral Game Theory: Experiments in Strategic Interaction”, Princeton University Press
Expected competences acquired after completion of the module: Students should be able to read and understand the literature on learning in games. They should acquire several necessary theoretical and experimental tools that can be a starting point for independent Ph.D.
Lecture | |||||||
15.10.19 – 03.12.19 | Tuesday | 13:45 – 15:15 | L9, 1–2, 002 | ||||
E700- E703, E801- E806
In this seminar participants present and discuss their current research as well as ideas for future research. An important goal of the seminar is to provide a forum for students working on projects that use experimental methods or relate to themes in behavioral economics.
Grading and assignment of ECTS credits
Presentation and active participation
Further information
If you are interested in the seminar, please contact Henrik Orzen.
Designing laboratory or field experiments; Executing research projects; Presenting own research results.
Seminar | |||||||
04.09.19 – 04.12.19 | Wednesday | 10:15 – 11:45 | L7, 3–5, P044 |
E700-E703, E801-E806
This module intends to introduce PhD students to current topics in Experimental and Behavioral Economics and to familiarize them with recent advances in the field. The course will be delivered via a mix of lectures, joint readings of papers, in-class discussions and project work. The lectures will provide introductions to various topics and give relevant background information. Selected papers from the recent relevant literature will be discussed in depth. For this to work all participants will have to read specific papers in advance of individual meetings. Over the course of the semester each student is expected to lead the in-class discussion of two of the papers. The module will also provide a forum for students to discuss research ideas and preliminary work. In fact, students are expected to develop a research project of their own and present their advances, experimental design or data. This can be done individually or in pairs.
Grading and assignment of ECTS credits
This course employs a pass/
Advanced understanding of experimental methods; Acquiring knowledge about currently discussed research questions in the experimental literature; Developing a research agenda.
Lecture | |||||||
05.09.19 – 05.12.19 | Thursday | 15:30 – 17:00 | L7, 3–5, P043 | ||||
05.09.19 – 05.12.19 | Thursday | 17:15 – 18:45 | L7, 3–5, P043 | ||||
This course is targeted to second-year Ph.D. students in economics. Students are expected to have completed first-year micro and macro theory courses.
This course is an introduction to international trade at the Ph.D. level. The first part of the course will have a lecture structure and we will discuss the core models of modern international trade theory. We will study neoclassical trade models, i.e., the Ricardian- and Heckscher-Ohlin models and then move to trade models with imperfect competition. Particular emphasis will be given to models with firm-level heterogeneity. We will also cover the role of multinational firms and the effects of offshoring.
The second part of the course will be organized as a seminar: depending on the number of participants, either students will present papers at the research frontier or there will be a reading group format. Topics covered depend on the students’ interest.
Requirements for the assignment of ECTS-Credits and Grades
Class room participation, problem sets, oral presentation.
Students will be familiar with the core models and methods used in modern research in international trade. They will know the research frontier in this field and will be able to start independent research projects that may lead to a dissertation in international trade.
Lecture | |||||||
03.09.19 – 19.11.19 | Tuesday | 10:15 – 11:45 | L7, 3–5, 410 | ||||
26.11.19 | Tuesday | 10:15 – 11:45 | SO 133 (Schloss Schneckenhof Ost) | ||||
03.12.19 | Tuesday | 10:15 – 11:45 | L7, 3–5, 410 | ||||