Course Catalog

E8010: Econometrics Research Seminar (3rd & 4th year)

Lecturer(s)

Andreas Gerster

Course Type: elective course

Course Number: E8004

Credits: 2.5

Prerequisites

First-year sequence in the Economics PhD program.

Requirements for the assignment of ECTS-Credits and Grades: Presentations

Course Content

Students will read, present and discuss papers in environmental economics.

Competences acquired

Presentation skills
Participation in scientific discourse
Absorption of recent research in environmental economics
Acquisition of a reading routine

Schedule

Lecture
Lecture	09.09.24 – 18.11.24	Monday (bi-weekly)	13:45 – 15:15	410 (L7, 3–5)

E8017: Macroeconomic Shocks and Propagation: Methods and Applications (2nd year)

Lecturer(s)

Christoph Rothe

Course Type: elective course

Course Number: E8010

Credits: 5

Course Content

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.

Competences acquired

Contact information: Christoph Rothe, Phone: (0621) 181-1921, email: rothe@vwl.uni-mannheim.de, Office 1.11, L7,3–5, Office hours: by appointment

Schedule

Lecture
Lecture	05.09.24 – 05.12.24	Thursday	15:30 – 17:00	002 (L9, 1–2)

E8028: Financial Contract Theory (2nd year)

Lecturer(s)

Matthias Meier

Course Type: elective course

Course Number: E8017

Credits: 7.5

Prerequisites

E700–703, E801–806

Requirements for the Assignment of ECTS Credits and Grades

A research paper and regular assignments.

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.

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)

Competences acquired

The course introduces students to econometric methods and macroeconomic applications with a focus on business cycles.

Schedule

Lecture
Lecture	04.09.24 – 04.09.24	Wednesday	10:15 – 11:45	L7, 3–5, P044
Lecture	04.09.24 – 04.09.24	Wednesday	17:15 – 18:45	L9, 1–2, 003
Lecture	11.09.24 – 11.09.24	Wednesday	10:15 – 11:45	L7, 3–5, P044
Lecture	11.09.24 – 11.09.24	Wednesday	17:15 – 18:45	L9, 1–2, 003
Lecture	23.09.24 – 23.09.24	Monday	17:15 – 18:45	L7, 3–5, 410
Lecture	23.09.24 – 23.09.24	Monday	19:00 – 20:30	L7, 3–5, 410
Lecture	25.09.24 – 25.09.24	Wednesday	10:15 – 11:45	L7, 3–5, P044
Lecture	25.09.24 – 25.09.24	Wednesday	17:15 – 18:45	L9, 1–2, 003
Lecture	02.10.24 – 02.10.24	Wednesday	10:15 – 11:45	L7, 3–5, P044
Lecture	02.10.24 – 02.10.24	Wednesday	17:15 – 18:45	L9, 1–2, 003
Lecture	11.10.24 – 11.10.24	Friday	10:15 – 11:45	L7, 3–5, 410
Lecture	11.10.24 – 11.10.24	Friday	17:15 – 18:45	L7, 3–5, 410
Lecture	16.10.24 – 16.10.24	Wednesday	10:15 – 11:45	L7, 3–5, P044
Lecture	16.10.24 – 16.10.24	Wednesday	17:15 – 18:45	L9, 1–2, 003
Lecture	26.11.24 – 26.11.24	Tuesday	09:00 – 18:00	L9, 1–2, 210

E8034: Machine Learning for Economists (2nd year)

Lecturer(s)

Ernst-Ludwig von Thadden

Course Type: elective course

Course Number: E8028

Credits: 5

Prerequisites

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%).

Course Content

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:

Contracts and contingent markets
Debt Contracts
Hidden actions
Incomplete contracts and renegotiation.

Competences acquired

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.

Contact Information: Ernst-Ludwig von Thadden. Phone: (0621) 181 – 1914; email: vthadden@uni-mannheim.de; Office: 3.19, VWL-Building; Office hours: upon appointment.

Schedule

Lecture
Lecture	02.09.24 – 02.12.24	Monday	10:15 – 11:45	P 044 (L7, 3–5)

E8036: Research Seminar in Applied Economics

Lecturer(s)

Christoph Rothe

Course Type: elective course

Course Number: E8034

Credits: 5

Prerequisites

E700-E703, E801-E806

Course Content

The course is an introduction to modern machine learning (ML) methods for economists. In particular, we will discuss methods from the world of supervised and unsupervised ML, with an emphasis on the challenges and opportunities of integrating these methods in empirical economics, and the relevance of ML to policy analysis and causal inference.

Competences acquired

Upon course completion, students will be able to understand the idea behind modern machine learning methods, and both their advantages and disadvantages in the context of empirical economic research. They will also be able to apply these methods for their own project. In addition to that, students will acquire knowledge of theoretical foundations behind these methods.

Further information

A core reference for this course will be Hastie, Tibshirani & Friedman (2019), The Elements of Statistical Learning, Springer.

Further references and journal articles will be announced in class.

Contact Information

Christoph Rothe; Phone: (0621) 181 1921; email: rothe(at)vwl.uni-mannheim.de, Office: 1.11, Office hours: by appointment

Schedule

Lecture
Lecture	03.09.24 – 03.12.24	Tuesday	08:30 – 10:00	P 043 (L7, 3–5)

E8037: Public Economics I (2nd year)

Lecturer(s)

Philipp Ager

Antonio Ciccone

Course Type: elective course

Course Number: E8036

Credits: 2.5

Course Content

The research seminar is a forum for applied economics research in all fields (e.g. micro as well as macro). Participants will be asked to present their preliminary ideas and more advanced research or present the papers they are planning to base their research on. We will then discuss (further) open research questions and empirical strategies to address these questions.

Schedule

Lecture
Lecture	04.09.24 – 27.11.24	Wednesday (bi-weekly)	10:15 – 11:45	P 043 (L7, 3–5)

E8040: Research Seminar – Topics in Experimental Econometrics and Causal Inference (3rd & 4th year)

Lecturer(s)

Eckhard Janeba

Course Type: elective course

Course Number: E8037

Credits: 7.5

Prerequisites

E700-E703 or equivalent

Grading

One 120-minute written exam (100%)

Course Content

This course is intended to be the first part of the two-semester PhD-level Public Economics sequence. The field is large, with significant theoretical and empirical components. The first course covers core ideas in the areas of market failures and public intervention, optimal taxation, provision of public goods, political economy of taxation and redistribution, tax incidence, tax evasion. We consider both normative approaches, that is, we ask what an ideal state would do in order to achieve distributive objectives, as well as positive perspectives, that is, how policies affect outcomes and how they come about. The contents will be mostly but not exclusively theoretical, and the theoretical foundations will work as building blocks for empirical studies which will be covered in more detail in Public Economics II.

Topics to be covered:

Public Goods
Externalities
Price vs. Quantity Regulations
Introduction to Taxation / Tax Incidence
Excess Burden
Optimal Commodity Taxation
Optimal Income Taxation
Taxation of Firms/Capital
Taxation of Mobile Firms and Households
Tax Evasion

Competences acquired

The course introduces the core topics in Public Economics. The course should prove useful for any student interested in analyzing policy issues.

Further information

Lecture notes will be provided.

Useful references

Gruber, Public Finance and Public Policy, Worth Publishers, 2019
Atkinson and Stiglitz, Lectures on Public Economics, Mc Graw-Hill, 1980
Salanié, Microeconomics of market failures, MIT Press, 2010
Cornes and Sandler, The Theory of Externalities, Public Goods and Club Goods, Cambridge University Press, 2012
Salanié, The economics of taxation, MIT Press, 2011
Myles, Public Economics, Cambridge University Press, 1995
Mas-Collel, Whinston, Green, Microeconomic Theory, Harvard University Press, 1996
Stiglitz, Economics of the Public sector, 3rd Edition, 2000, Norton & Company
Hindriks and Myles, Intermediate Public Economics, MIT Press

Schedule

Lecture
Lecture	02.09.24 – 02.12.24	Monday	08:30 – 10:00	P 043 (L7, 3–5)
Lecture	04.09.24 – 27.11.24	Wednesday (bi-weekly)	08:30 – 10:00	P 043 (L7, 3–5)

E8041: Environmental Economics Research Seminar (3rd & 4th year)

Lecturer(s)

Markus Frölich

Course Type: elective course

Course Number: E8040

Credits: 5

Prerequisites

Successful completion of first two years of PhD programme

Requirements for the assignment of ECTS Credits and Grades: A written seminar paper on a topic of own choice and a presentation in class.

Course Content

Research seminar where Ph.D. students, who have completed their course work, present their own research and receive feedback. This 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.

Competences acquired

Doctoral Students will know how to
– identify a research question,
– put a research question into context of the relevant literature,
– present their current stage of research to their peers in a seminar environment.

Schedule

Lecture
Lecture	04.09.24 – 04.12.24	Wednesday	12:00 – 13:30	410 (L7, 3–5)

E8042: Economic History (2nd year)

Lecturer(s)

Andreas Gerster

Course Type: elective course

Course Number: E8041

Credits: 2.5

Course Content

In this seminar, internal and external speakers discuss their recent research in environmental economics. Students working on an empirical or theoretical project that is related to environmental economics are welcome to present. Please contact the instructor to set up a date.

Schedule

Lecture
Lecture	10.09.24 – 19.11.24	Tuesday (bi-weekly)	12:00 – 13:30	P 043 (L7, 3–5)

9 ECTS

Lecturer(s)

Alexander Donges

Course Type: elective course

Course Number: E8042

Credits: 9

Prerequisites

E601-E603 (or equivalent)

Grading

Writing a research proposal (70%), presenting + discussing a paper (20%), active participation (10%).

Course Content

Economic history is important for understanding long-run economic development and to study the question, why some countries became rich, while others remained poor. In this course, we focus on selected topics of quantitative economic history that have been explored by economists and economic historians in recent years. Topics include trade, the role of institutions in economic development, religion, human capital, innovation, market integration, financial development, inequality, migration, epidemics, and climate change. The weekly lecture (2 hours) will give you an overview on recent empirical research on each topic. In the weekly exercise sessions (2 hours), we will then discuss key research papers in more depth. Each student is required to presents a critical discussion of one research paper. The presentation accounts for 20% of the final grade, and the participation in class discussions accounts for 10% of the final grade.

Competences acquired

Students will acquire thorough knowledge of empirical methods used in modern applied economics and quantitative economic history. They will be able to apply their knowledge of econometrics in analyzing research questions in economic history and discuss potential policy implications, for example with respect to development policies. The course also aims at enabling students to critically evaluate empirical research designs that may encounter in their future career.

Further information

A detailed syllabus (including literature) is available on my website (https://www.vwl.uni-mannheim.de/en/donges/)

Contact Information

Dr. Alexander Donges; phone: 0621-181-3428; e-mail: donges@uni-mannheim.de; office: L7, 3–5, room 403.

Schedule

Lecture
Lecture	05.09.24 – 05.12.24	Thursday	12:00 – 15:15	003 (L9, 1–2)

E8054: Research in Health and Labor Economics (2nd & 3rd year)

10 ECTS

Lecturer(s)

Ziebarth Nicolas R.

Course Type: elective course

Course Number: E8054

Credits: 10

Prerequisites

Requirements for the assignment of ECTS-Credits and Grades:

Paper presentation: 10%
Research sketches on promising research ideas: 25%
Report on fellow student’s research sketches: 15%
End-of-semester presentation of most promising research sketch: 15%
Extended research sketch on most promising research idea and design: 25%
Class attendance: 5%
Class participation: 5%

Total: max 100%

Course Content

This course has two main objectives: (i) To teach PhD students the process of developing research ideas and carrying out research themselves. (ii) To provide a state-of-the-art overview of research topics at the intersection of health and labor economics.

Competences acquired

Acquiring an understanding of the process of doing research.
Acquiring tools and techniques to publish scientific papers in the field of applied economics.
Learning how to generate and dismiss research ideas.
Acquiring the ability to write concise and high-quality research sketches and provide constructive feedback on other students’ sketches.
Obtaining an up-to-date overview of the studies, methods, and findings of the applied economics literature at the interaction of health and labor.
Applying knowledge from (applied) (micro)econometrics and microeconomic theory to topics in health and labor.
Improving presentation and communications skills.
Discussing others’ work in a constructive manner, and to learn how to deal with constructive critique.

Further information:

Syllabus will be posted in the first week of class. Readings for each week will be announced each week.

Schedule

Lecture
Lecture	03.09.24 – 03.12.24	Tuesday	13:45 – 15:15	002 (L9, 1–2)
Lecture	05.09.24 – 05.12.24	Thursday	15:30 – 17:00	P 043 (L7, 3–5)

E8057: Research Empirical Industrial Organization

E8060: Colloquium for Doctoral Students (3rd & 4th year)

Lecturer(s)

Michelle Sovinsky

Course Type: elective course

Course Number: E8057

Credits: 7.5

Prerequisites

Second year empirical IO PhD or instructor permission.

Requirements for the assignment of ECTS-Credits and Grades
Pass/Fail based on discussion and presentation in class

Course Content

This course is for PhD students writing their dissertation in Empirical Industrial Organization. It is intended to guide students in their dissertation research.

Competences acquired

Doctoral students will learn how to solve common problems arising during the research process, how to present their results, how to write up their project, and how to present their research.

Further information
Please send a CV 2 weeks prior to registration

Schedule

Lecture
Lecture	05.09.24 – 05.12.24	Thursday	11:00 – 13:45	002 (L9, 1–2)

E8061: Nonparametric Methods (2nd year)

Lecturer(s)

Philipp Ager

Antonio Ciccone

Course Type: elective course

Course Number: E8060

Credits: 2.5

Prerequisites

Dissertation advised by Ager or Ciccone, or by invitation

Requirements for the assignment of ECTS-Credits and Grades
Presentations and papers

Grading and ECTS credits:
100% weight on presentation and papers

Course Content

The course wants to (1) help students start on their dissertation research (2) help students in writing their research papers (3) help students in improving their skills in presenting their research

Competences acquired

Develop the ability to start, write up, and present their own research

Schedule

Lecture
Lecture	05.09.24 – 28.11.24	Thursday (bi-weekly)	10:15 – 11:45	P 044 (L7, 3–5)

E8063: Empirical Energy Economics (2nd year)

Lecturer(s)

Mengshan Xu

Course Type: elective course

Course Number: E8061

Credits: 5

Prerequisites

E700-E703, E803 (or equivalent)

Grading: Final exam (90 min, 100%)

Course Content

This course provides an introduction to nonparametric estimation, viewed from both theoretical and applied perspectives. Nonparametric methods do not rely on the assumption that models can be defined by finite-dimensional parameters. Instead, infinite-dimensional classes of targets under smoothness conditions are considered, such as a class of smooth density functions. The discussed methods are suitable for students who do not possess prior knowledge of the functional structures of the underlying models. The course begins by briefly reviewing density estimation and regression problems based on kernel estimators. It then shifts focus to Series estimation, Nonparametric IV, and Nonparametric identification. The statistical properties of the estimators, including consistency, upper bounds for estimation risk, and asymptotic normality, will be explored. Throughout the course, students will encounter typical phenomena like the curse of dimensionality, which has attracted significant attention and serves as the foundation for numerous develompents in the analysis of big data.

Competences acquired

Upon completing this course, students will have acquired a working knowledge of classical nonparametric methods for estimating conditional mean functions. They will understand the theoretical background of these methods and become familiar with concepts that enable them to describe and assess the properties of estimators. The students will be able to apply the discussed estimation procedures to data using statistical software. Furthermore, they will be aware of the strengths and limitations of the nonparametric techniques introduced throughout the course.

Further Information

Recommended textbooks:

Econometrics, Bruce E. Hansen, University of Wisconsin (2021)
Semiparametric and nonparametric methods in econometrics, Horowitz (2009)
Introduction to Nonparametric Estimation, Tsybakov (2009)

Contact information

Name: Prof. Mengshan Xu, PhD.; Email: Mengshan.Xu(at)uni-mannheim.de; Office: L7, 3–5, room 1.08; Office hours: upon appointment

Schedule

Lecture
Lecture-coursetimes have changed!	05.09.24 – 17.10.24	Thursday	17:15 – 18:45	tba
Lecture	06.09.24 – 18.10.24	Friday	13:45 – 15:15	211 (B6, 30–32)

E823: Advanced Time Series Analysis (2nd year)

Lecturer(s)

Mateus Souza

Course Type: elective course

Course Number: E8063

Credits: 5

Prerequisites

E700-E703, E801-E806

Grading

Sketch research proposal (20%); final research proposal (40%); presentation (20%); referee report (20%).

Course Content

The course will provide an overview of recent empirical research in energy economics. Most of the mandatory readings are journal articles that rigorously employ reduced-form methods for causal inference. Students will also learn about recent applications of machine learning for research in energy/environmental economics. More focus will be placed on demand-side applications, with some coverage of supply-side (electricity market) issues as well. Main topics:

The “Energy Efficiency Gap” and possible explanations;
Misaligned incentives for energy efficiency, the “landlord-tenant problem” and policies to address it;
Discrepancies between projected and realized savings from energy efficiency policies/programs;
Energy price elasticities in the residential sector;
Real-time pricing and time-of-use pricing;
Energy price elasticities in manufacturing and commercial sectors;
Behavioral energy economics;
Energy efficiency in transportation;
Machine learning applications in energy economics;
Targeting energy interventions;
Overview of electricity markets;
Electricity markets with expanding renewables and storage capacity.

Competences acquired

The course will provide highly specialized knowledge related to empirical applications for energy economics. This knowledge will help students to identify “gaps” in the field and promising new avenues of research. By developing a research proposal, students will enhance their ability to summarize complex information, to perform independent work, and to write to academic audiences. Student presentations will foster the development of communication skills, especially with regards to exchanging ideas, as well as providing and receiving feedback within academic environments.

Further information

At the beginning of the term, students will be provided with a syllabus, including a list of required and recommended readings (journal articles, working papers, and handbook chapters)

Contact Information

Dr. Mateus Souza; email: mateus.souzamail-uni-mannheim.de

Schedule

Lecture
Lecture	06.09.24 – 06.12.24	Friday	10:15 – 11:45	P 044 (L7, 3–5)

9 ECTS

Lecturer(s)

Carsten Trenkler

Course Type: elective course

Course Number: E823

Credits: 9

Prerequisites

PhD program in economics: E700-E703 and E801-E806; other programs: E700, E703, E803, and E806 or equivalent courses

Examination

Paper (40%), presentation (30%), assignments (30%)

Course Content

The lecture will focus on multivariate time series models. After reviewing some fundamental theoretical time series concepts, 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 integrated multivariate processes, i.e. will we deal with unit root econometrics as well as cointegration. If time permits, we may consider factor models or high-dimensional VARs. 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 Autoregressive 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, VARs, VARMA models, etc.. This course is complementary to the course Structural Vector Autoregressive 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.

Competences acquired

The students have acquired the necessary demanding econometric, statistical, and mathematical techniques to understand and solve theoretical problems in univariate 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 synthesize 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 can present, discuss, and defend research results in written and oral form.

Literature

Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press
Hayashi, F. (2000), Econometrics, Princeton University Press
Kilian und Lütkepohl (2017), Structural Vector Autoregressive Analysis, CUP
Lütkepohl, H. (2005), New Introduction to Multiple Time Series Analysis, Springer
Lütkepohl, H. and Krätzig, M. (2004), Applied Time Series Econometrics, CUP
White, H. (2000), Asymptotic Theory for Econometricians, Academic Press.

Further literature will be announced at the beginning of the course.

Contact Information

Prof. Dr. Carsten Trenkler, e-Mail: trenkleruni-mannheim.de, L7, 3–5, Raum 105, Tel. 181-1852

Schedule

Lecture
Lecture	02.09.24 – 02.12.24	Monday	15:30 – 17:00	P 043 (L7, 3–5)
Lecture	05.09.24 – 05.12.24	Thursday	10:15 – 11:45	410 (L7, 3–5)

E839: Topics in Macroeconomics (3rd & 4th year)

E846: PhD Reading Course in Industrial Organization (2nd-4th year)

Lecturer(s)

Michèle Tertilt

Matthias Meier

Course Type: elective course

Course Number: E839

Credits: 5

Prerequisites

first and second year Ph.D. courses

Requirements for the assignment: Presenting of Research Projects

Course Content

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.

Schedule

Lecture
Lecture	04.09.24 – 04.12.24	Monday	15:30 – 17:00	P 043 (L7, 3–5)

E859: Institutional Economics and Economic Policy (2nd year)

Lecturer(s)

Volker Nocke

Course Type: elective course

Course Number: E846

Credits: 5

Prerequisites

Requirements for the Assignment of ECTS Credits and Grades: Presentation (100%)

Prerequistes: All of the first-year PhD courses

Course Content

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.

Competences acquired

Doctoral Students wil know how to
– identify a research question
– put a research question into context of the relevant literature
– present their current stage of research to their peers in a seminar environment

Contact person: Prof. Volker Nocke, Ph.D. E-Mail: volker.nockemail-uni-mannheim.de

Schedule

Lecture
Lecture	04.09.24 – 04.12.24	Wednesday	12:00 – 13:30	P 043 (L7, 3–5)

E866: Research Seminar in Economic Policy (3rd & 4th year)

Lecturer(s)

Hans Peter Grüner

Course Type: elective course

Course Number: E859

Credits: 7.5

Prerequisites

PhD students/Master of Economic Research students: E700-E703, E801-E806
Master of Economics students (fall 2015 only): Participants should ideally have received a grade of at least 2.3 in E601 (or an equivalent course). If in doubt, please contact the course instructor.

Requirements for the assignment of ECTS-credits and grades: written exam (90 minutes)

Course Content

Introduction
Mechanism Design Theory: Basics
Mechanisms with lower informational requirements Robust mechanism design
Strategically simple mechanisms
The boundaries of institutions
Delay in information processing and decentralization
Provision of public goods (with transfers)
Financing indivisible public goods with possible use exclusion Theory
Experimental evidence
Preference aggregation with voting rules and related mechanisms Linear voting rules
Information aggregation in committees
Prediction markets and crowdfunding
Models of fiscal instability
Mechanisms for fiscal stability
European economic governance

Competences acquired

Students learn about theories of information aggregation in institutions. They learn to apply them to practical problems.

Responsible teacher of the module: Prof. Dr. Grüner, Tel. (0621) 181-1886, E-Mail: gruener@uni-mannheim.de, Office: L7, 3–5, room 2–05

Schedule

Lecture
Lecture	02.09.24 – 02.12.24	Monday	13:00 – 15:15	002 (L9, 1–2)

E873: Research Seminar Public Economics (3rd & 4th year)

Lecturer(s)

Hans Peter Grüner

Course Type: elective course

Course Number: E866

Credits: 5

Prerequisites

E700-E703, E801-E806
Grading: 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.

Course Content

Students present and discuss policy related economic research

Competences acquired

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, E-Mail: gruener@uni-mannheim.de, Office: L7, 3–5, room 2–05

Schedule

Lecture
Lecture	02.09.24 – 02.12.24	Monday	15:30 – 17:00	002 (L9, 1–2)

E877: Behavioral Game Theory (and Experiments) (2nd year)

Lecturer(s)

Eckhard Janeba

Arthur Seibold

Course Type: elective course

Course Number: E873

Credits: 5

Prerequisites

at least second year Ph.D. or Research Master

Requirements for the assignment of ECTS-Credits and Grades: Oral presentation of own reserach, contribution to discussion of other perticipants' reserach; only pass/ fail.

Course Content

Presentation and discussion of current research in public economics (external and internal speakers)

Competences acquired

Improve presentations skills, obtain feedback to improve research paper.

Schedule

Lecture
Lecture	03.09.24 – 03.12.24	Tuesday	12:00 – 13:30	P 044 (L7, 3–5)

4 ECTS

Lecturer(s)

Jörg Oechssler

Course Type: elective course

Course Number: E877

Credits: 4

Prerequisites

First year courses

Grading and assignment of ECTS credits

Written exam (90 min)

Course Content

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

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

Competences acquired

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.

Lecturer: Prof. Jörg Oechssler, Ph.D., Heidelberg University

Schedule

Lecture
Lecture	15.10.24 – 03.12.24	Tuesday	12:00 – 13:30	002 (L9, 1–2)

E878: Advanced PhD Seminar in Experimental Economics (2nd year)

E883: Topics and projects in experimental economics (2nd year)

Lecturer(s)

Henrik Orzen

Course Type: elective course

Course Number: E878

Credits: 5

Prerequisites

E700-E703, E801-E806

Grading: Attendance and participation in discussion and presentation of own research. Grades are assigned on a pass/non-pass basis.

Course Content

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.

Competences acquired

Designing laboratory and/or field experiments; Executing research projects; Presenting own research results.

Further information: If you are interested in the seminar, please contact Henrik Orzen.

Contact Information: Prof. Dr. Henrik Orzen; Phone: (0621) 181 – 1890; email: henrik.orzen@uni-mannheim.de; Office: Room 4.01; Office hours: Tuesdays, 4–5pm (by appointment only).

Schedule

Lecture
Lecture	03.09.24 – 03.12.24	Tuesday	13:45 – 15:15	410 (L7, 3–5)

10 ECTS

Lecturer(s)

Wladislaw Mill

Henrik Orzen

Course Type: elective course

Course Number: E883

Credits: 10

Prerequisites

E700-E703, E801-E806.

Grading: Attendance and participation in discussion and presentation of own research. Writing a research proposal. Grades are assigned on a pass/non-pass basis.

Course Content

This module is intended to introduce 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 student-led presentations, joint readings of papers, in-class discussions and project work. Selected papers from the recent relevant literature will be discussed in depth and participants will jointly work on developing research ideas. A goal of the module is that at the end of the semester students have identified some interesting research questions and are able to outline concrete plans of how they can be answered. The role of the group is not only to provide a forum for individuals to get feedback on their ideas but to become actively engaged with each project. For this to work participants have to be prepared to read papers, to do some literature research and to contribute actively to the class discussion.

Competences acquired

On completion of the module students will have gained insights into recent topics of research in experimental and behavioral economics. They will have improved their ability to present—in a clear and structured manner—their own research ideas. They will have gained practice in adequately and constructively criticizing research ideas and their implementation, and they will have acquired advanced skills in communication and team work. They will have developed an improved sense of recognizing the potentials of a research idea.

Further information: Please refer to the syllabus of this course for further information, in particular on the required presentations in week two of the semester.

Contact Information: Prof. Dr. Henrik Orzen; Phone: (0621) 181 – 1890; email: henrik.orzen@uni-mannheim.de; Office: Room 4.01; Office hours: Tuesdays, 4–5pm (by appointment only).

Schedule

Lecture
Lecture	05.09.24 – 05.12.24	Thursday	13:45 – 17:00	410 (L7, 3–5)

E918: Labor Markets and Heterogenity (2nd year)

E919: Colloquium for students interested in Economic History (3rd & 4th year)

Lecturer(s)

Moritz Kuhn

Course Type: elective course

Course Number: E918

Credits: 5

Prerequisites

Requirements for the assignment of ECTS-Credits and Grades

After the introduction to the topic (4–6 classes), each student is expected to present a paper related to the topic of the course. The plan is to have one paper presented and discussed each week. Active participation in the discussion in each week is expected. Each presentation should include a discussion of the paper using some empirical and/or quantitative theoretical work related to the paper. Each student is expected to write a research proposal that has to be handed in. The research proposal must sketch a clear idea for a research project and must contain some empirical and/or quantitative work. There will be additional time to work on research proposals after the last meeting.

Grade will be 65% research proposal, 25% presentation in class, 10% participation in discussion.

Course Content

In this class, we discuss the existing literature that explores how heterogeneity across workers, firms, or locations affects labor market outcomes. The class starts with an introduction to search models of the labor market and discusses simple extensions to include heterogeneity. One particular focus of the class will be on recent papers exploring the interaction of workers at the workplace and production in teams. I will go over some seminal papers on heterogeneity.

Competences acquired

Upon completion, students will be able: (i) to understand, work, and extend heterogeneous agent models with frictional labor markets, (ii) connect the theoretical models and existing empirical evidence, (iii) work with microdata related to labor market models.

Further

Any questions should be sent to Moritz Kuhn, mokuhnmail-uni-mannheim.de

Schedule

Lecture
Lecture	03.09.24 – 03.12.24	Tuesday	10:15 – 11:45	P043

E920: Uncertainty, Learning and Dynamics (2nd year)

Lecturer(s)

Philipp Ager

Jochen Streb

Alexander Donges

Course Type: elective course

Course Number: E919

Credits: 2.5

Prerequisites

Students interested in Economic History (3^rd year and higher). By invitation.

Grading and ECTS credits:

100% weight on presentation and papers.

Course Content

The course wants to (1) help students interested in Economic History start on their dissertation research (2) help students in writing their research papers (3) help students in improving their skills in presenting their research.

Competences acquired

Develop the ability to start, write up, and present their own research.

Responsible teacher of the module
Philipp Ager and Jochen Streb

Additional teachers
Alexander Donges

Schedule

Seminar
Seminar	11.09.24 – 04.12.24	Wednesday (every two weeks)	08:30 – 10:00	P043

10 ECTS

Course Type: elective course

Course Number: E920

Credits: 10

Prerequisites

First year PhD courses

Course Content

The gradual acquisition of information over time is a key aspect of many economic
interactions. This course covers the main dynamic models of learning in economics,
and some of their manifold applications. The canonical models include games of experimentation
(Keller, Rady, and Cripps (2005)), the ‘complex environments’ introduced by
Callander (2011), and ‘flexible’ learning (Zhong (2022)). Applications include contest
design, R&D delegation, elections, incentivising teams, product placement, consumer
search, and ‘information design’ (that is, the optimal disclosure of information geared at
influencing behaviour, e.g. by a seller to potential buyers).
Lectures will take place during the first half of the course, and student presentations
in the second half. The lectures will cover the seminal papers on the topic (including the
aforementioned ones), as well as some basics of dynamic optimisation. Student presentations
will each cover one other paper in the literature.
The course evaluation is based upon the presentations. Each presentation is allocated
45 minutes. Students should prepare slides (as a PDF) for a 30-minute talk, with the
remaining 15 minutes available for questions and discussion.

Lecturer:

Dr. Gregorio Curello

Schedule

Lecture
Lecture	30.09.24 – 30.09.24	Monday	17:15 – 18:45	B6, 30–32, 230
Lecture	01.10.24 – 01.10.24	Tuesday	10:15 – 11:45	B6, 30–32, 230
Lecture	08.10.24 – 08.10.24	Tuesday	10:15 – 11:45	B6, 30–32, 230
Lecture	10.10.24 – 10.10.24	Thursday	15:30 – 17:00	B6, 30–32, 230
Lecture	15.10.24 – 15.10.24	Tuesday	17:15 – 18:45	B6, 30–32, 230
Lecture	17.10.24 – 17.10.24	Thursday	15:30 – 17:00	B6, 30–32, 230
Lecture	22.10.24 – 22.10.24	Tuesday	10:15 – 11:45	B6, 30–32, 230
Lecture	24.10.24 – 24.10.24	Thursday	15:30 – 17:00	B6, 30–32, 405
Lecture	29.10.24 – 29.10.24	Tuesday	10:15 – 11:45	B6, 30–32, 230
Lecture	31.10.24 – 31.10.24	Thursday	15:30 – 17:00	B6, 30–32, 230
Lecture	05.11.24 – 05.11.24	Tuesday	17:15 – 18:45	B6, 30–32, 230
Lecture	07.11.24 – 07.11.24	Thursday	15:30 – 17:30	B6, 30–32, 230
Lecture	11.11.24 – 11.11.24	Monday	17:15 – 18:45	B6, 30–32, 230
Lecture	12.11.24 – 12.11.24	Tuesday	17:15 – 18:45	B6, 30–32, 230
Lecture	18.11.24 – 18.11.24	Monday	17:15 – 18:45	B6, 30–32, 230
Lecture	19.11.24 – 19.11.24	Tuesday	10:15 – 11:45	B6, 30–32, 230
Lecture	25.11.24 – 25.11.24	Monday	17:15 – 18:45	B6, 30–32, 230
Lecture	26.11.24 – 26.11.24	Tuesday	17:15 – 18:45	B6, 30–32, 230
Lecture	02.12.24 – 02.12.24	Monday	17:15 – 18:45	B6, 30–32, 230
Lecture	03.12.24 – 03.12.24	Tuesday	17:15 – 18:45	B6, 30–32, 230

E921/E5091: Matching Theory Based Market Design

Prof. Achim Wambach, Ph.D.
Gian Caspari, Ph.D.

Course Type: elective course

Course Number: E921/E5091

Credits: 5

Prerequisites

E601- E603 (or equivalent)

Requirements for the assignment of ECTS-Credits and Grades

Presentation (30 min, 50%), report (22,000 characters including spaces, 50%)

Course Content

The seminar covers the most prominent market design applications rooted in matching theory. The purpose of this seminar is to let students present research papers on market design, get familiar with the state of art in the field and inspire their own research in this area.

Competences acquired

Students have gained knowledge about the most prominent matching based market design applications. They can apply their expertise and methods to analyze and evaluate ongoing debates in both the academic and the policy-oriented literature. The students have broadened their analytical abilities as well as their presentation and discussion skills.

Lecturers

Contact

Gian Caspari, Ph.D.; Email: gian.casparimail-zew.de

Info session 21/8, 1.45 pm : https://uni-mannheim.zoom-x.de/j/67287794528?pwd=eVxbXICzZhNXeS1OOYovDV6O4QabNn.1

Schedule

Lecture
Info session	21.08.24 – 21.08.24	Wednesday	13:45 – 15:15	Zoom (see description)
Block seminar	05.12.24 – 06.12.24		00:00 – 00:00	ZEW, time tba

RES (Bridge course): Lecture series “Data Science in Action”

and:
https://www.linkedin.com/posts/mannheimdatascience_the-fall-semester-is-approaching-and-with-activity-7221818722364080128-_JW7?utm_source=share&utm_medium=member_desktop

Course Type: elective course

Course Number: RES (Bridge course)

Credits: 5

Course Content

Our colleagues from the Mannheim Center for Data Science are offering a lecture series “Data Science in Action” for the upcoming fall term. The lecture series is online and starts on tbc.

GESS doctoral students can attend the event as a bridge course. In order to receive the 5 ECTS points, you need to take part in at 80% of the lectures and write a 15 page essay (pass/fail assessment).

For more information and registration, please visit the website: https://www.uni-mannheim.de/datascience/details/ringvorlesung-data-science-in-action-hws-2024-donnerstags-12-1330-uhr-online-via-zoom/

RES (bridge course): Mental health during dissertations (GESS doctoral students only)