BE INSPIRED

"The CDSB core courses and especially the electives are very useful because they equip us with solid skills in our field of research as well as in related fields." Kirstin Becker, CDSB

Course Catalog

Fall 2018

Lecturer(s)


Course Type: core course

Course Number: ACC 902

Credits: 8

Course Content

This course investigates strategies of normative research with regard to International Financial Reporting Standards (IFRS) from an interdisciplinary perspective. In the first part of the course, we discuss the foundations of normative accounting research. In particular, we show how this research methodology can successfully be applied despite claims of its alleged impossibility. Furthermore, we compare the legal traditions of normative interpretation in the US and in Europe. In the second part, we analyze the existing system of IFRS from different conceptual approaches and develop grounds for their further general development as well as solutions.

Learning outcomes: The purpose is to equip PhD students with the ability to do normative research in financial accounting, thus, to reason qualitatively on topical issues in the field of global financial reporting. The focus is on investigating strategies of normative research with regard to International Financial Reporting Standards (IFRS) from an interdisciplinary perspective, comprising fields as legal theory and other social sciences.

 

Form of assessment: Paper, Presentation


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-off
21.09.18
Friday
14:00
16:00
O 254


Course Type: core course

Course Number: ACC/TAX 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. For each presentation, a separate preparation session for the Ph.D. students is offered in advance by rotating faculty. Overall, the course deepens the students’ insights into a variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.



Course Type: core course

Course Number: ACC/TAX 920

Course Content

The course is taught in a seminar-style format. Students present their own research ideas at different stages of the project (early ideas, preliminary results, and complete working papers). The presentations involve an interactive discussion between faculty and students about the project’s potential contribution, related literature, research design and interpretation of results.

Learning outcomes: Students will learn how to present and discuss their own research results in a scientific format. They will become acquainted with acting as a discussant for other topics. Students will gain insights into the assessment of contribution, research design, and interpretation of research papers. The development of these skills is also helpful for writing scientific referee reports.


Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Course Content

The course is designed to offer an advanced treatment to econometric theory and applications. Topics covered include: Repetition of ordinary least squares and generalized least squares, instrumental variables estimation, simultaneous equations, generalized method of moments and maximum likelihood estimation, time series and panel data econometrics. Attendance in the lectures and exercise sessions are mandatory. Attempting exercise questions ahead of each session and taking active part during the course of the sessions is essential.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
02.10.18
04.12.18
Tuesday
10:15
11:45
SN 169
11.10.18
06.12.18
Thursday
10:15
11:45
O 135
Tutorial
10.10.18
05.12.18
Wednesday
12:00
13:30
L7, 3-5, room 257
12.10.18
07.12.18
Friday
13:45
15:15
L9, 1-2, room 009

Lecturer(s)


Course Type: core course

Course Number: E700

Credits: 6

Prerequisites

Basic mathematical knowledge


Course Content

The course consists of four chapters:

  • Chapter 1: basic mathematical concepts like sets, functions and relations are introduced and discussed. Strict mathematical reasoning is explained and applied.
  • Chapter 2: covers the concept of metric and normed spaces and discusses the convergence of sequences in these spaces, the continuity of functions, and the concept of compact sets.
  • Chapter 3: deal with vector spaces. matrix algebra, linear transformation, and eigenvalues of matrices.
  • Chapter 4: covers a multivariate concept of differentiability and its application in solving unconstraint and constrained optimization problems.

Requirements for the assignment of ECTS Credits and Grades

Exam (120 min)

The exam takes place on October 4, 2018, 08:30-10:30


Competences acquired

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 2+3

Claudio Kretz (CDSE)

 

Exercise Group 4+5

Can Çelebi (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.09.18
24.09.18
Monday
10:15
11:45
A5, 6, C015
04.09.18
25.09.18
Tuesday
10:15
11:45
A5, 6, C014
05.09.18
26.09.18
Wednesday
10:15
11:45
A5, 6, C013
06.09.18
27.09.18
Thursday
10:15
11:45
209 in B6, 30-32
written exam
04.10.18
Thursday
08:30
10:30
L7, 3-5, 001
Tutorial
Group 2
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A303
Group 3
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A302
Group 4
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A301
Group 5
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A301
Group 2
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A302
Group 3
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A302
Group 4
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A301
Group 5
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A301
Group 2
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A302
Group 3
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A302
Group 4
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A303
Group 5
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A301
Group 2
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A302
Group 3
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A301
Group 4
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A303
Group 5
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A303

Lecturer(s)


Course Type: core course

Course Number: E701

Credits: 8

Prerequisites

E700


Course Content

The course gives a foundation for studies for microeconomics at the PhD level. The first part is devoted to consumer and producer theory. It is organized as follows:

 

1. Choice, preference and utility

2. Structural properties of preferences and utility functions

3. Basics of consumer demand

4. Expenditure minimization

5. Classical demand theory

6. Competitive and profit-maximizing firms

7. Consumer and producer surplus

8. Choice under uncertainty

9. Utility for money

 

The second part covers game theory and is organized as follows:

10. Static games of complete information: Rationalizability and iterated strict dominance

11. Static games of complete information: Nash equilibrium

12. Static games of incomplete information

13. Dynamic games: The extensive form

14. Dynamic games: Equilibrium concepts

 

Requirements for the assignment of ECTS-Credits and Grades

  • Written exam: 120 min (90% weighting)
  • Exercises (10% weighting)

 

Literature

Recommended textbooks:

  • Fudenberg, D & Tirole, J. (1991). Game Theory. MIT Press
  • Kreps, D. (2012). Microeconomic Foundation 1: Choice and Competitive Markets. Princeton University Press.
  • Mas- Colell, A. Whinston, M.D. & Green, J. (1995). Microeconomic Theory. Oxford University Press.
  • Osborne M. and Rubinstein, A. (1994): A Course in Game Theory. MIT Press

 



Competences acquired

Students learn the basic tools for graduate level microeconomic analysis. The concepts learned in the course serve as building blocks for more advanced topics such as the ones studied in Advanced Microeconomics 2 and 3 and also for macroeconomics and empirical studies. Students also learn using rigorous formal proofs for microeconomic questions.

 

Teaching Assistant

Can Çelebi


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
08.10.18
03.12.18
Monday
10:15
11:45
L7, 3-5, 001
10.10.18
05.12.18
Wednesday
10:15
11:45
L7, 3-5, 001
Written Exam
14.12.18
Friday
08:30
10:30
L7, 3-5, 001
Retake
28.01.19
Monday
10:15
12:15
B6, 30-32, 212
Tutorial
08.10.18
03.12.18
Monday
08:30
10:00
B6, 30-32, 211
09.10.18
04.12.18
Tuesday
08:30
10:00
B6, 30-32, 211

Lecturer(s)


Course Type: elective course

Course Content

This course aims to provide a working knowledge of basic probability theory and inductive statistics. The course is especially recommended for students wanting to refresh the skills required to attend the course Advanced Econometrics I (E703). The topics roughly align with appendices B, C, and D of the book Econometric Analysis by William H. Greene (2008, 6th ed.), for example: random variables, expectations, probability distributions, random sampling, point estimators, confidence intervals, hypothesis testing, large sample distribution theory. 


Background reading material: 

  • Greene, W. H., Econometric Analysis. Upper Saddle River: Pearson Prentice Hall, 2008. 
  • Introduction to Econometrics by Stock and Watson (2007, 2nd ed.), chapters 2 and 3. 
  • Introduction to Probability Models by Ross (2000, 2nd ed.), chapters 2.1-2.5, 2.7, and 3.1-3.4
  • http://theanalysisofdata.com/probability/0_1.html

Please note that the Statistics Refresher course will cover integrals and most of the basic statistics you’ll need in Advanced Econometrics I. These topics won’t be covered again in Advanced Econometrics I. Hence you are advised to attend the Statistics Refresher course, if you have some doubts about your knowledge regarding the above mentioned topics.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
07.09.18
21.09.18
Friday
10:15
18:45
O 226/228

Lecturer(s)


Course Type: elective course

Course Number: ACC 905

Credits: 8

Course Content

Based on an overview of current trends in empirical accounting research, the publication process, and typical project workflows, the course introduces relevant data sources and gives an introduction to empirical research using the statistical software STATA. The core part of the course consists of a group assignment that requires the replication of a high quality research paper in accounting, finance or tax research.

Learning outcomes: Know how to plan an empirical project in our field of research, how to execute an empirical analysis in STATA and learn the basics about selecting an appropriate outlet and getting through the publication process. The course is designed to prepare students to efficiently execute their own empirical research ideas in our field going forward.

Form of assessment: Oral exam (30 minutes), 25 %, Presentation 75 %



Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.09.18
03.12.18
Monday
13:45
17:00
O 326/28

Lecturer(s)


Course Type: elective course

Course Number: ACC 906

Credits: 8

Prerequisites

ACC 802

Recommended: Agency-theory, Decision theory and Game theory


Course Content

Selected accounting issues presented in a seminar-like form.

Learning outcomes: Students develop and present their own model dealing with a recent accounting or auditing issue.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
04.09.18
04.12.18
Tuesday
10:15
11:45
O 255


Course Type: elective course

Course Number: ACC 918

Credits: 8

Course Content

This course is aimed at doctoral students in accounting and neighboring fields including economics, finance and operations management. The course seeks to provide an introduction to the role of accounting information in (a) measuring cost and profitability, (b) accounting-based managerial performance measures, (c) cost allocation and internal pricing in multi-divisional firms and (d) financial ratios and firm value.
 
The main topics covered in this course include:
 
1.         Measures of Product Cost and Relevant Costs
2.         Measures of Profitability
3.         Managerial Performance Evaluation
4.         Internal Pricing
5.         Accounting-based Equity Valuation and Financial Ratios
 
The primary objective of the course is to introduce students to current research paradigms on these topics and to identify promising avenues for future research. The course readings include recent theoretical and empirical papers.

 

Learning outcomes: Understand the lecture materials and readings assigned as part of this course.

Form of assessment: Written exam (180 Min., open books and open notes exam): 40%, oral participation: 30%, case study: 30%

 

Please note:

On October 25 the course will take place in room O 326/328


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
27.09.18
06.12.18
Thursday
15:30
17:00
O 254

Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Course Content

The course is designed to offer an advanced treatment to econometric theory and applications. Topics covered include: Repetition of ordinary least squares and generalized least squares, instrumental variables estimation, simultaneous equations, generalized method of moments and maximum likelihood estimation, time series and panel data econometrics. Attendance in the lectures and exercise sessions are mandatory. Attempting exercise questions ahead of each session and taking active part during the course of the sessions is essential.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
02.10.18
04.12.18
Tuesday
10:15
11:45
SN 169
11.10.18
06.12.18
Thursday
10:15
11:45
O 135
Tutorial
10.10.18
05.12.18
Wednesday
12:00
13:30
L7, 3-5, room 257
12.10.18
07.12.18
Friday
13:45
15:15
L9, 1-2, room 009

Lecturer(s)


Course Type: core course

Course Number: E700

Credits: 6

Prerequisites

Basic mathematical knowledge


Course Content

The course consists of four chapters:

  • Chapter 1: basic mathematical concepts like sets, functions and relations are introduced and discussed. Strict mathematical reasoning is explained and applied.
  • Chapter 2: covers the concept of metric and normed spaces and discusses the convergence of sequences in these spaces, the continuity of functions, and the concept of compact sets.
  • Chapter 3: deal with vector spaces. matrix algebra, linear transformation, and eigenvalues of matrices.
  • Chapter 4: covers a multivariate concept of differentiability and its application in solving unconstraint and constrained optimization problems.

Requirements for the assignment of ECTS Credits and Grades

Exam (120 min)

The exam takes place on October 4, 2018, 08:30-10:30


Competences acquired

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 2+3

Claudio Kretz (CDSE)

 

Exercise Group 4+5

Can Çelebi (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.09.18
24.09.18
Monday
10:15
11:45
A5, 6, C015
04.09.18
25.09.18
Tuesday
10:15
11:45
A5, 6, C014
05.09.18
26.09.18
Wednesday
10:15
11:45
A5, 6, C013
06.09.18
27.09.18
Thursday
10:15
11:45
209 in B6, 30-32
written exam
04.10.18
Thursday
08:30
10:30
L7, 3-5, 001
Tutorial
Group 2
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A303
Group 3
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A302
Group 4
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A301
Group 5
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A301
Group 2
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A302
Group 3
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A302
Group 4
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A301
Group 5
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A301
Group 2
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A302
Group 3
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A302
Group 4
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A303
Group 5
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A301
Group 2
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A302
Group 3
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A301
Group 4
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A303
Group 5
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A303

Lecturer(s)


Course Type: core course

Course Number: E701

Credits: 8

Prerequisites

E700


Course Content

The course gives a foundation for studies for microeconomics at the PhD level. The first part is devoted to consumer and producer theory. It is organized as follows:

 

1. Choice, preference and utility

2. Structural properties of preferences and utility functions

3. Basics of consumer demand

4. Expenditure minimization

5. Classical demand theory

6. Competitive and profit-maximizing firms

7. Consumer and producer surplus

8. Choice under uncertainty

9. Utility for money

 

The second part covers game theory and is organized as follows:

10. Static games of complete information: Rationalizability and iterated strict dominance

11. Static games of complete information: Nash equilibrium

12. Static games of incomplete information

13. Dynamic games: The extensive form

14. Dynamic games: Equilibrium concepts

 

Requirements for the assignment of ECTS-Credits and Grades

  • Written exam: 120 min (90% weighting)
  • Exercises (10% weighting)

 

Literature

Recommended textbooks:

  • Fudenberg, D & Tirole, J. (1991). Game Theory. MIT Press
  • Kreps, D. (2012). Microeconomic Foundation 1: Choice and Competitive Markets. Princeton University Press.
  • Mas- Colell, A. Whinston, M.D. & Green, J. (1995). Microeconomic Theory. Oxford University Press.
  • Osborne M. and Rubinstein, A. (1994): A Course in Game Theory. MIT Press

 



Competences acquired

Students learn the basic tools for graduate level microeconomic analysis. The concepts learned in the course serve as building blocks for more advanced topics such as the ones studied in Advanced Microeconomics 2 and 3 and also for macroeconomics and empirical studies. Students also learn using rigorous formal proofs for microeconomic questions.

 

Teaching Assistant

Can Çelebi


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
08.10.18
03.12.18
Monday
10:15
11:45
L7, 3-5, 001
10.10.18
05.12.18
Wednesday
10:15
11:45
L7, 3-5, 001
Written Exam
14.12.18
Friday
08:30
10:30
L7, 3-5, 001
Retake
28.01.19
Monday
10:15
12:15
B6, 30-32, 212
Tutorial
08.10.18
03.12.18
Monday
08:30
10:00
B6, 30-32, 211
09.10.18
04.12.18
Tuesday
08:30
10:00
B6, 30-32, 211

Lecturer(s)


Course Type: core course

Course Number: FIN 801

Credits: 8

Prerequisites

E 700


Course Content

The aim of this course is to provide students with the foundations of financial economics in a rigorous way. The course contains a lecture component with advanced exercise sessions and a seminar component where students are asked to prepare a term paper on one of the topics covered in class. We start by discussing several key concepts from the theory of choice (also known as utility theory), including the axioms of expected utility, risk aversion and stochastic dominance. We then move to the portfolio theory and capital market equilibrium (CAPM and APT). The focus of the course is on the consumption-based approach to asset pricing. We introduce concepts such as the stochastic discount factor (or pricing kernel), contingent claims and risk-neutral valuation, and consider the beta representation framework and examples of factor pricing models. We study single- and multi-period models and look eventually at the role of information for asset pricing.

Form of Assessment: Written Exam (90 minutes) 60%, Class Participation (incl. term paper) 40%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.09.18
05.11.18
Monday
17:00
18:30
L9, 1-2, room 409
21.09.18
09.11.18
Friday
10:15
11:45
SO 133
16.11.18
Friday
08:00
15:00
L9, 1-2, room 409

Lecturer(s)


Course Type: core course

Course Number: FIN 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.


Lecturer(s)


Course Type: elective course

Course Content

This course aims to provide a working knowledge of basic probability theory and inductive statistics. The course is especially recommended for students wanting to refresh the skills required to attend the course Advanced Econometrics I (E703). The topics roughly align with appendices B, C, and D of the book Econometric Analysis by William H. Greene (2008, 6th ed.), for example: random variables, expectations, probability distributions, random sampling, point estimators, confidence intervals, hypothesis testing, large sample distribution theory. 


Background reading material: 

  • Greene, W. H., Econometric Analysis. Upper Saddle River: Pearson Prentice Hall, 2008. 
  • Introduction to Econometrics by Stock and Watson (2007, 2nd ed.), chapters 2 and 3. 
  • Introduction to Probability Models by Ross (2000, 2nd ed.), chapters 2.1-2.5, 2.7, and 3.1-3.4
  • http://theanalysisofdata.com/probability/0_1.html

Please note that the Statistics Refresher course will cover integrals and most of the basic statistics you’ll need in Advanced Econometrics I. These topics won’t be covered again in Advanced Econometrics I. Hence you are advised to attend the Statistics Refresher course, if you have some doubts about your knowledge regarding the above mentioned topics.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
07.09.18
21.09.18
Friday
10:15
18:45
O 226/228

Lecturer(s)


Course Type: core course

Course Number: IS 801

Credits: 8

Course Content

Since the 90’s information and communication technology (ICT) has fundamentally changed the way organizations are conducting business. Organizations and the entire society are challenged with the effective design, delivery, use, and impact of ICT. The IS discipline addresses this challenge and investigates the phenomena that emerge when the technological and the social system interact. A decade ago, an intensive discussion on the relevancy and impact of IS research has started. In this context, several scholars have suggested that the IS community returns to an exploration of the "IT" that underlies the discipline. Design research has potentials to address this challenge. As such, it is nothing new: Design can be found in many disciplines and fields, notably Engineering and Computer Science, using a variety of approaches, methods, and techniques.

This course intends to provide a comprehensive overview on design science in IS research from different perspectives: basic definitions, principles and theoretical foundations, frameworks and methodologies, theory building, as well as design science research examples published in top journals.

Learning outcomes: PhD students are introduced to the exciting field of design science research. They understand the basic principles for successfully carrying out design science research.

Form of assessment: Assignment, Presentation, Discussion


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick Off
18.09.18
Tuesday
12:00
13:30
L15, 1-6, room 411/412

Lecturer(s)


Course Type: core course

Course Number: IS 901

Credits: 8

Course Content

This course is designed for doctoral students in information systems and other managerial disciplines. It provides a basic understanding of philosophy of science and its epistemological foundations. On the one hand, the course will focus on those concepts which derive knowledge from observation, induction, and refutation of facts. Furthermore, it also takes experiments as well as the new experimentalism into account in order to refer to those disciplines that focus on the evaluation of artifacts like prototypes and algorithms for example. Thus, the underlying epistemological foundations are of central interest to every doctoral student who studies the structure and behavior of information systems and operations/logistics phenomena. The course will be offered in an interactive style. All doctoral students have to offer at least one presentation and a documentation regarding a specific epistemological stance. Assignment of topics will be conducted by the lecturer.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
14.09.18
Friday
13:45
17:00
L 15, 1-6, room 715
19.10.18
Friday
13:45
17:00
L 15, 1-6, room 715
26.10.18
Friday
13:45
17:00
L 15, 1-6, room 715
09.11.18
Friday
13:45
17:00
L 15, 1-6, room 715
16.11.18
Friday
13:45
17:00
L 15, 1-6, room 715
23.11.18
Friday
13:45
17:00
L 15, 1-6, room 715
30.11.18
Friday
13:45
17:00
L 15, 1-6, room 715


Course Type: core course

Course Number: IS/OPM 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.



Course Type: elective course

Course Number: IE 710

Course Content

This course has been replaced by the course Computional Text Analysis.

Please register for the above mentioned course.


Lecturer(s)


Course Type: elective course

Course Number: MET

Credits: 6 + 4

Course Content

The course offers an overview and several hands-on experiences on some of the most relevant methods and tools developed in the field of natural language processing, which have been often adopted as basis for quantitative content analyses in social science research. Attention is dedicated to tasks such as collection building, topic modeling, sentiment analysis, text classification, clustering and scaling as well as to the application of methods such as latent Dirichlet allocations, word embeddings and entity linking. A brief introduction to practices such as web scraping and text pre-processing (e.g. tokenisation, part-of-speech tagging, lemmatisation and stemming) is also offered.


The programming language adopted is Python (and in particular the use of Jupyter Notebooks). No previous programming experience is needed.

Further information is available on Federico's web page.

A maximum of 10 ECTS can be obtained for the successful completion of this course. 

6 ECTS written exam
4 ECTS coding exercise

 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
not on 3, 24 and 31 October
05.09.18
05.12.18
Wednesday
10:15
11:45
C 108 Methods lab in A5, 6 entrance C
01.10.18
Monday
10:15
11:45
209 in B6, 30-32
17.10.18
Wednesday
15:30
17:00
EO 162 CIP-Pool
07.11.18
Wednesday
15:30
17:00
EO 162 CIP-Pool

Lecturer(s)


Course Type: core course

Course Number: MAN 802

Credits: 6

Course Content

The course aims to provide the basic understanding of the institutions belonging to the nonprofit sector. Furthermore, the course addresses the relevant economic and managerial theories in order to be able to analyze the specific managerial problems of nonprofit organizations (NPOs).

Topics that may be touched include "History and Scope of the Nonprofit Sector", "Nonprofits and the Marketplace", "Nonprofits and the Polity", "Key Activities in the Nonprofit Sector", and "Mission and Governance".

Learning outcomes: This course aims to provide a basic understanding of the theory and management of nonprofit organizations. Each student will be asked to read a basic scientific (“classical”) paper, enrich this paper by adding latest research results from currently published journal papers, and present the findings in class, where the results will be discussed.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-Off
10.09.18
Monday
14:30
16:30
L 5, 4, room 207-209
Q&A-session
15.10.18
Monday
15:00
16:30
L 5, 4, room 207/209
Presentation day
12.11.18
Monday
09:00
17:30
L 5, 4, room 207/209
Presentation day
19.11.18
Monday
09:00
17:30
L 5, 4, room 207/209

Lecturer(s)


Course Type: core course

Course Number: MAN 805

Credits: 6

Course Content

This module offers an overview of the statistical procedures and methods that are relevant in management research. After having gained a broad understanding of the methods that are important in the respective literatures, students integrate this knowledge by examining some exemplary research studies for each method and by asking how they would go about in conducting their own research in this field. Students apply their knowledge from the seminar presentations in several exercises.

In particular, the course covers the following topics:

  • Moderation and Mediation
  • Control Variables
  • Scales and scale analysis
  • Common Method Variance
  • Hypothesis testing
  • Outliers
  • Multicollinearity
  • Missing data
  • Multilevel modelling

Learning outcomes: By the end of the module students will be able to:

  • Identify issues and problems in quantitative management research
  • Perform statistical analyses in selected areas (e.g., multilevel modeling and scale analysis)
  • Design quantitative research projects that consider contemporary standards and suggestions in management research
  • Learn how to address methodological issues in research papers

Form of assessment: Oral exam, Presentation


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
09.11.18
23.11.18
Friday
09:00
17:00
O 326/28

Lecturer(s)


Course Type: core course

Course Number: MAN 806

Credits: 6

Course Content

Students will gain an overview of fundamental topics in the fields of organization and innovation. The course starts with a kick-off. A list of required readings and a detailed course program will be provided at this meeting. Then, students have one month to prepare their input for the blocked seminar. During the blocked seminar, the papers, they will have read and prepared, will be presented and discussed. Afterwards there will be a general discussion. Besides the content itself, conceptual framing and methodology (strengths and weaknesses) will be reviewed. The papers selected for presentation will cover different quantitative and qualitative methods.

Students will learn to critically assess existing literature, to formulate research questions, to frame theoretical contributions and to design and implement a research design to be able to derive causal results.

Form of Assessment: Presentation 50%, Discussion 50%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-off
18.09.18
Tuesday
14:00
17:00
L 9, 1-2, room 210
Presentations 1
23.10.18
Tuesday
09:00
18:00
Presentations 2
30.10.18
Tuesday
09:00
18:00
L 9, 1-2, room 210

Lecturer(s)


Course Type: core course

Course Number: MAN 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.


Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Course Content

The course is designed to offer an advanced treatment to econometric theory and applications. Topics covered include: Repetition of ordinary least squares and generalized least squares, instrumental variables estimation, simultaneous equations, generalized method of moments and maximum likelihood estimation, time series and panel data econometrics. Attendance in the lectures and exercise sessions are mandatory. Attempting exercise questions ahead of each session and taking active part during the course of the sessions is essential.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
02.10.18
04.12.18
Tuesday
10:15
11:45
SN 169
11.10.18
06.12.18
Thursday
10:15
11:45
O 135
Tutorial
10.10.18
05.12.18
Wednesday
12:00
13:30
L7, 3-5, room 257
12.10.18
07.12.18
Friday
13:45
15:15
L9, 1-2, room 009

Lecturer(s)


Course Type: core course

Course Number: MKT 801

Credits: 6

Course Content

The primary objective of this course is to gain a detailed understanding and practical working knowledge of research design and methodology fundamentals in marketing. This understanding requires a fluency in the terminology of research, as well as an appreciation of basic research techniques and concepts drawn from such diverse fields as psychology and statistics. Secondary objectives include stimulating research creativity and critical thinking in the realm of research design and methodology, and introducing and integrating a wide variety of research techniques relating to design and methodology issues.

In this course, a diversity of instructional approaches (e.g., lecture, in-depth analysis and discussion of assigned articles, student presentations, a term paper, an examination) will be used. The emphasis will be on the practical application of research in furthering marketing knowledge.

By the end of the course, students should be able to use fundamental research concepts gained in the course in designing and evaluating research in marketing.


Form of assessment: Paper 30%, Presentation 70%

 

Please note: The course does not take place on October 26, 2018


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
07.09.18
07.12.18
Friday
10:15
11:45
L9, 1-2, room 009

Lecturer(s)


Course Type: core course

Course Number: MKT 903

Credits: 6

Course Content

The goal of the course is to provide Ph.D. students an introduction in and overview of state-of-the-art discrete choice methods in business and marketing research. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. The course will also cover procedures for endogeneity and expectation-maximization algorithms. Participants will study a variety of articles and case studies which demonstrate the application of such models to real business phenomena.

The lectures on "Advanced Business Econometrics" cover the following topics:

  • Properties of Discrete Choice Model
  • Logit Model
  • Numerical Maximization
  • Nested Logit
  • Probit Model
  • Mixed Logit
  • Conditional Distributions of Individual-level Parameters
  • Endogeneity: BLP, Control functions, Latent Instruments

 

Form of assessment: Written Exam (60 minutes) 50%, Home Assignments 50%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
15.10.18
Monday
09:30
18:00
L5, 1, room 009
26.10.18
Friday
09:30
18:00
L5, 1, room 009
29.10.18
Monday
09:30
18:00
L5, 1, room 009
26.11.18
Monday
09:30
18:00
L5, 1, room 009

Lecturer(s)


Course Type: core course

Course Number: MKT 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.


Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Course Content

The course is designed to offer an advanced treatment to econometric theory and applications. Topics covered include: Repetition of ordinary least squares and generalized least squares, instrumental variables estimation, simultaneous equations, generalized method of moments and maximum likelihood estimation, time series and panel data econometrics. Attendance in the lectures and exercise sessions are mandatory. Attempting exercise questions ahead of each session and taking active part during the course of the sessions is essential.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
02.10.18
04.12.18
Tuesday
10:15
11:45
SN 169
11.10.18
06.12.18
Thursday
10:15
11:45
O 135
Tutorial
10.10.18
05.12.18
Wednesday
12:00
13:30
L7, 3-5, room 257
12.10.18
07.12.18
Friday
13:45
15:15
L9, 1-2, room 009

Lecturer(s)


Course Type: core course

Course Number: E700

Credits: 6

Prerequisites

Basic mathematical knowledge


Course Content

The course consists of four chapters:

  • Chapter 1: basic mathematical concepts like sets, functions and relations are introduced and discussed. Strict mathematical reasoning is explained and applied.
  • Chapter 2: covers the concept of metric and normed spaces and discusses the convergence of sequences in these spaces, the continuity of functions, and the concept of compact sets.
  • Chapter 3: deal with vector spaces. matrix algebra, linear transformation, and eigenvalues of matrices.
  • Chapter 4: covers a multivariate concept of differentiability and its application in solving unconstraint and constrained optimization problems.

Requirements for the assignment of ECTS Credits and Grades

Exam (120 min)

The exam takes place on October 4, 2018, 08:30-10:30


Competences acquired

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 2+3

Claudio Kretz (CDSE)

 

Exercise Group 4+5

Can Çelebi (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.09.18
24.09.18
Monday
10:15
11:45
A5, 6, C015
04.09.18
25.09.18
Tuesday
10:15
11:45
A5, 6, C014
05.09.18
26.09.18
Wednesday
10:15
11:45
A5, 6, C013
06.09.18
27.09.18
Thursday
10:15
11:45
209 in B6, 30-32
written exam
04.10.18
Thursday
08:30
10:30
L7, 3-5, 001
Tutorial
Group 2
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A303
Group 3
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A302
Group 4
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A301
Group 5
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A301
Group 2
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A302
Group 3
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A302
Group 4
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A301
Group 5
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A301
Group 2
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A302
Group 3
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A302
Group 4
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A303
Group 5
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A301
Group 2
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A302
Group 3
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A301
Group 4
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A303
Group 5
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A303

Lecturer(s)


Course Type: core course

Course Number: E701

Credits: 8

Prerequisites

E700


Course Content

The course gives a foundation for studies for microeconomics at the PhD level. The first part is devoted to consumer and producer theory. It is organized as follows:

 

1. Choice, preference and utility

2. Structural properties of preferences and utility functions

3. Basics of consumer demand

4. Expenditure minimization

5. Classical demand theory

6. Competitive and profit-maximizing firms

7. Consumer and producer surplus

8. Choice under uncertainty

9. Utility for money

 

The second part covers game theory and is organized as follows:

10. Static games of complete information: Rationalizability and iterated strict dominance

11. Static games of complete information: Nash equilibrium

12. Static games of incomplete information

13. Dynamic games: The extensive form

14. Dynamic games: Equilibrium concepts

 

Requirements for the assignment of ECTS-Credits and Grades

  • Written exam: 120 min (90% weighting)
  • Exercises (10% weighting)

 

Literature

Recommended textbooks:

  • Fudenberg, D & Tirole, J. (1991). Game Theory. MIT Press
  • Kreps, D. (2012). Microeconomic Foundation 1: Choice and Competitive Markets. Princeton University Press.
  • Mas- Colell, A. Whinston, M.D. & Green, J. (1995). Microeconomic Theory. Oxford University Press.
  • Osborne M. and Rubinstein, A. (1994): A Course in Game Theory. MIT Press

 



Competences acquired

Students learn the basic tools for graduate level microeconomic analysis. The concepts learned in the course serve as building blocks for more advanced topics such as the ones studied in Advanced Microeconomics 2 and 3 and also for macroeconomics and empirical studies. Students also learn using rigorous formal proofs for microeconomic questions.

 

Teaching Assistant

Can Çelebi


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
08.10.18
03.12.18
Monday
10:15
11:45
L7, 3-5, 001
10.10.18
05.12.18
Wednesday
10:15
11:45
L7, 3-5, 001
Written Exam
14.12.18
Friday
08:30
10:30
L7, 3-5, 001
Retake
28.01.19
Monday
10:15
12:15
B6, 30-32, 212
Tutorial
08.10.18
03.12.18
Monday
08:30
10:00
B6, 30-32, 211
09.10.18
04.12.18
Tuesday
08:30
10:00
B6, 30-32, 211


Course Type: core course

Course Number: IS/OPM 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.



Course Type: core course

Course Number: OPM 805

Credits: 8

Course Content

The goal of this seminar is to introduce the participants to the conducting of scientific research. It thereby prepares them for the writing of their dissertation proposal. Participants will carry out a literature study on a given topic in the domain of business analytics and discuss the results in a written report and in an oral presentation.

Learning outcomes: Students will learn how to analyze the academic literature on a given topic. They will become acquainted with the setup and composition of academic publications. They will also learn how to the present the results of their analysis.

Form of assessment: Paper 70 %, Presentation 30 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-Off
10.09.18
Monday
10:15
11:45
SO 322


Course Type: core course

Course Number: OPM 901

Credits: 8

Course Content

This course aims at PhD students in business administration. The course is taught in a seminar-style format.  Students present their own research and discuss the presentations of other students. Students are introduced in writing referee reports to (drafts of) papers. Allocation of topics will be done together in class.

Learning outcomes: Students will learn how to present and discuss their own research ideas and results. They will become acquainted with acting as discussant for other topics. Additionally, they will learn how to write a referee report.

Form of assessment: Presentation, Assignment


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.09.18
06.12.18
Thursday
12:00
13:30
SO 318

Lecturer(s)


Course Type: elective course

Course Number: OPM 801

Credits: 8

Prerequisites

Recommended: Fundamentals in mathematics (including Linear Programming), knowledge of GAMS modelling language


Course Content

This course aims at Ph.D. students in information systems, business administration, and computer science. It provides a basic understanding of linear and mixed-integer optimization models and solution methods. The course is partly taught in a seminar-style format. Allocation of topics will be done together in the class.

Learning outcomes: The course aims to introduce the students to fundamental linear and combinatorial optimization problems. They learn to formulate optimization models as mixed-integer linear programs, how to solve them with standard software, and how to construct heuristic solution algorithms. The students learn to deal with the complexity of real-world problems via aggregation, relaxation, and decomposition techniques.

Form of assessment: Assignment, Presentation, Class Participation


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.10.18
05.12.18
Wednesday
15:30
18:45
SO 322

Lecturer(s)


Course Type: elective course

Course Number: OPM 803

Credits: 8

Prerequisites

Recommended: Fundamentals in mathematics (including linear programming)


Course Content

Many optimization problems in practice are nonlinear. This course introduces PhD students of information systems, business administration, and computer science to the fundamentals of nonlinear optimization theory and solution methods. The course is partly taught in a seminar-style format. Topics will be assigned in class based on student preferences and needs with regard to their thesis.

Learning outcomes: Students will get a fundamental understanding of problems, theory and solution methods in nonlinear optimization. This includes to learn how to formulate a nonlinear optimization problem mathematically, how to analyze its structure to detect e.g. convexities, how to implement and solve a problem with state-of-the-art modeling environments and solvers. Students can bring in and work on their own problems of interest, e.g. a specific one that they might face in their thesis or an actual standard problem often encountered in practice.

Form of assessment: Assignment, Presentation, Class Participation


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
12.10.18
07.12.18
Friday
10:15
13:30
SO 322


Course Type: core course

Course Number: ACC/TAX 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. For each presentation, a separate preparation session for the Ph.D. students is offered in advance by rotating faculty. Overall, the course deepens the students’ insights into a variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Seminar Dates are announced here.



Course Type: core course

Course Number: ACC/TAX 920

Course Content

The course is taught in a seminar-style format. Students present their own research ideas at different stages of the project (early ideas, preliminary results, and complete working papers). The presentations involve an interactive discussion between faculty and students about the project’s potential contribution, related literature, research design and interpretation of results.

Learning outcomes: Students will learn how to present and discuss their own research results in a scientific format. They will become acquainted with acting as a discussant for other topics. Students will gain insights into the assessment of contribution, research design, and interpretation of research papers. The development of these skills is also helpful for writing scientific referee reports.


Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Course Content

The course is designed to offer an advanced treatment to econometric theory and applications. Topics covered include: Repetition of ordinary least squares and generalized least squares, instrumental variables estimation, simultaneous equations, generalized method of moments and maximum likelihood estimation, time series and panel data econometrics. Attendance in the lectures and exercise sessions are mandatory. Attempting exercise questions ahead of each session and taking active part during the course of the sessions is essential.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
02.10.18
04.12.18
Tuesday
10:15
11:45
SN 169
11.10.18
06.12.18
Thursday
10:15
11:45
O 135
Tutorial
10.10.18
05.12.18
Wednesday
12:00
13:30
L7, 3-5, room 257
12.10.18
07.12.18
Friday
13:45
15:15
L9, 1-2, room 009

Lecturer(s)


Course Type: core course

Course Number: E700

Credits: 6

Prerequisites

Basic mathematical knowledge


Course Content

The course consists of four chapters:

  • Chapter 1: basic mathematical concepts like sets, functions and relations are introduced and discussed. Strict mathematical reasoning is explained and applied.
  • Chapter 2: covers the concept of metric and normed spaces and discusses the convergence of sequences in these spaces, the continuity of functions, and the concept of compact sets.
  • Chapter 3: deal with vector spaces. matrix algebra, linear transformation, and eigenvalues of matrices.
  • Chapter 4: covers a multivariate concept of differentiability and its application in solving unconstraint and constrained optimization problems.

Requirements for the assignment of ECTS Credits and Grades

Exam (120 min)

The exam takes place on October 4, 2018, 08:30-10:30


Competences acquired

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 2+3

Claudio Kretz (CDSE)

 

Exercise Group 4+5

Can Çelebi (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.09.18
24.09.18
Monday
10:15
11:45
A5, 6, C015
04.09.18
25.09.18
Tuesday
10:15
11:45
A5, 6, C014
05.09.18
26.09.18
Wednesday
10:15
11:45
A5, 6, C013
06.09.18
27.09.18
Thursday
10:15
11:45
209 in B6, 30-32
written exam
04.10.18
Thursday
08:30
10:30
L7, 3-5, 001
Tutorial
Group 2
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A303
Group 3
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A302
Group 4
03.09.18
24.09.18
Monday
13:45
15:15
B6, 23-25, A301
Group 5
03.09.18
24.09.18
Monday
15:30
17:00
B6, 23-25, A301
Group 2
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A302
Group 3
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A302
Group 4
04.09.18
25.09.18
Tuesday
13:45
15:15
B6, 23-25, A301
Group 5
04.09.18
25.09.18
Tuesday
15:30
17:00
B6, 23-25, A301
Group 2
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A302
Group 3
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A302
Group 4
05.09.18
26.09.18
Wednesday
13:45
15:15
B6, 23-25, A303
Group 5
05.09.18
26.09.18
Wednesday
15:30
17:00
B6, 23-25, A301
Group 2
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A302
Group 3
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A301
Group 4
06.09.18
27.09.18
Thursday
13:45
15:15
B6, 23-25, A303
Group 5
06.09.18
27.09.18
Thursday
15:30
17:00
B6, 23-25, A303

Lecturer(s)


Course Type: core course

Course Number: E701

Credits: 8

Prerequisites

E700


Course Content

The course gives a foundation for studies for microeconomics at the PhD level. The first part is devoted to consumer and producer theory. It is organized as follows:

 

1. Choice, preference and utility

2. Structural properties of preferences and utility functions

3. Basics of consumer demand

4. Expenditure minimization

5. Classical demand theory

6. Competitive and profit-maximizing firms

7. Consumer and producer surplus

8. Choice under uncertainty

9. Utility for money

 

The second part covers game theory and is organized as follows:

10. Static games of complete information: Rationalizability and iterated strict dominance

11. Static games of complete information: Nash equilibrium

12. Static games of incomplete information

13. Dynamic games: The extensive form

14. Dynamic games: Equilibrium concepts

 

Requirements for the assignment of ECTS-Credits and Grades

  • Written exam: 120 min (90% weighting)
  • Exercises (10% weighting)

 

Literature

Recommended textbooks:

  • Fudenberg, D & Tirole, J. (1991). Game Theory. MIT Press
  • Kreps, D. (2012). Microeconomic Foundation 1: Choice and Competitive Markets. Princeton University Press.
  • Mas- Colell, A. Whinston, M.D. & Green, J. (1995). Microeconomic Theory. Oxford University Press.
  • Osborne M. and Rubinstein, A. (1994): A Course in Game Theory. MIT Press

 



Competences acquired

Students learn the basic tools for graduate level microeconomic analysis. The concepts learned in the course serve as building blocks for more advanced topics such as the ones studied in Advanced Microeconomics 2 and 3 and also for macroeconomics and empirical studies. Students also learn using rigorous formal proofs for microeconomic questions.

 

Teaching Assistant

Can Çelebi


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
08.10.18
03.12.18
Monday
10:15
11:45
L7, 3-5, 001
10.10.18
05.12.18
Wednesday
10:15
11:45
L7, 3-5, 001
Written Exam
14.12.18
Friday
08:30
10:30
L7, 3-5, 001
Retake
28.01.19
Monday
10:15
12:15
B6, 30-32, 212
Tutorial
08.10.18
03.12.18
Monday
08:30
10:00
B6, 30-32, 211
09.10.18
04.12.18
Tuesday
08:30
10:00
B6, 30-32, 211

Lecturer(s)


Course Type: core course

Course Number: E702

Credits: 8

Prerequisites

E700


Course Content

This course provides an introduction to the foundations of modern macroeconomic analysis. The main object of this course is 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.

Grading and ECTS Credits

  • Problem sets (15 %)
  • Midterm exam (90 min, 35 %)
  • Final exam (120 min, 50 %)

Literature/Textbooks

Stokey, Nancy, and Robert Lucas with Edward Prescott (1989): Recursive Methods in Economic Dynamics. Harvard University Press.

Ljungqvist, Lars, and Thomas J. Sargent. (2012) Recursive macroeconomic theory. MIT press.

Acemoglu, Daron (2009): Introduction to Modern Economic Growth, Princeton University Press.


    Competences acquired

    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.

    Contact information

    Prof. Minchul Yum, Ph.D. (0621) 181-1853; myum(at)mail.uni-mannheim.de; L7, 3-5, P09; Tue 3-5 pm

    Teaching Assistant

    Timo Reinelt


    Schedule

    Type
    From
    To
    Weekday
    From
    To
    Room
    Material
    Lecture
    08.10.18
    03.12.18
    Monday
    15:30
    17:00
    L7, 3-5, S031
    09.10.18
    04.12.18
    Tuesday
    15:30
    17:00
    L7, 3-5, S031
    Written Exam
    19.12.18
    Wednesday
    13:00
    15:00
    L7, 3-5, 001
    Retake
    22.01.19
    Tuesday
    10:15
    12:15
    B6, 30-32, 211
    Tutorial
    10.10.18
    05.12.18
    Wednesday
    08:30
    10:00
    B6, 30-32, 209
    11.10.18
    06.12.18
    Thursday
    08:30
    10:00
    B6, 30-32, 209

    Lecturer(s)


    Course Type: core course

    Course Number: FIN 801

    Credits: 8

    Prerequisites

    E 700


    Course Content

    The aim of this course is to provide students with the foundations of financial economics in a rigorous way. The course contains a lecture component with advanced exercise sessions and a seminar component where students are asked to prepare a term paper on one of the topics covered in class. We start by discussing several key concepts from the theory of choice (also known as utility theory), including the axioms of expected utility, risk aversion and stochastic dominance. We then move to the portfolio theory and capital market equilibrium (CAPM and APT). The focus of the course is on the consumption-based approach to asset pricing. We introduce concepts such as the stochastic discount factor (or pricing kernel), contingent claims and risk-neutral valuation, and consider the beta representation framework and examples of factor pricing models. We study single- and multi-period models and look eventually at the role of information for asset pricing.

    Form of Assessment: Written Exam (90 minutes) 60%, Class Participation (incl. term paper) 40%


    Schedule

    Type
    From
    To
    Weekday
    From
    To
    Room
    Material
    Lecture
    03.09.18
    05.11.18
    Monday
    17:00
    18:30
    L9, 1-2, room 409
    21.09.18
    09.11.18
    Friday
    10:15
    11:45
    SO 133
    16.11.18
    Friday
    08:00
    15:00
    L9, 1-2, room 409

    Lecturer(s)


    Course Type: elective course

    Credits: 8

    Prerequisites

    Basic understanding of EU Law and Tax Law


    Course Content

    European Union Law has an increasing impact on the taxation of private individuals as well as of companies doing business in Europe. While the European Union has no original tax authority its law has a major influence on national tax laws. 
    The course will start with an introduction into European Union Law. It will describe the nature of European Law and the European institutions. After that the course will cover the positive harmonisation of indirect taxes mainly by European directives. In a third part the course will focus on secondary law harmonising direct taxes in Europe, e.g. the Parent-Subsidiary Directive. In a last section the course deals with the importance of the fundamental freedoms for the taxation in Europe. A special focus will be put on the case law of the European Court of Justice.


    Schedule

    Type
    From
    To
    Weekday
    From
    To
    Room
    Material
    Lecture
    06.09.18
    06.12.18
    Thursday
    12:00
    13:30
    W 114 (Palace West Wing)

    Lecturer(s)


    Course Type: elective course

    Course Content

    This course aims to provide a working knowledge of basic probability theory and inductive statistics. The course is especially recommended for students wanting to refresh the skills required to attend the course Advanced Econometrics I (E703). The topics roughly align with appendices B, C, and D of the book Econometric Analysis by William H. Greene (2008, 6th ed.), for example: random variables, expectations, probability distributions, random sampling, point estimators, confidence intervals, hypothesis testing, large sample distribution theory. 


    Background reading material: 

    • Greene, W. H., Econometric Analysis. Upper Saddle River: Pearson Prentice Hall, 2008. 
    • Introduction to Econometrics by Stock and Watson (2007, 2nd ed.), chapters 2 and 3. 
    • Introduction to Probability Models by Ross (2000, 2nd ed.), chapters 2.1-2.5, 2.7, and 3.1-3.4
    • http://theanalysisofdata.com/probability/0_1.html

    Please note that the Statistics Refresher course will cover integrals and most of the basic statistics you’ll need in Advanced Econometrics I. These topics won’t be covered again in Advanced Econometrics I. Hence you are advised to attend the Statistics Refresher course, if you have some doubts about your knowledge regarding the above mentioned topics.


    Schedule

    Type
    From
    To
    Weekday
    From
    To
    Room
    Material
    Lecture
    07.09.18
    21.09.18
    Friday
    10:15
    18:45
    O 226/228

    Lecturer(s)


    Course Type: elective course

    Course Number: TAX 916

    Credits: 8

    Course Content

    The course gives an applied introduction to the methodology employed in the empirical research literature. The main topics include: Ordinary least squares, instrumental variables estimation, and panel data econometrics. Further topics may also be included according to demand by participants.

    The covered material enables students to apply the econometric methods which are commonly used in economic research. Special attention is given to the interpretation of empirical results and understanding the potential caveats of different approaches.

    Form of assessment: Oral exam (10 minutes) 50%, Class Participation 50%


    Schedule

    Type
    From
    To
    Weekday
    From
    To
    Room
    Material
    Lecture
    03.09.18
    03.12.18
    Monday
    08:30
    10:00
    O 226/228
    05.09.18
    05.12.18
    Wednesday
    08:30
    10:00

    Register

    Business Fall 2018

    ACC 902
    Normative Accounting Research
    ACC/TAX 910
    Area Seminar Accounting & Taxation
    ACC/TAX 920
    Brown Bag Seminar Accounting & Taxation
    E 703
    Advanced Econometrics I
    E700
    Mathematics for Economists
    E701
    Advanced Microeconomics I
    Statistics Refresher
    ACC 905
    Applied Methods & Tools in Empirical Accounting Research (Paper Replication)
    ACC 906
    Model Development Workshop (Model Building)
    ACC 918
    The Role of Accounting Information in Managing and Valuing Businesses 
    FIN 801
    Discrete-Time Finance
    FIN 910
    Area Seminar Finance
    IS 801
    Fundamentals of Design Science Research
    IS 901
    Epistomological Foundations
    IS/OPM 910
    Area Seminar Information Systems & Operations Management
    IE 710
    Computer-based Content Analysis
    MET
    Computational Text Analysis
    MAN 802
    Fundamentals of Non-Profit Management Science
    MAN 805
    Applied Methods in Management Research
    MAN 806
    Advances in Organization and Innovation Research
    MAN 910
    Area Seminar Management
    MKT 801
    Fundamentals of Marketing Research
    MKT 903
    Advanced Business Econometrics
    MKT 910
    Area Seminar Marketing
    OPM 805
    Research Seminar Business Analytics 
    OPM 901
    Research Seminar Operations Management & Operations Research
    OPM 801
    Optimization and Heuristics
    OPM 803
    Selected Topics in Nonlinear Optimization
    E702
    Advanced Macroeconomics I
    European Tax Law
    TAX 916
    Applied Econometrics