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 2016

Lecturer(s)


Course Type: core 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
16.09.16
Friday
10:15
18:45
O326/328
23.09.16
Friday
10:15
18:45
O326/328
30.09.16
Friday
10:15
18:45
O326/328
07.10.16
Friday
10:15
13:30
SO 115
14.10.16
Friday
10:15
13:30
SO 115
21.10.16
Friday
10:15
13:30
O226
28.10.16
Friday
10:15
13:30
SO 115

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.

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 70%, Presentation 30%    

 

Schedule

  • Kick-off: 14. September: 17:15 to 20:30, SO 133
  • Coaching-Dates: Individual
  • Presentations: 01. December: 12:00 to 17:00

 


Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Prerequisites

E700


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.

Form of Assessment: Written exam (180 minutes) 90 %, Assignment 10 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.10.16
08.12.16
Thursday
10:15
11:45
SO 133
11.10.16
06.12.16
Tuesday
10:15
11:45
L9, 1-2, 409
Tutorial
06.10.16
08.12.16
Thursday
13:45
15:15
L7, 3-5, 257
07.10.16
09.12.16
Friday
13:45
15:15
SO 133
18.11.16
Friday
13:45
15:15
L 9, 1-2 room 001

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)

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:

Daria Khromenkova (CDSE)

Ekaterina Kazakova (CDSE)

 

The exam will take place on 5 October 2016 from 17:15 to 19:15 in L7, 3-5 - 001


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
05.09.16
26.09.16
Monday
10:15
11:45
A5, C 013
06.09.16
27.09.16
Tuesday
10:15
11:45
A5, C 013
07.09.16
28.09.16
Wednesday
10:15
11:45
A5, C 013
08.09.16
29.09.16
Thursday
10:15
11:45
A5, C 014
First Exam Date:
05.10.16
Wednesday
17:15
19:15
L7, 3-5 - 001
Retake Exam Date:
18.01.17
Wednesday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 302
Exercise Group 2
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 303
Exercise Group 3
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 302
Exercise Group 4
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 303
Exercise Group 1
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 302
Exercise Group 2
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 303
Exercise Group 3
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 302
Exercise Group 4
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 303
Exercise Group 1
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 302
Exercise Group 2
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 303
Exercise Group 3
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 302
Exercise Group 4
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 303
Exercise Group 1
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 302
Exercise Group 2
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 303
Exercise Group 3
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 302
Exercise Group 4
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 303

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

 

Teaching method

Lecture (3 SWS), Exercise (1.5 SWS)

 

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:

Paolo Conteduca (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.10.16
05.12.16
Monday
10:15
11:45
L7, 3-5 - 001
12.10.16
07.12.16
Wednesday
10:15
11:45
L7, 3-5 - 001
First Exam Date:
12.12.16
Monday
10:00
12:00
L9, 1 - 004
Retake Exam Date:
20.01.17
Friday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
10.10.16
05.12.16
Monday
12:00
13:30
L7, 3-5 - P044
Exercise Group 2
10.10.16
05.12.16
Monday
13:45
15:15
L7, 3-5 - P044


Course Type: elective course

Course Number: ACC/TAX 920

Credits: 6

Course Content

This course aims at students in accounting and taxation. 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 determined in class.
Students will learn how to present and discuss their own research results. They will become acquainted with acting as discussant for other topics. Additionally, they will learn how to write a referee report.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.09.16
Tuesday
14:00
15:00
SO 133
13.09.16
27.09.16
Tuesday
12:00
13:30
SO 133
04.10.16
Tuesday
13:45
15:15
SO 133
11.10.16
08.11.16
Tuesday
12:00
13:30
SO 133
15.11.16
Tuesday
13:45
15:15
SO 133
22.11.16
29.11.16
Tuesday
12:00
13:30
SO 133
06.12.16
Tuesday
13:45
15:15
SO 133

Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Prerequisites

E700


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.

Form of Assessment: Written exam (180 minutes) 90 %, Assignment 10 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.10.16
08.12.16
Thursday
10:15
11:45
SO 133
11.10.16
06.12.16
Tuesday
10:15
11:45
L9, 1-2, 409
Tutorial
06.10.16
08.12.16
Thursday
13:45
15:15
L7, 3-5, 257
07.10.16
09.12.16
Friday
13:45
15:15
SO 133
18.11.16
Friday
13:45
15:15
L 9, 1-2 room 001

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)

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:

Daria Khromenkova (CDSE)

Ekaterina Kazakova (CDSE)

 

The exam will take place on 5 October 2016 from 17:15 to 19:15 in L7, 3-5 - 001


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
05.09.16
26.09.16
Monday
10:15
11:45
A5, C 013
06.09.16
27.09.16
Tuesday
10:15
11:45
A5, C 013
07.09.16
28.09.16
Wednesday
10:15
11:45
A5, C 013
08.09.16
29.09.16
Thursday
10:15
11:45
A5, C 014
First Exam Date:
05.10.16
Wednesday
17:15
19:15
L7, 3-5 - 001
Retake Exam Date:
18.01.17
Wednesday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 302
Exercise Group 2
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 303
Exercise Group 3
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 302
Exercise Group 4
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 303
Exercise Group 1
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 302
Exercise Group 2
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 303
Exercise Group 3
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 302
Exercise Group 4
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 303
Exercise Group 1
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 302
Exercise Group 2
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 303
Exercise Group 3
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 302
Exercise Group 4
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 303
Exercise Group 1
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 302
Exercise Group 2
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 303
Exercise Group 3
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 302
Exercise Group 4
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 303

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

 

Teaching method

Lecture (3 SWS), Exercise (1.5 SWS)

 

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:

Paolo Conteduca (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.10.16
05.12.16
Monday
10:15
11:45
L7, 3-5 - 001
12.10.16
07.12.16
Wednesday
10:15
11:45
L7, 3-5 - 001
First Exam Date:
12.12.16
Monday
10:00
12:00
L9, 1 - 004
Retake Exam Date:
20.01.17
Friday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
10.10.16
05.12.16
Monday
12:00
13:30
L7, 3-5 - P044
Exercise Group 2
10.10.16
05.12.16
Monday
13:45
15:15
L7, 3-5 - P044

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
12.09.16
07.11.16
Monday
17:00
18:30
L9, 7 - room 308
30.09.16
11.11.16
Friday
10:15
11:45
L9, 7 - room 308
21.11.16
Monday
17:00
18:30
L9, 7 - room 308
02.12.16
Friday
10:15
15:45
L9, 7 - room 308


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 Information Systems 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 Information Systems 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.

Form of Assessment: Assignment 60%, Presentation 20%, Discussion 20%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
27.09.16
Tuesday
14:00
16:00
L15, 1-6 – room 714
04.10.16
Tuesday
14:00
16:00
L15, 1-6 – room 714
11.10.16
Tuesday
13:00
15:00
L15, 1-6 – room 714

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 operations/logistics. 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. Furthermore, participants have to discuss an article from literature in order to apply and reinforce the epistemological stance presented. Assignment of topics will be conducted by the lecturer.

Learning outcomes:

  • Positivism: Deriving theories from facts
  • Anti-Positivism: Falsification, interpretativism
  • Non method-centric stances
  •  Philosophical foundations of the sciences of the artificial: mathematical and logical deduction, creating technological artifacts
  • Bridging the past and the future: Realism and Anti-realism

 

Assignments:

During the first session, topics will be assigned to participating doctoral students. Each student will be asked to elaborate a presentation with regard to the assigned topic which goes beyond the introductory literature as well as to lead the discussion regarding his/her topic. Further details will be provided in the first session.

Form of Assessment: Assignment 60%, Presentation 20%, Discussion 20%

 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
09.09.16
Friday
14:30
17:00
L15, 1-6 – room 715
14.10.16
Friday
14:30
17:00
L15, 1-6 – room 715
28.10.16
Friday
14:30
17:00
L15, 1-6 – room 715
11.11.16
Friday
14:30
17:00
L15, 1-6 – room 715
25.11.16
Friday
14:30
17:00
L15, 1-6 – room 715
09.12.16
Friday
14:30
17:00
L15, 1-6 – room 715

Lecturer(s)


Course Type: core course

Course Number: BAS

Credits: 2

Course Content

In recent decades, applications of statistics and formal modeling have become part of the main stream in the social sciences. Their contribution to our fields cannot be overestimated. However, using these methods may be cumbersome without knowledge of the fundamental math behind. This course is to provide you with some of these fundamentals, which are beneficiary to your understanding of formal methods (like game theory) and statistics during your PhD studies here in Mannheim. It is therefore highly recommended to take the course at the beginning of your PhD.

The exam is scheduled for 15 December 2016 from 9am to 11am in room A203 in B6, 23-25, entrance A, 2nd floor

Basic readings:

  • Knut Sydsaeter and Peter Hammond. 2008. Essential Mathematics for Economic Analysis. 3rd edition. Harlow: Prentice Hall


Additional readings:

  • Alpha C. Chiang and Kevin Wainwright. 2005. Fundamental Methods of Mathematical Economics. 4th edition. Boston, Mass.: McGraw-Hill
  • Jeff Gill. 2006. Essential Mathematics for Political and Social Research. Cambridge: Cambridge University Press.
  • Malcolm Pemberton and Nicholas Rau. 2007. Mathematics for Economists. 2nd edition. Manchester: Manchester University Press.
  • Carl P. Simon and Lawrence E. Blume. 1994. Mathematics for Economists. New York: W. W. Norton & Company. McGraw-Hill.

Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
07.09.16
06.12.16
Wednesday
08:30
10:00
308 in L9, 7

Lecturer(s)


Course Type: core course

Course Number: MAN 802

Credits: 6

Course Content

This course addresses the relevant economic and managerial theories in order to be able to analyze the economic behaviour and management of nonprofit organizations (NPOs).

Topics that will be discussed include “theories of nonprofit organizations”, “organizational behaviour and performance”, “nonprofit management”, “financing nonprofit organizations”, and “governance and accountability”.

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.

Form of Assessment: Presentation 60%, Discussion 20%, Class Participation 20%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
15.09.16
Thursday
10:15
12:30
L5,4 room 207/209
05.10.16
Wednesday
15:00
16:30
L5,4 room 207/209
21.11.16
Monday
09:00
12:30
L5,4 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

 

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 (20 minutes) 75%, Presentation 25%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
07.10.16
21.10.16
Friday
09:00
17:00
O 326

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
20.09.16
Tuesday
14:00
17:00
L4, 1 – room 004
24.10.16
Monday
14:00
18:30
L4, 1 – room 004
25.10.16
Tuesday
09:00
18:30
L4, 1 – room 004

Lecturer(s)


Course Type: core course

Course Number: MET

Credits: 6

Course Content

All researchers face similar challenges with core issues of research design. A research design is a plan that specifies how you are going to carry out a research project and, particularly, how to use evidence to answer your research question. The goal of this course is to jump-start students with their dissertation proposal. This course should help students to see the trade-offs involved in choosing a particular research design in their research projects. Consequently students are expected to develop own ideas about potential research questions and actively participate in those seminar-style meetings that are organized within this lecture course.


Material


Schedule

Type
From
To
Weekday
From
To
Room
Material
Workshop
06.09.16
06.12.16
Tuesday
12:00
13:30
B143 in A 5, 6 Bauteil B


Course Type: elective course

Course Number: MAN 912

Credits: 6

Course Content

The amalgamation of “family” & “business” is a phenomenon of eminent societal
& economic importance. This many-faceted phenomenon embraces the disciplines economics, business
studies, sociology, and psychology. Due to its elusive and multi-chromatic nature, research in this discipline
is fun, fascinating, but non-trivial at times.
This PhD course includes a comprehensive treatment and introduction to the intriguing scholarly domain
"Family Business Research" and its recent seminal articles. The course will discuss and reflect ideas and
concepts on how related questions, e.g. “Are family CEOs (or firms) superior performers (or innovators)?”
or “(Why) Do family firms differ in social responsibility from other firms?”, can be researched. Analytic
issues in real research projects, such as definitions & operationalization, measurement, designs, sampling,
and econometric strategies & techniques will be discussed in the format of an academic conference simulated
in class. In addition, the course will cover an introduction to the art of journal article writing (and
an introduction to specific econometric techniques if requested). Participants will jointly write family
business research articles using self-gathered or provided data with the option of subsequent submission
to a leading conference for peer-feedback.

The course consists of three components: I. Attendance & discussion, II. Student presentation, and III. Written article. Each component accounts for 33,3 % of the course grade.


Material


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
22.09.16
Thursday
17:15
18:45
L9, 1-2, room 210
04.10.16
Tuesday
08:30
11:45
L9, 1-2, room 210
11.10.16
Tuesday
08:30
11:45
L9, 1-2, room 210
18.10.16
Tuesday
08:30
11:45
L9, 1-2, room 210
08.11.16
Tuesday
10:15
11:45
L9, 1-2, room 210
06.12.16
Tuesday
08:30
11:45
L9, 1-2, room 210

Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Prerequisites

E700


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.

Form of Assessment: Written exam (180 minutes) 90 %, Assignment 10 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.10.16
08.12.16
Thursday
10:15
11:45
SO 133
11.10.16
06.12.16
Tuesday
10:15
11:45
L9, 1-2, 409
Tutorial
06.10.16
08.12.16
Thursday
13:45
15:15
L7, 3-5, 257
07.10.16
09.12.16
Friday
13:45
15:15
SO 133
18.11.16
Friday
13:45
15:15
L 9, 1-2 room 001

Lecturer(s)


Course Type: core course

Course Number: MKT 801

Credits: 6

Prerequisites

Some familiarity with marketing research and statistical analyses at the level of a master’s course is assumed.    


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%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
09.09.16
02.12.16
Friday
10:15
11:45
SO 133

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
23.09.16
Friday
09:30
18:00
10.10.16
Monday
09:30
18:00
07.11.16
Monday
08:30
18:00
25.11.16
Friday
09:30
18:00

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)

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:

Daria Khromenkova (CDSE)

Ekaterina Kazakova (CDSE)

 

The exam will take place on 5 October 2016 from 17:15 to 19:15 in L7, 3-5 - 001


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
05.09.16
26.09.16
Monday
10:15
11:45
A5, C 013
06.09.16
27.09.16
Tuesday
10:15
11:45
A5, C 013
07.09.16
28.09.16
Wednesday
10:15
11:45
A5, C 013
08.09.16
29.09.16
Thursday
10:15
11:45
A5, C 014
First Exam Date:
05.10.16
Wednesday
17:15
19:15
L7, 3-5 - 001
Retake Exam Date:
18.01.17
Wednesday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 302
Exercise Group 2
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 303
Exercise Group 3
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 302
Exercise Group 4
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 303
Exercise Group 1
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 302
Exercise Group 2
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 303
Exercise Group 3
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 302
Exercise Group 4
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 303
Exercise Group 1
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 302
Exercise Group 2
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 303
Exercise Group 3
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 302
Exercise Group 4
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 303
Exercise Group 1
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 302
Exercise Group 2
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 303
Exercise Group 3
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 302
Exercise Group 4
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 303

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

 

Teaching method

Lecture (3 SWS), Exercise (1.5 SWS)

 

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:

Paolo Conteduca (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.10.16
05.12.16
Monday
10:15
11:45
L7, 3-5 - 001
12.10.16
07.12.16
Wednesday
10:15
11:45
L7, 3-5 - 001
First Exam Date:
12.12.16
Monday
10:00
12:00
L9, 1 - 004
Retake Exam Date:
20.01.17
Friday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
10.10.16
05.12.16
Monday
12:00
13:30
L7, 3-5 - P044
Exercise Group 2
10.10.16
05.12.16
Monday
13:45
15:15
L7, 3-5 - P044

Lecturer(s)


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.

 

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
08.09.16
01.12.16
Thursday
10:15
13:30
SO 322

Lecturer(s)


Course Type: elective course

Course Number: OPM 801

Credits: 8

Prerequisites

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. 

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 50%, Presentation 40%, Class Participation 10%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
19.10.16
07.12.16
Wednesday
15:30
18:45
SO 322

Lecturer(s)


Course Type: elective course

Course Number: OPM 803

Credits: 8

Prerequisites

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.

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: Assignments 40%, Presentations 40%, Class Participation 20%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
09.09.16
09.12.16
Friday
10:15
13:30
SO 318

Lecturer(s)


Course Type: core 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
16.09.16
Friday
10:15
18:45
O326/328
23.09.16
Friday
10:15
18:45
O326/328
30.09.16
Friday
10:15
18:45
O326/328
07.10.16
Friday
10:15
13:30
SO 115
14.10.16
Friday
10:15
13:30
SO 115
21.10.16
Friday
10:15
13:30
O226
28.10.16
Friday
10:15
13:30
SO 115

Lecturer(s)


Course Type: core course

Course Number: E 703

Credits: 8

Prerequisites

E700


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.

Form of Assessment: Written exam (180 minutes) 90 %, Assignment 10 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.10.16
08.12.16
Thursday
10:15
11:45
SO 133
11.10.16
06.12.16
Tuesday
10:15
11:45
L9, 1-2, 409
Tutorial
06.10.16
08.12.16
Thursday
13:45
15:15
L7, 3-5, 257
07.10.16
09.12.16
Friday
13:45
15:15
SO 133
18.11.16
Friday
13:45
15:15
L 9, 1-2 room 001

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)

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:

Daria Khromenkova (CDSE)

Ekaterina Kazakova (CDSE)

 

The exam will take place on 5 October 2016 from 17:15 to 19:15 in L7, 3-5 - 001


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
05.09.16
26.09.16
Monday
10:15
11:45
A5, C 013
06.09.16
27.09.16
Tuesday
10:15
11:45
A5, C 013
07.09.16
28.09.16
Wednesday
10:15
11:45
A5, C 013
08.09.16
29.09.16
Thursday
10:15
11:45
A5, C 014
First Exam Date:
05.10.16
Wednesday
17:15
19:15
L7, 3-5 - 001
Retake Exam Date:
18.01.17
Wednesday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 302
Exercise Group 2
05.09.16
26.09.16
Monday
13:45
15:15
B6, A 303
Exercise Group 3
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 302
Exercise Group 4
05.09.16
26.09.16
Monday
15:30
17:00
B6, A 303
Exercise Group 1
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 302
Exercise Group 2
06.09.16
27.09.16
Tuesday
13:45
15:15
B6, A 303
Exercise Group 3
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 302
Exercise Group 4
06.09.16
27.09.16
Tuesday
15:30
17:00
B6, A 303
Exercise Group 1
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 302
Exercise Group 2
07.09.16
28.09.16
Wednesday
13:45
15:15
B6, A 303
Exercise Group 3
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 302
Exercise Group 4
07.09.16
28.09.16
Wednesday
15:30
17:00
B6, A 303
Exercise Group 1
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 302
Exercise Group 2
08.09.16
29.09.16
Thursday
13:45
15:15
B6, A 303
Exercise Group 3
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 302
Exercise Group 4
08.09.16
29.09.16
Thursday
15:30
17:00
B6, A 303

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

 

Teaching method

Lecture (3 SWS), Exercise (1.5 SWS)

 

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:

Paolo Conteduca (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.10.16
05.12.16
Monday
10:15
11:45
L7, 3-5 - 001
12.10.16
07.12.16
Wednesday
10:15
11:45
L7, 3-5 - 001
First Exam Date:
12.12.16
Monday
10:00
12:00
L9, 1 - 004
Retake Exam Date:
20.01.17
Friday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
10.10.16
05.12.16
Monday
12:00
13:30
L7, 3-5 - P044
Exercise Group 2
10.10.16
05.12.16
Monday
13:45
15:15
L7, 3-5 - P044

Lecturer(s)


Course Type: core course

Course Number: E702

Credits: 8

Prerequisites

E700.


Course Content

We will cover the neoclassical growth model in continuous time and discrete time. We will also use recursive methods. Then we cover stochastic growth and overlapping generations, followed by Arrow-Debreu and recursive equilibria in discrete time. We study an individual savings problem with uninsurable idiosyncratic shocks, and if time permits, conclude with the incomplete markets model a la Aiyagari-Huggett.

 

Teaching Method

Lecture (3 SWS), Exercise (1.5 SWS)

 

Requirements for the assignment of ECTS Credits and Grades

  • Midterm exam 90 min (24%)
  • Final exam 120 min. (36%)
  • Weekly problem sets (40%)

 

Literature

Textbooks:

  • Ljungqvist, L. Sargent, T.J. (2004). Recursive Macroeconomic Theory. MIT Press.
  • Prescott, E.C. Lucas, R.E. Stokey, N.L. (1989). Recursive Methods in Economic Dynamics. Harvard University Press.

Competences acquired

Students who have successfully completed this course have acquired the knowledge of the mathematical concepts related to dynamic programming (sequence problem, transversality condition, Bellman equations) and uncertainty (Markov chains, complete markets), as well as foundations of modern macroeconomic research: variants of the growth model, 1st and 2nd Welfare Theorems, complete insurance and incomplete markets equilibrium.

 

Teaching Assistant: 

Niklas Garnadt (CDSE)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.10.16
05.12.16
Monday
17:15
18:45
L7, 3-5 - S 031
12.10.16
07.12.16
Wednesday
17:15
18:45
L7, 3-5 - S 031
First Exam Date:
14.12.16
Wednesday
15:00
17:00
L9, 1 - 004
Retake Exam Date:
24.01.17
Tuesday
10:00
12:00
L9, 1 - 003
Tutorial
Exercise Group 1
11.10.16
06.12.16
Tuesday
13:45
15:15
L7, 3-5 - P043
Exercise Group 2
12.10.16
07.12.16
Wednesday
13:45
15:15
L7, 3-5 - P043

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
08.09.16
08.12.16
Thursday
12:00
13:30
W 114


Course Type: elective course

Course Number: ACC/TAX 920

Credits: 6

Course Content

This course aims at students in accounting and taxation. 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 determined in class.
Students will learn how to present and discuss their own research results. They will become acquainted with acting as discussant for other topics. Additionally, they will learn how to write a referee report.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
06.09.16
Tuesday
14:00
15:00
SO 133
13.09.16
27.09.16
Tuesday
12:00
13:30
SO 133
04.10.16
Tuesday
13:45
15:15
SO 133
11.10.16
08.11.16
Tuesday
12:00
13:30
SO 133
15.11.16
Tuesday
13:45
15:15
SO 133
22.11.16
29.11.16
Tuesday
12:00
13:30
SO 133
06.12.16
Tuesday
13:45
15:15
SO 133

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
08.09.16
08.12.16
Thursday
15:30
17:00
O 226/28
13.09.16
22.11.16
Tuesday
15:30
17:00
L 9, 1-2 – room 409

Register

Business Fall 2016

Statistics Refresher
ACC 902
Normative Accounting Research
E 703
Advanced Econometrics I
E700
Mathematics for Economists
E701
Advanced Microeconomics I
ACC/TAX 920
Brown Bag Seminar Empirical Accounting & Taxation
FIN 801
Discrete-Time Finance
IS 801
Design Science Research
IS 901
Epistemological Foundations
BAS
Mathematics for Social Scientists
MAN 802
Fundamentals of Non-Profit Management Science
MAN 805
Applied Methods in Management Research
MAN 806
Advances in Organization and Innovation Research
MET
Crafting Social Science Research
MAN 912
Family Business Research and the Art of Article Writing
MKT 801
Fundamentals of Marketing Research
MKT 903
Advanced Business Econometrics
OPM 805
Research Seminar Business Analytics
OPM 801
Optimization ans Heuristics
OPM 803
Selected Topics in Nonlinear Optimization
E702
Advanced Macroeconomics I
European Tax Law
TAX 916
Applied Econometrics I