Category Archives: University of Hamburg – BWL

Uni Hamburg: PhD Course Advanced Modelling and Optimization

Course Instructor: Prof. Fliedner/Prof. Haase

Course Value: 2 SWS or 5 LP

Teaching language: English

Registration: via Email to  ana-jelena.peric@uni-hamburg.de

Course Objectives:

This course builds up on the fundamentals of linear and combinatorial optimization and equips students with a set of advanced modeling tools to solve optimization models from different fields of application. Students learn to formulate optimization models as   mixed- integer linear programs, how to solve them with standard software and how to construct heuristic solution algorithms. Successful participants will be able to deal with the  complexity of real-world decision problems via aggregation, relaxation, and decomposition techniques. This course is aimed at Ph.D. students in information systems, business administration, and computer science. Participants are expected to have a solid understanding of the basics of modeling and optimization and will be provided with an advanced understanding of algebraic optimization models and solution  methods

Student evaluation:

Successful completion of work assignments

Uni Hamburg: PhD Course Survey Research

Dates & Time:
Kick-Off: November 18, 2019; 6 pm
Seminar: February 10 – 12, 2020; full time (tba)
Exam: February 17, 2020; 9 am

Location:     
Universität Hamburg, Moorweidenstr. 18, room 0005.1 (for 18 Nov 2019, 10 – 12 Feb 2020); room for exam tba

Instructor:
Prof. Dr. Karen Gedenk

Teaching Language:
English

Credit Points: 
2 SWS/5 LP

Registration: 
until November 11, 2019. Please send an e-mail to Elke Thoma (elke.thoma@uni-hamburg.de) which  informs about:

  • your name
  • your email address
  • the supervisor of your doctoral thesis and topic
  • your background in statistics and empirical research.

Objectives:

This course is designed to lay the foundations of good survey-based research in different areas of Business Administration. Through a critical review of existing literature, presen- tations and discussions, students become acquainted with common problems in survey- based research and advanced methods for solving them. Students get an overview of dif- ferent methods in the survey research “tool box”. This helps them identify appropriate methods for their own research and evaluate research done by others.

Prerequisites:

Students should have a solid foundation in statistics and be familiar with the basics of multivariate data analysis.

Student Evaluation:

To pass the course, participants are required to make a successful presentation. In addi- tion, they need to read one paper on each topic, participate in class discussions, and pass the exam.

Contents & Working Requirements:

Exemplary topics are preference measurement, measurement models for complex con- structs, structural equation models, moderation and mediation, multicollinearity, heter- ogeneity, endogeneity, common method bias. A list of topics and readings will be pro- vided at the kick-off meeting.

Participants prepare and hold a presentation – either alone or in a group (depending on the number of participants). In their presentation, participants explain, compare and evaluate methods relevant for their specific problem. All presentations should contain a practical example based either on an own dataset or on published research. Participants also take an exam at the end of the course.

Coordination/Contact

Prof. Dr. Karen Gedenk (karen.gedenk@uni-hamburg.de).

For all organiziational issues please contact Elke Thoma  (elke.thoma@uni-hamburg.de).

 

Uni Hamburg: PhD Course Behavioral & Experimental Economics

Dates: The course takes place on four days. Sessions are scheduled in both the winter term and the summer term, such that participants have sufficient time to develop and run their experiments:

November 22nd, 2019; November 27th, 2019; March 27th, 2020.

The last session will take place either in May or June 2020, and will be scheduled in the second meeting.

Time 10am—4pm
Place Universität Hamburg (more details follow)
Instructor Prof. Dr. Markus Nöth and Prof. Dr. Guido Voigt (both UHH)
Teaching language English
Credit Points 2 SWS/5 LP
Registration kathrin.marina.heim@uni-hamburg.de

(first come, first-served)

Objectives:

The main goal of this course is to introduce the design and implementation of both laboratory and field experiments in various fields of Economics and Business Administration. PhD students who have some experience with or who consider to set up an experiment are welcome to par- ticipate in this course.

First, we will identify different research questions for a laboratory or a field experiment. We start with discussing critical theory assumptions. We then show how research hypotheses can be inferred from behavioral models and how these hypotheses may be tested in lab or field studies.

Second, participants will present and discuss an experimental paper (either provided by us or self-selected) that is instructive for their own research field.

Third, participants will develop an experimental design and conduct a pilot experiment that is run in class. We introduce basic statistics along with a discussion how they relate to the exper- imental design. Alternatively, for participants who do not plan to conduct their own experi- ments, a second paper will be reviewed.

Participants have the option to take a research ethics training (https://about.citipro- gram.org/en/homepage/) that becomes increasingly important to conduct research projects with colleagues from the Unites States and in the European Union. All students will learn the basic requirements of a human subjects committee.


Some topics:

  • Identify a suitable research question for an experiment
  • Ethical and scientific standards: historical and scientific reasons, consent requirements, hu- man subjects committee, special requirements (children, elderly people, inmates, …), data collection and evaluation
  • Individual and group experiments in the laboratory
  • Surveys and internet experiments
  • Field experiments in cooperation with a company


Prerequisites:

Basic background in microeconomics, game theory and statistics.

Student evaluation:

  • Presentation and critical discussion of one or two experimental papers,
  • Optional but encouraged: experiment design presentation (extended summary on eco- nomic question, relevant literature, hypotheses, design: presentation with 10 slides or max. five pages extended abstract); running a pilot experiment

 

Schedule (tentative) 

Day Topics Suggested Readings
1st Session Introduction to the field

Game theoretic models, critical as- sumptions, Behavioral Models and Research Hypothesis

Laboratory Experiments

Katok (2018)
2nd Session Presentation and discussion of as- signed papers.

Statistics & Design Choices IRB, Field-Experiments

Hyndman, K. and Embrey, M. (2018)
3rd Session Presentation of research (Problem De- scription, Research Hypothesis, Exper- imental design)

Visit of WiSo-Experimentallabor (z- Tree, Eye-Tracking, etc.)

4th Session Presentation of pilot studies (Note: Pilot studies need to be scheduled in- dependently by participants)

Suggested readings before the course:

Katok, E. (2018) Designing and Conducting Laboratory Experiments, pages: 1-33 in Donohue, K.; Katok, E.; Leider, S. (Hg.). The handbook of behavioral operations. John Wiley & Sons, 2018. (online available)

Hyndman, K. and Embrey, M. (2018) Econometrics for Experiments, pages: 35-88 in Donohue, K.; Katok, E.; Leider, S. (Hg.). The handbook of behavioral operations. John Wiley & Sons, 2018. (online available)

 

Other useful resources:

Baum, C. F. (2006) An introduction to modern econometrics using Stata. Stata press Camerer, C (2003) Behavioral Game Theory, Princeton University Press.

Holt, C. (2019), Markets, Games, and Strategic Behavior: A First Course in Experimental Economics, 2nd edition, Princeton Universtity Press

Kagel, J. and A. Roth (1995) Handbook of Experimental Economics, Princeton University Press.

Sheskin, D. J. (2011) Handbook of parametric and nonparametric statistical procedures. 5. ed. CRC Press.

Other material (e.g., papers to be presented etc.) will be distributed once we know who participates.

 

Graduate School der Universität Hamburg – Promotionsstudiengang der Fakultät für Wirtschafts- und Sozialwissenschaften – Kursangebot im Wintersemester 2019/20 (Stand: 28.08.2019)

Eine Komplettübersicht des aktuellen Kursprogramms der WiSo-Graduate-School der Universität Hamburg finden Sie hier. Bitte beachten Sie die Anmeldefristen.

Hamburg Business School: Doctoral study courses in winter semester 2018/19

The following doctoral study courses will be on offer at the Hamburg Business School in winter semester 2017/18:

  • HCHE Research Seminar and PhD Course (12.-13.11.2018)
    Patricia Born (Informationen)
  • Behavioral & Experimental Economics (4 Termine, Start 14.12.2018)
    Markus Nöth & Guido Voigt (Informationen)
  • Advanced Modelling and Optimization (Blockkurs 17.-21.12.2018)
    Malte Fliedner & Knut Haase (Informationen)
  • Recent Developments in Causal Inference (Blokkurs im Januar)
    Martin Spindler (Informationen)
  • Survey Research (4.-6.2.2019, Kick-off 5.11.2018)
    Karen Gedenk (Informationen)
  • Recent Developments in Audit Research and an Approach to getting Published (20.-22.2.2019)
    Nicole Ratzinger-Sakel (Informationen)

See also https://www.bwl.uni-hamburg.de/en/forschung/promotion.html for further information on the doctoral studies program of the Hamburg Business School.

University of Hamburg – Behavioral & Experimental Economics (PhD Course)

(The course takes place on four Fridays. Sessions are scheduled in both the winter term and the summer term, such that participants have sufficient time to develop and run their experiments)

14th December 2018, 18th January 2019, 22nd February, 7th June

10:00 – 16:00 h

Universität Hamburg (more details follow)

Course Instructor: Prof. Dr. Markus Nöth and Prof. Dr. Guido Voigt (both UHH)

Course Value: 2 SWS or 5 LP

Teaching language: English

Registration: guido.voigt@uni-hamburg.de, (First come, first-served)

Objectives:
The main goal of this course is to introduce the design and implementation of both laboratory and field experiments in various fields of Economics and Business Administration. PhD students who have some experience with or who consider to set up an experiment are welcome to participate in this course.

First, we will identify different research questions for a laboratory or a field experiment. We start with discussing critical theory assumptions. We then show how research hypotheses can be inferred from behavioral models and how these hypotheses may be tested in lab or field studies.

Second, participants will critically discuss an experimental paper (either provided by us or self-selected) that is instructive for their own research field.

Third, participants will develop an experimental design and conduct a pilot experiment
that is run in class. We introduce basic statistics along with a discussion how they relate
to the experimental design.

Participants have the option to take a research ethics training (https://about.citiprogram.org/en/homepage/) that becomes increasingly important to conduct research projects with colleagues from the Unites States. All students will learn the basic requirements of a human subjects committee.

Some topics:

  • Identify a suitable research question for an experiment
  • Ethical and scientific standards: historical and scientific reasons, consent requirements,
    human subjects committee, special requirements (children, elderly people, inmates, …), data collection and evaluation
  • Individual and group experiments in the laboratory
  • Surveys and internet experiments
  • Field experiments in cooperation with a company

Schedule (tentative)

Day Topics Suggested Readings
1st SessionIntroduction to the field

Game theoretic models, critical assumptions, Behavioral Models and
Research Hypothesis

Laboratory Experiments
Katok 2012
2nd SessionPresentation and discussion of assigned papers.

Statistics & Design Choices

IRB, Field-Experiments
Baum 2006,
Sheskin 2011
3rd SessionPresentation of research (Problem Description, Research Hypothesis, Experimental design)

Visit of Experimentallabor (z-Tree, Eye-Tracking, etc.)
4th SessionPresentation of pilot studies (Note: Pilot studies need to be scheduled independently by participants)

Prerequisites:
Basic background in microeconomics, game theory and statistics.

Student evaluation:

  • Critical discussion of an experimental paper, experiment design presentation (extended summary on economic question, relevant literature, hypotheses, design: presentation with max. 10 slides or max. five pages extended abstract).
  • Running a pilot experiment is optional, but encouraged.

Recommended Texts:
Statistical analysis
Baum, C. F. 2006. An introduction to modern econometrics using Stata. Stata press
Camerer, C, 2003, Behavioral Game Theory, Princeton University Press.
Kagel, J. and A. Roth, 1995, Handbook of Experimental Economics, Princeton University
Press.
Sheskin, D. J. 2011. Handbook of parametric and nonparametric statistical procedures.
5. ed. CRC Press.
How to design laboratory experiments
Katok, E. 2012. Using laboratory experiments to build better operations management
models. Foundations and trends in technology, information and operations management 5(1) 1–88.

Other material (e.g., papers to be presented etc.) will be distributed once we know
who participates

University of Hamburg – School of Business: Recent developments in audit research and an approach to getting published

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course Instructor: Professor Nicole Ratzinger-Sakel (UHH)

Course Value: 2 SWS or 4 LP

Block course:
20 February, 2019 – 22 February, 2019,
Time: 9 a.m. – 5 p.m.

Location: tba

Language of instruction: English

Application: Please send a current CV until January 12, 2019 to nicole.ratzingersakel@uni-hamburg.de.

Course Overview:
The main objectives of this PhD course include:

  • Introduce students to recent developments in audit research; hereby students will get
    knowledge about a selection of audit research papers recently published in highly ranked academic journals.
  • In addition, the course will enhance students’ ability to critically review the quality of research papers which is a meaningful element of the double-blind review process and extremely important for the quality of their own work. To do so, students will get an idea which “list” reviewers typically follow. Students are further expected to present and critically discuss papers that will be assigned to them.
  • Students will further get advices to getting their work published.
  • Finally, students should present their (first ideas of) own (audit) research ideas during the
    course.

Student evaluation: Presentation and critical discussion of assigned papers (papers will be
assigned to students after their application; each student is expected to present and critically
discuss one paper).

University of Hamburg – School of Business: Risk adjustment methods for quality of care outcomes with administrative data

Institution: Universität Hamburg, Hamburg Center for Health Economics

Course Instructors: Prof. Dr. Marco Caliendo / Prof. Dr. Tom Stargardt

Course Value: 5 ECTS

Block course:
24.09.2018: 9:00 am ‐ 12:30 pm / 01:30 pm ‐ 05:00 pm
25.09.2018: 9:00 am ‐ 12:30 pm / 01:30 pm ‐ 05:00 pm
26.09.2018: 9:00 am ‐ 12:30 pm / 01:30 pm ‐ 05:00 pm

Place: Universität Hamburg

Classroom: 4029, Esplanade 36

Language of instruction: English

Registration: Please contact  Elena Phillips, elena.phillips@wiso.uni-hamburg.de (first come, first-served)

Course Overview:
The course will cover methods for drawing causal inference in interventional, non‐
experimental/non‐randomized studies on quality of care with administrative data. In order to control for confounders between intervention and control group, at first simple methods (such as stratification and standardization) as well as advanced methods (Propensity Score Matching, Difference‐in‐Differences, Regression‐Discontinuity Designs) are taught. The course will also give an overview on common risk‐adjustment instruments (generic and disease specific risk‐adjustment scores based on diagnoses or ATC codes) for use with health outcomes.

The course will be split in theoretical and practical sessions. During the practical sessions we are going to implement the discussed estimators with STATA. Hence, a basic knowledge of STATA (data handling, running do‐files, etc.) is a prerequisite for the course. If you are not familiar with STATA you might want to check the online introduction from the UCLA Institute for Digital Research and Education https://stats.idre.ucla.edu/stata/. The relevant estimation commands and ado‐files will be explained during the course; some of them require STATA 13 or higher.

Assessment: Students will have to complete an assignment doing (statistical) analyses of a dataset. Results have to be presented in the form of a short summary paper.

More information: https://www.bwl.uni-hamburg.de/forschung/promotion/phd-risk-adjustment-module-description.pdf

University of Hamburg – School of Business: Behavioral & Experimental Economics

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course Instructors: Prof. Dr. Markus Nöth and Prof. Dr. Guido Voigt (both UHH)

Course Value: 2 SWS/4 LP

Date: The course takes place on four Fridays in the summer term 2018: 6.4. / 20.4. / 18.5. / 6.7., 10-12.30h and 13.30-16h

Place: Universität Hamburg

Room: tba

Language of instruction: English

Registration: Please contact stefanie.nonnsen@uni-hamburg.de (first come, first-served)

Course Overview & Contents:
The course discusses the basic steps of performing behavioral research. We start with discussing critical assumptions of game theoretic models. We then show how research hypotheses can be inferred from behavioral models and how these hypotheses may be tested in lab studies. Critical design factors of laboratory experiments and the most commonly applied statistical tests will be presented.
We will further visit the Lab at the UHH while discussing options (e.g. eye-tracking) and limits
(e.g. subject pool, size of the lab) for conducting lab experiments at UHH. The course also provides an overview of commonly applied software tools that are used for behavioral modelling (Maple), software for computerized experiments (z-Tree), and statistical analysis (Stata). Ethical aspects of conducting laboratory experiments underpin the theoretical/fundamental part of this course.
Based on these theoretical foundations, participants are asked to design an experiment. The
presentations will be the basis for passing/failing the course. The topic of the experiment is
open. We may also suggest a topic. If this is the case, please send your research interest along
with the registration.

Prerequisites: Basic background in microeconomics, game theory and statistics.

Assessment: Assessment will be based on active participation. Grading for students
of University of Hamburg will be pass/fail.

More information: https://www.bwl.uni-hamburg.de/forschung/promotion/phd-kurs-noeth-voigt-ss18.pdf

Hamburg Business School: Doctoral study courses in winter semester 2017/18

The following doctoral study courses will be on offer at the Hamburg Business School in winter semester 2017/18:

  • Recent Developments in Causal Inference (Jan 31-Feb 2 2018)
    Martin Spindler (Information)
  • Microeconometrics (Nov 14-16 2017)
    Stefan Hoderlein (Information)
  • Writing skills, intellectual property rights and research integrity (Nov 17 2017)
    Andrea Sanchini (Information)
  • Project management and time/self-management skills (Dec 20 2017)
    Anette Hammerschmidt (Information)

See also https://www.bwl.uni-hamburg.de/en/forschung/promotion.html for further information on the doctoral studies program of the Hamburg Business School.