Author Archives: Axel Czaya

GIGA Summer Term Programme 2017, 24 April – 27 June 2017

Institution: GIGA German Institute of Global and Area Studies

Location:
GIGA German Institute of Global and Area Studies
Neuer Jungfernstieg 21
20354 Hamburg

The following seminars are open to doctoral students and postdoctoral researchers at the GIGA and its partner institutions. Please note that other external participants are asked to pay a small course fee.

24 – 25 April Qualitative Interviews Dr Alenka Jelen-Sanchez, University of Stirling
3 – 4 May Introduction to R Dr Florian Weiler, University of Kent
8 May Research Data Management – Introductory Course for Doctoral Students Dr Birte Pfeiffer, GIGA
10 May CAS & Global Studies I: Growth and Development: Basic concepts, measurement and data Apl Prof Dr Jann Lay, GIGA
18 – 19 May QCA and Case Selection Prof Ingo Rohlfing Ph.D., University of Cologne
1 – 2 June Process tracing methods – an Introduction Prof Derek Beach, University of Aarhus
7 June CAS & Global Studies II: Studying Presidential Term Limits in Africa and Latin America Dr Mariana Llanos, GIGA
13 – 14 June Introduction to Grounded Theory Alice Mattoni, Scuola Normale Superiore Florence
27 June CAS & Global Studies III: Rising Powers in World Politics Prof Dr Sandra Destradi, GIGA

Information on Registration:
Participants need to register online by filling in the registration form that is available on the website of the respective event.

Questions should be addressed to Laura Carolin Freitag.

Registration deadline: Monday, 17 April 2017

Upcoming courses at the Institute for Employment Research (IAB)

Einführung in Octave

Course instructor: Dr. Ludsteck
Date: 24.-26.04.2017

Quantil Regression

Course instructor: Prof. Fitzenberger
Date: 19./20.09.2017

Causes and Consequences of Migration

Course instructor: Prof. Spitz-Oener
Date: 16./17.11.2017

Institution: Institute for Employment Research (IAB) of the German Federal Employment Agency (BA)

More information is coming soon!

Invitation to 6 Doctoral Scholarships with a maximum duration of 3 years, beginning 1 October 2017

The Institute for Employment Research (IAB) and the School of Business and Economics of the
University of Erlangen-Nuremberg (FAU) offer a joint doctoral programme in labour market
research (GradAB), which prepares graduates for a career in academics and in policy consulting.
IAB and FAU jointly constitute one of the most important hubs for labour market research in
Germany and provide optimal conditions for more than 200 labour market researchers from
different disciplines to conduct high-quality academic research.

  • The Graduate Center GradAB offers a three-year programme of high-level training in
    labour market research, which can be extended for another year under certain conditions.
  • Doctoral students benefit from a professional research and policy-consulting environment
    in one of the key institutions advising high-ranking social policymakers.
  • The course programme provides training on labour market research, methods, and data at an advanced level and is held in English.
  • The GradAB works closely together with its partners from a large network of renowned
    national and international universities, research and policy institutions.
  • The scholarship offers financial support of 1,350€ / month. In addition, funding is
    available for participation in scientific conferences and further training.
  • Scholarship holders are granted access to the IAB’s unique data resources on employment
    and social security (administrative and survey data).

We invite applications from outstanding graduates in the fields of economics, sociology or other social sciences who hold a master’s degree or diploma and have a strong interest in labour market research.

For further information on the programme, admission requirements, and the application process, please see our website www.iab.de/en/gradab.

Please submit your application in English by 31 March 2017 to:
Dr Sandra Huber
E-mail: sandra.huber@iab.de

Experimental Economics

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course instructor: Prof. Dr. Markus Nöth (Universität Hamburg)

Date: block course:

April 7 th, 2017: 8:15am-5:00pm (10*45min)
May 5th, 2017: 8:15am-1:00pm (6*45min)
June 2nd, 2017: 8:15am-5:00pm (10*45min)
June 21st, 2017: 6:00pm-7:30pm (2*45min)

Room: tbd (Moorweidenstraße 18, Von-Melle-Park 5 (ExpLab))

Course Value: 2 SWS or 4 LP

Teaching language: English

Registration: Send an email to markus.noeth@uni-hamburg.de until March 17th, 2017; please indicate if you prefer some specific topics to be covered.

Course Overview:
The main goal of this course is to give an introduction to 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. Second, based on a literature review (for some research fields that are proposed by the participants) an experimental design is developed and a pilot experiment will be set up and run in class. As part of this exercise, students will learn the basic requirements of a human subjects committee.

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

General literature:

  • Kagel, John H., and Alvin E. Roth, 1995, The Handbook of Experimental Economics, Princeton University Press, Princeton/Oxford
  • Gerber, Alan S., and Donald P. Green, 2012, Field Experiments, W.W. Norton & Company, London/New York.
  • Kagel, John H., and Alvin E. Roth, 2015, The Handbook of Experimental Economics Volume 2, Princeton University Press, Princeton/Oxford

Assessment:

  • Paper presentation (May 5th)
  • 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

University of Hamburg: Introduction to Research in Closed-Loop Supply Chains

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course instructor: : Prof. Gilvan Souza (Kelley School of Business, Indiana University)

Date: June 16th 2017, 09:00-13:00 h  (block course)

Room: tba

Course Value: 1 LP

Teaching language: English

Registration: Please register via email to stefanie.nonnsen@uni-hamburg.de

Course Overview:
This course will provide an overview of research and tools used in closed-loop supply chain management research in operations management. A closed-loop supply chain is a supply chain with flows of products post-consumer use from consumers to retailers, manufacturers, and/or suppliers. Examples include consumer returns, and post-lease products. Emphasis will be given to strategic decision-making, such as product line extension, choice of product quality, and take-back legislation.

Course Contents:

  • An overview to closed-loop supply chains (CLSCs): types of product returns, and types of disposition decisions.
  • Examples of strategic, tactical and operational decisions in CLSCs
  • Strategic decision 1: Should an Original Equipment Manufacturer (OEM) offer a remanufactured product in its product line?
    • Monopoly pricing for a single product, and for a vertically differentiated product line under linear demand curves and constant marginal costs
    • The fundamental trade-off: Market expansion vs. cannibalization
    • Extension: non-linear demand curves
    • Competition between an OEM and a third-party remanufacturer
  • Strategic decision II: What is the optimal product quality when there is product recovery in the form of remanufacturing and/or recycling?
    • Introduction to classical quality choice models without product recovery (Mussa and Rosen, 1978)
    • Quality choice with product recovery: monopoly (Atasu and Souza 2013)
    • Quality choice with product recovery: competition between an OEM and a third-party remanufacturer (Orsdemir et al. 2014)
  • Strategic decision III: Design of optimal take-back legislation from a policy maker’s perspective, and an OEM’s response to it
    • The concept of welfare and its components: firms’ profits plus consumer surplus minus environmental impact
    • The model by Atasu and Van Wassenhove (2009)
  • Incentives and coordination in CLSCs
    • Reducing consumer returns through retailer effort (Ferguson, Guide, and Souza, 2006)
  • Overview of tactical decision making in CLSCs
    • Production planning for remanufactured products: product acquisition, grading, and disposition decisions
    • Hybrid inventory systems

Prerequisites: Background in Operations and Supply Chain Management is preferred but not absolutely necessary.

Assessment: Participation in discussion

University of Hamburg: HCHE Research Seminar and PhD Course 24 to 25 April 2017

Institution: Hamburg Center for Health Economics (HCHE)

Course instructor: Professor Mike Drummond, Professor of Health Economics and former Director of the Centre for Health Economics at the University of York

Date: 24-25 April 2017

Time:

  • 24 April: arrival of Prof. Mike Drummond, individual meetings (please ask for an appointment: andrea.buekow@uni-hamburg.de)
  • 24 April, 4:30 pm: HCHE Research Seminar Title: Where politics and economics collide: the case of orphan drugs
  • 25 April, 9:00 am – 5:00 pm: PhD Course Title: Methodological and Policy Issues in Economic Evaluation

Place: HCHE, Esplanade 36

  • HCHE Research Seminar: Rooms 4011/13
  • PhD Course: Rooms 4030/31

Credit Points: 1 SWS/2 LP (Universität Hamburg)

Teaching language: English

Registration for the PhD Course:  andrea.buekow@uni-hamburg.de, no later than 14 April 2017

University of Hamburg: Statistical Analysis of Big Data

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course instructor: Prof. Martin Spindler (UHH)

Date: Semester course, Time: T or W, 8-10am

Place: tba

Course value: 2 SWS or 4 LP

Course overview:
The main goal of this course is to give an introduction to statistical methods for the analysis of big data. Recently developed methods are discussed, in particular various methods of machine learning are presented and basic concepts for the analysis of big data are introduced. The course is based on the recent book by Efron and Hastie (2016).

Reference: Efron, B. and T. Hastie. Computer Age Statistical Inference. Cambridge University Press 2016.

Teaching language: English

Student evaluation: paper presentation/presentation of a chapter of the book

Registration: by email to martin.spindler@uni-hamburg.de

The GIGA Doctoral Programme invites applications from prospective doctoral students to join the programme on 1 October 2017

The GIGA German Institute of Global and Area Studies / Leibniz-Institut für Globale und Regionale Studien is an independent social-science research institute based in Hamburg. It analyses political, social and economic developments in Africa, Asia, Latin America, and the Middle East and links them to questions of global significance. The GIGA combines this analysis with innovative comparative research in the fields of Accountability and Participation, Peace and Security, Growth and Development, and Power and Ideas across multiple levels of analysis. The GIGA Doctoral Programme is a three-year structured programme for junior academics, in which they can pursue their research and professional development, particularly in the field of comparative area studies (CAS). We strongly welcome international applications.

Please find the Call and further information regarding the application process on our website: https://www.giga-hamburg.de/de/dp/application/fellow

The deadline for applications is 1 February 2017.

46th GESIS Spring Seminar: Causal Inference with Observational Data

Date: 06.03 – 24.03.2017

Location: GESIS Location in Cologne. For a list with hotel recommendations, information about Cologne as well as on how to get to GESIS please click here.  

Language of instruction: English

 

Introduction:
The GESIS Spring Seminar (formerly ZA Spring Seminar) has been taking place in Cologne annually for more  than 45 years. It offers three consecutive one-week courses in advanced methods  of quantitative data analysis for Social Scientists. Language of instruction is English.

Week 1 (06.-10.03.2017)

  • Causal Analysis with Panel Data: Potentials and Limitations – Prof. Dr. Michael Windzio, Jun. Prof. Dr. Marco Giesselmann (for further information and registration please click here)

Week 2 (13.-17.03.2017)

  • Structural Equation Models (SEMs)  – Prof. Kenneth Bollen, PhD with Zachary Fisher (for further information and registration please click here)

Week 3 (20.-24.03.2017

  • Potential Outcomes and Treatment Effects: Modern Methods of Causal Inference  – Prof. Dr. Ben Jann, Dr. Rudolf Farys (for further information and registration please click here)

Reminder HSU-Doktorandenkurs: Measuring Preferences using Conjoint Analytic Methods and Advanced Compositional Approaches, 01.12.2016

Institution: Helmut-Schmidt-University Hamburg/Syddansk Universitet, Sønderborg (SDU), Denmark

Lecturer: Prof. Martin Meißner, Department of Environmental and Business Economics, SDU

Date: 01.12.2016, 09:00-17:00 (incl. breaks)

Place: Helmut-Schmidt-Universität, Holstenhofweg 85, 22043 Hamburg, Aula-Gebäude, Raum 3

Language of instruction: English

Registration: Non-members of the Helmut-Schmidt-Universität may click here firstly to create an HSU-Ilias-account, and secondly here to join the course.

Contents:
The participants of this course develop a sound understanding of the benefits of using conjoint analytic preferences measurement approaches and alternative advanced compositional approaches. Participants gain practical experience of using conjoint-analytic methods, and develop a better understanding of the value of measuring preferences.

The course starts with introducing the basic concepts behind the measurement of stated preferences, specifically focusing on conjoint analysis. The most often used approaches, i.e. traditional conjoint analysis, adaptive conjoint analysis and choice-based conjoint analysis are introduced. We deliberate on advantages and disadvantages of the approaches and also discuss advanced compositional approaches, like pairwise-comparison based preference measurement and the adaptive self-explicated approach. During the workshop we will further talk about all the important stages of designing a preference measurement study. We pay special attention to the types of research questions that conjoint analysis can answer. We also discuss the most important questions you should answer before setting up your preference measurement/conjoint study: What is the optimal choice of attributes and attribute level? What is a good experimental design? How should I design my survey design and present potential choice scenarios? How do I analyze the results?

Participants will have the opportunity to use Sawtooth Software on their own laptops and build their own conjoint analysis survey during the course. Based on this experience, participants will be able to improve the planning of their own future experiments.

Recommended literature and pre-readings:

  • Bradlow, Eric T. (2005), “Current Issues and a ‘Wish List’ for Conjoint Analysis,” Applied Stochastic Models in Business and Industry, 21 (4-5), 319-323.
  • Hauser, John R. and Vithala Rao (2003), “Conjoint Analysis, Related Modeling, and Applications,” in Advances in Marketing Research: Progress and Prospects, in Marketing Research and Modeling: Progress and Prospects, Wind, Jerry and Paul Green (eds.), New York: Springer, 141-168.
  • Huber, Joel (1997), “What We Have Learned from 20 Years of Conjoint Research: When to Use Self-Explicated, Graded Pairs, Full Profiles or Choice Experiments,” Sawtooth Software Conference Proceedings, Sequim, WA., 243-256.
  • Scholz, Sören W., Martin Meissner, and Reinhold Decker (2010), “Measuring Consumer Preferences for Complex Products: A Compositional Approach Based on Paired Comparisons,” Journal of Marketing Research, 47 (4), 685-698.