Category Archives: IRWS

International Research Workshop

Questionnaire Design

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. David Richter (German Institute for Economic Research – DIW Berlin)

Date: Monday, 11/09/17 – Wednesday, 13/09/17 (09:00 – 12:30)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The course aims to provide an overview of the theoretical basics and empirical evidence related to questionnaire design. The cognitive process of survey responding, challenges of designing effective survey questions including aspects of proper question wording and optimal response formats, as well as pretest techniques for evaluating survey questions will be discussed.

Requirement of students: None.

Recommended literature and pre-readings: tba.

You have to register for the 11th International Research Workshop to participate in this course.

Handling of Missing Data

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Martin Spiess (University of Hamburg)

Date: Thursday, 14/09/17 (09.30 – 18.00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

If the missing information is selective with respect to the research question, then simply ignoring unobserved information or applying other ‘ad hoc’ methods usually leads to invalid inferences, i.e. to biased estimators or actual rejection rates of ‘true’ null hypotheses being too high. In this seminar, basics of the missing data problem and some techniques to compensate missing values are discussed. A main topic in the introductory part is the missing data mechanisms, i.e. the mechanism that led to the missing information. The way how to deal with the missing data problem such that scientifically interesting inferences are valid depends mainly on assumptions about this process. A particularly important question is whether the precise missing mechanism can be ignored in downstream analysis, or if it as to be modelled explicitly. In the second part, an overview of various approaches to deal with the missing data problem is given. Besides ‘ad-hoc’ techniques which often lead to invalid inferences, model-based approaches like maximum likelihood methods as well as weighting and imputation methods will be considered. Most of the latter methods assume that the missing mechanism is ignorable. However, we will also consider a simple approach to estimate a model based on a non-ignorable missing mechanism. The third part deals with one missing data technique in more detail: Multiple imputations to deal with missing items. The concepts are illustrated with the help of examples, the software used is R.

Requirement of students: Statistical knowledge on the master level of an applied science programme is required.

Recommended literature and pre-readings:

  • Spiess, M. (2016). Dealing with missing values. In: C. Wolf, D. Joye, T.W. Smith and Y. Fu (Eds.), The SAGE Handbook of Survey Methodology (Chapter 37, pp. 595-610). Sage Publications: Thousand Oaks, CA.

You have to register for the 11th International Research Workshop to participate in this course.

Case Study Research

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Kamil Marcinkiewicz (University of Hamburg)

Date: Monday, 11/09/17 – Wednesday, 13/09/17 (14.30 – 18.00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The case study research is frequently applied in the social sciences. It is particularly popular among political scientists, especially those specialising in area studies. The ubiquity of the case study research contrasts with the scarcity of theoretical reflection on its core methodological aspects. Also, the benefits of comparative analyses are often underestimated. In this course, participants will have an opportunity to learn more about what the case study research is, what are its weakness and strengths and how should we go about the core question in designing a case study: selection of cases. The course combines lectures with practical exercises and discussion of students’ projects.

Requirement of students: None.

Recommended literature and pre-readings:

  • Gerring, J. (2007). Case Study Research: Principles and Practices (pp. 17-63). Cambridge: Cambridge University Press.
  • George, A. L., & Bennett, A. (2005). Case Studies and Theory Development in the Social Sciences (pp. 1-34). Cambridge, MA: MIT Press.
  • Rueschemeyer, D. (2003). Can One or a Few Cases Yield Theoretical Gains? In J. Mahoney and D. Rueschemeyer (Eds.), Comparative Historical Analysis in the Social Sciences (pp. 305-337) Cambridge: Cambridge University Press.
  • Hall, P.A. (2008). Systematic Process Analysis: When and How to Use it. European Political Science, 7(3), 304-317.

You have to register for the 11th International Research Workshop to participate in this course.

Researching, Writing, and Publishing a Literature Review

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Christina Hoon (Bielefeld University)

Date: Thursday, 14/09/17 (09:30 – 18:00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

As you embark on your PhD, or indeed any research undertaking, you always start with producing a review of the existing literature on the topic of your research field. However, given that a literature review constitutes a study in itself, a review study can also be one of the separate, publishable papers your PhD thesis consists of.

This workshop outlines the purpose, scope, methods, and contribution of a literature review. What constitutes a good literature review? How do you evaluate and assess the broad range of knowledge and information? How do you make a substantive contribution, thereby producing a publishable paper? This course will address the different forms of literature reviews (systematic reviews, meta-synthesis, meta-analysis). The analytical tools and methods of each of these different forms of a review are offered, along with illustrative examples. This course is structured to guide students throughout the process of conducting and writing a literature review: identifying and developing individual research interests, searching for relevant information resources, assessing and evaluating the extant literature, and concluding with the writing of a literature review.

Requirement of students: None.

Recommended literature and pre-readings:

  • Rousseau, D.M., Manning, J. and Denyer, D. (2008). Chapter 11: Evidence in management and organizational science: Assembling the field’s full weight to scientific knowledge through synthesis. Academy of Management Annals, 2, pp. 475–515.
  • Torraco, R.J. (2005). Writing integrative literature reviews: Guidelines and examples. Human Resource Development Review, 4, pp. 356-367.

You have to register for the 11th International Research Workshop to participate in this course.

Grounded Theory

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Christina Hoon (Bielefeld University)

Date: Monday, 11/09/17 – Wednesday, 13/09/17 (09:00 – 12:30)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

The key purpose of this workshop is to increase participants’ understanding of the key concepts, strategies, and steps in grounded theory research. This workshop intends to deepen theoretical and practical understanding of the constant comparative method, open, axial and selective coding. Further, the participants will learn the key elements of theoretical sampling, theoretical saturation, and theoretical sensitivity. In addition, common challenges and pitfalls in grounded theory research will be discussed. To assist participants to craft valuable and effective research papers, exemplars from current research projects will be assessed and critically reviewed.

Requirement of students: None.

Recommended literature and pre-readings:

  • Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. London, UK: Sage.
  • Gioia, D. A., Corley, K. G., & Hamilton, A. (2013). Seeking qualitative rigor in inductive research: Notes on the Gioia methodology. Organizational Research Methods, 16, 15-31.
  • Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Grounded theory procedures and techniques (2nd Ed). Thousand Oaks, CA: Sage.

You have to register for the 11th International Research Workshop to participate in this course.

Measuring Preferences using Conjoint Analytic Methods and Advanced Compositional Approaches

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Martin Meissner (University of Southern Denmark/Department of Environmental and Business Economics)

Date: Thursday, 14/09/17 (09:30 – 18:00 h)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

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 developed 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 analyse 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.

Requirement of students: Basic knowledge in inferential statistics is recommended.

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 Marketing Research and Modeling: Progress and Prospects, Wind, Jerry and Paul Green (eds.), New York: Springer, 141-168.

You have to register for the 11th International Research Workshop to participate in this course.

Reminder – 10th International Research Workshop “Methods for PhD”

September 25 – 30, 2016

NB! There are only a few places left!

Empirical research is seeking through methodological processes to discover, hopefully, nontrivial facts and insights. Beside choosing a topic and grounding an idea in theory, empirical research consists of gathering and analysing data as well as presenting results in scientific contexts. Our workshop tackles these steps of your research project:

  • Gathering data via (un)structured interviews or surveys and
  • using the computer for qualitative and quantitative data analysis.

The regular workshop fee is 449 Euro. It covers the participation in three courses, meals and accommodation. The workshop fee is 289 Euro without accommodation (only meals are included).

We are offering up to three funded scholarships to support refugee postgraduate students from Germany. Full details including eligibility criteria and how to apply for a scholarship can be found on the workshop website.

It is possible to get a certificate on 5 credit points (according to the European Credit Transfer System).

The following courses will be offered:

Parallel morning session 1 (26-28 September 2016):

  • Data Analysis with R
  • Data Analysis with Stata
  • Grounded Theory
  • Qualitative Interviewing
  • Developing Theoretical Contributions

Parallel afternoon session 2 (26-28 September 2016):

  • Qualitative Comparative Analysis (QCA)
  • Case Study Research
  • Introduction to the German Socio-Economic Panel Study (SOEP) and Applied Survival Analysis
  • Analyzing Panel and Spatial Data
  • Questionnaire Design

Parallel session at the SDU (30 September 2016):

  • Academic English Writing
  • Computable General Equilibrium (CGE) Modelling and Its Applications to Policy Impact Analysis
  • Introduction to Social Network Analysis
  • Reproducible Research with R and RStudio
  • Analysis of Qualitative Data and Exploratory Statistics

PLEASE note that the number of participants is limited to 20 persons per course! For further information, especially lecturers, program, organizers and registration visit our website: http://www.phd-network.eu/

For any questions don’t hesitate to contact the workshop committee (irwsnetwork@gmail.com).

The International Research Workshop is organised by

  • Prof. Dr. Wenzel Matiaske, Faculty of Economics and Social Sciences, Helmut-Schmidt-University/University of Federal Armed Forces and Research Professor at the German Institute for Economic Research (DIW Berlin)
  • Asst. Prof. Dr. Simon Fietze, University of Southern Denmark, Campus Sønderborg
  • Dr. Heiko Stüber, Institute for Employment Research (IAB), The Research Institute of the Federal Employment Agency in Nuremberg

The workshop is supported by

  • University of Southern Denmark, Department of Entrepreneurship and Relationship Management
  • University of Southern Denmark, Department of Environmental and Business Economics
  • University of Flensburg
  • University of Hamburg, Faculty of Economics and Social Sciences
  • University of Hamburg, School of Business
  • Leuphana University Lüneburg, Faculty of Economics
  • Werkstatt für Personal- und Organisationsforschung e.V.
  • German Socio-Economic Panel Study (SOEP) at the DIW Berlin

10th International Research Workshop “Methods for PhD”

September 25 – 30, 2016

Empirical research is seeking through methodological processes to discover, hopefully, nontrivial facts and insights. Beside choosing a topic and grounding an idea in theory, empirical research consists of gathering and analysing data as well as presenting results in scientific contexts. Our workshop tackles these steps of your research project:

  • Gathering data via (un)structured interviews or surveys and
  • using the computer for qualitative and quantitative data analysis.

The regular workshop fee is 449 Euro. It covers the participation in three courses, meals and accommodation. The workshop fee is 289 Euro without accommodation (only meals are included).

We are offering up to three funded scholarships to support refugee postgraduate students from Germany. Full details including eligibility criteria and how to apply for a scholarship can be found on the workshop website.

It is possible to get a certificate on 5 credit points (according to the European Credit Transfer System).

The following courses will be offered:

Parallel morning session 1 (26-28 September 2016):

  • Data Analysis with R
  • Data Analysis with Stata
  • Grounded Theory
  • Qualitative Interviewing
  • Developing Theoretical Contributions

Parallel afternoon session 2 (26-28 September 2016):

  • Qualitative Comparative Analysis (QCA)
  • Case Study Research
  • Introduction to the German Socio-Economic Panel Study (SOEP) and Applied Survival Analysis
  • Analyzing Panel and Spatial Data
  • Questionnaire Design

Parallel session at the SDU (30 September 2016):

  • Academic English Writing
  • Computable General Equilibrium (CGE) Modelling and Its Applications to Policy Impact Analysis
  • Introduction to Social Network Analysis
  • Reproducible Research with R and RStudio
  • Analysis of Qualitative Data and Exploratory Statistics

PLEASE note that the number of participants is limited to 20 persons per course! For further information, especially lecturers, program, organizers and registration visit our website: http://www.phd-network.eu/

For any questions don’t hesitate to contact the workshop committee (irwsnetwork@gmail.com).

The International Research Workshop is organised by

  • Prof. Dr. Wenzel Matiaske, Faculty of Economics and Social Sciences, Helmut-Schmidt-University/University of Federal Armed Forces and Research Professor at the German Institute for Economic Research (DIW Berlin)
  • Asst. Prof. Dr. Simon Fietze, University of Southern Denmark, Campus Sønderborg
  • Dr. Heiko Stüber, Institute for Employment Research (IAB), The Research Institute of the Federal Employment Agency in Nuremberg

The workshop is supported by

  • University of Southern Denmark, Department of Entrepreneurship and Relationship Management
  • University of Southern Denmark, Department of Environmental and Business Economics
  • University of Flensburg
  • University of Hamburg, Faculty of Economics and Social Sciences
  • University of Hamburg, School of Business
  • Leuphana University Lüneburg, Faculty of Economics
  • Werkstatt für Personal- und Organisationsforschung e.V.
  • German Socio-Economic Panel Study (SOEP) at the DIW Berlin

Computable General Equilibrium (CGE) Modelling and Its Applications to Policy Impact Analysis

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Hans Kremers (Independent Researcher)

Date: Thursday, 29/09/16 (09:30 – 18:00)

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Computable General Equilibrium (CGE) modelling has become a popular tool for policy impact analysis at many government, policy oriented, and academic institutions such as the EU, economic university departments, or policy assessment institutes such as the ZEW in Mannheim, CPB in The Netherlands. It even looks ’trendy’ to have your own CGE model. During the negotiations between the Greek government and the IWF, EU, and EZB, negotiatiors often call for quantitative assessments of the proposals, which might well be based on an application of the EU’s computable general equilibrium models. CGE models, like many other quantitative economic models are often unjustly considered to be the main culprit of economists supposed to be unaware of a financial crisis in the global finance system before 2008. In this short course, I want to provide more background information on what these models are and how they are applied to policy impact analysis. The course attendants should get some idea on what these models are good for and about their limitations. I refer to existing courses on CGE modelling regularly given by institutes such as GTAP (https://www.gtap.agecon.purdue.edu), ECOMOD (http://ecomod.net), by the Gempack community at the Center of Policy Studies (CoPS) of Victoria University in Melbourne (http://www.copsmodels.com/gempack.htm), and by the GAMS community (http://www.gams.com) among many others. Furthermore, I refer to Shoven and Whalley (1992) and Ginsburgh and Keyzer (1997) as underlying standard literature.

We consider three significant developments in economics during the 20th century that have lead to the rise of CGE modelling within policy impact analysis. CGE models are calibrated on a social accounting matrix, comparable to a much extended input output table. This hence refers to long time developments in input-output modelling pioneered by the Russian economist Wassily Leontief, see Leontief (1936). Parallel to these developments, a mathematical theory of general equilibrium has been developed by well-known economists like Arrow, Debreu, Hahn, using insights from mathematical programming, often related to so-called fixed point proofs and related algorithms to prove the existence and uniqueness of an equilibrium. I refer to the PhD thesis of Gerard Debreu which builds up the general equilibrium model in all its mathematical detail, Debreu (1959), or to Arrow and Hahn (1971). The latter idea points us to the third development in economics, namely in developments of mathematical programming algorithms to compute an economic equilibrium in a general equilibrium model. The work of Herbert Scarf, Scarf and Hansen (1973), was seminal here, and formed the basis from which John Shoven and John Whalley built their CGE models. The introduction of computing equipment provided the means to be able to solve large models efficiently. The morning part of the course in CGE modelling is dedicated to a more detailed description of these three developments in economics and how they cooperate in what we nowadays call CGE modelling. We also describe how we perform a CGE analysis to assess the impact of a policy.

The afternoon is dedicated to introduce several existing CGE models and their applications of CGE modelling. We do so by presenting an existing study on the application of each model. Originally, following the Uruguay trade rounds, CGE models were applied to assess the impact of trade and tax policies until the Kyoto Protocol was signed to support a global effort to curb carbon emissions, which was expected to have significant effects on international trade flows. I again refer to Shoven and Whalley in Shoven and Whalley (1984) and Shoven and Whalley (1992) for applications on trade and taxes. Hence, the application of CGE models was extended to the assessment of climate policies. The GTAP model and underlying Social Accounting Matrix at Purdue University originated as a pure trade CGE model and database following the Uruguay trade rounds, but has, over time been extended to include climate related issues such as economy related carbon emissions, energy substitution, land use. The research, models and data can be found on their website, https://www.gtap.agecon.purdue.edu. To further improve its application on this area, a demand arose to link, among others, CGE models with models from other, climate related areas such as meteorology, into so-called integrated assessment models. The increased attention of policy makers to the climate as well as signals that our current dependency on fossil fuel energy and issues of energy supply security endanger the economy also raised an interest in applying CGE models. Applying a CGE model to assess the impact of climate policies required an extension of the model. Again, a lot on this can be found in the extensive research database at GTAP. There exists an energy substitution variant of the GTAP model, referred to as GTAP-E (see Burniaux and Truong (2002)), which is often applied and extended to such issues as energy substitution, emission permits and carbon taxes, land use.

We also look at applications of CGE modelling to assess the impact of transport policies on the economy following the rise in transport problems such as congestion with the growth of many economies. An example of such transport issues is the inclusion of road pricing to stop congestion around big cities. There is a single country CGE model for Austria that looks at road pricing from a tax point of view. The model is referred to in Steininger and Friedl (2004). In Kalinowska, Kremers, and Truong (2008), we apply this model to the German case.

We will look at the application of a CGE model to a developing economy like Mongolia, where two large mines have been discovered, with a large impact on the local underdeveloped post-communist economy and neighbouring China and Russia. This regional single country CGE model is known as the Mon-CGE model and has been applied to the Mongolian economy to assess the impact of introducing an Energy Master-Plan within a project by the Asian Development Bank (ADB). For a description of the Mon-CGE model, as well as an application of the model to the Mongolian economy, I refer to Corong et al. (2011). Enkhbayar et al. (2010) also provide an interesting application of a regional CGE model to the Mongolian economy, within project based research.

Last but not least, we are currently looking at the construction and application of a regional CGE model to Sønderborg and the Southern Denmark regions within project zero (http://projectzero.dk). This project intends to offer a platform for initiatives in the Sønderborg region to introduce emission reduction measures such as renewable energy technologies into the local and regional economy of Sønderborg.

Attendants of this course are expected to have some background in economics, in particular micro economic theory, although I do not intend to go very deep into economic theory. I would like to ask interested PhDs to send an email to hkremers@icloud.com with a description of their background and what would interest them (models, applications, political issues etc.) in this course.

References

  • Arrow, K., and F. Hahn (1972), General Competitive Analysis, San Francisco, Holden-day.
  • Burniaux, J.M., and T.P. Truong (2002), “GTAP-E: An Energy-Environmental Version of the GTAP Model”, GTAP Technical Paper No. 16, GTAP, Purdue.
  • Corong, E., B. Decaluwé, and V. Robichaud (2011), “Assessing the Impact of Increased Foreign Direct Investment in Mongolia: A Computable General Equilibrium (CGE) Approach”, Mimeo, Asian Development Bank.
  • Debreu, G. (1954), Theory of Value, New-York, Wiley.
  • Enkhbayar, S., D. Roland-Holst, T. Oi, and G. Sugiyarto (2010), “Mongolia’s Investment Priorities from a National Development Perspective”, Mimeo, Asian Development Bank.
  • Ginsburgh, V., and M. Keyzer (1997), The structure of applied general equilibrium models, Cambridge, Massachusetts Institute of Technology Press.
  • Kalinowska, Kremers, and Truong (2004), “Fitting passenger travel into a CGE model”, mimeo, DIW Berlin.
  • Leontief, W. (1936), “Quantitative input and output relations in the economic system of the United States”, Review of Economics and Statistics.
  • Scarf, H., and T. Hansen (1973), The Computation of Economic Equilibria, New Haven, Yale University Press.
  • Shoven, J.B., and J. Whalley (1984), “Applied general equilibrium models of taxation and international trade”, Journal of Economic Literature 22, 1007-1051.
  • Shoven, J.B., and J. Whalley (1992), Applying General Equilibrium, New York, Cambridge University Press.
  • Steininger, K. and B. Friedl (2004, June), “Economic and distributional impacts of nationwide car road pricing: a CGE analysis for Austria”, Paper submitted to the Thirteenth Annual Conference of the European Association of Environmental and Resource Economists, Budapest.

You have to register for the 10th International Research Workshop to participate in this course.

Data Analysis with Stata

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich (GESIS – Leibniz Institute of Social Sciences)

Date: Monday, 26/09/16 – Wednesday, 28/09/16 from 09.00-12.30 h

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Stata is a statistical program package widely used (not only) in the social and economical sciences; it is used for data management, statistical graphics and analysis of quantitative data. Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program and to document these tasks to keep them reproducible.

For Beginners with no or very little Stata knowledge!

Course topics cover:

  • “What You Type is What You Get”: Basic stata Command syntax
  • Getting (and Understanding) Help within stata: stata Bulit-in Help System
  • Basic Data Management: Load and Save stata Datasets, Generate and Manipulate Variables, Describe and Label Data and Variables, Perform Basic uni- and bivariate Analyses, Change the Structure of your Data
  • Basic stata Graphics: Scatterplot, Histogram, Bar Chart
  • Working with “Do-” and “Log-” Files

You have to register for the 10th International Research Workshop to participate in this course.