This course on qualitative and quantitative research methods will provide a general introduction about 1) methodological underpinnings of research methods 2) research designs 3) different forms of methods and field analysis 4) modelling and simulation and finally about 5) the combination of quantitative and qualitative approaches. The course focuses on differences and similarities in both methods. Moreover, we discuss quality assessment and possibilities of potential synthesis among different approaches in a fruitful manner.

On the one hand, students will get introduced into contemporary discourses on methods by carrying out and presenting literature reviews. On the other hand, they will experiment with some basic examples from field analysis and modelling/simulation (Computational Social Science), thereby building foundational knowledge for a further applied deepening in the winter term.

After successful completion of this introduction, studentswill be able to:

• understand different research methods and strategies

• know how to draft various tools for empirical analysis

• differentiate between a variety of top-down and bottom-upmodelling techniques in economics

• acquire basic programming skills for agent-based modelling

• work with a simulation tool-kit and generate computationalexperiments with given models

• write a criticalreflection on quantitative and qualitative methods

80% attendance of the class is required! If you miss a class, please inform us in advance!

prepare the literature for discussions in class

• actively participate in assignments in class (hands-onexercises)

• analyse + interpret given models and simulations

• conduct simulation experiments with given models

• basic hands-on programming exercises

• submit an individual seminar paper

80% attendance of theclass is required! If you miss a class, please inform us in advance!

Grading:

• Class participation (30%)

• Oral presentation (30%)

• Individual seminar paper reflecting on different methods (40%)

SEEP courses do not allow creation of assignments, exam answers or other assessed work using generative AI (e.g. ChatGPT).  All such work is expected to be the original work by the student concerned and is assessed as such.  Work copied from a generative AI source is equivalent to plagiarism and will be treated as such.

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Barbara.Haas@wu.ac.at

Manuel.scholz-waeckerle@wu.ac.at