Universität Wien

210102 SE M5: European Political Economy An Integrated, Hands-on Approach Using R (2024W)

9.00 ECTS (2.00 SWS), SPL 21 - Politikwissenschaft
Continuous assessment of course work

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Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes

Please note that we have a 5-hour block session scheduled on November 8th, from 13:15 to 18:15, in Hörsaal 3 (H3), NIG 2nd floor, room D0212. There will be an optional joint dinner afterwards. This session is mandatory and crucial as it provides a fundamental, beginner-friendly introduction to R. To accommodate this extended session, three of the regular weekly sessions during the semester will be cancelled.

DO 10.10.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 17.10.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 24.10.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
FR 08.11.2024 13.15-18.15 Hörsaal 3 (H3), NIG 2. Stock (Bestätigt)
DO 14.11.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 21.11.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 28.11.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 05.12.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 12.12.2024 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 16.01.2025 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 23.01.2025 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)
DO 30.01.2025 13.15-14.45 Hörsaal 2 (H2), NIG 2.Stock (Bestätigt)


Information

Aims, contents and method of the course

This course offers an *integrated* and *hands-on* introduction to European Political Economy (EPE) *and* `R` - no prior knowledge of either is required. EPE is a subfield of political science at the intersection of comparative and international political economy and European Union studies. `R` is a free and open-source programming language for statistical computing and graphics. The point behind teaching both in one course is to allow students to get the best of both worlds. On the one hand, they will get a good sense for how to actually do European political economy research: how to get data, how to bring them in the right shape, how to visualize them, and how to analyze them in basic ways. On the other hand, students will get a practical but also substantively interesting introduction to `R`. After basic introductions to both EPE and `R`, we will have 2 substantive blocks on the political economy of climate change and economic security respectively. In both blocks, we will first read general political economy scholarship, then discuss related work on the EU specifically, and finally, in third session, try to redo some of analyses in the papers in `R` or learn about new things in `R` using similar data or approaches. The goal is not full replication, but learning, *in principle*, how to get EPE data, transform them, and use them to address substantively important questions. The course concludes with a basic introduction to `Quarto` which helps prepare students for writing their final papers.

The course aims to equip students with basic knowledge of EPE and `R`. At the end of the course, students should be able to

- describe and summarize key arguments and debates in EPE;

- understand basic concepts of data science and their implementation in the `R` tidyverse;

- critically assess key arguments from the substantive areas of EPE research covered in the course;

- apply insights from EPE and basic knowledge of `R` operations to develop and start answering research questions of their own.

Assessment and permitted materials

Students are required to attend classes and come prepared. Three assignments will make up their final grade (there will be no student presentations). The first assignment needs to be done by every student themselves, whereas the second and third assignment can also be done in groups of two.

- The first assignment consists of two in-depth response papers on two of the three main substantive sessions (week 3, week 5, week 8). These reflection papers should be between 600 and 800 words and will make up *20%* of the overall grade. These response papers are not meant to be summaries of the texts. Instead, students should reflect on how the theories, arguments, or approaches discussed in the readings could inform their own final term paper.

- The second assignment consists of 3 short and basic coding tasks that requires students to import, transform, and visualize data related to the various substantive areas we cover. This, too, will make up *20%* of their overall grade. Assignments will be administered through Posit Cloud (formerly RStudio Cloud).

- The third assignment will be a final research paper that independently develops a EPE-related research questions and *starts* elaborating and answering it with data. Elaborating means that students use `R` to set up an empirical puzzle or potentially interesting question (e.g. by showing an interesting correlation or descriptive statistics). Answering means using visualization, descriptive analysis, or basic inferential statistics to sketch an answer or possible ways of going about answering the question more systematically. The emphasis here is less on having a fully-fledged, well-polished final paper than on demonstrating that you have understood how one would could, in principle, go about developing, theoretically grounding, and answering a EPE-related research question. Ideally, you can build on your reflection papers and coding experience from the first two assignments; and perhaps you can even build on your research paper in your M.A. thesis. This final research paper will make up *60%* of your overall grade. It is meant to be between 4000-5000 words long (if you decide to write the paper with a fellow student, it should be between 7500-9000 words long). The deadline for the paper will be **Wednesday, Feb 19, 2025**.

Minimum requirements and assessment criteria

You need to submit all the required assignments to pass the course. However, in exceptional circumstances, alternative assignments may be permitted as a substitute. Your final grade will be a weighted average of the above-described assignments. The grading scale used ranges from 0-100 points (used for all assignments). A passing grade requires you to obtain an weighted average of 61 points or higher. The grading scale translated into the university grading scale as follows:

- **91-100** = 1 (*very good*)
- **81-90** = 2 (*good*)
- **71-80** = 3 (*satisfactory*)
- **61-70** = 4 (*sufficient*)
- **< 61** = 5 (*not sufficient*)

Examination topics

see syllabus

Reading list

see syllabus

Association in the course directory

Last modified: Mo 30.09.2024 18:26