「Courses, Colloquia & Guest Lectures」

DATE: Monday, 07 to Friday, 11 April 2025;

PLACE: Main courses will be conducted in-person at Feldkirchenstraße 21, 96052, Bamberg. Side events will either be conducted hybrid or on-site. Please find more information below.

TIME: All main courses will be taught between 09.30 a.m. and 01.00 p.m. Find more information on the time of the side events below. 

NUMBER OF PARTICIPANTS: A maximum of 15 participants per main course. Priority will be given to members of BAGSS. In case of free places, priority will be given to members of partner institutions (LIfBi and TRAc). Participation in the side events is open for all members of BAGSS, unless stated otherwise. 

REGISTRATION: Mail to courses.bagss(at)uni-bamberg.de. Registration is mandatory. The number of participants
is limited to 15 for each course. The registration phase ends at 04 February 2025.

For more information, visit the page of BAGSS Internal Methods Institute.

Case Based Research Design

5-day Workshop (7-11 April 2025)

INSTRUCTOR: Professor Dr Derek Beach, Aarhus University

Course outline

This five-day course provides a hands-on introduction to case-based designs, enabling participants to use them in their own research. The course is designed to be relevant for participants from a range of different social science disciplines. A constant theme throughout the course will be on debating the strengths and limitations of different case-based methods, illustrating the types and scopes of inferences that are possible, and how they differ from what variance-based methods enable.

The course will first introduce the foundations of case-based designs in terms of taking cases as the analytical point of departure. The course will distinguish between comparative and within-case designs. Day 2 deals with concepts and theories in case-based designs. After discussing how concept structure is dealt with, we will explore different types of theoretical relationships that are assessed using case-based designs, including necessary and sufficiency, as well as theories of causal processes (aka mechanisms).

Day 3 unpacks different tools for comparative analysis, including more simple comparisons using tools such as Mill’s methods, and most-similar and most-different systems designs. Participants will also be introduced to the basics of Qualitative Comparative Analysis (QCA).

Day 4 deals with within-case analysis, focusing in particular on process-tracing methods. Using a published example, we will discuss how theories about causal processes can be developed and what elements they should include, as well as how process tracing works with empirical evidence.

Day 5 presents the most central case selection principles, including typicality, deviant cases, and theoretical likelihood (most- and least-likely cases). We will then discuss how cross-case comparisons and within-case tracing can be combined in practice.

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Machine Learning for Macroeconomic Modeling

5-day Workshop (7-11 April 2025)

INSTRUCTOR: Dr Tato Khundadze, The New School of Social Research

Course outline

This course aims to provide participants with an in-depth understanding of advanced modeling and control techniques applicable to economic systems. Through a combination of theoretical knowledge and practical case studies, students will explore Nonlinear Model Predictive Control (NMPC), machine learning, and dynamical systems identification. The course will also highlight the application of these concepts to urgent global challenges, including climate change and wealth disparities.

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Multilevel Modeling

5-day Workshop (7-11 April 2025)

INSTRUCTOR: Research Professor Levente Littvay, HUN-REN Centre for Social Sciences

Course outline

Multilevel data structures are all over the social sciences: observations within municipalities, cantons, districts, or countries. Students within schools. Patients within hospitals. Multiple observations taken from the same person or any other unit of analysis. In quantitative studies, relevant predictors appear on all these levels of analysis. But how do we deal with them?

The course is designed to provide scholars with a basic understanding of multilevel (a.k.a. Hierar-chical linear or mixed effects) regression models designed to solve these problems. Special attention is given to the translation of theoretical expectations into statistical models, the interpretation of results in multilevel analyses, and the general use and misuse of multilevel models in the social sciences. While the course is predominantly designed to give you the knowledge of multilevel regres-sion modeling, it does also arm you with the basic tools to run multilevel models in R. (I also have Stata code for most of the models presented thanks to a former teaching assistant, but I am not a Stata user so there you are on your own.) Applications will include models with continuous and limited dependent variables in hierarchical, longitudinal, and cross-classified nesting situations and, if time allows, multilevel structural equation models. The goal of the course is to offer a basic intro-duction and the foundation for participants to start using and critically assessing multilevel models and also have the ability to independently discover and master advanced multilevel statistical topics. Upon completion, the participants will have a basic conceptual understanding of multilevel modeling and its statistical foundations. Participants will be able to critically assess the appropriateness of such techniques in their own and other people’s research and conduct multilevel modeling them-selves to the highest academic standards.

Prerequisites

A solid foundation in linear regression. (Knowing what to click in SPSS and how to copy and paste the table does not constitute a solid foundation. Knowing the assumptions of regression models like homoskedasticity and no autocorrelation does.)

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The Statistics of Causal Inference

5-day Workshop (7-11 April 2025)

INSTRUCTOR: Professor Dr Elias Dinas, European University Institute

Course outline

The objective is to learn how statistical methods can help us to draw causal claims about phenomena of interest. Participants will be introduced into an authoritative framework of causal inference in social sciences, i.e. the potential outcomes framework. By the end of the course, students will be in position to:

1. critically read and evaluate statements about causal relationships based on some analysis of data;

2. apply a variety of design-based easy-to-implement methods that will help them draw causal inferences in their own research.

3. think about archival data under the logic of causal inference. Either explicitly or implicitly, the goal of most empirical research is to interpret causally the co-occurrence of interesting phenomena.

Addressing causality, however, has been notoriously difficult without the luxury of experimental data. This course will introduce you to methods that allow you to make convincing causal claims without working with experimental data. In the first part of the course, we will look at three such designs:

1. Difference-in-Differences estimation;

2. Instrumental Variables and;

3. Regression Discontinuity Design

For every method, the following structure will be employed: first, a running example will provide the motivation and intuition. We will then proceed with the formal identification derivation and finally we will focus on estimation strategies and robustness checks. For each method there will be a hands-on lab section, where we will apply these methods with real data.

We will not have the time to cover two topics, which I would love to talk about: attrition and bounds.

Do ask me about this towards the second part of the course

Derek Beach is

a professor of Political Science at Aarhus University, Denmark, where he does research on research methodology and European integration. He has authored articles, chapters, and books on research methodology, policy evaluation, international negotiations, referendums, and European integration, and co-authored the book Process-tracing Methods: Foundations and Guidelines (2019, 2nd edition, University of Michigan Press).

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Tato Khundadze is 

a political economist currently working as a Teaching and Research Assistant at the New School for Social Research in New York City, where he is pursuing his PhD in Economics. Additionally, he holds the position of Associate Professor of Economics at the Georgian American University in Tbilisi, where he teaches intensive courses in statistical analysis. His research interests include development economics, trade policy and industrial policy.

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Levente Littvay is

a Research Professor (part-time) at the Centre for Social Sciences of the Hungarian Academy of Sciences Centre of Excellence. His research interests include multilevel & structural equation models, populist polarization, in particular the measurement & mitigation of partisan motivated democracy eroding policy preferences, and motivations underlying secessionist attitudes.

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Elias Dinas is 

a professor at the European University Institute and holds the Swiss Chair in Federalism, Democracy and International Governance. He holds a PhD in Political Science from the European University Institute (2010) and his research interests include the dynamics of political socialization, the downstream effects of institutional interventions and the legacy of authoritarian rule on the ideological predispositions of citizens in new democracies. He has also a keen interest in research methodology. 

Coffee Breaks

Coffee and Snacks will be served at the BAGSS kitchen every day, from 07 to 11 April. Please feel free to serve yourselves!

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Welcome Dinner

Monday, 07.04.2025 at 6.00 p.m.

We are pleased to invite all participants to join us for a common Welcome Dinner on Monday, at 06 p.m. at Hofcafé (Austraße 14, 96047 Bamberg). Registration for the Welcome Dinner is mandatory and binding. We will contact all participants to confirm their registration for the welcome dinner and their food choices.

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Meet the Data

THE EUROPEAN SOCIAL SURVEY

Tuesday, 08.04.2025, 2 to 4 p.m. via Zoom and in FG1/00.06 (Stream)

The GESIS team (Leibniz Institute for Social Sciences) will offer an online introduction to the data of the European Social Survey (ESS) as part of the Internal Methods Institute 2025. The European Social Survey is an academically driven cross-national survey that has been conducted across Europe since its establishment in 2001. Every two years, face-to-face interviews are conducted with newly selected, cross-sectional sampes. The participants will be introduced to the content and the data structure of this very extensive survey. We will also broadcast the event in our seminar room FG1/00.06.

Zoom link: TBA

Password: TBA

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BAGSS Semester Colloquium

Interpretation of Statistical Analyses Using Quantities-of-Interest

Wednesday 09.04.2025 at 6 p.m.; Hybrid session via Zoom and at Feldkirchenstraße 21, Room FG1/00.08 (BAGSS).

Invited Speaker: Professor Thomas Gschwend, PhD, University of Mannheim

Thomas Gschwend is Professor for Political Science, Quantitative Methods in the Social Sciences atthe School of Social Sciences and a project directorat the Mannheimer Zentrum für Europäische Sozialforschung. His substantive research focuses onelectoral behavior, public opinion and comparativepolitics.This lecture makes the case that social scientiss should take their model results more seriously by using them to strengthen the substantive implications of their research. Raw regression coefficients, particularly in non-linear models, offer only limited substantive insights at best.

Zoom link:https://uni-bamberg.zoom-x.de/j/63143486739

Password: 8+bFu2

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BAGSS Roundtable

Unofficial Biographies

Thursday 10.04.2025 at 2 p.m.; Room FG1/00.08 (BAGSS).

Have you ever looked at an academic resume and wondered how they managed their career so flawlessly? It is time to look behind the scenes and reveal the real stories behind official CVs. Our course instructors and members of the faculty will share their pitfalls, problems and anecdotes in an informal discussion.

Please send your questions to courses.bagss[at]uni-bamberg.de and we will ask them anonymously to the speakers. Afterwards, you can enjoy a farewell coffee and cake and continue the conversation with your fellow students and instructors.

Panel:

TBA

Moderation:

TBA