Doctoral theses supervised by professors in the department of Sociology will be discussed.
Crafting Social Science Research, Literature Review
The goal of this course is to provide support and crucial feedback on writing students' dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis.
You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?
Nota bene: Further meeting dates will be determined during the first session.
Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.
Workshop | |||||||
further dates tbd | 14.02.23 | Tuesday | 10:15 – 11:45 | Zoom | Link | ||
Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.
Course requirements & assessment
Active participation, term paper (graded)
Workshop | |||||||
biweekly | 17.02.23 – 31.03.23 | Friday | 13:45 – 17:00 | 211 in B6, 30–32 | |||
biweekly | 21.04.23 – 02.06.23 | Friday | 13:45 – 17:00 | 211 in B6, 30–32 | |||
Participation is mandatory for first to third year CDSS Sociology students. Participation is recommended for later CDSS doctoral candidates, but to no credit.
The goal of this course is to provide support and crucial feedback for CDSS doctoral candidates in sociology on their ongoing dissertation project. In this workshop CDSS students are expected to play two roles. They should provide feedback to their peers as well as present their own work in order to receive feedback.
The workshop takes place on Wednesdays from 3.30 to 4.30pm on the following days:
March 15, 22, 29
April 26
May 3, 10, 17, 24
Workshop | |||||||
irregular, see course description | 15.03.23 – 24.05.23 | Wednesday | 15:30 – 16:30 | 209 in B6, 30–32 | |||
CDSS doctoral students in political science and sociology can choose freely which weekly colloquium to attend. Colloquia must be attended regularly in year two and three of doctoral studies.
Please choose from
MZES A Colloquium “European Societies and their Integration”
MZES Colloquium B “European Political Systems and their Integration”
Please refer to the MZES webpages for all further details. The talk announcements will be communicated via the CDSS mailing list as well.
Alternatively you can attend the Mannheim Research Colloquium on Survey Methods (MaRCS), which will be announced through the Faculty of Social Sciences mailing list.
CSSR, Literature Review
The goal of this course is to provide guidance and constructive feedback on writing academic papers in English. Each session will guide students through techniques for writing and/
Workshop | |||||||
16.02.23 – 01.06.23 | Thursday | 12:00 – 13:30 | A 103 in B6, 23–25 | Link | |||
CDSS doctoral students have privileged access to the GESIS Summer School in Survey Methodology as well as GESIS workshops are exempt from course fees*.
Contact the Center Manager before registering for any of the courses and only thereafter register directly through the GESIS web page making sure to mention that you are a CDSS doctoral student.
The GESIS summer school takes place in Cologne from 2 to 25 August. Detailed information about the summer school program is available on the GESIS website.
*According to the provisions stated in §3 (5) of the GESIS CDSS cooperative treaty.
Knowledge of Multivariate Analysis
The goal of this course is to provide an introduction into maximum-likelihood estimation.
Students who wish to pass this course must complete homework assignments and produce a research paper. Participation in the tutorial session (2 ECTS) is mandatory for the assignments which complement the lecture (6 ECTS).
Literature
Course requirements & assessment
Homework assignements, research paper (all graded)
Tutorial
The tutorial accompanies the course “Advanced Quantitative Methods” in Political Science. The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected.
Lecture | |||||||
15.02.23 – 31.05.23 | Wednesday | 08:30 – 10:00 | B 244 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
Oliver Rittmann | 16.02.23 – 01.06.23 | Thursday | 10:15 – 11:45 | tbc | |||
Domantas Undzenas | 16.02.23 – 01.06.23 | Thursday | 15:30 – 17:00 | A102 in B6 23-25 | |||
Tbc
Course requirements & assessment
Seminar | |||||||
15.02.23 – 31.05.23 | Wednesday | 15:30 – 17:00 | A 102 in B6, 23–25 |
Experimental research designs are called the silver bullet or ‘Königsweg’ for causal identification. In recent years, the growing interest in causal identification and mechanism testing made experimental designs a regular empirical research tool in the social sciences – most recently in political science and sociology. This seminar shall give a broad overview of the range of experimental methods such as survey, field, lab-in-the-field, and laboratory experiments. We will discuss classical and recent work, including shortcomings and best practices like transparency (open science) and ethical considerations in experimental research methods. In addition, students will learn to think critically about different (experimental) research designs and design their own experiment to answer a research question they have developed.
Course requirements & assement
Weekly preparation of two discussion-questions, one presentation (allocated text(s), discussion preparation), active participation in seminar, presentation of the Exposé of the seminar paper (graded (incl. peer-feedback)), research design seminar paper (graded)
Seminar | |||||||
18.04.23 – 30.05.23 | Tuesday | 08:30 – 11:45 | C 116 in A5, 6 entrance C | Link |
Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of survey design. The course covers the major steps of implementing and conducting a survey and design decisions at each step. In addition, sources of error at each step are discussed. For illustration purposes and exercise, the course will draw on well-known large-scale surveys such as the German General Survey (ALLBUS), European Social Survey (ESS), European Values Study (EVS), and the German Socio-economic Panel (SOEP).
Course requirements & assessment
Active participation, homework assignments/
Seminar | |||||||
16.02.23 – 01.06.23 | Thursday | 13:45 – 15:15 | tbc |
In addition to a thorough understanding of the substantive field you are studying you need firm methodological and statistical knowledge in order to successfully conduct quantitative social research. This seminar will give you the opportunity to apply and expand your knowledge of social research by replicating published research findings.
The research that we are going to replicate was conducted with data from publicly available survey data like the European Social Survey (ESS), the International Social Survey Programme (ISSP) or the European Values Study (EVS). Data from surveys like these have several advantages: the surveys follow a repeated cross-section design, a research design particularly well suited to study social change; they are comparative surveys allowing you to compare data cross-nationally on a broad range of topics; the surveys follow rigorous methodological standards and, finally, data are available at no cost and can be downloaded from the web.
Replicating published research has the advantage that you are able to check your results against existing results. By trying to replicate previous research you learn where the original researcher has made tacit decisions not documented in the paper (e.g. defining the analysis sample, coding of variables, treatment of missing values). Replicating social research also trains you to judge the validity of research results.
In addition to these primarily pedagogical aspects replicating research is important from an epistemological point of view as well. Through replication of research by independent research groups biases in previous work can be discovered and findings can be validated (see Hendrick 1991, King 1995).
Course requirements & assessment
-Active participation
-Participants should choose a published paper and try to replicate the findings reported in it using the same data. The results to be replicated often will be given in a table containing the outcome of a multivariate model. Please document each step in your attempt to replicate the findings, report and explain the decisions you had to make during data preparation and data analysis. If you fail to replicate the results please indicate possible explanations. Your paper should not exceed 5,000 words; please add your documented syntax in the appendix.
Papers should be delivered in electronic form no later than July 31, 2023.
Seminar | |||||||
biweekly | 17.02.23 – 31.03.23 | Friday | 10:15 – 13:30 | C 108 in A5, 6 entrance C | Link | ||
biweekly | 12.05.23 – 26.05.23 | Friday | 10:15 – 13:30 | C 108 in A5, 6 entrance C | |||
02.06.23 | Friday | 10:15 – 13:30 | C 108 in A5, 6 entrance C |
Some basic knowledge of statistical inference and R is required
Lecture
The course provides a broad overview of methods used in longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-section data, using measurements of the same individuals taken repeatedly through time can lead to better causal inferences in some cases, and can also give the possibility to learn more about the dynamics of individual behavior. The first objective of this course is to discuss the advantages of panel data, and the characteristics of the structure of panel data. Then, the course will give an overview of the main models (pooled OLS, fixed effects, random effects, first-differences) and provide the tools to choose betwen these models. The course will also discuss panel generalized linear models. Finally, an overview of event history analysis will be presented.
Tutorial
Using R, we apply methods of longitudinal data analysis (presented in the lecture “Longitudinal Data Analysis”) to real survey data.
The course will be taught by Dr. Danielle Martin
Course requirements & assessment
Lecture – Three quizzes (two must be a pass), regular attendance, written examination (graded, closed-book)
Tutorial – compulsory attendance, twelve homework assignments of which nine must be passed
Lecture | |||||||
13.02.23 – 22.05.23 | Monday | 10:15 – 11:45 | B317 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
14.02.23 – 30.05.23 | Tuesday | 12:00 – 13:30 | B 318 in A5, 6 entrance B | Link | |||
14.02.23 – 30.05.23 | Tuesday | 15:30 – 17:00 | A 102 in B6, 23–25 | Link | |||
Please register for the course program via the online registration tool between 01 and 19 February 2023. You can request the respective link from Annette Förster (foerster@smip.uni-mannheim.de).
Some programming skills (Python, R, JAVA, C, HTML, BASH, etc.) OR the motivation to learn some python (and some other languages) on your own.
**Requirement: Students should bring their own laptop (on which you can also install programmes, not just apps).**
This course is intended to show you all the major steps involved in completing a statistical analysis within the fields of exploratory data analysis and data science.
This seminar is divided into 3 parts:
First, we will go through the basics of Python and the most important libraries for data science with excursuses into “programming paradigms” and “big data”.
Second, we will learn data exploration, data visualisation and statistical modelling with python.
Third, we will go through the basics of machine learning (supervised, unsupervised and semi-supervised) and neural networks with excususes into the fields of “computer vision”, “computer linguistics” and “AI”.
And finally, we will apply all of this to real-world projects.
For this course, I’ve chosen several different statistical problems to be solved with regression and classification in python.
Course requirements & assessment
Coding-homework, Data analysis project written in python including data transformation, visualisation and analysis (graded)
Seminar | |||||||
biweekly | 24.02.23 – 24.03.23 | Friday | 08:30 – 13:30 | C 112 in A5, 6 entrance C | |||
biweekly | 21.04.23 – 02.06.23 | Friday | 08:30 – 13:30 | tbc |
The reading course is aimed at Ph.D. students in or beyond their second year to support them during their research phase. 1st year PhD students are welcomed to attend the class as well.
Recommended: Knowledge of basic statistics and prior experience with R or Stata is helpful, but not necessary.
This reading course provides a hands-on and paper-based approach to understanding and analyzing data. For many projects, collection of new data or experimental designs are the only way to answer a research question or to provide the decisive complementary evidence. Different ways to collect data can have important implications for model estimation and evaluation, parameter inference, and policy conclusions. Standard econometric methods start from assumptions about the sampling procedure and try to cope with the limitations of a given dataset. Instead, we start at the design stage and examine the interplay between sampling and experimental methods, statistical inference and estimation of causal effects. We will use the German Business Panel as point in case and implement cutting-edge methods to gain insights into the causal mechanisms behind reported outcomes. In each session, one of the participants will present a research paper, which we will discuss in light of concrete implementation at trial scale. Participants are encouraged to present research that is valuable for their own thesis or may be assigned to present a topic.
In addition to presenting a paper and participating in the discussion, students are expected to write a short technical report that summarizes the methods and implications in a way useful for peers who want to use the newly collected data or learn about experimental results.
Learning outcomes:
The specific applications cover a broad set of skills with a focus on design of questionnaires and survey experiments, data analysis and quantitative methods, classification, inference, writing of own reports, and opportunities for own research.
Form of assessment: Paper (technical report) (optional), Presentation (50 %), Class Participation (50 %)
The course is also part of the TRR 266 Accounting for Transparency
Lecture | |||||||
Lecture | 14.02.23 – 30.05.23 | Tuesday | 10:15 – 11:45 | B 144, A5, 6 – B | |||
The course will assume that participants have a background in core graduate‐level finance. The course will cover topics from a variety of subfields in finance (asset pricing, financial intermediation, household finance, corporate finance). The introductory block of three classes is intended to orient students to the science of climate change as well as to refresh key concepts from economics and finance; the remaining classes will dive into detail on current research in different subfield. We will conclude with a discussion of open topics in this field. We expect that the course will be useful to doctoral students in finance, economics, and accounting. As a global class, we will largely be on Zoom. Beyond weekly preparation and participation, students will be expected to write a paper either laying out a potential research topic or synthesizing a set of related papers that were not discussed in class.
The purpose of the course is to (a) introduce graduate students to questions and methods in the rapidly evolving fields of climate/
Addressing climate change demands changes in natural, social, and economic systems and will require greater collaboration. In that spirit, this course is being offered by a team of professors from different schools and universities across the globe. Each instructor will deliver one or more lectures and there will be students from a number of different schools. Our teaching group consists of current and former AFA and EFA presidents and some of the leading climate finance scholars, including Laura Starks (current AFA President), Patrick Bolton (former AFA President), Stefano Giglio, Marcin Kacperczyk (former EFA President), Caroline Flammer, Geoff Heal, Stefan Reichelstein, Ben Caldecott and Peter Tufano.
Assessment
Beyond weekly preparation and participation, students will be expected to write a paper either laying out a potential research topic or synthesizing a set of papers related to Climate Change and Sustainability that were not discussed in class.
This course starts early (January 24), please make sure to register until December 20, 2022!
Lecture | |||||||
Lecture | 24.01.23 – 11.04.23 | Tuesday | 17:00 – 19:00 | online (Zoom) | |||
We live in interesting times both, economically and politically. Many observers point to crises and uncertain developments in the economic and political world. Making sense of the nature of these challenges and pointing toward economic and political solutions for the future requires new perspectives. This is a course about the big and bold questions in economics and politics. How can or should economics and politics be organized to best serve society? What does it mean to put humans as they really are at the center of economic and political thinking? What role do morals and values, or dignity and respect, play for the way economics and politics work? What are the implications of digitalization for capitalism and freedom?
We will try to come to grips with these questions by reading and discussing four key books on various new perspectives at the intersection between economics and politics. The aim of this course is to go as deep as we can and to get as much out of an in-class discussion of the material as possible. Willingness to acquire and read the books is a must. If you are unsure about whether or not you would want to take on the commitment of reading four books in one semester then this course is probably not the right one for you.
Students need to be willing to read books, form their own opinions on them, and elaborate on and defend their own views in group discussions and a final essay.
Required Readings
Friedman, M. (1963). Capitalism and Freedom. University of Chicago Press.
Greene, J. (2015). Moral Tribes. Atlantic Books.
Sandel, M. J. (2020). The Tyranny of Merit: What’s Become of the Common Good?. Penguin UK.
Zuboff, S. (2016). The Age of Surveillance Capitalism. PublicAffairs.
Seminar | |||||||
24.02.23 – 24.02.23 | Friday | 13:45 – 15:15 | D002 in B6, 27–29 | ||||
21.04.23 – 02.06.23 | Friday | 10:15 – 13:30 | D002 in B6, 27–29 |
This course is exclusively geared towards students who are currently doctoral students at the GESS of the University of Mannheim. It is intended for beginning as well as advanced doctoral students. This course is an elective course and counts as a 'Bridge Course'. Maximum number of participants is 15. If the course is not fully booked, non-GESS students from Business, Economics, or the Social Sciences or from other related disciplines can enroll. As a necessary requirement you need to make a working paper draft available to all of us that you present in our ‘Mini Research Day’.
This course will introduce students to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS. This year, the course will be given by one senior researchers from each center of the GESS, i.e., you will have the unique opportunity to receive truly interdisciplinary feedback on your work from three different angles.
The course consists of four core building blocks:
1. Kick-Off & Introductory Session: What is interdisciplinary research.
After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by the instructors, each participant will shortly (max 5 min, 2–3 slides per person) present the core idea of an interdisciplinary paper published in a top journal in her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is. Alternatively, you can also present a dataset or a methodology and highlight how students from other GESS centers might take advantage of it.
2. Mini-Research-Day
The second component of the course is a ‘Mini-Research-Day’ which is intended to introduce the kind of topics you are working on to other course participants. You will give a presentation on a current working paper or research project of yours and you will discuss a paper/
3. Science Speed Dating
The science speed dating event – organized by your student representatives – involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a student from another field (preferably from our course).
4. Project Presentations & Writeups
This proposal will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. Each research team will also prepare a short write-up of their proposal (max. 5 pages, incl. references) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in two weeks after the presentation. Moreover, you will also discuss another team project.
Objectives
Upon successful completion of this course, students will
Assessment
This is a pass/
Please register by the registration deadline given below, by sending a title and an abstract of the research project/
Please note that the course is limited to a maximum of 15 participants, and seats will be allocated on a first come first served basis.
Course dates
Upon successful completion of this course, students will
Interested in learning about Open Science, reproducibility, and transparency in research and all things related to research data management? Then don’t wait, join our Research Skills Seminar Series and learn the skills needed to create an optimised and transparent research workflow that is embedded in Open Science and facilitates research data management. From conceptual issues like the replication crisis, to learning skills like pre-registration and wrangling data in R, this seminar series has got you covered and is here to support you.
Digital transformations in companies, in sectors of the economy, in the labor force, and in the world of work in general are one of the most fundamental societal transformations in contemporary history. Digital transformations of work and beyond shape our daily lives and might trigger fundamental challenges to the organization of work and beyond. How do we conceptualize these digital transformations? Are these rather social or rather technical transformations? What are the main characteristics of these transformations? How does digitalization permeate the world of work? Is it a perpetuating process? How can we measure digital transformations? What are the drivers of digital transformations? And what are the consequences for individuals and families? The seminar will address these questions and offers conceptual and empirical insights in the discussion of the digital transformations of work.
Course requirements & assessment
Regular small assignments (developing research questions based on the readings, short presentations); compulsory attendance; participating in active discussion.
Written term paper (graded, max. 5000 words), deadline: July 31, 2023
Seminar | |||||||
biweekly | 15.02.23 – 29.03.23 | Wednesday | 08:30 – 11:45 | tbc | Link | ||
biweekly | 19.04.23 – 03.05.23 | Wednesday | 08:30 – 11:45 | tbc | |||
24.05.23 | Wednesday | 08:30 – 11:45 | tbc |
Field experiments are powerful tools for investigating causal claims about social phenomenon in real-life contexts. This block seminar will provide students with a practice-based introduction to field experiments. While we cover the logic behind experimentation and the potential outcomes framework, the heart of the course will focus around analyzing examples of actual experimental designs. In this way, students will gain hands-on experience in navigating the myriad issues that may arise when conducting, analyzing, and interpreting field experiments. Students will also have the opportunity to obtain feedback on their own experimental research projects.
The seminar will be taught by Nan Zhang, PhD
Course requirements & assessment
Oral participation, homework, presentations, compulsory attendance
Term paper (graded, 5000 words)
Seminar | |||||||
biweekly | 02.03.23 – 30.03.23 | Thursday | 10:15 – 13:30 | tbc | Link | ||
biweekly | 20.04.23 – 01.06.23 | Thursday | 10:15 – 13:30 | tbc |
In the age of increasing migration and the raise of right-wing populist parties the question of how to measure and explain xenophobic and populist attitudes becomes very important. While xenophobia has already been investigated for a long time, even if it still constitutes a controversial issue how to measure it, research on populist attitudes has started only very recently. In this seminar current and innovative approaches as well as ideas for further developments will be discussed. Moreover, existing studies will be replicated to explore them more deeply.
Course requirements & assessment
Participation, weekly reading, presentation of an empirical study, term paper (graded)
Seminar | |||||||
15.02.23 – 31.05.23 | Wednesday | 10:15 – 11:45 | B 317 in A5, 6 entrance B | Link |
What explains the rise of the Medici in 15th century Florence? Why did thousands of women join the guerilla war in 1980s El Salvador? What can online book co-purchases tell us about ideological differences between Republicans and Democrats in contemporary America? These are some of the questions we will grapple with as we explore how social scientists have applied network analysis to the study of politics.
The course is designed as a general introduction to social network analysis, but it focuses heavily on examples from political sociology (and adjacent fields) as one area in which network theories and methodologies have had a great influence. We will treat network analysis both as a theoretical approach that regards relations as the basic building blocks of social life, and as a methodological toolkit for visualizing and analyzing the structure of relations. Many of these methods involve the quantitative measurement of network structures (e.g., the degree to which networks are clustered) and different positions within the network (e.g., central vs. peripheral actors). The course is organized around a set of key concepts and theoretical insights in network analysis – such as weak ties, brokerage, and diffusion – which we will apply to a variety of substantive issues ranging from recruitment into social movements to the emergence of new political identities to the nature of political action.
The best way to learn about social networks is to work with them, which is why the class has a large practical component. After developing the theoretical foundations in class discussions, students will learn how to analyze networks in a series of practical assignments. The final project will give students an opportunity to follow their own curiosity and apply the analytical tools introduced in class to an empirical context of their choosing.
This course will be taught by Benjamin Rohr
Course requirements & assessment
Regular & active participation, formulation of questions/
Seminar | |||||||
13.02.23 – 22.05.23 | Monday | 13:45 – 15:15 | C 217 in A5, 6 entrance C |
What makes people healthy or ill? Individual health is surely shaped by individual decisions regarding lifestyle or use of healthcare. However, the systematic social inequalities in health are large and persist over time. People's social position plays a fundamental role in shaping their health. The characteristics of the society as a whole are likely important too. This course offers an introduction to the health consequences of people’s social position and social circumstances.This 3-part course introduces students to selected topics in health sociology.
The first part discusses key notions of health sociology and the role of social factors in the historical development of population health.
In the second part, we tackle the topic of individual factors associated with health inequalities. We begin by reviewing the role of socioeconomic status and education and discuss the empirical patterns in light of the selection vs. social causation hypothesis. Subsequently, we address the role of gender, work, and migration in creating and sustaining health differences.
In the third part, the course shifts the focus to the macro determinants of health. We begin by reviewing the discussion on income inequalities and health and address the role of gender inequality. To address the underlying mechanisms, we look at the role of perceived (vs. objective) inequality. Subsequently, we discuss the role of social capital, and the role played by policies.
The course will be taught be Malgorzata Mikucka, PhD
Course requirements and assessment
Students are required to attend all classes (two absences will be excused). Credits will be granted for active participation, an oral presentation, and a paper on one of the themes of the seminar. Final paper (graded, 4,000–4,500 words) Submission deadline 12 June 2023
Seminar | |||||||
15.02.23 – 31.05.23 | Wednesday | 13:45 – 15:15 | A 103 in B6, 23–25 | Link |
Doctoral theses supervised by professors in the department of Political Science will be discussed.
Please check with individual chairs for dates and times.
Crafting Social Science Research, Literature Review
The goal of this course is to provide support and crucial feedback on writing students' dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis.
You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?
Nota bene: Further meeting dates will be determined during the first session.
Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.
Workshop | |||||||
further dates tbd | 14.02.23 | Tuesday | 10:15 – 11:45 | Zoom | Link | ||
Knowledge of Multivariate Analysis
The goal of this course is to provide an introduction into maximum-likelihood estimation.
Students who wish to pass this course must complete homework assignments and produce a research paper. Participation in the tutorial session (2 ECTS) is mandatory for the assignments which complement the lecture (6 ECTS).
Literature
Course requirements & assessment
Homework assignements, research paper (all graded)
Tutorial
The tutorial accompanies the course “Advanced Quantitative Methods” in Political Science. The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected.
Lecture | |||||||
15.02.23 – 31.05.23 | Wednesday | 08:30 – 10:00 | B 244 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
Oliver Rittmann | 16.02.23 – 01.06.23 | Thursday | 10:15 – 11:45 | tbc | |||
Domantas Undzenas | 16.02.23 – 01.06.23 | Thursday | 15:30 – 17:00 | A 102, in B6, 23–25 | |||
Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.
Course requirements & assessment
Active participation, term paper (graded)
Workshop | |||||||
biweekly | 17.02.23 – 31.03.23 | Friday | 13:45 – 17:00 | 211 in B6, 30–32 | |||
biweekly | 21.04.23 – 02.06.23 | Friday | 13:45 – 17:00 | 211 in B6, 30–32 | |||
Participation is mandatory for first to third year CDSS students of Political Science. Participation is recommended for later CDSS PhD candidates, but to no credit.
Other young researchers in the social sciences affiliated with the University of Mannheim (incl. MZES) are also invited to attend the talks.
The goal of this course is to provide support and crucial feedback for CDSS doctoral students on their ongoing dissertation project. In this workshop they are expected to play two roles – provide feedback to their peers as well as present their own work in order to receive feedback.
In order to receive useful feedback, participants are asked to circulate their paper and two related published pieces of research one week before the talk.
Workshop | |||||||
13.02.23 – 22.05.23 | Monday | 15:30 – 17:00 | 211 in B6, 30–32 | ||||
CDSS doctoral students in political science and sociology can choose freely which weekly colloquium to attend. Colloquia must be attended regularly in year two and three of doctoral studies.
Please choose from
MZES A Colloquium “European Societies and their Integration”
MZES Colloquium B “European Political Systems and their Integration”
Please refer to the MZES webpages for all further details. The talk announcements will be communicated via the CDSS mailing list as well.
Alternatively you can attend the Mannheim Research Colloquium on Survey Methods (MaRCS), which will be announced through the Faculty of Social Sciences mailing list.
CSSR, Literature Review
The goal of this course is to provide guidance and constructive feedback on writing academic papers in English. Each session will guide students through techniques for writing and/
Workshop | |||||||
16.02.23 – 01.06.23 | Thursday | 12:00 – 13:30 | A 103 in B6, 23–25 | Link | |||
CDSS doctoral students have privileged access to the GESIS Summer School in Survey Methodology as well as GESIS workshops are exempt from course fees*.
Contact the Center Manager before registering for any of the courses and only thereafter register directly through the GESIS web page making sure to mention that you are a CDSS doctoral student.
The GESIS summer school takes place in Cologne from 2 to 25 August. Detailed information about the summer school program is available on the GESIS website.
*According to the provisions stated in §3 (5) of the GESIS CDSS cooperative treaty.
Tbc
Course requirements & assessment
Seminar | |||||||
15.02.23 – 31.05.23 | Wednesday | 15:30 – 17:00 | A 102 in B6, 23–25 |
Experimental research designs are called the silver bullet or ‘Königsweg’ for causal identification. In recent years, the growing interest in causal identification and mechanism testing made experimental designs a regular empirical research tool in the social sciences – most recently in political science and sociology. This seminar shall give a broad overview of the range of experimental methods such as survey, field, lab-in-the-field, and laboratory experiments. We will discuss classical and recent work, including shortcomings and best practices like transparency (open science) and ethical considerations in experimental research methods. In addition, students will learn to think critically about different (experimental) research designs and design their own experiment to answer a research question they have developed.
Course requirements & assement
Weekly preparation of two discussion-questions, one presentation (allocated text(s), discussion preparation), active participation in seminar, presentation of the Exposé of the seminar paper (graded (incl. peer-feedback)), research design seminar paper (graded)
Seminar | |||||||
18.04.23 – 30.05.23 | Tuesday | 08:30 – 11:45 | C 116 in A5, 6 entrance C | Link |
Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of survey design. The course covers the major steps of implementing and conducting a survey and design decisions at each step. In addition, sources of error at each step are discussed. For illustration purposes and exercise, the course will draw on well-known large-scale surveys such as the German General Survey (ALLBUS), European Social Survey (ESS), European Values Study (EVS), and the German Socio-economic Panel (SOEP).
Course requirements & assessment
Active participation, homework assignments/
Seminar | |||||||
16.02.23 – 01.06.23 | Thursday | 13:45 – 15:15 | tbc |
Some basic knowledge of statistical inference and R is required
Lecture
The course provides a broad overview of methods used in longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-section data, using measurements of the same individuals taken repeatedly through time can lead to better causal inferences in some cases, and can also give the possibility to learn more about the dynamics of individual behavior. The first objective of this course is to discuss the advantages of panel data, and the characteristics of the structure of panel data. Then, the course will give an overview of the main models (pooled OLS, fixed effects, random effects, first-differences) and provide the tools to choose betwen these models. The course will also discuss panel generalized linear models. Finally, an overview of event history analysis will be presented.
Tutorial
Using R, we apply methods of longitudinal data analysis (presented in the lecture “Longitudinal Data Analysis”) to real survey data.
The course will be taught by Dr. Danielle Martin
Course requirements & assessment
Lecture – Three quizzes (two must be a pass), regular attendance, written examination (graded, closed-book)
Tutorial – compulsory attendance, twelve homework assignments of which nine must be passed
Lecture | |||||||
13.02.23 – 22.05.23 | Monday | 10:15 – 11:45 | B317 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
14.02.23 – 30.05.23 | Tuesday | 12:00 – 13:30 | B 318 in A5, 6 entrance B | Link | |||
14.02.23 – 30.05.23 | Tuesday | 15:30 – 17:00 | A 102 in B6, 23–25 | Link | |||
Please register for the course program via the online registration tool between 01 and 19 February 2023. You can request the respective link from Annette Förster (foerster@smip.uni-mannheim.de).
Some programming skills (Python, R, JAVA, C, HTML, BASH, etc.) OR the motivation to learn some python (and some other languages) on your own.
**Requirement: Students should bring their own laptop (on which you can also install programmes, not just apps).**
This course is intended to show you all the major steps involved in completing a statistical analysis within the fields of exploratory data analysis and data science.
This seminar is divided into 3 parts:
First, we will go through the basics of Python and the most important libraries for data science with excursuses into “programming paradigms” and “big data”.
Second, we will learn data exploration, data visualisation and statistical modelling with python.
Third, we will go through the basics of machine learning (supervised, unsupervised and semi-supervised) and neural networks with excususes into the fields of “computer vision”, “computer linguistics” and “AI”.
And finally, we will apply all of this to real-world projects.
For this course, I’ve chosen several different statistical problems to be solved with regression and classification in python.
Course requirements & assessment
Coding-homework, Data analysis project written in python including data transformation, visualisation and analysis (graded)
Seminar | |||||||
biweekly | 24.02.23 – 24.03.23 | Friday | 08:30 – 13:30 | C 112 in A5, 6 entrance C | |||
biweekly | 21.04.23 – 02.06.23 | Friday | 08:30 – 13:30 | tbc |
The reading course is aimed at Ph.D. students in or beyond their second year to support them during their research phase. 1st year PhD students are welcomed to attend the class as well.
Recommended: Knowledge of basic statistics and prior experience with R or Stata is helpful, but not necessary.
This reading course provides a hands-on and paper-based approach to understanding and analyzing data. For many projects, collection of new data or experimental designs are the only way to answer a research question or to provide the decisive complementary evidence. Different ways to collect data can have important implications for model estimation and evaluation, parameter inference, and policy conclusions. Standard econometric methods start from assumptions about the sampling procedure and try to cope with the limitations of a given dataset. Instead, we start at the design stage and examine the interplay between sampling and experimental methods, statistical inference and estimation of causal effects. We will use the German Business Panel as point in case and implement cutting-edge methods to gain insights into the causal mechanisms behind reported outcomes. In each session, one of the participants will present a research paper, which we will discuss in light of concrete implementation at trial scale. Participants are encouraged to present research that is valuable for their own thesis or may be assigned to present a topic.
In addition to presenting a paper and participating in the discussion, students are expected to write a short technical report that summarizes the methods and implications in a way useful for peers who want to use the newly collected data or learn about experimental results.
Learning outcomes:
The specific applications cover a broad set of skills with a focus on design of questionnaires and survey experiments, data analysis and quantitative methods, classification, inference, writing of own reports, and opportunities for own research.
Form of assessment: Paper (technical report) (optional), Presentation (50 %), Class Participation (50 %)
The course is also part of the TRR 266 Accounting for Transparency
Lecture | |||||||
Lecture | 14.02.23 – 30.05.23 | Tuesday | 10:15 – 11:45 | B 144, A5, 6 – B | |||
This lecture offers an introduction to current research topics in the field of International Political Economy (IPE). It examines how international and domestic politics interact with global flows of goods, finance, and people across national borders. After introducing what it means to study IPE in the age of globalization, the course addresses four major themes of current IPE research. We will learn about internationale trade and the chances and challenges that come with the intensifying exchange of goods across the globe. Lectures on international finance will focus on how global financial flows interact with political and economic stability, instability, and crises. We will also focus on international development and will learn about patterns of global economic inequality and development aid. The lecture will also adress the role of international institutions for the globalized economy.
Course requirements & assessment
Active participation, term paper (graded)
Lecture | |||||||
19.04.23 – 31.05.23 | Wednesday | 10:15 – 11:45 | C 217 in A5, 6 entrance C | Link | |||
20.04.23 – 01.06.23 | Thursday | 13:45 – 15:15 | B 243 in A5, 6 entrance B | ||||
Elections are key institutions in democracies and provide opportunities to bring about changes in the partisan balance which, in turn, can affect government policies. This seminar focuses on the analysis of changes in voting behavior at the individual and aggregate level. Thereby, it tackles questions such as how and why such changes occur or not. It will address key concepts and theories, substantive and methodological issues in the field. Students will review empirical studies in the field and prepare research papers in which they analyze specific questions using available data.
Course requirements & assessment
Active participation, oral presentation, regular attendance is recommended
Term paper (graded)
Seminar | |||||||
16.02.23 – 01.06.23 | Thursday | 12:00 – 13:30 | B 318 in A5, 6 entrance B |
In this course, we study economic inequality from a political economy perspective. First, we will discuss various concepts of economic inequality and different ways to measure it. Then, we will investigate general trends in these various forms of economic inequality across the world. Second, we will discuss the scholarly literature on the determinants of economic inequality, focusing on both political and economic factors. In a third section, we will examine the literature on the implications of economic inequality as regards a variety of political and economic outcomes. The methodological focus of this seminar will be on quantative methods for causal inference.
Course requirements & assessment
Active participation, term paper (graded)
Seminar | |||||||
18.04.23 – 30.05.23 | Tuesday | 13:45 – 15:15 | B 143 in A5, 6 entrance B | Link | |||
20.04.23 – 01.06.23 | Thursday | 15:30 – 17:00 | B 143 in A5,6 entrance B |
The course will assume that participants have a background in core graduate‐level finance. The course will cover topics from a variety of subfields in finance (asset pricing, financial intermediation, household finance, corporate finance). The introductory block of three classes is intended to orient students to the science of climate change as well as to refresh key concepts from economics and finance; the remaining classes will dive into detail on current research in different subfield. We will conclude with a discussion of open topics in this field. We expect that the course will be useful to doctoral students in finance, economics, and accounting. As a global class, we will largely be on Zoom. Beyond weekly preparation and participation, students will be expected to write a paper either laying out a potential research topic or synthesizing a set of related papers that were not discussed in class.
The purpose of the course is to (a) introduce graduate students to questions and methods in the rapidly evolving fields of climate/
Addressing climate change demands changes in natural, social, and economic systems and will require greater collaboration. In that spirit, this course is being offered by a team of professors from different schools and universities across the globe. Each instructor will deliver one or more lectures and there will be students from a number of different schools. Our teaching group consists of current and former AFA and EFA presidents and some of the leading climate finance scholars, including Laura Starks (current AFA President), Patrick Bolton (former AFA President), Stefano Giglio, Marcin Kacperczyk (former EFA President), Caroline Flammer, Geoff Heal, Stefan Reichelstein, Ben Caldecott and Peter Tufano.
Assessment
Beyond weekly preparation and participation, students will be expected to write a paper either laying out a potential research topic or synthesizing a set of papers related to Climate Change and Sustainability that were not discussed in class.
This course starts early (January 24), please make sure to register until December 20, 2022!
Lecture | |||||||
Lecture | 24.01.23 – 11.04.23 | Tuesday | 17:00 – 19:00 | online (Zoom) | |||
We live in interesting times both, economically and politically. Many observers point to crises and uncertain developments in the economic and political world. Making sense of the nature of these challenges and pointing toward economic and political solutions for the future requires new perspectives. This is a course about the big and bold questions in economics and politics. How can or should economics and politics be organized to best serve society? What does it mean to put humans as they really are at the center of economic and political thinking? What role do morals and values, or dignity and respect, play for the way economics and politics work? What are the implications of digitalization for capitalism and freedom?
We will try to come to grips with these questions by reading and discussing four key books on various new perspectives at the intersection between economics and politics. The aim of this course is to go as deep as we can and to get as much out of an in-class discussion of the material as possible. Willingness to acquire and read the books is a must. If you are unsure about whether or not you would want to take on the commitment of reading four books in one semester then this course is probably not the right one for you.
Students need to be willing to read books, form their own opinions on them, and elaborate on and defend their own views in group discussions and a final essay.
Required Readings
Friedman, M. (1963). Capitalism and Freedom. University of Chicago Press.
Greene, J. (2015). Moral Tribes. Atlantic Books.
Sandel, M. J. (2020). The Tyranny of Merit: What’s Become of the Common Good?. Penguin UK.
Zuboff, S. (2016). The Age of Surveillance Capitalism. PublicAffairs.
Seminar | |||||||
24.02.23 – 24.02.23 | Friday | 13:45 – 15:15 | D002 in B6, 27–29 | ||||
21.04.23 – 02.06.23 | Friday | 10:15 – 13:30 | D002 in B6, 27–29 |
This course is exclusively geared towards students who are currently doctoral students at the GESS of the University of Mannheim. It is intended for beginning as well as advanced doctoral students. This course is an elective course and counts as a 'Bridge Course'. Maximum number of participants is 15. If the course is not fully booked, non-GESS students from Business, Economics, or the Social Sciences or from other related disciplines can enroll. As a necessary requirement you need to make a working paper draft available to all of us that you present in our ‘Mini Research Day’.
This course will introduce students to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS. This year, the course will be given by one senior researchers from each center of the GESS, i.e., you will have the unique opportunity to receive truly interdisciplinary feedback on your work from three different angles.
The course consists of four core building blocks:
1. Kick-Off & Introductory Session: What is interdisciplinary research.
After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by the instructors, each participant will shortly (max 5 min, 2–3 slides per person) present the core idea of an interdisciplinary paper published in a top journal in her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is. Alternatively, you can also present a dataset or a methodology and highlight how students from other GESS centers might take advantage of it.
2. Mini-Research-Day
The second component of the course is a ‘Mini-Research-Day’ which is intended to introduce the kind of topics you are working on to other course participants. You will give a presentation on a current working paper or research project of yours and you will discuss a paper/
3. Science Speed Dating
The science speed dating event – organized by your student representatives – involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a student from another field (preferably from our course).
4. Project Presentations & Writeups
This proposal will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. Each research team will also prepare a short write-up of their proposal (max. 5 pages, incl. references) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in two weeks after the presentation. Moreover, you will also discuss another team project.
Objectives
Upon successful completion of this course, students will
Assessment
This is a pass/
Please register by the registration deadline given below, by sending a title and an abstract of the research project/
Please note that the course is limited to a maximum of 15 participants, and seats will be allocated on a first come first served basis.
Course dates
Upon successful completion of this course, students will
Interested in learning about Open Science, reproducibility, and transparency in research and all things related to research data management? Then don’t wait, join our Research Skills Seminar Series and learn the skills needed to create an optimised and transparent research workflow that is embedded in Open Science and facilitates research data management. From conceptual issues like the replication crisis, to learning skills like pre-registration and wrangling data in R, this seminar series has got you covered and is here to support you.
Crafting Social Science Research, Literature Review
The goal of this course is to provide support and crucial feedback on writing students' dissertation proposal. Such a proposal is a research outline that delineates the doctoral thesis project, including the motivation for research question(s), the survey of the relevant theoretical and empirical contributions, the development of a theoretical framework, the specification of the methodology and planned empirical analysis.
You should be prepared to address the following questions: What makes that an interesting question? Is it an important question? What contributions would this question and the answers make to the scholarly literature? What strategies are there to answer your research question(s)?
Nota bene: Further meeting dates will be determined during the first session.
Information on how to submit the dissertation proposal (8 ECTS) can be retrieved from the CDSS regulations section.
Workshop | |||||||
further dates tbd | 14.02.23 | Tuesday | 10:15 – 11:45 | Zoom | Link | ||
Questions of cause and effect are at the heart of social science. And yet, establishing credible causal effects in empirical analyses is a difficult enterprise. This course will introduce some of the key conceptual and methodological approaches to tackle the causal inference problem: the potential outcomes model of causal inference, experimental designs, matching and regression, instrumental variables, regression discontinuity designs as well as difference-in-differences and fixed effects.
Course requirements & assessment
Active participation, term paper (graded)
Workshop | |||||||
biweekly | 17.02.23 – 31.03.23 | Friday | 13:45 – 17:00 | 211 in B6, 30–32 | |||
biweekly | 21.04.23 – 02.06.23 | Friday | 13:45 – 17:00 | 211 in B6, 30–32 | |||
TCBI, CSSR, Dissertation Proposal
Please check with individual chairs in the Psychology department for dates and times of research colloquia.
Participation is mandatory for first to third year CDSS doctoral students of Psychology. Participation is recommended for later CDSS doctoral students, but to no credit.
Research in Psychology: Research projects cognitive psychology and neuropsychology are planned, conducted, analyzed, and discussed.
Application via 'Studierendenportal' is necessary to have access to the course material provided in ILIAS.
Literature: References will be given during the course.
Talk schedule
Improvement in research skills and communication of research results.
Workshop | |||||||
13.02.23 – 29.05.23 | Monday | 15:30 – 17:00 | B 317 in A5, 6 entrance B | Link | |||
CSSR, Literature Review
The goal of this course is to provide guidance and constructive feedback on writing academic papers in English. Each session will guide students through techniques for writing and/
Workshop | |||||||
16.02.23 – 01.06.23 | Thursday | 12:00 – 13:30 | A 103 in B6, 23–25 | Link | |||
CDSS doctoral students have privileged access to the GESIS Summer School in Survey Methodology as well as GESIS workshops are exempt from course fees*.
Contact the Center Manager before registering for any of the courses and only thereafter register directly through the GESIS web page making sure to mention that you are a CDSS doctoral student.
The GESIS summer school takes place in Cologne from 2 to 25 August. Detailed information about the summer school program is available on the GESIS website.
*According to the provisions stated in §3 (5) of the GESIS CDSS cooperative treaty.
Knowledge of Multivariate Analysis
The goal of this course is to provide an introduction into maximum-likelihood estimation.
Students who wish to pass this course must complete homework assignments and produce a research paper. Participation in the tutorial session (2 ECTS) is mandatory for the assignments which complement the lecture (6 ECTS).
Literature
Course requirements & assessment
Homework assignements, research paper (all graded)
Tutorial
The tutorial accompanies the course “Advanced Quantitative Methods” in Political Science. The lab sessions will focus on the practical issues associated with quantitative methods, including obtaining and preparing data sets, how to use statistical software, which tests to use for different kinds of problems, how to graph data effectively for presentation and analysis, and how to interpret results. The seminar will also serve as a software tutorial. No prior knowledge of statistical programming is expected.
Lecture | |||||||
15.02.23 – 31.05.23 | Wednesday | 08:30 – 10:00 | B 244 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
Oliver Rittmann | 16.02.23 – 01.06.23 | Thursday | 10:15 – 11:45 | tbc | |||
Domantas Undzenas | 16.02.23 – 01.06.23 | Thursday | 15:30 – 17:00 | A102 in B6 23-25 | |||
Tbc
Course requirements & assessment
Seminar | |||||||
15.02.23 – 31.05.23 | Wednesday | 15:30 – 17:00 | A 102 in B6, 23–25 |
Experimental research designs are called the silver bullet or ‘Königsweg’ for causal identification. In recent years, the growing interest in causal identification and mechanism testing made experimental designs a regular empirical research tool in the social sciences – most recently in political science and sociology. This seminar shall give a broad overview of the range of experimental methods such as survey, field, lab-in-the-field, and laboratory experiments. We will discuss classical and recent work, including shortcomings and best practices like transparency (open science) and ethical considerations in experimental research methods. In addition, students will learn to think critically about different (experimental) research designs and design their own experiment to answer a research question they have developed.
Course requirements & assement
Weekly preparation of two discussion-questions, one presentation (allocated text(s), discussion preparation), active participation in seminar, presentation of the Exposé of the seminar paper (graded (incl. peer-feedback)), research design seminar paper (graded)
Seminar | |||||||
18.04.23 – 30.05.23 | Tuesday | 08:30 – 11:45 | C 116 in A5, 6 entrance C | Link |
Surveys are a major data source for quantitative social science research. This graduate-level course will teach the fundamentals of survey design. The course covers the major steps of implementing and conducting a survey and design decisions at each step. In addition, sources of error at each step are discussed. For illustration purposes and exercise, the course will draw on well-known large-scale surveys such as the German General Survey (ALLBUS), European Social Survey (ESS), European Values Study (EVS), and the German Socio-economic Panel (SOEP).
Course requirements & assessment
Active participation, homework assignments/
Seminar | |||||||
16.02.23 – 01.06.23 | Thursday | 13:45 – 15:15 | tbc |
Some basic knowledge of statistical inference and R is required
Lecture
The course provides a broad overview of methods used in longitudinal data analysis, with a focus on the analysis of panel data. Compared to cross-section data, using measurements of the same individuals taken repeatedly through time can lead to better causal inferences in some cases, and can also give the possibility to learn more about the dynamics of individual behavior. The first objective of this course is to discuss the advantages of panel data, and the characteristics of the structure of panel data. Then, the course will give an overview of the main models (pooled OLS, fixed effects, random effects, first-differences) and provide the tools to choose betwen these models. The course will also discuss panel generalized linear models. Finally, an overview of event history analysis will be presented.
Tutorial
Using R, we apply methods of longitudinal data analysis (presented in the lecture “Longitudinal Data Analysis”) to real survey data.
The course will be taught by Dr. Danielle Martin
Course requirements & assessment
Lecture – Three quizzes (two must be a pass), regular attendance, written examination (graded, closed-book)
Tutorial – compulsory attendance, twelve homework assignments of which nine must be passed
Lecture | |||||||
13.02.23 – 22.05.23 | Monday | 10:15 – 11:45 | B317 in A5, 6 entrance B | Link | |||
Tutorial | |||||||
14.02.23 – 30.05.23 | Tuesday | 12:00 – 13:30 | B 318 in A5, 6 entrance B | Link | |||
14.02.23 – 30.05.23 | Tuesday | 15:30 – 17:00 | A 102 in B6, 23–25 | Link | |||
Please register for the course program via the online registration tool between 01 and 19 February 2023. You can request the respective link from Annette Förster (foerster@smip.uni-mannheim.de).
Some programming skills (Python, R, JAVA, C, HTML, BASH, etc.) OR the motivation to learn some python (and some other languages) on your own.
**Requirement: Students should bring their own laptop (on which you can also install programmes, not just apps).**
This course is intended to show you all the major steps involved in completing a statistical analysis within the fields of exploratory data analysis and data science.
This seminar is divided into 3 parts:
First, we will go through the basics of Python and the most important libraries for data science with excursuses into “programming paradigms” and “big data”.
Second, we will learn data exploration, data visualisation and statistical modelling with python.
Third, we will go through the basics of machine learning (supervised, unsupervised and semi-supervised) and neural networks with excususes into the fields of “computer vision”, “computer linguistics” and “AI”.
And finally, we will apply all of this to real-world projects.
For this course, I’ve chosen several different statistical problems to be solved with regression and classification in python.
Course requirements & assessment
Coding-homework, Data analysis project written in python including data transformation, visualisation and analysis (graded)
Seminar | |||||||
biweekly | 24.02.23 – 24.03.23 | Friday | 08:30 – 13:30 | C 112 in A5, 6 entrance C | |||
biweekly | 21.04.23 – 02.06.23 | Friday | 08:30 – 13:30 | tbc |
The reading course is aimed at Ph.D. students in or beyond their second year to support them during their research phase. 1st year PhD students are welcomed to attend the class as well.
Recommended: Knowledge of basic statistics and prior experience with R or Stata is helpful, but not necessary.
This reading course provides a hands-on and paper-based approach to understanding and analyzing data. For many projects, collection of new data or experimental designs are the only way to answer a research question or to provide the decisive complementary evidence. Different ways to collect data can have important implications for model estimation and evaluation, parameter inference, and policy conclusions. Standard econometric methods start from assumptions about the sampling procedure and try to cope with the limitations of a given dataset. Instead, we start at the design stage and examine the interplay between sampling and experimental methods, statistical inference and estimation of causal effects. We will use the German Business Panel as point in case and implement cutting-edge methods to gain insights into the causal mechanisms behind reported outcomes. In each session, one of the participants will present a research paper, which we will discuss in light of concrete implementation at trial scale. Participants are encouraged to present research that is valuable for their own thesis or may be assigned to present a topic.
In addition to presenting a paper and participating in the discussion, students are expected to write a short technical report that summarizes the methods and implications in a way useful for peers who want to use the newly collected data or learn about experimental results.
Learning outcomes:
The specific applications cover a broad set of skills with a focus on design of questionnaires and survey experiments, data analysis and quantitative methods, classification, inference, writing of own reports, and opportunities for own research.
Form of assessment: Paper (technical report) (optional), Presentation (50 %), Class Participation (50 %)
The course is also part of the TRR 266 Accounting for Transparency
Lecture | |||||||
Lecture | 14.02.23 – 30.05.23 | Tuesday | 10:15 – 11:45 | B 144, A5, 6 – B | |||
During recent years interventions using diary methods became increasingly popular within several fields of psychology, including health psychology and organizational psychology. These interventions use „intensive longitudinal designs“ to apply the treatment and to assess the data and build on daily-survey approaches that aim at „capturing life as it is lived” (Bolger, Davis, Rafaeli, 2003, p. 579). Frequent assessments typically implemented in daily-survey approaches allow for modeling change in affect, attitude, and behavior over time.
In this course we will discuss the nature of diary interventions, the research options they offer, as well as potential problems and challenges.
Literature (a more comprehensive list will be available in the first meeting)
Bolger, N., Davis, A., & Rafaeli, E. (2003). Diary methods: Capturing life as it is lived. Annual Review of Psychology, 54, 579–616.
Lischetzke, T., Reis, D., & Arndt, C. (2015). Data-analytic strategies for examining the effectiveness of daily interventions. Journal of Occupational and Organizational Psychology, 88, 587–622. doi:10.1111/joop.12104
Course requirements & assessment
Participation, presentation, term paper (graded)
Seminar | |||||||
16.02.23 – 01.06.23 | Thursday | 17:15 – 18:45 | tbc |
We invite CDSS doctoral candidates to discuss their research with experts in the field. The chair of Clinical Psychology and Biological Psychology and Psychotherapy pursues a wide range of topics and brings together a large spectrum of research approaches. We address open questions regarding each step of creative research and prolific publication of our scientific results. Each week we select one or two of our own projects for discussion.
Seminar | |||||||
14.02.23 – 30.05.23 | Tuesday | 12:00 – 13:00 | 016–017 in L13, 15–17 |
The course will assume that participants have a background in core graduate‐level finance. The course will cover topics from a variety of subfields in finance (asset pricing, financial intermediation, household finance, corporate finance). The introductory block of three classes is intended to orient students to the science of climate change as well as to refresh key concepts from economics and finance; the remaining classes will dive into detail on current research in different subfield. We will conclude with a discussion of open topics in this field. We expect that the course will be useful to doctoral students in finance, economics, and accounting. As a global class, we will largely be on Zoom. Beyond weekly preparation and participation, students will be expected to write a paper either laying out a potential research topic or synthesizing a set of related papers that were not discussed in class.
The purpose of the course is to (a) introduce graduate students to questions and methods in the rapidly evolving fields of climate/
Addressing climate change demands changes in natural, social, and economic systems and will require greater collaboration. In that spirit, this course is being offered by a team of professors from different schools and universities across the globe. Each instructor will deliver one or more lectures and there will be students from a number of different schools. Our teaching group consists of current and former AFA and EFA presidents and some of the leading climate finance scholars, including Laura Starks (current AFA President), Patrick Bolton (former AFA President), Stefano Giglio, Marcin Kacperczyk (former EFA President), Caroline Flammer, Geoff Heal, Stefan Reichelstein, Ben Caldecott and Peter Tufano.
Assessment
Beyond weekly preparation and participation, students will be expected to write a paper either laying out a potential research topic or synthesizing a set of papers related to Climate Change and Sustainability that were not discussed in class.
This course starts early (January 24), please make sure to register until December 20, 2022!
Lecture | |||||||
Lecture | 24.01.23 – 11.04.23 | Tuesday | 17:00 – 19:00 | online (Zoom) | |||
We live in interesting times both, economically and politically. Many observers point to crises and uncertain developments in the economic and political world. Making sense of the nature of these challenges and pointing toward economic and political solutions for the future requires new perspectives. This is a course about the big and bold questions in economics and politics. How can or should economics and politics be organized to best serve society? What does it mean to put humans as they really are at the center of economic and political thinking? What role do morals and values, or dignity and respect, play for the way economics and politics work? What are the implications of digitalization for capitalism and freedom?
We will try to come to grips with these questions by reading and discussing four key books on various new perspectives at the intersection between economics and politics. The aim of this course is to go as deep as we can and to get as much out of an in-class discussion of the material as possible. Willingness to acquire and read the books is a must. If you are unsure about whether or not you would want to take on the commitment of reading four books in one semester then this course is probably not the right one for you.
Students need to be willing to read books, form their own opinions on them, and elaborate on and defend their own views in group discussions and a final essay.
Required Readings
Friedman, M. (1963). Capitalism and Freedom. University of Chicago Press.
Greene, J. (2015). Moral Tribes. Atlantic Books.
Sandel, M. J. (2020). The Tyranny of Merit: What’s Become of the Common Good?. Penguin UK.
Zuboff, S. (2016). The Age of Surveillance Capitalism. PublicAffairs.
Seminar | |||||||
24.02.23 – 24.02.23 | Friday | 13:45 – 15:15 | D002 in B6, 27–29 | ||||
21.04.23 – 02.06.23 | Friday | 10:15 – 13:30 | D002 in B6, 27–29 |
This course is exclusively geared towards students who are currently doctoral students at the GESS of the University of Mannheim. It is intended for beginning as well as advanced doctoral students. This course is an elective course and counts as a 'Bridge Course'. Maximum number of participants is 15. If the course is not fully booked, non-GESS students from Business, Economics, or the Social Sciences or from other related disciplines can enroll. As a necessary requirement you need to make a working paper draft available to all of us that you present in our ‘Mini Research Day’.
This course will introduce students to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS. This year, the course will be given by one senior researchers from each center of the GESS, i.e., you will have the unique opportunity to receive truly interdisciplinary feedback on your work from three different angles.
The course consists of four core building blocks:
1. Kick-Off & Introductory Session: What is interdisciplinary research.
After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by the instructors, each participant will shortly (max 5 min, 2–3 slides per person) present the core idea of an interdisciplinary paper published in a top journal in her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is. Alternatively, you can also present a dataset or a methodology and highlight how students from other GESS centers might take advantage of it.
2. Mini-Research-Day
The second component of the course is a ‘Mini-Research-Day’ which is intended to introduce the kind of topics you are working on to other course participants. You will give a presentation on a current working paper or research project of yours and you will discuss a paper/
3. Science Speed Dating
The science speed dating event – organized by your student representatives – involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a student from another field (preferably from our course).
4. Project Presentations & Writeups
This proposal will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. Each research team will also prepare a short write-up of their proposal (max. 5 pages, incl. references) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in two weeks after the presentation. Moreover, you will also discuss another team project.
Objectives
Upon successful completion of this course, students will
Assessment
This is a pass/
Please register by the registration deadline given below, by sending a title and an abstract of the research project/
Please note that the course is limited to a maximum of 15 participants, and seats will be allocated on a first come first served basis.
Course dates
Upon successful completion of this course, students will
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