The intensification of digital communication and the increase in the performance of digital computer architectures, which is often associated with the keyword "digitization", opens up a multitude of new technical possibilities, but also presents politics and society with new challenges.
The purpose of the research cluster is to bundle the competencies available at the university in the field of data analysis and data processing in order to support politics and society in dealing with these challenges through basic and application research and to make contributions to computer-aided social research.
The immense performance of modern computers makes it possible to work on new content-related and methodological issues. In particular, the use of Monte Carlo methods to analyze the quality of statistical estimation methods and the use of computationally intensive methods for calculating statistical estimated values (bootstrap, Monte Carlo integration, Markov chain Monte Carlo simulation of posterior distributions) should be mentioned here.
(Prof Dr Joachim Behnke) For more than 20 years, various reform proposals and possibilities of reform regarding the electoral system of the German Bundestag have been discussed. The focus of the discussion is on ”Überhangmandate” (surplus seats) and the associated enlargement of the Bundestag. For the assessment of the effects of various reform proposals and their comparison, simulations are used as a means to provide estimates for the effects of certain reforms and to elaborate the sensitivity by modifying the model parameters. One of the more specific aims of the project is to illuminate how the size of the Bundestag is affected by various options of institutional reform.
(Leonie
Geyer & Prof
Dr Joachim Behnke) The political competition between parties is often described using so-called spatial models.
These focus on the consequences and implications of voters’ and parties’ locations on one or several issue dimensions. In these models, parties are seen as being in a economic competition for the votes of citizens as their “customers”. As voters’ choice of party depends on the political proximity of their position to that of the parties, parties can use their choice of position strategically to improve their outcome. Since voters choose parties by comparing parties’ positions on several dimensions and the effect of one party’s changing position depends on the positions of other parties, who in turn can adjust their own positions, the interaction patterns of parties’ positional changes are very complex and can hardly be modelled analytically. Agent-based models are one possibility to calculate the results of complex analytical calculi using simple adaptation strategies that are ”more realistic” in this respect and therefore may provide valuable information about the actual dynamics of party competition.
(Prof Dr Martin Elff) Multi-level analysis is often used in comparative social research to trace the influence of the social and political context on individual behavior. This method is often used on the data of multinational surveys (such as the Eurobarometer or the European Social Survey), which are characterized by a large number of units of investigation at the individual level (respondents) but a small number of units at higher aggregation levels (states). To what extent the multilevel analysis still delivers reliable results under these circumstances and to what extent accurate statistical inference can be achieved are some of the questions that this project deals with.
(Prof Dr Martin Elff) The reconstruction of the positions of political actors is essential for a variety of political science issues. In analyzing the formation of government coalitions, as well as understanding changes in patterns of electoral behavior, it is essential to consider the political positions of parties. However, the reconstruction of these positions turns out to be anything but easy. There are two basic approaches for this: on the one hand, ratings by experts (i.e. country experts assign positions to the parties on predetermined scales), on the other hand, the quantitative analysis of the parties' election programs (i.e. based on the statistical analysis of prepared texts and with the aid of spatial models the positions estimated). The research project follows the second approach. As part of the project, on the one hand, existing procedures are to be improved and examined with regard to their reliability; on the other hand, they are to be used to create a comprehensive database of party positions with which the patterns of party competition can be determined. An application for funding has been submitted to the Deutsche Forschungsgemeinschaft (DFG) to support the project.
(Prof Dr Martin Elff) The data analysis software R is on the one hand a comprehensive infrastructure for data analysis and data management, on the other hand it is a programming language for statistics and graphics. Due to this dual character, it can be used in a variety of ways. Their field of application ranges from the analysis of experimental data, through the analysis of survey data, to the analysis of massive data sets of behavioral traces. However, the data structures relevant for this are not yet very familiar in the social sciences; on the other hand, the support for survey data sets that are typical for social research through R packages can still be expanded. The book project is intended to build the corresponding bridges: on the one hand, the common data structures are presented and discussed, on the other hand, it addresses the special packages relevant for the analysis of survey data.
Behnke, Joachim Prof Dr
Chair of Political Science
Elff, Martin Prof Dr
Chair of Political Sociology
Geyer, Leonie
Research Fellow at the Chair of Political Science
The speed of trading in financial markets has increased immensely in recent years. Data sets are now available in milliseconds, microseconds and even nanoseconds. The analysis of such data requires appropriate statistical models and computer-aided processes.
(Prof Dr Franziska Peter) Funded by the Deutsche Forschungsgemeinscahft (DFG), duration 2018-2020, (project number 389577820)
This project examines volatility in connection with risk forecasting and risk management on intraday frequency. Current financial market literature shows that the options-based measure of implied volatility contains information related to future stock market volatility that cannot be derived from historical stock prices. Prominent examples of such implicit volatility measures are the VIX or its German counterpart, the VDAX. In this research project, an implicit volatility measure for stocks of individual companies is developed, which is based on high-frequency option prices. This measure is calculated for a sample of European and US American companies and makes it possible to examine several important aspects relating to the assessment of stock market risk.
(Prof Franziska Peter and Thomas Heil) Research in “Computational Sciences” is largely a result of the availability of new data. Not only extraordinarily large data sets (“Big Data”) require new analysis methods and new statistical procedures for their analysis. Especially high-frequency traders with a focus on "algorithmic trading" need input and analysis at a very high frequency. It is therefore of great importance to be able to predict the volatility structures within a day. In addition, this allows us to filter and understand consistent structures (“Pattern Recognition”) within one trading day. The analysis of these structures and their prediction is carried out using algorithms from the field of machine learning. These new findings make it possible to create new statistical models and key figures for intra-day volatilities.
(Prof. Franziska Peter and Thomas Heil) The calculation of the Value at Risk or Expected Shortfall requires the estimation of the expected return as well as the estimation of the future volatility. However, greatly simplifying assumptions about the latent process of volatility often lead to inaccurate calculations of the value at risk and thus the expected shortfall. In principle, classical statistical models offer the possibility of predicting a density function from time series of returns, but these models are subject to severe restrictions, which leads to a poor prediction of the non-negative densities. The applicability of machine learning (neural networks, SVM) is proving to be very promising in the prediction of densities, since as the ultimate function approximators it is superior to classical statistical models when dealing with non-linear data. Based on such an estimate or prediction of the return densities, a direct calculation of the value at risk and the expected shortfall can be made. In addition, it is possible to increase the frequency of observations in order to be able to identify patterns in the volatility structure within a day. The prediction of the densities is done with "Mixture Density Networks".
Peter, Franziska Prof Dr
Chair of Empirical Finance and Econometrics
Heil, Thomas
Research Fellow at the Chair of Empirical Finance and Econometrics
On April 14, 2023, the Computational Social Science Cluster has invited to a lecture by Professor Dr. Steven Ongena from the University of Zurich on the topic ""There is no planet B", but for banks there are "countries B to Z": Domestic climate policy and cross-border bank lending".
The research cluster Computational Social Science hosted Professor Marco Steenbergen, PhD from the University of Zurich on December 6th, 2022, who gave a lecture entitled "Causal Inference for Latent Variables".
On September 30, 2022, we welcomed Professor Joanna Bryson, PhD from the Hertie School of Governance, who gave a lecture on "Science and Power in a Context of AI Policy".
We were delighted to welcome Professor Dr. Winfried Pohlmeier from the University of Konstanz in the lecture series of the Computational Social Science Cluster. Prof. Pohlmeier gave a lecture on "Portfolio Pretesting with Machine Learning" on December 08, 2021.
Phone: | +49 7541 6009-1376 |
Fax: | +49 7541 6009-1399 |
Room: | Semi 1.05 |
Anja Achtziger graduated in Psychology in 1997 (Technical University of Darmstadt, Germany) and received her PhD in Psychology in 2003 (University of Konstanz, Germany). She worked as a Postdoc and Temporary Professor of Social Psychology and Motivation at the University of Konstanz. She later moved to the Zeppelin University Friedrichshafen, Germany, there she holds the Chair in Social and Economic Psychology. Anja was a Visiting Professor of Psychology at New York University Abu Dhabi from August 2019 to May 2020. From March 2018 to December 2019 she was the speaker of the research unit “Psychoeconomics,” funded by the German Research Foundation. Anja is an associate editor of the Journal of Economic Psychology since January 2019. She is the deputy speaker of the coordination committee of the Consumer Research Network of the Federal Government of Germany appointed by the Minister of Justice and Consumer Protection Heiko Maas in 2015 and by Dr. Katarina Barley in 2018.
Anja Achtziger’s research focuses on human decision making, algorithm aversion and appreciation, self-control, and motivation. She uses a multi-method approach to investigate human cognition, with techniques encompassing laboratory and field experiments, eye-tracking, and electroencephalography (EEG). Her work ins interdisciplinary and includes collaboration with researchers from economics, management science, consumer research, computer science, and ethics. Her most recent research project, on the consequences of using algorithmic decision-making systems in legal systems for society, is “Deciding about, by, and together with algorithmic decision-making systems,” funded by the Volkswagen Foundation in its program “Artificial Intelligence and the Society of The Future”.
Phone: | +49 7541 6009-1431 |
Fax: | +49 7541 6009-1499 |
Room: | Semi 0.02 |
In his research, Joachim Behnke deals from a theoretical perspective with political institutions, the process of decision-making and the design of politics in certain political fields. In doing so, he focuses on a methodologically motivated actor and process perspective, as is also reflected in modern "governance" research.
The second strand of his research links theory to empirical findings. For this purpose, he uses methods of action and decision theory, game theory, as well as empirical survey and evaluation methods.
Phone: | +49 7541 6009-2411 |
Room: | Semi 0.06 R |
Steffen Eckhard deals in his research with the management of public organizations and their influence on politics and society. He examines the phenomenon of administration in its entirety, from the municipal level and interaction with citizens to international organizations in global policy making and implementation. In addition to the application of qualitative and quantitative scientific research methods, Steffen Eckhard also uses the computer-based analysis of large amounts of text to record political phenomena.
Phone: | +49 7541 6009-1369 |
Fax: | +49 7541 6009-3009 |
Room: | FAB 3 | 1.81 |
Martin Elff holds the Chair of Political Sociology since February 2015. His research activities cover a variety of topics, including the relation between social structure and electoral behaviour, the estimation of parties‘ political positions from their electoral platforms, measuring democracy, and methodological questions of quantitative political research.
Findings of his research have been published or are forthcoming in Acta Politica, the British Journal of Political Science, Electoral Studies, the European Journal of Political Research, German Politics, Perspectives on Politics, Political Analysis and Politics and Governance.
Phone: | +49 7541 6009-1241 |
Fax: | +49 7541 6009-1499 |
Room: | Semi 0.03 R |
Jarko Fidrmuc gained interdisciplinary experience at universities and other research institutes. He received his doctorate from the University of Vienna. Before accepting the call to Zeppelin University, he worked at the Institute for Advanced Studies in Vienna and at the Department for Foreign Studies at the Oesterreichische Nationalbank. In 2005, he was appointed W2 professor for political economy and European integration at the Faculty of Economics and at the Geschwister-Scholl Institute of the Ludwig-Maximilians-University in Munich. In 2011, he accepted the offer to continue his research as a professor for international economic theory and policy at Zeppelin University.
In his research, Jarko Fidrmuc places a strong focus on European integration, globalization and political economy. He answers macroeconomic questions by using newly developed tools to analyze microeconomic data on individual households, companies and banks. Another field of research focuses on the interdisciplinary application of meta-analysis.
Phone: | +49 7541 6009 -1231 |
Room: | Semi 1.13L |
In research and teaching, Florentina Paraschiv deals with a wide range of issues from banking and finance with a focus on green finance and fintech. Part of the research focuses on the strategic implications of the challenges posed by sustainability issues for the financial system. She proposes solutions on how to deal with financial risks arising from social and sustainability problems, including responsible investing according to environmental, social and governance (ESG) criteria.
In the field of fintech, Florentina Paraschiv deals with machine learning methods, applied to a wide range of issues such as insolvency prediction or credit risk assessment, as well as the effects of digitalization of financial processes on bank profitability or customer loyalty.
Phone: | +49 7541 6009-2231 |
Fax: | +49 7541 6009-1299 |
Room: | Semi 1.06 |
Since January 2016, Franziska Peter holds the Chair of Empirical Finance and Econometrics. Her research activities are in the field of analysis of financial market data, in particular the information and volatility transfer processes of different trading platforms. The focus here is not only on the traditional markets, e.g. stock exchanges, but also on digital trading venues for cryptocurrencies. Another focus is the analysis of social media data and its connection with financial markets. Her research has been published in the Journal of Financial and Quantitative Analysis, Studies in Nonlinear Dynamics and Econometrics, SoftwareX, and the Journal of Banking and Finance.
Research Fellow at the Chair of Finance
Research Fellow at the Chair of Political Sociology
Postdoctoral Research Fellow at the Cluster Computational Social Science and the Research Methodology Training Centre
Research Fellow at the Chair of Political Science
Research Fellow at the Chair of Empirical Finance and Econometrics
Research Fellow at the ZEPPELIN-Chair of International & Digital Economics
Postdoctoral Research Fellow at the Chair of Social and Economic Psychology