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Humboldt-Universität zu Berlin - School of Business and Economics

Ongoing collaborative research projects at the School of Business and Economics

This website informs about ongoing collaborative research projects members of our School are participating in.

Research at the School of Business and Economics is largely driven by cooperation within collaborative research projects which are predominantly funded Deutsche Forschungsgemeinschaft. Within these collaborative research consortia the School cooperates with partner instituations in Berlin, Germany and beyond.


Collaborative Research Centres and Transregios

Rationality and Competition: The Economic Performance of Individuals and Firms (TRR 190)

The CRC-Transregio combines the research programs of behavioral and neoclassical economists to study applied economic questions that are of high policy relevance. The CRC¿s focus is on the economic behavior and performance of individuals and firms: How do systematic biases in expectations, decision processes, and preferences affect the most important economic decisions of households, about education, health, labor supply, financial investments and the purchase of durable consumption goods? How do firms respond to behavioral biases of their customers and their employees, for example by adjusting their marketing strategies, their organizational design, their incentive schemes and their innovation activities? Does competition reduce or amplify the effects of behavioral biases of individuals and firms? What economic policy interventions are effective to protect consumers and employees from exploitation and how can they prevent the destabilization of markets (due to bubbles and crashes)? Thus, the CRC will analyze the allocative consequences and the economic policy implications of different aspects of rationality and deviations from rationality in competitive environments.An important empirical question is in what environments behavioral biases have a quantitatively large effect and under what circumstances the standard, neoclassical model is sufficient to explain observed behavior. Answering this question requires the close collaboration of behavioral and neoclassical economists that the CRC is set up to promote. We will employ modern microeconomic theory (including behavioral economic theory) to generate testable hypotheses as well as a wide set of empirical methods using field data, survey data, administrative data and economic experiments.

Funding period: since 2017

Participating members of the School: Georg Weizsäcker (vice speaker), Christoph Breunig, Dirk Engelmann, Bernd Fitzenberger, Daniel Klapper, Lukas Menkhoff, Alexandra Spitz-Oener, Roland Strausz, Nikolaus Wolf

Further participating institutions: Ludwig-Maximilians-Universität Munich

Further information: Website


Accounting for Transparency (TRR 266)

The Collaborative Research Center/Transregio "Accounting for Transparency" explores how accounting influences transparency and how transparency affects society. Calls for increased transparency are pervasive, particularly after the recent series of financial crises. Many transparency-related regulations in the area of taxation as well as financial and managerial accounting significantly increased the reporting burden of firms. However, public trust in the business sector tends to be very low, particularly in Germany. The historical role of accounting is to aggregate firm-level information into quantitative data. These data are communicated to insiders and outsiders of the firm, who use it to levy taxes and to support investment as well as other economic decisions. The digital revolution has drastically changed the information environment: Information has become ubiquitous, is being generated by diverse senders and distributed via a variety of channels to heterogeneous receivers who process and analyze the data and base various decisions on it. It is unclear how the traditional methods of accounting, which focus on numbers, facts, and verified judgments, can continue to create transparency in this transformed landscape.The researchers of the TRR address this topic. They collect field data to analyze the perception, processing and handling of accounting information. They study how regulations, behavior, and preferences of economic agents shape accounting information and its effects on the transparency of firms. One focus in this regard lies on the transparency of the business taxation system. Furthermore, they assess the consequences of transparency for firms, their stakeholders and the general public. The insights from these activities will allow a well-founded assessment of regulatory reforms in the area of business taxation and financial reporting. Thus, the TRR will contribute to evidence-based policy making and to establishing a transparent tax system. Consequently, the results of the TRR 266 will contribute not only to the academic debate but also to the transparency of the economic system.

Funding period: since 2019

Participating members of the School: Joachim Gassen (vice speaker), Ulf Brüggemann, Ralf Maiterth, Anja Schöttner

Further participating institutions: Universität Paderborn, Universität Mannheim

Further information: Website



(International) Research Training Groups

Quantitative economics often faces the challenge of modelling high dimensional, unstructured data and nonstationary time series. The standard tool sets that are based on a low parameter dimension and a growing number of observations are not applicable and one needs to use adaptive techniques and local stationary models to match data phenomena. The IRTG investigates how high complexity and dimensionality can be downscaled to lower dimensional structures. The dynamic of which can be understood via dimension reduced statistical modelling. The key goals is the development of new statistical and econometric theory to create a broader field of analysis supported by e.g. time varying machine learning or network techniques. The computational methods will be provided on a free accessible platform that allows for transparent and reproducible scientific research. Areas of application include neuroscience, high frequency finance, time varying clustering of unstructured data, dynamic topic modelling, sentiment reactions and herding effects. For realistic adoption of these new tools one needs to eliminate, or at least relax, Gaussianity assumptions via various types of regularizations. A new estimation theory based on functional structural sparsity will allow a fair balance between model interpretability, distributional flexibility and structural complexity. A typical example is time varying Lasso with predictable and economically interpretable sparseness parameter. A graph based view on time series data is necessary if one considers e.g. the dynamics of social or systemic risk networks. Here the IRTG contributes via research on combinatorial inference on e.g. which nodes are central and which nodes are infectious in the sense of creating similar sentiments in a financial context. Such analysis is also demanded in the rapidly growing crypto currency system, where one likes to identify market movers and dynamic survival rates of crypto currencies. To achieve these research goals the qualification programme requires a multi facet course programme that involves solid mathematical and statistical training in combination with modern machine learning skills. Short courses augmenting knowledge on current topics in dimension reduction, dynamic sparseness and networks are held by visiting researchers.

Funding period: since 2013

Participating members of the School: Wolfgang Härdle (speaker), Christoph Breunig, Michael Burda, Bernd Fitzenberger, Stefan Lessmann, Brenda López Cabrera, Weining Wang

Further participating institutions: Xiamen University, China

Further information: Website



Priority Programmes

The recent severe recession has led to a reassessment of labour market policies across many industrialised countries. Technological change and changes in the division of labour, trade liberalisation, increasing labour mobility, demographic changes, low fertility rates, changes in labour force participation as well as labour market reforms have reshaped the way economies and their labour markets operate. The central purpose of the Priority Programme is to develop a deeper understanding of the challenges facing labour markets in Germany in particular and throughout Europe in a global context.

The Priority Programme addresses pertinent research issues on the link between trade, technology and demographic changes as they affect wages and employment. In an international perspective, the Priority Programme will analyse empirically the way the German labour market works with particular emphasis on labour market flows, on the role of institutions and policies, on the explanation for the increase in inequality, on demographic changes and on the links to education and important non-economic motives and outcomes.

An understanding of these issues is key for policies relating to skills development of the population at all ages, family issues and gender in the labour market, demography, child development, health, social policies, crime, immigration, as well as the macroeconomic performance of the labour market. The challenges posed by competition and potential immigration combined with demographic developments will not only affect various labour market groups in different ways, but also force human resource management practices to adapt.

The Priority Programme will take an interdisciplinary approach linking economic research with research in sociology and in human resource management and organisation in business administration. Building on theoretical contributions, the Priority Programme mainly involves empirical research making use of large micro-data sets with an emphasis on a comprehensive descriptive analysis or on estimating causal effects in the treatment-control group paradigm.

A particular focus will be given to projects that investigate labour market flows from micro- and macro-economic perspectives. Trademarks of this Priority Programme are the access to individual-level and firm-level labour market data of exceptional quality, state-of-the-art experiments and the close link to the policy debate.

Funding period: since 2014

Participating members of the School: Michael Burda (only 1st funding period), Bernd Fitzenberger (speaker), Alexandra Spitz-Oener

Further information: Website


Computer systems pervade all parts of human activity and acquire, process and exchange data at a rapidly increasing pace. As a consequence, we live in a Big Data world where information is accumulating at an exponential rate and often the real problem has shifted from collecting enough data to dealing with its impetuous growth and abundance. As the speed improvement of single processing cores has basically stalled, the hardware industry keeps on increasing the number of processors/cores per board or graphics card, and also invests into improved storage technologies. This means our algorithms must become massively parallel using memory access patterns with high locality. More and more often, we will not even be able to consider all available data. These are challenges that need new algorithmic ideas. The Priority Programme wants to improve the situation by bringing together expertise from different areas. On the one hand, recent hardware developments and technological challenges need to be appropriately captured in better computational models. On the other hand, both common and problem specific algorithmic challenges due to big data are to be identified and clustered. Considering both sides, a basic toolbox of improved algorithms and data structures for big data sets is to be derived, where we do not only strive for theoretical results but intend to follow the whole algorithm engineering development cycle. Concrete algorithmic challenges include exploiting parallelism (multicores, GPUs, clouds) and memory-hierarchies (hard-disks, flash-memory, caches), dealing with large-scale dynamic data updates, processing compressed and encrypted data, approximation and online processing under resource constraints or reducing the consumption of energy by algorithmic measures. What distinguishes our initiative from most previous work is that we do not only want to tackle certain problems in isolation but aim to find solutions for several aspects at once: for example, given a concrete application challenge, how can we use massive parallelism, memory-hierarchies, specific data features and novel algorithmic techniques to yield better overall performance. Right from the start, a close interaction with various applications areas (like bioinformatics and information retrieval) will make sure that besides fundamental problems, a bunch of practically relevant questions will be tackled for the benefit of several communities.

Funding period: since 2014

Participating members of the School: Max Klimm

Further information: Website



Leibniz Science Campus

Promoting consumers’ rights, prosperity, and wellbeing are core values of the European Union. A wide array of laws, institutions, and regulations – which can be generally termed as consumer policies – aim at protecting consumers by ensuring adequate and truthful information in the marketplace as well as preventing firms from engaging in unfair and competition-impairing practices.

While some of these policies directly affect consumers, for instance consumer protection and dissuasive taxation, others only indirectly benefit consumers by governing market functions through regulation and competition policies. The interactions between these different policies are not yet fully understood.

The aim of the Berlin Centre for Consumer Policies (BCCP) is to create an enduring international platform in the broad area of competition and consumer policies, where excellent interdisciplinary research can actively and effectively inform policy makers on issues that are highly relevant to the current policy debate.

The strong focus of the partner institutions in industrial organization, behavioral economics and competition law, as well as a strong policy focus makes Berlin the perfect location for a ScienceCampus focused on consumer policies. The main goal of BCCP is to fully exploit, reinforce, and institutionalize this exceptional environment to answer specific questions on the optimal design of consumer policies.


Funding period: since 2015

Participating members of the School: Dirk Engelmann, Wolfgang Härdle, Ulrich Kamecke, Daniel Klapper, Roland Strausz, Georg Weizsäcker

Further participating institutions: Freie Universität Berlin, Technische Universität Berlin, European School of Management and Technology, Hertie School of Governance, German Institute for Economic Research (DIW), Berlin Social Science Center (WZB)

Further information: Website