Current Research

Academic Knowledge: Does it Reflect the Combinatorial Growth of Technology?
Preprint available on arXiv. Revise & Resubmit in the European Economic Review
    I explore the concept of growth being rooted in the recombination of existing technology as an explanation for the remarkable growth witnessed during the Industrial Revolution as it was recently proposed by Koppl et al. (2023). I adapt their combinatorial growth theory to assess its applicability in generating academic knowledge within universities and research institutions, particularly in the field of economics. The central question is whether significant combinatorial growth can also be anticipated in academia. The current career structures discourage the recombination of ideas, theories, or methods, making it more advantageous for early career researchers to stick to the status quo. I employ machine-learning-based natural language analysis of the top 5 journals in economics. The analysis reveals limited correlations between topics over the past three decades, suggesting the presence of isolated topic islands rather than productive recombination. This confirms the theoretical considerations beforehand. Overall, the institutional order of academia makes combinatorial growth at the research frontier unlikely.
Presented at the 11th Erfurt Workshop on the Renewal of Ordo Economics

Trapped in Transformative Agreements? A Multifaceted Analysis of >1,000 Contracts
Joint with Ulrich Herb (SULB, U Saarland, DE) and Laura Rothfritz (IBI, HU Berlin, DE)  - preprint available on arXiv.
Revise & Resubmit in the Quantitative Science Studies
Transformative agreements between academic publishers and research institutions are ubiquitous. The "Efficiency and Standards for Article Charges" (ESAC) Initiative lists more than 1,000 contracts in its database. We make use of this unique dataset by web-scraping the details of every contract to substantially expand the overview spreadsheet provided by the ESAC Initiative. Based on that hitherto unused data source, we combine qualitative and quantitative methods to conduct an in-depth analysis of the contract characteristics and the TA landscape. Our analysis demonstrates that research institutions seem to be `trapped' in transformative agreements. Instead of being a bridge towards a fully Open Access world, academia is stuck in the hybrid system. This endows the legacy (non-Open Access) publishing houses with substantial market power. It raises entry barriers, lowers competition, and increases costs for libraries and universities.
Replication package openly available on Zenodo.
Upcoming presentations: TU Ilmenau Brown Bag Seminar (DE), CWTS Research Seminar at Leiden University (NL)

La Révolution Dévore ses Enfants: Pricing Implications of Transformative Agreements
Fully revised version available on arXiv.
With the widespread dissemination of the internet, academia envisioned free availability and rapid dissemination of new knowledge. However, most researchers continued publishing in established journals instead of switching to fully open-access alternatives. That preserved the market power of the large commercial publishing houses owning thousands of journals behind paywalls. To turn these portfolios into open access, research institutions around the globe have been negotiating `transformative agreements:' Papers are published fully open access, and universities pay only for the publication but not for subscriptions any longer. In this paper, I demonstrate that publishers controlling a large stock of paywalled publications can use them as leverage to ensure high revenues even with decreasing publication numbers. By that, transformative agreements may harm competitors that only publish under open access. This could harm competition and perpetuate the position of the incumbent players.
Upcoming presentations: Kolloquium Wissensinfrastruktur, Bielefeld University (DE)
Presented at the 11th OLIGO Workshop at the University of Padova (IT); 57th Hohenheim Colloquium at Bauhaus University Weimar (DE)
Title change! A previous version has been circulated under the title "The ‘Must Stock' Challenge in Academic Publishing: Pricing Implications of Transformative Agreements" on arXiv (earlier version v1)

The X Factor: Open Access, New Journals, and Incumbent Competitors
Current Version available here (G-Drive). Earlier version published as MSI Working Paper 2307 here (outdated), new version in preparation.
The academic publishing market is considerable in its size, its highly oligopolistic structure, and the profits it extracts from researchers and their universities. In this paper, I evaluate whether there exists a citation advantage for open access publications and whether new market entrants suffer from less recognition. To do so, I exploit a quasi-causal setting created by Elsevier. In 2019, the publisher launched its 'X journals:' Relying on the editorial process of their `parent journals,' X journals were the full open access derivatives of established outlets. In parallel, Elsevier continued to offer authors an open access option for their publications within the established outlets. Exploiting this threefold variation, I cannot detect any impact of open access on citations within the incumbent journals. However, a large and adverse effect exists for the novel journals. This `X factor' represents a nonnegligible entry barrier for potential competitors in the publishing market. My findings do not only question how far researchers will follow the call for more open access but raise doubts about to which extent competition can be enhanced in this market, which would benefit researchers, universities, and ultimately the public.

Presented at VfS Jahrestagung 2024 [Annual Conference of the German Economic Association] (TU Berlin, DE), EARIE Annual Conference (U van Amsterdam, NL); EEA Annual Conference (Erasmus U Rotterdam, NL); Munich Summer Institute 2024 (Bavarian Academy of Sciences/Max Planck Institute for Innovation & Competition, Munich, DE); TU Ilmenau Brownbag Seminar (DE); the Workshop: “The Organisation, Economics and Policy of Scientific Research," Collegio Carlo Alberto, Turin (IT); RISE 6 Workshop, Max Planck Institute for Competition & Innovation (DE); CWTS Research Seminar at Leiden University (NL); Lunchtime Seminar at Leipzig University (DE); the REGIS Summer School at the Sant'Anna School of Advanced Studies Pisa (IT); DICE PhD Workshop (DE, internal), Eucken Institute Seminar

Collusive Compensation Schemes Aided by Algorithms
Joint with  Simon Martin - current version available here (G-Drive)
Recent advances in demand forecasting algorithms enable firms to predict future market conditions more precisely. As firms engaging in anti-competitive conduct frequently employ sophisticated collusive compensation schemes (e.g., assigning future market shares or direct transfers), predictive ability affects both the overall stability of collusion and also the choice of the optimal compensation scheme. We find that across compensation schemes, prices, and profits are inverse U-shaped in prediction ability. Assigning future market shares is optimal when prediction ability is intermediate, and otherwise, direct transfers are optimal, which has novel and important implications for competition policy. 

Presented at the 10th OLIGO Workshop on Industrial Economics at the University of Cyprus, the 5th CESifo Area Conference on the Economics of Digitization, the 92nd IAES Conference, the SasCa PhD Conference 2021, and the DICE PhD Research Workshop. Earlier versions:  CESifo Working Paper No. 9481, Conference draft for the CESifo Area Conference on the Economics of Digitization 2021. Further materials: Extended Abstract, Slides of my presentation at the CESifo Area Conference on the Economics of Digitization 2021

Quantitative Tools for Time Series Analysis in Natural Language Processing
Preliminary Working Paper available on arXiv
Natural language processing tools have become frequently used in social sciences such as economics, political science, and sociology. Many publications apply topic modeling to elicit latent topics in text corpora and their development over time. Here, most publications rely on visual inspections and draw inference on changes, structural breaks, and developments over time. We suggest using univariate time series econometrics to introduce more quantitative rigor that can strengthen the analyses. In particular, we discuss the econometric topics of non-stationarity as well as structural breaks. This paper serves as a comprehensive practitioners guide to provide researchers in the social and life sciences as well as the humanities with concise advice on how to implement econometric time series methods to thoroughly investigate topic prevalences over time. We provide coding advice for the statistical software R throughout the paper. The application of the discussed tools to a sample dataset completes the analysis.

EAGER: PBI: Paving the Path to Market: The Role of Place-Based Innovation in R&D Product Availability
joint with David Campbell (Elsevier ADS) and Jiajie Xu (U Iowa)
The proposed research project will enhance understanding of factors affecting how innovative research and development effectively translate into commercial products by focusing on place-based innovation (PBI) ecosystems. PBIs are regions where a variety of stakeholders collaborate in close geographic proximity (for example, Silicon Valley is a well-known example of a PBI ecosystem). The National Science Foundation's Regional Innovation Engines (NSF Engines) program has recently started funding PBI ecosystems to bridge the regional technological divide in the United States. By uncovering critical factors that facilitate or hinder successful R&D commercialization, this project will provide valuable insights to support the continuous improvement of NSF Engines and PBI ecosystems more broadly. The significance of this project therefore lies in its potential to promote inclusive economic growth and resilience throughout the United States. Technically, the study will involve linking vast, regionalized data sources that cover the innovation pipeline, from academic publications and patents to market-ready products. The study aims to characterize the rate at which R&D outputs are translated into new products and the time it takes for this translation to occur through advanced statistical modeling. By testing a broad range of factors that can be optimized through PBI interventions, the research will address critical questions about these factors influence on R&D translation and commercialization timelines. The project will leverage transdisciplinary perspectives and novel data on patent-protected products, advancing existing methods of measuring regional innovative activities. The project will also innovate on various methods to enhance understanding of regional innovation dynamics. As an example, the measurement of a regions related capabilities in a specific area will be improved by relying on co-citation as opposed to specialization patterns. The study will notably inform NSFs monitoring, evaluation, and learning approaches for the NSF Engines. It will also support the monitoring of regional R&D initiatives more broadly, as well as provide methods to obtain relevant local baselines for assessing other regional innovation ecosystems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
This work is funded by the U.S. National Science Foundation  grant award number #2431145 

RIDE or Die: Criteria for a Successful Open Access Transition - joint with Laura Rothfritz (IBI, HU Berlin, DE) & Ulrich Herb (SULB, U Saarland, DE)
Policy makers, librarians, and science managers around the world work on changing the academic system towards more openness in publishing, peer review, and data work. While there exists a plethora of initiatives, programs, and attempts, few succeed, while many fail. We argue that too many decision-makers do not take the individual researcher's perspective and ignore their incentive structures but rather set moral standards, such as fairness. This is evident, for example, in the open access community, which overly emphasizes the researchers' responsibility to contribute to the allegedly common good of open science and academia. Although done with the best intentions, ignoring the motives of the researchers, their incentives, and needs will likely fail many more initiatives. We discuss criteria that are important for the success of open access approaches and develop the \textbf{RIDE} requirements that every open access initiative should address.

Cartels to Protect the Commons- joint with Lukas Breide (TU Ilmenau, DE)
Societies struggle with the protection of natural resources. Even though governmental regulation and private certification exist, over-fishing and exaggerated timber harvesting are a constant threat to the stability of ecological systems. It may foster deforestation and the extinction of marine creatures, which lead to a decrease in biodiversity. To overcome the economic incentive of overuse, one needs to make it optimal for the exploiting firms to reduce output. Here, antitrust could come into play: In the present paper, we discuss to which extent legalizing horizontal agreements may protect natural resources. While the mechanism is intriguing on the micro-level of natural resource exploitation, the risks for competition beyond the static collusive single-market equilibrium have been overlooked. We consider innovation, vertical integration, political economy, and institutional embedding. Based on our analysis, we curb the enthusiasm that `green' antitrust could be reached by simply softening its enforcement and allowing for horizontal agreements.
Working Paper coming soon.  Upcoming presentation at the 61st Hohenheim Colloquium at Heinrich Heine University (DE)

Boards Backing Out: The Costs and Benefits of Parting Ways - joint with Laura Rothfritz (IBI, HU Berlin, DE)
Early stage work in progress. This project is co-funded by a Connex grant from the Hans Riegel Foundation.