Veranstaltungen

Abstract folgt.

Ansprechpartner: David Heller

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

In this paper, we investigate one factor that can directly contribute to—as well as indirectly shed light on the other causes of—the gender gap in academic publishing: time and length of peer review. Using detailed administrative data from an economics field journal, we find that referees spend longer reviewing female-authored papers, are slower to recommend accepting them, manuscripts by women go through more rounds of review and their authors spend longer revising them. Less disaggregated data from 32 economics and finance journals corroborate these results. We conclude by showing that all gender gaps decline—and eventually disappear—as the same referee reviews more papers. This pattern suggests novice referees initially statistically discriminate against female authors, but are less likely to do so as their information about and confidence in the peer review process improves. More generally, they also suggest that women may be particularly disadvantaged when evaluators are less familiar with the objectives and parameters of an assessment framework.

Link to paper
 

Ansprechpartnerin: Svenja Friess

Estimating Technological Gains and Losses from Environmental Regulation
Presenter: Albert Roger (Max-Planck-Institut für Innovation und Wettbewerb)
Discussant: Kyung Yul Lee (TUM)

The Locus of Value Capture
Presenter: Adrian Goettfried (TUM)
Discussant: Katerina Dubovska (ISTO)

We study the impact of disclosing greenhouse gas emissions (CO2) on the liquidity of firms’ equity. For the subset of firms that report emissions, we find that higher emissions lead to lower liquidity. However, firms that do disclose emissions have lower bid-ask spreads than firms that do not. This is because these firms are more liquid before disclosing emissions but also because when firms first disclose emissions, bid-ask spreads decrease by roughly 13%. These results hold for high information asymmetry firms, for high and low carbon intensity firms, and for early and late disclosing firms. Our results are consistent with theory that shows that more information asymmetry leads to lower liquidity and that ESG-motivated investors may also be noise traders.

Ansprechpartner: David Heller

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Women continue to be underrepresented in the field of economics, especially among permanent faculty. Using 40 years of Danish administrative data combined with bibliometric data on publications from the Scopus database, we study the impact of children on women’s probability of successful academic careers. Our event study estimates show that parenthood reduces women’s likelihood of staying in academia by 10 percent relative to men, and the gap appears to be permanent. We further document a gender gap in the likelihood of getting tenure in the three years following parenthood, conditional on staying in academia, while the gender gap in publications is insignificant.

Ansprechpartnerin: Marina Chugunova

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

This paper analyzes the unexpected success of AlphaFold V1, an AI-based software program representing a publicly available and novel methodological advance within the “protein folding” (PF) subfield of computational biology. As a novel tool that represented a significant advance, AlphaFold V1 influenced the size and the expertise composition of academic research labs already producing similar software in the PF subfield. Specifically, AlphaFold V1 caused the principal investigators of established labs to reconsider the size, and the depth and breadth of expertise necessary to capitalize on the advance; and even to decide whether their labs should continue work in the PF subfield altogether. Results show that impacted labs adapted to the new methodological advance by becoming larger and broader in expertise. This study contributes findings on: (i) the mechanisms of new opportunity and increased competition that shape lab composition; (ii) the complexity of science at the frontier of human expertise and artificial intelligence; and (iii) the role of companies in the collective effort to produce scientific knowledge. The results carry implications for further research on the integration of disciplinary insights, the scaled computational capabilities enabled by artificial intelligence, and the organization of science itself.

Ansprechpartner: Michael E. Rose

Firms apply for patents for a variety of reasons. In addition to trying to prevent others from copying a commercialized patented invention, firms also patent one technology to support the commercialization of their other innovations (which we call “pre-emptive patents”). At the same time, many patent applications fail to yield commercialized products. A variety of policy debates revolve around the relative rates of these different uses of patents.  In particular, there is a concern that a large number of patents are not commercialized (with a common folk statistic stating that 10% or fewer are commercialized), raising concerns of over-patenting, with possible adverse effects on the innovation system. However, it has been difficult to get systematic evidence on the relative incidences of commercialized versus pre-emptive or failed patents. This paper applies advanced natural language processing (NLP) and machine learning (ML) methods to US patent documents to estimate the rates of patent uses of various types, over time at scale. We first use a survey of US inventors on the commercialization and other outcomes of their patents as independently labeled data for training our ML models. Using a combination of context embedding codings of the patent text (based on BERT) and bibliometric indicators from the patent documents, we develop a random forest model predicting different outcomes for patented inventions. We find that adding BERT coding of patents’ text contents offers new information beyond commonly used numeric and categorical variables reflecting patent characteristics (technology class, number of claims, patent class span, etc.) or token-based text analytics indicators, highlighting the benefits of adding context embedding NLP when categorizing patents. We check the validity of the trained model using external data on Virtual Patent Marking, and show that our model predicts high commercialization rates among patents that are indeed associated with commercialized products. We apply this trained model to the universe of all granted US patents, 1981-2015 to estimate the probabilities of various uses of the patents in this population. These estimates of usage probabilities are publicly available for other researchers to use in follow-on studies. Among US granted patents 1981-2015, the mean probability of commercialization is .59, and the mean probability of pre-emptive use is .19. Finally, we show how these probabilities vary by year, patent class, firm size, and government interest. The paper makes several contributions to understanding the uses of patents, as well as how to use ML to analyze patent data. In particular, we show that estimated rates of commercialized patents are substantially higher than is often asserted in policy discussion.

Ansprechpartnerin: Elisabeth Hofmeister

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

In this talk, Ali Aslan Gümüsay intends to bring together multiple projects around innovative templates, circular forms of organizing, and futures. As new forms of organizing enter a field, they may need to co-create innovative templates to tackle institutional tensions. Equally, they may question and innovate organizational purpose, processes and practices. Given planetary boundaries and infringement on academic jurisdictions, there is a need to not only study these forms of organizing, but also reflect upon the role of scholarship to possibly co-create desirable futures. This includes to think about how to theorize data before it exists – moving from post-factual to pre-factual – and how to (re)organize scholarship itself.

Ansprechpartnerin: Anna-Sophie Liebender-Luc

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Business dynamism, i.e., the process of new efficient firms entering the market, grow and force less efficient competitors to contract and exit, is believed to be key both for productivity and employment growth. A particular role in that take young high growth firms with the potential to fundamentally disrupt the economy. Business dynamism and firm high growth, however, are in decline in many advanced countries, most prominently shown for the US, which has important long term effects on the transformation process of the economy. Based on firm-level data, originating from Germany’s largest credit rating agency (Creditreform), covering the period 2002–2019, we show some new insights in firm high growth dynamics. By that, we look at secular trends, heterogeneity in terms of firm size and age as well as sectoral differences.

Taken this as background information, the presentation will proceed by introducing a larger research project that we are currently setting up jointly with IWH (Halle Institute for Economic Research). Here, a unique new data infrastructure, linking the above treated firm-level data with establishment and employee data from IAB will be developed and exploited. This new data infrastructure will allow to respond to several crucial questions in the literature of entrepreneurship, business dynamism, and firm high-growth. More precisely, the research agenda comprises the analysis of who creates jobs in Germany (small vs. big vs. young), as well as the investigation of the conditions (rural arears vs. economic centres, IT infrastructure, closeness to scientific institutions) spurring firm high growth and regional development. Furthermore, we ask the question of the role of entrepreneur characteristics to high growth firm outcomes, such as age, experience, education and migrant status, and the role of inventors and workers. Lastly, the project also comprises the analysis of the effect of M&A activity on firm growth and the innovativeness of the economy.

Ansprechpartner: Albert Roger

Eintragung in den Einladungsverteiler und mehr Informationen auf Seminarseite.