Veranstaltungen

This paper analyzes the recognition of women’s innovative ideas. Bibliometric data from research in economics are used to investigate gender biases in citation patterns. Based on deep learning and machine learning techniques, one can (1) establish the similarities between papers (2) build a link between articles by identifying the papers citing, cited and that should be cited. This study finds that, on average, a paper omits almost half of related prior papers. There are, however, substantial heterogeneities among the authors. In fact, omitted papers are 15% to 30% more likely to be female-authored than male-authored. First, the most likely to be omitted are papers written by women (solo, mostly female team) working at mid-tier institutions, publishing in non-top journals. In a group of related papers, the probability of omission of those papers increases by 6 percentage points compared to men in similar affiliation when the citing authors are only males. Overall, for similar papers, having at least one female author reduces the probability of omitting other women’s papers by up to 10 percentage points, whereas having only male authors increases the probability of being omitted by almost 4 percentage points. Second, the omission bias is twice as high in theoretical fields that involve mathematical economics than it is in applied fields such as education and health economics. Third, men benefit twice as much as women from publishing in a top journal, in terms of likelihood of being omitted. Lastly, being omitted with respect to past publications affects future productivity and reduces the probability of getting published in a top journal. Finally, peer effects and more editorial board diversity tend to counteract and reduce the omission bias.

Ansprechpartnerin: Marina Chugunova

Using data from a prominent online platform for launching new digital products, we document that the composition of the platform’s ‘beta testers’ on the day a new product is launched has a systematic and persistent impact on the new product’s success. Specifically, we use word embedding methods to classify products launched on this platform as more or less focused on the needs of women customers, and show that female-focused products launched on a typical day – when the majority of beta testers are male – experience 30% less growth and are 3.5 percentage points less likely to be operating a year after launch. Exploiting exogenous variation in the composition of users who visit the platform we find that this product gender gap shrinks to zero on days when more female beta testers are present on the website, suggesting that it is the composition of early users, rather than unobserved differences in the growth potential of products catering to women, that is driving our results. Our findings highlight the importance of understanding sampling bias in entrepreneurial experiments and how such bias may lead to a dearth of innovations aimed at consumers who are underrepresented among early-users. (Joint work with Rembrand Koning and Ruiqing Cao)

Ansprechpartner: Rainer Widmann

The debate surrounding escalating prescription drug prices has increasingly focused on the legitimacy of the practice of brand-name manufacturers receiving patent protection on peripheral features of the drug such as the route of administration, as opposed to just the active-ingredient itself. The key question is whether these later-obtained, secondary patents protect novel features and represent true innovation or, instead, provide little to no innovative benefit and improperly delay generic entry. In this paper, we explore how the Patent Office may improve the quality of the secondary patents issued – thereby reducing the degree of unnecessary and harmful delays of generic entry – by giving examiners more time to review patent applications. Our findings suggest that current examiner time allocations are causing patent examiners to issue low quality secondary patents on the margin. We further set forth evidence suggesting that the costs to investing in greater ex ante scrutiny of secondary pharmaceutical patent applications by the Patent Office are greatly outweighed by the benefits, which include the avoidance of downstream litigation expenses and gains to consumer and total surplus from reduced drug prices.

Ansprechpartnerin: Lucy Xiaolu Wang

Understanding the factors affecting the direction of innovation is a central aim of research in the economics and strategic management of innovation. Progress on this topic has been inhibited by difficulties in measuring the location and movement of innovation in ideas space. We introduce and explore an approach based on an unassisted machine learning technique, Hierarchical Dirichlet Process (HDP), that flexibly generates categories from a corpus of text and enables calculations of the distance and movement in ideas space. We apply our algorithm to patent abstracts from the period 2000-2018 and demonstrate that, relative to the USPTO taxonomy of patent classes, our algorithm provides a leading indicator of a shift in innovation topics and enables a more precise analysis of movement in ideas space.

Ansprechpartner: Michael E. Rose

This paper analyses the effect of strategic patenting on firm and competitor performance, productivity, innovative output and market concentration. Using a novel definition of strategic patenting, this paper finds a positive effect of strategic patenting on market concentration. The results for the patentee show a positive effect of profit growth, and positive but significantly smaller contribution of strategic patenting to total factor productivity compared to novel technological patents. In contrast, peers suffer from a decrease in total factor productivity, innovative output and both profit and sales growth following strategic patenting by the focal firm. These findings suggest a conflict between patent policies designed to promote innovation while still providing incentives for the firms to capture market share and defend monopolistic positions.

Ansprechpartner: David Heller

In many countries formal, professionally managed establishments have significantly higher productivity than informal work arrangements which are often conducted from home. To understand the impact of these establishments on productivity we use a field experiment in India to test how much of the effect is due to a causal treatment effect versus workers self-sorting into more productive work arrangements. We find a strong positive treatment effect of working from the office, but negative sorting on productivity. Even productive employees choose working from home despite the negative treatment effect, especially if they have domestic responsibility such as child care. The effect is stronger for women and families with children.

Ansprechpartnerin: Marina Chugunova

Studying 5.6 million biomedical science articles published over three decades, we show that controlling for selective attrition reconciles conflicts in a longstanding, interdisciplinary literature. While research quality declines monotonically over the career, this decline is easily overlooked because the highest “ability” authors have the longest publishing careers. Our results have implications for broader questions of human capital accumulation over the career and also for federal research policies that shift funding from late- to early-career researchers – while providing more funding to researchers when they are most creative, these policies must be undertaken carefully because young researchers are less “able” on average.

(Joint work with Huifeng Yu, Gerald Marschke, Matthew B. Ross and Joseph Staudt)

Ansprechpartner: Rainer Widmann

What is the relationship between science and market structure? We answer this question using the natural experiment of the NDM-1 (New Delhi Metallo-Beta-Lactamase 1) superbug discovery in India reported in August 2010 in Lancet Infectious Diseases. This article shows that NDM-1 superbug was resistant to the broad-spectrum antibiotics carbapenems, widely recognized as a weapon of last resort against infectious bacterial diseases. Using a difference in differences strategy, we find that multinational firms reduced their market share in sales of carbapenems (treated markets) in India compared to narrow-spectrum antibiotics (control markets) immediately after the NDM-1 2010 discovery. We also document a concurrent shift in the prescription behavior of physicians and associated shifts in channel incentives. Our results are robust to pre-trends, alternative controls and account for regional heterogeneity. The results are consistent also with synthetic controls. We are also able to show differential multinational responses given their apriori variation in capabilties from scientific alertness. Our findings have implications for the apriori information revealing role of science for resolving managerial uncertainty within firms and for the ex-post role of social planners in correcting market failures in healthcare. In addition, with the WHO issuing recent warnings around antimicrobial resistance during our current COVID-19 crisis, our results have important current healthcare policy implications. (Joint work with Mayank Aggarwal & Anindya Chakrabarti, IIM Ahmedabad)

Ansprechpartner: Rainer Widmann

Das Max-Planck-Institut für Innovation und Wettbewerb, die Technische Universität München und BRICK, Collegio Carlo Alberto, organisieren den jährlichen Workshop “The Organisation, Economics and Policy of Scientific Research”.

Das Programm zum Download liegt hier.

We present a new platform for large scale networks experiments in continuous time and conduct three experiments on it: groups range from 8 all the way to 100 subjects. These experiments involve pure linking games as well as games with linking and public goods provision.

The major finding is that subjects create sparse networks that are almost always highly efficient. In some cases networks have a very unequal distribution of connections and exhibit small average distances, while in others subjects create equal and dispersed large distance networks. In some cases highly connected nodes earn vastly more while in other cases they earn significantly less than their less connected cohort. Informational overload helps in explaining why highly connected nodes make excessive investments but earn less than the spokes. (Joint work with Syngjoo Choi and Frédéric Moisan)

Ansprechpartner: Michael E. Rose