Veranstaltungen

On 16/17 December 2019, the Max Planck Institute for Innovation and Competition will host the 2nd Research on Innovation, Science and Entrepreneurship Workshop, an annual workshop for Ph.D. students and Junior Post-docs in Economics and Management.

The goal of the RISE2 Workshop is to stimulate an in-depth discussion of a select number of empirical research papers. It offers Ph.D. students and Junior Post-docs an opportunity to present their work and to receive feedback.

Keynote speaker of the RISE2 Workshop is Pierre Azoulay (MIT & NBER).

Get the program here.
See RISE Workshop.

Max-Planck-Institut für Innovation und Wettbewerb, München, Raum 313

This paper estimates the social returns to investments in innovation. The spillovers associated with innovation, including imitation, business stealing, and intertemporal spillovers, have made calculations of the social returns difficult.  Here we deploy the core ideas of economic growth to provide an economy-wide, average estimate that nets out the many spillover margins.  We further assess the role of diffusion delays, capital investment, productivity mismeasurement, health outcomes, and international spillovers in assessing the average social returns. Overall, our estimates suggest that the social returns are very large.  Even under conservative assumptions, $1 invested in innovation efforts produces at least $5 of benefits on average.

Ansprechpartner: Rainer Widmann

The Workshop on Entrepreneurship and Innovation is supported by the Collaborative Research Center Transregio “Rationality and Competition” (CRC), the Ludwig-Maximilians-Universität (LMU Munich) and the Max Planck Institute for Innovation and Competition.

In case of any questions, please contact Marina Chugunova.

See Program

Max-Planck-Institut für Innovation und Wettbewerb, München, Raum 313

In this paper we investigate the effect of an unexpected increase in the availability of scientific articles on the follow-on scientific usage of the knowledge incorporated. We focus on the launch of Sci-Hub, a Kazakhstan-based website that provides free access to scientific literature, gathering data from the first three months of activity of the website (from September to December 2011). Then we link downloaded scientific articles to their corresponding bibliographical information retrieved from Web of Science. Finally we reconstruct the entire flow of citations pertaining to these scientific articles to measure the effects of a reduction in their access costs on their rate of usage within the scientific community. Our main hypothesis is that reducing the cost of accessing scientific knowledge lead to higher rates of knowledge usage by the scientific community. The introduction of Sci-Hub induced a large increase in citations to downloaded articles coming from scholars located in developing countries. This effect is persistent across article cohorts. As expected, the effect is absent when we consider citations whose scholars are located either in European developed countries or in the United States.

Ansprechpartner: Michael E. Rose

Max-Planck-Institut für Innovation und Wettbewerb, Raum 313

Max-Planck-Institut für Innovation und Wettbewerb

Weitere Informationen finden Sie hier:

https://www.southcentre.int/call-for-papers-september-2019/

Max-Planck-Institut für Innovation und Wettbewerb, München, Raum 313

It is by now well-documented that performance pay has positive effort and selection effects in routine, easy to measure tasks, but its effect in knowledge creation is much less understood. This paper studies the effect of performance pay on knowledge creation through effort and selection effects using the introduction of performance pay in German academia as a natural experiment. To this end, I consolidated information from various, unstructured data sources to construct a data set that encompasses the affiliation history and publication records of the universe of academics in Germany. The performance pay reform introduced attraction and retention bonuses, as well as relatively weaker on-the-job performance bonuses that take effect at a later point in time. I estimate the pure effort effect of these performance pay incentives in a difference-in-differences framework, comparing changes in research productivity of a treated cohort of academics, who receive performance pay because they started their first tenured position after the reform, with a control cohort that receives flat wages because they started their first tenured position just before the reform. I find a positive effort effect of performance pay that is economically large; amounting to a 12 to 16% average increase in research productivity. This increase manifests itself most robustly as an increase in research quantity and persists for a number of years. The effort response is strongest and most robust for less productive academics, with increases in pure quantity as well as quality-adjusted research output, while the average impact of the work of top quartile academics decreases. Performing textual analysis on paper abstracts to construct novelty and impact metrics, I find that the novelty of the work of top quartile academics declines. This work however does find more follow-on research in subsequent papers in the same field and is thus more impactful. I estimate the selection effect by analyzing the rate at which academics of different productivity levels switch to the performance pay scheme. I use the fact that the old and new wage schemes compare differently for academics at different ages, which gives rise to selection incentives that are inversely related to age. Exploiting this variation in a difference-in-differences framework, I find that more productive academics are more likely to select into performance pay. Hence, performance pay increases research output in academia through both effort and selection effects. However, because the effort effect is strongest for relatively less productive academics, while relatively more productive academics select into performance pay, the selection effect partially counteracts the impact of the effort effect.

Ansprechpartner: Marina Chugunova

Am 28. und 29. November findet die „Artificial Intelligence & Intellectual Property Conference” in Singapur statt. Die Veranstaltung, die von der School of Law der Singapore Management University (SMU) gemeinsam mit dem Max-Planck-Institut für Innovation und Wettbewerb und der juristischen Fakultät der Chinese University of Hong Kong (CUHK) organisiert wird, richtet sich an Wissenschaftler, politische Entscheidungsträger, Juristen und Vertreter aus der Praxis. Im Fokus des Programms stehen die rechtlichen Auswirkungen Künstlicher Intelligenz in verschiedenen Ländern. Diskutiert werden nicht nur theoretische Ansätze, sondern auch die Umsetzung neuer technologieorientierter Gesetze sowie Leitlinien für Regulierungsbehörden, die eine Änderung ihres IP-Rechts in Betracht ziehen.

Zur Website

Max-Planck-Institut für Innovation und Wettbewerb, München, Raum 313

The increasing use of algorithms in legal and economic decision-making has led to calls for a “right to explanation” to be given to the subjects of automated decision-making. A growing literature in computer science has proposed a vast number of methods to generate such explanations. At the same time, legal and social science scholars have discussed what characteristics explanations should have to make them legally and ethically acceptable. These debates suffer from two shortcomings. First, very little connection exists between these two strands of literature. Second, we do not know what effects such explanations would have on the behavior of decision subjects and on their perception of decision-making algorithms. In this field experiment, we aim to address these gaps by empirically testing how different types of explanations affect the subjects’ attitude towards decision-making algorithms. Distilling various factors that constitute a good explanation of algorithmic decision-making, we collect data on which factors are useful to decision subjects: local or global explanations, explanations which are selective, contrastive and/or are displayed as conditional control statements versus correlations. In the setting of a scholarship awarded by a machine learning algorithm to promising students, our experiment thus investigates which kind of explanations can lead to increased acceptance of algorithmic decision-making.

Ansprechpartner: Dr. Marina Chugunova

Die Phänomene im Zusammenhang mit der Entwicklung intelligenter Lösungen für die städtische Mobilität werfen Fragen in verschiedenen Rechtsbereichen auf, die das Zusammenspiel von Technologie, Recht und öffentlicher Ordnung aufzeigen. Diese komplexe Beziehung kann aus verschiedenen Blickwinkeln analysiert werden: aus der Perspektive des öffentlichen Sektors, aus der Perspektive des privaten Sektors und aus der Perspektive der Bürger.