Events

From 10 to 11 December 2018, the Max Planck Institute for Innovation and Competition will organize the first junior researcher workshop:

From Science to Innovation

The goal of the workshop is to stimulate a rigorous in-depth discussion of a number of selected research papers. It offers PhD students and junior Post-docs an opportunity to present their work, receive feedback and connect with peers from other departments. Each paper will be discussed by a discussant. The workshop will be held at the Max Planck Institute for Innovation and Competition, room E10.

Overview
The workshop will focus on the following areas:

• Economics of Science and Innovation
  

• Human Capital in the Science Production Function
• Financial Incentives in Science
• Corporate Strategy to Access Scientific Knowledge
• Organization of Innovation within Firms
• Knowledge Spillovers between Firms




• Legal Analysis of Knowledge Approbability
  

• Knowledge Appropriability in R&D Partnerships
• Big Data Ownership and Accessability

We are happy to announce Jeff Furman (Boston University & NBER) as our keynote speaker who will also provide feedback during sessions.

Program
The full program is available here. Should you be interested in attending the workshop without paper presentation, please contact us directly no later than October 31. There is only a small number of places available.

Max Planck Institute for Innovation and Competition, Room E10

Further information
Any questions concerning the From Science to Innovation workshop should be directed to Dennis Byrski.

Full-day workshop

Contact: Dr. Matthias Lamping

Website IPDR-Forum

Max Planck Institute for Innovation and Competition, Munich, Room 313

 Considering that both patents and trade secrets can promote knowledge diffusion via licensing, we compare patents and secrets on the way they facilitate diffusion through non-exclusive licensing. This comparison is important because AI algorithms are not patentable. Patents differ from trade secrets on the easiness of imitation when licensed to many downstream producers. In view of this, we argue that secrets are better in defending one’s monopoly under the threat of imitation, inducing market failure on the diffusion of AI. We also find a non-linear relationship between patent strength and the diffusion of ideas, i.e., patents of intermediate patent strength are best as diffusion instruments.

Contact: Dr. Fabian Gaessler

Toshiko Takenaka, Hunter Simpson Professor of Technology Law, University of Washington School of Law

Max Planck Institute for Innovation and Competition, Room E10

We would like to kindly ask you to register before 21 November by sending an e-mail to elisabeth.amler(at)ip.mpg.de.

Max Planck Institute for Innovation and Competition, Munich, Room 313

We theoretically derive a simple rule for the optimal patent breadth and duration of pharmaceutical patents. The rule requires only data on generic firms’ investments in imitation prior to the expiry of originator patents. We then test the rule using a unique patent level data set from the US. Paragraph IV challenges offer a clear metric of imitation and patent term extensions create the variation in patent term. Using two quasi-experimental approaches and newly constructed data, we document that extending patent length increases incentives to imitate whereas broadening patents reduces these incentives. Our results together suggest that effective terms of new drug patents should be made shorter and delays in commercialization of new drugs should be compensated by increasing breadth.

Contact: Felix Poege

The lecture will be held in German.

Vorab wird im Rahmen der „Aktuellen Viertelstunde“ Frau Dr. Katharina Kolb, Associate bei Milbank in München, über die „Reichweite der Schadensvermutung im Kartellschadensersatzrecht im Lichte der jüngsten Rechtsprechung“ referieren.

Wie immer lädt das Münchner Kartellrechtsforum anschließend zum informellen Austausch bei Getränken und Häppchen ein.

Wir freuen uns auf Ihr Kommen und bitten um Anmeldung bis zum 15.11.2018 bei delia.zirilli(at)ip.mpg.de.

Abstract

Governments have increasingly been using predictive algorithms created through the use of machine learning to assist them in making a wide variety of decisions. They consult predictive algorithms about everything from promoting teachers to assigning police patrols, paroling prisoners, and investigating child welfare. When the governments in question are democratic, there must be some way for citizens to hold them accountable for their use of these algorithms, and to consider whether the algorithms are inaccurate, biased, or otherwise flawed. Yet that kind of accountability requires an understanding of how such algorithms are constructed, and requires disclosure by governments of the choices made and the tests performed during such construction.

This talk will walk through the process of constructing a predictive algorithm, and consider the value choices made in doing so. It will then present the results of a study that filed 42 open records requests in 23 states to seek information about six predictive algorithm programs. That study concludes that most governments do not currently disclose enough information about predictive algorithms to enable evaluation of their accuracy and fairness. Publicly-deployed algorithms will be sufficiently transparent only if (1) governments generate appropriate records about their objectives for algorithmic processes and subsequent implementation and validation; (2) government contractors reveal to public agencies sufficient information about how they developed algorithms; and (3) public agencies and courts treat trade secrecy claims as the limited exception to public disclosure that the law requires.

Speaker Bio

Robert Brauneis is Professor of Law and Co-Director of the Intellectual Property Law Program at the George Washington University Law School. He is a founding member of the Project Board of the Munich Intellectual Property Law Center. He is also a past President of the Giles Rich Inn of Court and a Trustee of the Copyright Society of the USA, and is an Advisor to the Restatement of the Law, Copyright. 

Moderation: Victoria Rivas

Max Planck Institute for Innovation and Competition, Room E 10

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

The effects of increases in external funding on firm-level patenting are empirically investigated. Results indicate that the impact of finance on inventive activities is more multilayered than commonly suggested. In fact, changes in the level of funding affect value-relevant characteristics of patents filed. In a quasi-natural experimental setup, staggered and country-specific legislative amendments of the European financial market harmonization during the 2000s are utilized as an exogenous shift improving firms’ access to funding. First, it will be shown that financial integration leads to increased bank lending to ex ante financially constrained firms. Second, it will be analyzed whether affected firms changed their patenting activities. The finding is that increased funding is associated with more patents in quantitative terms but of lower average technological quality and value. Further, affected firms alternate towards filing fewer explorative (i.e., impactful and generally applicable) but rather incremental patents. By providing new insights on the relation between finance and firm-level inventions, the results therefore suggest that it is important to acknowledge potentially diverse effects arising from improved access to funding.

Contact Person: Zhaoxin Pu