Veranstaltungen

This paper studies the relationship between climate policy, market power and innovation. Using data on patenting and firms' balance sheets, I document four stylized facts. Most importantly, I find that firms with a higher degree of market power are, on average, more invested in dirty technologies than their direct competitors. Motivated by the empirical evidence, I develop a model of directed technical change with strategic innovation incentives. A carbon tax affects market power within industries due to technology lock-in and firm heterogeneity. Strategic incentives lead some firms to respond to climate policy by increasing their dirty innovation investments. In the calibrated model, a carbon tax lowers aggregate markups and increases clean innovation along the green transition, highlighting the importance of firms' strategic decisions for climate policy.

Ansprechpartner: Fernando Loaiza

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Das Munich Summer Institute (MSI) wird veranstaltet von Center for Law & Economics der ETH Zürich, der Universität Lausanne, der Cornell University, dem Imperial College, dem Lehrstuhl für Technologie- und Innovationsmanagement der TUM, dem Lehrstuhl für Innovationsökonomie der TUM, dem Institut für Strategie, Technologie und Organisation (ISTO) der LMU München und dem Max-Planck-Institut für Innovation und Wettbewerb.

Weitere Informationen auf der Webseite des MSI

The workshop will cover the MSI’s three focus areas:

• Digitalization, Strategy and Organization
• Innovation and Entrepreneurship
• Law & Economics of Intellectual Property, Innovation & Digitalization

Like the Munich Summer Institute, the MSI Ph.D. Workshop will focus on quantitative empirical research. In the workshop, participants will present their working papers, receive comments from senior scholars, and discuss their papers with other participants. The number of participants is limited. Discussants will be senior scholars who participate in the Munich Summer Institute’s main conference.

Program

We advance the proxy variable approach to production function estimation. We show that the invertibility assumption at its heart is testable. We characterize what goes wrong if invertibility fails and what can still be done. We show that rethinking how the estimation procedure is implemented either eliminates or mitigates the bias that arises if invertibility fails. In particular, a simple change to the first step of the estimation procedure provides a first-order bias correction for the GMM estimator in the second step. Furthermore, a modification of the moment condition in the second step ensures Neyman orthogonality and enhances efficiency and robustness by rendering the asymptotic distribution of the GMM estimator invariant to estimation noise from the first step.

Ansprechpartner: Jordan Bisset

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Mehr Information auf der SIPLA Webseite

The Munich Center for Transformative Technologies and Societal Change (TransforM) invites you to our first installment of the TranforM Futures public event series.

Let's talk about MOONSHOT INNOVATIONS! This event will feature a panel discussion with experts at the nexus of academia and industry with a focus on when, why and how moonshot innovations emerge, scale-up and effect real societal change. Following the discussion, there will be a chance for audience interaction and networking.

Registration

We examine how artificial intelligence impacts three core pillars of collaboration—performance enhancement, expertise integration, and social engagement—through a pre-registered field experiment with 791 professionals at Procter & Gamble, a global consumer packaged goods company. Working on real product innovation challenges, professionals were randomly assigned to work either with or without AI, and either individually or with another professional in new product development teams. Our findings show that (1) AI significantly enhances performance: individuals with AI matched the performance of teams without AI, suggesting that AI can effectively replicate certain benefits of human collaboration. Moreover, (2) AI helps bridge functional silos: without AI, R&D professionals tended to suggest more technical solutions, while Commercial professionals leaned toward commercially-oriented proposals. Professionals using AI produced more balanced solutions, regardless of their professional background. (3) AI’s language-based interface prompted more positive self-reported emotional responses among participants, suggesting it can fulfill part of the social and motivational role traditionally offered by human teammates. Finally, decomposing the innovation process suggests that AI primarily enhances the quality of generated ideas, shifting the distribution of creative output upward, while human judgment retains value in evaluative selection. This finding highlights the multiple and complementary roles that human and AI partners can play in new product development tasks and creative problem solving. More generally, our results suggest that AI adoption in knowledge work affects not only performance but also how expertise and sociality appear within teams, offering insights into the impact of GenAI on collaborative work within organizations.

Ansprechpartnerin: Marina Chugunova

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

The idea that inventions are solutions to specific technical problems is foundational to innovation research—yet, so far, there is no systematic way of measuring which problem an invention addresses. The problem that a battery overheats, for instance, may be solved through inventions in electrochemistry, materials science, or mechanical engineering. In existing patent data, these solutions would appear unrelated, because the data are organized around the technology employed, not the problem addressed. This missing problem dimension means we cannot observe which technical problems attract competing solutions from different fields, how broadly firms search across alternative solution paths, or how inventive labor is divided between those who recognize problems and those who develop solutions. This project constructs a new dataset that makes the link between inventions and the problems they address visible at scale.

Ansprechpartnerin: Elisabeth Hofmeister

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.

Weitere Informationen

We use quasi-random local variation in the number of young men who died as a result of World War I to estimate the impact of this demographic shock on innovation and structural change in France. Our analysis shows that excess mortality led to an increase in patenting activity in counties with high pre-war education levels, driven predominantly by innovations in labor-saving technologies. Our estimates imply that an additional 6,000 patents were filed in the 15 years following the war, amounting roughly to the average annual number of patents filed pre-war.We find a positive association between war-related mortality and wage growth as well as with the adoption of machines in the agricultural sector, providing additional evidence that incentives to escape labor scarcity are driving the innovation response to mortality.

Ansprechpartner: Dominik Asam

Eintragung in den Einladungsverteiler und mehr Informationen auf der Seminarseite.