Events

Title and abstract will follow.

Contact person: Elisabeth Hofmeister

Subscription to the invitation mailing list and more information on the seminar page.

Title and abstract will follow.

C0ntact person: Daehyun Kim

Subscription to the invitation mailing list and more information on the seminar page.

Title and abstract will follow soon.

Contact person: Elisabeth Hofmeister

Subscription to the invitation mailing list and more information on the seminar page.

The Munich Summer Institute (MSI) is hosted by the Center for Law & Economics at ETH Zurich, University of Lausanne, Cornell University, the Chair for Technology and Innovation Management at TUM, the Chair for Economics of Innovation at TUM, the Institute for Strategy, Technology and Organization (ISTO) at the LMU Munich and the Max Planck Institute for Innovation and Competition.

Further information on the website of the 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. Participants are expected to have read all presented papers. The number of participants is limited to 12. Discussants will be senior scholars who participate in the Munich Summer Institute’s main conference.

Title and abstract will follow.

Contact person: Elisabeth Hofmeister

Subscription to the invitation mailing list and more information on the seminar page.

Title and abstract will follow soon.

Contact person: Elisabeth Hofmeister

Subscription to the invitation mailing list and more information on the seminar page.

Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid to how AI might change the nature of work itself. How do individuals, especially those in the knowledge economy, adjust how they work when they start using AI? Using the setting of open source software, we study individual level effects that AI has on task allocation. We exploit a natural experiment arising from the deployment of GitHub Copilot, a generative AI code completion tool for software developers. Leveraging millions of work activities over a two year period, we use a program eligibility threshold to investigate the impact of AI technology on the task allocation of software developers within a quasi-experimental regression discontinuity design. We find that having access to Copilot induces such individuals to shift task allocation towards their core work of coding activities and away from non-core project management activities. We identify two underlying mechanisms driving this shift - an increase in autonomous rather than collaborative work, and an increase in exploration activities rather than exploitation. The main effects are greater for individuals with relatively lower ability. Overall, our estimates point towards a large potential for AI to transform work processes and to potentially flatten organizational hierarchies in the knowledge economy.

Contact person: Cheng Li

Subscription to the invitation mailing list and more information on the seminar page.

Title and abstract will follow soon.

Contact person: Michael Rose

Subscription to the invitation mailing list and more information on the seminar page.

This study examines whether access to generative AI (GenAI) technologies affects entrepreneurial entry and, if so, how. We propose two mechanisms for a potential positive effect: (1) an augmentation channel that pulls prospective entrepreneurs into opportunity-driven entrepreneurship as they automate various peripheral tasks, and (2) an automation channel that pushes displaced wage workers into necessity-driven entrepreneurship as firms automate their core tasks. Leveraging the sudden release of ChatGPT, which democratized public GenAI access, we exploit industry variation in GenAI exposure for the science, technology, engineering, and mathematics (STEM) workforce in a difference-in-differences design. We find that GenAI access leads to increased incorporated entrepreneurship for individuals with higher GenAI exposure. Mechanism tests support the augmentation channel and reveal important heterogeneities in who benefits more from GenAI.
 

Contact person: Daehyun Kim

Subscription to the invitation mailing list and more information on the seminar page