The Economics of AI, Innovation, and Technological Change

Abstract

This course explores how innovation and AI drive growth, reshape production, and create policy challenges. It covers innovation economics, intellectual property, AI’s role in technological change, and methods to measure innovation, preparing students to analyze impacts on firms, markets, productivity, policy, and write successful funding proposals.

Objective

After taking this course, students will be able to: • Analyze how innovation and artificial intelligence affect production, firm behavior, and economic growth. • Apply economic models of innovation (e.g., task-based production, spillovers, competition) to real-world settings. • Assess the role of market structure and externalities in shaping innovation incentives and outcomes. • Evaluate the design and effectiveness of innovation policies, including IPR, R&D subsidies, and targeted funding programs. • Measure technological progress and innovation using both traditional indicators (e.g., TFP, patents) and AI-based methods. • Integrate theoretical and empirical insights to develop and present a coherent innovation funding proposal.

Content

1) Production, Technology, and AI • Production functions and the role of technological change • Directed technical change and endogenous innovation • Task-based models of production and automation • Integration of AI into task-based production frameworks • Knowledge spillovers, networks, and diffusion mechanisms - Network structure and firm centrality in innovation - Optimal R&D investment under network spillovers • Empirical identification of spillovers using AI-based methods - Text data (e.g., news) and hyperlink/network data 2) Innovation, Market Structure, and Market Failures • Competition, market power, and innovation incentives • Schumpeterian vs. Arrowian innovation dynamics • Externalities in knowledge production and diffusion • Sources of market failure in innovation (appropriability, coordination, information frictions) • Implications of AI for market concentration and entry barriers 3) Innovation Policy and Institutional Design • Intellectual Property Rights (IPR) and innovation incentives • R&D tax credits and direct subsidies - Policy design in the presence of spillovers and networks • Targeting and selection in innovation policy - Screening based on observables (e.g., business plans, firm performance) - Non-random selection and evaluation challenges • Overview of innovation policy instruments with a focus on Switzerland 4) Measuring Technological Change and Innovation • Total Factor Productivity (TFP) and its limitations • Patent-based measures of innovation output and quality • AI-based approaches to identifying breakthrough innovations • Web-based and alternative data sources for innovation measurement • Linking measurement to policy evaluation and firm performance 5) Applied Case: Innosuisse • Structure and objectives of Innosuisse funding programs • Practical insights from project coaching and evaluation • How funding decisions are made in practice • Best practices for preparing successful applications 6) Practical Component: Funding Proposal (Graded) • Development of a full innovation funding proposal • Integration of economic theory, empirical evidence, and policy design • Peer feedback and evaluation criteria aligned with real-world funding processes

Resources