Foundational Technology and Downstream Innovation: The Case of LLMs and Mobile Applications
How do applications amplify AI’s value?
I study innovation, competition,
and the digital economy.
I am a Ph.D. candidate in Economics at the University of Michigan. I am on the 2026–2027 job market.
Field: Industrial Organization
JOB MARKET PAPER
Can policy spur innovation?
Accepted for presentation at the 2026 Econometric Society European Winter Meeting.
I develop a dynamic oligopoly model to quantify the returns to R&D and the effects of innovation policies in product-line markets. In such markets, firms invest in R&D to advance the technological frontier and adjust their product menus to serve heterogeneous consumers and to compete with rivals. I apply the model to the desktop graphics processing unit (GPU) market, a duopoly between Nvidia and AMD. I find that, over 2011–2020, the average dollar of private R&D generates about $9 of within-market surplus net of that dollar, with the firms capturing $3 and consumers the remainder. I then compare the two levers of innovation policy: an R&D credit that lowers the cost of research, and product rebates intended to raise its reward. Counterfactual simulations reveal that public support generates far less surplus per dollar than the average social return to private R&D. A subsidy on frontier products can even discourage innovation: it may lower prices for consumers and raise the firms' profit, but reduce the incentive to advance the cutting edge.
How do applications amplify AI’s value?
What persuades consumers?
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