Never-ending Search for Innovation
Jean-Michel Benkert, Igor Letina

TL;DR
This paper presents a dynamic model of innovation investment where researchers choose among multiple projects, showing that ongoing search continues indefinitely until success, which may never occur with positive probability.
Contribution
It introduces a novel dynamic framework modeling innovation search with multiple projects and demonstrates that the optimal strategy involves never ending the search until success.
Findings
Search continues indefinitely until success is found
Positive probability that the search never ends
Optimal investment strategy involves persistent exploration
Abstract
We provide a model of investment in innovation that is dynamic, features multiple heterogeneous research projects of which only one potentially leads to success, and in each period, the researcher chooses the set of projects to invest in. We show that if a search for innovation starts, it optimally does not end until the innovation is found -- which will be never with a strictly positive probability.
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Taxonomy
TopicsDiffusion and Search Dynamics · Innovation Policy and R&D · Intellectual Property and Patents
MethodsSparse Evolutionary Training
