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DYNAMIC INCENTIVES IN A MODEL OF SEQUENTIAL INNOVATION
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We study the problem of introducing a sequence of innovations whose value is private information. We study three cases: patents, no-patents and patent-pools. With patents the probability of innovation decreases as the sequence progresses, converging to zero in the limit. Without patents, the probability of innovation is constant and generally higher than in the patents case. A patent-pool increases the probability of innovation in comparison with the patents case, and dynamic incentives imply a higher probability of innovation than in the static case, strengthening previous results in the literature. We show that innovation is suboptimal in the three cases analyzed
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Thu 3 Sep 2009 |
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DYNAMIC INCENTIVES IN A MODEL OF SEQUENTIAL INNOVATION.pdf
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