Abstract

The valuation of patents is an important, albeit challenging task. Extant research to identify patent value indicators has so far relied on expert estimates of patent value, exploited patent renewal data, or depended on more indirect measures of patent value. Recently, specialized market places for patent transactions have emerged that allow us for the first time to directly observe patent's private value. One of the most prominent market places for patents is Ocean Tomo, a platform that offers periodical patent auctions. We make use of this auction data to empirically test predictions on patent value identifiers on real-world auction prices. We find empirical support for forward citations and the patent's family size; however, both indicators explain only a small variance in patent value. In contrast, our full model explains a large share of variance, making us optimistic that with increased directly observed patent value, such models can be useful tools in patent valuation.

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