Although previous empirical studies have found relationships between patent characteristics and value, none have determined how specific attributes relate to auction value or even the probability of a successful auction sale. Using a Heckman two-step model, we regress thirteen independent variables against unique patent auction data, finding that publicly-owned and frequently referenced patents are more valuable, and that other things equal, there is an optimal time to offer a patent up for auction.
This paper evaluates the contribution of patent-related events to changes in stock prices, proposing that economics has traditionally failed to find much effect for two reasons which we identify and correct. First, patents vary widely in quality so we use quantile analysis and alternative measures of patent quality to identify effects. Second, we permit the possibility that information leaks out into investor sentiment during the long and uncertain time until patent grant, so evaluate the stock price effect at four different dates in the life of each patent. As a case study to test this approach, track all patents over a 27-year period for Apple Inc., permitting design patents to have different effects that traditional utility-model patents, and isolate the effect that Steve Jobs’s name on a patent has at each stage of a patent’s life.