Learning, Externalities, And The Sale Of Inventions To Firms With Correlated Valuations

I examine how an inventor's ability to learn affects the bargaining outcome when she attempts to sell a discovery to one of two oligopolistically competitive firms with correlated and private valuations. It is shown that learning gives the inventor an incentive to lower her proposed price to the first firm approached since being rejected would cause her to be pessimistic when dealing with the second firm. At the same time, however, the inventor would like to raise her proposed price since this pessimism is weaker if she is rejected upon making a high proposal. Another incentive to raise the proposal comes from the fact that learning increases the first firm's willingness to pay for the invention. Computational results suggest that the first effect dominates and thus the inventor lowers her proposal in the first round. When dealing with the second firm, it is shown that learning results in a lower equilibrium proposal and contracting with more types. Moreover, it is shown that the cost of lowering the proposed price outweighs the benefit of contracting with more types so that learning in general reduces the continuation value associated with contracting in the second round.