Krishwords

One of the three Nobel Prize Winners in Economics this year (2007) is Eric S. Maskin. I am reproducing the conclusion of his recent paper.

Intellectual property appears to be an area in which results that seem secure in a static model may be overturned in a sequential setting. The prospect of being imitated inhibits inventors in a static world; in a dynamic world, imitators can provide benefit to both the original inventor and to society more generally. Patents may be desirable to encourage innovation in a static world, but they are less important in a sequential setting, where they may actually inhibit complementary innovation.

The static-sequential distinction is more than just a theoretical nicety. Indeed, it may help resolve a puzzle emanating from the U. S. natural experiment in software patents. Strikingly, the firms that obtained the most software patents (largely firms in the computer and electronics hardware industries) actually reduced their R&D spending relative to sales after patent protection was strengthened (Bessen and Hunt 2004). This behavior is difficult to reconcile with the static model, in which the prospect of patents should encourage R&D, but is quite consistent with the sequential model and specifically Proposition 7.

Thus we would suggest a cautionary note about intellectual property protection. The reflexive view that “stronger is better” could well be too extreme; rather, a balanced approach seems called for. The ideal patent policy limits “knock-off” imitation, but allows developers who make similar, but potentially valuable complementary contributions. In this sense, copyright protection for software programs (which has gone through its own evolution over the last decade) may have achieved a better balance than patent protection.

In fact, this is the premise behind open source. Open source, by allowing “imitation”, helps companies and organizations innovate. We have seen many examples of such an innovation including Linux, Apache, MySQL, etc. If we even look back further, we can note that science had the same kinda approach from the beginning. Sharing of knowledge leads to innovation. Software is knowledge and its sharing is crucial in future innovations.