A Model of Optimal Software Patent Policy Design

1. A Model of OptimalSoftware Patent Policy Design Professor Matt Thatcher

2. Trade Secret Laws • Uniform Trade Secrets Act (UTSA) • gives right to companies to keep certain information secret (to maintain competitive edge) • covers formulas, patterns, programs, devices, methods, processes • Must have the following characteristics: • be novel • represent economic benefit to firm • involved some cost and effort to develop • is generally unknown to the public • company must show effort to keep the information secret

3. Trade Secret Laws (cont.) • Problems: • Software often must be put into the public realm, making it difficult to keep secret (and generally unknown to the public) • does not protect from independent discovery • Economic Espionage Act (1996) • penalties: up to $10 million and 15 years prison for theft of trade secrets • IP lost in industrial espionage  > $300 bill / year

4. Trade Secret Laws (cont.) • How do you show you are keeping information secret? • identify all information to be protected • label it confidential • educate employees of importance of trade secrets • make only accessible to limited # of people on a need-to-know basis • develop non-disclosure agreements • develop non-compete clauses • Compuserv v. IBM (2005) • technology protections • firewalls, encryption, secure databases, etc.

5. Why Do Firms Patent Software? Number of Software Patents Issued Per Year [Bessen and Hunt (2004)]

6. Improvement to the Basic Product Patent Width (w = h - ) Patent Height (h) Allowable Imitation () Basic Product (s = 0) Patent Height: Protection from improvements Patent Width: Protection from imitation Patent Length: Duration of protection

7. Patent Laws • Requires that innovation under review must be: • new, useful, and non-obvious to a person of ordinary skill in the relevant field • Once awarded, a patent provides patent-holder: • scope of protection from imitation for 20 years • protects functions/behaviors of the program • protects from independent discovery • Cannot patent • abstract ideas, laws of nature, scientific principles

8. Patent Laws (cont.) • U.S. Patent and Trademark Office (USPTO) • patent examiners (~3000) search for prior art • existing body of knowledge that is available to a person of ordinary skill in the art • what is the problem with this in the software arena? • determine originality and novelty • ~ 25 month application process • details about patented innovations are placed in the public domain • No limit to monetary penalty

9. Debating Patent Policy Design • Why reform the U.S. patent system? • Samuelson (2004) • What is wrong with software patent quality? • patent height is too low! • patent width is too wide! • patent length is too long! • Economic perspective • National Academies(2004) • Federal Trade Commission(2003)

10. Research Questions • What is the target of feasible patent policy designs? • Which policy designs in the target • are good/bad for society? • are good/bad for consumers? • Which policy design is socially optimal? • How do changes to an established policy design affect social welfare? That is, what happens if the authority • increases height? • narrows width? • shortens length? • Should software products be patentable at all?

11. Model of Duopoly Competition(R&D Race / Product Improvements / Price) • Pre-game • posit a basic, well-known software product • where quality of basic product is normalized to zero • Free Market Competition (No Patent Model) • Stage 1: two firms compete in R&D to develop a novel idea • Stage 2: the innovator (n) transforms a novel idea into an improvement (sn > 0) to the basic product at substantial fixed cost, C(sn)=ksn2 /2 • Stage 3: the imitator (m) observes the innovator’s product improvement and decides to what extent it will imitate at zero fixed cost, sm [0,sn] • Stage 4: the firms simultaneously set prices and offer products, where MC(sn) = MC(sm) = 0

12. Vertically Differentiated Demands (Stage 4) • Individual’s utility function: • Individuals’ purchase decisions: • Solving for product demands:

13. Graphical Representation of Demand (Stage 4)

14. Graphical Representation of Demand(Stage 4)

15. Solving for Prices (Stage 4) • Firms’ profit functions: • Profit functions (given quality levels) are concave in prices: • First Order Conditions (F.O.C.s): • Solving the F.O.C.s gives:

16. Performance Measures (Stage 4) • Firms’ profit functions (after substitution): • Consumer surplus function: • Social welfare function:

17. Solving for Imitator Quality(Stage 3) • Imitator profit function: • Profit function is concave in quality: • F.O.C.: • Solving the F.O.C. gives the imitator’s best response function:

18. Solving for Innovator Quality(Stage 2) • Innovator’s profit function is concave in quality: • F.O.C.: • Solving the F.O.C. gives the free market outcome (MO) values:

19. The Patent Model • Patent policy is set before the game begins: • patent height (h) • patent imitation level () • patent length (t) where 0 <  < h and t [0,1] • Which policies give the innovator profit incentive to seek a patent?

20. Conclusions • The POR is the target of feasible patent policy designs • Impact of changes to established policy design on social welfare •  patent length   social welfare • but contracts the POR and eliminates good policy options •  patent width   social welfare •  patent height   social welfare if patent is long and high • Optimal patent policy design • max length and set height/width to intermediate levels • if length is short  set the highest, widest policy in the POR • reduces R&D incentives to discover a novel idea • Is policy too low, too wide, and too long? • it depends!!!! • many factors may prevent the policymaker from identifying the POR or hitting a good

21. Questions?