1 Alternative Mechanism for Technology Transfer: Licensing YoungJun Kim Department of Economics The George Washington University

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1 Alternative Mechanism for Technology Transfer: Licensing YoungJun Kim Department of Economics The George Washington University

2 Why We Should Care About Licensing  Promote Technology Diffusion: existing technologies face a better chance of being used extensively.  Enhance Technology Innovation: firms invest extra dollars in R&D since technology innovator can profit from their technologies even if they do not commercialize them on their own.

3 Recent Evidences   Inefficiency of licensing market: large companies in United States, Western Europe, and Japan ignore a large portion of their patented technologies, which could be licensed or profitably sold, British Technology Group (1998)   Significant use of licensing: average of 1,150 licensing transactions worth $25 billion per year occurred worldwide in technology-intensive industries in the period of , Arora, Fosfuri and Gambardella (2001)

4 Purpose of Study Understanding of technology holders’ incentives to license their technology, theoretically and empirically Why do firms license their technology? Are there differences in licensing activities across firms, industries and technologies? What factors affect firm’s licensing behavior?

5 Two Main Effects of Licensing (i) revenue effect (positive): a fixed licensing fee and royalty payment from an additional licensee (ii) competition effect (negative): profit of incumbent licensor firm is dissipated due to an increased competition with new entrant licensee at the product market

6 Theoretical Model Assumptions:  N (i = 1,2,…,N) technology (i.e. patent) holders (licensors)  Many potential licensee firms who can produce once they obtain technology from one of technology holders  Technologies (products) are differentiated - across technology holders, and across a technology holder and its licensees  Knowledge is imperfectly appropriable

7 Game Structure  The first stage (“Competition at the technology market”): each incumbent technology holder decides how many licenses to sell to entrant licensees  The second stage (“Competition at the product market”): all firms – both licensors and licensees – that have technology supply products

8 Theoretical Results The strong IPR (patent) protection induce technology holders to license more Technology holders license more the more homogeneous is the technology (product) across technology holders Technology holders license more the more differentiated is the technology (product) across a technology holder and its licensees Transaction costs affect technology holders’ incentives to license negatively

9 Empirical Analysis Data source ‘Innovation Network Database (INNET)’ by the Center for International Science and Technology Policy, The George Washington University:  ’Strategic Alliances Database’ complied by Thomson Financial’s SDC (Securities Data Company)  ‘CompuStat’ by Standard & Poor; financial information of companies (sales, R&D expenditures,…)  ‘Patent Database’ by USPTO

10 Total Number of Licenses Sold by Industry, Sample (786 firms): Publicly-held firms that provide all necessary information from 1990 to 1999 SIC 73=Business Services; SIC 36=Electronic & Other Electronic Equipment; SIC 28=Chemicals; SIC 35=Industrial Machinery & Equipment; SIC 38=Instruments & Related Products

11 Firm Licensing Frequency Distribution,

12 FirmNumber of Licenses Sold 1. IBM54 2. Microsoft42 3. Apple Computer29 4. Qualcom Inc28 5. Sun Microsystem28 6. Hewlett-Packered Co26 7. Texas Instrument26 8. Intel Corp23 9. Adobe Systems Inc Motorola Corp18 Leading Licensors,

13 Methodology Econometric model for count panel data Fixed effects negative binomial (Negbin) model by Hausman, Hall, and Griliches 1984 Overcome ‘unobserved heterogeneity’ and ‘overdispersion’ problem

14 Variables Dependent variable: Number of licenses sold by firm i at time t. Independent variables: (a) Characteristics of licensor firm i at period t Firm i’s patent stock at t Firm i’s patent stock at t-1 Sales of firm i at t (b) Characteristics of industry of firm i at t Concentration ratio of industry Growth rate of industry Patent intensity of industry Dummy for ‘infrastructural’ industry that belong to Information and Communication technologies (ICTs), biotechnologies, and advanced materials; Strength of industry IPR

15 Empirical Results  Firms with bigger patent stock license more  Large firms license more  Firms in high-concentrated industry license less  Firms in high growing industry license more  Firms in patent-intensive industry license more  Firms in ‘infrastructural’ industry license more  Firms in strong IPR industry license more

16 Policy Implications   What is the optimal level of Intellectual Property (IP) protection?   Tension between Intellectual Property Rights (IPRs) and Antitrust