1 / 10

Commentary

Commentary. Comments on Rogers et al. An analysis of the characteristics of small and medium enterprises that use intellectual property, and An analysis of the association between the use of intellectual property by UK SMEs and subsequent performance Stuart Graham UC Berkeley and Georgia Tech.

huy
Download Presentation

Commentary

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Commentary • Comments on Rogers et al. • An analysis of the characteristics of small and medium enterprises that use intellectual property, and • An analysis of the association between the use of intellectual property by UK SMEs and subsequent performance Stuart Graham UC Berkeley and Georgia Tech

  2. Summary • Two reports, related • Description of new dataset • Exciting • Comprehensive • Some beginning analysis • Relationship (econometrically) between use of intellectual property and various characteristics

  3. Report 1: Comments, in general • Give me more confidence statistically • T-stats and p-values, std. error, std. dev. • Probably all ok with your large numbers, but show them just the same • Give me more information about the variation in your data • Explore some of the “unstated” relationships and potential explanations for what you see, or don’t see, in the data

  4. Tables 4-5: Survivorship, Distribution, Normalize

  5. Tab 9 & 10: Who, and What

  6. Table 11 & 12: Survivors and Sectors

  7. Table 13: DV = IP Intensity: quadratics in age and size • Yes, curved, but only marginally 1bn

  8. Report 2: Amount of IP • One patent ≠ another patent, same with TM • Weight / correct for • Cites? Claims? Words? Family size? • Table 3: What share exited, when? • Age dynamics of time • By Sector!!! • Table 7: Probit Regressions • Give me some reduced form models testing specific RQ’s or H1, H2, etc. prior to “full model” • Control from size/quality of IP

  9. Shameless plug • 13,000 technology startups • Software and allied, Biotechnology, Medical Devices, other sectors • In the field now, US • Mit der ZEW, jetz in Feld.

  10. In sum • Heroic effort, wonderful new data • Hooray! • More statistics, more analysis • Match up with survey data (extant, generate) • One Appendix on the CIS • Self-generate survey data • Looking fwd. to what you do with it

More Related