1. Patent Quality, Intellectual Property Rights, and Technology Transfer in the Solar Sector: All in the Family?

2. Introduction Importance of green technologies increasing
Durban Conference and COP 21 (U.N. Climate Conference) highlighted concern with facilitating transfer of climate-change mitigating tech
Legally binding agreements commit countries to reducing CO2-causing emissions

3. Introduction Solar technology: Prices falling  expanding market
Global patenting in green tech ↑ ~20%/year between 1997–2008
Solar investments ↑ ~30% between 2013–2014
Solar PV capacity ↑ ~25% between 2014–-2015
Size of solar PV market 10x larger than last decade

4. Introduction Important questions emerge:
Do stronger IPR laws facilitate more transfer of solar technology?
Are higher-quality patents more likely to be filed abroad?
Turns out…
Answer depends on how “patent flows” are defined

5. Organization (1) What we know (aka, lit review)
(2) Patent equivalents vs. extended patent families
(3) Description of Study
(4) Results
(5) Conclusion

6. What We Know
Patent citations are good measure of patent quality and patent value
Forward vs. backward citations
Weighted better
Strengthening IPR laws has mixed effect on patent flows
Positive effect in middle- and high-income nations; no or negative effect in poor nations
Sector effects can differ

7. What We Know Disaggregated better Consider separate industries
Consider similar countries
In green sector, strengthened IPR laws have mixed results depending on type of technology
Positive, SS: wind, solar, hydro
No effect: biomass, geothermal, waste

8. Patent Equivalents vs. Extended Patent Families
No legal definition of these: Each organization (e.g., USPTO, EPO, WIPO, OECD) creates its own
Data for this study from European Patent Office (EPO)
EPO patent equivalents: Documents whose priorities are same
In other words, same declaration of priority, or patent document, has been filed in more than one place
AKA patent-to-patent or a “simple patent family”*
*Intellogist, 2016; EPO, 2016

9. Patent Equivalents vs. Extended Patent Families
EPO extended patent families: comprises “all the documents sharing – directly or indirectly (e.g. via a third document) – at least one priority. This includes all the patent documents resulting from a patent application submitted to a patent office as a first filing and from the same patent application filed within the priority year with a patent office in any other country”*
Wider definition than equivalent
*Espacenet, 2016

10. Patent Equivalents vs. Extended Patent Families
D2–D3: Equivalents, or simple family, because they share same priorities, P1 and P2
Extended families (last column) are much broader and include documents that are only indirectly linked to one another
Figure from European Patent Office, “Definitions,” Accessed

11. Patent Equivalents vs. Extended Patent Families
D2-D4 are in the same family (P2) because they share at least one priority with another member
BUT only D2 and D3 are associated with P1, but D4 is not
Yet, because of this indirect relationship, D2 and D4 are in the same family
Figure from European Patent Office, “Definitions,” Accessed

12. Patent Equivalents vs. Extended Patent Families
Research has shown that extended families may cover completely different inventions that are related only by sector
Figure from European Patent Office, “Definitions,” Accessed

13. Patent Equivalents vs. Extended Patent Families
Which is better?
Equivalents: Compare patent-to-patent, so researchers can follow trail of small piece of tech globally, from patent office to patent office
But products rarely contain only one patent
If intent is to track transfer of complete invention, equivalents may not be best method
Equivalent method could result in over-counting of technologies

14. Patent Equivalents vs. Extended Patent Families
Which is better?
Extended families: Compare technology-to-technology to track completed invention globally
Families are defined differently office to office
Indirect relationships determine family
Patents in family may not actually related
Not tracking one technology or invention

15. Description of Study
Based on theoretical and econometric framework of Gallini et al. (2006)
Dependent variable pijt: Number of patents filed from country i (U.S.) in country j in year t
pijt has high number zeros, so use negative binomial specification

16. Description of Study Variables of interest:
qual: weighted proxy for aggregate quality of patents being filed in country j from U.S. in year t
Equal to total number of citations received by all patents from U.S. filed in country j in year t divided by total number of patents filed in country j in year t
Theory predicts + effect

17. Description of Study Variables of interest:
ipr: Ginarte and Park index, measures “how strongly patent rights will be protected”* in a given country
Scale is measured from 0 to 5, with 0 representing the weakest patent laws and 5 representing the strongest patent laws
Expect + results (due to high level of R&D investment required)
*Ginarte and Park, 1997

18. Description of Study Control variables:
gdp: GDP and per capita GDP (+)
humk: Measure of human capital (+)
dist: How close countries are (-)
imps: Bilateral trade flows (+)
lang: Dummy indicating whether country j has English as official language (+); measure of cost
renew: Dummy indicating whether country has pro-green-energy policies (+)
sun: Average hours sunshine per year (+)

19. Results

20. Results Three analyses for each dataset: w/o sun variable
w/sun variable
w/sun and sun_qual
interaction term
No overlap in results for
variables of interest

21. Conclusion
Do strengthened IPR laws lead to more solar patenting abroad?
Equivalents: NO. IPRs have no effect
Extended families: YES. IPRs facilitate transfer of green tech

22. Conclusion
Are higher-quality solar patents more likely to be filed abroad?
Equivalents: YES
Families: MAYBE, in countries with more sunshine on average

23. Conclusion What accounts for differences?
Might expect that because extended family dataset has more patents being filed on average, and a much larger average quality measure than equivalents data …
Quality variable would yield a statistically significant result in extended family group
However…

24. Conclusion Two case studies*
Extended families data contain a significant amount of “noise” that most likely affects results
(1) In large patent families, only a few patents account for large majority of citations
(2) Only a few families in aggregate country quality measure account for majority of citations
Even though total number of citations and patents filed is, on average, much larger, quality measure (ratio of citations/patents filed) is in reality much smaller
*Chosen arbitrarily from a larger, but less complete in terms of control variables, dataset

25. Conclusion
When extended families data re-run without large outliers in quality measure…
Results same in terms of sign, coefficient size, and significance
Mean of pijt is higher, so effects at mean may be larger
Ergo, controlling for “noise” doesn’t seem to resolve different results
*Chosen arbitrarily from a larger, but less complete in terms of control variables, dataset

26. Conclusion But equivalents may not be better
Over-counting could inflate both citations and results
Solutions/Future Research:
Conduct same analysis for other groups of countries, not just high income, and see if differences persist
Compare all individual patents contained in each dataset; beyond scope of this study
Use “expert-validated families based on novel technical content”* to more clearly define families and their technologies
Use firm-level data; may not be available, reliable from public sources
*Martínez (2011)

27. Conclusion
Question of equivalents vs. extended patent families is of vital importance to current and future policies designed to increase access to climate-change-mitigating technologies
Results presented here should give patent researchers pause, and encourage us all to consider more carefully how we define and use our data
*Martínez (2011)