Patent Disclosure 180811 · • Patents filed on/after Nov 29, 2000 are published 18 months after...

Patent Disclosure

Deepak Hegde NYU SternKyle Herkenhoff University of Minnesota

Chenqi Zhu NYU Stern

August 11, 2018AoM 2018 Patents PDW

The grand bargain of patents

for

“the right to exclude others from making, using or selling the invention throughout the United States”(35 U.S.C.)

“the [patent] specification shall contain a description of the invention in such full, clear, concise andexact terms as to enable any person skilled in the art ... to make and use the same”(35 U.S.C. § 112)

Existing research focuses on the monopoly effects of patents

Do patent rights encourage inventors? Machlup (1958), Nordhaus (1969), Mansfield, Schwartz, & Wagner (1981), Levin et al (1987), Cohen, Nelson & Walsh (2000), Cohen, Goto, Nagata, Nelson & Walsh (2002), Hall & Ziedonis (2001), Schankerman & Pakes (1986), Schankerman (1998), Moser (2005), Gans, Hsu & Stern (2008), Balasubramanian & Sivadasan (2011), Moser (2013), Gaulle (2015), Kogan, et al (2016), Farre-Mensa, Hegde & Ljungqvist (2017)

Do patent rights discourage follow-on invention?Williams (2013), Galasso & Schankerman (2015), Branstetter, Chatterjee & Higgins (2016) Sakakibara & Branstetter (2001), Lampe & Moser (2010), Moser & Voena (2012), Galasso & Schankerman (2016), Schankerman & Pakes (1986), Schankerman (1998), Bhaskarabhatla & Hegde (2015), Sampat & Williams (2015)

Research on patent disclosure is limited and inconclusive

Does patent disclosure harm inventors?• Yes (Modigliani et al 1999)

• Not necessarily (Long 2002, Graham & Hegde 2015, Hegde & Luo 2017)

Does patent disclosure affect follow-on invention? • 64% of nanotech researchers gathered “important technical information” from patents (Ouellette 2012)

• 50-80% of firms considered patents a key channel for learning about rivals’ R&D (Cohen et al 2002)

• “Patent disclosures play an insignificant role in promoting R&D spillovers” (Roin 2005, p 2027; Menell & Meurer 2011 )

Related Theory/ResearchFromer (2009), Anton & Yao (2002, 2003), Aoki & Spiegel (2009), Bhattacharya & Guriev (2006), Hopenhayn & Squintani (2014), Horstmann et al (1985), Johnson & Popp (2003)

How does pre-grant disclosure affect knowledge diffusion, follow-on invention and patenting?

U.S. patent applications historically disclosed only when granted• Applications took 36 months to be granted in 2000

American Inventor's Protection Act (AIPA) • Patents filed on/after Nov 29, 2000 are published 18 months after filing, regardless of grant

• Applicants may opt out upon agreeing not to file abroad

• Harmonization with foreign patents which always published at 18 months after (first) filing

Quasi-experiment • Compare US patents filed before and after AIPA

• Compare US patents with European “twins” before and after AIPA

• Outcomes: rate & extent of knowledge diffusion, technological overlap (duplication), patent breadth & quality

Theory: Endogenous innovation model of appropriation strategy

Two period model with heterogeneous firms

• Firms draw ideas, decide to file a patent, keep trade-secret or enter competitive market

• If patent, make investments in patenting in Period 1, earn monopoly profits in Period 2 (if granted patent)

• Trade secrecy requires investments, increasing in idea quality

• Patenting process Pre-AIPAFirms make investments before patent decision without seeing competing patents in cohort

• Patenting process Post-AIPAFirms observe competing patents before making additional investments

Freeride on information to reduce cost of own invention, and to make patenting investments

Theory: Testable implications

“AIPA-as news” assumption suggests two empirical tests:

1. The time it takes to receive a citation drops as knowledge diffuses during the patenting process after AIPA.

2. Citations should increase conditional on disclosure, since more recent patents are more relevant components of prior-art and are now revealed sooner

The model yields the following testable predictions:

3. Patent abandonment rates decline after AIPA.

4. In less crowded technological areas, patents become more similar after AIPA.

5. In more crowded technological areas, patents become more unique after AIPA.

6. Patent scope may increase or decrease. Whenever the inventive step drops (i.e. similarity increases), patent scope declines, whereas the opposite is true if inventive step becomes larger.

7. AIPA’s impact on overall innovation is ambiguous. Free-ridership decreases innovation, but reduced uncertainty about competing patents increases innovation.

Sample: USPTO’s PAIR and EPO’s PATSTAT databases

1.54 Million (all) U.S. applications filed during 1998-2003 (45% are pre-AIPA)

• 8.9% of U.S. patents opt out of 18-month disclosure post-AIPA

• 16% of U.S. patents matched to European twin using PATSTAT (for twin analysis)

Outcome Variables

i. Knowledge diffusion

– Citations lag in months for 1/3/5/7 citations from application date (no self citations)

– Number of citations 3/5/7/10 years from disclosure date (no self citations)

ii. Invention similarity

– Pairwise cosine distance measure based on IPC assignments of patents; distance b/w future patents filed [19-36] months and focal patent)

iii. Patenting characteristics

– Filings, abandonments (0/1), no. of claims, no of words per claim

Knowledge diffusion accelerates after AIPA’s enactment

2829

3031

3233

1998m1 2000m1 2002m1 2004m1

A. Time Lag of Receiving 1 Forward Citations

3436

3840

1998m1 2000m1 2002m1 2004m1

B. Time Lag of Receiving 3 Forward Citations

3638

4042

44

1998m1 2000m1 2002m1 2004m1month

Pre-AIPA Post-AIPA

C. Time Lag of Receiving 5 Forward Citations

3840

4244

461998m1 2000m1 2002m1 2004m1

month

Pre-AIPA Post-AIPA

D. Time Lag of Receiving 7 Forward Citations

Knowledge diffusion increases after AIPA

3.2

3.4

3.6

3.8

44.

2

1998m1 2000m1 2002m1 2004m1

A. 3-Year Forward Citations

5.5

66.

57

1998m1 2000m1 2002m1 2004m1

B. 5-Year Forward Citations

78

910

1998m1 2000m1 2002m1 2004m1

Pre-AIPA Post-AIPA Pre-trend

C. 7-Year Forward Citations

1011

1213

14

1998m1 2000m1 2002m1 2004m1


D. 10-Year Forward Citations

Distant patents become more similar, similar patents less so after AIPA.0

03.0

04.0

05.0

06.0

07

1998m1 2000m1 2002m1 2004m1

A. 5th Percentile Similarity

.025

.03

.035

.04

.045

1998m1 2000m1 2002m1 2004m1

D. 25th Percentile Similarity

.1.1

2.1

4.1

6

1998m1 2000m1 2002m1 2004m1

E. 50th Percentile Similarity

.42

.43

.44

.45

.46

1998m1 2000m1 2002m1 2004m1


G. 85th Percentile Similarity

.5.5

1.5

2.5

3.5

4

1998m1 2000m1 2002m1 2004m1


H. 90th Percentile Similarity

.61

.62

.63

.64

.65

.66

1998m1 2000m1 2002m1 2004m1


I. 95th Percentile Similarity

AIPA appears to affect several patent characteristics.2

.25

.3.3

5

aban

donm

ent r

ate

1998m1 2000m1 2002m1 2004m1


A. Abandonment Rates

.15

.2.2

5.3

1998m1 2000m1 2002m1 2004m1


B. Abandonments without Continuation Filings

1000

015

000

2000

025

000

3000

0

1998m1 2000m1 2002m1 2004m1

# applications # granted applicationsapplication pre-trend granted application pre-trend

C. Patenting Intensity

1617

1819

20

allo

wed

cla

ims

1998m1 2000m1 2002m1 2004m1


D. Average Number of Allowed Claims

2.8

2.9

33.

13.

2

inde

pend

ent c

laim

s

1998m1 2000m1 2002m1 2004m1


E. Average Number of Independent Claims

145

150

155

160

165

num

ber o

f wor

ds

1998m1 2000m1 2002m1 2004m1


F. Average Words in Independent Claims

Identification Strategy #1: Before and After Analysis

!"#$ℎ& where t = (1,2,3….72)

I = 1 for post-AIPA months (=1 for 37 months)

Estimation approach pioneered by Gross, Notowidigdo, and Wang (2013) permits controlling for pre-trend

Allows estimation of treatment-specific trend effects and examination of treatment effects in different treatment windows

We present mean of '& (standard errors calculated using the delta method)

()$*"+,-& = /0 + 23∈567&

'& ∗ 9 !"#$ℎ& = : + ; !"#$ℎ& + /<=>?@AB?>#$- + /C(D$()$- + E,*ℎF= + G-&

Before and After Estimates of AIPA’s effects

Identification Strategy #2: “Twin” Analysis

!"#$%&' controls for unobserved characteristics of invention and patent common to U.S. & EP

()*+ℎ- where t = (1,2,3….72)

Estimation approach used in previous studies such as Graham et al. (2003) and Graham and Harhoff

(2006)

./ identifies effect of disclosure in the US alone, for identical twins also disclosed in Europe at 18

months

Identifying assumption: Citations by inventors and examiners are highly localized (Harhoff 2008)

01+2)#3'4- = .6 + .89:4 + ./9:4 ∗ <)=+>?<>- + @A4 + !"#$%&' + ()*+ℎ- + B'4-

Knowledge diffusion of U.S. twins accelerates after AIPA

2530

3540

4550

1998m1 2000m1 2002m1 2004m1

US EP

A. Time Lag of Receiving 1 Forward Citations

3035

4045

50

1998m1 2000m1 2002m1 2004m1

US EP

B. Time Lag of Receiving 3 Forward Citations

3540

4550

1998m1 2000m1 2002m1 2004m1

US EP

C. Time Lag of Receiving 5 Forward Citations

3540

4550

1998m1 2000m1 2002m1 2004m1

US EP

D. Time Lag of Receiving 7 Forward Citations

Knowledge diffusion of U.S. twins increases after AIPA

.6.7

.8.9

1

3.5

44.

55

5.5

Cita

tions

to U

S pa

tent

s

1998m1 2000m1 2002m1 2004m1

A. 3-Year Forward Citations

11.

21.

41.

61.

8

Cita

tions

to E

P pa

tent

s

56

78

9

1998m1 2000m1 2002m1 2004m1

B. 5-Year Forward Citations

1.2

1.4

1.6

1.8

22.

2

68

1012

Cita

tions

to U

S pa

tent

s

1998m1 2000m1 2002m1 2004m1

US EP

C. 7-Year Forward Citations

1.5

22.

53

Cita

tions

to E

P pa

tent

s

1012

1416

18

1998m1 2000m1 2002m1 2004m1

US EP

D. 10-Year Forward Citations

Technological overlap for U.S. twins increases after AIPA in less crowded areas; decreases in more crowded areas

.002

.003

.004

.005

.006

1998m1 2000m1 2002m1 2004m1

5th Percentile Similarity

.008

.01

.012

.014

.016

1998m1 2000m1 2002m1 2004m1


.06

.08

.1.1

2.1

4

1998m1 2000m1 2002m1 2004m1


.3.3

5.4

.45

1998m1 2000m1 2002m1 2004m1

US EP


.35

.4.4

5.5

.55

1998m1 2000m1 2002m1 2004m1

US EP


.5.5

5.6

.65

1998m1 2000m1 2002m1 2004m1

US EP


“Twin Analysis” estimates of AIPA’s effects

Similarity decreases for close patents after AIPA

Patent disclosure affects knowledge diffusion, follow-on invention and patenting

U.S. pre-grant disclosure rule increased rate and magnitude of knowledge diffusion• Citations delay decreased 12-20 percent

• Citations increased by 4-19 percent

• Diffusion effects of disclosed but abandoned patents represent pure gains (11% of citations by 2015 patent applications to abandoned patents )

Pre-grant disclosure decreased overlap with close substitutes • Post-AIPA issued patents are better differentiated, sharper scope

• Highly similar patents drop out of patenting, decreasing abandonments

Opt-out patents: free-riders in early disclosure regime?• Emerge with broad claims, have higher overlap with future patents and lower knowledge spillovers (“submarine

patents?”)

• But, limits those who value pre-grant secrecy from dropping out of patenting..

Thank you!Email: [email protected]

Patent Disclosure 180811 · • Patents filed on/after Nov 29, 2000 are published 18 months after...

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