China's Patent Explosion

1. The Phenomena and Questions for Study2. Data Sets: SIPO via Google linked to Firms and USPTO3. Analysis and Findings4.Conclusion: future work

Richard B. Freeman, Harvard University, NBERLintong Li, Peking UniversityHKUST, Feb 22, 2017Preliminary Analysis of New Data; Comments appreciated.

1. Patent Growth “faster than a speeding bullet”

The study of patents

Primary economic motivation is to explain growth. First major modern researcher was Jacob Schmookler, Invention and economic growth (Harvard University Press, 1962). Zvi Griliches developed econometric analysis with firm level data.

“Patent and patent statistics have fascinated economists for a long time. Questions about sources of economics growth, the rate of technological change , the competitive position of different firms and countries……all tend to revolve around notions of inventiveness……In this desert of data, patent statistics loom up as a mirage of wonderful plentitude and objectivity. They are available; they are by definition related to inventiveness” (Griliches, 1990)

Patents are not innovation in the Schumpeter/Oslo convention sense since most patents do not lead to new products or processes, but they are valuable indicator of new ideas intended to produce innovation and thus provide insight into China's move from developing economy to innovative knowledge-based economy.

Debate over innovation in China

May 2014, VP Joe Biden at Air Force Graduation: “Name to me one innovative project, one innovative change, one innovative product that has come out of China”

March 2014 Harvard Business Review, experts debated whether China's government structure is compatible with “true spirit of entrepreneurship”

February 2015, Economist debate “Is China a global innovative powerhouse?” with debaters focused on how much government domination of economy discourages innovation

Winter 2017 “ Chinese firms have ... a capacity to become more innovative in response to wage pressure and global opportunities…we should not be pessimistic about ... a successful transition to a more innovation-based growth model.” Wei, Xie and Zhang, JEP,

Goals for Innovation in 2016-2020 5 Year Plan

Rankings in National Innovation Capacity 18 15

Contribution of Science and Technology to Production (%) 55 60

R&D intensity (%) 2.1 2.5

High-tech Firm's Revenue (Trillion RMB) 22.2 34

Share of value added from knowledge intensive service industry in total GDP (%) 15.6 20

Share of R&D expenditure in Revenue for above-scale Industrial Firms (%) 0.9 1.1

Rank in International Science Paper's Citations 4th 2nd

Count of PCT applications 3.05 6.1

Patents per 10k people 6.3 12

Revenue of technology contract (billion RMB) 984 2000

Fraction of citizens with science literacy (%) 6.2 10

Five Big Questions

1 – What is quality of Chinese patents and impact of quality on number and growth of patents compared to US/other countries?

2 – How much patent growth is catch-up (inventions new to China) vs frontier (inventions new to world)?

3 – What is impact of “ innovation” associated with patents on economic outcomes?

4 – What are driving forces behind the patent explosion?

5-- Can patent-related innovation help ameliorate China's increased inequality and the pollution/ environmental costs of rapid growth?

2. SIPO-Firm-USPTO data set

State Intellectual Property Office (SIPO): bibliometric data 1985-2012, by application year; Google patent search: web scraping (using Java Jsoup package) with additional data. Data set includes references (backward citations) for SIPO patents granted in 2009-2015s/forward citations for earlier patents put in by examiners/applicants; technology classes of patents; addresses for assignees and inventors; names of firms matched with 1998-2007 data in Annual Survey of Industrial Firms.

United States Patent and Trademark Office (USPTO): 1976-2015 (grant year)-- using public data but parsed for latest years (Used Python Element tree package)

USPTO-SIPO Matched Patent subset for same patents in USPTO as in SIPO

Data Set includes patent references/citations

Patent references are on the front page of a granted patent. They identify “prior art” upon which the current invention builds. The greater the number of backward citations, the more a patent relies on previous work

Using references/backward citations, we construct forward citation measure for every patent. Since we only have backward citation data 2009-2015. the forward citations is downward biased for patents granted before 2009.

The number of forward citations shows the impact of a patent on other inventions and is an indicator of the value of the patent. (Trajtenberg, 1990; B. H. Hall, 2000; Bloom and Reenen, 2002) and of the geography of knowledge spillovers (Jaffe, Trajtenberg and Fogarty, 2000; Thompson and Fox-Kean, 2005)

Identifying Same Patents in SIPO and USPTO as bridge between patent offices from 35,989 candidate matches

National patents provide IP protection in country so companies will seek protection for more important inventions in more countries

Bridging #

Details

Incentives for more patents notwithstanding, Chinese firms do not break one USPTO patent into several SIPO patents. More likely they take the same patent and translate it.Matching between SIPO and USPTO for the “Matching Part”

USPTO 1 2 3 4+ Total

SIPO

1 11,472(83%) 1,050 687 109 12,871 2 330 76 42 8 456 3 9 30 9 33 81

4+ 33 26 24 324 407 Total 11,844 1,182 315 474 13,815

Number of matched SIPO-USPTO patents

1 – What is quality of Chinese patents?

Patent quality is lower in China than in US and declined during explosive growth but upward trend in Chinese patents raised its share of world patent citations as well as its share of world patents. 1.1 Chinese patents make lower claims than US patents

1.2 SIPO patents make smaller number of citations than USPTO patents, but part of difference is due to greater propensity for US firms to reference older patents in USPTO.

1.3 Trend decline in citations per SIPO patent

1.4 China explosion of patents occurs in all major patent offices. This means China had most rapid growth of top

patents among major countries. (Has distribution by citations gotten more unequal?).

3. Analysis and Findings: answers to questions

1.1 US firms make more patent claims than Chinese firms

Patent claims state the subject of inventions and are principle factor in determining whether a proposed invention infringes on existing patents. Dependent claims refer to other patents and claims; independent claims have no references.

● Chinese firm SIPO patents have fewer claims than Chinese firm SIPO-SUPTO patents. 2005 decline in USPTO claims increase of $18 to $50 per claim in excess of 20. (Harhoff, 2016)

1.2 More Patent citations in USPTO than SIPO:quality or patenting norm? same China patent cites less in SIPO

1.3 Decline in citations per China patent Relative to US addressed patent in USPTO (from annual regressions)

1.4 China explosion of patents not just in SIPO2010-2015 growth rates of 27% in SIPO; 25% in USPTO; 27% EPO; and fastest of 43% in JPO

● Alternative Exchange Rates Between China Patents in USPTO AND SIPO and US USPTO patents

Q2 How much patent growth is catch-up (inventions new to China) vs frontier (inventions new to world)? Most likely catch-up but rapid growth at frontier.

2.1 China origin patents grow rapidly in USPTO, country becomes #5 foreign source of patents

2.2 But Citations to China in USPTO fall from above to normal for to other USPTO Patents

2.3 China Share of USPTO Citations Rises, especially for newest cohorts of patents

2.4 Cosine Similarity Distribution of Chinese Patents Converges toward US Patents in Technology Space

Patent offices use numerical technology codes to categorize technologies of patents; USPTO has USPC 150,000 codes; SIPO, IPC 70,000 codes. Number of classes of patents increases in SIPO (improved patent office?); country patterns similar, save for China variability with small numbers in early USPTO

q3 –What is impact of “ innovation” associated with patents on economic outcomes?

China patents are associated with higher productivity, higher profit margin and higher growth rate, within industry and weaker effects for same firm over time.

Estimated effects on outcomes in production function regressions as comparable to those for US patents

Relation associated largely with higher citation patents.

  (1) (2) (3) (4) (5) (6)

  Ln(output) Margin Employment Growth

Ln(output) Margin Employment Growth

Ln (patent stock+1) 0.067*** 0.026*** 0.031*** 0.013*** 0.001 0.005

(0.002) (0.001) (0.002) (0.003) (0.001) (0.003)

Industry FE Yes Yes Yes No No No

Firm FE No No No Yes Yes Yes

Observations 1911990 1911990 1351307 1788105 1788105 1258923

R2 0.947 0.079 0.019 0.971 0.574 0.216

  (1) (2) (3) (4) (5) (6)  Ln(output) Margin Employment

GrowthLn(output) Margin Employment

GrowthLn (patent stock) 0.027*** 0.014*** 0.021*** 0.011*** 0.001 0.006

(0.003) (0.001) (0.002) (0.004) (0.001) (0.004)Industry FE Yes Yes Yes No No NoFirm FE No No No Yes Yes YesObservations 36644 36644 31590 33682 33682 28964R2 0.971 0.090 0.047 0.987 0.631 0.261

Note: In column 1&4, ln(capital), ln(employment) and ln(materials) are omitted. We control for years, ages and ownership types. Cluster standard errors at firm level in parentheses. Output and input have been deflated by 2-digit industry deflators. * p < 0.10, ** p < 0.05, *** p < 0.01

Substantial positive patent effects on productivity, profitability and employment growth within a industry. and on productivity and weakly on employment growth for same firm

  (1) (2) (3) (4) (5) (6)

  Ln(output) Margin Employment Growth

Ln(output) Margin Employment Growth

Ln (high quality patent stock+1)

0.063*** 0.025*** 0.031*** 0.015*** 0.002 0.008

(0.003) (0.002) (0.003) (0.004) (0.002) (0.005)

Ln (low quality patent stock+1)

0.027*** 0.010*** 0.009*** 0.001 -0.001 -0.003

(0.004) (0.002) (0.003) (0.005) (0.002) (0.005)

Industry FE Yes Yes Yes No No No

Firm FE No No No Yes Yes Yes

Observations 1911990 1911990 1351307 1788105 1788105 1258923

R2 0.947 0.079 0.019 0.971 0.574 0.216

  (1) (2) (3) (4) (5) (6)

  Ln(output) Margin Employment Growth

Ln(output) Margin Employment Growth

Ln (high quality patent stock)

0.021*** 0.009*** 0.009** 0.012 0.007** 0.001

(0.005) (0.002) (0.004) (0.009) (0.003) (0.010)

Ln (low quality patent stock)

0.008* 0.003 0.006 0.001 0.001 0.000

(0.005) (0.003) (0.004) (0.008) (0.003) (0.008)

Industry FE Yes Yes Yes No No No

Firm FE No No No Yes Yes Yes

Observations 10127 10127 9033 9125 9125 8151

R2 0.977 0.120 0.072 0.989 0.655 0.260

Relation Stronger for Highly Cited Patents and Outcomes

4—Conclusion and Future Work

4.1 Magnitude of China's explosion in patents overwhelms lower and falling quality so that China's share of world patent citations and of world claims has increased.

4.2 Despite quality issues, China's patents have similar impact on production measures as patents in advanced countries.

4.3 China's patents converging in technology space toward US.

Data on technical classes provides a route to study whether patent-related innovation could ameliorate China's increased inequality and the pollution/environmental problem and its movement toward higher-tech industries. Expect to see rapid growth in all classes and industries.

Likely driving forces behind the patent explosion include: expanded number of university graduates, government incentives for patents, foreign direct investment and transfer of knowledge.

Finally, our data set can be used to examine other questions regarding the patent explosion in China.

Using data on the location of patents, researchers can examined local knowledge spillovers effect – 25% citation pairs are located within a province.

Using backward citations to USPTO patents; EPO patents and to JPO patents. Researchers can uncover the knowledge diffusion path from developed countries to developing countries and assess the effect of FDI on technology transfer

With information on particular products in different industries, and of the share of new products and processes in firm sales the patent data can also tighten the link between patent-driven innovation and economic success.

Appendix

Odd Patterns in USPTO DataJUSPTO shows increased references by applicants in USPTO, especially for US origin applicants while examiners references remain stable. No such pattern in SIPO

Technology Space Calculation

 

Comparing Groups to Measure Patent Quality and Trend

 

Comparison in USPTO (1998-2015)

Note: Robust standard errors in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01. We control assignee’s type, application year dummies, grant year dummies, 7 digit IPC dummies and 7 digit IPC dummies interact time trend. The benchmark for the set of dummies are a combination of countries unlisted here.

  (1) (2) (3) (4) (5) (6)

  Citations Citations (excluding

self-citations)

Citations (excluding

own country ones)

Citations(applicant)

Citations(examiner)

Claims

US assignee 3.549*** 2.962*** -4.841*** 2.846*** 0.405*** 2.873***

  (0.033) (0.032) (0.026) (0.028) (0.005) (0.019)

CN assignee 0.543*** 0.405*** -2.393*** 0.357*** 0.067*** -2.532***

  (0.034) (0.033) (0.029) (0.029) (0.009) (0.045)

DE assignee -1.441*** -1.503*** -2.707*** -0.970*** -0.383*** -0.985***

  (0.036) (0.036) (0.032) (0.031) (0.007) (0.027)

JP assignee -1.766*** -1.929*** -3.423*** -1.646*** -0.077*** -4.131***

  (0.033) (0.032) (0.028) (0.028) (0.006) (0.020)

KR assignee -1.363*** -1.369*** -3.107*** -1.175*** -0.138*** -2.373***

  (0.040) (0.040) (0.035) (0.034) (0.008) (0.029)

TW assignee -1.163*** -1.153*** -2.888*** -1.156*** -0.069*** -2.546***

  (0.042) (0.041) (0.035) (0.035) (0.009) (0.031)

IN assignee -0.101 -0.065 -2.768*** -0.252*** -0.047** -0.814***

  (0.090) (0.089) (0.078) (0.078) (0.019) (0.141)

N 3495698 3495698 3495698 3495698 3495698 3495698

r2 0.236 0.239 0.171 0.198 0.259 0.0964

Y mean 8.665 8.165 3.815 5.738 2.042 17.07

Correlation of citations, claims, technologiesChina SIPO patents

(1) (2) (3) (4) (5) Citations Citations Citations Citations Citations Firm (Dummy) 0.139*** 0.129*** 0.136*** (0.005) (0.005) (0.005) Institution (Dummy) 0.323*** 0.326*** 0.330*** (0.006) (0.006) (0.006) Number of Claims 0.010*** 0.009*** (0.001) (0.001) Number of Technologies 0.050***

(0.001) Application & Grant Year FE Yes Yes Yes Yes Yes Technology FE No Yes Yes Yes Yes N 807,202 806,689 806,689 806,689 806,689 Adjusted R2 0.078 0.135 0.139 0.139 0.142 Y mean 0.907 0.907 0.907 0.907 0.907

US USPTO patents

(1) (2) (3) (4) (5) Citations Citations Citations Citations Citations Number of Claims 0.291*** 0.282*** (0.003) (0.003) Number of Technologies 0.566***

(0.008) Application & Grant Year FE Yes Yes Yes Yes Yes Technology FE No Yes Yes Yes Yes Assignee Type FE No No Yes Yes Yes N 2,254,907 2,247,091 2,247,090 2,247,090 2,247,090 Adjusted R2 0.083 0.208 0.208 0.219 0.221 Y mean 16.104 16.097 16.097 16.097 16.097