Introduction Methodology Results Discussion

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Patent Subsidy and Patent Filing in China Zhen Lei1 1 Department

Zhen Sun2

Brian Wright2

of Energy and Mineral Engineering and the EMS Energy Institute Penn State University

2 Department

of Agricultural and Resource Economics University of California, Berkeley

Conference on Innovation and Patent Harmonization September 30 & October 1, 2011 .

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Patent Subsidy and Patent Filing in China

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What’s going on?

"The leadership in China knows that innovation is its future," ... "They are doing everything they can to drive innovation, and China’s patent strategy is part of that broader plan." "When innovation, too, is made in China", NYT, January 1st, 2011

Such incentives produce results... China’s overall patent filings grew by 26% a year between 2003 and 2009...Growth was much slower elsewhere: 6% in America, 5% in South Korea, 4% in Europe and 1% in Japan. ...the generosity of China’s incentives for patent-filing may make it worthwhile... to patent even worthless ideas. "Patents are easy to file,"..."but gems are hard to find in a mountain of junk." "Patents, yes; ideas, maybe?", The Economist, Oct 14th, 2010

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Introduction Methodology Results Discussion

. Outline 1.

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Introduction Background Research Question Methodology Research Strategy Data Results The Quantity of Invention Patents The Quantity of Utility Model and Design Patents The Quality of Invention Patents .

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Background Research Question

China’s Indigenous Innovation Policies

Medium to Long Term Plan for the Development of Science and Technology (Jan, 2006) Measures to promote Chinese IP and innovation capacity Government procurement policy Tax incentives and support for R&D and patenting China-specific technical standards Enforcement of Anti-monopoly Act

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Background Research Question

Patent Subsidy Policy in China Increase IP awareness; encourage patenting; promote innovation

Policies at province and city level in China Subsidies for patent filings Reward for patent grants

Policies at national level in China Article 98: 60%-85% of the patent fees postponement for applicants who have financial distress

Other nations have similar policies for small entities: USA: 50% reduction in filing fees since 1982 (in recent reform, 75% for micro-entities) South Korea: 70% reduction in filing fees Singapore: up to 30,000 SGD .

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Patent Subsidy and Patent Filing in China

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Background Research Question

Patent Application Growth in SIPO Applications for invention patents: 1985-2010

320,000 Domestic

Number of invention patent

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Introduction Methodology Results Discussion

Foreign

240,000

160,000

80,000

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1985

1990

1995

2000

2005

2010

Year .

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Background Research Question

Research Question

What are the effects of the patent subsidy on patent filings in China, in terms of both quantity and quality of patent applications?

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Research Strategy Data

A Case Study

Compare 6 neighboring county-level cities within the SuZhou Municipality ZhangJiaGang, WuJiang, TaiCang, SuZhou, KunShan and Changshu After June 2006, ZhangJiaGang increased its patent subsidies while the other cities’ policies have not changed.

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Research Strategy Data

Subsidies for Invention Patents within the Suzhou Municipality* . City ZhangJiaGang WuJiang TaiCang SuZhou KunShan ChangShu a b c *

June 2004 a

1500 2000 4000+5000 4000 4000 2000

June 2006 3000+10000 unchanged unchanged unchanged unchanged unchanged

June 2008 b

unchanged until 2010 unchanged until 2010 unchanged until 2010 unchanged unchanged 3000+5000c

the subsidy is in Chinese Yuan (RMB). the subsidy after "+" is for granted patents. the subsidy changed after April 2008. the subsidies for utility model and design patents in Zhangjiagang increased from 1000 and 500 RMB to 1500 and 1000 RMB respectively after June 2006. The subsidies for the other cities (not shown here) remain unchanged. .

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Research Strategy Data

Patent Fees . Type Invention Utility Model Design a b c

Application 950 500 500

a

Examination 2500 N/A N/A

Agency fee 4000+ 2500+ 1500+

Maintenance/year

b

900-8000c 600-2000 600-2000

the subsidy is in Chinese Yuan (RMB). the exact agency fee depends on patents and agencies. the maintenance fee increases incrementally.

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Research Strategy Data

A diff-in-diffs method

Treated city: ZhangJiaGang Control cities: WuJiang, TaiCang, SuZhou, KunShan, ChangShu July 2004 – June 2006: before the policy change in ZhangJiaGang July 2006 – June 2008: after the policy change in ZhangJiaGang

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Research Strategy Data

Data

We have the published application data for all three types of patents in these cities from July 2004 to the end of June 2008. The time unit considered in the study is half a year. Therefore, the time scope is divided into 8 half-years.

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

The Quantity of Invention Patents The Quantity of Utility Model and Design Patents The Quality of Invention Patents

Model . Model:

yict = β · xct + αi + λt + εict yict is the number of invention patents applied by firm i of city c in half-year t. xct is the policy variable: xct = 1 for ZhangJiaGang after June 2006. αi is the firm fixed effect, λt is the half-year time fixed effect. Unbalanced panel. Use placebo treatment to test the validity of controls & result robustness.

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

The Quantity of Invention Patents The Quantity of Utility Model and Design Patents The Quality of Invention Patents

Model . Model:

yict = β · xct + αi + λt + εict yict is the number of invention patents applied by firm i of city c in half-year t. xct is the policy variable: xct = 1 for ZhangJiaGang after June 2006. αi is the firm fixed effect, λt is the half-year time fixed effect. Unbalanced panel. Use placebo treatment to test the validity of controls & result robustness.

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Patent Subsidy and Patent Filing in China

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The Quantity of Invention Patents A significant increase in ZhangJiaGang after June 2006

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treatcity/control

WuJiang

TaiCang

SuZhou

KunShan

ChangShu

Other

ZhangJiaGang SD # of applicants # of observations

0.239*** (0.0795) 384 2506

0.201*** (0.0716) 325 2101

0.166** (0.0701) 1088 7234

0.224*** (0.0724) 456 3007

0.0406 (0.0838) 447 2921

0.168*** (0.0635) 1928 12709

-0.0376 (0.0681) 323 2077

-0.0754 (0.0659) 1086 7210

-0.0151 (0.0679) 454 2983

-0.199** (0.0800) 445 2897

-0.0827 (0.0597) 1735 11444

-0.0378 (0.0553) 1027 6805

0.0190 (0.0586) 395 2578

-0.160** (0.0716) 386 2492

-0.0382 (0.0482) 1735 11444

0.0588 (0.0564) 1158 7711

-0.125* (0.0706) 1149 7625

0.00347 (0.0462) 1735 11444

-0.183** (0.0729) 517 3398

-0.0670 (0.0496) 1735 11444

WuJiang SD # of applicants # of observations TaiCang SD # of applicants # of observations SuZhou SD # of applicants # of observations KunShan SD # of applicants # of observations ChangShu SD # of applicants # of observations

0.148** (0.0648) 1735 11444

Robust standard errors clustered at applicant level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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The Quantity of Invention Patents ChangShu Removed

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treatcity/control

WuJiang

TaiCang

SuZhou

KunShan

Other

ZhangJiaGang SD # of applicants # of observations

0.239*** (0.0795) 384 2506

0.201*** (0.0716) 325 2101

0.166** (0.0701) 1088 7234

0.224*** (0.0724) 456 3007

0.189*** (0.0643) 1674 11053

-0.0376 (0.0681) 323 2077

-0.0754 (0.0659) 1086 7210

-0.0151 (0.0679) 454 2983

-0.0603 (0.0609) 1481 9788

-0.0378 (0.0553) 1027 6805

0.0190 (0.0586) 395 2578

-0.0161 (0.0495) 1481 9788

0.0588 (0.0564) 1158 7711

0.0597 (0.0467) 1481 9788

WuJiang SD # of applicants # of observations TaiCang SD # of applicants # of observations SuZhou SD # of applicants # of observations KunShan SD # of applicants # of observations

-0.0433 (0.0513) 1481 9788

Robust standard errors clustered at applicant level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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The Quantity of Invention Patents by Firms . treatcity/control

WuJiang

TaiCang

SuZhou

KunShan

Other

ZhangJiaGang SD # of firms # of observations

0.337*** (0.133) 220 1426

0.305*** (0.110) 179 1154

0.241** (0.115) 554 3644

0.378*** (0.105) 274 1788

0.287*** (0.0998) 855 5591

-0.0244 (0.123) 151 966

-0.102 (0.127) 526 3456

0.0377 (0.116) 246 1600

-0.0638 (0.115) 731 4784

-0.0696 (0.0990) 485 3184

0.0662 (0.0898) 205 1328

-0.0261 (0.0847) 731 4784

0.140 (0.0952) 580 3818

0.115 (0.0878) 731 4784

WuJiang SD # of firms # of observations TaiCang SD # of firms # of observations SuZhou SD # of firms # of observations KunShan SD # of firms # of observations

-0.116 (0.0829) 731 4784

Robust standard errors clustered at firm level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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The Quantity of Invention Patents by Individuals . treatcity/control

WuJiang

TaiCang

SuZhou

KunShan

Other

ZhangJiaGang SD # of individuals # of observations

0.0644 (0.0609) 164 1080

0.0220 (0.0696) 146 947

0.0123 (0.0540) 534 3590

-0.0191 (0.0769) 182 1219

0.0153 (0.0513) 819 5462

-0.0466 (0.0651) 172 1111

-0.0525 (0.0467) 560 3754

-0.0813 (0.0718) 208 1383

-0.0573 (0.0449) 750 5004

-0.0105 (0.0583) 542 3621

-0.0426 (0.0789) 190 1250

-0.00781 (0.0563) 750 5004

-0.0305 (0.0654) 578 3893

0.00730 (0.0404) 750 5004

WuJiang SD # of individuals # of observations TaiCang SD # of individuals # of observations SuZhou SD # of individuals # of observations KunShan SD # of individuals # of observations

0.0391 (0.0634) 750 5004

Robust standard errors clustered at individual level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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Introduction Methodology Results Discussion

The Quantity of Invention Patents The Quantity of Utility Model and Design Patents The Quality of Invention Patents

Why Individual Applicants Are Not Responsive?

They could be owners of some private firms who decide to have patents under their names so that the inventions are not controlled by the firms (or other investors), They could be employees in some firms but do not report the patent applications to the firm. In both cases, they do not want to claim the subsidy. Under Article 98, individuals already enjoyed a 85% of patent fees postponed (waived).

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Z.Lei, Z.Sun, B.Wright

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

The Quantity of Invention Patents The Quantity of Utility Model and Design Patents The Quality of Invention Patents

Why Individual Applicants Are Not Responsive?

They could be owners of some private firms who decide to have patents under their names so that the inventions are not controlled by the firms (or other investors), They could be employees in some firms but do not report the patent applications to the firm. In both cases, they do not want to claim the subsidy. Under Article 98, individuals already enjoyed a 85% of patent fees postponed (waived).

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Patent Subsidy and Patent Filing in China

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Robustness Check 1 Remove firms that never filed invention patent applications

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treatcity/control

WuJiang

TaiCang

SuZhou

KunShan

Other

Zhangjiagang SD # of firms # of observations

0.796*** (0.287) 98 635

0.807*** (0.288) 69 438

0.611** (0.271) 241 1584

0.936*** (0.252) 108 716

0.715*** (0.238) 369 2422

0.0467 (0.286) 69 439

-0.187 (0.258) 241 1585

0.144 (0.232) 108 717

-0.0977 (0.232) 320 2105

-0.217 (0.256) 212 1388

0.0823 (0.249) 79 520

-0.130 (0.230) 320 2105

0.332 (0.217) 251 1666

0.264 (0.197) 320 2105

WuJiang SD # of firms # of observations TaiCang SD # of firms # of observations SuZhou SD # of firms # of observations KunShan SD # of firms # of observations

-0.283 (0.189) 320 2105

Robust standard errors clustered at firm level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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Robustness Check 2: One-year Unit Time Use one-year instead of half-year as the time unit

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treatcity/control Zhangjiagang SD # of firms # of observations WuJiang SD # of firms # of observations

WuJiang

TaiCang

SuZhou

KunShan

Other

0.590** (0.248) 220 764

0.562*** (0.200) 179 622

0.428* (0.227) 554 1947

0.677*** (0.204) 274 961

0.510*** (0.195) 855 2998

-0.0271 (0.211) 151 522

-0.162 (0.233) 526 1847

0.0832 (0.211) 246 861

-0.0926 (0.208) 731 2566

-0.134 (0.182) 485 1705

0.111 (0.154) 205 719

-0.0577 (0.147) 731 2566

0.252 (0.187) 580 2044

0.203 (0.171) 731 2566

TaiCang SD # of firms # of observations SuZhou SD # of firms # of observations KunShan SD # of firms # of observations

-0.213 (0.161) 731 2566

Robust standard errors clustered at firm level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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Robustness Check 3: Diff-in-diff-in-diffs The effect is due to other city-specific changes in Zhangjiagang?

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treatcity/control Zhangjiagang SD # of applicants # of observations WuJiang SD # of applicants # of observations

WuJiang

TaiCang

SuZhou

KunShan

Other

0.266* (0.146) 384 2506

0.282** (0.130) 325 2101

0.230* (0.128) 1088 7234

0.399*** (0.130) 456 3007

0.270** (0.113) 1674 11053

0.0239 (0.139) 323 2077

-0.0415 (0.134) 1086 7210

0.132 (0.136) 454 2983

-0.00115 (0.123) 1481 9788

-0.0579 (0.114) 1027 6805

0.112 (0.118) 395 2578

-0.0202 (0.102) 1481 9788

0.170 (0.116) 1158 7711

0.105 (0.0968) 1481 9788

TaiCang SD # of applicants # of observations SuZhou SD # of applicants # of observations KunShan SD # of applicants # of observations

-0.159 (0.104) 1481 9788

Robust standard errors clustered at applicant level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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Robust Check 4: Anticipation Effect Firms in Zhangjiagang postponed their applications in anticipation of the policy change?

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treatcity/control Zhangjiagang SD # of firms # of observations Wujiang SD # of firms # of observations

WuJiang

TaiCang

SuZhou

KunShan

Other

0.140 (0.166) 220 546

0.0382 (0.139) 179 438

0.0115 (0.204) 554 1428

0.0740 (0.168) 274 692

0.0430 (0.162) 855 2171

-0.0717 (0.119) 151 362

-0.129 (0.194) 526 1352

-0.0668 (0.149) 246 616

-0.113 (0.156) 731 1860

-0.0359 (0.157) 485 1244

0.0341 (0.126) 205 508

-0.00606 (0.114) 731 1860

0.0624 (0.192) 580 1498

0.0797 (0.172) 731 1860

Taicang SD # of firms # of observations SuZhou SD # of firms # of observations KunShan SD # of firms # of observations

-0.0393 (0.163) 731 1860

Robust standard errors clustered at firm level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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The Quantity of Utility Model Patents No significant difference in ZhangJiaGang after June 2006

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treatcity/control ZhangJiaGang SD # of applicants # of observations WuJiang SD # of applicants # of observations TaiCang SD # of applicants # of observations

WuJiang

TaiCang

SuZhou

KunShan

ChangShu

Other

0.110 (0.109) 384 2506

0.0391 (0.0827) 325 2101

-0.0446 (0.0915) 1088 7234

0.163* (0.0985) 456 3007

-0.109 (0.101) 447 2921

0.000348 (0.0778) 1928 12709

-0.0695 (0.0965) 323 2077

-0.156 (0.103) 1086 7210

0.0553 (0.109) 454 2983

-0.220** (0.112) 445 2897

-0.124 (0.0919) 1735 11444

-0.0805 (0.0755) 1027 6805

0.124 (0.0825) 395 2578

-0.145* (0.0861) 386 2492

-0.0390 (0.0600) 1735 11444

0.209** (0.0925) 1158 7711

-0.0651 (0.0957) 1149 7625

0.0950 (0.0712) 1735 11444

-0.274*** (0.102) 517 3398

-0.194** (0.0812) 1735 11444

SuZhou SD # of applicants # of observations KunShan SD # of applicants # of observations ChangShu SD # of applicants # of observations

0.128 (0.0847) 1735 11444

Robust standard errors clustered at applicant level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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The Quantity of Design Patents No significant difference in ZhangJiaGang after June 2006

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treatcity/control ZhangJiaGang SD # of applicants # of observations WuJiang SD # of applicants # of observations TaiCang SD # of applicants # of observations

WuJiang

TaiCang

SuZhou

KunShan

ChangShu

Other

-0.270 (0.946) 384 2506

-0.851 (1.233) 325 2101

-0.563 (0.402) 1088 7234

-0.861* (0.482) 456 3007

-0.0623 (0.457) 447 2921

-0.528 (0.418) 1928 12709

-0.609 (1.459) 323 2077

-0.296 (0.865) 1086 7210

-0.589 (0.902) 454 2983

0.205 (0.892) 445 2897

-0.294 (0.871) 1735 11444

0.327 (1.161) 1027 6805

0.0160 (1.193) 395 2578

0.812 (1.186) 386 2492

0.402 (1.163) 1735 11444

-0.308 (0.292) 1158 7711

0.493** (0.246) 1149 7625

0.0647 (0.296) 1735 11444

0.794** (0.361) 517 3398

0.397 (0.321) 1735 11444

SuZhou SD # of applicants # of observations KunShan SD # of applicants # of observations ChangShu SD # of applicants # of observations

-0.538* (0.282) 1735 11444

Robust standard errors clustered at applicant level in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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Introduction Methodology Results Discussion

The Quantity of Invention Patents The Quantity of Utility Model and Design Patents The Quality of Invention Patents

Model

Model:

gict = β · xct + Ti + αc + λt + εict gict is a dummy indicating the grant of the patent i. xct is the policy variable: xct = 1 for ZhangJiaGang after July 2006. Ti is the technology fixed effect. αi is the firm fixed effect, λt is the half-year time fixed effect. Use placebo treatment to test the validity of controls & result robustness.

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Patent Subsidy and Patent Filing in China

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The Quality of Invention Patents No significant difference in ZhangJiaGang after June 2006

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treatcity/control

WuJiang

TaiCang

SuZhou

KunShan

Other

ZhangJiaGang SD # of patents

-0.0516 (0.0663) 595

0.147* (0.0720) 391

-0.0413 (0.0808) 1590

-0.0787 (0.103) 1004

-0.0478 (0.0725) 2770

0.264*** (0.0845) 446

0.00741 (0.0794) 1645

0.0381 (0.102) 1059

0.0271 (0.0811) 2500

-0.158 (0.0953) 1441

-0.205* (0.118) 855

-0.184* (0.0912) 2500

-0.103 (0.0745) 2054

-0.0480 (0.0597) 2500

WuJiang SD # of patents TaiCang SD # of patents SuZhou SD # of patents KunShan SD # of patents

0.103 (0.0797) 2500

Robust standard errors clustered at technology field in parentheses ** p < 0.10 ** p < 0.05 *** p < 0.01

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Introduction Methodology Results Discussion

Discussion

Chinese firms in economically developed regions still had financial constraints in patenting: After the policy, applications increased but quality didn’t drop Increased propensity to file, not increased innovation

Low subsidy on filing fee but high reward on patent grant discourage applicants to file low quality applications: Little impact on filings of utility model and design patents Invention patent applications’ quality did not decrease after the policy

Implications for patent fee subsidy policy in other countries? .

Z.Lei, Z.Sun, B.Wright

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Discussion

Chinese firms in economically developed regions still had financial constraints in patenting: After the policy, applications increased but quality didn’t drop Increased propensity to file, not increased innovation

Low subsidy on filing fee but high reward on patent grant discourage applicants to file low quality applications: Little impact on filings of utility model and design patents Invention patent applications’ quality did not decrease after the policy

Implications for patent fee subsidy policy in other countries? .

Z.Lei, Z.Sun, B.Wright

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Discussion

Chinese firms in economically developed regions still had financial constraints in patenting: After the policy, applications increased but quality didn’t drop Increased propensity to file, not increased innovation

Low subsidy on filing fee but high reward on patent grant discourage applicants to file low quality applications: Little impact on filings of utility model and design patents Invention patent applications’ quality did not decrease after the policy

Implications for patent fee subsidy policy in other countries? .

Z.Lei, Z.Sun, B.Wright

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Patent Subsidy and Patent Filing in China

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Introduction Methodology Results Discussion

Discussion

Chinese firms in economically developed regions still had financial constraints in patenting: After the policy, applications increased but quality didn’t drop Increased propensity to file, not increased innovation

Low subsidy on filing fee but high reward on patent grant discourage applicants to file low quality applications: Little impact on filings of utility model and design patents Invention patent applications’ quality did not decrease after the policy

Implications for patent fee subsidy policy in other countries? .

Z.Lei, Z.Sun, B.Wright

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Patent Subsidy and Patent Filing in China

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