Can Huang
School of Management, Zhejiang University
Hangzhou, P.R. China
September 26th, 2013
1.
2.
3.
4.
5.
6.
Motivation
Hypotheses
Data
Empirical strategy
Results
Discussion and conclusion
2
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
In many industries firms use secrecy or lead time
rather than patent as appropriation methods
(Levin et al. 1987, Brookings Pap Eco Ac; Arundel
and Kabla, 1998, Res Policy)
Firms that patented innovations are expected to
earn almost 50% more on average than if they
had not patented those innovations (Arora et al.,
2008, Int J Ind Organ)
This value increment is defined as patent
premium
3
It seems to be paradoxical that despite the
weak IPR protection and possibly low patent
premium in China, patenting activities there
have surged in the last ten years.
600,000
USPTO
400,000
EPO
300,000
JPO
200,000
SIPO (China)
100,000
KIPO
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
0
1995
Patent Applications
500,000
Number of Annual Invention

4
80%
Food
Tobacco
70%
Textiles
Wearing apparel
60%
Leather products
Wood products
50%
Paper products
Publishing and printing
40%
Petroleum products
Chemicals
30%
Rubber and plastics products
Other non-metallic mineral products
20%
Basic metals
Fabricated metal products
Machinery except electrical
10%
Electrical machinery
Medical, precision and optical instruments
0%
Transport equipment
furniture and manufacturing not elsewhere classfied
5
Struggler
Strategist
Global
Degree of
geographical
differentiation
of the firm’s IP
policy
Singaler
Speculator
Local
Pessimistic
Optimistic
Expectation about the
future appropriation regime
Source: Keupp, Marcus Matthias; Friesike, Sascha and von Zedtwitz, Maximilian,
2012. How do foreign firms patent in emerging economies with weak appropriability
regimes? Archetypes and motives, Research Policy, 41, 8, 1422-1439.
6
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
H1a: Multinational Corporations (MNCs) in
countries with weak IPR protection obtains
positive patent premium.
H1b: Local firms in countries with weak IPR
protection obtains positive patent premium.
We define patent premium as the higher total
factor productivity (TFP) a patenting firm can
achieve than had it not patented.
7
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
Resource-based view: patents as unique
resources to build up competitive advantage
(Amit and Shoemaker, 1993, Strateg Manage
J)
Patent premium are not only determined by
the value of the underlying innovations, but
also by the extent to which the patents can
render competitive advantages
◦ Complex and discrete product technology
◦ Product lifecycle
8
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Rival firms’ patents may negatively impact productivity of
the focal firm (competition effect)
Rival firms’ preemptive or defensive patenting activities
might stimulate the focal firm’s own patenting activities
which lead to its productivity gain (stimulation effect)
Effect of competition on patent premium is theoretically
ambiguous
H2a: The patent premium of MNCs in countries with weak
IPR protection increases with the intensity of competition.
H2b: The patent premium of local firms in countries with
weak IPR protection increases with the intensity of
competition.
9
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Annual Survey of Industrial Enterprises, National Bureau of
Statistics of China
◦ Coverage:1999-2007; all state-owned firms and non-state-owned
firms with more than RMB five million in revenue
◦ E.g. 146,251and 336,732 manufacturing firms in the dataset for the
years 1999 and 2007, respectively
◦ 50 firm-level statistical indicators, including input, output, R&D
expenditure, capital composition, employment, geographical location,
the four-digit industry in which a firm operates, ownership status, and
assets and liabilities.

China Patent Abstract Database, State Intellectual Property
Office (SIPO) of China
◦ Coverage: Over four million patent applications submitted to SIPO
during the period of 1985–2009
◦ Information includes patent application and publication number,
application and publication date, patent number, title, international
patent classification (IPC) class, abstract, claims, legal status
10

Nine students assist manually matching firms in in the
precision instruments and office machinery industry (a
intensive patenting industry)

Each firm was searched independently by two students

Discrepancy is further analyzed in the second round search
to achieve the high accuracy
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
Dataset for this study: 3,244 firms in the industry; 947
patenting firms (677 domestic and 270 foreign); 2297
non-patenting firms (1,401 domestic and 896 foreign)
We plan to match the whole two databases using
algorithms which are developed against the humanmatched results
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Calculation of TFP
◦ Olley and Pakes (1996, Econometrica)’s estimator
◦ Levinsohn and Petrin (2003, Rev Econ Stud)’s estimator as robustness
check
◦ Here I present the result based on fixed-effects estimator
(1) tfpit  yit  bl lit  bk kit  bm mit
Estimation of Patent premium
◦ Rescale the time periods that all the firms started patenting at the year
t=0. t=-1 is the pre-patenting year prior to the year t=0.
◦ Dummy Patenti =1 if a firm i applied for patents in 1999-2007 and 0
otherwise.
◦ Patent premium is the below equation (average treatment effect for the
treated)
(2) E{tfpit1  tfpit0 | Patenti  1}  E{tfpit1 | Patenti  1}  E{tfpit0 | Patenti  1}
where the superscript equals to 1 if the firm i applied for patent and 0
otherwise.
◦ The key is to estimate the unobservable counterfactual or the tfp of a
patenting firm had it not applied for patents tfpit0 | Patenti  1
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Two assumptions
◦ All differences between a focal patenting firm and the control non-patenting firms
can be captured by a vector of covariates (unconfoundedness)
◦ The firms with the same value of covariates have a positive probability of being
both patenting and non-patenting firms (overlap/common support)
Use the nearest-neighbor matching estimator developed by Abadie and Imbens
(2002, NBER) to find a group of control firms that are as close as possible to the focal
patenting firm in terms of their pre-patenting characteristics
Covariates: tfpi,-1 , firm size (li,-1 ), ownership status (state i,-1, collective i,-1, private i,1, HKMT i,-1 and foreign i,-1), year and four-digit industry dummies.
Use the weighted average tfp of these control firms to estimate the counterfactual
tfpit0 | Patenti  1

Use the estimator of propensity score matching (Rosenbaum and Rubin, 1983,
Biometrika) as robustness check. The result is not materially different.
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Calculate the
Herfindahl index
for each of the 24
four-digit
industries every
year
Average the index
for each industry
Rank the averages
Rank
Four-digit
industry
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
4111
4130
4142
4112
4119
4113
4128
4141
4122
4114
4123
4190
4115
4154
4153
4129
4155
4126
4121
4159
4125
4152
4151
4124
Average
Herfindahl
index
0.022
0.022
0.024
0.041
0.042
0.050
0.058
0.058
0.071
0.093
0.102
0.130
0.134
0.138
0.139
0.139
0.157
0.158
0.175
0.276
0.383
0.513
0.531
0.733
Competition
Strong
Strong
Strong
Strong
Strong
Strong
Strong
Strong
Strong
Strong
Strong
Strong
Weak
Weak
Weak
Weak
Weak
Weak
Weak
Weak
Weak
Weak
Weak
Weak
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t
0
1
2
3
4
5
6
7
General
domestic
.060***
(.017)
.11***
(.027)
.075***
(.029)
.066**
(.036)
.19***
(.055)
.21***
(.060)
.26***
(.081)
.25
(.20)
N0
treated
384
287
206
127
95
63
33
10
N0
controls
4827
3424
2355
1448
944
600
249
66
General
foreign
.012
(.024)
.028
(.028)
.0072
(.034)
.083
(.049)
.016
(.058)
.045
(.062)
-.040
(.074)
.16
(.12)
N0
treated
163
134
105
70
55
39
29
11
N0
controls
3749
2860
2123
1330
965
658
380
146
15
t
0
1
2
3
4
5
6
7
.056***
(.020)
.12***
(.029)
.10***
(.032)
.067*
(.042)
.24***
(.063)
.18***
(.052)
.18***
(.066)
.034
(.095)
N0 treated
323
242
169
100
77
50
27
9
N0 controls
4179
2979
2055
1269
828
531
238
63
Domestic, weak
competition
-.020
(.047)
.035
(.072)
-.017
(.064)
.084
(.074)
.11
(.077)
.26
(.19)
N/A1
N/A1
N0 treated
60
42
33
23
18
12
7
2
Domestic,
strong
competition
N0 controls
648
445
300
179
116
69
11
16
Foreign, strong
competition
N0 treated
.043*
(.025)
131
.031
(.028)
112
.030
(.035)
88
.046
(.040)
60
.093*
(.048)
47
.11*
(.059)
33
.024
(.074)
23
.16
(.13)
10
N0 controls
2888
2223
1679
1161
844
576
328
142
Foreign, weak
competition
N0 treated
-.13*
(.066)
32
.048
(.093)
22
-.077
(.10)
17
.29
(.22)
8
-.34
(.23)
8
-.30
(.21)
6
-.28
(.19)
6
N0 controls
861
580
444
169
89
50
52
N/A1
1
45
Note: 1. We do not report the matching results when the overlap (common support) assumption
is not satisfied.
16

The patenting domestic firms in the Chinese
precision instrument and office machinery industry
achieved higher TFP than had they not patented in
the period of 1999-2007.

The patent premium lasted till the sixth year after a
domestic firm filed the first patent

The domestic firms which faced strong competition
attained patent premium

The foreign firms and the domestic firms which faced
weak competition did not obtain patent premium
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18
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Prevent other firms from making, using or selling
the patented products or technologies
Build up patent portfolios to prevent others from
suing the firms for infringement
Use patents as bargaining chips to reach crosslicensing agreements to cut through patent
thickets
Enhance prospects for attracting investors, being
acquired or issuing initial public offerings
Obtain tax reduction from local governments
(e.g. in Shanghai, China)
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