Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

Chapter 1
The Sources and Impacts of Firm-Level Innovationin China, Japan, and the U.S.*
GONG Zhenyu and Gary H. JEFFERSON
Abstract: This paper employs a cross-country panel of firm-level data spanning 20102019 to compare firm performance across three countries: China, Japan, and the U.S.
Specifically, we formulate a three-equation system that enables us to estimate andcompare innovation efficiency and the impact of innovation, measured in terms of patentproduction, on firm-level sales and profits. We estimate the model with a seeming
unrelated regression (SUR) estimator. In order to minimize indigeneity bias, we employ
a five-year differencing of the data and industry-level fixed effects. The results show
different degrees of innovation efficiency with the sample of Chinese firms exhibiting theleast impact of R&D expenditure on patenting and the least impact of patenting on firmsales and profits. The paper also profiles the evolving concentration of patent production
and holdings. As compared with Japan and the U.S., over the sample period, the data
show in China a substantial reduction in firm-level patent concentration, although such afall in concentration and redistribution of patenting activity is evident in all three
economies. This change in patent concentration, particular in China, raises importantquestions regarding the heterogeneity of firms within the sample and the ways in whichthat heterogeneity is changing over time and the implications of that change for overall
firm performance.
Key Words: China, patent production, firm performance, firm heterogeneity, country
comparisons*

The authors very much appreciate the resource and technical support provided by Koichiro

Kimura.
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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

1. Introduction
The first two decades of the current century have witnessed a surge of innovation activity,
particularly in Asia, most dramatically in China, but also in the OECD economies,
including Japan and the U.S. It is not surprising that this surge has been most evident for
China, given that it only promulgated its patent law in 1985, followed by a dramaticincrease in R&D spending. By 2015, China’s ratio of R&D to GDP surpassed two percent,enabling China’s R&D intensity to rise to the range of 2-3%, comparable to that of thelarger OECD economies.
Our objective in this paper is to examine both the source of a key measure ofinnovation, i.e., patent grants, the effectiveness of R&D in producing patent grants andthe impact of patents on firm-level performance, i.e., both sales and profitability. Whilea substantial literature has emerged concerning patenting in China, little of it is supported
by firm-level data. The paper supports three objectives: Identify the incidence, distribution, and concentration of innovation effort andinnovation outcomes;
 Estimate the impact of innovation effort on innovation outcomes; and Estimate the impact of innovation outcomes on enterprise performance.
Robert Solow’s seminal contribution to economic growth (1956), followed by a
substantial body endogenous growth theory and application confirmed the central role oftechnical change as the principal driver of long-run growth and rising living standards.
Whereas during the first three decades of China’s economic transformation, Chinese
producers were generally able to imitate and absorb readily available technologies fromabroad, often without formal applications of research and development spending, during
the past decade, China’s continued movement toward the international technology
frontier has required more formal and costly modes of innovation. Such formal
applications of R&D spending have resulted in widely-publicized technology
achievements, including those in renewable energy, electric vehicles, and various 5G
technologies, as well as in the defense sector.
The surge in patenting both domestically and internationally has drawn substantial
academic attention. Jefferson and Jiang (forthcoming) review much of this literature.
While firm-level data had been available and used in some quarters prior to 2010, during
the recent decade, as China has increasingly expanded its R&D and patenting, limited

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

amounts of firm-level data have been accessible. The research project of which this paper
is a part seeks to remedy this paucity of analysis.
A key finding of this study is that like Japan and the U.S., estimates of China’s
patent-R&D elasticity are positive and highly robust. However, as compared with these
two large OECD economies, the magnitude of the Chinese estimates is relatively small.
One result that is unexpected and difficult to explain is that the impact of patentproduction on overall firm performance – sales and profits – appears at best to be
negligible. Taking the estimates at face value, the results show that greater patentproduction in China’s firm sector has a negative impact on firm performance.
This study raises certain questions regarding the quality and consistency of thedata. We attempt to examine these. Furthermore, a time series analysis of theconcentration of patenting indicates that the concentration profile differs substantiallyacross groupings of firms; moreover, that profile is shifting as the China, substantiallymore so than Japan or the U.S., is exhibiting a substantial shift in patenting concentration
away from its largest firms. Hence, we see not only a substantial heterogeneity of firms
within the three counties, but also shifting profiles of this heterogeneity over our sample
period.

2. Literature Review
Table 1 outlines 14 published papers relating to patent production; most also report the
impact of patent production on some measures of firm performance. All but two papers
use U.S. firms; the remaining two consist of samples from Germany and India. Most of
the samples are relatively small. Only two – the Indian study and a study using Compustat
data – include more than 1,000 firms. None provides country comparisons. Most use datathat are single period cross sections. While the data sets may include more than one yearof data, in order to accommodate a time structure involving a substantial lag of uncertain
duration between R&D activity and the filing or granting of the resulting patents, theformatted data combine two or more years of the innovation input and output measures,
thereby smoothing the data. Finally, a number of the patents examine the recursive natureof patent production in which the patent outcomes significantly affect measures of firm
performance.

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

Table 1: Firm-Level Studies
Authors

SampleVariables

MethodFindings

Scherer(1965)

365 firms from theFortune 500 list(USA)Patents granted 1959

Cross-section analyses

Positive relationshipbetween patents granted
and sales growthProfits, sales growth,
profit ratio (1955–1960)

Time-lag of four years
between invention (1955)
and patent grant (1959)

Patents granted have apositive impact on profits
via sales increases

Dummy-variable perindustry

Regression analyses
between patents granted
in 1959 (1955), andsubsequent yearly
success variables (1955–
1960)

No impact of patents
granted on the profit ratioi.e., profits as percentage of
sales

Patent applications(1952–1957)
Patents granted (1955–
1960)

Cross-section analyses

Positive relationshipbetween patentapplications, patents
granted and sales

Sales from productinnovations in the first 2
years after market
introduction (1955–1960)

Time-lag of 3 years
between patentapplications and firstcommercial use

Larger influence of patentapplications on sales

Comanor and Scherer(1969)

57 firms from thepharmaceutical industry

Correlation analyses
Griliches et al. (1991)

Austin (1993, 1995)

340 firms USA

20 biotechnology firms
USA

Successful patentapplications (1970-1980)

Panel analyses fixed
effect.

No influence of unexpected
patent applications on themarket valueMarket value (1973–
1980)

Unexpected patentapplications as thedifference between
present and predictedpatent applications

Present and past patentapplications explain 5% of
the variance in market
value changes

Dummy-variable per firm

Estimation of a patentprediction function under
the assumption of lagged
effects of past patents
and past R&D of up to
three years
Event study

Present patent applications
alone explain 0.1% of thevariance in market valuechanges

550 patents granted

Key patents patentcitations.

Weighting of patentvariables by quality
indicators key patents.

Change of relative market
value during the first 2
days after the patent had
been granted
Narin et al. (1987)

Ernst (1995, 2001)

16 firms from thepharmaceutical industry
USA

50 firms from themachine-tool industry(Germany)

Positive influence ofpatents granted on market
value
Stronger influence of key
patents on market value
Negative influence on themarket value of competing
firms

Patents granted (1975–
1982)

Cross-section analyses

Positive relationshipbetween patent citations perpatent granted and financial
performance

Patent citations (1975–
1982)

No time-lag

No relationship between
the number of patents
granted or of patentcitations and financial
performance

Patent citations per patent
granted (1975–1982)

Correlation analyses

Concentration ratio

Weighting of patentvariables by quality
indicators

Aggregated measure offinancial
Patent strategies
consisting of multiple
patenting indicators:
number of patentapplications, share of4

Cross-section analyses

Firms with many patents ofhigh quality are
significantly more
successful with regard to
all three success variables

Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

patents granted, share ofvalid patents, share offoreign patentapplications, patentcitation ratio andconcentration ratio (1979–
1992)
Sales growth, sales per
employee, development ofsales per employee(1984–1992)

Chauvin and Hirschey(1993)

Roughly 1500 firms fromCOMPUSTAT

R&D intensity and R&D
expenditure (1988-1990)

Capitalized Market Value
without accounting-based
adjustment
Intercept dummy variableinteractions for industry
group classification
Belderbos et al. (2004)

53 firms from
Community Innovation
Surveys (CIS) conducted
in 1996 and 1998
(Netherlands)

Patents granted

Different R&D
cooperation profiles

Erickson and Jacobson(1992)

99 U.S. firms

Labour productivity andproductivity in innovative
sales new to the market
R&D expenditures

Stock returnBosworth and Rogers(2001)

Miller (2006)

60 firms from IBIS
large ¢rm
database

806 firms in theCompustat
Industry Segment data
(1990)

Specify R&D to be
influenced byconcentration, current
profitability, and level ofdebt at the beginning of
the period.
Patents granted (19941996)

Time-lag partly
incorporated

Firms with few patents oflow quality are
significantly less successful
with regard to all threesuccess variables

Various multivariate data
analysis techniques

Firms with a systematic
patent strategy are
significantly more
successful than firms withunsystematic patentactivities

Weighting of patentvariables by quality
indicators
Cross-section analyses

No time-lag

Regression between
market value, R&D andadvertisement
expenditure
Cross-section analyses

Cooperating firms are
generally engaged in higher
level innovative activities

Correlation analyses

Supplier and competitor
cooperation have asignificant impact on laborproductivity growth

Panel analyses fixed
effectNeither R&D nor
advertising expenditures
increase the market valueof the firm more than othertypes of investments or
expenditures.
Obtaining a comparativeadvantage through R&D oradvertising depends
crucially on the specificnature of the expenditure

Instrumental variable(IV) estimation
Instrumental variable
combined with serial
correlation
Instrumental variable
combined with serial
correlation and fixed
effect
The competitive process
and isolating mechanisms

Least Square Dummy
Variable

Market value (1994-1996)

Fixed-effect model

Expenditure on R&DIntellectual property
Patents granted

Cross-section analyses

5

Positive effects ofadvertising and R&D
expenditures on the market
value of the firm
size advantages exist inadvertising and R&D
activity

R&D and patent activity
are positively andsignificantly associatedwith market value
Private returns to R&D inAustralia are low byinternational standards

Evidence from a large
sample of firms shows the
positive relationshipbetween diversification
based on technologicalKimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

diversity and market-based
measures of performance
Patent citations
Tobin’s q
Lee et al. (2006)

Basant and Fikkert(1996)

258 technology-based
US-based
Firms (1985-1999)

4975 Indian firms (19741975, 1981-1982)

Tobin’s q as market value

Dummy variables fordifferent categories
Patents granted, convert
both R&D/marketing
spending and firm value
into ratio measures
Output, was constructedby deflating the value offirms' reported output
using wholesale pricedeflators
Firms' book values forphysical capital wereconverted into net capitalstocksAnnual R&D
expenditures, foreigntechnical knowledge
purchased, spillover R&D
emanating from otherdomestic firms, and so on
Lo et al. (2006)

344 largest publiccompanies in thetechnology sector (19962001)

Three years total
shareholder returns

R&D spending

Technological diversity,
multiple equations
Dummy variable forstatus
Cross-section analyses

A firm's commercialization
orientation can play a more
important role than R&D in
the process of exploiting
the value of technology
assetsMultiple equations

There are substantial
returns to be had fromincreasing the levels of TP
expenditures.

Fixed-effect model

The private returns totechnology purchases are
estimated to be high andstatistically significant,while the private returns tofirms' own R&D
expenditures are somewhat
lower and are often
insignificant.

Output follows the CobbDouglas production
function, capital/stock
follows the Generalized
Leontief- Linear
functional form.
Estimating Annual TFP
Cross-section analyses

Correlation analyses

Independent outside
directors had aneffect of the strength but
not the form of therelationship
External monitors canaffect the form and thestrength of the relationshipbetween R&D spending
and performance.

Institutional ownership

Source: Prepared by the authors.

Viewed against this literature, the similar and distinctive features of our study are
as follows: A cross-country comparison of patenting activity and impacts in three countries –China, Japan, and the U.S.
 Relatively large firm-level samples, each exceeding 2,000 firms.
 Similar to most of the studies included in Table 1, we combine multiple years to
input and output measures to create a single composite measure of inputs andoutput, i.e. R&D and patents and patent and measures of firm performance.
However, because we have access to 10 years of data, the two sub-periods of 5

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

years apiece enable both a considerable smoothing of the data and ability tominimize the possible endogenous effects.
 Given our three-equation model, we use a seemingly unrelated regression (SUR)
estimator.
Given that our focus in primarily on China’s innovation performance over theperiod 2010-2019, we make not of several of the Chinese patenting research highlights.

3. Patenting
China’s patent office – renamed in 2018 at the China National Intellectual Property
Administration – issues three types of patents. These are invention patents, utility model
patents, and design patents. A Chinese invention patent is similar to a United States utility
patent and protects a new technical solution relating to a product, a process, or an
improvement thereof. An invention patent has a 20-year term. A Chinese utility model
patent, on the other hand, covers a new technical solution relating to a product's shape,
structure, or a combination thereof. A utility model patent has a 10-year term. Utility
model patents are not substantively examined and are granted after formality examination,
which generally takes about one to one-and-a-half years or less. In contrast, invention
patents are substantively examined and can take three to five years to grant. Therefore, itis advantageous to have early issuance of a utility model patent to sue for infringement or
to serve as a deterrent, in addition to or in substitution for an invention patent.
Partly due to the relatively new establishment of China’s patent system, the system
has experienced an evolving legal, regulatory, and policy environment. 1 It has been awidespread practice of patent applicants to obtain invention patents and utility model
patents on the same inventions, although such a practice has discouraged by the courts.
Therefore, some double patenting has occurred in China. This practice continued until theState Intellectual Property Office ("SIPO") amended its Patent Examination Guidelines
to limit its occurrence in July 2007.

1https://www.jonesday.com/en/insights/2009/01/what-does-the-third-amendment-to-chinas-

patent-law-mean-to-you

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

The Amendment substantially adopts the 2007 SIPO approach and stipulates thatthe same invention can be granted only one patent at any given time. While the same
applicant can file an application for both an invention patent and a utility model patent
related to the same invention on the same day, the invention patent can be granted only
when the applicant declares his intention to abandon the previously granted utility model
patent, if such utility model patent has not lapsed.
However, ambiguities still exist. For example, it is not clear whether theprohibition against double patenting applies only to same-invention double patenting (i.e.,
applications with identical claims), or whether it also applies to obviousness-type double
patenting (i.e., applications with indistinguishable claims). Furthermore, it is not clear
whether a genus claim and species claim will be considered as double patenting.
A further condition that has likely contributed to lower quality patent proliferationis the creation, particularly by lower levels of government, of patent incentive system thatreward the filing or grant of patents. Studies show that this practice sometimes leads tothe splitting of patents by differentiating claims that would otherwise have been integrated
into a single filing into two or more patents.

4. The Data: A Statistical Overview
Table 2 shows a variety of measures for the three key variables used in this study: thepatent count,2 R&D expenditure, and sales revenue. Each of the measures is based on thesize of the firm sample, which is largely unbalanced over the sample period 2010 to 2019.
This 10-year sample period is broken into two 5-year sub-periods, 2010-2014 and 20152019. In the Chinese case, for example, the mean and median patent counts for the 9,373
firms during 2010-2014 are 15.87 and 9.63. This disparity underscores the extent to whichpatent production is concentrated in the larger firms within the sample. The skewedness
in patent counts is further underscored by comparing the average patent count for the2This study employs the total patent count for each firm – invention, utility model, and design

patents. We have only recently learned that the Orbis data set from which we draw the data
enables a distinction between the higher quality invention patents and the other two patent types– utility model and design patents. We hope to be able to reestimate our model, so as todistinguish the effects of the invention patents vs. other patent types.
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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

lowest, middle, and top quintile firms. For all three countries, the patent count balloons
for the top quintile of firms.
Table 2: Summary Statistics

China

Japan

US

mean
medianst. dev# of firms# of year
observations
ratio
quintiles: 1st
middletop
mean
medianst. dev.
# of firms# of year
observations
ratio
quintiles:
1st
middletop
mean
medianSt. dev.
# of firms# of year
observations
ratio
quintiles: 1st
middletop

Patent count2010-20142015-2019
15.87
17.99
9.63
7.96
174.50153.149,373
9,373

R&D expenditure
2010-2014 2015-2019
3,400
6,977
510.39985.9936,64052,154
9,373
9,373

Sales revenue
2010-20142015-2019373,511467,983
38,221
25,407
5,881,207
5,597,704
9,373
9,373

2.43
48.6%
5.5
10.59
15,875240.9333.54
1308.88
2,289

2.57
64.3%
4.5
8.81
10,116
246.4339
1235.722703
2,289

2.77
55.3%
255.20672.372,128,639
58,5622454.93361,290
2,289

3.86
96.5%
328.131398.99
1,847,692
48,4223874.11
281,562
2,289

2.77
55.3%
26234
44989
412,664,635
2,488,421
368,0319,436,258
2,289

3.85
96.4%
7552.5441643
343,353,940
2,092,278
353,985
7,811,392
2,289

3.44
68.7%
11
36.56
25751

3.38
67.6%
10.5
49.80
24552.5

4.80
96.0%
23.24
4,101.83
8,814,1315.0
100%
1609.41
5,647.25
7,633,736

4.80
96.0%
118,900
567,327
233,119,133

5.0
100%
125,224
537,159
209,911,126

98.75
20.58
694.882,123106.2813.75
778.12
2,123

119,9429347.45
611,742
2,123

165,265
18,015899,5022,123

2,599,818
79,331
14,894,380
2,123

2,638,047
110,912
13,149,833
2,123

3.04
60.7%
9.13
20.98
18,498

3.13
62.5%
7.50
17.52
19,333

3.93
78.5%
3,048.64
14,5299,872,000

4.28
85.6%
5,593.92
28,227
19,164,092

4.13
82.6%
12,114142,165
420,720,800

4.37
87.4%
27,124219,422
243,252,321

Source: Calculated by the authors.
Given that each firm-level observation used for each 5-year period is an averageof the available year observations for that period, Table 2 also reports the number of year
observations falling within each 5-year period for each firm. Thus, for the patent count

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

for China during 2010-2014, the 5-year observations used in the regression exercise arebased on the average of 2.43 year observations.
For China, from the earlier to the later period, the measures of patents, R&D, andsales all increase, although the change in the three variables varies somewhat. Specifically,
while the patent count and sales show modest increases – 13.5% for the former and 25.3%
for the latter –Table 2 shows R&D spending more than doubling during the sample period. The
implication is that while R&D intensity rises from 0.91% in the earlier period to 1.45%
in the later period, R&D productivity – patents per unit of R&D – and sales revenue
decline. Clearly, these changes are not representative of the overall change in Chinese
patenting. We examine this disparity below.

5. The Model and Estimation Strategy
In this section, we formulate a model that enables us to achieve the following: Identify the impact of innovation effort, measured as R&D expenditure, on
innovation outcomes, i.e. total patent grants;
 Identify the impact of patent production on firm performance, i.e., sales revenue
and profitability.
In order to identify and estimate these relationships, the model includes the following
three equations:𝑙𝑙𝑙𝑙𝑙𝑙(𝑃𝑃𝑃𝑃𝑇𝑇𝑡𝑡 ) = 𝑙𝑙𝑙𝑙𝑙𝑙(𝑅𝑅&𝐷𝐷𝑡𝑡−1 ) + 𝑎𝑎𝑖𝑖 + 𝑢𝑢𝑖𝑖𝑖𝑖
𝑙𝑙𝑙𝑙𝑙𝑙(𝑅𝑅&𝐷𝐷𝑡𝑡 ) = 𝑙𝑙𝑙𝑙𝑙𝑙(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡−1 ) + 𝑎𝑎𝑖𝑖 + 𝑢𝑢𝑖𝑖𝑖𝑖

𝑙𝑙𝑙𝑙𝑙𝑙(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡 ) = 𝑙𝑙𝑙𝑙𝑙𝑙(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑡𝑡−1 ) + 𝑙𝑙𝑙𝑙𝑙𝑙(𝑅𝑅&𝐷𝐷𝑡𝑡−1 ) + 𝑎𝑎𝑖𝑖 + 𝑢𝑢𝑖𝑖𝑖𝑖

(1)
(2)
(3)

In the above specification, t and t-1 represent the two five-year periods 2010-2014
and 2015-2019. The variable ai represents the 30 two-digit sectoral classifications asshown in Annex 1. We use the two five-year periods for several reasons. The first is thatthe sample is highly unbalanced. For all the full sample of 9,373 Chinese firms, eachreports at least one year-observation for each of the two sub-periods. As shown in Table
2, the average number of year observations for each 5-year period ranges from a low of
2.4 to a high of 3.9. For Japan and the U.S., incidence of reporting is somewhat higher,

10Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

significantly so for Japan for which the reporting incidence for both R&D expenditureand sales revenue is 4.8 for the earlier period and 5.0 for the later period.
The first reason for the division of the data over the 2010-2019 period into two 5year sub-periods is an attempt to capture the dynamic interaction, or time structure of thefirms within our sample. Estimating the relationship between innovation – innovation
inputs and output, firm size and innovation effort, and innovation outputs and firm
performance – generally spans multi-year periods. This is particularly the case for our
only measure of patent production, i.e., patent grants, which may materialize only several
years after innovation resources, i.e., R&D spending are committed to projects thateventually yield patent grants. As reported in our literature review, a significant share of
the literature in the field of patent production incorporate multi-year lags between R&D
input and patent count output. Likewise, for the sales and profit equations, we anticipatea lag between patent production and firm performance. To the extent that new patents
represent new products, product quality improvements, or process improvements, these
are likely to materialize in the market only with a significant lag.
A second, related reason for the two 5-year segments is to minimize endogeneitybias. The greater lag between innovation input and innovation output is likely to enable afuller assessment of innovation input-output causality, rather than the simply a correlationin which positive shocks to patent production result in commitments of greater R&D
resources.
While the time dimension of our panel does not allow for shorter time horizons
that would ideally enable a panel consisting of additional numbers of time-series
observations for each firm, thus enabling the application of fixed effects, we do include
fixed effects for industry classifications. Given our formulation of the 3-equation modelof firm innovation and performance, we anticipate a degree of correlation of shocks acrossthe equations. That is, firm-level shocks to the innovation equation may be correlatedwith shocks to the firm performance equations. Likewise, shocks to the sales equation arelikely to be correlated with shocks to the profit equation. In order to internalize
information from these shocks into the estimation procedure, thereby improving theefficiency of the estimation results, we employ a seemingly unrelated regression (SUR)
estimator for each country.

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

6. Estimation and Results
Tables 3-5 show the estimation results for three sets of regressions – patents, sales, andprofit – for China as well as, for purposes of comparison, Japan and the U.S. Each of thetables reports a p-statistic for each point estimate. The results are quite robust, for the
relevant explanatory variables, each of the country three-equation models reports p-statsof 0.00. Nonetheless, between the three countries, the results show significant differencesin the point estimates.
Table 3: Patent Creation, PATt
China
Japan
U.S.
R&Dt-1
0.286
0.534
0.433
(0.00)(0.00)(0.00)
intercept
0.065-1.554-0.702(0.81)(0.00)(0.25)#observations
9373
2289
2123
Adj. Rsq.
0.191
0.437
0.403
*The numbers in parentheses are p-stats; the time period, t, spans 5years. t-1 spans the preceding 5-year period.
Source: Estimated by the authors.
Table 4: Impact of Patenting on Sales, SALESt
China
Japan
U.S.
SALESt-1
1.298
0.853
0.570
(0.00)(0.00)(0.00)
PATt-1-0.1320.053
0.282(0.00)(0.00)(0.00)
intercept-3.991
1.898
4.284(0.00)(0.00)(0.00)#observations
9373
2289
2123
Adj. Rsq.
0.689
0.955
0.781
*The numbers in parentheses are p-stats; the time period, t, spans 5years. t-1 spans the preceding 5-year period
Source: Estimated by the authors.

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

Table 5: Impact of Sales and Patents on Profit, PROFt
China
Japan
U.S.
SALESt-1
1.209
0.761
0.529
(0.01)(0.00)(0.00)
PATt-1-0.1140.114
0.329(0.02)(0.00)(0.02)
intercept-3.6221.468
3.301(0.37)(0.22)(0.61)#observations
9373
2289
2123
Adj. Rsq.
0.650
0.894
0.746
*The numbers in parentheses are p-stats; the time period, t, spans 5years. t-1 spans the preceding 5-year period.
Source: Estimated by the authors.
We first examine the results in Table 3 regarding the power of R&D spending todrive patent production. As expected, these results are highly robust, both for China andthe other two economies. However, as shown, the estimated patent-R&D elasticity for
China – 0.286 – is substantially smaller than the counterpart estimates for Japan and the
U.S. The overall adjusted Rsq. measure is also substantially less. The implication is thatwithin China, spending on R&D does not exercise as direct an impact on overall patentproduction as it appears to exert on patent production in Japan and the U.S. There areseveral possible explanations for this difference.
The first is that, because China’s total patent count includes a substantial portionof lower-quality patents – utility and design patents – as compared with Japan and the
U.S. for which the proportion of such patents is rather low, we anticipate that many of thelower quality patents materialize without substantial applications of formal F&D
spending. The fact that the relative intercept values show China producing more patents
without applications of R&D spending as compared with Japan and the U.S. likely reflects
the fact that many Chinese patents result from learning by doing and technology spillovers.
A second possible explanation for the relatively weak effect of R&D expenditureon patent production was foreshadowed by Hu and Jefferson (2009). Using a large panelof Chinese firm level data for 1995-2001, as in this study, these authors estimate theimpact of R&D on patent production. They find substantially weaker elasticity estimates
than those reported in Table 3. Hu and Jefferson explain that the likely reason for the low
estimates is the relatively robust role that industry foreign direct investment played inpromoting patenting activity. Having focused on a period nearly two decades earlier thanour sample period when imitation was a far more active pathway for technology transfer

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

and patenting, their result was not surprising. While FDI may continue to be a stimulant
to Chinese innovation, independent of R&D spending, its effect is likely to be greatly
diminished. Nonetheless, whether the impact is direct or through its interaction with R&D
spending, FDI is likely to continue in some sectors to be a gateway for Chinese patenting.
A third factor concerns changes in China’s patent law and other special, evolving
features of China’s patent regulatory landscape. Such changes that alter appraisal
standards, including those incorporated the patent system’s China’s Third Amendment
could potentially weaken the input-output link in patent production. 3 Such changes in the
Third Amendment include the implementation of more rigorous novelty standards forboth invention and design patents, limitation of double patenting, including obtaining a
fast-approved lower-quality patent followed by a standard higher-end 20-year patent.
Other such changes during this period include a variety of provincial and local
governments instituting reward systems for patent filings and grants. One difficulty withthese policy schemes, however, is that the reward systems are often transitory, subject torestructuring or outright elimination, again with hard-to-predict impacts on overall patentproduction. The upshot is that such changes in patent standards and the incentive system,
may cause our estimates to be less efficient than they are for the more stable and uniform
R&D and patent systems in Japan and the U.S.
Table 4 reports estimation results for the role of prior sales and patenting on sales.
Here the differences between China and Japan and the U.S. are notable and puzzling;differences are not only statistical different with estimates of the same sign, but show
results that are signed differently. First, for all three countries, as expected, sales revenue
over the earlier 2010-2014 period is a robust predictor of sales volume during the recent
five years. Nonetheless, the differences are striking, with the estimate for China showing
at 1.30, while those reported for Japan and the U.S. are 0.85 and 0.57. The fact that China
shows a result exceeding unity, more than twice that of the U.S. begs explanation. That
the Chinese firms show an estimate for SALEL-1 likely reflects the fact, as shown in the
Table 2 Summary Statistics, that from 2010-2014 to 2015-2019, average sales revenue
grew by 25%. By comparison, for the Japanese sample, sales shows a substantial decline,
while for the U.S, average sales revenue remains little unchanged from the early to later
period.
3

https://www.jonesday.com/en/insights/2009/01/what-does-the-third-amendment-to-chinas-

patent-law-mean-to-you

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

Quite likely, the difference between China and the U.S. is shown in comparisonsof the means and median values of sales revenue. That China shows the coincidence of a
substantial increase in the means paired with a substantial decline in median sales
indicates that firms with the largest sales during 2010-2014 enjoyed the most rapid
increase in sales revenue during the latter half of the sales period. For the U.S. the result
is different, median sales grow faster than the mean, suggesting that smaller firms enjoyedrelatively robust sales growth during the sample period. These firm size-relateddifferences can account for the difference in the estimates of the impact of sales. Thispattern is also likely to account for the similar counterpart estimates for profit.
The most surprising result for the sales and profit equations is the difference in
the impact of innovation on the firm’s later performance. For the U.S. and, to a lesser
degree, for Japan, the results show an extremely robust, positive impact of early patenting
on later sales and profit performance. In Table 2, the mean and median results for both
China and the U.S. shows what appears to be a greater concentration of patenting in larger
firms from the early to the later 5-year period. As firms that are the most patent productive
during 2010-2014 become even more comparatively patent productive during 2015-2019,
we would expect this shifting heterogeneity to impart an upward bias to estimates of thepatent coefficient. While this may be the case for the U.S., reporting estimates in excess
of 0.5, the contrary appears to be true for Chinese firms that report estimates of -0.11 orless.
At this point, we advance two possible, related, explanations for this set ofsurprising results. One possibility is that the firms with the greatest patent count in 20102014 tend to undertake the greatest restructuring during 2015-2019. In particular, theirrestructuring is outside their main product line. We know for Chinese firms that when
they report their sales revenue to the National Bureau of Statistics, the accounting is solely
for the firm’s “principal business.” Sales activities that falls outside the high-patenting
firm’s principal business are not included in the formal reporting of sales revenue. Related
to this explanation is the possibility that China’s high-volume patent producers tend tosell their patents, thereby generating revenue that falls outside their official reporting
channels. These possible conditions require further exploration.

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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

7. Patenting Concentration
We find it somewhat curious that in our data set, only the largest size firms report owning
patents. Taking the reported patents on their face value, we investigate the concentrationof patenting within the sample of the largest 1,000 firms. By computing these ratios, weare able to estimate changes in patent concentration over the period 2010 to 2018. The
results are shown in Table 6. 4
Table 6: Patent Concentration by Number of Firms
Top # of
firms
China
2010
2018
Japan
2010
2018

5

10

25

100

500

25,591
39%
17,10620%

29,15645%
22,522
26%

35,38654%
31,36036%

45,49970%
49,292
56%

59,03390%
75,08786%

101,066
21%
39,451
20%

165,680
34%
57,89229%

251,966
52%
89,00445%

379,23978%
149,52076%

476,84598%
192,862
97%

U.S.
2010

54,97673,75399,039131,015
157,988
34%
45%
61%
80%
97%
2018
28,47740,892
55,17073,53388,355
31%
45%
60%
80%
96%
*% represents patent production as a share to the total number of patents produced by the1000 largest patent producers in the given year.

Source: Calculated by the authors.
For all the countries, as anticipated as the proportion of firms included in theconcentration counts increases – from 10 out of 1,000 to 500 of 1,000 – the patent share
increases. In 2010, China reports the highest patent concentration for its top five firms.
At the other end of the distribution, for the top 500 firms, while at 90%, the concentration
is high, it is less than the concentration ratios reported for Japan and the U.S.
For China, Table 6 shows a substantial decline in patent concentration from 2010
to 2018, whereas for Japan and the U.S. the concentration ratios are either stable or show
4

Note that in each period, i.e., 2010 and 2018, the 5, 10, 25…1000 firms may not be the samefirms; they are, within their numerical group, the largest patent producers within each period.
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Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

a small decline. For all three countries, the number of patents held by the top 5 firms
declines substantially from 2010 to 2018. For China, the decline persists, but diminishes,for the top 10 and top 25 firms. For the top 100 and top 500 firms, the total patent countthen grows from 2010 to 2018. For both Japan and the U.S., the total patent count declines
substantially over the sample period. Whereas for the U.S. the decline is consistently
somewhat less than one half, for Japan the reductions lie in the range of 2.5 to 3.
Overall, the results reported in Table 6 raise important issues for our analysis. This
shift in the concentration and distribution of patent productivity raises critical issues forour interpretation of the estimation results shown in Tables 3-5. That is, from the earlier
to the later period, the concentration distribution of patent production is changing
dramatically as between the larger and smaller firms within our sample, our results may
be overlooking key structural changes within the data that are obscured by the aggregationof the data. These changes argue for a more granular examination of the data, exploring
the nature of our three relationships between R&D and patenting and patenting and firm
performance sub-samples or interaction effects accounting for size and industry
differences.

8. Conclusion and Discussion
This study investigates the impact of innovative activity at the firm level within China.
For purposes of comparison, we extend the analysis to samples of firms in Japan and the
U.S. The comparisons are helpful, showing that while China shows impressive numericcomparisons with the OECD economies in relation to R&D intensity and overall patentcounts, the productivity of its innovation system and the impact of that innovation, in turn,on firm performance may continue to lag behind OECD standards.
These results must be tentative. At this point, the research encounters a number oflimitations resulting from limitations of or difficulty in interpreting the data on the data
set made available for this study. There are two key difficulties:
 The principal difficulty is ambiguity regarding which firms are included andexcluded from the data set. The fact that for China, less than 10,000 firms report
data with sufficient consistency to conduct this research raises deeply serious
problems with respect to selection bias. Unable to use the data set to identify
selection criteria that are associated with the included and excluded firms, we are17

Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

unable to correct for the resulting selection bias associated with the omission ofseveral million firms from the data set.
 A second problem is that of identifying patent quality. The first quality-related issue
is that of distinguishing between different patent types – higher quality invention
patents and lower quality utility and design patents. Furthermore, within the patentdata, we are unable to identify the number of claims and citations – backward and/or
forward – that serve to differentiate patent quality. With recent clarification of thedata set, it appears that some of this patent quality control can be incorporated into
the analysis. This should be attempted.
Nonetheless, given these limitations, this study raises important questions andpossibilities. One such issue is concerning the vast heterogeneity across firms within thedata set and the transitioning of this heterogeneity even over the relatively short period
covered by the data. Table 6, for example, shows substantial evolution with our firm
sample of R&D effort, patent production, and sales and profit outcomes by firm size. Thatis, the concentration of Chinese patents appears to be substantially flattening as
increasingly numbers of firms acquire innovation capabilities. Key issues concern the
differences across industries that are becoming more technology and patent intensive,
particularly as these may relate to China so-called “pillar industries” and the priorities set
forth in China 2025.
A final issue concerns location, the recent study by Jiang et al (2019) using
USPTO patent data finds extreme geographic concentration of Chinese patents filed andgranted by the U.S. patent agency. According to these authors, 66.7% of the USPTO
patent grants originating from China originate from the residents of only three cities –Beijing, Shanghai, and Shenzhen – representing just 4.25% of the population. The abilityof China to diffuse its innovation capabilities across a larger swath of Chinese geography
and population is a key challenge to the country’s ability to achieve a deep and wideangled set of technology frontier capabilities.

References
Austin, D.H. (1993) “An event-study approach to measuring innovative output: the caseof biotechnology,” American Economic Review 832: pp. 253–258.
Austin, D.H. (1995) “The power of patents,” Resources 119: pp. 2–5.

18

Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

Basant, R., and B. Fikkert (1996) “The Effects of R&D, Foreign Technology Purchase,and Domestic and International Spillovers on Productivity in Indian Firms,” The
Review of Economics and Statistics 78(2): pp. 187–199.
Belderbos, R., M. Carreeb, and B. Lokshinb (2004) “Cooperative R&D and firm
performance,” Research Policy 33: pp. 1477–1492.
Bosworth, D., and M. Rogers (2001) “Market Value, R&D and Intellectual Property: An
Empirical Analysis of Large Australian Firms,” The Economics Record 77(239):
pp. 323–337.
Chauvin, K.W., and M. Hirschey (1993) “Advertising, R&D Expenditures and the Market
Value of the Firm,” Financial Management 22(4): pp. 128–140.
Comanor, W.S., and F.M. Scherer (1969) “Patent statistics as a measure of technicalchange,” Journal of Political Economy 77: pp. 392–398.
Erickson, G., and R. Jacobson (1992) “Gaining comparative advantage throughdiscretionary,” Management Science 38(9): pp. 1264-1279.
Ernst, H. (1995) “Patenting strategies in the German mechanical engineering industry andtheir relationship to firm performance,” Technovation 154: pp. 225–240.
Ernst, H. (1997) “The use of patent data for technological forecasting: the diffusion of
CNC-technology in the machine tool industry,” Small Business Economics 94: pp.
361–381.
Griliches, Z., B.H. Hall, and A. Pakes (1991) “R&D, patents, and market value revisited:is there a second technological opportunity related factor?” Economics ofInnovation and New Technology 1: pp. 183–201.
Hu, A. G.Z, and G. H. Jefferson (2009) “A great wall of patents: What is behind China's
recent patent explosion?” Journal of Development Economics 90(1): pp. 57–68.
Jefferson, G. H., and R. Jiang (forthcoming) “China’s S&T Progress through the Lens ofPatenting,” The Oxford Handbook of China Innovation, Oxford: Oxford
University Press.
Jiang, R., G. H. Jefferson, and H. Shi (2019) “Measuring China’s International
Technology Catchup,” Journal of Contemporary China, published online, Oct.
2019, https://www.tandfonline.com/doi/abs/10.1080/10670564.2019.1677362
Lin, B.W., Y.K. Lee, and S.C. Hung (2006) “R&D intensity and commercialization
orientation effects on financial performance,” Journal of Business Research 59:
pp. 679–685.

19

Kimura, Koichiro, ed. (2020) Innovation in East Asia (BRC Research Report), Bangkok: Bangkok
Research Center, JETRO Bangkok/IDE-JETRO.

Lo, S.A., B. Walters, and M. Kroll (2006) “The moderating effects of external monitorson the relationship between R&D spending and firm performance,” Journal ofBusiness Research 59: pp. 278–287.
Maltza, E., W.E. Souderb, and A. Kumar (2001) “Influencing R&D/marketing integrationand the use of market information by R&D managers: intended and unintended
effects of managerial actions,” Journal of Business Research 52(1): pp. 69–82.
Miller, D.J. (2006) “Technological diversity, related diversification and firm
performance,” Strategic Management Journal 27: pp. 601–619.
Narin, F., E. Noma, and R. Perry (1987) “Patents as indicators of corporate technologicalstrength,” Research Policy 16: pp. 143–155.
Scherer, F.M. (1965) “Corporate inventive output, profits and growth,” The Journal of
Political Economy 733: pp. 290–297.

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Research Center, JETRO Bangkok/IDE-JETRO.

Annex 1: List of Included Classifications & # of Firms
Classifications
China
Japan
Agriculture, Horticulture & Livestock
144
20
Banking, Insurance & Financial Services
1026
Biotechnology and Life Sciences
43
18
Business Services
751
848
Chemicals, Petroleum, Rubber & Plastic
1332
673
Communications
364
110
Computer Hardware
78
19
Computer Software
246
210
Construction
110
1145
Food & Tobacco Manufacturing
273
261
Industrial, Electric & Electronic Machinery
2404
1792
Leather, Stone, Clay & Glass products
213
164
Media & Broadcasting
448
82
Metals & Metal Products
525
594
Mining & Extraction
119
16
Miscellaneous Manufacturing389
118
Printing & Publishing49
105
Property Services
31
192
Public Administration, Education, Health Social Services
79
72
Retail188
361
Textiles & Clothing Manufacturing
208
134Transport Manufacturing
378
210Transport, Freight & Storage
115
141
Travel, Personal & Leisure52
240
Utilities
209
39
Waste Management & Treatment
33
69
Wholesale992
1897
Wood, Furniture & Paper Manufacturing
161
307
Source: Calculated by the authors.

21

U.S.
2
17
200
86
453
108
41
99
7
39
708
10
25
54
46
17
6
3
24
18
11
72
7
13
17
5
29
23