Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

Analysis of Firm Size Effect on R&D Activities in Japan1
By
Akiko Nakajo*

Abstract

In this paper we examine the effect of firm size on R&D activities using regression

analysis.

We choose 377 firms from 6 industries to show both intra-industry and interindustry differences in R&D activities. Our results reveal that (1) firm size explains a largepart of the differences in R&D spending levels, (2) we cannot easily decide the functional
form representing firm size-R&D relationship because a few large firms influence the modelsignificantly, and (3) firm-specific and industry-specific variables, representing the state oftechnology, should be considered in the future.

1.

Introduction

In the past few decades, a considerable number of studies devoted to the analysis on the relationship between firm size and the level of R&D expenditure, have suggested that large firms
would have the advantage over relatively small firms in R&D activities. In fact, we can observe
intra-industry differences in R&D intensity, which is generally used as the measure of R&D
performance. Cohen and Klepper (1992) have taken some important steps in this direction,
examining the pattern of R&D intensity distributions at the SIC two-digit level using the individual FTC lines of business data. They tried to deduce a probabilistic model of R&D in orderto account for the distributional regularities. Their conclusion returns to the long discussed mat

ter: the effects of firm size on R&D and innovation. Numerous attempts to solve this problem,
however, use rather old data of the 1960s and the 1970s. This urgently calls for an examination

with recent data on how firm size plays an important role in conducting R&D. To begin with,
we review the previous studies and indicate what problems still remain. Next, after presenting
the characteristics of our sample data used in this paper, a comparison of the firm size and the
R&D intensity distributions between industries is provided. Following the presentation of themodel and its estimation results, some remaining issues are discussed at the end of the paper.

2.

Analytical Viewpoints in the Previous Studies

Mansfield (1963) noticed about 30 years ago that there is a critical investment level required forinnovation, and found that the four largest companies made up a large share of the innovations.
He also pointed out in his successive work (1964), which examined the data of 38 firms in 5
industries from the period 1945 to 1959, that firm size is one of the determinants of R&D
expenditure level. This issue on the relationships between firm size and R&D expenditure

has led to the discussion on how market concentration affects R&D performance. Althoughconcentration has been a topic of study for a long time, there is little agreement to the degree
which it is desirable for the maximization of R&D activities2.
Manuscript received March 13, 1995. Revised June 27, 1995.

* Faculty of Information And Communication, Bunkyo University

11 wish to express my gratitude to the anonymous referee for valuable comments and criticisms.
2 For more details about the theoretical framework, see Kamien and Schwarts (1976), Loury (1979), andDasgupta and Stiglits (1980).

Analysis of Firm Size Effect on R&D Activities in Japan81

Without definite results from empirical analyses during the 1980s, firm size, however, isstill believed to be a determinant of R&D level.

One of the exceptional approaches is madeby Pakes and Schankerman (1984), which refers to the appropriability of R&D outcome andthe technological opportunities3 corresponding firms face. They admit the limit of their modeland data because both appropriability and technological opportunity are unobservable and theycannot separate the contribution of these two factors on intra- and interindustry differences in
R&D intensity. In the late 1980s, researchers seemed to be mixed up in choosing independent

variables in their models4.
Although the differences in innovative activities are believed to be caused by the joint effectof factors relating to production and R&D, what those analyses tried to reveal was ambiguous.

Cohen, Levin and Mowery (1987), however, indicate that both business unit and firm size do
not explain the variance of R&D intensity, and that what influences this variance is industrial
effect: differences in technological opportunity, appropriability and market condition. Again,
it was their failure to confirm the effect of firm size that have driven them to depend on thesetroublesome variables. There is one further problem that we must not ignore. Most of the works
during the 1980s are based on 1970s data, when many developed countries experienced structuralchanges. For this reason, results of those analyses cannot be accepted as decisive conclusion.
Several articles have analyzed this subject in Japan since more than a decade ago using similar
approaches. For example, Nakanishi et al. (1983) deduces that industrial concentration has
a negative effect on R&D performance. Another work by Doi (1977), however, shows thatfour-firm concentration does not have a significant effect but firm size does at 1% level. Uekusa(1982) concludes that R&D expenditure level increases as firm size becomes larger until firm size
reaches some critical points. He classifies industries into three categories: innovative, average,
and maturing. He also suggests that it is the larger firms in innovative industries that have theadvantage over smaller firms. There is sufficient evidence to show that, in Japan, firms withlarger capital, more employees, and larger sales spend more R&D expenditure than "smaller"
firms. Nakajo (1994) has examined R&D concentration on large firms using data from the Surveyof Research and Development by the Statistics Bureau at the Management and Coordination
Agency. R&D expenditures of the top 5 companies in an industry are found to account for morethan 50% of total industry expenditures in 16 industries. Compared with sales concentration in
the top 5 firms, R&D concentration is distinctly observed in more industries. Although Uekusa(1982) deduced the foregoing conclusion based on 1960s' data, our data may also show similar
results that large size is conducive to innovative performance. Since data at the industry levelare only available from the Survey of Research and Development, we have to use individual firm's
R&D data in its financial statement. Unfortunately, however, not all companies report their
R&D spending as there is no legal obligation to announce it. Even when R&D expenditures
are reported, R&D expenditures are sometimes entered as different items of the account as
to different firms. Moreover, there are some companies which declare their R&D spending
intermittently and this does not allow us to perform time series analysis.

3.

Data

In this paper, the sample firms are chosen from 6 industries: textiles, iron and steel, generalmachinery, transport equipment, electrical machinery, and precision instruments5. Firms which
3 According to Scherer (1965), technological opportunity indicates animation of "scientific climate" and pos
sibility that new technology appears.

4 For example, Acs and Audretsch (1988) select eight independent variables, including one regarding labor
union, to show how these inputs are transformed into innovative outputs.

5 Chemical industry accounts for above 15% of R&D expenditure in Japan, but they are excluded from thesample. This industry includes chemical fiber, oil and paint, drugs and medicines, and other chemical products,
all of which are quite different from one and another in terms of technology. Technological heterogeneity in one

82 Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

are not listed in the First Section at the Tokyo Stock Exchange in fiscal year 1993, and thosewhich do not report R&D expenditure of the corresponding year are excluded from this sample6.
In the end, 29 out of 46 firms (63%) in textiles, 22 out of 38 firms (58%) in iron and steel,66 out of 96 firms (69%) in general machinery, 34 out of 56 firms (61%) in transport equipment,
83 out of 121 firms (69%) in electrical machinery, and 15 out of 21 firms (71%) in precision
instruments remain. We found that about 30% or 40% of these firms, an unexpectedly large
portion of the whole, do not earmark R&D expenditures. Compared with data of the Surveyof Research and Development by the Statistics Bureau at the Management and Coordination

Agency, however, R&D by firms in this sample represents on average 55% of the corresponding
industrial R&D \ The sample size is reduced considerably, including 250 firms in all. This isunavoidable due to the limitation of data because we can neither ascertain the reason why eachfirm does not report its R&D expenditure nor estimate it directly from its financial statement.

R&D expenditure data of individual firms are also reported in other sources such as Kaisha

Shikiho (Firm Quarterly Report). More firms announced their respective R&D expenditures in
Kaisha Shikiho than in financial statement, but for some unknown reasons, R&D expenditurereported in Kaisha Shikiho is usually larger than that in financial statement (generally 2 or 5

times to 181 times at maximum). In this paper, R&D expenditure data are taken from financial
statement because sales data are also taken from financial statement in this paper. As a matterof fact, sales data in Kaisha Shikiho are also quoted from financial statement. It is important
to bear in mind that since the listed companies meet the requirements of listing, they are firms
beyond certain "size".

According to the listing standard, they are required to reach certain
levels in terms of (l)the number of listed stocks, (2) the number of stockholders, (3) the numberof years they do business continuously, (4) net assets, (5) annual net profit, and (6) dividend(under Article 7, Clause 1 and 2, Article 13 of the Listing Agreement). In other words, the firms
we examine rank high in terms of sales or profits in their respective industries. Our analysis arestill important, however, because there are some vital differences in their R&D activities evenamong relatively large firms. To begin with, we represent the distribution of firm size (measuresin terms of sales) by industry, including the firms with no R&D reports (Figure 1). The. blackbars in the histograms indicate the number of the firms excluded from our sample. It should be
noted that the scales of the horizontal axis are different among the industries.
As Figure 1 shows, the solid black bars clustered at the left hand side of the histograms. Thismeans that relatively small firms tend not to disclose their R&D activities. Although this data
restriction has been pointed out in various studies, our analysis cannot but be biased toward
larger firms.

One exception is the case of transport equipment industry (Figure 1-d). Most of the world
famous auto-makers with large sales compared with other companies do not report their R&D

spending level7. In addition, we also cannot obtain the R&D data of several other firms withrelatively large sales. These companies definitely consider R&D activities as important and musthave spent a certain amount of R&D expenditures. If they had declared their R&D spending,we could have deduce more precise explanation about size effect on R&D performance in thetransport equipment industry.

industry should be discussed at more disaggregated level in the future.

6 We also exclude firms which (l)consign research to other firms or institutions and report that expenses as
general and administrative expenses, (2) report R&D expenditures not as general and administrative expenses but
as research depreciation included in non-operating expenses, (3) report R&D as research depreciation of deferredassets in balance sheet, and (4) report spending on experiment tools (which are presumably R&D-related but
cannot be identified exactly).

7In fact, this happens not only for 1993 but every year, hence we cannot made estimation by using the previous
year data.

ALL FIRMS

NO R&DALL FIRMS

NO R&D

Analysis of Firm Size Effect on R&D Activities in Japan

TextilesFigure 1-a: Firm Size Distribution

Iron and Steel

Figure 1-b: Firm Size Distribution

8384 Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

NO R&DALL FIRMS

30000

15000090000

270000210000390000330000570000720000450000Figure 1-c: Firm Size Distribution

General Machinery

NO R&DALL FIRMS

Figure 1-d: Firm Size Distribution
Transport Equipment

Analysis of Firm Size Effect on R&D Activities in Japan 85

NO R&DALL FIRMS

Figure 1-e: Firm Size Distribution

Electrical Machinery

NO R&DALL FIRMS

Figure 1-f: Firm Size Distribution

Precision Instruments

Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

Table 1: Descriptive Statistics on Firm Sales, R&D Expenditures, and R&D Intensity by Industry

Sales(million yen]

Industry

All Companies

R&D Expenditures

R&D Intensity(million yen)Sample

(%)

mm.

max.

mm.

max.

min.

max.

min.

Textiles

2248

99448816829

994488

25

38999

0.08

Iron &; Steel

8596

2368853

15489

2368853

64

35265

0.06

2.79

General Machinery

9198

7485939198

748593

7

27161

0.03

7.15

Transport Equipment

max.

5.30

23995

9030857

23995

2615959

20

64186

0.03

3.32

Electric Machinery

9724

4550086

13342

381149870

319278

0.14

13.32

Precision Instruments

16297

1036938

16297

1036938

111

118282

0.24

11.41

Table 1 summarizes the range of firm sales, R&D expenditure, and R&D intensity (the ratioof R&D expenditures to sales) by industry. The differences between minimum and maximum
R&D expenditure within the industry are extremely large. In general machinery, for example,
the company with the maximum R&D expenditure spends about 4,000 times more than the
one with the minimum R&D expenditure. The intraindustry variation in R&D activity is also

reflected in the wide range of R&D intensity8.
Some companies spend heavily on R&D activities, while others seem to regard them lessimportant and/or are not able to spare enough budget for them. If minimum R&D level requiredfor continuous and successful innovation activities does exist, as Mansfield mentioned long ago,the lower limit would reflect the marginal capacity of R&D performance.

Figure 2 also* illustrates the R&D intensity distribution by industry. All the industries show

similar pattern9.
A substantial number of zero reports are excluded, as mentioned above. When converting
this pattern into a prototypical frequency, we notice that R&D intensity in our sample can beclassified into three groups. Group one consists of those whose intensity is less than 1. The
second group is the one positioned at the middle. The last group contains the companies withhigh intensity and sometimes these companies are also the largest in their respective industries.
That is, the largest firms are more innovating and may take a leadership in R&D performance.
This frequency pattern we observed is different from the one examined by Cohen and Klepper(1992). The distributions in their paper are positively skewed with a tail to the right, and we
can safely say that this feature is roughly the same as ours. They could not find, however,intra-industry groups classified in terms of R&D performance, which may be an important clue
to explain the difference in R&D strategies among firms in the same industry.

8 We can also observe the inter-industry differences in R&D intensity. This issue will be discussed in the laterpart of this paper.

9 However, the pattern of the precision instruments industry presented in Figure 2-f is rather different fromthose in other industries, but this is largely due to the small sample size.

0.2
1.6

1.4

1.8

1.6

2.0

1.8

2.2

2.0

2.6
2.8

2.6

3.0

2.8

3.2

3.2

...

3.4
3.6

3.8
4.0

4.2
4.4

4.6
4.8

5.0
5.2

5.4

Analysis of Firm Size Effect on R&D Activities in Japan 87

2.4

2.4

Textiles2.2

3.0

Figure 2-a: R&D Intensity Distribution

1.4

1.2

1.2

1.0

1.0

0.8

0.8

0.6

0.6

0.4

0.4

0.2

Iron and Steel

Figure 2-b: R&D Intensity Distribution

88 Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

0.3

0.9

0.6

1.5

1.2

2. 1

1.8

2.7

2.4

3.3

3.0

3.9

3.6

4.5

4.2

5. 1

4.8

5. 7

5.4

6.3

6.0

6.9

6.6

7.5

7.2

8. 1

7.8

Figure 2-c: R&D Intensity Distribution
General Machinery

0.2

0.6
0.4

\. 0
0.8

1.4
1.2

1.8
1.6

2.2
2.0

2.6
2.4

3.0
2.8

3.4
3.2

3.8
3.6

Figure 2-d: R&D Intensity Distribution
Transport Equipment

4.2
4.0

4.6
4.4

5.0
4.8

5.4
5.2

Analysis of Firm Size Effect on R&D Activities in Japan 89

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

8.5

9.0

9.5 10.5 11.5 12.5 13.5
10.0 11.0 12.0 13.0

Figure 2-e: R&D Intensity Distribution
Electrical Machinery

0.5

1.5
1.0

2.5
2.0

3.5
3.0

4.5
4.0

5.5
5.0

6.5
6.0

7.5
7.0

8.5
8.0

9.5
9.0

Figure 2-f: R&D Intensity Distribution
Precision Instruments

10.5

10.0

11.5

11.0

12.5

12.0

13.5

13.0

90 Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

4.

Regression Results and Implications

To examine the relationship between firm size and R&D activities, our model is specified asfollows,(1)

log # = #, + /?! logS

(2)

2

(3)

where R is R&D expenditure, and 5 is sales, a proxy for firm size. We leave out functional
forms representing the relationship between R&D intensity and firm size. Consider for instancethe following function,

R/S = f(S)(4)

As long as R&D intensity can be described as a ratio of R to S, Model (4) is just another formof Model (1). Hence, we examine (1) linear model, (2) logarithmic model, and (3) quadratic
function model to decide which form is the most suitable10.
The estimation results are shown in Table 2, and the number in the second column indicate
the model used. Table 2 reveals that, all the six industries are better characterized by Model(1) and (3) than by Model (2). Surprisingly, Model (1) contains only one independent variable

S and explains large part of the size-R&D relationship.

Considering R2 as the goodness offit, could we choose between models (1) and (3) ? The main reason why the different models
present nearly the same level of fit is that a few large size firms affect the functional form. Whendrawing size-R&D plots (not shown in this paper), we notice that relatively small firms in our
sample are on linear lines, while a small number of large firms are rather off the lines. Hence,
it is dangerous to conclude from our estimates that relationship between firm size and R&D
activities is generally quadratic.

Our results lead to the conclusion that:

1. firm size is still the determinant of R&D spending level in Japan,

2. firm size-R&D relationships can be described as either linear or quadratic functional form,
and

3. we may have missed what represent firm-specific and industry specific variables in thesemodels.

10 It is possible to deliberate the relationships between firm size expansion and R&D activity. This may reflect
the idea that size increase will require more technological knowledge to be used as an input for production.
Unfortunately, however, as far as our estimation period is concerned, firm's sales were generally declining andstatistically significant estimates could not be obtained from the size expansion model. It is interesting to findthat firms continue to spend money on R&D activity even when sales are declining. The R&D strategies of firms
is, however, a question which I would not deal with in this paper.

Analysis of Firm Size Effect on R&D Activities in Japan 91

Table 2: Estimation Results
Industry
Textiles

Model

(1)
(2)
(3)

Iron & Steel

(1)
(2)
(3)

General Machinery

(1)
(2)
(3)

Transport Equipment

(1)
(2)
(3)

Electric Machinery

(1)
(2)
(3)

Precision Instruments

(1)
(2)

(3)

Independent Variables
const.

S-1652.1.0422(-1.857)(13.168)

log S

S2
.870

-749907045.97(-6.232)(6.739).636-1906.5.0453-4.E-09(-1.671)(4.998)(-.366)343.563.0144(.221)(6.753).695-657726027.92(-5.837)(6.442).675-2671.2.0355-l.E-08(-2.361)(8.728)( • )*

667.785.0116(1.243)(4.471)-19196

1929.80(-4.472)(4.970)-830.06.0378-4.E-08(5.473)(• )-1608.7.0215(18.053)-929118325.28(6.706)-1137.0.0185

1.3E-09(4.519)

(• )

.0754

(23.217)33138.2(-8.867)(9.374).520-3829.9.0597(-1.313)

5.1E-09(4.746)( • )-7343.8.1095(15.657)

.872
.950

-207419

19252.5(-3.666)(3.958).546-76.924.0289

8.2E-08(-.048)(2.254)(6.516)

we cannnot calculate t value in terms of these coefficients.

.912

.869

-363866(-3.085)

.394

.584

(-1.081)-5640.4

.238

.911

(-6.242)(-2.201)

.882

.278

(-1.363)(-1.888)

.870

.989

92 Journal of Applied Input-Output Analysis, Vol.2, No.2, 1995

5.

Further Discussion

Although the relationship between firm size and R&D expenditure is generally significant, wehave to explain what causes intra-industry variation in RkD (why do the largest firm(s) spend
on R&D more than proportionately) and inter-industry variation (why do textile and generalmachinery industries fit worse than others) in the future. Scott (1984) estimates the model
which control both company and industry effects. It would be desirable to assume potentiallythat each company has its own R&D history and is conditioned by market and technologicalsituation of its industry. Some researchers mention technological opportunities and market con
ditions (appropriability), but few of them succeed in dealing with these two characteristics. The
term "technological opportunity" could be defined as closeness to science and/or industry maturity (Cohen, Levin, and Mowery (1987)). It is entirely conditioned on production but difficult
to seize objectively using observable indices. By investigating how much an industry is close

to science, we may break down technology which the industry adopts into technical elements11
and examine the degree with which its technology is based on scientific fields. Furthermore, wemust be careful in referring "industry maturity" as technological opportunity because maturity
would be caused not only by the technology state but also by the demand condition. It would

be better to exclude this demand side maturity12 from technological opportunity. On the other
hand, "appropriability" will be derived from competitive advantage in the market. Although it
might be natural that appropriability is one of the determinants of R&D activity level, we may

also need to consider the opposite causal relationship. Successful R&D performance, with newor improved technology, might lead to competitive advantage. The firm(s), owing to its (their)innovations, could enjoy profits from product differentiation at least as long as the lead time. If
it is difficult for other firms to imitate the new (improved) product or process easily (that is, thelead time is very long), the innovative firm(s) will soon obtain monopoly power with increasing
amount of sales. Therefore, it is necessary to limit ourselves to just one phase of appropriability:
technological appropriability. This is not the market condition but depending on the character

istics of R&D outcome and of the technical elements, for example, easiness to imitate or spill
over, or not widely adopted by other firms due to R&D accumulation required. As mentioned
above, it is difficult to define and capture both technological opportunity and appropriability

in positive analyses, but they are definitely important in deciding the technological situation of
the respective firm and industry. Without data well-defined in technological opportunity andappropriability, we have to establish a measurement framework which divides technology into
its components. When this new approach is developed, a large part of the interindustry variancein R&D activities would become clearer.

11 In this context, technical elements are considered to be corresponding to procedures such as chemical treat
ment and separation and mixing, usage of scientific techniques related to high polymer chemistry, mechanicalengineering, optical mechanism, electronics, communication engineering, and so on.

Discussion of technicalelements first appears in Nakajo (1992).
12This is equal to market maturity: demand for a product does not increase even when its price goes down.
This is also described as price elasticity.

Analysis of Firm Size Effect on R&D Activities in Japan 93

References[1] Acs, Z.J. and D.B. Audretsch (1988), "Innovation in Large and Small Firms: An Empirical Analysis," The American Economic Review, Vol.78, No.4, pp.678-690.

[2] Cohen, W.M. and S. Klepper (1992), "The Anatomy of Industry R&D Intensity Distribution," The
American Economic Review, Vol.82, No.4, pp.773-799.

[3] Cohen, W.M., R.C. Levin, and D.C. Mowery (1987), "Firm Size and R&D Intensity: A Reexamination," The Journal of Industrial Economics, Vol.35, No.4, pp.543-565.

[4] Dasgupta, P. and J. Stiglitz (1980), "Industrial Structure and the Nature of Innovative Activity,"
Economic Journal, Vol.90, pp.266-93.

[5] Doi, N. (1977), "Kenkyu Kaihatsu to Shijyokozo," Nihon Keizaiseisaku Gakkai Kansaibukai
Hokokuyosi.

[6] Kamien, M.I. and N. Schwartz (1976), "On the Degree of Rivarly for Maximum Innovative Activ
ity," Quarterly Journal of Economics, Vol.90, pp.245-60.

[7] Loury, G.C. (1979), "Market Structure and Innovation," Quarterly Journal of Economics, Vol.93,
pp.395-409.

[8] Mansfield, E, (1963), "Size of Firm, Market Structure, and Innovation," Journal of Political Econ
omy, Vol.71, pp.556-576.

[9] Mansfield,

E. (1964),"Industrial Research and Development Expenditures Determinants,

Prospects, and Relation to Size of Firm and Inventive Output," Journal of Political Economy,

Vol.72, pp.319-340.

[10] Nakajo, A. (1992), "Diversification of R&D Activities in Japan," Innovation & 1-0 Technique,Vol.3, No.4, pp.48-59.

[11] Nakajo, A. (1994), "Firm Size and R&D Activity," Information and Communication Study, Vol.15,
Kanagawa, Japan, Bunkyo University, pp.85-96.

[12] Nakanishi, K., S. Kishida, S. Mizuhara, H. Terada, T. Iguchi, K. Matsuoka, and T. Konoike (1983),
Kigyo Kodo no Tamenteki Bunseki, Japan, Koyo Shobo.

[13] Pakes, A. and M. Schankerman (1984), "An Exploration into the Determinants of Research Intensity," in Z. Griliches (eds.), R&D, Patents, and Productivity, Chicago, The University of Chicago
Press.

[14] Scherer, F.M. (1965), "Firm Size, Market Structure, Opportunity and the Output of Patented
Inventions," The American Economic Review, Vol.55, pp. 1097-1125.

[15] Scott, J.T. (1984), "Firm versus Industry Variability in R&D Intensity," in Z.Griliches (eds.), R&D,
Patents, and Productivity, Chicago, The University of Chicago Press.

[16] Uekusa, M. (1982), Sangyososhikiron, Tokyo, Japan, Chikuma Shobo.

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\bibitem{WL}Leontief, W.W.(1951), {\it The Structure of the American
Economy, 1919—1939: An Empirical Application of Equilibrium Analysis},
Oxford Univ.

Press.

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