Hitotsubashi University
Institute of Innovation Research

Allocation of Research Resources and Publication
Productivity in Japan:
A Growth Accounting Approach

Shuhei Aoki
Megumi Kimura

IIR Working Paper WP#13-24

Mar. 2014

Institute of Innovation Research
Hitotsubashi University
Tokyo, Japan
http://www.iir.hit-u.ac.jp

Allocation of Research Resources and Publication Productivity inJapan: A Growth Accounting Approach∗
Shuhei Aoki†
Faculty of Economics, Hitotsubashi University
Megumi Kimura‡Institute of Innovation Research, Hitotsubashi University
March 10, 2014

Abstract
In Japan, as in many developed countries, the government’s agencies for science have implemented
several reforms to the scientific research system, which has concentrated research resources in the top
research universities. However, the growth of research papers has stagnated in Japan during the
2000s. To analyze the reason for this, this paper develops a framework that decomposes the changes
in research output. The framework is based on a model of universities and is an application of
growth accounting that is widely used in economics. Using the framework, we find that the change
in the allocation of research funds between universities had only a small eﬀect on research output.
The stagnation in research output during the 2000s was mainly accounted for by the decrease inresearch time. We also conduct a counterfactual experiment to examine how the research output
would increase if the misallocation of research resources were completely removed.
JEL Codes: C43, D24, D61
Keywords: growth accounting; publication productivity; research time; allocation of research funds∗ We thank Hiroyuki Tomizawa, Ayaka Saka, and Masatsura Igami of NISTEP for kindly providing valuable data andhelpful discussions. We also thank Masashi Shirabe, Kotaro Yamano, Kenta Ikeuchi, Yuya Hoshino, and Shinichi Akaikefor helpful comments and suggestions. This research was supported by RISTEX, JST.
† Address: 2-1 Naka, Kunitachi, Tokyo 186-8601, Japan. Phone: +81 (42) 580-8477. Fax: +81 (42) 580-8195. Email:shuhei.aoki@gmail.com.
‡ Address: 2-1 Naka, Kunitachi, Tokyo 186-8603, Japan. Phone: +81 (42) 580-8414. Fax: +81 (42) 580-8410. E-mail:kimura@iir.hit-u.ac.jp.

11Introduction

In Japan, as in many developed countries, the government’s agencies for science have implemented several
reforms to make the scientific research system more “performance-based.” One motive of these reforms
is to provide the bulk of research funds and grants to the top research universities. Such reforms brought
about two big changes in the systems of the country’s universities, especially the national ones. The firstchange, in the 1990s, was an increase in competitive research funds, which aim to be supplied to top
researchers and universities. The second was an institutional change in the national universities in 2004,
whereby these universities became independent of the government, and subsidies, which were allocatedequally for them, have decreased.
However, the outcome of these policy changes has not necessarily been satisfactory. The left panelin Figure 1 plots the cross-country trend of the number of research papers listed in Web of Science byThomson Reuters (data in Figure 1 are taken from Saka and Kuwahara, 2013). It shows that the numberof research papers in Japan has stagnated in the 2000s, compared with that in other countries or in theprevious period. To take the quality of research papers into account, the right panel in Figure 1 plots thenumber of “top 10% research papers,” that is, the top 10% most cited research papers in each research
field in each year.1 This panel also shows stagnation in the publication of research papers in Japan in
the 2000s.

Insert Figure 1 here.

Probably, motivated in part by the outcome, some scientists have expressed their opposition to thesereforms. For example, Kobayashi (2013), a well-known physicist who won the Nobel Prize in 2008, told
Nikkei newspaper, “Too much competition is problematic.” “It is diﬃcult to forecast which research
will be successful in advance.” “Diversity of research projects must be maintained.” Toyoda (2012), a
biologist and a member of the government’s council for Science and Technology policy, wrote in his blog,“Several policies around the period of the institutional change in the national universities, for example,
the decrease in the subsidies, an increasing burden on the university management ... and the gap inresearch funds between the top and the second tier universities must have contributed to stagnation in
the number of research papers.”
1 For details on the definition of “top 10% research papers,” see Saka and Kuwahara (2012 and 2013).

2

The purpose of this paper is to evaluate the outcome of this reforms policy. We analyze the reason
behind the stagnation in research output in Japan and the extent to which the concentration of researchfunds in top universities aﬀects this outcome. For the purpose, we construct a framework that decomposes
the causes of the stagnation. The framework is based on a model of research activities in universities andis an application of growth accounting in economics literature (see for example, Basu and Fernald, 2002).
Using the framework, we decompose the change in research output of the national universities inJapan during the late 2000s.2 We find that while the change in the allocation of research funds among
these universities had a positive eﬀect on research output, the magnitude is quantitatively small. We
further conduct a counterfacual experiment to examine how the research output of the country would
increase if the resource misallocation is completely removed. We find that the eﬀect is also quantitatively
small.
Our decomposition reveals that despite the increase in research funds for the national universities,
measured research productivity has decreased in each university, which results in the stagnation in thegrowth of research papers. A cause of the decrease in measured research productivity is the decline inresearch time. Possibly due to several reforms since the late 1990s, faculty members in universities haveallocated more time to social service activities and less time to research activities. We show that thedecrease in research time accounts for most of the decrease in measured research productivity.
Several papers estimate production functions of research output measured by the number of research
papers (Averch, 1987 and Jacob and Lefgren, 2011 at the project-level, Adams and Griliches, 1998, Abigail
and Siow, 2003, and Yonetani et al., 2007 at the university-level, Crespi and Geuna, 2006 at the research
field-level, and Crespi and Geuna, 2008 at the cross-country-level). Diﬀerences between these papers andours are attributable to those in economics between the regression analysis on production function andgrowth accounting. While the former estimates parameters using regressions, the latter calibrates thembased on the employed model. A characteristic of the latter approach is that the calibrated parameters
are unbiased as long as the model and assumptions are correct. It is well known that when regressing
the production function the endogeneity bias problem arises, because the independent variables, which
consist of the inputs of the production function correlate with the error term, which includes productivity
shocks. For example, if the future prospect of a research project is favorable, it is likely that the project2 We focus our analysis on national universities, because most of the research papers in Japan originate in national
universities. For details, see Section 4.1.

3

can collect the research resources more easily. Then, the endogeneity bias problem occurs. Our approach
can avoid the bias.
Some papers analyze the eﬃciency of the allocation of research resources between universities or
research projects. Using a structural model, Arora et al. (1998) analyze the extent to which the research
output would increase if marginal productivies were equalized between research projects. As in theirpaper, ours is model based, while ours is more analytically tractable, which enable us to derive analyticalexpression of the decomposition of research output growth. Adams and Clemmons (2009) decomposes
the labor productivity growth of research output and measure the extent to which reallocation of researchresources between universities contributed the increase or decrease of the productivity growth. Comparedwith theirs, ours is model-based and decomposes the research output growth, which makes easier toanalyze the cause of the stagnation in research output. Hayashi and Tomizawa (2007) analyzes the
allocation of funds between universities in Japan. Their scientometrics research shows a scatter plot
between research funds and research output over universities. Our paper provides a microfoundation to
use the scatter plot and quantify the eﬀect of resource misallocation on research output.
Finally, our study is also closely related with Kanda and Kuwahara (2011), who analyze the declining
research time of faculty members in Japan. They find from the micro-level data on researchers’ time
use that the average research time of a faculty member at a national university has decreased by 20%
from 2002 to 2008. Instead, faculty members have spent more time on education, as well as social
service activities such as attending the government’s councils, transferring technologies to industry, andcommercializing research outcomes. Our study uses a growth accounting approach to quantify the impactof the decline in research time.
The remainder of the paper is structured as follows. Section 2 sets up a model of universities. Using
the model, in Section 3, we derive a decomposition formula that decomposes the change in research
output into several factors such as the productivity eﬀect and allocation eﬀect. Using the decomposition
formula, in Section 4, we analyze the publication of research papers at national universities in Japan
during the late 2000s. Finally, we present our concluding remarks in Section 5.

4

2

Model

2.1

Decision problem of a university

Let us consider a model of the government and universities. The government allocates funds (money) touniversities. Given the funds Ii allocated to the university, each university (denoted by i) maximizes theresearch output measured by the number of research papers (or the number of top 10% most cited research
papers), yi . For the purpose, the university buys equipment and goods mi to be used for research andemploys faculty members ℓi . Therefore, the university’s maximization problem can be stated as follows:

max yi =ai fi (mi , ℓi ),mi ,ℓisubject to the budget constraint of the university,

pmi + wi ℓi ≤ Ii .

(1)

Here, we assume that the university chooses mi and ℓi under the condition that the price p of equipment
and goods and labor cost wi are exogenously given (we allow the labor cost wi to vary across universities).
ai is the productivity of the university that can be interpreted as the quality of the institution or its faculty
members’ abilities, or both. Note that the maximization is a static problem under a single-year budget
constraint. Although the decision problem of a university might be dynamic in the real world, as abenchmark, we adopt the static setting.
We assume that the production function of a university is a homogeneous function, i.e.,fi (nmi , nℓi ) = nγ fi (mi , ℓi ).

(2)

We assume the diseconomies of scale, i.e., γ < 1. The assumption is necessary to guarantee that theco-existence of several universities is not ineﬃcient. Otherwise, it becomes eﬃcient for the government
to allocate all of the funds to a university whose productivity is the highest.

5

The first order conditions (FOCs) of the problem areai fim =pλi , ai fiℓ = wi λi , λi =

dyi
,
dIi

(3)

where fim ≡ ∂fi (mi , ℓi )/∂m and fiℓ ≡ ∂fi (mi , ℓi )/∂ℓi . λi is the Lagrange multiplier of the maximization
problem and can be interpreted as the marginal return of research from funds, which measures the increase
in research output when the budget of the university increases by an additional unit. Applying Euler’s
theorem to (2) and substituting the budget constraint (1) and FOCs (3), we obtain

γyi =ai fim mi + ai fiℓ ℓi = λi Ii .

(4)

The equation shows that under (2), the marginal return of research, λi = dyi /dIi , is proportional to theaverage return of research, yi /Ii , which measures the research output per unit of funds.

2.2

Resource misallocation

The funds allocated to a university, Ii can be linked with the sum of these funds, I ≡∑i Ii as follows(for the derivation, see Appendix A.1):

Ii =

yi 1
I,
y λ̃i

Note that y is the sum of the research output, that is, y ≡(5)∑i yi , and λ̃i satisfies

11= ∑ λyij 1 .
λ̃i
j y λj(6)

Because λi can be interpreted as the return of research from funds at university i, λ̃i can be interpreted
as the relative return of research at university i.
The relative return λ̃i is a measure of distortion. Suppose the resource allocation that maximizes theresearch output of the country is

max y =∑

yi , subject to pmi + wi ℓi ≤ Ii for all i, and

i

∑
i

6

Ii = I.

Under the eﬃcient allocation, which maximizes the research output of the country, the return of researchis equalized across universities, λi = λj , and thus the relative return of research λ̃i is equal to unity for
all universities.
To consider the intuition of the result, suppose that the return of research is diﬀerent across universities, e.g., λi < λj . Then, by transferring one unit of funds at university i to university j, the research
output of the country increases without increasing the resources, which contradicts the eﬃciency of
allocation.

3

Decomposition of Research Output

Using the model introduced in the previous section, this section provides a framework to decompose thecauses of the change in research output in Japan. We first explain how the research output of a university
is decomposed. Then, we explain how the research output of the country is decomposed. Combining
these results, we derive the key equation of decomposition used for measurement.
The research output of a university can be decomposed as follows:d ln yid ln yid ln mi +d ln ℓid ln mid ln ℓipmi
wi ℓi=d ln ai + λid ln mi + λid ln ℓi
yi
yi
(
)
yi
=d ln ai + γ d ln − d ln λ̃i + d ln I
y
(
)
pmi
wi ℓi
−γ
d ln p +d ln wi .
Ii
Iid ln yi =d ln ai +

(7)

(8)

To derive the result, we use the FOCs (3), Euler’s theorem (4), and the following equation obtained bytotally diﬀerentiating the budget constraint (1):d ln Ii =pmi
wℓi(d ln p + d ln mi ) +(d ln wi + d ln ℓi )
Ii
Ii

7

On the other hand, the research output of the country can be decomposed as follows:d ln y ≈∑ d ln (∑ exp {ln yi })id ln yi

i

=

∑ yi
i

y

d ln yid ln yi .

(9)Combining (8) and (9), we finally obtaind ln y ≈

∑ yi
i

−γ

y
(

d ln ai + γd ln I − γ∑ yi pi mi
i

y

i

)

Ii

∑ yi

d ln p − γyd ln λ̃i∑ yi wi ℓiiy Ii

d ln wi .

(10) is the key equation of the paper. Note that to derive (10), we use the property that(10)∑i (yi /y)d ln(yi /y)becomes approximately zero (see Appendix A.2).
(10) decomposes the growth rate of the research output in a country into several factors in the righthand side (RHS) of the equation. The first term of the RHS is the weighted average of the productivity
growth rate and the second term is the growth rate of total funds invested in the country. The higher
these terms, the higher is the growth rate of research output. The third term of the RHS includes λ̃i andmeasures the eﬀect of resource misallocation between universities. The fourth and fifth terms measure
the price and wage change eﬀects, respectively. The fourth and fifth terms exist because total funds I
in the second term are measured in nominal terms. That is, when there is inflation and the price levelof goods increases, the equipment and goods a university can purchase decreases if its nominal budget
remains unchanged. Similarly, if labor cost increases, the number of faculty members a university canemploy decreases. The fourth and fifth terms capture these eﬀects.
All the variables in (10) except for the economies of scale parameter γ can be measured from data.
• Measurement of d ln ai : Substituting (4) into (7), we measure d ln ai by using the following equation:d ln ai =d ln yi − γ

pmi
wi ℓi
d ln mi − γ
d ln ℓi .
Ii
Ii• Measurement of λ̃it : λ̃it in each year is measured from (5).

8

(11)

• Measurement of d ln p and d ln wi : For the former, we use the growth rate of the GDP deflator. For
the latter, we use the wage rate for researchers.
• Variables such as yi /y: In case of yi /y, we use the average of yit−1 /yt−1 and yit /yt .
• The economies of scale parameter γ: γ is not directly measured. Instead of measuring it, we set
γ = 0.85 that is a commonly used value for the extent of decreasing returns in a firm’s establishmentlevel analysis (see Restuccia and Rogerson, 2008).

4

Measurement

4.1

Data

We focus on national universities in our analysis. One reason for doing so is data availability. The otherreason is that most of the research papers in Japan originate in national universities. Figure 2 compares
research papers at the national level and at national universities. As the figure shows, about 70–90% of
the research papers in Japan originate in national universities.

Insert Figure 2 here.

Our sample comprises 63 Japanese national universities that have a science or technology department.
Thus, for example, Hitotsubashi University, a national university specializing in social sciences, is notincluded, because it does not have a science or technology department. We also exclude Sokendai, anothernational university, because many of its faculty members also belong to other universities such as the
University of Tokyo.
We use data from 2005 and 2009, that is, t − 1 = 2005 and t = 2009.3 For research output (yi in themodel), we use data provided by Saka and Kuwahara (2012), who construct data from Web of Scienceby Thomson Reuters. We use both the number of research papers and top 10% research papers in themeasurement. For the number of faculty members ℓi , funds and grants Ii , and labor costs wi ℓi , we use
3 More precisely, there is a diﬀerence in time intervals between research output data and other data. The research output
data count research papers published in 2002–2006 and in 2007–2011, whereas other data are measured at 2005 and 2009.
We only adjust the growth rate of research output by multiplying it by 4/5. This is because there is a five-year interval for
research output data (between the periods 2002–2006 and 2007–2011), whereas there is a four-year interval for other data
(between 2002 and 2006).

9

data provided by Ishibashi and Tomizawa (2006) and Ishibashi (2011). For the data on price p, we use
the GDP deflator.

4.2

Relationship between funds and research output

The model presented in Section 2 predicts that if the resource allocation of funds between universities is
eﬃcient, the research output–funds ratio that measures the return of research from funds is also equal
between universities. To observe this property in the data, Figure 3 plots the funds and research outputof the Japanese national universities (the left panel uses the number of research papers and the rightpanel uses the number of top 10% research papers for research output).4 If the allocation were eﬃcient,
the scatter plot would be in the straight line crossing the origin. For both t = 2005 and t = 2009, somedispersion from the straight line is observed. To quantify how big the dispersion is and how it changes
over time, in the next sections, we measure (10) to determine the eﬀect of misallocation on research
output in Japan.

Insert Figure 3 here.

4.3

Decomposition

Table 1 shows the results of the decomposition using (10). The upper table shows the results when
research output yi is measured by the number of research papers and the lower table shows the results
when output is measured by the number of top 10% research papers. Each column calculates each termin (10). For example, d ln yi measures the left-hand side (LHS) of (10), the growth rate of paper output;
and d ln ai measures the first term of the RHS of (10), the weighted average productivity growth rate.
We can confirm that in the tables, the d ln yi term is equal to the sum of the remaining terms.
Table 1 shows that the increase in funds, d ln I, has a large positive impact on research production.
This reflects the fact that in the 2000s, the volume of competitive research funds has substantially
increased. However, the growth rate of research output, d ln yi , falls short of the fund growth. The
decrease in growth of average productivity explains the discrepancy. The price eﬀect is positive becauseof deflation during the period. The wage eﬀect is negative because wage increased during this period.
4 Hayashi and Tomizawa (2007) plot the same kind of scatter plots.

10

The allocation eﬀect, d ln λ̃i , is positive. This is because more funds were allocated to top universities
such as the University of Tokyo, where the return of research from funds, yi /Ii is higher. On the other
hand, the magnitude of this eﬀect is small, as compared to the productivity and fund eﬀects.
For each term, a large part of the contribution comes from top universities. For example, in the
productivity eﬀect, the contribution of the University of Tokyo is about −2% when yi is measured by the
number of research papers and is about −1% when yi is measured by the number of top 10% research
papers. This is because the size distribution of universities, whose size is measured by, for example,
research output, follows a Power law. That is, the distribution has a very unequal fat-tail distribution.
As a result, the size of and eﬀect in top universities such as the University of Tokyo becomes far larger
than those of other universities.

Insert Table 1 here.

4.4

Magnitude of resource misallocation

In the previous section, we measured the impact of a change in resource allocation on the growth rateof research output. This section analyzes the magnitude of the misallocation. Specifically, we measure
how yt would increase if misallocation suddenly and counterfactually disappeared in 2009, that is, λ̃i = 1,
for all universities. We assume that the productivities ai , the volume of funds I, the price level p, andwage rates wi are not changed by the sudden disappearance of misallocation. We further assume thatthe research output share yi /y is also unchanged by the disappearance of misallocation. Then, from (10),the increase in research output by the sudden disappearance of misallocation can be calculated byd ln y = γ∑ yi,2009iy2009ln λ̃i,2009 ,(12)

where yi,2009 and λ̃i,2009 are the research output and distortions, respectively, observed in 2009.
Table 2 calculates (12). The research output increases by 2.3% when yt is measured by number of
research papers and by 8.5% when yt counts the number of top 10% research papers. These values are
small, as compared to the productivity or fund eﬀects in Table 1, taking into account the property that11

the removal of the misallocation is a one-shot eﬀect, whereas the other factors, especially funds, can becontinuously increased.
Our assumption that the research output share yi /y is not changed by the disappearance of misallocation is somewhat restrictive. This is because if universities are substitutes or complements to one
another, the output share of a university changes after the disappearance of misallocation. However, also
note that our result in Table 2 holds even if we allow the research output share yi /y to change after thedisappearance of misallocation, if the size of a university yi /y is uncorrelated with the (log of) distortions
at the university, ln λ̃i,2009 (for the proof, see Appendix A.3).

Insert Table 2 here.

4.5

A cause of productivity decline: Shrinking research time

What is the reason for the decline in measured productivity? Some researchers suggest the decrease inresearch time as a possible cause. Kanda and Kuwahara (2011) report that the annual average researchtime of a faculty member at a national university has decreased by 20%, from 1,526 hours in 2002 to
1,234 hours in 2008. They find that faculty members have spent more time on education and social
service activities, such as attending the government’s councils, transferring technologies to industry, andcommercializing research outcomes, than on research. Our decomposition framework (10) is flexible
enough to deal with the reduction of research time. This section formulates and measures the eﬀect of
decreasing research time on research output.
When we incorporate research time into the model in Section 2, only the production function ismodified as follows:yi = ai fi (mi , hℓi ),where h is the hours a faculty member spends on research. For simplicity, we assume that h is equal acrossfaculty members in diﬀerent universities. Under the setting, the equation describing the productivity

12growth of a university (11) is rewritten as

d ln ai + γ

wi ℓi
pmi
wi ℓi
d ln h =d ln yi − γ
d ln mi − γ
d ln ℓi .
Ii
Ii
Ii

Then, the productivity eﬀect in the benchmark decomposition (10) is rewritten as
∑ yi
i

y

(
d ln ai + γ∑ yi wi ℓi
i

y Ii

)
d ln h.

The equation shows that the productivity eﬀect in the benchmark decomposition is further divided intothe (modified) productivity eﬀect and the research time eﬀect.
Table 3 reports the results that take into account the decrease in research time. The decrease inresearch time accounts for most of the decrease in the productivity in Table 1. Thus, our result confirms
the view suggested by Kanda and Kuwahara (2011) that the decline in research time, possibly induced byseveral kinds of reforms since the late 1990s, has a substantially negative impact on research activities,
especially the publication of research papers.

Insert Table 3 here.

5

Conclusion

In this paper, we analyzed the reasons for the stagnation in research output in Japan during the 2000s.
We developed a model of universities, and by using this model, we devised a framework to decompose
the change in research output at that time. We applied the framework to the data on research output
from the national universities in Japan during the late 2000s. We found that the main reason for thestagnation was the decrease in measured research productivities in each university. The eﬀect of themisallocation of research funds among universities was small. We also found that the decrease in researchtime of faculty members accounts for the decline in the measured research productivity.
We have to note the limitations of our results. First, we do not take into account “postdocs” andgraduate students. Most of them engage in research at top universities, but are low-paid or pay tuition
fees by themselves. Their existence should contribute to higer measured productivities and returns of13

research by funding at top universities. Second, we do not consider the recruiting eﬀect. Top universities
sometimes recruit researchers at second-tier universities before their important results are published. For
example, Professor Yamanaka, famous for his “iPS cell”research, moved to Kyoto University from Nara
Institute of Science and Technology (NAIST) in 2004. Even if his most cited papers were written at
Kyoto, the research begun at NAIST. If the research funds allocated selectively, because the measured
returns are high, the resource for research might not be given to “future Yamanaka.” The recruiting
eﬀect should also contribute to higer measured productivities and returns of research by funding at top
universities. These are left for future research.

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A

Derivations

A.1

Derivation in Section 2.2

Ii can be rewritten as follows:yi λi Ii 1
yi
1
1
yi
y yi λiy γ λi
λi
∑
∑
I
=
I
=
I.
yj
1
yj λj Ij 1y j yyj λ1j
j y γ λjj y yj λj

λi Ii

Ii = ∑ λλi j Ij I = ∑j

λj

By redefining variables, we obtain (5).

A.2

Derivation in Section 3

Here, we show that∑i (yi /y)d ln(yi /y) becomes approximately zero. Define xi ≡ yi /y. Then,∑i xi = 1

and
∑ yi
i

A.3

y

(
d ln

yi
y

)
=

∑

xi d ln xi ≈

i

∑
i

xi

dxi
= 1 − 1 = 0.
xi

Derivation in Section 4.4

The proposition can be shown as follows. First, if yi /y and ln λ̃i,2009 are uncorrelated,∑i (yi /y − yi /y) ·(ln λ̃i,2009 − ln λ̃i,2009 ) = 0 (variables with upper bars are the average of original variables). By rewriting
the equation, we obtain
∑ yi
i

y

∑
ln λ̃i,2009 =yi
ln λ̃i,2009 = ln λ̃i,2009 .
y

Then,

d ln y = γ

∑ yi
i

y

ln λ̃i,2009 = γln λ̃i,2009 .

16

(13)

Second, the RHS of (12), ignoring γ, can be interpreted as the weighted average of ln λ̃i,2009 .
Because yi /y and ln λ̃i,2009 are uncorrelated, the (normal) average of ln λ̃i,2009 is equal to the weighted
average of ln λ̃i,2009 . Therefore, (13) becomes equal to (12).

17d ln y2.0%

yi : Number of research papers
d ln aid ln I d ln λ̃i d ln p
−14.5% 16.0% 1.1% 1.3%

d ln wi−1.9%

yi : Number of top 10% research papers
d ln yd ln aid ln I d ln λ̃i d ln p d ln wi
11.6% −5.6% 16.0% 2.4% 1.3% −2.5%
Table 1: Decomposition of research output growth
Data source: Saka and Kuwahara (2012), Ishibashi and Tomizawa (2006), and Ishibashi (2011).
Notes: The tables show the decomposition of research output in Japan using (10). The upper table shows
the results when the number of research papers is used for research output yi , whereas the lower tableshows the results when the number of top 10% research papers is used.

yi : number of research papers
2.3%

yi : number of top 10% research papers
8.5%

Table 2: Eﬀects of the disappearance of misallocation on research output
Data source: Saka and Kuwahara (2012), Ishibashi and Tomizawa (2006), and Ishibashi (2011).
Notes: This table calculates how research output would increase if all of the misallocation disappeared.
The left column calculates the value for the case where research output is measured by the number of
research papers. The right column calculates the value for the case where research output is measured
by the number of top 10% research papers.

yi : Number of research papers
d ln ai in Table 1 modified d ln ai
d ln h
−14.5%−4.7%−9.8%
yi : Number of top 10% research papers
d ln ai in Table 1 modified d ln ai
d ln h
−5.6%
3.9%
−9.4%
Table 3: Eﬀects of decreasing research time
Data source: Saka and Kuwahara (2012), Ishibashi and Tomizawa (2006), Ishibashi (2011), and Kanda
and Kuwahara (2011).
Notes: The tables refine the decomposition in Table 1 to take into account the contribution of the researchtime of faculty members. Then, d ln ai in Table 1 is divided into the (modified) d ln ai term and the d ln hterm, the latter capturing the eﬀect of the change in research time on research output. For the growthrate of research time d ln h, we use the average growth rate of research time of a faculty member at anational university from 2002 to 2008. The upper table shows the results when the number of research
papers is used for research output yi , whereas the lower table shows the results when the number of top
10% research papers is used.

18

180,000

350,000

16,000160,000

300,000

14,000140,000
100,000

200,000

80,000150,000

60,000

6,000

1980
Japan

1985

1990

1995

U.K.

Germany

2000

France

2005

2010

China

Korea

20,0004,000

10,000

2,000

0

0

0

0

30,0008,000

50,00020,00040,00010,000100,000

40,00050,00012,000250,000

120,000

60,000

U.S.

1980

1985

1990

Japan

U.K.

Germany(a) Number of research papers

1995

2000

France

2005

2010

China

Korea

U.S.

(b) Number of top 10% research papers

Figure 1: Cross-country trends of the number of research papers
Data source: Saka and Kuwahara (2013). Original data are taken from Web of Science by Thomson
Reuters.
Notes: The left panel plots the number of research papers by country, whereas the right panel plots thenumber of the top 10% most cited research papers by country. For the U.S. in both panels, see thesecondary axis.

120,000	  	
  100,000	
  	
  80,000	
  	
  

72%	
  

76%	
  
77,588	
  	
  71,728	  	
  60,000	
  	
  

79%	
  
76,607	
  	
  59,316	
  	
  51,636	
  	
  60,817	
  	
  40,000	
  	
  

100%	
  

8,000	
  	
  

90%	
  

7,000	
  	
  

80%	
  

6,000	
  	
  

70%	
  

1997-­‐2001	
  Japan	  2002-­‐2006	
  Na4onal	
  Univs	
  5,975	  	
  5,633	
  	
  

100%	
  
90%	
  
80%	
  
70%	
  

5,238	  	
  5,000	
  	
  

50%	
  

4,000	
  	
  

50%	
  

40%	
  

3,000	
  	
  

40%	
  

4,617	
  	
  

60%	
  

30%	
  

2,000	
  	
  

20%	
  

0	
  	
  

6,594	  	
  6,059	
  	
  

60%	
  

30%	
  

20,000	
  	
  

92%	
  

88%	
  

82%	
  

10%	
  

1,000	
  	
  

0%	
  

0	
  	
  

2007-­‐2011	
  

20%	
  
10%	
  
0%	
  
1997-­‐2001	
  Share	  of	
  Na4onal	
  Univs	
  Japan	  (a) Number of research papers

2002-­‐2006	
  Na4onal	
  Univs	  2007-­‐2011	
  Share	  of	
  Na4onal	
  Univs	  (b) Number of top 10% research papers

Figure 2: Publication of research papers in Japan at the national level and at national universities
Data source: Saka and Kuwahara (2012 and 2013). Original data are taken from Web of Science byThomson Reuters.
Notes: The bar graphs in the left panel compare the number of research papers in Japan at the national
level with that of national universities for the periods 1997–2001 to 2007–2011. The line graph in theleft panel shows the national universities’ share of research papers in Japan. The right panel plots thesegraphs for the number of the top 10% most cited research papers.

19

2005	
  

0.30	
  	
  

2009	
  

2.5	
  	
  

#(top	
  10%	
  publica5ons)	
  /#(faculty	
  members)	
  #(publica2ons)/#(faculty	
  members)	
  

3.0	
  	
  

2.0	
  	
  
1.5	
  	
  
1.0	
  	
  
0.5	
  	
  
0.0	
  	
  

2005	
  

2009	
  

0.25	
  	
  
0.20	
  	
  
0.15	
  	
  
0.10	
  	
  
0.05	
  	
  
0.00	
  	
  

0	
  	
  

500	
  	
   1000	
  	
   1500	
  	
   2000	
  	
   2500	
  	
   3000	
  	
   3500	
  	
   4000	  	
  #(funds)/#(faculty	
  members)	
  

0	
  	
  

(a) Number of research papers

500	
  	
   1000	
  	
   1500	
  	
   2000	
  	
   2500	
  	
   3000	
  	
   3500	
  	
   4000	  	
  #(funds)/#(faculty	
  members)	
  (b) Number of top 10% research papers

Figure 3: Funds–research output relationship
Data source: Saka and Kuwahara (2012), Ishibashi and Tomizawa (2006) and Ishibashi (2011).
Note: The figures show the scatter plots between funds and the number of research papers or the numberof top 10% research papers (both per faculty member).

20