Development Bank of Japan
Research Report
No. 23

Microstructure of persistent ROA decline in theJapanese corporate sector:
Inter-company disparities and investment strategies

March 2002

Economic and Industrial Research Department
Development Bank of Japan

Contents
Summary ............................................................................................................................. iii
Introduction .......................................................................................................................... 1
I.

Persistent ROA Decline of the Japanese Corporate Sector...........................................3
1. Theoretical Background and Measurement Issues.................................................................. 3
2. Evidence from Aggregated Data ............................................................................................... 5
3. Overview of Trends by Industry................................................................................................ 7

II. Microstructure of ROA Decline .................................................................................. 12
1. Significance of Analysis Using Individual Company Data...................................................12
2. ROA Distribution of Individual Companies and Its Changes– Descriptive Statistical Observations – .................................................................................13
3. Structure of ROA Decline from the Perspective of Inter-Company Disparities andResource Reallocation ...............................................................................................................19
III. The Nature and Background of Inter-Company ROA Disparities ............................ 24
1. Persistence of ROA Disparities ...............................................................................................24
2. ROA Disparities and Investment Strategies...........................................................................27
Concluding Remarks -In pursuit of improvement in Japanese corporate ROA- .............. 35
Appendix ............................................................................................................................ 37
References........................................................................................................................... 39

Development Bank of Japan Research Report/ No. 23iMicrostructure of persistent ROA decline in the Japanese
corporate sector:
Inter-company disparities and investment strategies

Summary
1. The stagnation in ROA (return on assets) and other asset profitability ratios of Japanesecompanies has been called into question reflecting the intensification of global competition
and the harsh evaluation of the market in recent years. Their improvement has become
perceived not only as an issue of management targets of individual companies but also as an
issue in the revitalization of the macro-economy.
In this report, we investigate the background of aggregated (overall corporate sector)
ROA decline over a long time period based on listed company data from the micro
perspective. We furthermore focus on the inter-company disparities thought to be the key toaggregated ROA improvement and empirically analyze their characteristics and relationships
to capital investment strategies.
2. There has been a persistent trend of decline in the aggregated ROA of Japanese companies
since the 1980s in both manufacturing and non-manufacturing industries.
The transitions in ROA in Japanese, U.S. and German companies since the 1980s
indicate that, aside from cyclical movements, the U.S. and Germany, unlike Japan, havegenerally maintained a certain level.
3. Based on corporate statistics, decade-long transitions in ROA by industry show that ROA
declined in virtually all industries in both the 1980s and 1990s regardless of whether
manufacturing or non-manufacturing, growth industry or not, regulated industry or not.
Changes in ROA of all industries are decomposed into the contribution of ROAchanges within individual industries (“within” effect) and the contribution of resource
reallocation based on changes in the total assets weight between companies (“between” effect)．
It becomes clear that the “between” effect, in which a positive contribution would normallybe anticipated, was small with the inclusion of some negative years and was essentially zero on
average while the “within” effect was negative on average in both manufacturing and nonmanufacturing industries.
4. The frequency distribution of ROA every five years of some 1,400 companies (common
firms) listed continuously since the 1980s indicates that the distribution location shifted
consistently to the left (low ROA), and that for the distribution configuration the breadth of
the right-hand tail (high ROA) has been lost.
Based on individual company data, unlike the situation of industry data near totalcollapse, 14% of the common firms experienced an increase in ROA even in the stagnant

Development Bank of Japan Research Report/ No. 23

iii

1990s. However, that rate represents a broad decline compared to the 30% of the 1980s, anddynamism to create opportunities for profit has weakened. In addition, when comparing thetransitions in ROA of all the listed companies, including those newly listed since the 1980s
and those that delisted from the stock market, with the common firms base, it is possible tosee an ROA boosting effect through new entries and exits, limited though it has been in scale.
5. There was a tendency toward an expansion in inter-company ROA disparities throughout the
1990s. Inter-company disparities are decomposed into disparities due to industry
characteristics (variability between industries, namely, inter-industry variability) and disparities
between companies within individual industries (variability within the same industry, namely,
intra-industry variability). It becomes evident that variability within the same industry explainsvirtually everything, and expanded during the 1990s in most industries; however, there wasalso a considerable tendency toward a decline in ROA of the industry overall as the disparities
expanded, suggesting that this was a disparity expansion in the direction of a decline in ROA(loss of profit opportunities).
Changes in ROA of listed companies (common firms) overall are decomposed into thecontribution of ROA changes of individual companies (“within” effect) and the contributionof resource reallocation due to changes in total assets weight between companies (“between”
effect). The “within” effect, which accounted for the majority, was negative on average while
the year-by-year contribution of the “between” effect was small, though a consistent positive
tone was evident unlike the breakdown by industry. By company level, the shift of the total
assets weight (resource reallocation) to companies with high ROA supported the ROA of themacro-economy, though not greatly.
6. The differences between the ROA of individual companies and the industry average aredefined as excess profit rate. A certain degree of persistence is observed in time-seriestransitions of the excess profit rate, i.e., inter-company disparities in ROA.
Such persistence strongly suggests that inter-company disparities in ROA are mainly due
to firm-specific factors such as capital investment strategies. To examine this point, we extract
the characteristics of investment strategies by the principal components analysis from theresults of the Corporate Investment Attitude Survey released by the Development Bank ofJapan in October 1999. The relationship to the excess profit rate is empirically investigatedusing the extracted data and the following can be pointed out. First of all, the characteristics
that have had a crucial impact on ROA disparities are significantly related to the order ofpriority between qualitative and quantitative factors when making investment decisions.
“Discretionary investment behavior” such as taking into account inter-divisionary balance,
strategies of other companies and other qualitative factors, has had a negative impact on theexcess profit rate, while “non-discretionary investment behavior” such as placing the priority
solely on quantitative assessments of investment profitability, has had a positive impact. In
this respect, so-called Japanese-style management that is closely related to “discretionary
investment behavior” has not been effective at least since the 1980s. Secondly, no significant
relationship was observed between excess profit rate and characteristics such as risk
preference (low-risk or high-return) or attitude toward sales or market share. In this sense,
there have not been any particular problems with “Japanese-style” investment decisions (lowrisk orientation and sales or market share orientation).
7. The expansion of the disparities between companies in the direction of increasing the ROA(creation of profit opportunities) can be seen as the key to realizing an enhancement ofiv

Development Bank of Japan Research Report/No.23

aggregated ROA. The disparities in ROA between companies are largely attributable todisparities between companies within the same industry rather than disparities based on
industry characteristics, that is, investment strategies and other individual company factors.
Implementing quantitative assessments consistently in investment decisions is an especiallycrucial issue in ROA improvement.
It has become evident recently that the penetration of investment decisions based on
quantitative assessments and a move toward restructuring operations and assets are alsosteadily accelerating in Japanese companies. It is anticipated that such changes in behavior willlead to aggregated ROA improvements not only through the enhancement of ROA of
individual companies (enhancing the positive “within” effect) but also the shift of assets tocompanies that are more highly efficient (“between” effect).
Junichi Nakamura (e-mail: junakam@dbj.go.jp)

Development Bank of Japan Research Report/ No. 23v

Introduction
The stagnation in ROA (return on assets) and other asset profitability ratios of Japanese firms
has been called into question in recent years reflecting the intensification of global competition
and the harsh evaluation of the market in recent years. Though an improvement in aggregatedROA (of the corporate sector overall) and the enhancement of the per capita welfare level are
not always compatible propositions, it is probably natural that attention should be focused on thestagnation in ROA, a symbol of the efficiency and dynamism of the corporate sector (process ofgrowth and culling through competition) when compared to the U.S., which enjoyed an
unprecedented favorable business climate during the 1990s. Nevertheless, regardless of how
strong that attention may be, it would seem that the empirical examination of the mechanism for
aggregated ROA variability is still inadequate.
It is not necessarily appropriate to discuss changes in the ROA at an aggregated level,
looking upon the overall corporate sector as if it were, so to speak, a single firm (or, in otherwords, setting up the hypothesis of the representative firm). First of all, since changes inaggregated ROA offsets changes of rise and decline on the corporate level, the moreheterogeneous these individual changes (the greater the variance of the individual growth rates)
become, the less representativeness there is. Secondly, ROA on the aggregated level does notconsist only of changes in the ROA of individual firms but is also the result of the inter-company
reallocation of resources (changes in individual weight of total assets) as well as new market
entries and exits. Thirdly, the ROA of individual firms does not move in mutually independent
directions. If one firm wins out in the competition and improves its ROA, there is a strong
possibility that that will bring about a drop in the ROA of industry peers. On the other hand, anabrupt change in a number of firms to management that gives priority to ROA could possibly
result instead in a decline in ROA overall due to the intensification of competition.
Taking these points into account, it is important when attempting to elucidate themechanism behind aggregated ROA variability not only to look at the aggregate amount but also
to use analysis procedures building from micro-data. Actually, the mechanism for variability inemployment, productivity and the like using this approach has already become clear in the U.S.1
In this study, we clarify the actual situation surrounding the persistent decline in aggregated
ROA since the 1980s (1980-99)2 from the micro-structural perspective of ROA variability at thelevel of individual firms as well as inter-company ROA disparities and resource reallocation using
broad-based panel data developed from financial data of 3,300 listed companies (excluding
financial institutions and insurance firms) and the results of the Corporate Investment Attitude
Survey released by the Development Bank of Japan in October 1999. We furthermore focus on
the issue of inter-company disparities, the possible key to realizing improvement in the ROA
hereafter, and empirically analyze the nature of this issue and relationship with investment
strategies.
The study is organized as follows. In Chapter I, after pointing out the theoreticalbackground and measurement issues relating analysis by ROA, we show some evidence of
persistent ROA decline in Japan and confirm the crux of the problem using the aggregated dataof the Corporate Statistics while exploring trends by industry and their implications. In Chapter
II, we develop a framework for empirical analysis using individual corporate financial data andanalyze the background of the persistent decline in aggregated ROA from the standpoint of
microstructure, namely trends and disparities of individual ROA, the inter-company resource
reallocation and so forth. In Chapter III, after once verifying a certain persistence in inter1
2

Refer to Haltiwanger (1997, 2000) for a survey of research in this field.
Refer to Nakamura (2000), p. 1, footnote 1, for the meaning of the analysis period of “since the 1980s.”
Development Bank of Japan Research Report/No.23

1

company ROA disparities (excess profit rate), we combine that with the outcome of the above
attitude survey and examine the correlation with investment strategies. In the Conclusion, wesummarize the implications obtained from the outcome of empirical analyses of the persistentdecline in the ROA and the direction leading to improvement.

2

Development Bank of Japan Research Report/No.23

I. Persistent ROA Decline of the Japanese Corporate Sector
1. Theoretical Background and Measurement Issues
In this study, we conduct analyses focusing solely on ROA (return on assets)1 as a representative
variable of corporate profitability and asset efficiency. From the standpoint of traditional
corporate financial analyses, ROA can be thought of as the index that expresses in the moststraightforward manner how effectively assets entrusted by investors (in the form of liabilities orshareholder capital) are being used. For example, since the level of ROE (return on equity)2,
frequently used in tandem with ROA, depends on the distribution of risk between creditors andshareholders through capital structure (the extent of leverage)3, it is subordinate to ROA as anindex expressing corporate profitability. In addition, due to the simplicity of ROA, it is readily
available as data and also has the great advantage of lending itself well to empirical analysis
through longitudinal data as in the present study.
It is also necessary, however, to keep the following points in mind in order to appropriatelyinterpret the results of the analyses of this study.
a.

Distortions in accounting data

Since ROA is calculated based on publicly released accounting data, it is difficult to avoid various
distortions arising from the accounting system, taxation, discretionary accounting procedures andthe like.
The effect of accounting and taxation systems is an especially great hindrance when making
international comparisons and, as indicated in this chapter, statements based on comparisons of
ROA level are extremely limited. However, from a different perspective such as, for example,
comparisons of time-series transitions between countries, it becomes possible to extract
implications in a form with few distortions. It could furthermore be said that fewer changes anddifferences in systems in time-series and cross-sectional comparisons within the same country,
which is the primary purpose of the analysis of this study, will result in relatively fewer distortions
than in international comparisons.
Discretionary accounting procedures (in which a choice of various accounting methods isavailable and their revision is also possible), regardless of how acceptable they may be in terms ofaccounting theory, are the cause of distortions when measuring true profitability. On the other
hand, even if ROA varies due to the transfer of assets or liabilities to the off-balance sheet orother unsubstantial transactions4, such variation will not be linked to changes in true profitability.5
Nevertheless, even if it were possible to produce ROA with all of these distortions modified inanalyses of individual firms, it would not be realistic in analyses of all listed companies as in thisstudy. It would moreover be difficult to find a practical index as an alternative to ROA.
Conversely, even with serious distortions in individual firm analyses, as long as they are not1Though opinions regarding what to use in the concept of the profit as the numerator are not necessarily unanimous, based on
the idea that it is gross profit obtained through the investment of total assets for distribution to the providers of total capital, it
is appropriate to use profit before payment of interest and before taxes. In this study, in principle, business profit/loss(º operating profit/loss + interest dividends) is used.
2
The general practice is to use current income after payment of interest and after taxes in the concept of the profit as thenumerator in the form of returns to the equity provider.
3
Refer, for example, to Kurosawa and Wakasugi (1982) for the general interpretation of this point.
4
This applies to asset sale and lease back, debt assumptions and other similar transactions and the practices of accounting rules
for account settlement manipulation using this type of substantial transaction are gradually becoming more strict.
5
It seems, for example, that the use of a robust cash-flow based profitability index for certain settlement manipulations isincreasing among investors and others; however, the acquisition of longitudinal data is not only especially difficult but, sincenoise cannot be eliminated completely, it cannot be considered suitable for the purposes of this study.
Development Bank of Japan Research Report/No.23

3

systematic in nature accompanying system revisions and so forth, they would present no
particular problem in certain respects in analyses consisting of pooled data. Thus, in this study,
these distortions in accounting are all deemed to be a part of the disturbance term (i.e., notengendering bias in a certain fixed direction) and analyses are conducted without the addition of
any special modification of the ROA.
b.

Microeconomics interpretation

Although it is clear that ROA must be improved intuitively in Japan, it would not likely be such asimple matter to provide a lucidly defined basis in economics for this insight. In terms of
economics, ROA corresponds to average return on assets6; however, the goal of firms is tomaximize firm value (current discounted value of firm profit in future years) and it is necessary totake note of the fact that the average return on capital is nothing other than the outcome.
It is possible, for example, to conceive of the following argument in opposition to the view thatpersistent ROA decline is a problem. Assuming the usual productivity function in which marginal
productivity gradually decreases7, if the capital-labor ratio (capital per worker) rises together withchanges in the rate of time preference of consumers, the return on capital (both marginal andaverage) would drop8. The decline in the ROA under such circumstances is the naturalconsequence of the maximization of profit and attempting to increase the capital-labor ratio andenhance the return on capital means deviating from economic rationality. In addition, the realinterest rate also declines along with the marginal return on capital; however, if this is the resultof the maximization assuming a new consumer utility function, there is no problem in terms of
economic welfare.
However, we should not overlook two important points. The first is that the level of the
return on capital is not determined only by the factor input ratio (capital-labor ratio) but is also
affected by total factor productivity (TFP)9. If we assume that the decline in capital productivity
is due more to changes (decline) in the TFP than to changes in the rate of time preference, thenconsumer utility will decline together with the real interest rate. It would not be appropriate toclaim at this time that there is no problem because the marginal conditions for the maximizationof profit are satisfied. Likewise, increases in the ROA are also not caused solely by changes in thefactor input ratio. If it is an increase in the ROA associated with an increase in the TFP, the levelof welfare will be raised without any deviation from the marginal conditions.
The second is the possibility of a failure in maximization by misreading demand. In actual
firm operations, it would be difficult to conceive that it is possible to fully foresee demand in
relation to its own output and, looking at it after the fact, there is a strong possibility thatmarginal conditions will not be satisfied or that production will be implemented within apotential frontier. If the ROA declines as the result of such failures in maximization, that means
profit and economic welfare are not maximized, and so its improvement is important.
In simple terms, the judgment of whether or not to see persistent ROA decline as aproblem ultimately depends on which of the following two aspects has actual importance. These
are, namely, the aspect of the optimization by the firm in regard to changes in the rate of time
preference or labor supply and the aspect originating in management inefficiency such as TFP
6

In economics, capital usually means tangible fixed assets but, here, it is also considered to include other corporate assets.
In the production function Y = F (K, L), decreasing marginal productivities means ¶Y / ¶K > 0, ¶ 2Y / ¶K 2 < 0, ¶Y / ¶L > 0,
¶ 2Y / ¶L2 <0. Note that this is not decreasing returns to scale λY > F (λK, λL).
8∵ marginal return on capital = marginal capital productivity – capital depletion rate (constant). Average return on capital also
declines along with the decline in the marginal return on capital.
7

94

Assuming the Cobb-Douglas production function Y = AK a L1-a (A º TFP), marginal capital productivity ¶Y / ¶K = Aα(L/K)1- α.
Development Bank of Japan Research Report/No.23

stagnation or misreading demand. Verifying this point based on data would in itself be a difficult
task and would have to be seen as an issue for the future; however, the fact that corporations
with high shareholding rate by foreign investors who are considered to engage in more rationaland selective investment behavior than Japanese investors also have a high level ROA10 can beconsidered strong supporting evidence that addresses the practical importance of ROA as anindex of management efficiency. We proceed below with an analysis based on the general viewthat ROA decline is an expression of a decline in efficiency of the corporate sector.
2. Evidence from Aggregated Data
Aggregated ROA of Japanese corporations since the 1980s has continued a trend of decline inboth manufacturing and non-manufacturing industries (Fig. 1-1). According to aggregate data of
the corporate sector based on the Quarterly Report on Financial Statement Statistics ofCorporations, ROA11 indicating management efficiency of total assets showed a decline from
9.7% in FY 1980 to 3.4% in FY 1998 for the manufacturing industry total and a decline from
7.7% in FY 1980 to 3.1% in FY 1998 for the non-manufacturing total. This is a drop by morethan half in both cases. Though this has improved somewhat since FY 1999 due to recovery inthe business climate, excluding cyclical variation, aggregated ROA has maintained a consistentand clearly-defined downward sloping trend. Likewise, operating profit margin on tangible fixed
assets excluding land as an index of management efficiency of real assets indicates a drop that isessentially the same as ROA. In spite of the many arguments pointing to the failure of financial
management technology (zai-teku) at the time of the collapse of the bubble economy as the causeof ROA decline, it is evident from a long-term perspective that it is possible to conclude that it
was primarily a decline in efficiency in real terms.
Fig. 1-1(% )Persistent ROA Decline in the Japanese Corporate Sector
Manufacturing

(%)

(%)

10
9

40

8

35

7

30

6

25

5

20

4

15

3

10

2

Non-manufacturing

(% )
30
25

8
7
6
5

20
15

4
3
2
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
FY

ROA

10
5
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
FY

Operating profit margin on tangible fixed assets (right-hand gradations)

Notes: 1. ROA = ordinary profit before interest payment/average total assets at the beginning and end of the term
2. Tangible fixed assets exclude land.
Source: Prepared based on the Quarterly Report on Financial Statement Statistics of Corporations (Ministry of Finance)

10
11

Refer to Fig. 7, p.33, Maeda and Yoshida (1999).
The definition of ROA used below is based in principle on (operating profit/loss + interest dividends)/average total assets atthe beginning and end of the term; however, ordinary profit before interest payment/average total assets at the beginning andend of the term is used here due to limitations in quarterly Statistics of Corporations report data.
Development Bank of Japan Research Report/No.23

5

Next is a simple international comparison for the purpose of determining whether or not
persistent ROA decline is a phenomenon unique to Japan. Transitions in aggregated ROA sincethe 1980s based on corporate statistical data from the U.S. and Germany12 (Fig. 1-2) indicate that,while there was a temporary decline in the U.S. corporate sector together with the slowdown inthe business environment at the beginning of the 1990s, there was a recovery by the late 1990s toabout 7-8%, no less than that of the 1980s. Corporate ROA also recovered in Germany (former
West Germany) after dropping immediately after the unification, reaching a stable level of some
10-11% by the late 1990s, a level comparable to the 1980s. Meanwhile, the ROA of Japanese
corporations calculated according to the same criteria shows a consistent trend of decline fromabout 5% in the early 1980s to about 2% recently. Though we must avoid reaching theconclusion that the ROA in Japan is at a low level in a simple comparison of levels neglecting
differences in the accounting rules, the range of aggregation and other factors, the slump in theJapanese economy is striking when compared to time-series transitions in other countries where
this problem is not so serious (Fig. 1-3).
Fig. 1-2

International Comparison of Corporate ROA in Japan, the U.S. and Germany
Value of Corporate ROA

12
10
8
6
4
2
0
80

81 82

83

84

85 86

87

88

Japan

89 90

91

92

93 94

U .S.

95

96

97 98

99

96

97

99

Germany

Difference from Average of the 1980s

2
1
0
-1
-2
-3
-4
-5
-6
80

81

82

83

84

85

86

Japan

12

6

87

88

89

90

91

92

93

U .S.

94

95

98

Germany

Since data limitations render it impossible to calculate ROA as defined above from Statistics of Corporations in the U.S. andGermany, we carried out the comparisons between Japan and the U.S. with ROA defined as operating profit and loss/average
total assets at the end of the term and between Japan and Germany with current income before payment of interest and before
taxes/total assets at the end of the term. Since differences in the accounting rules and the industries being aggregated still
remain (refer to the diagram notes), comparisons of level are not possible in the strict sense.
Development Bank of Japan Research Report/No.23

Notes: 1. Due to data limitations, operating profit and loss/average total assets at the end of the term is used forcomparisons between Japan and the U.S. and current income before payment of interest and before taxes/total
assets at the end of the term is used for comparisons between Japan and Germany.
2. Not included are the financial and insurance industries in Japan, non-manufacturing industries other than themining, wholesale and retail industries in the U.S. and non-manufacturing other than electricity, natural gas, watersupply, mining, construction, wholesale/retail and transportation industries in Germany. In addition, figures forGermany are limited to corporations in the former West Germany only.
3. Not indicated due to the considerable discontinuity in ROA data in the U.S. prior to 1981 and the fact that 1999
ROA by industry in Germany has not yet been released.
4. Values for the period 1982-89 are used to determine the average for the 1980s in the U.S.
Source: Prepared based on the Annual Report on Financial Statement Statistics of Corporations (Japanese Ministry of
Finance), Quarterly Financial Report for Manufacturing, Mining and Trade Corporations (U.S. Department ofCommerce) and Monthly Reports (Deutsche Bundesbank, Germany). The term is fiscal year for Japan and calendar
year for the U.S. and Germany.

3. Overview of Trends by Industry
Before proceeding with an analysis based on individual company data, we will give an overview
of ROA trends by industry, the effects of changes in the industrial structure and so forth basedon the Statistics of Corporations. Since aggregate data is used, there is the limitation of being
unable to grasp internal trends within industries, though it does have the advantage of coveragethat is wider than that of listed companies only when observing the relationship between themacro-level and industry level.
Aggregated ROA is equivalent to the weighted average of the ROA of each component
element, such as individual industry or individual company (expressed by the subscript i; thesuperscript line expresses average) by weight W of total assets.

ROA = å i ( ROA i ´ Wi )............................................................................(1)13

The five charts, known as skyline charts because of their configuration, of Fig. 1-3 attempt
to visually grasp the background of the decline of aggregated ROA since the 1980s. Charts (1), (3)and (5) express industry-specific ROA every ten years (FYs 1980, 1990 and 1999) (vertical axis)
and the weight of total assets of individual industries in proportion to the sum of all industries(horizontal axis). Meanwhile, (2) and (4) express the breadth of decade-long changes in industryspecific ROA (vertical axis).
The major characteristic is the decline in ROA in virtually all industries during both the
1980s and 90s, as is evident in charts (2) and (4). Though the extent of the decline differs
according to the industry, the important bottom line of manufacturing and non-manufacturingindustry averages indicates that, while manufacturing industries managed to maintain a structureof relatively higher ROA, they kept pace with one another in declining during both the 1980s and1990s. In other words, the direct cause of aggregated ROA decline since the 1980s is not thestagnation of those industries that have been dubbed the “losers” but is thought rather to be theoverall deterioration.

13

Derived as indicated below.
ROA = S iEi / S iAi = S i (Ei / S iAi ) = S i ((Ei / Ai) (Ai / S iAi)) = S i (ROAi ´ Wi )Where, E: operating profit/loss, A: total assets, W: total assets weight
Development Bank of Japan Research Report/No.23

7

6

8

Foods

10

8

2

0

10

10

Electricalequipment

20

M anufacturing average
4 .0 ％

2030-1.7 ％pt

Construction

40

Construction

30
40

Construction

40

50

Wholesale

50

Development Bank of Japan Research Report/No.23
60

Wholesale
RetailManufacturing average
8.0 ％

50
60

Wholesale50

Average of all industries: 3.7 ％Retail60

Wholesale
RetailManufacturing average
Non-manufacturing average-3.9 ％pt-2.7 ％pt

3.5 ％0RetailRetailReal estate

60

70

Real estate

70
80

Average of all industries:6.8 ％6Real estate

70
80

Real estate

Average of all industries: -3.1 ％pt

7080

Non-manufacturing average

80

90

90

90

90

Other nonmanufacturing

Other services

Business services

Electricity &gas supply

80

Other nonmanufacturing

40

70

Business
services

Other
services

90
Other non-manufacturing

Manufacturing average–1.7% pt
60

Other services

Construction

Real estate
Other nonmanufacturing

Other services

Business services

Electricity &gas supply

Other transportation & communication

Overland and marinetransport

RetailBusiness services-250

Overland andmarine transport

8.5%

Other transportation & communication

Average of all in du stries: 8.5%

Electricity &gas supply

7.7%

Other transportation &communication

Other
manufacturing

Transport
equipment
Precisionequipment

Electricalequipment

Generalequipment

Metal products

Nonferrous metals

Iron & steel

Ceramics, stone and clay

Petroleum andcoal products

Chemicals

Average of all industries

Electricity &gas supply

30
40

Overland andmarine transport

30
Other
manufacturing

Transport
equipment
Precision equipment

Non-manufacturing average

9.7%

Other transportation &communication

Other
manufacturing

Electricalequipment

30

Overland andmarine transport

20

Other
manufacturing

Transport
equipment
Precision equipment

Metal products
Generalequipment

Manufacturing averageElectricity &gas supply

020

Wholesale

Other transportation &communication

0
Nonferrous metals

Foods
TextilesPaper & pulp

Construction

Overland andmarine transport

-6

20

Other
manufacturing

10

Transport
equipment

2Electricalequipment

10

Precision equipment

0
Iron & steel

10Electricalequipment(2) Magnitude of change FY 1980 à FY 1990 (total assets weights are based on FY 1980)
Ceramics, stone and clay

2

Generalequipment0

Nonferrous metals
Metal products-6
Petroleum andcoal products0

Nonferrous metals
Metal products
Generalequipment

2
Chemicals

4

Iron & steel-4

Petroleum and coal products
Ceramics, stone and clay
Iron & steel

Foods

6

Transport
equipment
Precision equipment-4
Paper & pulp

(1) FY 1980

Generalequipment

4
Chemicals

12

ChemicalsPetroleum andcoal products
Ceramics, stone and clay

8
Textiles2

Chemicals

10

Foods

0

TextilesPaper & pulp

8

Petroleum and coal products
Ceramics, stone and clay
Iron & steel
Nonferrous metals
Metal products

-2
Foods

10

TextilesPaper & pulp

12Paper & pulp

4

TextilesFig. 1-3 Transitions in Industry-Specific ROA (skyline charts)

Vertical axis: ROA (%), horizontal axis: Total assets weight (%)

0100

Average
Average ofof all industries

Non-manufacturing average-1.5 ％pt

100(3) FY 1990

Non-manufacturing average

0
6.2 ％

100

(4) Magnitude of change FY 1990 à FY 1999 (total assets weights are based on FY 1990)-8100(5) FY 1999

12

Other nonmanufacturing

Business
services

Other services

Note: ROA = ordinary profit before interest payment/average total assets at the beginning and end of the term
Source: Prepared based on Quarterly Report on Financial Statement Statistics of Corporations (Ministry of Finance)100

We will look now at changes in relative performance between industries expressed in thecharts in order to confirm this point. In the case of manufacturing industries, precisionequipment (12.5%), electrical equipment (11.3%) and other equipment industries were
outstanding in FY 1980. These dropped broadly, however, during the 1980s for various reasons
including the sharp appreciation of the yen. Relatively good performance in the metal productand iron & steel industries was notable in FY 1990 urged on by increased construction demandduring the so-called Heisei boom; however, there was a broad drop during the 1990s andequipment industries also continued to decline in the midst of stiff global competition.
As a result, among manufacturing industries, the situation during FY 1999 indicates animprovement in the relative status of chemicals and foods, which had demonstrated a narrow
range of decline in the 1990s. At the same time, transport equipment and electrical equipment
achieved no more than the overall manufacturing industry average while general equipment andsteel plummeted.
In the case of non-manufacturing industries, regulated industries such as electricity, naturalgas, water supply, other transport and communication and retail were outstanding in 1980 but
declined broadly during the 1980s due to the intensification of competition following
deregulation and other reasons. A broad decline was evident during the 1990s not only inconstruction, real estate and other industries that were strongly impacted by the collapse of the
bubble economy but also in other services and other industries. As a result, the situation in FY
1999 shows that the relative status of electricity, natural gas, water supply and other transport andcommunication, which declined slightly during the 1990s, improved again. Meanwhile, the service
industry, which had been a growth industry, did no better than the non-manufacturing industry
average. It can thus be pointed out that changes in the relative performance between industries
throughout the twenty-year period since the 1980s did not reflect progress to an industrial
structure of being outperformed by growth industries.
Using the above industry level data, we shall attempt a decomposition analysis of thechanges in aggregated ROA. Analyses heretofore focused solely on changes in industry-specific
ROA as the background of aggregated ROA decline; however, changes in the total assets weightof each industry to the sum of all industries Wj (changes in the industrial structure) also have an
impact on aggregated ROA. That is because, even if, for example, industry-specific ROA were at
the same level as previously in all industries, aggregated ROA will also increase to the same extent
as increases in the weight of industries with a relatively high ROA. That is, changes in aggregatedROA (compared to the previous year) according to formula (1) can be decomposed as indicatedbelow (subscripts t and t-1 express points in time; superscript lines express weighted average).
ROA t - ROA t -1 = å j (ROA j , t ´ W j , t - ROA j , t - 1 ´ W j , t - 1 )= å j (ROA j,t - ROA j,t -1 ) ´ W j,t -1 ..............................................(a)+ å j (ROA j , t -1 - ROA t -1 ) ´ (W j , t - W j , t -1 ) .................... (b)+ å j (ROA j , t - ROA j , t -1 ) ´ (W j , t - W j , t - 1 ) .....................(c)........................................................... (2)Term (a) of formula (2) is described below as the “within” effect as a factor that expresses
the contribution of changes in industry-specific ROA and reflects the efficiency of theDevelopment Bank of Japan Research Report/No.23

9

reallocation of resources within industries. Term (b) is described below as the “between” effect asa factor that expresses the contribution of changes in the industrial structure and reflects theefficiency of the reallocation of resources between industries14. Term (c) is a cross term of the“within” and “between” effects. Though industrial structure is not something that changes to any
sizable extent within a short time, the direction of the changes is thought to reflect dynamic
efficiency of resource allocation in the overall economy and the “between” effect of term (2) also
has the potential for strongly dominating the aggregated ROA level. Accordingly, to wrap up thissection, we will conduct a contribution decomposition analysis (referred to below as “withinbetween” analysis) based on formula (2) of aggregated ROA variability and quantitatively observe
the structure of aggregated ROA decline since the 1980s.
Fig. 1-4 Industry-based “Within-Between” Decomposition of Changes in Aggregated
ROA from the Previous Year
1.0

0.5

0.0

-0.5

betw een+crossw ithin effect (of non-manufacturing industries)
w ithin effect (of manufacturing industries)
total

-1.0

-1.5
81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

Av平均
arage

Notes: 1. ROA = ordinary profit before interest payment/average total assets at the beginning and end of the term
2. The change in aggregated ROA from the previous year (“total”) is decomposed into the contribution of thechange in ROA for each industry from the previous year (“within” effect), contribution of the change in total
assets weight for each industry from the previous year (“between” effect) and the cross term of both (“cross”). In
the chart, the “within” effect is divided between manufacturing and non-manufacturing industries, and the“between” effect is indicated summed up with the cross term.
Source: Prepared based on Quarterly Report on Financial Statement Statistics of Corporations (Ministry of Finance)

In Fig. 1-4, “within-between” decomposition of the previous year change in ROA for allindustries is carried out for each year since FY 1981, the “within” effect is divided between
manufacturing and non-manufacturing industries and the “between” effect is indicatedaggregated with the cross term. As the chart clearly shows, the contribution of the “between”
effect to changes in aggregated ROA each year is rather small; however, this is nothing other than
the reverse of the fact that changes in the industrial structure are small in the short term. What ismore noteworthy, however, is that there are also negative years that emerge sporadically in the
direction of the contribution of the “between” effect and that the twenty-year averagecontribution shown at the far right is essentially zero. This means that changes in the industrial
structure did not move in a definite direction such as a shift in resources from industries with low
profitability to those with high, which is also consistent with the results of the skyline charts.
We confirmed from the results of the analyses based on the individual industry data above thatthe decline in aggregated ROA since the 1980s was due to a decline in the efficiency of resource
14

The term ROA t-1 proves to be the redundant because (S j (ROA t-1 ´( Wj, t - Wj, t-1 ))=0), but is indicated in order to clarify themeaning of the “between” effect in which aggregated ROA rises as the increase in the weight of industries with relatively high
ROA.

10

Development Bank of Japan Research Report/No.23

allocation within industries, whether manufacturing or non-manufacturing (negative “within”
effect), and also to the lack of apparent progress in the industrial structure in which growthindustries would realize high returns and boost growth overall (the “between” effect was alsoessentially zero). In the next chapter, we will examine even more closely those causes that induce
this deterioration throughout all industries based on individual company data.

Development Bank of Japan Research Report/No.23

11

II. Microstructure of ROA Decline
1. Significance of Analysis Using Individual Company Data
As stated in the Introduction, it is not necessarily appropriate taking corporate heterogeneity into
account to see the decline in aggregated ROA as if it were a phenomenon appearing upon one
firm. The same can be said of the variability in ROA at the industry level analyzed in the previous
chapter. Of course, if there is no more than a small degree of heterogeneity, this would benothing more than a trivial problem. However, in the background of the analyses using microdata that have been conducted so enthusiastically in recent years, especially in the U.S., there is ashared awareness that heterogeneity at the micro-level exerts an effect on aggregated data
variability that cannot be neglected. Haltiwanger (1997), for example, points out based on
longitudinal establishment level data of the manufacturing sector that the fraction of crosssectional variance of establishment level growth rates for employment, output, productivity andother indices explained by 4-digit industry fixed effects is no more than 10% of the total, that is,even if considerably minute industry characteristics are taken into account, significant
heterogeneity still remains.
In the analyses based on individual industry data in the previous chapter, although changes
were apparent in relative performance between industries, the ROA of all industries declined with
virtual uniformity. Based on the outcome of empirical analyses in the U.S., however, there is astrong possibility that the variability in ROA seen in firms may be far more heterogeneous thanthat in industries. “In the fastest-growing industries, a large fraction of establishments experience
substantial declines, whereas in the slowest growing industries, a large fraction of establishments
exhibit dramatic growth. During severe recessions virtually all industries decline, but within eachindustry a substantial fraction of establishments exhibit substantial growth. Likewise, during
robust recoveries, a substantial fraction of establishments are contracting” (Haltiwanger, 1997,p.55). If this were to apply to Japan since the 1980s in a situation that could almost be called total
defeat when viewed by industry, analyses of variability in ROA at the firm level and its
background may make it possible to identify the factors behind this total defeat or signs ofrevitalization. In this chapter, we will observe first of all the situations and changes of distributionof the ROA at the corporate level both for the whole sample and for each industry as the firststage in the analysis of the microstructure. Following that, we will analyze the microstructure of
the persistent decline in ROA both aggregated and at the industry level from the standpoint ofinter-company disparities and the inter-company reallocation of resources and point out theimportance of disparities between firms within the same industry.
The source of the data in the following analyses is non-consolidated settlement financial
data1 of listed companies2, excluding financial institutions and insurance firms, stored in thecorporate financial data bank at the Development Bank of Japan and, the following analyses
mainly focus on some 1,400 firms listed continuously from FY 1980 through FY 1999 (referred
to as “common firms”) as the statistical population3.

1

Based on normalized data adjusted for irregular accounting data brought about by changes in settlement periods, mergers, etc.
Listed companies in regional stock exchanges (other than the Tokyo Stock Exchange, Osaka Stock Exchange and Nagoya Stock
Exchange), NASDAQ Japan and TSE Mothers are not included. In addition, since records of OTC (JASDAQ) listed company
data begin in December 1987, they are not included in common firms from FY 1980.
3
There were about 3,300 firms listed in FY 1999.
2

12

Development Bank of Japan Research Report/No.23

2.

ROA Distribution of Individual Companies and Its Changes – Descriptive Statistical
Observations –Observing the situations and changes of distribution of individual companies’ ROA can beconsidered the most fundamental approach for the purpose of comprehending the
microstructure of ROA at the aggregated or industry level. Though the purpose here is not toverify the anticipated distribution based on a specific theoretical model, we will conduct aconceptual simulation before proceeding with histogram (frequency distribution table)
observations as a way of clarifying the points that should be noted.
First of all, assuming a state in which all markets are perfectly competitive and the risk of
profit variability does not exist, it is thought that ROA distribution itself would degenerate since
the ROA of any firm would converge in an equilibrium, at a single required profit rate (minimum
profit rate required by investors). Next, if individual firms confront common profit variability risk
occurring randomly, the ROA distribution would probably approach a normal distribution.
Furthermore, under conditions in which the degree of profit variability risk confronted by firms
differs by industry, it is anticipated that, in the economy overall, the distribution would have abroader tail than the distribution within the industry since the level of the required profit ratewould differ according to the industry4.
The discussion thus far has remained within a static framework and, setting aside random
profit variability, the ROA of individual firms corresponds to the required profit rate5. However,in dynamic processes in which creative destruction6 occurs constantly through innovation, there
would be both firms that achieve an excess profit rate higher than the required profit rate(creation of profit opportunities) and firms that lose out in the competition with profit dropping
below the required profit rate (loss of profit opportunities)7. In economies both the creation andthe loss of profit opportunities frequently occur through creative destruction, the distribution
would have an asymmetric configuration with the broader tail on the high profit side, since firms
dropping below the required profit rate are not sustainable.
In addition, it is possible to position the “bipolar and “winner-takes-all” phenomena, afrequent topic of discussion in recent years, as dynamic processes and, if the expansion of intercompany disparities actually occurs in a form such as this, the distribution could possibly inextreme cases be of a double-peak or uniform configuration.
We shall now proceed with ROA histogram observations taking the conceptual simulation
above into account. Let us first attempt a histogram for every five years since FY 1980 not
divided by industry8 (Fig. 2-1). The characteristics that draw attention include that, in shape, it
generally resembles a normal distribution with a single bell-shaped peak and that the distribution
4

In an industry such as mining, for example, firms are seen that record an abnormally high ROA but, on the other side of thecoin, there is also the possibility of high profit variability risk.
5
Excluding cases of imperfect competition.
6
Needless to say, creative destruction is a concept that forms the core of Schumpeter’s economic growth theory but it draws
attention again in the early 1990s within the context of endogenous growth theory. In addition, since creative destructionmeans that both creation and destruction occur simultaneously, it is a field in which analyses using micro-data are most effective(refer to the Introduction of this study) and it also has strong links to a line of empirical studies relating to employment,
productivity and the like such as those referred to in this report. Refer to Caballero and Hammour (1996) and associatedreferences for the flow of theoretical research and to Haltiwanger (1997, 2000) and associated references for the flow of
empirical research.
7
Profit opportunities are considered to be a sort of intangible asset theoretically equivalent to the numerator of Tobin’s q. The
ideas relating to the creation or loss of profit opportunities are suggested by the concepts of total job creation and total job
destruction already established in employment analyses. Refer to Tanaka (2000) and associated references for the analysis of job
creation and destruction in Japan.
8
The Development Bank of Japan industrial classification mid- and sub-categories summarized into 32 groups, as in the table in
the appendix of this study, are used as the industrial classification in the analysis of individual company data beginning with thischapter.
Development Bank of Japan Research Report/No.23

13

shifts overall to the left as average ROA drops. Other basic statistics indicate that, althoughstandard deviation reduces in size along with the decline in the average, the coefficient ofvariation indicates that inter-company disparities increase from 1995 on. Skewness (0 withnormal distribution; a positive value indicates a broader right-hand tail and a negative value
indicates a broader left-hand tail)9 in the past had a shape with the right-hand tail somewhat
broader than a normal distribution. Beginning in the mid-1990s, however, it significantly
approached a normal distribution.
Fig. 2-1 ROA Frequency Distribution of the Common Firms for Every 5 years (horizontal
axis: ROA (%), vertical axis: relative frequency (%))
20
全産業

18

Number of observations
観測数
Arithmetic mean平均値
Median
中央値
Standard deviation
標準偏差
Coefficient of variation
変動係数
Skewness
歪度
Kurtosis
尖度

16
14

80fy
85fy
90fy
95fy
99fy

12
10
8
6

80fy
1447
9.21
8.54
5.45
0.59
1.14
5.09

85fy
1447
6.69
6.26
5.29
0.79
0.27
3.63

90fy
1447
6.86
6.41
4.06
0.59
0.93
3.73

95fy
1447
3.26
3.19
3.72
1.14
-0.08
3.57

18

20

22

24

99fy
1447
2.85
2.61
3.78
1.33
0.15
3.22

4
2
0
〜-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

25〜

Notes: 1. The population consisted of those firms listed continuously from FY 1980 through FY 1999. Refer to the text
for details.
2. Since deviation readily increases due to outliers, skewness and kurtosis were calculated with the two upper andtwo lower values both eliminated. Since the sample skewness and sample kurtosis formulae in the spreadsheet
software Excel were used in numerical calculations, they different in strict terms from skewness and kurtosis as
defined in the text, though that does not have any particular effect on the analyses.

Since it is also possible to interpret this point as suggesting the stagnation of creative
destruction, further verification along with the analyses below is considered to be necessary.
Kurtosis (0 with a normal distribution; a positive value indicates that the tail is shorter than anormal distribution and a negative value indicates that the tail is longer)10 indicates that the tail isconsistently shorter than a normal distribution. This may also suggest that either the effect ofinter-industry disparities or the effect of random profit variability risk or both of them are small;
however, this too must verified along with later analyses.
We will next observe the transitions every five years in like manner with the population
divided between manufacturing and non-manufacturing industries (Fig. 2-2). First of all, the trend
toward decline of the average and the trend toward increase in the coefficient of variation(expansion of inter-company disparities) are recognized to be shared by both. In regard to
skewness, manufacturing industries have been relatively close to a normal distribution since the1980s and the direction of time-series changes has been ambiguous. With non-manufacturingindustries, a clearly-defined broadening of the right-hand tail greater than a normal distribution
was observed until FY 1990 but this has rapidly approached a normal distribution since 1995. If
9Third order moment (central moment) divided by the third power of standard deviation. Since deviation readily increases due
to outliers, calculations have been made with the two upper and lower two data both eliminated.
10
Fourth order moment (central moment) divided by the 4th power of the standard deviation less 3, standardized so that it has
the value of 0 in the case of a normal distribution. Since deviation readily increases due to outliers as in the case of skewness, it
was calculated with the two upper and lower values both eliminated.
14

Development Bank of Japan Research Report/No.23

we accept the hypothesis above that the reduction of the left-hand tail is indicative of stagnationin creative destruction, then it would also be possible to interpret that manufacturing had alreadylost that dynamism in the 1980s and non-manufacturing industries by the latter half of the
1990s11. Focusing next on the left-hand tail of the distribution, the ratio of firms showing red ink
has increased substantially from 1995. Conceptually, businesses that would not pay even if thecost of capital were zero are clearly not sustainable and the left-hand tail of the distribution
should exhibit a truncated shape.
Fig. 2-2 ROA Frequency Distribution of the Common Firms for Every 5 years – By
Industry(horizontal axis: ROA (%), vertical axis: relative frequency (%))

Manufacturing

20

製造業
観測数
Number of observations
平均値
Arithmetic mean
中央値
Median
標準偏差Standard deviation
変動係数
Coefficient ofvariation
Skewness 歪度
Kurtosis 尖度

18
16
80fy
85ｆｙ
90fy
95fy
99fy

14
12
10
8

80fy
1001
9.61
9.00
5.47
0.57
0.76
3.13

85fy
1001
6.77
6.58
4.66
0.69
-0.01
2.39

90fy
1001
7.02
6.67
4.09
0.58
0.73
2.68

95fy
1001
3.14
3.22
3.80
1.21
-0.38
2.93

22

24

99fy
1001
2.81
2.61
3.87
1.38
0.14
2.21

6
4
2
0
〜-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

25〜

Non-manufacturing
26
24
22

非製造業

Number of 観測数
observations
Arithmetic平均値
meanMedian 中央値
Standard deviation
標準偏差
Coefficient変動係数
of variation
Skewness 歪度
Kurtosis 尖度

20
80fy
85ｆｙ
90fy

18
16
14

95fy
99fy

12
10
8

80fy
446
8.30
7.39
5.29
0.64
1.05
1.97

85fy
446
6.50
5.61
6.48
1.00
1.10
3.48

90fy
446
6.52
5.88
3.96
0.61
1.20
3.25

95fy
446
3.52
3.09
3.51
1.00
0.72
2.51

22

24

99fy
446
2.96
2.62
3.58
1.21
0.34
4.27

6
4
2
0
〜-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

25〜

Note: Refer to the notes of Fig. 2-1.

The fact that the left-hand tail remains unchanged even in the red-ink zone suggests a delay
in structural adjustment (exit of stagnating firms or the reallocation of resources to growthindustries). Kurtosis indicates consistent shortness in the tail in relation to a normal distribution
in both manufacturing and non-manufacturing industries, and, in the case of non-manufacturingindustries, this tendency is gradually becoming stronger.
11

It is necessary to note, however, that, since many previously regulated industries are included among non-manufacturingindustries, there is also the effect of excess profit rate that is generated because the market is not competitive.
Development Bank of Japan Research Report/No.23

15

In comprehending the situations of creative destruction, that is, the situations of thecreation and loss of profit opportunities, besides the distribution of ROA level, the distributionof change is also important. Let us consider, for example, an economy in which, even though the
ROA declines by 1% in the economy overall, all firms drop by 1% and another economy inwhich there is a substantial number of firms with an increase in ROA (however, the contributionof these firms is overwhelmed by the stronger effect of the declined firms). No margin exists inthe case of the former for an enhancement of the ROA in the economy overall through thereallocation of resources. However, a margin does exist in the latter case for a futureenhancement of the ROA in the economy overall through the reallocation of resources fromweakly competitive to strongly competitive firms. In that respect, there are considerable
discrepancies in latent vitality within these economies. Observing the distribution of changes
makes it possible to precisely comprehend these differences in potential. In addition, theobservation of changes is also important for the purpose of verifying bipolarization. That is
because, even if the distribution (of level) were currently a bell-shaped curve, if the distribution ofchange were bipolarized persistently, there is a strong possibility that the distribution of level
would also become bipolarized in the future.
Fig. 2-3 illustrates by histogram the magnitude of ROA change of each firm from FY 1980
through FY 1990 (i.e., “1980s”) based on all industries and the same for the period of FY 1990
through FY 1999 (“1990s”). First of all, the shape is a single-peak bell-shaped curve generally
resembling a normal distribution and the distribution in the 1990s has shifted overall to the left
compared to the 1980s.
Fig. 2-3 Frequency Distribution of the Magnitude of ROA Change of the Common
Firms in the 1980s & 1990s(horizontal axis: ROA (%), vertical axis: relative frequency (%))
14
80→90
90→99

12
10
8
6
4
2
0
〜-15

-10

-5

0

5

10

15

Note: Refer to the notes of Fig. 2-1.

Thirty percent of the firms increased their ROA during the 1980s, which then dropped to
14% during the 1990s with mounting stagnation in the move toward the creation of profit
opportunities. The view is also important, however, that, while in the analyses of data by industry
in Chapter I, only business service firms increased their ROA during the 1990s, when viewed byfirm, 14% managed to increase their ROA during the so-called “lost decade” of the 1990s.
To wrap up this section, we will take a look at the situations of ROA distribution with theinclusion of both newly listed companies and those that withdrew from the market. Analyses thus
far have all been conducted based on the common firms since FY 1980 and the population has
16

Development Bank of Japan Research Report/No.23

consisted of traditional firms that have been listed for at least twenty years. If the ROA of firms
such as these does decline, we naturally suspect that they are perhaps not typical of the economy
overall. In addition, the contribution due to the exit of inefficient firms from the stock market isalso not taken into account on the common firm basis. If we then proceed with a comparison of
the distribution of ROA of the some 1,650 firms newly listed since FY 1981 with that of thecommon firms as of FY 1999 (Fig. 2-4), we see that they are positioned somewhat to the right ofthe common firms and are dominant with a weighted average ROA of 5% compared to 3.7% for
the common firms. In regard to other fundamental statistics, while the coefficient of variation
was somewhat higher for the common firms, skewness and kurtosis were characterized, like thecommon firms, by a broader right-hand tail and shorter tail than a normal distribution. However,
the right-hand tail broader and somewhat longer than the common firms suggests greater relative
vitality. Next, transitions in the weighted average ROA of all firms (approx. 3,300) including
firms that delisted (approx. 200) along with the newly listed companies in the populationcompared to the common firm base (Fig. 2-5) indicate that the total assets weight of newly listed
firms to all firms was not particularly great, amounting to no more than 22% even in FY 1999,
and the divergence between the two was only about 0.3% at most. In addition, transitions inweighted average ROA of newly listed companies alone (Table 2-1) show that they maintained adominant position over the common firms in the range of about 1 – 2% since the latter half ofthe 1980s, while following a downward trend virtually in parallel with them. Considering all ofthese points, though the newly listed companies, as may be expected, have a higher ROA thanthat of the common firms and also have greater potential vitality, the effect of eliminating themfrom the population is limited.
Fig. 2-4 Comparison of ROA Frequency Distribution in FY 1999 for the Common Firms
and Firms Newly Listed Since FY 1981
(horizontal axis: ROA (%), vertical axis: relative frequency (%))
20
18

Common Newly listed
firms
会社 新規 firms
場
Number of observations 1447
1649
Weighted average 3.67
5.00
Arithmetic mean
2.85
5.72
Median2.61
4.79
Standard deviation 3.78
6.01
Coefficient of variation 1.33
1.05
Skewness
0.15
0.96
Kurtosis

Common
共通会社
firms
Newly listed
新規上場
firms

16
14
12
10
8
6

3.22

2.70

20

25

4
2
0
〜-10

-5

0

5

10

15

Notes: 1. Refer to the notes of Fig. 2-1.
2. Refer to the main text for newly listed firms.

Development Bank of Japan Research Report/No.23

17

Fig. 2-5 Comparison of ROA of Common Firms and All the Listed Firms
10

(%)
(%)

(%pt)
(%pt)
Common firms
共通会社
All listed firms
全上場企業

9

Difference (subtract common
from all, right-hand gradations)

8

0.5
0.4
0.3

7

0.2

6

0.1

5

0.0

4

-0.1

3

-0.2
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99(FY)
年度

Notes: 1. Refer to the notes of Fig. 2-1.
2. All listed companies include firms newly listed since FY 1981 and those that have delisted since FY 1981.
The number of firms differs by year (3,309 in FY 1999).

Table 2-1

Total Assets Weight and ROA of Firms Newly Listed Since FY 1981
(unit: %)

80fy
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99

Total assets
weight

ROA

0.3
0.8
1.1
1.4
2.0
7.1
7.4
8.1
9.7
10.5
11.1
11.5
13.6
15.2
17.1
18.0
19.8
20.8
21.7

33.0
13.5
12.0
12.5
27.0
7.5
8.7
9.6
8.3
8.2
7.1
6.8
5.2
5.5
5.6
6.1
5.3
4.8
5.0

(Reference)
ROA ofcommon firms
8.9
8.1
7.3
7.3
7.7
7.0
6.0
6.2
6.8
6.8
6.8
5.9
4.5
3.7
40
4.0
4.2
4.1
3.4
3.7

Notes: 1. Refer to the notes of Fig. 2-1.
2. Total assets weight is calculated as the weight to all the listed firms.
3. There is considerable variation in the figures for the ROA of firms newly listed since FY 1981 due to the small
number of firms through about 1985.

18

Development Bank of Japan Research Report/No.23

3.

Structure of ROA Decline from the Perspective of Inter-Company Disparities andResource Reallocation
It is possible to decompose the relative position of ROA of Firm i in relation to average ROA of
all the firms into the two primary elements of the characteristics of Industry j, to which Firm ibelongs, and the positioning of Firm i within Industry j. Thus (superscript lines express average):
ROA i - ROA all = ( ROA j - ROA all ) + ( ROA i - ROA j )Characteristics ofIndustry j

Positioning of Firm iwithin Industry j.......................................................(3)If this way of thinking were extended to the overall population, it would be possible todecompose the magnitude (total variability) of inter-company disparities from a macro
perspective into disparities due to the characteristics of the industries to which each firm belongs(variability between industries) and disparities between firms within the relevant industry(variability within the industry). Thus:å i ( ROA i - ROA all )2= å i ( ROA j - ROA all ) 2 + å i ( ROA i - ROA j ) 2 + 2 å i ( ROA j - ROA all ) (ROA i - ROA j )Variability between industries

Variability within the industry

Cross term.......................................................(4)Here, variability refers to the sum of the squares of mean deviation, variability divided by
the number of observations is variance, while variance standardized by the arithmetic mean is thecoefficient of variation. In addition, the summation of variability within the industry for all thefirms i in Industry j coincides with the total variability of Industry j.
Fig. 2-6 indicates the transitions in total variability since FY 1980 in the common firms andtheir decomposition in accordance with the definition above. Incidentally, the cross term isindicated included in variability between industries. Total variability declined broadly in the latter
half of the 1980s and continued to decline slowly subsequent to that, reflecting the downward
Fig. 2-6 Inter-company ROA Disparities (Total Variability) and Their Decomposition
for the Common Firms(% pt)(%)

50000

Variability within the
産業内変動
industry
Total variability
総変動

Variability between
産業間変動
industries
Coefficientof
変動係数（右目盛）
variation (right-handgradations)

40000
30000

2.0

1.5

1.0
20000
0.5

10000
0
80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

0.0
99年度
FY

Notes: 1. Refer to the notes of Fig. 2-1.
2. Variability between industries indicates ROA disparities attributable to industry characteristics and variability
within the industry indicates ROA disparities within the same industry.
3. Coefficient of variation = standard deviation/arithmetic mean

Development Bank of Japan Research Report/No.23

19

trend of average ROA. However, in spite of stable movement during the 1980s in the degree ofinter-company disparities evident in the coefficient of variation, this tended to expand during the
1990s. The outcome of the decomposition of total variability indicates that inter-company
disparities were largely due to variability within industries (89% on a 20-year average).
Thus, viewing transitions in disparities between firms within the same industry, which
played an important role in forming inter-company disparities, by industry (Fig. 2-7) indicates that
(coefficient of variation, moving average after 5 years), as one may expect, to a greater or lesser
extent, after the beginning of the 1990s, there was a confirmable tendency toward expansion ininter-company disparities in virtually all industries. In addition, in manufacturing industries, there
was a conspicuous trend toward an expansion of disparities in the iron & steel and generalequipment industries, while those in the food and chemical (excl. pharmaceuticals) industries
were more gradual. Electrical equipment and automobiles can be positioned in a groupintermediate between these. When compared with the results of the skyline analyses of Chapter I,
industries experiencing a larger expansion in inter-company disparities tend to face a broader
decline in industry ROA. It can thus be seen that it is the loss of profit opportunities, rather thantheir creation, that plays the primary role in the expansion of disparities between firms within thesame industry, which for the most part explains aggregated inter-company disparities.
Finally, we will now apply the “within-between” decomposition technique to individualcompany ROA of the common firms (refer to section 3 of Chapter I for an explanation of theconcept and terminology). In the analysis of individual industry data in Chapter 1, we
decomposed the changes in aggregated ROA into the factors that reflect changes in ROA of eachfirm or the efficiency of resource allocation within the industry (“within” effect) and factors thatreflect changes in the structure of the industry or the efficiency of resource allocation between
industries (“between” effect). In contrast to this, in this section, the factors that reflect changes in
ROA of each firm or the efficiency of resource allocation within the firm is considered to be the“within” effect and factors that reflect changes in the share of total assets between firms or theefficiency of resource allocation between firms is considered to be the “between” effect. For therecord, when decomposition identity is shown, as in formula (5) (Wi = weight of total assets ofFirm i, subscripts t and t-1 express points in time and superscript lines express weighted average),(a) is the “between” effect, (b) is the “within” effect and (c) is the cross term.
ROA t - ROA t -1 = å i (ROA i , t ´ Wi , t - ROA i , t - 1 ´ Wi , t -1 )= å i (ROA i , t - ROA i , t -1 ) ´ Wi , t -1 ............................................(a)+ å i ( ROA i, t -1 - ROA t -1 ) ´ ( Wi, t - Wi, t -1 ) ....................... (b)+ å i ( ROA i, t - ROA i, t -1 ) ´ ( Wi, t - Wi, t -1 ) ...........................(c)........................................................... (5)20Development Bank of Japan Research Report/No.23

Fig. 2-7 Within-Industry ROA Disparities for the Common Firms (Coefficient of
Variation Based on Moving Average of the last 5 years)

Manufacturing
(%)

製造業

2.0
1.5
1.0
0.5
年度
0.0
84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 FY
Foods
食品
General
一般機械
equipment

Chemicals (excl.
化学（除く
医薬品）
pharmaceuticals)Electrical
電気機械
equipment

Iron & steel
鉄鋼
Automobiles (&自動車
automotive parts)

Non-manufacturing
(% )

非製造業

2.0
1.5
1.0
0.5
年度

0.0

84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 FY
Construction
建設

不動産
Real estateSpecialized trading
専門商社
firms
Communication &通信・放送
broadcasting

小売
RetailElectricity & gas
電力・ガス
supplyNotes: 1. Refer to the notes of Fig. 2-1.
2. Calculated as coefficient of variation based on the moving average of the last 5 years = standard deviation(moving average of the last 5 years)/arithmetic mean (moving average of the last 5 years)

The results of the decomposition are as indicated in Fig. 2-812. The fact that the “within”
effect explains virtually all of the ROA changes in each year and is negative on average is thesame as the case seen by industry (Fig. 1-4); however, in the case of the “between” effect,
although the year-to-year contribution is small, it has a consistent positive tone that differs fromthe case by industry. It should be noted, therefore, that, in terms of averages, it projects a certain
12“Total” in Figs. 2-8 and 2-9 is the difference in weighted average ROA of the common firms from the previous year and the
movement differs, though only slightly, from the analyses of Chapter I. (Fig. 1-4) based on individual industry data in theStatistics of Corporations.
Development Bank of Japan Research Report/No.23

21

sense of presence and contributes to a boost in the ROA (in contrast to the total average of–0.28% points, “within” is –0.33% points and “between” is +0.05% points). The presence of the“between” effect is especially strong in times when ROA decline is most severe such as during
the strong yen recession (FY 1985-86) and after the collapse of the bubble economy (FY 92-93),
which can be seen as a fact with an abundance of suggestions13.
As stated previously, it is also important to investigate the situations of gross “within” effect,
namely to sum up the positive contribution of firms with improving ROA and negative
contribution of firms with deteriorating ROA separately, from the standpoint of gauging themagnitude of the creation and loss of profit opportunities in the analysis of individual company
data (Fig. 2-9). First, when looking at the twenty-year average, –0.33% points of the net “within”
effect is decomposed into –0.78% points for the gross negative effect (contribution of firms withdeteriorating ROA) and +0.45% points for the gross positive effect (contribution of firms withimproving ROA). This considerable magnitude of the gross positive effect gives rise to somewhat
of a change in the impression of total collapse when seen by industry. However, in the averagefor the 1980s (1981-89), the gross positive effect was +0.56% points while, in the average for the
1990s (1990-99), it dropped to +0.36% points (+0.46% if FY 1991-93 after the collapse of the
bubble economy are excluded). Thus, it is not possible after all to deny the steady weakening of
the creation of profit opportunities as a major trend. In addition, movements for each fiscal year
indicate that, when the gross negative effect grew larger (smaller) in size, the gross positive effectbecame smaller (larger), exerting a constant overall influence in the same direction. Rather thancreative destruction characterized by an expansion of both positive and negative, there seems to
be a strong possibility that fluctuations in cyclical demand are the primary cause14.
Fig. 2-8 Firm-based “Within-Between” Decomposition of Changes in Weighted
Average ROA of the Common Firms from the Previous Year
1.0
0.5
0.0
-0.5
-1.0
-1.5

between+crossbetween+cr

within

total

-2.0
81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99
FY

Average

Notes: 1. Refer to the notes of Fig. 2-1.
2. The change in weighted average ROA of the common firms from the previous year (total) is decomposed into
the contribution of the change in ROA for each firm from the previous year (“within” effect), contribution ofchange in total assets weight for each firm from the previous year (“between” effect) and the cross term of both(“cross”). In the charts, the “between” effect is shown aggregated with the cross term.

Based on the analysis of this section, it has been quantitatively supported that withinindustry disparities are more important than industry characteristics in inter-company disparities
13

Caballero and Hammour (1996) theoretically analyzed the efficiency of the process of creative destruction concentrated inperiods of recession when opportunity cost of resource reallocation is small and the possibility that such efficiency could behindered by a decentralized economy.
14
In spite of that, it should probably be borne in mind that there always were firm groups in existence that generate a positive“within” effect even in recessions.
22

Development Bank of Japan Research Report/No.23

and that expansions in inter-company disparities are generated as dynamism weakens.
Accordingly, in the next chapter, we will focus on the existence of the excess profit rate as animportant key when considering the way to improve such situations and elucidate its character
while analyzing the link to investment strategies.
Fig. 2-9 Firm-based “Within-Between” Decomposition of Changes in Weighted
Average ROA of the Common Firms from the Previous Year (Gross Effect)
(%)
1.5
1.0
0.5
0.0
-0.5
-1.0
wwithinithin プラス＋
wwithinithin マイナス
−

-1.5

betw
een +cro ss
between+cross
tototal
tal

-2.0
81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

年度 FY

平均
Average

Notes: 1. Refer to the notes of Fig. 2-1.
2. The difference in weighted average ROA of the common firms from the previous year (total) is decomposed into
the contribution of the difference in ROA for each firm from the previous year (“within” effect), contribution ofdifference in total assets weight for each firm from the previous year (“between” effect) and the cross term ofboth (“cross”). In the charts, the “within” effect is divided into gross positive and gross negative effect and the“between” effect is shown aggregated with the cross term.

Development Bank of Japan Research Report/No.23

23

III. The Nature and Background of Inter-Company ROA Disparities
1. Persistence of ROA Disparities
Based on the analyses of the previous chapter, it is probably easy to see that realizing an
improvement in the ROA of Japanese corporate sector overall or of specific industries is simply amatter of revitalizing dynamism that would continuously produce firms that create markets on
their own and earn excess profit (improvement of the “within” effect) and shifting assets overall
to firms that have high efficiency (positive “between” effect). Such arguments, however, only
have practical validity when the specific nature of that excess profit rate is clarified to a certain
extent.
Thus, in this chapter, we will first of all analyze the time-series character of the ROA
disparities that exist between firms to determine whether they are merely transitory or are
persistent. Though such analytical methods are well known in the field of traditional industrialorganization economics, their main concern rested on the persistence of the excess profit rate asa proxy variable of the degree of market competitiveness. In contrast, our goal in focusing on thepersistence of ROA disparities is to explore the intuition that, in light of the importance of intraindustry disparities in inter-company ROA disparities, highly profitable firms perhaps havecharacteristics in common in terms of management, regardless of what kind of industry they
belong to.
The framework for analysis is as given below1. First of all, excess profit rate Pit of Firm i in
Industry j at point in time t is defined as ROAit−ROA j. Next, suppose the time-series pattern ofexcess profit rate Pit is following the first order autoregressive process (AR(1)) indicated below
in common with each firm (partial adjustment model).
Pit º ai + bi･Pi,t−1 + uit................................................................................................. (6)In formula (6), a and b are parameters that assume different values depending on the firm
and u is an individual company (idiosyncratic) mutually non-correlated disturbance term withzero mean (white noise). If bi is within the range of –1 <bi < 1, long-term excess profit rate ofFirm i, PLRi º lim Pit, will converge to ai /(1- bi). Thus, once we obtain estimated values of aiｔ→∞and bi from the transitions in ROA of the 1,447 common firms over the twenty-year period since
FY 1980, as was also used in Chapter II, it becomes possible to calculate the long-term excess
profit rate extracted from historical data (implied PLRi). If a significant positive correlation isthen recognized between the implied PLRi and excess profit rate Pi0 at some initial point 0, it
could be considered there is persistence in ROA disparities.
The results of the estimation are indicated below. The estimated value of b fell within therange of 0≦bi < 1 (average 0.59), which, from a theoretical standpoint, can be considered themost natural outcome since it implies monotonous convergence to the implied P LRi.2 The
frequency distribution of the estimated value of b and value t is a indicated in Fig. 3-1. The
estimated value is significant at the 5% level in 80% of the firms. Meanwhile, it was not possible
to significantly discard the hypothesis that excess profit rates do not exist (equivalent to theindustry average profit rate) in 83% of the firms in which the estimated value of a is significant at
1
2

The framework below is based primarily on Odagiri and Yamawaki (1986, 1990).
Though there is convergence to the implied PLRi in the case of –1 < bi < 0, moving toward convergence while fluctuating
above and below the implied PLRi is somewhat unnatural as a movement of the firm profit rate.

24

Development Bank of Japan Research Report/No.23

the 5% level and in 74% of the firms even at the 10% level (Fig. 3-2). This instability of theestimation results is actually the same as in Odagiri and Yamawaki (1990) and other earlier
research, suggesting some possible limitations of this type of analysis. Nevertheless, in this study,
as in the earlier research, if the long-term excess profit rate obtained from these estimated values
has a clearly-defined relationship to the profit rate at the initial point in time, it is thought toindicate the existence of an economic factor that cannot be disregarded.
Accordingly, other than the ten firms in which the estimated value of b is 1 or more and theimplied PLRi explodes, when the implied PLRi is regressed to Pi0 (here, initial point 0 is theaverage of FY 1995-99), the following result is obtained (the figures in parentheses to the right ofthe estimated values are standard error).
implied PLRi = 0.0202(0.0835) + 0.9265(0.0272) Pi0
Fig. 3-1

R2=0.4470

Results of the Examination of Persistence of ROA Disparities (1)1. Frequency distribution of the estimatedvalue of b

2. Frequency distribution of t-value of theestimated value of b

350

1200

300

1000

250

800

200
600

150
400

100

200

50
0

0

〜0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1〜

Fig. 3-2

1.65

1.96
10%
significant

2.58
5%
significant

2.58〜
1%
significant

Results of the Examination of Persistence of ROA Disparities (2)1. Frequency distribution of the estimatedvalue of a

2. Frequency distribution of t-value of theestimated value of a

700

1200

600

1000

500

800

400
600

300
400

200

200

100

0

0
-5

-4

-3

-2

-1

0

1

2

3

4

5

5〜

1.65

1.96

2.58

2.58〜

10%
significant

5%significant

1%significant

Development Bank of Japan Research Report/No.23

25

The coefficient of determination is at a decent level as a cross-sectional estimation with allindustries pooled, and the estimated value of the coefficient of Pi0 suggest that the excess profit
rate observed on average in FY 1995-99 (corresponding to the profitability of each firm in recent
years) is maintained even in the long term at a ratio of about 90-95%3. In other words, a highlevel of persistence is recognized in ROA disparities.
Next, we will look at the relationship between the long-term excess profit rate and theexcess profit rate at the initial point (FY 1995-99 average) in eleven major industries (refer toTable 3-1). The industry with the lowest Pi0 coefficient is iron & steel at 0.56 and the highest ispharmaceuticals at 1.04. There are four industries that are above the coefficient when allindustries are pooled and seven that are below. Even when viewed by industry, a high level of
persistence is recognized in ROA disparities and this can be seen as results that indicate theimportance of disparities between firms within the same industry as also confirmed in theprevious chapter. In addition, compared to the results of analysis using the skyline charts ofChapter I again for manufacturing industries, there is an apparent tendency for the Pi0
coefficient of relatively robust industries such as foods, chemicals and pharmaceuticals to berelatively large and of stagnating industries such as iron & steel and general equipment to be small.
In other words, this suggests the possibility that a positive correlation, weak though it may be,
exists between industry ROA performance and the Pi0 coefficient, namely the level of
persistence of ROA disparities.
Though it is possible to make various theoretical interpretations of the persistence in ROA
disparities itself4, the positive correlation observed between industry average ROA and the Pi0
coefficient suggests that the existence of firms that maintain an excess profit rate supports thevitality of the industry overall. Accordingly, to wrap up the analysis of this study, we will
empirically clarify what kind of difference in investment strategies produce persistent ROA
disparities using the results of the Corporate Investment Attitude Survey released by theDevelopment Bank of Japan in October 1999.

3
4

With one standard error above and below the estimated value.
As stated previously, in research by Odagiri and Yamawaki (1986, 1990) and others in traditional industrial organization theory,
persistence of ROA disparities is interpreted to be a measure of the imperfectness of market competition. However, there
probably is not a large number of cases in which long-term monopolies, oligopolies, cartels, etc., have exerted a dominant
influence on profit rate disparities since the 1980s, the subject analysis term in this study (incidentally, the term of the analysesof Odagiri and Yamawaki (1990) was FY 1964-82).

26

Development Bank of Japan Research Report/No.23

Table 3-1 Estimation Results for Relationship Between Long-Term Excess Profit Rate
(Implied PLRi) and Excess Profit Rate Pi0 at the Initial Point (FY 1995-99 Average)

Estimated equation: implied PLRi = g + dPi0
Industry
Foods
Chemicals (excl. pharmaceuticals)
Pharmaceuticals
Iron & steel
General equipment
Electrical equipment
Automobiles (& automotive parts)
Construction
Specialized trading firms
RetailTransportation

Number ofobservations
91
102
32
53
154
131
73
120
72
48
95

Estimated value
of d
0.92
0.81
1.04
0.56
0.73
0.82
0.95
0.69
0.73
1.03
0.85

R2
0.70
0.70
0.83
0.54
0.59
0.67
0.64
0.61
0.69
0.93
0.67

Notes: 1. Refer to the main text for the definitions, data preparation methods, etc.
2. Two outliers in chemicals (excl. pharmaceuticals) were excluded from the estimation.

2. ROA Disparities and Investment Strategies
In the analysis in this section, we make use of the results of the Corporate Investment Attitude
Survey (“original survey”), a special survey of the Surveys of Planned Capital Spending (large
firms) by the Development Bank of Japan in 1999, as a variable relating to the investment
strategies of individual firms. It was conducted as an extremely wide-ranging survey for this typetargeting 3,302 firms with ¥1.0 billion or more in capital, excluding financial, insurance and someother industries, and responses were obtained from 2,113 firms, 64% of the target firms5. Thus,
when combined with listed company data based on the common firms through the previous
section, it is possible to use a sample consisting of 692 firms (427 manufacturing, 265 nonmanufacturing firms). Although investment strategies reflect only one aspect of the corporate
management, they appear to be quite suitable material for the analysis here since they areassociated with the most strategic decision-making process and the results are directly linked to
ROA.
Used below are ten items picked up from various questions of the original survey “II.
Investment decision-making criteria and their changes” and “IV. Points at issue in causes ofJapanese corporate investment acceleration in the 1980s.” Specifically, they are items (1) - (10)listed in Table 3-2. All of the questions involved a single choice of two alternatives and individual
responses were obtained of the one that applies (applied) to either of two points in time, namely,
the “present” (August 1999, when the survey was conducted) and during the 1980s.
The basic viewpoint in setting up the questions was the extraction of the intensity of
behavioral characteristics thought to have a strong relationship to so-called “Japanese-style”656Refer to the Development Bank of Japan (1999) for survey details and tabulated results.
Research relating to “Japanese-style management” and the “Japanese-style corporate system” includes a vast array ofcontentions centered on corporate governance and no consensus even exists regarding the basis for a strict definition of“Japanese-style.” For the definition of “Japanese-style management” elaborating on the intent of the results of the Corporate
Investment Attitude Survey, refer to Nakamura (2000), pp. 8-11, who surveyed research in this field and presented a series ofhypotheses thought to have suitable popularity as the “Japanese corporate image.”
Development Bank of Japan Research Report/No.23

27

management. It is possible to position choice 1 as a “Japanese” characteristic (an impression of
being inherently Japanese) and 0 as the opposite. Since data characteristics are best expressed in
the results of the cross tabulation with ROA in FY 1998 (targeting about 1,000 firms for which
ROA could be calculated in FY 1998) conducted by Nakamura (2000), those charts are
reproduced in Fig. 3-3. Among notable characteristics, it can be pointed out first of all that
overall changes in behavior were apparent that leaned toward the restraint of corporate
investment with a declining rate of selection of “bottom-up,” “addition of qualitative factors,”“pursuit of long-term profit,” “concern for balance between divisions” and “following/emulatingother firms” and an increasing rate of selection of “priority on certainty”7. Secondly, it can also be
pointed out as an important fact relevant to this study that such changes in behavior were
especially conspicuous in that group of firms with low ROA while, conversely, the group of firms
with high ROA did not considerably change the corporate investment behavior that could bereferred to as “Japanese-style” characterized by “pursuit of long-term profit” and “orientation
toward maintaining/expanding sales share”8.
Table 3-2
only)

Question Items in the Corporate Investment Attitude Survey (related items(1) Decision-making style regarding important investment projects
Top-down = 0, bottom-up = 1(2) Basic criteria for judgment in prioritizing investment projects
Based in principle on quantitative evaluation of investment profitability = 0, also considerable
addition of qualitative factors = 1(3) Quantitative evaluation criteria of investment profitability - time horizon
Priority on those with high growth rate = 1, priority on those with early improvement in returns=0(4) Quantitative evaluation criteria of investment profitability - attitude toward risk
Priority on those with high profits = 0, priority on those with high certainty = 1(5) Judgment criteria other than quantitative evaluation of investment profitability
If (2) is 0 = 0
If (2) is 1 with concern for balance between divisions = 1, if (2) is 1 and concentrate resources inpriority divisions = 0(6) Judgment criteria other than quantitative evaluation of investment profitability
If (2) is 0 = 0
If (2) is 1 and invest following/emulating other firms = 1, if (2) is 1 and follow own firm’s
investment criteria = 0(7) - (10) Causes of Japanese corporate investment acceleration in the 1980s (no = 0, yes = 1)(7) existence of a main bank, (8) existence of stable shareholders, (9) long-term business
relationships with business partners and clients, (10) orientation toward maintaining/expanding
sales or market share7

It is not clear of course whether or not these changes in behavior actually tend to “restrain” capital investments; however, suchinterpretation is made in this study based on the series of hypotheses relating to the capital investment behavior of Japanesefirms presented on pp. 8-11 of Nakamura (2000). This assumption, however, does not have any essential effect on thediscussion that follows.
8
For details, refer to Nakamura (2000), pp. 15-17.
28

Development Bank of Japan Research Report/No.23

Fig. 3-3 Cross Tabulation Results of the Attitude Survey and Financial Data (ROA in
FY 1998)a) Investment decision-making criteria and their changes
Bottom-up decision making
50

Addition of qualitative factors

Priority on growth
80

50

1980s
80 年
現
Present

70
40

40

60

1980s
80年
Present
現
30

30

Over
4%J4%

2%-4%
2〜 4

Less2%than
未 2%

Priority
確 実on ･certainty

50

Over
4%4%
J

2%-4%
2〜 4

Less
than 2%
2 %未

8 0年
1980s
現
Present

Over
4%4%
J

Concern 部
for balance
between divisions
門 間 バ ラ

2%-4%
2〜 4

Less
than 2%
2 %未Following/emulatingother firms
他 社 に 追
40

50

90

8 0年
1980s
現
Present

8 0年
1980s
現
Present

40

8 0年
1980s
Present
現

30

80

70

60

30

20

20

10

10

Over
4%4%
J

2%-4%
2〜 4

0
4 %J
Over
4%

Less2 than
%未 2%

2〜 4
2%-4%

2 %未
Less
than 2%Over
4 %J4%

2%-4%
2〜
4

Less
than 2%2% 未b)of Japanese
corporate
acceleration in the 1980sb Points
8 0 年 at代issueに in我causes
が 国
企 業 の
設 備 investment･
Main
メ イ bank
ン
60
50

Stable shareholders
安 定
30

70

Long-termbusiness
取 引
先 ・ relationships
顧 客
60

8 0年
1980s
現
Present

8 0年
1980s
現
Present

80 年
1980s
現
Present

40
20

30

50

20
10
0

10
4 %J4%
Over

2〜 4
2%-4%

2%than未 2%
LessOver4%
4%
J

2%-4%
2〜 4

Less2%than
未 2%

40

Over
4%J 4%

2%-4%
2〜
4

Less
than 2%
2 %未Sales or売market
上 ・ shareシ ェ orientation
ア ̀
90
80
80 年
1980s
現
Present70

横縦軸： 9 8 年 度 R
軸 ：
当 該 項

Horizontal axis: ROA for目FYF 1998 (%)
Vertical axis:
Rate of selection of the relevant item (%)

60
50

（ 備 考
意 of
識 the
調 attitude
査 結survey
果 は
、 日本
政策on
投 the
資 results
銀 行of ﾌNote:The）results
were
based
調 査 the報 “Corporate
告 （ 19 9 9Investment
年 8 月 調 Attitude査 ） Survey”
」
に in
おthe
け “Report
る 「 of ･
関 す theる Survey
意 識of調Planned
査 F Capital Spending for FY 1998, 1999 and2000” of the Development Bank of Japan.

Over
4%
4 %J

2%-4%
2〜 4

Less
than 2%
2 %未Development Bank of Japan Research Report/No.23

29

What this suggests is not the uniform evolutionary change in investment style commonlyreferred to as the switch “from Japanese-style to global standards” but rather the diversificationof choices within the elements of Japanese-style investment behavior and the disparities in asset
efficiency.
In this section, we will examine a hypothesis to explain disparities in ROA (excess profit
rate of each firm) in each decade by the difference in investment strategies adopted during the
1980s, which is expected to be true from the above point of view. The analytical procedure is as
given below. First of all, since an interpretation of the results of the estimation is far too complex
when behavioral characteristics encompassing all ten items in the original survey are used intact
as explanatory variables, we will summarize them into several factors using principal components
analysis9. In the analysis, we use data in which the response results as for investment strategies
adopted during the 1980s are converted to dummy variables. Next, we observe the correlation
between each principal component and the ten items in the original survey and profile theprincipal components. Finally, we regress the average excess profit rate of each firm to theprincipal component score (characteristics of investment strategies extracted from the attitude
survey) of the relevant firm for each of the five-year periods of the early 1980s (1980-84), late1980s – early 1990s (1988-92) and late 1990s (1995-99) and verify the hypothesis given above. To
confirm that the problem of sample bias does not exist, the ROA distribution for every five yearsof the 692 firms that were subjected to the analysis of this section and a comparison of the ROA
distribution in FY 1999 with the 1,447 common firms are shown in Fig. 3-4. Apparently, weobserve no divergence that would obstruct the analysis in any of them.
Fig. 3-4 Statistical Characteristics of the ROA of the 692 Firms that Responded to the
Attitude Survey

1. ROA frequency distribution of firms
2. Comparison of the ROA frequency
responding to the attitude survey for every 5
distribution in FY 1999 of firms responding
years
to the attitude survey and the common
firms(horizontal axis: ROA (%), vertical axis: relative frequency (%))

(horizontal axis: ROA (%), vertical axis: relative frequency (%))

20

20

80fy
85fy
90fy
95fy
99fy

15

Based on the (692) firms responding to
意識調査回答会社（
theattitude survey 692 社）ベース

15

Based
on the1,447(1,447)common firms
共通会社（
社）ベース

10

10

5

5

0

0

-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

22

24

25〜

-10

-8

-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

22

Notes: 1. Refer to the notes of Fig. 2-1.
2. Refer to the main text for the firms responding to the attitude survey.

9

Principal components analysis is an analytical procedure for minimizing the loss of information while summarizing andreducing the number of dimensions of the data by linearly combining multidimensional data taking correlations between
variables into account.

30

Development Bank of Japan Research Report/No.23

24

25〜

The results of analysis using the above method are as given below. First of all, the numberof principal components utilized was set at 4 taking into account eigen values and cumulative
contribution rate10 as well as the ease of interpretation (Table 3-3). Next, viewing the correlationof the four principal components and the ten items in the original survey (Fig. 3-5), principal
components no. 1 and 2 embody the shared characteristic of a strong correlation withcharacteristics other than the quantitative evaluation criteria of investment profitability (i.e.,
priority on balance between sectors and an orientation toward uniformity with other firms),
namely, the characteristic of discretionary investment behavior. In addition, principal component
no. 1 has a strong element of corporate investment promotion by Japanese-style corporate
governance, such as the existence of a main bank and stable shareholders, while principal
component no. 2 is weak in that respect (strong aspect of firms following their own judgment).
Next, it is evident by observing the correlation with characteristics other than the quantitativeevaluation criteria of investment profitability that principal components no. 3 and 4 embody thecharacteristic of non-discretionary investment behavior that places greater importance onquantitative evaluation than principal components no. 1 and 2. In addition, principal component
no. 3 has a strong correlation with such items as bottom-up investment decision-making, capital
investment promotion effect of sales or market share orientation and priority on certainty and it
projects the image of a large stable firm with “up the ladder” style white-collar management.
Principal component no. 4 is notable in the characteristics of top-down decision-making as well
as strong growth and profit rate orientations and it projects the image of a profit-seeking firm
under the leadership of owner-manager type of management. The investment strategies adopted
by each of the firms during the 1980s are characterized by the size of the point scores of thesefour principal components.
Table 3-3 Statistics of the Principal Components Utilized
Principal component no. 1
Principal component no. 2
Principal component no. 3
Principal component no. 4

Eigen value
1.88
1.54
1.05
1.02

Cumulative contribution rate
0.19
0.34
0.45
0.55

Table 3-4 indicates the results of the cross-sectional estimation in which the average excess
profit rate of each firm is regressed to the scores of the four principal components. It is evident
based on the results that the relationships indicated below exist between ROA disparities andinvestment strategies. First, focusing on the correspondence of the estimated values of thecoefficients, principal components no. 1 and 2 are constantly negative, while principal
components no. 3 and 4 are constantly positive. In other words, that means that, even in the early
1980s or the early 1990s when the Japanese economy remained robust, investment behavior thatwas discretionary in terms of asset efficiency was always surpassed by non-discretionary
investment behavior.

10

Eigen values indicate the volume of data (size of dispersion) explained by the relevant principal component and the cumulative
contribution rate indicates the extent of the data in the original data set that is covered when utilization is terminated as far as
the relevant principal component.
Development Bank of Japan Research Report/No.23

31

Fig. 3-5 Summarization of Characteristics of Investment Behavior During the 1980s by
Principal Components Analysis
Principal component no. 1
Bottom-up decision-making

型意思決定Top-downトップダウン
decision-making

Judgment by quantitative
factors
定量的要因で判断

Addition of qualitative factors
Priority on growth

早期収益改善重視
Priority on early improvement
in returns

Priority on certainty

Priority on highprofits
収益率重視
Concern for balance between
divisions(-)
部門間バランス配慮（-）

Concern for balance between divisions (+)
Following/emulating other firms (+)

Following/emulating他社に
other
随 firms (-)
追Investment promotion
byクが投資を
main bank(-)
メイン バン
促進（-）

Investment promotion by main bank (+)

Investment promotion安定株主
by stable shareholders (-)

Investment promotion by stable shareholders (+)

Investment promotion by long-termbusiness relationships (-)
長期的取引がInvestment promotion by long-term business relationships (+)

Investment promotion売上・シェア指向が投資をby sales or market share orientation
(-)
促進（-）

Investment promotion by sales or market share orientation (+)

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Principal component no. 2
Bottom-up decision-making

Top-down
decision-making
トップダウン型意思決定

Addition of qualitative factors

Judgment by quantitative
factors
定量的要因で判断
Priority on early improvement
in returns
早期収益改善重視

Priority on growth

Priority on highprofits
収益率重視

Priority on certainty
Concern for balance between divisions (+)

Concern for balance between
divisions(-)
部門間バランス配慮（-）

Following/emulating other firms (+)

Following/emulating
other
他社に
随 firms (-)
追メイン バン
促進（-）
Investment promotion
byクが投資を
main bank(-)

Investment promotion by main bank (+)

Investment promotion by stable shareholders (-)

Investment promotion by stable shareholders (+)

Investment promotion by long-term business relationships (-)

Investment promotion by long-term business relationships (+)

促進（-）
Investment promotion売上・シェア指向が投資をby sales or market share orientation(-)

Investment promotion by sales or market share orientation (+)

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Principal
no. 3
第 component
成分
Top-downトップダ
decision-making
ウン 型意思決定

Bottom-up decision-making
Addition of qualitative factors

Judgment by quantitative
factors
定量的要因で判断
Priority on early improvement
in returns
早期収益改善重視

Priority on growth

Priority on highprofits
収益率重視

Priority on certainty
Concern for balance between divisions (+)

Concern for balance between
divisions(-)
部門間バランス配慮（-）

Following/emulating other firms (+)

Following/emulating他社に
other
随 firms (-)
追Investment promotion
byクが投資を
main bank(-)
メイン バン
促進（-）

Investment promotion by main bank (+)

Investment promotion by stable shareholders (-)

Investment promotion by stable shareholders (+)

Investment promotion by long-term business relationships (-)

Investment promotion by long-term business relationships (+)

Investment promotion売上・シェア指向が投資をby sales or market share orientation
(-)
促進（-）

Investment promotion by sales or market share orientation (+)

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Principal component no. 4
トップダウン型意思決定
Top-down
decision-making

Bottom-up decision-making
Addition of qualitative factors

定量的要因で判断
Judgment by quantitative
factors

Priority on growth

早期収益改善重視
Priority on early improvement
in returns
収益率重視
Priority on highprofits

Priority on certainty

部門間バランス配慮（-）
Concern for balance between
divisions(-)

Concern for balance between divisions (+)

他社に随追Following/emulatingotherfirms (-)

Following/emulating other firms (+)

メイン バン クが投資を 促進（-）
Investment promotion
by main bank (-)

Investment promotion by main bank (+)

Investment promotion by stable shareholders (-)

Investment promotion by stable shareholders (+)

Investment promotion by long-term business relationships (-)

Investment promotion by long-term business relationships (+)

促進（-）
Investment promotion売上・シェア指向が投資をby sales or market share orientation(-)

Investment promotion by sales or market share orientation (+)

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

Note: The values on the horizontal axis indicate the degree of correlation of the principal component of the factors on theright-hand vertical axis.
32

Development Bank of Japan Research Report/No.23

Table 3-4 Estimation Results of the Correlation between Excess Profit Rate andInvestment Behavior (Principal Component no. 1 ~ 4)** = significant at 1%, * = significant at 5%

Dependent variable: Average excess profit rate FY 1980-84
Estimated value of coefficientt valuePrincipal
component no. 1▲0.490**2.69

Principal
component no. 2▲0.1140.50

Principal
component no. 3
0.511**
2.96

Principal
component no. 4
1.060**
3.92

Principal
component no. 3
0.143
1.02

Principal
component no. 4
0.137
0.63

Principal
component no. 3
0.263*
2.14

Principal
component no. 4
0.354
1.84

Dependent variable: Average excess profit rate FY 1988-92
Estimated value of coefficientt valuePrincipal
component no. 1▲0.476**
3.22

Principal
component no. 2▲0.221
1.21

Dependent variable: Average excess profit rate FY 1995-99
Estimated value of coefficientt valuePrincipal
component no. 1▲0.379**2.92

Principal
component no. 2▲0.1200.75

Especially, the estimated value of the coefficient of principal component no. 1, which
embodies discretionary investment behavior supported by Japanese-style corporate governancesuch as the main bank or stable shareholders, is significantly negative. Discretionary corporate
investment behavior supported by the main bank is generally considered to lag behind the times
as the result of changes in the environment in the 1990s when it was no longer possible toneglect global competition; it is evident based on the analysis of this section, however, that suchtendency had already emerged at least by the 1980s.
Next, turning attention to characteristics by period, it can be pointed out that therelationship between excess profit rate and investment strategies becomes generally less distinct(significant) around 1990, that is, the time of the bubble economy, than at other periods. The
profit rate essentially should have the functions of conveying the market evaluation of theoutcome of investment strategies and promoting efficiency through the reallocation of resources
and the revision of corporate investment strategies; the possibility has been pointed out, however,that the surge in asset prices, the prosperity of equity finance and other distortions caused by the
expansion of financial activities that are far apart from the real economy may have weakened thesignal function of profit rate.
It was possible to confirm the following points based on the analysis:
1. Though not all, a certain portion of inter-company disparities in ROA is explained bydifferences in investment strategies.
2. The diverging point of investment behavior that is critical in determining ROA disparities iswhether qualitative factors are added (discretionary) or not, namely the absolute priority on
quantitative evaluation (non-discretionary) and non-discretionary surpasses discretionary. In
this sense, the so-called “Japanese-style” management has not been effective since at least
the 1980s.

Development Bank of Japan Research Report/No.23

33

3.

11

In determining ROA disparities, it is not possible to tell which is the most outstanding of thecharacteristics of whether bottom-up or top-down, low-risk orientation (priority on
certainty) or high-return orientation (priority on profit rate) or whether or not there is a sales
or market share orientation. It is thought rather that multiple optimal solutions exist basedon business characteristics, conditions of competition, corporate governance and various
other factors and, in this respect, there were not any particular problems with “Japanesestyle” investment decisions11.

Based on the results of the cross tabulation of Nakamura (2000) reproduced in Fig. 3-3, this point is consistent with the factthat firms with favorable business performance have not necessarily changed their behavior in regard to bottom-up decisionmaking, pursuit of long-term profit, priority on certainty and an orientation toward maintaining and expanding sales or market
share. In contrast, points with a strong relationship to discretionary investment behavior, such as considerable addition ofqualitative factors, concern for balance between sectors and following/emulating other firms are moving toward decline without
regard to management performance.

34

Development Bank of Japan Research Report/No.23

Concluding Remarks -In pursuit of improvement in Japanese corporate ROAWe would like to give consideration finally to the direction for realizing improvement in the
ROA of Japanese corporations while referring back to the analyses thus far.
The results of the analysis of the microstructure of the persistent ROA decline indicate thatmovement toward the creation of profit opportunities has stagnated not only at the industry levelbut also at the firm level and that it is dominated by a major trend of overall deterioration. Even
taking into consideration the fact that the subjects of the analyses were listed companies at amature stage as corporations, these are results that give us a renewed awareness of the harshsituation Japanese corporations have been facing.
However, the true value of microstructure analyses, rather than confirming the harshsituation of Japanese firms, is utilizing them for the purpose of finding the first step toward a
breakthrough. What became clear as a result of the analyses in Chapter II of inter-company
disparities in ROA is that, rather than disparities based on industry characteristics, it is far more
important to attribute them to disparities between firms within the same industry, i.e., firmspecific factors such as investment strategies. It was also found that industries in which ROA
decline was relatively small maintained a broad right-hand tail (high ROA side) in the distribution
of ROA by firm. These facts when viewed from a different perspective indicate that, regardlessof the industry, there is potential for the continuous emergence of firms that acquire an excess
profit rate (creation of profit opportunities) and raise their ROA through competition or
innovation relating to corporate management. When expressing this process within theframework of “within-between” analysis, a virtuous cycle becomes apparent in which the positive
contribution of the gross positive “within” effect (creation of profit opportunities) first expands
and the gross negative “within” effect of firms that are affected by that (loss of profit
opportunities) is absorbed in the course of time by the positive contribution of the “between”
effect due to the reallocation of resources (ceaseless shift of resources toward relatively dominantfirms). Unfortunately, the current situation of listed companies in Japan is characterized byexpanding inter-company disparities due to the accelerating broadening of the left-hand tail ofthe distribution (loss of profit opportunities) within the context of a small gross positive “within”
effect with the level overall declining and, with the exception of a slightly positive “between”
effect, gives the appearance of a state of extreme opposites.
There is the argument that the forced exit of firms with poor performance should bepromoted in order to find a way to break with these circumstances. However, given the scarcity
of firms that are in a position to create profit opportunities and serve as absorbers for the assets
and employment of the firms that exit, that would require careful consideration. Though it isimportant of course to provide further for an environment (legal, taxation, flexibility of financial
and labor markets) that would allow a smooth exit from the market through M&As or the sale offirms and assets, in light of the current situation in which the persistence of the excess profit rate
has a positive correlation with industry ROA, stagnation in the creation of profit opportunities isseen to be a more fundamental issue. Aside from how the move toward acquisitions and capital
participation by foreign firms, which has been picking up speed in recent years, can be evaluatedin terms of accepting the task of maintaining and creating jobs in the domestic market, there is no
doubt that it is necessary to demand outstanding management whether domestic or foreign.
Meantime, the purpose of the analysis of Chapter III is to conduct the fact finding that isrequired for the purpose of promoting sound competition leading to the creation of profit
opportunities and for Japanese corporations not to lose sight of the path to proceed, focusing on
differences in investment strategies that have given rise to ROA disparities. Though signifying
nothing more than relative worth in the midst of overall decline, solid persistence was recognized
Development Bank of Japan Research Report/No.23

35

in ROA disparities and that was largely attributable to firm-specific factors. What becomes clear
as the background of ROA disparities is the fact that, whether or not absolute priority is placedon quantitative evaluations in corporate investment behavior is virtually the only factor that hascontinued to decide the outcome. The truth of the matter is that there has been no definite
tendency indicating which of the other factors are responsible for ROA disparities and thatmeans that there is a strong possibility that multiple optimal solutions exist based on firm
characteristics, conditions of competition, corporate governance and various other factors. Even
though “Japanese-style” management has been responsible for the decline in efficiency, in thesense of adding qualitative factors, the stereotypical idea that conventional investment judgments
and employee relations must all be discarded as so-called “global standards” are adopted is also a
misleading view and what is truly necessary now is a cool-headed and steady attitude to address
problems.
It has become evident recently that the penetration of corporate investment behavior basedon quantitative evaluation and the move toward restructuring operations and assets1 have beensteadily accelerating among Japanese corporations. It is anticipated that such changes in behavior
will lead to an improvement in aggregated ROA through ROA improvement of individual firms(enhancement of the “within” effect)2 and dynamism in resource allocation that expands the asset
share of firms that are the most highly efficient (“between” effect).
Junichi Nakamura (e-mail: junakam@dbj.go.jp)

1

Restructuring of assets referred to here does not of course mean the retirement of assets that have already become obsolete or
the unsubstantial shift of assets to the off-balance sheet such as those described in Chapter 1. It means finding buyers that are
more capable of managing the assets in question with greater efficiency than your own firm and enhancing your own ROA,
while shifting assets in a way that enhances asset efficiency for the economy as a whole.
2
From the perspective of creative destruction, there is also the approach, as indicated by Caballero and Hammour (1996), forexample, that the incompleteness of contracts between labor and management over the firm-specific investment causes
inefficiency and stagnation in innovation due to disparities between creation and destruction. We hope to deal with this issue in
future empirical analyses taking theoretical developments of recent years such as this into account.
36

Development Bank of Japan Research Report/No.23

Appendix – Correspondence between the industry classification used in the study
beginning in Chapter II and the industry classification of the Development Bank ofJapan (mid- and sub-categories)
Code
000100000300000700000900001100001160001300001500001700001900002100002300002500002700002910002900003100009110000500009120009130009140009150009160009190010100010500020100030100030300039100040110040100040310040320040390040330060100070100070300070500070700070900071100071300071500090510080110080310090100090300050190090700090990091100091312091500092100099100Development Bank of Japan classification (mid- and sub- categories)
Industry
Foods
TextilesPaper & pulp
Publishing & printing
Chemicals *1
Pharmaceuticals
Oil refining
Rubber products
Ceramic, stone & clay products
Iron & steel
Nonferrous metals
Metal products
General equipment
Electrical equipment
Automobiles & automotive parts
Transport equipment *2
Precision equipment
Plastic products
Lumber & wood products
Leather products
Furniture & fittings
Other petroleum products
Coal products
Weaponry
Other manufacturing industries
Agriculture
Fisheries, marine & aquaculture
Mining
Civil engineering and construction
Dredging
Other (construction)
General trading firms & commodity sales
Wholesale *3
Department stores
Supermarkets
Other retailRestaurant operators
Real estate
Rail roads
Roadway passenger transport
Roadway cargo transport
Shipping
Airlines
Warehousing
Other transportation-related
Communication
Private sector broadcasting
9 electrical powerGas supply
HotelsAmusement services
Money lending, etc.
Automobile-related services
Other rental & leasing
Medical treatment
Research institutes
Information services
Leasing
Other services

Corresponding industry
classification in the study
1
3
7
9
11
12
13
15
17
19
21
23
25
27
29
30
31
32
91
91
91
91
91
91
91
101
101
101
301
301
301
401
402
403
403
403
404
601
701
701
701
701
701
701
701
715
715
801
801
901
903
991
991
991
991
991
991
991
991

Development Bank of Japan Research Report/No.23

37

Code
1
3
7
9
11
12
13
15
17
19
21
23
25
27
29
30
31
32
91
101
301
401
402
403
404
601
701
715
801
901
903
991

Industry classification used in the study
Industry
Foods
TextilesPaper & pulp
Publishing & printing
Chemicals (excluding pharmaceuticals)
Pharmaceuticals
Oil refining
Rubber products
Ceramic, stone & clay
Iron & steel
Nonferrous metals
Metal products
General equipment
Electrical equipment
Automobiles (& automotive parts)
Other transport equipment
Precision equipment
Plastic products
Other manufacturing industries
Agriculture, forestry, fisheries & mining
Construction
General trading firms
Specialized trading firms
RetailRestrant
Real estateTransportation
Communication & broadcastingElectricity & gas supply
HotelsAmusement services
Other services

Notes: 1. Excluding pharmaceuticals (001160)
2. Excluding automobiles & automotive parts (002910)
3. Excluding general trading firms & commodity wholesales (040110)

38

Development Bank of Japan Research Report/No.23

References(In Japanese)
Development Bank of Japan, 1999. “1998･1999･2000 nendo Setsubi Toshi Keikaku Chosa
Hokoku (Survey on Planned Capital Spending for Fiscal Years 1998, 1999 and 2000),”
Chosa 2 (October).
Kurosawa, Y. and Wakasugi, T. 1982. “Business Risk to Shihon Kosei (Business risk and capitalcomposition),” Keizai Keiei Kenkyu 3-1, Research Institute of Capital Formation, Japan
Development Bank.
Maeda, E. and Yoshida, K. 1999. “Shihon Koritsu wo Meguru Mondai ni Tsuite (Problems
relating to capital efficiency),” Chosa Geppo (October), pp. 27-53, Bank of Japan.
(In English)
Caballero, R. J., and M. L. Hammour, 1996. “On the Timing and Efficiency of Creative
Destruction,” Quarterly Journal of Economics, 111(3), pp. 805-852.
Haltiwanger, J. C., 1997. “Measuring and Analyzing Aggregate Fluctuations: The Importance of
Building from Microeconomic Evidence,” Federal Reserve Bank of Saint Louis Review
May/June.
Haltiwanger, J. C., 2000. “Aggregate Growth: What Have We Learned from Microeconomic
Evidence?,” OECD Economics Department Working Papers, 267.
Nakamura, J., 2001. “Empirical Reassessment of Japanese Corporate Investment Behavior:
Features and Changes since the 1980s, based on Micro-level Panel Data,” DBJ Research
Report 12 (March).
Odagiri, H., and H. Yamawaki, 1986. “A Study of Company Profit-rate Time Series: Japan andthe United States,” International Journal of Industrial Organization, 4: 1986, pp. 1-23.
Odagiri, H., and H. Yamawaki, 1990. “The Persistence of Profits in Japan,” in D.C. Mueller eds.
“The Dynamics of Company Profits an International Comparison,” Cambridge University Press,
Chapter 8.
Tanaka, K., 2000. “Job Creation and Job Destruction in Japan, 1978 – 1998: An Empirical
Analysis Based on Enterprise Data,” DBJ Research Report 10 (September).

Development Bank of Japan Research Report/No.23

39

List of Back Numbers (Including JDB Research Report)
No. 23 Microstructure of persistent ROA decline in the Japanese corporate sector: Inter-company disparities andinvestment strategies (this issue)
No. 22 Recent Trends in the Japanese Economy: The Japanese Economy under Deflation and Prospects ofEvolution, February 2002
No. 21 Survey on Planned Capital Spending for Fiscal Years 2000, 2001 and 2002, December 2001
No. 20 Current Situation and Challenges for Cable Television in the Broadband Era, October 2001
No. 19 Recent Trends in the Japanese Economy: The Japanese Economy under Deflation, August 2001
No. 18 Introduction of a Home Appliance Recycling System: Effects & Prospects: Progress towards Utilisation of
Recycling Infrastructure, June 2001
No. 17 Survey on Planned Capital Spending for Fiscal Years 2000 and 2001, June 2001
No. 16 Revitalization of Middle-aged and Elderly Workers in Japan’s Labor Markets: Requiring the Expansion of
the Vocational Training Functions, March 2001
No. 15 Risk-Averting Portfolio Trends of Japanese Households, March 2001
No. 14 Consumption Demand Trends and the Structure of Supply: Focus on Retail Industry Supply Behavior,
March 2001
No. 13 Recent Trends in the Japanese Economy: Weakness of Current Economic Recovery and Its Background,
March 2001
No. 12 Empirical Reassessment of Japanese Corporate Investment Behavior: Features and Changes since the 1980s,
based on Micro-level Panel Data, March 2001
No. 11 Survey on Planned Capital Spending for Fiscal Years 1999, 2000 and 2001, October 2000
No. 10 Job Creation and Job Destruction in Japan, 1978-1998: An Empirical Analysis Based on Enterprise Data,
September 2000
No. 9

Recent Trends in the Japanese Economy: Information Technology and the Economy, September 2000

No. 8

Trend of International Reorganization Affecting the Japanese Automobile and Auto Parts Industries, June
2000

No. 7

Survey on Planned Capital Spending for Fiscal Years 1999 and 2000, June 2000

No. 6

Current Status and Future Perspective of the Japanese Remediation Industry: Technology and Market for
Underground Remediation, May 2000

No. 5

Recent Trends in the Japanese Economy: The 1990s in Retrospect, March 2000

No. 4

Destabilized Consumption and the Post-bubble Consumer Environment, February 2000

No. 3

The Slump in Plant and Equipment Investment in the 1990s: Focusing on Lowered Expectations, the Debt
Burden and Other Structural Factors, January 2000

No. 2

Survey on Planned Capital Spending for Fiscal Years 1998, 1999 and 2000, November 1999

No. 1

Corporate Strategies in Japan’s Semiconductor Industry: Implications of Development in Other AsianCountries, November 1999

JDB Research Report

No. 96 Recent Trends in the Japanese Economy: Focused on Fixed Investment and Capital Stock, August 1999

No. 95 Efforts to Protect the Natural Environment in the United States and Germany: Environmental Mitigation
and Biotope Conservation, July 1999
No. 94 Survey on Planned Capital Spending for Fiscal Years 1998 and 1999, June 1999
No. 93 Towards the realization of ‘environmental partnership’: A survey of Japan’s environmental NPO sector
through comparison with Germany, June 1999
No. 92 The Impact of Demographic Changes on Consumption and Savings, March 1999
No. 91 Recent Research and Development Trends in Japanese Enterprises: Technology Fusion, March 1999
No. 90 Recent Trends in the Japanese Economy: Prolonged Balance Sheet Adjustment, January 1999
No. 89 Impact of Asset Price Fluctuations on Household and Corporate Behavior: A Comparison between Japanand the U.S., December 1998
No. 88 Survey on Planned Capital Spending for Fiscal Years 1997, 1998, and 1999, December 1998
No. 87 Foreign Exchange Rate Fluctuations and Changes in the Input-Output Structure, November 1998
No. 86 Structural Changes in Unemployment of Japan: An Approach from Labor Flow, November 1998
No. 85 Recent Trends in the Japanese Economy: Characteristics of the Current Recession, August 1998
No. 84 R&D Stock and Trade Structure in Japan, August 1998
No. 83 Survey on Planned Capital Spending for Fiscal Years 1997 and 1998, August 1998
No. 82 The Significance, Potential, and Problems of DNA Analysis Research: Establishing Public Acceptance isEssential, May 1998
No. 81 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1996, 1997 and 1998
Conducted in August 1997, March 1998
No. 80 Recent Trends in the Japanese Economy: Growth Base of the Japanese Economy, January 1998
No. 79 Information Appliances: The Strength of Japanese Companies and Tasks for the Future, January 1998
No. 78 Challenges and Outlook for the Japanese Machinery Industries: Impact of ISO14000 Series andEnvironmental Cost, January 1998
No. 77 Current Conditions and Issues of Computerization in the Health Care Industry: For the Construction of a
Health Care Information Network, January 1998
No. 76 Household Consumption and Saving in Japan, December 1997
No. 75 The Direction of Japanese Distribution System Reforms: Strengthening the Infrastructure to Support
Diverse Consumer Choices, November 1997
No. 74 Foreign Direct Investments by Japanese Manufacturing Industries and Their Effects on International Trade,
October 1997
No. 73 The Impact of the Changing Trade Structure on the Japanese Economy: With Special Focus on the Effects
on Productivity and Employment, October 1997
No. 72 An Analysis of Foreign Direct Investment and Foreign Affiliates in Japan, August 1997
No. 71 Recent Trends in the Japanese Economy: Stock Replacement and New Demand as Aspects of Economic
Recovery, August 1997
No. 70 Corporate Fundraising: An International Comparison, June 1997
No. 69 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1996 and 1997
Conducted in February 1997, May 1997
No. 68 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1996 and 1997
Conducted in August 1996, August 1997

No. 67 An International Comparison of Corporate Investment Behavior: Empirical Analysis Using Firm Data
from Japan, France and the US, April 1997
No. 66 Housing in the National Capital: Analysis of the Market for Housing using Micro Data, March 1997
No. 65 The Environment for Locating Business Operations in Major East Asian Cities, January 1997
No. 64 Direction of Reconstruction of Business Strategy in the Chemical Industry, January 1997
No. 63 Reflection on Discussions Concerning Regulation of the Electric Power Industry: Deregulation of theElectric Power Industry in Japan and Implication of Experiences in the United States, December 1996
No. 62 Current Status and Future Perspective of the Japanese Semiconductor Industry, November 1996
No. 61 A Breakthrough for the Japanese Software Industry?: Responsiveness to Users’ Needs is the key, October
1996
No. 60 Recent Trends in the Japanese Economy Focusing on the Characteristics and Sustainability of the Current
Economic Recovery, September 1996
No. 59 Analysis of the Primary Causes and Economic Effects of Information: Related investment in the UnitedStates and Trends in Japan, August 1996
No. 58 Selected Summaries of Research Reports: Published in FY1995, June 1996
No. 57 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1995 and 1996
Conducted in February 1996, May 1996
No. 56 Recent Trends in the Japanese Economy, May 1996
No. 55 Issues Concerning the Competitiveness of the Japanese Steel Industry, February 1996
No. 54 Changes in the Financial Environment and the Real Economy, January 1996
No. 53 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1994, 1995 and 1996
Conducted in August 1995, October 1995
No. 52 Current Economic Trends: Focusing on the Appreciation of the Yen and its Effects, October 1995
No. 51 Problems Concerning the International Competitiveness of the Petrochemical Industry, October 1995
No. 50 An Economic Approach to International Competitiveness, October 1995
No. 49 Selected Summaries of Research Reports Published in FY1994, July 1995
No. 48 Strategies for Improving the Efficiency of the Japanese Physical Distribution System: Part 2, July 1995
No. 47 Issues on International Competitive Strength of the Auto Industry, June 1995
No. 46 Problems Concerning the International Competitiveness of the Electronics and Electric Machinery
Industry, June 1995
No. 45 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1994 and 1995
Conducted in March 1995, June 1995
No. 44 Strategies for Improving the Efficiency of the Japanese Physical Distribution System, March 1995
No. 43 Capital Spending Recovery Scenario Cycle and Structure, August 1994
No. 42 Progress of International Joint Development between Industrialized Countries on the Private Level, May
1994
No. 41 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1993, 1994 and 1995
Conducted in August 1994 , November 1994
No. 40 Selected Summaries of Research Reports Published in FY1993, June 1994
No. 39 Recent Trends in Japan’s Foreign Accounts, April 1994

No. 38 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1993 and 1994
Conducted in March 1994, April 1994
No. 37 Economic Zones and East Asia Prospect for Economic Activity Oriented Market Integration, December
1993
No. 36 Japanese Corporate Responses to Global Environmental Issues, December 1993
No. 35 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1992, 1993 and 1994
Conducted in August 1993, September 1993
No. 34 Structure of Profit to Capital in the Manufacturing Industry, September 1993
No. 33 Comparison of the Japanese and The U.S. Labor Markets, October 1992
No. 32 The Relative Competitiveness of U.S., German, and Japanese Manufacturing, March 1993
No. 31 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1992 and 1993
Conducted in March 1993, April 1993
No. 30 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1991, 1992 and 1993
Conducted in August 1992, December 1992
No. 29 Flow of Funds in the 80s and Future Corporate Finance in Japan, November 1992
No. 28 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1991 and 1992
Conducted in February 1992, April 1992
No. 27 An Analysis of Foreign Direct Investment in Japan, March 1992
No. 26 Projection of Japan's Trade Surplus in 1995: Analysis of Japan's Trade Structure in the 80s, February 1992
No. 25 Intra-Industry Trade and Dynamic Development of The World Economy, November 1991
No. 24 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1990, 1991 and 1992
Conducted in August 1991, September 1991
No. 23 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1990 and 1991
Conducted in February 1991, March 1991
No. 22 Trends of the Petrochemical Industry and its Marketplace in East Asia, March 1991
No. 21 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1989, 1990 and 1991
Conducted in August 1990, September 1990
No. 20 Deepening Economic Linkages in The Pacific Basin Region: Trade, Foreign Direct Investment andTechnology, September 1990
No. 19 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1989 and 1990
Conducted in February 1990, March 1990
No. 18 Petrochemicals In Japan, The US, and Korea an Assessment of Economic Efficiency, February 1990
No. 17 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1988, 1989 and 1990
Conducted in August 1989, October 1989
No. 16 Impact of the EC Unification on Japan’s Automobile and Electronics Industries, August 1989
No. 15 Industrial and Trade Structures and the International Competitiveness of Asia’s Newly Industrializing
Economies, August 1989
No. 14 The Japan Development Bank Reports on Capital Investment Spending: Survey for Fiscal Years 1988 and1989 Conducted in February 1989, March 1989
No. 13 The Japan Development Bank Reports on Capital Spending: Survey for Fiscal Years 1987, 1988 and 1989
Conducted in August 1988, September 1988

No. 12 Growing Foreign Investors’ Activities and the Future of Internationalization, September 1988
No. 11 Futures Tasks and Prospects for the Japanese Machine-Tool Industry, July 1988
No. 10 International Division of Labor in the Machine Industries Among Japan, Asia’s NICs and ASEANCountries, June 1988
No. 9

Trends of the Petrochemical Industry and its Marketplace in East Asia around Japan, May 1988

No. 8

The International Competitiveness of Japan and U.S. in High Technology Industries, April 1988

No. 7

The Japan Development Bank Reports on Private Fixed Investment in Japan, March 1988

No. 6

Economic Projections of the Japan’s Economy to the Year 2000, February 1988

No. 5

The Japan Development Bank Reports on Private Fixed Investment in Japan, September 1987

No. 4

Current Trends in the Japanese Auto Parts Industry in Overseas Production, July 1987

No. 3

Current Moves for Foreign Direct Investment into Japan, May 1987

No. 2

Overseas Direct Investments by Japanese Corporations, May 1987

No. 1

Current U.S. Consumption Trends, May 1987