Development Bank of Japan
Research Report
No. 12

Empirical Reassessment of Japanese Corporate
Investment Behavior:
Features and Changes Since the 1980s,
Based on Micro-level Panel Data

March 2001

Economic and Industrial Research Department
Development Bank of Japan

Contents

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

Background and Evidence from Aggregated Data .......................................................3
1. Three Phases of Business Fixed Investment Fluctuations Since the 1980s ........................ 3
2. ROA and Business Fixed Investment Fluctuations ................................................................ 4

II Basic Concepts and Data Sets .......................................................................................7
1. Theoretical Background .............................................................................................................. 7
1.1 Fundamentals and Non-fundamentals in Investment Decision-making .................. 7
1.2 Hypotheses on Japanese Corporate Investment Behavior.......................................... 8
2. Characteristics of Micro-level Data Sets.................................................................................11
2.1 Analytical Subjects...........................................................................................................11
2.2 Constructing the Basic Data Set from Corporate Financial Data............................12
2.3 Generating the Combined Data Set by Adding Results of Corporate Investment
Attitude Survey ................................................................................................................13
3. Evidence from Cross-tabulation of Financial Data and Survey Results............................15
III Panel Data Estimation of Micro-level Investment Equations .................................... 19
1. Specification of the Empirical Model and Estimation Methods.........................................19
1.1 Basic Framework of the Empirical Model...................................................................19
1.2 Selection of Fundamental Explanatory Variables Fi ..................................................20
1.3 Selection of Non-fundamental Explanatory Variables Ni .........................................21
1.4 Estimation Methods for Panel Data.............................................................................22
2. Estimation Results Using the Basic Data Set and Its Interpretation..................................24
2.1 Increasing Sensitivity to ROA .......................................................................................25
2.2 Uniqueness of Investment Behavior in Phase 2 .........................................................27
2.3 Testing the Existence of Internal Funds Effect..........................................................27
2.4 Interpretation of the Coefficient on Corporate Age..................................................30
2.5 Comparison of Manufacturers and Non-manufacturers ...........................................30
3. Estimation Results Using the Combined Data Set and Its Interpretation ........................30

Development Bank of Japan Research Report/ No. 12 i

3.1

Testing Hypotheses on Japanese Style of Investment
Decision-making Criteria................................................................................................30
3.2 Testing Hypotheses on Influence of Japanese Style ofCorporate Governance on Investment ........................................................................32
Supplement: Testing the Existence of Free Cash Problem .................................................32
Conclusion .......................................................................................................................... 35
References........................................................................................................................... 37

ii

Development Bank of Japan Research Report/ No. 12

Empirical Reassessment of Japanese Corporate Investment Behavior:
Features and Changes Since the 1980s, Based on Micro-level Panel Data
Summary
1. Compared to GDP, business fixed investment generally shows greater volatility, but in theJapanese economy of the 1980s investment displayed stable high growth, particularly in the
expansion years of the Bubble economy. To explain such unique investment dynamics, there wasmuch debate on the existence of so-called “Japanese-style enterprise behavior,” mainly in thesense that it must have been a source of competitive strength. After the Bubble burst, however,such views disappeared, and it is naively believed that Japanese corporate investment behavior
has been switching toward the strict pursuit of capital efficiency. This report empiricallyreexamines the various points debated on Japanese corporate investment behavior, based on thelatest micro-level panel data. The data sets used here include not only financial data but also theresults of the “Corporate Investment Attitude Survey” released by The Development Bank ofJapan in October 1999, which enriches our analysis. Analyzing the period of approximately 20
years from a consistent viewpoint, we will find some new evidence on the features of andchanges in corporate investment behavior since the 1980s.
2. Observing investment fluctuations in the Japanese economy in the last two decades, we
discern three phases: The first, to around 1986, displayed relatively stable moderate growth; thesecond, from 1987 to around 1992, saw a double-digit boom over roughly three years out of five;and the third, starting after 1993, was characterized by two large declines and instability, with nodiscernible upward trend.
3. Based on the Financial Statement Statistics of Corporations, we find a sharp divergence fromthe balanced growth path of assets, sales and profits since around the end of Phase 2, whichmeans a substantial and prolonged decline in capital efficiency (i.e. ROA, or return on assets).
Although the investment to capital stock ratio in principle has been closely correlated with ROA,
it was relatively more stable than ROA in Phase 1, but in Phase 2 it grew far faster than ROA. As
for the balance sheet structure, the ratio of liquidity to capital stock grew strongly in Phase 2.
This suggests that abundant liquidity on hand promotes excessive investment and invites a
decline in capital efficiency as a result.
4. According to the “Corporate Investment Attitude Survey,” fewer firms focused on the
pursuit of long-term profits, and following and emulating other companies as criteria forinvestment decision-making, while more firms put stress on certainty, compared to the situationin the 1980s. Fewer firms cited maintenance and expansion of sales and market share as thereasons for investment acceleration. These results reveal an overall shift toward holding back on
investment, and combining the survey results with financial data, such a shift is far more evident
for low ROA firms and high debt-equity ratio firms. In other words, major differences ininvestment behavior result from differences in management performance and financial
conditions, again as compared to the 1980s.

Development Bank of Japan Research Report/ No. 12 iii

5. Using micro-level financial data of listed or publicly traded companies in the years from FY
1980 to FY 1998, we carry out panel data estimation of micro-level investment equations
respectively for each of the three periods: FY 1982-86 (corresponds to Phase 1), FY 1988-92(Phase 2) and FY 1994-98 (Phase 3). The estimation results show two major features and changes
in corporate investment behavior since the 1980s. First, the coefficient on ROA was always
positive and statistically significant throughout the 1980s and thereafter, and its value grewsignificantly period by period, indicating that Japanese corporations’ investment behavior became
increasingly focused on capital efficiency. Second, the estimation result of Phase 2 is clearly
different from those of other periods. Specifically, the coefficient on sales growth rate, which was
positive and statistically significant in other periods, turns out to be not significant, and neither
was the coefficient on debt-equity ratio, which was negative and statistically significant in otherperiods. Instead, the value of the coefficient on liquidity to capital stock ratio (positive andstatistically significant in all periods) was far above those of the other periods, suggesting thatinvestment was driven by abundant liquidity and diverged somewhat from fundamentals.
6. Next, we carry out another series of estimations by coupling the “Corporate Investment
Attitude Survey” data to financial data, with the following key results. First, the coefficient on“Stress on certainty” as a dummy variable was negative and statistically significant in all periods,
with no significant differences in the absolute value of the coefficient. In Phase 3, rather morecompanies attached importance to certainty, and this emphasis on certainty has tended tosuppress investment. Second, the coefficient on “Following and emulating other companies” as adummy variable was positive and statistically significant in Phases 1 and 2, but its influence
disappeared in Phase 3. Third, the coefficient values of the liquidity to capital stock ratio and thedebt-equity ratio of companies that cited main banks and cross shareholdings as reasons foraccelerating investment had no significant differences in any period compared with those ofcompanies that did not cite these reasons. We therefore believe that these Japanese style ofcorporate governance factors had no influence, neither positive nor negative, on investment
behavior during and after the 1980s.
7. In conclusion, leaving aside the special differences of Phase 2, it is found that Japanese
corporate investment behavior over the time horizon of this report, centering on listed or
publicly traded companies, tended to sensitively reflect disparities and changes in capitalefficiency, and there was a structural strengthening of emphasis on the likelihood of recouping
investment. Against a background of stiffening global competition and merciless market
evaluations on management performance and financial condition, we believe that such changes
will surely accelerate in the future. The transition process toward investment behavior that
pursues capital efficiency and certainty simultaneously tends to suppress investment anddestabilize it on the macroeconomic level, but if Japanese corporations successfully link it withsteady structural improvements, we anticipate that over the intermediate to long term, this willlead to expanded investment in growth fields.

iv Development Bank of Japan Research Report/ No. 12

Introduction
In the Japanese economy of the 1980s and 1990s,1 there were great changes in macro-level
patterns2 of fluctuation in business fixed investment, and the widely-held views on Japanese
corporate investment behavior changed substantially. In the 1980s, investment that usually tends
to show high volatility relative to GDP trended steadily upward, and particularly in the Bubble
era’s expansionary period it attracted worldwide attention because of its high rates of growth thatclosely resembled those of the postwar high growth era. The situation triggered much discussion
about Japanese-style investment behavior, to the effect that Japanese corporations do not worry
overly about their current business conditions, but invest aggressively for the long term. It also
attracted much interest in Japan’s unique style of corporate governance, symbolized by the mainbank system and the role of inter-corporate relationships underlying the aggressive investment
behavior. However, the state of the economy changed completely after the Bubble burst:
investment became erratic and entered a two-stage full-scale contractionary phase, causing the
economic recession to deepen more than expected. As a result, there has been almost no
discussion of Japan’s unique characteristics in recent years; as worldwide competition intensifies
and the market principle becomes entrenched, Japanese corporate investment behavior appears
to be changing course toward stricter pursuit of capital efficiency.
Whether or not these changes are actually occurring is important in considering the future
direction. But because the principal concern of empirical research has heretofore been theexistence or otherwise of Japanese uniqueness, beginning with the effect of the main bank system,
we believe that there has been insufficient examination of changes in investment behavior overtime.3 This report sets out to reorganize the various points of arguments developed on an ad hoc
basis to date; investigates the features and changes in investment behavior over our time horizon
with regard to Japanese uniqueness; and subjects the content and periods to a detailed empiricalanalysis. To that end, we will estimate investment functions by time period based on large-scale
panel data constructed from financial data on about 2,800 listed or publicly traded companies andthe results of the “Corporate Investment Attitude Survey” released by the Development Bank ofJapan in October 1999.
This report is structured as follows. In Chapter 1, we will indicate the three phases into
which macro-level patterns of investment fluctuation can be divided since the 1980s, and fromaggregated corporate financial data, deduce the changes in investment behavior over time.
Chapter 2 presents the theoretical backgrounds and establishes hypotheses related to Japaneseuniqueness and its changes over time. We will also explain the construction and characteristics ofour data set, and review the implications of cross-tabulation results of financial data and theattitude survey. Using these data sets, Chapter 3 estimates investment equations for each of
Chapter 1’s three phases. As a result, we will show that (1) Japanese corporate investment
behavior from the 1980s has undergone continual structural change stressing pursuit of capitalefficiency and certainty, (2) abundant liquidity almost caused the famous free cash problem
discussed by Jensen (1986) during the Bubble era, in other words liquidity-driven investment
diverged from fundamentals, and (3) Japanese style of corporate governance – the main bank1

2

3

Although the division here is a matter of convenience in a sense, it is used in this analysis to denote the end of the high growth
period and a period of continuity to the present. We can also refer to Yoshikawa’s (1992) division of the postwar Japanese
economy into four periods: (1) Recovery (1945-55), (2) high growth (1955-70), (3) adjustment (1970-80) and (4) present stage(1980-).
In the discussion that follows, as to investment fluctuations over time we are assuming the existence of a fixed patterncharacterized by average and standard deviation in the time series of growth rate for each period selected appropriately.
The issue of whether any Japanese uniqueness exists has not been resolved yet. Refer to Chapter 2 for future research.
Development Bank of Japan Research Report/ No. 12 1

system and stable stockholding – has had no influence on investment over our time horizon. In
the final section, we present our conclusions based on all of the preceding discussions.

2

Development Bank of Japan Research Report/ No. 12

I Background and Evidence from Aggregated Data
1. Three Phases of Business Fixed Investment Fluctuations Since the 1980s
As the premise of our analysis of investment behavior based on micro-level data, we outline thepatterns of fluctuation in investment over our time horizon based on macroeconomic statistics,
and consider the special characteristics of each decade.
Figure 1-1 displays quarterly trends in real GDP growth rates and the degree of contributionof each demand item, derived from the Annual Report on National Accounts.4 Singling out theinvestment contribution, there were almost no negatives in the 1980s, but from 1988 to around1990 there was an extended plateau that turned down in the 1990s and trended lower in two
broad stages that caused GDP to fall.
Taking business cycle peaks and valleys into consideration, this report classifies theinvestment fluctuation patterns over the two decades into the following three phases: The first(1980 to around 1986) was one of relatively stable moderate growth; the second (1987 to around1992) was characterized by about three years of double-digit investment boom; and the third(after 1993) saw a two-stage major decline to unstable low levels.5 If we combine the average
growth rates and standard deviations of the three phases in fixed periods and express thembroadly, we arrive at Table 1-1.
Figure 1-1. GDP Growth Rates and Investment Contributions
(%)
10

5

0

-5
80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

00

(Calendar Year Quarters)
実質ＧＤＰ前年同期比Real
GDP YtoY % Change
民間内需の寄与度
Contributionof Private Sector
Domestic Demand

Source:Contributionof Investment
設備投資の寄与度
公的需要・外需(純輸出)の寄与度
Contributionsof Public Sector Demand and External
Demand (Net Exports)

Cabinet Office’s “Annual Report on National Accounts,” 1990 basis

Table 1-1. Trends in Macroeconomic Investment Fluctuation Patterns
Average Growth Rate
Standard Deviation of Growth Rate

Period 1
Moderate
Low

Period 2
High
Low (to high)Period 3
Low
High

4

The growth rate and degree of contribution are year-to-year comparisons. The same applies hereinafter unless otherwise
specified.
5
The second phase coincides largely with what is generally called the “Bubble era” or “Bubble economy.” But because ouranalysis does not focus on the effects of asset price variations we use a neutral designator to avoid preconceptions.
Development Bank of Japan Research Report/ No. 12 3

2. ROA and Business Fixed Investment Fluctuations
Keeping in mind the three phases related to investment fluctuation patterns, we now consider thechanges over time in investment behavior since the 1980s, based on the corporate sector’saggregated financial indicators.
Figure 1-2 indexes on a real basis assets, sales and profit growth to 1979, based on Financial
Statement Statistics of Corporations. As our concept of profit corresponding to total assets, wetake recurring profits before interest payments6, with the comparison between the two equivalent
to ROA (return on assets, the ratio of profits to total assets). According to the figure, total assets,
sales and profit grew in general balance with each other up to the second half of Phase 2, butfrom the end of that phase to the early stage of Phase 3, sales growth stopped despite thecontinuing increase in total assets, and profit started to fall, generating a divergence among thethree elements that has since not narrowed. Thus from the end of Phase 2, ROA and other asset
efficiency indicators for Japanese corporations as a whole declined significantly. The figure also
illustrates no change in the basic situation of tangible fixed assets, as distinct from total assets,suggesting that the cause of the decline in asset efficiency lay principally in physical assets, notfinancial factors.
Figure 1-2. Assets, Sales and Profit Growth (Current Price, Indexed to the 1979 Averageas 100)500

Total Assets
総資産
Tangible Fixed Assets (Excluding Land)
有形固定資産（除土地）
400

Sales
売上高
Recurring Profit before Interest
利払前経常利益
Payments

300

200

（暦年四
100
80

Source:

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

00

(Calendar Year Quarters)
Ministry of Finance’s “Quarterly Report on Financial Statement Statistics of Corporations,” Cabinet Office’s “Annual
Report on National Accounts,” 1990 basis

ROA indicates the investment efficiency of existing assets, in other words the results of past
investment behavior. But if the earning rate on existing assets is a good substitute variable forinvestment profitability of new capital assets, it can also be considered as a cause of present
investment behavior.7 On the latter view, Figure 1-3 compares the ratio of investment to capitalstock (the proportion of new investment amounts to the outstanding balance of existing tangible
6

In Chapter 3’s analysis on individual corporate data, the ROA numerator is defined as the sum of operating profit and interestand dividends received. Here, however, the data are limited, so recurring profit before interest payments is substituted. The
difference between the two is other non-operating income/expenditure (profit/loss on sale of marketable securities equivalent
to current assets, real estate lease fees paid or received if unrelated to principal business, and the like).
7
In actuality, a direct correlation is normally recognized between corporate earnings and investment. As the reasons for this,besides those mentioned in this report, we can cite the effects of the fund procurement aspect, acting through increases ininternal funds, in accelerating investment. These and other reasons are dealt with in the next chapter.
4

Development Bank of Japan Research Report/ No. 12

fixed assets), as an indicator of investment behavior aggressiveness, with ROA trends. As
predicted, the ratio has a high correlation to ROA, but in Phase 1 it was stable in relation to ROA
and then far exceeded ROA in Phase 2. Analyzing this together with the characteristics ofinvestment fluctuation pattern in each phase seen in the preceding section, it appears that Phase
1 investment in energy-saving measures and R&D, and in such growth industries as services, wascarried out regardless of the underlying ROA, and served to stabilize overall investment. And in
Phase 2 when investment ballooned, a number of factors other than the investment earnings
ratio suggested by ROA (whose level was lower than in Phase 1) served to fuel investment.
Figure 1-3. Investment to Capital Stock Ratio and ROA
(%)

(%)

35

10
Investment to Capital
設備投資比率Stock Ratio
ROA (right scale)
ROA（右目盛）

30

8

25
6
20
4

15

2

10
80

Source:

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

00

(Calendar Year Quarters)
Ministry of Finance, “Quarterly Report on Financial Statement Statistics of Corporations”

Investment to capital stock ratio = new investment / tangible fixed assets (ex-land)

The stability of investment undertaken independently of immediate business conditions inPhase 1 attracted the attention of academic economists in the U.S., where the recovery ofindustrial competitiveness was a major problem at the time, and suggested the “long-term
perspective” of Japanese corporations. Overcoming the sharp rise in the yen after 1985, thecontinuing active investment through Phase 2 seemed to be consistent with a series ofhypotheses, the so-called “Japanese-style enterprise” theory, that the key to Japan’s economic
success was its unique investment behavior with a long-term perspective, supported by theJapanese style of corporate governance such as the main bank system and interlocking
shareholdings. With hindsight, the subsequent collapse of the Japanese economy and full-scale
retreat in investment proved that these hypotheses were simply incorrect. But did Japanesecompanies’ investment behavior really change, or did those special characteristics never actuallyexist? And did the Japanese style of corporate governance have any real impact? These issues
have never been resolved.
Regarding the Phase 2 surge in investment, there was an equity financing boom in those days,
and it is likely that the ready availability of money (free cash8) which corporate managers could

8

In this context, the term “free cash flow hypotheses” or simply “cash flow” is often used because they discuss in terms of theflow variable, but considering the true meaning of hypothesis we recognize it is more appropriate to discuss in terms of thestock variables, so in this report we will use “free cash.”
Development Bank of Japan Research Report/ No. 12 5

use freely, for better or worse, accelerated investment.9 If we look at the liquidity to capital stock
ratio (the total of cash and deposits plus liquid marketable securities to tangible fixed assets) in
corporate balance sheets, we see that such cash spurred the substantial growth in Phase 2 (Figure1-4). Naturally, if the liquidity to capital stock ratio rises with liabilities it is not free cash in thetrue sense, but in this period the debt-equity ratio did not rise. Consequently, our interpretation
including the subsequent ROA decline suggests that abundant liquidity on hand encouraged
aggressive investment, leading to the decline in capital efficiency. The fact that the investment
boom of Phase 2 involved everyone, independently of a company’s performance, supports the
hypothesis that the influence of free cash was dominant.
Figure 1-4. Balance Sheet Changes
(%)

(%)

100
1.0

600
6
Liquidity to capital stock ratio
手元流動性比率Debt-equity ratio (right scale)
負債比率（右目盛）

0.880

5
500

0.660

400
4

0.440

300
3

80
Source:

9

6

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96 97 98 99 00(Calendar Year Quarters)

Ministry of Finance, “Quarterly Report on Financial Statement Statistics of Corporations”
Liquidity to capital stock ratio = (cash and deposits + marketable securities posted in current assets) / tangible fixed
assets (ex-land)

Regarding the investment acceleration effect of free cash, the debate continues with improvement of analytical methods, boththeoretically and empirically, about whether or not there is such an effect, and whether accelerated investment is efficient orinefficient in maximizing a corporation’s value. See the next chapter for details.
Development Bank of Japan Research Report/ No. 12

II Basic Concepts and Data Sets
1. Theoretical Background
1.1 Fundamentals and Non-fundamentals in Investment Decision-making
What is the theoretical background for our consideration of the special characteristics ofinvestment behavior and their changes? Generally, when all markets satisfy the hypothesis thatthey are completely competitive, corporations’ investment levels determined by dynamically
optimized activity have a 1-to-1 correspondence with Tobin’s q (marginal q); in other words, q isa sufficient statistic. Expressed another way, any difference in actually-observed investment levels
is attributable to a difference in levels of q that summarize all the information related tofundamentals, in which case it is meaningless to consider characteristics of and changes ininvestment behavior.
Yet, even though the q theory of investment has a solid theoretical foundation, for empiricalanalysis the explanatory power of investment equations based on q is disappointing. And as anexperiential fact, investment behavior certainly varies widely by country and time period. For thatreason, both theoretical and empirical studies to explain actual investment movements haveprogressed on the hypothesis of imperfections in the various markets.10 A typical example ofmarket imperfection is information asymmetry and the conflicts of interest among shareholders,managers, creditors and other stakeholders, leading to additional costs of external fund raising.11
At such times, the assumption underlying the q theory, namely that funds can be procured fromthe markets at a fixed cost, is not true,12 and investment levels are influenced by the availability ofinternal funds. Further, the nature and magnitude of such influence are closely related to eachcountry’s particular social system and commercial practices (these are often called “economic
system” generically). Therefore, many studies have been carried out on the basis that the uniqueinvestment behavior of Japanese corporations is greatly influenced by Japan’s economic system,and that a company’s targets (the objective function of the optimization problem) are notnecessarily maximization of shareholder value.
Our empirical analysis follows a similar line of study; we predict that investment levels are
influenced by non-fundamentals such as the size of internal funds and special features ofcorporate governance, as well as investment profitability fundamentals represented by q. Out of
the large body of empirical literature, we especially refer to Takeuchi and Hanazaki (1997)
regarding “stylized facts” of Japanese corporate investment behavior and empirical methodology.
This report, however, makes no international comparisons, but focuses on the changes ininvestment behavior over time.

10

As the most recent investment research survey, see Miyagawa (1997), for example.
To expand on this more, we suppose shareholders and managers as insiders and new shareholders and creditors as outsiders.
Besides, we assume that information related to investment project quality is imperfect, so that there is the risk of insiders
pursuing their own private profit at the expense of outsiders. To raise funds from outsiders then, there are the costs ofobtaining information required to avoid this risk, and monitoring costs, in addition to the normal cost of capital. Otherwise, apremium is required for the expected loss generated in the event that no countermeasures are taken. Such inefficiencies causedby leaving investment of assets to an agent or proxy are generally called agency problems, and the associated costs are calledagency costs.
12
We find the theoretical grounds for this assumption in the famous Modigliani-Miller Theorem (MM Theorem). Including
matters not dealt with in this report, there are various cases in which the theorem does not come into play. Details of examplesof empirical investment research in such cases are given in Asako, Kuninori, Inoue and Murase (1991).
11

Development Bank of Japan Research Report/ No. 12 7

1.2 Hypotheses on Japanese Corporate Investment Behavior
We will now establish hypotheses related to the special features and changes in Japanese
corporate investment behavior, particularly the “non-fundamentals” aspect, to be tested inestimating the investment equations in Chapter 3. The hypotheses comprise the following fiveissues. All have mutual interrelations as components of the provisional “Japanese corporate
image” alluded to in the preceding chapter’s analysis of macroeconomic aspects. But from theviewpoint of empirical testing, these hypotheses are independent of each other since they are notderived deductively from original theoretical models. In Chapter 3, we will test and revise thehypotheses by using micro-level data, and thus reconstruct the final “Japanese corporate image”
as a conclusion.
[Hypothesis 1] Long-term Perspective and Its Changes
In the past, investment focused on the pursuit of long-term profits and was not swayed by
immediate differences and changes in underlying fundamentals (as a result, investment increased
steadily). But with the recent stiffening of competitive pressure, investment projects are now
screened carefully according to differences and changes in capital efficiency and profit margins(as a result, investment is suppressed and more unstable).
Our term “pursuit of long-term profits” is meant to be an issue of outward appearance,
regardless of whether it means pure optimization activity as the exact opposite of myopia.
[Hypothesis 2] Growth Intentions and Their Changes
In the past, investment was undertaken not only to maximize shareholder profits, but also fromthe standpoint of growing the scale of the enterprise, including sales and market share, or supply
responsibility based on customer trust (as a result, investment rose).13 Recently, however,diffusion of the capital market principle has resulted in loss of scope for investment based on
growth intent and supply responsibility, which does not always enhance shareholder value (andso investment is reduced).
[Hypothesis 2-1] The Model of Japanese Enterprises in Aoki (1988)
The Japanese enterprise is “a federated body in which a shareholder collective and an employee
collective divide added value.” Its management strategy tends to pursue high growth, rather thanan enterprise dominated solely by shareholders seeking to maximize short-term stock price andone dominated solely by employees seeking to maximize their profit. If we assume schematicallythat the Aoki model of a federated body corresponds to the traditional Japanese corporation anda shareholder-dominated firm corresponds to the modern Japanese corporation, and supposethat other conditions are fixed, then investment rises at the traditional corporation, companies
typically have a long history (number of years since establishment), decisions are made from thebottom up, and importance is placed on balancing investment among divisions.
[Hypothesis 2-2] Following and Emulating Investment Behavior and Its Changes
In the past, the Japanese style of business strategy based on boosting market share led toinvestment behavior that followed and emulated other companies, whatever the fundamentals
and strategies of one’s own company, and so investment rose by a corresponding amount.
Recently, however, owing to the same causes as in Hypothesis 2, this style has been disappearing.
13

8

Share expansion and supply responsibility are not short-term matters, but can be considered as being rationally carried out
linked to long-term maximization of shareholder value. In that case, even if the capital market principle diffuses, changes ininvestment behavior will not be seen (the hypothesis is denied).
Development Bank of Japan Research Report/ No. 12

[Hypothesis 3] Certainty Tendency and Its Changes
Japanese corporations originally had a tendency to stress certainty over high earnings in theirinvestment behavior because of the strong influence of banks on management. Recently,
although the influence of banks has weakened, this tendency has become even stronger because
the economic pie has stopped expanding and the markets have been taking a closer look atmanagement results and financial conditions.
[Hypothesis 4] Influence of Internal Funds and Debt-Equity Ratios, and Their Changes
As we saw in the preceding chapter, trends in aggregated financial data of Japanese corporations
showed that Phase 2 investment swelled beyond the trend of ROA, while the liquidity to capitalstock ratio rose substantially in parallel. As mentioned briefly, if we agree that the availability ofinternal funds (the sum of cash flow in the current period and procurement by drawing down
cash on hand) has a significant influence on investment level, then the welfare implications of
this effect are the exact opposite depending on the financial status of the company.
In the first case, internal funds are limited while external funds incur extra costs due toinformation asymmetry and conflicts of interest among stakeholders, leading to under-investmentin projects with positive discounted present value. In such a case, an increase in investment
propelled by the accumulation of internal funds is desirable for the overall economy, andcorporations with the institution to solve the agency problem, even with the same quantity ofinternal funds, can achieve higher corporate value.14 Almost all theories and empirical research
related to the effect of internal funds have assumed such financing constraints.
On the contrary, Jensen (1986) pointed out that plentiful internal funds enable all investment
projects with positive discounted present value to be executed, and the remaining free cash isused for inefficient investment (negative present discounted value)15 by managers intent on scale
expansion. In this situation, investment boosted by higher internal funds is the opposite of Case
1, and is not desirable for the economy as a whole.
An example of empirical analysis of the internal funds effect hypothesized in Case 1 is thefamous 1988 study by Fazzari, Hubbard and Petersen (hereinafter abbreviated as “FHP”)
utilizing U.S. corporate micro-level data (financial data for 422 manufacturers over the period
1970-84). Its content was exhaustively explained in Asako, Kuninori, Inoue and Murase (1991),
but in summary, it divides the analytical universe into three a priori classes by the degree offinancing constraints they face, and estimates for each class the investment equations
incorporating cash flow variables and stock variables that express internal liquidity. The result isthat the greater a corporation’s financing constraints, the greater its internal funds effect.
In this respect, Kaplan and Zingales (1997, hereinafter abbreviated as “KZ”) used a portion16of the FHP sample and estimated investment equations by revising to more appropriate forms
the q estimation method and the method of classification by degree of financing constraints.
Their conclusion was contrary to FHP’s, namely that the better the financial status of a company
the greater the investment acceleration effect (the size of the coefficient on cash flow variables
controlling q) of cash flow, and that investment-cash flow sensitivities are insufficient as ameasure of financing constraints. In addition, Cleary (1999), using financial data for a large
sample of 1,317 U.S. corporations (ex-financials, insurance and the like) over the period 1988-94,
14Jensen and Meckling (1976), for example, suggested the theoretical possibility that monitoring by banks can solve the agency
problem, which had a major influence in forming the so-called “main bank theory.”
15
Jensen (1986) stated on page 323 that “Managers have incentives to cause their firms to grow beyond the optimal size. Growthincreases managers’ power by increasing the resources under their control. It is also associated with increases in managers’
compensation.”
16
A group of 49 companies with the smallest dividend rates (the group that FHP thought of as facing the heaviest financing
constraints).
Development Bank of Japan Research Report/ No. 12 9

obtained the same estimation results as KZ. The conclusion that the better the financial status ofa company the higher its investment cash flow sensitivity is interpreted as supporting theassertions of Jensen (1986) related to the free cash effect.
The FHP-KZ dispute remains unresolved,17 but at least in respect of the Japanese
investment jump that occurred in Phase 2, the free cash hypothesis seems to be more applicablethan the financing constraint hypothesis, especially when we consider the large ROA decline
thereafter. The empirical analysis undertaken below is not intended as a validation of bothhypotheses, but by estimating micro-data based investment equations, and studying the sensitivityof investment to fundamentals along with the effects of debt-equity ratios and other financial
matters, we will examine not only whether or not internal funds accelerate investment, but also
their efficiency.
This report’s hypotheses regarding the influence of internal funds and debt-equity ratios are
as follows. The first is that independently of the financial status (financing constraint/abundant
free cash) of the company, the abundance and increase of internal funds have the effect ofaccelerating investment. The second is that regarding the financing constraint hypothesis, theextent of the debt-equity ratio and its rise has the effect of holding investment back.18 The third
is that, while internal funds boost investment, when sensitivity to fundamentals and theinvestment-limiting effect of liabilities are weak, then the free cash hypothesis holds true (i.e.,
inefficient investment is carried out). This case may be applicable to Phase 2.
[Hypothesis 5] Influence of Japanese Style of Corporate Governance Such As Main
Banks and Stable Stockholding, and Their Changes
From the late 1980s to the early 1990s, there was heated debate about the effects of internalfunds on investment, assuming the existence of information asymmetry and the agency problem.
During this period Japanese corporations made huge investments and performed well, despite far
higher debt-equity ratios than other leading advanced countries, and so attracted much researchinterest. To explain the miracle of Japanese corporations, researchers predicted that the Japanesestyle of corporate governance system, comprising main banks and stable stockholding,successfully controlled information asymmetry and the conflicts of interest among stakeholders,thus reducing the capital cost of investment and execution of optimal long-term investment (theso-called “Japanese-style enterprise” theory or the “Japanese style of corporate system” theory.
Many empirical studies were also carried out, such as that by Hoshi, Kashap and Sharfstein(1991, hereinafter abbreviated as “HKS”), using financial micro-level data for 145 Japanesemanufacturers over the period 1977-82.19 They divided their analytical universe into three groups:(1) Those clearly affiliated with “Keiretsu” (judged by main bank relations), (2) clearly
independent companies, and (3) companies between the two. As with FHP, for each of (1) and(2) investment equations are estimated incorporating the cash flow variable. Because the internalfunds effect detected in group (2) was not recognized in group (1), the conclusion was that theexistence of main banks reduces agency costs and accelerates investment.
After the Bubble’s collapse, however, the business performance of Japanese corporations
worsened considerably, and those with high debt-equity ratios faced high capital costs demanded
by banks and the markets, thus sending investment plunging. The emergence of this reverse
17

Refer to Fazzari, Hubbard and Petersen (2000) and Kaplan and Zingales (2000).
Because in the financing constraint hypothesis the higher the liability ratio (degree of dependence on external cash) the greater
the agency problem, when raising new external funds either the procurement cost rises or the quantity obtainable becomes
limited.
19
Refer to Horiuchi and Hanazaki (2000) for a comprehensive survey of studies on the correlation between the states of financial
intermediation functions like main bank relationship and managerial efficiency.
18

10 Development Bank of Japan Research Report/ No. 12

situation stopped the debate about the Japanese style of corporate system. Further, Hayashi in1997 tested the existence of the internal funds effect in investment equations over the same
1977-82 period as in HKS, based on the sample in the 1991 study by Hayashi and Inoue, andconcluded that differences in the internal funds effect do not stem from the existence orotherwise of a main bank relationship.
This report conjectures that the influence of the Japanese style of corporate governance,with its main banks and stable shareholders, has both merits and demerits, and is something thatcan change over time. We believe that the influence, if it exists, finds expression in differences in
the investment promotion effect of internal funds and in the investment restraint effect of debt.
Most previous studies, led by HKS, investigate whether or not influence is exerted in the“meritorious” aspects such as the easing of the agency problem, which causes financing
constraints, thanks to the existence of main banks and stable shareholders, and accelerating
investment with positive discounted present value. If such influence does exist, we would expect
the effects of internal funds-driven investment acceleration and of liability-driven investment
restraint to be smaller in companies with main banks and stable shareholders than in companies
without them. But as has been previously noted, the internal funds effect is not caused solely byfinancing constraints; rather, in Japan’s Phase 2, the free cash hypothesis appeared to hold true.
Bearing this in mind, if a main bank uses appropriate monitoring to restrain managers fromwasteful investment (the “meritorious” influence), then the internal funds investment
acceleration effect in companies with main banks and stable shareholders would be smaller thanin companies without them, as in the financing constraint hypothesis. Conversely, if an indulgent
main bank’s lending attitude and unprotesting stable shareholders lead to escalation of inefficientinvestment by managers intent on scale expansion to protect (the “culpable” influence), then theacceleration effect in companies with main banks and stable shareholders may be even larger thanin companies without them.
2. Characteristics of Micro-level Data Sets
In this section we will explain the construction of individual company data sets necessary to test
the foregoing hypotheses. The sets comprise corporate financial data and the results of theattitude survey related to investment behavior.
2.1 Analytical Subjects
In estimating investment equations by micro-level data, analytical subjects are usually limited to
manufacturers (or some segment thereof).20 The reasons for excluding non-manufacturers are
not clear, but it can be surmised that their business and financial data variability is wider than thatof manufacturers, and especially in estimations based on precise theoretical models as q, theresults are unstable and interpretation is difficult. But in recent years non-manufacturers’
investment has been roughly double that of manufacturers, and we cannot exclude them from
our analytical subjects21 for a comprehensive explanation of Japanese corporate investment
behavior in and after the 1980s. We therefore explore the special characteristics that are robustly
observed to be common to all, even with non-manufacturers’ wide variety and heterogeneity. As
we give greater priority to breadth of analytical subjects, our investment equations mentioned
later unavoidably depart somewhat from the q model. But in view of various limitations such as
the historical or book price base of the original financial data and the arbitrariness of accounting
methods (changes in account settlement policy and accounting methods), our approach is a valid

20
21

The aforementioned Cleary (1999) is one of the few exceptions.
Only finance and insurance are excluded, because their data are highly specialized.
Development Bank of Japan Research Report/ No. 12 11

one.
The analytical time frames follow those of Chapter 1, in which we established three periods
for examination of the special features of macroeconomic investment: Phase 1 (FY 1982-86),
Phase 2 (FY 1988-92) and Phase 3 (FY 1994-98) – each of five years, with intervals of one year.
We will estimate investment equations for each, and analyze their characteristic features andchanges.
2.2 Constructing the Basic Data Set from Corporate Financial Data
Regarding the corporate financial data set (hereinafter called “the basic data set”), we depend on
The Development Bank of Japan’s database that contains the financial report-based
unconsolidated accounting data of about 3,100 domestic listed and publicly traded companies,
excluding financial and insurance firms.22 Because analytical data are limited to those easily
obtainable for listed and publicly traded companies, as in other leading studies, it must be
remembered when interpreting the estimation results for Japanese companies as a whole that the
sample is biased.
The sample includes data on companies newly listed and taken public, and those delisted andremoved from OTC registration. In other words, the analysis was undertaken on an unbalanced
panel, with different numbers of cross section data (number of companies) for each fiscal year.
This was because when analyzing the same companies over the target period (this type of data set
is called an balanced panel), changes in the industrial structure and the tendency of rising newcompanies during the period cannot be taken account of. Further, the problem of survival bias,
namely that the only companies eligible are those that survive competition and maintain theirlistings, arises.23
The data of the companies that close their accounts in months other than March are treatedas being of the fiscal years to which their accounting year-end months belong (for example, aterm from April 1980 to March 1981 becomes the data for FY 1980). But companies withmultiple accounting year-ends due to accounting term changes are excluded from the samples forthat fiscal year and the next. The “regularization” alternative is widely used when handlingcompanies that change their fiscal year-ends, the longer period being used and profit/loss
statement items converted to the full-year (12 months) basis. But we find scattered instances ofclear seasonality in numbers due to the industrial characteristics and of special accounting
treatment prior to accounting period changes, which can easily result in abnormal values, so
regularization has not been undertaken in this report. Hence, whereas in other studies to build
the aforementioned “balanced panel” data sets, companies that change their fiscal years evenonce during the analytical period are excluded from the sample for the entire period, in thisreport, to maximize information, we have chosen to exclude from the sample only the period onwhich the fiscal year change has a direct influence, since excluding the following fiscal year leads
to abnormal growth rate values.24 In the case of mergers (only those of listed or publicly traded
companies), moreover, in “regularization” by summing the pre-merger numbers of both
22

Those listed on the first and second sections of the Tokyo, Osaka, Nagoya and other regional stock exchanges, and thoseregistered over-the-counter. Recognition by the existence of securities reports includes some companies just prior to listing or
public trading, but not those on markets established after the analytical period (Mothers, NASDAQ Japan). The number ofcompanies trended up, from no more than 1,615 in FY 1980 to over 3,000 recently (maximum of 3,099 in FY 1997). Data on
company ages (the number of years since establishment) not included in the Bank’s database were obtained from Tanaka(2000).
23
Balanced and unbalanced types should be differentiated by the analytical objective; it is meaningless to say that the unbalanced
type is always superior.
24
Concern over exclusion from the sample arises because dropping the data for large corporations affects the whole. But inregard to the variables in our estimation, it is necessary to use ratios to standardize processing in order to eliminate theinfluence of corporate size. Therefore, we believe that there is no major distortion in the estimate results.
12 Development Bank of Japan Research Report/ No. 12

companies it is difficult to adjust for business relationships; as in fiscal year changes, therefore,
they are excluded from the sample in the fiscal year of the merger and in the following year, andthe pre- and post-merger companies are treated as entirely different entities.25 New exchange
listings and companies newly taken public are added to the sample starting with data for thepreceding two fiscal years, to enable the year-to-year growth rates of the previous term to becomputed.
2.3 Generating the Combined Data Set by Adding Results of Corporate Investment
Attitude Survey
Matters related to the long-term perspective, growth intentions, following and emulating withothers, pursuit of certainty and other investment determinants and strategies are not only
surmised indirectly from movements of the amounts of investment and financial data; directsurveys of corporate attitudes can be used in our estimation to enable a more multivariate study.
An example of research using questionnaire surveys to estimate investment equations is Guiso
and Parigi (1999). With the principal Italian manufacturers as their subjects, in their analysis of
the influence of demand uncertainty on investment they used as indicators of uncertainty the dataof “subjective probability distribution of the evolution of the future demand for its product”
found in the Bank of Italy’s survey of investment in manufacturing, and obtained very interesting
results.
As special research within its investment planning studies, The Development Bank of Japanin October 1999 released its “Results of corporate investment attitude survey.”26 This survey
covered 3,302 companies capitalized at ¥1 billion or more, excluding financial and insurance
firms, as did the survey on planned capital spending. Of these, as many as 2,113, or 64%, gave
useful responses. The survey was designed to elucidate the present condition of and changes ininvestment behavior as the background of investment restraint in recent years,27 a survey which
had many points in common with this report.
Here we generate “the combined data set” by incorporating the results of the survey’s
question topics “II. Investment decision-making criteria and its changes” and “IV. Points at issue
in causes of Japanese corporate investment acceleration in the 1980s”28 as dummy variables into
our basic data sets. The survey’s questions gave two choices for each topic: Which applies more
to your company now?, and, Which applied more in the 1980s? In relating the answers to thethree analytical periods, responses related to “the 1980s” were considered to apply to Phase 1(FY 1982-86) and Phase 2 (FY1988-92) in common, while answers related to the “present” wereassumed to come under Phase 3 (FY 1994-98).
The correspondence between topics II and IV above and this report’s hypotheses is asshown in Table 2-1. Although the survey’s question topics were not prepared with this report inmind, the correspondence is self-evident from the explanations so far. It is not necessarily selfevident in relation to question II-1b, but as questions II-3a and 3b are assumed to be “Nonquantitative judgment factors”, question II-1b is also considered to correspond to Hypothesis 2.
Table 2-1. Correspondence Between Investment Behavior Attitude Survey Results
25

Given the special difficulties attendant on mergers with non-public companies, sales of business divisions, internal company
spin-offs and the like, no adjustments are made for such cases.
26
See pp. 36-42 of The Development Bank of Japan (1999).
27
The main concern of this survey is not a simple decline in the amount of investment, but a structural tendency of increasing
caution in investment behavior compared to the trends in cash flow and investment profitability. Hence even in the present
situation of recovery in the amount, the basic perception is unchanged.
28
The attitude survey did not necessarily cover listed and publicly traded companies, so the sample number obtainable from bothfinancial data and attitude survey results was even recently about 1,000 companies.
Development Bank of Japan Research Report/ No. 12 13

(Question Topics Excerpts from Related Segments Only) in The Development Bank ofJapan (1999)) and This Report’s Hypotheses
II. Investment decision-making criteria and its changes(Select the alternative that is closer to your company’s decision-making criteria in consideration of inter-divisional investment
allocation and individual investment proposals.)II-1. Decision-making style and basic criteria
II-1a. Decision-making style regarding important investment projects→ Corresponds to Hypothesis 2-1
Choice 1: Top down (other things being equal, there is a strong tendency for managers to exercise their guidance
authority)
Choice 2: Bottom up (other things being equal, there is a strong tendency to attach importance to opinions of workers
on the spot)
II-1b. Basic criteria for judgment in prioritizing investment projects→ Corresponds to Hypothesis 2
Choice 1: In principle, depends on quantitative evaluation (profit margin, recovery period, etc.) of investment
profitability
Choice 2: Many factors other than quantitative evaluation of investment profitability are taken into consideration(qualitative factors that are not quantifiable)
II-2. Criteria for quantitative evaluation of investment profitability
II-2a. Long-term growth or short-term profit?
→Corresponds to Hypothesis 1
Choice 1: Pursue long-term profit, prioritize high growth even if profit is low for the time being
Choice 2: Even if growth potential is limited, prioritize rapid improvement of earnings
II-2b. High earnings or low risk?
→ Corresponds to Hypothesis 3
Choice 1: There is earnings variability risk, but prioritize business for which high average profit margins can be
expected
Choice 2: Even if profit margins are somewhat low, prioritize business with high certainty
II-3. Judgment factors other than quantitative evaluation of investment profitability (when Choice 2 for question II-1b isselected)II-3a. Diversified or concentrated?
→ Corresponds to Hypothesis 2-1
Choice 1: To improve workers’ morale and to diversify all-company business risk, inter-division balance is considered
Choice 2: Concentration of management resources in priority divisions
II-3b. Mindful of other companies or independent?
→ Corresponds to Hypothesis 2-2
Choice 1: Do you follow or emulate other companies’ investments for capacity increases and R&D?
Choice 2: Regardless of other companies, do you judge according to your own company’s investment criteria?
IV. Points at issue in causes of Japanese corporate investment acceleration in the 1980s(For each point, select the answer that is closer: It is a cause of investment acceleration, or not particularly related.)
Point a: Ease of fund procurement due to existence of main bank or main correspondent financial institution→ Corresponds to Hypothesis 5
Point b: Long-term perspective because of existence of stable shareholders→ Corresponds to Hypothesis 5

Point c: Long-term relationships of trust with business partners and customers→ Corresponds to Hypothesis 2

Point d: Maintenance and expansion of sales and market share→ Corresponds to Hypothesis 2

14 Development Bank of Japan Research Report/ No. 12

3. Evidence from Cross-tabulation of Financial Data and Survey Results
Of the survey respondents, about 1,000 companies sharing common financial data sets werelisted or publicly traded. We cross-tabulated financial data and survey results, and observed theinfluence of good or poor management performance on investment behavior’s special
characteristics and changes. In the financial indicators subject to cross-tabulation, we selected FY
1998 ROA ((operating profit + interest and dividends received) / average of total assets at the
beginning and end of the period), and the debt-equity ratio at the beginning of the period(liabilities / net worth) as representative of management results (flow aspect) and financial
condition (stock aspect), respectively. Selecting boundary limit values for each indicator (4% and
2% for ROA, 100% and 300% for debt-equity ratios), we divided the sample into three
approximately equal segments, and for each segment tabulated the survey responses. The results
are shown in Table 2-2.
Table 2-2. Results of Cross-tabulation of Attitude Survey and Financial Data
1. Results of Cross-tabulation of Attitude Survey and ROA (return on assets)
ROA at beginning of FY 1998

How investment intentions should be determined, and their changes

Under 100% 100-300%

Over 300%

Overall

Bottom up (other things being equal, there is a strong tendency to 1980s
attach importance to opinions of workers on the spot)
Present

36.7%

42.1%

43.4%

40.7%

35.3%

36.9%

39.3%

37.2%

Many factors other than quantitative evaluation of investment
profitability are taken into consideration (qualitative factors thatare not quantifiable)
Pursue long-term profit, prioritize high growth even if profit is
low for the time being

1980s

42.8%

45.9%

43.5%

43.9%

Present

39.2%

39.7%

33.0%

37.0%

1980s

71.5%

74.1%

67.1%

70.6%

Present

70.7%

64.8%

51.5%

61.8%

Even if profit margins are somewhat low, prioritize business with 1980s
high certainty
Present

70.2%

67.2%

60.7%

65.8%

72.7%

82.1%

78.6%

77.6%

To improve workers’ morale and diversify risk, inter-divisionbalance is considered

1980s

37.5%

32.5%

43.2%

37.8%

Present

27.2%

18.4%

23.7%

23.4%

Follow or emulate other companies’ investments for capacity
increases and R&D

1980s

17.4%

30.4%

23.7%

23.5%

Present

8.7%

14.8%

14.4%

12.4%

Points at issue in causes of Japanese corporate investment acceleration in the
1980s
Ease of fund procurement due to existence of main bank, etc.

ROA at beginning of FY 1998
Under 100% 100-300%

Over 300%

Overall

1980s

42.9%

52.5%

56.8%

50.8%

Present

16.7%

21.8%

27.0%

22.0%

Long-term perspective because of existence of stable shareholders 1980s

21.3%

16.8%

23.9%

21.0%

Present

18.8%

14.4%

21.5%

18.6%

Long-term relationships of trust with business partners andcustomers

1980s

47.7%

45.4%

51.4%

48.5%

Present

44.4%

41.9%

46.5%

44.5%

Maintenance and expansion of sales and market share

1980s

81.7%

83.8%

85.3%

83.6%

Present

74.4%

60.6%

59.9%

65.1%

Development Bank of Japan Research Report/ No. 12 15

2. Results of Cross-tabulation of Attitude Survey and DER (debt-equity ratio)
ROA at beginning of FY 1998

How investment intentions should be determined, and their changes

Under 100% 100-300%

Over 300%

Overall

Bottom up (other things being equal, there is a strong tendency to 1980s
attach importance to opinions of workers on the spot)
Present

36.9%
35.3%

39.9%
35.7%

46.0%
41.6%

40.7%
37.2%

Many factors other than quantitative evaluation of investment
profitability are taken into consideration (qualitative factors thatare not quantifiable)
Pursue long-term profit, prioritize high growth even if profit is
low for the time being

43.1%
39.3%

40.9%
38.1%

49.3%
32.9%

43.9%
37.0%

Present

71.3%
66.9%

70.8%
65.0%

69.4%
51.4%

70.6%
61.8%

Even if profit margins are somewhat low, prioritize business with 1980s
high certainty
Present

65.6%
72.0%

66.7%
76.6%

64.6%
85.1%

65.8%
77.6%

To improve workers’ morale and diversify risk, inter-divisionbalance is considered

1980s

33.0%
23.5%

39.6%
24.4%

40.4%
21.3%

37.8%
23.4%

Follow or emulate other companies’ investments for capacity
increases and R&D

1980s

17.2%
9.5%

26.8%
15.2%

25.3%
11.0%

23.5%
12.4%

1980s
Present
1980s

Present
Present

Points at issue in causes of Japanese corporate investment acceleration in the
1980s
Ease of fund procurement due to existence of main bank, etc.

1980s
Present

Long-term perspective because of existence of stable shareholders 1980s
Present
Long-term relationships of trust with business partners andcustomers

1980s

Maintenance and expansion of sales and market share

1980s

Present
Present

ROAat beginning of FY 1998
Under 100% 100-300%

Over 300%

Overall

41.0%
14.4%

50.4%
22.7%

62.1%
29.1%

50.8%
22.0%

19.7%
17.4%

22.5%
21.3%

20.4%
15.8%

21.0%
18.6%

46.8%
44.6%

48.8%
45.3%

49.8%
43.2%

48.5%
44.5%

82.7%
76.9%

85.6%
65.1%

81.8%
52.3%

83.6%
65.1%

Remarks: Development Bank of Japan (1999), corporate financial data, others.
In this table, “Overall” denotes the result of the whole of the cross-tabulation sample, which is not the same as theresults of the overall attitude survey.

Regarding the special characteristics seen in the cross-tabulation results, first we note thatirrespective of management performance, there is a clear tendency of the changes in investment
behavior. As for decision-making style and basic criteria, the rates of selection of “Bottom up,”“Consideration of qualitative factors,” “Pursuit of long-term profit,” “Inter-divisional balance”
and “Following and emulating other companies” have all declined since the 1980s, while only therate for “Stress on certainty” has increased. All of these changes serve to restrain investment.
Further, in regard to the causes of Japanese corporate investment acceleration in the 1980s, on all
four points the selection rates declined, also signaling the emergence of a change to investment
restraint.
A second characteristic is that the aforementioned tendency is stronger in the unsatisfactory
management performance group (low return on assets, high debt-equity ratio), centering on
topics related to investment decision-making criteria such as, “Pursuit of long-term profit,“ “Stress on certainty” and “Maintenance and expansion of sales and market share.” But
regarding the effect of corporate governance organization – main banks and stable shareholders

16 Development Bank of Japan Research Report/ No. 12

– almost no differences were observed depending on the management performance.
In conclusion, the third characteristic is that in relation to the 1980s, the variations ininvestment behavior arising from management performance differences expanded, especially the
portions related to investment decision-making criteria. Stated another way, the group ofcompanies with poorer management efficiency and financial conditions were punished byunforgiving markets, and soon were forced to screen investment more stringently; aggregatedinvestment was therefore held back and destabilized. The group with no management problems,on the other hand, saw no great changes in their Japanese-style “Pursuit of long-term profit” and“Maintenance and expansion of sales and market share” investment behavior. It is interesting tonote that for the same “Japanese-style” element, the effect of main banks in accelerating
investment declines considerably regardless of the management performance. To date, various
components of the Japanese-style enterprise system have been debated as a single set under the
fixed concept that “it was a good system up through the 1980s, but not during stiffer global
competition in the 1990s, and the practice as a whole is likely to be abandoned”. But the resultsof cross-tabulation challenge this concept, and suggest that the components should be
distinguished from each other; structural and temporary, efficient and inefficient, pre-existing or
not pre-existing. In the next chapter we will carry out panel data estimation of micro-level
investment equations, to investigate not only the hypotheses set in the first section, but also toelicit suggestions resulting from these questions.

Development Bank of Japan Research Report/ No. 12 17

III Panel Data Estimation of Micro-level Investment Equations
1. Specification of the Empirical Model and Estimation Methods
In this chapter we will estimate investment equations using micro-level data, and test a series ofhypotheses related to the investment behavior of Japanese corporations. In this section, as
preparation, we will select an appropriate empirical model and estimation methods, bearing in
mind the various forms of bias and noise in corporate financial data. As noted in the previous
chapter, in this report’s basic framework, in addition to the “fundamentals” of investment
profitability as represented by q, we attached importance to the influence on investment levels ofsuch non-fundamentals as the size of internal funds and the peculiarities of corporate governance.
Accordingly, we will examine the selection of explanatory variables used in the estimation
formulas by classifying them as “fundamental” and “non-fundamental.” In this examination,reference is made to the 1997 study of Takeuchi and Hanazaki (hereinafter abbreviated as “TH”),
which used individual company financial data for Japanese, U.S. and French manufacturers toestimate investment equations in the same form for each country, and from an international
comparative standpoint to test hypotheses related to Japanese-style characteristics such as
emulating behavior and long-term perspective.
1.1

Basic Framework of the Empirical Model

Our point of departure is the following investment equation based on the q model:[1]

I / K = α + βq + ∑ γ i N iin which I : investment, K: capital stock at beginning of period, q: Tobin’s q, andNi : non-fundamental explanatory variable

Assuming that adjustment costs of investment are expressed in the quadratic function of I/K,
we obtain Formula [1]29 from corporate value maximization conditions related to capital stock K,
and information about the fundamentals of investment profitability is concentrated in only one
explanatory variable, q (marginal q). However, because marginal q as a shadow price of capital is apurely theoretical concept, expedients are required for use in empirical analysis. According to
Asako and Kuninori (1989), the methods are broadly divided into two. One assumes equivalenceof marginal q and average q (corporate value / current cost of capital) and uses average q instead,which can be derived from market capitalization and others. Another estimates marginal q fromobserved values of profit margins and discount rates on some assumptions. In estimating
marginal q, however, market price information of balance-sheet items is necessary. For thisreason TH, who used book value or historical cost-based corporate financial data, employed thelatter concept but did not estimate marginal q. Instead, they made their estimation of investment
equations using proxy variables for q’s component elements (profit margins and discount rates)
as fundamental explanatory variables (see pages 37-38).
This report, like TH, is based on book value or historical cost-based financial data andestimates investment equations using q’s component elements as fundamental explanatory
29

Refer to Asako and Kuninori (1999) for the process of deduction. Theoretically, being brought in from corporate value
maximization terms is a correspondence relation between I/K and q, and there is no causal relation from q to I/K.
Consequently, it is more precise to call Formula [1] an investment equation, not a function, but in this report the more familiar“function” is used in empirical analysis.
Development Bank of Japan Research Report/ No. 12 19

variables instead of q itself. In other words, we use the following form of equations:[2]

I / K = α + ∑ β i Fi + ∑ γ i N iin which I: investment, K: capital stock at beginning of period, Fi : fundamental explanatory
variable, and Ni : non-fundamental explanatory variable
As for the dependent variables, we use the book value-based I/K, denoted instead as Ibook /Kbook (the subscript book means book value), which can be derived from financial data as follows:
Ibook: Net increase in the period’s outstanding balance of tangible fixed assets (ex-land) +depreciation on the period’s tangible fixed assets
Kbook: Outstanding balance of tangible fixed assets (ex-land) at the end of the previous period
Because the Ibook concept is “gross investment,” depreciation is added back in. But there are
no data on sales and disposals during the period, so revisions are not made. Ibook / Kbook may have anegative value, but in those cases it is treated as a loss value. Unless otherwise specified below,
the entries are simply I/K.
1.2 Selection of Fundamental Explanatory Variables Fi
In the fundamental explanatory variables that are q’s component elements, TH too used ROA30
as a proxy variable for the marginal profit of capital, and also incorporated the price-to-bookratio (PBR = ratio of stock market capitalization31 to book value of net worth) and the real sales
growth rate (SGR = sales growth rate adjusted for the 1990-based GDP deflator).32 PBR and
SGR are concepts more closely related to average q than to marginal q, and do not have a precise
theoretical foundation. But the intention is to assure robustness suitable for estimationencompassing the widely diverse and qualitatively different data for non-manufacturers, throughincorporation of a wide range of fundamental information.
ROA, PBR and SGR are all variables that impact positively on q, and its coefficients in
respect of investment are normally expected to have a positive sign. But in the most extreme
cases of the Japanese enterprise model wherein investment behavior is dominated mainly by nonfundamentals, the estimated coefficients are considered to become statistically insignificant or
have a negative sign.
All of these variables use data from previous periods (the end of the previous period for
PBR). Actually, in q model-based investment equation estimation, the question of when to use q(or its component elements) as an explanatory variable is not obvious due to the following two
problems. The first is that in Formula [1], I/K and q are theoretically determined simultaneously,and even in Formula [2], which breaks q down into its components, there can occur asimultaneity bias in the ordinary least-squares (OLS) estimator. The second problem lies in theexistence of a time lag (time to build) from the decision to invest to recognition as assets, withthe length of lag diverging widely depending on the type and scale of asset (buildings, machinery,etc.). The time to build problem, moreover, makes it more difficult to resolve the simultaneitybias. The report chooses to use ROA, PBR and SGR data not for the current but for the previous
period, in order to ease the simultaneity problem.
30(Operating profit + interest and dividends received) / average of total assets at beginning and end of period. For the relation
between the marginal profit of capital and the realized value of profit margin, see Asako and Kuninori (1989).
31
Valued at the average of the period’s highest and lowest stock prices.
32
Here the real sales growth rate is taken as a proxy variable for the expected profit growth rate. The realized value of the profit
growth rate has a higher conceptual conformability as a proxy variable than the real sales growth rate, but the problem of highvolatility and red ink loss values led us to use the more stable sales growth rate.
20 Development Bank of Japan Research Report/ No. 12

The proxy variable used for discount rate is excluded from our explanatory variables.
Although many previous studies including TH used the ratio of interest to interest-bearing
liabilities (interest and discount fees paid / outstanding balance of interest-bearing liabilities) as
the discount rate proxy variable, there are scattered cases of widening gaps between beginningand end-of-period balances and the average balance during the period, owing to such causes as(1) short-term cash balance adjustments at the end of the fiscal year, (2) time slippage in interest
payments based on special treatments related to deferred and accrued accounts, and (3) use ofderivatives. The reasons for excluding the discount rate proxy variable are that it is especially easy
for abnormal values to emerge in companies with small interest-bearing debt balances and in the
non-manufacturers not analyzed in TH, and because no other appropriate proxy variables can beobtained.
1.3 Selection of Non-fundamental Explanatory Variables Ni
As non-fundamental variables unrelated to investment profitability, we used three based on theprevious chapter’s series of hypotheses about Japanese corporate investment behavior: The
liquidity to capital stock ratio LNK, the debt-equity ratio DER and the company age AN.
LNK takes the sum of the previous year-end’s liquidity on hand (cash and deposits +marketable securities posted under current assets) and the current year’s cash flow (after-tax net
profit – dividends and bonuses to directors + depreciation), standardizes it by the previous yearend’s outstanding balance of tangible fixed assets (ex-land), and uses it as a proxy variable forinternal funds in Hypothesis 433, so the coefficient’s sign is expected to be positive.
DER is the previous year-end’s ratio of liability balance to net worth, and is used as avariable to express the seriousness of the agency problem in Hypothesis 4. It is expected that if
the agency problem exists, the sign of the coefficient will be negative. If, despite any positive
influence exerted on investment by LNK the debt-equity ratio’s coefficient is not statisticallysignificant, it is considered that the internal funds effect will not be based on financing
constraints, and instead Jensen’s free cash hypothesis (in which surplus funds encourage
inefficient investment) may emerge.
AN, the number of years since a company’s establishment, is related to Hypothesis 2-1,
wherein the older the company the greater the tendency to consider not only shareholders but
also employee benefit in growth-oriented investment behavior (Japanese enterprise model of
Aoki (1988)). If this is true, the coefficient’s sign is expected to be positive. However, there isanother aspect of corporate age, that is, the younger the company the greater its growth
opportunities, thus pushing up its investment rate. If this aspect cannot be accounted for only by
fundamental-related variables, the coefficient may become negative.
In addition to the foregoing, estimation combined with the investment behavior survey data
introduces one serial dummy variable for each hypothesis (including its sub-hypotheses), as in
Table 2-1. When multiple question topics correspond to a single hypothesis, while looking at thestatistical characteristics of each we have used as explanatory variables the following five series toselect only one which we believe best captures the essence of the hypothesis, or combined them.
(1) Growth Tendency Dummy D20 (corresponds to Hypothesis 2): We attach 1 if thecompany answers to Question IV-d that focus on maintaining and expanding sales andmarket share drive investment acceleration, 0 otherwise. The sign of the coefficient is
expected to be positive as a constant term dummy.
(2) Bottom Up Dummy D21 (corresponds to Hypothesis 2-1): We attach 1 if the33

The financial balance (procurement, repayment) is not considered. The stock variable is incorporated in LNK, so thesimultaneity bias problem can be ignored.
Development Bank of Japan Research Report/ No. 12 21

(3)

(4)

(5)

company chooses “bottom up” as its investment decision-making style in Question II1b, 0 otherwise. The sign of the coefficient is expected to be positive as a constantterm dummy.
Following and Emulating Tendency Dummy D22 (corresponds to Hypothesis 2-2):
We attach 1 if the company chooses “following and emulating other companies” as a
judgment factor other than quantitative evaluation of investment profitability in
Question II-3b, 0 otherwise. The sign of the coefficient is expected to be positive as aconstant term dummy.
Certainty Tendency Dummy D30 (corresponds to Hypothesis 3): We attach 1 if thecompany answers to Question II-2b that it gives priority to high certainty as a criterion
for quantitative evaluation of investment profitability, 0 otherwise. The sign of thecoefficient is expected to be negative as a constant term dummy.
Main Bank, Stable Shareholder Dummy D50 (corresponds to Hypothesis 3): We
attach 1 if the company answers to Questions IV-a and IV-b that the existence ofmain banks (or main correspondent financial institutions) and stable shareholders
accelerates its investment, 0 otherwise. As coefficient dummies for LNK and DER, wewill investigate the role played by the Japanese style of corporate governance (mainbanks and stable shareholders) in relation to the influence on investment exerted byinternal funds and debt-equity ratios (Hypothesis 4). If the impact of Japanese-style
governance is a “meritorious” aspect, then the expected sign of the coefficient dummy
for LNK is negative and that for DER is positive, and vice versa.

In the foregoing, we can consider constant dummies (1) to (4) as “Japanese-style special
characteristics” related to criteria for investment choices, and coefficient dummy (5) as a“Japanese-style special characteristic” of the influence on investment of corporate governance.
1.4 Estimation Methods for Panel Data
Based on the foregoing specified formulations and variables, we will estimate investment
equations for Phase 1 (FY 1982-86), Phase 2 (FY 1988-92) and Phase 3 (FY 1994-98) using thepanel data constructed in the previous chapter.34 In our estimation methods, the principal
technique used is what is called panel analysis. In this, cross section and time series data arepooled without distinction as equal samples. Compared to using the ordinary least-squares
method (plain OLS, hereinafter abbreviated as “POLS”), this enables us to take account of thepeculiarities (individual effects) of each company (that is, cross section direction). In panel
analysis, various models can be considered, but generally two are used: The fixed effect model(hereinafter “FE”), in which individual effects are considered to be shown in a constant termsuch as a corporate dummy variable, and the random effect model (“RE”), in which individual
effects are assumed to be expressed by an error term. In cases wherein the cross section numberof samples constitutes a huge volume of data, as in this report, there is almost no meaning inanalyzing the differences between constant terms company by company, so RE is normally used.
But when there are correlations between individual effects and explanatory variables, values ofcoefficients estimated by RE are no longer consistent estimators and therefore the use of FE ismore appropriate. We arrive at our estimation by POLS, FE and RE, and use statisticalverification techniques in relation to model selection. Where in the first place there are no special
company-by-company special characteristics (individual effects) POLS is used, and where there

34

Regarding dummy variables, the content of responses for the 1980s is treated as the data for Phases 1 and 2, and for responses
related to the present is processed as Phase 3 data. This is as noted in the previous chapter when constructing the data.

22 Development Bank of Japan Research Report/ No. 12

exist individual effects but with correlation between explanatory variables we use FE; otherwise
we use RE. These are the methods, thought to be optimum for each sample, used for theestimation results.
In the actual estimation process, we eliminate negative values that are never present in theory,and use all other data after logarithmic conversion of percentages (the original numbers for ROA
and SGR are used as is). Including these points, the final definitions for all variables andestimation formulae are brought together in Table 3-1.
Table 3-1. Summary Table of Definitions of Variables and Estimation Formulas
1. Definitions of Variables
Dependent Variables
Designation
I/K

Name
Investment ratio

Definition(This period’s net increase in tangible fixed assets
balance (ex-land) + tangible fixed asset depreciation)/ balance of tangible fixed assets at end of previous
period (ex-land)

Remarks
Logarithmic
conversion ofpercentages

Explanatory Variables
a. Fundamentals-related (data for one previous period are used)
Designation
ROA

Name
Return on assets

PBR

Price book-value ratio

SGR

Real sales growth rate

Definition(Operating profit + interest and dividends received) /average of total asset balances at beginning and end of
periodAverage of highest and lowest stock prices in period x
number of issued shares at end of period / balance of paidin capital at end of period
Nominal sales growth rate – growth rate of GDP deflator

Remarks

Logarithmic
conversion ofpercentage

b. Matters Related to Non-fundamentals
Designation
LNK

Name
Liquidity to capitalstock ratio

DER

Debt-equity ratioAN

Age of company

Fiscal year – year of establishment

D20

Growth tendency
dummy

D21

Bottom-up dummy

D22

Following andemulating tendency
dummy
Certainty tendency
dummy
Main bank/stableshareholder dummy

Companies that responded to Question IV-d(maintenance/expansion of sales and share is a cause ofinvestment promotion) = 1, otherwise = 0Companies that responded to Question II-1b (bottom-up
selection) = 1, otherwise = 0Companies that responded to Question II-3b (following
and emulating other companies) = 1, otherwise = 0

D30
D50

Definition((End-of-period balance of cash and deposits + securities
posted as current assets) + (after-tax net profit – dividends
and director’s bonuses + depreciation)) / balance oftangible fixed assets (ex-land) at end of previous period
Balance of liabilities / Net Worth, both at end of previous
periodCompanies that responded to Question II-2b (selection ofhigh priority to certainty) = 1, otherwise = 0Companies that responded to Question IV-a (existence ofmain bank, etc.) and Question IV-b (existence of stableshareholders) as investment promotion causes = 1,otherwise = 0

Remarks
Logarithmic
conversion ofpercentage
Logarithmic
conversion ofpercentage
Logarithmic
conversion
Constant dummy
Constant dummy
Constant dummy
Constant dummy
LNK, DER
coefficient dummy

Development Bank of Japan Research Report/ No. 12 23

2. Estimation Formulas for the Basic Data Set (Note: Subscript i denotes individual company,
subscript t denotes fiscal year (time).)Least-squares Method
I / K i ,t = α + β1ROAi ,t −1 + β 2 PBR i ,t −1 + β 3 SGR i ,t −1 +γ 1 LNK i ,t + γ 2 DER i ,t + γ 3 AN i ,t + ε i ,tαi = fixed effect
I / K i ,t = α + β1ROAi ,t −1 + β 2 PBR i ,t −1 + β 3 SGR i ,t −1 +γ 1 LNK i ,t + γ 2 DER i ,t + γ 3 AN i ,t + ε i ,tPanel analysis (fixed effect model)

δi = random effect
I / K i ,t = α + β1ROAi ,t −1 + β 2 PBR i ,t −1 + β 3 SGR i ,t −1 +γ 1 LNK i ,t + γ 2 DER i ,t + γ 3 AN i ,t + δ i + ε i ,tPanel analysis (random effect model)

3. Estimation Formulae for the Combined Data Set

Least-squares Method
I / K i ,t = α + β1ROAi ,t −1 + β 2 PBR i ,t −1 + β 3 SGR i ,t −1 +( γ 1 + γ 1d D 50 ) LNK i , t + ( γ 2 + γ 2 d D 50 ) DERi , t + γ 3 AN i , t +γ 4 D 20 + γ 5 D 21 + γ 6 D 22 + γ 7 D 30 + ε i ,tαi = fixed effect
I / K i ,t = α + β1ROAi ,t −1 + β 2 PBR i ,t −1 + β 3 SGR i ,t −1 +( γ 1 + γ 1d D 50 ) LNK i ,t + ( γ 2 + γ 2 d D 50 ) DER i ,t + γ 3 AN i ,t +γ 4 D 20 + γ 5 D 21 + γ 6 D 22 + γ 7 D 30 + ε i ,tPanel analysis (fixed effect model)

δi = random effect
I / K i ,t = α + β1ROAi ,t −1 + β 2 PBR i ,t −1 + β 3 SGR i ,t −1 +( γ 1 + γ 1d D 50 ) LNK i ,t + ( γ 2 + γ 2 d D 50 ) DER i ,t + γ 3 AN i ,t +γ 4 D 20 + γ 5 D 21 + γ 6 D 22 + γ 7 D 30 + δ i + ε i ,tPanel analysis (random effect model)

2. Estimation Results Using the Basic Data Set and Its Interpretation
In this section, we examine the estimation results for a large sample based on the basic data set.
The number of samples after eliminating companies in the case of accounting term alteration,
mergers, right after new listings and new public trading, loss values, etc., is a maximum of 2,845
in cross section (number of companies), which becomes 12,380 on pooling with time series (FY
1994-98). Estimated coefficient values with results of significance testing are shown in Table 3-2.
The objective of this report’s analysis is to examine special characteristics across industries, so thediscussion focuses on estimation results derived from the all-industry data shown in Table 3-2,
but for reference Table 3-3 shows estimation results for manufacturers and non-manufacturers.

24 Development Bank of Japan Research Report/ No. 12

2.1 Increasing Sensitivity to ROA
Looking at the coefficient on ROA, which is believed to be the most important of thefundamentals-related variables, we obtain significantly positive estimation values in all threephases. This shows that investment was carried out basically in accordance with the tendency of
ROA or implied marginal profit of capital (Table 3-2). But note particularly the chronologicalchanges in the size of the coefficient: Estimated values of the coefficient on ROA were 1.20
(0.77-1.62) for Phase 1, 2.96 (2.23-3.69) for Phase 2 and 5.05 (4.53-5.57) for Phase 3, i.e., thenumber increases each period by a statistically significant margin (the figures in parentheses arefor the 95% confidence level, which also applies hereinafter), indicating that the sensitivity ofinvestment to capital efficiency increased steadily. This tendency was almost the same for bothmanufacturers and non-manufacturers (Table 3-3). In other words, investment behavior moved
away from seeking long-term profit regardless of differences and changes in capital efficiency,
thus generally supporting Hypothesis 1 (long-term perspective and its changes). However, it isalso clear that this phenomenon is not new to recent years, e.g., post-Bubble, which was never
expected before estimating micro-level investment equations.
Table 3-2. Estimation Results Using the Basic Data Set
Sign

FY 1982-86(Phase 1)

FY 1988-92(Phase 2)

FY 1994-98(Phase 3)

ROA

＋

1.20

2.96

5.05

5.48 **

7.95 **

19.2 **

PBR＋

19.6×10-2
10.8 **-5.33×10-2 ×-2.03 *

13.7×10-2
7.80 **

SGR＋

8.95×10-1
10.6 **

0.00×10-1
0.15

9.19×10-1
12.0 **

LNK＋

6.83×10-2
6.63 **

17.6×10-2
14.8 **

8.95×10-2
9.91 **

DER－-18.8×10-2-16.8 **

-1.17×10-2-0.71-6.95×10-2-6.39 **

AN＋

-8.11×10-2 ×-2.64 **

-13.1×10-2 ×-3.59 **

-0.09×10-2 ×
-0.04

RE

FE

RE

0.001

0.000

0.000

0.801

0.001

0.122

7,578

9,172

12,380

1,681

2,199

2,845

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

Remarks:
1. For definition of variables and estimation formulas, see Table 3-1.
2. The numbers in the upper segment of each cell are estimated values of the coefficient (a cross X to the right indicates thatsign conditions are not satisfied), and those in the lower segment are t-values (a double asterisk ** to the right indicatesthe 1% significance level, a single asterisk * indicates the 5% level). As a result of the Breusch-Pagan and White tests,
there is a high possibility of heteroscedasticity, so in calculating t-values we make use of the heteroscedasticity consistent
standard error (HCSE) based on White’s modification.
3. The abbreviations for the models used are POLS for the ordinary least-squares method, FE for the fixed effect model and
RE for the random effect model. As the process of model selection we first perform an F test for the null hypothesis thatthe individual effect does not exist. If the hypothesis is rejected, we use panel analysis (FE or RE); if not, we use POLS.
When panel analysis is used and we test (the Hausman test) for the null hypothesis that there is no specification error in
RE, we select RE if the hypothesis is rejected and FE if it is not. Further, if in all tests the p-value does not amount to 0.05(5%), the null hypothesis is rejected.

Development Bank of Japan Research Report/ No. 12 25

Table 3-3. Estimation Results Using the Basic Data Set, by Industry Category
Manufacturers
ROA

Sign

FY 1982-86(Phase 1)

FY 1988-92(Phase 2)

FY 1994-98(Phase 3)

＋

1.79

2.96

6.03

5.36 **

7.87 **

15.7 **

PBR＋

14.3×10-2
6.43 **-8.77×10-2 ×-2.70 **

6.97×10-2
2.75 **

SGR＋

10.6×10-1
8.33 **

5.88×10-1
4.87 **

10.1×10-1
7.54 **

LNK＋

10.1×10-2
4.86 **

18.7×10-2
10.5 **

6.77×10-2
4.45 **

DER－-13.9×10-2-8.34 **

2.24×10-2 ×
1.03-2.92×10-2
-1.64

AN

＋

-9.69×10-2 ×-2.93 **

-7.00×10-2 ×-1.63

7.30×10-2
2.22 *

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

POLS

FE

POLS

0.109

0.000

0.219

－
5,140

0.000
5,829

－
7,189

1,137

1,371

1,619

Sign

FY 1982-86(Phase 1)

FY 1988-92(Phase 2)

FY 1994-98(Phase 3)

＋

0.52

2.01

4.41

1.14

4.30 **

10.1 **

Non-manufacturers
ROA
PBR

＋

17.5×10-2
4.69 **-1.67×10-2 ×-0.52

15.3×10-2
5.46 **

SGR＋

5.96×10-1
2.90 **-0.02×10-1 ×-1.24

8.02×10-1
6.91 **

LNK＋

8.05×10-2
4.57 **

19.7×10-2
13.8 **

13.2×10-2
9.96 **

DER－-17.5×10-2-7.91 **

-1.67×10-2-0.79-3.44×10-2
-1.94

AN

＋

-20.1×10-2 ×-3.68 **

-19.9×10-2 ×-4.47 **

-22.8×10-2 ×-5.78 **

POLS

RE

RE

0.593

0.038

0.013

－
2,438

0.143

0.383

3,343

5,191

550

834

1,234

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

Remarks: See Table 3-2. The fiscal years are different for the maximum values of numbers of manufacturing and nonmanufacturing companies, so the combined sums of both exceed the all-industry totals, even though the sampling
population is exactly identical.
26 Development Bank of Japan Research Report/ No. 12

2.2 Uniqueness of Investment Behavior in Phase 2
Turning our attention to variables other than ROA, the uniqueness of Phase 2 becomes apparent.
In Phases 1 and 3, PBR, SGR, LNK and DER all significantly satisfied the sign conditions. But inPhase 2, only the coefficient on LNK satisfied the sign conditions and was statistically significant.
Further, the estimation value of the coefficient on LNK was prominently high at 17.6 (15.3-20.0)
in Phase 2, compared to Phase 1’s 6.83 (4.81-8.85) and Phase 3’s 8.95 (7.18-10.7), indicating aremarkable degree of sensitivity. In its relation to Hypothesis 4 (influence of internal funds anddebt-equity ratios, and its changes), we see in Phases 1 and 3 that an abundance of internal funds
and its increase promote investment, and a high debt-equity ratio and its increase serve to restrain
it, suggesting a financing constraint situation. In Phase 2, in contrast, while the result is the samein respect of an abundance of internal funds and its increase, the coefficient on DER is notstatistically significant, the coefficient on LNK is significantly larger relative to other phases, andthe values of fundamental variables PBR and SGR do not satisfy sign conditions and losesignificance. In summary, the suggestion is that Jensen’s free cash hypothesis applies. These
special characteristics of Phase 2 are macro-level observation results and coordinated, and evenwhen estimating by industry category are basically unchanged (Table 3-3).35
2.3 Testing the Existence of Internal Funds EffectTo test further the implications of the investment promotion effect of internal funds, we divided
the sample corporations into two groups related to the degree of financing constraint, andassessed whether there are differences in the size of the coefficient on LNK. Specifically, weadded the LNK coefficient dummy Dnfc to the estimation formula based on the basic data set.
For the company group with debt-equity ratios less than 300% and a low probability of being
faced with financing constraints, we estimated using Dnfc = 1, and for the group with debt-equity
ratios exceeding 300% and a high probability of being faced with financing constraints, we used
Dnfc = 0. If the financing constraint situation is predominant, the coefficient on Dnfc is expected
to become negative (equivalently the coefficient on LNK will be larger for the group ofcompanies with a high probability of being faced with financing constraints); conversely, thecoefficient becomes insignificant or even significantly positive if the free cash hypothesis
predominates.
The estimation results are shown in Table 3-4, with the coefficient on Dnfc significantly
positive for all phases. Looking at the estimation values, 1.40 (0.16-2.65) for Phase 1, 4.02 (2.555.49) for Phase 2 and 4.11 (2.75-5.47) for Phase 3, we see that they become larger in and after
Phase 2, especially large compared to the coefficient on LNK in Phase 3. As for the coefficienton DER, it was significantly negative in Phase 1, the same result as the estimation not including
the coefficient dummy, while in Phases 2 and 3 different results were obtained (significantly
positive /negative but not significant, respectively). Similarly, in the estimation for manufacturers
and non-manufacturers, the coefficient on Dnfc was significantly positive for the most part andthe overall tendency corresponds closely between both categories (Table 3-5).

35

If we venture to cite the differences with all industries, the coefficient on SGR has a positive significance for manufacturers inPhase 2, and the coefficient on DER has no significance for either manufacturers or non-manufacturers in Phase 3. If,
however, we consider that in Phase 2 even manufacturers’ PBR has negative significance, and that in Phase 3 both of theseindustries significantly satisfy all sign conditions for fundamental variables, the uniqueness of Phase 2 remains unchanged.
Development Bank of Japan Research Report/ No. 12 27

Table 3-4. Estimation Results Using the Basic Data Set (with Coefficient Dummies)
Sign
ROA

＋

PBR

＋

SGR

＋

LNK

＋
Dnfc (coefficient dummies for companies with
DER under 300%)

－

DER

－

AN

＋

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

FY 1982-86(Phase 1)
1.17
5.36 **
19.4×10-2
10.7 **
8.91×10-1
10.5 **
6.33×10-2
6.01 **
1.40×10-2 ×
2.21 *-16.0×10-2-9.61 **
-8.03×10-2 ×-2.62 **RE

FY 1988-92(Phase 2)2.90
7.80 **-4.15×10-2 ×-1.58
0.00×10-1
0.18
15.7×10-2
12.6 **
4.02×10-2 ×
5.37 **
5.84×10-2 ×
2.67 **-13.3×10-2 ×-3.66 **FE

FY 1994-98(Phase 3)
5.00
19.0 **
14.2×10-2
8.13 **
9.01×10-1
11.8 **
6.44×10-2
6.47 **
4.11×10-2 ×
5.92 **-1.62×10-2-1.15
0.50×10-2
0.21
RE

0.001

0.000

0.000

0.705
7,578
1,681

0.001
9,172
2,199

0.137
12,3802,845

Remarks: See Table 3-2

Table 3-5. Estimation Results Using the Basic Data Set (with Coefficient Dummies), by
Industry Category
Manufacturers
Sign
ROA

＋

PBR

＋

SGR

＋

LNK

＋
Dnfc (coefficient dummies for companies with
DER under 300%)

－

DER

－

AN

＋

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

28 Development Bank of Japan Research Report/ No. 12

FY 1982-86(Phase 1)
1.75
5.26 **
14.1×10-2
6.33 **
10.6×10-1
4.36 **
9.27×10-2
4.36 **
1.88×10-2
2.34 *-10.3×10-2-4.35 **
-9.61×10-2 ×-2.91 **POLS

FY 1988-92(Phase 2)
2.88
7.69 **-6.77×10-2 ×-2.07 *
5.82×10-1
4.94 **
15.8×10-2
8.21 **
3.87×10-2
4.29 **
8.02×10-2 ×
3.11 **-7.41×10-2 ×
-1.73
FE

FY 1994-98(Phase 3)
5.94
15.4 **
8.74×10-2
3.40 **
9.91×10-1
7.37 **
3.76×10-2
2.22 *
4.00×10-2
4.02 **
0.90×10-2 ×
0.45
7.67×10-2
2.34 *
POLS

0.092

0.000

0.234

－
5,140
1,137

0.000
5,829
1,371

－
7,189
1,619

Non-manufacturers
Sign
ROA

＋

PBR

＋

SGR

＋

LNK

＋
Dnfc (coefficient dummies for companies with
DER under 300%)

－

DER

－

AN

＋

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

FY 1982-86(Phase 1)
0.54
1.18
17.7×10-2
4.73 **
6.01×10-1
2.94 **
8.45×10-2
4.56 **-1.17×10-2 ×-0.95-19.7×10-2-5.84 **
-20.3×10-2 ×-3.71 **POLS

FY 1988-92(Phase 2)
1.70
2.29 *-5.70×10-2 ×-1.17-0.02×10-1 ×-0.59
17.4×10-2
9.03 **
3.92×10-2 ×
3.01 **
5.93×10-2 ×
1.58-31.2×10-2 ×-5.17 **FE

FY 1994-98(Phase 3)
4.39
10.1 **
15.5×10-2
5.52 **
7.92×10-1
6.83 **
11.6×10-2
7.85 **
2.76×10-2 ×
2.58 **
0.64×10-2 ×
0.27-22.0×10-2 ×-5.56 **
RE

0.605

0.022

0.013

－
2,438
550

0.007
3,343
834

0.488
5,191
1,234

Remarks: Remarks: See Table 3-2. The fiscal years are different for the maximum values of numbers of manufacturing andnon-manufacturing companies, so the combined sums of both exceed the all-industry totals, even though thesampling population is exactly identical.

From the foregoing results we can infer the following three points. First, in all estimation periods,
as in Kaplan and Zingales (1997) and Cleary (1999), the better a corporation’s financial status thehigher the investment sensitivity to internal funds, suggesting that even in Phases 1 and 3 thefinancing constraint situation is not clearly supported. Rather, there always exists the possibilityof a liquidity surplus situation, which implies the potential free cash problem. In and after Phase
2 in particular, the liquidity surplus situation is more likely to dominate over the financing
constraints situation.36
The second point is that in Phases 1 and 3, the coefficients on variables related tofundamentals such as PBR and SGR are significantly positive, and there is no further proof thatthe liquidity surplus situation was linked to inefficient investment; that is, the potential free cash
problem emerged. In contrast, in Phase 2, in light of the loss of explanatory power of PBR and
SGR, there is a high possibility that the free cash problem existed, as internal funds had a muchgreater effect in promoting investment than in other periods and so had a stronger influence.
The third point is that in the estimation not including coefficient dummies, in Phases 1 and 3
the coefficient on DER was significantly negative, which can be interpreted consistently with theabove two points as follows. Namely, for the reason that the greater the pressure to pay principal
and interest, the greater the caution about using internal funds for investment, in the estimation
not including coefficient dummies the coefficient on DER becomes negative, and in theestimation including them the coefficient on LNK becomes smaller for the group having high36This is not a denial of the financing constraint situation. Actually, companies in that situation are intermixed with those in aliquidity surplus situation, meaning that we cannot say that the financing constraint situation is dominant overall. If it isconsidered that this report’s analytical universe is companies listed or publicly traded in and after the 1980s, this result should
not be surprising.
Development Bank of Japan Research Report/ No. 12 29

debt-equity ratios. In Japanese-style financing, which demands that corporations possess certain
amounts of cash and deposits or marketable securities as one type of collateral for bank loans,the appearance of this situation is not unnatural. The problem lies in whether the investment
restricted by this mechanism was the efficient type that maximizes corporate value, or the
inefficient type in which management pursues private benefit. Even if the coefficient on LNK issmall for the high debt-equity ratio group, if the result is restriction of efficient investment, theeffect is not one of debt-driven discipline but of a variant of the “financing constraint problem.”
The fact that in Phases 1 and 3 the coefficients of fundamental-related variables were all
significant suggests that the characteristics of a metamorphosed “financing constraint problem”
became more pronounced. We shall leave clarification of this point for future study.
2.4 Interpretation of the Coefficient on Corporate AgeReturning to estimation not including coefficient dummies, we see that the coefficient on AN
was significantly negative in Phases 1 and 2, and negative but statistically not significant in Phase
3. There was thus no verification in relation to Hypothesis 2-1 on the effect that “the greater theage of a corporation, the stronger the tendency to consider not only maximization of shareholder
benefits but also those of employees, boosting investment to that extent.” Rather than a rejectionof Hypothesis 2-1, however, this suggests that another characteristic of corporate age as a proxyvariable for growth opportunities arose. In actuality, looking at estimation results by industry
category, among manufacturers which are more mature in comparison to the non-manufacturingindustry where there are fewer companies newly listed or publicly traded, we see in Phase 3 apositive significance for the coefficient on corporate age (Table 3-3). Regarding Hypothesis 2-1,
we will test further estimation incorporating the results of the attitude survey.
2.5 Comparison of Manufacturers and Non-manufacturers
As we have seen, there are no great differences between manufacturers and non-manufacturers
regarding the principal points at issue. But focusing on those differences, we note the following
regarding the effect of fundamentals. Although differences in ROA and SGR are not statisticallysignificant, for manufacturers the coefficient estimation values are consistently higher, while
those for PBR are higher for non-manufacturers (though again the differences are not statisticallysignificant). Broadly, we hypothesize that manufacturers are responsive to the immediatesituation, and non-manufacturers to evaluation of their future potential. However, this conjectureneeds to be verified separately.
3. Estimation Results Using the Combined Data Set and Its Interpretation
We now examine estimation results using a relatively small sample combining financial data andthe results of the investment behavior attitude survey. The number of samples in cross section(number of companies) is a maximum of 1,038, and 4,620 on time series pooling (FY 1994-98),
and was thus just over one-third the size of the estimation using the basic data set (financial dataonly). Estimated coefficient values with the results of significance testing are shown in Table 3-6.
The estimation results of financial data-related explanatory variables show almost the sametendencies as estimation using the basic data set, and we believe that the sample bias arising fromcombination with the attitude survey can be ignored.
3.1 Testing Hypotheses on Japanese Style of Investment Decision-making Criteria
Looking at the estimation results of four constant dummies – growth tendency, bottom-up styleof decision-making, following and emulating tendency, and certainty tendency – we observe
overall that all of the coefficients on the four constant dummies satisfy the sign conditions
30 Development Bank of Japan Research Report/ No. 12

(certainty tendency is negative, all others positive), and are statistically significant in at least twophases. From this we infer the existence of Japanese special characteristics related to investment
decision-making criteria, namely, the broad tendency toward higher investment by companies
where there is focus on growth, bottom-up style of decision-making, and following andemulating tendency (Hypotheses 2, 2-1 and 2-2), but lower investment among companies
focusing on certainty (Hypotheses 3).
Table 3-6. Estimation Combining Financial Data and Attitude Survey Results
Sign
D20

(Growth tendency dummy)＋

D21(Bottom-up dummy)＋

D22(Following and emulating tendency
dummy)＋

D30(Certainty tendency dummy)

－

ROA

＋

PBR

＋

SGR

＋

LNK

＋
D50 (Main bank, stable shareholder
dummy)DER－－

D50 (Main bank, stable shareholder
dummy)AN＋＋

Model Usedp-value of F test related to existence of individual
effects
p-value of Hausman test’s χ2 statistic
Number of Valid Samples
Number of Companies (Maximum Values)

FY 1982-86(Phase 1)

FY 1988-92(Phase 2)

FY 1994-98(Phase 3)

8.77×10-2
2.32 *
1.34×10-2
0.49
17.3×10-2
4.41 **-9.73×10-2-3.44 **
1.28
3.11 **
18.2×10-2
6.89 **
8.77×10-1
5.51 **
5.92×10-2
3.33 **
0.67×10-2 ×
0.18-21.2×10-2-10.5 **
-2.53×10-2 ×-0.80-3.96×10-2 ×
1.00
POLS

7.60×10-2
2.19 *
6.80×10-2
2.50 *
11.8×10-2
2.48 *-7.24×10-2-2.58 *
4.49
11.2 **-2.68×10-2 ×
1.00-0.00×10-1 ×-0.74
18.0×10-2
13.4 **-0.22×10-2-0.08-3.23×10-2-1.75-0.38×10-2 ×-0.15-4.99×10-2 ×
-1.26
RE

15.3×10-2
4.52 **
11.3×10-2
3.46 **
4.77×10-2
0.86-12.7×10-2-3.33 **
5.77
9.06 **
12.7×10-2
3.45 **
9.58×10-1
4.01 **
7.21×10-2
3.77 **
7.06×10-2 ×
1.34-8.74×10-2-3.73 **
-5.89×10-2 ×-1.39-20.2×10-2 ×-3.63 **
FE

0.087

0.000

0.000

－
3,438
751

0.115
3,833
897

0.000
4,620
1,038

Remarks: See Table 3-2

Looking now at individual special features for each, we see that the coefficient on growthtendency dummy is statistically significant for all phases, with estimation values (those inparentheses are for the 95% confidence level; the same applies hereinafter) of 8.77 (1.35-16.2) for
Phase 1, 7.60 (0.78-14.4) for Phase 2, and 15.3 (8.68-22.0) for Phase 3; the Phase 3 values arelarge but the differences are not statistically significant. The coefficient on bottom-up dummy is
not statistically significant for Phase 1, but is for Phases 2 and 3; as we would expect, the Phase 3
values are larger, but the differences among the estimation values are not statistically significant(Phase 2, 6.80 (1.46-12.1), Phase 3, 11.3 (4.90-17.7)). It is not correct to conclude from this thatthe so-called “Japanese characteristics” are becoming more pronounced, inasmuch as in theDevelopment Bank of Japan Research Report/ No. 12 31

previous chapter we saw that in both the growth and bottom-up types the Phase 3 selection rates
declined in comparison to those of the 1980s (Phases 1 and 2). Consequently, even though Phase
3’s coefficients are larger, this is not the overall trend; rather, it is more appropriate to interpretthat the companies focusing on growth and bottom-up style at present have stronger tendencies
than others. In contrast, the coefficient on following and emulating dummy was the exact
opposite of that of the bottom up, being significant in Phases 1 and 2 – 17.3 (9.59-25.0) and 11.8
(2.47-21.1), respectively – and with values being larger in Phase 1, although the differences were
not statistically significant. Phase 3’s estimation values were not significant by themselves. The
decline in the selection rate for following and emulating tendency reveals the weakening influenceof this Japanese special characteristic compared to the 1980s. At first glance growth, bottom up
and emulating appear to be similar modes of behavior, but the reason why the influence ofemulating tendency alone has clearly weakened is thought to be closely linked to the recent
abandoning of industry practices such as fixed market shares and strong regulatory guidance.
The coefficient on certainty tendency dummy was statistically significant for all phases. The
estimation value for Phase 1 was–9.73 (-15.3 to -4.19) and for Phase 2 was–7.24 (-12.7 to -1.75).
In comparison, the value for Phase 3 was larger (in absolute value) at –12.7 (-20.1 to -5.20),
though the difference is not statistically significant. Despite the fact that in comparison to the
1980s the proportion of companies selecting certainty increased, it is noteworthy that thischaracteristic was not diluted. In other words, regarding emphasis on certainty of recouping
investment, we believe that intensifying global competition and the consequent difficulty offorecasting the business environment have had a more pronounced effect as a “Japanese special
characteristic” in comparison to the 1980s.
3.2 Testing Hypotheses on Influence of Japanese Style of Corporate Governance on
Investment
Moving to the estimation results for the main bank/stable shareholder dummy, which is thecoefficient dummy for LNK and DER, we see that none of the coefficient dummies are
statistically significant. As for Hypothesis 4 (influence of internal funds and debt-equity ratios,
and its changes), the estimation results using the basic data set of the previous section suggeststhat listed and publicly traded companies in their entirety have been in a situation of liquidity
surplus rather than financing constraints during the 1980s and 1990s. Then in Phase 2, internalfunds and the disappearance of investment restrictions of debt had a notable investment
acceleration effect, and consequently abundant internal funds suggested the existence of the free
cash problem that is linked to inefficient investment. Besides, the estimation results with thecoefficient dummy of this section show that in such a situation, main banks/stable shareholders(more precisely, main banks/stable shareholders as investment accelerants) did not influence theacceleration effect of internal funds and the restrictive effect of debt. As for listed and publicly
traded companies since the 1980s, if Japanese style of corporate governance played no role inresolving the financing constraint problem or preventing the free cash problem, neither did theyworsen them; they were in fact generally neutral factors that had no influence.
Supplement: Testing the Existence of Free Cash Problem
The logic of the free cash problem is that, if a corporation already possesses ample cash for
efficient investment, then an additional increase in internal funds will result in inefficientinvestment. By analyzing the empirical evidence, however, it is relatively easy to prove theproposition that “the increase in internal funds is used for investment” but it is difficult to
examine whether or not a company “originally had ample cash to fund efficient investment.” In
previous studies as well, classification of a company’s financial status continues to rely on trial
32 Development Bank of Japan Research Report/ No. 12

and error. In this report, the analysis was carried out with the debt-equity ratio as a proxy variable,
leading to a tentative conclusion, so further verification is necessary.
In addition to refining our methods of classifying corporate liquidity situations, we can
examine from individual corporate data the effects of investment on subsequent corporate
performance. For reference here, we will use the same samples as in the panel analysis for a
simple test following the tendency of the latter, and vis-à-vis FY 1998’s ROA we will examine bycross section its correlation with investment behavior for each fiscal year since the 1980s. If weconsider the number of years of useful life of facilities, those acquired in the first half of the
1980s are unlikely to have had any direct influence on FY 1998’s ROA, but here we focus onwhether or not the behavioral “pattern” exhibited in each fiscal year’s investment is consistent
with present ROAs (market evaluations).
Specifically, we will first conduct a regression analysis for each fiscal year t where the fixed
dependent variable FY 1998’s ROA98 is explained by standardized investment ratio NIKt =(I/K)t (I/K)80 as a single explanatory variable with a constant term. Standardization is required tocontrol the industrial attributes (number of years of useful life of facilities, differences in growthpotential, etc.) reflected in I/K and to educe only the portion related to pure corporate strategy.
We take FY 1980, which is believed to be broadly neutral in respect of such major changes as theappearance and collapse of the Bubble, as the benchmark year. The estimation results are shownin Table 3-7 (estimation formula 1). Because this is a cross sectional analysis by each fiscal year,
the estimation’s performance in respect of statistic significance is not very good, but only over aseven-year period (FY 1986-92) centering on Phase 2 it is noteworthy that the sign of thecoefficient became negative. Of course, changes in the industrial structure have led to great
differences (negative correlation) between the former investment behavior (NIKt) and the present
market evaluation (ROA98), but we would generally expect such tendency to become stronger
with greater differences in time, and the positive values prior to FY 1985 are not in conformity.37
Consequently, the FY 1986-92 coefficient suggests the special investment behavior characteristics
of Phase 2, similar to the results of the macroeconomic analysis and panel analysis of micro-level
data. This is supported by the fact that within the seven-year period FY 1991’s estimation values
were the largest and most significant.
Table 3-7. Correlations Between Each Fiscal Year’s Investment Ratio and FY 1998’s ROA
Estimation formula 1

Note:

ROA98 = α + βNIK t + ε in which NIK t = ( I / K )t − ( I / K )80

ROA is expressed as a percentage, and I/K is a logarithmic conversion value of a percentage expression.

Estimation formula 2 (with an additional explanatory variable of previous period’s ROA)
ROA98 = α + β1 NIKR t + β 2 ROAt −1 + ε
Note:

37

Regarding NIKR, we first compute the elements not explained by the previous period’s ROA based on the results ofpanel data estimation and others, and then like NIK, take the differential relative to FY 1980. Others are the same asin estimation formula 1.

Although FY 1981’s coefficient estimate values are large and statistically significant, there is not much sense in seeking areasonable interpretation for this because of the closeness to the benchmark year.
Development Bank of Japan Research Report/ No. 12 33

Overview of estimation results
Fiscal
Year
97
96
95
94
93
92
91
90
89
88
87
86
85
84
83
82
81

Estimation Formula 1
NIKt
Estimation Value (t-value)
2.92 ( 7.90) **2.31 ( 3.37) **1.17 ( 2.41) *0.68 ( 1.79) ・0.09 ( 0.23)-0.66 (-1.46)-0.97 (-2.14) *-0.16 (-0.38)-0.64 (-1.28)-0.39 (-0.70)-0.34 (-0.66)-0.30 (-0.68)
0.03 ( 0.04)
0.65 ( 1.56)
0.37 ( 0.76)
0.15 ( 0.27)
1.35 ( 2.25) *Estimation Formula 2
NIKRt
ROAt-1
Estimation Value (t-value)
Estimation Value (t-value)
2.59( 6.18) **0.015( 0.22)1.40( 2.56) *0.120( 3.32) **0.89( 1.82) ・0.042( 2.02) *0.67( 1.69) ・0.002( 22.7) **0.05( 0.12)-0.002(-0.21)-0.73(-1.53)-0.000(-0.02)-0.97(-1.98) *0.017( 1.27)-0.44(-0.95)-0.016(-1.69) ・-1.06(-2.21) *0.024( 1.29)-0.72(-1.30)0.020( 0.77)-0.48(-0.87)0.048( 2.09) *-0.28(-0.63)-0.004(-0.15)-0.52(-0.99)0.022( 1.39)0.53( 1.27)0.037( 2.55) *0.26( 0.52)0.083( 2.15) *0.21( 0.39)0.071( 2.08) *2.36( 3.48) **0.088( 3.98) *Remarks
1. The shaded areas denote negative coefficient estimation values.
2. Two asterisks ** to the right of the t-value show the 1% significance level, one asterisk * the 5% level and a dot • the 10%
level. As in Table 3-2, the heteroscedasticity consistent standard error (HCSE) is used in computing t-values.

Using only the analysis results of estimation formula 1, however, we cannot link the special
characteristics of investment behavior of Phase 2 to the free cash problem, because we cannot
remove the possibility that this phenomenon merely reflects changes in ROA, which is the mostimportant determinant of investment level. If so, the special characteristics of Phase 2’s
investment behavior may merely reflect a completely changed result of the ROA or market
evaluation itself, and not a change in the corporation’s investment principles.
Next, we extract from the investment ratio I/Kt the components not explained by ROAt-138
and, as with NIK, define as NIKR the standardized level of FY 1980. With NIKRt and ROAt-1 as
explanatory variables, we then conduct another regression analysis using Formula 2 for eachfiscal year t. Looking at the estimation results in Table 3-7, we see that, in the seven-year period
in which the coefficient on NIK was negative, there were only three years in which the ROAt-1
coefficient was negative, whereas the NIKRt coefficient was negative in all fiscal years and was,moreover, statistically significant in FY 1989 and FY 1991. The special characteristics ofinvestment behavior in Phase 2, in other words, were very likely caused by other than ROAchanges, which supports the conclusion of the panel analysis that the free cash problem appearedin Phase 2.

38

This is equivalent to the remaining difference after subtracting from I/Kt the panel analysis-derived ROAt-1 coefficientestimation value x ROAt-1. The coefficient on ROAt-1 is fixed within each estimation period (phase), and we took the average ofthe beginning and ending of the estimation period as for the central year.

34 Development Bank of Japan Research Report/ No. 12

Conclusion
In this report we have sought to rearrange various points of dispute related to Japanese
corporations’ investment behavior, and have approached its special features and changes in andafter the 1980s using both macro and micro-level data for a comprehensive verification.
Although some issues related to further proof and empirical analysis methods remain to be
improved, we review below the results and summarize Japanese corporate investment behavior
centering on listed and publicly traded companies.
1. Japanese corporate investment behavior in the 1980s and 1990s has tended to increasingly
reflect differences in ROA and their changes, and to focus on certainty of recouping investment.
This has been a consistent metamorphosis, prompted by intensifying global competition andharsh business outlook, a shift in inter-company relations from informed mutuality to arm’s
length, and greater predominance of market evaluations of management results and financial
condition.
2. This trend was disturbed by the special characteristics of investment behavior in the Bubble
years. This was a long-lasting period of good business conditions and a financial environmentthat favored borrowers, thus causing the free cash problem which likely pushed up investment toinefficient levels. Unless this point is considered, a simple comparison of investment behavior in
and after the Bubble may lead to overestimation of the magnitude of change. The characteristics
of investment behavior today have more in common with those of the first half of the 1980s
than the Bubble years.
3. Investigating the points of dispute regarding the Japanese-style enterprise theory for listed andpublicly traded companies in and after the 1980s, we broadly confirm the existence in the 1980sof special characteristics related to such investment decision-making criteria as long-term
perspective, growth and emulating tendency. A growth tendency and others also exert someinfluence at present. However, we were unable to confirm the influence of main banks and stableshareholders, i.e. the special characteristics of Japanese-style corporate governance. Therefore,
following on from this report’s analysis, we need to identify the various causes of the fixed
concept of Japanese-style special characteristics in more detail, and investigate which of them areessential characteristics.
4. Regarding the major changes in investment behavior – pursuit of capital efficiency and stresson certainty – in light of the Japanese-style enterprise theory, we conclude that the former is aconvergence toward worldwide trends (or, departure from the Japanese focus on long-term
perspective and steady investment behavior), and that the latter is a strengthening of Japanesestyle focus on certainty. The shift in investment behavior toward capital efficiency and pursuit ofcertainty is restraining and destabilizing investment during the transition process, and thisinfluence is seen on macro-level investment as well. However, by improving the quality ofJapanese corporations over the intermediate and long term, we anticipate that investment will
flourish in growth fields.
［Junichi Nakamura (E-mail: junakam@dbj.go.jp )］Development Bank of Japan Research Report/ No. 11

35

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38 Development Bank of Japan Research Report/ No. 11

List of Back Numbers (Including JDB Research Report)
No.12

Emipirical Reassessment of Japanese Corporate Investment Behavior: Features and Changes since the1980s, based on Micro-level Panel Data (This issue)

No.11

Survey on Planned Capital Spending for Fiscal Year 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, May 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.81The 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 Datefrom 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 FY 1995, 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 FY 1994, July 1995
No. 48 Strategies for Improving the Efficiency of the Japanese Physical Distribution System: Part2, 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 FY 1993, 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 August1990,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