Does government promote or hinder capital
accumulation?

Evidence from Japan’s high-growth era

Mariko Hatase
Yoichi Matsubayashi

February 2016
Discussion Paper No.1602

GRADUATE SCHOOL OF ECONOMICS
KOBE UNIVERSITYROKKO, KOBE, JAPANDoes government promote or hinder capital
accumulation?
Evidence from Japan’s high-growth era
Mariko Hatase †, Yoichi Matsubayashi‡This Version: February 2016

Abstract
Governments occasionally intervene in private sector economic activities to promote
specific industries and enhance economic growth. During Japan’s high-growth era, thegovernment used various policy tools to intervene in private sector capital investments.
We examine the effects of these policy tools on capital accumulation. We employ firmlevel data sets, identify policy actions using historical records and find that they wereapplied intensively to specific sectors and firms and that government intervention
partially affected those firms’ capital investment decisions. For some industries, such as
steel, chemicals and textiles, investment-promoting policy tools resulted in accelerating
capital investments or relatively higher resource allocations of capital to labour. There
were also cases in which policy actions aimed at curbing investments resulted in slower
investments or lower allocations of capital to labour, but the effects were weak and small.
Discouraging policy tools had contradictory effects on some industries and enhanced
capital investments. The latter phenomenon was observed when the government
attempted to control private sector capital investments based on the current share of
production or production capacities.
JEL classification: E22, N15, O25
Keywords: capital accumulation, industrial policy, capital distortion, high-growth era†Bank of Japan‡Graduate School of Economics, Kobe University

The views expressed here are not those of the Bank of Japan or any other organization with which theauthors are affiliated. We are grateful to Susano Basu (Boston College) and Simon Gilchrist (Boston
University) for their comments during an earlier stage of the project. For their helpful comments onan earlier draft, we thank Tsutomu Miyagawa (Gakushuin University), participants at the 2015
Japanese Economic Association Autumn Meeting (Sophia University) and the seminar at the Tokyo
University of Foreign Studies.

1. Introduction
Public entities often intervene in private sector economic activities for various reasons, and economic
growth tends to be the motivating factor behind such interventions. The effects of industrial policy—
defined as the government’s actions to intervene in private economic activities such that they affectindustrial structure1—on economic growth have been examined for decades in a significant numberof studies. Some previous studies were sceptical about the overall effects of industrial policy on
economic growth. For example, the World Bank (1994) found that industrial policy generally
increased growth rates by less than one per cent. Despite such negative views, the role of governmentin enhancing economic growth has been a regular theme in policy debate.2
To conduct effective policies, it is necessary to examine the effects of each policy
intervention tool. Governments attempting to intervene in industrial activities frequently rely on awide range of methods, from direct instructions to incentive mechanisms.
The results of empirical studies on the effects of such policy tools on targeted industries are
mixed. For example, Beason and Weinstein (1996) reported that industrial policy tools in Japanaffected growth, capital investments and outputs, but they did not increase productivity. Noland (1993)
found that they affected trade specialisation. Lee (1993) concluded that industrial policy affected theindustrial structure through scale economies, whereas Noland and Pack (2003) noted that considering
the aggregate data sets used, this outcome through the calibration of a general equilibrium model was
not plausible. Yamawaki (1988) stressed that the decisions of each firm dominated capital investmentsin the steel industry in Japan during the high-growth era, even though that industry is known as a targetof an aggressive industrial policy. Tsuruta (1988) stated that policies were influential in the

1 The World Bank (1993) distinguished industrial from trade policy and defined it as ‘government efforts
to alter [the] industrial structure to promote productivity-based growth. Productivity-based growth may
derive from learning, technological innovation, or catching up to international best practice’ (p. 304). The
definition by Komiya (1984) states, ‘the central mission of industrial policies is to solve market failures
regarding resource allocations’ (p. 5). Okuno and Suzumura (1986) stated, ‘industrial policy is defined
here as the totality of governmental policies undertaken with the object of changing the allocation of
resources among industries from what it would otherwise be, or intervening in the industrial organisationof a specific industry, in order to enhance a country's economic welfare when unrestricted functioning of
the competitive market mechanism is seen to fail in serving that end’ (p. 24). Noland and Pack (2003)
stated, ‘we define selective intervention or industrial policy briefly as an effort by a government to alter
the sectorial structure of production towards sectors it believes offer greater respect’.
2

The Industry Committee of the OECD compiled a report about Japan’s industrial policy after sending a
mission to Japan in 1972. In it, the chairman of the committee states, ‘industrialised, as well as developing,countries have reasons to look with inquisitive interest at Japanese industrial policy. Many governments
would like to derive—or ought to seek—inspiration and guidance in the Japanese experience when
formulating their own policies’ (Organisation for Economic Co-operation and Development, 1972, p. 5).
The report concludes, ‘in summary, it is clear that Japan's outstanding economic performance since the war
is attributed largely to the close, purposeful co-operation between government, industry, the financial
institutions and labour. Under MITI's guidance, the nation's productive resources have been effectively
marshalled towards the achievement of national economic objectives, leading to build-up of internationallycompetitive industrial capacity in certain sectors’ (Organisation for Economic Co-operation andDevelopment, 1972, p. 170).

2petrochemical industries because the ceiling for capital investments was binding on the surface but
might have had effects that contradicted the original intent of the policy goal because they provokedunnecessary investments. Kiyota and Okazaki (2013) found that the effects of removing foreignexchange quotas, which occasionally worked as industrial policy tools, did not affect productivity,
concluding that the effects of industrial policy in the 1960s were fairly small. Ogura and Yoshio (1985)
estimated the amount by which interest payments and taxes reduced inexpensive public lending andspecial depreciation for capital investments. They concluded that government support to the shipping,electricity and shipbuilding industries had a crucial effect on capital investments, whereas support toother industries increased capital stock by only a small percentage during a recession.
However, the debate on the effectiveness of policies with respect to targeted industries’
investments has yet to be settled because the entire industrial policy system is complicated (Komiya
1988). It frequently seems impossible to identify the effect of each detailed policy action taken by thegovernment among the group of policy tools utilised at the same time in the same industry. For
example, adopting measures that have opposite effects on overall investments, such as simultaneously
allowing only designated machines for work and subsidising the introduction of new machines withnew technology for a particular industry, makes it difficult to scale the effects of each tool.
This study aims to re-examine the contribution of government actions that intervene inprivate sector investment decisions regarding the accumulation of capital stock using newly
constructed data sets at the firm level during the high-growth era in Japan, information on policy
actions extracted by employing the narrative approach and an indicator showing resource-allocation
bias. Previous studies, such as those by Noland (1993), Lee (1993) and Beason and Weinstein (1996),
relied only on macro-level data sets for empirical studies. However, policies are usually detailed for atargeted industry and, thus, tests using macro-level data sets cannot effectively capture its effect. In
contrast, we believe applying firm-level data will enable us to scale the effects quantitatively and moreaccurately. Although Kiyota and Okazaki (2013) were among the few to use micro-level data, theyexamined the effects of policies on productivity rather than on capital stock. Another issue encounteredin previous studies is the endogenous bias problem. Some proxy variables for policy action in previous
studies could be both a cause and a result of a policy action, and the selection of such a variable could
raise endogenous bias problems. The narrative approach, following Romer and Romer (2007), allows
us to avoid this problem. In addition, the continual upward trend in capital investments may have been
the cause of ambiguous results in empirical studies because such a trend can mask the negative effects
of policies on capital accumulation. Hsieh and Klenow (2009) focused on the effects of government
interventions on relative resource allocations, estimating the extent of relative allocation of capitalagainst labour in an industry in which intervention was prevalent and comparing it with an industry
that was subject to no such intervention. The ratio between the marginal cost of capital and that oflabour shows whether there was a ‘misallocation’ of resources caused by external factors in an industry.
3As a first step, it is essential for the public sector to test the results of government
interventions in capital stock if it wants to achieve economic growth through the use of policies. We
take Japan’s high-growth era as an example because it helps showcase policy tools for government
intervention, from the formally institutionalised intervention to informal moral suasions and from theheavily controlled interventionist and paternalistic policy tools to those that rely on market
mechanisms.
The remainder of this paper is organised as follows. Section 2 provides a historical background ofJapan’s industrial policy, primarily during the 1950s and 1960s. Section 3 investigates the effect ofpolicy actions on the capital accumulation of sample industries. Section 4 concludes the paper.

2. Historical Background
2.1 Japan’s high growth, capital investments and industrial policy
In the 1950s and 1960s, Japan achieved high economic growth. The country’s GNP increase
between 1955 and 1971 averaged 9.3 per cent per annum. The GNP components that contributed tosuch rapid growth were capital investments and private consumption (Figure 1).

[Figure 1]

Capital stocks expanded by more than five per cent per annum in the late 1950s and enjoyeddouble-digit growth during the 1960s, according to figures from Long-Term Economic Statistics(Ohkawa et al. 1966). The leading industries that contributed to this rapid growth of capital
investments were steel, which accounted for more than one-third of total investments among large
firms, and chemicals and transport equipment, which accounted for approximately 10 per cent during
the high-growth era. Textiles, paper and pulp also occasionally accounted for a double-digit share(Table 1).

[Table 1]

One of the driving forces behind this rapid capital development was said to be government
policies, represented by the directions of the Ministry of Trade and Industry (MITI). These aggressive
policies were dubbed ‘Japan Inc’. strategies. Through them, the government was believed to play asignificant role in economic growth, although the extent of its contribution varies across studies.
The goals and means of industrial policy changed over time. Policies implemented
immediately following the Second World War were designed for reconstruction. Because of theshortages of crucial resources and funds, the occupation authorities and the Japanese government
directly controlled resource allocation. Directives and guidance were used frequently to control the4economy (Komiya 1988). The major economic policy-making tools used were material rationing,
price controls and loans by the Reconstruction Finance Bank, which was owned by the government(Kosai 1988).
Once the economic recovery was on track in the early 1950s, policy goals and their meansof implementation shifted. Japan experienced chronic current-account deficits during this period. The
country relied on the temporary military demands caused by the Korean War, which were considereda type of aid from the United States. The primary purpose of the industrial policy at the time was toachieve economic independence aimed at maintaining external balances without temporary militarydemands (Takeda 1989). The intermediate target was the rationalisation of industry, particularly
through the provision of inexpensive coal and steel, which were considered prerequisites forcontinuing economic growth. This method was known as the Priority Production System; under it, thecoal and steel sectors were given top priority in resource allocation (Kosai 1988).
Around this onset of the high-growth period, one of the goals of the previous period—
independence from military demands—was perceived as having been reached to some extent (Takeda
1989). The new goals were accelerating growth, raising living standards and achieving full
employment. Strict controls on economic activities, such as trade, were eventually eased, and theintermediate goal was to improve the competitiveness of Japanese industries. The primary aim
immediately following independence from the Allied Powers in 1951 was export promotion; however,from the mid-1950s, the focus shifted to promoting investments. Increases in exports were graduallyseen as having been realised because of investments (Takeda 1989). To bring about their rationalisation,
the targeted industries were given public financial support, such as exemptions from import tariffs andloans from the government and public financial institutions at relatively low interest rates. At the sametime, the government took the initiative of developing medium-term investment plans for thoseindustries considered important. The prevailing thought in government was that allowing private firms
to decide on their investments was insufficient as a means to avoid recession, and interventions by thegovernment in the decision-making process of the private sector were justified. It was considerednecessary to promote investment through the provision of incentives to important industries. The
major targeted industries for rationalisation were coal, steel, copper mines, chemical fibres andelectricity (Takeda 1989). The steel industry was subject to three government-led rationalisation plans(Kosai 1988). The textiles industry was also sometimes viewed as a priority industry for industrial
promotion (Takeda 1989).
Changes in the international environment during the 1960s led to a shift in the goals andmethods of industrial policy. Improving Japanese industries’ competitiveness to a level sufficient forsurvival in international markets was prioritised in economic policy (Tsuruta 1988). Tradeliberalisation continued globally during this period. In such an environment, Japan started subjecting
itself to obligations under Article 8 of the Agreement of the International Monetary Fund (IMF) in
51964, and it was required to abolish all types of controls on current-account transactions. Japan becamea member of the Organisation for Economic Co-operation and Development (OECD) in 1964.
Although the IMF allowed its members to impose restrictions on capital-account transactions, theOECD required free capital transactions for its members and asked Japan to liberalise its direct
investments in 1965 (Washizawa 1991). Joining such international organisations meant integrating theJapanese economy with international markets and receiving less protection from the government.
Domestic firms were expected to face fiercer competition once restrictions protecting domestic
industries were lifted. Improving the competitiveness of important industries became the goal of
economic policy. Steel was considered an export industry and the basis of other export industries.
Machineries and chemicals were expected to increase export volumes and thus were also treated asimportant (Takeda 1989).
To adapt to changes in international environments, the government pursued the liberalisationof economic activity. Direct policy tools, such as foreign-exchange rationing, were seen as ineffective.
Industrial policy tools changed accordingly; direct-control policy tools, such as setting investment
ceilings, gave way to indirect means to control incentives that relied on market mechanisms (Takeda
1989). Except for designated cartels, the major tool of industrial policy was inexpensive lending by
the Japan Development Bank (JDB) and other public financial institutions. Many of the policy
initiatives in the general machinery, electric machinery and transport equipment industries—theleading industries from the late 1960s described in the official history of the MITI—were funded by
the JDB or other public financial institutions. Even for the steel industry—one of the major targets ofintensive intervention by the government—only three out of eight policies called for direct means, andthe others represented inexpensive funding to rationalise the industry. The JDB had access to the Fiscal
Investment and Loan Programme, which collected public deposits through the Postal Savings system
and mobilised the public pension system’s resources. In addition, given its higher credibility throughits government guarantee as opposed to a private bank, the JDB could raise money inexpensively, evenin overseas markets. For instance, the JDB could float bonds in New York in 1961. Its role was tosupplement private funds, and its lending practices were not very different from commercial lendingin terms of borrower credibility. The interest rates offered by the JDB could be lower than those ofprivate banks, but they had to be at a level sufficient to cover funding costs, operational costs andlosses caused by its lending activities (Hidaka 2009). Following an era of high growth, the content ofindustrial policy changed significantly (Komiya 1988).

2.2 Institutional features of industrial policy
Policies in the 1960s at the time tended to be planned and implemented by sector rather thancovering all industries. One of the reasons for this was the role played by the institutions. The major
controller of industrial policy was the MITI. Primary decision-making bodies within the MITI were6

bureaus for each industry (industrial branch bureau). For example, the steel division in the heavy andchemical industry bureau dealt with matters related to the steel industry. The policies planned by abureau covered only the sectors over which the bureau had administrative powers. Inter-sector policies
were sometimes made, but this was not widespread.
The other major player was the Fair Trade Commission (FTC) because the policy
instruments frequently took the form of permissions from the commission to form designated cartelsor to coordinate capital investment plans and become exempt from the purview of antitrust legislation.
Occasionally, formal legislation was behind such actions, such as the Machinery Industry Promotion
Temporary Measures Law (MIPTM Law), which was passed by the Diet in 1956; this law contained
a clause permitting cartels as an exception to the antitrust law.
Credits by the JDB and the Japan Finance Corporation for Small and Medium Enterprise(JFCSME) were the major tools aimed at encouraging investment. Some lending schemes were backed
by law. For example, based on the MIPTM Law, machine tool firms could borrow from the JDB atrelatively lower rates. The Electric Machinery Industry Promotion Temporary Measures Law, similar
to the one for general machineries, was enacted in 1957.
Councils set up to coordinate opinions of the government and private firms were the central
bodies for policy formation. Under the policy council system, important policies were first discussed
in a council. Reports were then sent to the ministries responsible for the industry in question. The
system became established as the main protocol in the 1960s, and the Industrial Structure Council(ISC) sat at the top of the hierarchy. Members of the ISC were usually former bureaucrats, journalists
and representatives from private sectors. Steel was one of the active areas discussed by the ISC.
Policy enforcement was sometimes based on the law; however, in many cases, policies wereconducted informally. In the case of the steel industry, the government attempted to coordinate capital
investment decisions among private firms by relying on administrative guidance rather than on legal
grounds.
3. Empirical Analysis
Using the facts laid out in the previous section, we analyse whether the policy actions
affected private capital investments and achieved the intended effects.

3.1 The target industries
The industrial policy was often implemented by sector. Steel, textiles, chemicals and pulp
and paper were the sectors targeted for intensive government intervention (Itoh et al. 1988, Tsuruta
1988).3 We focus on these sectors to examine the effects of policy actions.
3

The MITI had an industrial branch bureau specialising in the chemical industry. Other branch bureaus
specialised in the heavy; textiles and general merchandise; public utilities; and minerals, oil and coal mining
industries (OECD, 1972).

7

3.2 Data
A detailed analysis of the policies on capital investments requires firm-level data sets. For
the corporate side, we construct semi-annual data sets from 1964 by drawing on the statistics compiledby the Mitsubishi Economic Research Institute (Mitsubishi Keizai Kenkyu Sho). These statistics arebusiness figures originally published in financial statements for stockholders or investors. One of theadvantages of using these figures is their quality; the financial reports were compiled in compliancewith regulations, and the variability in data arising from differences in the definitions used by firms is
expected to be small. We collected firm-level data sets for capital stocks and sales from Mitsubishi
statistics. The coverage of Mitsubishi statistics for capital investments against the survey for thefinancial statements statistics of corporations by industry, which is used for estimating GDP statistics,
is 47.8 per cent in the manufacturing sector in 1965. We also rely on this statistic when defining subsectors for chemicals, textiles and pulp and paper to divide these sectors into categories that are moredetailed and to analyse the effects of policy actions.
We draw on industry-level data when firm-level data are not available. For wages, we use
data from the monthly labour survey by industry. For variables representing policy actions, we apply
the narrative approach introduced by Romer and Romer (2007). They used narrative records, such aspresidential speeches, executive-branch documents and Congressional reports, to identify the size,
timing and principal motivation for tax policy actions. This approach enables researchers to identify
exogenous policy actions in various fields. Some previous studies used the gap between averagelending rates and rates for one particular industry as a proxy for public lending if the latter were lower
than the former. On the one hand, such a gap can be interpreted as a policy action. On the other, it canshow the results of public lending because lower interest rates could be an outcome of the supply of
extra funds through public lending. These types of problems force us to adopt a cautious approach tointerpreting the results of estimates. In contrast, taking one policy action in a historical record as avariable enables us to avoid an endogenous bias. We utilise the official history of the MITI, theJFCSME and the annual reports of the FTC to determine the historical records from which to extract
policy actions. The advantage of relying on these official histories is that they cover all types of tools,
regardless of formality and intent. The types of policy tools aimed at private capital investments were
wide ranging, from formal orders backed by law to informal moral suasions by ministries and frominvestment-stimulating ones to investment-discouraging ones. The policies that attempted to control
capital investments frequently had motivations that contradicted each other. Some industries were
subject to both investment-stimulating and investment-discouraging methods. Therefore, we needrecords that cover both categories of policy tools with information on the direction of the expected
effects to examine their outcomes accurately.
We pick all policy actions that attempted to control the amount of capital investments for a8particular industry and classify them into two categories: those that aimed at encouraging investments
and those that aimed at curbing them. For example, inexpensive public funds were provided to special
steel manufacturers in 1964 to increase productivity. We classify this action as an investmentpromoting policy action. The MITI and the FTC frequently issue orders prohibiting additional
investments for a particular industry, such as textiles, to maintain ‘orderly competition’. We classify
these actions as investment-discouraging actions. The list of both types of policy tools we use as
variables is available in the appendix.4

3.3 The implementation of policy actions
We first examine how policy tools were applied to each firm in the four major targetedindustries using the Mitsubishi data and historical records mentioned in the previous section.
Table 2 shows when the policies were applied to each firm between 1964 and 1972.5[Table 2]

Policy actions, regardless of whether they were investment discouraging or encouraging,were inclined to be applied intensively by period and sub-sector in an industry. Unlike the stereotypicaldescription of Japanese industrial policies, sometimes labelled as the Japan Inc. model hinting atgovernment intervention in private economic activities, only a limited number of firms and sectors
were subject to such intensive policies in the 1960s. 6 For instance, in the steel industry, theinvestment-discouraging actions aimed at controlling the volume of investment, such as postponing

4

Apart from the instruments in the appendix, direct subsidy and special depreciation were frequently
mentioned as major policy tools. We exclude these two tools from our variables. The former primarily
represented measures used during the reconstruction period rather than the high-growth era. For the latter,accurately determining the point at which one policy action was applied to one industry is difficult
because the special depreciation system was complex due to its inclusion of a series of institutionalchanges. Even the Tax Institution Council for the government claimed in a report that ‘only the specialist
with high skills can tell if one case is subject to the special depreciation as standards for the application
was set in details’, and the number of industries to receive special treatment exceeded 2,000 (Ogura andYoshino 1988).
5With respect to controlling investment plans for blast furnace steel manufacturers, the list of target
firms is available from the Japan Iron and Steel Federation (1969). For other policy actions, we assume
that a firm producing a particular product, subject to some kind of intervention by the government, was atarget company for a policy action. For example, a company producing polyvinyl chloride pipes isassumed to be the subject of restrictions for capital investments since November 1967. We collectinformation about products for each company from financial statements for the first half year of 1965 foreach firm; if that is not available, we use one closest to that period to specify the products.
6

To interpret the phenomena that appear in this table, the following facts should be noted; the Mitsubishi
statistics only cover listed companies, and the results in the table could underestimate the coverage ofgovernment actions as small and medium sized companies, which are excluded from samples of the
Mitsubishi data series, were often subject to stimulative policies.

9

investments for a specified period, were applied mainly to blast furnace steel manufacturers, whereas
those aimed at encouraging investments were mainly applied to non-blast furnace steel producers. For
chemicals, pervasive official controls were only imposed for sectors producing specific products, suchas ammonia, polyvinyl chloride products and petrochemicals; manufacturers producing final
consumer goods were rarely covered by policy actions.7 The spinning industry was the major target
in textiles in this period, while woollen manufacturers, who were frequently subject to various policy
actions in the 1950s, were free from government interventions in this period. For pulp and paper,
paperboards and core base papers were the major targets of industrial policy.

3.4 Effects of policy actions on capital investment levels
The conclusions of previous studies on the effectiveness of policies are mixed. Some studies
say policy actions had the intended effects. Other studies are sceptical for various reasons, including
the overwhelming characteristics of each firm’s decision and the small share of public funding in total
capital investments. In this section, we estimate the effects of policy actions on each industry using
firm-level data sets for the steel, chemicals, textiles and pulp and paper industries. These fourindustries meet the conditions of having been subject to more than three initiatives during the sample
periods and of being named a major target of industrial policy. These four industries accounted forover half the total capital investments for major firms during the high-growth era (Table 1).
Investments in these four industries increased rapidly, particularly during the 1960s and the early
1970s (Figure 2). The target sectors for industrial policy were both growing and declining (Noland1993). The four industries mentioned above fall in either category. The steel industry and chemicalindustry are considered samples of growing industries, whereas the textiles and pulp and paperindustries are samples of declining industries.

[Figure 2]

As shown in Table 2, policy actions were applied to a limited number of firms producing
specific products or relying on specific technologies; therefore, we divide these four sectors—steel,chemicals, textiles and pulp and paper—into sub-sectors. For steel industries, we categorise firms as
either blast or non-blast furnace steel manufacturers to estimate the effects of official interventions
because these two types of manufacturers tended to be treated differently for industrial policy.8 For
example, MITI implemented the rationalization plan for non-blast furnace steel producers (Hira-denro
7Companies categorized as 'other chemical products' in Table 2-2 are mainly those producing consumer
goods.
8
We classify a firm as a blast furnace steel producer if it is listed as having blast furnace facilities in theJapan Iron and Steel Federation (1969) table of firms.

10meka gourika taisaku) in 1965 (MITI, 1990). For other industries, we follow the definition of the
Mitsubishi statistics or historical records. As a result, we analyse the effect of policy actions for sevensub-sectors: blast furnace steel manufacturers with seven firms, non-blast furnace steel manufacturers
with 18 firms, organic chemicals with 13 firms, inorganic chemicals with 16 firms, cotton and staple
fibres with nine firms, pulp with four firms and paper with 11 firms. We estimate the following
equation: =  +  + (1)

where  is the capital investment ratio, calculated as the semi-annual changes in capital stock (thesum of buildings, machinery and other fixed capital) plus depreciation divided by the amount of capitalstock (fixed capital) at the end of the previous term;  is the profit ratio, calculated as semi-annual
net profits divided by the amount of capital stock (fixed capital) at the end of the previous term; and is an industrial policy action, which takes the value 1 when an action is taken and null otherwise.
Previous studies that stressed each firm’s decision often noted that policies capping investments were
not effective because the original investment plans by the MITI often ended in larger investments
breaking the ceilings. To clarify the effects of the intentions, we then estimate the equations with two
types of investment policies: discouraging policies (IP1) and encouraging policies (IP2).
We estimate equations without lags, with a one-period lag and with two-period lags because
introducing new equipment or building a factory after an investment decision is made usually takes
time.9 The sample period is between 1964 and 1972 because data on the number of employees areavailable from 1964 and 1972 was the last year in the high-growth period without a two-digit priceincrease before the first oil shock.
We regress the equation using pooled ordinary least squares (OLS) and panels in both fixedand random-effects models. The results of the estimate are presented in Table 3.

[Table 3]

For the steel industry, profits are significant and positive in all cases with one exception, theestimation with two-period lagged variables of fixed-effect estimation in non-blast furnace steel. These
results confirm that capital investments increase when profits expand.
For the effects of investment curbing policy tools (IP1), current or one-period lagged actions
are not significant, whereas those for two-period lags are significant and positive in the case of blast
9

At the time, Japanese firms generally planned investments six months ahead (Okazaki 2002). Someempirical studies, such as Noland (1993), confirmed that lagged variables tend to be significant, unlike
current variables.

11

furnace steel manufacturers.10 These results indicate that tools intended to discourage investments did
not have an effect in the short term and may have had an effect on the policy goals in the long run in
the case of larger manufacturers with blast furnace facilities. The estimates for non-blast furnace steel
manufacturers for the same kinds of actions are mixed. The simultaneous effects are not significant inboth fixed- and random-effects estimations. 11 For one-term lagged periods, it is insignificant but
positive.12 The effects are positive and insignificant in the fixed-effects method and significant in the
random-effects method in the case of two-term lags. 13 Investment-discouraging actions by thegovernment do not seem to have had any solid effects, judging from these inconclusive estimations.
The results of investment-encouraging tools (IP2) appear sceptical for the effects of interventions by
the government because there is no case with significant variables.
For chemicals, profits are significant and positive in all cases for both organic and inorganic
chemicals; capital investments increase when profits expand. Policy tools applied to dampen
investments (IP1) are significant with a negative sign only in a system of simultaneous equations fororganic chemicals, suggesting that government interventions worked successfully only in the shortrun. 14 In other cases, they are insignificant with positive or negative signs. The investmentdiscouraging efforts by the government had a very short-term limited effect on private investments.
For investment-stimulating policies (IP2), simultaneous cases are significant with positive signs only
for inorganic chemicals, whereas others are insignificant with positive signs for both organic andinorganic chemicals. Again, government actions had limited, short-lived intended effects.
Unlike these two sectors, profits are not significant in all cases for textiles (cotton and staple
fibres) and pulp and paper.
For policy variables in the case of textiles, the effects of discouraging tools (IP1) changed
over time; it is significant with negative signs simultaneously, then becomes insignificant withnegative signs with one-period lag and finally turns out to be significant with positive signs.15 Thisshows that government interventions to curb investments worked well in the short term but had the
opposite effects in the longer term. Investment-enhancing policies resulted in success because IP2 issignificant with positive signs; capital investment increased when encouraging tools were applied.
For pulp and paper, actions by the government for calming down investments were generally
in vain because policy variables appear insignificant except in one case—current variable for pulp
sector—which is significant and positive, indicating that it had short-lived undesirable effects.
10

The results of the Hausman test suggest that fixed-effects models are reliable for this sector.

11

The results of the Hausman test for this period are inconclusive.

12

The Hausman test suggests the fixed-effects models.

13

The results of the Hausman test are inconclusive.

14

The results of the Hausman test support the fixed-effects models.
The Hausman test suggests random-effects models.

15

12

Our tentative conclusion is that government efforts to influence the volume of capital
investments had limited weak effects or, in some cases, undesirable effects. Only one sector—
textiles—warranted industrial policy for capital growth, although discouraging policies had only
short–lived effects. Actions for chemicals influenced current investment volumes for direction inorganic chemicals and enhancing investments in inorganic chemicals. The efforts to cap investmentsin the steel sector may have had opposite results six months later or one year later. The same
phenomenon was observed in the pulp sector in the short term, and other actions to influence
investment volumes ended in failure.

3.5 Effects of policy actions on resource allocations
3.5.1 ‘Distortion’ in resource allocations
One of the disadvantages of using a high-growth era as a sample is that determining theeffects of tools aimed at curbing investments is not straightforward because the effects, if any, might
have been masked by overall increasing trends in investments. Although capital investments in anindustry increased under government interventions that discouraged them, the policy action should be
evaluated as effective if the growth rate was slower compared with the case without a policy action.
Another example of the difficulty of evaluating policy effects is when growth in investment continues
but slows down. If the shrinkage of the growth rate was smaller compared with the case in which there
was no investment-supporting government activities, the policy conducted should be assessed as
effective. These types of evaluations require counterfactual tests; however, proper instruments were
not available (Turuta 1988). Thus, the views of previous studies on the effectiveness of government
interventions are mixed.
Instead of conducting counterfactual tests, we apply an indicator introduced by Hsieh andKlenow (2009) to gauge the extent of the ‘distortion’ of resource allocations between capital and labour.
When some ‘distortion’ exists for capital, firms in an industry tend to allocate more capital relative tolabour than when a firm is in a perfectly competitive final output market. This indicator can be aneffective tool in determining the effects of policy actions because the ‘distortion’ can mean the gap
between a relative allocation ratio with and without government interventions. If such gaps areobserved, policy actions are proven to affect the relative allocation between capital and labour.

3.5.2 Theoretical modelThis section introduces a basic theoretical model to capture the effect of a firm’s resource‘misallocation’. Hsieh and Klenow (2009) argued that misallocation of resources between firms within
industries can be crucial to investigate differences in total factor productivity across countries. First,
we provide a brief outline of the Hsieh and Klenow (2009) model.

At the aggregation level, final output Y is produced by combining output from manufacturing
13

using the Cobb–Douglas production technology:

industries
Y = ∏



(2)where θ is the value-added share of sector s and S is the total number of manufacturing industries.
In an industry, heterogeneous firms exist with monopolistic competition. In this case, industry output
is a constant elasticity of substitution (CES) aggregate of  differentiated products:= ∑




where











(3)

is a differentiated product by firm i in industry s and σ is the elasticity of substitution

among factor inputs in . Each differentiated product is produced by firms with heterogeneous

productivity !  , labour "  and capital   using the Cobb–Douglas technology.
# # = !    (4)where  is the input share of capital and is assumed to be different between industries.
The main characteristic of their model is that each firm is not heterogeneous with respect toproductivity and each firm faces idiosyncratic distortions to input and output prices. In their model,
two types of distortions are considered. The first represents output distortions that affect the quantityof production but leave the input mix unaffected. This type is modelled as a tax on production that is
independent of factor use. The second type represents the capital distortions that affect the use ofcapital relative to labour. This type forms the tax on capital and thus affects the input mix decision.
Both distortions are exogenous, calculated from actual data and subsequently discussed. In thisframework, profits depend on not only prices but also two types of distortions. The profits of each firm
are described as follows:$  =   %1 − ()  * − +"  − %1 + (,  *- (5)where π  is the profit, w is the wage rate, r is the rental price of capital, ()  is the output distortionand (,  is the capital distortion. This model assumes that the wage rate and the rental price of capitalare the same across firms. Profit maximisation leads to the standard first condition for which price isa fixed mark-up over its marginal cost. In addition, the optimal capital-to-labour ratio is given as
follows:

14

,0
10

=

# 2



(6)

# 3 %4560 *Isolation of (,  yields the following condition:(,  =# 210# 3,0−1(7)

3.5.3 Measurement of capital distortion
Following the Hsieh and Klenow (2009) model, we attempt to calculate capital ‘distortion’ inJapanese companies using actual data. The previously noted condition indicates that capital distortion
21
is affected by two factors: input share of capital (α) and the labour income–capital income ratio (3,0).
0

L and K are extracted from the Mitsubishi statistics for each firm (for details, see Section 3.1), and w
represents average wages in an industry from the monthly labour survey. αs are the same acrossindustries and are based on calculations in previous studies, and αs is set as 0.5 based on Harada and
Hino (2002), who estimated the labour share from the 1950s to the 2000s and noted that it was a stable
50 per cent during the high-growth era. r is the sum of real interest rates and depreciation rates (Hsieh
and Klenow 2009). Real interest rates were the same across industries, and they are average nominalbank rates applied to new lending in the final month of each term less the inflation rates of capital
goods. Depreciation ratios are calculated by industry, relying on figures in Financial Statement
Statistics of Corporations by Industry; depreciation allowances for fixed assets, excluding intangible
and other assets, are divided by stocks of fixed assets, excluding intangible and other assets. The
average level of (,  for the four industries is shown in Table 4.
[Table 4]
The development of the average (,  shows remarkable differences among industries. When(,  is above one, the industry in question is in a state of undercapitalisation, while it is in a state ofexcess capital when the ratio is less than one. Steel, inorganic chemicals and pulp and paper were
mostly in a state of excess capital throughout the period (with some exceptions in 1972). Organic
chemicals was in a state of excess capital before becoming undercapitalised. Cotton and staple fibres
were always undercapitalised.

3.5.4 Effects of policies on capital ‘distortion’We regress allocation gaps against their one-period lag and investment-discouraging andinvestment-promoting policy actions by industry. The equations are specified as follows:( =  + ( + (8)15

where ( is a ‘distortion’ of relative capital to labour and  is an industrial policy action, taking thevalue of 1 if an action is taken and null otherwise. We estimate the equations in both fixed and random
models. For comparison purposes, we also estimate the OLS using pooled data.16
Again, the seven sub-sectors of steel, chemicals, textiles and pulp and paper are selected, andthe results are shown in Table 5. We find that the results give a different story from the regressions
with the investment ratio as an independent variable.

[Table 5]

The results of one-term lagged independent variables are identical across sectors in all cases,
and they are significant with positive signs.
With regard to the effects of policy actions, those for blast furnace steel manufacturers andnon-blast ones show differences. Investment-discouraging policy tools (IP1) are significant withnegative signs for one- and two-period lags for the former, indicating that government actions curbing
capital investment resulted in larger allocations of capital and thus had the opposite effects of what it
was designed for.17 By contrast, the discouraging actions are insignificant with positive signs for nonblast furnace steel manufacturers, suggesting that government actions did not have any effect. For
investment-enhancing policies (IP2), they are mostly significant with negative signs, indicating thatthey increased firms’ allocation of capital relative to labour in some cases. These results, together withthe results shown in Table 4, suggest that investment-enhancing devices were not strong enough toraise investment volumes but were effective enough to increase relative capital allocations to someextent in the steel industry.
For the chemical industry, discouraging tools (IP1) are insignificant with negative signs inorganic and inorganic chemicals. Encouraging policy tools (IP2) are significant with negative signs
for organic chemicals from current to two-period lags, suggesting that these tools induced higher
shares of capital to labour even though the capital investments did not seem to increase in the longer
term. For inorganic chemicals, IP2 is not significant; thus, the short-lived effects of increasing
investment volumes were not large enough to be gauged by this indicator.
For textiles, discouraging tools (IP1) are not significant, whereas policy-enhancing tools are

16

The OLS estimator for the dynamic panel model used in our estimation is well known to be biased
because the lagged dependent variable generates a correlation with the disturbance term. A solution is toemploy the instrumental variable method, known as the system of generalized method of moments(GMM) estimator, proposed by Arellano and Bond (1991). However, in our estimation, the sample size t
is small, and setting adequate instrumental variables to obtain stable estimation results is difficult. To
overcome this difficulty, we specify both the fixed- and random-effect models.
17

The results of the Hausman test suggest that the fixed-effects models are reliable for this sector.

16

significant simultaneously with positive signs. For lagged policy, the variables are insignificant. These
results show slight divergence from that for investment volumes because IP2 shows positive effects
for lagged cases. This could mean that policy-encouraging tools had a strong effect in the very shortterm, increasing capital allocation in firms to which the policy tool was applied, but the positive effects
gradually faded to a level that could not be captured by this indicator. Therefore, the probable
undesirable results of capping capital investments, which caused an increase in the volume later, were
not serious.
For the pulp industry, policy actions are insignificant in all cases, suggesting that government
efforts to control capital investments were in vain. In the paper industry, the short-lived desirable
effects of hampering allocation of capital are observed because the discouraging tools are significant
with positive signs in the system of simultaneous equations.
In a nutshell, investment-discouraging policies had short-lived weak effects in line with theoriginal goal of the paper industry, but they were generally unsuccessful because in almost all cases,
the policy tools failed to show significance. Investment-encouraging actions, in contrast, worked wellin terms of the direction in steel and organic chemicals. Firms in these industries allocated relatively
more capital to labour when the government employed investment-stimulating policies. Judging fromthe level of ‘distortions’, these policies accelerated excess capital. For cotton and fibres, the target ofintensive government interventions, policy actions had weak, short-lived intended effects, and theycorrected the undercapitalised structure of this industry.18
For some industries, such as non-blast furnace steel manufacturers and cotton, fibre and paper,
policy actions introduced to cap investments might have acted as catalysts for promoting capital
investments. The government’s attempts to achieve ‘orderly competition’ were in vain.
Determining the reasons for the investment-accelerating effects of easing antitrust rules isbeyond the scope of this study. However, some assumptions suggested by previous studies, such as
Tsuruta (1988), could provide an interpretation for our findings. According to Tsuruta (1988),
restrictions on capital investments usually resulted in the allocation of additional capital investments
to each firm based on current shares. A firm with a relatively larger current share in production volume
or production capacity was likely to obtain a larger investment share in the future, and this systemprovided advantages to the haves and disadvantages to the have-nots. Under such circumstances, eachfirm had to obtain certain shares to leave room for future growth. In other words, firms had the
incentive to accumulate as much capital stock as possible when applications of investment ceilings
were expected in the future. Industries that experienced significant policy device variables with
opposite effects of what it was designed for were frequent targets of these ceilings. For example, cottonand staple fibres faced such restrictions seven times, and pulp and paper faced them nine times during
the high-growth era (1955–1973); therefore, the hypothesis could apply to these industries.
18

This interpretation is suggested by Tsutomu Miyagawa.

17

In short, the empirical tests for the four sectors often identified as targets by the government
for intensive policy actions confirm that government interventions were successful for steel, chemicals
and textiles to promote investments, although their effects were sometimes weak or faded easily.
Successful tools often took the form of cheap lending, and investment decisions were usually in thehands of private sectors. In contrast, investment-discouraging tools, generally taking the form ofgovernment orders or collective actions by private firms belonging to the same association, were noteffective in general or were short lived even if they were effective. In some cases, investment-curbing
actions had unintended effects in terms of direction if the industry in question was often targeted for
direct control of volume, although the adverse effects were usually not serious.

4. Conclusion
The Japanese government is said to intervene actively in investment decisions of private
sectors during high-growth eras, and our search of historical records finds that policy tools forcontrolling capital investments tended to be applied intensively to particular sectors and firms. These
interventions affected firms’ capital investment decisions to some extent. For some industries, such as
steel, chemicals and textiles, the investment-promoting policy tools—frequently in the form of
inexpensive funding—led to accelerated investments or relatively higher resource allocations ofcapital to labour. Policy actions aimed at curbing investments by directly deciding the investment
volumes resulted in slower or decreased capital investments in limited cases but rarely achieved lower
allocations of capital to labour. They did have contradictory effects on some industries, enhancing
capital investments. The latter phenomenon was observed in industries that were often a target ofcontrols by the government, such as chemicals, textiles and pulp and paper, where the government
attempted to control private sector capital investments based on the current share of production or
production capacities. To avoid unexpected results, the overall conditions of the industry in question
should be considered, and the mean of highly effective policies and policies without serious adverse
effects should be carefully selected.

18

Figure 1

Components of Growth of Real GNP
20 (y/y,%)Government Consumption

Capital Investment

Real GNP

Exports1510
50Imports

19
71

19
69

19
67

19
63

19
61

19
59

19
57

19
55

19
53

19
51

19
49

19
65

Changes in Stocks

-5
19
47

PrivaeConsumption(Source） Estimate of Long-Term Economic Statistics I, National Income

19

Table 1
The share of capital investments by industry (%)
Generalmachinery

Chemicals

Paper and
pulp

Food

Precision
Instruments

Petroleum

TextilesSteelElectric
M achinery

Non-ferrous
metalTransport
equipment

Ceramics

1960.1

2.92

13.29

10.31

4.18

0.97

2.83

7.20

25.09

14.84

1.25

11.88

5.24

1960.2

2.78

8.65

6.63

3.37

0.83

2.70

5.12

41.88

12.44

1.25

11.14

3.21

1961.1

3.36

11.88

4.67

4.52

1.19

3.24

5.05

34.31

12.90

-0.03

14.38

4.54

1961.2

3.57

11.96

5.53

6.39

1.02

2.21

4.60

30.67

14.71

2.05

12.76

4.50

1962.1

3.21

8.51

4.24

6.89

1.51

2.08

5.85

32.50

14.62

1.05

15.24

4.29

1962.2

2.46

11.61

3.55

6.26

1.82

1.82

7.93

33.71

11.54

0.96

13.24

5.12

1963.1

2.98

10.41

4.45

6.37

2.29

3.27

10.40

29.85

9.32

0.49

15.85

4.33

1963.2

3.35

12.31

4.18

3.59

3.29

2.72

13.84

19.22

9.85

0.43

22.08

5.13

1964.1

2.14

11.43

6.45

4.42

1.57

3.30

11.12

22.48

8.31

0.75

22.92

5.10

1964.2

2.27

13.07

3.93

5.40

1.53

3.31

6.72

25.28

8.71

1.26

25.62

2.91

1965.1

1.50

9.56

7.28

6.46

1.13

4.29

3.76

37.65

5.40

-3.06

23.49

2.55

1965.2

1.46

13.30

5.50

4.53

1.00

2.99

3.58

33.56

13.44

5.18

12.48

2.98

1966.1

2.41

10.74

11.48

4.25

1.69

4.86

4.66

41.02

-4.39

1.75

17.85

3.68

1966.2

2.12

11.46

6.08

2.96

1.28

2.42

5.16

38.14

7.96

1.57

19.07

1.79

1967.1

2.08

7.61

3.58

2.80

1.00

1.85

4.17

52.20

6.34

1.08

14.85

2.43

1967.2

2.01

9.25

5.27

2.19

1.11

2.65

5.65

38.29

8.10

1.18

21.38

2.93

1968.1

2.28

9.98

4.36

2.53

0.99

3.62

4.44

37.28

7.46

1.45

22.64

2.97

1968.2

2.86

8.69

5.64

2.85

1.22

5.74

3.11

37.41

8.52

1.33

18.86

3.77

1969.1

3.25

7.72

4.16

2.86

1.20

3.76

4.68

38.51

10.59

1.96

17.64

3.67

1969.2

3.23

11.52

4.19

2.54

1.42

3.56

4.34

37.43

10.34

1.09

17.39

2.94

1970.1

3.20

10.16

3.34

2.58

1.94

2.84

6.85

42.68

11.02

1.74

9.94

3.71

1970.2

2.45

10.23

4.11

1.85

1.08

3.60

5.08

40.31

7.55

2.23

18.92

2.58

1971.1

2.16

9.71

5.82

2.70

0.90

3.95

3.90

43.99

7.00

1.45

16.02

2.39

1971.2

2.10

9.13

3.33

3.60

1.12

3.27

3.31

42.51

7.24

1.84

19.51

3.03

1972.1

2.68

7.67

5.03

4.80

1.43

3.23

3.00

42.50

8.30

1.14

16.44

3.77

1972.2

1.87

6.57

4.94

5.81

1.13

3.16

3.01

37.54

8.09

1.43

22.02

4.43

1973.1

2.82

9.11

4.56

3.50

1.33

3.26

4.19

30.77

12.26

1.46

22.62

4.12

1973.2

2.37

8.60

3.87

2.82

0.93

2.76

4.35

35.38

10.79

1.24

21.20

5.69

(Source) Mitsubishi Economic Research Institute, Analysis of Domestic Economic Activities
Note: The amount of capital investments is the sum of the differences in capital stocks (the sum of buildings, machinery and other fixed capitals) of thecurrent and previous term and depreciation amounts

20

Figure 2

The Development of capital stocks for four sample industries(thousand yen, chemicals, textiles, paper and pulp)(thousand yen, steel)
450000000

120000000

400000000
100000000

350000000
300000000

80000000

250000000
60000000

200000000
150000000

40000000

100000000
20000000

5000000000chemicals

paper and pulp

texitiles(Source) Mitsubishi Economic Research Institute, Analysis of Domestic Economic Activities

21

steel

Table 2-1-1
Applications of policy actions to each firm for steel industry, actions to curb capital investments
Blast Furnace Steel
Manufacturess
1

2

3

4

5

Non-Blast Furnance Steel Manufactures67

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

1963

1
2
1964
1
2
1965
1
2
1966
1
x x x x2x x x x
1967
1
x x x x x xxx2x x x x x x
x
x
1968
1
x x x x x xxx2x x x x x x
x
x
1969
1
x x x x x xxx2x x x x x x
x
x
1970
1
x x x x x xxx2x x x x x x
x
x
1971
1
x x
x
x
x
2
x x
x
x
x
1972
1
x x
x
x
x
2
x x
x
x
x
1973
1
x x
x
x
x
2
x x
x
x
x
x: policy actions were applied to a firm in question.
Note: the name of the firms are as follows. 1 Nissin Seiko, 2. Kawasaki Seitetsu, 3. Kobe Seikousyo, 4. Sumitomo Kinzokukogyo,
5. Nippon Kokan, 6. Nippon Steel, 7. Nakayama seikousyo, 8. Nihon Seikousyo, 9. Azuma seikousyo, 10. Amagasaki Seikousyo,
11., Kantou Seikou, 12. Daido Kouhan, 13. Mitsubishi Kozai, 14. Toyo Kohan, 15. Mitsubishi Seikou, 16. Nichia Seikou, 17. Nihon Kosyuha Kogyo,
18. Yahata Kokan, 19. Nihon Yakin Kogyo, 20. Yodogawa Seikousyo, 21. Nihon Kinzoku, 22. Nihon Teppan, 23. Daidou Seikou,
24. Tokyo Tankousyo, 25., Kurimoto Tekkosyo

Table 2-1-2
Applications of policy actions to each firm for steel industry, actions to enhance capital investments
Blast Furnace Steel
Manufacturess
1

1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973

1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2

x
x
x
x
x
x
x
x
x
x
x
x
x
x

2

3

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

4

x
x
x
x
x
x

5

x
x
x
x
x
x
x
x
x
x
x
x
x
x

6

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

Non-Blast Furnance Steel Manufactures78

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

x
x
x
x
x
x
x
x
x
x
x
x
x
x

22

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x

x
x
x
x
x
x

Table 2-2-1
Applications of policy actions to each firm for chemical industry, actions to curb capital investments
Organic Chemicals
1

1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973

2

1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2

3

3

4

5

6

7

x
x

8

8

9 10 11 12 13

x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x

Inorganic Chemicals

Oils
and
fats

Pharmaceutical Products

Paints, Ink

Other
Chemicals

14 15 16 17 18 19 19 20 21 22 23 24 25 26 27 28 29

30 31

32 33 34 35 36 37 38 39

40 41 42 43 44

45 46 47

x
x

x
x

x
x

x
x

x
x

x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x

x: policy actions were applied to a firm in question.
Note: The name of the firms are as follows. 1 Taoka Cheicals, 2. Showa Chemicals, 3. Sekisui Chemicals, 4.Daiseru, 5. Nihon Carlit, 6. Nihon Kayaku, 7. Nihon Syokubai Kagaku, 8. Sumitomo Bakelite, 9. Nittetsu Kagaku Kogyo,
11. Kanegafuchi Chemicals, 12. Dainihon Ink, 13. Toyo Linoleum, 14. Showa Denkou, 15. Chisso, 16. Ishihara Sangyo, 17. Teikoku kakou, 18. Tekkousya, 19.Toa Gousei Kagaku, 20. Sumitomo Chemicals,
21. Nitto Chemicals, 22. Nihon Chemichals, 23. Rin Chemicals, 24. Ibigawa Denki Kogyo, 25. Sakai Chemicals, 26. Toyo Sanso,
27. Tokuyama Soda, 28, Nihon Soda, 30. Kao Sekken, 31. Nihon Yushi, 32. Sankyo, 33. Shionogi Seiyaku, 34. Daiichi Seiyaku, 35. dainihon Seiyaku, 36.Tanabe Seiyaku, 37. Nihon Shinyaku, 38. Fujisawa Yakuhin,
40. Kansai Paint, 41. Shinto Toryo, 42. Dainihon Toryo, 43. Toa Paint, 44. Nihon Paint, 45. Shieido, 46. Lion Hamigaki, 47. Oriental Shashin Kogyo

Table 2-2-2
Applications of policy actions to each firm for chemical industry, actions to enhance capital investments
Organic Chemicals
1

1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973

1x
2x
1x
2x
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2
1
2

2

x
x
x
x

3

3

x
x
x
x

4

x
x
x
x

5

x
x
x
x

6

x
x
x
x

7

x
x
x
x

8

8

x
x
x
x

9 10 11 11 12 13

x
x
x
x

x
x
x
x

x
x
x
x

x
x
x
x

Inorganic Chemicals

Oils
and
fats

Pharmaceutical Products

Paints, Ink

Other
Chemicals

14 15 16 17 18 19 19 20 21 22 23 24 25 26 27 28 29

30 31

32 33 34 35 36 37 38 39

40 41 42 43 44

45 46 47

x
x
x
x

x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x

x
x
x

x
x
x

x
x
x

x: policy actions were applied to a firm in question.
Note: The name of the firms are as follows. 1 Taoka Cheicals, 2. Showa Chemicals, 3. Sekisui Chemicals, 4.Daiseru, 5. Nihon Carlit, 6. Nihon Kayaku, 7. Nihon Syokubai Kagaku, 8. Sumitomo Bakelite, 9. Nittetsu Kagaku Kogyo,
11. Kanegafuchi Chemicals, 12. Dainihon Ink, 13. Toyo Linoleum, 14. Showa Denkou, 15. Chisso, 16. Ishihara Sangyo, 17. Teikoku kakou, 18. Tekkousya, 19.Toa Gousei Kagaku, 20. Sumitomo Chemicals,
21. Nitto Chemicals, 22. Nihon Chemichals, 23. Rin Chemicals, 24. Ibigawa Denki Kogyo, 25. Sakai Chemicals, 26. Toyo Sanso,
27. Tokuyama Soda, 28, Nihon Soda, 30. Kao Sekken, 31. Nihon Yushi, 32. Sankyo, 33. Shionogi Seiyaku, 34. Daiichi Seiyaku, 35. dainihon Seiyaku, 36.Tanabe Seiyaku, 37. Nihon Shinyaku, 38. Fujisawa Yakuhin,
40. Kansai Paint, 41. Shinto Toryo, 42. Dainihon Toryo, 43. Toa Paint, 44. Nihon Paint, 45. Shieido, 46. Lion Hamigaki, 47. Oriental Shashin Kogyo

Table 2-3-1
Applications of policy actions to each firm for chemical industry, actions to curb capital investments
Cotton, Staple Fibers
1

2

3

4

5

6

7

8

9

Wool

LinensChemical Fibers

Other Textiles

10 11 12 13

14 15 16

17 18 19 20

21 22 23 24 25 26

1963

1
2
1964
1
2
1965
1
2 x x x x x x x x x
1966
1 x x x x x x x x x
2 x x x x x x x x x
1967
1 x x x x x x x x x
2
1968
1
2
1969
1
2
1970
1
2
1971
1
2
1972
1
2
1973
1
2
x: policy actions were applied to a firm in question.
Note: The name of the firms are as follows. 1 Kitanihon Boseki, 2. Kurashiki Boseki, 3. Kyowa Boseki, 4.Shin Naigaimen, 5. Daiwa Boseki, 6. Nisshin Boseki,
7. Hirata Boseki, 8. Fuji Boseki, 9. Wakabayashi Boseki, 10. Daito Bosyoku, 11. Daido Keori, 12. Chuo Keori, 13.Nihon Keori, 14. Teikou Seni,
15. Teikoku Sangyo, 16. Teikoku Seima, 17. Teijin, 18. Toho Rayon, 19. Toray, 20. Sakai seni Kogyo, 21. Soto Kogyo, 22. Nihon Felt, 23. Dynik,
24. Sumie Orimono, 25. Ashimori Kogyo, 26. Fukusuke

Table 2-3-2
Applications of policy actions to each firm for chemical industry, actions to enhance capital investments
Cotton, Staple Fibers
1

1963

2

3

4

5

6

7

8

9

Wool

LinensChemical Fibers

Other Textiles

10 11 12 13

14 15 16

17 18 19 20

21 22 23 24 25 26

1
2
1964
1
2
1965
1
2
1966
1
2
1967
1 x x x x x x x x x
2 x x x x x x x x x
1968
1 x x x x x x x x x
2 x x x x x x x x x
1969
1 x x x x x x x x x
x
2 x x x x x x x x x
x
1970
1 x x x x x x x x x
x
2 x x x x x x x x x
x
1971
1
x
2
x
1972
1
x
2
x
1973
1
x
2
x
x: policy actions were applied to a firm in question.
Note: The name of the firms are as follows. 1 Kitanihon Boseki, 2. Kurashiki Boseki, 3. Kyowa Boseki, 4.Shin Naigaimen, 5. Daiwa Boseki, 6. Nisshin Boseki,
7. Hirata Boseki, 8. Fuji Boseki, 9. Wakabayashi Boseki, 10. Daito Bosyoku, 11. Daido Keori, 12. Chuo Keori, 13.Nihon Keori, 14. Teikou Seni,
15. Teikoku Sangyo, 16. Teikoku Seima, 17. Teijin, 18. Toho Rayon, 19. Toray, 20. Sakai seni Kogyo, 21. Soto Kogyo, 22. Nihon Felt, 23. Dynik,
24. Sumie Orimono, 25. Ashimori Kogyo, 26. Fukusuke

Table 2-4
Applications of policy actions to each firm for pulp and paper industry, actions to curb
capital investments
Pulp
1 2 3 4
1963 12
1964 12
1965 12
1966 12
1967 12
1968 12
1969 12
1970 121971 12
1972 12
1973 1
2

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

Paper
5 6 7 8 9 10 11 12 13 14 15

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x

x: policy actions were applied to a firm in question.
Note: The name of the firms are as follows. 1 Koujin, 2. Sanyo Pulp, 3. Kokusaku Pulp, 4.Tohoku Pulp,
5. Kitanihon Seishi, 6. Jujo Seishi, 7. Daisyowa Seishi, 8. Oji Seishi, 9. Nihon Kakou Seishi, 10. Nihon Shigyo,
11. Honsyu Seishi, 12. Hokuetsu Seishi, 13. Mitsubishi Seishi, 14. Kanzaki Seishi, 15. Tokyo Cellophane25

Table 3
The effects of intervention tools on resource allocations
steel
blast furnace steel manufacturers

Constant

OLS (pooling data)
simultaneouslag (-1)
0.07
0.06<2.98><2.59>lag (-2)
0.05<1.85>

fixed effects
simultaneous
0.07<2.71>lag (-1)
0.06<2.27>lag (-2)
0.05<1.56>

random effects
simultaneous
0.07<2.94>lag (-1)
0.06<2.54>lag (-2)
0.05<1.82>

PK

1.35<2.63***>

1.52<2.96***>

1.76<3.33***>

1.52<2.67***>

1.69<2.98***>

1.94<3.35***>

1.35<2.59**>

1.52<2.91***>

1.76<3.27***>

IP1

0.04
<1.49>

0.04<1.50>

0.05<2.04**>

0.04<1.36>

0.04<1.35>

0.05<1.91*>

0.04<1.47>

0.04<1.47>

0.05<2.00**>

IP2

0.01<0.63>

0.02<0.82>

0.02<0.76>

0.00<0.10>

0.01<0.28>

0.01<0.19>

0.01<0.62>

0.02<0.81>

0.02<0.75>lag (-2)
0.11<7.64>

fixed effects
simultaneous
0.11<6.61>lag (-1)
0.11<6.95>lag (-2)
0.12<6.66>

random effects
simultaneous
0.10<7.75>lag (-1)
0.10<7.77>lag (-2)
0.11<7.51>

Hausman statistic
simultaneous lag (-1)
0.80
0.73
<0.85><0.87>lag (-2)0.81<0.85>

Hausman statistic
simultaneous lag (-1)
2.68
3.04
<0.44><0.38>lag (-2)
2.88<0.51>

non-blast furnace steel manufacturers

Constant

OLS (pooling data)
simultaneouslag (-1)
0.10
0.10<7.87><7.89>

PK

0.44<2.44**>

0.48<2.75***>

0.47<2.61***>

0.42<1.69**>

0.42<1.75**>

0.37<1.50>

0.44<2.41**>

0.48<2.71***>

0.47<2.57**>

IP1

0.06<1.65*>

0.08<2.04**>

0.09<2.21**>

0.01<0.20>

0.02<0.30>

0.04<0.72>

0.06<1.63>

0.08<2.01**>

0.09<2.18**>

IP2

-0.02
<-0.71>-0.03<-1.09>-0.04<-1.57>-0.00<-0.09>-0.03<-0.84>-0.05<-1.23>-0.02<-0.70>-0.03<-1.07>-0.04<-1.54>

simultaneous lag (-1)
0.09
0.09
<6.61><6.12>lag (-2)
0.09<5.77>

simultaneous lag (-1)
0.08
0.07
<5.56><4.90>lag (-2)
0.08<4.68>

simultaneous lag (-1)
0.09
0.08
<4.75><5.00>lag (-2)
0.08<4.57>

chemicalsorganic chemicals
Constant

PK

1.07<5.71***>

1.11<5.76***>

1.14<5.72***>

1.23<5.79***>

1.29<5.84***>

1.30<5.61***>

1.17<5.82***>

1.19<5.90***>

1.22<5.77***>

IP1

-0.06
<-2.62***>-0.04<-1.85*>-0.04<-1.71*>-0.06<-2.02**>-0.03<-0.92>-0.03<-0.96>-0.06<-2.24**>-0.04<-1.47>-0.04<-1.35>IP2

0.02<0.67>

0.02<0.81>-0.01<-0.36>0.02<0.93>

0.03<1.06>-0.00<-0.01>0.02<0.85>

0.03<0.96>-0.00<-0.18>simultaneous lag (-1)
0.11
0.11
<13.41><12.90>lag (-2)
0.11<12.43>simultaneous lag (-1)
0.11
0.11
<13.33><12.64>lag (-2)
0.11<12.08>simultaneous lag (-1)
0.11
0.11
<9.79><9.50>lag (-2)
0.11<9.16>

33.88<0.00>

51.98<0.00>

55.66<0.00>

1.07<0.78>

0.40<0.94>

0.85<0.84>

0.01<1.00>

0.00<1.00>

0.00<1.00>

1.14<0.57>

0.60<0.74>

0.64<0.73>

2.23<0.33>

0.67<0.72>

1.92<0.38>

inorganic chemicals
Constant

PK

0.56<3.90***>

0.56<3.76***>

0.53<3.50***>

0.50<3.02*:*>

0.53<3.06***>

0.51<2.88***>

0.54<3.51***>

0.55<3.46***>

0.53<3.25***>

IP1

-0.02
<-0.71>0.01<0.33>

0.01<0.41>-0.03<-1.02>0.02<0.48>

0.03<0.81>-0.03<-0.88>0.01<0.41>

0.02<0.62>

IP2

0.05<1.91*>

0.03<1.13>

0.03<1.07>

0.07<2.33**>

0.04<1.38>

0.04<1.37>

0.06<2.14**>

0.04<1.26>

0.04<1.23>

simultaneous
0.09<8.32>lag (-1)
0.08<7.16>lag (-2)
0.06<5.92>

simultaneous
0.09<7.78>lag (-1)
0.08<6.80>lag (-2)
0.06<5.81>

simultaneous
0.09<8.25>lag (-1)
0.08<7.12>lag (-2)
0.06<5.48>

PK

0.15<0.81>

0.28<1.51>

0.21<1.25>

0.14<0.61>

0.30<1.38>

0.21<1.07>

0.15<0.81>

0.28<1.50>

0.21<1.20>

IP1-0.03<-1.93*>-0.01<-0.48>0.03<1.88*>-0.03<-1.91*>-0.01<-0.49>0.03<1.84*>-0.03<-1.91*>-0.01<-0.48>0.03<1.88*>

IP2

0.04<2.86***>

0.05<3.51***>

0.07<5.25***>

0.04<2.79***>

0.05<3.37***>

0.07<5.21***>

0.04<2.84***>

0.05<3.49***>

0.07<5.27***>

simultaneous
0.08<5.05>lag (-1)
0.09<5.71>lag (-2)
0.09<5.39>

simultaneous
0.07<2.90>lag (-1)
0.10<4.14>lag (-2)
0.09<3.40>

simultaneous
0.07<2.89>lag (-1)
0.09<3.80>lag (-2)
0.08<2.67>-0.58<-0.73>-0.15<-0.18>-0.37<-0.43>-0.68<-0.67>-0.73<-0.67>-0.95<-0.84>-0.67<-0.73>-0.41<-0.43>-0.77<-0.73>0.03<1.65>

0.01<0.39>

0.02<1.13>

0.05<1.89*>

0.00<0.16>

0.03<1.20>

0.04<1.82*>

0.01<0.29>

0.03<1.22>

simultaneous
0.14<9.84>lag (-1)
0.15<10.21>lag (-2)
0.14<9.83>

simultaneous
0.12<6.10>lag (-1)
0.14<7.00>lag (-2)
0.13<6.55>

simultaneous
0.14<9.75>lag (-1)
0.15<10.07>lag (-2)
0.14<9.73>

PK-0.32<-0.84>-0.20<-0.50>-0.13<-0.31>-0.30<-0.73>-0.21<-0.49>-0.16<-0.36>-0.32<-0.83>-0.20<-0.49>-0.13<-0.31>IP1-0.02<-0.91>-0.03<-1.43>-0.02<-1.10>0.02<0.66>-0.01<-0.18>0.01<0.45>-0.02<-0.91>-0.03<-1.41>-0.02<-1.09>Textilescotton, staple fibres
Constant

Pulp and paper
pulp
Constant

PK

IP1

paper
Constant

Note: t-Statistic in parenthesis.
*significant at 10%; ** significant at 5%; *** significant at 1%.

26

Table 4
The average level of τ among firms
steelchemicals

blast furnace non-blast
steel
furnace steel
manufacturers manufacturers

textilespulp and
paper
paper

organic chemicals

inorganic
chemicalscotton, staple
fibrespulp

1963-0.628-0.262

0.578

0.069

2.293

0.284

-0.1211964-0.633-0.367

0.612

0.063

2.173

0.256

-0.017

1965-0.535-0.116

0.852

0.256

3.495

0.629

0.359

1966

-0.583-0.183

1.03

0.591

4.252

0.665

0.563

1967

-0.605-0.132

0.847

0.527

3.399

0.667

0.563

1968

-0.567-0.054

0.969

0.393

3.806

0.583

0.473

1969

-0.598-0.036

1.345

0.521

4.806

1.006

0.804

1970

-0.62

-0.093

1.038

0.534

5.132

0.931

0.729

1971

-0.605

0.005

1.606

0.54

5.662

0.801

0.633

1972

-0.497

0.394

2.09

1.53

9.37

1.369

1.151

Sources: Financial Statement Statistics of Corporations by Industry, (Hojin Kigyou Toukei Kihou Syuran, Mof, Securities Bureau) 1977,
One Hundred Year History of the Bank of Japan, Volume of collection of historical materials, Hundred-Year Statistics of Wholesale Price Indexes
in Japan, Mitsubishi Economic Research Institute (Mitsubishi Keizai Kenkyuusho), Analysis of Domestic Economic Activities (Honpo Jigyo
Seiseki Bunseki), each issue, Ministry of Labour, Monthly Labour Survey, each issue.

27

Table 5
The effects of intervention tools on resource allocations
steel
blast furnace steel manufacturers

Constant

OLS (pooling data)
simultaneouslag (-1)
-0.07
-0.07
<-2.22><-2.30>lag (-2)-0.08<-2.42>

fixed effects
simultaneous-0.24<-4.98>lag (-1)-0.24<-5.08>lag (-2)-0.26<-5.38>

random effects
simultaneous-0.07<-2.34>lag (-1)-0.07<-2.42>lag (-2)-0.08<-2.60>

τ(-1)

0.83
<15.75***>0.83<15.56***>0.81<14.70***>0.55<7.01***>

0.54<6.94***>

0.48<5.91***>

0.83<16.62***>

0.83<16.38***>0.81<15.83***>

IP1

-0.03
<-2.36**>-0.03<-2.54**>-0.03<-2.65***>-0.02<-1.55>-0.02<-1.95*>-0.03<-2.83***>-0.03<-2.49**>-0.03<-2.68***>-0.03<-2.85**>

IP2

-0.02
<-1.64>-0.01<-1.26>-0.02<-1.95*>-0.03<-1.98**>-0.02<-1.31>-0.04<-2.28**>-0.02<-1.73*>-0.01<-1.32>-0.02<-2.10**>Hausman statistic
simultaneous lag (-1)
24.14
23.52
<0.00><0.00>lag (-2)
29.93<0.00>

simultaneous
46.61<0.00>lag (-1)
41.51<0.00>lag (-2)
46.14<0.00>

33.9<0.00>

52.0<0.00>

55.7<0.00>

8.37<0.04>

8.50<0.04>

9.88<0.02>

0.00<1.00>

0.00<1.00>

0.00<1.00>

9.33<0.01>

7.33<0.03>

10.83<0.00>

32.46<0.00>

28.88<0.00>

37.89<0.00>

non-blast furnace steel manufacturers
simultaneous
0.05<2.52>lag (-1)
0.05<2.28>lag (-2)
0.05<2.46>

simultaneous
0.06<2.43>lag (-1)
0.04<1.74>lag (-2)
0.05<2.02>

simultaneous
0.05<2.67>lag (-1)
0.05<2.40>lag (-2)
0.05<2.61>

τ(-1)

0.92<24.17***>0.93<24.27***>0.92<23.27***>0.55<8.38***>

0.57<8.58***>

0.53<7.77***>

0.92<25.61***>

0.93<25.50***>0.92<24.71***>

IP1

0.06
<0.88>

0.05<0.67>

0.05<0.62>

0.02<0.12>

0.07<0.73>

0.08<0.81>

0.06<0.93>

0.05<0.70>

0.05<0.66>

IP2-0.07<-1.70*>-0.05<-1.07>-0.04<-0.84>-0.27<-3.93***>-0.20<-3.03***>-0.19<-2.81***>-0.07<-1.80*>-0.05<-1.13>-0.04<-0.90>simultaneous lag (-1)
0.45
0.41
<4.84><3.77>lag (-2)
0.44<3.76>

simultaneous lag (-1)
0.45
0.41
<5.20><4.25>lag (-2)
0.44<4.28>

τ(-1)

0.75<13.95***>0.67<11.31***>

0.66<10.75***>0.40<4.87***>

0.20<2.42**>

0.17<1.88*>

0.75<14.98***>0.67<12.74***>0.66<12.25***>

IP1

-0.33
<-0.94>-0.21<-0.52>-0.17<-0.41>-0.32<-0.93>-0.30<-0.82>-0.30<-0.80>-0.33<-1.01>-0.21<-0.59>-0.17<-0.47>IP2-1.45<-6.15***>-0.15<-0.60>-0.09<-0.36>-1.14<-4.97***>-0.53<-2.28**>-0.47<-1.98**>-1.45<-6.60***>-0.15<-0.68>-0.09<-0.41>

simultaneous lag (-1)
0.11
0.11
<2.74><2.66>lag (-2)0.10<2.44>

simultaneous lag (-1)
0.18
0.18
<3.82><3.78>lag (-2)
0.19<3.74>

simultaneous lag (-1)
0.11
0.11
<2.72><2.64>lag (-2)0.10<2.42>

τ(-1)

1.05<26.81***>

1.05<26.72***>

1.05<25.55***>0.89<12.43***>0.88<12.38***>0.85<11.22***>

1.05<26.58***>1.05<26.50***>1.05<25.39***>

IP1

-0.19
<-1.09>-0.13<-0.74>-0.04<-0.22>-0.17<-0.95>-0.12<-0.67>-0.03<-0.18>-0.19<-1.08>-0.13<-0.73>-0.04<-0.22>IP2-0.13<-1.01>-0.12<-0.93>-0.08<-0.64>-0.13<-0.87>-0.12<-0.80>-0.08<-0.49>-0.13<-1.00>-0.12<-0.92>-0.08<-0.63>simultaneous
0.05<2.52>lag (-1)
0.05<2.28>lag (-2)
0.05<2.46>

simultaneous
0.06<2.43>lag (-1)
0.04<1.74>lag (-2)
0.05<2.02>

simultaneous
0.05<2.67>lag (-1)
0.05<2.40>lag (-2)
0.05<2.61>

0.92<24.17***>0.93<24.27***>0.92<23.27***>0.55<8.38***>

0.57<8.58***>

0.53<7.77***>

0.92<25.61***>

0.93<25.50***>0.92<24.71***>

IP1

0.06
<0.88>

0.05<0.67>

0.05<0.62>

0.01<0.12>

0.07<0.73>

0.08<0.81>

0.06<0.93>

0.05<0.70>

0.05<0.66>

IP2-0.07<-1.70*>-0.05<-1.07>-0.04<-0.84>-0.27<-3.93***>-0.20<-3.03***>-0.19<-2.81***>-0.07<-1.80*>-0.05<-1.13>-0.04<-0.90>simultaneous
0.07<1.07>lag (-1)
0.10<1.58>lag (-2)
0.09<1.42>

simultaneous
0.10<1.06>lag (-1)
0.17<2.13>lag (-2)0.22<2.56>

simultaneous
0.07<1.12>lag (-1)
0.10<1.63>lag (-2)
0.09<1.50>

τ(-1)

1.02<19.73***>

1.03<19.75***>1.02<18.80***>0.67<5.35***>

0.71<5.17***>

0.58<3.92***>

1.02<20.65***>

1.03<20.38***>1.02<19.94***>

IP1

0.01
<0.12>-0.05<-0.51>-0.02<-0.23>0.24<1.42>

0.10<0.67>

0.17<1.21>

0.01<0.13>-0.05<-0.53>-0.02<-0.25>

simultaneous
0.10<1.97>lag (-1)
0.12<2.53>lag (-2)
0.13<2.46>

simultaneous
0.19<2.72>lag (-1)
0.26<4.22>lag (-2)
0.30<4.63>

simultaneous
0.10<2.07>lag (-1)
0.12<2.64>lag (-2)0.13<2.62>

0.94<30.28***>0.66<11.28***>0.67<11.29***>0.61<9.86***>

0.95<33.14**>0.94<33.05***>0.94<32.31***>-0.00<-0.05>0.21<1.91*>

0.07<0.78>

0.12<1.24>

0.01<0.25>-0.02<-0.42>-0.00<-0.06>

Constantchemicalsorganic chemistry
Constant

simultaneous lag (-1)
0.83
0.99
<7.54><7.79>lag (-2)
1.07<7.93>

inorganic chemistry
Constant

textilescotton, staple fibres
Constant

τ(-1)

pulp and paper
pulp
Constant

paper
Constant

τ(-1)

0.95
0.94
<31.54***> <31.70***>

IP1

0.01
<0.24>-0.02<-0.40>Note: t-Statistic in parenthesis.
*significant at 10%; ** significant at 5%; *** significant at 1%.

28

Appendix: The list of policy actions for the steel , textile and paper and pulp industry between 1964 and 1972

steelsIP1

IP2

restrictions on new investments by the moral suasion forstainless steel plates (six firms only allowed to introduce new
equipment's by rotation), April 1967-March 1971

lending by the Japan Development Bank for special steels,1966

the coordination of capital investments in steels under theadministrative guidance by the MITI, May 1967-March 1970
designated cartels in special steels, November 1971-June1973

public lending for changes in industrial structure of special
steels, 1967-1970

public lending for alloy iron, 1968-1970
lending by the JDB for special steels, 1964, 1965, 1967-1969
public lending for the improvement of industrial structure forother textile products, 1967-1970

chemicals

restrictions on new investments by the moral suasion for
sodium sulphide, 1957

lending by the JDB, 1963-1964

postponing new investments decided by the Council for
Financial Institution Funding for synthetic organic chemistry,
1957

public lending for the improvement of industrial structure forammonia, 1968-1970

setting the standards for approving investments increasing
production capacity by the council for polyethylene, 1967

lending by the JDB, 1966

restrictions on new investments backed by the antitrust law
for vinyl chloride resin, January 1967-September 1967

public lending for the improvement of industrial structure forpetrol-chemical products, 1967-1968

restrictions on new investments backed by the antitrust law
for polyvinyl chloride pipe, November 1968-

textilesrestrictions on new investments backed by the antitrust law
for cotton rayon staple fiber, October 1965-March 1967

pulp and paper

restrictions on new investments for white paper under thedesignated cartel in a recession, February 1967-December
1967
restrictions on new investments for corrugating medium core
paper, November 1965 July 1966, February 1967-July 1967
restrictions on new investments for lining papers, November
1965-March 1967

Note: IP1 actions for curbing investments, IP2 actions for promoting investments

29

public lending for industrial for other textile products, 19671970

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