2014-22
What Most Affects A Firm’s Costs:
Internal or External Factors, or Both?
Fumitoshi Mizutani Eri Nakamura

What Most Affects A Firm’s Costs:
Internal or External Factors, or Both?
Fumitoshi Mizutani
Kobe University
Graduate School of Business Administration
2-1 Rokkodai, Nada-ku, Kobe 657-8501 Japantoshi@kobe-u.ac.jp

andEri Nakamura
Kobe University
Graduate School of Business Administration
2-1 Rokkodai, Nada-ku, Kobe 657-8501 Japanenakamura@person.kobe-u.ac.jp
Correspondent Author: Fumitoshi Mizutani
toshi@kobe-u.ac.jp[Abstract]: The main purpose of this study is to investigate what kind of internal and external
factors most affect a firm’s costs. We consider governance structure and business diversification
strategy as internal factors and regulation and competition as external factors.

By using 358

observations comprised of Japanese firms from public utility and manufacturing industries from1989 to 2002, we estimate the translog cost function. The main findings are as follows:
governance factor has an important effect on a firm’s cost structure.

(i) TheAs the ratio of foreign

shareholders increases and there is more dependence on one main bank, the costs of a firm decrease.
(ii) The rate of increase in total costs for diversification is relatively low. A 1% increase in businesssegments leads to only a 0.1 or 0.2% increase in total costs.

(iii) The regulation factor does notaffect the cost structure. (iv) Compared with the regulation factor, the competition factor shows aquite clear effect on a firm’s cost reduction.

Overall, our empirical result suggests that governancestructure as an internal factor and competition as an external factor are especially important for cost
reduction.

[Key Words]: Governance, Diversification Strategy, Regulation, Competition, Japanese Firms

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What Most Affects A Firm’s Costs:
Internal or External Factors, or Both?

1. Introduction
In the area of cost studies of firms, external factors such as regulation and competition are
typically examined as important determinants of cost structure (e.g. Berg and Jeong (1991), Antel etal. (1995), Pantalone and Platt (1997), Schneider (2003), Fenn et al. (2008), Ter-Martirosyan andKwoka (2010)).

However, recent developments in internal corporate management studies indicatethat effective management could induce efficient cost structure of firms.

For example, corporate

governance and business diversification strategy are shown to be important factors in firms’ cost
efficiency (e.g. Berger and Hannan (1998), Fries and Taci (2005), Jeng and Lai (2005), Zelenyuk
and Zheka (2006) and Berger et al. (2009)).

Thus, in addition to the external forces influencing

firms’ behavior, such as regulation and competition, internal factors like governance structure andbusiness diversification strategy also play an important role.

Nevertheless, these internal factors

are rarely investigated in the area of firms’ cost analysis, while they are the major determinants in thefirms’ performance analysis.
The main purpose of this study is to investigate what kind of internal and external factors
most affect a firm’s cost. We consider governance structure and business diversification strategy asinternal factors and regulation and competition as external factors.

Firms taken in this study are

public utility firms and manufacturing firms in Japan.
This study makes several main contributions to the literature.

First, this is the only study

so far to consider together the four important factors mentioned above (i.e. governance structure,business diversification strategy, regulation by government, and competition among firms) and toinvestigate which are most effective in reducing the costs of a firm.

As stated before, while studies

of firms’ cost structure have examined various external factors in the form of regulation andcompetition, they rarely investigate internal factors. Recently firms are under great pressure fromoutside forces such as foreign shareholders, making it difficult for them to maintain autonomy ofmanagement. It is required that internal management as well as the external environment take on
important roles in cost reduction.

By considering both factors in the analysis, we can identify

which internal or external factors are important for firms’ costs.
Second, we apply the factors considered important in the performance analysis to the cost
analysis.

Since the cost reduction is one process for improving firm’s performance, we candistinguish the effects of these internal management factors on costs from those on performance byfocusing on the firm’s costs.

For example, most studies on corporate governance examine

performance by looking at profitability and corporate value as factors impacted by governance2

structure.

However, in this study, by looking closely at previous research (e.g. Berger and Hannan(1998), Fries and Taci (2005), Jeng and Lai (2005), Zelenyuk and Zheka (2006) and Berger et al.
(2009)), we investigate to what degree the governance structure improves costs.

Similarly, we

include a variable for the strategic behavior of a firm in the cost function. Many firms operate inmore than two industries. In this study, the effect of a diversified strategy (i.e. a multi-segment
strategy) is investigated.

If a firm diversifies into several industries, the cost structure of the firm isdifferent from that of the non-diversified firm.

Therefore, it is necessary to include this variable.

Third, this study uses the quantity rather than the quality variable of regulation.

In previous studies(e.g. Berg and Jeong (1991), Antel et al. (1995), Ai and Sappington (2002), Schneider (2003),
Fabrizio et al. (2007), Ter-Martirosyan and Kwoka (2010)), regulation is commonly represented as adummy variable, whether regulation is applied or not, or whether it has been enacted or not.

On theother hand, in this study, we use “the degree of regulation” as a quantity variable. The measure of
the degree of regulation refers to how many laws and regulations are applied to each specified
industry.
1.0.

If a firm in a certain industry is almost completely regulated, then the measure becomes

But for an industry with no regulation, then the measure is 0.0. Last, as for regulation issues,

unlike in previous studies, we try to obtain more general results in both public utility andmanufacturing industries.

Heretofore, analysis has focused either only on specific types ofregulation: environmental regulation (e.g. Nowell and Shogren (1994)), incentive regulation (e.g.
Berg and Jeong (1991), Vogelsang (2002), Mizutani et al. (2009), Ter-Martirosyan and Kwoka(2010)), and price regulation (e.g. Cabral and Riordan (1989), Bös and Peters (1995), Vogelsang(2002)); or on specific industries: the energy industry (e.g. Nelson and Wohar (1983) and Majumdar
and Marcus (2001)), rail (e.g. Mizutani et al. (2009)), and postal service (e.g. Mizutani and Uranishi(2003)).

It cannot be assumed that, when the focus shifts to general regulation or to otherindustries, the results will be the same as in the specific cases listed here.
This paper consists of five parts after the introduction.

In the second section, wesummarize previous studies, focusing especially on the relationship between costs and the four
factors (i.e. governance structure, business diversification strategy, regulation, and competition).
the third section, the empirical model is specified.
analysis.

In

We employ the translog cost function for the

The fourth section presents an explanation of the data used in this study.

There are atotal of 358 observations here, from the years between 1989 and 2002, obtained from public utility
and manufacturing firms in Japan.

The definitions of variables are also given in this section.

the fifth section, the empirical results are summarized.

An explanation of the regression results isfollowed by an evaluation of the effects of the four factors on cost.
concluding remarks.

3In

The last section contains

2. Previous Studies
In this section, we will summarize previous studies concerning the relationship between
the four important factors (i.e. governance structure, business diversification, regulation, andcompetition) and firms’ costs.

2.1 Governance Structure
Although governance structure affects a firm’s costs through the discipline of corporate
management, few studies have investigated the relationship between governance structure and thecosts of a firm.

There are, however, a few studies, such as Berger and Hannan (1998), Fries andTaci (2005), Jeng and Lai (2005), Zelenyuk and Zheka (2006) and Berger et al. (2009), which
evaluate to what degree governance structure improves cost efficiency.
As for the measures of governance structure, there are (i) insider ownership (e.g. Berger
and Hannan (1998)), (ii) foreign ownership (e.g. Fries and Taci (2005), Zelenyuk and Zheka (2006),
Berger et al. (2009)), (iii) large shareholders (e.g. Berger and Hannan (1998) and Berger et al.
(2009)) and (iv) governmental or public ownership (e.g. Berger et al. (2009)).

In addition to thesemeasures, as characteristics of Japanese governance structure, (v) ‘keiretsu’ (e.g. Jeng and Lai(2005)) and (vi) main bank (e.g. Weinstain and Yafeh (1998)) are often used. ‘Keiretsu’ is anindustrial group of firms affiliated with each other for mutual help and monitoring throughshareholding, an arrangement typical of Japanese manufacturing and financial industries. Mainbank is a bank that has established a close relationship with firms by providing extensive financing
and consulting services through a system unique to Japanese governance.
These measures of governance structure are commonly defined as either the ratio or
dummy variable.

For example, some studies (e.g. Berger and Hannan (1998), Fries and Taci (2005),

Zelenyuk and Zheka (2006)) take the ratio of these governance measures to total shares or total
assets.

On the other hand, some studies (e.g. Berger and Hannan (1998) and Weistain and Yafeh(1998)) treat the governance measure as a dummy variable.

Furthermore, in addition to thesemethods, some studies analyze the effect of the governance structure by comparing results obtained
from different observations according to type of governance structure (e.g. Berger et al. (2009) and
Jeng and Lai (2005)).
Finally, we will summarize the empirical results of our study of governance structure’s
effect on cost efficiency as follows.

First, foreign ownership improves cost efficiency, as Zelenyuk

and Zheka (2006) and Berger et al. (2009) show. Second, the existence of large shareholders has
differing results.

Berger and Hannan (1998) analyze the banking industry and they obtain the resultthat large shareholders decrease cost efficiency. On the other hand, a more recent study by Berger
et al. (2009), an analysis of the banking industry in China, produced the opposite result that large
shareholders increase cost efficiency.

Furthermore, Berger et al. (2009) also obtain a result4contradictory to what is commonly perceived as the effect of governmental ownership.

Accordingto their results, governmental ownership increases cost efficiency. As for insider ownership, anincrease in the manager’s ownership tends to decrease cost efficiency but the effect is notstatistically significant.

As for the characteristics of Japanese governance structure, ‘keiretsu’

increases cost efficiency, according to Jeng and Lai (2005), who argue that ‘keiretsu’ fosters strong
relationships among firms inside the ‘keiretsu,’ and main bank. As a result, cost efficiency is
increased by the fact that firms inside the ‘keiretsu’ monitor each other, the search costs for
information are reduced, and firms can attain cheaper capital costs.

It is worth noting that one

result has shown that the main bank system has merit only for the main bank and that the main banksystem causes firms to increase capital costs.

2.2 Diversification Strategy
There are few previous studies analyzing to what extent a business diversification strategy
affects the costs of firms.
directions.

Business diversification could propel the costs of a firm in two different

If there exist economies of scope among diversified businesses, the more diversified

firms have smaller costs than otherwise.

On the other hand, more diversified firms might havebigger costs if they are promoting excess investment and cross-subsidies among diversified
divisions.
Some previous empirical studies investigate the relationship between businessdiversification and the cost efficiency of a firm (e.g. Ferrier et al. (1993), Rajan et al. (2000), Jengand Lai (2005)).

These studies focus on industries such as banking (e.g. Ferrier et al. (1993), Rajan

et al. (2000)) and insurance (e.g. Jeng and Lai (2005)) and conclude that diversification causes costinefficiency through the promotion of excess investing and cross-subsidizing.

On the other hand,in the Italian bus industry, there exist economies of scope (e.g. Ottoz and Di Giacomo (2012)).
Although his study is a productivity analysis of Italian manufacturing firms, Vannoni (2000)
concludes that the degree of diversification is not significantly related to productivity.

2.3 Regulation
Studies have been done to determine the degree to which regulation affects a firm’s costs.
The most common approach is to use a cost function such as the translog cost function (e.g. Bergand Jeong (1991), Antel et al. (1995), Pantalone and Platt (1997), Schneider (2003), Ter-Martirosyan
and Kwoka (2010)).

Some studies analyze the cost efficiency change due to regulatory reform byusing the stochastic cost frontier function (e.g. Kleit and Tecrell (2001) Mizutani et al. (2009)).
Also, theoretical studies have been done which construct the relationship between regulation and thecosts of a firm (e.g. Cabral and Riordan (1989), Bös and Peters (1995), Vogelsang (2002)).
Second, in most previous studies, the measure of regulation is used as a dummy variable,

5whether or not there is regulation (e.g. Berg and Jeong (1991), Antel et al. (1995), Ai and Sappington(2002), Schneider (2003), Fabrizio et al. (2007), Ter-Martirosyan and Kwoka (2010)). Most suchstudies are limited to public utility industries such as electric power, gas, and transport industries.
Other measures on regulation vary by individual study, with, for example, the revenue ratio of a
hospital under regulation defined as a proxy variable for regulation in Antel et al. (1995). There arealmost no studies in which the degree of regulation is measured as a directly obtained continuous
variable.
Third, most previous studies focus on some specific regulation: environmental regulation(e.g. Nowell and Shogren (1994)), incentive regulation (e.g. Berg and Jeong (1991), Vogelsang(2002), Mizutani et al. (2009), Ter-Martirosyan and Kwoka (2010)), and price regulation (e.g. Cabraland Riordan (1989), Bös and Peters (1995), Vogelsang (2002)).

There are few studies on how

regulation itself in general affects the efficiency of individual firms.
Fourth, previous studies have produced conflicting results, with many studies supporting
the idea that regulation reduces costs (e.g. Cabral and Riordan (1989), Kleit and Tecrell (2001), Ai
and Sappington (2002), Ter-Martirosyan and Kwoka (2010), Nakamura (2010) and Buranabunyut
and Peoples (2012), and other studies showing that regulation increases productivity (e.g. Dufour etal. (1998), Berman and Bui (2001), Majumdar and Marcus (2001), Alpay et al. (2002) and Knittel(2002)).

On the other hand, some studies show that regulations increase the costs of firms (e.g.

Gollop and Roberts (1983), Berg et al. (2005) and Fabrizio et al. (2007)), while others suggest that
regulation decreases firms’ productivity (e.g. Christainsen and Haveman (1981), Gollop and Roberts(1983), Gray (1987), Majumdar and Marcus (2001) and Nicoletti et al. (2003)).
In addition to these results, some studies show that regulation does not affect cost structure.
For example, studies such as Antel et al. (1995), Berg and Jeong (1991) and Bös and Peters (1995)
conclude that the cost effect of regulation is not significant.

Furthermore, there are two studies,

Pantalone and Platt (1997) and Meyer and Leland (1980), which have different results.

Pantaloneand Platt (1997) conclude that effect on costs by regulation varies according to the difference inability to respond to environmental change. Although Gutierrez’ study (2003) is not a cost but a
productivity study, Gutierrez concludes that regulatory governance has a positive effect on sector
performance and efficiency.
Thus, empirical results have not produced a consistent conclusion.

In general,

regulations create extra constraints for each individual firm and could therefore increase a firm’s
costs.

However, under the private interest theory (capture hypothesis), it is also possible that

regulations reduce costs.

If regulations are created under the capture hypothesis, regulatory

programs could be advantageous for the regulated firms, resulting in lower costs than for
unregulated firms.

In fact, some studies support the private interest theory from a theoretical andempirical point of view: for example, Stigler (1971), Peltzman (1976), Primeaux Jr. et al. (1984),

6

Nowell and Shogren (1994), Antel et al. (1995), Dnes et al. (1998), Dnes and Seaton (1999),
Kroszner and Strahan (1999), Nakamura (2010) and Benmelech and Moskowitz (2010).

On theother hand, Smyth and Soderberg (2010) support the public interest theory.

2.4 Competition
First, competition among firms certainly affects firms’ costs.

Most previous studies takecost efficiency as dependent variables: for example, Berger and Hannan (1998), Sari (2003) andFenn et al. (2008).

As a definition of competition, the Herfindahl-Hirschman index (e.g. Berger

and Hannan (1998), Sari (2003)) and a concentration ratio of the top 5 firms (e.g. Fenn et al. (2008))
are often used.

Most studies conclude that competition can improve cost efficiency.

According toFenn et al. (2008), competitive pressures impose the threat of bankruptcy on firm managers and thus
work as an incentive to cut inefficiency. Moreover, firm owners can judge the performance of theircompany by comparing it to rival firms when the industry is competitive, which results inappropriate pressure on the firm.

On the other hand, Nakamura (2010) shows that competition

sometimes worsens internal efficiency, since competitive pressures can drive firm managers to
reduce necessary investment and costs. Sari (2003) integrates these conflicting results by pointing
out that the relationship between cost inefficiency and competition is U-shaped, indicating that whilea certain degree of competition improves cost efficiency, too much competition creates the opposite
effect.

3. Empirical Model
As we mentioned before, the main purpose of this study is to investigate what kinds offactors most affect a firm’s costs. Governance structure and diversification strategy as internal
factors and regulations and competition as external factors are examined.

Our sample includes

Japanese public utilities and manufacturing industries but excludes other industries such as service
and retailing, since cost structures of the latter industries are substantially different from those of theformer.
As many public utility firms and manufacturing firms are privately owned, governance bysignificant private actors is important. Proper governance structure, including private ownership andmonitoring, might reduce the costs of a firm.
business.

Furthermore, many firms have diversified their

If there exist economies in business diversification, a more diversified firm can attain ahigher cost efficiency than others.

On the other hand, a diversification strategy might generate

extra costs through unnecessary investment and cross-subsidies. As public utility firms are in
general regulated and limited in terms of competition, too much regulation might lead to theover-costing of a firm.

Manufacturing firms are also partly regulated but the market of the industry

7

itself is characterized by competition among firms.

We will analyze how these four importantfactors (i.e. governance structure, diversification strategy, regulations, and competition) affect firms’
costs.
To investigate this theme, we estimate the cost function because it can reveal the current
situation relatively accurately.

With regard to the cost function, the following points are important.

As stated in the purpose of our analysis above, in addition to output (Q) and input factor prices (w),
we include the four key variables of governance structure (GS), diversification strategy (STR),
regulation (RG), and competition (CMP).

First, governance structure and diversification strategy

are factors over which a firm can exercise a degree of control.
internal environment.

Each individual firm can change its

If a firm can gain cost advantages from business diversification, then thefirm has incentive to diversify.

At the same time, it can be easily seen that governance structure

affects a firm’s cost structure, in that a firm with strict management discipline adopting proper
governance structure would generate less cost than a firm with loose management.

On the other

hand, variables such as regulation and competition reflect the situation of the external environment
in which each firm is involved. These are factors the firm cannot change, as set by the governmentor as the industry was created by the market.

In addition to these four factors, it is also necessary tocontrol for macro-level differences among industries.
others are growing.
variables (IND).

Some industries might be declining while

Therefore, we include an industry’s characteristics variables as control

As a result, with these variables, the cost function (C) is expressed as output (Q),

input factor price (w), and technology (T) as follows.
C = min iwixi

subject to Q = g(xi; GS, STR, RG, CMP, IND, T)

C = f(Q, wi, GS, STR, RG, CMP, IND, T)
where

(1)
(2)

C: cost,
Q: output,
wi: input factor price of input-i,
xi: input-i,
T: technology,
GS: governance structure,
STR: diversification strategy,
RG: regulation,
CMP: competition,
IND: characteristics of industry as a control variable.

The empirical cost model in this study is the translog cost function, which has been widelyused in previous cost studies.

Costs for the estimation are total costs, and the cost function is8specified as three-input-factor-price model of labor (wL), material and service (wM) and capital (wK).
Because we use panel data, we include time trend (T) to control for technology progress.
As for the governance structure1, we consider the following variables: stock ratio held byforeign shareholders (GSFRN), stock ratio held by the top 10 shareholders (GSTOP), and main bankvariable (GSBANK).

As for the strategy variable, we define the number of industries in which eachfirm is involved (STRDIV).

As for regulation, we take the degree of regulation (RGREG).

This

variable is a quantity variable showing the magnitude of regulation. As for the competition factor,
we consider two possible variables: the Herfindahl-Hirschman index (CMPHHI) and theconcentration ratio of 4 firms (CMPCR4).

Finally, as for control variables for industries in which

each firm is involved, we consider the industry’s bankruptcy ratio (INDBKT), and the industry’s
profitability (INDPRF).
As a result, the cost function is expressed as follows.
lnC = 0 + Q lnQ + iwilnwi + 1/2QQ(lnQ)2 + 1/2 ij wiwj lnwilnwj +iQwi lnQ lnwi + mGSm lnGSm + DIV lnSTRDIV + REG lnRGREG +lCMPl lnCMPl, + nEXn lnINDn +TT + DNPU
where

(3)

C: total costs,
Q: revenues,
wi, wj: i, j= L (labor price), M (material and service price), K (capital price),
T: time trend,
GSm: m = FRN (stock ratio held by foreign shareholders), TOP (stock ratio heldby top 10 shareholders), BANK (main bank index),
STRDIV: number of segments,
RGREG: degree of regulation,
CMPl: l = HHI (Herfindahl-Hirschman index), CR4 (concentration ratio of 4
firms),
INDn: n = BKT (industry’s bankruptcy ratio), PRF (industry’s profitability),
DNPU: non-public utility dummy (i.e. non-public utility =1, otherwise =0).

We apply Shepard’s lemma for the cost function.

As a result, the share equations are

obtained as follows.
1

There are two reasons why our model does not include a variable for ‘keiretsu.’ First, our sample
is comprised of large firms, which are mostly parent companies influencing the management ofmember firms. This means that the effect of keiretsu on our sample firms is minor. Second, mainbank variable can control the effect of keiretsu in a group simultaneously because the power ofkeiretsu is determined by financing from the main bank (Nakamura (2010)).
9Si = i + jwij lnwj + QwilnQ
where

(4)

Si : share of input i (i, j = K, L, M).

The estimation method is the Seemingly Unrelated Regression (SUR) method forequations (3) and (4).

We also impose restrictions in equation (3) as follows: iwi = 1, jwLj = 0,jwMj = 0, jwKj = 0, iQwi =0, wiwj = wjwi .

4

Data

4.1 Sample
As we mentioned before, we collected observations from both public utility industries andmanufacturing industries.

As other industries such as service industries (e.g. retail, finance,

agriculture, and mining) are quite different in cost structure, we limited our sample to public utilities
and manufacturing industries only.

At first, we selected a total of 300 firms in Japan, consisting of

150 firms in the public utility industry and 150 from the manufacturing industry, for the 14 years
from 1989 to 2002.

The public utility industries in this study are electricity supply, gas supply,

water supply, transportation (i.e. air, railway, bus, and truck), telecommunications, and broadcasting.
In order to avoid estimation bias by size difference, in the sample selection of manufacturingindustries, we selected firms similar in size to public utility industries.

Finally, the total sample size

is reduced to 358, since some variables such as diversification strategy are not available for allobservations.

4.2 Definition of Variables
Table 1 shows the definition of all variables used for the estimation of total cost functionin this study.

First, total costs (C) in this study are defined as the sum of labor, material (including

energy) and capital costs. Capital costs include depreciation and interest payments.
As for output (Q), we define total sales as total output because there are many variations if
we select physical output measures. Therefore, we choose output measure as monetary values.
We use three kinds of input factor prices: (i) labor, (ii) material and service, and (iii)
capital.

First, labor price (wL) is obtained by dividing labor costs by the total number of employees.

Second, material and service price (wM) is defined as domestic Corporate Goods Price Index (CGPI)
weighted by divisional sales ratio.

Last, capital price (wK) is defined as the sum of depreciation rate

(depreciation per fixed asset) and interest rate (interest payment per debt).
Time trend (T) is a proxy variable for technology progress.

In this study, 1989 is definedas the starting year.
As for the governance structure, we consider three kinds of measures: the stock ratio held10

by foreign shareholders (GSFRN), the stock ratio held by the top 10 shareholders (GSTOP), and themain bank (GSBANK).

First, the stock ratio held by foreign shareholders (GSFRN) is defined as thenumber of shares held by non-Japanese relative to the total number of shares. Second, the stock
ratio held by the top 10 shareholders (GSTOP) is defined as the number of shares held by the largest
ten shareholders to the total number of shares.

Third, as for the characteristics of Japanese

corporate governance structure, main bank index (GSBANK) is chosen.

Main bank index is thestandard deviation of the ratios of debt loan by each financial institution.

This variable expresses

the pressure on a firm’s management by a main bank. The main bank index is large, which meansthat a firm obtains its loans mainly through a certain single bank.
becomes larger, the effect of a main bank becomes larger.

Therefore, as this variable

On the other hand, the fact that the mainbank index is small means that a firm obtains a loan by diversifying financial sources among various
financial institutions.
As for the diversification strategy variable (STRDIV), the number of segments is defined as
the number of industries in which each firm is involved.

This variable expresses the extent ofdiversification of the firm.
As for regulation, we choose “degree of regulation.” The degree of regulation (RGREG)
shows to what degree each firm is subjected to regulation, or its “regulation weight,” as originallydefined by the Management and Coordination Agency (Somucho).

The original data source forregulation weight is the JIP database for 2006, issued by the Research Institute of Economy, Tradeand Industry (RIETI). This measure is obtained by counting the number of existing laws andregulations in each industry, by which process we can determine quantitatively the degree ofindustries’ regulation.

However, this measure does not include information regarding types ofregulations (i.e. environment, safety, and price regulation).

Finally, it is worth noting that while

this measure is based on industry summaries, many firms provide various services in diversified
industries.

The degree of regulation referred to in this study is calculated by weighted revenues of

the industries in which each firm is involved.
As for competition factors, we choose two kinds of measures, the Herfindahl-Hirschmanindex (CMPHHI) and the concentration ratio of 4 firms (CMPCR4).

These measures are obtained ona revenues basis and again are obtained by using weights of each firm’s individual industry’s
revenues.
As for characteristics of industry as a control variable, there are two variables: industry’s
bankruptcy ratio (INDBKT) and industry’s profitability (INDPRF).

First, industry’s bankruptcy ratio(INDBKT) is obtained by dividing the number of bankrupt firms by existing firms.

Last, industry’s

profitability (INDPRF) is defined as the weighted average profitability of the industries to which eachfirm belongs.

For example, if a firm is involved in four industries, this variable is obtained by theweighted average profitability of the four industries. The weight is used by the firm’s revenues

11from each industry.

**********
Table 1**********

5. Empirical Results
We estimate the total cost function shown in equation-(3) with equation-(4). For ourestimation, we use the seemingly unrelated regression (SUR) method according to the total costfunction and input share equations.

The estimation results of the total cost function aresummarized in Table 2. We show four cases in Table 2: (i) Case 1, regulation only; (ii) Case 2 andCase 3, with regulation and competition; (iii) Case 4 and Case 5, with regulation, competition,
governance and diversification strategy; (iv) Case 6, Case 7 and Case 8, with regulation, competition,
governance, diversification strategy and external environments.
The goodness-of-fit in the regressions is acceptably high for these cases because pseudo R2 isvery high at over 0.96. As for the required properties in the cost function, first, symmetry andhomogeneity conditions in input factor prices are satisfied, because we imposed restrictions on thecost model. Second, as for monotonicity conditions, it is necessary that the cost function be a
non-monotone decreasing function in both output and input factor prices.

Whether or not themonotonicity conditions are satisfied was evaluated by checking that the partial derivative of thecost function with respect to output and input factor prices is not negative (i.e. lnC/lnQ > 0,
lnC/lnwj > 0).

Around the sample mean, these conditions are satisfied.

Determining whether or

not the Hessian matrix holds negative semi-definite can test for the concavity condition in input
factor prices.

In our test results, 12.6% to 20.7% of observations satisfy the concavity condition.

Among these cases, Case 4 is the best because the log of likelihood statistics and R2 are large,
the concavity condition is relatively high, and key variables such as competition factor show thecorrect sign.

If we consider the external environment, Case 6 seems to be second.

discuss our findings based mainly on these results.

**********
Table 2**********

12

Therefore, weFirst, governance factors are clearly important in the cost structure.

Among three

governance variables, both the stock ratio held by foreign shareholders (GSFRN) and main bank
(GSBANK) are statistically significant.

As the foreign shareholders’ ratio becomes larger and moreconcentrated in a single main bank, the costs of a firm become smaller.

As for foreign

shareholders’ effect, our result is consistent with Zelenyuk and Zheka (2006) and Berger et al. (2009).
The result that firms under main bank influence have smaller costs needs to be discussed, since mainbank has both positive and negative effects on firm management.

While Weinstain and Yafeh(1998) state that the main bank system increases the cost of capital, Jeng and Lai (2005) argue thatthe close relationship with main bank results in better monitoring and reduced information costs.
Our result is consistent with Jeng and Lai (2005).
Second, the fact that all empirical diversification strategy (STRDIV) shows the positive signwith a statistical significance of 1% means that as a company diversifies more from its core industry
to other industries, the costs of all the firm’s business increase. This result is consistent withprevious studies, which are analyses of the financial industry, such as Ferrier et al. (1993), Rajan etal. (2000) and Jeng and Lai (2005).
is relatively low.

However, the rate of increase in total costs for diversification

A 1% increase in the number of business segments leads to only a 0.1 % increase

in total costs, indicating there exist cost economies of diversification.
Third, the regulation factor (RGREG) does not affect the cost structure.

Although it shows

the negative sign, which means that regulation does reduce the cost, the regulation factor is notstatistically significant.

These results are consistent with previous studies such as Antel et al.

(1995), Berg and Jeong (1991) and Bös and Peters (1995).
either the public or private interest theory.

Our empirical results do not support

We think that regulation itself does not affect costs.

Fourth, compared with the regulation factor, the competition factor is quite clear andconsistent with previous results.

As the empirical results show, competition (CMPHHI, CMPCR4) has

the effect of reducing the costs of a firm.

The market becomes more competitive, which means thatas CMPHHI or CMPCR4 decreases, the cost becomes smaller.
Fifth, the non-public utility dummy (DNPU) shows the correct sign (i.e. the negative sign)in case 4 but with a statistical significance of at most 10%.
statistically significant.

However, results in other cases are not

Presumably, as we include many factors in order to explain the costdifference, the non-public utility dummy does not affect the costs.
Last, as for characteristics of industry as a control variable, as industry’s bankruptcy ratio(INDBKT) increases and industry’s profitability (INDPRF) decreases, the cost of a firm becomes large.
In summary, our empirical result suggests that internal factors as well as external factors
are important for cost reduction or efficiency. Both governance factors and the diversification
factor are statistically significant.

On the other hand, as the regulation variable is not significant,13among external factors, traditionally considered the main determinants of a firm’s cost level, there
are some factors whose effects on a firm’s cost structure is minor.

6. Conclusion
The main purpose of this study is to investigate how the four factors of governancestructure, business diversification strategy, regulation, and competition affect the cost structure offirms.

Among the four factors, governance structure and business diversification strategy are

considered internal factors amenable to change at the will of a firm seeking to achieve managerial
efficiency. On the other hand, regulation and competition are considered external factors that are
beyond a firm’s control.
the given conditions.

A firm must accept these factors, while striving to attain efficiency under

Our main research question is this: among these four factors, which is themost influential?
From the empirical analysis, we found the following results.
(i)

The governance factor has an important impact on firms’ cost structure.

Empirical results

show that as the ratio of foreign shareholders becomes larger and there is more concentration ona single bank, a firm’s costs decrease.

As for foreign shareholders’ effect, our result is

consistent with Zelenyuk and Zheka (2006) and Berger et al. (2009).
(ii) As a company diversifies more from its core industry into other industries, the costs of all afirm’s business increase. Our results are consistent with previous studies such as Ferrier et al.
(1993), Rajan et al. (2000) and Jeng and Lai (2005). However, the rate of increase in total
costs for diversification is relatively low, indicating there exist cost economies indiversification.
(iii) The regulation factor does not affect the cost structure.

Our results are consistent withprevious studies such as Antel et al. (1995), Berg and Jeong (1991) and Bös and Peters (1995).
(iv) Compared with the regulation factor, the competition factor shows a quite clear effect inreducing a firm’s costs.

This result is consistent with theory and supports previous literature.

(v) Another important finding is that as an industry’s bankruptcy ratio increases and its profitability
decreases, the costs of a firm increase.
Overall, we can conclude that competition is an important factor in reducing a firm’s costs,
and that, contrary to traditional expectations, regulation as an external factor does not have asignificant effect on cost structure.

Also, governance structure is an important factor affecting cost

structure.

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18

Table 1 Definition and Statistics of Variables

Mean

Standard
Deviation

Minimum

Maximum

408,031543,665

1,843

3,042,338

415,140

554,060

1,926

3,000,000

6,260

2,375

1,068

15,907-95.789926.4882

7.3416249.9917-

0.11310.03570.02580.2802-8.4916

3.78171.000015.0000

0.05840.05910.00000.40240.38130.12300.08370.78760.09080.06450.01980.65663.43301.36982.000012.0000-

0.45850.39200.00001.0000-0.46770.25050.01611.0000-0.71540.29360.01191.0000-0.20320.36220.00080.9828-0.87310.38840.25105.9841-0.50000.50070.00001.0000-0.16570.07630.03930.5384-0.72930.08680.41580.9067-0.10500.06620.01770.3374

Variable

Unit

TC(total cost)Q(output)wL(labor price)wM(material price)wK(capital price)T(time trend)
GS FRN (stock ratio held
by foreign shareholders)
GS TOP (stock ratio heldby top 10 shareholders)
GS BANK(main bank dummy)
STRDIV (number of industries inwhich a firm is involved)
RGREG(degree of regulation)
CMPHHI(Herfindahl-Hirschman index)
CMPCR4(concentration ratio of 4 firms)
IND BKT(industry’s bankruptcy ratio)
INDPRF(industry’s profitability)
DNPU(non-public utility dummy)
SL(share of labor)
SM(share of material and service)SK(share of capital)

Millionyen
Millionyen
Thousandyen

19

Table 2 Estimation Results
Variableln Q

Case 1
0.9670***(0.0100)
0.1974***(0.0050)
0.6386***(0.0076)
0.1640***(0.0057)-0.0038**(0.0015)
 .0358***(0.0073)-0.0698***(0.0077)0.0340***(0.0068)
0.2088***(0.0119)-0.1390***(0.0092)
0.1051***(0.0108)-0.0228(0.0154)0.0162(0.0186)
0.0066(0.0164)

Case 20.9690***(0.0100)
0.1973***(0.0050)
0.6399***(0.0076)
0.1628***(0.0057)-0.0038**(0.0015)
0.0361***(0.0073)-0.0699***(0.0077)
0.0339***(0.0067)
0.2064***(0.0118)-0.1364***(0.0092)
0.1025***(0.0107)-0.0219(0.0153)0.0148(0.0186)
0.0071(0.0164)

Case 30.9653***(0.0099)
0.1975***(0.0050)
0.6390***(0.0076)
0.1635***(0.0057)-0.0038**(0.0015)
0.0363***(0.0073)-0.0703***(0.0077)0.0340***(0.0068)0.2079***(0.0118)-0.1376***(0.0092)
0.1036***(0.0108)-0.0257*(0.0153)
0.0134(0.0185)0.0123(0.0164)ln GS FRN---

ln GS TOP---ln GS BANK

-

-

-

ln STRDIV----0.0007(0.0014)-0.0006(0.0014)0.0292*(0.0153)-0.0001(0.0014)

ln wL
ln wM
ln wK
(ln Q)2(ln wL)2
ln wL•ln wM
ln wL•ln wK(ln wM)2
ln wM•ln wK(ln wK)2
ln Q•ln wL
ln Q•ln wK
ln Q•ln wM

ln RGREG

Case 40.9661***(0.0123)0.1944***(0.0049)
0.6461***(0.0074)
0.1595***(0.0058)-0.0043**(0.0015)0.0359***(0.0073)-0.0635***(0.0076)0.0275***(0.0069)
0.1862***(0.0121)-0.1227***(0.0097)
0.0952***(0.0113)-0.0114(0.0157)-0.0012(0.0188)0.0125(0.0165)-0.0214***(0.0085)-0.0079(0.0359)-0.0815***(0.0232)
0.1455***(0.0302)-0.0014(0.0014)0.0472***(0.0156)

Case 50.9632***(0.0121)0.1947***(0.0049)0.6447***(0.0074)
0.1607***(0.0059)-0.0044***(0.0015)
0.0362***(0.0073)-0.0639***(0.0075)
0.0277***(0.0070)0.1886***(0.0121)-0.1248***(0.0098)
0.0971***(0.0114)-0.0155(0.0155)-0.0028(0.0187)
0.0183(0.0164)-0.0210**(0.0084)0.0047(0.0360)-0.0748***(0.0230)0.1503***(0.0300)-0.0007(0.0014)0.0222***(0.0030)-0.0347(0.0274)
12.2080***(0.0316)0.0154**(0.0062)-0.1512***(0.0348)0.0281***(0.0034)
0.0255(0.0337)
12.1651***(0.0327)

0.0510***(0.0146)
0.0152**(0.0061)-0.1472***(0.0346)
0.0271***(0.0034)
0.0365(0.0337)
12.1684***(0.0321)

Case 80.9611***(0.0121)0.1932***(0.0049)
0.6430***(0.0075)
0.1638***(0.0060)-0.0048***(0.0016)0.0356***(0.0073)-0.0611***(0.0075)
0.0255***(0.0071)
0.1927***(0.0121)-0.1316***(0.0099)
0.1061***(0.0117)-0.0227(0.0154)-0.0068(0.0188)0.0296*(0.0168)-0.0234***(0.0082)
0.0024(0.0359)-0.0717***(0.0229)0.1817***(0.0305)-0.0001(0.0014)-0.0014(0.0257)
0.0521**(0.0247)0.0152**(0.0061)-0.1473***(0.0346)
0.0271***(0.0034)
0.0366(0.0338)
12.1686***(0.0325)901.368

902.790915.185916.358916.5440.97090.97130.97190.9722

0.9722ln CMPHHI-

ln CMPCR4--

0.0428***(0.0144)-0.0559***(0.0148)ln IND BKT

-

-

-

-

-

ln INDPRF

-

-

-

-

-

0.0224***(0.0029)-0.0467*(0.0252)
12.2528***(0.0303)

0.0225***(0.0029)-0.0373(0.0256)
12.2398***(0.0310)0.0217***(0.0029)-0.0259(0.0259)
12.2359***(0.0307)

0.0233***(0.0030)-0.0483*(0.0271)
12.2052***(0.0323)894.485

897.344900.1120.9676

0.96780.9681T
DNPU
Constant

Log-likelihood

R2

-

20

-

Case 6
0.9637***(0.0121)0.1930***(0.0049)0.6443***(0.0075)
0.1628***(0.0060)-0.0048***(0.0016)0.0354***(0.0073)-0.0607***(0.0075)
0.0253***(0.0071)
0.1906***(0.0121)-0.1299***(0.0099)
0.1047***(0.0116)-0.0191(0.0154)-0.0052(0.0189)0.0243(0.0167)-0.0238***(0.0083)-0.0092(0.0356)-0.0780***(0.0229)0.1781***(0.0306)-0.0007(0.0014)0.0426***(0.0153)-

Case 70.9611***(0.0120)0.1932***(0.0049)
0.6429***(0.0074)
0.1639***(0.0060)-0.0048***(0.0016)0.0356***(0.0073)-0.0611***(0.0075)
0.0255***(0.0071)
0.1929***(0.0121)-0.1319***(0.0099)
0.1064***(0.0117)-0.0226(0.0153)-0.0068(0.0188)0.0294*(0.0166)-0.0234***(0.0082)
0.0022(0.0357)-0.0719***(0.0227)0.1817***(0.0304)-0.0001(0.0014)-

Concavity
12.6%
13.1%
12.8%
20.7%
Condition(Note):(1) Numbers in parentheses are standard errors.
(2) Sample size is 358.
(3) Statistically significant at 1% (***), 5% (**) and 10% (*).

19.6%

17.9%

15.4%

15.9%

[2014.9.11 1169]

21