Dynamic Performance and Structural Changes of Korean Firms after the Financial Crisis:
Evidence from Survey of Business Structure and Activities (2005-2007)
By Hak K. Pyo and Keun Hee, Rhee*

Abstract

This paper introduces Survey of Business Structure and Activities conducted by National
Statistical Office in Korea during the period of 2005-2007 and analyzes Korean firms’
activities after the financial crisis of 1998-1998. Korean firms are found to have increased
their R&D and managerial innovation from e-business. The higher the transparency oftechnologies of the industry to which the firm belongs is, the higher the effect of a firm’s
catch-up

withadvancedfirms.

Korean

firms

have

also

increased

theirglobal net working and outsourcing activities. There was also a positive correlation between
R&D intensity and size of firms. These findings are in accord with the Japanese firms’ recent
activities observed in Japan’s Basic Survey of Business Structure and Activities.

* Professor of Economics and Director of Center for National Competitiveness, Seoul
National University and Senior Researcher at Korea Productivity Center respectively. All
correspondences can be directed to pyohk@plaza.snu.ac.kr

1

1. Introduction

In the market economy system, firms are the most important economic agents taking chargeof production activities which are the ultimate sources of returns to capital and labor income.
Since the growth and the development of firms are directly linked with national well-being,firms’ performance reflects the nation’s economic progress in living standard. Therefore, theneed for firm-specific database has been emphasized in recent years and national statistical
offices have paid due attention to enhance firm-specific data in addition to conventional
establishment-based survey data.

There have been two approaches for researches on firms’ activities. First is the industry-levelapproach. An industry can be defined as the aggregation of firms performing similar businessactivities, and therefore, the industry-level approach is to analyze firms’ activities by using
aggregated data on an industry, not on each firm. Until 1970s and 1980s, most studies onfirms’ activities were based on the industry-level approach. More recent studies by Pyo, Rhee
and Ha (2007)(2008) and Chun, Pyo and Rhee(2008) have adopted this approach. However,under the traditional static theory of firms, it was difficult to explain why there exist
successful firms and unsuccessful firms under the same regulatory conditions andsurrounding factors. Second is the firm-level approach, which analyzes patterns andcharacteristics of firms’ activities and estimate firms’ achievements based on informationfrom each firm, not from the aggregated data. Recent studies in Korea include Hahn
(2000)(2004), Ahn, Fukao and Kwon (2004), Ahn (2005) and Rhee and Pyo (2008).

The firm-level approach has gradually gained popularity since 1990s. For example, in case of
Korea, we had to pay deep attention to why there were significant differences in performance
among different firms within the same industry during the financial crisis. The industry-level
analysis could not reveal factors behind the firms’ up-and-down phenomenon and therefore
called for re-orientation of the research on firms toward the increasing use of micro-based
firm-specific data. The popularity of this emerging research can also be due to the increased
availability of micro-level data and to the dissatisfaction with the concept of aggregate
production function. The most important motivation, however, has been the emergence ofinteresting questions that can be addressed effectively only with the use of micro data given2the severe heterogeneity of firms’ characteristics, such as size and performance. The otherobvious reason for the usefulness of the large samples of the micro-level panel data is that itallows us to control a number of factors to obtain more robust parameter estimates.

On the other hand, we also have to pay due attention to the limitation of firm-level data when
we want to expand firm-based findings to the industry-level and national level because firmspecific micro data are usually limited in sample size and therefore, tend to be sensitive to theway samples are stratified and surveys are conducted. In other words, it will be appropriate to
examine the firm-level data and findings and compare those with empirical results at
industry-level and national level. At the same time, many sources of micro data are private
and commercially funded. For example, Korea Investors Service Co. (KIS) or National
Information and Credit Evaluation Co. (NICE) provide listed firms’ firm-specific financial
information but they may lack non-financial information and do not provide unlisted andunincorporated firms.

With these developments in mind, Survey of Business Structure and Activities was conductedby National Statistical Office of Korea during the period of 2005-2007. While the Mining andManufacturing Census and Survey are establishment-based and production-oriented, Surveyof Business Structure and Activities was conducted to make full-scale firm statistics including
wide spectrum of business activities such as business structure, R&D, external service,
networking between firms, business strategy, the use of information technology, and the useof management information system. In what follows, the outline of the survey will bepresented in section 2. Section 3 summarizes major findings of the survey and analyses ondeterminants of business activities. Section 4 concludes the paper.

2. Outline of Survey of Business Structure and Activities (2005-2007)

The purpose of conducting a Survey of business structure and activities 1 is to provide basic
data for the policy authorities by examining the actual conditions of firms’ businessenvironments, management strategies such as diversification, globalization, and strategic

1

Report by Lee and Pyo(2009).

3

alliances and the changes in their industrial structure through a comprehensive survey offirms’ diverse economic activities. The first survey was conducted in 2006 and has been
conducted every year since 2006. So far the database for three consecutive years (2005-2007)
has been built.
The scope of the survey in terms of industry classification covers the entire industries
including Agriculture & Forestry, Mining & Manufacturing and Services as shown in Table 1.
The survey was conducted to about 12,000 firms with more than 50 employees and capital
above 300 million Won (in case of Retail & Wholesale and other Services, the firms with lessthan 50 employees but with capital above 100 million Won) as of December 31 every year.
These firms’ sales amount covers about 70 percent of total sales so that the sample seems torepresent well the population of entire firms.
Table 1 Number of Firms in Survey of Business Structure and Activities (2005)(unit: numbers, %)Industrial Classification

Incorporated
Firms
(B)

Surveyed Firms(A)

Agriculture, forestry, and fishing
Mining and quarrying, andmanufacturing
Electricity, gas, steam and water supply
Construction
Wholesale and Retail trade
Accommodation and food service
activities
Transportation
Information and communications
Financial and insurance activities
Real estate activities and renting andleasingServices
Total(A)/(B)

25

474

5.3

6,408

53,131

12.1

48
675
886

108
36,84945,341

44.4
1.8
2.0

182

1,429

12.7

743
56
233

13,603
715
2,158

5.5
7.8
10.8

161

5,680

2.8

1,829
9,147

28,078
187,566

6.5
4.9

Source: Lee and Kim (2009)

Korea’s Survey of Business Structure and Activities is quite similar to Japan’s Basic Survey ofBusiness Structure and Activities in terms of both the scope and the contents of survey except the way
the survey was conducted: interview or mail survey as summarized in Table 2. France’s survey seems
to cover relatively more small firms including those with employees over 10.

4

Table 2 Comparison of Survey of Business Structure and Activities :Korea, Japan and France

Surveyed
name

Coverage

Korea
Survey of Business Structure
and Activities

Japan
Basic Survey of Business
Structure and Activities-Total industries-employees over 50 withcapital over 300 million won-except Financial andinsurance activities,
Transportation, Construction
and other services-employees over 50 withcapital over 30 million yen-Total industries-sampling by domestic
investment firms or foreign
investment firms, and by
employees over 10 and sales
over 38 million euro or
employees under 10 andsales under 38 million euro

every year

every year

every year

2006

1992

1996

2008

2008

2008

2 kinds(by industry)

1

2 kinds(by size of firms`)

Surveyfrequency
First survey
year
Recentsurvey year
Kinds ofquestionnaire

Surveycontents-7 fields except organizations
within the firm, and thenumber of employees-11 fields except organizations
within the firm, and thenumber of employees

Surveymethodtemporarily-hired survey
conductors

mail survey

FranceStructural Enterprise Statistics-firms' transition-by organization, size,
industry, and types ofbusiness-firms' innovation-firm's subsidiary system-firm’s asset and businessperformance
mail survey

Source: Lee and Kim (2009)

As shown in Table 3, the contents of the survey include a firm’s general information(company name, location, representative director’s name, year of establishment, form ofestablishment, and capital) and general information on the business management andstrategies such as outsourcing, R & D, possession of technology, management information
system, operations in overseas markets and strategic business alliances etc. The mostnoticeable characteristic of the survey on business structure and activities is that it includes
information on the management indicators and strategies, which were not covered by theprevious statistical surveys on the Mining & Manufacturing industry and the Service
industries.

5

Table 3 Contents of Survey on Business Structure and Activities
a. General Information-

Company name, location, representative director’s name, year of establishment, form of establishment,
and capital (paid-in capital)b. Organizations within the firm, and the number of employeesc. Assets and liabilities, and items related to capitald. Business performancese. Affiliated companies (subsidiaries, related companies, parent companies)
f. Transactions with other firms and overseas transactions (proportion of branches and subsidiaries)
g. Cost of outsourcing
h. Research and Development
i. Possession of technology and use
j. Management information systemk. Firm’s management practices-

Franchise, operation in overseas markets, new-business launch, strategically allied companies-

Performance-based compensation system

Table 4 Comparison between Survey of Business Structure and Activities and KIP2008 Database
Survey of BusinessYear

Nominal Values Structure and Activities (A)(Million won)
Net

2005

Value-added
Gross Output
Net

2006

Value-added
Gross Output
Net

2007

KIP2008 Database

Value-added
Gross Output(B)(Million won)(A)/(B)
Ratio

240,882,685

699,409,600

0.34

1,396,790,127

1,861,198,561

0.75

252,172,660

730,731,500

0.35

1,490,000,000

1,972,167,346

0.76

295,474,883

778,873,900

0.38

1,683,730,838

2,102,098,612

0.80

Note: In case of Survey of Business Structure and Activities; Gross Output=Total Sales; Net Value-added=Ordinary
Income + Total Salary + Tax + Depreciation Costs + Rent + Bad debt expenses
Sources: Lee and Pyo (2009)6

The 2006 Survey on business structure and activities was conducted to a total of 10,786 firms(affiliated with 68,202 firms). To check the degree of representation of this survey which
includes the general information on the firms, the total value added and total amount of
production for 2005-2007, we have compared the survey results with the figures in KIP2008
Database, which can be regarded as the industrial database. As shown in Table 4, the nominal
net value-added amount and the nominal gross output in the 2005 Survey of businessstructure and activities accounted for 34% and 75% respectively of the KIP Database. The
nominal net value-added as well as the nominal gross output accounted for 35% and 76%
respectively in 2006 and 38% and 80% in 2007 respectively.

According to Sohn (2009), while the number of subsidiary enterprises of total firms surveyed
is only 2.1% of the total number of enterprises, they account for 21.4% of the total number of
employee in employment, and 38.8% of GDP in value-added. The number of firms has
declined from 10,908 in 2005 to 10,749 in 2007 but the number of subsidiary enterprises
increased by 9,422 from 60,317 in 2005 to 69,728 in 2007.

The firms’ regional distribution shows 63.3% of the surveyed firms are centered in themetropolitan area and 84.7% of their subsidiary enterprises are also centered in themetropolitan area. The firms’ concentration ratio in the metropolitan area has increased from
62.5% in 2005 to 63.3% in 2007 and their subsidiaries’ concentration ratio also increased
from 82.4% to 84.7% during the same period. In terms of business diversification, 31.4% offirms are engaged in other industrial activities except main business and the ratio of otherbusiness ratio has increased from 23.2% in 2005 to 31.4% in 2007. In terms of management
performance, Finance and Insurance activities and Electricity, Gas, and Water Supply haverecorded large profits. The trend of business profit indicates that profits of Professional,
Scientific and Technical Activities have been largely expanded but on the other hand,
Agriculture & Forestry, Business and Personal Services recorded lower profits.

Korean firms are found to have increased their operations abroad during the period of 20052007 significantly. While the total number of firms surveyed declined by 159 firms, thenumber of firms which have engaged in overseas operation has increased by 792 firms.
Among them there were 414 Manufacturing firms, 74 Construction firms, 84 Retail &7

Wholesale firms and 79 Printing and Visual Communication firms. As shown in Figure 1, theratio of firms which have engaged in foreign business activities in total number of firms
surveyed by industries indicates the largest in crease in Electricity and Gas (15.4 %) which isfollowed by Construction (12.1 %) and Finance and Insurance (10.4 %).
Figure 1 Increase in the Ratio of Business with Foreign Operations by Industry (2005-2007)(unit: %point)

Source: Sohn (2009)

3. Major Findings from Survey of Business Structure and Activities

The major findings from Survey of Business Structure and Activities are summarized in thissection and compared with recent findings from studies on Japanese firm activities.

3.1 Diversification and Internationalization

Park (2009) analyzed aspects of diversification and internationalization of Korean firms’
activities and identified the decision factors of diversification and internationalization. In
8addition, the correlation between the two indicators and its impact on business performancehas been assessed. The result of analysis has found the following facts. First, the important
decision factors of diversification and internationalization are firm’s size and age. The larger
the firm is, the deeper diversification and internationalization is, and the older the firm is, thehigher possibility of the diversification. Second, the relative importance of import and export
and the possession of subsidiaries in foreign countries have affected firms’ diversification andinternationalization. The firm which has higher degree of diversification tends to have higher
weight of import and export and more subsidiaries in foreign countries in non-financial sector.

On the other hand, the result showed that there is no significant relationship in financial
sector. Third, there is a significant relationship between diversification and the possession ofsubsidiary. The possession of domestic subsidiaries is in general connected to horizontal
diversification while the possession of subsidiaries in foreign countries is connected to related
diversification. Fourth, the effect of diversification and internationalization on the businessachievement is in general positive effect in financial sector, but there is no significant finding
in non-financial sector.

Table 5 Correlation between Diversification and Internationalization Indicators (Non-financial Sector)

SR
BI
DT
DR
DU
Weight of export andimportWeight of foreign
outsourcing
Weight of foreign capital

Weight ofexport andimportWeight offoreignoutsourcing

SR

BI

DT

DR

DU

1
-0.99***-0.97***-0.69***-0.70***

1
0.98***
0.69***
0.73***

1
0.76***
0.70***

1
0.16***

1-0.07***

0.07***

0.08***

0.06***

0.05***

1

0.01

0

0

-0.02

0.01

0.14***

1

-0.01

0.01

0.01

0.01

0

0.22***

0.03***

Weight offoreigncapitalWeight ofsubsidiaryin foreigncountry

Weight of subsidiary in-0.13***
0.14*** 0.14*** 0.07*** 0.14***0.30***
0.14***-0.04***
1foreign country
Note: ***, **, and * mean each 1%, 5%, and 10% significance level. ; SR-Specialized Rate, BI-Berry Index, DT-total diversification index, DRrelated diversification index, DU-unrelated diversification index
Source: Park (2009)9

Table 6 Correlation between Diversification and Internationalization Indicators (Financial Sector)
Weightofforeigncapital

SR

BI

DT

DR

DU

SR
BI
DT
DR
DU

1
-0.99***-0.98***-0.96***-0.31***

1
0.99***
0.97***
0.30***

1
0.99***
0.27***

1
0.12*

1

Weight of foreign capital

0.06

-0.05

-0.05

-0.04

-0.09

1

Weight of the possession ofsubsidiary in foreigncountry

-0.02

0

0.01

-0.01

0.07

-0.14**

Weight ofthepossessionofsubsidiaryin foreigncountry1

Note: ***, **, and * mean each 1%, 5%, and 10% significance level. ; SR-Specialized Rate, BI-Berry Index, DT-total
diversification index, DR-related diversification index, DU-unrelated diversification index
Source: Park (2009)

3.2 Outsourcing, Strategic Alliance, and R&D

Kim (2009) finds the importance of outsourcing and strategic alliance in Korean firms’ recent
business activities. However there have been few empirical studies on outsourcing andstrategic alliance. What factors make firm carry in outsourcing or strategic alliance, and what
outsourcing or strategic alliance affect on firm achievement is greatly important topic ofresearch. The result of analysis is that there are totally different results by model’s form in thecase of the outsourcing decision factors, and in the case of the effect that diversification andinternationalization affect on the business achievement, there needed the following researchthrough longer time series. In order to increase the success possibility of outsourcing andstrategic alliance in the future, the result pointed out that many research is required about therole of firm and government.

Chun (2009) shows there was a positive relation between R&D intensity and firm size in
manufacturing, but the degree of correlation was less apparent in service. The analysis ofeach industry shows a positive relation between R&D intensity and firm size inpetrochemicals and transport equipment, but R&D intensity did not change according to firmsize. The business innovation by R&D and e-business has had mutually supplementary
relationship. Survey of Business Structure and Activities includes questions on factors related10with R&D and business, such as e-business, diversification, internationalization andmanagement structure. Since the firm’s business renovation and R&D usually have an effecton firm’s performance Survey of Business Structure and Activities has required a long-term
panel data.

Figure 2 Matrix of Advance to New Industry (2005-2007)

Source: Kim (2009)11

Table 7 Regression Result of R&D Intensity (Manufacturing)
2005

Emp
Emp2/100
CR3
Age
Num of obs
R-squared(1) OLS
0.088*(0.045)-0.025(0.063)0.003(0.003)-0.013***(0.004)6,210
0.0863(2) Tobit
0.345***(0.095)-0.387**(0.155)0.004(0.004)0.008(0.006)
6,210
0.0268

2006(3) OLS
0.079*(0.041)-0.013(0.051)0.006**(0.003)-0.02***(0.004)6,183
0.0858(4) Tobit
0.308***(0.093)-0.31**(0.142)0.011***(0.004)-0.003(0.006)
6,183
0.026

2007
(5) OLS
0.164***(0.050)-0.114*(0.067)-0.012***(0.004)-0.033***(0.004)6,251
0.0807(6) Tobit
0.422***(0.107)-0.447***(0.165)-0.021***(0.005)-0.020***(0.007)6,251
0.0199Note: The number in parenthesis are Standard deviations.; ***, **, and * mean each 1%, 5%, and 10%
significance level.; Emp-Employee, CR3-Market share of top 3 companies in sales
Source: Chun (2009)

Table 8 e-business Effect on R&D Intensity (2007)
Total Industry

Emp
Emp2/100
CR3
Age
ebiz
ebiz - inebiz - out
Num of obs
R-squared(1) Tobit
0.222**(0.095)-0.19(0.155)-0.016***(0.005)-0.018***(0.006)1.603***(0.151)8,717
0.0348(2) Tobit
0.184*(0.096)-0.144(0.156)-0.016***(0.005)-0.018***(0.006)
1.179***(0.151)0.834***(0.186)
8,717
0.0343

Manufacturing(3) Tobit
0.337***(0.107)-0.339**(0.165)-0.022***(0.005)-0.024***(0.007)1.432***(0.167)6,251
0.0223(4) Tobit
0.315***(0.108)-0.313*(0.166)-0.022***(0.005)-0.024***(0.007)1.084***(0.168)0.620***(0.220)6,251
0.0218Services(5) Tobit-0.392(0.299)1.461(0.963)0.016(0.017)0.01(0.017)2.295***(0.363)2,466
0.0264(6) Tobit-0.492(0.303)1.674*(0.970)0.015(0.017)0.012(0.017)1.569***(0.369)1.458***(0.377)2,466
0.0262

Note: The numbers in parentheses are Standard deviations.; ***, **, and * mean each 1%, 5%, and 10%
significance level.; Emp-Employee, CR3-Market share of top 3 companies in sales, ebiz-Utilization of ebusiness(1=utilization, 0=non-utilization), ebiz-in - Internal utilization of e-business(1=utilization, 0=nonutilization), ebiz-out - External utilization of e-business(1=utilization, 0=non-utilization)
Source: Chun (2009)12

Lim and Lee (2009) analyzed outsourcing of R&D and have summarized the following
findings. First, R&D outsourcing was an important strategy to not only large enterprises but
also many small and medium-size firms. The 18 percent of firms with R&D activities haveoutsourced, R&D resulting in the share of external R&D cost in total R&D cost has becomein the range of 33 percent to 35 percent.

Table 9 Tobit Regression Result of Weight of R&D Outsourcing
Tobit (5)Coef.
-1.157

_cons
ebiz
PL

Tobit (6)
S.E.

***

0.155

***

0.231

*

0.062
0.037
0.122

2

(PL)
RDINT

-0.0070.020

2(RDINT)
RDP
Size
Size

0.084
2.676

***

0.036
0.551

0.037

Ind1

0.288

Ind2
Ind3

0.058
0.068

0.086
***

0.272

Ind5

0.419

***

/sigmaNum of obs.
Log Likelihood
LR chi2
Pseudo R2

0.833

Ind4

0.063

0.143

***

0.037

0.700

***

0.254

-0.436
1.320

**

0.219

***

0.332

*

0.236

5589
148.520-2579.615***
0.028

0.056

0.036

6.693

***

1.040

-6.614

***

1.504

0.052

0.059

0.263

0.055

0.003
0.037

0.055
***

S.E.
***

-0.436
**

2

BHI

Coef.
-1.181

0.086
***

0.059
0.056
0.055

0.207

***

0.058

0.060

0.396

***

0.060

0.026

0.832

0.056

0.026

5589
201.060-2553.344***0.038

Note: The number in parenthesis are Standard deviations.; ***, **, and * mean each 1%, 5%, and 10%
significance level.; ebiz-Utilization of e-business(1=utilization, 0=non-utilization), PL(Technology Level)=the
number of patent/employee, RDINT(R&D intensity), RDP-Possession of internal institute(1=possession, 0=nonpossession), Size- normalization of sales, BHI(Berry-Herfindahl Index), ind1-chemistry, ind2-electric andelectronic , ind3-machinery, ind4-services, ind5-Wholesale and retail trade, and social overhead capital
Source: Lim and Lee (2009)

For firms with relatively lower technology level, outsourcing activity is the way to fill thetechnology gap, but for large firms outsourcing activity is the supplement to internal R&D.
13

Second, R&D outsourcing is relatively weak in small and medium-sized enterprises. The
reason is not only the lack of R&D ability by themselves, but also the lack of management
capacity to perform outsourcing activities. Third, the feature of technological innovation is
the results of interaction and networking between universities and firms. Government
promotion of the interaction has much influenced in R&D outsourcing activities than internal
R&D investment activities. However, external and internal R&D costs are treated in the same
way as the tax support to current R&D investment. As a way to encourage networking with
university, it seems desirable to find a scheme to grant tax incentives to R&D outsourcing
investment more than to internal R&D investment. Fourth, in the process of technologicalinnovation technology outsourcing and R&D outsourcing has been the core way to supply
technology from external sources. However, Korean firms have lacked the ability oftechnology outsourcing on compared with advanced nations’ firms. It is important to improve
management capacity in terms of technology outsourcing in the future. Thus it is to be highly
recommended for firms to accumulate the compound capacity such as know-how (how they
can develop technology) for technology innovation, know-why (why technology innovation
is important), know-where (where they can get technology) and know-who (from whom they
can get technology).

3.3 Determinants of Business Performance and Growth

Determinants of business performance and growth of firms in Korea by Lee and Kang (2009)
have shown that higher export share in total sales has negative effects on profitability, laborproductivity and growth of firms. These findings are in general contrary to the other existingstudies and, therefore, call for special attention or interpretation. Also, the ratio of foreign
capital and market share has also negative effects on these performance indicators in the
regression of profitability using ROS (return on sales) as dependent variable. Profitability
seems to be significantly affected by the turnover ratio of total liabilities and net worth. ROA(return on assets) can be expressed to multiply ROS by the turnover ratio of total liabilities
and net worth. If the turnover ratio of total liabilities and net worth is high, ROA cannot bethat different even though ROS is low. The regression of profitability using ROA as
dependent variable showed that the share of advertising in the total sales affected profitability
negatively, but the share of advertising did not affect profitability. However, except for the14regression using ROA, this finding was nor repeated in other regression. The growth
regression where growth is defined as the growth rate of sales reported that the expenditure ofadvertising costs significantly affected positively the growth of firm. Although the effect ofadvertising costs seemed to be similar to the result of previous researches, the effect of R&D
and the number of patent registrations did not produce any significant effect on the growth offirm. The R&D intensity is shown to have a negative effect on the business performance
when ROS is used as dependent variable, so that it was opposite to expectation. Patent did notshow any significant result. However, the result of the regression should be carefullyinterpreted considering the following potential problems. First, even though macro factors
such as exchange rate variation should be controlled, Survey of Business Structure andActivities was not controlled by macroeconomic variables, because the time series of data wasvery short. Second, in this research, the export was the direct export amount which went
through customs clearance under the firm’s name not indirect export amount.

Table 10 Determinants of Business Performance:A Synthesis of Regression Results
Variables

ROA(return on assets)

Weight of external(-)
and import
Weight of foreign(+)
capitalWeight of(-)
outsourcing costMarket Share
Weight of advertising
costs
Weight of R&D
the first term (-)
The number of patent
Source: Lee and Kang (2009)

ROS(return on sales)

Labor
Productivity

Growth of Firms

(-)

(-)

(-)

(+)
(-)

the first term (-)

(- ~)

(+)

the first term(-)(+)

3.4 Comparative Findings with Japanese Firms

Jung (2009) compared the productivity between Korean firms and Japanese firms, andconfirmed that sales per firm in 2005 and 2006 were on the average 1.7 times greater thanthose in Korea. Regarding a firm’s average scale, it was observed that there was a significant
difference by industry between Korea and Japan. However, Korean firm’s net profits werehigher than Japanese firms by 10 percent. This means that the net profit rate observed by
Korean firms is higher than that of Japanese firms since sales per firm in Korea are less than15

those in Japan. While labor productivity in Korea was lower by about 10 percent on the
average in 2005 and 2006, capital productivity in Japan was lower by about 10 percent. It was
confirmed that the total factor productivity (TFP) of Japanese firms in the manufacturingindustry was lower than that of Korean firms by about 2.7 percent. Recent researches haveobserved that the gap in total factor productivity between Korean firms and Japanese firms
has been narrowed. Regarding Korean firms’ productivity, the productivity of big
corporations was higher than that of small- and medium-sized firms, and that the difference
was more pronounced in 2006 than in 2005. Data in 2007 also showed that such polarization
was becoming much deeper compared with the previous year. It was also observed that whenlarger sample firms were used big corporations possess relatively higher productivity.
Meanwhile, upon analyzing the catch-up factors, the Survey of Business Structure andActivities seem to have produced highly reliable results representing many industries,
compared with Jung, Lee and Fukao (2008) which had used samples of listed companies only.
Analysis proved that the higher the transparency of a technology in the industry to which afirm belongs, the higher the effectiveness of its catch-up. Also, the big-brother effect of the
top ranking firm in the industry was proven to be strongly effective. In other words, ananalysis indicates that the leading productivity enhancement of first-rated firms such as
Samsung Electronics, Hyundai Motors and POSCO has significantly affected other firms
within the same industry through technology transfer, manpower transfer, spill-over inmanagement know-how, strategic alliance in the global market and production networking.
Also, by utilizing patent data, the number of patents representing a firm’s innovation capacity
is found to have a positive effect on productivity catch-up.

Figure 3 Trend of Polarization Index of Total Factor Productivity in Korea

Source: Jung (2009)16

Table 11 Comparison of Firm Productivity between Korea and Japan
2005

2006

Korea(A)Japan(B)

Ratio
(B/A)

Korea(A)Japan(B)

Ratio
(B/A)

96

110

1.14

97

104

1.06

0.23

0.2

0.86

0.22

0.21

0.95

96

100

1.042

98.7

100

1.013

Labor Productivity(Value Added/
Employees, a hundred
won)

Capital Productivity(Value Added/Total asset)

TFP index
Source: Jung (2009)

Recent empirical research by Fukao and Kwon (2009) using a basic survey on the businessactivities and the latest JIP database has estimated the total factor productivity trends in Japanamong different industries. The rising TFP rate of the market economy as a whole stayed at
an average annual rate of 0.2%, but from 2000 to 2005 rose by more than 1% to 1.3%. This
research analyzed the productivity trends from 1996 to 2000 and from 2001 to 2005 by using
the micro-data of the Survey of Business Structure and Activities of which the questionnaire
included most of the business activities in Japan. When TFP increase was decomposed bywithin-effect, reallocation effect, and entry and exit effect, the TFP increase since 2000, either
in manufacturing or non-manufacturing, was caused mainly by the within-effect. Regarding
dynamic metabolism through entry and exit effects, little improvement was observed. It isinteresting to note exit effect on TFP was found to be negative in many industries since 2000.

The analysis on the data of ongoing businesses in order to examine the content of the withineffect showed that considerable part of the acceleration of TFP growth was achieved by
restructuring within the firm and that the restructuring was achieved mainly in exporting
firms, multinational enterprises, and firms practicing R&D. It was observed that firms whosedebt-equity ratio is less than 25% had noticeably low TFP level in the early period but raised
their TFP by sharply reducing all production inputs even during the boom periods. The
problem of the Zombie firms in Japan is likely to be solved by restructuring rather thanremoval. Clearly, restructuring accelerated the growth of a firm’s TFP. Other factors that
contributed to the increase in TFP include technology transfer between parent companies andaffiliates, the catch-up effect through the spill-over of technology within the industry, and17

progress in internationalization and investments in R&D.

Table 12 Analysis on Determinants for TFP Growth Rate
Manufacturing

Non manufacturing

Manufacturing

Non manufacturing

Pooled OLS
Restructuring firms dummy(Firms
to decrease employee over 5% = 1,
Not = 0)Restructuring firms dummy(Firms
to decrease employee over 10% =1, Not = 0)0.009 ***

0.006 ***

(10.72)(3.35)
0.015 ***

0.012 ***

(11.63)(4.80)

0.204 ***

0.236 ***

0.203 ***

0.235 ***

(41.06)(46.29)(40.93)(46.22)0.006 ***

-0.0010.006 ***

-0.001(14.96)(-0.75)(14.77)(-0.89)

Export intensity

0.016 ***
(4.41)

0.051 ***
(3.01)

0.015 ***
(4.24)

0.051 ***
(3.01)

R&D intensity

0.165 ***
(6.32)

0.140 ***
(2.73)

0.165 ***
(6.34)

0.137 ***
(2.68)

0.002 *
(1.78)

0.004(1.35)

0.002 *
(1.76)

0.004(1.35)

0.010 ***
(14.22)0.013 ***
(8.13)

0.010 ***
(14.44)0.013 ***
(8.08)

Foreign capital dummy

0.028 ***
(6.76)-0.001(-0.14)0.028 ***
(6.82)-0.001(-0.19)constant-0.024 ***(-9.98)-0.013 **(-2.03)-0.023 ***(-9.56)-0.012 *(-1.93)the number of obs.

36,111

40,76836,111

40,768R-squared

0.194

0.128

0.195

0.128

TFP gap (t)Firm's Size (t)Multinational corporate
dummy(Firm to invest abroad
subsidiary firms = 1, not =0)
Domestic firms' subsidiarycompany dummy（t）

Note: Regression is included to industry dummy and year dummy; Thu number in parenthesis is White t value to consider serial; ***, **, and* mean each 1%, 5%, and 10% significance level correlation;
Source: Fukao and Kwon (2009)

The management activities and strategies of firms such as diversification, internationalization,
strategic alliance’, R&D activities, profitability, and productivity improvement are eventuallyrelated with the survival of firms in the market. The life cycle of a firm is the process of entry,
survival and exit in the market. Whether this process could be explained through the
productivity difference among firms has been an important issue in productivity studies. In
other words the higher a firm's productivity is, the better performance of management
activities it has. So the possibility of firm's survival will be growing and vice versa.

18

Empirical research by Miyagawa, Rhee, and Pyo (2009) on the firm dynamics between Korea
and Japan has analyzed the productivity growth between entry firms, continuous firms andexit firms and their contribution to the productivity growth of industry through thedecomposition of total factor productivity. In general continuous firms tend to have an
initiative of the productivity growth due to the entry barrier such as technology level andprice barrier. Rhee and Pyo (2008) have found a similar result from Korean firms, and the
productivity enhancement of the continuous firms has been also found after strong
restructuring process since economic crisis in 1998. Fukao and Kwon (2006) has analyzed
productivity trend in Japanese firms, and revealed the higher productivity firms are included
among exit firms.

Based on the Survey of Business Structure and Activities, Inui et al (2008) has analyzed that
there is a reversed U-shaped pattern between market competition and innovation activities offirms. Namely firms have an incentive to conduct innovation to escape from competition. On
the other hand other firms that are far from the technology frontier have little incentive toinnovate because the productivity gains being derived from innovation activities are small.
Firms have devoted to improve productivity through various management activities forsurviving in competition, and to intensify the innovation activities in nature. Consequently
when technological innovation such as product innovation and process innovation has beenachieved, the possibility of survival in the market has improved. Under the globalized
economy the competition is challenging. It is to be an inevitable strategy for firms to raise
productivity for competitiveness and survival in the market.

Table 13 Decomposition of TFP Growth Rate between Korea and Japan in Manufacturing (%)
PeriodRhee andPyo(2008)
Fukao andKwon(2006)‘92-03‘94-01

WithinEffect(a)-0.52(-0.29)1.20(0.56)

Between
Effect(b)-0.48(-0.27)-0.09(-0.04)

Covariance
Effect(c)
1.12(0.62)
0.42(0.20)

d=a+b+c
0.12(0.07)
1.53(0.73)

Entry
Effect(e)
1.47(0.81)
1.13(0.53)

Exit
Effect(f)
0.21(0.12)-0.52(-0.24)g=e+f
1.69(0.93)
0.61(0.29)

Total
Effect(d+g)
1.81(1.00)
2.10(1.00)

Note: d=Sum of Firm's Within Effect, Between Effect, and Covariance Effect, g=Net Entry EffectSource: Miyagawa, Rhee and Pyo (2009)19

4. Concluding Remarks

As firm activities become diversified, a variety of statistics on firm activities are needed foranalyzing firms in various different angles, but existing firm statistics are not sufficient bothin depth and coverage. Under this circumstance, National Statistical Office of Korea haslaunched the development firm statistics on diverse activities by constructing database since2003. Survey of Business Structure and Activities launched in 2006 has surveyed eight fields the basic information of firms, structure and restructuring of firms, systemization,internationalization, business direction of firms, earning structure and investment, R&D andpossession of intellectual property rights, information management and management
direction of firms – and the target of the statistics was over 11,000 firms of over 3 hundred
millions Won capital and over 50 employees. Survey of Business Structure and Activities canprovide basic data for industrial policy.

From the viewpoints of policy implementation, the significance of conducting researches onfirms is to enable one to understand what firm characteristics can generate higher businessperformance and to present which policies could be adopted by firms in order to figure out its
business strategies. In this regard, based on in-depth analysis utilizing the Survey of Business
Structure and Activities, this research presents the following policy implications. First,
managerial innovation through research and development and e-business was found to havemutually supplementary relations between technological innovation and non-technologicalinnovation. It proves the necessity of integrated industrial support system such as support for
the firm’s research and development and information-based system. Second, modern
technological innovation can effectively motivate the interaction between industries and theacademia, and that the core of interaction and networking is the outsourcing of research anddevelopment. To promote interaction and networking, the government should realize that
outsourcing research and development activities is more important than investing in internal
research and development activities. But in the current system of tax support for research anddevelopment investments, the external research and development cost and the internal
research and development cost are equally treated. As a means to encourage networking
between industries and academia, giving greater tax incentives to outsourcing research anddevelopment investments than to internal research and development should be explored.
20

Third, this research proved that the higher the lucidity of technologies of the industry towhich a firm belongs, the higher the effect of a firm’s catch-up with advanced firms. Also, theeffects of the top ranking firm within the industry were very strong to the followers.

In order to provide more concrete and more effective policy implications, researches on firms
with diverse concerns related to policy decision-making should be actively pursued and that
the Survey of Business Structure and Activities, which is a very helpful statistical base, should
be developed continually. If the Survey of Business Structure and Activities is actively used as
basic data for establishing and implementing government’s policies and scientific researches,it will greatly contribute to strengthening national industrial policies and researches on firms.
Despite the value of the Survey of Business Structure and Activities statistics, since it is in theearly stage of development, the survey needs to be developed before being completely
utilized and expanded.

The first thing to be considered is to build the firm’s panel data by continuously securing thetime series. For example, in researches on innovation, which is a major research theme formost firms, empirical analysis from other countries reflects time lags before the innovation
activities in the firm’s business performance and growth. There are limitations in terms ofsignificance in findings since the statistics that are currently used are limited to those forthree years only (2005 to 2007). A longer period of time is needed in order to come up withthorough research on the dynamics of firms to investigate what kind of firms attain growthand bring about the growth of an industry.

The second consideration is that efforts should be made to continuously improve statisticalsurvey systems. Many survey items in the Survey of Business Structure and Activities need tohave economic and scientific definitions. With the continuous exchange and interaction
among the users of the statistics, survey items should be defined and adjusted and those who
prepare and use these data should cooperate in improving these items. In Japan for example,
the research results that utilize micro-data are automatically submitted to the person who
prepares the statistics, and the Office of Statistics then examines diverse problems found in
the statistics so as to reflect them in improving the data.

21

Third, the Survey of Business Structure and Activities can be utilized in association not onlywith statistical surveys on diverse businesses that have been produced by the Office of
Statistics but also with several other statistics that have been prepared by private firms. If so,
the usefulness of the survey’s information will drastically increase through synergy effects.
Efforts should be made in exploring the effects of developed statistics on firms by improving
the statistics with different characteristics and by connecting them with statistics on business
entities and enterprises. The value of information inherent to statistics must also be enhanced,
which is nothing but the efforts to enhance the productivity of national statistics.

Fourth, the Survey of Business Structure and Activities is a full-scale panel statistics on firms.
It is therefore important to provide diverse aggregated statisticcal tables. Furthermore, thevalue of the statistics will be greatly enhanced if it can be actively utilized as micro-data. And
upon fully utilizing the micro-data, the difficulties that many researchers and scholars haveexperienced in carrying out researches on firms will be greatly reduced, if not completely
eliminated. Efforts, therefore, should be made to build a base that shall continuously expand
the provision of micro-data.

Finally, despite the usefulness and value of the Survey of Business Structure and Activities
statistics, there has not been much active use of this statistics since they are still in its infantstage. It is important to actively promote and expand understanding of the statistical records
and data in order to enhance the productivity of statistics and improve the degree of
information resources that are useful on a national basis.

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