ownership structure and export performance: firm-level evidence from the republic of korea

7/27/2019 Ownership Structure and Export Performance: Firm-Level Evidence from the Republic of Korea

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ADB EconomicsWorking Paper Series

Ownership Structure and ExportPerormance: Firm-Level Evidencerom the Republic o Korea

Sangho Kim and Donghyun Park

No. 295 | December 2011


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ADB Economics Working Paper Series No. 295

Ownership Structure and Export

Perormance: Firm-Level Evidence

rom the Republic o Korea

Sangho Kim and Donghyun Park

December 2011

angho im is rofessor at the epartment of nternational rade, onam niversity. onghyun ark is

rincipal conomist in the conomics and esearch epartment, Asian evelopment Bank. An earlier

version of this paper was published in August 2011 as anyang echnological niversity conomic rowth

Centre orking aper o. 2011/1. he authors accept responsibility for any errors in the paper.


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Asian evelopment Bank

AB Avenue, Mandaluyong City

1550 Metro Manila, hilippines

www.adb.org/economics

2011 by Asian evelopment Bankecember 2011

155-5252

ublication tock o. 12440

he views expressed in this paper

are those of the authors) and do not

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of the Asian evelopment Bank.

he AB conomics orking aper eries is a forum for stimulating discussion and

eliciting feedback on ongoing and recently completed research and policy studies

undertaken by the Asian evelopment Bank AB) staff, consultants, or resource

persons. he series deals with key economic and development problems, particularly

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methodological issues relating to project/program economic analysis, and statistical data

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availability of statistical data and development indicators for monitoring development

effectiveness.

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journals or chapters in books. he series is maintained by the conomics and esearch

epartment.


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Contents

Abstract v

. ntroduction 1

. wnership tructure and xport erformance

Conceptual Basis and mpirical iterature 2

A. Conceptual verview 2

B. mpirical iterature

. ata and ariables 4

. Main mpirical indings

A. ogit stimation of xporters versus onexporters

B. obit stimation of xport ropensity 10

. Concluding bservations 14

eferences 15


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Abstract

he central objective of our paper is to empirically examine the relationship

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so, we use data from the epublic of orea, a classic example of successful

export-oriented industrialization. hile a large and growing empirical literature

investigates the relationship between the ownership structure and overall

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whether the concentration of ownership has a positive or negative effect on

export performance. he primary contribution of our study is to help remedy

this serious gap in the empirical literature on ownership and performance. urHPSLULFDOUHVXOWVLQGLFDWHWKDWRUHDQUPVZLWKPRUHFRQFHQWUDWHGRZQHUVKLSDUH

more likely to be exporters, and to export more.


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I. Introduction

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performance. n a seminal paper, Berle and Means 192) proposed a simple intuitive

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incentives to engage in monitoring the management since they incur high monitoring

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more closely monitored and will perform better. At the same time, there are theoretical

reasons for why concentrated ownership may harm corporate performance. or example,

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minority shareholders oh 200).

n theory, ownership concentration can thus have either a positive or negative impact on

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through empirical analysis. A large and growing empirical literature has sprung up to

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have elaborated upon the empirical methodology. or example, in order to account for

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data. owever, the overall evidence on the relationship between ownership structure and

corporate performance remains mixed and inconclusive.

he central objective of our paper is to empirically examine the relationship between

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overall corporate performance. At the same time, there are some conceptual grounds forDUHODWLRQVKLSEHWZHHQDUPVRZQHUVKLSVWUXFWXUHDQGLWVSHUIRUPDQFHDVH[SODLQHGLQ

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export due to the higher risk of exporting vis--vis selling in the domestic market. hile

a large and growing empirical literature investigates the relationship between ownership

structure overall corporate performance, there are almost no studies that delve into the

relationship between ownership structure and export performance. he main contribution


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of our study is to help remedy this serious gap in the empirical literature by investigating

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At a broader level, the epublic of orea is a well-known example of highly successful

export-led industrialization and growth. nderlying its export prowess is the successof orean companies such as amsung, , and yundai, which have become global

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in terms of structural characteristics, including size and ownership concentration, export

a broad range of manufactured products. iven the export success of orean companies

and their structural diversity, it would be interesting to examine whether ownership

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ownership structure and corporate performance.

he rest of the paper is organized as follows. ection outlines a conceptual basis forDUHODWLRQVKLSEHWZHHQWKHRZQHUVKLSVWUXFWXUHRIUPVDQGWKHLUH[SRUWSHUIRUPDQFH

and reviews the empirical literature on this relationship. ection describes the data

and variables used in the empirical analysis, and ection reports and discusses the

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observations.

II. Ownership Structure and Export Perormance:

Conceptual Basis and Empirical LiteratureQWKLVVHFWLRQZHUVWRXWOLQHWKHFRQFHSWXDOEDVLVIRUDUHODWLRQVKLSEHWZHHQWKH

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empirical literature.

A. Conceptual Overview

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concentrated ownership will try to minimize risk and thus concentrate on the domestic

2 | ADB Economics Working Paper Series No. 295


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market. his manager wants to achieve concrete results in a short period by focusing on

the less risky domestic market rather than the more risky foreign market. he implication

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his study will hypothesize that managers preferences toward risk are related to itsRZQHUVKLSVWUXFWXUHQDUPZLWKDGLIIXVHRZQHUVKLSVWUXFWXUHWKHPDQDJHUPD[LPL]HV

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sum of upfront sunk costs, including adapting products to foreign consumer preferences,

complying with foreign government regulations, and building distribution networks.

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B. Empirical Literature

As noted earlier, there is a large and growing empirical literature that delves into the

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literature looks at the relationship between ownership concentration and measures of

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there are only a few empirical studies investigating the nexus between ownership andexports. Most of the few studies look at the impact of foreign ownership rather than

ownership concentration on export performance.

Cole, lliot, and irakul 2010) investigate the relationship between foreign ownership

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to examine the relationship between foreign ownership and exports in the ietnamese

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ownership, i.e., 90 or more foreign-owned, make a disproportionate contribution to

iet ams manufacturing exports. A number of additional empirical studies examine the

relationship between foreign ownership and export performance in other countries. hese

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Ownership Structure and Export Performance: Firm-Level Evidence from the Republic of Korea | 3


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o summarize our literature review, it should be clear that the empirical literature on

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foreign ownership on export performance. ome studies compare the export performance

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delve into dimensions of ownership structure other than foreign ownership. n particular,

the studies do not look at the effect of ownership concentration on export performance.

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underlying intuition is that exporting is fundamentally risky activity, as explained above.

III. Data and Variables

n this section, we describe the data and variables used in our empirical analysis of the

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data set used in this paper is an unbalanced panel consisting of annual time-series for

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xports are observed in 1,40 observations, which is about 29.5 of total observations.

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binary variable on the set of explanatory variables that include concentration rate and

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censored data will be useful.1

ur key variable of interest is the ownership concentration rate C) since the centralobjective of our empirical analysis is to investigate the effect of ownership structure on

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management. C is a good proxy for ownership structure since dominant shareholders

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o accurately estimate the impact of ownership concentration on exports, we have to

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standard variables such as wage rate, capital intensity, research and development

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FDSLWDOLQWHQVLW\UHSUHVHQWWKHWUDGLWLRQDOIDFWRUHQGRZPHQWWKHRU\'VWRFNUHHFWVWKHtechnology gap theory of trade see osner 191, rugman 199) or the product cycle

theory see ernon 19) in which technological innovation plays a central role in shaping

international trade structure. Many empirical studies have analyzed the impact of on

UPVH[SRUWDFWLYLW\VHH umar and iddharthan 1994, irsch and Bijaoui 1985, akelin

1998).

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information, establishing a distribution network, and adapting products to foreign tastes

and regulations. ince these costs are sunk costs, uncertainty may cause persistence

in export participation. irms may continue to export even though it is temporarily

XQSURWDEOHWRGRVRRUKHVLWDWHWRH[SRUWGXHWRWKHRSWLRQYDOXHRIZDLWLQJIRUPRUHinformation see oberts and ybout 199). or this reason, a number of studies point

out that exporters are large and productive enough to absorb the costs of waiting see

ichardson and indal 1995, Bernard and ensen 199a and 199b, Bleaney and

akelin 1999, oberts and ybout 199). irm size affects export performance through

economies of scale in production and export marketing, higher capacity for taking risks,

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decision to export. he effect of productivity on exports is intuitively straightforward since

global markets are typically much more competitive than the domestic market. herefore,

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technology, which can be an important tool for exports. he positive impact of age might

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e compute the wage rate by dividing total labor costs by the number of employees

). otal labor costs consist of wages, bonuses, retirement compensation, and all other

costs associated with employee remuneration. he capital stock K) is the real amount

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net interest payments, rents, taxes other than corporate tax, and depreciation costs.

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ollowing much of the literature, we apply a depreciation rate of 10. irm age is

calculated from the founding year.All variables are converted into constant 2000 prices.



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able 1 presents sample means and standard deviations. e perform the t-test on the

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this implies that exporters have higher ownership concentration than nonexporters. n

addition, relative to nonexporters, exporters pay higher wages and have greater capitalintensity ratio, stock, labor productivity, and sales.

Table 1: Variables or Ownership Concentration and Exports o Korean Manuacturing

Firms: Means (standard deviations)

Variable (Abbreviation) Defnition Exporters Nonexporters

Exporters Exporters i exports>0 1640+ 3916Export propensity Exports/sales 0.410(0.291)Ownership concentration rate (OC) Largest shareholders share rate 29.74(19.16) 25.76(19.51)Wage rate (Wage) Labor costs/employment 14.69(19.94) 11.83(17.78)Capital intensity (K/L) Fixed capital (K)/employment (L) 1.875(2.410) 1.581(1.845)Research and Development Stock (R&D) R&D stock 264.76(2008.7) 77.67(933.0)

Labor Productivity (Prod.) Value added (VA)/employment (L) 17.42(30.44) 13.28(29.94)Firm age (Age) Years elapsed rom oundation 28.65(11.91) 28.74(16.73)Sales Total sales 10927(54940) 2621(12434)

Note: + denotes the number o exporting frms. All the other variables are in 10 million Korean won in 2000 constant prices,except largest shareholders share rate and frm age. To convert into approximate US dollars, divide by 1,000.

IV. Main Empirical Findings

n this section, we report and discuss the main results from our empirical analysis, which

consists of two parts i) logit estimation of the decision to export or not and ii) tobit

estimation of export propensity. Before estimating the logit and tobit models, we examine

the correlation between explanatory variables. able 2 reports the earson correlation

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stock and both sales and employment, and sales and employment. e do not use

these pairs of variables together in regressions to avoid multicollinearity.2

2 Putting these correlated variables together changed the signifcance and sign o coecient estimates, which isapparent symptom o multicollinearity.



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Table 2: Correlation between the Variables or Ownership Concentration and Exports

o Korean Manuacturing Firms: Pierson Correlation Coecient

Variable OC Wage K/L R&D Prod. Age Sales

Wage 0.0615

K/L 0.0930 0.2273R&D 0.0617 0.1099 0.0223Prod. 0.0355 0.855 0.1803 0.1496Age 0.0817 0.0427 0.1526 0.0135 0.0328Sales 0.0531 0.176 0.1113 0.7279 0.2372 0.0162L 0.0771 0.0777 0.0313 0.6499 0.1087 0.0566 0.7775

Age = frm age, K/L = capital intensity, OC = ownership concentration rate, Prod. = labor productivity (=VA/L), R&D = research anddevelopment, Sales = total sales, Wage = wage rate.

Source: Authors estimates.

A. Logit Estimation o Exporters versus Nonexporters

able reports the results of our logit estimation of the export decision, i.e., whether or

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variable of exporter or nonexporters as the dependent variable. or our purposes, the key

explanatory variables is the ownership concentration rate. Additional explanatory variables

include variables widely used in the trade literature, such as wage rate, capital intensity,

and stock. e experiment with various permutations of explanatory variables to

estimate four different models.

Table 3: Logit Regression or Ownership Concentration and Exports o Korean

Manuacturing Firms: Dependent Variable (exporters/nonexporters)

Variable Model(i) (ii) (iii) (iv)

OC0.005***

(0.001)0.005***

(0.001)0.005***

(0.001)0.006***

(0.001)

Wage0.005***

(0.001)0.004***

(0.001)0.004***

(0.001)

K/L0.055***

(0.014)0.057***

(0.014)0.034**(0.014)

0.073***(0.015)

R&D0.0001***(0.00004)

0.0001***(0.0000)

0.0001***(0.0000)

Prod.0.003***

(0.001)

Age0.005

(0.008)

Age2 0.0003***(0.0001)

Sales0.00001***

(0.00000)

Constant1.181***

(0.064)1.167***

(0.063)1.131***

(0.060)1.007***

(0.139)LLR 2937.85 2938.46 3212.95 2906.21

x2 4( ) 65.47*** 64.25*** 101.16*** 128.75***

No. o Obs. 4837 4837 5261 4837

***, ** and * denote statistical signifcance at the 1%, 5% and 10% level, respectively.Age = frm age, K/L = capital intensity, OC = ownership concentration rate, Prod. = labor productivity (=VA/L), R&D = research and

development, Sales = total sales, Wage = wage rate.Note: Standard errors are in parentheses.Source: Authors estimates.



16/25

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DUPVSUREDELOLW\RIHQWHULQJWKHIRUHLJQPDUNHWLQFUHDVHVZLWKRZQHUVKLSFRQFHQWUDWLRQ

UDWHZDJHVUDWHFDSLWDOLQWHQVLW\DQG'VWRFN7KLVLPSOLHVWKDWH[SRUWLQJUPVSD\

higher wages and have greater capital intensity and stock. Model ii) substituteswage rate with labor productivity as explanatory variable. hese two variables are closely

correlated.7KHFRHIFLHQWHVWLPDWHVRIDOOWKHH[SODQDWRU\YDULDEOHVUHPDLQSRVLWLYHDQG

VLJQLFDQW7KLVLVVWLOOWKHFDVHZKHQ'VWRFNLVUHSODFHGZLWKVDOHVLQRGHOLLL4

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WRRGHOL7KHFRHIFLHQWHVWLPDWHVRIWKHEDVLFH[SODQDWRU\YDULDEOHVUHPDLQWKH

VDPH+RZHYHUWKHFRHIFLHQWRIDJHLVSRVLWLYHO\LQVLJQLFDQWDQGLWVVTXDUHGWHUPLV

QHJDWLYHO\VLJQLFDQW5 his suggests that the impact of business experience on entering

H[SRUWPDUNHWGLPLQLVKHVDVUPVJURZROGHUHYHQWKRXJKLWPLJKWLQLWLDOO\KDYHDSRVLWLYH

LQXHQFH

RVWVLJQLFDQWO\RXUHVWLPDWLRQUHVXOWVVKRZWKDWKLJKHURZQHUVKLSFRQFHQWUDWLRQUDWHLQFUHDVHVWKHSUREDELOLW\RIUPVHQWHULQJIRUHLJQPDUNHWV7KHUHVXOWVWKXVVXSSRUW

RXUFHQWUDOK\SRWKHVLVWKDWUPVZLWKFRQFHQWUDWHGRZQHUVKLSYHQWXUHLQWRULVN\H[SRUW

PDUNHWVWRPD[LPL]HH[SHFWHGSURWVZKHUHDVUPVZLWKGLVSHUVHGRZQHUVKLSWHQGWR

stay home to avoid the risk of incurring the large sunk costs associated with exporting.

DQDJHUVLQUPVZLWKGLVSHUVHGRZQHUVKLSSUHIHUWRDYRLGULVNDQGDFKLHYHFRQFUHWH

business outcomes in a short period. his discourages them from entering risky foreign

PDUNHWVZKLFKUHTXLUHODUJHVXQNFRVWVWKDWFDQRQO\EHUHFRYHUHGLQWKHORQJUXQXU

HPSLULFDOUHVXOWVFRQUPWKHH[LVWHQFHRIDQDJHQF\SUREOHPULVNDYHUVHPDQDJHUVRI

UPVZLWKGLIIXVHRZQHUVKLSGRQRWH[SRUWHYHQWKRXJKH[SRUWLQJLVSURWDEOHDQGWKXV

EHQHFLDOIRUVKDUHKROGHUV

:LWKUHVSHFWWRRXUFRQWUROYDULDEOHVRXUUHVXOWVVKRZWKDWUPVDUHPRUHOLNHO\WREH

exporters as wage rate, capital intensity, stock, productivity, and sales increase. ur

UHVXOWVFRQUPWKDWZLWKLQWKHRUHDQPDQXIDFWXULQJVHFWRUH[SRUWHUVDUHODUJHUPRUH

productive, more capital- and -intensive, and pay higher wages than nonexporters.

XUHYLGHQFHLVFRQVLVWHQWZLWKDODUJHERG\RIHPSLULFDOOLWHUDWXUHWKDWQGVLPLODU

differences between exporters and nonexporters see Bernard and ensen 199a and

EAitken, anson, and arrison $ZDQG+ZDQJ&OHULGHVDFKDQG

7\ERXWDQGREHUWVDQG7\ERXW6XFKHYLGHQFHLVLQWXLWLYHO\SODXVLEOHVLQFH

PRUHHIFLHQWDQGODUJHUUPVZLWKDGHTXDWHUHVRXUFHVDUHEHWWHUDEOHWKHODUJHVXQN

FRVWVUHTXLUHGWRHQWHUIRUHLJQPDUNHWV

3 Coecient estimates o these two variables become insignifcant due to multicollinearity when they are bothincluded.

4 Multicollinearity causes coecient estimates o R&D to be insignifcant when these two variables are bothincluded.

5 Coecient estimates o wage rate, labor productivity, and R&D stock become insignifcant due to multicollinearitywhen labor productivity and sales are added to Model (iv).



17/25

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UHUXQRGHOLYLQ7DEOHIRUUPVLQGLIIHUHQWLQGXVWULHV7DEOHUHSRUWVWKHUHVXOWV7KH

FRHIFLHQWHVWLPDWHVRIFRQFHQWUDWLRQUDWHDUHSRVLWLYHO\VLJQLFDQWLQWKHWH[WLOHVSDSHU

EDVLFPHWDODQGIDEULFDWLRQLQGXVWULHVEXWQHJDWLYHO\VLJQLFDQWLQWKHFKHPLFDOLQGXVWU\

DQGLQVLJQLFDQWLQWKHRWKHULQGXVWULHV$QLQFUHDVHLQFRQFHQWUDWLRQUDWHLQFUHDVHVWKHprobability of entering the export market in more industries four industries out of seven)

than not. owever, the correlation is negative in the chemical industry, which consists of

ODUJHUPVSURGXFLQJVWDQGDUGL]HGUDZPDWHULDOVDQGSURGXFWVIRUWKH3HRSOHVHSXEOLF

RI&KLQDPDUNHW7KHRZQHUVKLSRIWKHVHUPVLVGLVSHUVHGVLQFHWKLVLQGXVWU\LVPDWXUH

enough to attract a large number of investors. Moreover, entering the Chinese market

PLJKWQRWSRVHPXFKULVNWRWKHUPVLQWKLVLQGXVWU\GXHWRERWKSURGXFWVWDQGDUGL]DWLRQ

and robust structural demand.

Table 4: Logit Regression or Ownership Concentration and Exports o Korean

Manuacturing Firms by Industry: Dependent Variable (exporters/nonexporters)

VariableIndustry

Food Textiles Paper Chemical Nonmetal Basic Metal Fabrication

OC0.005

(0.009)0.013**(0.006)

0.020**(0.008)

0.008**(0.003)

0.012(0.010)

0.023*(0.005)

0.018*(0.002)

Wage0.033*(0.008)

0.040***(0.022)

0.014(0.015)

0.005(0.003)

0.013(0.013)

0.012(0.008)

0.002(0.002)

K/L0.347**

(0.162)0.317**

(0.127)0.282*(0.077)

0.218*(0.033)

0.102*(0.039)

-0.031(0.041)

0.167*(0.060)

R&D0.0009

(0.0006)-0.008

(0.013)0.017**(0.008)

0.001*(0.0003)

0.001(0.001)

0.0002(0.0002)

0.0001*(0.0000)

Age0.088*(0.033)

0.262*(0.049)

0.058(0.074)

0.011(0.016)

0.084(0.140)

0.052(0.039)

0.035**(0.016)

Age20.0006**

(0.0003)

0.002*

(0.0005)

-0.001

(0.001)

0.0002

(0.0002)

0.001

(0.001)

0.0006

(0.0006)

0.001*

(0.0002)Constant

4.157*(0.908)

7.265*(1.064)

3.285*(1.209)

0.542***(0.284)

0.862(2.466)

2.131*(0.624)

1.001*(0.240)

LLR 153.64 202.41 117.53 699.52 112.80 286.07 1051.73

x2 8( ) 27.07* 69.20* 38.25* 137.37* 15.85** 32.43* 105.49*

Obs. 399 412 224 1281 274 446 1706

***, ** and * denote statistical signifcance at the 1%, 5% and 10% level, respectively.Age = frm age, K/L = capital intensity, OC = ownership concentration rate, R&D = research and development, Wage = wage rate.Note: Standard errors are in parentheses. For others, see notes to Table 3.Source: Authors estimates.

7KHFRHIFLHQWHVWLPDWHRIWKHZDJHUDWHLVSRVLWLYHDQGVLJQLFDQWLQWKHIRRGDQG

WH[WLOHVLQGXVWULHV&DSLWDOLQWHQVLW\LVSRVLWLYHDQGVLJQLFDQWLQWKHSDSHUFKHPLFDODQGQRQPHWDOLQGXVWULHVEXWQHJDWLYHDQGVLJQLFDQWLQWKHIRRGWH[WLOHVDQGIDEULFDWLRQ

LQGXVWULHV'VWRFNLVSRVLWLYHDQGVLJQLFDQWLQWKHSDSHUFKHPLFDODQGIDEULFDWLRQ

PHWDOLQGXVWULHV$JHLVSRVLWLYHDQGVLJQLFDQWLQWKHIRRGWH[WLOHVDQGIDEULFDWLRQ

LQGXVWULHVDQGDJHVTXDUHGLVQHJDWLYHDQGVLJQLFDQWLQWKHVDPHLQGXVWULHVXUUHVXOWV

6 The oundation o Korean chemical industry was built up in the early 1970s.



18/25

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wages only in the food and textiles industries. ur results suggest a nonlinear initiallySRVLWLYHEXWVXEVHTXHQWO\QHJDWLYHLPSDFWRIUPDJHLQWKHIRRGWH[WLOHVDQGIDEULFDWLRQ

LQGXVWULHV7KHVLJQVDQGVLJQLFDQFHRIWKHFRHIFLHQWHVWLPDWHVUHPDLQWKHVDPHLQ

every industry when we substitute labor productivity for wage rate.

B. Tobit Estimation o Export Propensity

he previous section treated exporting as a zero-one binary variable by dividing the

VDPSOHUPVLQWRH[SRUWHUVDQGQRQH[SRUWHUVIWKHUHDUHPDQ\GLIIHUHQWH[SRUWPDUNHWV

WKDWUHTXLUHVHSDUDWH[HGFRVWVWRHQWHUULVNDYHUVHUPVDUHOLNHO\WRH[SRUWWRDVPDOOHU

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export performance as export propensity, or the ratio of export revenues to total sales.

7DEOHUHSUHVHQWVWKHFRHIFLHQWHVWLPDWHVRIWKHWRELWHVWLPDWLRQRIH[SRUWSURSHQVLW\

IRURUHDQPDQXIDFWXULQJUPV([SRUWSURSHQVLW\GHQHGRQ>@LVWKHGHSHQGHQW

YDULDEOHZKHUHVWDQGVIRUQRQH[SRUWHUVDQGVWDQGVIRUUPVH[SRUWLQJWKHLUHQWLUH

RXWSXW$SSO\LQJRUGLQDU\OHDVWVTXDUHVHVWLPDWLRQPHWKRGWRWKLVFHQVRUHGGDWDZLOO

FDXVHFRHIFLHQWHVWLPDWHVWREHELDVHGVLQFHWKLVPHWKRGFDQJHQHUDWHSUHGLFWHGYDOXHV

of the dependent variable that lie outside the feasible range. o deal with the problem,

we use a tobit model censored at both right and left ends. As for the logit estimation, our

key explanatory variable of interest is the ownership concentration rate. n addition, weinclude explanatory variables widely used in the trade literature such as wage rate, capital

intensity, and stock. n estimation, a semi-log model is utilized, which transforms

DOOH[SODQDWRU\YDULDEOHVLQWRORJDULWKPVWRFRQWUROIRUKHWHURVFHGDVWLFLW\DULVLQJIURPUP

scale. owever, we use the dependent variable in its original form to keep its censored

characteristics.8 e estimate four models, which represent various permutations of the

explanatory variables.

7 The results we obtain when we substitute labor productivity or wage are available upon request. Laborproductivity has a positive and signifcant eect on a frms decision to export.

8 However, age and its square term is used in their original orm because the logs o these variables are perectlycorrelated.



19/25

Table 5: Tobit Regression or Ownership Concentration and Exports o Korean

Manuacturing Firms: Dependent Variable (exports/sales)

VariableModel

(i) (ii) (iii) (iv)

log(OC) 0.083***(0.018)

0.086***(0.018)

0.076***(0.018)

0.079***(0.018)

log(Wage)0.078***

(0.011)0.096***

(0.011)0.147(0.097)

log(K/L)0.021*(0.012)

0.011(0.013)

0.048***(0.012)

0.005(0.013)

log(R&D)0.009**(0.003)

0.021***(0.003)

0.006*(0.003)

0.002(0.003)

log(Prod)0.071***

(0.010)0.097***

(0.012)

Age0.001(0.003)

0.0008(0.003)

Age20.0001***

(0.0000)0.0001***

(0.0000)

log(L) 0.022(0.097)

Constant1.455***

(0.174)1.964***

(0.200)1.620***

(0.180)2.574***

(0.217)LLR 2471.92 2473.02 2418.36 2377.50

x2 4( ) 117.90*** 115.72*** 225.02*** 306.75***

No. o total Obs.(let, right censored)

3947(2731, 32)

. ***, ** and * denote statistical signifcance at the 1%, 5% and 10% level, respectively.Age = frm age, K/L = capital intensity, OC = ownership concentration rate, Prod. = labor productivity (=VA/L), R&D = research and

development, Wage = wage rate.Notes: Standard errors are in parentheses. For others, see notes to Table 3.Source: Authors estimates.

7KHFRHIFLHQWHVWLPDWHVRIRZQHUVKLSFRQFHQWUDWLRQUDWHFDSLWDOLQWHQVLW\DQG'

VWRFNDUHDOOSRVLWLYHO\VLJQLFDQWEXWWKDWRIZDJHUDWHLVQHJDWLYHO\VLJQLFDQWLQ

RGHOL(VWLPDWLRQUHVXOWVVKRZWKDWUPVH[SRUWSURSHQVLW\ULVHVZLWKWKHRZQHUVKLS

concentration rate, capital intensity, and stock, but falls with the wage rate. Model ii)

substitutes wage rate with labor productivity as explanatory variable. hese two variables

are closely correlated.97KHFRHIFLHQWHVWLPDWHVRIFRQFHQWUDWLRQUDWH'VWRFN

DQGODERUSURGXFWLYLW\DUHSRVLWLYHDQGVLJQLFDQWEXWWKDWRIFDSLWDOLQWHQVLW\EHFRPH

LQVLJQLFDQW:KHQERWKDJHDQGVTXDUHGWHUPRIDJHDUHDGGHGDVH[SODQDWRU\YDULDEOHV

LQRGHOLLLWKHFRHIFLHQWHVWLPDWHVRIRULJLQDOH[SODQDWRU\YDULDEOHVDUHSRVLWLYHO\

VLJQLFDQWEXWWKDWRIDJHLVSRVLWLYHO\LQVLJQLFDQWDQGLWVVTXDUHWHUPQHJDWLYHO\VLJQLFDQW:KHQODERUSURGXFWLYLW\DQGHPSOR\PHQWDUHDGGHGLQRGHOLYWKH

cRHIFLHQWHVWLPDWHVRIZDJHUDWHFDSLWDOLQWHQVLW\DQG'VWRFNEHFRPHLQVLJQLFDQW

due to multicollinearity.

9 Coecient estimates o these two variables become both insignifcant due to multicollinearity when both areincluded.



20/25

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hey may prefer instead to concentrate on fast-growing export markets that they are

more familiar with due to geographical proximity. his type of export strategy is less

risky and involves lower sunk costs than exporting to many different countries. or

example, the eoples epublic of China is a highly promising market for a large number

RIRUHDQUPVUHJDUGOHVVRIWKHLURZQHUVKLSVWUXFWXUHQWKHRWKHUKDQGRXUUHVXOWV

LQGLFDWHWKDWUPVZLWKPRUHFRQFHQWUDWHGRZQHUVKLSDUHPRUHOLNHO\WREHDUWKHKLJKHU

risk associated with exporting to slower growing and less familiar markets. ur evidence

VXSSRUWVWKHH[LVWHQFHRIDJHQF\SUREOHPLQDUPVGHFLVLRQPDNLQJDERXWWKHQXPEHU

RIH[SRUWPDUNHWVLVNDYHUVLRQGHWHUVWKHPDQDJHUVRIUPVZLWKGLVSHUVHGRZQHUVKLS

IURPH[SRUWLQJWRPRUHPDUNHWVHYHQWKRXJKGRLQJVRPD\UDLVHSURWVDQGWKXVEHQHWshareholders.

ith respect to our control variables, much of our evidence mirrors the results of our logit

DQDO\VLVRUHVSHFLFDOO\RXUWRELWUHVXOWVLQGLFDWHWKDWUPVZLWKKLJKHUFDSLWDOLQWHQVLW\

stock, and productivity export to more markets. ne departure from the logit results

LVWKDWUPVSD\LQJORZHUZDJHVDUHOLNHO\WRHQWHUPRUHH[SRUWPDUNHWVWKDQUPVSD\LQJ

higher wages. ur tobit results are based on comparing the wage rates of exporters with

those of other exporters while our logit results are based on comparing the wage rates of

exporters and nonexporters. ur tobit results suggest that exporters paying lower wages

export to more countries than exporters paying higher wages, whereas our logit results

suggests that exporters pay higher wages than nonexporters.

6LQFHUPVH[SRUWSURSHQVLW\PLJKWGLIIHUDFURVVLQGXVWULHVZHDOVRUHUXQRGHOLLLLQ

7DEOHIRUUPVLQGLIIHUHQWLQGXVWULHV7DEOHUHSRUWVWKHUHVXOWV&RHIFLHQWHVWLPDWHV

RIFRQFHQWUDWLRQUDWHDUHSRVLWLYHO\VLJQLFDQWLQWKHWH[WLOHVEDVLFPHWDODQGIDEULFDWLRQ

LQGXVWULHVEXWQHJDWLYHO\VLJQLFDQWLQWKHFKHPLFDOLQGXVWU\DQGLQVLJQLFDQWLQWKH

other industries. mpirical results show that increase in concentration rate increases

the probability of entering more export markets in three industries out of seven, but

decreases the probability in the chemical industry. he results are very similar with

industry-level estimation results from logit analysis, except in the paper industry, where

WKHUHODWLRQVKLSWXUQVLQVLJQLFDQWXUUHVXOWVDUHWKXVIDLUO\UREXVWDFURVVGHSHQGHQW

variable and estimation models.

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QRQPHWDOLQGXVWULHVEXWQHJDWLYHDQGVLJQLFDQWLQWKHSDSHUEDVLFPHWDODQGIDEULFDWLRQ

LQGXVWULHV&DSLWDOLQWHQVLW\LVSRVLWLYHDQGVLJQLFDQWLQWKHSDSHUFKHPLFDODQGQRQPHWDO

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21/25

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Table 6: Tobit Regression or Ownership Concentration and Exports o Korean

Manuacturing Firms by Industry: Dependent Variable (exports/sales)

VariableIndustry

Food Textiles Paper Chemical Nonmetal Basic Metal Fabrication

log(OC)0.017(0.031)

0.253*(0.096)

0.094(0.059)

0.086*(0.030)

0.025(0.065)

0.330*(0.047)

0.182*(0.032)

log(Wage)0.006(0.016)

0.245*(0.078)

0.302*(0.082)

0.025(0.025)

0.157**(0.069)

0.126*(0.026)

0.155*(0.019)

log(K/L)0.018

(0.024)0.284*(0.086)

0.152**(0.059)

0.209*(0.023)

0.090***(0.053)

0.093*(0.030)

0.054**(0.028)

log(R&D)0.021**(0.009)

0.022***(0.013)

0.002(0.009)

0.009(0.008)

0.073**(0.032)

0.007(0.005)

0.004(0.008)

Age0.005***

(0.003)0.111*(0.022)

0.042(0.026)

0.0002(0.006)

0.071**(0.032)

0.002(0.010)

0.014**(0.006)

Age2 0.00005***(0.00003)

0.0009*(0.0002)

0.0004(0.0003)

0.0001**(0.0000)

0.0009**(0.0004)

0.0000(0.0001)

0.0004*(0.0001)

Constant0.842**

(0.333)1.122

(1.197)3.429*(0.883)

2.533*(0.336)

0.186(0.756)

0.994**(0.400)

1.279*(0.349)

LLR 80.14 102.94 60.31 608.66 83.95 168.37 961.14

x2 8( ) 18.09* 70.84* 29.11* 157.11* 12.79** 63.77* 187.83*

No. o Obs.(let, rightcensored)

364(307, 0)

228(166, 0)

166(124, 0)

1125(807, 1)

239(199, 2)

332(181. 0)

1415(904, 28)

***, ** and * denote statistical signifcance at the 1%, 5% and 10% level, respectively.Age = frm age, K/L = capital intensity, OC = ownership concentration rate, R&D = research and development, Wage = wage rate.Note: Standard errors are in parentheses. For others, see notes to Table 3.Source: Authors estimates.

(VWLPDWLRQUHVXOWVVKRZUPVSHFLFIDFWRUVKDYHDGLIIHUHQWLQXHQFHRQH[SRUWDFWLYLW\

DFURVVGLIIHUHQWLQGXVWULHVHODWLYHO\OHVVFDSLWDOLQWHQVLYHUPVSD\LQJORZHUZDJHVKDYH

higher export propensity in the basic metal and fabrication industries, while the reverse

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EDVLFPHWDODQGIDEULFDWLRQLQGXVWULHVEXWFDSLWDOLQWHQVLYHUPVGRVRLQWKHQRQPHWDO

industry. As wage rate rises and capital intensity falls, export propensity rises in the

WH[WLOHVLQGXVWU\EXWIDOOVLQWKHSDSHULQGXVWU\7KHVHUHVXOWVLPSO\WKDWUPVSURGXFLQJ

human capital-intensive clothes and materials perform better in the textiles industry. he

FRPSHWLWLYHDGYDQWDJHRIRUHDQUPVLQWKLVPDWXUHLQGXVWU\PLJKWWKXVOLHLQGHVLJQHU

clothing, high-end functional clothes, and differentiated textile materials. hese productsDUHFXVWRPPDGHDQGSURGXFHGLQVPDOOTXDQWLWLHV+RZHYHUUPVPDVVSURGXFLQJ

standardized products in large factories tend to export more in the paper industry, where

competitive advantage is based mainly on production costs. urthermore, the scope for

product differentiation is limited in the paper industry.



22/25

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LVQHJDWLYHDQGVLJQLFDQWLQWKHIRRGWH[WLOHVFKHPLFDODQGIDEULFDWLRQLQGXVWULHV7KHVH

results imply that the positive impact of experience on export performance generally

GHFOLQHVDVUPVJHWROGHU6LJQDQGVLJQLFDQFHRIFRHIFLHQWHVWLPDWHVUHPDLQVPRVWO\unchanged when we substitute labor productivity for wage rate.10

V. Concluding Observations

he central objective of our study was to empirically examine the relationship between

WKHRZQHUVKLSVWUXFWXUHRIUPVDQGWKHLUH[SRUWSHUIRUPDQFHRUHVSHFLFDOO\XVLQJ

data from the orean manufacturing sector, we investigate the relationship between

ownership concentration and export performance. n contrast to the large and growing

empirical literature that delves into the relationship between the ownership structure of

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level evidence from the epublic of orea.

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to examine the relationship between ownership concentration and export performance.

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of our empirical results for policy makers is that the positive effect of concentrated

ownership on exports is an important additional factor that must be factored into

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governance. ur evidence lends support to the conventional wisdom that originally

IDPLO\RZQHGUPVZLWKKLJKO\FRQFHQWUDWHGRZQHUVKLSNQRZQDV chaebols, made a big

contribution to the epublic of oreas export success. iven the importance of exports

in the orean economy, our analysis suggests a need to exercise caution in policies that

seek to regulate and control the chaebols.11

hile our study empirically investigates an important but previously underexploredrelationship between ownership structure and export performance, it is by no means the

10 The results we obtain when we substitute labor productivity or wage are available rom authors upon request.R&D stock has positive signifcant impact on frms exports only in the chemical, basic metal, and abricationindustries. Labor productivity has a positive signifcant eect in every industry except the paper and nonmetalindustries.

11 The chaebols have been blamed or contributing to the Republic o Koreas collapse during the Asian fnancial crisiso 19971998 through excessive investment and expansion. More recently, they are widely blamed or the growingconcentration o economic power and the consequent lack o a dynamic small and medium enterprises sector.



23/25

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the issue. here are several promising directions for future research. erhaps the most

promising research area is to examine the relationship between ownership structure and

export performance in other successful export-led ast Asian economies. t would also beLQWHUHVWLQJWRWDNHDORRNDWWKHRZQHUVKLSH[SRUWVUHODWLRQVKLSLQPRUHPDWXUHDGYDQFHG

economies such as the , which have different corporate governance environments.

inally, another potential extension of our research would be to look at the relationship

between ownership structure and foreign direct investment.

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About the PaperSangho Kim and Donghyun Park empirically examine the relationship betweenthe ownership structure of firms and their export performance. To do so, they usefirm-level data from the Republic of Korea, a classical example of successful export-oriented industrialization. Their empirical results indicate that Korean firms with moreconcentrated ownership are more likely to be exporters and export more.

About the Asian Development BankADBs vision is an Asia and Pacific region free of poverty. Its mission is to help itsdeveloping member countries reduce poverty and improve the quality of life of theirpeople. Despite the regions many successes, it remains home to two-thirds of theworlds poor: 1.8 billion people who live on less than $2 a day, with 903 millionstruggling on less than $1.25 a day. ADB is committed to reducing poverty throughinclusive economic growth, environmentally sustainable growth, and regionalintegration.

Based in Manila, ADB is owned by 67 members, including 48 from the region. Itsmain instruments for helping its developing member countries are policy dialogue, loans,

equity investments, guarantees, grants, and technical assistance.

Asian Development Bank6 ADB Avenue, Mandaluyong City1550 Metro Manila, Philippineswww.adb.org/economicsISSN: 1655-5252Publication Stock No. WPS124406

December 2011

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ownership structure and export performance: firm-level evidence from the republic of korea

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