Intangible Investment and Changing Sources of Growth in Koreahompi.sogang.ac.kr/hchun/chun_jer_2016.pdf · INTANGIBLE INVESTMENT AND CHANGING SOURCES OF GROWTH IN KOREA By HYUNBAE

INTANGIBLE INVESTMENT AND CHANGINGSOURCES OF GROWTH IN KOREA

By HYUNBAE CHUN† and M. ISHAQ NADIRI‡

†Sogang University ‡New York University

We examine how intangible investments change the sources of growth in the Koreaneconomy. After constructing a novel industry-level data set on intangibles, we estimate thecontribution of intangible-intensive industries and other industries to aggregate productiv-ity growth in 1981–2008. The contribution of intangible-intensive industries to aggregatelabour productivity growth has significantly increased, whereas that of other industries hassubstantially decreased. The increased contribution of intangible-intensive industries ismainly associated with total factor productivity growth rather than with input growth. Thissuggests that innovations related to intangible investments in these industries mightbecome a new key source of productivity growth in Korea.JEL Classification Numbers: O47, E22, O14, O53.

1. Introduction

Firms in the knowledge economy invest in a wide range of intangible assets rather thana single type of intangible asset such as R&D and information technology (IT). However,systematic attempts to broaden the range of intangible assets in research on the sourcesof growth are still quite recent. Corrado et al. (2005, 2006) provide a more or lesscomplete list of intangible assets and quantify the amount of intangible investment in theUS economy that is also integrated into the national accounts. Based on this widelyadopted definition in Corrado et al. (2005, 2006), many studies find that investment inintangible assets has become a new source of economic growth in developed countries.1

While most of these studies have been conducted for developed countries at the aggre-gate level, studies on developing countries, in particular at the industry level, are rela-tively scant.

In this paper, we investigate the role of intangible assets in sources of growth for theKorean economy. In particular, we focus on the interrelatedness of intangible investmentsand industrial transformation in order to explain changes in the sources of growth inKorea. During the past few decades, Korea has transitioned toward a knowledge-basedeconomy by investing massively in intangibles such as industrial R&D and IT.2 Thedeveloping Korean economy also experienced a rapid transformation of its industrialstructure by shifting from agriculture to manufacturing and later to services. This tran-sitional experience of Korea to a knowledge economy highlights a unique feature

1 The studies include Jalava et al. (2007) for Finland; Van Rooijen-Horsten et al. (2008) for the Netherlands;Fukao et al. (2009) for Japan; Marrano et al. (2009) for the UK; Edquist (2011) for Sweden; and Baldwinet al. (2012) for Canada.

2 R&D spending as a percentage of GDP reached approximately 3.7% in 2010, which ranked third amongOECD countries (OECD, 2012b). Business internet use and business with a broadband connection alsoranked in the top five among OECD countries (OECD, 2012a).

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associated with changing sources of growth, which contrasts with transition in developedcountries.3

Accordingly, we employ a definition of intangible assets suggested by Corrado et al.(2005, 2006), which encompasses a broad range of intangibles, including industrial R&D,computer-related information, and various firm-specific human and organizationalresources.4 The measurement of this broad range of intangible assets, particularly at theindustry level, is crucial for our study because of the industry-specific nature of intangibleinvestment, such as industrial R&D in manufacturing-intensive countries and IT in service-intensive countries. After constructing this novel industry-level data set, we examine twodistinctive channels of intangible assets that contribute to aggregate labour productivity(ALP) growth: the total factor productivity (TFP) growth effect and the intangible capitaldeepening effect.5 The former is related to technological innovations stemming fromknowledge accumulation through intangible investments, whereas the latter is related to theinput accumulation effect associated with intangible capital deepening.

We employ the methods of Stiroh (2002) and Jorgenson et al. (2007) to link industry-level productivity growth to aggregate growth. Then, we decompose industries’ contribu-tions to ALP growth into their direct productivity effects and resource reallocation effects.In particular, we compare the direct effects of two industry groups: intangible-intensiveindustries and other industries. We define the top one-third of 27 industries with highintangible investment rates as intangible-intensive industries and the others as intangible-less-intensive (hereafter, non-intangible) industries.6 The contribution of intangible-intensive industries to ALP growth steadily increased during 1981–2008 and accounted formore than 60% of ALP growth in 2001–2008. Moreover, the contribution of intangible-intensive industries to ALP growth is mainly attributed to their TFP growth rather than toinput growth. In contrast, the contribution of non-intangible industries to ALP growth hasdecreased, which is associated with both sluggish physical investment and lowered TFPgrowth. Consistent with our finding on TFP growth as the main source of the increasedcontribution of intangible-intensive industries, reallocation of hours worked to high-productivity industries is relatively small, and its contribution to ALP growth decreasesover the sample period. Overall, our findings suggest that the main source of ALP growthin the Korean economy has shifted from the accumulation of tangible capital in non-intangible industries toward TFP growth in intangible-intensive industries.

3 Some studies indicate the diffusion of IT as a key source of recent structural changes, such as highproductivity growth in some service industries, in advanced countries (Jorgenson and Timmer, 2011).

4 The positive relationship between these intangibles and firm performance is found in a number of studies,such as Stiroh (2002) and Brynjolfsson and Hitt (2003) for IT; Griliches (1986) and Griffith et al. (2004)for R&D; and Ichniowski et al. (1997) and Bloom and van Reenen (2007) for firm-specific human andorganizational resources.

5 This approach is similar to that of Oliner and Sichel (2000), who examine the contribution of IT to theUSA. ALP grows through two channels: TFP growth in IT-producing industries and IT capital deepeningin IT-using industries. Furthermore, Stiroh (2002) estimates a direct link between TFP growth and IT useat the industry level. Unlike IT hardware, most Corrado et al. (2005, 2006) intangibles are produced andused in the same industry. Therefore, we do not distinguish between intangible-using and intangible-producing industries.

6 To select intangible-intensive industries, we use the average intangible investment rate over the wholesample period. However, the selection of 9 intangible-intensive industries based on either the whole sampleperiod or a specific period of every decade gives us similar sets of industries because the ranking ofintangible intensity is stable over the sample period.

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Next, we examine the input accumulation effect of intangibles on ALP growth. To doso, we employ the method proposed by Corrado et al. (2005, 2006) and treat expendi-tures on intangibles as investments rather than as expenses. Given that the intangiblecapital deepening effect is included as an additional source of labour productivitygrowth, other sources of growth, such as tangible capital deepening, labour qualitygrowth and TFP growth are reduced. However, the magnitude of the reductions is rela-tively small. This confirms that the contribution of intangible-intensive industries to ALPgrowth through TFP growth is not an artifact of measurement errors due to a missinginput. We also find that the slowdown in tangible investment is partially mitigated by anincrease in intangible investment in intangible-intensive industries, but such mitigationdoes not occur in non-intangible industries. From the 1990s to the 2000s, the increasedcontribution of intangible capital deepening in intangible-intensive industries offset thedecreased contribution of tangible capital deepening, whereas this shift was not observedin non-intangible industries.

Our study is distinguished from previous works in several ways such that our findingsprovide meaningful implications for understanding the sources of growth in Korea aswell as the role of intangibles in economic growth. We have made the first attempt toexplain the changing sources of growth in Korea by examining not only industrial trans-formation in the development process but also the recent rapid technological progresscharacterized by massive intangible investments. Our approach provides better explana-tory power than the conventional theory on structural transformation to explain thechanging sources of growth in the Korean economy: this is because we rely on industrialshifts, first from agriculture to manufacturing, and later from manufacturing to services,during the development stages (Kuznets, 1966; Imbs and Wacziarg, 2003). In conven-tional theories, a sectoral shift to manufacturing raises aggregate productivity, while ashift to services limits aggregate productivity growth, because productivity in manufac-turing is higher than that in both agriculture and services (Baumol, 1967; Restucciaet al., 2008; Duarte and Restuccia, 2010). Rather, the recent technological progress asso-ciated with the IT revolution may alter sectoral productivity levels themselves, which istrue not only for developed countries but also for developing countries (Inklaar et al.,2005). Contrary to the stylized facts observed in developed countries, the transition frommanufacturing to services has evidently not been observed in Korea. In fact, the manu-facturing share has been stable since reaching its highest level (almost 30% of the grossdomestic product (GDP)) in the late 1980s.7 Instead, the expansion of intangible-intensive industries, not only in manufacturing but also in services, accounts for recentshifts in the sources of both output and productivity growths in Korea. This suggests thatthe development process of the Korean economy may not be the same as those of exist-ing developed countries.

In contrast to most previous studies on the Corrado et al. intangibles performed at theaggregate level (e.g. Corrado et al., 2006; Fukao et al., 2009; Marrano et al., 2009) or atthe sectoral level (Barnes, 2010; Dal Borgo et al., 2013),8 our study examines the role of

7 Despite the stable manufacturing share since the late 1980s, the service sector has steadily expanded as theagriculture and mining sectors have shrunk. In 2012, the agriculture and mining sectors accounted for only3% of GDP, and, thus, the future expansion of the service is unsustainable without a decline in themanufacturing sector.

8 See Barnes (2010) for Australia and Dal Borgo et al. (2013) for the UK at the one-digit industry level.

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intangibles at the detailed industry level.9 Because of the limitation of the aggregate dataanalysis, Corrado et al. (2005, 2006) and most previous studies examine only the inputaccumulation effect of intangibles on productivity growth and not the TFP effect associatedwith knowledge accumulation. The growth accounting analysis using industry-level intan-gible data enables us to identify the two channels of intangibles on ALP growth. In thisstudy, we focus on the TFP effect of intangible-intensive industries on ALP growth.Although the growth accounting analysis cannot be used to identify the underlying mecha-nism of this TFP effect,10 our findings shed light on the importance of innovations stem-ming from intangible investments and invite future research.

The remainder of this paper is organized as follows. Section 2 presents our data onindustry-level intangible investments following the definition of Corrado et al. (2005,2006) and other variables for growth accounting analyses. Section 3 presents our method-ology. Section 4 reports the results for the industry origins of both aggregate output andproductivity growth. Section 5 concludes with a discussion of the results and implicationsfor future research.

2. Data

2.1 Measuring intangibles

As discussed in Hulten (1979), any use of resources that reduces current consumption inorder to increase consumption in the future qualifies as an investment. This is true forspending on tangibles, including equipment and plants, as well as on intangibles, includingsoftware and R&D. However, in measuring GDP, spending on intangibles such as R&D istreated as an intermediate input, such as electricity. Except for mineral exploration andsoftware, the System of National Accounts (SNA) currently treats intangible spending asintermediate consumption (i.e. expenses). The 2008 revision of the SNA treats R&Dspending as investments.11 Compared to the definition of intangibles by Corrado et al.(2006), R&D is only a type of intangible asset. Spending on advertising, training and otherintangibles is not regarded by the SNA as investing in intangible assets.

In contrast to the narrow definition used in the SNA, a broader definition of intangibleinvestment is developed by Corrado et al. (2005, 2006, 2009). In the present paper, wefollow this broader definition and construct three types of intangible investments: comput-erized information (CI), innovative property (IP) and economic competencies (EC). Inmeasuring each type of intangible investment, we also use other complementary methodssuggested by researchers, including Fukao et al. (2009), Corrado et al. (2012) and DalBorgo et al. (2013). Computerized information consists mainly of software investment.Innovative property includes both scientific and non-scientific R&D. Non-scientific R&Dincludes costs of: new financial product development; copyright and license; product,machine and architectural design; and mineral exploration. Economic competenciesinclude advertising, training costs and investments in the organizational structure.

9 An exception is Miyagawa and Hisa (2013) for Japan at the two-digit industry level.

10 For example, technology spillovers among firms within intangible-intensive industries may increase theTFP of the firms (Bernstein and Nadiri, 1989).

11 Along with the reclassification of R&D as investments, GDP will be revised in 2013 for the USA and in2014 for Korea and Europe.



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First, computerized information at the aggregate level is obtained from aggregate soft-ware investment in the National Accounts published by the Bank of Korea (BOK). Weallocate the aggregate software investment into 27 industries12 by using the industry shareof total software investment calculated from the Fixed Capital Formation Table, a sup-plementary table of the Input–Output (IO) Table, which provides the industry-by-assetmatrix of fixed capital formation.

For the second category of intangible investments, we construct two types of investmentson innovative property: scientific R&D and non-scientific R&D. We obtain industry-levelscientific R&D expenditures from the Survey of Research and Development published bythe Ministry of Education, Science and Technology. Scientific R&D of an industry is R&Dfunded by that industry. Government-funded R&D is not included. The aggregate level ofscientific R&D is the sum of industry R&D expenditures. Non-scientific R&D includes:the costs of developing new products in the financial service and insurance industries;copyrights and license costs; product, machine and architectural design costs; and the costof mineral exploration in the mining industry.

Financial product development costs in Corrado et al. (2005, 2006) are assumed to be20% of the intermediate inputs used by the financial industry. In this paper, we followthe labour-based production cost method for measuring costs of developing new financialproducts adopted in intangible database projects for the EU and other advanced coun-tries, such as COINVEST and INNODRIVE (Jona-Lasinio et al., 2011).13 This followsthe approach of Hunt (2010), who argues that most of the cost of innovation in thefinancial service sector consists of researcher compensation. Because data on thedetailed occupation structure are usually not available, we use 8% of the compensationof high skilled workers (i.e. college graduate workers) in the financial industry as newproduct development costs, which is a good approximation and is also adopted in the twoprojects listed previously. Financial product development costs solely belong to thefinancial industry.

Using IO tables, industry-level copyright and license costs are constructed as inter-mediate inputs from the newspaper, publishing, broadcasting, movie, music, art andtheater industries. Industry-level costs of product, machine and architectural design aresimilarly estimated using IO tables. These costs include external expenditures on designbut not own-account expenditures.14 The aggregate-level costs for copyrights and licenseand design are defined as the sum of industry-level costs. Investment in mineral explo-ration, which is included solely for the mining industry, is obtained from the NationalAccounts.

The third category of intangible investments relates to economic competencies, whichinclude both brand equity (including expenditures on advertising) and firm-specific human

12 Based on the Korea Standard Industry Classification (KSIC) rev. 9 in 2008, the National Accounts publishindustry-level GDP for 27 industries, which include 11 manufacturing and 16 non-manufacturing indus-tries. Following this 27-industry classification, we construct the industry-level intangible investment.Detailed descriptions for the 27-industry classification are provided in Table A1 of the Appendix.

13 More detailed information for the COINVEST and INNODRIVE projects is available at http://www.coinvest.org.uk and http://www.innodrive.org, respectively. Details about another project related tothese two projects are available at http://www.intan-invest.net (Corrado et al., 2012).

14 Because data on wage bills of design workers is not available at the industry level, we could not estimatethe in-house design costs. Omission of own-account costs may underestimate the total design costs.



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http://www.coinvest.org.uk

http://www.coinvest.org.uk

http://www.innodrive.org

http://www.intan-invest.net

and organizational resources.15 To obtain advertising spending (including marketingresearch spending) at the aggregate level, we use the gross output of the advertisingindustry. Following Corrado et al. (2005, 2006), we assume that only 60% of the totaladvertising spending has a long-term effect. To estimate the industry-level advertisingexpenditures, we allocate aggregate advertising expenditures to 27 industries by using theratio of advertising spending to the total intermediate inputs for each industry, which aresourced from the IO tables.

Employer-provided training costs are obtained from the Report on Labor Cost of Enter-prise Survey (RLCES) published by the Ministry of Labor. This survey includes trainingcosts only for establishments with 30 or more employees.16 To estimate the training cost forsmall firms, we use the Survey on Actual State of SME (SASS) published by the Small andMedium Business Administration. We estimate the ratio of training costs of firms with 30or fewer employees and firms with 30 or more employees as approximately 0.5.17 Then, weapply this number to estimate training costs for firms with 30 or fewer employees in theRLCES. Total training costs are defined as the sum of the direct costs of training and theopportunity costs of training. Because data for the opportunity costs of training are notavailable, we assume that the direct costs of training are equal to the opportunity costs. Theconsulting costs are considered as firm-specific investments in organizational resources. Toobtain expenditures on consulting at the aggregate level, we the use gross output of theconsulting industry. The industry-level consulting costs are also estimated using the IOtables. The construction methods and sources for each type of intangible are summarizedin Table A2 in the Appendix.18

2.2 Intangible investment in Korea

2.2.1 Intangible investment at the aggregate level

Figure 1 compares intangible investment with two types of tangible investments: equip-ment and non-residential structures. Equipment investment is defined as the sum ofmachinery and transportation equipment, but it does not include software and mineralexploration because these investments are considered to be intangibles. As pointed out inthe growth literature on Korea and other fast-growing Asian countries (Krugman, 1994;Young, 1995), Figure 1 confirms a high ratio of tangible investment to GDP. Throughoutthe period 1981–2008, the average ratios for equipment and non-residential structures were13.5 and 14.9%, respectively. However, the total tangible investment has significantlydeclined since the late 1990s. In contrast, intangible investment has rapidly increased from2.3% in 1981 to 8.3% in 2008, which is equivalent to approximately 72% of equipment

15 Knowledge accumulation from business practices in professional services, such as law and education, arenot included in the Corrado et al. (2005, 2006) intangibles.

16 In particular, while the RLCES included firms with 30 or more employees before 1998, it has extendedthe coverage to firms with 10 or more employees since 1998.

17 Our estimate is not much different from that of Corrado et al. (2005, 2006), showing that 69% of smallestablishments (i.e. with fewer than 50 employees) in the USA provided formal training in 1995 comparedwith medium-sized (50–249 employees) and large (250 or more employees) establishments.

18 Our intangible data set based on the Corrado et al. (2005, 2006) definition is constructed by revising theindustry-level data set reported in Chun et al. (2012).



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investment. Declines in the intangible investment are observed only for the 2 years of theAsian financial crisis. Combining both tangible and intangible investments shows noevidence of a significant decline in the total investment in the Korean economy during thepast two decades.19 This result suggests that the slowdown in physical investment after thecrisis might be partly mitigated by the increase in intangible investment.20

Both Figure 2 and Table 1 show the share of the five intangible components as apercentage of GDP. Although the intangible share has increased more than three times since1981, the contribution of each intangible component to growth in the total intangibleinvestment varied substantially. Investments in both computerized information and inno-vative property (scientific and non-scientific R&D) have increased rapidly, whereas invest-ments in economic competencies (brand equity and firm-specific resources) have increasedslowly. In particular, the share of economic competencies declined from the 1990s to the

19 Chun et al. (2008) document the sluggish investment in Korea after the Asian financial crisis in 1997.Kinkyo (2007) finds that Korea’s lowered investment after the Asian financial crisis was caused bychanges to underlying fundamentals, such as deterioration in terms of trade.

20 This may also suggest that there has been substitution away from tangible investment toward intangibleinvestment in Korea.

0.0

2.5

5.0

7.5

(%)

10.0

12.5

15.0

17.5

20.0

1981 1986 1991 1996

Year

2001 2006

IntangiblesEquipment excluding intangiblesNon-residential structures

FIGURE 1. Intangible and tangible investments (as percentages of GDP) in KoreaNotes: Intangibles include investments in computerized information, innovative property and economic

competencies based on the work by Corrado et al. (2006). Equipment excludes intangibles such as softwareand mineral exploration.



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2000s, contrasting with the recent experience in the USA, where firm-specific resources,non-scientific R&D RLCES and computer software exhibited relatively faster growth, asreported in Corrado et al. (2005, 2006). As previously mentioned, this difference in therelative importance of the intangible categories might stem from the difference in industrystructure. For example, the manufacturing share of GDP is significantly higher in Koreathan in the USA, reiterating the importance of industry-level data for a cross-countryintangibles analysis.

0

2

4

6

8

10

1981 1986 1991 1996

(%)

2001 2006

Computerized information

Scientific R&D

Non-scientific R&D

Brand equity

Firm-specific resources

Year

FIGURE 2. Intangible investment (as a percentage of GDP) in KoreaNotes: The total intangible investment as a percentage of GDP in the figure consists of the sum of the five

types of intangibles.

TABLE 1Intangible investment (as a percentage of value-added) in Korea, 1981–2008

(1) 1981–2008 (2) 1981–1990 (3) 1991–2000 (4) 2001–2008 (4)/(2)

Computerized information 1.10 0.41 1.18 1.85 4.47Innovative property 2.35 1.51 2.45 3.28 2.18

Scientific R&D 1.72 0.97 1.81 2.56 2.63Non-scientific R&D 0.63 0.53 0.64 0.72 1.35

Economic competencies 2.10 1.67 2.40 2.25 1.35Brand equity 0.66 0.58 0.75 0.64 1.12Firm-specific resources 1.44 1.10 1.65 1.61 1.47

Total 5.55 3.60 6.03 7.38 2.05



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Table 2 presents the investment share of intangibles for Korea, the USA, the UK andJapan from 2001 to 2008. The intangible share as a percentage of output is the highest inthe USA, whereas that in Korea is approximately 35% below the US level. Shares ofcomputerized information and scientific R&D in Korea approximate those in the otherthree developed countries, but the share of economic competencies is much lower thanthose in the USA and the UK. Compared to the USA, the sources of low intangibles varyacross countries. Shares of scientific R&D and brand equity in the UK as well as the shareof economic competencies in Japan are lower than those in the USA.

2.2.2 Intangible investment at the industry level

Table 3 presents industry-level intangible intensity, defined as the ratio of total intangibleinvestment to industry value-added.21,22 In Figure 3, industries are sorted by their intangibleintensities. Both Table 3 and Figure 3 indicate a substantial variation in intangible intensityacross industries. Among manufacturing industries, electrical and electronic equipment(10), transport equipment (12) and machinery equipment (9) show a high intangible intensitythat is mainly due to high investment in innovative property (in particular, scientific R&D).Among non-manufacturing industries, information and communication (21), businessservices (22) and financial intermediation (19) show a high intangible intensity that isassociated with high investments in computerized information and innovative property. Ingeneral, investment in innovative property is higher in the manufacturing industries, whereas

21 Omission of the own-account costs of software, design, and copyrights and license may affect the rankingof industry-level intangible intensity. However, there is little change in the set of intangible-intensiveindustries with the inclusion of own-account costs because most software-intensive industries are alreadyincluded as intangible-intensive industries, and both design and copyrights and license costs account fora relatively small portion of the total intangible investment. We are grateful for an anonymous refereepointing this out.

22 This paper analyses the whole economy, including the private and public sectors, whereas most previousstudies based on Corrado et al. (2005, 2006) intangibles examine the business sector. In our 27-industryclassification, some industries, such as education (24) and health and social work (25), include both theprivate and the public sectors. However, our data set is not detailed enough to separate intangibleinvestments in the private sector from those in the public sector for the two industries.

TABLE 2Intangible investments: Cross-country comparison

Korea USA UK Japan

Computerized information 1.85 1.67 1.70 2.10Innovative property 3.28 4.12 2.33 4.13

Scientific R&D 2.56 2.08 0.96 2.67Non-scientific R&D 0.72 2.04 1.37 1.45

Economic competencies 2.25 5.55 5.25 2.28Brand equity 0.64 1.47 1.05 1.23Firm-specific resources 1.61 4.07 4.20 1.05

Total 7.38 11.33 9.28 8.51

Notes: All numbers are percentage of value-added output averaged over 2001–2008. US and UK data areobtained from the INTAN-Invest database (http://www.intan-invest.net; Corrado et al., 2012). Japanese data issourced from the Japan Industrial Productivity intangible database (http://www.rieti.go.jp/en/database/JIP2011;Miyagawa and Hisa, 2013).



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http://www.intan-invest.net

http://www.rieti.go.jp/en/database/JIP2011

that in computerized information is higher in the non-manufacturing industries, furtherconfirming the industry-specific use of intangibles.

We choose the top 9 industries that are above the average intangible intensity(approximately 5.5%) of the 27 industries. In addition, a substantial intensity gap existsbetween financial intermediation (the 9th industry) and furniture and other manufactur-ing (10th industry). We thus define these 9 industries as intangible-intensive industries,whereas we define the other 18 industries as non-intangible industries. Intangible-intensive industries are in boldface in the first column of Table 3 and are not character-ized using a single type of intangible. For example, computerized information isintensively used in business services (22); innovative property (scientific R&D) in elec-tric and electronic equipment (10); and economic competences (brand equity) in food,beverages and tobacco (3). Among the 9 intangible-intensive industries, 6 belong to themanufacturing sector, while 3 belong to the non-manufacturing sector. This implies thatintangible-intensive industries belong to neither a particular sector nor consist of a par-ticular type of intangible.

TABLE 3Intangible investment by industry, 1981–2008

Industry Total CI IP EC

1 Agriculture, forestry and fishing 0.2 0.0 0.1 0.12 Mining and quarrying 2.9 0.0 2.5 0.43 Food, beverages and tobacco 9.5 1.1 2.0 6.44 Textiles and leather 5.0 0.5 1.3 3.15 Wood, paper and printing 4.2 0.6 1.5 2.16 Petroleum, coal and chemicals 8.0 0.5 3.8 3.77 Non-metallic mineral products 3.0 0.1 1.6 1.48 Metal and fabricated metal products 3.3 0.2 1.4 1.79 Machinery equipment 12.3 0.9 8.0 3.3

10 Electrical and electronic equipment 18.0 0.9 13.6 3.511 Precision instruments 10.3 1.2 6.1 3.012 Transport equipment 12.5 0.5 9.8 2.213 Furniture and other manufacturing 5.3 0.5 1.4 3.414 Electricity, gas and water supply 4.6 2.4 1.2 1.015 Construction 3.0 0.3 0.8 1.816 Wholesale and retail trade 3.5 0.7 1.0 1.817 Restaurants and hotels 3.0 0.0 0.8 2.218 Transport and storage 2.2 0.3 0.4 1.519 Financial intermediation 6.7 1.7 2.3 2.720 Real estate and renting 4.2 3.7 0.2 0.321 Information and communication 11.0 2.4 3.4 5.222 Business services 8.5 3.6 2.1 2.823 Public administration and defense 4.3 1.0 0.8 2.524 Education 4.0 1.4 1.1 1.425 Health and social work 2.2 0.8 0.3 1.126 Culture and entertainment 5.3 0.6 1.5 3.127 Other service activities 5.1 0.7 3.0 1.4

Intangible-intensive 10.5 1.5 5.6 3.5Non-intangible 3.3 0.9 0.8 1.5Manufacturing 9.4 0.6 6.0 2.8Non-manufacturing 4.2 1.3 1.1 1.9

Notes: Numbers denote intangible investment as a percentage of industry value-added averaged over 1981–2008. The top one-third of industries (9 out of 27 industries) based on the total intangible are in boldface. CI,computerized information; EC, economic competencies; IP, innovative property.



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0 5 10 15 20

Agriculture, forestry and fishing

Health and social work

Transport and storage

Mining and quarrying

Construction

Non-metallic mineral products

Restaurants and hotels

Metal, Fabricated metal products

Wholesale and retail trade

Education

Real estate and renting

Wood, paper and printing

Public administration and defense

Electricity, gas and water supply

Textiles and leather

Other service activities

Culture and entertainment

Furniture and other manufacturing

Financial intermediation

Petroleum, coal and chemicals

Business services

Food, beverages and tobacco

Precision instruments

Information and communication

Machinery equipment

Transport equipment

Electrical and electronic equipment

CI

IP

EC

FIGURE 3. Intangible investment by industryNotes: Industries are sorted based on their intangible investment as a percentage of industry value-added

averaged over 1981–2008.



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Table 4 shows intangible intensity by period for two industry groups: intangible-intensive and non-intangible industries.23 On average, the intensity of intangible-intensiveindustries is more than three times higher than that of their counterparts. Among the threecomponents, the difference in innovative properties is the highest, whereas that in com-puterized information is the lowest. Despite this large gap in intangibles between the twogroups, the gap has not widened over the sample period. In other words, no convergenceexists among the two groups. This persistent gap again validates our industry grouping.

2.3 Output and input variables

2.3.1 Output, labour and capital stock

We obtain data for industry-level value-added, labour and physical capital from the KoreaIndustrial Productivity (KIP) database. The KIP database contains gross output, value-added output, and five inputs of capital, labour, energy, materials and purchased services(KLEMS) following the guideline of the EU KLEMS project (Timmer et al., 2007) from1970 to 2008 for 72 industries.24 Following the industry classification in the NationalAccounts, we reclassify 72 industries into 27 industries.

Based on the EU KLEMS manual, the KIP database has 18 categories of labour: twogenders (male and female), three age groups (below 30, 30–49, and 50 or above), and threeeducation levels (middle school or below, high school, and college or above). Labourservices are calculated from a Tornqvist aggregation of these 18 types of labour hours withtheir compensation weights. The growth rate of labour composition (quality) is defined asthe growth rate of labour services minus the growth rate of hours.

Capital in the KIP database consists of 11 types of assets: (i) residential structures; (ii)non-residential structures; (iii) infrastructure; (iv) transport equipment; (v) computing

23 Value-added used in Table 4 does not include intangibles. However, the use of value-added, includingintangibles, generates qualitatively similar results.

24 The KIP database is available at http://www.kpc.or.kr/eng/state/2010_kip.asp?c_menu=5&s_menu=5_4.The EU KLEMS database compiled from the raw data set of the KIP database is available at http://www.euklems.net.

TABLE 4Intangible investment (as a percentage of value-added): Intangible-intensive versus non-intangible industries

(1) 1981–2008 (2) 1981–1990 (3) 1991–2000 (4) 2001–2008 (4)/(2)

Intangible-intensive industriesComputerized information 1.46 0.65 1.43 2.49 3.84Innovative property 5.56 3.99 5.77 7.24 1.81Economic competencies 3.51 3.31 3.79 3.43 1.04Total 10.53 7.95 11.00 13.15 1.65

Non-intangible industriesComputerized information 0.92 0.34 1.06 1.46 4.36Innovative property 0.84 0.67 0.93 0.95 1.42Economic competencies 1.49 1.14 1.78 1.56 1.36Total 3.25 2.15 3.78 3.97 1.85



61

http://www.kpc.or.kr/eng/state/2010_kip.asp?c_menu=5&s_menu=5_4

http://www.euklems.net

http://www.euklems.net

equipment; (vi) communications equipment; (vii) other machinery and equipment; (viii)products of agriculture and forestry; (ix) other products; (x) software; and (xi) otherintangibles. Capital services are calculated using a Tornqvist aggregation of these 11 typesof assets. To estimate rental costs of the capital stock, we use depreciation rates from Pyoet al. (2007) and Timmer et al. (2007) and capital gains calculated from the 5-year movingaverages of asset deflators.

Through standard growth accounting, we use the KIP capital stock that includes intan-gibles included in the National Accounts, such as software and mineral exploration. Toperform a growth accounting analysis with intangible assets, we define tangible andintangible capital stock. Tangible capital stock is KIP capital stock minus the two intangi-bles of software and mineral exploration. The intangible capital stock consists of comput-erized information, innovative property and economic competencies, as described in theprevious section.

2.3.2 Intangible capital stock

To capitalize intangible investments, it is necessary to measure both the deflator and thedepreciation rate for each type of intangible. The software deflator is obtained from thesoftware investment deflator published by the BOK. The initial capital stock of softwareis set to zero for the year 1969. Following Corrado et al. (2005, 2006), the depreciationrate of the software stock is set to 0.315. The software capital stock is constructed usingthe perpetual inventory method. The GDP deflator is used for scientific R&D. The initialcapital stock of R&D is set to zero for 1969 because the ratio of business sector R&Dto GDP (0.07%) is very close to zero in 1969. The private R&D investment ratio to GDPwas very low in the 1970s (approximately 0.2%) and has rapidly increased since theearly 1980s. Among non-scientific R&D, we use the gross output deflator of the news-paper, publishing, movie, music, broadcasting, art and theater industries for copyrightand licensing costs, and that of other businesses, including the design industry, forproduct, machine and architectural design. We also use the gross fixed capital formationdeflator for mineral exploration. Following Corrado et al. (2005, 2006), the depreciationrates of both scientific and non-scientific R&D stock are set to 0.20. We use the grossoutput deflators of advertising, education and consulting industries for the deflators ofbrand equity, firm-specific training and organizational structure, respectively. The depre-ciation rates are 0.60 for brand equity and 0.4 for firm-specific human and organizationalresources. The source and method for the deflator and the depreciation rate for each typeof intangible asset are summarized in Table A2 in the Appendix.25

2.3.3 Adjustment for output and inputs

When we treat intangibles as investments, we must adjust value-added and labour andredefine the tangible capital stock. The National Accounts treats most Corrado et al.(2005, 2006) intangible spending as expenses, except for mineral exploration and

25 The growth accounting results in Section 4 are qualitatively similar to those for alternative depreciationrates.



62

software.26 The value-added in the KIP obtained from the National Accounts includesonly software, mineral exploration, and both labour and capital costs in scientific R&D.Thus, we add all other intangibles to the value-added. We also adjust for the doublecounting of the labour cost of scientific R&D in the KIP labour data. Tangible capital isdefined as the KIP capital stock exclusive of software, mineral exploration and capitalcosts of scientific R&D.

3. Methodology

In this section, we estimate the contributions of two groups of intangible-intensive indus-tries and non-intangibles industries to aggregate output and productivity growth. To do this,we employ the methodologies used in Stiroh (2002) and Jorgenson et al. (2007) and thendevelop them to determine the industry origin for aggregate output and productivitygrowth.27

To investigate the industry origin of the aggregate output growth, we employ theproduction possibility frontier approach used in Jorgenson et al. (2007). The key feature ofthis approach is that the aggregate value-added does not assume that the price of output isthe same across industries.28 Thus, the aggregate real value-added growth rate (ΔlnY)is defined as

Δ ΔlnY w Yi i

i

= ∑ ln , (1)

where ΔlnYi is the real value-added growth of industry i. Time subscripts are suppressed forconvenience. wi is the 2-year averaged share of industry nominal value-added in the

aggregate as wP Y

P Yi

Y i i

Y i i

i

=∑

,

,

and w w wi i t i t= × +( )−0 5 1. , , . PY,i is the value-added deflator for

industry i, and Δ denotes the difference between 2 adjacent years. Aggregate value-addedgrowth is decomposed into contributions from the two groups of intangible-intensive andnon-intangible industries as

Δ Δ ΔlnY w Y w Yi i

i I

i i

i N

= +∈ ∈∑ ∑ln ln , (2)

where I and N denote the intangible-intensive and non-intangible industries, respectively.The first and second terms on the right-hand side of Equation (2) are the contributions ofthe intangible-intensive and non-intangible industries to the aggregate real value-addedgrowth, respectively.

26 The 1993 System of National Accounts (SNA) treats R&D spending as an expense, but the new 2008 SNAtreats it as investment.

27 These methods are also applied by Eicher and Roehn (2007) and Oliner et al. (2007).

28 The production possibility frontier approach allows heterogeneous types of labour and capital inputs, butthe price (i.e. rental price and wage rate) of each type of capital and labour is assumed to be identical forall industries. Thus, the aggregate capital and labour service growth rates do not require industry-leveldata and are calculated as the weighted averages of the heterogeneous types of capital assets and workersin the whole economy.



63

Next, we consider the industries’ contributions to ALP growth. ALP growth isdefined as

Δ Δ Δln ln ln ,Y H Y H( ) = − (3)

where H is hours worked. The industry-level labour productivity growth is similarlydefined as

Δ Δ Δln ln ln .Y H Y Hi i i i( ) = − (4)

After aggregating industry-level labour productivity over industries and combiningEquations (3) and (4), we have

Δ Δ Δ Δ

Δ

ln Y H w Y H w H H

w Y H R

i i i

i

i i

i

i i i

i

( ) = ( ) + −⎡⎣⎢

⎤⎦⎥

= ( ) +

∑ ∑∑

ln ln ln

ln HH ,(5)

where the first term on the right-hand side is a pure productivity effect equal to theweighted average of industry labour productivity growth rates, and the second term(RH) is the reallocation of hours worked to high-productivity industries (Stiroh, 2002).29

The aggregate hours growth approximately weights industries by their share of aggregatehours, and so, aggregate productivity rises if industries with value-added sharesabove their hours’ shares (i.e. industries with relatively high productivity levels) experiencegrowth in hours (Oliner et al., 2007). Therefore, Equation (5) decomposesALP growth into two sources: the direct contribution from industry-level productivitygrowth and the indirect contribution from resource reallocation toward high-productivityindustries.

Industries’ direct contributions to ALP growth are further decomposed into contribu-tions of intangible-intensive and non-intangible industries, thus rearranging Equation (5) asfollows:

Δ Δ Δln Y H w Y H w Y H Ri i i

i I

i i i

i N

H( ) = ( ) + ( ) +∈ ∈∑ ∑ln ln , (6)

where I and N denote the intangible-intensive and non-intangible industries, respectively.The first and second terms in Equation (6) are the contributions of the intangible-intensiveand non-intangible industries to ALP growth, respectively.

Finally, we further decompose each industry group’s direct productivity effect into threecomponents as: (i) capital deepening; (ii) labour quality growth; and (iii) TFP growth. Thefirst and second terms in Equation (6) are decomposed as follows:

w Y H w K H w Q w Ti i i

i I

i K i i i

i I

i L i i

i I

iΔ Δ Δ Δln ln ln ln, ,( ) = ( ) + +∈ ∈ ∈∑ ∑ ∑ν ν FFPi

i I∈∑ (7a)

29 In this direct aggregation over industries, the price of each type of input is no longer assumed to be thesame across industries, so that mobility of inputs is allowed across industries.



64

w Y H w K H w Q w Ti i i

i N

i K i i i

i N

i L i i

i N

iΔ Δ Δ Δln ln ln ln, ,( ) = ( ) + +∈ ∈ ∈∑ ∑ ∑ν ν FFPi

i N∈∑ , (7b)

where νK and νL are 2-year averages of capital and labour cost shares, respectively. Qrepresents labour quality, and labour quality growth is defined as Δ ln Qi = Δ ln Li − Δ ln Hi.Industry-level capital and labour growth rates are defined as the weighted averages of theheterogeneous types of capital assets and workers, respectively. Capital and labour growth

are Δ Δln K w Ki k i k i

k

= ∑ , ,ln and Δ Δln L w Li l i l i

l

= ∑ , ,ln , where wP K

P Kk i

K k i k i

K k i k i

k

,, , ,

, , ,

=∑ and

wP L

P Ll i

L l i l i

L l i l i

l

,, , ,

, , ,

=∑ . Subscripts k and l denote the type of capital and labour, respectively.

After treating spending on intangibles as investments, we consider a model with two typesof capital: tangible and intangible capital. Equations (7a) and (7b) can be rewritten asfollows:

w Y H w v KT H w v KI Hi iA

ii I

i KT i i i

i I

i KI i i i

i

Δ Δ Δln ln ln, ,( ) = ( ) + ( )∈ ∈ ∈∑ ∑

II

i L iA

i

i I

i iA

i I

w v Q w TFP

∑∑ ∑+ +

∈ ∈, ln lnΔ Δ (8a)

w Y H w v KT H w v KI Hi iA

i

i N

i KT i i i

i N

i KI i i i

i

Δ Δ Δln ln ln, ,( ) = ( ) + ( )∈ ∈ ∈∑ ∑

NN

i L iA

i

i N

i iA

i N

w v Q w TFP

∑∑ ∑+ +∈ ∈

, ln ln ,Δ Δ (8b)

where KT and KI are tangible and intangible capital, respectively. Adding intangiblesrequires adjustments for the value-added (Yi

A), labour cost share ( vL iA, ) and TFP (TFPi

A)variables.30

4. Results

Following the method used in the previous section, we decompose the aggregate outputgrowth into contributions from intangible-intensive and non-intangible industries. Then,we decompose ALP growth into direct productivity contributions of intangible-intensiveand non-intangible industries and the reallocation effect. Furthermore, we reexamine theseanalyses when expenditures on intangibles are treated as investments.

4.1 Industry origins of aggregate output growth

Table 5 reports the average growth rate and share for each industry group by period and itscontribution to the aggregate real value-added growth. The contribution is calculated usingthe average growth rate multiplied by the share of each industry group. In Panel A, the

30 Labour hours and industry share variables also change, but the same variable names are used forconvenience.



65

whole economy grew, on average, at an annual rate of 6.64% during the period 1981–2008.Approximately each half of the aggregate growth is attributable to intangible-intensive andnon-intangible industries.31 Contrary to the results for the whole sample period, the con-tribution of the intangible-intensive industries increased rapidly from 36.7% in the 1980sto 65.1% in the 2000s. The contribution of the intangible-intensive industries in the 2000sis almost two times larger than that of the non-intangible industries. This indicates that theindustry origin of economic growth in Korea shifted from non-intangible industries towardintangible-intensive industries over the past three decades.

In contrast, the contribution of the manufacturing industries to the aggregate outputgrowth showed little change: 35.1% in the 1980s, 37.5% in the 1990s and 37.8% in the2000s.32 The contrasting results between the manufacturing and intangible-intensive

31 Among the intangible-intensive industries, the contribution of two IT-producing industries, i.e. electricaland electronic equipment (10) and information and communication (21), has increased more rapidly thanthat of other intangible-intensive industries, but the magnitude is relatively small because of the smalloutput share.

32 Detailed results are available on request.

TABLE 5Contributions to aggregate real value-added growth: Intangible-intensive versus non-intangible industries

Panel A. Conventional case

(1) 1981–2008 (2) 1981–1990 (3) 1991–2000 (4) 2001–2008 (3) − (2) (4) − (3)

Growth ratesWhole economy 6.64 9.40 6.12 3.85 −3.28 −2.26

Intangible-intensive 10.86 14.15 10.78 6.83 −3.36 −3.95Non-intangible 4.84 7.84 4.01 2.12 −3.84 −1.88

Value-added shareIntangible-intensive 30.5 24.5 31.3 37.0 6.8 5.7Non-intangible 69.5 75.5 68.7 63.0 −6.8 −5.7

ContributionsIntangible-intensive 3.13 3.45 3.32 2.51 −0.13 −0.81Non-intangible 3.51 5.95 2.80 1.34 −3.15 −1.45

Panel B. Including intangibles

(1) 1981–2008 (2) 1981–1990 (3)1991–2000 (4) 2001–2008 (3) − (2) (4) − (3)

Growth ratesWhole economy 6.78 9.56 6.19 4.03 −3.37 −2.15

Intangible-intensive 11.07 14.46 10.82 7.13 −3.64 −3.69Non-intangible 4.87 7.91 4.01 2.15 −3.90 −1.86

Value-added shareIntangible-intensive 31.3 25.1 32.2 38.1 7.1 5.9Non-intangible 68.7 74.9 67.8 61.9 −7.1 −5.9

ContributionsIntangible-intensive 3.28 3.61 3.42 2.69 −0.19 −0.73Non-intangible 3.49 5.95 2.76 1.34 −3.19 −1.43

Notes: Aggregate real value-added growth rates are averages of industry-level valued-added growth ratesweighted using the industries’ nominal value-added share within the whole economy, averaged over 2 adjacentyears. Contributions are calculated as industries’ real value-added growth rates multiplied by their value-addedshares. Thus, the sum of the two industry groups’ contributions equals the value-added growth rate of the wholeeconomy.



66

industries are presented in Figure 4.33 The stable contribution of the manufacturingindustries may reflect a divergence in the performance of two industry groups withinmanufacturing: intangible-intensive manufacturing industries have grown quickly, whereasnon-intangible manufacturing industries have grown more slowly.

In Panel B of Table 5, we report the results for the contributions of the two industrygroups to the aggregate output growth when intangible expenditures are treated as invest-ments. As previously mentioned, this treatment may change both the level and the growthof value-added. The aggregate growth rate increased from 6.64 to 6.78% in the period1981–2008. This treatment increases the aggregate growth rate by adding 0.16, 0.07 and0.18 percentage points in the 1980s, 1990s and 2000s, respectively. However, the magni-tudes were too small to reverse the slowdown in economic growth during the past threedecades.

The adjustments for the contributions of intangible-intensive and non-intangible indus-tries are not the same because of differences in intangible investments in the two industrygroups. As expected, the contribution of intangible-intensive industries to aggregate growthincreased from 3.13 to 3.28%, whereas that of non-intangible industries showed littlechange. Similar to the results for the whole economy, the effects on the two industry groups

33 Consistently, the value-added share of the manufacturing sector in the whole economy hardly changed,from 24.9% in the 1980s to 25.8% in the 2000s, whereas the value-added share of the intangible sectorincreased significantly, from 24.5% in the 1980s to 37.0% in the 2000s.

0

20

40

60

(%)

80

100

1981–1990

1991–2000

2001–2008

1981–1990

1991–2000

2001–2008

Intangible-intensive (left)manufacturing (right)

Non-intangible (left)non-manufacturing (right)

Intangible-intensiveversus non-intangible

Manufacturingversus non-manufacturing

FIGURE 4. Contributions to the aggregate real value-added growth: Intangible-intensive versusmanufacturing industries

Notes: The three bars on the left present the relative contributions of intangible-intensive (light blue) andnon-intangible industries to the aggregate real value-added growth. The three bars on the right are similarly

defined for manufacturing and non-manufacturing industries.



67

were also too small to change the results reported in Panel A of Table 5. This again confirmsthat our finding on the increased contribution of intangible-intensive industries to theaggregate growth is not affected by treating intangibles as investments.

4.2 Industry origins of aggregate labour productivity growth

In this section we present results for the sources of ALP growth as described in Equa-tions (6), (7) and (8). ALP growth is decomposed into three components: (i) labourproductivity growth in intangible-intensive industries; (ii) labour productivity growth innon-intangible industries; and (iii) hours reallocated toward high-productivity industries.The direct productivity contribution of each industry group is further decomposedinto three components: (i) capital deepening; (ii) labour quality growth; and (iii) TFPgrowth, as described in equations (7a) and (7b). Finally, treating intangibles as invest-ments, we reexamine whether the direct contributions of the two industry groupschanged significantly. In this case, the direct contribution of each industry group isdecomposed into four components: (i) tangible capital deepening; (ii) intangible capitaldeepening; (iii) labour quality growth; and (iv) TFP growth. Our findings are presentedin Table 6.

First, the top three rows in Panel A of Table 6 present the results for ALPgrowth decomposed into the aggregate real value-added and hours growth rates, asdescribed in Equation (3). The ALP growth rate was, on average, 5.34% in the period1981–2008 and declined steadily from 7.39% in the 1980s to 3.48% in the 2000s.During the past three decades, both output and hours worked decreased. However, theformer decreased more rapidly than the latter, suggesting that the decreased ALP growthis mainly associated with a slowdown in output growth rather than the slowdown inhours growth.34

Second, the bottom part in Panel A of Table 6 presents results for the decompositionsof the ALP growth rate into the weighted average of the LP growth rates in the twoindustry groups and the reallocation effect. The breakdown of the direct productivityeffect into the two industry groups shows that the productivity contribution of theintangible-intensive industries increased over the period 1981–2008, whereas that of thenon-intangible industries decreased in the same period. The contribution of intangible-intensive industries to ALP growth was 1.80% in the 1980s, which is approximatelyhalf the contribution of the non-intangible industries in the same period.35

However, because the contribution of the intangible-intensive industries increased overthe sample period, the contribution of the intangible-intensive industries in the 2000s isalmost three times larger than that of the non-intangible industries. Although ALPgrowth declined sharply from 7.39% in the 1980s to 4.79% in the 1990s, the intangible-intensive industries’ contribution increased in the same period. Furthermore, thiscontribution changed little from the 1990s to the 2000s. Thus, the contribution

34 The sharp decline in hours worked is attributable to the decreased hours per worker rather than to thedecreased number of workers.

35 This small contribution of intangible industries is mainly attributable to their small share of value-addedin the whole economy, approximately 24.5% in the 1980s. The average labour productivity growth ofintangible industries in the 1980s was approximately 7.2%, which is higher than the corresponding valuefor the non-intangible industries.



68

of the intangible-intensive industries accounted for approximately 24% of ALP growth inthe 1980s. This contribution increased significantly in the 2000s, accounting for approxi-mately 64% of ALP growth. In contrast, the contribution of non-intangible industriesaccounted for almost half the ALP growth in the 1980s and for only approximately 20%of the same in the 2000s. The sharp decline in the contribution of non-intangible indus-tries accounted for approximately 83% of the deceleration in ALP growth from the 1980sto the 1990s.

TABLE 6Decompositions of aggregate labour productivity (ALP) growth

Panel A. Conventional case

(1)1981–2008

(2)1981–1990

(3)1991–2000

(4)2001–2008 (3) − (2) (4) − (3)

ALP growth 5.34 7.39 4.79 3.48 −2.59 −1.31Aggregate value-added growth 6.64 9.40 6.12 3.85 −3.28 −2.26Aggregate hours growth 0.82 1.21 0.89 0.24 −0.32 −0.65

Contributions to ALP growth(1) Intangible-intensive industries’

LP growth2.13 1.80 2.39 2.21 0.59 −0.18

(1A) Capital deepening 0.76 1.06 0.75 0.39 −0.30 −0.36(1B) Labour quality growth 0.19 0.14 0.16 0.29 0.02 0.13(1C) TFP growth 1.18 0.60 1.48 1.53 0.88 0.05

(2) Non-intangible industries’LP growth

1.97 3.53 1.37 0.78 −2.16 −0.58

(2A) Capital deepening 1.89 2.73 1.85 0.89 −0.88 −0.96(2B) Labour quality growth 0.24 0.26 0.18 0.30 −0.07 0.12(2C) TFP growth −0.16 0.54 −0.67 -0.41 −1.21 0.26

(3) Hours reallocation 1.24 2.06 1.04 0.49 −1.02 −0.55

Panel B. Including intangibles

(1)1981–2008

(2)1981–1990

(3)1991–2000

(4)2001–2008 (3) − (2) (4) − (3)

ALP growth 5.53 7.61 4.88 3.75 −2.74 −1.13Aggregate value-added growth 6.78 9.56 6.19 4.03 −3.37 −2.15Aggregate hours growth 0.74 1.12 0.83 0.17 −0.28 −0.67

Contributions to ALP growth(1) Intangible-intensive industries’

LP growth2.32 1.96 2.50 2.56 0.54 0.06

(1A) Tangible capital deepening 0.66 0.99 0.62 0.31 −0.37 −0.32(1B) Intangible capital deepening 0.35 0.26 0.26 0.58 0.01 0.32(1C) Labour quality growth 0.17 0.13 0.14 0.25 0.01 0.11(1D) TFP growth 1.14 0.59 1.47 1.42 0.89 −0.05

(2) Non-intangible industries’LP growth

1.98 3.55 1.36 0.80 −2.19 −0.57

(2A) Tangible capital deepening 1.76 2.63 1.69 0.76 −0.93 −0.94(2B) Intangible capital deepening 0.14 0.19 0.17 0.04 −0.01 −0.14(2C) Labour quality growth 0.23 0.25 0.18 0.29 −0.07 0.11(2D) TFP growth −0.15 0.49 −0.68 −0.28 −1.17 0.40

(3) Hours reallocation 1.23 2.10 1.02 0.40 −1.08 −0.62

Notes: ALP growth equals the sum of: (i) the weighted average of intangible-intensive industries’ labourproductivity growth (LP); (ii) the weighted average of non-intangible industries’ LP growth; and (iii) hoursreallocation.



69

Third, the contributions of the two industry groups toALP growth are further decomposedinto capital deepening, labour quality growth and TFP growth.36 In the period 1981–2008,TFP growth in intangible-intensive industries accounted for approximately 55% of labourproductivity growth in these industries, whereas almost all labour productivity growth innon-intangible industries is attributed to their capital deepening. From the 1980s to the2000s, theTFP contribution of intangible-intensive industries toALP growth increased from0.52 to 1.42%.37 In contrast, the TFP contribution of non-intangible industries sharplydropped from the 1980s to the 1990s. The TFP contribution improved in the 2000s, but thenon-intangible industries remained negative contributors, suggesting that this sluggish TFPgrowth in the non-intangible industries (including some traditional manufacturing and mostservices industries) might have been an obstacle to the economy-wide resurgence in TFPgrowth after theAsian financial crisis (Kim, 2007; Chun et al., 2008).This drastic shift of theindustry TFP growth toward intangible-intensive industries suggests a structural change inKorea toward technology-oriented industries. The contribution of capital deepeningdecreased in both industry groups. However, the reduced contribution of capital deepeningin the intangible-intensive industries was offset by the increased contributions of TFPgrowth, labour quality growth and intangible capital deepening. The capital deepeningcontribution of non-intangible industries continuously decreased and became a major sourceof the decreased labour productivity growth in these industries in the 2000s. The fall incapital deepening has been partly offset by the intangible capital deepening in the intangibleintensive industries, but not in non-intangible industries.38

Fourth, the bottom row in Panel A of Table 6 shows a small reallocation effect. Thereallocation of hours worked contributed approximately 1.24% to ALP growth during1981–2008,39 which accounted for approximately 20% of ALP growth. The magnitude ofreallocation contribution decreased over the sample period. The findings suggest that ALPgrowth is attributable to the direct productivity effect stemming from high TFP growthwithin intangible-intensive industries rather than from active reallocation of labour input tohigh-productivity industries. If the productivity gap between low-productivity and high-productivity industries remains constant, the aggregate productivity growth can be largely

36 In Table 6, the contribution of labour quality growth to ALP growth in non-intangible industries is greaterthan that in intangible-intensive industries. Labour quality growth (assuming that the number of workersfor each group remains unchanged) depends on changes in the ratio of high to low-wage workers ratherthan changes in the absolute wage rate for each type of worker. If the wage-increasing effect across highand low-wage workers is more equally distributed in intangible-intensive industries, the labour qualitygrowth in intangible-intensive industries can be smaller than that in non-intangible industries. This isconfirmed in our data set. The wage rates of both high and low-wage workers in intangible-intensiveindustries are higher than those in non-intangible industries. However, the wage gap between high andlow-wage workers in intangible-intensive industries is rather smaller than that in non-intangible indus-tries. We are grateful for an anonymous referee pointing this out.

37 Rhee and Pyo (2012) find that while the contribution of ICT-producing industries to the aggregate TFPgrowth decreased during the past three decades, that of ICT-using industries increased. However, anincreasing trend in the TFP contribution of ICT industries is not evident. The total TFP contribution of thetwo sectors increased from the 1980s to the 1990s but decreased from the 1990s to the 2000s.

38 The high intangible intensity in intangible-intensive industries does not necessarily imply lower returns tointangible capital in intangible-intensive industries compared to non-intangible industries, if the produc-tion structure is different or changes differently across industries.

39 Our finding of a positive effect of hours reallocation is also consistent with that in Rhee and Pyo (2012),although the magnitude is not directly comparable because they analyse both labour and capitalreallocations.



70

explained by the resource reallocation between the two industry groups.40 However, if theproductivity gap widens, then the aggregate productivity growth can be accounted for byproductivity growth within the high-productivity industry group rather than by the resourcereallocation (Timmer and de Vries, 2009). The expansion of intangible-intensive industriesand its impact on ALP in Korea presents the latter case; that is, high productivity growthin intangible-intensive industries.41 This finding sharply contrasts with the structural trans-formation of industries in the development stage, which suggests that the former caseholds; that is, resource reallocation between industries with different productivity levels.

Finally, we reexamine the above results when intangible expenditures are treated asinvestments, and, thus, we consider the input accumulation effect of intangibles throughintangible capital deepening on the ALP growth. The results are presented in Panel B ofTable 6. With this treatment, the ALP growth increases from 5.34 to 5.53%, which ismainly attributable to the increased output growth in intangible-intensive industries. Thesub-period results are also qualitatively the same. After including intangible capital deep-ening as the fourth component of labour productivity growth in the intangible-intensiveindustries, the contributions of the other three components decrease. The contribution oftangible capital deepening decreases by 0.1 percentage points, whereas those of the labourquality and TFP growth show little change. These results suggest that our finding of theincreased contribution of TFP growth in intangible-intensive industries is not affected bythis treatment. In other words, the TFP channel of the intangible-intensive industries toALP growth is not an artifact of measurement errors stemming from a missing input.Regarding tangible and intangible capital deepening effects, we have contrasting results forintangible-intensive and non-intangible industries. The slowdown in physical investmentsis known as the main source of the decreased output and labour productivity growth in theKorean economy. For intangible-intensive industries, a slowdown in tangible investment ispartly mitigated by an increase in intangible investment. In particular, the increasedcontribution of intangible capital deepening from the 1990s to the 2000s fully offset thedecreased contribution of intangible capital deepening, and, thus, the sum of the tworemained unchanged. In contrast, the slowdown in the tangible investment of non-intangible industries was not mitigated by their intangible investment.

Furthermore, we reclassify 27 industries into 9 ICT industries (7 ICT-using and 2ICT-producing industries) and 18 non-ICT industries, as in Jorgenson et al. (2007) andRhee and Pyo (2012). As shown in Table A1 in the Appendix, 9 intangible-intensiveindustries consist of 2 ICT-producing industries, 4 ICT-using industries and 3 non-ICTindustries. Approximately two-thirds of the intangible-intensive industries are either ICT-using or ICT-producing industries, which suggests that both ICT and intangible invest-ments may be complementary (Corrado et al., 2013). We perform growth accountinganalyses for ICT-using, ICT-producing, and non-ICT industries.42 For example, accountingresults with intangibles show that ICT-using and ICT-producing industries made differingcontributions between the 1990s and 2000s. The contribution of ICT-using industries toALP growth rapidly rose in the 2000s, while that of ICT-producing industries rapidly rose

40 If friction in the labour market or misallocation exists, the magnitude of the reallocation effect may notbe large enough to explain the aggregate productivity growth.

41 This is consistent with the finding in Timmer and de Vries (2009); namely, that the contribution of thesectoral reallocation effect in the aggregate productivity growth in Korea is relatively smaller than that ofthe within effect.

42 The growth accounting results are not reported in the paper. These results are available upon request.



71

in the 1990s. In particular, this difference is more apparent in TFP growth between the twoindustry groups. In the whole sample period, the sum of the two ICT industries’ contribu-tion to ALP growth is approximately 1.79%; that is, approximately three-quarters of thecontribution of intangible-intensive industries. Overall, the results suggest that ourintangible-based industry classification allows better industry grouping to capture thechanging structure of the Korean economy since the 1980s than the ICT-based one.

Overall, we find that the contribution of intangible-intensive industries increased overthe period 1981–2008 and that the increased contribution is attributable to the increasedTFP growth in the intangible-intensive industries.43 In particular, the TFP growth inintangible-intensive industries is found to be the main contributor to ALP growth in2001–2008. The decreased contribution of non-intangible industries is associated withdeclines in both TFP growth and capital deepening.

5. Conclusion

During the industrialization period of the 1970s and the 1980s, the Korean economyexperienced rapid economic growth. However, economic growth slowed down from theearly 1990s, especially after the Asian financial crisis in 1997. Most studies have attemptedto explain this slowdown as a result of sluggish investment (in physical capital) andshortened hours worked, but they are silent on the underlying transformation of industrystructure combined with recent technological progress. In this study, we construct a uniquedata set on the industry-level intangible investment based on the widely adopted studies ofCorrado et al. (2005, 2006, 2009) and examine changes in the sources of growth in Korea,focusing on industrial shifts associated with technological progress stemming frommassive intangibles investments.

Throughout our growth accounting analyses, we find that the industries using intangiblesintensively increased their contributions to both aggregate output and productivity growth,while the non-intangible industries decreased their contributions. This increased contribu-tion of the intangible-intensive industries to aggregate labour productivity growth is mainlyattributable to TFP growth rather than to input growth. In contrast, both the sluggishphysical investment and TFP growth account for the decreased contribution of the non-intangibles industries. Our study presents a new explanation for recent changing sources ofgrowth in Korea, by focusing on industrial shifts away from traditional industries, towardknowledge-intensive industries. The recent rapid technological progress associated withthe IT revolution structurally changed many developed countries, which past studies revealby investigating, for example, productivity surges in certain service industries. In thisstudy, we relate this technological progress to a country with an industrial structure thatdiffers from that of developed countries, to determine the changing sources of growth inKorea. Our finding on the overarching role of the intangible-intensive industries in therecent growth of the Korean economy invites a new perspective for future research ineconomic development and growth in the age of the IT revolution.

43 Our results are qualitatively similar although two IT-producing industries (electrical and electronicequipment (10) and information and communication (21)) are excluded from intangible-intensiveindustries.



72

Acknowledgments

We thank Kyoji Fukao, Shoichi Hisa and Tsutomu Miyagawa for the collaboration for theconstruction of data sets on intangible assets. We are also most grateful to the Co-editorsEtsuro Shioji and Taiji Furusawa, and to two anonymous referees for their particularlyhelpful comments. A part of this research was done while Hyunbae Chun was visiting NewYork University. This work was supported by the National Research Foundation of KoreaGrant funded by the Korean Government (NRF-2012S1A2A1A01030658).

Appendix

TABLE A1Industry classification

Number Industry nameClassification:

Intangible-intensiveClassification:

ICTClassification:Manufacturing

1 Agriculture, forestry and fishing Non-intangible Non-ICT Non-manufacturing2 Mining and quarrying Non-intangible Non-ICT Non-manufacturing3 Food, beverages and tobacco Intangible-intensive Non-ICT Manufacturing4 Textiles and leather Non-intangible Non-ICT Manufacturing5 Wood, paper and printing Non-intangible Non-ICT Manufacturing6 Petroleum, coal and chemicals Intangible-intensive Non-ICT Manufacturing7 Non-metallic mineral products Non-intangible Non-ICT Manufacturing8 Metal and fabricated metal products Non-intangible Non-ICT Manufacturing9 Machinery equipment Intangible-intensive ICT-using Manufacturing

10 Electrical and electronic equipment Intangible-intensive ICT-producing Manufacturing11 Precision instruments Intangible-intensive Non-ICT Manufacturing12 Transport equipment Intangible-intensive ICT-using Manufacturing13 Furniture and other manufacturing Non-intangible Non-ICT Manufacturing14 Electricity, gas and water supply Non-intangible Non-ICT Non-manufacturing15 Construction Non-intangible Non-ICT Non-manufacturing16 Wholesale and retail trade Non-intangible Non-ICT Non-manufacturing17 Restaurants and hotels Non-intangible Non-ICT Non-manufacturing18 Transport and storage Non-intangible Non-ICT Non-manufacturing19 Financial intermediation Intangible-intensive ICT-using Non-manufacturing20 Real estate and renting Non-intangible Non-ICT Non-manufacturing21 Information and communication Intangible-intensive ICT-producing Non-manufacturing22 Business services Intangible-intensive ICT-using Non-manufacturing23 Public administration and defense Non-intangible ICT-using Non-manufacturing24 Education Non-intangible ICT-using Non-manufacturing25 Health and social work Non-intangible Non-ICT Non-manufacturing26 Culture and entertainment Non-intangible ICT-using Non-manufacturing27 Other service activities Non-intangible Non-ICT Non-manufacturing

Notes: Information and communication (21) includes telecommunications, broadcasting, publishing, movies,music and information services.



73

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74

Final version accepted 14 July 2015.

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