INTANGIBLE INVESTMENT IN JAPAN: MEASUREMENT AND CONTRIBUTION TO ECONOMIC GROWTH

Review of Income and WealthVolume 55, Issue 3 p. 717-736 Free Access INTANGIBLE INVESTMENT IN JAPAN: MEASUREMENT AND CONTRIBUTION TO ECONOMIC GROWTH Kyoji Fukao, Kyoji Fukao Hitotsubashi University and RIETISearch for more papers by this authorTsutomu Miyagawa, Corresponding Author Tsutomu Miyagawa Gakushuin University and RIETI *Tsutomu Miyagawa, Faculty of Economics, Gakushuin University, 1-5-1, Mejiro, Toshima-ku, Tokyo, 171-8588, Japan ([email protected]).Search for more papers by this authorKentaro Mukai, Kentaro Mukai Cabinet Office, Government of JapanSearch for more papers by this authorYukio Shinoda, Yukio Shinoda Cabinet Office, Government of JapanSearch for more papers by this authorKonomi Tonogi, Konomi Tonogi Hitotsubashi University and Cabinet Office, Government of JapanSearch for more papers by this author Kyoji Fukao, Kyoji Fukao Hitotsubashi University and RIETISearch for more papers by this authorTsutomu Miyagawa, Corresponding Author Tsutomu Miyagawa Gakushuin University and RIETI *Tsutomu Miyagawa, Faculty of Economics, Gakushuin University, 1-5-1, Mejiro, Toshima-ku, Tokyo, 171-8588, Japan ([email protected]).Search for more papers by this authorKentaro Mukai, Kentaro Mukai Cabinet Office, Government of JapanSearch for more papers by this authorYukio Shinoda, Yukio Shinoda Cabinet Office, Government of JapanSearch for more papers by this authorKonomi Tonogi, Konomi Tonogi Hitotsubashi University and Cabinet Office, Government of JapanSearch for more papers by this author First published: 20 August 2009 https://doi.org/10.1111/j.1475-4991.2009.00345.xCitations: 95 Note: We would like to thank the anonymous referees for valuable suggestions that helped to substantially improve our paper. We also thank Dr. Paul Schreyer of the OECD, Dr. Carol Corrado of the Conference Board, Professor Jonathan Haskel of Queen Mary University of London, and the participants of the OECD workshop on the Measurement of Intellectual Assets in National Accounts, the 2007 NBER/CRIW Summer Institute, and the National Academies conference on Intangible Assets for their excellent comments. We are grateful to Professors Bart van Ark and Marcel Timmer of the University of Groningen and Mr. Yoshiaki Tojo of the OECD for valuable comments on earlier drafts. Thanks are also due to Mr. Takayuki Sumita of the Ministry of Economy, Trade and Industry and participants of the seminar at the Research Institute of Economy, Trade, and Industry (RIETI). We appreciate the excellent research assistance provided by Mr. Sumio Hamagata (Central Research Institute of Electric Power Industry), Dr. Shoichi Hisa (Hitotsubashi University), and Professor Miho Takizawa (Toyo University). The views expressed in this paper are those of authors and should not be attributed to any of the organizations to which the authors belong. AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Following the approach of Corrado, Hulten, and Sichel (2005, 2006), we measure intangible investment and examine the contribution of intangible capital to economic growth in Japan. We find that the ratio of intangible investment to GDP in Japan has risen during the past 20 years and now stands at 11.1 percent, which is lower than the ratio estimated for the U.S. in the early 2000s. The ratio of intangible to tangible investment in Japan is also lower than equivalent values estimated for the U.S. In addition, we find that, in stark contrast to the U.S., where intangible capital grew rapidly in the late 1990s, the growth rate of intangible capital in Japan declined from the late 1980s to the early 2000s. Our conclusions regarding intangible investment in Japan remain largely unchanged even if, using data with respect to firm-specific resources, we take on-the-job training into account. 1. Introduction In the 1990s, the United States enjoyed rapid rates of productivity growth. A major contributing factor was the revolution in information and communication technology (ICT). The resurgence of U.S. productivity growth led governments of other developed countries such as the U.K., Germany, France, the Netherlands, and Japan to promote ICT investment in order to catch up with U.S. productivity levels. In Japan, ICT investment has shown steady growth, increasing at an annual average rate of 8.6 percent from 1995 to 2005 and reaching 23.5 trillion yen in 2005 (in 2000 constant prices), which is equivalent to 18 percent of total investment. Yet, the increase in ICT investment in Japan so far has failed to close the productivity gap with the U.S.1 Examining the reasons for the productivity gap, we find that a major factor is the low multi-factor productivity (MFP) growth in services that use ICT, such as distribution services, finance and business services, etc., as shown in Table 1. The table also indicates that in the case of the European Union (EU) countries, too, the productivity gap vis-à-vis the U.S. is due to the low productivity growth in ICT-using services. Table 1. MFP Growth and Share in Total Hours Worked by Sector, Major Developed Economies (%) 1995–2005 MFP Growth Average Share in Total Hours Worked Japan U.S. France Germany Italy U.K. Japan U.S. France Germany Italy U.K. Market economy total 0.5 1.7 0.8 0.4 −0.7 0.9 100.0 100.0 100.0 100.0 100.0 100.0 Electrical machinery, post and communication 5.4 8.7 5.9 4.7 2.7 3.7 5.0 4.3 4.5 5.1 3.7 4.9 Manufacturing, excluding electrical −0.7 2.2 1.8 1.3 −1.2 0.8 19.4 15.7 18.3 23.4 22.4 18.0 Other goods producing industries 0.0 −0.3 0.7 1.4 −0.1 0.1 20.0 14.3 19.2 15.6 16.6 13.9 Distribution services 0.9 2.1 0.4 1.5 −0.9 1.1 26.2 27.1 24.2 25.8 26.2 26.7 Finance and business services −0.1 0.4 −0.8 −3.3 −0.4 1.1 12.8 21.2 21.1 17.3 13.7 23.0 Personal and social services −0.1 0.0 0.9 −0.7 −2.0 −0.7 16.6 17.4 12.8 12.7 17.4 13.5 Source: EU KLEMS Database, March 2008. Examining the slow productivity growth in EU countries, van Ark (2004) suggested that the difference with the U.S. might be explained by differences in the accumulation of intangible assets which play a complementary role to ICT capital. Studies that have addressed the role of intangible assets include those by McGrattan and Prescott (2005), who took intangible investment at the macro level into account in order to explain the solid growth of the U.S. economy during the 1990s, and Corrado, Hulten, and Sichel (2005, 2006), who measured intangible investment in the U.S. and showed the significant contribution of intangible capital to U.S. productivity growth. The aim of this paper is to measure intangible investment and to examine its contribution to economic growth in Japan. We have two reasons for focusing on the measurement of intangible investment. The first is that we want to check whether trends in intangible investment can explain the productivity gap between the U.S. and Japan in the 1990s. The second is that to date practically no studies have been carried out on intangible capital in Japan. The Japanese government has made an acceleration of economic growth the cornerstone of its economic policy, and given the economic challenges facing Japan, it is crucial to understand why productivity growth has lagged behind that in the U.S. The role of intangible capital potentially is one key factor, and understanding if and why this is the case may make an important contribution to policy design. Our paper consists of four sections. In the next section, we estimate time series of intangible investment following the methodology developed by Corrado, Hulten, and Sichel (2005, 2006). We find that the ratio of intangible to tangible assets is lower in Japan than in the U.S. We also estimate intangible investment by sector and find that the intangible investment/value added ratio in the service sector is much lower than that in the manufacturing sector. In Section 3, we construct intangible capital by using the intangible investment series and conduct a growth accounting exercise. The results of the growth accounting with intangible capital show that the contribution of intangible capital to economic growth is small because the share of intangible capital in total capital is also relatively small. However, this result does not mean that the potential role of intangible capital is not important for economic growth. If intangible capital in Japan were to contribute to economic growth at the same rate as it does in the U.S., labor productivity growth in Japan would be 0.3 percentage points higher than it actually is. In Section 4, we conduct a sensitivity analysis focusing on the parameters used for estimating investment in firm-specific resources. We find that when we take Japanese data concerning firm-specific human resources and organizational structure into account, the intangible investment/GDP ratio is higher than that estimated in the base case. On the other hand, the effect of intangible capital deepening becomes smaller than that estimated in the base case, because the growth in firm-specific human capital in the alternative case is slower than that estimated in the base case. The final section summarizes our results and their policy implications, and discusses future tasks. 2. Measurement of Intangible Investment in Japan In this section, we describe how we measure intangible investment in Japan and look at the major trends in intangible investment. In order to measure intangible investment, we follow the approach of Corrado, Hulten, and Sichel (2005, 2006) (abbreviated as CHS hereafter), who classify intangibles into three major types of assets: computerized information, innovative property, and economic competencies. Computerized information consists of, for example, software and databases. Innovative property includes scientific and non-scientific research and development (R&D), where the latter refers to, for example, mineral exploitation, copyright and license costs, and other product development, design, and research expenses. Economic competencies, finally, include brand equity, firm-specific human capital, and organizational structure. 2.1. Computerized Information We take data on investment in computerized information from the 2008 version of the Japan Industrial Productivity Database (JIP Database).2 This database was constructed by us and other economists and provides data on the output, intermediate input, and labor and capital input of 108 industries from 1970 to 2005. In the JIP 2008 Database, investment in custom software and packaged software is estimated using sales data for the information service industry from the Survey on Selected Service Industries and data from the Input–Output Tables. The Survey on Selected Service Industries is conducted annually by the Ministry of Economy, Trade, and Industry (METI) and includes information on the sales, number of workers, assets, operating costs, and year of establishment of about 7000 firms in the service sector, including the information service industry. We measure in-house software investment using the ICT Workplace Survey and the Population Census. The ICT Workplace Survey, which is also conducted annually by METI, provides information on enterprises and organizations which heavily use ICT equipment with regard to their labor costs, other expenditure, and number of employees categorized by job type such as programmers, systems engineers, and network managers. As the ICT Workplace Survey does not cover all workers who are involved in making in-house software in Japan, we employ the following estimation procedures. From this survey, we take two types of costs: the first is wages for workers in divisions which are specialized in in-house software development; and the second is costs for hiring temporary workers for making in-house software in these divisions. Using these values, we calculate the cost of in-house software investment per engineer and programmer. We then multiply the result by the total number of engineers and programmers in the market economy, which is available from the Population Census, and derived in-house software investment in the market economy. The estimates for in-house software investment we arrive at are largely consistent with those obtained by Nomura (2005). Finally, investment in databases is estimated using sales data for the information service industry from the Survey on Selected Service Industries and data from the Establishment and Enterprise Census. 2.2. Innovative Property For data on investment in science and engineering R&D, we use the Survey of Research and Development. The Survey of Research and Development is conducted by the Ministry of Internal Affairs and Communications and includes information on research expenditures categorized by several types of research expenses such as material costs, labor costs, and depreciation costs for about 19,000 enterprises, universities, and research institutions. We use the expenses on materials and labor costs for R&D activities from this survey as our data on investment in science and engineering R&D. Data on investment in mineral exploitation were obtained from the Handbook of the Mining Industry and the Annual Report on Natural Gas. Next, for copyright and license costs, we take data from the JIP 2008 Database, using the nominal output data of JIP 2008 industry no. 92 (publishing and newspaper industry; it corresponds to ISIC codes 2211, 2212, and 2213) and JIP 2008 industry no. 93 (video picture, sound information, character information production, and distribution industry; it corresponds to ISIC code 9211).3 Nominal output in the JIP Database is based on the Input–Output Tables constructed by the Ministry of Internal Affairs and Communications. Relatively reliable, the Input–Output Tables are published every five years. Fukao et al. (2007) constructed annual nominal output series using the Linked IO Tables published by the Ministry of Internal Affairs and Communications, the Extended IO Tables published by the Ministry of Economy, Trade and Industry, and the SNA IO Tables published by the Cabinet Office. For the measurement of other product development, design, and research expenses, CHS (2005) summed the following three items: (1) new product development costs in financial services and other service industries such as book publishing, motion picture production, sound recording production, and broadcasting; (2) new architectural and engineering designs which roughly account for half of industry purchased services (CHS (2005) estimated this value from the revenues of architectural and engineering design industries reported in the Census Bureau's Services Annual Survey); and (3) R&D in social sciences and humanities which is estimated as twice industry purchased services to include own-account expenses on R&D in social sciences and humanities (this item is also estimated from the revenues of the Census Bureau's Services Annual Survey). Here, we estimate investment in (1) by focusing on new product development costs in financial services, because we do not have any reliable data for estimating new product development costs in other service industries. Using data on intermediate purchases in JIP 2008 industries no. 69 (finance industry; it corresponds to ISIC codes 6511, 6519, 6592, 6599, 6711, 6712, and 6719) and no. 70 (insurance industry; it corresponds to ISIC codes 6601, 6603, and 6720), we count 20 percent for intermediate costs in financial services as investment in new product development. To measure investment in (2), we use the nominal output data of the design, display, and machinery design industries from the Input–Output Tables as investment in new architectural design, while for investment in engineering design, we use data from METI's Survey on Selected Service Industries. We are unable to find suitable data for (3). 2.3. Economic Competencies With regard to investment in brand equity, we follow the approach adopted by CHS (2005), taking 60 percent of the nominal output purchased by other industries from the advertising industry (JIP 2008 industry no. 85; it corresponds to ISIC code 7430). Firm-specific human capital is accumulated through both on-the-job and off-the-job training. Following CHS (2005), we only estimate off-the-job training costs here and assume that these costs consist of two types of expenses: (1) direct firm expenses for off-the-job training of employees; and (2) opportunity cost (the wage and salary costs of employees' time spent in getting off-the-job training). In our sensitivity analysis in Section 4, we estimate on-the-job training costs and examine how our results on Japan's intangible investment change when such costs are included. For the first item, direct firm expenses, we use data on vocational education costs per worker from the General Survey on Working Conditions (Shugyo Joken Sogo Chosa) conducted by the Ministry of Health, Labour and Welfare. The purpose of this survey is to statistically review the wage system, fringe benefits, and retirement system of Japanese firms. It covers about 5,000 Japanese firms and asks them about training costs, including the wage and salary costs of employees who teach workers in an off-the-job mode or employees who support the off-the-job training processes. For the second item, opportunity cost, we use the results obtained by Ooki (2003). Using micro-data of the Japan Institute for Labour Policy and Training's Survey on Personnel Restructuring and Vocational Education/Training Investment in the Age of Performance-Based Wage Systems (Gyoseki-shugi Jidai no Jinji Seiri to Kyoiku/Kunren Toshi ni Kansuru Chosa), Ooki calculated the average opportunity cost ratio of off-the-job training to direct firm expenses for training in 1998 for the whole business sector. The value was 1.51. We use this value to estimate the opportunity cost. CHS (2005) argue that investment in organizational structure consists of a purchased “organizational” or “structural” component (such as management consultant fees) and an own-account component, which can be measured in terms of the value of executive time. With regard to the first component, CHS (2005), Giorgio Marrano and Haskel (2006), and Giorgio Marrano et al. (2007) use sales data for consulting firms. However, we are not able to find suitable data for the consulting industry in Japan. For the measurement of the second component, own-account investment in organizational structure, we use the Survey on Financial Statements of Business Enterprises. This survey is conducted annually by the Ministry of Finance and gathers the financial statements of enterprises whose capital is above 2 million yen. Following CHS (2005), we approximate this component by taking 20 percent of the salaries and bonuses for executives from this survey. 2.4. Measurement Results for Intangible Investment in Japan Our measurement results are shown in Table 2. Our estimates suggest that the annual average amount of intangible investment in Japan from 2000 to 2005 was 53 trillion yen. The share of intangible investment in GDP in the same period was 11.1 percent, which is similar to the estimate for the U.S. by CHS (2006) and larger than that for the U.K. by Giorgio Marrano and Haskel (2006). However, the figure for the U.S. obtained by CHS (2006) is for the period from 1998 to 2000, and more recent, but as yet unpublished estimates by Dr. Corrado suggest that the intangible investment/GDP ratio in the U.S. in the early 2000s had reached 13.8 percent, meaning that the equivalent ratio for Japan is lower than that for the U.S. While the investment/GDP ratios for computerized information and innovative property are larger than those estimated for the U.S. and the U.K., the GDP ratio of economic competencies is much smaller than those estimated for the U.S. and U.K. due to the low GDP ratio of investment in firm-specific human capital and organizational structure. However, it should be noted that our measurement of intangible investment in Japan is likely to be an underestimation due to the lack of reliable data for the estimation of investment in other product development, design, and research, firm-specific human capital, and organizational structure. Table 2. Intangible Investment by Category: Comparison among Japan, the U.S., and the U.K. Japan2000–05 U.S.CHS (2006)1998–2000 U.K.MH (2006)2004 (billion yen) GDP Share (billion U.S. dollars) GDP Share (billion pounds) GDP Share Computerized information 10,803 2.2 154 1.7 19.8 1.7 Custom software 6,584 1.4 1511 1.61 7.52 0.62 Packaged software 848 0.2 In-house software 2,332 0.5 12.43 1.13 Databases 1,039 0.2 3 0.0 Innovative property 28,629 6.0 425 4.6 37.6 3.2 Science and engineering R&D 13,690 2.8 184 2.0 12.4 1.1 Mineral exploitation 16 0.0 18 0.2 0.4 0.0 Copyright and license costs 5,161 1.1 75 0.8 2.4 0.2 Other product development, design, and research expenses 9,761 2.0 149 1.6 22.4 1.9 Economic competencies 13,764 2.9 505 5.4 58.8 5.0 Brand equity 5,534 1.2 140 1.5 11.1 1.0 Firm-specific human capital 2,241 0.5 3654 3.94 28.5 2.4 Organizational structure 5,988 1.2 19.2 1.6 Total 53,197 11.1 1,085 11.7(13.8)5 116.2 10.0 Intangible investment/tangible investment 0.6 1.2(1.1)5 1.1 Notes: 1 Figures include not only custom software but also packaged software and in-house software. 2 Figures include not only custom software but also packaged software. 3 Figures include not only in-house software but also databases. 4 Figures include not only firm-specific human capital but also organizational structure. 5 Figures in parentheses indicate estimates for the period from 2000 to 2003. Source: Japan: authors' calculations; U.S.: Corrado, Hulten and Sichel (2006); U.K.: Giorgio Marrano and Haskel (2006). Moreover, comparing the relative levels of intangible and tangible investment in Japan and the U.S., other significant differences emerge. For example, CHS (2006) found that in the U.S., intangible investment was 1.2 times the level of tangible investment. However, according to our estimation, the ratio of intangible to tangible investment in Japan was only 0.6. Given that the share of intangible investment in GDP in Japan is similar to that in the U.S., the low ratio of intangible to tangible investment in Japan indicates not that investment in intangibles is small, but that investment in tangibles is exceptionally large. Figure 1 shows the ratios of tangible and intangible investment to GDP in Japan and the U.S. We find that in Japan, the GDP ratio of intangible investment is still much smaller than that of tangible investment, while in the U.S., intangible investment has exceeded tangible investment since 2000.We suspect that the difference in investment behavior between Japan and the U.S. is at least partially due to differences in the financial system. In Japan, financial institutions such as banks play a major role in the provision of corporate funds, and they typically require tangible assets as collateral to provide financing. As a result, Japanese firms have preferred to accumulate tangible assets which can be used as collateral. In addition, small firms have been hampered in their growth because they often possess insufficient tangible assets to increase borrowing. These mechanisms as a result of Japan's financial system are likely to be important reasons why the ratio of intangible to tangible investment is low in Japan.4 Figure 1Open in figure viewerPowerPoint Business Investment (Percentage of Business Output)Source: Authors' calculation. The share of each type of intangible investment is shown in Table 3. The largest component of intangible investment in Japan is innovative property with a share of nearly 54 percent in the early 2000s. The share of computerized information has increased during the past 20 years. Table 4 presents the ratio of intangible investment to GDP by category. The table shows that all categories contributed to the increase in the ratio of total intangible investment to GDP. Table 3. Intangible Investment by Category: Share in Total Intangible Investment (%) Japan U.S. U.K. 1980–89 1980–84 1985–89 1990–99 1990–94 1995–99 2000–05 1998–2000 2004 Computerized information 10.4 8.1 12.7 16.9 15.7 18.1 20.4 14.2 17.0 Custom software 5.2 4.0 6.5 8.7 7.7 9.8 12.4 6.52 Packaged software 0.5 0.4 0.6 0.8 0.8 0.8 1.6 13.91 In-house software 3.6 2.8 4.5 5.9 5.9 6.0 4.5 10.73 Databases 1.0 0.9 1.1 1.5 1.3 1.6 1.9 0.3 Innovative property 56.5 56.5 56.6 53.8 54.6 53.1 53.7 39.2 32.4 Science and engineering R&D 25.3 25.3 25.2 25.1 24.8 25.4 25.5 17.0 10.7 Mineral exploitation 0.1 0.2 0.1 0.1 0.1 0.1 0.0 1.7 0.3 Copyright and license costs 10.7 10.7 10.6 10.4 10.5 10.2 9.8 6.9 2.1 Other product development, design, and research expenses 20.5 20.2 20.7 18.3 19.1 17.5 18.4 13.7 19.3 Economic competencies 33.0 35.4 30.7 29.2 29.7 28.8 26.0 46.5 50.6 Brand equity 9.8 10.7 8.9 9.7 9.2 10.2 10.3 12.9 9.6 Firm-specific human capital 8.3 8.3 8.3 6.5 7.2 5.7 4.3 33.64 24.5 Organizational structure 14.9 16.4 13.5 13.1 13.4 12.8 11.3 16.5 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Notes: 1 Figures include not only custom software but also packaged software and in-house software. 2 Figures include not only custom software but also packaged software. 3 Figures include not only in-house software but also databases. 4 Figures include not only firm-specific human capital but also organizational structure. Source: Japan: authors' calculations; U.S.: Corrado, Hulten and Sichel (2006); U.K.: Giorgio Marrano and Haskel (2006). Table 4. The Ratio of Intangible Investment to Value Added: by Category and Year (%) Japan 1980–89 1980–84 1985–89 1990–99 1990–94 1995–99 2000–05 Computerized information 0.8 0.6 1.1 1.6 1.4 1.8 2.2 Custom software 0.4 0.3 0.5 0.8 0.7 1.0 1.4 Packaged software 0.0 0.0 0.1 0.1 0.1 0.1 0.2 In-house software 0.3 0.2 0.4 0.6 0.5 0.6 0.5 Databases 0.1 0.1 0.1 0.1 0.1 0.2 0.2 Innovative property 4.3 3.9 4.7 5.1 5.0 5.3 6.0 Science and engineering R&D 1.9 1.7 2.1 2.4 2.3 2.5 2.8 Mineral exploitation 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Copyright and license costs 0.8 0.7 0.9 1.0 1.0 1.0 1.1 Other product development, design, and research expenses 1.6 1.4 1.7 1.7 1.8 1.7 2.0 Economic competencies 2.8 2.8 2.9 3.2 3.1 3.2 3.4 Brand equity 0.7 0.7 0.7 0.9 0.8 1.0 1.1 Firm-specific human capital 0.6 0.6 0.7 0.6 0.7 0.6 0.5 Organizational structure 1.1 1.1 1.1 1.2 1.2 1.3 1.2 Total 7.6 6.9 8.3 9.6 9.2 9.9 11.1 Source: Authors' calculations. 2.5. Intangible Investment by Sector As discussed in Section 2.1, our measurement of intangible investment mainly relies on the JIP 2008 Database. Because this database includes data on output, intermediate input, labor input, and capital services in 108 industries, we are able to measure intangible investment by sector. Table 5 shows intangible investment in the manufacturing sector and the service sector.5 Table 5. Intangible Investment by Category in the Manufacturing Sector and the Service Sector Manufacturing Sector Service Sector 2000–05(billion yen) Ratio to Value Added (%) 2000–05(billion yen) Ratio to Value Added (%) Computerized information 2,447 (2.1) 6,125 (2.4) Custom software 1,526 (1.3) 4,197 (1.6) Packaged software 184 (0.2) 388 (0.1) In-house software 510 (0.4) 1,065 (0.4) Databases 226 (0.2) 475 (0.2) Innovative property 13,316 (11.5) 9,161 (3.6) Science and engineering R&D 9,312 (8.0) 1,052 (0.4) Mineral exploitation 0 (0.0) 16 (0.0) Copyright and license costs 472 (0.4) 4,152 (1.6) Other product development, design, and research expenses 3,531 (3.0) 3,940 (1.5) Economic competencies 3,579 (3.0) 8,364 (3.2) Brand equity 1,876 (1.6) 3,477 (1.3) Firm-specific human capital 584 (0.5) 1,334 (0.5) Organizational structure 1,120 (0.9) 3,553 (1.4) Total 19,342 (16.6) 24,577 (9.2) Intangible investment/tangible investment 0.8 0.5 Source: Authors' calculations. In Table 5, we find that intangible investment in the service sector is larger than that in the manufacturing sector. However, as for the r