1. KLEMS Database Including Intangible Assets and Productivity Analysis 2 nd Asia KLEMS Conference at Seoul (July 5, 2012) Kyoji Fukao (Hitotsubashi University and RIETI) Tsutomu Miyagawa (Gakushuin University and RIETI) Joji Tokui (Shinshu University and RIETI) 1

2. Contents 1.Features of the KLEMS Model 2.Extension of the KLEMS Model 3.Measurement of Intangible Investment at the Aggregate Level 4. Growth Accounting with Intangibles 5. An Empirical Analysis Using Industry-Level Data 6. Studies on Intangible Assets at the Firm Level 7. Concluding Remarks 2

3. 1. Features of the KLEMS Model (1)Standardized method by Jorgenson and Griliches (1967)→International comparison of productivity growth (2)Measurement of productivity by industry→Specifying low productivity sectors and examining resource reallocation between sectors 3

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5. Korea and Japan experienced relatively higher TFP growth in the IT-producing sector. The problem for Japan is that TFP growth in IT- using service sectors, such as distribution services (retail, wholesale and transportation) and in the rest of the manufacturing sector (i.e., excluding electrical machinery), declined substantially after 1995. The US experienced an acceleration in TFP growth in IT-using sectors. 5 1. Some Results of Sectoral TFP Analysis

6. Japan’s IT investment-GDP ratio in IT-using service sectors, such as distribution services and in the rest of the manufacturing sector is very low in comparison with other major developed economies. Source: EU KLEMS 2009. 6

7. International collaboration for the creation of a KLEMS type database made this kind of cross-country comparisons possible for the first time. 7

8. 2. An Extension of KLEMS Model However, the conventional KLEMS database does not provide enough information for productivity growth in advanced countries after the Information and Communication Technology (IT) Revolution. The IT Revolution started in the 1990s. Since the mid 1990s, many US firms have pioneered new businesses utilizing IT (such as Amazon. com., Google, etc.). This new wave of businesses accelerated US productivity growth and boosted the US economy (Oliner and Sichel (2000) and Jorgenson (2001)). The major EU countries and Japan tried to catch up with the US economy. However, the productivity gap still exists between the US and other advanced countries (van Ark (2004) and Inklaar, Timmer, and van Ark (2007)).

10. 2. The Extension of KLEMS Model (cont’d) The Economic Report of the President in the US in 2007 stated “Only when they made intangible investments to complement their IT investments did productivity growth really take off.” Based on the above discussion, Corrado, Hulten and Sichel (2009) (hereafter we refer to as CHS) measured intangible investment in the US and conducted growth accounting including intangible assets. Many economists in advanced countries such as Australia, Canada, France, Germany, Italy, Japan, Korea, Netherlands, Spain, the UK measured the aggregate intangible investment following CHS →http://www.intan- invest.net.

11. 3. The Measurement in Intangible Investment at the Aggregate Level Japanese case (Fukao, et, al. (2009) ): 1. Computerized information Software and databases → IO tables, Survey on Selected Service Industries, IT Workplace Survey, etc. 2. Innovative property Scientific and nonscientific R&D, mineral exploitation, copyright and license costs, and other product development, design, and research expenses → Japan Industrial Productivity (JIP) Database, Survey of Research and Development, etc. 3. Economic competencies Brand equity, firm-specific human capital, and organizational structure → JIP Database, The General Survey on Working Conditions, and Financial Statements Statistics of Corporations by Industry

12. 3. The Measurement in Intangible Investment at the Aggregate Level (contd.) Annual intangible investment in Japan was on average 53 trillion yen from 2000 to 2005. The ratio of intangible investment to GDP in Japan was 11.1%, smaller than the estimate for the US by CHS (2009) and for the UK by Marrano, Haskel and Wallis (2009). While investment in computerized information and innovative property in Japan was as high as in the US and the UK, investment in economic competencies (especially firm-specific human capital and organizational change) was much lower.

15. 3. The Measurement in Intangible Investment at the Aggregate Level (contd.) Why has Japan’s intangible investment ratio to GDP stagnated in the 2000s? Preliminary answers: (1)The lower share of firm-specific human capital and organizational change: Japanese firms reduced training expenses and remuneration for executives as part of restructuring measures. (2)The effects of Japan’s financial system, where banks play a central role: Because banks require collateral to provide funds to firms, Japanese firms tend to accumulate tangible assets.

16. 3-3. The Contribution of Intangible Assets to the Aggregate Economic Growth We construct data of intangible assets in Japan by accumulating intangible investment. Intangible capital in 2005 accounts for 200 trillion yen Assets in innovative property dominate over 50% of the total intangible capital. Growth rate in intangible capital has declined. Especially, growth in firm-specific human capital turned negative after 1995 due to the hard restructuring.

18. 4. Growth Accounting with Intangibles ・ The growth accounting framework including intangible assets is as follows: A production function with intangibles (1) Y:value added, K:tangible capital, Z:intangible capital, L:labor input, A:TFP National accounting identity (2)

19. 4. Growth Accounting with Intangibles (contd.) We assume a one goods economy. Then, Revising conventional GDP measure, growth accounting with intangibles is expressed as follows. (3) (4)

20. 4. Growth Accounting with Intangibles (contd.) 1. The contribution of intangible capital accumulation to labor productivity has declined since 1990. 2. When we compare the results in growth accounting between Japan and the US, we find that the gap in labor productivity growth between two countries can be explained by the difference in intangible capital deepening. 3.If intangible capital deepening in Japan was as large as in the US, Japanese productivity growth would catch up with the US. 4.In Korea, the contribution of intangible assets as well as that of tangible assets is larger than that of Japan.

22. 5. An Empirical Analysis Using Industry- Level Data Although growth accounting approach showed the contribution of intangible assets to economic growth, it did not explain the effect of intangibles on traditional TFP growth. Aggregate data of intangibles do not provide enough samples for empirical analysis.→measurement of intangible investment at the industry level. Chun, Fukao, Hisa, and Miyagawa (2012): Based on a similar framework to CHS and Fukao et, al. (2009), intangible investment in 27 industries (in the case of Japan 108 industries) was estimated.

23. 5. An Empirical Analysis Using Industry- Level Data (contd.) The JIP database (and the KIP database) is very useful for measuring intangible investment by industry. Some components of intangible assets are treated as intermediate inputs→We are able to measure intangible investment by industry by using I-O table in the JIP database The JIP Database can be found at: http://www.rieti.go.jp/jp/database/JIP2011/index.h tml

25. 5. An Empirical Analysis Using Industry- Level Data (contd.) Using industry-level data, we examine the effect of intangible investment on productivity growth. In this case, we assume the following production function. (5) (6)

26. 5. An Empirical Analysis Using Industry- Level Data (contd.) From Equation (5) and (6), we obtain the following equation which we will estimate. (7)  Z is the gross private return of intangible assets. Dependent variable: TFP growth Independent variable: intangible investment calculated by Chen et, al. (2012). Estimation method: IV (instrumental variables: ratio of highly educated workers, cash flow ratio, 2 years lagged variable of intangible investment ratio).

27. 5. An Empirical Analysis Using Industry- Level Data (contd.) Estimation Results (1)Market economy: Intangible investment contributed to productivity growth. However, in the estimation after the IT revolution, we do not find significant evidence of the effect of intangible investment on productivity growth. (2)IT industries: Similar results to those in the market economy→Complementarity between IT and intangibles is partly found. (3)Non IT industries: As for the investment in economic competencies and computerized information, we find a significant effect of intangible investment on productivity growth.

31. 5. An Empirical Analysis Using Industry- Level Data (contd.) Estimated  Z in the market economy is 3.9% which is almost equal to the average real rate of return in the period from 1982 to 2008 (3.7%). However, it is lower than the gross rate of return (25.7%). Estimated rate of return in IT industry is also lower than the gross rate of return.

32. 5. An Empirical Analysis Using Industry- Level Data (contd.) However, Jones and Williams (1998) pointed out that the estimated rate of return in Equation (7) is biased when we assume endogenous economic growth. When we replace Equation (6) with the following equation, considering spillover effect of past knowledge. (8) Log linearizing (8) around the balanced growth path, we get (9)

33. 5. An Empirical Analysis Using Industry- Level Data (contd.) The revised estimation improved estimation results. In the market economy, the rate of return on intangible assets increased. In the estimation of IT industries, we find the effect of intangible investment on productivity growth after the IT revolution as well as before the IT revolution. The complementarity between IT and intangible investment is confirmed.

34. 5. An Empirical Analysis Using Industry- Level Data (contd.) The rate of return on intangible assets in IT industry after the IT revolution is higher than gross rate of return. Policy implication: If the government wants to make IT industries grow, it has to support not only investment in IT equipment but also intangible investment.

38. 6. Studies on Intangible Assets at the Firm Level Measurement issues of CHS (1)On-the-job training is not included in the measurement of investment in firm-specific resources employed CHS (2009). However, Japanese firms often utilize on-the-job training to accumulate firm-specific human capital. (2)The gap in expenditure on organizational structure between the US and Japan may reflect the difference in remuneration of executives in both countries.

40. 6. Studies on Intangible Assets at the Firm Level (cont’d) We do not have reliable data on organizational structure and firm-specific human capital which affect the differences in intangible investment between advanced countries or industries. To overcome this difficulty, many researchers have focused on the measurement in intangibles at the firm level.→the measurement of intangibles using market value.

41. 6. Studies on Intangible Assets at the Firm Level (cont’d) Market value approach: Utilizing the information representing market value, researchers estimate the value of intangible assets. The market value of firm i (V it ) with multiple assets (including intangible assets) is expressed as follows; (12) K: tangible asset, Z: intangible asset

42. 6-3. Intangible Assets and Firm Values (cont’d) In a neoclassical framework, (J=K or Z) is 1 and after tax rate of return of each asset is equalized. In this framework, McGrattan and Prescott (2005) and Arato and Yamada (2012) estimated intangible assets. Their estimates of intangible assets are larger than those by CHS and Fukao, et, al. (2009). Our estimates using DBJ data and CHS approach are similar to McGrattan and Prescott (2005) and Arato and Yamada (2012).→market evaluates unmeasured intangible assets or scale effects?

44. 7. Concluding Remarks A summary of our discussion (1)KLEMS database is very useful for international comparison of productivity growth and studying resource reallocation. (2)We have to consider intangible assets in KLEMS database to study productivity growth after the IT revolution. (3)The conventional industry classification is not useful for productivity analysis after the IT revolution. We need the revised industry classification which captures features of new businesses after the IT revolution.

45. 7. Concluding Remarks (contd.) (4) In the IT industries, we find the positive contribution of intangible investment to productivity growth. (5) The above result show that the revised industry classification provides new policy implication for enhancing productivity in IT industries (6) However, we have to check plausibility of the measurement of intangible capital in industry- level database by using firm-level data.

46. References Arato, H. and K. Yamada (2012), “Japan’s Intangible Capital and Valuation of Corporations in a Neoclassical Framework,” Review of Economic Dynamics forthcoming. Barnes, P and A. McClure (2009), Investments in Intangible Assets and Australia’s Productivity Growth, Productivity Commission Staff Working Paper. Chun, H., K. Fukao, S. Hisa, and T. Miyagawa (2012), “ Measurement of Intangible Investment by Industry and Its Role in Productivity Improvement Utilizing Comparative Studies between Japan and Korea” RIETI Discussion Paper Series 12-E-037. Corrado, C., C. Hulten, and D. Sichel.(2009), “ Intangible Capital and U.S. Economic Growth.” Review of Income and Wealth 55, pp. 658-660. Fukao, K., T. Miyagawa, K. Mukai, Y. Shinoda, and K. Tonogi. (2009),” Intangible Investment in Japan: Measurement and Contribution to Economic Growth”. Review of Income and Wealth 55, pp.717-736.

47. References Fukao, K., T. Miyagawa, H. Pyo, and K. Rhee (2012) “Estimates of Total Factor Productivity: the Contribution of ICT and Resource Reallocation Effects in Japan and Korea,” in M. Mas and R. Stehler eds., Industrial Productivity in Europe growth and Crisis, Edward Elgar. Jones, C. and J. Williams (1998), “Measuring the Social Return to R&D” Quarterly Journal of Economics, 113, pp. 1119-1135. Inklaar, R., M. Timmer, and B. van Ark (2007), “Mind the Gap! International Comparisons of productivity in Services and Goods Production’ German Economic Review 8, pp. 281-307. Jorgenson, D. (2001), “Information Technology and the U.S. Economy,” American Economic Review 91, pp. 1-32. Marrano, M, J. Haskel, and G. Wallis (2009), What Happened to the Knowledge Economy? ICT, Intangible Investment, and Britain’s Productivity Revisited,” Review of Income and Wealth 55, pp. 661-716. McGrattan, E. and E. C. Prescott (2005) “Taxes, Regulations, and the Value of U.S. and U.K. Corporations” Review of Economic Studies 72, pp. 767-796.

48. References Oliner, S. and D. Sichel (2000), “The Resurgence of Growth in the Late 1990s: Is Information Technology the Story?,” Journal of Economic Perspectives, 14, pp. 3-22. Pyo, Hak, K., Hyunbae Chun, and Keun Hee Rhee (2010), “The Productivity Performance in Korean Industries (1990-2008): Estimates from KIP Database,” presented at RIETI/G-COE Hi-Stat International Workshop on Establishing Industry Productivity Database fro China, India, Japan and Korea Van Ark, B. 2004. “The Measurement of Productivity: What Do the Numbers Mean?” in Fostering Productivity, in G. Gelauff, L. Klomp, S. Raes, and T. Roelandt (eds), Elsevier, pp. 29-61.

49. Thank you for your attention!