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Innovation, Intangibles and Economic Growth: Towards a Comprehensive Accounting of the Knowledge Economy Bart van Ark* University of Groningen and The Conference Board Seminar on Measurement of Capital – Beyond the Traditional Measures Conference of European Statisticians 12 June 2007, Geneva * In co-operation with Charles Hulten, University of Maryland and The Conference Board 1 Grab your iPod, flip it over, and read the script at the bottom. It says: "Designed by Apple in California. Assembled in China." Where the gizmo is made is immaterial to its popularity. It is great design, technical innovation, and savvy marketing that have helped Apple Computer sell more than 40 million iPods. Yet the folks at the BEA don't count what Apple spends on R&D and brand development, which totaled at least $800 million in 2005. Rather, they count each iPod twice: when it arrives from China, and when it sells. That, in effect, reduces Apple -- one of the world's greatest innovators -- to a reseller of imported goods. 2 Do the Official Statistics Capture the Knowledge Economy? How do we measure innovation? New ways of making current products better, faster, cheaper Creating something not previously created Is the impact of innovations accurately represented in official statistics on national income and productivity? NO !! “You see the computers everywhere except in the productivity data.” Solow (1987) Official statistics “miss the most important technological revolutions in history.” Nordhaus (1997) Hence: “Whilst the knowledge economy is all around us, it is still hard to see it in the official statistics” Skepticism about GDP, CPI and productivity statistics capturing key components of the knowledge economy3 National Accounts Framework Provides Adequate Point of Departure Basic solutions require rethinking of: The scope of national accounts on output side The measurement of output in particular in services The measurement of prices to capture product quality Consistency of output and input measures to provide productivity The treatment of inputs in terms of expenditure versus investment Development of growth accounts in conjunction to national accounts is key KLEMS framework Measurement of intangibles 4 Basic Determinants of Sources of Growth/ Growth Accounts Model Output is key measure of standard of living Output is driven by capital (K) labor (L) intermediate inputs (E, M, S) productivity (LP, MFP) Capital and labor can by divided into quantity quality/composition Output increases that cannot be explained by these “inputs” are attributed to multifactor productivity (MFP) 5 EU KLEMS Growth and Productivity Accounts Complements National Accounts EU KLEMS is analytical research database, based on national accounts and complementary official sources (LFS and production statistics) Long time coverage 1970-2004, with greatest detail for post-1995 Harmonized industry classification, capital and labour input, deflation and industry aggregations (e.g. market economy, market services) Decomposition of capital and labour input: Capital assets in 7 asset types Labour input in 18 categories (3 x skill; 3 x age; gender) Broad coverage of EU countries and comparisons with U.S. and Japan Public database: www.euklems.net 6 Growth in Quantity of Standard Factor Inputs Accounts for only Small Part of Real GDP Growth in Market Economy 4.0 1980-1995 1995-2004 3.0 2.0 1.0 0.0 EU15ex excludes Portugal, Luxembourg, Ireland, Sweden and Greece -1.0 EU15ex USA-SIC Japan EU15ex Hours worked USA-SIC Japan Growth in Quantity of Standard Factor Inputs Accounts for only Small Part of Real GDP Growth in Market Economy 4.0 1980-1995 1995-2004 3.0 2.0 1.0 0.0 -1.0 EU15ex USA-SIC Japan Hours worked EU15ex USA-SIC Non-ICT Capital Japan Even in the Traditional Growth Accounts System the Knowledge Economy Features Strongly but Unequal 4.0 1980-1995 1995-2004 3.0 2.0 1.0 0.0 -1.0 EU15ex USA-SIC Japan Hours worked EU15ex Non-ICT Capital USA-SIC Japan ICT Capital Even in the Traditional Growth Accounts System the Knowledge Economy Features Strongly but Unequal 4.0 1980-1995 1995-2004 3.0 2.0 1.0 0.0 -1.0 EU15ex USA-SIC Japan EU15ex USA-SIC Japan Hours worked Non-ICT Capital ICT Capital Labour Composition Even in the Traditional Growth Accounts System the Knowledge Economy Features Strongly but Unequal 4.0 1980-1995 1995-2004 3.0 The knowledge economy 2.0 1.0 0.0 -1.0 EU15ex USA-SIC Japan Hours worked ICT Capital MFP EU15ex USA-SIC Japan Non-ICT Capital Labour Composition Fast Growing Countries Get Bigger Bang from Knowledge Economy, Notably MFP 5.0 4.0 3.0 2.0 1.0 0.0 -1.0 GER ITA LUX DNK BEL Hours worked ICT Capital MFP FRA AUT NLD SWE UK ESP USA Non-ICT Capital Labour Composition FIN Unmeasured intangible capital is hidden in MFP a) Physical Capital a1) ICT capital (IT hardware, communications equipment) a2) Other capital (plant, machinery, buildings) b) Human Capital b1) Formal Education b2) Company training c) Knowledge Capital c1) Research and Development c2) Patents Asbrands, long as intangibles c3) Licenses, copyrights c3) Other technological innovations, not related to b1) to b3) capital remain [c4) Software]* unmeasured, its c5) Mineral Exploration productivity effects c6) Experience are hidden in MFP d) Process Capital d1) Engineering design d2) Organisation design d3) Construction and use of data bases d4) Remuneration of innovative ideas e) Customer Capital e1) Marketing of new products f) Multi Factor Productivity (residual) Corrado, Hulten and Sichel (CHS, 2005) calculated intangible investment in U.S. Inherent measurement difficulties of intangible capital going beyond those of tangible capital as follows: The knowledge-input problem The knowledge-investment problem The quality improvement problem The obsolescence problem (Howell, 1996) But no clearcut distinction between tangibles and intangibles that justify a distinction between capitalizing and expensing “Any outlay than is intended to increase future rather than current consumption is treated as a capital investment” 14 Source: Corrado, Hulten and Sichel (2005) CHS (2005) measure $1.2 trillion of intangible investment in U.S. nonfarm business, 1998-2000 COMPUTERIZED INFORMATION ($154,$154) COMPUTER SOFT WARE ($151) COMPUTERIZED DATABASES ($3) SCIENTIFIC AND CREATIVE PROPERTY ($424,$424) SCIENTIFIC R&D ($184) MINERAL EXPLORATION ($18) COPYRIGHT AND LICENCE COSTS ($75) OTHER PRODUCT DEVELOPMENT (FINANCE, ARCHIT.) ($149) ECONOMIC COMPETENCIES ($642,$505) BRAND EQUITY (ADVERTISING) ($236) FIRM-SPECIFIC HUMAN CAPITAL (TRAINING) ($116) ORGANIZATIONAL STRUCTURE MANANGEMENT CONSULTING, PLANNING ETC.) ($291) 16 Source: Corrado, Hulten and Sichel (2005) When including intangibles, investment share in U.S. GDP holds up 17 Source: Corrado, Hulten and Sichel (2005) … but the difference in growth rates arises from firm specific resources, not R&D 18 Source: Corrado, Hulten and Sichel (2005) Results for U.S. Economy, 2000-03 (70.4%) (60%) (29.6%) (25%) (15%) 19 Source: Corrado, Hulten and Sichel (2005) When including intangibles in growth accounts the weight on capital raises 20 Source: Corrado, Hulten and Sichel (2006) SOURCES OF GROWTH IN OUTPUT PER HOUR NFB 1995-2003 3.09% 2.78% 25% 11% 14% 50% INTANG 27% IT CAP 19% L QUAL 8% 11% MFP 35% IT CAP L QUAL MFP WITHOUT INTANGIBLES WITH INTANGIBLES 21 Source: Corrado, Hulten and Sichel (2006) SOURCES OF GROWTH IN OUTPUT PER HOUR NON-FARM BUSINESS SECTOR 3.09% 1.63% 26% INTANG 18% 15% 15% 25% IT CAP L QUAL MFP MFP 1973-1995 INTANG 27% IT CAP 19% L QUAL 8% 11% MFP 1995-2003 35% 22 Source: Corrado, Hulten and Sichel (2006) CONTRIBUTION OF DIFFERENT INTANGIBLES TO ANNUAL CHANGE IN LABOR PRODUCTIVITY 0.84% SOFTWARE 32% 0.43% 28% SOFTWARE 12% SCI R&D 19% N SCI R&D 9% L QUAL BRAND MFP 30% FIRM MFP SPEC 1973-1995 SCI R&D 10% N SCI R&D 17% BRAND 10% FIRM SPEC 32% 1995-2003 23 Source: Corrado, Hulten and Sichel (2006) The Research Program on Intangibles Extend studies to more countries UK: Haskell and Marrano Japan: Fukao et al. Ongoing work for Finland, France and Netherlands Price and output statistics that explicitly recognize product innovations (“quality” change). Uncover the subtleties of interaction between tangibles/intangibles and innovation/productivity growth A stronger link in the data between human capital and worker competencies More detailed study at industry level (mnf/services) Intangibles need more accurately represented in the financial data of the innovators themselves 24 The Role of National Statistical Institutes Intangible accounting is in early days, but statistical description of knowledge economy is too far removed from reality to ignore Official statistics need to be as precise as possible … but it is sometimes better to be “imprecisely right than precisely wrong” (Keynes) … requiring a balance between research and official statistics NSI’s could help to: develop concepts of intangibles set (international) standards for measurement provide value metrics of intangibles, e.g., survey metrics on innovation with quantitative magnitudes. Transfer experimental and research based measures into national accounts satellites that can help to move the 25 measurement agenda forward