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Capital Boundaries

Capital Boundaries. CES seminar MEASURING CAPITAL – BEYOND THE TRADITIONAL MEASURES Session II: Capital boundaries in the revision of the System of National Accounts 1993 Walter Radermacher Geneva 12 June 2007. Papers . Capital Measurement in the Netherlands

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Capital Boundaries

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  1. Capital Boundaries CES seminar MEASURING CAPITAL – BEYOND THE TRADITIONAL MEASURES Session II: Capital boundaries in the revision of the System of National Accounts 1993 Walter Radermacher Geneva 12 June 2007

  2. Papers • Capital Measurement in the Netherlands • M. de Haan, D. van den Bergen and M. van Rooijen-Horsten, CBS-NL • The Capital Boundary in the 1993 SNA, Rev. 1 – Challenges for National Statistical Offices • P. Sollberger, Ph. Stauffer and R. Meier, SFO-CH • Capitalisation of research and development expenditure: points of view and experiences in the European Union • G. Gueye and F. Malherbe, Eurostat • An Integrated System of Capital Flow and Stock Statistics • P. Harper, ABS-AUS

  3. Focus of the Papers

  4. The dictum: • “The only statistics you can trust are those you falsified yourself“ • Churchill’s authorship has not been proved to this day! • A slander campaign in the propaganda war? • Possible author:Churchill’s arch-enemyJoseph Goebbels ?

  5. This is what Winston Churchill really said: “You must look at the facts because they look at you!” Speech in the British House of Commons, 7 May 1925

  6. This is ascribed to Kennedy: / Statistics are like a bikini, what they reveal is suggestive, but what they conceal is vital. • Aaron Levenstein (1901-1986), economics professor in New York, is the real author

  7. Goodhart‘s Law • Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes (Charles Goodhart) • or more generally: • When a measure becomes a target, it ceases to be a good measure (Keith Hoskin)

  8. “Good policy needs good statistics” (Tony Blair) Theoretical Consistency Quality of Statistics Political Relevance Empirical Measurability

  9. Capital  Economic Assets Entities functioning as a store of value over which ownership rights are enforced by institutional units, individually or collectively, and from which economic benefits may be derived by their owners by holding them or using them over a period of time public goods and infrastructure resulting from an accumulation of knowledge

  10. The Large Hadron Collider (LHC) - a particle accelerator at CERN near Geneva • Final works in these months to switch on in 2007 – 27 km circumference –not far away from here (literally under our feet) • Example for basic research that would be classified as freely available Source: CERN

  11. Interaction Water Knowledge Skills Land Air Human being Nature Mineral resources Biodiversity Abilities Creativity S A Y Land Capital Labour

  12. Land Capital Labour Nonfinancial Assets S N A Nonproduced assets Produced assets Tangible nonproduced assets Land Subsoil assets Intangible nonproduced assets Patented entities Leases Fixed assets Inventories Valuables Precious metals Antiques 93 Tangible fixed assets Intangible fixed assets R E V 1 Buildings and structures Machinery and equipment Cultivated assets Computer software Entertainment, literary or artistic originals Mineral exploration Research and Development

  13. Human capital Non-scientific innovations Marketing assets (brands…) Organisation and management … What is Software?  What is R&D? Identification problem

  14. Identification, Valuation, Depreciation: Difficulties • Identification and Classification of the product • Valuation of the gross fixed capital formation (GFCF) of different types of R&D - imputations like capital services of the stock of current knowledge • Estimation of mortality tables and expected service lives on an objective basis • Availability of long series of GFCF as precondition of the perpetual inventory method • Availability of deflators – price indices for never standardised R&D services • Valuation of a specific contribution of R&D to production, (based on the accumulation of knowledge)

  15. Future Work • Investigate via satellite accounts • Bridging R&D statistics to national accounts • Imputation of yearly (and quarterly) SNA data without yearly R&D surveys • Deflators and long time series • Service lives and mortality/retirement function • … •  Satellite accounts should be applied to examine the effects of different solutions of the identification problem (e.g. public goods)

  16. Measuring wealth and productivity The concept of capital services An integrated system of capital flow and stock statistics Accumulation (investment) Gross stock Tradit.: Capacity Potential Retirements Accumulation (investment) Accumulation (investment) + Return to Capital S N A Net stock Wealth Productive stock Capital services Depreciation

  17. Questions to the authors • Netherlands: • Delineation of knowledge capital creation by R&D and the creation of human capital and other forms of “intangibles” – conceptual level and implementation in practice? • Netherlands and Australia: • How do you see the interdependence of capital services for non-market producers and the valuation of R&D according to non-market production? • Proposal for the further treatment of technical issues – a new forum, new project, new revision or what else? • Switzerland: • Reliability of the national accounts data including R&D from your first estimates for political purposes? • Impact on level and growth rate of GDP?

  18. Questions to the authors (2) • Eurostat: • Ideas for the work of the Eurostat Task Force on the development of satellite accounts for R&D in the light of the OECD Task Force working in parallel? • Is the quality of primary statistics on R&D appropriate? Do national R&D-figures adequately reflect the shift in economy towards globalised ways of production and towards a higher importance of service industries? • Australia: • To what extent is the concept of capital services necessary for the analysis of productivity? How far does it help to show the productivity effects of “intangibles” better than now?

  19. Questions for the general discussion • R&D – difficult to measure in any case • Rough estimate or no estimate at all? • Very rough estimates may mislead users vs. Rejection of estimation may damage the macroeconomic quality of the accounts • Should national accounts data be based on statistically measurable variables, focused on observable market transactions rather than imputations? • Extension of the capital boundary  Switching over to net domestic product for international comparisons?

  20. „You have to have facts. Theories are not good unless you have facts to back them.“ (Wassilij Leontief) Consistency Quality of Statistics Relevance Measurability THANK YOU VERY MUCH FOR YOUR ATTENTION !

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