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Industry Productivity Levels - PowerPoint PPT Presentation


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Recent Data Work at the Groningen Growth and Development Centre Complementing PWT with capital (global, 1980) 10-Sector database (global, 10 sector, 1950) Historical national accounts (global, 10 sector, 1870-1950) EU KLEMS Growth Accounts (OECD, 30 sector, 1970)

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recent data work at the groningen growth and development centre
Recent Data Work at the Groningen Growth and Development Centre
  • Complementing PWT with capital (global, 1980)
  • 10-Sector database (global, 10 sector, 1950)
  • Historical national accounts (global, 10 sector, 1870-1950)
  • EU KLEMS Growth Accounts (OECD, 30 sector, 1970)
  • EU KLEMS Level Accounts (OECD, 30 sector, 1997)
  • World Input-Output Database (global, 30 sector, 1995):
    • International trade flows
    • National Supply and Use Tables
    • Environmental accounts
    • Socio-economic accounts
slide2

INDUSTRY PRODUCTIVITY LEVELSby Robert Inklaarand Marcel P. Timmer Groningen Growth and Development CentreUniversity of Groningen

The EU KLEMS project is funded by the European Commission, Research Directorate General as part of the 6th Framework Programme, Priority 8, "Policy Support and Anticipating Scientific and Technological Needs".

motivation
Motivation
  • Complementing EU KLEMS Growth and Productivity Accounts
  • Industry perspective
  • Why are levels interesting?
    • Explaining differences in output (per hour) across countries
    • Competitiveness (unit labour costs)
    • Measure of technology: distance to the frontier
    • Differences in input use (ICT, skills, energy, business services)
coverage
Coverage
  • For benchmark year 1997
  • 28 industries plus aggregates as in EU KLEMS
  • 30 countries as in EU KLEMS
  • Extrapolation possible with EU KLEMS
what s new
WHAT’S NEW?
  • Long tradition GGDC and NIESR (single deflated labour productivity mostly). This data set provides
    • Multilateral KLEMS type comparisons
    • More countries and industries covering whole economy
    • Mix of production and expenditure PPPs
  • Methodology for multilateral MFP from Jorgenson and Nishimizu (1978) and CCD (1982).
    • Primal approach to retain consistent breakdown of real GDP
    • Add sectoral output and intermediate inputs measures which allow aggregation across industries
methodology
Methodology
  • Labour productivity
  • Multi factor productivity
nominal data
Nominal Data
  • National Supply and Use tables, transformed into industry-by-industry IOT (45 industries) at basic prices
  • Normalized on EU KLEMS value added and gross output
  • Breakdown of intermediate inputs into domestic E,M,S and imports
  • Breakdown of value added into
    • labour compensation (30 types)
    • capital compensation (8 types) and profit
price data
Price Data
  • Two alternative sets for output PPPs
    • OECD/Eurostat PPPs for expenditure categories
      • Expenditure prices, incl margins / net taxes / imports, excl exports
      • Based on specified prices
    • GGDC PPPs from production side
      • Producer output prices, incl exports
      • Based on unit value ratios
  • Mix of both is ideal
    • PPP-O: agriculture / mining / utilities / manufacturing (partly) / communication / transport / trade
    • PPP-E: manu (partly) / construction / finance / business services / personal services
price data 2
Price Data (2)
  • Intermediate input PPPs based on output PPPs weighted with shares in total intermediate input.
  • Labour PPPs based on relative wages (5x2x3 types)
  • Capital PPPs based on relative rental prices (8 types)
  • Non-market services: Implicit output PPP based on input PPPs such that MFP=1
some results
Some Results
  • FIG 1 Value added per hour worked, 2005, US=1
  • FIG 2 Sensitivity of LP:
    • Single versus double deflation of value added
    • Set of output PPPs (expenditure PPPs versus mix)
  • FIG 3 ICT and Non-ICT capital services per hour worked, 1997
  • FIG 4 MFP, 2005, US=1
concluding remarks
Concluding remarks
  • Industry level accounts are feasible
  • Importance of sectoral output measures
  • Further research
    • DATA
      • Hours worked
      • Intangibles
      • Recent benchmark year
    • METHOD
      • Ex-ante measures of capital and loss of duality
      • Time-space consistency with more benchmarks
      • CCD and heterogeneity: role for MST?
      • More data, more noise?
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