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Annalisa Castelli

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University of Rome Tor Vergata and ISTAT. Rome, 27 June 2003. Our Goal ... Review existing indicators in a perspective that permits to capture both old and ... – PowerPoint PPT presentation

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Title: Annalisa Castelli


1
Productivity and Competitiveness Indicators
database presentation Annalisa
Castelli University of Rome Tor Vergata and ISTAT
Rome, 27 June 2003
2
Our Goal
  • WP 5.2 Review and assessment of indicators and
    methodologies on productivity and competitiveness
    in the Network Economy
  • WP 5.3 Policy guidelines in relation to
    workpackage 5.2

3
1. Review 2. Assessment 3. Policy
guidelines
  • Review existing indicators in a perspective that
    permits to capture both old and new sectors
    performances
  • Assess the effectiveness of the indicators
    reviewed and suggest new/alternative measures
  • Analyse the information required for each
    indicator review current practice in data
    collection, definitions and methodologies

4
Elements for the data analysis
  • Multi level structure for data description
  • Two paths for inspection indicator and data set
  • Vertical and horizontal data mining
  • Easy implementation and fast deployment

5
Pros Cons of RDBMS
  • Multi-dimensional data structure
  • Flexibility in data structure
  • Easy usage and portability
  • Easy integration into Web Applications
  • Difficult implementation for 8-8 relations

6
Our methodology
  • Construction of a Relational Database (RDB)
    containing
  • existing indicators
  • data sets
  • information requirement for each indicator

7
Our results
  • Thanks to this DB it is possible to better
    identify
  • gaps in indicators coverage
  • linkages among indicators
  • useless duplications
  • definitional and methodological heterogeneities

8
DB Structure
9
Indicator
  • Composition (methodology)
  • Data source (NA, Commission studies, etc.)
  • Provider (Oecd, Eurostat, NSIs, etc.)
  • Data availability (country and time covering)
  • Dimension (readiness, impact, usage)
  • Segmentation (micro, meso, macro)
  • Type (Productivity, Competitiveness, Structural)
  • Strenghts and Weaknesses
  • Hierarchy (main or subordinate)

10
Data Set
  • Contents (subject of the data, methodology)
  • Data info (harmonisation, comparability,
    updating etc.)
  • Data availability (country and time covering)
  • Compiler (NSIs, Eurostat, etc.)
  • Link (connection to the website)

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