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Analysis of the main factors of regional growth an indepth study of the best and worst performing Eu

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to identify and analyse the underlying factors of this diverse ... and Silesia) 12 more to go this year _at_45 in total. Pulling Away. Dropping Back. Falling ... – PowerPoint PPT presentation

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Title: Analysis of the main factors of regional growth an indepth study of the best and worst performing Eu


1
Analysis of the main factors of regional growth -
an in-depth study of the best and worst
performing European regions
Ben Gardiner Cambridge Econometrics
08 July 2009
2
What is the Project About?
  • Objective(s)
  • to deepen the understanding of economic
    development in the regions of the EU27
  • to identify those (NUTS2-level) regions that have
    performed well and those that have performed
    poorly (relative to EU and/or national average)
  • to identify and analyse the underlying factors of
    this diverse (regional) performance
  • to draw out broad policy conclusions
  • Timeline
  • Year 1 literature review, problems challenges,
    statistical analysis, regional performance
    indicators
  • Year 2-4 case study analysis updating Year 1
    results
  • Project team
  • Cambridge Econometrics (UK), Applica (BE), wiiw
    (AT)
  • scientific committee
  • Further information
  • see http//www.euregionalgrowth.eu/

3
Growth theory offers limited help in working out
the answers
4
Data analysis helps a bit more, provided you know
what you are doing
5
What can be said about innovation and performance?
  • For the majority (but not all) of Member States,
    productivity is the main driver behind GDP per
    capita growth
  • But what drives / is associated with higher
    regional productivity growth
  • sector specialisation
  • innovation
  • trade and globalisation
  • education levels

6
Empirical analysis is more suggestive, even if
precision is a problem
  • Robust factors of growth
  • initial conditions
  • initial GDP per capita
  • human and physical capital endowment
  • high-skilled/low-skilled workforce
  • share of gross fixed capital formation
  • infrastructure variables
  • presence of airports, strength of road/rail
    networks
  • control variables
  • capital city dummy, CEE dummy
  • in some cases,
  • density variables (agglomeration effects)
  • population variables

7
Case study analysis should strengthen / validate
findings
  • Purpose
  • broaden and refine the picture of the main
    mechanisms of growth suggested by the
    quantitative approach
  • what role for public policy?
  • Selection process
  • hard limits on numbers of regions
  • selection in practice
  • quadrant analysis
  • typological aspects
  • Moving forward
  • 3 pilot studies (Bayern, Galicia, and Silesia)
  • 12 more to go this year
  • _at_45 in total

8
Conclusions
  • Ambitious goals
  • Main findings
  • Case study work
  • Summary statements
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