P. Annoni: The European Commission measures the level of regional competitiveness

Decima conferenza di statistica – ISTAT Roma 15-16 dicembre 2010 1

EU Regional competitiveness

The European Commission measures The European Commission measures the level of regional competitivenessthe level of regional competitiveness

Paola AnnoniUnit of Econometrics and Applied StatisticsEuropean Commission, Joint Research Centre – Ispra

http://easu.jrc.ec.europa.eu/



Joint project between DG JRC (Ispra) and DG Regional Policy (Brussels)

Measures the ‘level of competitiveness’ of EU regions at the NUT2 geographical level

RCI 2010 released in September 2010 and will be updated every 2 years



The concept is still controversial among the experts

Stands between micro (firm) and macro (country) competitiveness…. many analogies BUT with key differences:

unsuccessful firms can be expunged from business, underperforming countries cannot

competitions among firms is a zero-sum game (mors tua vita mea), the success of one country is generally positive for surrounding ones (spillover effects)

Territorial competitiveness, what are you?



Meyer-Stamer*, 2008, pg.7:

“We can define (systemic) competitiveness of a territory as the ability of a locality or region to generate high and rising incomes and improve livelihoods of the people living there”

Territorial competitiveness, what are you?

Social and human aspects play a key role

* Meyer-Stamer, Jörg, late German Political Scientist



1. Institutions

2. Macroeconomicstability

3. Infrastructure

4. Health

5. Qualityof Primaryand SecondaryEducation

6. HigherEducation/ Training and LifelongLearning

7. LaborMarket Efficiency

8. Market Size

9. TechnologicalReadiness

10. Business Sophistication

11. Innovation

Basic pillars

Efficiencypillars

InnovationpillarsThe RCI framework

Three macro dimensions

Basic Efficiency

Innovation

11 pillars

69 indicators

(out of 81 candidates)

Data sources: Eurostat OECD-PISA - OECD-Regional Patent Database European Cluster ObservatoryWorld Bank Governance Indicators Ease of Doing BusinessFlash Eurobarometer



Five Basic Pillars

Institutions(country level)

Macro-economic stability(country level)

Infra-structure

HealthPrimary and Secondary Education(country level)

CorruptionFraudGovernance IndicatorsEase of doing business

GovernmentdeficitSaving rateInflationLong term bond yields

RoadRailAir

Road fatalitiesHealthy life expectancyInfant MortalityCancer and heart disease death rateSuicide death rates

OECD PISA forReadingMathsScience



Basic Pillars

• Nordic countries score

high

• Macro economic stability

low in the south

• Governance and

corruption problematic

both east and south



Three Efficiency Pillars

Higher education and training

Labour Market Efficiency Market Size

GraduatesLifelong learning Early school leaversAccessibility to universities Higher education expenditure

Labour productivityEmployment rate in industry and servicesUnemployment rateLong-term unemploymentGender balance employmentGender balance unemployment

Potential market size expressed in GDPPotential market size expressed in populationGDP Compensation of employeesDisposable income



Efficiency Pillars

• Capital regions

consistently score higher

than surrounding regions

• Northwest scores best

• Southeast scores low



Three Innovation Pillars

Technological readinessBusiness sophistication

Innovation

Household access to broadband or internetIndividuals who ordered online for private useHousehold with access to internetEnterprises use of computers, access to internet, website, intranet, internal networksPersons employed by enterprises with an extranet or internet access

Employment and GVA in Financial and business services (NACE J_K)FDI intensityAggregate indicator for strength of regional clusters (European Cluster Observatory)

Patents Core Creative ClassKnowledge workersScientific publicationsR&D Human Resources in Science Technology (HRST) Hight tech and Knowledge-intensive employmentHigh-tech, ICT, Biotechnology inventors



Innovation Pillars

• Scores are high in the

Nordic countries, Benelux,

Germany and France

• Portugal and Southeastern

EU score low



Steps of the analysis:

Assessment of data quality, consistency and adequacy to the final goal (statistical analysis)

Data transformation and normalization

Data aggregation with different weights to different groups of pillars

Robustness analysis



Weights adjusted according to the level of development of the region(built on WEF-GCI) Three classes:

MEDIUM : <75% of EU GDP 2007 (PPP per head)INTERMEDIATE: between 75% and 100%HIGH: >100% It’s the threshold defined by

EU Commission for eligibility for the ‘Convergence’ objective


EU Regional competitivenessRCI 2010

Warsaw

Prague

Bratislava

Vienna

Budapest

Bucharest

Athens

Lisboa

Madrid

Paris

Rhône-Alpes

Sofia



Has the blue banana lost a part?



A focus on the Italian situation

Source: 21.09.2010REGIONI D'EUROPA: CHI É PIÙ COMPETITIVO?Paola Annoni , Kornelia Kozovska e Andrea Saltelli

Lavoce.info – www.lavoce.info



BASILICATA ITF5

0.0

0.2

0.4

0.6

0.8

1.0Institutions

Macroeconomic stability

InfrastructureHealth

Primary&Secondaryeducation

LOMBARDY ITC4

0.0

0.2

0.4

0.6

0.8

1.0Institutions




A focus on the Italian situation – basic pillarsVALLE D'AOSTA ITC2

0

0.2

0.4

0.6

0.8

1Institutions




LAZIO ITE4

0.0

0.2

0.4

0.6

0.8

1.0Institutions




RCI 65.3 RCI 35.8

RCI 27.7C RCI 58.5



A focus on the Italian situation – efficiency pillarsLOMBARDY ITC4

0.0

0.2

0.4

0.6

0.8

1.0Higher education and training

Labor market efficiency Market size

BASILICATA ITF5

0.0

0.2

0.4

0.6

0.8



VALLE D'AOSTA ITC2

0.0

0.2

0.4

0.6

0.8



LAZIO ITE4

0.0

0.2

0.4

0.6

0.8



RCI 65.3 RCI 35.8

RCI 27.7C RCI 58.5



LOMBARDY ITC4

0.0

0.2

0.4

0.6

0.8

1.0Technological readiness

Business sophisticationInnovation

A focus on the Italian situation – innovation pillars

BASILICATA ITF5

0.0

0.2

0.4

0.6

0.8



VALLE D'AOSTA ITC2

0.0

0.2

0.4

0.6

0.8



LAZIO ITE4

0.0

0.2

0.4

0.6

0.8



RCI 65.3 RCI 35.8

RCI 27.7C RCI 58.5



Further analysis (about to be published): Table 1: Correlation coefficients between RCI scores and exogenous indicators. Values in red are statistically significant at the level = 0.05.

RCI_total RCI_eff RCI_inn

population change 01-07 0.11 0.05 0.17

natural population change 01-07 0.11 0.01 0.25

net migration 01-07 0.07 0.06 0.06

share of population in LUZ 0.41 0.44 0.42

GDP growth average 00-07 -0.31 -0.17 -0.36




net migration 01-07 -0.04 0.04 -0.07


GDP growth average 00-07 -0.21 -0.15 -0.30




net migration 01-07 0.26 0.22 0.34


GDP growth average 00-07 0.25 0.46 0.36

all countries sample size N =268 critical value for N> 100 at level 0.05 = 0.195

group B sample size N = 65 critical value for N = 60 at level 0.05 = 0.25

group A sample size N =128 critical value for N> 100 at level 0.05 = 0.195

Spatial autocorrelation analysis

Relation with exogenous variables

P. Annoni: The European Commission measures the level of regional competitiveness

Education

Transcript of P. Annoni: The European Commission measures the level of regional competitiveness