Fine-Tuning the Interpretation of the EU-SPI Results FRANCESC - - PowerPoint PPT Presentation

Fine-Tuning the Interpretation of the EU-SPI Results

FRANCESC COLOMÉ MONTSERRAT & MARC TATARET BATALLA CATALONIA REGION 11/10/2019 – BRUSSELS E U E U-SPI P EER L EARNING W ORKSHOP – B ACK TO B ACK W ITH T HE E WRC 2019 THE COMPARABILITY ISSUE ON INDEXES: THE SPECIFIC CASE OF THE EU -SPI.

• With whom do we compare? E.g. with other regions,

countries, etc.?

• How have we done the selection process?
• How – in terms of methodology - do we compare their

performance?

Concrete experiences of f our region in terms of f comparability

Some examples:

• EU-SPI Peer Regions -> Problem: 6 regions from the same country

(Germany)

• With regions with similar problems
• The EU28 countries, including of course, your own country
• Other regions in your country
• Other criterion (regions with political parties member of EFA Group)
• Internally (NUTS 3 or county level)

EU-SPI Score – Catalonia and peer regions

45 50 55 60 65 70 75 80 85

Score

Score in the SPI 3 dimensions – Catalonia and peer regions

40 50 60 70 80 90 100

Score

Basic Human Needs Foundations of Wellbeing Opportunity

Catalonia component ranking in the EU-272 context

Rank = 11| Max. Gap = 3,77 Rank = 57| Max. Gap = 36,4 Rank = 74| Max. Gap = 9,09 Rank = 92| Max. Gap = 26,8 Rank = 117| Max. Gap = 7,42 Rank = 140| Max. Gap = 12,9 Rank = 151| Max. Gap = 29,7 Rank = 172| Max. Gap = 19,3 Rank = 184| Max. Gap = 26,6 Rank = 205| Max. Gap = 29,4 Rank = 240| Max. Gap = 53,1 Rank = 250| Max. Gap = 46,7

1 51 101 151 201 251 301

Nutrition and Basic Medical Care Environmental Quality Tolerance and Inclusion Access to Advanced Education Health and Wellness Personal Safety Access to Information and Communications Water and Sanitation Shelter Personal Freedom and Choice Personal Rights Access to Basic Knowledge

Posició

Posició de Catalunya en termes de PIB per càpita (2011) 68

Catalonia component ranking in the Spanish context

Rank = 5| Max. Gap = 9 Rank = 8| Max. Gap = 3,77 Rank = 8| Max. Gap = 6,75 Rank = 8| Max. Gap = 18,68 Rank = 10| Max. Gap = 22,24 Rank = 11| Max. Gap = 16,35 Rank = 13| Max. Gap = 6,33 Rank = 15| Max. Gap = 7,28 Rank = 17| Max. Gap = 36,44 Rank = 17| Max. Gap = 10,69 Rank = 17| Max. Gap = 11,25 Rank = 18| Max. Gap = 12,99

2 4 6 8 10 12 14 16 18 20

Access to Information and Communications Nutrition and Basic Medical Care Tolerance and Inclusion Access to Advanced Education Access to Basic Knowledge Water and Sanitation Health and Wellness Personal Rights Environmental Quality Personal Freedom and Choice Shelter Personal Safety

Posicó Rànquing

Posició de Catalunya en termes de PIB per càpita (2011) 4

EU-SPI and GDP per capita for the Spanish regions

62.00 64.00 66.00 68.00 70.00 72.00 74.00 16.00 18.00 20.00 22.00 24.00 26.00 28.00 30.00 32.00 34.00 SPI score PIB, x 1000 ppc

EU-SPI and Household Income for the Spanish regions

63.00 64.00 65.00 66.00 67.00 68.00 69.00 70.00 71.00 72.00 73.00 18.00 19.00 20.00 21.00 22.00 23.00 24.00 25.00 26.00 27.00 SPI score PIB, x 1000 ppc Galicia Principado de Asturias Cantabria País Vasco Comunidad Foral de Navarra La Rioja Aragón Comunidad de Madrid Castilla y León Castilla - La Mancha Extremadura Catalunya Comunidad Valenciana Illes Balears Andalucía Región de Murcia

CCAA and German Länder

68.00 69.00 70.00 71.00 72.00 73.00 74.00 75.00 18.00 23.00 28.00 33.00 38.00 43.00 48.00 53.00 SPI score PIB, x 1000 ppc

SPI vs PIB, Germany

62.00 64.00 66.00 68.00 70.00 72.00 74.00 16.00 21.00 26.00 31.00 36.00 SPI score PIB, x 1000 ppc

SPI vs PIB, Spain

According to the NUTS classification, the 16 German länders are NUTS 1. Since the EU-SPI is computed at NUTS 2 level, some calculations have been made to obtain the German länder data. There are 9 länders that are at the same time NUTS 1 and NUTS 2, and no calculation was necessary. These are: Brandenburg. Bremen, Hamburg, Mecklenburg-Vorpommern, Saarland, Sachsen-Anhalt, Schleswig-Holstein, Thüringen and Berlin. But there are 7 länderthat contain more than one NUTS 2 statistical unit, so we have computed the components of each NUTS 1 by adding the proportional value (according to its population) of each NUTS 2 unit that they contain. Finally, we have computed the dimensions and the EU-SPI final value by using a un-weighted generalized mean of order B=0,5 (as stablished in the EU-SPI methodology) . The länder in which we have applied these calculations are: Baden-Württemberg, Bayern, Hessen, Niedersachsen, Nordrhein-Westfalen, Rheinland-Pfalz and Sachsen.

EFA Countries

NUTS 3 and County Level

How does the possible exchange/learning process with the region/country which is used for the comparisons, look like?

Not always a good result of a peer region of GDP is applicable to another peer region of GDP, because the contextual factors can be very different. For this reason, we want to encourage the creation of a number of external indicators to contextualize.

Ge General limi mitations of f the EU EU-SPI in terms of f comparability

What are the limitations of the EU-SPI (and

• ther indexes – if you work with other ones)

in terms of comparability?

The EU-SPI analyses:

• Territories with very different populations
• Capitals regions and non-capital regions
• Rural and Urban regions
• Protestant, Catholic and Orthodox
• Mediterranean and Northern regions
• Perceptions
• Different Labor Markets and economic structures
• Decentralization levels
• Public Spending

Densely populated areas behave differently?

EU-SPI

R² = 0.5202 30 40 50 60 70 80 90 100

• €

10,000 € 20,000 € 30,000 € 40,000 € 50,000 € 60,000 € 70,000 € 80,000 € 90,000 €

Region GDPpc PPP 2011 EU-SPI Score Inner London 80.400 € 72,35 Luxembourg 66.700 € 73,4 Région de Bruxelles-Capitale / Brussels Hoofdstedelijk Gewest 55.600 € 66,85 Hamburg 50.700 € 74,21 Bratislavský kraj 46.600 € 62,59 Île de France 45.600 € 71,24 Groningen 45.600 € 80,55 Stockholm 43.300 € 79,9 Praha 42.900 € 65,85 Oberbayern 42.200 € 74,01 Wien 41.300 € 73,11

Perceptions and Objective Data

Different economic structures

How should the EU-SPI get adapted/improved in order to make it more usable for comparisons? (E.g. easily identification of regions with which a specific region would like to get compared.)

• The EU-SPI interpretation could use a series of external variables to help us

understand the EU-SPI results.

• Internal comparison of the EU-SPI results could also be improved, by finding

regions with similar profiles (and maybe similar problems).

How could the further developed EU-SPI get used by your region in the future?

• Policy making.
• Budgeting.
• Peer learning.

Internal Comparison -> Guidelines to better understand the possible roots of our problems.

Eg: If the EU-SPI shows a bad score and rank in the component shelter, you could check:

• Evolution of the perception of the cost of housing and related expenses
• Evolution of the purchase and rental prices
• Public housing
• Public investment in housing
• Others

Conclusions

• New criteria for selection of peers needed, both internally and

externally

• Guidelines for interpretation of the EU-SPI results could be usefull

Nutrition and Basic Medical Care

55 60 65 70 75 80 85 90 95

Score

Acces to Basic Knowledge

50 60 70 80 90

Score

Health and Wellness

40 50 60 70 80

Score

Water and Sanitation

40 50 60 70 80 90 100

Score

Shelter

40 50 60 70 80 90

Score

Personal Rights

20 30 40 50 60 70 80

Score