ESPON Workshop at the Open Days Brussels, 5 October 2010

1. ESPON Workshop at the Open Days Brussels, 5 October 2010 Cooperation: the benefits of cooperating across internal and external borders TIPTAP – Territorial Impact Package for Transport and Agricultural Policies Roberto Camagni – Politecnico di Milano

2. The Team Project Leader: DIG – Politecnico di Milano Roberto Camagni, Roberta Capello, Camilla Lenzi, Andrea Caragliu, Nicola Dotti, Paola Bolchi Partners and subcontractors: Centre for Rural Economy, School of Agriculture, Food and Rural Development, Newcastle University Mark Shucksmith, Marian Raley, Guy Garrod Department of Spatial Economics,Free University Amsterdam Ron Vreeker, Frank Bruinsma, Peter Nijkamp MCRIT SL, Barcelona Andreu Ulied, Efrain Larrea

3. The model: from TEQUILA to TIPTAP TEQUILA 1 TIPTAP (TEQUILA 2) T erritorialT erritorial E fficiencyI mpact QU alityPackagefor I dentityTransport and L ayeredAgricultural A ssessmentPolicies Model (Camagni, 2006; ESPON 2006) (ESPON 2013)

4. What is TEQUILA? • A MulticriteriaModelforTerritorial Impact Assessmentof EU policies: modelling + expert judgements • 2. Territorial impact = impact on the territorialcohesionprinciple • S.D.I.- Single Dimension Impacts: regional impacts: - on economy (GDP, GDP per capita) - on competitiveness (productivity, accessibility, congestion) - on society (unemployment, safety, social deprivation) - on sustainability and climate change (emissions, soil erosion) - on landscape and local identities (landscape fragmentation, ext. visitors, heritage products) 4. S.I.- Summative impacts: impacts on the three components of Territorial Cohesion: Territorial Efficiency, T. Quality, T. Identity

5. What is TEQUILA? 5. The 3 main components of territorial cohesion: Territorial Efficiency: resource-efficiency with respect to energy, land and natural resources; competitiveness and attractiveness; internal and external accessibility Territorial Quality: the quality of the living and working environment; comparable living standards across territories; fair access to services of general interest and to knowledge Territorial Identity: “social capital”; landscape and cultural heritage; creativity; productive “vocations” and “uniqueness” of each territory 6. General, Summative Impact = weighted impact (when allowed) 7. Relative importance of the single impacts: assessed by experts and by policy makers (questionnaire)

6. The Model TIMr = Σc θc . PIMr,c . Sr,c TIM = territorial impact θc = weightof the c criterion PIM = potential impactof policy Sr,c = sensitivityofregion r tocriterion c Sr,c = Dr,c . Vr,c Dr,c = desirabilityofcriterion c forregion r Vr,c = vulnerabilityofregion c to impact PIMc (receptivityfor positive impacts) Two alternative waysofcomputingPIMs: • Through econometric and simulation modelling (transport case) • Through statistical elaborations on indicators (agriculture case)

7. Criterion Sub-criter. Type Definition Measurement Economic Modulation/Total GDP; Modulation = [(regional increase in P2) – (regional cut in P1)] E1 % change in GDP Benefit growth (Unemployment rate) * (Share of TE Efficiency Unemploy- ment E2 agricultural employment)*(PIM_E1 normalised) % change in unempl. rate Cost (Number of beds in rural areas/Km2 in agriculture) * (PIM_E2 normalised) Tourism E3 new tourism beds per Km2 Benefit Diversificat. ((Total agricultural area entered into agri-environm. schemes under Pillar2 of Cap) / Total agricultural area)*100 Environment. % of agricultural areas into Q1 Benefit quality agri-environmt. schemes [((Share of areas occupied by farms <10 ha) +(share of population aged >65)+(share of employment in agriculture))*(PIM_E1 normalised)]/3 Community Q2 social deprivation Cost viability TQ Quality Variation in livestock emissions (Tons CH4 per year) Emissions Q3 emissions Cost Areas at risk of soil erosion (ton/ha/year)*(5% of areas of farms <10ha/total agricultural areas)*100 Risk of soil % of abandoned areas Q4 Cost erosion + erosion probability (5% of areas of farms <10ha / total agricultural areas)*100 Landscape % of abandoned /incorpor. I1 Cost diversity agricultural areas [(0,1*(Share of people aged >15 and <65) + (share of employment in agriculture) + (unempl. rate))*(PIM_E1 normalised)]*100/3 Community I2 outmigration probabil. (%) Cost TI Identity identity [(Employment in agriculture/ Gross Fixed Capital Formation in agriculture)*(PIM_E1 normalised)] / Max value Heritage product diversification I3 Benefit products and innovation probabil. Impact of CAP: indicators

8. Impact on Tourismdiversification Impacts are mainly positive, and the strongest conditions are found in Algarve, some Spanish regions along the Pyrenees, Auvergne and Franche-Comtée in France, Trentino-Alto Adige, Friuli, Marche, Abruzzo and Calabria in Italy, in many regions along the Baltic Sea in Germany, Poland and Latvia and in many internal regions in New Member countries like southern Poland, Czech Republic, Slovakia and Romania. Eastern Countries regions on the Black and the Adriatic seas could also benefit strongly from such diversification in economic activities.

9. Impact on Environmental Quality Positive outcomes are mainly visible in southern and western European regions, with strong country effects due to the national management of funds allocation among axes of Pillar 2. Most important impacts are forecasted in Southern Ireland, southern and western Austria and Attiki, but very good performances are shown by mainly all regions in Spain, France, UK, Italy and Greece. The lowest impacts are visible on New Member Countries.

10. Impact on TerritorialEfficiency Different weighting systems may change “Summative Impacts” Experts’ weights Policy makers’ weights

11. The Transport Scenario: newinfrastructure New roads New rail

12. Transport impact indicators

13. Impact on Economic growth – Baseline Scenario A generalized positive impact, though limited, is found throughout Europe, and in Eastern Countries in particular, thanks to new infrastructure provision and to processes of growth diffusion.

14. Impact on congestion costs – Pricing Scenario The negative sign is pervasive in the Baseline Scenario, in particular in many major northern metropolitan areas. However, pricing policies will reduce congestion overall and in particular in already heavily congested areas; exceptions regard mainly southern Italian and a few Spanish regions.

15. The FLAG Model: Baseline Scenario New Infrastructure Scenario Pricing Scenario

16. Thanks! Many thanks for your attention! Roberto CamagniBEST- Politecnico di MilanoPiazza Leonardo da Vinci 32 - 20133 MILANOtel: +39 02 2399.2744  - 2745 secr.fax: +39 02 2399.9477roberto.camagni@polimi.itwww.economiaterritoriale.it