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 alityP ackage for I dentityT ransport and L ayeredA gricultural A ssessmentP olicies Model (Camagni, 2006; ESPON 2006)(ESPON 2013)

4. What is TEQUILA? 1. A Multicriteria Model for Territorial Impact Assessment of EU policies: modelling + expert judgements 2. Territorial impact = impact on the territorial cohesion principle 3. 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 = Σ c θc. PIMr,c. Sr,c TIM = territorial impact θc = weight of the c criterion PIM = potential impact of policy Sr,c = sensitivity of region r to criterion c Sr,c = Dr,c. Vr,c Dr,c = desirability of criterion c for region r Vr,c = vulnerability of region c to impact PIMc (receptivity for positive impacts) Two alternative ways of computing PIMs: - Through econometric and simulation modelling (transport case) - Through statistical elaborations on indicators (agriculture case)

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

8. Impact on Tourism diversification 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 Territorial Efficiency Experts weights Policy makers weights Different weighting systems may change Summative Impacts

11. The Transport Scenario: new infrastructure New roadsNew 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! Roberto Camagni BEST- Politecnico di Milano Piazza Leonardo da Vinci 32 - 20133 MILANO tel: +39 02 2399.2744 - 2745 secr. fax: +39 02 2399.9477 roberto.camagni@polimi.it www.economiaterritoriale.it Many thanks for your attention!