ESPON Workshop at the Open DaysBrussels, 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

The Team

Project Leader: DIG – Politecnico di MilanoRoberto 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 UniversityMark Shucksmith, Marian Raley, Guy Garrod

Department of Spatial Economics, Free University AmsterdamRon Vreeker, Frank Bruinsma, Peter Nijkamp

MCRIT SL, BarcelonaAndreu Ulied, Efrain Larrea

The model: from TEQUILA to TIPTAP

TEQUILA 1 TIPTAP

(TEQUILA 2)

T erritorial T erritorial

E fficiency I mpact

QU ality P ackage for

I dentity T ransport and

L ayered A gricultural

A ssessment P olicies

Model

(Camagni, 2006; ESPON 2006) (ESPON 2013)

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

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 knowledgeTerritorial 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)

The Model

TIMr = Σc θc . PIMr,c . Sr,cTIM = territorial impactθc = weight of the c criterionPIM = potential impact of policySr,c = sensitivity of region r to criterion c

Sr,c = Dr,c . Vr,cDr,c = desirability of criterion c for region rVr,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)

Impact of CAP: indicators

Criterion Sub-criter. Type Definition Measurement

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 ofagricultural 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 <10 ha) +(share of population aged >65)+(share of employment in agriculture))*(PIM_E1 normalised)]/3

social deprivation

Q3 Emissions CostVariation 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

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.

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.

Impact on Territorial Efficiency

Experts’ weightsPolicy makers’ weights

Different weighting systems may change “Summative Impacts”

The Transport Scenario: new infrastructure

New roads New rail

Transport impact indicators

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.

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.

The FLAG Model:

Baseline Scenario New Infrastructure Scenario Pricing Scenario

Thanks!

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

Many thanks for your attention!