Regional Policies and Territorial Development C. Ciupagea JRC.IES X. Goenaga, JRC.IPTS 3 rd Annual JRC Modelling Conference, Petten, October 2013 Joint Research Centre www.jrc.ec.europa.eu Serving society Stimulating innovation Supporting legislation
Policy issues and JRC contribution PAST 5 YEARS Major policy issues JRC deliverables Regional Policies Cohesion Policy 2007-2013 TEN-T Cohesion Policy 2014-2020 Impact of TEN-T and Cohesion policy 2007-2013 on growth and employment Exploitation and integration of ecosystems services in regional development policies Development of regional geographical information 2
LUMP looks at territorial cohesion and environmental variables affected by regional policy; the regional economic effects are simulated with RHOMOLO QUEST (Dynamic Stochastic General Equilibrium) EU28, NUTS0 Long-run macroeconomic development RHOMOLO (Spatial Computable General Equilibrium) EU27, 267 NUTS2 Regional production Transport cost reductions Regional economy Accessibility TRANSTOOLS (Transport Forecasting and Scenario Testing ) EU28, NUTS3 LUMP (Land Use Modelling Platform) EU28, 100x100m Land use, energy CAPRI, POLES, IMAGE Operated in-house Operated by other DGs
Description of RHOMOLO: CGE/New Economic Geography Six sectors (Agriculture; Energy and Manufacturing; Construction; Wholesale and Retail Trade; Financial and Business Services, Public Services) Spatial agglomeration depends on the interaction between transportation cost and economies of scale A countervailing force is the entry of firms taking advantage of relatively low wages and a better competitive position in the home market of peripheral regions Standard CGE features regarding the behaviour of firms and consumers
Description of RHOMOLO - Consistent regional modelling databases Use of reliable statistical data (wherever possible, primary source Eurostat). Base year 2007, to be updated to 2010 asa data become available (including Croatia) Robust estimation of some data The national SAMs are regionalised based on Eurostat s regional accounts for production and consumption inter-regional trade data
Results of simulations already carried out with RHOMOLO Changes in real regional GDP (% of baseline in 2020) as a result of research and innovation support under Cohesion Policy (2007-2013) 6
RHOMOLO validation / peer review Extensive discussions with JRC.IPTS, DG ECFIN and DG REGIO modellers Presentation at conferences/seminars within and outside the EU Dedicated conferences at JRC.IPTS, Seville, e.g. 14 February 2013 and 2-3 December 2013 Preparation of 4 working papers on simulations carried (two already published in the JRC.IPTS website) Submission of material to peer-reviewed journals (1 already accepted). 7
RHOMOLO: further developments of the model Relatively simple: Endogenisation of impact of R&D (as in QUEST) Further development of the labour market modelling module Demographic development including migration of households and workers Investment modelling Expenditure financed by taxes More complex due to data issues: Refined demand effects of cohesion policy Sectoral disaggregation (up to 59 sectors) 8
Examples of future simulations to be carried out with RHOMOLO Further assessment of impact of expenditure in infrastructure, human capital development, R&D&I, as well as in support to business and the natural environment, e.g. concentration of certain categories of expenditure in capital regions wrt peripheral regions Ex-post evaluation of the of Cohesion policy funding for 2007-2013 - Replication of the 2014-2020 expenditure using final allocation of funds provided by MS - 2016 mid-term review of Cohesion policy 2014-2020 9
Conclusions RHOMOLO is the first model available to the Commission to assess ex ante impact assessments of growth enhancing policies at regional level; It can be easily integrated with other models focusing on other scales of analysis (QUEST), on specific aspects such as land use (LUMP) or on sectors (TRANSTOOLS); Need to assess if it is feasible for RHOMOLO to be operated by DG REGIO colleagues and trusted external organisations 10
What is LUMP Brief description The core of LUMP is a land use model which simulates future land use changes based on biophysical and socio-economic drivers. It assesses the land use impacts of European policies, thus contributing to more complete impact assessments. It is interlinked with several thematic models (water, forest, economy, demography, energy, ), ensuring coherence and consistency of the European scenarios. Main characteristics: - Spatial extent: EU-28 - Spatial resolution: 100 meters - Temporal resolution: yearly (up to 2050) - Primary output: Land use maps, land use changes - Secondary outputs: Spatially explicit thematic indicators 11
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Examples of Territorial Impact Assessment I - **Preliminary results ** Endowment of EU NUTS 2 regions in providing ecosystems services
Examples of Territorial Impact Assessment II - **Preliminary results ** Suitability and regional investment in for solar energy in EU Regions
Land Use Modelling Platform (LUMP): Products & Applications Integrated Coastal Zones Management IA Common Agricultural Policy (post 2013 IA) Blueprint to Safeguard Europe s Water Resources (IA) Implementation of the ENER-CLIMA Reference Scenario Assessment of Shale Gas extraction in PL and D (IA) Cohesion Policy post 2013 (on going) Resource Efficiency Roadmap (Part I completed)
LUMP results: peer-review, validation Extensive and continuous exchange of info (joint seminars, meeting etc.) and products with key client DGs (REGIO, ENV, CLIMA) and the JRC/IPTS/J.2 - Rhomolo team Outputs are based on solid modelling experience from JRC and from collaborating partners in several EU projects Scientific papers in peer-reviewed journals Presentation at conferences/seminars within and outside the EU Acknowledged applications in several policy domains 16
LUMP: recent and on-going developments of the model Expanding LUMP to interact with more JRC and outer models Inclusion of dedicated demand modules: for biomass, water use, land use required by industrial and commercial activity Dynamic population allocation Linking the model's land reference unit with environmental pressures and impacts, through a specific set of environmental indicators (global environmental indicators or life-cycle based indicators) Reinforcing the economic and social dimension Monetary valuations of eco-system services, based on various policy scenarios Feed-back with macro-economic models Endogenous generation of social related scenarios beyond 2020 17
On-going and future simulations and developments for Land Use Integrated Sustainability Assessments On-going simulations: - Resource efficiency road map (environmental consequences of different scenarios of land-take) - Cohesion Policy (potential land use & environmental impacts) Future focus on the following issues (examples): - Sustainable use of resources (e.g. land, water, biomass) - Ecosystem Services 18
LUMP - Conclusions LUMP has already proven to be a useful tool for impact assessments of policies with territorial implications (integrated coastal management, CAP, shale gas); On-going projects based on using LUMP with different policy scenarios (resource efficiency, cohesion policy) are setting the path for further enhancement of the modelling platform; The vision is to move towards an integrated impact assessment approach, through which European policies and targets are supported and monitored based on a coherent modelling platform. 19