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ESPON Project 1.4.4 Preparatory Study on Feasibility of Flows Analysis

ESPON Project 1.4.4 Preparatory Study on Feasibility of Flows Analysis. ESPON Seminar 14-15 November 2006 Espoo, Finland. Spiekermann & Wegener Urban and Regional Research (S&W) Dortmund, Germany (Lead Partner)

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ESPON Project 1.4.4 Preparatory Study on Feasibility of Flows Analysis

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  1. ESPON Project 1.4.4Preparatory Study on Feasibility of Flows Analysis ESPON Seminar 14-15 November 2006 Espoo, Finland

  2. Spiekermann & WegenerUrban and Regional Research (S&W)Dortmund, Germany (Lead Partner) • Institute of Geography and Spatial OrganisationPolish Academy of Sciences (IGIPZ PAN)Warsaw, Poland • TRTTrasporti e Territorio SrlMilano, Italy Transnational Project Group

  3. “Our societies are constructed around flows: flows of capital, flows of information, flows of technology, flows of organizational interactions, flows of images, sounds and symbols ... they are the expression of the processes dominating our economic, political, and symbolic life. Thus, I propose the idea that there is a new spatial form characteristic of social practices that dominate and shape the network society: the space of flows. (Castells, 1996, 412) Space of flows

  4. What flows can be integrated into the ESPON Analysis? • What are the implications of the integration of flow analysis? • What should ESPON focus on in the future? Key research questions

  5. Project structure

  6. Objectives: to address needs of European Spatial Observatory • Bottom-up approach: Analysis of all existing ESPON studies • Top-Down approach: Identification of potential value of flow analysis • From a theoretical perspective • From a political perspective ESPON needs for flow analysis

  7. Relevant thematic flow types: • Trade flows • Financial flows • Migration flows • Transport flows • Commuter flows • Information flows • Environmental flows • Tourism flows • Cultural exchange ESPON needs for flow analysis (2)

  8. Objectives: Analysis of availability of flow data in Europe • Availability of existing data and identification of data gaps • Information sources: • Data navigator and ESPON reports • Research into European and national statistics • Meta analysis of existing research reports Data availability

  9. Data availability (2): measurement points

  10. Data are in general incomplete or entirely lacking • Flow data contain very often only one spatial attribute (origin or destination or location passed through) • Flows between NUTS-2 or NUTS-3 regions exist, if at all, only within one country • Few trans-national flow data available suffer from insufficent spatial resolution and lack of standardisation Data availability (3)

  11. Objectives: Investigation of the availability and practicability of flow data generation methodologies • Check of reliability and validity of methodologies • Basic methodologies • Numeric algorithms -> Monte-Carlo method, entropy-maximisation approach, bi-proportional fitting • Modelling approaches -> make use of theories to explain flow pattern • In-depth examples: • Migration data generation methodologies • Transport flow data generation methodologies Data generation methodologies

  12. Objectives: Show potential of flow analysis for the enrichment of territorial analysis in ESPON • Data limitations: • Not always European-wide examples, but on selected territories • Not always down to NUTS-3 level • Data generation methodologies included • What is feasible and what can be expected from flow analysis within ESPON • Experiments with different forms of visualisation of flow data in form of maps and diagrams Demonstration examples

  13. Demonstration examples (2)

  14. Trade flows

  15. Trade The exchange of goods with other regions is the essential base for the economic development of regions. The volume and direction of international trade flows in Europe have undergone significant changes during the last two decades, in particular through the enlargement of the EU between the old and new member states. The analysis of trade flows between regions is important for the assessment of - transport demand - regional economic development - spatial cohesion and polycentricity The demonstration example deals with the foreign trade of Polish regions between 2000 and 2005.

  16. Data The database for the demonstration example were matrices of exports and imports between all European countries and 379 Polish counties (NUTS-4 = LAU 1) in 2000 and 2005 expressed in US Dollars. The data are based on the reporting from the companies conducting foreign trade and are estimated to include about 90% of all foreign trade. Comparison between 2000 and 2005 was not possible for counties that were divided between 2000 and 2005. Indicators were calculated by aggregating trade flows to origin and destination regions.

  17. Exports 2000-2005

  18. Imports 2000-2005

  19. Exports to Germany 2000-2005 Change of Polish regional exports to Germany 2000-2005 (2000=100)

  20. Exports and imports 2005 Export linkagesImport linkages

  21. Conclusions for ESPON Due to the key economic role of trade, information on trade flows is an important component of regional analysis. The analysis of trade flows is important for the assessment of transport demand, regional economic development and spatial cohesion and polycentricity. The dynamic analysis of trade flows is particularly relevant for the monitoring and forecasting of the spatial impacts of cohesion policies on convergence between the old and new EU member states. When coupled with freight transport analysis, the study of spatial trade patterns is relevant for future EU transport policy.

  22. Migration flows

  23. Definition of migration In 2005 the European Commission proposed a definition of international migration: • Immigration means the action by which a natural person establishes his or her usual residence in the territory of a Member State for a period that is, or is expected to be, of at least twelve months, having previously been usually resident in another Member State or a third country. • Emigration means the action by which a natural person having previously been usually resident in the territory of a Member State, ceases to have his usual residence in that Member State for a period that is, or is expected to be, of at least twelve months.

  24. Definition of migration However, these definitions are by no means used in all EU member states: • There is a great lack of uniformity in the definitions of migration used. • Definitions vary significantly not only between countries but also within countries over time. • Residence is a vaguely defined term; it can be inter-preted from a legal or actual point of view. • Duration of stay: The minimum time varies between three months and one year. • In some countries not actual but expected duration of stay is accounted for.

  25. Migration data Immigration v. outmigration 1999 (Eurostat)

  26. Forecasting migration There are essentially three main approaches to forecasting migration: • In net migration models the balance of immigration and outmigration of a region is modelled as a function of push and pull factors of the region. • In multiregional demography migration flows are the outcome of migration probabilities observed in the past (e.g. the probability that a person of a certain age and gender migrates from one region to another. • in push-and-pull migration models migration flows are the outcome of push factors in the origin region and pull factors in the destination region.

  27. Migration policy Migration function Population Income Labour force Unemploy- ment Migration in the SASI model

  28. Migration function The new migration function forecasts migration flows between NUTS-3 regions as a function of variables: SizePopulation of origin region Employment of destination region Push/pull low/high GDP per capita low/high quality of life low/high population density BarriersPolitical barriers to migration Cultural barriers to migration Language barriers to migration DistanceAir-line distance

  29. Model results EU27 internal and external migration flows 2002

  30. Model results Net migration (%) 2002

  31. Conclusions for ESPON Analysis and forecasting of migration flows is an indispen- sable component of regional analysis and forecasting. A model of interregional migration flows at the NUTS-3 level is feasible. Such a model should • distinguish between the different motives for student, labour and retirement migration, • take account of different age structures of student, labour and retirement migrants, • should explicitly address neglected issues of asylum seekers and illegal immigrants, • should pay attention to intraregional migration, such as suburbanisation.

  32. Passenger flows

  33. Mobility Mobility is a fundamental need of individuals. Most human activities require a trip to meet other people and to reach the place where the activity can take place. The continuous growth in affluence and car ownership, the emergence of the European high-speed rail network and the introduction of low-fare airlines and the rise of regional airports have made it possible for more and more individuals to travel. Mobility of individuals between regions and countries has grown with the political and economic integration of Europe.

  34. Data Two data sources were used for the demonstration example on passenger flows: • The ETIS-BASE database contains total passenger trips between NURS-2 regions. • The SCENES model produces intraregional and inter-regional trips between NUTS-2 regions segmented by trip purpose. In a strict sense the passenger flow data used represent no empirical data, such as traffic counts, but predictions by travel models. The passenger flow data were used to calculate a number of regional and network indicators.

  35. Passenger trips Passenger trips attracted from other regions (ETIS-BASE)

  36. Business trips Business trips attracted from other regions (ETIS-BASE)

  37. Business trips Tourist trips attracted from other regions (ETIS-BASE)

  38. Road link loads Source: SCENES

  39. Conclusions for ESPON Information on passenger flows is an important component of regional analysis, e.g. the analysis of polycentricity. Information on passenger flows is available only in the form of predictions by travel models of flows between NUTS-2 regions. However, a large part of personal mobility occurs inside of NUTS-2 regions. The TRANS-TOOLS model will provide NUTS-3 level passenger flow matrices. Extending the analysis to trips within NUTS-3 regions would require to collect more detailed data. Because the development and maintenance of a detailed travel model is a huge task, ESPON should co-operate with authors of existing travel models rather than develop its own travel modelling capability.

  40. Nine types of flows of particular importance for ESPON: trade flows, financial flows, migration flows, transport flows, commuter flows, tourist flows, cultural exchange, information flows and environmental flows • indispensable ingredients of a holistic analysis of spatial development and of direct relevance for EU Policies • significant importance for the main goals of the European Union, economic competitiveness, territorial cohesion and environmental sustainability Conclusions (1): Added value of flow analysis

  41. theoretical concepts and feasible analytical methods for monitoring, analysing, assessing and forecasting each of these types of flows at all spatial scales exist • Data on spatial flows are in general incomplete or entirely lacking • Methods of bridging data gaps or generating synthetic interregional flow data are major challenges of flow analysis • Not all types of flows are suitable for establishing a forecasting capability in ESPON • required complexity of the forecasting models • case for transport and environmental flows • use result of existing models and co-operation with other research institutions and European Agencies • For other types of flows, original innovative work by EPSON is required Conclusions (2): Feasibility of flows analysis

  42. Projects on specific flow types • Migration flows • Freight flows • Passenger flows • Projects on flows and spatial development • Polycentricity • Urban/rural relationships • Enlargement Conclusions (3): Future ESPON Projects

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