1. © Henley Business School 2010www.henley.reading.ac.uk School of Real Estate & Planning October 15 Flows & networks (WP2.3.1 / 2.3.2) Kathy Pain, Sandra Vinciguerra University of Reading

2. School of Real Estate & Planning 2.3.1 objectives  To answer the question globalization or “continentalization”. Requires assessing at different scales, openness to globalization and the geography of this openness to the outside world;  To assess the national/regional/cities position in the international division of labour;  To assess the territorial impacts of globalization inside Europe.

3. School of Real Estate & Planning The GaWC data to analyse the 2008 position of European cities in global advanced service networks 1.Europe in the world – top APS gateways (all sectors), financial services + each other sector individually. 2.Dyads – global connections versus European connections – all sectors, financial services + each other sector individually. 3.HQs – analysis of strategic network locations, in the world and within Europe. 4.Comparison between GaWC APS data and real estate financial flows. 3

4. School of Real Estate & Planning Example dyads - NW Europe in the world, 2008

5. School of Real Estate & Planning The GaWC data to analyse the fluid position of European cities in global advanced service networks 5.Time series data can be used to examine different changes, e.g. changing dyadic relations within Europe and between European cities and other world APS nodes + IFCs, also changing HQ strategic locations. 6.Identification of the key agents (firms) producing changing dyadic APS connections, and changing financial services connections, for different European cities. 5

6. School of Real Estate & Planning 2.3.2 objectives  To assess the position of Europe and its cities in global financial flows.  To explain the spatial consequences of the crisis.  To analyse data on real estate investment flows in Europe that create the ‘spaces of places’ in which the global service economy operates.

7. School of Real Estate & Planning The data to map & measure European financial flows through global RE city markets/infrastructure 1. Using RCA data on major deals to look at where deals have taken place  Possible to build a matrix of flows to/from cities.  Potential difficulty is that smaller European cities will only be represented by a small number of deals.  Possible to produce rankings of target cities. 7

8. School of Real Estate & Planning Rankings of target cities, RCA data example 8

9. School of Real Estate & Planning Preliminary 2006 RCA data analysis by Lizieri (International Handbook of Globalization, forthcoming) “As a further indicator of the globalization of property investment, the top thousand deals (which in total represent over 80% of all the sales in the data by value) were analysed and the head office of the acquiring investor were identified. Of these large deals, 44% of all property trades ($189billion) and 38% of office sales ($74billion) were cross-border. Nearly a quarter of all office sales were cross-border and took place in a top-ranked IFC. 50% of buyers were based in top ten international financial centres, a further 10% of buyers were in IFCs ranked 11-20, with less than a third of buyers not having a headquarters in a global financial centre.” *Untraceable private funds + local subsidiaries of non- domestic parent investors. Make these figures underestimates. 9

10. School of Real Estate & Planning 2. Data on rents & yields in European cities  Provide a benchmark and show rises and falls in rents and (hypothetical) capital values for different cities.  These can be mapped onto the capital flows and onto GaWC connectivity measures etc. analytically.  Lizieri has done work on the relationships between rent levels and global financial city status and GaWC ranking – they overlap, but both are statistically significant predictors of rent per square metre. 10

11. School of Real Estate & Planning Rents and yields in European cities 11

12. School of Real Estate & Planning 3. Data on overall capital flows, $billions (DTZ, JLL) 12