POLYCE Metropolisation and Polycentric Development in Central Europe: Evidence Based Strategic Options

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1 POLYCE Metropolisation and Polycentric Development in Central Europe: Evidence Based Strategic Options Roberto Camagni, Roberta Capello, Andrea Caragliu Politecnico di Milano ESPON Italian Evidence in Changing Europe ESPON and your Needs 21 May 2014, Roma

2 The project team Vienna University of Technology - Centre of Regional Science (AT), Leadpartner University of Ljubljana, Faculty of Civil and Geodetic Engineering Slovak University of Technology, Bratislava University of Szeged Czech Technical University in Praha, Faculty of Architecture CEPS/INSTEAD Center for Populations, Poverty and Public Policy Studies, Luxembourg Politecnico di Milano ABC Department, Italy

3 The project stakeholders Department of Urban Development and Planning, City of Vienna (Lead Stakeholder) Department for Spatial Systems Coordination, City of Bratislava Department of Spatial Planning, City of Ljubljana City Development Authority, City of Prague, Studio Metropolitana, Nonprofit Ltd., Hungary

4 General goal of the POLYCE project To contribute to the understanding of: - metropolisation and polycentric development Our task: - to enter the debate if an optimal city size exists at which cities tend to grow and; - to highlight the urban characteristics that allow a city to overcome the decreasing returns; - to measure the role of the urban characteristics on the equilibrium city size.

5 Main ideas throughtout the project (1) The main theory suggests that an optimal city size exists which is reached when the marginal location benefits equal marginal location costs. Cities are different one another and therefore they cannot reach the same city size. Each city maintains its own specificity and unicity, and consequently is attributed its own equilibrium size, i.e. a size that allows marginal location benefits to equate marginal location costs.

6 Main ideas throughtout the project (2) Cities can increase location benefits through: - their specialization in higher level functions; - in networking with other cities Given the same location costs, a city can achieve an equilibrium at a higher size than other cities with the same characteristics.

7 The European sample Canarias Sample of LUZ employed Guadeloupe Martinique Réunion Stockholm Helsinki Tallinn Guyane Madeira Glasgow Riga Belfast Copenhagen Vilnius Groningen Hamburg Szczecin Bremen London Amsterdam Rotterdam MagdeburgBerlin Warszawa Lodz Liège Erfurt Dresden Wroclaw Frankfurt am Main Praha Paris StuttgartRegensburg Freiburg im BreisgauMünchen Linz WienBratislava Budapest Graz Acores Lisboa Porto Madrid Bordeaux Toulouse Zaragoza Barcelona Lyon Ljubljana Milano Torino GenovaBologna Firenze Roma Sofia Bucuresti Valencia Napoli Sevilla Athina

8 Data ariabile Classe di variabili Variabili Indicatore Anni Fonte dei dati nte Dimensione fisica delle città Dimensione Popolazione nelle FUA 2010 ISTAT Benefici urbani tradizionali Qualità della vita Amenities Stanze d'albergo disponibili per 1000 abitanti 2002 ISTAT ente Creatività urbana Diversità Indice di diversità settoriale misurato come il complemento ad 1 dell'indice di Hirschman- Herfindahl calcolato sulle quote settoriali di occupazione 2001 Censimento nazionale dell?industria e dei Servizi 2001 Economie di agglomerazione Densità Densità di popolazione 2005 ISTAT Costi urbani tradizionali Costo della città Costo di un appartamento medio Osservatorio del Rendita fondiaria 2010 al metro quadro Mercato Immobiliare Conflitto sociale Malaise Omicidi registrati per 1000 Sistema di Indicatori 2005 abitanti Territoriali ISTAT Benefici urbani non convenzionali Partecipazioni di istituzioni della Reti urbane Reti urbane FUA a PQ5 sul totale degli occupati Totale CORDIS Funzioni urbane Costi urbani non convenzionali Forma urbana non compatta Funzioni urbane Sprawl Quota di imprese nei settori J e K sul totale delle imprese attive Percentuale di suolo non urbanizzato 2001 Censimento nazionale dell?industria e dei Servizi CORINE Land Cover

9 Theoretical predictions (1) 16,5 16,0 Paris Log predicted population ,5 15,0 14,5 14,0 13,5 Wien München Milano Lisboa Stuttgart Glasgow Frankfurt Budapest am Main Helsinki Lyon Praha Bucuresti Valencia Copenhagen Torino Stockholm Dresden Toulouse Porto Sevilla Utrecht Firenze Hannover Bordeaux Napoli Warszawa Amsterdam Rotterdam Zaragoza Belfast Genova Edinburgh Bremen Bratislava Riga Lodz Tallinn Bologna Wroclaw Ljubljana Vilnius Sofia Freiburg im Breisgau Linz Liège Erfurt Roma Hamburg Barcelona Athina Berlin Madrid London y = 0,822x + 2,5115 R² = 0,822 13,0 Magdeburg 13,0 13,5 14,0 14,5 15,0 15,5 16,0 16,5 Log real population

10 Predicted city size actual city size - European cities 8% 6% Cities that can still expand Cities that are already too large 4% 2% 0% Amsterdam Firenze Tallinn Graz Edinburgh Groningen Belfast Zaragoza Paris Lisboa Porto Dresden Glasgow Bratislava Bordeaux Bologna Regensburg Toulouse Freiburg im Breisgau Milano Wroclaw Linz Sevilla Genova Magdeburg Vilnius Lyon Ljubljana Helsinki Riga Erfurt Valencia München Utrecht Madrid Stockholm Frankfurt am Main Budapest Bremen Lodz Torino Stuttgart Athina Wien Liège Warszawa Copenhagen Praha London Barcelona Hannover Berlin Hamburg Rotterdam Roma Napoli Sofia Bucuresti -2% -4% -6% -8% Predicted equilibrium population over actual population (%)

11 Italian cities that can still expand Popolazione di equuilibrio predetta su popolazione reale (%) Torino Cuneo Brescia Foggia Pavia Roma Catania Macerata Enna Bergamo Cremona Mantova Treviso Rovigo Palermo Bari Perugia Salerno Reggio nell'emilia Verona Arezzo Latina Vicenza Caserta Sassari Bologna Caltanissetta Grosseto Alessandria Trapani Firenze Modena Lucca Taranto Ferrara Oristano Nuoro Como Piacenza Udine Vercelli Agrigento Rieti Benevento Asti Bolzano-Bozen Lecce Parma Pordenone Cosenza Reggio Pisa Avellino Genova Cagliari

12 Italian cities that can still expand Popolazione di equuilibrio predetta su popolazione reale (%) Varese Viterbo Chieti Trento Belluno Venezia Lecco Frosinone Napoli Crotone Novara Milano Potenza Padova Siracusa Massa-Carrara Campobasso Savona Verbano-Cusio-Ossola Pesaro Catanzaro Ancona Terni Messina La Spezia Forlì-Cesena Imperia Brindisi Ragusa Lodi Ravenna Pistoia Siena Prato Teramo Biella Livorno Matera Pescara L'Aquila Ascoli Isernia Aosta Sondrio Rimini Vibo Trieste Gorizia

13 Results by typology of regions 1.0% 0.5% Popolazione di equuilibrio predetta su popolazione reale (%) 0.0% -0.5% -1.0% Regione non metropolitana Regione metropolitana piccola Regione metropolitana media Regione metropolitana grande -1.5% -2.0%

14 Predicted equilibrium population for different levels of high-value urban functions Predicted equilibrium population Hannover Freiburg Copenhagen Praha RigaWroclaw Lodz Belfast Magdeburg Wien Hamburg im Erfurt Utrecht Toulouse Firenze Glasgow Bordeaux Edinburgh Stockholm Porto Bologna Vilnius Torino Helsinki Valencia Lisboa Budapest Breisgau Frankfurt Groningen Regensburg Ljubljana Szczecin Zaragoza Genova Linz Sofia Liège TallinnDresden am Main Bratislava Bremen Graz Bucuresti Napoli Stuttgart Warszawa Berlin Amsterdam Roma Athina München Lyon Rotterdam Sevilla Madrid Barcelona Milano Paris London % 1% 2% 3% 4% 5% 6% 7% High level urban functions (share of high-quality professions)

15 Predicted equilibrium population for different levels of networking with other cities Predicted equilibrium population Szczecin Erfurt Rotterdam Barcelona Sofia Liège Ljubljana Budapest Groningen Helsinki Lisboa Berlin Bratislava Utrecht Praha Bucuresti Freiburg Warszawa Dresden Hannover Tallinn Torino Zaragoza Milano Firenze Glasgow im Breisgau Valencia Magdeburg Belfast Riga Linz Bologna Stockholm Athina Bremen Frankfurt Regensburg Copenhagen Napoli Sevilla Porto Lyon am Main Wroclaw Vilnius Lodz Bordeaux Wien Stuttgart City networking (number of scientific collaborations per 1,000 workers)

16 Predicted equilibrium population for different levels of networking with other cities Predicted equilibrium population Szczecin Erfurt Rotterdam Barcelona Sofia Liège Ljubljana Budapest Groningen Helsinki Lisboa Berlin Bratislava Utrecht Praha Bucuresti Freiburg Warszawa Dresden Hannover Tallinn Torino Zaragoza Milano Firenze Glasgow im Breisgau Valencia Magdeburg Belfast Riga Linz Bologna Stockholm Athina Bremen Frankfurt Regensburg Copenhagen Napoli Sevilla Porto Lyon am Main Wroclaw Vilnius Lodz Bordeaux Wien Stuttgart City networking (number of scientific collaborations per 1,000 workers)

17 Conclusions - The size of the city is not the only one that explains location benefits and costs and that is behind the growth of cities; - City specificities are of great importance for the city capacity to grow; - decreasing returns to urban size can be postpone if efficiency policies on innovative functions and on networking with other cities are put in place.

18 Thank you very much for your attention!