Technological interdependence and regional growth in Europe: Proximity and synergy in knowledge spillovers
The economic growth literature suggests that knowledge spillovers are subject to distance decay effects. In this paper the main aim is to provide a theoretical framework and empirical evidence on the role played by other kinds of proximities, namely relational, social and technological proximity, in...
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| Published in | Papers in regional science Vol. 91; no. 4; pp. 697 - 722 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford, UK
Blackwell Publishing Ltd
01.11.2012
Wiley-Blackwell Springer |
| Subjects | |
| Online Access | Get full text |
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| Abstract | The economic growth literature suggests that knowledge spillovers are subject to distance decay effects. In this paper the main aim is to provide a theoretical framework and empirical evidence on the role played by other kinds of proximities, namely relational, social and technological proximity, in explaining productivity growth. Using a sample of 249 EU 27 NUTS 2 regions in the period 1990–2004, semiparametric spatial autoregressive models are estimated. Results provide evidence of a positive role of social and relational proximities as important channels of knowledge spillovers, and on the fact that, when simultaneously present, different kinds of proximities generate synergic effects on growth.
Resumen
La literatura sobre el crecimiento económico sugiere que los spillovers de conocimiento están sujetos a efectos de deterioro por distancia. El objetivo principal de este artículo es proporcionar un marco teórico y pruebas empíricas sobre el papel desempeñado por otros tipos de proximidades (relacional, social y tecnológica), a la hora de explicar el crecimiento de la productividad. Utilizando una muestra de 249 regiones NUTS 2 de la UE 27 para el período 1990‐2004, se estiman modelos autorregresivos espaciales semiparamétricos. Los resultados aportan pruebas del papel positivo de las proximidades sociales y relacionales como canales importantes de spillovers de conocimientos, y del hecho de que, cuando se presentan simultáneamente, los diferentes tipos de proximidades generan efectos sinérgicos sobre el crecimiento. |
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| AbstractList | The economic growth literature suggests that knowledge spillovers are subject to distance decay effects. In this paper the main aim is to provide a theoretical framework and empirical evidence on the role played by other kinds of proximities, namely relational, social and technological proximity, in explaining productivity growth. Using a sample of 249 EU 27 NUTS 2 regions in the period 1990-2004, semiparametric spatial autoregressive models are estimated. Results provide evidence of a positive role of social and relational proximities as important channels of knowledge spillovers, and on the fact that, when simultaneously present, different kinds of proximities generate synergic effects on growth. Resumen La literatura sobre el crecimiento económico sugiere que los spillovers de conocimiento están sujetos a efectos de deterioro por distancia. El objetivo principal de este artículo es proporcionar un marco teórico y pruebas empíricas sobre el papel desempeñado por otros tipos de proximidades (relacional, social y tecnológica), a la hora de explicar el crecimiento de la productividad. Utilizando una muestra de 249 regiones NUTS 2 de la UE 27 para el período 1990-2004, se estiman modelos autorregresivos espaciales semiparamétricos. Los resultados aportan pruebas del papel positivo de las proximidades sociales y relacionales como canales importantes de spillovers de conocimientos, y del hecho de que, cuando se presentan simultáneamente, los diferentes tipos de proximidades generan efectos sinérgicos sobre el crecimiento. The economic growth literature suggests that knowledge spillovers are subject to distance decay effects. In this paper the main aim is to provide a theoretical framework and empirical evidence on the role played by other kinds of proximities, namely relational, social and technological proximity, in explaining productivity growth. Using a sample of 249 EU 27 NUTS 2 regions in the period 1990–2004, semiparametric spatial autoregressive models are estimated. Results provide evidence of a positive role of social and relational proximities as important channels of knowledge spillovers, and on the fact that, when simultaneously present, different kinds of proximities generate synergic effects on growth. Resumen La literatura sobre el crecimiento económico sugiere que los spillovers de conocimiento están sujetos a efectos de deterioro por distancia. El objetivo principal de este artículo es proporcionar un marco teórico y pruebas empíricas sobre el papel desempeñado por otros tipos de proximidades (relacional, social y tecnológica), a la hora de explicar el crecimiento de la productividad. Utilizando una muestra de 249 regiones NUTS 2 de la UE 27 para el período 1990‐2004, se estiman modelos autorregresivos espaciales semiparamétricos. Los resultados aportan pruebas del papel positivo de las proximidades sociales y relacionales como canales importantes de spillovers de conocimientos, y del hecho de que, cuando se presentan simultáneamente, los diferentes tipos de proximidades generan efectos sinérgicos sobre el crecimiento. The economic growth literature suggests that knowledge spillovers are subject to distance decay effects. In this paper the main aim is to provide a theoretical framework and empirical evidence on the role played by other kinds of proximities, namely relational, social and technological proximity, in explaining productivity growth. Using a sample of 249 EU 27 NUTS 2 regions in the period 1990-2004, semiparametric spatial autoregressive models are estimated. Results provide evidence of a positive role of social and relational proximities as important channels of knowledge spillovers, and on the fact that, when simultaneously present, different kinds of proximities generate synergic effects on growth. // ABSTRACT IN : Resumen La literatura sobre el crecimiento económico sugiere que los spillovers de conocimiento están sujetos a efectos de deterioro por distancia. El objetivo principal de este artí ;culo es proporcionar un marco teórico y pruebas empíricas sobre el papel desempeñado por otros tipos de proximidades (relacional, social y tecnológica), a la hora de explicar el crecimiento de la productividad. Utilizando una muestra de 249 regiones NUTS 2 de la UE 27 para el período 1990-2004, se estiman modelos autorregresivos espaciales semiparamé ;tricos. Los resultados aportan pruebas del papel positivo de las proximidades sociales y relacionales como canales importantes de spillovers de conocimientos, y del hecho de que, cuando se presentan simultáneamente, los diferentes tipos de proximidades generan efectos sinérgicos sobre el crecimiento. Reprinted by permission of Blackwell Publihing |
| Author | Caragliu, Andrea Basile, Roberto Capello, Roberta |
| Author_xml | – sequence: 1 givenname: Roberto surname: Basile fullname: Basile, Roberto organization: Seconda Università degli Studi di Napoli, Department of Economics, Corso Gran Priorato di Malta, 1 Capua (CE), 81043 Italy (e-mail: roberto.basile@unina2.it) – sequence: 2 givenname: Roberta surname: Capello fullname: Capello, Roberta organization: Politecnico di Milano, Dep. BEST, Piazza Leonardo 32, 20133 Milan (MI), Italy (e-mail: roberta.capello@polimi.it, andrea.caragliu@polimi.it) – sequence: 3 givenname: Andrea surname: Caragliu fullname: Caragliu, Andrea organization: Politecnico di Milano, Dep. BEST, Piazza Leonardo 32, 20133 Milan (MI), Italy (e-mail: roberta.capello@polimi.it, andrea.caragliu@polimi.it) |
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| Keywords | Measurement Learning process Regional economy Proximity Economic growth Knowledge spillovers Model |
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Journal of Geographical Systems 12: 311-334 Coleman JS (1988) Social capital in the creation of human capital. American Journal of Sociology 94: S95-S120 Putnam RD (2000) Bowling alone. Simon and Schuster, New York Sala A, Landoni P, Verganti R (2011) R&D networks: An evaluation framework. International Journal of Technology Management 53: 19-43 Capello R (2009a) Spatial spillovers and regional growth. European Planning Studies 17: 639-658 Knack S, Keefer P (1997) Does social capital have an economic payoff? A cross-country investigation. Quarterly Journal of Economics 112: 1251-1288 Boschma RA (2005) Proximity and innovation: A critical assessment. Regional Studies 39: 61-74 Feldman M, Audretsch D (1999) Innovation in cities: Science-based diversity, specialization and localized competition. European Economic Review 43: 409-429 Rallet A, Torre A (eds) (1995) Économie industrielle et économie spatiale. Economica, Paris Anselin L (2004) Spatial externalities, spatial multipliers and spatial econometrics. International Regional Science Review 26: 153-166 Ciccone A (2002 )Agglomeration effects in Europe. European Economic Review 46: 213-227 Augustin N, Musio M, von Wilpert K, Kublin E, Wood S, Schumacher M (2009) Modelling spatio-temporal forest health monitoring data. Journal of the American Statistical Association 104: 899-911 Bode E (2004) The spatial pattern of localized R&D spillovers: An empirical investigation for Germany. Journal of Economic Geography 4: 43-64 Cappellin R (2003) Territorial knowledge management: Towards a metrics of the relational dimension of agglomeration economies. International Journal of Technology Management 26: 303-325 Coe DT, Helpman E (1995) International R&D spillovers. European Economic Review 39: 859-887 Frenken K, Ponds R, van Oort F (2010) The citation impact of research collaboration in science-based industries: A spatial-institutional analysis. Papers in Regional Science 89: 351-371 LeSage J, Pace RK (2009) Introduction to spatial econometrics. Taylor & Francis Group, London Maggioni M, Nosvelli M, Uberti E (2007) Space versus networks in the geography of innovation: A European analysis. Papers in Regional Science 86: 471-493 Mankiw NG, Romer D, Weil DN (1992) A contribution to the empirics of economic growth. Quarterly Journal of Economics 107: 407-437 Capello R (1999) Spatial transfer of knowledge in high-technology milieux: Learning vs collective learning processes. Regional Studies 33: 353-365 Wood SN (2006) Generalized additive models: An introduction with R. Chapman & Hall/CRC, Boca Raton, FL Scherngell T, Barber MJ (2009b) Spatial interaction modelling of cross-region R&D collaborations: Empirical evidence from the 5th EU Framework Programme. Papers in Regional Science 88: 531-546 Basile R (2009) Productivity polarization across regions in Europe: The role of nonlinearities and spatial dependence. International Regional Science Review 32: 92-115 2010; 12 1990; 105 2009b; 88 2009; 43 1965; 13 1995; 39 2009a; 43 2006; 38 2004; 26 1997; 112 2004; 4 2011; 53 1999; 45 2005; 21 1999; 43 2011; 16 2007; 34 2003; 52 1993; 3 1998; 17 2006; 20 2001 2000 1995; 27 2002; 46 2004; 35 1986 1983 2001; 15 2007; 2 2005; 39 2007; 22 1989; 79 2003; 43 1994; 76 2004; 44 2009b; 100 1993; 108 1997; 65 2000; 115 2009 2007 2009a; 17 1992; 107 2006 1995 1988; 94 2005 1993 2004 2003 1991 2002 1999 2009; 34 2001; 80 2010; 89 1963; 58 2011; 102 2009; 32 2011; 51 1920 1999; 33 2003; 26 1996; 40 2008; 87 2007; 41 1994; 1 2007; 86 1957; 27 2009; 104 Augustin (10.1111/j.1435-5957.2012.00438.x_b6) 2009; 104 Ertur (10.1111/j.1435-5957.2012.00438.x_b41) 2011; 16 Aldieri (10.1111/j.1435-5957.2012.00438.x_b3) 2009; 34 Bray (10.1111/j.1435-5957.2012.00438.x_b20) 1957; 27 Bourdieu (10.1111/j.1435-5957.2012.00438.x_b1001) 1983 Morgan (10.1111/j.1435-5957.2012.00438.x_b71) 1963; 58 Basile (10.1111/j.1435-5957.2012.00438.x_b11) 2009; 32 (10.1111/j.1435-5957.2012.00438.x_b37) 2005 Lòpez‐Bazo (10.1111/j.1435-5957.2012.00438.x_b63) 2004; 44 Almeida (10.1111/j.1435-5957.2012.00438.x_b4) 1999; 45 Resmini (10.1111/j.1435-5957.2012.00438.x_b78) 2003 Camagni (10.1111/j.1435-5957.2012.00438.x_b23) 2009 Keeble (10.1111/j.1435-5957.2012.00438.x_b57) 2000 Lundvall (10.1111/j.1435-5957.2012.00438.x_b64) 1994; 1 Blundell (10.1111/j.1435-5957.2012.00438.x_b16) 2003 Mora (10.1111/j.1435-5957.2012.00438.x_b69) 2010; 12 Karlsson (10.1111/j.1435-5957.2012.00438.x_b55) 2001 Acs (10.1111/j.1435-5957.2012.00438.x_b1) 1994; 76 Ponds (10.1111/j.1435-5957.2012.00438.x_b74) 2007; 86 Sala (10.1111/j.1435-5957.2012.00438.x_b80) 2011; 53 Scherngell (10.1111/j.1435-5957.2012.00438.x_b81) 2009; 43 Moreno‐Serrano (10.1111/j.1435-5957.2012.00438.x_b70) 2005; 39 Putnam (10.1111/j.1435-5957.2012.00438.x_b75) 2000 Cappellin (10.1111/j.1435-5957.2012.00438.x_b32) 2003; 26 Venables (10.1111/j.1435-5957.2012.00438.x_b83) 2002 Capello (10.1111/j.1435-5957.2012.00438.x_b31) 2011; 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| SubjectTerms | Bgi / Prodig Economic growth Empirical research Europe European Regions General and multiregional studies Productivity R11 Regional development Relational proximity semiparametric additive models social proximity Spillovers Technological dependence technological proximity The economics Vector-autoregressive models |
| Title | Technological interdependence and regional growth in Europe: Proximity and synergy in knowledge spillovers |
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