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on Economic Geography |
| By: | Roberta Capello (Politecnico di Milano, Italy); Andrea Caragliu (Politecnico di Milano, Italy, VU University Amsterdam, The Netherlands); Peter Nijkamp (VU University Amsterdam, The Netherlands) |
| Abstract: | Knowledge drives the growth of nations and regions in a competitive space-economy. Hence, we would expect a strong correlation between investments in R&D, knowledge and learning processes, on the one hand, and productivity increases, on the other. However, the empirical evidence shows consistent discrepancies between knowledge inputs and economic performance across geographical units. This paper addresses this intriguing issue at the regional level, by highlighting both theoretically and empirically the strategic importance played by cognitive elements as part of “territorial capital” in mediating between knowledge production and regional growth. The main proposition of the paper, subject to empirical testing, is that cognitive elements as part of territorial capital magnify the contribution of knowledge by determining the formation of increasing returns to knowledge exploitation. |
| Keywords: | territorial; capital; regional growth; cognitive; knowledge; rivalry; R&D |
| JEL: | R11 R15 R58 |
| Date: | 2009–07–28 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:uvatin:20090059&r=geo |
| By: | Nappi-Choulet, Ingrid (ESSEC Business School); Maury, Tristan-Pierre (EDHEC Business School) |
| Abstract: | This original study examines the potential of a spatiotemporal autoregressive Local (LSTAR) approach in modelling transaction prices for the housing market in inner Paris. We use a data set from the Paris Region notary office (“Chambre des notaires d’Île-de-France”) which consists of approximately 250,000 transactions units between the first quarter of 1990 and the end of 2005. We use the exact X -- Y coordinates and transaction date to spatially and temporally sort each transaction. We first choose to use the spatiotemporal autoregressive (STAR) approach proposed by Pace, Barry, Clapp and Rodriguez (1998). This method incorporates a spatiotemporal filtering process into the conventional hedonic function and attempts to correct for spatial and temporal correlative effects. We find significant estimates of spatial dependence effects. Moreover, using an original methodology, we find evidence of a strong presence of both spatial and temporal heterogeneity in the model. It suggests that spatial and temporal drifts in households socio-economic profiles and local housing market structure effects are certainly major determinants of the price level for the Paris Housing Market. |
| Keywords: | Hedonic Prices; Heterogeneity; Paris Housing Market; STAR Model |
| JEL: | C51 R33 |
| Date: | 2009–07 |
| URL: | http://d.repec.org/n?u=RePEc:ebg:essewp:dr-09004&r=geo |
| By: | Thomas Y. Mathä; Allison Shwachman |
| Abstract: | This paper empirically analyses the link between market potential and regional wages in the enlarged EU. We extend previous studies of EU regions in several ways. 1) we analyze the link between market potential and wages for the EU27, 2) correct for spatial autocorrelation present in the data, showing that by neglecting spatial autocorrelation the strength of the relationship between market potential and wages may be underestimated, 3) decompose total market potential into several geographical components and analyze their respective contributions to explaining the geographical wage structure, and 4) explore which regions have gained the most from European integration by calculating counterfactual market potential if they could only trade with other regions within the same country. Length: 48 pages |
| Date: | 2009–04 |
| URL: | http://d.repec.org/n?u=RePEc:bcl:bclwop:cahier_etudes_37&r=geo |
| By: | Jeffrey Lin |
| Abstract: | Where does adaptation to innovation take place? The author presents evidence on the role of agglomeration economies in the application of new knowledge to production. All else equal, workers are more likely to be observed in new work in locations that are initially dense in both college graduates and industry variety. This pattern is consistent with economies of density from the geographic concentration of factors and markets related to technological adaptation. A main contribution is to use a new measure, based on revisions to occupation classifications, to closely characterize cross-sectional differences across U.S. cities in adaptation to technological change. Worker-level results also provide new evidence on the skill bias of recent innovations. |
| Keywords: | Cities and towns ; Urban economics ; Labor market ; Job creation ; Technological innovations |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:09-17&r=geo |
| By: | Karine Roux (CEREFIGE - Institut National Polytechnique de Lorraine - INPL); Rani Jeanne Dang (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis); Catherine Thomas (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis); Christian Longhi (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis); D. Talbot (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - CNRS : UMR5113 - Université Montesquieu - Bordeaux IV) |
| Abstract: | A great deal of studies has focused on the role played by geographical location on the emergence and the building of localised learning capacities (Maskell, Malmberg, 1999). In this perspective, empirical studies have demonstrated that innovation dynamics of clusters results from the quality of interactions and coordination inside the cluster as well as interactions with external, often global, networks. In this context, knowledge exchange between firms and institutions are claimed to be the main drivers of spatial agglomeration (Canals et al, 2008). Hence, cluster policies have followed the main idea that geographic proximity facilitates collective innovation in so far as firms can capture knowledge externalities more easily. This idea is in fact very attractive but contains some limits (Suire et Vicente, 2007): if some clusters are successful others seem to decline. Therefore, in order to understand the territorial dynamics of clusters, the analysis of the specific nature of knowledge and information flows within a cluster is crucial. The objective of the paper is to enhance the analysis of the role of cognitive and relational dimensions of interactions on territorial dynamics of innovation. We focus on the key sub process of innovation: knowledge creation, which is above all a social process based on two key complex social mechanisms: the exchange and the combination of knowledge (Nahapiet and Goshal, 1996). We suggest building a theoretical framework that hinges on these two key mechanisms. In this perspective, we mobilise Boisot's I-Space model (Boisot, 1998) for the diffusion and exchange of knowledge and suggest completing the model by introducing the concept of architectural knowledge (Henderson and Clark, 1990) so as to take the complexity of the combination process into consideration. This analysis is conducted through the illustrative analysis of three different case studies. We will draw upon the case of Aerospace Valley Pole of Competitiveness (PoC), The Secured Communicating Solutions PoC, and Fabelor Competence Cluster. The cases show that the existence of architectural knowledge is pivotal to territorial innovation. |
| Keywords: | Architectural Knowledge, I-Space Model, Territorial Innovation, Geographical Clusters, Knowledge Management |
| Date: | 2009–07–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-00365192_v1&r=geo |
| By: | Angel de la Fuente |
| Abstract: | The central and regional governments of Spain have recently reached an agreement to reform the regional financing system. This paper describes the structure of the new system and provides preliminary estimates of its initial financial results. It also identifies some shortcomings of the new model. |
| Date: | 2009–07 |
| URL: | http://d.repec.org/n?u=RePEc:fda:fdacee:08-09&r=geo |
| By: | Marvin M. Smith; John Wackes; Tony E. Smith |
| Abstract: | This paper continues the use of the spatial void hypothesis methodology to analyze the location of alternative financial service providers, such as check cashing outlets and pawn shops, in New Castle County, Delaware, and Atlantic, Mercer, Monmouth, and Passaic counties in New Jersey. Also explores whether these providers are disproportionately serving minority and low-income areas. |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpcd:09-01&r=geo |
| By: | Kurt R. Brekke (Department of Economics and Helth Economics Bergen, Norwegian School of Economics and Business Administration); Luigi Siciliani (Department of Economics and Centre for Health Economics, University of York, Heslington); Odd Rune Straume (Universidade do Minho - NIPE) |
| Abstract: | We study the relationship between competition and quality within a spatial competition framework where firms compete in prices and quality. We generalise existing literature on spatial price-quality competition along several dimensions, including utility functions that are non-linear in income and cost functions that are non-separable in output and quality. Our main message is that the scope for a positive relationship between competition and quality is underestimated in the existing literature. If we allow for income effects by assuming that utility is strictly concave in income, we find that lower transportation costs always lead to higher quality. The presence of income effects might also reverse a previously reported negative relationship between the number of firms and equilibrium quality. This reversal result is further strenghtened if there are cost substitutabilities between output and quality. Equilibrium quality provision is always less than socially optimal in the presence of income effects. |
| Keywords: | Spatial competition; Quality; Income effects. |
| JEL: | D21 L13 L15 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:nip:nipewp:21/2009&r=geo |