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on Economic Geography |
| By: | Carlino, Gerald A. (Federal Reserve Bank of Philadelphia); Kerr, William R. (Harvard University, Bank of Finland, and NBER) |
| Abstract: | Draft chapter for the forthcoming Handbook of Regional and Urban Economics, Vols. 5A and 5B This paper reviews academic research on the connections between agglomeration and innovation. The authors first describe the conceptual distinctions between invention and innovation. They then discuss how these factors are frequently measured in the data and note some resulting empirical regularities. Innovative activity tends to be more concentrated than industrial activity, and the authors discuss important findings from the literature about why this is so. The authors highlight the traits of cities (e.g., size, industrial diversity) that theoretical and empirical work link to innovation, and they discuss factors that help sustain these features (e.g., the localization of entrepreneurial finance). |
| Keywords: | Agglomeration; Clusters; Innovation; Invention; Entrepreneurship |
| JEL: | J2 J6 L1 L2 L6 O3 R1 R3 |
| Date: | 2014–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedpwp:14-26&r=geo |
| By: | Aziza Garsaa; Nadine Levratto |
| Abstract: | This paper seeks to shed some light on the relationship between individual performance and local context. We empirically address this question focusing on the employment growth rate of French manufacturing establishments geo-referenced at the employment area level, an economically consistent territorial division. Using an unbalanced panel of 149,929 plants over the period 2004-2010, we estimate different growth models including local specific variables controlled with company specific ones. The results confirm that the firm growth rate is influenced by the local context and that some features such as unemployment, agglomeration effects or skills matter significantly. The robustness checks performed on subsamples, however, show that the profile of the areas or the market (local or larger) may significantly affect the intensity of the link between a firm and its environment. |
| Keywords: | firm growth, geographical location, manufacturing industry, panel data. |
| JEL: | L25 R11 C23 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2014-49&r=geo |
| By: | Rani Jeanne Dang (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR7321 - Université Nice Sophia Antipolis (UNS)); Karine Roux (CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - Université Nancy II : EA3942 - Université de Metz); Christian Longhi (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR7321 - Université Nice Sophia Antipolis (UNS)); Damien Talbot (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - CNRS : UMR5113 - Université Montesquieu - Bordeaux IV); Catherine Thomas (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR7321 - Université Nice Sophia Antipolis (UNS)) |
| Abstract: | Many studies have focused on the role played by geographical location in the emergence and building of localised learning capacities (Maskell and Malmberg, 1999). In this perspective, empirical studies have demonstrated that the innovation dynamics of clusters result 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 that firms can capture knowledge externalities more easily. This idea is in fact very attractive but contains some limitations (Suire and 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 this paper is to enhance the analysis of the role of cognitive and relational dimensions of interactions in 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 line, we apply 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 into consideration the complexity of the combination process. 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 the 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 |
| Date: | 2014–01–14 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-00929802&r=geo |
| By: | Stuart S. Rosenthal (Syracuse University); Stephen L. Ross (University of Connecticut) |
| Abstract: | This paper reviews recent literature that considers and explains the tendency for neighborhood and city-level economic status to rise and fall. A central message is that although many locations exhibit extreme persistence in economic status, change in economic status as measured by various indicators of per capita income is common. At the neighborhood level, we begin with a set of stylized facts, and then follow with discussion of static and dynamic drivers of neighborhood economic status. This is mirrored at the metropolitan level. Durable but slowly decaying housing, transportation infrastructure, and self-reinforcing spillovers, all influence local income dynamics, as do enduring natural advantages, amenities and government policy. Three recurring themes run throughout the paper: (i) Long sweeps of time are typically necessary to appreciate that change in economic status is common; (ii) history matters; and (iii) a combination of static and dynamic forces ensure that income dynamics can and do differ dramatically across locations but in ways that can be understood. |
| Keywords: | Neighborhood income dynamics; city income dynamics; durable housing; transportation infrastructure; spillovers; persistence, path dependence, and cycles. |
| JEL: | R0 R1 R2 R3 R4 |
| Date: | 2014–09 |
| URL: | http://d.repec.org/n?u=RePEc:uct:uconnp:2014-23&r=geo |
| By: | Pierre-Alexandre Balland, David Rigby & Ron Boschma; David Rigby; Ron Boschma |
| Abstract: | We study the resilience of cities by analyzing their relative capacity to sustain the production of technological knowledge in the face of adverse events. Using patent applications in 366 Metropolitan Statistical Areas in the United States from 1975 to 2002, we analyze the vulnerability and response of cities to technological crises. We define episodes of technological crisis as periods of sustained negative growth in patenting activity. We find that the frequency, intensity and duration of technological crises vary considerably across American cities. We test whether the technological knowledge bases of cities, their network openness and institutional environment condition their resilience to technological crises. Econometric analysis suggests that cities with knowledge bases that are diverse, flexible and that have a high degree of relatedness to technologies in which they do not currently possess comparative advantage tend to avoid technological crises, have limited downturns in patent production and faster recovery. |
| Keywords: | urban resilience, technological crisis, related knowledge structure, institutions, inter-city networks |
| JEL: | O33 R11 L65 D83 |
| Date: | 2014–10 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:1419&r=geo |
| By: | Mikel Navarro (Orkestra – University of Deusto); Juan José Gibaja (University of Deusto); Susana Franco (Orkestra – University of Deusto); Asier Murciego (Orkestra – University of Deusto); Carlo Gianelle (European Commission – JRC - IPTS); Alexander Kleibrink (European Commission – JRC - IPTS); Fatime Barbara Hegyi (European Commission – JRC - IPTS) |
| Abstract: | One of the most basic conditions required for drawing lessons from regional benchmarking is to compare homogeneous regions and learn from equivalents. This condition is not met when regions for comparison are chosen based on their high performance, overlooking their regional context or structural conditions. This paper aims to provide a new methodology for the identification of homogeneous regions for regional benchmarking; identifying groups of homogeneous regions using variables that are similar in nature; focusing solely on structural conditions, thereby overcoming the flaws produced by mixing variables of a different nature (comparing structural indicators with performance and / or behavioural indicators). Thus, regional benchmarking can be of great help in making strategic decisions within the process of the design and implementation of regional Research and Innovation Strategies for Smart Specialisation (RIS3), taking into account the relative position of the region to other regions in Europe. Following the RIS3 approach of looking beyond the regional administrative boundaries, benchmarking based on structural similarity enables the region to identify its competitive advantages through systematic comparisons with other regions or to map the national and international context in search of examples to learn from, or to mark a difference with. |
| Keywords: | European cohesion policy, Structural Funds, smart specialisation, regional benchmarking, structural similarity, policy learning |
| JEL: | C43 R12 R58 |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc89819&r=geo |
| By: | M. Scott Taylor (University of Calgary); Moreno |
| Abstract: | This paper sets out a simple spatial model of energy exploitation to ask how the location and productivity of energy resources may affect the distribution of economic activity around the globe. This is a very large research question, and we take one small step towards answering it by combining elements from resource and energy economics into one framework that links the spatial productivity of energy sources (both renewable and non-renewable) to the incentives for economic activity to concentrate. Our theory provides a novel scaling law; a magnification effect; and reveals a complementarity between infrastructure investment and spatially productive energy resources. Our empirical work provides estimates of key model attributes and reviews related empirical work supporting our approach. |
| Date: | 2014–09–29 |
| URL: | http://d.repec.org/n?u=RePEc:clg:wpaper:2014-67&r=geo |
| By: | John T. Addison (University of South Carolina, Durham University, GEMF-University of Coimbra, and IZA Bonn); McKinley L. Blackburn (University of South Carolina); Chad D. Cotti (University of Wisconsin-Oshkosh and University of Connecticut) |
| Abstract: | Recent attempts to incorporate spatial heterogeneity in minimum-wage employment models have been attacked for using overly simplistic trend controls, and for neglecting the potential impact on employment growth. We investigate whether such considerations call into question our earlier findings of statistically insignificant employment effects for the restaurant-and-bar sector. We find that a focus on employment levels is still appropriate, and nonlinear trend controls do not dislodge our limited support for the existence of minimum-wage effects. |
| Keywords: | minimum wages, employment, employment change, spatial controls. |
| JEL: | J23 J38 |
| Date: | 2014–09 |
| URL: | http://d.repec.org/n?u=RePEc:gmf:wpaper:2014-17.&r=geo |
| By: | Andrea Amaral (ISEG, University of Lisbon); Margarida Abreu (ISEG, University of Lisbon and UECE); Victor Mendes (CMVM and CEFAGE-UE) |
| Abstract: | We use a spatial Probit model to study the effect of contagion between banking systems of different countries. Applied to the late 90’s banking crisis in Asia we show that the phenomena of contagion is better seized using a spatial than a traditional Probit model. Unlike the latter, the spatial Probit model allows one to consider the cascade of cross and feedback effects of contagion that result from the outbreak of one initial crisis in one country or system. These contagion effects may result either from business connections between institutions of different countries or from institutional similarities between banking systems. |
| Keywords: | Spatial probit; Banking crises; Contagion. |
| JEL: | C21 C25 G01 G21 |
| Date: | 2014 |
| URL: | http://d.repec.org/n?u=RePEc:cfe:wpcefa:2014_05&r=geo |
| By: | Sunak, Yasin (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)); Madlener, Reinhard (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN)) |
| Abstract: | Today’s investment decisions in large-scale onshore wind projects in Germany are no longer determined only by the investment’s economic benefit, but also by concerns associated to social acceptance. Despite a mostly positive attitude towards the expansion of wind power, local public concerns often stem from the belief that the proximity to large-scale wind farms may lead to a decrease in property prices. In particular, the change in landscape caused by the construction of a wind farm may have an adverse impact on the view from some properties, and thus may negatively affect their price. To investigate the potential devaluation of properties in Germany due to wind farms, we use a quasi-experimental technique and apply a spatial difference-in-differences approach to various wind farm sites in the federal state of North Rhine-Westphalia. We adopt a quantitative visual impact assessment approach to account for the adverse environmental effects caused by the wind turbines. To properly account for spatial dependence and unobserved variables biases, we apply augmented spatial econometric models. The estimates indicate that the asking price for properties whose view was strongly affected by the construction of wind turbines decreased by about 10-17%. In contrast, properties with a minor or marginal view on the wind turbines experienced no devaluation. |
| Keywords: | Wind power; Difference-in-differences; Visual impact; Spatial dependence |
| JEL: | Q42 Q51 R31 |
| Date: | 2014–02 |
| URL: | http://d.repec.org/n?u=RePEc:ris:fcnwpa:2014_001&r=geo |