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on Economic Geography |
| By: | Lorenzo Caliendo; Fernando Parro; Esteban Rossi-Hansberg; Pierre-Daniel Sarte |
| Abstract: | We study the impact of regional and sectoral productivity changes on the U.S. economy. To that end, we consider an environment that captures the effects of interregional and intersectoral trade in propagating disaggregated productivity changes at the level of a sector in a given U.S. state to the rest of the economy. The quantitative model we develop features pairwise interregional trade across all 50 U.S. states, 26 traded and non-traded industries, labor as a mobile factor, and structures and land as an immobile factor. We allow for sectoral linkages in the form of an intermediate input structure that matches the U.S. input-output matrix. Using data on trade flows by industry between states, as well as other regional and industry data, we obtain the aggregate, regional and sectoral elasticities of measured TFP, GDP, and employment to regional and sectoral productivity changes. We find that such elasticities can vary significantly depending on the sectors and regions affected and are importantly determined by the spatial structure of the US economy. |
| JEL: | E0 F1 F16 R12 R13 |
| Date: | 2014–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:20168&r=geo |
| By: | Semih Akçomak (TEKPOL, Science and Technology Policy Studies, Middle East Technical University); Hanna Müller-Zick (Maastricht University) |
| Abstract: | This paper investigates the effect of trust on innovation. In addition to generalised trust we use a range of other indicators that could measure trust and investigate which trust related variables could explain innovation in 20 European countries divided into 135 regions. We specifically look at causal, non-linear and spatial forces. Our findings indicate that only generalised trust and non-egoistic fairness have robust effects on innovation in Europe. Using historical data on the extent and existence of universities and an instrumental variable strategy we set up a causal relationship between trust and innovation. Even after controlling for causal, spatial and non-linear forces there is a significant direct impact of trust on innovation. |
| Keywords: | trust, social capital, innovation, EU |
| Date: | 2013–12 |
| URL: | http://d.repec.org/n?u=RePEc:met:stpswp:1304&r=geo |
| By: | Katja Görlitz; Sylvi Rzepka |
| Abstract: | Using data from the National Educational Panel Study of 2009/2010, this paper investigates the relationship between regional training supply and employees’ training participation. Controlling for other regional factors such as the local unemployment rate, the educational level, the population density and the regional industry composition, the results indicate that training participation is significantly higher in regions with many firms in the training supply market. The predictive power of the other regional factors is rather minor. |
| Keywords: | Training; local labor markets |
| JEL: | J24 R12 |
| Date: | 2014–03 |
| URL: | http://d.repec.org/n?u=RePEc:rwi:repape:0479&r=geo |
| By: | Amit Basole |
| Abstract: | Artisanal industrial clusters, geographical agglomerations of small or micro, ‘flexibly-specialized’ enterprises, are an important component of the informal sector from employment generation, poverty alleviation, as well as export promotion perspectives. Two theoretical paradigms have commonly been employed to analyse such clusters: informality and flexible specialization. The first paradigm emphasizes precarious work, surplus labour, and low wages; the second, skilled labour, agglomeration economies, and fashion-sensitive products. This study brings these two perspectives together to address how informal institutions enable clusters to function and how they shape the distribution of risks and gains that accompany flexible specialization. Focusing on the artisanal weaving cluster in the city of Banaras, in North India, I examine the putting-out (subcontracting) system, the system of family-based apprenticeships, and the transfer of fabric designs between firms. In each case, I show how informality and flexible specialization complement and contradict each other. |
| Date: | 2014–06 |
| URL: | http://d.repec.org/n?u=RePEc:mab:wpaper:2014_07&r=geo |
| By: | Ron Boschma (CIRCLE - University of Lund); Carlo Gianelle (European Commission – JRC - IPTS) |
| Abstract: | This note studies the mechanisms through which regional economies diversify over time and formulates suggestions on how policy can influence such process. In particular, two closely related concepts will be defined, that is, technological relatedness and related variety. Regional diversification is a crucial process in order to develop new growth paths. It is understood as an emerging process through which new activities develop out of existing ones, but the scope and outcome of this process are fundamentally affected by technological and cognitive constraints. We discuss how technological relatedness may provide an input for effective policy making. In this respect, public policy should avoid picking winners that do not fit into the regional actual and potential industrial space and should prevent supporting declining industries that occupy a peripheral position in the industry space of a region. More in particular, we direct attention to various mechanisms through which new industries may be stimulated to connect to technologically related industries at the regional level. We also introduce the process of entrepreneurial discovery, in which entrepreneurs generate the key information guiding the selection of the domains of future regional specialization, and discuss its relationship with policy schemes based on related diversification. |
| Keywords: | European cohesion policy, Structural Funds, smart specialisation, related variety, regional branching, entrepreneurial discovery process |
| Date: | 2014–05 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc88242&r=geo |
| By: | Antonescu, Daniela (Romanian Academy, National Institute of Economic Research) |
| Abstract: | The general objective of this study is to evaluate regional disparities and the territorial convergence under the impact of the cohesion policy, in the context of the European Union integration. The specific objectives on which the research included in this work focused are the following: specific objectives: (i) analysis and interpretation of main theories of regional science, evolution and influence factors, main representatives; (ii) analysis of regional disparities in Romania in different fields of activity; (iii) analysis of convergence at regional level within the European Union; (iv) assessing the impact of implementing regional policy in Romania; and (v) suggestions regarding a possible model of regional strategy for the future programming period, from the perspective of the Europe 2020 Strategy. The study contains certain quantitative and qualitative estimates on the economic effects generated by Structural Funds at regional level in Romania. The data and information presented in the research paper regarding the gross impact of allocated resources are verified by computing first an average level of obtained effects. By using currently existing qualitative and quantitative data and some analysis techniques of territorial convergence recognised at international level, the study presents the trends at regional and local level in certain fields of activity. |
| Keywords: | regional convergence, economic and social cohesion, regional programmes and policies, territorial disparities, evaluation |
| JEL: | R11 R12 F02 |
| Date: | 2013–12 |
| URL: | http://d.repec.org/n?u=RePEc:ror:wpince:131209&r=geo |
| By: | Daniel Nepelski (European Commission – JRC - IPTS); Giuditta de Prato (European Commission – JRC - IPTS) |
| Abstract: | The European ICT Poles of Excellence project aims to identify ICT R&D&I-related activities which are geographically concentrated and which demonstrate high performance in ICT innovative activities: the European ICT Poles of Excellence. It also aims to help map the dynamics of ICT-related innovation and economic geography in Europe, pointing to the presence and possibly the emergence of agglomerated and globally performing ICT activities. This policy brief offers a synthesis of the major findings of the EIPE study. It also provides some insights into the policy implications these findings indicate. The study found significant evidence to show that Europe hosts a small number of highly ICT intensive regions, i.e. EIPEs. Together they participate in a networked ecosystem made up of very strong hubs in the global ICT innovation system and a multifaceted periphery with local and global links. Despite the highly specific nature of each of these regions, including the European ICT Poles of Excellence, whose characteristics vary considerably, their identification and analysis offer some strong implications for policy. |
| Keywords: | ICT; information and communication technologies; innovation, R&D, ICT industry; region; Europe; Poles of Excellence; clusters; indicators; methods |
| JEL: | O32 O52 R12 R28 |
| Date: | 2014–03 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc85408&r=geo |
| By: | Daniel Nepelski (European Commission – JRC - IPTS); Giuditta de Prato (European Commission – JRC - IPTS) |
| Abstract: | The EIPE project aims to identify activities related to ICT R&D and innovation which are geographically concentrated and which demonstrate high performance: the European ICT Poles of Excellence. Besides providing a comprehensive map of ICT-related activity in Europe, the project looks at five NUTS3 regions that can be considered as key elements of the European ICT landscape, i.e. Inner London East, Paris, Kreisfreie Stadt Darmstadt, Dublin and Byen Kobenhavn. The study identifies the strengths and weaknesses of each place and provides an overview of policy measures that were undertaken in each of them to facilitate the development of ICT R&D, innovation and business activities. |
| Keywords: | ICT; information and communication technologies; innovation, R&D, ICT industry; region; Europe; Poles of Excellence; clusters; indicators; methods |
| JEL: | O32 O52 R12 R28 |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc85354&r=geo |
| By: | Jens Sörvik (European Commission – JRC - IPTS); Alexander Kleibrink (European Commission – JRC - IPTS) |
| Abstract: | The Digital Agenda Toolbox provides support to regional and national authorities to develop a thorough understanding of the digital growth potential stemming from the Digital Agenda for Europe (DAE). It highlights the opportunities Information and Communication Technology (ICT) entails as a key element in their national or regional research and innovation strategies for smart specialisation (RIS3) and related Operational Programmes (OPs). At the same time, this Toolbox provides guidance for the fulfilment of the DAE-related ex-ante conditionalities that will form the basis for using European Regional Development Funds (ERDF) for ICT investments. It thus complements the RIS3 Guide and other related policy documents such as the Guide on Broadband Investment. The Toolbox furthermore provides hands-on assistance for developing a strategic policy framework for digital growth by discussing the dos and don'ts of the process and giving examples of good practises |
| Keywords: | Smart Specialisation, Digital Agenda for Europe, Structural and Investment Funds, Regional Innovation Policy, ICT Policy, Digital Growth Strategies, Broadband infrastructure, Next Generation Networks, Cloud computing, Key Enabling Technologies (KETs), eHealth, active & healthy ageing, eGovernment, Intelligent transport systems, Smart cities, Smart grids, Open data portals, cultural heritage, Innovation Vouchers, Digital skills, Living labs, ICT in education |
| Date: | 2014–04 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc88896&r=geo |
| By: | Gianfranco Piras (Regional Research Institute, West Virginia University) |
| Abstract: | In the present note we demonstrate how to implement the Lee and Yu (2010) procedure for fixed effects spatial panel data models available from the R (R Development Core Team 2012) package splm (Millo and Piras 2012). Additionally, we also show how to compute the impact estimates introduced by Kelejian, Tavlas, and Hondroyiannis (2006) and formalized in LeSage and Pace (2009). Unlike Matlab (MATLAB 2011), there was no R function specific to static panel data models for the calculation of the impact measures. After receiving numerous requests from the users of splm, we decided to extend the cross sectional functions available from spdep (Bivand 2013) to spatial panel data models. |
| Keywords: | spatial panel data models, R, computational methods, impact measures |
| JEL: | C4 C6 C21 |
| Date: | 2013–05 |
| URL: | http://d.repec.org/n?u=RePEc:rri:wpaper:201305&r=geo |