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This paper studies how the size of the labour market affects workers' decisions to invest in human capital. We consider a model of mismatch where firms rank workers according to their level of skills. The matching process operating in the market has the property that the job finding probability of workers depends on market size, market tightness and their ranking. The model is consistent with several facts highlighted in empirical studies: in bigger markets the distribution of human capital is more unequal and the returns to skill are higher.

Cross‐regional R&D networks are essential for regional innovativeness. Yet, we lack insights into technology field‐specific effects of a region's network connectivity. This study investigates key enabling technologies (KETs) to compare knowledge creation effects of EU funded R&D networks for different technological fields. By applying spatially filtered regression models together with marginal effect interpretations for non‐linear models we quantify and compare network effects across KET fields. Results show that the generally positive network effects differ depending on region‐internal endowments and the nature of the underlying technologies. Policy implications arise for the interrelations between EU research, industrial and regional policy.

In this paper, we analyse the effect of policy induced collaboration between secondary schools and higher education institutes (HEIs) on student flows in the Netherlands in the area of science and technology. We show that the policy intervention was not only effective but compared to other possible policy measures also quite efficient. We further demonstrate that the strength of collaboration between HEIs and secondary schools significantly reduces the negative effect of geographical distance on the number of students migrating from a particular secondary school to an HEI.

In this paper a 'search and matching' framework is used to examine the impact of advances in information technology on regional inequalities. While the relevant literature analyses the impact of technological progress with respect to changes in regional productivity, we take an alternative perspective: changes in the arrival rate of job offers and employment opportunities. Simulation experiments complement the theoretical framework, while some empirical evidence using a sample of NUTS 2 and NUTS 3 regions in Europe, is also presented. © 2013 The Author(s). Papers in Regional Science © 2013 RSAI.

In this paper, we introduce network dependence in European regional growth analyses in two new ways. First, we use detailed trade-flow data across European regions to decompose regional economic growth into two components: demand-led growth due to growing export markets and structural growth due to growing market shares in those export markets. Only structural growth, constituting on average approximately 20 per cent of total growth, is potentially affected by regionally varying locational characteristics. The second network novelty we introduce is revealed competition as a measure of regional network membership in the growth analysis. Applying a neo-classical regional growth model using geographically weighted regression, we show that the degree of revealed competition in trade and services between sectors moderates regional structural growth. Regions operating on similar international markets share more favourable structural growth prospects, with locational determinants being more – albeit still limited – significant due to similar externalities. With regional characteristics being of limited sectoral and geographical importance for structural growth, our results suggest that the recently advocated place-based development strategies of European regions should be complemented with competitive regional network strategies.

In this paper, we introduce network dependence in European regional growth analyses in two new ways. First, we use detailed trade-flow data across European regions to decompose regional economic growth into two components: demand-led growth due to growing export markets and structural growth due to growing market shares in those export markets. Only structural growth, constituting on average approximately 20 per cent of total growth, is potentially affected by regionally varying locational characteristics. The second network novelty we introduce is revealed competition as a measure of regional network membership in the growth analysis. Applying a neo-classical regional growth model using geographically weighted regression, we show that the degree of revealed competition in trade and services between sectors moderates regional structural growth. Regions operating on similar international markets share more favourable structural growth prospects, with locational determinants being more - albeit still limited - significant due to similar externalities. With regional characteristics being of limited sectoral and geographical importance for structural growth, our results suggest that the recently advocated place-based development strategies of European regions should be complemented with competitive regional network strategies.

The aim of this paper is to gain further insight into the way in which residential location choice behavior is related to the existence of public transport facilities and to distance to the workplace. More specifically, the objectives of this paper are twofold. The first objective is to gain more insight into the influence of the characteristics of residential locations on residential location choice behavior. The selected characteristics are related to three aspects: (a) the residence itself (dwelling type, costs, type of neighborhood); (b) the transportation facilities in the residential neighborhood (frequency of bus services, availability of railway station, accessibility to main road system); and (c) the travel time from the residential location to the workplace (car, public transportation, and bike). The second objective is to test a model of joint (multi-person) decision making behavior. The results of this research indicate that the preference for a particular residential location is highly dependent on the characteristics of the dwelling and its environment, and to a lesser extent on the travel time to the workplace. The characteristics pertaining to transportation facilities seem to be less important. These results imply that transportation policy is not necessarily an effective instrument to influence residential choice behavior and the associated mobility. An earlier version of this paper was presented at the 31st European Congress of the RSAI, Lisbon, Portugal, August 1991.

Cities are not only connected through conventional infrastructure, but also through digital infrastructure. This paper tests whether digital connectivity patterns follow traditional ones. Using a generalized spatial interaction model, this paper shows that geography (and distance) still matters for an extensive set of world cities. With a view to the rapidly rising urbanization, the attention is next focused on the emerging large cities in China to test the relevance of distance frictions - next to a broad set of other important explanatory variables - for digital connectivity. Various interesting results are found regarding digital connectivity within the Chinese urban system, while also here geography appears to play an important role. © 2014 The Author(s). Papers in Regional Science © 2014 RSAI.

This article aims to bring together insights from a broad body of recent literature concerned with the nature, the measurement and policy implications of benefits and costs of transport. It is argued that, for various reasons, transport cannot be treated as an ‘ordinary’ economic sector, and the policy implications of a number of the sector's peculiarities are addressed. Explicit attention is given to spatial aspects and network elements, internal and external benefits and co sts, and efficiency aspects and equity considerations in policy making.

This study presents novel evidence regarding the role of regional internet infrastructure in reducing regional per capita income disparities. We base our study on the assumptions that (1) the diffusion of information homogenizes regional economies through reducing the dissimilarities in institutions and culture, and (2) the telecommunication capacity, represented by the internet infrastructure of a region, facilitates this flow of information. Using the data from the 26 statistical NUTS-2 regions of Turkey for the period 1999-2011, we find evidence that internet infrastructure increases the speed of regional convergence.

We use data on Mexican and Chinese immigrants in the US to calculate the average marginal effects of residential and occupational segregation on immigrants' ability to speak English, and similarly the effects of English fluency of family members. Our results confirm that residential segregation is generally inversely related to English language proficiency of immigrants, except for skilled Chinese immigrants. Allowing for occupational fixed effects, the minority population share at the place of work is relevant for proficiency in English among skilled Chinese, but not for Mexicans and unskilled Chinese. We also find that the presence of English-speaking adults in the household increases the probability of immigrants' proficiency in English. © 2013 The Author(s). Papers in Regional Science © 2013 RSAI.

This paper examines the differences in the drivers of short and long distance firm relocations by conducting an event history analysis on a panel dataset of Dutch firms. Our findings indicate that short distance relocations (within municipalities and labour markets) are triggered by growth and the corresponding need for more space, while longer distance relocations are mainly influenced by regional characteristics. The spatial concentration of similar or related firms, a higher level of urbanization and R&D intensity keep firms from leaving their labour market region, but firms are more inclined to leave regions with a higher share of innovative firms.

Railway provision is often characterized by the intervention of either the public or private sector as network and/or infrastructure operator. In this paper we aim to develop a model of passenger railway provision where we assume that the public operator suffers a relative inefficiency. In relation to the public, private and the participation of both in the railway provision, we identify in the model different efficiency-based decision rules. The decision rules establish in which configuration welfare is maximized and bring to light the relative inefficiency of the public sector. The results give insight into how a reliable threat of private intervention can be used to maximize social welfare. © 2012 RSAI.

Standard Data Envelopment Analysis (DEA) is characterized by uniform proportional input reduction or output augmentation in calculating improvement projections. This paper develops a new Euclidean Distance Minimization model in the context of DEA in order to derive a more appropriate efficiency-improving projection model by means of a weighted projection function. The model is extended to the situation where some factor inputs are fixed, for instance, due to lumpiness or natural constraints. The extended DEA model is illustrated in the context of regional planning by using a data set on Italian tourist destination regions. © 2010 the author(s). Journal compilation © 2010 RSAI.

The aim of this research is to evaluate future retail developments in a medium-sized town and the indirect effects of individual behaviour on the local economy. Therefore we combine a spatial microsimulation model with a conditional logit model estimating the spatial shopping behaviour of households to simulate the effect of future retail developments. Then, we estimate the macro effects of these developments, mainly the effects on the retail sector, with help of an interregional SAM on town level. This analysis shows how different locations for retail developments have different impacts on households and firms in the local economy. © 2010 the author(s). Papers in Regional Science © 2010 RSAI.

We apply a Bayesian hierarchical Poisson spatial interaction to the paper trail left by patent citations between high-technology patents in Europe to identify and measure spatial separation effects of interregional knowledge flows. The model introduced here is novel in that it allows for spatially structured origin and destination effects for the regions. Estimation of the model is carried out within a Bayesian framework using data augmentation and Markov Chain Monte Carlo (MCMC) methods, related to recent work in Frühwirth-Schnatter and Wagner (2004). This allows MCMC sampling from well-known distribution families, and thus provides a substantial improvement over MCMC estimation based on Metropolis-Hastings sampling from non-standard conditional distributions.

This special section aims to fill a gap in the regional resilience literature and to stimulate future spatial studies of resilience to include the international dimension in empirical analyses. It demonstrates the do-ability and relevance by the natural experience of the global trade collapse that allows us to separate the effect of collapse upon event and ex-post recovery because no ex-ante resilience measures were taken. This is a great methodological advantage with respect to the literature on natural disasters and financial crises that is confronted with the difficulty of identifying resilience because of ex-ante measures (prevention or inherent resilience measures) and ex-post measures (recovery or adaptive resilience measures).

We investigate econometrically whether cultural diversity at the workplace boosts innovation. Our longitudinal linked employer-employee data combines two innovation surveys, with Dutch administrative, tax and regional data. We analyse the determinants of a firm's product and process innovations with respect to the firm's internal resources, employee composition and regional agglomeration externalities. We reconfirm the findings of several other recent studies showing a positive partial correlation between innovation and cultural diversity in pooled cross-sectional data; in some cases even when accounting for reverse causation. However, no statistically significant traces of benefit for innovation from cultural diversity remain after introducing firm fixed effects.

A standard result on international capital income taxation is that applying the residence principle does not affect industrial location and is therefore more efficient than applying the source principle. However, many countries do in fact apply the source principle. We argue that in a new economic geography framework the standard result needs to be qualified: the size of the market is crucial for industry location and it is changed by taxation and by public expenditures; we show that - for the high tax region - this effect dampens capital losses under the source principle and causes them under the residence principle. The sharp difference between the two taxation principles blurs and, unsurprisingly, both principles are found in taxation laws.

It has been argued that innovation increasingly depends on external knowledge sources. Still unclear is if relations to particular knowledge sources or to a broad variety of sources matter for innovation. Also, there is a debate on the issue which spatial levels are most relevant. In this context, we investigate for ICT firms in Austria the importance of variety in knowledge sourcing for their innovativeness and the relevance of geography in this respect. The results show that more innovative firms tend to exploit a larger variety of regional and international sources. We also find that R&D cooperations and in-house knowledge capabilities are highly important, while firm´s location only shows a weak association with their innovativeness.

Although the benefits of clustering for innovation have received much attention in the theoretical as well as empirical literature, analyses at the regional level often disregard the characteristics of local firms. We tackle both at the same time: agglomeration externalities (Marshall, Porter, Jacobs) from census microdata, and firm data from the Community Innovation Survey. Importantly, we allow for sectoral heterogeneity of agglomeration forces. We find that the firm characteristics, including those that proxy for 'absorptive capacity', have a much stronger relationship with the propensity to innovate than regular agglomeration externalities. The latter are only statistically significant for a few specific sectors, and even then only for some types of innovation. Sorting of innovation-prone firms into specific locations might therefore be much more important to explain spatial patterns of innovation than agglomeration externalities.

This study suggests a two-step approach to identifying and interpreting regional convergence clubs in Europe. The first step calculates Bayesian probabilities for various assignments of regions to two clubs using a general stochastic space-time dynamic panel relationship between growth rates and initial levels of income as well as endowments of physical, knowledge and human capital. The second step uses the club assignments in a dynamic space-time panel data model to assess long-run dynamic direct and spillover responses of regional income levels to changes in initial period endowments for clubs that were identified. We find different dynamic partial derivative responses to endowments by regions in the two clubs that appear consistent with low- and high-income regions as clubs.

This study analyses determinants of business relocation and identifies regional characteristics which attract relocating firms. Results indicate that the relocation decisions of firms are sector-dependent, and the migratory behaviour of firms in knowledge-intensive sectors notably differs from that in less knowledge-intensive sectors. Predominantly low-tech and medium-low-tech manufacturing and less knowledge-intensive service firms paying high average salaries have a higher probability to move out of their present location. For less knowledge-intensive service firms, the average municipal wage negatively affects their propensity to relocate, while those located in municipalities with high sector-specific wages have an increased likelihood to move. Relocating firms are generally attracted by densely populated municipalities with high wage levels, and primarily service firms are drawn to municipalities which are specialized in the firm's own sector and appeal to individuals. Sector-specific wages may either attract, or deter firms, suggesting that this variable may capture both the cost and the quality of the locally available workforce.

This study shows for eight science-based industries that the citation impact of research collaboration is higher for international collaboration than for national and regional collaboration. A further analysis of institutional affiliations shows that university-industry-government collaborations profit from being organized at the regional scale only in the cases of biotechnology and organic fine chemistry. The alleged importance of physical proximity for successful interaction between university, industry and government thus is not robust across industries. We discuss the policy implications that follow.

The last few years have witnessed an increasing interest in the geography of innovation. As noted by Autant-Bernard et al. (2007a), the geographical dimension of innovation deserves further attention by analysing such phenomena as R&D collaborations. In this study we focus on cross-region R&D collaborations in Europe. The European coverage is achieved by using data on collaborative R&D projects funded by the EU Framework Programmes (FPs) between organisation that are located in 255 NUTS-2 regions of the 25 pre-2007 EU member-states, as well as Norway and Switzerland. The objective is to identify separation effects - such as geographical or technological effects - on the constitution of cross-region collaborative R&D activities. We specify a Poisson spatial interaction model to analyse these questions. The dependent variable is the intensity of cross-region R&D collaborations, the independent variables include origin, destination and separation characteristics of interaction. The results provide striking evidence that geographical effects play an important role in determining R&D collaborations across Europe. Geographical proximity and co-localisation of organisations in neighbouring regions are important determinants of cross-region collaboration intensities. The effect of technological proximity is stronger than spatial effects. R&D collaborations occur most often between organisations that are located close to each other in technological space. R&D collaborations in Europe are also affected by language- and country border effects, but these are smaller than geographical and technological effects., 28 pages

The theory of endogenous growth and the geography and growth synthesis both consider that local growth and spatial concentration of economic activities emanate from localised knowledge spillovers (lucas 1988; martin and ottaviano 1999). Since the end of the 1980's, the spatial dimension of knowledge diffusion has been investigated from an empirical point of view, and the existence and role of local spillovers has been generally confirmed (see among others jaffe 1989; audretsch and feldman 1996). The concern that now arises is to unravel the mechanisms underlying and explaining the geographical knowledge spillovers. The aim of this special issue is to present the latest new findings on such questions and to identify some new lines of research for future work. Before presenting the content of this special issue, we very briefly review the main results of the empirical literature on the geography of innovation. We also explain the context of this special issue by pointing out some of the limitations faced by this literature and, by stressing the complex dynamic and network dimensions of the observed processes of production and diffusion of knowledge.

Environmental aspects of energy conversion, in particular the generation of electricity, play an important role in the decision process on energy projects. A decision support model is proposed which distinguished three evaluation levels of environmental aspects: the emission level, the concentration level and the effect level. Multi‐criteria analysis (a combination of the “expected value method” and the “weighted summation”) and graphical presentation methods are used in evaluate the model which is implemented for seven electricity producing energy conversion systems, ranging from nuclear and coal, to oil, gas and wind. These systems are evaluated on the following to environmental criteria: acidification, photo‐chemical pollution, climatic effects, noise, thermal pollution, solid and nuclear waste, land use requirement, risk and visual disturbance.

Even though a large share of the workforce belongs to two-earner households, job search models invariably ignore the interaction between the wage earners of the same household. In this article, job and residential search behaviour of two-earner households are simultaneously analysed. The main finding of the theoretical model is that two-earner households search less intensively in the housing market, and more intensively in the labour market, if the distance between the workplaces of the two wage earners is longer. In the empirical part the latter finding has been analysed based upon a data set for Dutch two-earner households.

Whatever the reasons at work – differences in locational endowments and/or externalities – a unit of capital is expected to be diversely productive according to the region where it is installed. This article determines which and the extent to which a regional policy could be implemented in order to make up for a productivity handicap. The model allows for comparing the efficiency of a productivity-enhancing instrument (a publicly provided input) with that of instruments that affect capital cost (a lower corporate tax rate, an investment tax credit, or a capital subsidy). The approach is illustrated in the contemporaneous context of France.