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The multivariate pluriformity and complexity of economic-geographic space (e.g., cities or countries) are reflected in their empirical multidimensional data structure with space–time characteristics. The need to reduce the multiple dimensions of an observation space is present in all social (and other) sciences seeking to identify basic patterns or key relations among critical indicators that characterize economic or social features of the phenomena concerned. For this purpose, multivariate statistics has developed an impressive toolbox, in which traditionally a prominent place is taken by the class of principal component analyses (PCA). This technique dates back to the beginning of the last century and is widely employed in empirical research aiming at reducing complexity in observation spaces toward manageable patterns of a smaller dimensionality. In the present study, we develop and present a new methodological contribution to in the PCA field, by shifting from conventional discrete static data to time-series data approximated by a continuous intertemporal curve reflecting the evolution of the socioeconomic data concerned. In this paper, the statistical foundation of this new approach, called multivariate functional principal component analysis (MFPCA), will be outlined and tested for a multivariate long-range data set on statistical indicators for several countries. The practical validity of the MFPCA method will be demonstrated by means of an application to the evolution of socioeconomic competitiveness (in this paper, we use the WEF definition of competitiveness, which is: “Competitiveness is the set of institutions, policies, and factors that determine the level of productivity of a country” WEF 2015) in different countries of the world, based on official World Economic Forum (WEF) data spanning the period 2008–2015. Our analysis brings to light interesting findings and differences compared to the initial, officially published WEF information.

The link between the management of uncertainty and knowledge creation is the core element behind firm survival, as these two factors are critical for true innovation. This article links the surviva...

The main objective of this study is to examine the effect of health on economic growth based on 719 estimates obtained from 64 studies from all over the world. We find evidence of a publication bias towards a positive estimated effect of health on economic growth. After accounting for heterogeneity of the estimates, we show that health has a genuine positive effect on economic growth. Less developed countries seem to enjoy a higher effect of health on growth driven by the ongoing economic-demographic transition in those countries. The variation of the health effect on economic growth is also influenced by the available data, estimation procedure, model specification, publication channel, and country characteristics in each study. Studies that do not account for endogeneity seem to create an upward bias. Studies with more comprehensive variables seem to increase the estimated effect of health on growth. A higher number of years of compulsory education, longer working experience, and more favourable environmental conditions also increase the effect size. Overall, our results confirm the key role of the health factor in explaining economic growth across countries.

This study combines three interconnected streams in tourism literature: analysis of the utilisation of common pool resources (CPR) in tourism, studies on sustainable tourism development and theoretical contributions to the articulation of roles, missions and strategies of a destination management organisation (DMO). Starting from an integrative literature review, our aim is to explore the symbiotic relationships between these approaches in order to design a conceptual framework that opens new research opportunities. Clearly, the concrete application of such a conceptual model depends on the resources of each destination, the type of tourism dynamics observed, the specific stakeholders involved and the power balance between them. Our approach integrates the principles of sustainable development into the strategic role of a DMO through the management of CPR, aiming at the achievement of significant benefits for the host communities within the three pillars of sustainable development (ecological, social and economic) through participatory processes of destination management. In addition, we present an exploratory illustration of this conceptual framework for the case of a rural destination of Kushiro-Akan (Hokkaido, Japan). Policy and managerial implications are discussed, along with the needs for further research.

Natural disasters are usually regarded as damage factors causing high private and social costs. Notwithstanding the incontestable validity of this premise, natural disasters do not necessarily lead to a structural deprivation of the area affected. Recent studies have clearly shown that in the long run one may even observe positive socio-economic effects (‘blessings in disguise’).This paper investigates this challenging proposition by developing a risk-disaster-opportunity framework for a territorial system, and by analysing the socio-economic impacts of natural shocks from a resilience perspective. This is inter alia done by designing a typology of natural disasters, and by presenting a systematic classification of long-range impacts.An empirical test of the above proposition of positive recovery effects of natural disasters is carried out by using, in particular, long-term data from the worldwide EM-DAT database. The attention is then focussed on positive feedback loops in spatial systems that are affected by a natural perturbation. Various case studies (USA, China, Haiti, Chile, Japan) are undertaken in order to test the existence of long-term ‘blessings in disguise’ effects, using in particular the HDI-index. In various cases, such positive effects appear to exist, depending on the effectiveness of public management of natural disaster phenomena.

The present study aims to test relative welfare differences among regions in Europe, so as to examine whether the post-communist era has led to more socio-economic cohesion in Europe. The performance of European regions is analysed, compared, and assessed by using the Regional Competitiveness Index (RCI) and stylised fixed nominal categories. The current status of regional cohesion is tested on the basis of detailed data on 268 NUTS 2 European regions by using a robust methodology oriented towards univariate comparison of location parameters, multivariate classification by the decision tree and CHAID algorithm, and comparison of nominal variables with four values based on density plots. Multivariate classification appears to offer statistically excellent results with an overall correct prediction rate for post-socialist and capitalist regions in Europe of 99.6%. The research results from the Higher education and Innovation pillars, reveal a convergence of capitalist and post-socialist regions with capital cities and a divergence of regions with administrative capitals and other regions. Relatively, the two groups which perform best are both groups with capitals, while the group of capitalist regions with a capital city is significantly better in almost all pillars. The key message is that the transition of post-socialist regions is not yet over. Capitalist regions in Europe perform better than post-socialist regions in eight of the nine pillars of regional competitiveness. Our research results also reveal that the group of post-socialist regions without capital cities are significantly lagging behind the rest of the regions in Europe, and thus form the most vulnerable group of European regions. As there is data continuity in the official RCI classification and measurement, policy makers will be able to compare the performance of their own regions over time and to design appropriate concerted strategies accordingly. From this perspective, our study draws several interesting lessons and results for policy makers at various levels. Place-based regional planning and policy based on our analysis framework may be helpful in developing effective measures to cope with the socio-economic legacy of the “Iron Curtain” and get closer to regional cohesion in Europe.

We study aspects of economic growth in a region that is creative in the sense of Richard Florida. We model creativity by supposing that the region under study has two sectors. The first sector uses physical capital $$\left\{ {K\left( t \right) } \right\} $$ and trained workers $$\left\{ {A\left( t \right) W\left( t \right) } \right\} $$ to produce creative capital $$\left\{ {R\left( t \right) } \right\} .$$ The second sector uses physical and creative capital to produce a final consumption good $$\left\{ {Q\left( t \right) } \right\} .$$ In this setting, we accomplish four tasks. First, we derive the equations of motion for physical capital per trained worker $$\left( k \right) $$ and creative capital per trained worker $$\left( r \right) .$$ Second, we find combinations of k and r for which $$\dot{k}=\dot{r}=0.$$ Third, we investigate whether the economy of our creative region has a balanced growth path (BGP). Finally, assuming that our region is initially on a BGP, we study the impact of a permanent increase in the savings rate $$\left( s \right) $$ on the trajectory of output per worker.

Regional development policy aims to cope with the challenge of spatial disparities. It is based on a smart combination of various critical capital assets in a region which functionally and spatially interact and which yield synergetic economic opportunities and promising challenges for innovation and progress. The present study regards sustainable territorial performance – as a manifestation of regional development – as the overarching principle for competitive advantages and economic growth in a system of regions, which is particularly induced by territorial capital, comprising human capital, infrastructural capital and social capital. In the long-standing tradition of regional development policy a wide variety of effective facilitators or drivers of accelerated spatial growth has been distinguished, for instance, industrial districts, growth poles, growth centers, industrial complexes, special economic zones, communication axes, and so forth. In the past decades, a new concept has been introduced, viz. economic-technological clusters. An avalanche of literature has been published on the conceptual, operational and policy foundation and relevance of this concept, especially in relation to previously developed regional growth concepts. In this paper, clusters will be regarded as the spatial foci of sustainable territorial performance strategies and synergetic actions by both public and private actors. The present paper aims to address the relevance of cluster concepts for an effective regional development policy, based on the above notion of territorial capital. It does so by introducing a new concept, viz. effective cluster, in which spatial-economic synergy, local/regional concentration of industry, and the supporting role of territorial capital are regarded as the main determinants of a highly performing cluster in a given territory. The effective cluster concept will be tested on the basis of a field study on the aviation and aerospace cluster ‘Dolina Lotnicza’ in the Podkarpackie region in South-East Poland. This is one of the most vibrant high-tech clusters in thecountry. A new approach based on a triple-layer architecture will be adopted here, viz.: a quantitative comparative analysis of the 16 Polish ‘voivodships’ (main administrative regions in the country, at a NUTS-2 level), a benchmark analysis of the 25 counties (‘powiats’) within the Podkarpackie voivodship (at a NUTS-4 level), and an effective industrial cluster analysis on the basis of the individual aviation firms located in the Podkarpackie region. In each step an extended Data Envelopment Analysis (DEA), characterised by a merger of a Slack-Based Measure (SMB) and a super-efficiency (SE) DEA, will be used in order to achieve an unambiguous ranking of the various regions or Decision Making Units (DMUs). The study will employ an extensive database on individual actors in the cluster, in combination with a broadly composed territorial-capital database for the areas under study. The paper will be concluded with some strategic policy lessons.

We analyze inefficiency and inequality associated with the use of creative capital to produce a final good. We first study a case in which the creative capital units are perfect substitutes in the production of the final good. We show that the equilibrium outcome is inefficient and that there is too little application of effort. Second, we define an indicator of inequality and show that an increase in inequality enhances efficiency and that it is possible to achieve complete efficiency. Third, we focus on the case where the individual creative capital units are perfect complements and show that the equilibrium outcome is inefficient with too little effort application. Finally, we contend that our theoretical results provide a possible rationale for the observed income inequality in cities and regions in which the activities of the creative class constitute a large part of all economic activities.

Entrepreneurship has been advocated as one of the major solutions for coping with (youth) unemployment in Europe during the recent economic downturn. Entrepreneurial activity is generally co-determined by economic and cultural factors. However, cultural change normally requires a much longer time to take place than economic changes do. This may prompt a so-called cultural hysteresis effect in the efficiency of entrepreneurial incentives. To analyze these effects, data from the Global Entrepreneurship Monitor (2003–2010) are used. A Two-Stage Least Square instrumental variable and a logit model with difference-in-differences are employed. We find that the cultural hysteresis is less prominent among Mediterranean countries. Moreover, it is almost negligible in the response to incentives by female youth.

Taking GDP as the standard economic indicator for economic welfare, recent Resources-Economy studies indicate the “dematerialization” of the economy, the so-called decoupling effect. This conclusion seems to alleviate concerns over resource scarcity and limits to growth, and feeds optimism for green growth and sustainability prospects. However, the validity of GDP as the sole and unambiguous measure of the ultimate outcome of the economy has been severely disputed. There is nowadays increasing interest in broader welfare measurements that capture more aspects of economic output and hence constitute better approximations of well-being. The present paper provides an overview of the above discussion and sets out to explore the relevance of three alternative welfare indicators – the Human Development Index (HDI), the Index of Sustainable Economic Welfare (ISEW) and the Genuine Progress Indicator (GPI) – as a basis for evaluating the dependency of welfare and its major engine, the economy, on natural resources. Increasing welfare appears to require a disproportionate use of resources. Strong and increasing dependency on resources at the global level and in giant countries such as China and India may have serious implications for current sustainability policies and the United Nations Sustainable Development Goals.

Usually, knowledge spillovers (KS) are related to geographic proximity. In the present study, we measure KS on the basis of different proximity matrices, focusing on the relational, social, cognitive and technological preconditions for knowledge diffusion. In the light of previous studies on KS, we examine: (i) which types of proximity enhance or hamper knowledge flows, and (ii) whether local absorptive capacity favour such flows. Our results indicate that KS across European NUTS2 regions measured through geographic, relational, social, cognitive and technological proximity channels increase with local absorptive capacity. This finding points towards the emergence of large clusters of regions (absorptive capacity clubs) where relational, cognitive, social and technological proximity lock-in maximizes the returns to local investment in R&D.

Sustainability assessment (SA) is a complex appraisal method. It is conducted for supporting decision-making and policy in a broad environmental, economic and social context, and transcends a purely technical/scientific evaluation. This paper focusses on the systematisation of knowledge on technical/scientific sustainability evaluation, by addressing critical decision-making elements focussed on by domain experts. We make a distinction between integrated assessment and SA. Our systemic approach outlines how to move from integrated assessment to SA. The fundamental differences involved concern three levels: ontological, methodological and epistemological. We present a novel methodological framework for SA, based on a literature meta-review of multi-scale and multi-purpose appraisal methodologies, models and indicators. SA is essentially a structured procedure encompassing different field-specific analytical methods and models, for specific applications and decision contexts. External inputs to the methodology are “values” considered in the analysis and boundaries defined, including the relevant sustainability framework. Internal methodological elements comprise approach to be adopted (e.g. “what-if” vs. “what-to”), scenario design and analytical models and measurable indicators for an operational analysis. Methods to quantify uncertainty are key ingredients of the assessment framework. The paper highlights the relevance of and policy challenges for SA development, with due attention for applicability in real-world decision contexts.

This paper seeks to highlight the efficiency of R&D output as a function of a cultural treatment (i.e. exposure) effect. The focus of our research is on the percolation of new R&D ideas from the immaterial world of creative ideas through the cultural lattice of the locality into the documented world of knowledge. Our conceptual model is illustrated with a novel numerical operationalization of the cultural percolation of ideas hypothesis, based on the six degrees of separation literature and using a dataset compiled from EUROSTAT and the European Social Survey. The estimation strategy for the current work relies on a difference-in-differences method from a network percolation approach, with a series of alternative controls and region-fixed effects. The results show a positive significant role of the stability (‘no change’) of the six degrees of cultural diversity (i.e., the likelihood to have six people in a row in a locality originating from a culturally different origin) as a treatment effect for R&D output efficiency (the latter being measured as the number of new ideas over a millions of euros of R&D investments). The main value added of the paper is that it offers a theoretical justification and numerical illustration on how the six degrees of separation paradigm can be used to approximate the tipping point of the percolation of new ideas through the local social network from the pool of ideas to efficient R&D investment decisions.

This article introduces cultural gravity as a concept that serves to better disentangle the direction and magnitude of the effects from migration, which is controversial in recent literature. The aim is to test for cultural gravity effects on both the geographic concentration and human capital productivity of immigrants in the EU15 countries. Operationally, we proceed to construct an empirical cultural gravity measure and test it with the use of a composite crosssectional database, comprising, inter alia, the World Value Survey and Eurostat Census data. After an initial exploration of relevant cultural data by means of multivariate statistical analysis, we present an extended formulation of a gravity model approached through logistic regression methods and a three-stage least-squares estimation. Our results clearly demonstrate the existence of a cultural gravity effect among immigrants. Finally, an interesting finding is that cultural gravity also plays a significant role in the context of the Culture-Based Development (CBD) growth model.

The present study aims to demonstrate the importance of digital data for investigating space–time dynamics of aggregated human activity in urban systems. Such dynamics can be monitored and modelled using data from mobile phone operators regarding mobile telephone usage. Using such an extensive dataset from the city of Amsterdam, this paper introduces space–time explanatory models of aggregated human activity patterns. Various modelling experiments and results are presented, which demonstrate that mobile telephone data are a good proxy of the space–time dynamics of aggregated human activity in the city.

Culture matters for economic development. This postulate has been a main conceptual concern for “old” institutional economics (OIE) and has lately also been tested through neoclassically inspired econometric techniques. This conceptual foundation has been confirmed in several quantitative studies on developed countries, in particular cases from the USA, Germany, and Italy. In less developed regions with a wealth of cultural heritage, particularly in South-East Europe, this postulate is still an underexplored issue from the perspective of advanced econometric approaches. Our goal is to examine the impact of the so called South-East European cultural corridors on welfare — and especially on total employment — at the local or regional level. Accounting for gross value added and sectoral specialization, we examine the effect of such corridors by considering the distance to a cultural corridor: namely, the East Trans-Balkan Road (crossing Romania, Bulgaria, and Greece) as an explanatory factor for regional development, particularly employment. Using the European University Institute (EUI) European Regional Dataset (ERD), as well as the geo-data from the Cultural Corridors of the South-East Europe website, we estimate a regression model using a 2SLS instrumental variable (IV) approach, with a pooled dataset at the NUTS 3 level (Eurostat) from 1980 to 2011.We then triangulate the results by using the distance to the cultural corridor concerned as a treatment effect in a propensity-score-matching and difference-in-differences exploratory analysis. The findings confirm the importance of distance to the cultural corridor under investigation as a strong predictor for local socio-economic development. The results further suggest that the slow evolution of culture over time is likely to lead to the gradual emergence of new geographical cultural centers and a new cultural path-dependence built-up of persistence chains.

Along with the increasing pace of globalization, recent decades faced a dramatically increase in international migrant flows as well. Compared to the flows of trade, capital and knowledge, we observe that contemporaneous complex institutional differences, historical backgrounds, and individuals' diverse socio-demographic characteristics make the migrant workers' choice of destination arguably much more uncontrollable. This study shows that migration is in a complex way intertwined with culture, networks and language, (i) by reviewing related studies on the barriers of culture, networks and language in international labor mobility, and (ii) by exploring missing gaps and prospective avenues for research. Nowadays, the migration pressure on Europe and the United states has created substantial challenges, leading to an urgent need to address the economic assimilation and social integration of migrants. Against this background, we emphasize that these non-economic factors have played an increasingly critical role in shaping international migration and its future socio-economic consequences for destination countries.

In the Netherlands the share of immigrants in the total population has steadily increased during recent decades. The present paper takes a look at wage differences between natives and migrants who are equally educated. This reduces potential skills biases in our analysis of wages. We apply a Mincer equation in estimating the wage differences between natives and migrants. We analyse only young graduates; the conventional human capital factor cannot explain the differences in monthly gross wages. Therefore, we have to look further into “otherness” factors, such as parents’ roots, to find an alternative explanation. Our empirical results show that acquiring Dutch human capital, such as Dutch-specific skills, language, and even integration in the long-term for first-generation migrants, and for a group of second-generation migrants with a non-OECD background, do not overcome wage differences in the Dutch labor market. Furthermore, age structure also plays a role in the payment of different wages in the labor market due to an age discrimination effect: immigrants who invest in their education at later age earn lower wages.

The current literature often values intangible goods like cultural heritage by applying stated preference methods. In recent years, however, the increasing availability of large databases on real estate transactions and listed prices has opened up new research possibilities and has reduced various existing barriers to applications of conventional (spatial) hedonic analysis to the real estate market. The present paper provides one of the first applications using a spatial autoregressive model to investigate the impact of cultural heritage-in particular, listed buildings and historic-cultural sites (or historic landmarks)-on the value of real estate in cities. In addition, this paper suggests a novel way of specifying the spatial weight matrix-only prices of sold houses influence current price-in identifying the spatial dependency effects between sold properties. The empirical application in the present study concerns the Dutch urban area of Zaanstad, a historic area for which over a long period of more than 20 years detailed information on individual dwellings, and their market prices are available in a GIS context. In this paper, the effect of cultural heritage is analysed in three complementary ways. First, we measure the effect of a listed building on its market price in the relevant area concerned. Secondly, we investigate the value that listed heritage has on nearby property. And finally, we estimate the effect of historic-cultural sites on real estate prices. We find that, to purchase a listed building, buyers are willing to pay an additional 26.9 %, while surrounding houses are worth an extra 0.28 % for each additional listed building within a 50-m radius. Houses sold within a conservation area appear to gain a premium of 26.4 % which confirms the existence of a 'historic ensemble' effect. © 2013 Springer-Verlag Berlin Heidelberg.

We theoretically study whether an environmentally conscious or “green” citizen ought to bicycle or take public transport to work. Focusing on the criterion of travel time minimization, we construct and analyze a simple stochastic model that sheds light on the above question. Our investigation leads to three findings. First, we compute the expected amount of time it takes to commute to work. Second, we derive a key inequality condition and show that only two cases need to be considered to determine whether a green citizen ought to bicycle or take public transport to work. Finally, we provide an intuitive explanation of why it suffices to consider only two cases to answer the question in the title of this note.

In the currently emerging ‘urban century’, large cities and urban agglomerations are increasingly turning into (socio-)economic and political powerhouses of great importance. This paper offers a comparative assessment of the multidimensional performance profile of major cities in our world, with particular emphasis on the livability and economic features of these cities. The explanatory cohesive framework in the present study is offered by the so-called ‘urban piazza’ model. Using an extensive database on various rankings of global 40 cities (the so-called GPCI data base), the relative performance of these cities is ‘explained’ in a qualitative sense by means of a non-parametric ordinal ranking method, known as rough set analysis. The approach allows us to identify the driving forces that altogether are responsible for the economic and livability achievements of these cities. The empirical analysis highlights the combined ‘power’ of selected success conditions and drivers of these cities concerned. Our empirical results demonstrate that the geographical accessibility of these urban areas appears to play in many cases an important role.

This paper provides an extension of the Schelling agent-based model (ABM) of segregation which is augmented here with a mechanism for the percolation of new ideas. The main objective of the paper is to demonstrate that individual segregation preferences affect not only the intensity of aggregate segregation, but also the aggregate efficiency from crucial decision-making processes, such as the decision to invest in new ideas. To perform our research, we implement a NetLogo simulation in two steps by (i) obtaining three sets, each composed of 500 random segregation patterns, generated through a one-step simulation of a Schelling ABM for three different levels of segregation preference: namely, 20, 25 and 30%; and (ii) using the obtained level of segregation, we set the porosity level in a model for the percolation of new ideas and record the observed speed of percolation of new ideas for the first 100 steps. We find that levels of segregation due to 20 and 25% individual preference for homophily produce a difference of 3.4% in their effect on the speed of the percolation of new ideas. The levels of segregation of 25 and 30% individual preference for homophily, however, produce a difference of 12.8% in their effect on the percolation of new ideas. This means that the increase of the individual preference for segregation increases the intensity with which segregation acts as a barrier for new ideas to percolate successfully in the world of R&D investment. The segregation-percolation model used can be extended with further dynamics and developed as a code to be added to the NetLogo library. The main implication of our findings is that small changes in segregation preferences as in the Schelling ABM model produces increasingly negative on aggregate level spillover effects on other socio-economic processes, such as percolation of new ideas, which depend on the connectivity between people in the local society.

We use a multi-region model and provide the first theoretical analysis of the effects of human capital use and a particular kind of innovative activity on economic growth. In each of the N heterogeneous regions in our model, consumers have constant relative risk aversion preferences, there are negative externalities in innovation, and there are three kinds of manufacturing activities involving the production of blueprints for inputs or machines, the inputs or machines themselves, and a single final good for consumption. Our analysis generates four salient findings. First, for each of the N regions, we define a balanced growth path equilibrium, we characterize the market clearing factor prices, and we determine the free entry condition in the R&D sector. Second, we show that without growth in human capital, there is no sustained economic growth in any of the N regions. Third, we show that human capital growth generates sustained economic growth in each of the N regions. Finally, when discussing the above three findings, we shed light on the spatial dimensions of economic growth in our multi-region aggregate economy. © 2012 Springer-Verlag.

This Manifesto provides a joint proposal to create a Regional Science Academy as a think-tank support platform for a strategic development of the spatial sciences. The Regional Science Academy is a strategic spatial knowledge catalyst: it acts as a global intellectual powerhouse for new knowledge network initiatives and scholarly views on regions and cities as vital centrepieces of interconnected spatial systems. This contribution highlights its role and presents various activity plans.

The increasing scarcity of natural resources prompts the need to develop effective strategies for sustainable development at regional levels with a view to balancing the interests of different groups of actors or stakeholders. This study aims to address the stakeholders' multifaceted viewpoints on future sustainable development, mainly at regional scales. To this end, five experimental test cases – in the form of five different case studies in Europe – are analyzed, to encapsulate different approaches and different needs for sustainable development. A ‘pentagon model’ is used to represent systematically five critical aspects of sustainability. To analyze the trade-offs and synergies between different objectives on sustainable development, four distinct scenarios – competitiveness ; continuity ; capacity ; and coherence – reflecting distinct and relevant images of sustainability are presented. The relative merits of these four scenarios are empirically assessed by means of a particular type of multi-criteria analysis: namely, regime analysis . The analysis is carried out by ranking different attributes of sustainable development, i.e. social, economic, ecological, institutional profile, and physical, from the perspective of different stakeholders. We find that the most preferred sustainable future is the coherence scenario, in which a combination of ecological and social aspects is the most important determinants.

SUMMARY Data envelopment analysis (DEA) has become an established approach for analyzing and comparing efficiency results of corporate organizations or economic agents. It has also found wide application in comparative studies on airport efficiency. The standard DEA approach to comparative airport efficiency analysis has two feeble elements, viz. a methodological weakness and a substantive weakness. The methodological weakness originates from the choice of uniform efficiency improvement assessment, whereas the substantive weakness in airport efficiency analysis concerns the insufficient attention for short-term and long-term adjustment possibilities in the production inputs determining airport efficiency. The present paper aims to address both flaws by doing the following: (i) designing a data-instigated distance friction minimization (DFM) model as a generalization of the standard Banker–Charnes–Cooper model with a view to the development of a more appropriate efficiency improvement projection model in the Banker–Charnes–Cooper version of DEA and (ii) including as factor inputs also lumpy or rigid factors that are characterized by short-term indivisibility or inertia (and hence not suitable for short-run flexible adjustment in new efficiency stages), as is the case for runways of airports. This so-called fixed factor case will be included in the DFM submodel of the DEA. This extended DEA—with a DFM and a fixed factor component—will be applied to a comparative performance analysis of several major airports in Europe. Finally, our comparative study on airport efficiency analysis will be extended by incorporating also the added value of the presence of shopping facilities at airports for their relative economic performance. Copyright © 2012 John Wiley & Sons, Ltd.

With tightening budgets and increasingly critical reviews of public expenditure, there is a need for a careful analysis of the performance of public bodies in terms of an efficient execution of their tasks. These questions show up everywhere in the public domain, for instance, in the provision of medical facilities, the operation of postal services, or the supply of public transport. A standard tool to judge the efficiency of such agencies is Data Envelopment Analysis (DEA). In the past years, much progress has been made to extend this approach in various directions. Examples are the Distance Friction Minimization (DFM) model and the Context-Dependent (CD) model. The DFM model is based on a generalized distance friction function and serves to improve the performance of a Decision Making Unit (DMU) by identifying the most appropriate movement towards the efficiency frontier surface. Standard DEA models use a uniform proportional input reduction (or a uniform proportional output increase) in the improvement projections, but the DFM approach aims to enhance efficiency strategies by deploying a weighted projection function. This approach may address both input reduction and output increase as a strategy of a DMU. A suitable form of multidimensional projection functions is given by a Multiple Objective Quadratic Programming (MOQP) model using a Euclidean distance. Likewise, the CD model yields efficient frontiers in different levels, while it is based on a level-by-level improvement projection. The present paper will first offer a new integrated DEA tool -merging from a blend of the DFM and CD model using the Charnes-Cooper-Rhodes (CCR) method - in order to design a stepwise efficiency-improving projection model for a conventional DEA. The above-mentioned stepwise-projection model is illustrated on the basis of an application to the efficiency analysis of public transport operations in Japan.

The recent empirical literature on the impact of migrant clustering on socio-economic welfare indicators shows inconclusive and often even contradictory results. In this paper we argue that there is not an unambiguous empirical outcome of migrant or ethnic diversity, but that it depends on the level of migrant or ethnic composition itself. A low degree of socio-economic and cultural diversity may be beneficial for neighbourhoods, whereas an excessive degree of diversity may be harmful. We test this hypothesis by (i) constructing a migrant clustering index for all neighbourhoods in the Netherlands based on a gamma index; and, subsequently, (ii) incorporating it in a regression framework to assess three relevant socio-economic outcomes: neighbourhood income, number of students, and average housing value. We show that there is apparently an optimal level of migrant clustering, and that it is remarkably robust. For the Netherlands as a whole and for the ten largest Dutch cities as well, it is striking that largely similar effects were found. Our results suggest that population composition in neighbourhoods may vary up to about 40 per cent from the national average before migrant clustering generates negative effects. © 2010 Elsevier Ltd.

This study aims to identify the critical factor(s) that determine the embeddedness level (EL) of rural entrepreneurs. In order to achieve this aim, existing applied studies on the embeddedness of entrepreneurs undertaken in different rural areas were systematically collected to create a database in order to provide the material for a systematic comparative analysis. This was done in order to highlight common and contrasting findings from a set of selected studies for different ELs. As many results of these studies were largely qualitative in nature and only partially comparable, a specific tool for analysing categorical data based on artificial intelligence methods, namely, rough set data analysis (RSDA), was employed. This experimental study is the first RSDA approach that compares the results of several rural case studies and infers general induction rules for the different ELs. The results of our analysis show that using and benefiting from local resources are the key factors that explain how entrepreneurs become embedded in rural areas. © 2010 The Authors. Tijdschrift voor Economische en Sociale Geografie © 2010 Royal Dutch Geographical Society KNAG.

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 theoretically and empirically the strategic importance played by intangible 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 intangible elements as part of territorial capital magnify the contribution of knowledge by determining the formation of increasing returns to knowledge exploitation. © 2010 The Authors. Tijdschrift voor Economische en Sociale Geografie © 2010 Royal Dutch Geographical Society KNAG.

In recent years, entrepreneurship among migrant minorities has increased significantly in the Netherlands. This paper addresses the key factors determining the economic position of migrant entrepreneurs in the urban economy in the Netherlands, with an application to Amsterdam. So far, little information on success conditions for migrant entrepreneurship is available, while quantitative knowledge on critical success factors (CSFs) is lagging far behind the rapid growth of migrant entrepreneurs in big cities like Amsterdam. The present study serves to fill this knowledge gap, by paying attention to the entrepreneurial behaviour of migrants, the role of their social networks, and the innovative potential of new growth markets in a modern city. In order to provide a solid assessment of CSFs for migrant entrepreneurs, and to understand business performance in a competitive urban environment, this study will investigate the entrepreneurial behaviour of migrants in Dutch cities from a micro-economic perspective. Due insight into individual entrepreneurial behaviour of migrants is needed to develop an urban business culture in which migrants are no longer a source of problems but of great socio-economic opportunities, both for the migrant groups concerned and the vitality of cities. Our research employs a comparative statistical analysis of empirical findings in the city of Amsterdam in order to map out opportunities, success conditions and bottlenecks for migrant entrepreneurs. Given our largely categorical (i.e. qualitative or soft) database, we will employ a qualitative causal pattern recognition technique, namely, rough set analysis, to systematically assess the conditions for successful entrepreneurship of migrants. © 2009 by the Royal Dutch Geographical Society KNAG.

A burgeoning literature has emerged during the last two decades to assess the economic impacts of immigration on host countries. In this paper, we outline the quantitative approaches presented in the literature to estimate the impact of immigration on the labour market, particularly at the regional level. We then revisit the joint impacts of immigration on wages and employment using a meta-analytic approach. As a novel contribution to previous meta-analyses on labour market impacts, we use a simultaneous equations approach to the meta-analysis of wage and employment effects. Using 129 effect sizes, we find that the observed local wage and employment effects are very small indeed. Generally, the employment impact is more pronounced in Europe than in the United States. Controls for endogeneity show a somewhat more negative impact. Wage rigidity increases the magnitude of the employment impact on the native born. The demarcation of the local labour market in terms of geography and skills matters also. © 2010 The Author(s).

The evaluation of real estate assets is currently one of the main issues addressed by territorial marketing strategies with a view to developing competitive cities. Given the complexity of the real estate market, it’s hard to identify a priori the factors that constitute a city’s competitive capacity to attract investments to this market. In this paper we design an integrated complex evaluation model able to map out and encapsulate the multidimensional spectrum of factors that shape the attractiveness each investment destination. The methodological approach is then illustrated through application of the model to a real-world case of investment choice in the residential sector of the city of Naples. La valorizzazione degli asset immobiliari rappresenta una delle principali attivita su cui si fondano le strategie di marketing territoriale in una prospettiva di crescita competitiva delle citta. Data la complessita dei mercati reali, e difficile definire a priori quali siano i fattori che determinano la capacita competitiva di ciascun territorio nell’attrarre investimenti nel settore immobiliare. Il contributo presenta un modello capace di esprimere la capacita di un’area di attrarre investimento nel mercato immobiliare. Il modello proposto sara applicato ad un caso esemplificativo delle scelte di investimento nel settore residenziale della citta di Napoli.

In this article, we present the results from a meta-analysis conducted over 44 experimental and field studies, which report individual discount rate estimates. We find in our research that the experimental design of a study has a decisive impact on these estimates, and conclude that meta-analysis, in the case of individual discount rates, has a low transfer value. © 2009 Taylor & Francis.

Regulations specify the maximum amount of waste that can be stored on site by a waste generating firm. When this regulatory threshold is reached, a polluting firm must move its on site waste to an off site recipient. In this setting, we analyse two questions in a stochastic framework from the viewpoints of a waste generator and a recipient that have received scant theoretical attention in the literature. First, given that off site storage is costlier than on site storage, we derive the long-run average cost incurred by a waste generating firm that stores waste both on and off site. Second, we compute the expected amount of time until the off site recipient's waste storage facility is full.

At any point in time, a cleared parcel of forest land (CPFL) used for swidden agriculture exists in either the fallow or in the non-fallow state. Further, the practice of swidden agriculture requires one to operate in an environment of uncertainty. These two points notwithstanding, there are virtually no probabilistic models of swidden agriculture that explicitly account for the above dichotomy. Hence, in this paper, we use a stochastic model and a long run perspective to shed light on two hitherto unstudied questions concerning a CPFL used for swidden agriculture. First, we use renewal theory to determine the long run fraction of time that our CPFL is in either the fallow or in the non-fallow state. Second, we use the hyperexponential distribution to compute the stationary probability that the excess variable associated with the stochastic process representing our CPFL exceeds a given value. © Springer-Verlag 2008.

The present paper aims to investigate and compare various modalities of migrant entrepreneurship in European countries in order to design a systematic classification of migrant entrepreneurship and to highlight key factors of migrant entrepreneurship in Europe. The paper is based on a comparative assessment of available quantitative data and qualitative information derived from a broad review of findings from previous studies in the literature. Our quantitative evaluation includes the European OECD countries, while our qualitative investigation addresses migrant entrepreneurship experiences in eight European countries: Denmark, Germany, Greece, Italy, the Netherlands, Portugal, Sweden, and the UK. The results of our comparative analysis show that the general picture of European migrant entrepreneurship is determined by some distinct push factors such as high unemployment rates and low participation rates or low status in the labour market as well as by an accompanying factor, namely mixed embeddedness. The results of our comparative evaluation are summarized in a systematic typological table. These show that, while an informal and labour-intensive sector, an underground economy, and small companies and traditional households prompt migrant entrepreneurship in Southern European countries, an over-representation of non-Western immigrants among the self-employed, as well as relatively lower income levels of self-employed immigrants compared to both self-employed natives and employed immigrants are decisive for migrant entrepreneurship in Northern European countries. © 2009 Taylor & Francis.

The widespread use of pesticides in agriculture shows a complex ramification of multiple negative externalities, ranging from food safety-related effects to the deterioration of farmland ecosystems. Recent research has demonstrated that the assessment of the economic implications of such negative processes is fraught with many uncertainties. This paper presents the results of an empirical study recently conducted in Northern Italy aimed at estimating the economic value of reducing the wide-ranging impacts of pesticide use, by deploying a Choice Experiment approach. The experimental design provides a meaningful tool to assign monetary values to the negative environmental effects associated with agrochemicals use. In this connection, the paper addresses in particular the reduction of farmland biodiversity, groundwater contamination and harm to human health. The resulting estimates confirm that, on average, respondents demonstrate a substantial willingness-to-pay a premium for agricultural goods (in particular, foodstuffs) produced in environmentally-benign ways. © 2008 Elsevier B.V. All rights reserved.

Resources such as orchards are vulnerable to the detrimental effects of successful invasions by alien animal or plant species. To outline an appropriate policy response, we first use renewal theory to construct a stochastic model of optimal orchard management in the presence of a deleterious alien species. Next, we derive the orchard manager's long run expected cost (LREC) of orchard management per unit time. Finally, we show that when confronted with a successful biological invasion, the optimal number of trees that need to be removed and replanted in order to keep the orchard under study sustainable in the long run minimizes the LREC function mentioned above. © Springer-Verlag 2008.

In recent years, an intensive debate on the economic valuation of biodiversity has entered the environmental-economics literature. The present paper seeks to offer first a critical review of key concepts that are essential for a proper understanding of such evaluation issues. Particular attention is given here to various monetary valuation approaches and to comparative (i.e., meta-analytical) methods from the perspective of conservation and sustainable use of biodiversity. Several illustrative examples are presented in order to highlight the usefulness of the various approaches discussed. Next, an attempt is made to infer general findings and lessons from past applied research by means of meta-analysis. In this context, a multi-dimensional technique originating from the field of artificial intelligence is deployed. It allows us to identify the most important variables responsible for changes in economic estimates of biodiversity. © 2008 Elsevier B.V. All rights reserved.

It is now common knowledge that the United States Patent and Trademark Office (USPTO) takes too long to process patent applications and that examiners make too many errors in the patent approval process. Given these twin concerns, we study the following question in this paper. Should the director of an organization such as the USPTO have a small number of examiners examine incoming patent applications less stringently or should this director have a large number of examiners examine the same patent applications more stringently? We employ a simple queuing model and show that if decreasing the average patent pendency is crucial then it makes more sense for the director to select the less stringent patent examination regime. In contrast, if reducing the number of examination errors in the patent approval process is more important then the director ought to choose the more stringent patent examination regime. © 2006 Elsevier Inc. All rights reserved.

Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of - 0.34 and - 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand. © 2007 Elsevier B.V. All rights reserved.

The Amsterdam Zuidas area is planned to become a large multi-functional development area with a mix of offices, dwellings and facilities. As part of a broader empirical investigation, the valuation of multi-functional land use of this mega-project by a specific class of stakeholders, namely, commercial investors, is examined in this paper. We are particularly interested in the expected impact of locational characteristics on urban land rent in the area. The study is based on an extensive interview questionnaire, in which future development scenarios and spatial externalities are also investigated. The study reveals that the expectations of investors are driven by a complex set of factors. Particularly important are accessibility and image. The relative importance of multi-functionality is found to be modest. © 2008 Royal Dutch Geographical Society KNAG.

This paper addresses the implications of the well-known ceteris paribus postulate for spatial–economic equilibrium analysis under conditions of complex (non-linear dynamic) interactions in open systems. Under ever changing (e.g., evolutionary) conditions, there is a need for adjusting the standard tools in spatial–economic analysis, with more emphasis on evolutionary algorithms and computer simulations to offer a solid statistical underpinning of regional analysis.