|
on Economic Geography |
| By: | Andreas P. Cornett; Nils Karl Sørensen |
| Abstract: | The purpose of the current paper is to analyze the impact of regional potentials on the process of growth. How are different types of regions (e.g. medium sized [city] regions, rural regions, urban regions or metropolitan and high-tech cluster regions) affected by improved performance, and to what extent can differences be explained by ex-ante difference in income? Based on data from the regional innovation scoreboard (RIS) is this issue addressed relative to the income level, previous growth performance and convergence. In the first part of the paper, the innovation performance of the regions is modelled relative to the income level and the underlying influencing factors are identified. Hereby, we are able to identify strengthens and weaknesses of the innovation structure in different regions. In addition the issues of returns to scale will be considered. In the second part of the paper the innovation performance is related to the process of convergence and divergence. Earlier research has shown that although convergence is present at aggregated European Union level a much more diversified picture is revealed at the disaggregated level. Here it is frequently observed that the more wealthy and central regions move away from the other regions. One of the results is that the economic crisis has reinforced not only intraregional divergence within countries but also the traditional divide between the stronger Northwest European countries and the South and East of Europe. Finally, the paper discusses and evaluates the impact of different types of innovation performance and the level of income on the perspectives of economic growth for different types of regions. A number of scenarios a sketched for the perspectives of the regions depending on endogenous as well as external factor endowment and dynamics. |
| Keywords: | Innovation- regional income differences - economic growth ? concentration - convergence & divergence |
| JEL: | R11 R12 R58 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p97&r=geo |
| By: | Tsvetkova, Alexandra; Partridge, Mark; Betz, Micael |
| Abstract: | In this paper, we explore how national economic trends in a set of industries that compose local economies and growth in nearby metropolitan areas affect local employment growth in different tiers of the urban-rural hierarchy, paying close attention to the effects of urban proximity. The results of our county-level analyses reveal heterogeneous responses. Favorable economic changes due to a fast-growing local industry composition have the largest positive impact on self-employment growth in small metropolitan areas and the smallest positive impact in rural counties. Self-employment in rural counties is fostered by growth in nearby small MSAs and is hampered by growth in nearby large MSAs. In micropolitan counties, there are no significant negative effects, whereas positive (or spread) effects are detected originating only from small and medium MSAs but not from large MSAs. In urban counties, growth in a nearby large MSA is not related to local self-employment growth in the lower tiers of the urban hierarchy. |
| Keywords: | Urban-rural hierarchy, self-employment, wage and salary employment, urban-rural interdependence |
| JEL: | O1 O51 R11 R12 |
| Date: | 2016–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75781&r=geo |
| By: | Jan Cornelius Peters |
| Abstract: | It is well known that wages in large cities are higher than elsewhere. There is only little empirical evidence on the mechanisms behind this phenomena. One channel, that is discussed in the literature, is learning. Provided that individuals learn by interacting with one another, an urban wage growth premium arises if a large labor market increases the speed of interactions between individuals (Glaeser, 1999). To analyze dynamic agglomeration benefits and the importance of learning effects, this paper makes use of a micro econometric framework described by Combes and Gobillon (2015), extents the work by De la Roca and Puga (2013) and, in contrast to previous papers, provides a consistent estimate of the elasticity between wages and the size of the labor market where experience was acquired. The analyzed wages refer to new employment relationships. They indicate how firms value working experience depending on the location where it was acquired. By including fixed effects and further control variables at both, the individual as well as the regional level, endogeneity is reduced. The paper also analyzes whether the value of experience depends not only on the size of the labor market where experience was acquired, but also on the size of the labor market where it is used. The analysis bases on a 5 percent sample of the Integrated Employment Biographies (IEB) of the Institute for Employment Research (IAB) and contains detailed information on the employment biographies from 1975 onwards for a sample of about 350,000 individuals with at least one new employment relationship in Germany between 2005 and 2011. The results indicate that experience acquired in large local labor markets has in fact a significantly higher valued than experience acquired in small labor markets. The elasticity has a fixed component and a component that depends on the size of the labor market where experience is used. The fixed component (about 0.07) points out, that experience acquired in large labor markets is in all regions valued higher than experience acquired in small labor markets. This supports the interpretation that workers learn more by working in large than in small labor markets, and that at least part of the accumulated knowledge are transferable to other regions. The second component suggests that the value of experience increases additionally with the size of the labor market where experience is used. One reasonable explanation is a combination of learning and matching effects. Since jobs in large labor markets are more specialized than jobs elsewhere, workers that worked in a large labor market accumulated knowledge that refers to the ?core task? of a job. The wage premium for this knowledge is supposed to be larger in large labor markets, since it is more likely there than in a smaller labor market, that a firm demands this specific knowledge. Moreover, workers moving from a large to a small labor market may lose since the new job contains a wider range of tasks. |
| Keywords: | Agglomeration economies; Learning; Urban wage growth premium; Transition to employment |
| JEL: | R23 J31 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p615&r=geo |
| By: | Alejandra Trejo-Nieto |
| Abstract: | The urban labour market is one of fundamental significance due to the possibilities and constraints that imposes on population´s wellbeing, and because its effects on national and local employment rates and wages. The urban dimension of the labour market is closely linked to the spatial proximity between residence and workplace, and therefore it depends on the urban structure. The localization of labour demand and supply and its proximity has been the source of multiple research. During the sixties the Spatial Mismatch Hypothesis (SMH), referring to the existence of a spatial gap between labour demand and supply within the cities, was formulated. The SMH means that workers and firms have different locations and, depending on the extent of the separation, it can have negative effects on the efficiency of the labour market and the city. Particularly, the mismatch increases transportation costs, reduces income, and reveals an unequal access to employment within cities. The hypothesis has been revived lately due to the interest on the rising tendency to polycentricism in big cities. Polycentricism has been considered as a path for the integration of large cities, which acts in favour of areas that are more distant from the Central Business District (CBD), improving accessibility to jobs. This paper deals with the SMH due to the importance of measuring and understanding location patterns of workers and jobs, and their interactions. We centre our attention on the location, concentration and the spatial separation of labour demand and supply as a first step to approach the spatial mismatch problem in urban labour markets. First, we aim at identifying the spatial patterns of workers and jobs; we measure by means of alternative techniques the spatial separation; finally, we investigate the differences between submarkets which are determined by the workers? level of education and the corresponding jobs according to their knowledge and technology level required. The manuscript will present the results for the biggest metropolitan area in Mexico, Mexico City metropolitan Area (MCMA) given its population size and economic significance (it concentrates 25% of national GDP and 23% of the jobs located in the country). The methodology we use incorporates as the main tool the Exploratory Spatial Data Analysis (ESDA), using LISAs and Moran indexes in their univariate and bivariate versions, we also employ the ?spatial mismatch index? developed by Raphael and Stoll (2002) and a spatial version proposed by Wong (2003). We use data from the population census of 2010 and the economic census of 2009 carried out by the National Institute of Geography, Informatics and Statistics (INEGI) at the level of the basic geo-statistic areas (AGEBs) in the country. Submarkets are identified according to occupied population?s education levels and the technology intensity of economic activities. |
| Keywords: | urban labour markets; spatial mismatch; spatial analysis |
| JEL: | R00 R23 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p124&r=geo |
| By: | Juan Moreno-Cruz; M. Scott Taylor (University of Basel) |
| Abstract: | This paper sets out a simple spatial model of energy exploitation to ask how the lo-cation and productivity of energy resources a ects the distribution of economic activityacross geographic space. By combining elements from energy economics and economicgeography we link the productivity of energy resources to the incentives for economicactivity to agglomerate. We nd a novel scaling law links the productivity of energyresources to population sizes, while rivers and roads e ectively magnify productivity.We show how our theory's predictions concerning a single core, aggregate to predictionsover regional landscapes and city size distributions at the country level. |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:bsl:wpaper:2017/01&r=geo |
| By: | Anastasiia Konstantynova; Tine Lehmann |
| Abstract: | In recent decades? industrial clusters and agglomerations were recognized as drivers of regional and often national economic growth and competitiveness. Based on this cluster policy has been widely used to spur economic change, especially on the sub-national level. The public support to cluster development was widely done following the observed examples in the United States aiming to follow their success stories. Most commonly applied cluster policy approach composed of cluster mapping, establishment of institutions (labelled as cluster initiative/ association) in respective clusters through public-private support of these institutions´ and companies´ activities. However, the implementation of blue-printed cluster policy did not always lead to positive paths of cluster development due to the negligence of country / region specific institutional frameworks. This paper fills this void, by exploring selected cases of cluster associations and how their activities are influenced by different sets of institutional framework conditions. Information and communication technologies (ICT) clusters and their associations in European Union (EU) and Non-EU countries are taken as cases for the analysis. |
| Keywords: | clusters; cluster policy; cluster association; institutions; ICT |
| JEL: | R11 R58 O18 M21 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p722&r=geo |
| By: | Emanuela Marrocu; Silvia Balia; Rinaldo Brau |
| Abstract: | Free patient mobility among autonomous providers has been often considered an effective stimulus for enhancing healthcare. However, some jurisdictions may underperform due to the existence of economies of scale and spatial spillovers. Where regions assume the costs of providing care to residents, this could challenge the sustainability of regional budgets in a decentralised National Health Service (NHS) and put at risk universalism and equity of health care. We use a ten years (2001-2010) panel of Italian data on hospital discharges to assess the determinants of inter-regional mobility and to distinguish between factors related with policies pursued by the regional health authorities from extra-regional (neighbouring regions or national-level) factors. Data on hospital discharges are merged with a set of variables on salient features of hospital care services in each Regional Health System (RHS) and with information on demographic and economic characteristics of Italian regions. We analyse bilateral Origin-to-Destination (OD) flows between any two regions by means of a gravity regression model that includes a rich set of push and pull factors. Compared to previous studies, mainly performed on cross-section samples, the longitudinal dimension of the data enables us to estimate a nonlinear conditionally correlated random effects dynamic model that accounts for region-pair-specific unobservable heterogeneity. Moreover, we address the issue of cross-regional dependence arising from the existence of regional spillovers by applying recent advances in spatial econometrics (Elhorst, 2014; Vega and Elhorst, 2015). The model is estimated for total inter-regional patient flows and for specific types of hospital admission, namely surgery, medicine and cancers. Finally, the estimation results are used to analyse specific what-if scenarios relevant to the health authorities for the national and sub-national management of services. Our main results suggest that, beside regional population and income, local supply factors such as hospital capacity and technology endowment, clinical specialization and performance indicators are important drivers of patient mobility. Moreover, geography matters and spatial proximity plays a relevant role in reinforcing inter-regional mobility patterns. Our econometric analysis has also detected a mildly explosive dynamics in inter-regional patient mobility over time. This result, coupled with the significant role played by factors not directly controlled by regional policy-makers and RHS managers (e.g. population, GDP per capita and spatial spillovers), might induce a polarisation between the group of the richest, most populated and best performing regions, which are increasingly capable of attracting more patients, and the group of the weakest regions, with growing patient outflows and severe financial and organizational problems. These considerations call for a thorough assessment of the long-run sustainability of the current decentralised NHS. RHS budget autonomy could not be entirely consistent with free patient choice. This opens a more general discussion on whether and to what extent the health financing system would require the introduction of appropriate equalising compensation schemes aimed at neutralising the financial consequences of mobility and, eventually, at guaranteeing universalism and equity in healthcare. |
| Keywords: | regional health systems; hospital admissions; gravity model; nonlinear gravity panel model; spatial spillovers |
| JEL: | C23 I18 H75 R23 R50 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p127&r=geo |
| By: | Tödtling, Franz; Sinozic, Tanja; Auer, Alexander |
| Abstract: | The health sector and medical technologies are of an increasing importance in society and for regional and national economies. Much like other life sciences industries, the medical devices sector relies upon specific factors and knowledge processes that shape and support its innovation capabilities and competitiveness. Previous studies have shown that growth and innovation in this sector depend on specific local factors and conditions as well as on markets and knowledge-interdependencies at higher spatial scales. There is still a research gap on the detailed nature of these driving factors and relationships, however. In this research, we have investigated these issues for the Vienna medical devices cluster that is part of the wider life sciences sector in this region. The main aims of the study were to generate insights into how different economic, knowledge- and policy conditions, and their spatial scales, interact to support and hinder development of the medical devices industry in Vienna, and to draw policy conclusions based on these findings. (authors' abstract) |
| Date: | 2016–06–20 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus009:5199&r=geo |
| By: | Calá, Carla Daniela |
| Abstract: | We analyse the determinants of firm dynamics in developing countries using Argentina as an illustrative case. We explain firm entry and exit at the regional level, distinguishing three groups of manufacturing activities: low, medium and high tech. We find that both region -and sector- specific determinants explain firm dynamics, but the impact is not homogeneous across sectors. In particular, for low tech industries, there is a need for explanatory variables that proxy for the specificities of developing economies (poverty, informal economy and idle capacity). We also find evidence of a core-periphery pattern according to which agglomeration economies and previous entries/exits have different effects in core and peripheral regions. These results are relevant for policy makers in developing countries, who should take into account not only the specificities of such economies, but also the regional heterogeneity both in terms of the level of development and industrial composition within the country. |
| Keywords: | Dinámica Empresarial; Creación de Empresas; Cese de Actividad; Relación Centro-Periferia; Modelo de Panel; Argentina; |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:nmp:nuland:2587&r=geo |
| By: | Jeffrey Zax |
| Abstract: | This paper assesses regional inequality in contemporary urban China by predicting earningss for individual workers in multiple provinces, comparing the province of maximum predicted earnings to the province of residence and assessing the predicted gains from relocation. The paper performs the same comparison for the U.S. in 1940 to provide an informal baseline comparison. Workers predicted relatively similar earningss in each of the nine U.S. Census divisions. Fewer than 10% of them predicted maximum earnings in divisions other than their home division that exceeded their predicted home division earnings by more than 20%. In contrast, 45% of Chinese urban workers in 1988 predicted maximum earnings in provinces outside their home province that exceeded their predicted home province earningss by more than 50%. The same was true of 54% of Chinese urban workers in 1995, 74% in 2002 and 57% in 2008. If all Chinese urban workers received the maximum of their predicted earningss across all provinces, rather than their predicted earnings in their home province, average earningss would approximately double, interpersonal inequality would decline by 40-50% and inter-provincial inequality would vanish. In all years, predicted earnings in Guangdong province have generally been greater than in any other province. The implicit value of the right to live in Guangdong was at least 26% of earnings in 1988 and 41% in 1995. It declined to about 7% of earnings in 2002 and 2008, but only because predicted earnings in Beijing and Shanghai had risen. The gaps between predicted earnings in Guangdong and other provinces in those years was similar to those in earlier years. |
| Keywords: | Inequality; Returns to human capital; Migration; Law of one price |
| JEL: | J24 J31 J61 R12 R23 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p693&r=geo |
| By: | Anna Bufetova |
| Abstract: | The introduction of market mechanisms regulating the economy in the Russian Federation has led to change of spatial distribution of economic activity and further increase of regional economic development disparities. All the approaches to the regional policy declared by the Government in the last decades didn't succeed. So the question of evolution of spatial distribution of economic activity and regional disparities remains very actual. The aim of this work was to analyze the evolution of spatial distribution of economic activity in the Russian Federation and the role of space in the inequality of regional development. We study the evolution of spatial distribution of economic activity and convergence process among regions from the change of the region relative position inside the cross-sectional distribution of regions in terms of gross regional product (GRP). The growth process is modeled as a first-order Markov chain. Spatial effects in our study are introduced within the Markov chain framework using regional conditioning and spatial Markov chain. By applying this technique we achieve a more detailed picture of the evolution of distribution of economic activity and spatial disparities than in other studies on the topic. These tools also allow studying how the economic performance of a region and its position inside the GRP distribution can be explained by its geographical environment. The results of the analysis, based on a data set for 79 Russian regions over 2001-2013 period suggest that the process of economic growth has been characterized by the continuing concentration of economic activity. Along with the preservation and strengthening of positions of the former centers, a number of new ones emerged, and at the same time some centers with resource specialization to some extent weakened their positions. The study showed a progressive bias toward a poverty trap. The ergodic distribution of the regions in terms of economic activity, achievable while maintaining trends of study period, shows the formation of a sufficiently large pole of relative poverty and pole of wealth that concentrates a significant proportion of manufacturing value added. Emerging group of regions with an average level of development is relatively small. Regional conditioning and spatial Markov chain clearly indicate that location and physical geography matter to explain growth and convergence process. The changes of the relative position of a region in the cross-sectional distribution are highly constrained by its geographical environment. Regions of almost all level of development have better evolutionary perspectives when surrounded by rich neighbors (but not less developed regions) and worse perspectives when surrounded by poor neighbors so that progressive bias towards poverty trap has a strong spatial explanation. In such circumstances, regional policy aimed at stimulating the developed regions, can reinforce the ongoing process of polarization. And policy aimed at smoothing the uneven territorial development in order to avoid excessive deepening of regional disparities and inequalities seems to be more adequate. |
| Keywords: | spatial distribution of regional economic activity; regional disparities; Markov chains |
| JEL: | R11 R12 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p104&r=geo |
| By: | Laura Resmini; Giuseppe Vittucci |
| Abstract: | This paper deals with the performance of multinational enterprises (MNEs) during the recent financial crisis in the EU regions. According to the existing literature both foreign affiliates and local territories may benefit one from each other. There is a huge literature suggesting that FDI is sensitive to transparent and open systems that may ensure a good access to local resources, such as human capital, knowledge and technology, as well as regions with enough capacity to ?absorb? the new technology, know-how and management practices brought into their territories by MNEs may enjoy faster economic growth. This implies that MNEs and regions hosting their foreign plants are interlinked; therefore, the (mis)fortunes of one may condition the performance of the other. The economic crisis that affected and still affects most of European regions both within and across countries has further emphasised the importance of this issue. Do regions hosting foreign production plants show a better resilience to crisis? Do MNEs survive better than indigenous firms during this period? And if yes, which characteristics allowed MNEs to better react to the crisis than other firms? In addressing these questions, we first examine if foreign ownership, and the associated involvement in global value chains, was a factor influencing firms? performance and, if so, through which channels. Then, the identified channels are shown to be also important to explain differences across firms in the response to the crisis. To the best of our knowledge, this is the first article addressing systematically the implications of the recent crisis for firms? performance and drawing from it insights about the EU regions resilience to global shocks. Our analyses rely on a comprehensive firm-level dataset including all firms active in the EU before the economic crisis (2006). Both indigenous and foreign firms are considered and several firm?s characteristics, i.e. size and experience, the market focus, and the ownership structure, have been accounted for in order to analyse the probability to survive to the crisis of domestic and foreign firms. Micro-data on firms is derived from the AMADEUS database of firm financial accounts which is provided by the Bureau Van Dijk. This paper offers several contributions to the existing debate on the importance of foreign firms for the performance of local economies. First all, it sheds light on the role of MNEs in EU regions resilience to the crisis. Secondly, it helps in understanding whether multinational firms acted as a stabilizer or a propagator of the crisis across EU regions. Finally, identifying firms ? both local and foreign ? that may improve regions? resilience to the crisis may help design more effective and better targeted policies for enhancing local development and attract foreign firms that suit better within the local context. |
| Keywords: | foreign divestments; EU regions? resilience; survival analysis |
| JEL: | F23 O52 R12 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p220&r=geo |
| By: | Paulino Montes-Solla; Andres Faina; Jesus Lopez-Rodriguez |
| Abstract: | This paper analyses the different factors that explain the pattern of economic growth in Spain along the last two decades, where has stood out the rapid growth of per capita income, capital accumulation and creation of employment. However, the most important structural phenomenon of the strong growth of the Spanish economy, especially in the decade from 1998-2007, was the limited growth in terms of output per worker and total factor productivity (TFP), which in combination with wage increases has led to a loss of competitiveness. An extended Solow growth model was estimated with panel data for the Spanish regions to measure the contribution of different factors of production (with special interest in the stock of private and human capital, as well as the gap of transport infrastructure capital) to the productivity of labour and the temporal evolution of TFP over the period 1989-2010. The results of our analysis provide strong evidence of stagnation in productivity throughout most of the period under study. The large investments and the strong growth in capital stocks were practically absorbed by an intense process of job creation. As a consequence, the capital/labour ratio and labour productivity levels remained almost constant whereas total factor productivity (TFP) decreased over the period of analysis. Therefore unlike other European countries, Spain did not experience a phenomenon of capital deepening with an increase in productivity. The intense GDP pc growth in Spain was of a rather "extensive" type, mainly based on a capital widening process. |
| Keywords: | Regional Development; Infrastructures; Capital Widening; Productivity stagnation; TFP |
| JEL: | R10 R11 R12 R13 R14 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p983&r=geo |
| By: | Mete Basar Baypinar |
| Abstract: | The ICT and software industry have evolved as twin global industries now spanning a large number of interconnected clusters in the developed and emerging countries. Firms, governments and other actors have re-established different relationships and structures throughout 1980-1984, early 1990s, 2000-2001 and 2007-2008 crises, often resulting in decline of older clusters and emergence or solidification of newer ones. Studies indicate that a cluster?s evolution, its position in the technological life-cycle, and dominancy are quite relevant with resilience of the cluster. On the other hand, region-specific factors seem to be important for specialization of ICT-software clusters, which, may work or against their benefit due to strategic geographic responses of larger actors in the industry, such as promotion of offshore outsourcing or onshore in-house activities. There is increasing evidence that these factors are recently used better by regional and national governments against clusters in more advanced regions, particularly by strategic use of timely legal reforms, state-sponsored large ICT-software projects and attempts to grow local ICT-software markets. Yet, the knowledge externalities created by these efforts are captured not only by large MNCs, but also by an increasing number of local companies, which are increasingly transforming into multi-national actors. This paper tries to evaluate how governments, local companies and MNCs establish strategic collaborations and promote growth of clusters in emerging country context, in the case of ICT-software industries. The study relies on secondary data resources and the literature in evaluating emerging country contexts, but also makes use of primary data, local and national strategic planning documents and interview interpretations in the context of Turkey?s clusters. The study?s main contribution lies in demonstrating how mixed core/periphery features, collaboration of local/national actors with global actors, and emerging new technologies play a role in the emergence of new forms and functional structures at industry level. |
| Keywords: | software; information and communication technologies; resilience; clusters; emerging countries |
| JEL: | H12 L86 O38 N90 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p232&r=geo |
| By: | Wyatt J. Brooks; Joseph P. Kaboski; Yao Amber Li |
| Abstract: | Industrial clusters are promoted by policy and generally viewed as good for growth and development, but both clusters and policies may also enable non-competitive behavior. This paper studies the presence of non-competitive pricing in geographic industrial clusters. We develop, validate, and apply a novel test for collusive behavior. We derive the test from the solution to a partial cartel of perfectly colluding firms in an industry. Outside of a cartel, a firm's markup depends on its market share, but in the cartel, markups across firms converge and depend instead on the total market share of the cartel. Empirically, we validate the test using plants with common owners, and then test for collusion using data from Chinese manufacturing firms (1999-2009). We find strong evidence for non-competitive pricing within a subset of industrial clusters, and we find the level of non-competitive pricing is about four times higher in Chinese special economic zones than outside those zones. |
| JEL: | L11 O1 O25 R11 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22947&r=geo |
| By: | Tsvetkova, Alexandra; Partridge, Mark; Betz, Michael |
| Abstract: | Economic development policies often revolve around supporting small businesses and new firm creation as they are locally grown and likely can be more influenced by state and local policy. Two prominent strands of current research—the regional economic growth and small business/entrepreneurship literatures—elucidate the importance of small, young firms for regional economic performance and the crucial role urban-rural proximity plays in the distribution of growth across space. Keeping these two research traditions in mind, we study the effects of self-employment on job growth in US counties. Our goal is to estimate the net employment spillovers from changes in self-employment (SE) and to compare them to spillovers from changes in wage and salary employment (WS). We ask the following research questions: Do exogenous net changes (shocks) in SE spur larger or smaller changes in employment than do equal changes in WS employment and do these effects vary across the rural-urban hierarchy? The answers to these questions are of paramount importance in devising economic development strategy across urban and rural settings. We use a differencing strategy and an exogenous measure of SE and WS employment shocks to estimate net multiplier effects and to investigate their relationship with proximity to differing-sized urban centers. The analysis uses US county-level data spanning the 2001-2013 period. The results suggest that marginal effects from self-employment are consistently larger than from paid employment, particularly in metropolitan counties. Given the dominant share of paid employment, however, the magnitude of economic impact is greater from wage and salary employment. Distance from urban centers generally offers protection that promotes SE growth but hinders WS employment growth. In an austere fiscal environment, spending a dollar to stimulate SE is likely to have greater returns as opposed to stimulating WS employment if the costs of creating one SE and one WS job are comparable. |
| Keywords: | self-employment; wage and salary employment; exogenous demand shocks; employment growth; job creation; regional economic growth |
| JEL: | O1 O51 R11 |
| Date: | 2016–12–23 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75777&r=geo |
| By: | Rolf Bergs |
| Abstract: | Nocturnal satellite images may offer an interesting tool to generate socio-economically relevant data and to analyse the evolution of space, e.g. cities or rural areas, and how spatial units interact over time. So far, the major purpose of using night satellite images for economic analysis has been the search for proxies for production and population density in countries with insufficient and unreliable data infrastructure. This essentially applies to less developed countries where weak data infrastructure is often part of overall underdeveloped administrative capacities. Error variance of light emission is constant over space and independent from error in official statistics. In industrialised countries official socio-economic data are deemed sufficiently reliable, a the reason why night satellite analysis has been more of relevance for developing countries. However, this differentiation only holds for purposes to derive proxies for production or population data. In fact, there is also reason to use this tool in the observation of (spatial) economic patterns and trends in the more industrialised countries. Spatial distribution of rural areas, urban agglomerations, border areas or other spatial categories are to be mentioned. More importantly, underlying patterns of spatial heterogeneity, such as Zipf?s law, or spatial dependence (change of spatial autocorrelation over time) can be made visible - without distortion implied by (changing) administrative boundaries. The images analysed in this paper are satellite images of the National Oceanic and Atmospheric Administration (NOAA). Global nighttime lights imagery data are collected by the Defense Meteorological Satellite Program Operational Line Scanner (the DMSP-OLS). The night imagery data have a spatial resolution of 30 arc-seconds and are recorded between 75°N and 65°S. We explore whether time series of nocturnal satellite imagery and the application of adequate image analysis software, such as ImageJ (in some cases to be complemented by further statistics software), opens a useful perspective for the analysis of spatial change. ImageJ is a widely used open source image analysis software that had been developed at the US National Institutes of Health since the end of the 1990s supported by a large international community of contributors. Its primary purpose has been to process images in medical and biological sciences where has obtained a de facto standard for image analysis. However, as the synopsis of literature shows, the software has a broader range of applications - beyond microscopy and medical imaging - such as astronomy, environmental analyses, earth sciences including remote sensing, material sciences, viticulture archaeology and others. This paper is an essay with first ideas for discussion; the approach is explorative-methodological rather than one putting an empirical focus on a defined research item. |
| Keywords: | nocturnal satelite images; spatial dependence; spatial heterogeneity |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p256&r=geo |
| By: | Duccio Piovani; Vassilis Zachariadis; Michael Batty |
| Abstract: | Newly available data on the spatial distribution of retail activities in cities makes it possible to build models formalized at the level of the single retailer. Current models tackle consumer location choices at an aggregate level and the opportunity new data offers for modeling at the retail unit level lacks a theoretical framework. The model we present here helps to address these issues. It is a particular case of the Cross-Nested Logit model, based on random utility theory built with the idea of quantifying the role of floor space and agglomeration in retail location choice. We test this model on the city of London: the results are consistent with a super linear scaling of a retailer's attractiveness with its floor space, and with an agglomeration effect approximated as the total retail floorspace within a $325m$ radius from each shop. |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1612.06441&r=geo |
| By: | Yingxia Pu; Ying Ge |
| Abstract: | With the development of global economy and rapid process of urbanization, migration has become one of the key forces in population redistribution and has important implications for socio-economic development in a region. As we all know, population migration flows between different regions are related to not only the origin- and destination-specific characteristics, but also to the migration flows to and from neighborhoods. Intuitively, changes in the characteristics of a single region will impact both inflows and outflows to and from other regions. In order to explore the spatial interaction mechanism driving the increasing population migration in China since the open door policy, this paper builds the spatial OD model of interprovincial migration flows based on the sixth national population census data and related social-economic data. The findings are as follows: (1) Migration flows show significant autocorrelation effects among origin and destination regions, which means that the migration behavior of migrants in some region is influenced by that of migrants in other places. The positive effects indicate the outflows from an origin or the inflows to a destination tend to cluster in a similar way. Simultaneously, the negative effects suggest the flows from the neighborhood of an origin to the neighborhood of a destination tend to disperse in a dissimilar way. (2) Multilateral effects of the regional economic and social factors through the spatial network system lead to the clustering migration flows across interrelated regions. Distance decay effect plays the most influential force in shaping the patterns of migration flows among all the factors and the negative spillover effect further aggravates the friction of distance. As for destinations, the influence of wage level and migration stocks is beyond the GDP and the positive spillover effects of these factors enhance the attraction of neighborhood regions. The spillover effects of unemployment rate and college enrollment of higher education are significantly negative while destination population is not significant. As for origins, population and migration stocks lead to positive spillover effects on the neighborhoods while the effects of other factors are negative. (3) Changes in the regional characteristics will potentially lead to a series of events to the whole migration system, and the flows to and from the center of oscillation and its neighborhoods vibrate greatly compared with other regions. The simulation results of 5% GDP increase in Jiangsu province indicate that the outflows to other regions decrease while the inflows from all others increase to some different extent. Comparatively, the influence on the flows to and from the regions neighboring Jiangsu is significant while that of remote regions is much less, which cannot be explained by the traditional gravity model. |
| Keywords: | population migration flows; network autocorrelation; multilateral effects; spatial OD model; spatial mechanism analysis; China |
| JEL: | C13 C15 C31 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p423&r=geo |
| By: | Jingjing Liu; Peter Nijkamp |
| Abstract: | Along with the globalization and information-economic epoch, international knowledge spillover plays an important role in regional development, and the regional innovation system becomes more and more open-ended. As a nexus of the destination and the outside world, inbound tourism brings various economic and social resources for the development of the host region, which may also contribute to a higher level of cognitive proximity and absorptive capability as well as to greater product variety and manifold consumption externalities. Much research has addressed the influence of innovation on the tourism industry development, but only a few studies have focused on the impact of tourism on innovation. This study focusses on the influence of inbound tourism on a regional innovation system. The aims of this research are to: (1) interpret the mechanism of how inbound tourism impacts regional innovation; (2) inquire the external influence factors of the performance of inbound tourism; (3) explore the different characteristics of these effects when considering different types of innovation; (4) revisit the Tourism-Led Growth (TLG) hypothesis, and consider whether innovation can be a new vehicle to explain the influence of inbound tourism on spatial economic development. The influence of inbound tourism on innovation will provide a new perspective for analyzing the long term impact of tourism development. Furthermore, it may also be a meaningful complement to studies on the relationship between immigration, culture diversity and innovation, especially in the context of developing regions. Our study is organized as follows. First, the theoretical framework and the related hypotheses on the interaction between inbound tourism and regional innovation are presented. The network structure and diverse demands approaches as well as the effect of the regional absorptive capacity are considered and highlighted. Next, data from 30 Chinese Mainland provinces (Tibet being excluded, because part of the important indicators are unavailable) for the years 2003-2012 are used for the empirical analysis. The data come from the Chinese Patent Statistical Yearbook, the Chinese Statistical Yearbook, and the China Economic & Industry Data Database. From a methodical perspective, an entropy method and a perpetual inventory method were undertaken to measure the key variables. Next, a descriptive analysis was used to reach a preliminary idea on the above relationship. As to the existence of spatial autocorrelation, spatial panel data analysis was conducted to test these hypotheses. The study finds that inbound tourism is a driving force for a regional innovation system in China and can bring a new life to regional economic development. Firstly, inbound tourism appears to have a direct and indirect impact on regional innovation, while absorptive capacity has a significant mediating effect in this relationship. Secondly, the impact of inbound tourism on regional innovation capacity tends to be stronger in the wealthier and more international-oriented provinces. Thirdly, the effect of inbound tourism on technological innovation is mostly weaker than that of social innovation. Fourthly, this study supports the TLG hypothesis with regional innovation as the mediating variable. |
| Keywords: | Inbound tourism; regional innovation; absorptive capability; spatial panel data analysis; China. |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p600&r=geo |
| By: | Jin Guo; Yingzhi Xu |
| Abstract: | Benefit from the advantage of externalities, urban agglomerations are playing more and more important roles in regional economic development. However, present literature failed to distinguish the differences between urban agglomerations? pecuniary externality and technology externality. In this paper, we took Chinese five national key construction urban agglomerations as cases to make more comprehensive empirical studies of these two types externalities? manifestations, mechanisms and key factors. The results indicated that (a) urban agglomerations? pecuniary externality manifested as inter-urban capital allocation while its technology externality manifested as inter-urban technology spillover. Currently, (b) the key factor for Chinese five national key construction urban agglomerations? pecuniary externality was market size, that meant to pursue larger market size was one main motivation in forming Chinese urban agglomerations, but the inter-urban capital allocation did not show a trend of shifting to cities with higher labor productivity. (c) The key factor for Chinese five national key construction urban agglomerations? technical externality was economical density, that meant to pursue higher economical density was another main motivation in forming Chinese urban agglomerations, but both cities? own research and development activities and the spread from other cities? failed to improve urban agglomerations? technological levels. Besides, (d) there was no evidences suggested diversification or specialization of industrial structure had relations with urban agglomerations? pecuniary externality or technology externality. The regressions of dummy variables indicated that (e) there were no significant differences in pecuniary externality between Chinese five national key construction urban agglomerations? core cities and surrounding cities, but their technology externality presented complex differences. |
| Keywords: | urban agglomeration; pecuniary externality; technology externality; agglomerate motivation |
| JEL: | O47 R1 R3 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p64&r=geo |
| By: | Milene Simone Tessarin; Paulo César Morceiro, André Luis Squarize Chagas |
| Abstract: | The innovation in industry occurs due to direct investment of the firm, motivated by economic interests, as profit, market share, economies of scope, etc. However, same these decisions can be influenced by indirect shocks occurring in closest industry, as an innovation in automobile industry motivating changes in its chain production. The aim of this paper is to evaluate the peer effects on the innovation indicators in Brazilian manufacturing industry. For this, we proposed a new way to measure the proximity of the industries. We consider the typical goods produced by an industry in the main subsector and in other sub-sectors. These sub-sectors are considered neighbors because they use the same technological and production bases. The sectorial proximity was building through a detailed “sectorial diversification matrix” of firms producing goods in one or more subsector (of a total 103 subsectors of the Brazilian manufacturing) in 2013. Brazilian Institute of Geography and Statistics (IBGE) provided the data from a specific request, special to this work. The data composed a W-matrix relating one by one sector. As an innovation proxy, we considered the number of engineers employed divided by the total number of 2 employees in each subsector. This indicator is a proxy recognized of the innovative efforts of companies, because innovation and technological intensity are related to technical staff' skills. To test the peer effects hypothesis we considered the Moran's I test, and we used the LM and the LM robust tests to choose a best econometric model that confirms the sectorial spatial dependence. The results suggest the existence of strong sectorial peer effects among subsectors with the same technological level (low and medium-low, and high and medium-high). Moreover, there is a weak neighborhood effect between subsectors of different technological levels. Therefore, the technological level of a sector is a good indicator of their relations of sectorial neighborhood. These results can be useful for policymakers assign public policies focused on subsectors generating greater spillovers effects on the production and innovation structure. We think this work is a contribution to the use of spatial econometric analysis beyond the geographical neighborhood. It also sheds light on a fertile research agenda, which is currently absent in the industrial organization literature. |
| Keywords: | Sectoral neighborhood; Innovation; Spatial econometrics |
| JEL: | C23 O3 L14 |
| Date: | 2016–12–07 |
| URL: | http://d.repec.org/n?u=RePEc:spa:wpaper:2016wpecon37&r=geo |
| By: | Edward L. Glaeser |
| Abstract: | Why are real estate bubbles so common? Can these bubbles actually do some good? Real estate booms have regularly occurred throughout the world leaving painful busts and financial crises in their wake. This paper suggests that real estate is a natural investment for more passive debt investors, including banks, because real estate’s flexibility makes it better collateral than specifically built production facilities. Passive capital’s preference for real estate will be particularly strong when agency problems bedevil equity investments. Consequently, passive capital may flow disproportionately into real estate and the errors of passive capital can generate real estate bubbles. The preference of banks for more fungible real estate assets can also explain why real estate is so often the source of financial crises. In principle, real estate bubbles can be welfare enhancing, if cities would otherwise be too small either because of agglomeration economies or building restrictions. But given reasonable parameter values, the large welfare cost of any financial crisis associated with a real estate bubble is likely to be much higher than the modest benefits of extra building. The benefits of real estate bubbles are welfare “triangles” while the costs of widespread default are welfare “rectangles,” which is why bubbles rarely appear to be benign events. |
| JEL: | G15 R10 R30 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22997&r=geo |
| By: | Rémi Lemoy; Charles Raux; Pablo Jensen |
| Abstract: | Reproducing the socio-spatial structure of cities is one of the challenges facing the standard urban economics model of Alonso, Muth, Mills (AMM model). In a widely cited paper, Jan K. Brueckner, Jacques-Fran çois Thisse and Yves Zenou (1999) asked "Why is central Paris rich and downtown Detroit poor?" and proposed a model with a positive central amenity to account for the structure of European cities, where the city center is usually rich, like in Paris. In this work, we exploit the power of the AMM model and show that various utility functions and plausible conditions offer alternative explanations of households' location by income within a city. We first propose to take into account the empirical fact that the share of income spent for housing decreases when income increases. With a Cobb-Douglas utility function and two income groups, this ingredient yields different social structures than the standard one with low income households in the center and rich ones in the periphery. Depending on the relative values of the city radius and a critical radius related to model parameters, different urban forms appear indeed. These include the existence of a "rich" center and more complex socio-spatial urban forms, for instance alternating a rich center, poor suburbs and a rich outer ring, which have not yet been derived from the AMM model to our knowledge. In this work, we combine analytical ideas and illustrations by the means of an agent-based model. Indeed, starting from a random configuration of the city, a system of agents given relevant behaviour rules can find the equilibrium configuration of the AMM model. This modelling approach is inspired from the Monte Carlo method, and from local search optimization algorithms in computer science. Following Brueckner, Thisse and Zenou (1999), we also study the hypothesis of a central amenity. We show that under certain conditions, a central amenity can also yield a rich city center, and even a U-shaped curve of the income as a function of the distance to the city center. This result can be related in particular to empirical findings in some older North American cities, like New York, Chicago or Philadelphia as well as European cities like Paris. We find with agent-based simulations that these outcomes depend strongly on the respective locations of the employment and the amenity centers. Indeed, considering that the CBD and the amenity do not coincide has an important influence on the socio-spatial structure of the city. |
| Keywords: | urban economics; location; income; amenity; agent-based model |
| JEL: | D11 R14 C63 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p524&r=geo |
| By: | Andrea Morescalchi |
| Abstract: | This paper investigates the spatial connotations of job search methods of unemployed people, and in particular whether search methods lead to local vis-Ã -vis non-local jobs. The data set used is the British Household Panel Survey (BHPS), a longitudinal survey collecting yearly interviews for about 10,000-15,000 individuals. Information on the current labour market spell at the time of interview and on all previous spells back to one year before is used to construct unemployment duration data. Unemployment spells are defined as a series of monthly episodes ending up in a transition to job or out of labour force, or right-censored. For any unemployment spell recorded at the time of interview, the individual is asked to report on the search methods used in the last four weeks. A total of five methods can be selected, namely whether he/she (a) applied directly to an employer (DAE); (b) studied or replied to advertisements (ADS); (c) contacted a private employment agency or Job Centre (EA); (d) asked friends or contacts (SOCNET); (e) took steps to start own business (SEMP). Exits to job are decomposed between exits to local and to non-local jobs (Munch et al., 2006; Battu et al., 2008; Monchuk et al., 2014). Exits to non-local jobs are defined as exits associated to a residential move in a distant area occurring between 12 months before and 12 after the entry into job. Long-range moves are defined as moves between any of the 434 Local Authority Districts (LAD) in the UK. Exits to local jobs are defined residually as exits associated either to no move or to within-LAD move. All spells starting after September 1995 and until 2009 are used in the analysis. The resulting sample consists of 1,611 unemployment spells: 137 (8.5%) end with exit to non-local job, 908 (56.4%) with exit to local job, 244 (15.1%) with exit out of the labour force, and 322 (20%) are right censored. In order to identify search methods conducive to local or non-local employment, an unemployment duration model with competing risks is estimated. The three possible unemployment exits are modeled against the probability of remaining unemployed. Following Monchuk et al. (2014) and Morescalchi (2015), hazards are treated as intrinsically discrete by employing a multinomial logit model with data organized in person-month form (Allison, 1982). A large set of control variables is included to account for individual and household characteristics, and for macro-economic effects at the national, regional and local level. Results show that SOCNET and ADS have positive significant impact on exit rates to local employment, while DAE has positive significant impact on exit rates to non-local employment. EA and SEMP have no effect on any exit to job. The present results provide a novel perspective to assess the outcome of the job search process. Since geographic mobility can importantly compensate for regional shocks and it is considered as one of the ways to promote full employment in Europe, as set out at the ?Lisbon Strategy? (European Commission, 2001), the present evidence appears of interest. |
| Keywords: | job search; search methods; regional labour markets; mobility |
| JEL: | J61 J64 R23 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p307&r=geo |
| By: | Bastian Heider; Martin T.W. Rosenfeld; Albrecht Kauffmann |
| Abstract: | Public sector activities are often neglected in economic approaches to analyze the driving forces of urban growth and changes in urban hierarchies. One crucial aspect of public sector activities is the institutional status of cities as regional capital. The paper is reporting on a quasi natural experiment on East German county towns. Since 1990, cities in East Germany have shown remarkable differences in their population development. During the same period many towns have lost their former status as county seat due to several administrative reforms. Using a Difference-In-Difference approach we compare the population development of former county capitals to cities successfully holding a capital status over the observed period. The estimation results show a statistically significant and economically relevant positive effect of holding a county capital status on annual population change. We further observe that the difference in population developments is increasing over time. Our results are not only of empirical interest but contribute to the general literature, explaining urban hierarchies and should be considered by policymakers for future policy measures stimulating urban economic growth. |
| Keywords: | Urban Economic Growth; Centrality; Institutions; Public Sector; East Germany; Post-socialist Cities; Capital Cities; County Towns; County Government Reform |
| JEL: | R1 R5 P2 H1 H7 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p308&r=geo |
| By: | Peter Schmidt |
| Abstract: | This paper analyses the effects of EU regional policy transfer payments on net migration flows among the EU-28 countries. The hypothesis is tested that EU transfer payments do hamper internal migration across the EU. On the one hand, this is done by reestimating the results found by Egger, Eggert and Larch (2014): "Structural Operations and Net Migration Across European Union Member Countries", Review of International Economics, 22(2), pp. 352-378 for a longer time period, who basically tested a NEG model where they derived the above hypothesis from. On the other hand, a more neoclassical model of the migration-regional policy-nexus is tested. Like in Egger et al. (2014) a significant effect of EU regional policy expenditures on net bilateral migration among the EU-28 member countries is identified. However, contrary to Egger et al. (2014), the effect is not negative but positive. On average, a one percentage point increase of structural funds expenditures in percent of GDP leads to an increase in the measure of net bilateral migration by about 0.2-0.6%. Hence, EU regional policy transfer payments spur instead of hamper internal migration across EU member countries. |
| Keywords: | EU regional policy; structural funds; internal migration; convergence; European integration |
| JEL: | E62 F15 F22 H53 I38 R58 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p172&r=geo |