nep-geo New Economics Papers
on Economic Geography
Issue of 2010‒12‒04
fourteen papers chosen by
Vassilis Monastiriotis
London School of Economics

  1. Defening and Measuring Polycentric Regions.The Case of Tuscany By Davide Burgalassi
  2. Educational Performance and Spatial Convergence in Peru By S. J. Rey
  3. Chow-Lin Methods in Spatial Mixed Models By Wolfgang Polasek; Richard Sellner; Carlos Llano
  4. Visualizing Regional Income Distribution Dynamics By S. J. Rey; A. T. Murray; L. Anselin
  5. Measuring industrial agglomeration with inhomogeneous K-function: the case of ICT firms in Milan (Italy) By Giuseppe Espa; Giuseppe Arbia; Diego Giuliani
  6. The Importance of Broadband Provision to Knowledge Intensive Firm Location By E. A. Mack; L. Anselin
  7. The Influence of Role Models on Immigrant Self-Employment: A Spatial Analysis for Switzerland By Giuliano Guerra; Roberto Patuelli
  8. Subsidy Policy for Innovation: A way to reach objectives of both higher growth and equity? By Benjamin Montmartin
  9. The Dynamics of Labour Productivity across Italian Provinces: Convergence and Polarization By Davide Fiaschi; Lisa Gianmoena; Angela Parenti
  10. Measuring Spatial Dynamics in Metropolitan Areas By S. J. Rey; L. Anselin; D. C. Folch; M. L. Sastre-Gutierrez
  11. An Ensemble Approach to Space-Time Interpolation By E. A. Wentz; D. J. Peuquet
  12. Financial system, innovation and regional development: a study on the relationship between liquidity preference and innovation in Brazil By João Prates Romero; Frederico G. Jayme Jr
  13. The Spanish technnical change: A regional and a dynamic analysis (1994-2007) By Ana Karina Alfaro; José Javier Núñez Velázquez
  14. Regional Sources of Growth Acceleration in India By Ravindra H. Dholakia

  1. By: Davide Burgalassi
    Abstract: Polycentric development in regions has many dimensions, which involve several definitions and measures. This paper tackles the problem of defining and measuring polycentricity under an integrated and multi- dimensional perspective. Firstly, the policy relevance of polycentricity is analysed. Then, the paper identifes the definitions and measures of polycentricity by surveying the literature. It also provides a taxonomy among two main aspects involved in the definition of polycentricity: the morphological dimension and the functional dimension. Based on this background, an empirical analysis is carried out, by using data about population and commuting flows in the Tuscany Region (Italy). The results show that Tuscany can be viewed as a polycentric spatial structure, both considering rank-size distribution of cities and spatial interaction.
    Keywords: Polycentric Development, Spatial Structure, Rank-size Estimations, Spatial Interaction, Tuscany.
    JEL: O18 R11 R12
    Date: 2010–01–18
    URL: http://d.repec.org/n?u=RePEc:pie:dsedps:2010/101&r=geo
  2. By: S. J. Rey
    Abstract: While an enormous and growing literature exists on the topic of regional income convergence, other aspects of socioeconomic well-being and development have attracted much less attention. Social indicators are a valuable complement to economic indicators when analyzing spatial patterns in a given geographic region, and can often yield a more comprehensive view about regional socioeconomic behavior. In poorer nations dominated by many low income areas that exhibit similar economic performance, social indicators may reveal further insight into the differences among regions. This paper explores the issue of educational convergence in Peru over the period 1993 to 2005. Using both exploratory spatial data analysis and spatial econometrics, the study is conducted at province level in order to uncover potential spatial patterns that help explain variation in educational performance over time, among regions, and across different terrain.
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:asg:wpaper:4&r=geo
  3. By: Wolfgang Polasek (Institute for Advanced Studies, Vienna, Austria; University of Porto, Porto, Portugal; The Rimini Centre for Economic Analysis (RCEA)); Richard Sellner (Institute for Advanced Studies, Vienna, Austria); Carlos Llano (Universidad Autónoma de Madrid, Facultad de Ciencias Económicas y Empresariales, Departamento de Análisis Económico, Madrid, Spain)
    Abstract: Missing data in dynamic panel models occur quite often since detailed recording of the dependent variable is often not possible at all observation points in time and space. In this paper we develop classical and Bayesian methods to complete missing data in panel models. The Chow-Lin (1971) method is a classical method for completing dependent disaggregated data and is successfully applied in economics to disaggregate aggregated time series. We will extend the space-time panel model in a new way to include cross-sectional and spatially correlated data. The missing disaggregated data will be obtained either by point prediction or by a numerical (posterior) predictive density. Furthermore, we point out that the approach can be extended to more complex models, like ow data or systems of panel data. The panel Chow-Lin approach will be demonstrated with examples involving regional growth for Spanish regions.
    Keywords: Space-time interpolation, Spatial panel econometrics, MCMC, Spatial Chow-Lin, missing regional data, Spanish provinces, MCMC, NUTS: nomenclature of territorial units for statistics
    JEL: C11 C15 C52 E17 R12
    Date: 2010–01
    URL: http://d.repec.org/n?u=RePEc:rim:rimwps:47_10&r=geo
  4. By: S. J. Rey; A. T. Murray; L. Anselin
    Abstract: This paper introduces a new approach to the analysis of regional income distribution dynamics. Drawing on recent advances in geovisualiza- tion, we suggest a spatially explicit view of income mobility. Based on the integration of a dynamic local indicator of spatial association (LISA) together with directional statistics, this framework provides new insights on the role of spatial dependence in regional income growth and change. These new ap- proaches are illustrated in a case study of state level incomes in the U.S. over the 1969-2008 period.
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:asg:wpaper:3&r=geo
  5. By: Giuseppe Espa; Giuseppe Arbia; Diego Giuliani
    Abstract: Why do industrial clusters occur in space? Is it because industries need to stay close together to interact or, conversely, because they concentrate in certain portions of space to exploit favourable conditions like public incentives, proximity to communication networks, to big population concentrations or to reduce transport costs? This is a fundamental question and the attempt to answer to it using empirical data is a challenging statistical task. In economic geography scientists refer to this dichotomy using the two categories of spatial interaction and spatial reaction to common factors. In economics we can refer to a distinction between exogenous causes and endogenous effects. In spatial econometrics and statistics we use the terms of spatial dependence and spatial heterogeneity. A series of recent papers introduced explorative methods to analyses the spatial patterns of firms using micro data and characterizing each firm by its spatial coordinates. In such a setting a spatial distribution of firms is seen as a point pattern and an industrial cluster as the phenomenon of extra-concentration of one industry with respect to the concentration of a benchmarking spatial distribution. Often the benchmarking distribution is that of the whole economy on the ground that exogenous factors affect in the same way all branches. Using such an approach a positive (or negative) spatial dependence between firms is detected when the pattern of a specific sector is more aggregated (or more dispersed) than the one of the whole economy. In this paper we suggest a parametric approach to the analysis of spatial heterogeneity, based on the socalled inhomogeneous K-function (Baddeley et al., 2000). We present an empirical application of the method to the spatial distribution of high-tech industries in Milan (Italy) in 2001. We consider the economic space to be non homogenous, we estimate the pattern of inhomogeneity and we use it to separate spatial heterogeneity from spatial dependence.
    JEL: C15 C21 C59 R12
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:trn:utwpde:1014&r=geo
  6. By: E. A. Mack; L. Anselin
    Abstract: Despite the volume of literature afforded knowledge work and innovations in information and communications technologies (ICTs), few studies have examined the importance of ICTs to firms in knowledge industries. This study will develop spatial econometric models to examine the relative importance of the level of broadband provision to knowledge intensive firms in select U.S.  metropolitan statistical areas (MSAs). Results demonstrate the need for both a spatial econometric and a metropolitan area specific evaluation of this relationship. They also suggest potential spillover effects to knowledge intensive firm location, which may explain why some regional economies are relatively more successful at stimulating firm growth in this increasingly important sector of the U.S economy.
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:asg:wpaper:9&r=geo
  7. By: Giuliano Guerra (Institute for Economic Research (IRE), University of Lugano, Switzerland); Roberto Patuelli (Institute for Economic Research (IRE), University of Lugano, Switzerland; The Rimini Centre for Economic Analysis, Italy)
    Abstract: Theoretical and empirical research suggests a connection between the presence of role models and the emergence of entrepreneurs. Existing entrepreneurs may act as role models for self-employment candidates by providing successful examples. By explicitly considering the self-employment rates of the natives, which may influence locally the decisions of immigrants towards entrepreneurship, we develop a simple model that explains immigrant self-employment rates for a sample of 2,490 Swiss municipalities. In addition, we accommodate for the presence of spatial spillovers in the distribution of rates, and test a spatial autoregressive model which takes into account the average self-employment rates of immigrants living in nearby municipalities. Our evidence shows a significant (positive) effect of such spatial network effects, which are characterized by a quick distance decay, suggesting spatial spillovers at the household and social network level. Additionally, we show that local conditions and immigrant pool characteristics differ, with respect to self-employment choices, when examining separately urban and rural contexts.
    Keywords: immigrants, self-employment, role models, Switzerland, spatial lag
    JEL: C21 J24 J61 O15 R23
    Date: 2010–11
    URL: http://d.repec.org/n?u=RePEc:lug:wpaper:1010&r=geo
  8. By: Benjamin Montmartin (GATE Lyon Saint-Etienne - Groupe d'analyse et de théorie économique - CNRS : UMR5824 - Université Lumière - Lyon II - Ecole Normale Supérieure Lettres et Sciences Humaines)
    Abstract: Since the Lisbon Agenda (2000), the European Union policies are in- creasingly oriented towards innovation as attested to by the deep change of the new Regional Policy. This paper proposes an analysis of an innovation subsidy policy in an agglomeration and growth model à la Martin and Ottaviano (1999). In this two-regions model, we assume that the policy is implemented by a central authority that taxes the profit of industrial firms to subsidy employment in innovative activities. We show that the positive effects on growth and equity of such a policy, as highlighted by Martin (1999), hold in the case where the policy is not geographically differentiated. In the case where the government however grants larger subsidies to the poorer region in order to reduce the concentration of the innovative sector, we show that the policy can be inefficient if it is not of sufficient magnitude.
    Keywords: economic geography; endogenous growth; public policy; subsidies; Regional Policy
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:hal:journl:halshs-00537867_v1&r=geo
  9. By: Davide Fiaschi; Lisa Gianmoena; Angela Parenti
    Abstract: This paper analyses the dynamics of labour productivity across Italian Provinces in the period 1995-2006. Inequality decreased but a clear pattern of polarization emerged, with the formation of a cluster of high-productive provinces in the North and Center-West of Italy and a cluster of low-productive provinces in the South and in the Center-East. A core of provinces belonging to ?ve regions (Lombardy, Veneto, Emilia-Romagna, Tuscany and Lazio) appears to bene?t of a higher growth of productivity. This regional component favoured both inequality and polarization, while the initial level of productivity decreased inequality but increased polarization.
    Keywords: distribution dynamics, spatial dependence, output composition, entrepreneurial fabric, human capital.
    JEL: C21 R11 O47 O52
    Date: 2010–10–10
    URL: http://d.repec.org/n?u=RePEc:pie:dsedps:2010/105&r=geo
  10. By: S. J. Rey; L. Anselin; D. C. Folch; M. L. Sastre-Gutierrez
    Abstract: This paper introduces a new approach to measuring neighborhood change. Instead of the traditional method of identifying “neighborhoods†a priori and then studying how resident attributes change over time, our approach looks at the neighborhood more intrinsically as a unit that has both a geographic footprint and a socioeconomic composition. Therefore, change is identified when both as- pects of a neighborhood transform from one period to the next. Our approach is based on a spatial clustering algorithm that identifies neighborhoods at two points in time for one city. We also develop indicators of spatial change at both the macro (city) level as well as local (neighborhood) scale. We illustrate these methods in an application to an extensive database of time-consistent census tracts for 359 of the largest metropolitan areas in the US for the period 1990-2000.
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:asg:wpaper:5&r=geo
  11. By: E. A. Wentz; D. J. Peuquet
    Abstract: There has been much excitement and activity in recent years related to the relatively sudden availability of earth-related data and the computational capabilities to visualize and analyze these data. Despite the increased ability to collect and store large volumes of data, few individual data sets exist that provide both the requisite spatial and temporal observational frequency for many urban and/or regional-scale applications. The motivating view of this paper, however, is that the relative temporal richness of one data set can be leveraged with the relative spatial richness of another to fill in the gaps. We also note that any single interpolation technique has advantages and disadvantages. Particularly when focusing on the spatial or on the temporal dimension, this means that different techniques are more appropriate than others for specific types of data. We therefore propose a space- time interpolation approach whereby two interpolation methods – one for the temporal and one for the spatial dimension – are used in tandem in order to maximize the quality of the result. We call our ensemble approach the Space-Time Interpolation Environment (STIE). The primary steps within this environment include a spatial interpolator, a time-step processor, and a calibration step that enforces phenomenon-related behavioral constraints. The specific interpolation techniques used within the STIE can be chosen on the basis of suitability for the data and application at hand. In the current paper, we describe STIE conceptually including the structure of the data inputs and output, details of the primary steps (the STIE processors), and the mechanism for coordinating the data and the 1 processors. We then describe a case study focusing on urban land cover in Phoenix Arizona. Our empirical results show that STIE was effective as a space-time interpolator for urban land cover with an accuracy of 85.2% and furthermore that it was more effective than a single technique.
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:asg:wpaper:7&r=geo
  12. By: João Prates Romero (Cedeplar-UFMG); Frederico G. Jayme Jr (Cedeplar-UFMG)
    Abstract: This paper discusses and assesses the features of the Brazilian Financial System, as well as the impacts of Liquidity Preference on Regional Development in Brazil. In the post-Keynesian literature, money is considered endogenous to the economic system, introduced in the economic activity through the credit provided by banks. Taken as non-neutral, banks are economic agents which can present lower or higher liquidity preference. Because of that, banks are also particularly important to the development process. Precisely, we tested the influence of credit and the role of banks in regional development. We estimate a panel across states in Brazil in order to test the impact of liquidity preference and other financial variables on Brazilian states’ number of patents, aiming at testing the importance of the bank system to technological progress and regional development. Conclusions confirm both hypotheses.
    Keywords: Monetary System, National Innovation System, Credit, Brazil
    JEL: R10 G21 O30
    Date: 2010–11
    URL: http://d.repec.org/n?u=RePEc:cdp:texdis:td412&r=geo
  13. By: Ana Karina Alfaro (Departamento de Estadística, Estructura y O.E.I. Universidad de Alcalá.); José Javier Núñez Velázquez (Departamento de Estadística, Estructura y O.E.I. Universidad de Alcalá.)
    Abstract: Studying wage dispersion, many researchers have found that the skill premium (the ratio of skilled workers’ wages to unskilled ones) has increased after 1979 in many developed countries, when there was a very sharp increase in the supply of skilled workers. The recent consensus is that technical change favours skilled workers, replacing tasks previously performed by the unskilled and exacerbating inequality. In the Spanish case, Nuñez and Alfaro (2009) have found evidences of a decline in the wage premium during the nineties. So, in this paper, we distinguish between skilled and unskilled workers differentiating the efficiency units of both types of workers. Moreover, we calculate the Spanish technology frontier and the technology differences between the Spanish Regions in 2006 and we analyze the evolution of the Spanish technology frontier over 1994-2007, testing the kind of technical change. In addition, a coherent Spanish wage micro-data base is achieved, using data from Eurostat: ECHP and EU-SILC.
    Keywords: Technological frontiers, technological differences, technical change, skills
    JEL: J24 O14 O33
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:alc:alcamo:1002&r=geo
  14. By: Ravindra H. Dholakia
    Abstract: Gujarat, West Bengal, Karnataka, Maharashtra, Kerala and Tamil Nadu were the major contributors to the growth acceleration in India after 1991-92. Although the Regional Disparity may increase temporarily, causality test provides support to the hypothesis about spread effects. The Regional growth targets assigned by the 11th Plan in India seem to rely on the spread effects of economic growth acceleration in the better off states to achieve its 9 percent growth target and reduce regional disparity in the long run. To strengthen spread effects, the domestic economy should be further integrated and interlinked with free flow of goods, services and factors of production. [W.P. No. 2009-03-06]
    Keywords: Gujarat, West Bengal, Karnataka, Maharashtra, Kerala, Tamil Nadu
    Date: 2010
    URL: http://d.repec.org/n?u=RePEc:ess:wpaper:id:3220&r=geo

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