nep-geo New Economics Papers
on Economic Geography
Issue of 2011‒12‒19
nine papers chosen by
Vassilis Monastiriotis
London School of Economics

  1. Feeding the Cities and GHG Emissions: Beyond the Food Miles Approach By Stéphane De Cara; Anne Fournier; Carl Gaigné
  2. Metody identyfikacji efektow zewnetrznych funkcjonowania klastrów przemyslowych By Dorota Ciolek
  3. Estimating Verdoorn law for Italian firms and regions By Fazio, Giorgio; Maltese, Enza; Piacentino, Davide
  4. GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors By Cizek, P.; Jacobs, J.P.A.M.; Ligthart, J.E.; Vrijburg, H.
  5. "The regional distribution of unemployment. What do micro-data tell us?" By Enrique López-Bazo; Elisabet Motellón
  6. How Local Are Labour Markets? Evidence from a Spatial Job Search Model By Alan Manning; Barbara Petrongolo
  7. Convergence among Italian Regions, 1861-2011 By Giovanni Iuzzolino; Guido Pellegrini; Gianfranco Viesti
  8. A Comparative Perspective on Italy’s Human Capital Accumulation By Giuseppe Bertola; Paolo Sestito
  9. The development potential of clusters in Romania By Prejmerean (Dan), Mihaela Cornelia

  1. By: Stéphane De Cara (UMR 210 Economie Publique, INRA-AgroParisTech.); Anne Fournier (UMR 7235 EconomiX-CNRS, University of Paris Ouest); Carl Gaigné (UMR 1302 SMART, INRA)
    Abstract: In this paper, we study the impact of urbanization on the location of agricultural production and the GHG emissions related to transportation. We develop an economic geography model where the location of agricultural activities and urban population are endogenous. We show that increasing yields induce the spatial concentration of agricultural production in the most urban-crowded region if collection costs are relatively low and in the smallest one otherwise. In addition, we find that inter-regional trade in agricultural commodities may be desirable to reduce GHG emissions, except when urban population is equally split between cities. Finally, we highlight that the market may induce an excess of agricultural agglomeration when yields are high and/or collection costs are low.
    Keywords: Urbanization, Agricultural location, Transport, Greenhouse gas, Food miles
    JEL: F12 Q10 Q54 Q56 R12
    Date: 2011–08
  2. By: Dorota Ciolek (Faculty of Management, University of Gdansk)
    Abstract: Methods of identification of external effects of functioning of industrial clusters. The aim of the paper is to present methods used to identify the external effects of the industrial clusters. One of them is to evaluate a regional growth regression with a cluster index as one of the explanatory variables. Such regression should also implement a concept of a spatial character of regional growth what means that condition of the region depends also on the situation of the neighborhood. The second suggestion for testing the effects of clusters is to verify an agglomeration effects in total economy.
    Keywords: klaster przemys³owy, efekty zewnêtrzne, metody iloœciowe
    JEL: C23 L16 L23
    Date: 2011–11
  3. By: Fazio, Giorgio; Maltese, Enza; Piacentino, Davide
    Abstract: In empirical regional economics, returns to scale are typically estimated at the regional level in search for evidence on alternative theories of growth and agglomeration. However, returns to scale may also have a firm-level dimension. In this paper, we exploit micro level data and estimate the dynamic Verdoorn law in a multilevel-setting, where returns to scale are obtained simultaneously for the micro and the regional level. Using Italian firm-level data and the NUTS-3 level of aggregation, we estimate the classic and augmented versions of Verdoorn law for all sectors and separately for manufacturing. Our results show that increasing returns to scale co-exist at both levels, with some degree of regional heterogeneity across the Italian peninsula.
    Keywords: Returns to scale; Verdoorn Law; Multilevel models; Italian firms
    JEL: O47 C31 R12 R11
    Date: 2011–12
  4. By: Cizek, P.; Jacobs, J.P.A.M.; Ligthart, J.E.; Vrijburg, H. (Tilburg University, Center for Economic Research)
    Abstract: We extend the three-step generalized methods of moments (GMM) approach of Kapoor et al. (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory variables. Combining the extended Kapoor et al. (2007) approach with the dynamic panel data model GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) and specifying moment conditions for various time lags, spatial lags, and sets of exogenous variables yields new spatial dynamic panel data estimators. We prove their consistency and asymptotic normality for a large number of spatial units N and a xed small number of time periods T. Monte Carlo simulations demonstrate that the root mean squared error of spatially corrected GMM estimates|which are based on a spatial lag and spatial error correction|is generally smaller than that of corresponding spatial GMM estimates in which spatial error correlation is ignored. We show that the spatial Blundell-Bond estimators outperform the spatial Arellano-Bond estimators.
    Keywords: Dynamic panel models;spatial lag;spatial error;GMM estimation.
    JEL: C15 C21 C22 C23
    Date: 2011
  5. By: Enrique López-Bazo (Faculty of Economics, University of Barcelona); Elisabet Motellón (Faculty of Economics, University of Barcelona)
    Abstract: Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual’s education are shown to play a major role.
    Keywords: Regional labour markets, Regional unemployment, Education, Gap decomposition for non-linear models. JEL classification:C25, J64, J70, R23
    Date: 2011–12
  6. By: Alan Manning; Barbara Petrongolo
    Abstract: This paper uses data on very small UK geographies to investigate the effective size of local labour markets. Our approach treats geographic space as continuous, as opposed to a collection of nonoverlapping administrative units, thus avoiding problems of mismeasurement of local labour markets encountered in previous work. We develop a theory of job search across space that allows us to estimate a matching process with a very large number of areas. Estimates of this model show that the cost of distance is relatively high - the utility of being offered a job decays at exponential rate around 0.3 with distance (in km) to the job - so that labour markets are indeed quite 'local'. Also, workers are discouraged from applying to jobs in areas where they expect relatively strong competition from other jobseekers. The estimated model replicates fairly accurately actual commuting patterns across neighbourhoods, although it tends to underpredict the proportion of individuals who live and work in the same ward. Finally, we find that, despite the fact that labour markets are relatively 'local', local development policies are fairly ineffective in raising the local unemployment outflow, because labour markets overlap, and the associated ripple effects in applications largely dilute the impact of local stimulus across space.
    Keywords: Job search, local labour markets, location-based policies, ripple effects
    JEL: J61 J63 J64 R12
    Date: 2011–12
  7. By: Giovanni Iuzzolino (Bank of Italy, Naples Branch); Guido Pellegrini (Università degli Studi di Roma "La Sapienza"); Gianfranco Viesti (Università degli Studi di Bari "Aldo Moro")
    Abstract: In 150 years, the trends in regional disparities in economic development within Italy have differed depending on whether they are gauged by longitude or by latitude. The disparities between western and eastern regions first widened and then closed; the North-South gap, by contrast, remains the main open problem in the national history of Italy. This work focuses on the underlying causes of the turning points in regional disparities since national unification in 1861. The first came in the late nineteenth and early twentieth century, with the industrialization of the so-called “industrial triangle”. This was followed by the “failed new turn” during the interwar years: not only were the beginnings of convergence blocked but the North-South gap, until then still natural, inevitable, was transformed into a fracture of exceptional dimensions. The second turning point, in the twenty years after the World War, produced the first substantial, lasting convergence between southern and northern Italy, powered by rising productivity and structural change in the South. The last turning point was in the mid-1970s, when convergence was abruptly halted and a protracted period of immobility in the disparity began.
    Keywords: Italy, regional disparities
    JEL: N63 N93 R11 R12
    Date: 2011–10
  8. By: Giuseppe Bertola (Edhec Business School and CEPR); Paolo Sestito (Bank of Italy)
    Abstract: This paper reviews the evolution of educational institutions and outcomes over the 150 years since Italy’s unification, and discusses their interaction with national and regional growth patterns. While initial educational conditions contributed to differentiate across regions the early industrial take off in the late 19th century, and formal education does not appear to have played a major role in the postwar economic boom, the slowdown of Italy’s economy since the 1990s may be partly due to interactions between its traditionally low human capital intensity and new comparative advantage patterns, and to the deterioration since the 1970s of the educational system’s organization.
    Keywords: Education systems, tracking, economic growth, regional convergence
    JEL: N30
    Date: 2011–10
  9. By: Prejmerean (Dan), Mihaela Cornelia
    Abstract: Nations and regions find themselves in a constant competition for attracting direct foreign investments, the most important producers, specialized work force, the best researchers etc. From this point of view the former communist countries could be in an unfavorably situation because they just recently managed to adopt the system of the market economy. Clusters are seen as a solution for the economical success in the global competition. The western European countries have in this way a one century tradition, and continue to sustain and finance programs for the development and expansion of clusters. Taking in account the western experience, the question arises if also in the former communist countries clusters can give the key for development and rapid fulfillment of objectives regarding cohesion, regional development, competitiveness at international and global level. The paper investigates the potential of forming clusters in Romania and gives an orientation in the decisional process for founding, localization, development of clusters.
    Keywords: cluster; Romania; competitive advantage; SWOT analysis
    JEL: R10 R11
    Date: 2011–07–30

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