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Neighborhood and Efficiency in Manufacturing in Brazilian Regions: a Spatial Markov Chain Analysis

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  • Daniela Schettini
  • Carlos Roberto Azzoni
  • Antonio Páez

Abstract

More competitive regions tend to present higher level of economic growth, with positive reflexes on social aspects. The different economic performances observed among regions are explained mainly by the spatial concentration of the economic activities. This paper aims to analyze the influence of space on the regional competitiveness behavior of the Brazilian manufacturing industry. In doing so, it uses a panel data of 137 mesoregions and industry sectors that are aggregated in four categories according to technology intensity, during 2000 to 2006. We apply the stochastic frontier of production methodology to obtain the measures of regional efficiency and the Markov spatial transition matrixes that analyze the dynamic of the transition of the regions among efficiency categories considering their local spatial context. We found evidences that there is a higher probability of the regions to become less competitive when the neighborhood is not considered. On the other hand, when considering spatial influences, we observed that the probability of a good neighborhood (more competitive) in stimulating the region's efficiency is higher than the probability of a bad neighborhood (less competitive) in lowering its efficiency. In other words, the pull effect of the neighborhood in the competitiveness of the Brazilian regions is stronger than the drag effect.

Suggested Citation

  • Daniela Schettini & Carlos Roberto Azzoni & Antonio Páez, 2011. "Neighborhood and Efficiency in Manufacturing in Brazilian Regions: a Spatial Markov Chain Analysis," ERSA conference papers ersa10p1052, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa10p1052
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    Cited by:

    1. Massimiliano Agovino & Alessandro Crociata & Pier Sacco, 2016. "Location matters for pro-environmental behavior: a spatial Markov Chains approach to proximity effects in differentiated waste collection," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 295-315, January.
    2. M. Agovino, 2014. "Do “good neighbors” enhance regional performances in including disabled people in the labor market? A spatial Markov chain approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 93-121, August.
    3. Massimiliano Agovino & Massimiliano Cerciello & Aniello Ferraro & Antonio Garofalo, 2022. "A Regional Perspective on Social Exclusion in European Regions: Context, Trends and Policy Implications," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 8(2), pages 409-433, July.
    4. Haddad, Eduardo & Mena-Chalco, Jesús & Sidone, Otávio, 2015. "Scholarly Collaboration in Regional Science in Developing Countries: The Case of the Brazilian REAL Network," TD NEREUS 4-2015, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
    5. Sergio J. Rey & Wei Kang & Levi Wolf, 2016. "The properties of tests for spatial effects in discrete Markov chain models of regional income distribution dynamics," Journal of Geographical Systems, Springer, vol. 18(4), pages 377-398, October.
    6. Sergio Rey, 2014. "Rank-based Markov chains for regional income distribution dynamics," Journal of Geographical Systems, Springer, vol. 16(2), pages 115-137, April.
    7. Agovino, Massimiliano & Crociata, Alessandro & Sacco, Pier Luigi, 2019. "Proximity effects in obesity rates in the US: A Spatial Markov Chains approach," Social Science & Medicine, Elsevier, vol. 220(C), pages 301-311.
    8. Eduardo A. Haddad & Jesús P. Mena-Chalco & Otávio J. G. Sidone, 2017. "Scholarly Collaboration in Regional Science in Developing Countries," International Regional Science Review, , vol. 40(5), pages 500-529, September.
    9. Massimiliano Agovino, 2014. "Is there convergence in the performance of Italian regions in including disabled people in the labour market? A local Moran approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 6(1), pages 103-120, March.

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