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Identification of Regional Clusters in Mexican Manufacturing Industry

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Listed:
  • Chávez Juan Carlos
  • Katia García Loredo

Abstract

This research presents a methodology to identify regional clusters based on the estimation of location's coefficients and measures of spatial autocorrelation. Local Moran I index is used as a measure of spatial autocorrelation, which allows to obtain a more varied typology of regional clusters. The methodology was applied to both the Mexican manufacturing industry as a whole, and its partition in 14 industry groups for 1993 and 2008. The results indicate the existence of heterogeneity in regional patterns of agglomeration of manufacturing activity at the aggregate level and at group level. It is shown that the process of relocation of manufacturing industry that occurred after the entry into force of the North American Free Trade Agreement (NAFTA) differentially affected the patterns of agglomeration of activity in different regions of the country.

Suggested Citation

  • Chávez Juan Carlos & Katia García Loredo, 2015. "Identification of Regional Clusters in Mexican Manufacturing Industry," Working Papers 2015-19, Banco de México.
    • Handle: RePEc:bdm:wpaper:2015-19
    as

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    References listed on IDEAS

    as
    1. Michael Carroll & Neil Reid & Bruce Smith, 2008. "Location quotients versus spatial autocorrelation in identifying potential cluster regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(2), pages 449-463, June.
    2. Krugman, Paul & Elizondo, Raul Livas, 1996. "Trade policy and the Third World metropolis," Journal of Development Economics, Elsevier, vol. 49(1), pages 137-150, April.
    3. Michael Porter, 2003. "The Economic Performance of Regions," Regional Studies, Taylor & Francis Journals, vol. 37(6-7), pages 549-578.
    4. Ellison, Glenn & Glaeser, Edward L, 1997. "Geographic Concentration in U.S. Manufacturing Industries: A Dartboard Approach," Journal of Political Economy, University of Chicago Press, vol. 105(5), pages 889-927, October.
    5. Edward Feser & Edward Bergman, 2000. "National Industry Cluster Templates: A Framework for Applied Regional Cluster Analysis," Regional Studies, Taylor & Francis Journals, vol. 34(1), pages 1-19.
    6. repec:bla:jecsur:v:13:y:1999:i:4:p:355-79 is not listed on IDEAS
    7. Brian Roberts & Robert J. Stimson, 1998. "original: Multi-sectoral qualitative analysis: a tool for assessing the competitiveness of regions and formulating strategies for economic development," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 32(4), pages 469-494.
    8. Hanson, Gordon H, 1997. "Increasing Returns, Trade and the Regional Structure of Wages," Economic Journal, Royal Economic Society, vol. 107(440), pages 113-133, January.
    9. Frank A. Cowell & Fatemeh Mehta, 1982. "The Estimation and Interpolation of Inequality Measures," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(2), pages 273-290.
    10. Edward Feser & Stuart Sweeney & Henry Renski, 2005. "A Descriptive Analysis of Discrete U.S. Industrial Complexes," Journal of Regional Science, Wiley Blackwell, vol. 45(2), pages 395-419, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Spatial autocorrelation; Location coefficient; Regional clusters; Manufacturing;
    All these keywords.

    JEL classification:

    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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