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Industrial Location and Space: New Insights


  • Liviano Solís, Daniel
  • Arauzo Carod, Josep Maria


This paper tries to resolve some of the main shortcomings in the empirical literature of location decisions for new plants, i.e. spatial effects and overdispersion. Spatial effects are omnipresent, being a source of overdispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm’s location decisions. Using Count Data models, empirical researchers have dealt with overdispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further, by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial overdispersion and spatial dependence simultaneously. Data for Catalonia is used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, overdispersion is descomposed into an unstructured iid effect and a spatially structured effect. Keywords: Bayesian Analysis, Spatial Models, Firm Location. JEL Classification: C11, C21, R30.

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  • Liviano Solís, Daniel & Arauzo Carod, Josep Maria, 2011. "Industrial Location and Space: New Insights," Working Papers 2072/152137, Universitat Rovira i Virgili, Department of Economics.
  • Handle: RePEc:urv:wpaper:2072/152137

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    References listed on IDEAS

    1. Josep Arauzo Carod & Daniel Liviano Solís & Mònica Martín Bofarull, 2008. "New business formation and employment growth: some evidence for the Spanish manufacturing industry," Small Business Economics, Springer, vol. 30(1), pages 73-84, January.
    2. Lambert, Dayton M. & McNamara, Kevin T. & Garrett, Megan I., 2006. "An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(01), April.
    3. Josep-Maria Arauzo-Carod & Daniel Liviano-Solis & Miguel Manjón-Antolín, 2010. "Empirical Studies In Industrial Location: An Assessment Of Their Methods And Results," Journal of Regional Science, Wiley Blackwell, vol. 50(3), pages 685-711.
    4. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392.
    5. Josep Maria Arauzo Carod & Miguel C. ManjÛn AntolÌn, 2004. "Firm Size and Geographical Aggregation: An Empirical Appraisal in Industrial Location," Small Business Economics, Springer, vol. 22(3_4), pages 299-312, April.
    6. Josep-Maria Arauzo-Carod & Elisabet Viladecans-Marsal, 2009. "Industrial Location at the Intra-Metropolitan Level: The Role of Agglomeration Economies," Regional Studies, Taylor & Francis Journals, vol. 43(4), pages 545-558.
    7. Todd Gabe, 2003. "Local Industry Agglomeration and New Business Activity," Growth and Change, Wiley Blackwell, vol. 34(1), pages 17-39.
    8. Josep-Maria Arauzo-Carod & Miguel Manjón-Antolín, 2012. "(Optimal) spatial aggregation in the determinants of industrial location," Small Business Economics, Springer, vol. 39(3), pages 645-658, October.
    9. Natalia Barbosa & Paulo Guimaraes & Douglas Woodward, 2004. "Foreign firm entry in an open economy: the case of Portugal," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 465-472.
    10. Smith Jr. , Donald F. & Florida Richard, 1994. "Agglomeration and Industrial Location: An Econometric Analysis of Japanese-Affiliated Manufacturing Establishments in Automotive-Related Industries," Journal of Urban Economics, Elsevier, vol. 36(1), pages 23-41, July.
    11. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
    12. Roberto, Basile, 2004. "Acquisition versus greenfield investment: the location of foreign manufacturers in Italy," Regional Science and Urban Economics, Elsevier, vol. 34(1), pages 3-25, January.
    13. C. Autant-Bernard & V. Mangematin & N. Massard, 2006. "Creation of Biotech SMEs in France," Small Business Economics, Springer, vol. 26(2), pages 173-187, March.
    14. Craig Brett & Joris Pinkse, 1997. "Those Taxes are all over the Map! A Test for Spatial Independence of Municipal Tax Rates in British Columbia," International Regional Science Review, , vol. 20(1-2), pages 131-151, April.
    15. Susanne Gschlößl & Claudia Czado, 2008. "Modelling count data with overdispersion and spatial effects," Statistical Papers, Springer, vol. 49(3), pages 531-552, July.
    16. repec:eee:ecomod:v:202:y:2007:i:3:p:225-242 is not listed on IDEAS
    17. Philip Mccann & Stephen Sheppard, 2003. "The Rise, Fall and Rise Again of Industrial Location Theory," Regional Studies, Taylor & Francis Journals, vol. 37(6-7), pages 649-663.
    18. Blonigen, Bruce A. & Davies, Ronald B. & Waddell, Glen R. & Naughton, Helen T., 2007. "FDI in space: Spatial autoregressive relationships in foreign direct investment," European Economic Review, Elsevier, vol. 51(5), pages 1303-1325, July.
    19. Josep Maria Arauzo Carod, 2005. "Determinants of industrial location: An application for Catalan municipalities," Papers in Regional Science, Wiley Blackwell, vol. 84(1), pages 105-120, March.
    20. List, John A., 2001. "US county-level determinants of inbound FDI: evidence from a two-step modified count data model," International Journal of Industrial Organization, Elsevier, vol. 19(6), pages 953-973, May.
    21. Todd M. Gabe & Kathleen P. Bell, 2004. "Tradeoffs between Local Taxes and Government Spending as Determinants of Business Location," Journal of Regional Science, Wiley Blackwell, vol. 44(1), pages 21-41.
    22. Roberto Basile & Luigi Benfratello & Davide Castellani, 2010. "Location Determinants of Greenfield Foreign Investments in the Enlarged Europe: Evidence from a Spatial Autoregressive Negative Binomial Additive Model," Working papers 10, Former Department of Economics and Public Finance "G. Prato", University of Torino.
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    Cited by:

    1. Buczkowska, Sabina & de Lapparent, Matthieu, 2014. "Location choices of newly created establishments: Spatial patterns at the aggregate level," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 68-81.

    More about this item


    Localització industrial; Anàlisi espacial (Estadística); Estadística bayesiana; 332 - Economia regional i territorial. Economia del sòl i de la vivenda;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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