IDEAS home Printed from https://ideas.repec.org/a/eee/regeco/v48y2014icp68-81.html
   My bibliography  Save this article

Location choices of newly created establishments: Spatial patterns at the aggregate level

Author

Listed:
  • Buczkowska, Sabina
  • de Lapparent, Matthieu

Abstract

This paper explores the problems associated with the location choice of newly created establishments at the aggregate level. Much work has been done in this domain, however, several issues arise when analyzing involved phenomena, which scholars have yet to fully explore: 1) addressing the excess of zeros problem in the location choice model in highly heterogeneous geographic areas and 2) determining an appropriate way to accommodate spatial effects for location decisions. We tested models that include both stocks of pre-existing establishments and variables that represent measures of accessibility to the workforce and population, proximity to shops, services, transport infrastructure, availability of land, as well as prices and tax levels. We concluded that an establishment does not act in isolation during its decision-making processes and that it is likely to be influenced by other establishments located nearby. When selecting the appropriate location in which to set up in the market, an establishment may consider not only the characteristics of a particular area, but also the characteristics of neighboring zones. Having estimated 84 nested and non-nested count data models, we found that the hurdle models are preferred for taking into account the presence of excess zeros. Hurdle models offer greater flexibility in modeling zero outcomes and relax the assumption that the zero observations and the positive observations come from the same data generating process. In addition, the paper finds that the models tested with the distance matrix indicate that the incorporation of spatial spillovers leads to an enhancement in the models’ performance.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:regeco:v:48:y:2014:i:c:p:68-81
    DOI: 10.1016/j.regsciurbeco.2014.05.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0166046214000520
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Combes, Pierre-Philippe & Lafourcade, Miren & Thisse, Jacques-François & Toutain, Jean-Claude, 2011. "The rise and fall of spatial inequalities in France: A long-run perspective," Explorations in Economic History, Elsevier, vol. 48(2), pages 243-271, April.
    2. 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.
    3. Allen, W. Bruce & Liu, Dong & Singer, Scott, 1993. "Accesibility measures of U.S. metropolitan areas," Transportation Research Part B: Methodological, Elsevier, vol. 27(6), pages 439-449, December.
    4. Lambert, Dayton M. & Brown, Jason P. & Florax, Raymond J.G.M., 2010. "A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application," Regional Science and Urban Economics, Elsevier, vol. 40(4), pages 241-252, July.
    5. André de Palma, 2011. "The ‘Grand Paris' Project: Tools and Challenges," International Transport Forum Discussion Papers 2011/28, OECD Publishing.
    6. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
    7. Bondonio, Daniele & Greenbaum, Robert T., 2007. "Do local tax incentives affect economic growth? What mean impacts miss in the analysis of enterprise zone policies," Regional Science and Urban Economics, Elsevier, vol. 37(1), pages 121-136, January.
    8. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    9. Devereux, Michael P. & Griffith, Rachel & Simpson, Helen, 2007. "Firm location decisions, regional grants and agglomeration externalities," Journal of Public Economics, Elsevier, vol. 91(3-4), pages 413-435, April.
    10. Harald Strotmann, 2007. "Entrepreneurial Survival," Small Business Economics, Springer, vol. 28(1), pages 87-104, January.
    11. Neumark, David & Kolko, Jed, 2010. "Do enterprise zones create jobs? Evidence from California's enterprise zone program," Journal of Urban Economics, Elsevier, vol. 68(1), pages 1-19, July.
    12. 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.
    13. Hanna Maoh & Pavlos Kanaroglou, 2007. "Business establishment mobility behavior in urban areas: a microanalytical model for the City of Hamilton in Ontario, Canada," Journal of Geographical Systems, Springer, vol. 9(3), pages 229-252, September.
    14. Michiel de Bok, 2004. "Explaining the location decision of moving firms using their mobility profile and the accessibility of locations," ERSA conference papers ersa04p338, European Regional Science Association.
    15. Sutton, John, 2007. "Market Structure: Theory and Evidence," Handbook of Industrial Organization, Elsevier.
    16. Smirnov, Oleg A., 2010. "Modeling spatial discrete choice," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 292-298, September.
    17. Balz R. Bodenmann & Kay W. Axhausen, 2012. "Destination choice for relocating firms: A discrete choice model for the St. Gallen region, Switzerland," Papers in Regional Science, Wiley Blackwell, vol. 91(2), pages 319-341, June.
    18. Leo van Wissen, 2000. "A micro-simulation model of firms: Applications of concepts of the demography of the firm," Papers in Regional Science, Springer;Regional Science Association International, vol. 79(2), pages 111-134.
    19. Klier, Thomas & McMillen, Daniel P, 2008. "Clustering of Auto Supplier Plants in the United States," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 460-471.
    20. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
    21. Luc Anselin, 2003. "Spatial Externalities, Spatial Multipliers, And Spatial Econometrics," International Regional Science Review, , vol. 26(2), pages 153-166, April.
    22. repec:eee:jotrge:v:19:y:2011:i:2:p:294-303 is not listed on IDEAS
    23. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
    24. Garrido, Rodrigo A. & Mahmassani, Hani S., 2000. "Forecasting freight transportation demand with the space-time multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 403-418, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jean-François Richard, 2015. "Likelihood Evaluation of High-Dimensional Spatial Latent Gaussian Models with Non-Gaussian Response Variables," Working Paper 5778, Department of Economics, University of Pittsburgh.
    2. Sabina Buczkowska & Nicolas Coulombel & Matthieu de Lapparent, 2015. "Euclidean distance versus travel time in business location: A probabilistic mixture of hurdle-Poisson models," ERSA conference papers ersa15p1060, European Regional Science Association.
    3. Minghao Li & Stephan J. Goetz & Mark Partridge & David A. Fleming, 2016. "Location determinants of high-growth firms," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 28(1-2), pages 97-125, January.

    More about this item

    Keywords

    Location choice model; Count data models; Hurdle model; Spatial spillovers;

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:regeco:v:48:y:2014:i:c:p:68-81. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/regec .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.