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

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  • 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.

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  • 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
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    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. Youngsoo An & Li Wan, 2019. "Monitoring Spatial Changes in Manufacturing Firms in Seoul Metropolitan Area Using Firm Life Cycle and Locational Factors," Sustainability, MDPI, vol. 11(14), pages 1-22, July.
    3. 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.
    4. Ioannis Baraklianos & Louafi Bouzouina & Ouassim Manout & Patrick Bonnel, 2018. "To what extent do location choices of new and relocating economic establishments differ in terms of preference for accessibility?," Working Papers hal-01801448, HAL.
    5. 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.
    6. Ioannis BARAKLIANOS & Louafi BOUZOUINA & Patrick BONNEL, 2018. "The impact of accessibility on the location choices of the business services. Evidence from Lyon urban area," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 48, pages 85-104.
    7. Sabina Buczkowska & Nicolas Coulombel & Matthieu Lapparent, 2019. "A comparison of Euclidean Distance, Travel Times, and Network Distances in Location Choice Mixture Models," Networks and Spatial Economics, Springer, vol. 19(4), pages 1215-1248, December.
    8. Craig W. Carpenter & Anders Van Sandt & Rebekka Dudensing & Scott Loveridge, 2022. "Profit Pools and Determinants of Potential County-Level Manufacturing Growth," International Regional Science Review, , vol. 45(2), pages 188-224, March.
    9. Juan Lin & Han Li & Mingshui Lin & Chuhai Li, 2022. "Rural e‐commerce in China: Spatial dynamics of Taobao Villages development in Zhejiang Province," Growth and Change, Wiley Blackwell, vol. 53(3), pages 1082-1101, September.
    10. Vanessa Hellwig, 2023. "Digital gravity? Firm birth and relocation patterns of young digital firms in Germany," Journal of Regional Science, Wiley Blackwell, vol. 63(2), pages 340-378, March.
    11. Keqiang Wang & Guoxiang Li & Hongmei Liu, 2020. "Location choice of industrial land reduction in Metropolitan Area: Evidence from Shanghai in China," Growth and Change, Wiley Blackwell, vol. 51(4), pages 1837-1859, December.

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    More about this item

    Keywords

    Location choice model; Count data models; Hurdle model; Spatial spillovers;
    All these keywords.

    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)

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