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Firm relocation patterns incorporating spatial interactions

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  • Cao Nguyen
  • Kazushi Sano
  • Tu Tran
  • Tan Doan

Abstract

This paper developed a relocation pattern for analyzing decisions regarding the relocation process of individual firms by using discrete choice models. Within this framework, three decision points in the relocation process are maintained in the micro-simulation modeling. The first decision that is move or non-move is modeled by using a binary logit form with the outcome of the probability of moving. The second decision, choosing the destination region, is modeled as a multinomial logit model with the outcome of the conditional probability of choosing a region. The final decision, choosing the new zone, is estimated by considering the spatial interactions. For example, the correlation among firms in the deterministic term and the spatial correlation among zones in the error term are considered by mixed logit models. The results of the study indicated that large firms and older firms have a lower probability of relocation. Moreover, this research found out that migrating firms are more attracted in regions with high accessibility. Finally, spatial factors and land prices in a given zone strongly affect the zone choice decision-making process of all firms. Copyright Springer-Verlag 2013

Suggested Citation

  • Cao Nguyen & Kazushi Sano & Tu Tran & Tan Doan, 2013. "Firm relocation patterns incorporating spatial interactions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(3), pages 685-703, June.
    • Handle: RePEc:spr:anresc:v:50:y:2013:i:3:p:685-703
    DOI: 10.1007/s00168-012-0523-3
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    Cited by:

    1. Tessa Conroy & Steven Deller & Alexandra Tsvetkova, 2017. "Interstate Relocation Of Manufacturers And Business Climate," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 29(1), pages 18-45, March.
    2. Federica Rossi & Magdalena Dej, 2020. "Where do firms relocate? Location optimisation within and between Polish metropolitan areas," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(3), pages 615-640, June.
    3. 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.
    4. Jean Dubé & Cédric Brunelle, 2014. "Dots to dots: a general methodology to build local indicators using spatial micro-data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 245-272, August.
    5. In Hyeock (Ian) Lee, 2022. "Startups, relocation, and firm performance: a transaction cost economics perspective," Small Business Economics, Springer, vol. 58(1), pages 205-224, January.
    6. Conroy, Tessa & Deller, Steven & Tsvetkova, Alexandra, 2016. "Regional business climate and interstate manufacturing relocation decisions," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 155-168.
    7. Y Nguyen CAO, 2021. "Modeling Logistic Enterprise Re-Location Decision By A Nested Logit Model," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 49-57, June.
    8. Dario Musolino & Ilaria Mariotti & Aleid E. Brouwer, 2020. "Stated and revealed locational preferences of firms: a national scale perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(3), pages 493-499, June.

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    More about this item

    Keywords

    R14;

    JEL classification:

    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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