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Logistics agglomeration and logistics productivity in the USA

Author

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  • Bowen Sun

    (Peking University)

  • Haomin Li

    (Peking University)

  • Qiuyun Zhao

    (Peking University)

Abstract

Logistics agglomeration refers to the geographical concentration of logistics companies and activities. The growing trend of logistics agglomeration in the USA has drawn significant attention from both researchers and policy makers, and its benefits are being widely recognized. However, understanding of logistics agglomeration is still limited. The purposes of this paper are to confirm and quantify productivity gains for the logistics industry from the trend of agglomeration, using the County Business Patterns dataset for the US counties from 2007 to 2014. Panel unit root and panel cointegration test results suggest that a long-run equilibrium relationship between logistics agglomeration and logistics industry productivity exists. We then apply the panel fully modified ordinary least squares regression to estimate the long-run elasticity, and model estimation shows that the elasticity between concentration of logistics activities and industry productivity is 0.039. The study thus provides empirical evidence of the economic benefits associated this phenomenon and suggests that in a long run logistics agglomeration gives rise to higher industry productivity with an elasticity of 4%. In addition, our study results provide justification for policy makers to further invest in logistics agglomeration.

Suggested Citation

  • Bowen Sun & Haomin Li & Qiuyun Zhao, 2018. "Logistics agglomeration and logistics productivity in the USA," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(2), pages 273-293, September.
  • Handle: RePEc:spr:anresc:v:61:y:2018:i:2:d:10.1007_s00168-018-0867-4
    DOI: 10.1007/s00168-018-0867-4
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    2. Kang, Sanggyun, 2020. "Relative logistics sprawl: Measuring changes in the relative distribution from warehouses to logistics businesses and the general population," Journal of Transport Geography, Elsevier, vol. 83(C).
    3. Gordon, Joel A. & Balta-Ozkan, Nazmiye & Nabavi, Seyed Ali, 2022. "Beyond the triangle of renewable energy acceptance: The five dimensions of domestic hydrogen acceptance," Applied Energy, Elsevier, vol. 324(C).
    4. Holl, Adelheid & Mariotti, Ilaria, 2018. "Highways and firm performance in the logistics industry," Journal of Transport Geography, Elsevier, vol. 72(C), pages 139-150.
    5. Wang, Xuliang & Xu, Lulu & Ye, Qin & He, Shi & Liu, Yi, 2022. "How does services agglomeration affect the energy efficiency of the service sector? Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    6. Yang, Zhiwei & Chen, Xiaohong & Pan, Ruixu & Yuan, Quan, 2022. "Exploring location factors of logistics facilities from a spatiotemporal perspective: A case study from Shanghai," Journal of Transport Geography, Elsevier, vol. 100(C).
    7. M. A. Makushin & M. D. Goryachko, 2022. "The Geographical Patterns of the Warehouse Property Market in the Moscow Urban Agglomeration," Regional Research of Russia, Springer, vol. 12(4), pages 520-530, December.

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    JEL classification:

    • P25 - Political Economy and Comparative Economic Systems - - Socialist and Transition Economies - - - Urban, Rural, and Regional Economics
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies

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