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Gravity model estimation with proxy variables and the impact of endogeneity on transportation planning

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  • de Grange, Louis
  • Troncoso, Rodrigo
  • Ibeas, Angel
  • González, Felipe

Abstract

This study presents an alternative method for estimating gravity models by multiple linear regression that is based on proxy variables, thus circumventing the endogeneity problems arising when least-squares estimators are used. The proxy variable approach generates consistent estimators for a gravity model without endogeneity bias. The presence of endogeneity is tested for using statistical tests developed specifically for our application. We conclude that proxy variables eliminate the endogeneity and produce consistent estimators in gravity models estimated using least squares. We also find, however, that endogeneity bias has no significant impact either on gravity model prediction or on urban transportation system planning processes based on such models.

Suggested Citation

  • de Grange, Louis & Troncoso, Rodrigo & Ibeas, Angel & González, Felipe, 2009. "Gravity model estimation with proxy variables and the impact of endogeneity on transportation planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 105-116, February.
  • Handle: RePEc:eee:transa:v:43:y:2009:i:2:p:105-116
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    Cited by:

    1. Philipp Marek & Mirko Titze & Clemens Fuhrmeister & Ulrich Blum, 2017. "R&D collaborations and the role of proximity," Regional Studies, Taylor & Francis Journals, vol. 51(12), pages 1761-1773, December.
    2. Louis Grange & Felipe González & Ignacio Vargas & Rodrigo Troncoso, 2015. "A Logit Model With Endogenous Explanatory Variables and Network Externalities," Networks and Spatial Economics, Springer, vol. 15(1), pages 89-116, March.
    3. Fuhrmeister, Clemens & Titze, Mirko & Blum, Ulrich & Marek, Philipp, 2014. "Does Proximity Matter in the Choice of Partners in Collaborative R&D Projects? – An Empirical Analysis of Granted Projects in Germany," IWH Discussion Papers 12/2014, Halle Institute for Economic Research (IWH).
    4. Mohsen Nazem & Martin Trépanier & Catherine Morency, 2015. "Revisiting the destination ranking procedure in development of an Intervening Opportunities Model for public transit trip distribution," Journal of Geographical Systems, Springer, vol. 17(1), pages 61-81, January.
    5. Tanya Suhoy & Yotam Sofer, 2019. "Getting to Work in Israel: Locality and Individual Effects," Bank of Israel Working Papers 2019.02, Bank of Israel.
    6. Beata Udvari, 2016. "The Aid for Trade initiative and the export performance of the Iberian EU-countries," IWE Working Papers 225, Institute for World Economics - Centre for Economic and Regional Studies.
    7. Hu, Xinlei & Wang, Xiaokun (Cara) & Ni, Linglin & Shi, Feng, 2022. "The impact of intercity economic complementarity on HSR volume in the context of megalopolization," Journal of Transport Geography, Elsevier, vol. 98(C).
    8. Louis Grange & Angel Ibeas & Felipe González, 2011. "A Hierarchical Gravity Model with Spatial Correlation: Mathematical Formulation and Parameter Estimation," Networks and Spatial Economics, Springer, vol. 11(3), pages 439-463, September.
    9. Boshuai Zhao & Juliang Zhang & Wenchao Wei, 2019. "Impact of Time Restriction and Logistics Sprawl on Urban Freight and Environment: The Case of Beijing Agricultural Freight," Sustainability, MDPI, vol. 11(13), pages 1-17, July.

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