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Spatial regression-based model specifications for exogenous and endogenous spatial interaction

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  • LeSage, James P.
  • Fischer, Manfred M.
Abstract
Spatial interaction models represent a class of models that are used for modeling origin destination flow data. The interest in such models is motivated by the need to understand and explain the flows of tangible entities such as persons or commodities or intangible ones such as capital, information or knowledge between regions. The focus here is on the log-normal version of the model. In this context, we consider spatial econometric specifications that can be used to accommodate two types of dependence scenarios, one involving endogenous interaction and the other exogenous interaction. These model specifications replace the conventional assumption of independence between origin-destination-flows with formal approaches that allow for two different types of spatial dependence in flow magnitudes. (authors' abstract)

Suggested Citation

  • LeSage, James P. & Fischer, Manfred M., 2014. "Spatial regression-based model specifications for exogenous and endogenous spatial interaction," Working Papers in Regional Science 2014/03, WU Vienna University of Economics and Business.
    • Handle: RePEc:wiw:wus046:4759
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    2. Rodolfo Metulini & Roberto Patuelli & Daniel A. Griffith, 2018. "A Spatial-Filtering Zero-Inflated Approach to the Estimation of the Gravity Model of Trade," Econometrics, MDPI, vol. 6(1), pages 1-15, February.
    3. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    4. Rodolfo Metulini & Paolo Sgrignoli & Stefano Schiavo & Massimo Riccaboni, 2018. "The network of migrants and international trade," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(3), pages 763-787, December.
    5. Thomas-Agnan, Christine & Margaretic, Paula & Laurent, Thibault, 2022. "Generalizing impact computations for the autoregressive spatial interaction model," TSE Working Papers 22-1357, Toulouse School of Economics (TSE), revised Feb 2023.
    6. James Paul LeSage & Manfred M. Fischer, 2020. "Cross-sectional dependence model specifications in a static trade panel data setting," Journal of Geographical Systems, Springer, vol. 22(1), pages 5-46, January.
    7. Morton, Craig & Mattioli, Giulio, 2023. "Competition in Multi-Airport Regions: Measuring airport catchments through spatial interaction models," Journal of Air Transport Management, Elsevier, vol. 112(C).
    8. Fischer, Manfred M. & LeSage, James P., 2018. "The role of socio-cultural factors in static trade panel models," Working Papers in Regional Science 2018/04, WU Vienna University of Economics and Business.
    9. Manfred M. Fischer & James P. LeSage, 2020. "Network dependence in multi-indexed data on international trade flows," Journal of Spatial Econometrics, Springer, vol. 1(1), pages 1-26, December.
    10. Martina Neuländtner & Thomas Scherngell, 2020. "Geographical or relational: What drives technology-specific R&D collaboration networks?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(3), pages 743-773, December.
    11. Laurent, Thibault & Margaretic, Paula & Thomas-Agnan, Christine, 2021. "Do neighboring countries matter when explaining bilateral remittances?," TSE Working Papers 21-1221, Toulouse School of Economics (TSE).
    12. Yingxia Pu & Xinyi Zhao & Guangqing Chi & Jin Zhao & Fanhua Kong, 2019. "A spatial dynamic panel approach to modelling the space-time dynamics of interprovincial migration flows in China," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(31), pages 913-948.
    13. Moura, Ticiana Grecco Zanon & Chen, Zhangliang & Garcia-Alonso, Lorena, 2019. "Spatial interaction effects on inland distribution of maritime flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 1-10.
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