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Constrained Variants of the Gravity Model and Spatial Dependence: Model Specification and Estimation Issues

In: Spatial Econometric Interaction Modelling

Author

Listed:
  • Daniel A. Griffith

    (University of Texas at Dallas)

  • Manfred M. Fischer

    (Vienna University of Economics and Business)

Abstract

In this paper, we distinguish three constrained variants of the gravity model of spatial interaction: doubly constrained, production constrained and attraction constrained exponential gravity models. These model variants include origin and/or destination specific balancing factors that act as constraints to ensure that the estimated rows and columns of the flow data matrix sum to the observed row and column totals. Because flows are typically counts, the Poisson rather than the normal probability model specification furnishes the appropriate statistical distribution, and parameter estimation can be achieved via Poisson regression. This probability model specification motivates the use of origin and/or destination fixed effects or—under certain conditions—the use of origin and/or destination specific random effects for model estimation. The paper establishes theoretical connections between balancing factors, fixed effects represented by binary indicator variables, and random effects. The results pertaining to both the doubly and singly constrained cases of spatial interaction are illustrated with an empirical example, while accounting for spatial dependence between flows from locations neighbouring both the origins and destinations during estimation.

Suggested Citation

  • Daniel A. Griffith & Manfred M. Fischer, 2016. "Constrained Variants of the Gravity Model and Spatial Dependence: Model Specification and Estimation Issues," Advances in Spatial Science, in: Roberto Patuelli & Giuseppe Arbia (ed.), Spatial Econometric Interaction Modelling, chapter 0, pages 37-66, Springer.
  • Handle: RePEc:spr:adspcp:978-3-319-30196-9_3
    DOI: 10.1007/978-3-319-30196-9_3
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    Cited by:

    1. Justyna Wilk, 2015. "Using symbolic data in gravity model of population migration to reduce modifiable areal unit problem (MAUP)," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(2), pages 243-264, June.
    2. Wilk Justyna, 2015. "Using Symbolic Data in Gravity Model of Population Migration to Reduce Modifiable Areal Unit Problem (MAUP)," Statistics in Transition New Series, Statistics Poland, vol. 16(2), pages 243-264, June.
    3. Daniel A. Griffith & Manfred M. Fischer & James LeSage, 2017. "The spatial autocorrelation problem in spatial interaction modelling: a comparison of two common solutions," Letters in Spatial and Resource Sciences, Springer, vol. 10(1), pages 75-86, March.
    4. S. Bacci & B. Bertaccini, 2021. "Assessment of the University Reputation Through the Analysis of the Student Mobility," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 363-388, August.
    5. M. Alonso & M. Beamonte & P. Gargallo & M. Salvador, 2014. "Labour and residential accessibility: a Bayesian analysis based on Poisson gravity models with spatial effects," Journal of Geographical Systems, Springer, vol. 16(4), pages 409-439, October.
    6. Paula Margaretic & Christine Thomas-Agnan & Romain Doucet, 2017. "Spatial dependence in (origin-destination) air passenger flows," Papers in Regional Science, Wiley Blackwell, vol. 96(2), pages 357-380, June.
    7. Christoph Hammer & Aurélien Fichet de Clairfontaine, 2016. "Trade Costs and Income in European Regions," Department of Economics Working Papers wuwp220, Vienna University of Economics and Business, Department of Economics.
    8. Justyna Wilk, 2015. "Using Symbolic Data In Gravity Model Of Population Migration To Reduce Modifiable Areal Unit Problem (Maup)," Statistics in Transition New Series, Polish Statistical Association, vol. 16(2), pages 243-264, June.
    9. repec:osf:osfxxx:m3ah8_v1 is not listed on IDEAS
    10. Persyn, Damiaan, 2021. "Migrants looking for opportunities - On destination size and spatial aggregation in the gravity equation for migration," MPRA Paper 111064, University Library of Munich, Germany.
    11. Guo, Yiqing & Mao, Xiyan & Wei, Jianing & Liu, Mingyang & Chen, Yiqi & Zhou, Jie, 2025. "Changes in the distance of interprovincial coal transportation in China and its effect on carbon emissions," Journal of Transport Geography, Elsevier, vol. 123(C).
    12. Oshan, Taylor M., 2022. "Spatial Interaction Modeling," OSF Preprints m3ah8, Center for Open Science.
    13. 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.
    14. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    15. George Grekousis, 2025. "Geographical-XGBoost: a new ensemble model for spatially local regression based on gradient-boosted trees," Journal of Geographical Systems, Springer, vol. 27(2), pages 169-195, April.
    16. Chao Zhang & Si Chen & Chunyang Wang & Yi Zhao & Min Ao, 2022. "Population Flow and Epidemic Spread: Direct Impact and Spatial Spillover Effect," SAGE Open, , vol. 12(1), pages 21582440211, January.
    17. Elise Desjardins & Christopher D. Higgins & Darren M. Scott & Emma Apatu & Antonio Páez, 2022. "Correlates of bicycling trip flows in Hamilton, Ontario: fastest, quietest, or balanced routes?," Transportation, Springer, vol. 49(3), pages 867-895, June.
    18. 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.
    19. Daisuke Murakami & Daniel Griffith, 2015. "Random effects specifications in eigenvector spatial filtering: a simulation study," Journal of Geographical Systems, Springer, vol. 17(4), pages 311-331, October.
    20. Yingxia Pu & Jin Zhao & Fanhua Kong & Xinyi Zhao & Guangqing Chi, 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.
    21. Aurélien Fichet de Clairfontaine & Manfred Fischer & Rafael Lata & Manfred Paier, 2015. "Barriers to cross-region research and development collaborations in Europe: evidence from the fifth European Framework Programme," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 577-590, March.
    22. 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.
    23. repec:osf:osfxxx:42vxn_v1 is not listed on IDEAS

    More about this item

    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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