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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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    References listed on IDEAS

    as
    1. Manfred M. Fischer & Daniel A. Griffith, 2006. "Modeling Spatial Autocorrelation in Spatial Interaction Data: A Comparison of Spatial Econometric and Spatial Filtering Specifications," ERSA conference papers ersa06p10, European Regional Science Association.
    2. Yongwan Chun, 2008. "Modeling network autocorrelation within migration flows by eigenvector spatial filtering," Journal of Geographical Systems, Springer, vol. 10(4), pages 317-344, December.
    3. Manfred M. Fischer & Jinfeng Wang, 2011. "Spatial Data Analysis," SpringerBriefs in Regional Science, Springer, number 978-3-642-21720-3.
    4. Lambert, Dayton M. & Brown, Jason P. & Florax, Raymond J.G.M., 2010. "A two-step estimator for a spatial lag model of counts: Theory, small sample performance and an application," Regional Science and Urban Economics, Elsevier, vol. 40(4), pages 241-252, July.
    5. Cesario, Frank J., 1977. "A new interpretation of the "normalizing" or "balancing" factors of gravity-type spatial models," Socio-Economic Planning Sciences, Elsevier, vol. 11(3), pages 131-136.
    6. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, December.
    7. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin‐Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967, December.
    8. James P. LeSage & Manfred M. Fischer & Thomas Scherngell, 2007. "Knowledge spillovers across Europe: Evidence from a Poisson spatial interaction model with spatial effects," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 393-421, August.
    9. Daniel Griffith, 2009. "Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows," Journal of Geographical Systems, Springer, vol. 11(2), pages 117-140, June.
    10. J Ledent, 1985. "The Doubly Constrained Model of Spatial Interaction: A More General Formulation," Environment and Planning A, , vol. 17(2), pages 253-262, February.
    11. Bolduc, Denis & Laferriere, Richard & Santarossa, Gino, 1992. "Spatial autoregressive error components in travel flow models," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 371-385, September.
    12. A G Wilson, 1971. "A Family of Spatial Interaction Models, and Associated Developments," Environment and Planning A, , vol. 3(1), pages 1-32, March.
    13. Daniel A. Griffith, 2003. "Spatial Autocorrelation and Spatial Filtering," Advances in Spatial Science, Springer, number 978-3-540-24806-4.
    14. Daniel A. Griffith, 2009. "Spatial Autocorrelation in Spatial Interaction," Advances in Spatial Science, in: Aura Reggiani & Peter Nijkamp (ed.), Complexity and Spatial Networks, chapter 0, pages 221-237, Springer.
    15. repec:rre:publsh:v:37:y:2007:i:1:p:28-38 is not listed on IDEAS
    16. Daniel A. Griffith, 2000. "A linear regression solution to the spatial autocorrelation problem," Journal of Geographical Systems, Springer, vol. 2(2), pages 141-156, July.
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    16. 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.
    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. Oshan, Taylor M., 2022. "Spatial Interaction Modeling," OSF Preprints m3ah8, Center for Open Science.
    19. 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.

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    More about this item

    Keywords

    Constrained gravity models; Count data; Patent citation flows; Poisson; Spatial dependence in origin-destination flows; Spatial econometrics; Spatial filtering;
    All these keywords.

    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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