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Modeling spatial autocorrelation in spatial interaction data: empirical evidence from 2002 Germany journey-to-work flows

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  • Daniel Griffith

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  • 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.
    • Handle: RePEc:kap:jgeosy:v:11:y:2009:i:2:p:117-140
    DOI: 10.1007/s10109-009-0082-z
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    References listed on IDEAS

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    1. Okabe, Atsuyuki, 1976. "A theoretical comparison of the opportunity and gravity models," Regional Science and Urban Economics, Elsevier, vol. 6(4), pages 381-397, December.
    2. repec:cor:louvrp:-2168 is not listed on IDEAS
    3. 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.
    4. PEETERS, Dominique & THOMAS, Isabelle, 2009. "Network autocorrelation," LIDAM Reprints CORE 2168, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Griffith, Daniel A., 2002. "A spatial filtering specification for the auto-Poisson model," Statistics & Probability Letters, Elsevier, vol. 58(3), pages 245-251, July.
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    Citations

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    Cited by:

    1. Andrea Otero, 2012. "Cali a comienzos del Siglo XXI: ¿Crisis o recuperación?," Documentos de trabajo sobre Economía Regional y Urbana 172, Banco de la Republica de Colombia.
    2. Philipp Otto & Wolfgang Schmid, 2018. "Spatiotemporal analysis of German real-estate prices," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(1), pages 41-72, January.
    3. Oshan, Taylor M., 2020. "Potential and pitfalls of big transport data for spatial interaction models of urban mobility," OSF Preprints gwumt, Center for Open Science.
    4. Giuseppe Arbia & Francesca Petrarca, 2016. "Effects of Scale in Spatial Interaction Models," Advances in Spatial Science, in: Roberto Patuelli & Giuseppe Arbia (ed.), Spatial Econometric Interaction Modelling, chapter 0, pages 85-101, Springer.
    5. Lan Hu & Yongwan Chun & Daniel A. Griffith, 2020. "Uncovering a positive and negative spatial autocorrelation mixture pattern: a spatial analysis of breast cancer incidences in Broward County, Florida, 2000–2010," Journal of Geographical Systems, Springer, vol. 22(3), pages 291-308, July.
    6. 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.
    7. Hankach, Pierre & Gastineau, Pascal & Vandanjon, Pierre-Olivier, 2022. "Multi-scale spatial analysis of household car ownership using distance-based Moran's eigenvector maps: Case study in Loire-Atlantique (France)," Journal of Transport Geography, Elsevier, vol. 98(C).
    8. Giuseppe Ricciardo Lamonica & Barbara Zagaglia, 2013. "The determinants of internal mobility in Italy, 1995-2006," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(16), pages 407-440.
    9. Lenormand, Maxime & Bassolas, Aleix & Ramasco, José J., 2016. "Systematic comparison of trip distribution laws and models," Journal of Transport Geography, Elsevier, vol. 51(C), pages 158-169.
    10. Giuseppe Ricciardo Lamonica, 2018. "An analysis of methods for the treatment of autocorrelation in spatial interaction models," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 72(2), pages 2-9, April-Jun.
    11. 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.
    12. Sadasivuni, R. & Cooke, W.H. & Bhushan, S., 2013. "Wildfire risk prediction in Southeastern Mississippi using population interaction," Ecological Modelling, Elsevier, vol. 251(C), pages 297-306.
    13. 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.
    14. 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.
    15. Clément Gorin, 2016. "Patterns and determinants of inventors' mobility across European urban areas," Working Papers halshs-01313086, HAL.
    16. 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).
    17. Yu, Danlin & Murakami, Daisuke & Zhang, Yaojun & Wu, Xiwei & Li, Ding & Wang, Xiaoxi & Li, Guangdong, 2020. "Investigating high-speed rail construction's support to county level regional development in China: An eigenvector based spatial filtering panel data analysis," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 21-37.
    18. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    19. Oshan, Taylor M., 2022. "Spatial Interaction Modeling," OSF Preprints m3ah8, Center for Open Science.
    20. Cordera, Rubén & Sañudo, Roberto & dell’Olio, Luigi & Ibeas, Ángel, 2018. "Trip distribution model for regional railway services considering spatial effects between stations," Transport Policy, Elsevier, vol. 67(C), pages 77-84.

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    More about this item

    Keywords

    Distance decay; Gravity model; Spatial autocorrelation; Spatial filter; Spatial interaction; C21; J20; R49;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General
    • R49 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Other

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