Spatial Econometric OD-Flow Models

Reference work entry

Abstract

Spatial interaction or gravity models have been used in regional science to model flows that take many forms, for example, population migration, commodity flows, traffic flows, and knowledge flows, all of which reflect movements between origin and destination regions. This chapter focuses on spatial autoregressive extensions to the conventional least-squares gravity models that relax the assumption of independence between flows. These models, proposed by LeSage and Pace (2008, Spatial econometric modeling of origin-destination flows. J Reg Sci 48(5):941–967, 2009), define spatial dependence in this type of setting to mean that larger observed flows from an origin region A to a destination region Z are accompanied by (i) larger flows from regions nearby the origin A to the destination Z, say regions B and C that are neighbors to region A, which they label origin dependence; (ii) larger flows from the origin region A to regions neighboring the destination region Z, say regions X and Y, which they label destination dependence; and (iii) larger flows from regions that are neighbors to the origin (B and C) to regions that are neighbors to the destination (X and Y), which they label origin-destination dependence. Spatial spillovers in these models can take the form of spillovers to both regions/observations neighboring the origin or destination in the dyadic relationships that characterize origin-destination flows as well as network effects that impact all other regions in the network. We set forth a simulation approach for these models that can be used to produce scalar expressions for the various types of spillover impacts that arise from changes in the explanatory variables of the model.

Keywords

Spatial Dependence Gravity Model Network Effect Spatial Weight Matrix Destination Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Behrens K, Ertur C, Koch W (2012) “Dual” gravity: using spatial econometrics to control for multilateral resistance. J Appl Econom 27(5):773–794. doi:10.1002/jae.1231CrossRefGoogle Scholar
  2. Bolduc D, Laferriere R, Santarossa G (1992) Spatial autoregressive error components in travel flow models. Reg Sci Urban Econ 22(3):371–385CrossRefGoogle Scholar
  3. Curry L (1972) A spatial analysis of gravity flows. Reg Stud 6(2):131–147CrossRefGoogle Scholar
  4. Elhorst JP (2010) Applied spatial econometrics: raising the bar. Spatial Econ Anal 5(1):9–28CrossRefGoogle Scholar
  5. Fischer MM (2002) Learning in neural spatial interaction models: a statistical perspective. J Geogr Syst 4(3):287–299CrossRefGoogle Scholar
  6. Fischer MM, Griffith DA (2008) Modeling spatial autocorrelation in spatial interaction data: an application to patent citation data in the European Union. J Reg Sci 48(5):969989Google Scholar
  7. Fischer MM, Reismann M (2002) A methodology for neural spatial interaction modeling. Geogr Anal 34(2):207–228Google Scholar
  8. Fischer MM, Scherngell T, Jansenberger E (2006) The geography of knowledge spillovers between high-technology firms in Europe evidence from a spatial interaction modelling perspective. Geogr Anal 38(3):288–309CrossRefGoogle Scholar
  9. Getis A (1991) Spatial interaction and spatial autocorrelation: a cross-product approach. Environ Plan A 23(9):1269–1277CrossRefGoogle Scholar
  10. Gourieroux C, Monfort A, Trognon A (1984) Pseudo maximum likelihood methods: applications to Poisson models. Econometrica 52(3):701–720CrossRefGoogle Scholar
  11. Griffith D, Jones K (1980) Explorations into the relationships between spatial structure and spatial interaction. Environ Plan A 12(2):187–201CrossRefGoogle Scholar
  12. Lambert DM, Brown JP, Florax RJGM (2010) A two-step estimator for a spatial lag model of counts: theory, small sample performance and an application. Reg Sci Urban Econ 40(4):241–252CrossRefGoogle Scholar
  13. Lee M, Pace RK (2005) Spatial distribution of retail sales. J Real Estate Finance Econ 31(1):53–69CrossRefGoogle Scholar
  14. LeSage JP, Fischer MM (2010) Spatial econometric modeling of origin-destination flows. In: Fischer MM, Getis A (eds) Handbook of applied spatial analysis. Springer, Berlin/Heidelberg/New York, pp 409–433CrossRefGoogle Scholar
  15. LeSage JP, Llano C (2006) A spatial interaction model with spatially structured origin and destination effects. SSRN: http://ssrn.com/abstract=924603 or doi:10.2139/ssrn.924603. Accessed 17 Aug 2006
  16. LeSage JP, Fischer MM, Scherngell T (2007) Knowledge spillovers across Europe, evidence from a poisson spatial interaction model with spatial effects. Pap Reg Sci 86(3):93–421Google Scholar
  17. LeSage JP, Pace RK (2008) Spatial econometric modeling of origin-destination flows. J Reg Sci 48(5):941–967CrossRefGoogle Scholar
  18. LeSage JP, Pace RK (2009) Introduction to spatial econometrics. Taylor-Francis/CRC Press, Boca RatonCrossRefGoogle Scholar
  19. Porojan A (2001) Trade flows and spatial effects: the gravity model revisited. Open Econ Rev 12(3):265–280CrossRefGoogle Scholar
  20. Ranjan R, Tobias JL (2007) Bayesian inference for the gravity model. J Appl Econom 22(4):817–838CrossRefGoogle Scholar
  21. Roy JR, Thill JC (2004) Spatial interaction modeling. Pap Reg Sci 83(1):339–361CrossRefGoogle Scholar
  22. Sen A, Smith TE (1995) Gravity models of spatial interaction behavior. Springer, HeidelbergCrossRefGoogle Scholar
  23. Smith TE (1975) A choice theory of spatial interaction. Reg Sci Urban Econ 5(2):137–176CrossRefGoogle Scholar
  24. Tiefelsdorf M (2003) Misspecifications in interaction model distance decay relations: a spatial structure effect. J Geogr Syst 5(1):25–50CrossRefGoogle Scholar
  25. Wilson AG (1967) A statistical theory of spatial distribution models. Transp Res 1(3):253–269CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.G.R.E.M.A.Q.Toulouse School of EconomicsToulouseFrance
  2. 2.Department of Finance and EconomicsTexas State University – San MarcosSan MarcosUSA

Personalised recommendations