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Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows

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Author Info

  • LeSage, James P.

    (Department of Economics, University of Toledo)

  • Polasek, Wolfgang

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

Abstract

We introduce a regression-based gravity model for commodity flows between 35 regions in Austria. We incorporate information regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model. We find that our approach produces improved model fit and higher likelihood values. The model accounts for spatial dependence in the origin-destination flows by introducing a spatial connectivity matrix that allows for three types of spatial dependence in the origins to destinations flows. We modify this origin-destination connectivity structure that was introduced by LeSage and Pace (2005) to include information regarding the presence or absence of a major highway/train corridor that passes through the regions. Empirical estimates indicate that the strongest spatial autoregressive effects arise when both origin and destination regions have neighboring regions located on the highway network. Our approach provides a formal spatial econometric methodology that can easily incorporate network connectivity information in spatial autoregressive models.

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File URL: http://www.ihs.ac.at/publications/eco/es-188.pdf
File Function: First version, 2006
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Bibliographic Info

Paper provided by Institute for Advanced Studies in its series Economics Series with number 188.

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Length: 34 pages
Date of creation: May 2006
Date of revision:
Handle: RePEc:ihs:ihsesp:188

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Related research

Keywords: Commodity flows; Spatial autoregression; Bayesian; Maximum likelihood; Spatial connectivity of origin-destination flows;

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References

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  1. Ming-Long Lee & R. Kelley Pace, 2005. "Spatial Distribution of Retail Sales," The Journal of Real Estate Finance and Economics, Springer, vol. 31(1), pages 53-69, August.
  2. A. Porojan, 2001. "Trade Flows and Spatial Effects: The Gravity Model Revisited," Open Economies Review, Springer, vol. 12(3), pages 265-280, July.
  3. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De.
  4. Olivier Parent & James P. Lesage, 2007. "Bayesian Model Averaging for Spatial Econometric Models ," University of Cincinnati, Economics Working Papers Series 2007-02, University of Cincinnati, Department of Economics.
  5. Brian Cushing & Jacques Poot, 2003. "Crossing boundaries and borders: Regional science advances in migration modelling," Papers in Regional Science, Springer, vol. 83(1), pages 317-338, October.
  6. 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.
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Cited by:
  1. Katharina Pijnenburg & Konstantin A. Kholodilin, 2011. "Do Regions with Entrepreneurial Neighbors Perform Better? A Spatial Econometric Approach for German Regions," ERSA conference papers ersa11p58, European Regional Science Association.
  2. Shuangzhe Liu & Tiefeng Ma & Wolfgang Polasek, 2012. "Spatial System Estimators for Panel Models: A Sensitivity and Simulation Study," Working Paper Series 75_12, The Rimini Centre for Economic Analysis.
  3. Luisa Alamá Sabater & Laura Marquez Ramos & Celestino Suarez Burguet, 2011. "Regional Trade and Logistics Infrastructure: A Spatial Approach," ERSA conference papers ersa11p1737, European Regional Science Association.
  4. Luisa Alamá-Sabater & Laura Márquez-Ramos & Celestino Suárez-Burguet & J. Miguel Navarro-Azorín, 2012. "Interregional Trade and Transport Connectivity. An Analysis of Spatial Dependence," Working Papers 2012/20, Economics Department, Universitat Jaume I, Castellón (Spain).
  5. Seya, Hajime & Yamagata, Yoshiki & Tsutsumi, Morito, 2013. "Automatic selection of a spatial weight matrix in spatial econometrics: Application to a spatial hedonic approach," Regional Science and Urban Economics, Elsevier, vol. 43(3), pages 429-444.
  6. Adjemian, Michael K. & Cynthia Lin, C.-Y. & Williams, Jeffrey, 2010. "Estimating spatial interdependence in automobile type choice with survey data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 661-675, November.
  7. Laura M√°rquez-Ramos & Luisa Alam√°-Sabater, 2011. "Spanish exports and logistics needs. A spatial marked point pattern approach," ERSA conference papers ersa10p1475, European Regional Science Association.
  8. repec:asg:wpaper:1013 is not listed on IDEAS
  9. Liu, Shuangzhe & Ma, Tiefeng & Polasek, Wolfgang, 2014. "Spatial system estimators for panel models: A sensitivity and simulation study," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 101(C), pages 78-102.

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