IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa12p1021.html
   My bibliography  Save this paper

Spatial Filtering and Model Interpretation for Spatial Durbin Models

Author

Listed:
  • Matthias Koch

Abstract

Spatial Filter for spatial autoregressive models like the spatial Durbin Model have seen a great interest in the recent literature. Pace et al. (2011) show that the spatial filtering methods developed by Griffith (2000) have desireable estimation properties for some parameters associated with spatial autoregessive models. However, spatial filtering faces two conceptual weaknesses: First the estimated parameters lack in general, and especially for the Spatial Durbin Model a proper interpretation. Second, there exists an inherent tradeoff between the estimator bias and its efficiency, depending on the spectrum of the used spatial weight matrix. This paper tackles both problems by introducing a new four step estimation procedure based on the eigenvectors of the spatial weight matrix. This new estimation procedure estimates all parameters of interest in a Spatial Durbin model and thus allows for a proper model interpretation. Additionally the estimation procedure's efficiency is only marginally influenced by the number of added eigenvectors, which allows us to use approximatly 95% of the available eigenvectors. By using Monte Carlo Simulations we observe that the estimaton procedure has a lower (or equal) bias and smaller (or equal) sample variance as the corresponding Maximum Likelihood estimator based on normality.

Suggested Citation

  • Matthias Koch, 2012. "Spatial Filtering and Model Interpretation for Spatial Durbin Models," ERSA conference papers ersa12p1021, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa12p1021
    as

    Download full text from publisher

    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa12/e120821aFinal01023.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jesús Crespo Cuaresma & Martin Feldkircher, 2013. "Spatial Filtering, Model Uncertainty And The Speed Of Income Convergence In Europe," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 720-741, June.
    2. Fischer, Manfred M. & Scherngell, Thomas & Reismann, Martin, 2008. "Knowledge spillovers and total factor productivity. Evidence using a spatial panel data model," MPRA Paper 77762, University Library of Munich, Germany.
    3. Jesús Crespo Cuaresma & Gernot Doppelhofer & Martin Feldkircher, 2014. "The Determinants of Economic Growth in European Regions," Regional Studies, Taylor & Francis Journals, vol. 48(1), pages 44-67, January.
    4. Manfred M. Fischer & Daniel A. Griffith, 2008. "Modeling Spatial Autocorrelation In Spatial Interaction Data: An Application To Patent Citation Data In The European Union," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 969-989, December.
    5. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Nikolas Kuschnig, 2022. "Bayesian spatial econometrics: a software architecture," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-25, December.
    3. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    4. Smirnykh, Larisa & Woergoetter, Andreas, 2021. "Regional convergence in CEE before and after the Global Financial Crisis," IHS Working Paper Series 33, Institute for Advanced Studies.
    5. Kuschnig, Nikolas, 2021. "Bayesian Spatial Econometrics and the Need for Software," Department of Economics Working Paper Series 318, WU Vienna University of Economics and Business.
    6. Doris A. Oberdabernig & Stefan Humer & Jesus Crespo Cuaresma, 2018. "Democracy, Geography and Model Uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(2), pages 154-185, May.
    7. Philipp Piribauer & Jesús Crespo Cuaresma, 2016. "Bayesian Variable Selection in Spatial Autoregressive Models," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(4), pages 457-479, October.
    8. Forte, Anabel & Peiró-Palomino, Jesús & Tortosa-Ausina, Emili, 2015. "Does social capital matter for European regional growth?," European Economic Review, Elsevier, vol. 77(C), pages 47-64.
    9. Oshan, Taylor M., 2022. "Spatial Interaction Modeling," OSF Preprints m3ah8, Center for Open Science.
    10. Wolfgang Polasek & Richard Sellner, 2013. "The Does Globalization Affect Regional Growth? Evidence for NUTS-2 Regions in EU-27," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 1, pages 23-65, March.
    11. 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.
    12. Benos, Nikos & Karagiannis, Stelios, 2013. "Do Cross-Section Dependence and Parameter Heterogeneity Matter? Evidence on Human Capital and Productivity in Greece," MPRA Paper 53326, University Library of Munich, Germany.
    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. Olivier Parent, 2012. "A space-time analysis of knowledge production," Journal of Geographical Systems, Springer, vol. 14(1), pages 49-73, January.
    15. Daniele Fabbri & Silvana Robone, 2010. "The geography of hospital admission in a national health service with patient choice," Health Economics, John Wiley & Sons, Ltd., vol. 19(9), pages 1029-1047, September.
    16. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    17. 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.
    18. Umber, Marc P. & Grote, Michael H. & Frey, Rainer, 2014. "Same as it ever was? Europe's national borders and the market for corporate control," Journal of International Money and Finance, Elsevier, vol. 40(C), pages 109-127.
    19. Lungarska, Anna & Chakir, Raja, 2018. "Climate-induced Land Use Change in France: Impacts of Agricultural Adaptation and Climate Change Mitigation," Ecological Economics, Elsevier, vol. 147(C), pages 134-154.
    20. Raffaele Paci & Emanuela Marrocu, 2013. "Knowledge Assets and Regional Performance," Growth and Change, Wiley Blackwell, vol. 44(2), pages 228-257, June.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wiwrsa:ersa12p1021. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gunther Maier (email available below). General contact details of provider: http://www.ersa.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.