IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v40y2008i11p2751-2769.html
   My bibliography  Save this article

Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)

Author

Listed:
  • Daniel A Griffith

    (Ashbel Smith Professor, School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX, 75080-3021, USA)

Abstract

Interaction terms are constructed with georeferenced attribute variables and spatial filter eigenvectors, and then used to compute geographically varying regression coefficients. These coefficients, which are analogous to geographically weighted regression (GWR) coefficients, display preferable properties, and this specification is used to critique selected features of GWR. Comparisons are illustrated with the Georgia data appearing in the standard GWR tutorial.

Suggested Citation

  • Daniel A Griffith, 2008. "Spatial-Filtering-Based Contributions to a Critique of Geographically Weighted Regression (GWR)," Environment and Planning A, , vol. 40(11), pages 2751-2769, November.
    • Handle: RePEc:sae:envira:v:40:y:2008:i:11:p:2751-2769
    DOI: 10.1068/a38218
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/a38218
    Download Restriction: no
    File URL: https://libkey.io/10.1068/a38218?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. David Wheeler & Michael Tiefelsdorf, 2005. "Multicollinearity and correlation among local regression coefficients in geographically weighted regression," Journal of Geographical Systems, Springer, vol. 7(2), pages 161-187, June.
    3. Daniel A. Griffith, 2003. "Spatial Autocorrelation and Spatial Filtering," Advances in Spatial Science, Springer, number 978-3-540-24806-4, Fall.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jinjun Tang & Fan Gao & Fang Liu & Wenhui Zhang & Yong Qi, 2019. "Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM," Sustainability, MDPI, vol. 11(19), pages 1-19, October.
    2. 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.

    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. Reinhold Kosfeld & Christian Dreger & Hans-Friedrich Eckey, 2008. "On the stability of the German Beveridge curve: a spatial econometric perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(4), pages 967-986, December.
    2. 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.
    3. Hans-Friedrich Eckey & Reinhold Kosfeld & Matthias Türck, 2007. "Regionale Entwicklung mit und ohne räumliche Spillover-Effekte," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 27(1), pages 23-42, February.
    4. D’Aubigny Gérard, 2016. "A Statistical Toolbox For Mining And Modeling Spatial Data," Comparative Economic Research, Sciendo, vol. 19(5), pages 5-24, December.
    5. Gloria Alarcón-García & José Daniel Buendía Azorín & María del Mar Sánchez de la Vega, 2020. "Shadow economy and national culture: A spatial approach," Hacienda Pública Española / Review of Public Economics, IEF, vol. 232(1), pages 53-74, March.
    6. 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.
    7. Christoph Grimpe & Roberto Patuelli, 2011. "Regional knowledge production in nanomaterials: a spatial filtering approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(3), pages 519-541, June.
    8. 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.
    9. 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.
    10. 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.
    11. Roberto Patuelli & Norbert Schanne & Daniel A. Griffith & Peter Nijkamp, 2012. "Persistence Of Regional Unemployment: Application Of A Spatial Filtering Approach To Local Labor Markets In Germany," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 300-323, May.
    12. Gloria Alarcón García & José Daniel Buendía Azorín & María del Mar Sánchez de la Vega, 2018. "Tax Evasion in Europe: An Analysis Based on Spatial Dependence," Social Science Quarterly, Southwestern Social Science Association, vol. 99(1), pages 7-23, March.
    13. Enrico Marelli & Roberto Patuelli & Marcello Signorelli, 2012. "Regional unemployment in the EU before and after the global crisis," Post-Communist Economies, Taylor & Francis Journals, vol. 24(2), pages 155-175, January.
    14. Timo Mitze & Falk Strotebeck, 2012. "What Drives Regional Cooperative Behavior in German Biotechnology? Embedding Social Network Analysis in a Regression Framework," ERSA conference papers ersa12p629, European Regional Science Association.
    15. Roberto Patuelli & Daniel A. Griffith & Michael Tiefelsdorf & Peter Nijkamp, 2011. "Spatial Filtering and Eigenvector Stability: Space-Time Models for German Unemployment Data," International Regional Science Review, , vol. 34(2), pages 253-280, April.
    16. Roberto Patuelli & Norbert Schanne & Daniel A. Griffith & Peter Nijkamp, 2012. "Persistence Of Regional Unemployment: Application Of A Spatial Filtering Approach To Local Labor Markets In Germany," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 300-323, May.
    17. Moniruzzaman, Md & Páez, Antonio, 2012. "Accessibility to transit, by transit, and mode share: application of a logistic model with spatial filters," Journal of Transport Geography, Elsevier, vol. 24(C), pages 198-205.
    18. Buendía Azorín, José Daniel. & Sánchez De La Vega, Mª Del Mar, 2017. "Estimación del valor añadido bruto, dependencia espacial y datos de panel: Evidencia en el caso de los municipios de la Región de Murcia /Estimation of Gross Value Added, Spatial Dependence and Panel ," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 315-340, Mayo.
    19. Matías Mayor & Roberto Patuelli, 2012. "Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions," Advances in Spatial Science, in: Esteban Fernández Vázquez & Fernando Rubiera Morollón (ed.), Defining the Spatial Scale in Modern Regional Analysis, edition 127, chapter 0, pages 173-192, Springer.
    20. Eckey, Hans-Friedrich & Türck, Matthias, 2007. "Convergence of EU-Regions. A Literature Report," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 10, pages 5-32.

    More about this item

    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:sae:envira:v:40:y:2008:i:11:p:2751-2769. 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: SAGE Publications (email available below). General contact details of provider: .

    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.