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Hétérogénéité spatiale. Principes et méthodes

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  • Julie Le Gallo

Abstract

This article has a dual purpose. First, it describes the main econometric specifications which can be used to represent spatial heterogeneity, reflected inan instability ofparameters inspace and/or a heteroscedasticity oferror terms. Only the specifications valid in cross-section are examined. Second, it explains the links between spatial heterogeneity and autocorrelation, the other major feature of localised data, defined by the absence of independence between geographical observations. In particular, we look at the extent to which traditional tests of heteroscedasticity or instability need to be amendedtotakeaccountofspatialautocorrelation.Anapplicationdesignedtoillustratethemainmodelsandthedifferent tests is also proposed.

Suggested Citation

  • Julie Le Gallo, 2004. "Hétérogénéité spatiale. Principes et méthodes," Economie & Prévision, La Documentation Française, vol. 162(1), pages 151-172.
  • Handle: RePEc:cai:ecoldc:ecop_162_0151
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    Cited by:

    1. Florent Sari, 2020. "Spatial disparities in accessibility to recreational amenities: the case of Pokémon GO," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 389-419, April.
    2. Geniaux, Ghislain & Martinetti, Davide, 2018. "A new method for dealing simultaneously with spatial autocorrelation and spatial heterogeneity in regression models," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 74-85.
    3. Sébastien BOURDIN, 2013. "Une Mesure Spatiale Locale De La Sigma-Convergence Pour Evaluer Les Disparites Regionales Dans L’Union Europeenne," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 37, pages 179-196.
    4. Magali Jaoul-Grammare & Karine Pellier, 2020. "The evolution of regional differences in French university supply between 1980 and 2000: Specialisation or diversification? [L’évolution des écarts régionaux d’offre universitaire en France entre 1," Post-Print halshs-03345631, HAL.
    5. Yannick L'Horty & Florent Sari, 2015. "Why are there so many long-term unemployed in Paris?," TEPP Working Paper 2015-01, TEPP.
    6. Christian Lambert Nguena & Martial Bindoumou, 2024. "Climate Change and Farm Household Income in Northern Cameroon: A Ricardian Analysis," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(1), pages 179-197, March.

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