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Central command, local hazard and the race to the top

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  • Edoardo Di Porto

    ()
    (LABOR, Centre for Employment Studies)

  • Federico Revelli

    ()
    (University of Torino)

Abstract

This paper explores for the first time the consequences of centrally imposed local tax limitations on the modelling and estimation of spatial auto-correlation in local fiscal policies, and compares three spatial interaction estimators: a) the conventional maximum likelihood estimator that ignores censoring; b) a spatial Tobit estimator; c) a discrete hazard estimator. Implementation of the above empirical approaches on the case of local vehicle taxation in Italy provides a reasonably coherent picture in terms of the direction and size of the spatial interaction process, and offers a plausible spatial interpretation of the race to the top in provincial vehicle taxes.

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Bibliographic Info

Paper provided by Institut d'Economia de Barcelona (IEB) in its series Working Papers with number 2009/26.

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Length: 36 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:ieb:wpaper:2009/10/doc2009-26

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Keywords: vehicle taxation; spatial auto-correlation; censored data;

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