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Central command, local hazard and the race to the top

Edoardo Di Porto () and Federico Revelli ()

No 2009/26, Working Papers from Institut d'Economia de Barcelona (IEB)

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.

Keywords: vehicle taxation; spatial auto-correlation; censored data (search for similar items in EconPapers)
JEL-codes: C23 C25 H72 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2009
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