Central Command, Local Hazard and the Race to the Top
AbstractThis 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 InfoPaper provided by University of Turin in its series Department of Economics and Statistics Cognetti de Martiis. Working Papers with number 200909.
Length: 32 pages
Date of creation: Oct 2009
Date of revision:
Other versions of this item:
- Edoardo Di Porto & Federico Revelli, 2009. "Central command, local hazard and the race to the top," Working Papers 2009/26, Institut d'Economia de Barcelona (IEB).
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- H72 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Budget and Expenditures
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-04-04 (All new papers)
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