Categorisation of the European Union Countries in Relation to Efficiency Adjustment of Value Added Tax Collection Using Cluster Analysis and Multidimensional Scalling Cover Image

Categorisation of the European Union Countries in Relation to Efficiency Adjustment of Value Added Tax Collection Using Cluster Analysis and Multidimensional Scalling
Categorisation of the European Union Countries in Relation to Efficiency Adjustment of Value Added Tax Collection Using Cluster Analysis and Multidimensional Scalling

Author(s): Alena Andrejovská
Subject(s): Business Economy / Management, Methodology and research technology, EU-Accession / EU-DEvelopment, Fiscal Politics / Budgeting, EU-Legislation
Published by: Reprograph
Keywords: Value-addeded tax; tax harmonization; tax rate; Cluster analysis; Multidimensional scaling;

Summary/Abstract: The issue of the value added tax efficiency is intensively debated these days both at the level of individual governments, and the level of the European institutions and bodies, as well. The whole Europe is trying to mobilize and implement effective measures which would be able to improve the collection of taxes without increasing tax rates. VAT is currently the most harmonized tax, but states still retain some sovereignty regarding the level of rates, reduced rates and exemptions. Different Tax legislation in the countries, in combination with the application of its own VAT policy preferences and lack of control of tax administration causes growing the gap between actual and theoretical base for income taxes. The paper is devoted to the quantification of VAT system setup from the view of revenue collection efficiency of this tax using cluster analysis including 27 EU countries. It is also devoted to the identification of countries groups with similar situation of VAT collection and their common features. In a statistical meta- analysis there are compared several methodological approaches: variant of agglomerative hierarchical cluster analysis, the outputs of k- means, k- medoid and also fuzzy c- means method. The results are in qualitative agreement with multidimensional scaling.

  • Issue Year: IX/2014
  • Issue No: 30
  • Page Range: 580-583
  • Page Count: 4
  • Language: English