Vše

Co hledáte?

Vše
Projekty
Výsledky výzkumu
Subjekty

Rychlé hledání

  • Projekty podpořené TA ČR
  • Významné projekty
  • Projekty s nejvyšší státní podporou
  • Aktuálně běžící projekty

Chytré vyhledávání

  • Takto najdu konkrétní +slovo
  • Takto z výsledků -slovo zcela vynechám
  • “Takto můžu najít celou frázi”

Public Administration in EU: Harmonization of Income Taxes

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F04130081%3A_____%2F19%3AN0000054" target="_blank" >RIV/04130081:_____/19:N0000054 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://mmi.fem.sumdu.edu.ua/sites/default/files/22_A279-2019_Korecko%20et%20al.pdf" target="_blank" >https://mmi.fem.sumdu.edu.ua/sites/default/files/22_A279-2019_Korecko%20et%20al.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.21272/mmi.2019.4-22" target="_blank" >10.21272/mmi.2019.4-22</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Public Administration in EU: Harmonization of Income Taxes

  • Popis výsledku v původním jazyce

    In the European communities, the need for tax harmonization has begun to commence since the beginning of integration efforts in the 1960s. The first attitudes to tax harmonization were very ambitious. The plan was not only structural harmonization but also harmonization of tax rates. The paper examines the nature and course of the direct tax harmonization process, describes its advantages and disadvantages as well as the positive and negative effects of tax competition. The paper aims to examine the development and volume of selected income taxes collected in the Member States of the European Union. It tells whether the harmonization of income taxes is still a stagnant process. Cluster analysis deals with looking for similarities of multidimensional objects. Two clustering methods were used - hierarchical agglomeration clustering and non-hierarchical clustering. Cluster analysis aimed to achieve groups of states that would have some homogeneity. Cluster analysis sorted the data into sets with the highest possible similarity within the group and the most significant difference between the groups. Analysis of tax burden and income tax rates confirmed significant differences in these indicators across the EU. On the other hand, cluster analysis revealed similar developments in tax systems in terms of their geographical location in Europe. Cluster analysis can be used to suggest possible steps to co-operate in harmonizing Member State taxes in the future. The authors of this article propose the possibility of harmonizing taxes and cooperating gradually within clusters rather than trying to apply uniform rules in all EU Member States at the same time. The conclusion of the article raises problems in the field of harmonization of direct taxes in the EU. The possibility of preserving autonomy in deciding on tax burden in the country is left to the many Member States because they see that autonomy as a competitive advantage, particularly in the field of investment.

  • Název v anglickém jazyce

    Public Administration in EU: Harmonization of Income Taxes

  • Popis výsledku anglicky

    In the European communities, the need for tax harmonization has begun to commence since the beginning of integration efforts in the 1960s. The first attitudes to tax harmonization were very ambitious. The plan was not only structural harmonization but also harmonization of tax rates. The paper examines the nature and course of the direct tax harmonization process, describes its advantages and disadvantages as well as the positive and negative effects of tax competition. The paper aims to examine the development and volume of selected income taxes collected in the Member States of the European Union. It tells whether the harmonization of income taxes is still a stagnant process. Cluster analysis deals with looking for similarities of multidimensional objects. Two clustering methods were used - hierarchical agglomeration clustering and non-hierarchical clustering. Cluster analysis aimed to achieve groups of states that would have some homogeneity. Cluster analysis sorted the data into sets with the highest possible similarity within the group and the most significant difference between the groups. Analysis of tax burden and income tax rates confirmed significant differences in these indicators across the EU. On the other hand, cluster analysis revealed similar developments in tax systems in terms of their geographical location in Europe. Cluster analysis can be used to suggest possible steps to co-operate in harmonizing Member State taxes in the future. The authors of this article propose the possibility of harmonizing taxes and cooperating gradually within clusters rather than trying to apply uniform rules in all EU Member States at the same time. The conclusion of the article raises problems in the field of harmonization of direct taxes in the EU. The possibility of preserving autonomy in deciding on tax burden in the country is left to the many Member States because they see that autonomy as a competitive advantage, particularly in the field of investment.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    50204 - Business and management

Návaznosti výsledku

  • Projekt

  • Návaznosti

    N - Vyzkumna aktivita podporovana z neverejnych zdroju

Ostatní

  • Rok uplatnění

    2019

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Marketing and Management of Innovations

  • ISSN

    2218-4511

  • e-ISSN

    2227-6718

  • Svazek periodika

    2019

  • Číslo periodika v rámci svazku

    4

  • Stát vydavatele periodika

    UA - Ukrajina

  • Počet stran výsledku

    12

  • Strana od-do

    280-291

  • Kód UT WoS článku

    000526405100001

  • EID výsledku v databázi Scopus