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@inproceedings{1435436,
author = {Konôpková, Zlatica and Buček, Jakub},
address = {Praha},
booktitle = {The 36th International Conference Mathematical Methods in Economics, Conference Proceedings.},
editor = {L.Váchová, V. Kratochvíl},
keywords = {Tax Burden; World Tax Index (WTI); Tax Quota; Principal Component Analysis; Factor Analysis; Non-negative Matrix Factorization; Czech Republic},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Praha},
isbn = {978-80-7378-372-3},
pages = {240-245},
publisher = {MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University},
title = {World Tax Index: Results of the Pilot Project},
url = {https://mme2018.fm.vse.cz/},
year = {2018}
}
TY - JOUR
ID - 1435436
AU - Konôpková, Zlatica - Buček, Jakub
PY - 2018
TI - World Tax Index: Results of the Pilot Project
PB - MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University
CY - Praha
SN - 9788073783723
KW - Tax Burden
KW - World Tax Index (WTI)
KW - Tax Quota
KW - Principal Component Analysis
KW - Factor Analysis
KW - Non-negative Matrix Factorization
KW - Czech Republic
UR - https://mme2018.fm.vse.cz/
L2 - https://mme2018.fm.vse.cz/
N2 - Taxes are the essential parts of models of economic growth. They may have negative impact on economy and burden part of the economic activity. Therefore, we need to be able measure the size of tax burden correspondingly. The most popular indices are tax quota and implicit tax rates, but there are also other alternative indicators including World Tax Index (WTI). WTI is an overall multi-criteria indicator of the tax burden designed for OECD countries and constructed as a combination of hard tax data weighted by soft data (QEO) gathered through an online questionnaire survey among tax specialists. In 2016 we introduced new methodology of WTI based on factor analysis and pilot project was held in 2017 for the Czech Republic to test the relevance of the method. In this paper we present and discuss the results of pilot project. We use three different factorization methods (namely Principal Component Analysis, Factor Analysis and Non-negative Matrix Factorization) to find latent factors in data and afterward compute new WTI values for each factorization method. All three methods suggest that corporate and personal income taxes have the highest tax burden effect.
ER -
KONÔPKOVÁ, Zlatica and Jakub BUČEK. World Tax Index: Results of the Pilot Project. Online. In L.Váchová, V. Kratochvíl. \textit{The 36th International Conference Mathematical Methods in Economics, Conference Proceedings.}. Praha: MatfyzPress, Publishing House of the Faculty of Mathematics and Physics Charles University, 2018, p.~240-245. ISBN~978-80-7378-372-3.
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