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Significant Variables of Personal Income Tax Revenues
Weberová, Jana ; Kubátová, Květa (advisor) ; Vančurová, Alena (referee) ; Nerudová, Danuše (referee)
The dissertation is devoted to the questions of personal income tax. Because of the fundamental role of the personal income tax in the public finance area, it is very difficult to know variables that have an effect on its revenues in various countries and times. The attention is targeted on OECD countries. The paper begins with some thesis about tax functions of personal income tax in public finance and also with its importance in the tax mix in the nearly last forty years. Following part of the dissertation includes identification and a description of these variables that may have and effect on tax revenues regarding if these may have an effect on the personal income tax revenues. The variables were categorized into three groups -- economic, demographic and politico-sociologic. The main part of the paper is panel regression analysis with the fixed effects that is aimed at searching of various variables that have significant effect on the personal income tax revenues. In this part there are some regression models with the regression function linear in parameters or regression function nonlinear in parameters. The results of analysis are compared to each other and also to other author's results. Interpretation and summary of the results of analysis are also introduced.
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The influence of the taxation on donating to non-profit organizations
Špetla, Ondřej ; Slintáková, Barbora (advisor) ; Klazar, Stanislav (referee)
The thesis examines the influence of the tax deduction by reason of granting the donation on the taxpayers' behavior. The examination is working with Household Expenditure Survey (2004, 2005) of Czech Statistical Office and with author's own questionnaire survey (2007). In the first part the regression of demographical and economic characteristics on the amount of donation and its probability is run. There are the internal opinions of informant according to the filled questionnaire described in the second part. The regression was processed using Logit, Probit and Tobit models; the following section consists of frequency analysis.
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