F38 - International Financial Policy: Financial Transactions Tax; Capital ControlsReturn

This article aims to analyse possible forms of taxation in the financial sector and, based on financial institutions’ data, estimate the potential contribution to the state revenue of the Czech Republic, if the tax is levied on the banks’ assets with the progression tax rate. The exponential smoothing methods were used to predict banks’ assets for the following five years. Actual data from the MagnusWeb database and annual reports for Czech banks from 2008 until 2021 were used. This article estimates tax revenues for the Czech Republic by using the parameters of bank tax proposed by several political parties and comparing the results with the latest windfall tax proposal. Based on the results, the bank tax would represent the additional revenue of CZK 23.4–28.7 bn (0.34–0.39% of GDP) each year for the following five years, with an increasing trend for the basic scenario. The proposed windfall tax should represent the additional tax revenue of CZK 33 bn for 2023 with decreasing trend, as the tax should be temporary and levied only on excessive profits.

The research revolves around the topic of offshore destinations and role of tax in the decision where to locate TNCs’ investments or relocate employees. This paper exploits rich country-by-country reporting (CbCR) data that banking institutions operating in the EU with annual turnover over 750 million are obliged to provide publicly as of 2014 on a yearly basis. Database includes 47 banks over 5 years and 27,533 datapoints. I explore whether there is any connection between effective tax rate (ETR) and number of employees in respective subsidiaries of banking institutions. In consequent multiple regression analysis, I add more variables to the model: such as profitability, labour productivity, and other controlling variables. Conclusion is that there is no significant correlation between ETR and employee count and that TNCs tend to locate their employees on a different basis. This is a unique analysis of data that can be used by other tax avoidance researchers and policy makers.