Geopolitics of taxation: a panel data analysis on G-20 developed economies wit- hin the framework of political systems and public finance

In the simplest terms, tax; refers to the econo- mic values that the state collects from real and le- gal entities to finance public services and invest- ments based on its sovereign power. Taxation policy is a sub-branch of economic policies. Many factors affect these policies, such as sociological, economic, etc. In today’s globalising world, one of these factors is geographical factors. The effect of geographical factors on the functioning of the economy and economic policies with geopolitical factors is expressed as geo-economy. The geopo- litics of taxation as a newly developing economy and geo-economic field; examines the effects of geographical factors on the formation and results of taxation policies on a local, regional and global scale. To determine these effects accurately, it is necessary to determine the geopolitical typologi- es expressed by the geographical factors. In this context, the aim of this study is; It is to determine how the geopolitics of taxation differs according to the colonial (Marine), terrestrial and transition (Mixed, both maritime and terrestrial) geopolitical typologies within the framework of the G-20 de- veloped economies. Countries with colonial typo- logy; USA, UK, Japan, terrestrial typology; Ger- many, Russian Federation, Canada; Countries with a transitional typology; Brazil, China, and India. Panel robust regression and panel VAR method were used in the study. The observation interval of the study is the period between 1990-2019 at a monthly frequency. According to the panel’s Robust Regression results, taxation policies’ effi- ciency in terrestrial typology wae low. In the colo- nial typology, the effectiveness of taxation polici- es was observed to be high. Taxation policies effective in the transitional typology but somew- hat less so than in the colonial typology. While the effect of commercial taxes on growth was posi- tive in colonial and continental typologies, it was negative in transition typology. Dynamic analysis with the Panel VAR method also supported static results obtained in robot regression.