FINANCIAL SECRECY, CHARACTERISTICS OF CORPORATE TAX HAVENS AND TAX REVENUE PERFORMANCE: CLASSIFICATION OF COUNTRIES THROUGH CLUSTER ANALYSIS
Öz
This study aims to identify country profiles based on financial secrecy, corporate tax haven characteristics and tax revenue performance. The analysis includes 49 countries and three variables: the Haven Score of the Corporate Tax Haven Index (CTHI), the Secrecy Score of the Financial Secrecy Index (FSI) published by the Tax Justice Network, and total tax revenue as a percentage of GDP from the OECD Global Revenue Statistics database. K-Means clustering was used to classify the countries and the classification was compared with Ward.D2 hierachical clustering. The results of the correlation analysis show that there is a significant negative correlation between financial secrecy and tax revenue and there is no statistically significant relationship between corporate tax haven characteristics and tax revenue. The clustering analysis identified two different country profiles. The first cluster consists of 32 countries with lower Haven and Secrecy Scores and a higher average tax revenue ratio. The second cluster is composed of 17 countries with higher Haven and Secrecy Scores but a lower tax revenue ratio. The average tax revenue difference between the two clusters is 14.60 percentage points. Overall, the results highlight different country profiles in the sample concerning financial secrecy, corporate tax haven characteristics and tax revenue performance.
Anahtar Kelimeler
Financial Secrecy, Corporate Tax Havens, Tax Revenue, K-Means Clustering
Kaynakça
- Alstadsaeter, A., Johannesen, N., & Zucman, G. (2019). “Tax Evasion and Inequality.” American Economic Review, 109(6): 2073–2103. doi:10.1257/aer.20172043
- Beer, S., de Mooij, R., & Liu, L. (2020). “International Corporate Tax Avoidance: A Review of The Channels, Magnitudes, and Blind Spots”. Journal of Economic Surveys, 34(3): 660–688. doi:10.1111/joes.12305
- Belnap, A., Thornock, J., & Williams, B. (2024). “Hidden Wealth And Automatic Information Sharing.” The Journal of Law and Economics, 67(4), 905–949. https://doi.org/10.1086/731738
- Bénétrix, A., Emter, L., & Schmitz, M. (2024). “Automatic For The (Tax) People: Information Sharing and Cross-border Investment in Tax Havens”. Economic Policy, 39(120), 853–895. https://doi.org/10.1093/epolic/eiae041
- Bratta, B., Santomartino, V., & Acciari, P. (2024). “Assessing Profit Shifting Using Country-By-Country Reports: A Nonlinear Response to Tax Rate Differentials.” National Tax Journal, 77(2), 349–380. https://doi.org/10.1086/729293
- Chiari, A. (2024). “Revenue Losses From Corporate Tax Avoidance: Estimations From The UNU-WIDER Government Revenue Dataset”. Review of Development Economics, 28(2): 600–629. doi:10.1111/rode.13072
- Cobham, A., & Janský, P. (2018). “Global Distribution of Revenue Loss From Corporate Tax Avoidance: Re-estimation and Country Results”. Journal of International Development, 30(2): 206–232. doi:10.1002/jid.3348
- Cobham, A., Janský, P., & Meinzer, M. (2015). “The Financial Secrecy Index: Shedding New Light on The Geography of Secrecy”. Economic Geography, 91(3): 281–303. doi:10.1111/ecge.12094
- Crivelli, E., de Mooij, R., & Keen, M. (2015). “Base Erosion, Profit Shifting and Developing Countries.” IMF Working Paper 15/118. Washington, DC: International Monetary Fund. doi:10.5089/9781513563831.001
- Delis, F., Delis, M. D., Laeven, L., & Ongena, S. (2025). “Global Evidence on Profit Shifting Within Firms and Across Time.” Journal of Accounting and Economics, 79(2–3), 101744. https://doi.org/10.1016/j.jacceco.2024.101744