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Detail práce
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Who wins and who loses due to financial secrecy? The Net Bilateral Financial Secrecy Index.
Název práce v češtině: Kdo vydělává a prodělává na finančním tajemství?
Název v anglickém jazyce: Who wins and who loses due to financial secrecy? The Net Bilateral Financial Secrecy Index.
Klíčová slova: Finanční tajemství, daňové ráje, daňový únik, secrecy jurisdiction
Klíčová slova anglicky: Financial Secrecy, tax haven, tax evasion, secrecy jurisdiction
Akademický rok vypsání: 2017/2018
Typ práce: bakalářská práce
Jazyk práce: angličtina
Ústav: Institut ekonomických studií (23-IES)
Vedoucí / školitel: PhDr. Miroslav Palanský, Ph.D.
Řešitel: skrytý - zadáno vedoucím/školitelem
Datum přihlášení: 21.03.2018
Datum zadání: 21.03.2018
Datum a čas obhajoby: 11.06.2019 09:00
Místo konání obhajoby: Opletalova - Opletalova 26, O105, Opletalova - místn. č. 105
Datum odevzdání elektronické podoby:10.05.2019
Datum proběhlé obhajoby: 11.06.2019
Oponenti: Mgr. Ing. Martin Štěpánek, M.A., Ph.D.
 
 
 
Kontrola URKUND:
Seznam odborné literatury
Janský, P., Meinzer, M. & Palanský, M., 2018. “Is Panama really your tax haven?: Secrecy jurisdictions and the countries they harm”. Tax Justice Network / Utrecht University.

Cobham, A., Petr J., and Meinzer, M. 2015. “The Financial Secrecy Index: Shedding New Light on the Geography of Secrecy.” Economic Geography 91 (3): 281–303. https://doi.org/10.1111/ecge.12094.

Tax Justice Network. 2018. “Financial Secrecy Index 2018: Methodology.” Tax Justice Network.
http://www.financialsecrecyindex.com/PDF/FSI-Methodology.pdf

Schjelderup, G. 2015. “Secrecy Jurisdictions.” International Tax and Public Finance, Forthcoming; NHH Dept. of Business and Management Science Discussion Paper No. 2015/12. Available at SSRN: https://ssrn.com/abstract=2576228 or http://dx.doi.org/10.2139/ssrn.2576228

Johannesen, N. and Zucman, G. 2014. “The end of bank secrecy? An evaluation of the G20 tax haven crackdown.” American Economic Journal: Economic Policy, 6 (1). pp. 65-91. ISSN 1945-7731
Předběžná náplň práce
The Financial Secrecy Index is a ranking that measures each jurisdiction’s contribution to global financial secrecy in a way that highlights harmful secrecy regulations. However, different secrecy jurisdictions specialize in providing services to the citizens of different countries, and thus are important for different countries to a varying extent. To account for this heterogeneity, Janský and Palanský (2018) developed the so-called Bilateral Financial Secrecy Index which estimates a ranking of the importance of each secrecy jurisdiction for each country. Who wins and who loses out due to financial secrecy? What do these countries have in common?

Research question and motivation
In my bachelor thesis I will analyse which secrecy jurisdictions harm individual countries the most by examining the relationship between selected jurisdiction and its secrecy jurisdictions. Although my thesis will be based of the Financial Secrecy Index (FSI), which is a “measure of each jurisdiction’s contribution to the global problem of financial secrecy” (Tax Justice Network 2018), I will be working more with the Bilateral Financial Secrecy Index (BFSI), which specifically aims to identify secrecy jurisdictions for specific countries, bilaterally (Janský, Meinzer, Palanský 2018). On the basis of the BFSI, I develop the Net Bilateral Financial Secrecy Index which will enable a deep analysis of each secrecy jurisdiction’s overall contribution to the global financial secrecy on both the supplying and the receiving side.
Further, I would like to compute several alternative versions of BFSI based on other data than Janský, Meinzer, Palanský used in their work, and use the Net BFSI to test the following hypotheses:
1) Countries that have a higher net BFSI are more successful in attracting foreign bank deposits.
2) Countries with a high Net BFSI have lower corporate tax rates than the countries with which they directly compete for foreign capital; and
3) Countries with higher Net BFSI are more often perceived as tax havens because they are often listed on blacklists of different studies and international organizations.
Based on all these results, I will then estimate which countries win and which lose out due to financial secrecy.


Contribution
My thesis will give new insights in analysing financial secrecy. From the results of my thesis we will be able to recognize not only how much the particular tax haven is used by the entities from other countries, but also how much the entities from particular tax haven use on contrary the other jurisdiction as a tax haven. After providing these calculations where this bilateral usage of the secrecy jurisdiction will cancel out. Therefore, the Net Financial Bilateral Index will much more precisely indicate how truly harmful the particular jurisdiction is. Further, through computing different alternatives of the Net BFSI based on different data, I will broaden, affirm and ameliorate my results to discover who truly wins or loses due to the financial secrecy.
Hopefully my bachelor thesis will contribute to the literature by providing additional evidence about the role of secrecy jurisdictions, which can help the anti-offshore policy throughout the world to truthfully recognize how important and harmful the secrecy jurisdiction of the particular country is, not only for the purpose of making better tax haven blacklists.


Methodology
Since the FSI is a well-established indicator in both policy and academic discourse (Cobham, Janský, and Meinzer 2015) as well as the Bilateral FSI, I will maintain this methodology. The FSI is composed of two parts, which are called secrecy scores (SS) and global scale weights (GSW). Whereas the BFSI is composed of also SS and BSW, so it uses the same information for secrecy scores as published in the 2018 version of the FSI, but the second part is not the GSW, but the bilateral scale weight (BSW) specific for each country. BSW is based on the IMF’s 2015 data on total portfolio investment as an approximation for financial services exports. By comparing the BFSI supplied and the BFSI received I will compute the Net Bilateral Financial Secrecy Index.
Further, I will focus on developing alternative versions of BFSI and then the Net BFSI subsequently by using other data than the IMF’s 2015 data on total portfolio investment. The data I will use are for example: for foreign direct investment from IMF Coordinated Direct Investment Survey, for foreign bank deposits from Bank for International Settlements Locational Banking Statistics or also KPMG corporate tax rate tables. Using this data, I will test my previously mentioned hypotheses.

Outline
1. Introduction to the topic, basic definitions (Tax haven, Financial Secrecy Index, Bilateral Financial Secrecy Index) 2. Literature review
3. Empirical part
3.1. Data description, used methodology (computing Net Bilateral Financial Secrecy Index and the alternatives of the original Bilateral Financial Secrecy Index)
3.2. Data analysis
3.3. Testing hypotheses (which I have mentioned earlier)
4. Results
5. Conclusion
 
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