2012
University of Groningen Faculty of Economics and Business
Gergana Stoyanova s2130211 email: s2130211@student.rug.nl
Master thesis supervisor: Prof. Dr. Steven Brakman Research methodology supervisor: Prof. Dr. Erik Dietzenbacher
TAX DIFFERENTIALS AS
2
Abstract: This paper analyzes the effect of corporate tax rate on FDI inflows in 13 European
countries for twelve-year period of time. The underlying model is the gravity framework. Market size of home and host country, distance, corporate tax rate and tax preferences in taxation of MNEs are used to explain the volume of inward FDI in the sample countries. The results obtained show that the corporate tax rate is not detrimental to FDI inflows in the EU countries, but it gives empirical evidence that preferable taxation, here defined by the country being a tax haven, have positive effect on attracting FDI flows. After controlling for additional variables, namely labor costs and government investments the result for corporate tax remain unchanged and the significance of tax haven is improved. Adding political stability to the equation hardly makes a difference. When controlling for gdp per capita of the host country the significance of taxes improves, but the coefficient of tax haven turns negative.
3 I. Introduction
There are a lot of factors which are influencing FDI activities. Among others market size, labor costs, tariff barriers, and taxes etc. influence the location decision of MNEs. The current paper is focused specifically on taxes and taxation regimes as determinant of FDI. The main findings in this research area show that corporate taxation is important for FDI, but it is serving as an additional factor in favor of the location decision and not as a main determinant. The ability of tax havens on attracting more FDI inflows than non-tax haven countries is also investigated in this analysis, which distinct the research of the other existing works. The effect of corporate tax burden has been analyzed by various author, among others Wolff (2007), Benassy- Quere at al. (2007), but none of them focuses on tax havens. The common research literature with regard to tax havens analyzes their effect either on the economic activity of neighboring non-tax haven countries (Blanco and Rogers 2009; Desai, Foley and Hines 2006) or on other tax-haven countries (Blanco and Rogers 2011), while I have investigated the straight-forward relationship between tax havens and foreign direct investment in order to find out what is their effect on FDI inflows.
4 haven countries and the neighboring non-tax haven countries (Blanco and Rogers 2009; Desai, Foley and Hines 2006). The conclusion which could be made on the basis of this research and with the support of the findings of the other authors is that corporate taxes could influence FDI inflows, but they could not be described as detrimental. Instead, they are more a factor which could give additional motive to the location decision of MNEs.
The paper proceeds as follows: in the next section is provided a literature review on taxes, tax havens and the existing literature dealing with the topic as well as the theoretical framework and the testable hypotheses of the research. In Section 3 is given a description of the dataset and in Section 4 are shown the estimation technique, results and the robustness checks. In the last Section is made a conclusion and a short evaluation of the research.
II. Literature Review
5 (2009) argue that tax elasticity of FDI is higher than with respect of infrastructure, which would lead to undersupply of infrastructure. Antonakakis and Tondl (2012) share the same statement. They also claim, in line with the OECD Policy Brief (Feb. 2008) that vertical FDI is being more sensitive to tax differentials. Moreover, they add that for VFDI not only corporate taxes might be important, but also other tax rates, namely taxes on wages.
The topic of corporate taxes as determinant of FDI is considered by quite a number of authors. All of them find that there is a relationship between corporate tax rates and FDI. Hansson and Olofsdotter (2010) find that tax differentials are negatively related to FDI but this relationship is more significant for the periphery EU countries. Wolff (2007) also finds effect of tax rate on FDI and he captures also the influence of home country corporate tax rates. This finding is following the logic that if home country taxes are rising, an investment abroad could be undertaken in order to escape the higher taxation. In line with the economic theory are also the findings of Benassy-Quere et al. (2007). A double confirmation of the results of these and also other papers in this research field is made by the meta analysis of de Mooij et al. (2001), who make a synthesis of all relevant works up to 2001.
6 neighboring country; the other way round, they complement the economic activity. However, these papers focus on the aspect of proximity, while here the analysis is made on the basis of taxation regimes. In the current economic research the straight-forward relationship between tax haven countries and the FDI inflows into these countries is sought. It investigates whether the preferable taxation in these countries accounts for more FDI inflows than in the other European countries. The effect specifically towards the FDI flows is analyzed and not for the economic activity at all, which differs the research from Desai et al. (2006).
Although the reviewed papers on the effect of corporate taxation on FDI are in line with the economic theory which predicts that taxes would have negative effect on investment, all authors also find that the significance of corporate taxes is higher in combination with other determinants of FDI. Hansson and Olofsdotter (2010) find that taxes are more important for agglomeration economies, where also the labor costs are lower. Such economies attract more efficiency seeking FDI, on which tax incentive have greater influence (Antonakakis and Tondl (2012)). Also according to Wolff (2007) the importance of corporate taxes as main determinant for FDI inflows cannot be confirmed. Benassy-Quere et al. (2007) also come to the conclusion that tax differentials are more important in combination with other factors. They made the statement that even if countries apply zero taxation that would not be enough by itself to determine the location decision of MNEs. Moreover these conclusions are confirmed by the meta-analysis of de Mooij and Ederveen (2001). They make the results of all researches in the field of taxes and FDI from 1984 until 2001 comparable and confirm one more time the original findings. All authors reach the same conclusions about the effect of taxation on FDI activity and similar results are reported later on in the paper.
Most of the above stated articles apply the gravity framework in the analysis on FDI flows. The gravity model is commonly accepted framework for analyzing foreign direct investment and it is also applied in this paper.
The Gravity model and trade
7 the two countries and the distance between them. Later on an important contribution to the theory makes, in his research, Anderson and van Wincoop (2004) provide some further justification of the model as one used to define the trade between countries. He shows that the gravity model could be based on the characteristics of the expenditure system. Moreover, he finds that the model could be best applied to countries with similar characteristics. Another important research, which contributed to the enrichment of the gravity theory of trade, is made by Bergstand (1985), who estimates the gravity equation in a partial equilibrium. He finds out in his research about 15 OECD countries, that the distance affects the volume of trade flows in a negative way. According to his findings price and exchange rates could also influence trade flows.
The gravity model and FDI
8 economic development, which lies also in the basic assumption of the gravity model, that similar countries are expected to experience more investment flows. I assume that the FDI flows are function of:
where F is the bilateral FDI flow between country i and j, with country i being the home country and country j being the host country. GDPi is the GDP of country i, GDPj is respectively the GDP of country j, TAXj is the statutory corporate tax rate of country j and Hav is a variable which shows whether the analyzed host country is tax haven or not. According to my framework FDI flows are defined by the market size of the sending and receiving countries, which are captured by the GDP in the above-described function. This would help me to find out whether the FDI flows between the analyzed set of countries are with a market-seeking character. The distance variable captures motives for investing, which are detrimental for VFDI. It represents transaction costs, among others transportation and communication costs, sending personnel abroad, costs because of cultural and language differences, etc. Further, the corporate tax rate and the definition of the country as tax haven or not could capture the policy incentives for attracting FDI.
As stated above, I add two new variables to the model, which are of specific interest in this research – Tax and Hav. That is the underlying reason to define two hypotheses which I would test further in the empirical part of the research. The first hypothesis would include test of the effect of Tax on FDI. Accepting that there is no relationship between the two as my basis – zero hypothesis, I would try to prove that this does not fit the theory. The second hypothesis which I would test includes the coefficient of the variable Hav. I assume that there is no relationship between FDI and HAVEN, which would be the zero hypothesis of my test. My aim is to reject the zero hypothesis and in this way to prove that there is relationship which is positive and highly significant. A third hypothesis for the joint significance of the two coefficients is also tested in the course of the research.
III. Data
9 Portugal, Hungary, Cyprus, the Czech Republic, Austria and Finland. The choice of the countries is motivated by the fact that all the countries are European and quite similar in their economic environment. However, in the same time there are specific differences which give a good argument for division of sub-groups within the sample. For example, the Netherlands, Cyprus and Luxembourg are regarded as tax havens in the research (which is motivated a few alineas below), while the other countries do not treat so preferable foreign direct investment. A division could be made also by the characteristic of old and new member states of the European Union and it is a stylized fact that in the old members all expenses related to FDI are higher. As already stated the data is gathered for twelve-year period of time from 1999-2010. The so called sending countries are three and the choice of the countries is motivated by the fact that these are the main partners of the EU – the United States, Japan and Canada. There is data obtained for the GDP, based on the expenditure approach in current prices for each year and country in US dollars from the online database of the OECD. The FDI flows are also given in US dollars for almost every year for each country. The data for FDI flows is from the OECD online database. For Cyprus the FDI flows data is obtained first in millions euros from the database of Eurostat and then I have recalculated it into US dollars with the help of the current exchange rate euro/dollar1. This was necessary because the database of the OECD where the rest of the FDI data is obtained misses any statistics for Cyprus. Another important remark is that the FDI data for Belgium and Luxembourg from 1999 until 2001 is exactly the same because in this period the two countries were treated as one and the statistics were given for the two as a whole. Like Wolff (2007) and Hansson and Olofsdotter (2010) I use in the dataset the net FDI inflows, which causes the fact that some of the observations have negative values. FDI flows comprise of three kinds – the equity capital, reinvested earnings and other FDI capital, usually loans. In the analysis there is no distinction between the different sources and they are taken as a whole and named FDI inflows. I do not use the subdivision of FDI flows, because the aim of the research is to analyze the effect of taxes on FDI flows as a whole. The distance is in kilometers and it is obtained from the CEPII database. I follow Wolff (2007) and use the statutory corporate tax rates for each year of the twelve-year period. The data is in percentages and it is obtained from the OECD tax rates database. The Havj variable is an indicator variable which takes the value of 1 if the country is regarded as haven. A country is defined to be a tax haven if there exists a kind of preferable taxation. The definition of the countries tax havens is provided in Table 2.
1
10 Looking at the stylized facts we see that the development of the statutory corporate tax rate for all countries is similar. It has a downward tendency in the twelve-year period for which the analysis is carried out (Table 1a, b). In the same period the FDI flows does not have an obvious trend of development. There are periods of higher investment followed by periods of decline in FDI. These periods are associated with the famous crises in the economic world – the Dot-Com crisis in the early 2000s and, of course, the credit crisis from the recent years (graphs are shown in Appendix 1). A simple division to low and high tax countries among the sample is made. Low-tax are the countries which have statutory corporate tax rate below 21, 85% and high-tax are the countries whose corporate tax rate exceeds this level. The level of 21, 85% is the average statutory corporate tax rate among the EU 27 countries for 2011. According to the current tax rate (of 2011) the countries which fall under the label high-tax are Austria with a tax rate of 25%, Belgium: 33%, Finland – corporate tax rate of 26%, France: 33, 3%, Italy’s tax burden is 27, 5%, Luxembourg with 22, 1%, the Netherlands: 25% and Portugal: 25%. The rest of the countries could be described as low tax countries, which are Poland, Hungary and the Czech Republic with rate of 19%, Germany whose tax rate is 15, 8% and Cyprus with 10% (Rates according to the OECD).
Table 1a Statutory corporate tax rates
Year/Country Hungary Italy Luxembourg Netherlands Poland Portugal Cyprus
1999 18,0 37,0 30,0 35,0 34,0 34,0 28,0 2000 18,0 37,0 31,2 35,0 30,0 32,0 28,0 2001 18,0 36,0 31,2 35,0 28,0 32,0 28,0 2002 18,0 36,0 22,9 34,5 28,0 30,0 28,0 2003 18,0 34,0 22,9 34,5 27,0 30,0 15,0 2004 16,0 33,0 22,9 34,5 19,0 25,0 15,0 2005 16,0 33,0 22,9 31,5 19,0 25,0 10,0 2006 17,3 33,0 22,9 29,6 19,0 25,0 10,0 2007 20,0 33,0 22,9 25,5 19,0 25,0 10,0 2008 20,0 27,5 22,9 25,5 19,0 25,0 10,0 2009 20,0 27,5 21,84 25,5 19,0 25,0 10,0 2010 19,0 27,5 21,84 25,5 19,0 25,0 10,0
11 Table 1b Statutory corporate tax rate
Year/Country Austria Belgium Czech Republic Finland France Germany
1999 34,0 40,2 35,0 28,0 40,0 42,2 2000 34,0 40,2 31,0 29,0 37,8 42,2 2001 34,0 40,2 31,0 29,0 36,43 26,4 2002 34,0 40,2 31,0 29,0 35,43 26,4 2003 34,0 33,00 31,0 29,0 35,43 27,960 2004 34,0 33,00 28,0 29,0 35,43 26,38 2005 25,0 33,00 21,0 26,0 34,95 26,38 2006 25,0 33,00 24,0 26,0 34,43 26,38 2007 25,0 33,00 24,0 26,0 34,43 26,38 2008 25,0 33,00 21,0 26,0 34,43 15,83 2009 25,0 33,00 20,0 26,0 34,43 15,83 2010 25,0 33,00 19,0 26,0 34,43 15,83
Source: Made by the author using OECD tax rates database
12 named above. The column presenting the exemption treatment is important because such treatment is a main part of the taxation regime of a country, which motivates the location decision of an MNE. A column in which is stated whether information about trusts is published is included because it is important factor for indicating the transparency in the field. Not publishing information on trusts means that there is a lack of transparency. Following Hines (2007) that a tax haven should have a politically stable environment, an index of the political stability is also included. Finally I have added also a column with the FSI index of some of the countries (Financial Secrecy Index), which is developed by the Tax Justice Network in the project “Mapping Financial Secrecy”. The index is based on 12 key financial secrecy indicators, among others banking secrecy and public information about trusts. It could be concluded that this index comprises all of the characteristics of a tax haven and it is ranking the countries according to it. In the last column there is a conclusion about each country.
13 being taxed, which makes the country more attractive for investments. Van Dijk et al. (2006) give clear arguments why the Netherlands is usually regarded as tax haven:
The attractiveness of the Netherlands results from several factors. One of these is the so called ‘participation exemption’ that exempts dividends and capital gains from subsidiary companies abroad from corporate income tax in the Netherlands. A second reason is the unusually large Double Taxation Treaty (DTT) network that substantially reduces withholding taxes on dividend, interest and royalty payments between treaty countries and the Netherlands. A third reason is the advance tax ruling system that gives certainty to multinationals about how the income of their Dutch subsidiaries will be taxed. Other reasons include the special regime for group finance companies (CFA), which is currently being phased out, and general factors such as legal security and political and economic stability.2
To sum up, looking at the analyzed countries, they are all EU countries and it is obvious of the provided table that their taxation systems include special tax exemptions on dividend income as well as capital gains if certain requirements are met. Usually these requirements include 10% participation rule, minimum holding period from 12 months in some countries up to two years in others. In some of the countries there is also a third tax requirement. Most of them do not have banking secrecy, but also quite a number of the countries do not publish information about trust companies.
Table 2 Characteristics of countries tax havens Country Banking
secrecy
Zero or Low
tax rate Exemptions* Trusts**
Political stability***
FSI
index Tax Haven
Hungary no yes yes yes 0,78 75 could be
Italy no no yes yes 0,71 49 no
Luxembourg yes no yes yes 0,88 87 yes
Austria yes no yes yes 0,80 91 could be
Belgium no no yes yes 0,74 73 no
Netherlands no no yes yes 0,79 58 yes
Poland no yes yes n/a 0,82 n/a no
Portugal no no yes n/a 0,73 n/a no
Cyprus yes yes yes yes 0,72 75 yes
Czech no yes yes n/a 0,71 n/a no
Finland no no yes n/a 0,89 n/a no
Germany no yes yes yes 0,70 57 no
France no no yes no 0,67 n/a no
Source: Made by the author; Data source given in Bibliography * Exemptions on dividend income and capital gains; ** Characterized by the fact whether the country publishes information about trust companies YES – does not publish, NO – publishes; *** Political stability index 2010
2
14 As the paper seeks the relationship between the FDI inflows and the statutory corporate tax rates a number of figures with the development of the two parameters are provided in Appendix 1. The countries are divided into two groups, motivated by the criteria stated above – high-tax countries, including Austria, Belgium, Portugal, Finland and France; low-tax countries - Hungary, Czech Republic, Poland and Germany; and countries tax havens – Luxembourg, Cyprus and the Netherlands.
First to be analyzed is the group of the three countries which I refer to as tax havens – the Netherlands, Luxembourg and Cyprus. The FDI flows into the Netherlands originating from Canada have stable development throughout the whole period. The flows from Japan are characterized by a few peaks in the years 2000, 2003, 2006 and 2009. It is interesting to be stated that in these years in the Netherlands the number of the so called “mailbox companies” has risen. A “mailbox company” or also called a “shell company” is a company which does not possess any significant assets, nor it does have any economic activity. These companies usually have only a post adress in the host country, but they serve as a port for money transactions of other companies (Financial Crimes Enforcement Network, 2006). They are usually associated with tax avoidance. Therefore for the peaks in the FDI flows from Japan might have contributed also the preferable taxation regime of the EU country. If we look at the development of the FDI flows from the USA and the development of the tax rate in the Netherlands an explicit relationship cannot be found. Although, if we look at Figure 2, originally presented in the article of van Dijk (2006), we see that in the years 2000-2001 and 2006 until 2007 there is also increase in the number of “mailbox companies” registered in the Netherlands. The same peaks we observe on Figure 1 in the development of the FDI flows from the US into the Netherlands. This leads to the conclusion that a lot of the FDI in the country is in result of the “tax exemptions” offered by the country.
15 change in the law dealing with tax exemptions, specifically change in the percentage of withholding tax on dividends, in 2008, which was enforced since 2009. This makes the tax regime even more preferable and in the same time enhances the attractiveness of the country for investors. The change states that the withholding tax for multinational companies would be reduced to 5% of the dividends, compared to 15% for a domestic company. That means that if the home country of the parent company has signed a tax treaty with Luxembourg this withholding tax would be 0%. In Luxembourg, as well as in the Netherlands, the development of the statutory corporate tax rate cannot be compared to the trend of the FDI flows, because of the existence of the tax exemptions, which makes the two countries tax havens.
The third regarded as tax haven country, is Cyprus. After the association to the European Union the corporate tax rate in the country is reduced to 10% and it remains so until the end of the analyzed period in 2010. The first movement to becoming a tax haven Cyprus has made in 2002, when the tax rate is cut to 15%. With this reduction we see that in the same year – 2002, the FDI flows originating from the USA have jumped. They remain relatively high until 2005 and after that there is a slight downturn after which the FDI flows remain on almost the same amount. There is a lot of missing data about the FDI flows from Canada and Japan; however, we see that just in the same year – 2002, there is a serious increase in the investment flows. It could be concluded on the basis of the described trends that a relationship between them exists. Such a straight relationship is not found between the FDI flows and corporate tax in the other two tax havens, because the tax regime includes different treatment of foreign and home companies, while in Cyprus the corporate tax rate holds for both foreign and home owned firms.
The graphs and the additional information about any changes in tax regimes in the three tax havens give solid evidence that the preferences which hold for foreign owned companies in the Netherlands, Luxembourg and Cyprus are attractive for inward FDI. This fact, which is obvious of the Figures, is confirmed once again after the estimation of the gravity equation in Section 4. The obtained coefficient is positive which is also my expectation based on the data at first “glance”.
16 Firstly, looking at Figure 5, where the FDI flows development and the statutory corporate tax rate are presented, we see that the investment activities coming from Japan and Canada are being stable during the whole period. There is a slight increase in 2004 in the investment from Japan into Austria. Another slight peak in the inward FDI trend of Japan is in 2008. Looking at the tax rate we see that there has not been any change, which lead to the conclusion that the increase is not due to the relationship between taxes and FDI. Actually, the rise in the investments in 2008 is believed to be due to the foreign direct investment of Japan Tobacco in Austria Tobacco in 2007. The trend of the FDI flows originating from the USA does not seem to be influenced by any change in the corporate tax rate. It is quite stable until 2005 with a small peak around 2003. In 2006 and 2008 took place two enormous downfalls in the FDI flows from the USA. This could be explained by the fluctuations of the exchange rate dollar/euro. In 2007 the investments from the USA has sky-rocketed and the US is stated to be the second largest investor in the country after Italy. This increased interest in the country is believed to be because of the strategic geographic location of the country – close to the Central and East European countries. Most of the companies which entered the Austrian market in 2007 have established their headquarters in the country because of its closeness to East Europe.
17 extremely negative.” (De Beule and Van Den Bulcke (2010): p.4). This could be a useful explanation for the observed FDI activity. Also according to the Columbia FDI profile of Belgium (De Beule and Van Den Bulcke (2010)) the number of greenfield investments and M&A was around 300 in the years 2005 and 2007 and it has declined to 250 in 2008 and at lowest 224 in 2009, when we see from the graph is the bottom.
It is very interesting to follow the trend lines of the graphs in Figure 7, where we see that the decline in the corporate tax rate in France resembles the increase in the investment activities of the three partner countries. All three are rising since 2000 and peaked around 2001-2003, when the tax rate has fallen down to 35%. In 2003 the US FDI flows have slightly decreased, probably due to the aftermath of the Dot-com crisis. Since 2004 to 2006 there is small reduction in the French corporate tax rate and in the same time the FDI flows from US and Japan has also increased. The Canadian investment has slightly different development. There is a decline in 2007, although in a 2007 Report on Foreign Direct Investment in France, published by the Invest in France Agency is stated that there is an increase by 3% in the FDI originating from Canada. A possible explanation is that the French investment in Canada has increased even more which would lead to the negative number in the data tables, because the data represents net foreign direct investment flows. Since 2006 there was no change in the corporate tax rate but the volume of the investment has become smaller due to the financial crisis. This trend in the end of the period is also present in all of the countries.
18 Portugal is the other country which performs badly in attracting FDI into the country. As we can see from the graph provided in the Appendix the volume of investments of all three sending countries is quite small compared to the other analyzed countries. The change in taxation is also very small and it has no relation to the tendency of FDI flows. There are only two peaks in the graph in the investment flows from Canada in 2003 and 2006 respectively. No reasonable explanation could be found for them.
The last country in this group is Finland. It is obvious from the graphs included in the Appendix (Figure 10) that tax treatment is no driving force of the FDI activities in the country. The tax change in 2005 is moderate, only 3% and it does not contribute for any change in investment. Only FDI flows from the USA increased slightly in the same year, but this could not be regarded as any confirmation of relationship between tax and investment. All three lines have similar development in the end of the period which resembles the consequences of the global credit crisis.
19 The third group of countries which I analyze consists of Czech Republic, Hungary, Germany and Poland. I have grouped the four of them because they are applying relatively low corporate tax rate. Three of the countries are also new members of the EU, which makes them similar in economic and political environment and development.
First, the Czech Republic is characterized by smooth decrease in the corporate tax rate during the whole period. In 1999 it is 35% and in 2010 19%. In the year 2000 we observe an increase in the inward FDI from all three sending countries. That corresponds to a reduction in the corporate tax rate from 35% to 31%. After 2004 we see that there is increase in the FDI inflows from Canada and Japan which corresponds to a change in tax rate. It is, of course, due also to the fact that the Czech Republic joined the EU in 2004 which has increased the trust in the country and has attracted more investment. The volume of FDI peaked in 2007 and then breaks down in 2008 as a result of the global financial crisis. In 2009 the investment flows in the country originating from the USA recover and peak again, which is followed by another decrease in 2010.
Poland is considered to be the best performer in the field of attracting FDI among all Central and East European (CEE) countries, members of the EU. In fact the three CEE analyzed countries take first, second and third place. As a result of the accession in the EU the corporate tax rate is reduced to 19% and it remains the same until the end of the analyzed period. Both the accession and lower tax rate attract more FDI in the country which is obvious of the trends on Figure 12. Despite the fluctuations in the trend line of the USA FDI flows, the volume of the flows is considerably higher than in the years before 2004. This could be a reason to believe that in the case of Poland the relationship tax rate – inward FDI exists.
Looking into Hungary we see that according to the graphs there is no explicit relationship between the two analyzed parameters. The FDI inflow from all three sending countries has the same development until 2006 and it is not influenced by the fluctuations of the corporate tax rate. Since 2006 there is a sharp increase in FDI inflows from Canada and the United States. The reason for that is the accountability of Special purpose entities, earlier regarded also as “mailbox” or “shell” companies.
20 boom in the technology sector and we see that investments both from Japan and Canada rise since 2002, when the tax rate is decreased from 42% to 26%. Moreover there is also a peak of Japanese FDI in 2004 when a change in the German Corporation Tax Act encouraged companies to transform loans to their affiliates into equity capital. Again both Japan and Canada have peaks of FDI in 2008 when the corporate tax rate in Germany was decreased one more time with more than 10%, from 26% to above 15%. Up to here we can conclude that for Germany a close relationship between taxation and FDI flows from Canada and Japan exists and the evidence is found in the development of the two parameters during the period. On the other hand we can state that between FDI flows from USA and the taxation regime of multinationals in Germany a relationship does not exist. FDI flows have very dynamic development with two major falls in 2004 and 2008, which are due to the bursts of the two crises the Dot-com crisis in the yearly 2000s and the financial crisis of the recent years.
Although the graphs of Hungary, Czech Republic and Poland do not show explicit relationship between FDI flows and taxes, there are indications for this. Evidence for this give also the sensitivity analyses (results shown in Table 2, Appendix 2) which lead to the conclusion that for these countries corporate taxes have the expected negative effect. This is also the finding of Hansson and Olofsdotter (2010), who make the conclusion that the tax differentials in the periphery countries of the EU influence to a higher extent the volume of inward FDI. For Germany, we can conclude that the expected relationship between corporate tax rate and FDI inflows do exist. It is interesting to point out, that in the group of low-tax countries there are signs of the negative dependence between the two parameters, which is indicating that in fact corporate taxation is more important as additional motive for the decision where to invest, but it is not main determinant of FDI flows.
The in-depth look in the data leads to the conclusion that statutory corporate tax rate could support the location decision of MNEs, but there is no explicit relationship between the two parameters found, meaning that taxes are not detrimental to FDI. Empirical evidence for this is sought in the next section.
IV. Research methodology
21 taxes and tax havens. Moreover, the robustness of the results is checked by including a few control variables, namely annual wages, government investment as a proxy for infrastructure, gdp per capita and political stability of the host countries. Moreover, sensitivity analyses are included for two groups of countries – low tax countries including also the countries tax havens and high tax countries including tax havens as well.
Furthermore, three hypotheses are tested for the significance of tax and hav variables. The first hypothesis is whether the sign of β5 is negative and significant and the second hypothesis is whether the sign of β6 is positive and significant. The two hypotheses are tested on all three levels of significance – 10%, 5%, and 1%. A third joint hypothesis for the joint significance of the two variables is also conducted. Each of the hypotheses consists of null and alternative hypothesis. The first one, for the significance of β5 looks as follows: Ho is β5=0 and H1: β5<0. The hypothesis about β6 is of the kind: Ho: β6=0 and H1: β6>0. The third hypothesis states that Ho: both coefficients are zero, i.e. insignificant and the alternative H1: at least one of the coefficients is different from zero.
The relevant articles dealing with the topic also estimate the gravity equation, but different estimation techniques are used. Wolff (2007) considers the use of two different models – the Tobit model and the Probit model. He decides on using the Probit model because it is less restrictive. Hansson and Olofsdotter (2010) use the Heckman estimation technique which includes two-stages. On the first stage a correction procedure selection of the sample is predicted and on the second stage it is used to adjust the OLS estimates for the selection bias. For the estimation of my panel, which is with dimension 13x12x3, meaning thirteen receiving countries and three sending countries analyzed for twelve years I use the fixed-effects estimation to find out what would be the effect of higher taxes on the FDI flows. With the help of the between estimator I can capture the effect of preferable taxation on FDI flows, too. Fixed-effects estimation is the most suitable alternative because after performing the Hausman test for random-effects, which tests the consistency of the coefficients, they turn out to be inconsistent within this model. The fixed-effects is better technique for estimating panel data than OLS, which is used by Hansson and Olofsdotter (2010). I do not consider the Probit model as appropriate for my estimation as it is mostly suitable for binary outcome models, which is not the case. My econometric model is defined for the following equation:
22 For the estimation of panel data there are other methods which could be used. The pooled least squares model is one of them, which basically repeats the OLS estimation. In this model all the data is pooled together and no individual differences are allowed, which does not allow for different coefficients, too. However, this model is rejecting the character of the data, panel data, which is why the cluster-robust standard error estimation is used, where the assumption of zero correlation over time and individuals is relaxed and the possibility of heteroskedasticity is also allowed. Another appropriate estimation technique for this panel is the random-effects model. This model is based on the Generalized Least Squares estimation. The GLS is useful in this specific research because when a regression is estimated on the basis of panel data the OLS is no longer consistent. The random-effects estimation allows for time-invariant variables to have impact on the dependent variable. It is mainly used when the differences across individuals are believed to influence the dependent variable. Under this econometric model it is assumed that the individual countries are random and that all the differences between them are captured in the intercept. The intercept parameter β1 contains also a random element – β1=βi + ui, where ui is the random effects. This model looks like the most appropriate estimation technique for this research but it should be taken into account the possibility of correlation between one or more of the explanatory variables and the error term. If this is the case the coefficients of the random-effects estimation are no longer consistent and estimation by the fixed-effects is the better option. This is checked by performing a Hausman test for random-effects. Both fixed and random effects estimations are performed and although the random-effects are proved to be more efficient and to fit better the data they turn out to be inconsistent (Table 4, Appendix 2). On the other hand the fixed effects are usually inefficient but the coefficients are consistent even if there is correlation between explanatory variables and error term. The fixed-effects estimation does not allow being estimated coefficients of time-invariant variables, which in this research is the variable haven. This type of variables is captured in the intercept, but this would make it impossible to analyze the effect of haven on the FDI flows. In order to solve this problem and analyze the effect of haven even after the fixed-effects estimation, I use the between estimator, which is used to capture the fixed effect of a variable x on the dependent variable when x changes between individuals.
Results
23 million dollars with standard deviation 802185. The lowest GDP rate for the home countries is 825019 and the largest is 1.44e+07 dollars. Respectively for the countries receiving FDI flows the numbers are 9173 and 3058645 million dollars. The average distance between the countries is 7490,795 km as the countries which are closest to each other are at 5425 km distance and these which have the largest distance are on exactly 11156 km from each other. The average value of the net FDI inflows is 1487.979 million dollars and the average tax rate for the EU countries, included in the research is 27, 3451%. The minimum of the net FDI flows is negative number -14466.2 million dollars and the maximum is 108598.4 million dollars. Looking at the tax rates we see that the lowest tax rate is 10% and the highest is 42.3%. All exact coefficients are shown in Table 3.
Table 3 Summary statistics
Variable Obs Mean Std. Dev. Min Max
country 468 7 3,745661 1 13 year 468 2004,5 3,455747 1999 2010 fdiijt 468 1487,979 6660,099 -14466,2 108598,4 gdpit 468 5663101 4810500 825019 1,44E+07 gdpjt 468 666545,2 802185 9173 3058645 taxjt 468 27,3451 7,270202 10 42,3 distance 468 7490,795 1509,195 5425 11156 havj 468 0,230769 0,421776 0 1
Source: STATA summary statistics
24 3557) it is also obvious that the zero hypothesis cannot be rejected which means that a correlation between u_i, Xb exists and the assumption of zero correlation in the random-effects estimation no longer holds3. Fixed-effects estimation should be used. The results of the two estimations are shown in Table 4, below.
Table 4 Results of the estimation dependent Variable: fdi ij
explanatory variables: (1) (2) (3) gdpi 0.000 0.000 (3.62)** (3.53)** gdpj -0.001 0.000 (0.55) (0.11) tax j 8.699 48.418 (0.11) (0.88) distance -0.445 -0.493 (2.12)* (2.38)* hav 0.000 2,201.087 3,320.560 (.) (1.38) (2.30)* Constant 4,192.884 1,750.804 (1.08) (0.69) Observations 459 459 459 Number of country 13 13 13 R-squared 0.05 0.15 0.05
Absolute value of t statistics in parentheses * significant at 5%; ** significant at 1%
Source: STATA output; (1) Fixed-effects estimation; (2) Between estimation of hav; (3) Random-effects estimation
Looking at column (1) the coefficients of the two gdp variables – gdpit and gdpjt are respectively 0.0002285 and -0.0013691. The value of 0.0002285 for gdpit, which is the GDP of the sending country indicates that, if other things are held equal, a dollar increase in GDP would be related to 0.0002285 dollars increase in FDI flows outflowing of this country, i.e. a million dollar increase in GDP corresponds to an expected increase of 228, 5 dollar increase of investments into other countries. This coefficient is significant on the 1% significance level, which we see from the p-value = 0,0004. Looking this fact from an economic perspective could be concluded that the bigger the country the more it invests into other countries. This finding is in line with a stylized fact about FDI, according to Barba Navaretti and Venables (2004), who state that the most part of FDI is originating from advanced countries and it is flowing into advanced countries. This is true for my set of countries as for
3 Results of Hausman test shown in, Table 4, Appendix 2 4
25 sending countries are regarded the US, Japan and Canada. The gdpjt coefficient is -0.0013691, but it has p-value= 0,579, which indicates that the coefficients is insignificant. Another stylized fact is that in the world is predominating horizontal FDI (Barba Navaretti and Venables (2004)), which is market seeking, i.e. this coefficient is not in line with this fact. However, the insignificance of the result indicates that in a broader set of countries it would probably be reversed.
The distance variable has a negative coefficient, which means that between distance and FDI flows exists negative relationship. It means that if two countries are more distant the FDI flows between them would decrease, literally, 1 km increase in distance leads to -0.4453295 dollars decrease in the investment flows between the countries, other things being equal. This is exactly what the gravity framework theory predicts about the international trade flows, which in this research applies for the investment flows. It is stated that the more distant the countries the smaller the flows and vice versa. Countries would invest more into these which are closer to them. The coefficient is in line with the predictions of the theory and moreover it is significant at the 5% significance level.
The next coefficient shown in Table 4 is the one of the variable TAXjt. It takes the value of 8.699017. This result does not confirm the predictions of the economic theory. It shows that there is a positive relationship between higher tax rates and inward foreign investment for the analyzed set of countries. It is highly insignificant, though, t-value equals 0,11, which indicates that if in further research broader set of countries is taken the results might present another sign of the coefficient, but still for the observed EU countries the higher taxes lead to more investment from US, Japan and Canada.
26 As it was described previously three hypotheses are tested in this research. The first one is about the significance of β5, which is tax; the second one for the significance of β6, hav, and the third is a joint hypothesis test for the joint significance of the two parameters.
For the first test Ho is β5=0 and H1: β5<0. I use the p-value to test the hypothesis whether the coefficient of β5 is significant. The p-value is to be seen in Table 3, Appendix 2, p-value = 0.972, which shows that at each statistical significance level (1%, 5%, and 10%) the zero hypothesis is not rejected and the coefficient is insignificant, which was also stated above.
The second test is performed for the Ho: β6=0 and H1: β6<0. This is the hypothesis test for the significance of β6. We know that the p-value of the coefficient is 0,196. We use this value to test the hypothesis on all significance levels. Ho hypothesis cannot be rejected on any significance level. This means that the coefficient of the havj variable is insignificant.
For the third joint hypothesis the zero hypothesis looks as follows Ho: β5=β6=0 and the alternative is H1: β5≠0 and/or β6≠0. As both coefficients turned out to be insignificant it is already clear that the zero hypothesis for the joint significance would not be rejected on any significance level.
Robustness checks
In order to check the robustness of the obtained results a few robustness checks and sensitivity analyses are performed. First of all, a regression is estimated on all countries which have corporate tax rates of 21, 85% or below and the tax haven countries. The purpose of the estimation is to analyze whether the coefficients of the variables in this sample would change. In other words it is analyzed whether in a sample of countries with relatively low taxation and countries tax havens5 the determinants would affect FDI in the same way. The results are shown in Table 2, Appendix 2, column (1) and (1a). The coefficients of gdpi and distance remain significant, respectively on 1% and 5% significance levels. The other coefficients remain almost unchanged and insignificant, except the taxj coefficient. Its sign is no longer positive, but the coefficient is insignificant. This means that the coefficient is not robust and if other factors are present taxes would matter for FDI inflows. In columns (2) and (2a) of Table 2 are shown the results of the estimation of the gravity model for the same limited set of
27 countries, including a few control variables6 – annual wages, government investments as a proxy for infrastructure, gdp per capita of the host country and political stability. The results show that after controlling for these variables, gdpi and distance become insignificant. The significance of hav is slightly improved, but the coefficient remains insignificant. Tax remains almost unchanged, negative and insignificant. Another sensitivity analysis is performed for a sample including the high tax countries and the countries tax havens7 (results shown in Table 2, Appendix 2). The coefficient of the home country gdp (column 3) remains significant on the 1% level, but distance loses its significance for this sample. The coefficient of taxes (column 3) turns negative, but insignificant. It is interesting that in both sensitivity analyses tax have negative sign as it is predicted by the theory. A possible explanation is that FDI inflows are more sensitive to corporate taxes when the choice of locations is limited. The coefficient of hav is barely changed and remains positive and insignificant (column 3a). When including the control variables (column 4) the results are quite alike. The significance of the home country gdp is slightly decreased and it is significant on the 5% level. The significance of taxes is slightly improved as well as the significance of hav (column 4a), but both coefficients are still insignificant. The sensitivity analyses lead to the conclusion that corporate tax burdens and tax havens affect similarly both groups of countries.
A regression is estimated on the full set of countries with control for the same set of variables as described above and the results are presented in Table 1, columns (2) and (2a). According to them the GDP of the home country still remains significant on the 1% level. However, distance is no longer significant. The coefficient of taxj as well as hav is also affected by the control variables, and their signs are reversed, but the coefficients are insignificant.
The robustness checks proceed with the inclusion of each control variable apart. In column (3) of Table 1 (Appendix 2) the model is estimated with control for annual wages. The result for gdpi and distance remain significant. The other coefficients also remain almost unchanged, except the hav variable, its significance is slightly improved. When controlling for the gdp per capita of a host country, hav changes again, and the coefficient becomes negative. The significance of tax is quite higher compared to the basic estimation. The other variables seem not to be affected by the gdp per capita (column (4) and (4a), Table 1). In column (5) a
6 Data on control variables is described in Appendix 3 7
28 robustness check is performed with control for political stability. Controlling for this variable does not change the coefficients of tax and hav, which remain positive and insignificant. In the last column it is controlled for government investment as a proxy for infrastructure. Taxj remains insignificant, but the significance of hav is improved. The coefficient of gdpi is also unaffected and remains significant, but the coefficient of distance loses its significance. These additional estimations show that the obtained coefficients are not robust and in the most cases they are affected by the control variables.
All these results give empirical evidence for the conclusion made previously. Corporate taxes are not detrimental for FDI. That is easily seen by the fact that the coefficient of the variable changes in combination with other factors influencing the decision. However, the sensitivity analyses show that when the choice of locations is limited and the corporate tax rates are very close to each other, FDI inflows are more sensitive to tax burdens.
29 not have the expected sign. Most of the analyzed countries are developed countries with higher labor costs, which are discouraging for efficiency seeking FDI, and only small part of them, namely Hungary, Poland and Czech Republic are offering lower labor costs and attracting vertical investments. The fact that according to the results tax havens attract more FDI, which was also the prediction of the economic theory, suggest that in the future more countries would lower their tax rates, or would introduce another instruments for preferable taxation as an additional stimulus of FDI inflows. This effect would be supported also by the fact that the economic world is in a crisis and investment initiatives would be stimulated in order to stabilize the economy. Despite the expectations that tax competition would become more severe, zero tax rates would not be reached because taxes being an additional motive for FDI cannot compensate the lack of other important economic factors.
V. Conclusion
I have investigated in this research the relationship between the corporate tax rates and FDI inflows in thirteen European countries. Moreover, the effect of tax haven countries was analyzed. Two research questions were specified, whether high corporate taxes discourage FDI inflows and whether the countries which are tax havens, or have a preferable taxation regime attract more FDI inflows. In the first case, a negative relationship was expected and in the latter a positive one.
30 former case the significance of taxj is slightly improved and hav loses any significance at all, while in the latter taxj has hardly changed and hav has quite improved significance. The control for political stability does not indicate any difference in the results. The inclusion of gdp per capita of the host country increases the significance of tax, but hav turns negative. Two sensitivity analyses, for low- and high-tax countries were also conducted, which show that the effect of taxes and tax havens is similar for both groups, respectively negative and positive.
The two coefficients of the variables of interest – taxes and tax havens are insignificant, but they point the direction for further research. The insignificance of the positive coefficient of taxes indicates that the analyzed relationship is not present for the specific set of countries, but for a broader set of home and host countries as well as longer period of time the results would probably be reversed. Although insignificant, the tax havens coefficient points the direction of the relationship with FDI, which is positive.
The empirical analysis performed so far reflects the economic theory as well as the expectations for the relationship made on the basis of the data in section 3. The overall conclusion based on the theoretical and empirical analysis is that corporate taxes are supporting the location decision but cannot be detrimental for FDI inflows. As far as tax havens are concerned, they could also affect FDI inflows in a positive way, but a country just offering low or no taxation cannot compensate the lack of other economic factors.
31 on these two types apart. Despite the few points of critisism the paper is giving important insight on the effect of tax havens on FDI, which is not analyzed so far.
32 VI. References
Anderson, James E., “The Gravity Model”, 2010, NBER Working Papers, Working Paper 16576; http://www.nber.org/papers/w16576
Anderson, James E., Dec 2010, “The Gravity Model”, Section 1 – Traditional Gravity, NBER Working Papers
Antonakakis, Nikolas and Gabriele Tondl, January 2012, “Do determinants of FDI in developing countries differ among OECD investors? Insights from Bayesian Model Averaging”, Institute for European Integration, Discussion paper No1/12
Austrian Business Agency, “Austria the Bridge to New Markets”, 2010, p. 11 Multinationals choose Austria:
http://investinaustria.at/uploads/EasternEurope_2010_10702_EN.pdf
Bellak, Christian and Susanne Mayer, Inward FDI in Austria and its policy context, 2010, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
Bénassy-Quéré, Agnès, Lionel Fontagné, and Amina Lahrèche-Révil, 2004, “How does FDI react to corporate taxation?” CEPII
Bevan, Alan A. And Estrin, Saul, 2004, “The Determinents of Foreign Direct Investment into European Transition Economies”, Journal of Comparative Economics 32 (2004) 775–787
Blanco, Luisa and Rogers, Cynthia, “Are Tax Havens Good Neighbors? AN LDC Perspective”, SSRN Working Papers, 2009; http://ssrn.com/abstract=1432630
Blanco, Luisa and Rogers, Cynthia, “Competition between Tax Havens: Does Proximity matter?”, International Trade Journal, 2011
Brenton, Paul, Di Mauro, Francesca and Luecke, Matthias, 1999. "Economic Integration and FDI: An Empirical Analysis of Foreign Investment in the EU and in Central and Eastern Europe," Empirica, Springer, vol. 26(2), pages 95-121, June.
33 De Beule, Filip and Daniel Van Den Bulcke, Inward FDI in Belgium and its policy context, 2010, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
De Mooij, Ruud A and Sjef Ederveen, “Taxation and Foreign Direct Investment: A Synthesis of Empirical Research”, 2001, CESifo Working Paper No 588, Center for Economic Studies & Ifo Institute for Economic Research
Desai, Mihir A, C. Fritz Foley and James R. Hines Jr., ”Do Tax Havens Divert Economic Activity?”, Economic Letter 90 (2006) 219-224
Feenstra, Robert C., Advanced International Trade: Theory and Evidence (2002), Chapter 11: Multinationals and Organization of the Firm
Financial Crimes Enforcement Network, 2006, “The Role of Domestic Shell Companies in Financial Crime and Money Laundering: Limited Liability Companies”-> http://www.fincen.gov/news_room/rp/files/LLCAssessment_FINAL.pdf
Gordon , Roger H. and James R. Hines Jr., “International Taxation”, 2002, NBER Working papers, Working Paper 8854; http://www.nber.org/papers/w8854
Hanson, Asa and Karin Olofsdotter, 2010, “Tax Differences and Foreign Direct Investment in the EU 27”
Hill, Griffiths and Lim, 2012, “Principles of Econometrics”, Chapter 15: Panel Data Models
Hines, James R. Jr., “Tax Havens”, 2007, University of Michigan and NBER
Jost, Thomas, Inward FDI in Germany and its policy context, 2010, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
Jost, Thomas, Inward FDI in Germany and its policy context: Update 2011, 2011, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
34 Mutinelli, Marco and Lucia Piscitello, Inward FDI in Italy and its policy context, 2011, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
Navaretti, Giorgio Barba and Anthony J. Venables, 2004, 10 – Policy implications and Effects, 10.1.1 Tax Policies, 1 – Facts and Issues, 1.2. The facts: Empirical Overview – Fact 2 FDI originates predominantly from advanced countries
OECD Policy Brief, February 2008
Rose, Andrew K. and Mark M. Spiegel, 2007, “Offshore Financial Centers: Parasites or Symbionts?”, Royal Economic Society
Steinbock, Dan , Inward FDI in Finland and its policy context, 2011, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
Thanyakhan, Sutana, “The Determinants of FDI and FPI in Thailand: A Gravity Model Analysis”, 2008, Lincoln University
The European Banking Federation, Report on Banking Secrecy, 2004, Anti-Fraud and Anti-Money Laundering Committee & Fiscal Committee, Brussels - April 2004
Van Dijk, Michiel, Francis Weyzig and Richard Murphy, Nov. 2006, “The Netherlands: A Tax Haven?”, SOMO report (Stichting Onderzoek Multinationale Ondernemingen, Centre for Research on Multinational Corporations)
Wolff, Guntram B., 2007, “Foreign Direct Investment in the Enlarged EU: Do Taxes Matter and to What Extent?”, Open Econ Rev (2007) 18:327–346
Zimny, Zbigniew, Inward FDI in Poland and its policy context, 2010, Columbia FDI Profiles Country profiles of inward and outward foreign direct investment, issued by the Vale Columbia Center on Sustainable International Investment
Internet sources:
35
http://www.cs-avocats.lu/legal-news/corporate_and_tax/luxembourg-2009-tax-reform-introduced-law-16-december-2008/ Country Tax Haven Profiles:
http://www.taxhavens.biz/european_tax_havens/tax_haven_cyprus/ Country Tax Haven Profiles:
http://www.taxhavens.biz/european_tax_havens/tax_haven_luxembourg/ KPMG, Country Tax Profiles,
http://www.kpmg.com/global/en/whatwedo/tax/pages/eu-country-profiles.aspx Tax Justice Network Reports: Jurisdiction Report – Belgium, 2009:
http://www.secrecyjurisdictions.com/Archive2009/Jurisdiction%20Reports/Belgium.pdf Tax Justice Network Reports: Jurisdiction Report – Cyprus, 2009:
http://www.secrecyjurisdictions.com/Archive2009/Jurisdiction%20Reports/Cyprus.pdf Tax Justice Network Reports: Jurisdiction Report – Germany, 2011:
http://www.secrecyjurisdictions.com/PDF/Germany.pdf
Tax Justice Network Reports: Jurisdiction Report – Hungary, 2009:
http://www.secrecyjurisdictions.com/Archive2009/Jurisdiction%20Reports/Hungary.pdf Tax Justice Network Reports: Jurisdiction Report – Italy, 2011:
http://www.secrecyjurisdictions.com/PDF/Italy.pdf
Tax Justice Network Reports: Jurisdiction Report – Luxembourg, 2009:
http://www.secrecyjurisdictions.com/Archive2009/Jurisdiction%20Reports/Luxembourg.pdf Tax Justice Network Reports: Jurisdiction Report – Netherlands, 2009:
http://www.secrecyjurisdictions.com/Archive2009/Jurisdiction%20Reports/Netherlands.pdf Data Sources:
Cyprus FDI data in millions of euro:
http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/dataset?p_product_code =TGIBC410
36 Data on annual wages: Eurostat:
http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=earn_nt_net&lang=en Data on distance: http://www.cepii.fr/anglaisgraph/bdd/distances.htm Data on government investment in % of GDP: Eurostat:
http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&init=1&plugin=0&language=en&p code=tsdec210
Data on government investment in million us dollars: own calculations Data on political stability: The World Bank ->
info.worldbank.org/governance/wgi/pdf/PRS.xls
Data on GDP per capita: Unctad Statistics Database -> unctadstat.unctad.org -> Economic Trends/National Accounts -> Nominal and real GDP, total and per capita, annual, 1970-2010
Data on taxes:
http://www.oecd.org/document/60/0,3746,en_2649_34533_1942460_1_1_1_1,00.html
FDI inflows data in million dollars: stats.oecd.org -> data by themes -> globalization -> FDI investment statistics -> FDI flows by partner country
37
Appendix 1 – Tables and Figures
a. Statutory corporate tax rate and FDI flows in the Netherlands, Luxembourg, Cyprus Figure 1
Source: Figure created by the author using data of the OECD database -20000 -15000 -10000 -5000 0 5000 10000 15000 20000 25000
FDI flows into the Netherlands
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
38 Figure 2
39 Figure 3
Source: Figure created by the author using data of the OECD database -20000 0 20000 40000 60000 80000 100000 120000
FDI flows into Luxembourg
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
40 Figure 4
Source: Figure created by the author using data of the OECD database -100 -50 0 50 100 150 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
FDI flows into Cyprus
Canada Japan the US 0,0 5,0 10,0 15,0 20,0 25,0 30,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
41 b. Statutory corporate tax rate and FDI flows of Austria, Belgium, Finland, France, Italy and Portugal
Figure 5
Source: Figure created by the author using data of the OECD database -3000 -2000 -1000 0 1000 2000 3000 4000 5000
FDI flows into Austria
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
42 Figure 6
Source: Figure created by the author using data of the OECD database -6000 -4000 -2000 0 2000 4000 6000 8000 10000 12000 14000 16000
FDI flows into Belgium
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
43 Figure 7
Source: Figure created by the author using data of the OECD database -6000 -4000 -2000 0 2000 4000 6000 8000 10000 12000 14000
FDI flows into France
Canada Japan United States 31,0 32,0 33,0 34,0 35,0 36,0 37,0 38,0 39,0 40,0 41,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
44 Figure 8
Source: Figure created by the author using data of the OECD database -500 0 500 1000 1500 2000 2500 3000 3500
FDI flows into Italy
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
45 Figure 9
Source: Figure created by the author using data of the OECD database -1000 0 1000 2000 3000 4000 5000 6000 7000 8000
FDI flows into Portugal
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
46 Figure 10
Source: Figure created by the author using data of the OECD database -1200 -1000 -800 -600 -400 -200 0 200 400 600 800 1000
FDI flows into Finland
47 c. Statutory corporate tax rate and FDI flows of Czech Republic, Poland, Hungary and
Germany Figure 11
Source: Figure created by the author using data of the OECD database -600 -400 -200 0 200 400 600 800
FDI flows into the Czech Republic
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0
Corporate tax rate development
48 Figure 12
Source: Figure created by the author using data of the OECD database -400 -200 0 200 400 600 800 1000 1200 1400 1600
FDI flows into Poland
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
49 Figure 13
Source: Figure created by the author using data of the OECD database -15000 -10000 -5000 0 5000 10000 15000 20000 25000
FDI flows into Hungary
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Corporate tax rate development
50 Figure 14
Source: Figure created by the author using data of the OECD database -8000 -6000 -4000 -2000 0 2000 4000 6000 8000 10000
FDI flows into Germany
Canada Japan United States 0,0 5,0 10,0 15,0 20,0 25,0 30,0 35,0 40,0 45,0
Corporate tax rate development
51
Appendix 2 Estimation Results
Table 1 Estimation results; Source: STATA output
Absolute value of t statistics in parentheses * significant at 5%; ** significant at 1% dependent variable: fdi ij
independent variables: (1) (1a) (2) (2a) (3) (3a) (4) (4a) (5) (5a) (6) (6a)
52
