Specialization: International Financial Management
Foreign Bank Entry in Central and Eastern Europe: A
regulatory perspective
Faculty of Economics and Business University of Groningen
Address: Nettelbosje 2
9747 AD Groningen, the Netherlands
Name: D. Beunk Student Number: 1322095 Email Adress: d.beunk@student.rug.nl
Eastern Europe started to develop rapidly. This development was noticed by foreign banks and as a result, they started to expand to these countries. What are the motives for foreign bank entry in this region and to what extent is the regulatory environment influential? Using a pooled panel dataset and a cross-section analysis, we discover that the main motives are following the client and striving for new business opportunities. However, if a Regulatory Environment (RE) interaction variable is included and a Moderated Regression Analysis is completed, we perceive that the positive effects of the main motives on Foreign Bank FDI are diminished. Extreme differences and similarities between the host country and home country’s Regulatory Environment variable increases the incentive to expand to the host country. These results are somewhat surprising but can be interpreted in the following way:
1. INTRODUCTION ... 5
2. LITERATURE REVIEW ... 9
2.1 FOLLOW THE CLIENT... 10
2.2 BUSINESS OPPORTUNITIES... 12
2.3. REGULATIONS... 16
2.4 REGULATORY INTERACTION EFFECTS... 22
2.5 REGULATIONS HOME COUNTRY... 25
3. EMPIRICAL MODEL... 28
4. METHODOLOGY ... 31
5. THE DATA ... 34
5.1 FOREIGN BANK ENTRY (FDI) ... 34
5.2 FDI STOCK (FOLLOW THE CLIENT HYPOTHESIS) ... 34
5.3 GROSS DOMESTIC PRODUCT PER CAPITA (BUSINESS OPPORTUNITIES) ... 35
5.4 EU MEMBERSHIP (BUSINESS OPPORTUNITIES) ... 35
5.5 REGULATORY ENVIRONMENT (REGULATORY INDICATORS AND DEGREE OF OPENNESS)... 36
5.7 GEOGRAPHIC DISTANCE... 37
5.8 REGULATORY ENVIRONMENT HOME COUNTRY... 37
CORRELATION MATRIX TESTED VARIABLES... 38
6. RESULTS & DISCUSSION ... 39
7. ANALYSIS... 47
7.1 HIGH FDI STOCKS PER CAPITA AND HIGH GDP PER CAPITA... 47
7.1.1. Czech Republic... 48
7.1.2. Estonia ... 49
7.1.3. Hungary ... 50
7.1.4. Croatia ... 51
7.1.5. Slovenia... 52
7.2 MID-HIGH FDI STOCK AND MEDIUM GDP PER CAPITA... 53
7.2.1. Lithuania... 54
7.2.2. Slovakia... 55
7.2.3. Poland... 55
7.2.4. Latvia ... 56
7.3 MID LOW FDI STOCK AND/OR LOW GDP PER CAPITA... 57
8. CONCLUSION ... 60
9. REFERENCES ... 61
10. APPENDIX ... 65
10.1. APPENDIX A ... 65
10.2 APPENDIX B: DATA HIGH FDI; HIGH GDP CEE COUNTRIES... 68
10.3 APPENDIX C: DATA HIGH-MID FDI; MID GDP CEE COUNTRIES... 70
10.4 APPENDIX D: DATA MID-LOW FDI; LOW GDP CEE COUNTRIES... 72
1. Introduction
After the fall of the communist system, the banking systems in Central and Eastern Europe (CEE) had to change from a mono bank system (in which the state was the sole owner of the banks) towards a system which was based on more capitalistic basic ideas in which banks were private entities and could compete with each other. This transition period was characterized by several approaches. Some transition countries used the gradual approach, which meant that the banking system would first be decentralized and afterwards privatized. Other transition countries chose the shock effect approach, which meant that right after the fall of the communist regime, the banks where rapidly privatized and had to deal with the problems that occurred with this method. After a period of turmoil and destabilization in which no foreign bank presence was allowed (Soussa (2004)), the CEE banking sectors opened up their economies for foreign banking investment in their countries. As stated by Mathiesen and Roldos (2001), this implied that a large share of foreign companies entered the CEE region when the authorities began to actively pursue a policy of privatization of their developing banking systems by means of foreign direct investment (FDI). For the foreign banks this was a good time to enter the CEE region, because it showed significant economic growth implying the region was beginning to show potential in which the foreign banks were interested. Many theories exist why foreign banks desired to enter the CEE region. Two typical reasons, which are strongly motivated in the literature, are ‘following the client’ and locating business opportunities. Unfortunately, there has not been written a lot in the literature about the extent to which regulations are a factor in this foreign entry decision. Does the type of regulatory framework in the CEE country have an effect on foreign bank entry? Or does the regulatory framework of the home country of the foreign bank have an impact on entry as well? Moreover, is the geographic location of the CEE country relative to the home country a positive or negative factor?
The main problem statement of this thesis will be the following:
This thesis has a rather different approach in comparison to other literature in this field. In order to get a complete picture of the expansionary decisions to CEE by foreign banks, conventional determinants of foreign bank entry will be tested. In addition, there will be an extensive analysis of the regulatory framework of the selected CEE countries. The CEE countries which will be investigated are the following (in alphabetic order): Albania, Bosnia Herzegovina, Belarus, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Russia, Serbia & Montenegro, Slovakia, Slovenia and the Ukraine.
These seventeen CEE countries form a diverse mix of well performing countries with a high state of potential and lesser performing countries with a dubious state of potential. Examples of well-performing countries in the CEE region are the Czech Republic, Hungary, Poland and Latvia. In these countries, high FDI levels can be expected based on their economic performance. However, the CEE region also knows countries that are not that successful in their transitioning and economic performance. Ill- performing countries in the CEE region are for example, Albania, Bosnia, Belarus, Serbia & Montenegro and the Ukraine. These countries have not shown very high economic growth in the transition years (in some countries because of political turmoil) and are therefore expected to have a lower degree of FDI levels.
The home countries from which the banks will expand from are: Austria, Belgium, France, Germany, Greece, Italy, Netherlands, Switzerland, United Kingdom, United States and Sweden. These eleven countries of origin are (except for the United States) Western European countries. . These countries are used because they are one of the main non-bank FDI contributers in the CEE region1. Therefore, it is interesting to see to what extent their banks react on this fact. Furthermore, we will also take into account the extent to which the regulatory environment in the home country differs from the host country’s regulatory environment and the implication this gives on foreign bank entry from the home country. The Western European countries differ heavily in regulatory environments and therefore it is interesting to research to what extent this is a factor in
foreign bank entry.
The data that will be used is of a quantitative nature. Bank FDI data will be provided through the database program Bankscope. Furthermore, country specific data will be provided by databases set up by the International Monetary Fund2, UNCTAD3, Heritage Foundation Database and the European Central Bank. Data on Regulatory Environments on each specific country will be extracted from data sources provided by Kauffmann et al. (1997-2007) under supervision of the World Bank4.
This thesis will take an empirical research approach using several statistical methods to test the collected data. The statistical methods used will be panel data analysis using cross- section regressions. The influence of the regulatory environment on the other determinants will be measured with a Moderated Regression Analysis.
The added value of this thesis is that it will not only incorporate and test the more conventional determinants of foreign bank entry in CEE countries in the form of Follow the Client and Business Opportunities, but it will also test the extent to which the Regulatory Environment is a determinant. Moreover, it will be tested to what extent the Regulatory Environment has an influence on the conventional determinants on foreign bank entry. As a consequent, it will fill the gap in the literature that is concerned with the degree of determination that regulations have on the decision for foreign banks to expand abroad.
This thesis will have the following structure: The next section will describe the main view in literature concerning conventional motives and regulatory implications and gives room for the development of hypotheses. In addition, the basis for the model will be laid in the next section. The subsequent section will describe the model that will be used in the rest of the analysis. Afterwards, data and methodology will be described and an
2World Economic Outlook database (April 2008)
3World Investment Report 2007
2. Literature Review
In the literature, there has been extensive research in the field of foreign bank entry in the developed world. The approach is often single-sided in that the studies focus on one particular aspect of foreign bank entry. For example, on the one hand, Konopielko (1999); Buch (2000); Seth, Nolle and Mohanty (1998), all refer to the economic and business opportunities motives of foreign bank entry. On the other hand, studies by Barth et al.(2001); Kaufmann et al. (2008) have focused on regulations of banks or the regulatory framework of individual countries. In these regulatory articles there is not a clear association with foreign bank entry but this linkage will be established in this thesis. The approach I am intending to use will be based on economic, business opportunities and regulatory motives. Regulatory motives will be tested as a standalone and as an interactional variable. When using these approaches and combining them into one model, a more complete explanation of foreign bank entry in CEE can be given. Moreover, the discussion will also take the situation in the foreign bank’s home country with respect to regulations into account, because these home situations are ignored most of the times. However, one has to remember that the discussion involves bank entry in countries that are often relatively far away from OECD standards and are still not fully developed. As stated before, there is a large amount of literature focusing on the entry determinants of foreign banks in Central and Eastern Europe. In this section, the relevant literature will be discussed and consequently, I will work towards a framework in which the model of determinants of foreign bank entry will be established.
The next motive, which is going to be investigated, is the regulatory motive. There has not been much research on the effect of regulatory frameworks on bank’s entry decisions. For instance, a study that deals with regulations on banks is the article by Barth et al., (2001). In this study the authors have build up a database consisting of regulatory banking measures in several countries. They have constructed a set of best practices from this database, which will be discussed later on. In addition, studies have been performed on the regulatory environment in a country (Kaufmann et al. (2008)). In this study, the authors have selected several indicators, which together comprise the regulatory environment in a country. The database they have constructed includes virtually all countries in the world and gives an indication of the regulatory environment in these countries. This study will also be discussed later on.
The final motive that will be discussed, is the geographic distance between host and home country. Literature, in general, states that a low level of geographical distance between the host and home country has a positive effect on foreign bank entry.
In the next part, a discussion will be initiated concerning the four motives with the underlying determinants that determine the main motive. These underlying determinants are adapted from several articles that performed a similar study.
The discussion will be used towards building hypotheses, which will be tested in the analysis section. These tested hypotheses will be used to support arguments made to analyze the entry decisions of foreign banks in CEE.
2.1 Follow the client
Union, this decision is even less important. This is due to the harmonization of economical frameworks and tends to shift banking markets from national to a single European market.
If we shift our view towards the Central and Eastern European (CEE) region and the Baltic States, the follow the client motive becomes more evident. In these regions, economic welfare has been developing rapidly in the last twenty years after the fall of the communist systems. However, these countries still have a lot of catching up to do to achieve the same economic welfare of the other EU member states. This also expresses itself in the corporate markets in the CEE countries. Businesses are still not fully developed and therefore exhibit not the ‘pull’ effect on foreign banks as their Western European counterparts do. The developments of these businesses are going relatively fast, but especially in the first part of the 1990’s these enterprises were still insignificant in size to be attractive for foreign banks.
In the 1990’s many foreign (Western European) businesses saw the potential of the CEE region in economical terms. Especially the second part of the decade showed strong economic growth. It seemed that the CEE countries were very eager to catch up with the rest of Europe. At this time, many foreign businesses decided to expand towards CEE in order to reap some of the benefits of this economic growth. With the entry of foreign businesses, the CEE countries became important for foreign banks as well. Evidence in the literature is provided by, for example Buch (2000). She states that many foreign banks have build up a relationship with a large (corporate) client in the ‘home’ country. If a large client decides to expand abroad to a region where the bank is not represented, it can occur that the bank decides to follow the client for the simple fact that the client is too valuable to loose to a rival bank. Other studies (Konopielko (1999); Wezel (2004); Focarrelli & Pozollo (2000) also document this follow the client behaviour. As long as there are potential home-clients based in a non- home market, it can be profitable for a bank to expand to this country. Knowing the client’s demands and preferences in services in the home country can translate itself into a relative comparative advantage for the bank, and therefore implying a greater chance for success in the initial years abroad.
allocate larger shares of their lending portfolios to commercial and industrial loans than domestic banks ((Goldberg (1994); Clarke et al. (2003)) One of the reasons for this kind of behaviour in non-home markets is the shying away from small lendings due to organisational diseconomies, which makes relationship lending difficult. (Focarrelli & Pozollo, 2000). Therefore, in the initial years of entry in a foreign (CEE) market the focus of foreign banks is primarily on large home-based clients.
The presence of home-based companies (clients) can be found by looking at the particular FDI stocks in CEE countries. If a country has relatively high (non-bank) FDI stock, than it implies that there is much foreign economic activity in this economy and as a result the country is attractive for banks which are following home clients in CEE economies. (Konopielko, (1999)) This interconnection between a home and host economy in terms of FDI is important. If a home country has a high amount of FDI in the host country, it implies that a large share of home businesses is present in the host economy. Following the notion that a bank follows the client abroad, we can expect that this will have a positive effect on the decision of the bank to go abroad to that particular country as well. This view is consistent with a study performed by Brealey and Kaplanis (1996) that determines that countries with the highest foreign bank presence were those which had the greatest non-bank FDI links. In addition, similar results were obtained by Yamori (1998) and (Wezel (2004); Buch (2000)) for respectively Japanese and German banks.
Considering the evidence in the literature, it can be stated that one of the main factors for banks to move abroad is to follow the client. Following the main argument in the literature, we can state the following hypothesis:
H1: The presence of ‘home-based’ clients in a CEE country will have a positive effect on Foreign Bank entry.
2.2 Business opportunities
Konopielko (1999); Buch (2000)), banks also tend to strive for business opportunities in the host country. Considering the CEE region, we have to acknowledge that there is a very large potential in that region. Not only does every CEE country show significant structural economic growth, there is also a very large potential client base, which is achieving higher economic welfare each year. Claessens et al. (2004) state that foreign banks are attracted to markets with low taxes and high per capita income. In addition, Focarelli & Pozzolo (2000) noticed greater bank entry where the expected rate of economic growth is higher. This makes economic sense because it can predict the middle- to long- term potential of the market, ceteris paribus. As long as developing markets show high sustainable economic growth, it creates a strong pull effect on businesses, including banks. Also, Focarelli & Pozzolo (2000) find that there is a higher foreign bank entry in markets with inefficient capital use in the form of higher average costs, lower net interest rate margins, fewer charge-offs and higher cash flows. Inefficient capital use of domestic banks can create a comparative advantage for foreign banks in the sense that they can achieve higher profits due to efficient capital use. Furthermore, they may be able to offer superior products to CEE clients. According to a study performed by Demirguc- Kunt &Huizinga (2000), foreign banks initially have a higher profitability in developing countries than in developed countries. A main cause for this is that in the developing markets, the domestic banking sector is far less mature and liberalised than in the foreign bank home market. This enables foreign banks to reap certain benefits since the domestic banks tend to be far less efficient than the foreign banks. However, over time, market imperfections erode and domestic banks ‘learn by doing’ and will compete more severely. At that time, foreign banks can offer more sophisticated products but they will be less profitable
home clients towards serving small and medium sized clients (SME), who are located in the host country. Due to technological changes, it is profitable to lend to these local clients (think of data availability, sophisticated computer programs) due to a less visible physical presence in the host country. For example, a foreign bank serving mainly home-based clients can also serve host country SME’ s by means of a small local branch in which representatives from the foreign bank serve their local clients apart from the larger foreign accounts.
However, these local clients need some time to develop themselves in order to become interesting for the foreign banks. This development is parallel to the amount of economic growth in the host country. Therefore, economic growth is an important indicator for the development for new business opportunities considering foreign banks.
Economic growth is reflected in GDP per capita. As stated by Wezel (2004), GDP per capita reflects the countries purchasing power and reveals the potential of the market with respect to consumers. Studies performed by Brealey and Kaplanis (1996), Yamori (1998), and Buch (2000) support this notion. They also find a positive relationship between a high GDP per capita in the host country and banking FDI in the sense that the higher the degree of GDP p.c., the higher the economic welfare is in a country. Because the CEE countries are showing significant economic growth, a rise in GDP can be expected as well. Therefore, GDP per capita can be used a good indicator for the extent of economic welfare in a country. In effect, a relatively high GDP per capita in comparison with other CEE countries will have a pull effect on investors and will contribute to a higher presence of ‘home market companies’ and, consequently, home market banks. By means of the rise of GDP, a higher economic welfare will imply a further demand for banking services. Therefore, many banks take into account the opportunities which lie ahead for them. According to the theoretical evidence stated above, we can set up the following hypothesis:
Several authors ((Cetorelli (2004); Wezel (2004); Buch and Lapp (1998)) have shown the importance of EU membership with respect to business opportunities and consequently higher foreign bank penetration. If a country is an EU member, by definition, it facilitates easier business entry for financial and non-financial businesses and as a consequence the incentive for banks to expand is increased (Wezel, 2004).
EU membership presents disadvantages for the CEE country as well as advantages. For instance, a country that is becoming a member has to subject itself to certain EU standards, which for CEE countries might be difficult to sustain the first period, especially concerning economic standards. However, being subjected to these standards makes the countries also attractive for foreign businesses due to harmonization of laws and a lesser extent of bureaucracy when entering the CEE markets. This implies that entry and adjustment costs are lower in comparison to an economy that does not have an EU status. This also has an effect on bank entry. Especially initial entry costs in the CEE country can be lower. In view of this research, several countries are a member of the EU (since 2004 or 2007) and some are not. Therefore, it is interesting to see what kind of effect this has on foreign banking in EU and non-EU countries. Buch and Lapp (1998) used an EU dummy variable in their empirical research to investigate whether EU membership had a positive effect on financial system development. They concluded that this relation was semi-strongly significant. Cetorelli (2004) used a panel data set in order to test if EU membership led to increased competition in the bank sector. She concluded that EU membership increased competition within a bank sector in an EU country. This evidence was brought forward by the fact that relatively smaller foreign banks entered host EU markets, implying that because of the lower costs of entry and adjustment costs, it became feasible for smaller banks to expand and exploit business opportunities.
Considering the empirical evidence provided by the literature it can be stated that if a CEE country is a member of the EU this will result in a relatively higher amount of foreign bank activity in that particular CEE country.
H3: EU membership of CEE countries has a positive effect on foreign bank entry
2.3. Regulations
In light of a possible expansion to a different country, a bank should take into account the regulatory environment in which it will be operating. After all, this framework decides what is possible for the bank and what is not permitted. Furthermore, it is important to comprehend what the perception is concerning contractual obligations and judicial implications.
In the literature, there has been some interest in regulatory frameworks. The question which arises is what regulatory environments banks perform best in. For instance, Barth et al.(2004) have done intensive research to see which form of bank supervision and regulation works best. In this study, the authors have build up a database consisting of regulatory banking measures in the majority of the world’s countries. This regulatory database is complex and takes into account the majority factors involved in regulatory frameworks. Therefore, this database is too cumbersome to describe in detail. However, the main idea of their research is that they have established a regulatory framework of ‘best practices’ at which a regulator should comply. The most important features of this framework are the following.
Regulators have to build their regulatory framework in a way that facilitates the following:
1. Force accurate information disclosure
2. Empower private-sector corporate control of banks
3. Foster incentives for private agents to exert corporate control.
The authors state that these three practices are most successful to promote bank development, performance and stability.
majority of these banking markets are approaching maturity. However, a side-note has to be made.
According to the article by Talley et al. (1998), CEE banks are far more vulnerable to endogenous and exogenous shocks than their more developed Western European counterparts. Initially, this is because the directives which have been set by the European Union where designed for the fully matured banking market of Western Europe. Because CEE markets are not entirely matured, they might have difficulties with standards set by the EU, especially considering that EU directives are relatively stringent. Furthermore, CEE banks are more vulnerable for macroeconomic shocks as these countries are more instable than western European countries. Finally, the CEE countries are far less experienced in developing effective policies to minimize adverse effects of shocks to the economy.
This means that regulatory frameworks should be set differently for the CEE banking markets. However, since the majority of the CEE countries are now members of the EU, they have to meet standards that are set up by the EU directives and thus, we can expect a convergence in regulatory frameworks. A higher degree of banking supervision is needed in order to make sure that the above instability characteristics of the CEE banking systems can be minimized (Alimkulov (1999)).
As already described, it is difficult to investigate the regulatory frameworks of each country separately and is beyond the scope of this thesis. However, research concerning indicators that are able to approach the regulatory environment of a country has been performed. The most prominent and complete database is developed by Kauffmann et al. (2008) under the supervision of the World Bank5. The authors have established an indicatory database with several dimensions, which is able to determine the characteristics of the general regulatory environment. The dimensions are set up according to questionnaires answered by business representatives and regulators and therefore give a perception of the regulatory environment. The dimensions are the following:
1. Political Stability and Absence of Violence 2. Government Effectiveness
3. Regulatory Quality 4. Rule of Law
5. Control of Corruption
Dimension 1, 2 and 5 indicate the political climate in the country. These will be discussed later on in this thesis. The important dimensions with respect to regulations are dimensions 3 and 4. Dimension 3 gives an indication how the regulatory framework in a country is organized. In this dimension, there is also room for specific banking regulations perception like for instance the quality of deposit insurance schemes and capital adequacy measures. The regulatory quality perception measures the extent to which the government is able to formulate and implement well-functioning policies. Furthermore, it also measures the regulatory framework that permits or promotes the private sector development and consequently the banking sector as well. As indicated by Barth et al. (2001), regulatory frameworks influence banking development. Therefore, if a country sets their regulatory framework too strict compared to its fellow CEE countries, it implies that the climate to invest for foreign banks is not optimal. The regulatory framework can put restrictions on the bank sector in the form of strict capital adequacy requirements, restrictions of banking activities or denying entry for too dominant banks in order to protect the domestic banking market (Koehn and Santomero, 1980).
lesser degree of stringency to comply. It is a fact that companies (banks) investing in CEE have to be familiar with each other, especially when searching for new business opportunities. Although over time, contractual obligation perceptions are getting better, there still is a relatively large deviance between Western and Central Eastern European countries.
As already stated, foreign banks view favorable regulatory frameworks and a well functioning rule of law perception valuable determinants in the expansion decision. These perceptions intuitively support the set of best practices set by Barth et al. (2004). Forcing accurate information disclosure is achieved by having a good Regulatory Quality and Rule of Law as it insures transparency of the banks, private sector empowerment of control of banks as well as fostering private agents incentives are achieved by having a good Governmental Effectiveness. The reason for this is that an effective government has good knowledge of how bank supervision should be divided and therefore adapts towards the need of good practices.
Therefore, the following hypothesis can be developed:
H4a: Relatively stringent regulatory frameworks and weak perceptions of rule of law in the CEE country have a negative effect on foreign bank FDI.
Political Stability and the Control of Corruption are closely related to the regulatory framework in a country. A high level of political instability and/or corruption can imply a low level of regulatory quality (difficulties in implementing and supervising of regulatory standards), a low perception of the rule of law (low degree of law obedience) and a low level of government effectiveness (policies are ill-developed and the needs of the business environment are not met). Therefore, they are included in this Regulatory Environment section.
present. Especially in the final days of the communist system, it was customary to use bribes to satisfy your demands, particularly when faced with persons in lower ranked positions. This corruption was also evident in the period after the communist system. Many state officials and businesses were still using the bribery system, mainly because of inertia (Meyer, 1998). Although this corruption became less evident towards the end of the 1990’s and the beginning of the new millennium, foreign businesses still need to consider this when deciding to expand to these countries.
Corruption is less evident in the Western European countries and consequently, businesses from these countries are not familiar with corruption and will be influenced by the extent to which a country is corrupt. A study performed by Habib & Zurawicki (2002) points out that foreign direct investment is negatively associated with the level of corruption in a country. They notice that, in general, businesses are less eager to invest in countries where corruption levels are relatively high. The reasonis not only the higher amount of costs, but also the moral problem. Businesses from countries that have low corruption levels tend to have the moral problem that corruption is wrong. Therefore, they tend to shy away from investing in ‘corrupt’ countries.
instance: the attempted assassination on the elected president in the Ukraine, the assassination of a well-known spy in Russia who had vital government information, the close- to- dictatorship and corresponding violence in Belarus and ethnic violence in Bosnia & Herzegovina. However, the examples given are extremes. In many CEE countries, there is political violence to some extent although far milder. This political violence has its effect on FDI (bank and non-bank) in these countries. As stated by Jensen and Young (2006) and Li (2006), political violence is taken into consideration when businesses decide to expand abroad and a negative correlation can be established. Therefore, we can develop the following hypothesis:
H4b: A high level of corruption and/or a high level of political instability in the CEE country has a negative impact on banking FDI.
The investment climate is also part of the Regulatory Environment. Considering the fact that a harsh investment climate can shy away businesses, it also has an effect on banks looking for new opportunities (Wezel (2004)). The investment climate can permit or limit the investment activities of the bank. Sometimes certain activities that are demanded by the clients cannot be met, because regulatory standards limit the amount of activities of foreign banks. These limitations can be a result of protectionist measures by the CEE country government in order to protect the developing financial markets. These limitations can range from forcing the foreign bank to open a joint venture with a domestic bank to not permitting the bank to enter the market as a whole. These protectionist measures have a negative impact on the investment climate in the country. Several studies have been done to research the investment climate in selected countries. According to Sagari (1992) and Wezel (2004), several aspects determine the investment climate in a country:
- government ownership of banks
- restrictions on the ability of foreign banks to open branches and subsidiaries -government influence over the allocation of credit
- government regulations
These aspects determine the degree of openness with respect to the investment climate in a country. A high degree of openness implies a good investment climate for businesses including banks and as a result is considered having a positive influence on bank expansion. What should also be mentioned, is that restrictions in investments of banks have a negative influence on the decision to expand abroad. The following hypothesis can be developed:
H4c: A high degree of investment freedom has a positive effect on foreign bank entry.
Studies performed by Laporta et al. (1997) and Galindo et al. (2003) support the notion that relatively favorable regulatory environments imply a higher amount of Foreign Bank entry. Favorable RE’s are in this thesis RE’s that are relatively higher in comparison with the other CEE country counterparts. Using the framework established by Kauffmann et al. (2008) the regulatory indicators that will be used range from -2.5 for a ‘bad’ dimension to 2.5 for a ‘good’ (or favorable) dimension.
In conclusion To conclude of this regulatory environment section, it can be seen that these three hypotheses all have in common that they are part of the general Regulatory Environment in a country. Therefore, the hypotheses can be summarized in the following main regulatory hypothesis:
H4: A relatively favorable regulatory environment has a positive effect on foreign bank entry.
2.4 Regulatory Interaction Effects
it ‘strengthens’ the variable’s existence. For instance, if a CEE country shows a large amount of home-based clients, we can say that in the light of the developed hypothesis a high amount of banking FDI in this country can be expected. However, if the regulatory environment is also favorable for a foreign bank, this follow the client behavior is intensified because there is a lower threshold to follow the home-based clients implying an even higher degree of Banking FDI in this particular country.
A study performed by Lankes & Venables (1996) found that the regulatory environment in a country is a factor that determines the degree of FDI in a country. Especially factors that contribute to the Rule of Law in a country do have an influence on FDI. Having a weak regulatory environment implies higher costs, due to policy inefficiencies and the lack of well-functioning investor protection rights and this reduces the incentive for potential investors in a country to invest. In addition, Bolaky and Freund (2004) discovered that a highly regulated business environment has a negative effect on economic growth (which in the case of this thesis is represented by GDP per capita). This originates from the notion that a highly regulated market increases bureaucracy and consequently crowds out trade. This is caused by the fact that a high level of bureaucracy provides a disincentive for foreign partners to trade with the companies in the highly regulated country, because of higher trading costs. As economic theory suggests, trade is one of the main determinants for economic growth in a country. If trade is relatively low, this has a negative effect on economic growth (and thus GDP).
regression analysis (MRA), a method that will be explained in the methodology section. However, the Regulatory Environment variables that are used as a moderator in this thesis are, in essence, of a qualitative nature. This is because they are perceptive of nature provided by survey results. However, as the authors point out, if it is possible to quantify the variables to nominal data, the moderated regression approach can be used on qualitative data. The government indicators database provided by Kauffmann et al (2008) provide the RE variables in a nominal data structure implying that the quantification of these perceptive data sources can be used.
Using the same reasoning for the other variables and including the literate evidence, the following additional hypotheses can be developed:
H5a: A relatively good regulatory environment has a positive effect on the relation between FDI stock and foreign bank entry.
H5b: : A relatively good regulatory environment has a positive effect on the relation between GDP per capita and foreign bank entry.
H5c: : A relatively good regulatory environment has a positive effect on the relation between EU membership and foreign bank entry.
Please note that, in this thesis, a favorable regulatory environment has been appointed a relatively higher number in the five dimensions indicator framework (ranging from -2.5 to 2.56) than other CEE countries. Therefore, the RE variable that will be developed later on for each CEE country is ‘better’ if it is fairly higher than the mean of the RE variables of all the CEE countries.
2.5 Regulations home Country
In the literature, there is limited information about the extent to which the regulatory environment of a home country has an influence on the decision of banks to expand abroad. However, there are several studies that partly shed light on this matter.
H6a: Extreme differences between host and home country’s Regulatory Environments will have a positive effect on foreign bank entry.
H6b: Relative similarities between host and home country’s Regulatory Environments will have a positive effect on foreign bank entry.
Please note that this variable will not be tested but will be used as a supporting variable.
2.6 Geographic distance
decisions. The findings were that, except in the United States, all banks in the selected countries relied to some extent on the geographical distance for the decision to invest in a certain country. Moreover, as stated by Konopielko (1999), the monitoring costs for the bank’s headquarters increase if distance increases.
Therefore, the following hypothesis can be developed:
3. Empirical Model
According to the literature review, the following graphical representation of the model can be presented:
Follow the Client EnvironmentRegulatory OpportunitiesBusiness
Foreign Bank Entry
Regulatory Environment Home Country Geographic
Distance
In this model, the Regulatory Environment variable will be tested for a main effect as well as the Follow the Client and Business Opportunities variables. However, the RE variable will be also used as a moderator to test the interaction effect of the Regulatory Environment on the two main motives7. This interaction effect can either have a negative or positive influence on the other two motives in the decision of banks to expand abroad.
The other two motives are still valid for foreign bank entry, but are influenced by the moderator variable. Intuitively we can say that there is a direct and indirect influence of the Regulatory Environment variable on Banking FDI due to the two conventional motives for foreign bank entry. The Regulatory Environment in the home country of foreign banks will be used to determine the influence of this variable on the three main variables. Unlike the three main variables, this home country RE variable will not be tested in the model, but used as a supporting variable in the analysis. This is to see if this variable has an effect on the other three variables in terms of foreign bank entry. The same principle applies to the Geographic Distance variable that will be used to additionally explain the presence of foreign banks in the individual CEE countries. A side note on the RE variable of the home country must be pointed out in order to interpret this variable correctly. The RE Home Country variable defines the general Regulatory Environment in the home country in the same way as the RE for the CEE country. Therefore, the same measurement tool is applied (explained in the literature review section).
the foreign bank is used to this environment, it will have less problems to adapt (Laporta et al (1997)).
To summarize, if a home country shows an extremely deviant RE in comparison to the CEE country, it creates a larger incentive to expand to this country. The same applies if home and CEE country’s RE is similar. It is assumed that the model shows general consistency meaning that vice versa variable values have vice versa outcomes.
The model that will be tested in a formula form follows:
t i t i t i t i t i t i t i REGENVIRON GDPpc REGENVIRON EUdum REGENVIRON FDISTOCK GDPpc EUdum FDISTOCK REGENVIRON Bankentry , 6 , 5 , 5 , 4 3 , 2 , 1 , * * *
This main model will be derived in the results section of this thesis and will be adapted to test for main effects through cross- section regression and interaction effects through moderated regression analysis.
Please note that the model that will be tested does not include the regulatory environment in the home country and the geographical distance between host and home country. The reason for this is that the model incorporates all seventeen CEE countries subject in this thesis and will be tested as one region. Therefore, the two variables will not be tested since an implementation of these two variables in the existing model will have a statistical implication, which is beyond the statistical requirements of this thesis. However, these two variables will be used in the analysis section to support the models outcome.
In this formula, all three motives are tested with a regression with the dependent variable Bank entry. Please note that because of the use of panel data, this is a two-dimensional regression type (variable (i) and time (t)).
4. Methodology
The dataset will be tested using a pooled panel data set. A panel dataset is a statistical method in which several dimensions are incorporated. In this thesis, two dimensions are measured namely the independent variables (described in the data section) and time. The difference with a normal regression analysis is that a normal regression analysis only allows one dimension to be measured. The reason for using a panel data set is that we are interested in the change of importance of variables over the years. Using this method ensures that a cross section and a year analysis is performed simultaneously. The panel data is pooled, because a summation of the variables is performed. The panel data is tested using the statistical program E-views.
First, the main effect of the determinants on Bank FDI described in the literature review will be tested using a cross-section regression analysis in order to see if this research shows consistency with the literature. Second, a Moderated Regression Analysis (MRA) will be performed to see what the influence of the Regulatory Environment variable is on the positive or negative effect of the other determinants on Bank FDI. Conventionally, this MRA approach is used on pure quantitative data and since we use the perceptive (and consequently qualitative) data provided by Kauffmann et al. (2008), this incorporates the problem of inappropriate data. However, as stated by Baron & Kenny (1986), if a conversion of qualitative data to quantitative data can be made by using large survey respondents and quantifying this data into nominal data, the problem of inappropriate data will disappear. Considering the perceptive database by Kauffmann et al. (2008) is quantified, this problem is tackled.
Buch (2000) uses 245 observations. Nonetheless, according to the statistical book by Cohen (1988), 45 observations are sufficient in order to obtain reliable results for a panel data set. During the testing of the model, the problem of multicollinearity in the regulatory environment variable arose. Multicollinearity is a phenomenon in which two or more predicting variables in a regression model are highly correlated (values between 0.7 and 1). This high correlation between variables means that if variable A rises with an amount of one, variables B & C show similar upward movements, ranging between 0.7 and 1. This high correlation does not have a direct effect on the model in predictive terms, but it may not give valid results regarding the predictive power of individual variables. Looking at the table below, we see that correlations between the RE variables are very high ranging from 0.733 to 0.952 and thus multicollinearity arises. This notion can be supported by the fact that all variables are highly significant with each other. This can undermine the predicting power of the individual RE variables and might not give valid results.
Correlations Government Indicators
Government
Effectiveness Political Stability Regulatory Quality Rule of Law CorruptionControl of OpennessDegree of Pearson Correlation 1 ,855(**) ,913(**) ,952(**) ,937(**) ,795(**) Sig. (2-tailed) ,000 ,000 ,000 ,000 ,000 Government Effectiveness N 77 77 77 77 77 64 Pearson Correlation ,855(**) 1 ,769(**) ,881(**) ,871(**) ,733(**) Sig. (2-tailed) ,000 ,000 ,000 ,000 ,000 Political Stability N 77 77 77 77 77 64 Pearson Correlation ,913(**) ,769(**) 1 ,898(**) ,845(**) ,838(**) Sig. (2-tailed) ,000 ,000 ,000 ,000 ,000 Regulatory Quality N 77 77 77 77 77 64 Pearson Correlation ,952(**) ,881(**) ,898(**) 1 ,964(**) ,784(**) Sig. (2-tailed) ,000 ,000 ,000 ,000 ,000 Rule of Law N 77 77 77 77 77 64 Pearson Correlation ,937(**) ,871(**) ,845(**) ,964(**) 1 ,744(**) Sig. (2-tailed) ,000 ,000 ,000 ,000 ,000 Control of Corruption N 77 77 77 77 77 64 Pearson Correlation ,795(**) ,733(**) ,838(**) ,784(**) ,744(**) 1 Sig. (2-tailed) ,000 ,000 ,000 ,000 ,000 Degree of Openness N 64 64 64 64 64 64
In order to avoid this problem a factor has to be constructed. A factor is a bundling of the highly correlating variables and will be treated as one variable with a mean of 0. The factor variable in this thesis will be a bundling of the following variables: Government Effectiveness, Regulatory Quality, Rule of Law, Political Instability, Control of Corruption and the Degree of Openness. These variables effectively represent the Regulatory Environment variable. Since the factored variables represent parts of the Regulatory Environment, there is no problem to factorize them in the RE variable
The Factor variable will be used as the moderator variable. A moderator variable shows the interaction effect of the variable on another variable. In light of this thesis, the moderator will show how the regulatory environment influences the decision of bank to move abroad and therefore has an indirect influence on Bank FDI.
5. The Data
This section shortly describes the data used in the model. Descriptive statistics and correlation tables for this data can be found at the end of this section.
Dependent Variable
5.1 Foreign Bank Entry (FDI)
The dependent variable in this thesis is determined using the program Bankscope. The determinant for Foreign Bank Entry will be Foreign Bank FDI and is obtained by filtering the Bankscope database for the CEE region per individual country, and consequently filtering for foreign banks. After this two-step filtering, the dataset FB FDI was provided. This FB FDI variable will be used as a determinant of FB Entry, because it incorporates the total amount of foreign held bank assets in a particular CEE country. This dataset provides the total amount of assets held by foreign banks on a per year basis.
Tested independent Variables
5.2 FDI Stock (Follow the client hypothesis)
the UNCTAD database and ranges from 1996 to 2006.
5.3 Gross Domestic Product per capita (Business Opportunities)
Economic growth is reflected in GDP per capita. The higher the degree of GDP p.c., the higher the economic welfare is in a country. Because the CEE countries are showing significant economic growth, a rise in GDP can be expected as well. Therefore, GDP per capital can be used as a good indicator for the extent of economic welfare in a country. As stated by Wezel (2004), GDP per capita reflects the countries purchasing power and reveals the potential of the market with respect to consumers. Studies performed by Brealey and Kaplanis (1996), Yamori (1998), and Buch (2000) support this notion. They also discover a positive relationship between a high GDP per capita in the host country and banking FDI. Therefore, a relatively high GDP per capita in comparison with other CEE countries will have a pull effect on investors and will contribute to a higher presence of ‘home market companies’ and banks as well.
The GDP per capita variable is defined per country in the period 1996-2006. Data for this variable is extracted from the World Economic Outlook Database (April 2008) provided by the International Monetary Fund.
5.4 EU Membership (Business Opportunities)
5.5 Regulatory environment (Regulatory indicators and Degree of Openness)
The Regulatory Environment variables are adapted from the Government Indicators Database from the World Bank. These variables are perceptive in nature in the sense that they are constructed on the basis principle of multiple surveys performed by Kauffmann et al. (1997-2007). The variables range from a value of -2.5 to 2.5 where -2.5 is a (theoretical) bad perception of the regulatory environment and 2.5 a (theoretical) perfect perception.
The variables are measured during the period 1996-2007.
The variables measured will be Regulatory Quality, Rule of Law, Government Effectiveness, Political Instability and Control of Corruption. The latter two variables are not directly part of the regulatory framework but do influence the regulatory environment. A high level of political instability and/or corruption can imply a low level of regulatory quality (difficulties in implementing and supervising of regulatory standards), a low perception of the rule of law (low degree of law obedience) and a low level of government effectiveness (Policies are ill-developed and desires from the business environment are not achieved).
The investment climate is determined using the Degree of Openness in a CEE country. This variable ranges from 0 (implying a closed investment climate) to 100 ( a very open investment climate). A high degree of openness implies a relatively good investment climate for businesses including banks and therefore is considered having a positive influence on bank expansion. Restrictions in investments of banks have a negative influence on the decision to expand abroad. The variable is a weighted measure calculated using two dimensions (restrictions on the ability of foreign banks to open branches and subsidiaries, freedom to offer all types of financial services) in the Economic Freedom database provided by the Heritage Foundation. These two dimensions determine the extent to which a bank is ´free´ to do what it desires and thus indicates the investment climate for banks in particular. Degree of Openness is calculated for every CEE country in the period 1996-2007.
Supplementary independent Variables
5.7 Geographic distance
Geographical distance is a different variable in our model. This variable will not be tested because our general model does not take the particular distances between individual host (CEE) and home countries into account. Geographical distance will be used to explain ´gaps´ in the analysis section. Please note that a CEE country has, in general, several nationalities of banks in their banking sector. Therefore, several different geographical distances per CEE country will be described in the analysis.
5.8 Regulatory Environment home country
Descriptive Statistics Data Tested Variables
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
logBank FDI 77 10849,00 113000000,00 9554132,83 18801039,33 FDI Stock 67 413,00 103616,00 23314,15 24919,68 GDP p.c. 67 642,00 19021,00 5818,82 4011,18 RegEnv 64 -1,81 1,50 0,00 1,00 EU membership 77 0 1 0,2987013 0,46068985 Valid N (listwise) 64
Correlation matrix Tested variables
Correlations
logBank FDI FDI Stock GDP p.c. RegEnv
EU membership logBank FDI Pearson Correlation 1,00 0,64 0,37 0,22 0,44 Sig. (2-tailed) 0,00 0,00 0,08 0,00 N 77,00 67,00 67,00 64,00 77,00 FDI Stock Pearson Correlation 0,64 1,00 0,45 0,47 0,53 Sig. (2-tailed) 0,00 0,00 0,00 0,00 N 67,00 67,00 67,00 64,00 67,00 GDP p.c. Pearson Correlation 0,37 0,45 1,00 0,72 0,75 Sig. (2-tailed) 0,00 0,00 0,00 0,00 N 67,00 67,00 67,00 64,00 67,00 RegEnv Pearson Correlation 0,22 0,47 0,72 1,00 0,54 Sig. (2-tailed) 0,08 0,00 0,00 0,00 N 64,00 64,00 64,00 64,00 64,00 EU membership Pearson Correlation 0,44 0,53 0,75 0,54 1,00 Sig. (2-tailed) 0,00 0,00 0,00 0,00 N 77 67 67 64 77 **
6. Results & Discussion
The model has been run in several regression models in the statistical program E-views. These regression models are based on the main model as developed before. In the first regression, the variables are tested in a panel regression model to see what the main effect of each variable is on Banking FDI. In the following three regressions, each non-regulatory variable is tested against the Regulatory Environment variable (RegEnv) with respect to Banking FDI. By doing this, we can see if there is a positive or negative effect of the RE variable on the effect of the individual variable (FDI Stock, GDP per capita and EU membership) with respect to Banking FDI.
In the following regression output, the dependent variable, the logarithm of Bank FDI (logBankFDI) is the total sum of Banking FDI in the CEE region. The Regulatory Environment (RE) variable is the moderator variable.
The logarithm of Bank FDI is used for two reasons. First, it is used to ensure that the coefficients have a representative value (If the logarithm is not used, coefficients can have values exceeding 100). Second, Bank FDI is not normally distributed. In order to have as little anomalies as possible, the logarithm is used which ensures the data to approach a normal distribution.
Dependent: Bank FDI
Regression Main effects (1) Interaction efffect on FDI (2) Interaction effect on GDP (3)
Interaction effect on EU member (4)
Variables
FDI Stock 4,11E-05 6,26E-05 2,77E-05 2,95E-05
( 0,001)* ( 0)* (0,017)* ( 0,024)* GDPpc 0,000245 0,000232 0,000383 0,000266 (0,021)* (0,021)* ( 0)* (0,013)* EUMember -0,643 -0,34 0,29 1,72 (0,469) (0,689) (0,767) (0,222) RegEnv -0,089 0,37 -0,62 -0,71 (0,768) (0,231) (0,068) (0,074) RegEnv*FDIstock X -4,40E-05 X X X (0,007)* X X RegEnv*GDPpc X X -0,00026 X X X (0,034)* X RegEnv*EUMember X X X -2,54 X X X (0,02)
The first column represents the results of the panel regression and determines the main effect and significance of the variables with respect to Bank FDI. The second to fourth columns represent the effect of the moderator variable (RE) on the non-regulatory determinants (FDI Stock in column 2, GDP per capita in column 3 and EU membership in column 4.
In this table, the variables coefficients and P values are depicted. The raw results can be found in Appendix A.
Regression 1: The main relation between the independent variables and the
dependent variable Bank FDI.
t i t i t i t
i REGENVIRON FDISTOCK EUdum GDPpc
Bankentry, 1 , 2 , 3 4 ,
A regression is carried out in which the main effects of the variables on Bank FDI were investigated. We can see that, according to this regression output, both FDI Stock and GDP per capita are positively significant at a 5% significance level (at .001 and .021 respectively). This implies that high values of both variables have a positive influence on Bank FDI (Foreign Bank entry) over the years if we exclude the interaction effect of the Regulatory Environment. This means that high FDI Stock in a CEE economy, which can be interpreted as a high degree of home-based companies in the CEE economy, exhibits a strong pull effect on foreign banks. This finding is consistent with studies performed by Buch (2000); Brealey and Kaplanis (1996); Konopielko (1999); Wezel (2004); Focarrelli & Pozollo (2000) and provides evidence for the follow the client hypothesis.
positive effect of these variables. Several authors ((Cetorelli (2004); (Wezel, 2004); Buch and Lapp (1998)) have concluded that EU membership has a positive effect on foreign bank entry. Laporta (1997) and Calindo (2003) observe the same for the Regulatory Environment. However, as can be seen in our results, their influence is non-significant (0,469 (EU); 0,768 (RE)) and negative (-0,64 (EU); -0,08909 (RE)). The insignificance of the EU and Regulatory Environment variable can be interpreted as follows: They do not have the same impact as the two significant variables, which are concerned with the success the foreign bank can have in the host country. Therefore, a favorable regulatory environment or EU membership status in a country can never be the primary goal to expand abroad for a bank. It only shows the environment the bank operates in and can thus be a secondary justification for the decision to expand abroad.
Regression 2: The interaction effect of the RE variable on FDI stock with dependent
Bank FDI. t i t i t i t i t i REGENVIRON FDISTOCK GDPpc EUdum FDISTOCK REGENVIRON Bankentry , 5 , 4 3 , 2 , 1 , *
The next regression that is carried out, is the interaction effect of the RE variable on FDI stock with a dependent Bank FDI. This regression will measure the extent to which the Regulatory Environment on Bank FDI influences FDI Stock. In other words, the extent to which the Regulatory Environment influences the amount of home-based clients in the CEE region and consequently, the amount of Foreign Bank activities in this region. It measures the indirect effect on Bank FDI.
in the following way: A good regulatory environment and a high degree of FDI Stock reduces the incentive to expand, because the Regulatory Environment is matured to such an extent, that it is difficult to outperform domestic (or other foreign banks) in order to keep the client. As a result, banks find the cost to expand too high and the revenue, which can be obtained by keeping the client by following him to the CEE country, is too low to make an economic viable decision to entry.
Regression 3 : The interaction effect of the factor variable on GDP p.c. with
dependent Bank FDI.
t i t i t i t i t i REGENVIRON GDPpc GDPpc EUdum FDISTOCK REGENVIRON Bankentry , 6 , 4 3 , 2 , 1 , *
Regression 4: The interaction effect of the factor variable on EU membership with
dependent Bank FDI.
t i t i t i t i t i REGENVIRON EUdum GDPpc EUdum FDISTOCK REGENVIRON Bankentry , 5 , 4 3 , 2 , 1 , *
Finally, EU membership*RegEnv was regressed in order see if there are interaction effects between the Regulatory Environment and EU membership on Bank FDI. Once more, the output is contradictory as to what one might say. The interaction effect of the factor on EU membership is negative (coefficient -2,54) and significant (P value 0,02). This suggests that a good RE has a negative effect on the effect that EU Membership has on Banking FDI. The reasoning behind this is that if a CEE country has a good RE and is a member of the European Union, the domestic banks are relatively well developed. In the light of the strive for new Business Opportunities, foreign banks have a smaller incentive to invest in these markets, because there are only marginal returns possible due to the maturing of the domestic banks9.
The three moderated regression analyses give surprising results that do not show consistency (except for one hypothesis) with the literature as described in the literature section. The hypotheses concerned with this phenomenon can be rejected. However, taking into account that there is a limited amount of moderator effects in the banking entry literature, we have found some new insights in this matter.
Due to these findings, we can conclude that our hypotheses are partially correct. The notion that a high amount of home-based clients in the host country has a positive influence on foreign bank entry can be accepted. The exhibited pull- effect on foreign banks is large enough to provide statistical evidence for the follow the client phenomenon. Furthermore, a high degree of economic welfare in the host country has a positive influence on foreign bank entry. A high degree of economic welfare implies a potential for new business opportunities, which also creates a pull effect on foreign banks. Once again, there is sufficient statistical evidence to accept this hypothesis.
Unfortunately, several hypotheses cannot be accepted. We find that EU membership does not have a positive influence on foreign bank entry and is statistically insignificant. The same observation can be deducted for the regulatory environment. It can be believed that this is due to the nature of these two variables. EU membership and the Regulatory Environment are secondary determinants in term of foreign bank entry. The fact that a country is member of the EU or has a favorable Regulatory Environment does not exhibit the primary pull effect on foreign banks. The primary pull effect is reflected by means of a revenue rise when the bank expands abroad. In this thesis, the primary pull effect is represented by the follow the client and new business opportunities hypothesis. Because EU membership and the RE form the environment in which the primary effects are experienced, they are secondary and thus a sole reason to expand abroad. Therefore, using the same reasoning, when the RE of the countries of origin are incorporated later on, it will be assumes that this home RE will not be the sole reason for bank entry.
However, as already described in the model section, a distinction can be made with respect to the difference between a host and home country RE. In accordance with the literature, it will be assumed that an extreme deviance between the two RE’s will have a positive effect on foreign bank entry. The reasoning behind this is that if there are large deviances, there is room to reap benefits due to the different Regulatory Environments in the sense that a foreign bank can exploit its comparative advantage (Galindo et al. (2003)). In light of the thesis: if a foreign bank is used to a high RE in the home country, it is able to reap benefits from a relatively low RE in the CEE country due to the comparative advantages that it has achieved by operating in the high RE home country. In addition, if a foreign bank is used to a low RE in the home country, it has developed a sense for opportunities (development of business ‘instinct’ by means of less functional RE’s) and is able to react quickly upon these opportunities in a relatively well-functioning RE in the CEE country. Furthermore, if the RE between a home country and a CEE country is relatively similar, it can be expected that the foreign bank will have a larger incentive to expand to this particular CEE country. A reason for this is that similar RE’s indicate similar Regulatory Environments and since the foreign bank is used to this environment, it will have less problems to adapt.
7. Analysis
An overview of the key data of these countries can be found in the Appendix. Please note that the variable EU Membership and Regulatory Environment (as a main effect) will not be used anymore since they proved not to be significant in the results.
A distinction was made which divides the countries in three groups. First, the countries with a high FDI stock and GDP per capita will be discussed on a country-by-country basis. Second, a discussion concerning countries with average or above-average FDI stock and mid-level GDP p.c. will be provided on a country-by-country basis. Third, a discussion will be provided concerning low level FDI stock, low level GDP that will include the remaining eight countries. This section will be discussed taking the remaining countries together. This is done this way because in general, these countries have the same characteristics and have similar results. In order to avoid being repetitive, the countries are discussed as a group. The first two sections will be discussed on a country-to-country basis because they show dissimilarities among each other and an individual approach is necessary. In general, we can see that the better the economy is performing, the higher the amount of Bank FDI per capita is.
The countries will be analyzed in the following way: First, the pre-tested model is implemented and according to the model, assumptions will be made. Second, the results from the tested variables will be implemented and will be used to explain the amount of foreign bank entry in the CEE country. In addition, the RE of the country of origin and geographical relations will be discussed and will support the analysis.
7.1 High FDI Stocks per capita and high GDP per capita
