Changes In Quality of a Governance Environment and the Amount of FDI and FPI Received: An Examination of Less-Developed and Developing Countries

Environment and the Amount of FDI and

FPI Received:

An Examination of Less-Developed and

Developing Countries

by

D.J.S. Griffioen

S1345044

First supervisor:

Drs. H.C. Stek

Second supervisor:

Mr. Drs. H.A. Ritsema

University of Groningen

ABSTRACT

This research focuses on changes in quality of governance environment (GE) of less developed and developing countries and the difference these changes have on the amount of foreign direct investment (FDI) and foreign portfolio investment (FPI). By means of regression analysis we test for changes in GE over a 5-year time period and observe how FDI and FPI changed over the same period. In addition, we take the ratio of FPI/FDI to examine if this ratio has increased or decreased as a result of GE changes.

CONTENT

3.1 FDI and FPI determinants ... 16

3.2 Governance and Foreign Direct Investment ... 18

3.3 Governance and Foreign Portfolio Investment... 20

4. LINEAR REGRESSION MODEL ... 23

4.1 Model Specification... 23

4.2 Measurement of FDI and FPI ... 24

4.3 Measurement of Governance... 25

4.4 Measurement of GDP and GDP/capita... 27

5. RESULTS ... 29

6. DISCUSSION... 33

7. CONCLUSION ... 35

REFERENCES ... 37

1. INTRODUCTION

In recent decades there has been a change in the nature of overall global economic activity (Holsapple, Ozawa and Olienyk, 2006). The globalization of business and economic activity has led to increased levels of cross-border investment, where capital is allocated to areas with perceived opportunity in both industrialized countries as well as non-industrialized countries. Foreign investment has increased under the rapid growth of transnational corporations (TNCs) and has been encouraged by the liberalization of markets (Worldbank, 2004). With countries opening up their borders it becomes easier for foreign investors to invest in different advantageous locations. This has resulted in a changing pattern of capital flows through the internalization of transactions within transnational corporations and the increasing securitization of financial transactions (UNCTAD, 1999). According to the IMF (2003), in recent years foreign direct investment (FDI) flows and foreign portfolio investment (FPI) flows have surpassed private debt flows to become the major source of international capital.

The difference between both forms of foreign investment comes in a variety of ways. Foreign direct investment is the type of investment defined as a cross-border investment in which a resident in one economy (the direct investor) acquires a lasting interest in an enterprise in another economy (the direct investment enterprise) (IMF, 2003). More concretely, it may take the form of buying or constructing a factory in a foreign country or adding improvements to such a facility, in the form of property, plants, or equipment. FDI is more difficult to pull out or sell off. Consequently, direct investors may be more committed to managing their international investments, and less likely to pull out in situations of increased risk to their investment.

over management of the firm in which is invested in and it is much less volatile than foreign portfolio investment.

A major determinant for foreign investors on where to allocate their investments is the governance environment in a country (Globerman & Shapiro). Governance is a multifaceted concept encompassing all aspects of the exercise of authority through formal and informal institutions in the management of the resource endowment of a state. Keefer (2004) recognizes the difficulty of providing a definition of governance, but he stresses that commonly the characterization should encompass “the extent to which governments are responsive to citizens and provide them with certain core services, such as secure property rights and, more generally, the rule of law; and the extent to which the institutions and processes of government give government decision makers an incentive to be responsive to citizens.” The quality of governance is thus determined by the impact of this exercise of power on the quality of life enjoyed by its citizens (Huther & Shah, 1998). Kaufman, Kraay and Mastruzzi (2003) emphasize three aspects of governance, “(1) the processes by which governments are selected, monitored and replaced, (2) the capacity of the government to effectively formulate and implement sound policies, and (3) the respect of the citizens and the state for the institutions that govern economic and social interactions among them”.

institutions “shift the playing field favoring some deals and opportunities while disadvantaging others.” They force the investing firms to think strategically about how to avoid the limits imposed by domestic laws as well as how to reap the benefits that the law and particular circumstances are capable of providing.

By means of their policies and actions, local governments posses the power to alter the quality of governance within a country and, as such, have a persuasive effect on foreign investors’ decision where to allocate their resources. The results of increased quality of a country’s governance environment can have two effects: economic growth and development as well as more foreign investment; leading to more economic growth and development as well. With more economic prosperity within these countries, the quality of the institutions increases too. In line with United Nations’ Development Report (2006) with economic growth comes the opportunity to adjust institutions and improve governance so that a virtuous circle is created.

This virtuous circle is of particular importance for less developed and developing countries. These countries that are in search of improving their economic position may reap large benefits if they are capable of institutional improvement. In extreme cases, poor countries with institutions that are excessively deficient are found to grow more slowly than wealthy countries, even when other factors, including investments in human and physical capital, are taken into account. This manifestation of the “poor getting poorer” appears to be a direct consequence of the institutional environment in those countries (Keefer & Knack, 1997). So improving institutional quality and governance may lead to increasing amounts of foreign investment that helps accelerate such a virtuous circle. FDI brings with it the transfer of technology and skills, development of human capital through employee training and increased corporate tax revenues due to profits generated. In addition, increased opportunities for (foreign) trade and FDI can provide environmental and social benefits through higher standards at which the investors operate that will force others to raise their own standards and, as a consequence, increase economic development and growth (Razin & Sadka, 1999; Feldstein, 2000; Loungani & Razin, 2001 Evans, 2002). By increasing the liquidity of domestic stock markets as well as to develop market efficiency, FPI encourages the attractiveness of long-term investments (Atje & Jovanovic 1993; Evans, 2002).

their confidence in a country’s growth prospects or stability, it is easier for them to pull out their investment. Portfolio investment in this respect is more likely to react to such changes in confidence than FDI because portfolio investors only hold a small percentage of shares and are much more prone to withdraw their investment in the case of increased risk over their investment (Worldbank, 2004). Some experts named the East Asian financial crisis in 1997 as a negative example of the high mobility of capital and the openness of markets without having proper protection mechanisms in place for foreign investors. It becomes more and more important for less developed countries to create a favorable governance climate to not only attract foreign investors but also to prevent radical capital outflows. The lacking quality or even non-existence of such an environment has a negative influence on countries trying to receive foreign investment. A variety of scholars show the importance of having sound institutions that protect foreign investors. For attracting both foreign direct investment (e.g. Globerman & Shapiro, 2002; Daude & Stein, 2004; Baniak, Cukrowsky & Herczynski, 2005) as well as for attracting foreign portfolio investment (e.g. Hausman & Fernandez-Arias, 2000; Albuquerque, 2003; Daude & Fratzscher, 2006). Many of these studies have focused on a single institutional dimension or governance element in determining its importance on foreign direct or foreign portfolio investment.

by overseas investors. In their study the authors have focused on recent changing policies by Canadian government specifically aimed at attracting foreign investors. In his study on foreign portfolio investment and the economic development as well as the development of capital markets in emerging countries, Errunza (2001) also acknowledges the importance of governmental policies in attracting foreign portfolio investors. The foreign investors would demand timely and quality information, minority protection, as well as adequate market and trading regulations installed by local government. In addition, foreign portfolio investors will necessitate development of new institutions (Errunza, 2001). Islam (2003), additionally, mentions the importance of information and the ability by government to affect these information flows. Many of the institutions (laws, regulations, organs of the state) that governments design are created to manage the flow of information in an economy. The government as such is the sole repository for much of the information that decision makers in political and economic markets need (Islam, 2003).

Governmental policies and actions can affect the quality of countries’ governance. There are ambiguous views however, on the pace at which such policies can affect a governance environment. According to Williamson (2000) such changes take a very long time. He has presented a model of ‘new institutional economics’ in which he describes four different levels of social structures. He refers to the second level of his model as ‘first order economizing’ where the executive, judicial, and bureaucratic functions of government as well as the distribution of power across different levels of government are included. This is the level we are interested in. The definition and enforcement of property rights and of contract laws are also important features at this level. Considering possible changes at this level he concludes that “major changes in the rules of the game occur on the order of decades or centuries”.

2. RESEARCH DESIGN

The reader should now be familiar with the most important concepts this paper will address. Following the introduction we will now proceed with an elaboration of what the paper specifically intends to accomplish and the way in which it will try to do so.

2.1 Research objective

results clearly indicate that governance infrastructure is an important determinant of both FDI inflows and outflows (Globerman & Shapiro, 2002). It is our objective to extend this research by Globerman and Shapiro who examine the governance infrastructure as an explanatory factor of FDI in- and outflow. Globerman and Shapiro (2002) justified their research on the notion that “although many previous studies adopt measures that are closely related to the idea of governance infrastructure, there has as yet been no systematic attempt to relate directly governance infrastructure measures to FDI flows for a wide cross-section of countries” (Globerman & Shapiro, 2002).

With the use of the same encompassing governance concept as these authors used1 as opposed to a single governance element, this research will build further on their approach and examine both FDI and FPI inflows so a difference in importance of such a governance environment and the amount of FDI and FPI can be examined. In addition to their research we will use a time period to further examine changes in governance quality and if such changes can explain differences in the amount of FDI and FPI received by countries. Since there may be a delay in the amount of foreign investment received after governance quality has changed we examine the relationship between governance quality and each type of foreign investment for two points in time and compare the strength of each of these relationships, in doing so the intention is to deal with the time dimension. As far as we know the examination of both types of foreign investment in relation to changes in quality of governance over a period of time has not been done before. The aim is to fill that gap by considering the difference in reaction to changes in governance environment for the amount of FDI opposed to the amount of FPI received. The focus is specifically on less developed and developing countries because these countries can obtain the most advantages from increases is governance quality.

2.2 Research questions

The main research question we seek to answer is:

Do changes in the governance environment of less developed and developing countries have a different effect on the amount of FDI and the amount of FPI received by these countries?

1 _{Note that we use the term governance environment instead of governance infrastructure. We do deploy}

By different we mean if there is a difference in the magnitude of the effect of a changing governance environment on the amount of FDI/FPI received by these countries. If, for example the governance quality has increased significantly, the intention is to examine whether either of the two increased in a similar manner or if FDI reacted more to such a change than FPI, or vice versa.

The sub questions that need to be answered in order to be able to answer the main research question are:

What are important factors in determining FDI and FPI?

First factors need to be determined that influence the amount of foreign investment received by countries. This will provide an insight of what specific factors determine foreign investment flows. Because there are several governance/institutional factors, the goal is to highlight those that have the most importance for this study.

How are different institutional and governance elements related to FDI?

We are interested in a concept of governance that encompasses various institutional and governance elements. The answer to this question will give specific information on the influence of each of these elements on FDI.

How are different institutional and governance elements related to FPI?

The same will be done for FPI as has been done for FDI because this research makes a distinction between both types of foreign investment and we have to examine how each type is related to various institutional and governance elements.

These sub-questions provide a rationalization of the choice for the variable(s). The identified variables will form the basis for the model with which we want to answer the main research question. In addition, the importance of governance to each specific form of foreign investment has been shown.

2.3 Research Method

answer to each of these questions contributes to the overall understanding of the most important variables that will have to be taken into account.

With the use of existing literature we will be able to identify the variables needed for the tests to get the most representative results for answering the main research question. By examining these secondary sources we will be able to provide the reader the most important concepts and the relative importance of these concepts in determining the amount of FDI and FPI received by countries. The secondary sources consist of articles, working papers, books and websites.

To answer the first sub-question the main source of information will be existing literature and previous research. By examining secondary sources we will have comprehensive understanding of what results have been found on the relevant indicators for FDI and FPI. This will form a basic knowledge of what is known within the field of research.

For the second and third question again secondary sources will be made use of to provide a clear understanding of what various institutional factors are related to each form of foreign investment. For more detailed analysis, extensive use will be made of websites that are aimed at providing insights and analysis of country specific institutional and governance information.

The correct statistical test for an experiment largely depends on the nature of the independent and dependent variables analyzed. Categorical variables are variables for which it is not possible to put them into a sequential order or to differentiate them in a mathematical way. Examples include gender, political preference and field of study. On the other hand, variables of a continuous nature can be ordered in a sequential way and can be differentiated in a mathematical way, examples such as age, weight, and height and time measures. If the dependent and independent variables have a categorical nature then a different test is appropriate than when the variables have a continuous nature. See the following table2 for an overview.

Table 1. Nature of dependent and independent variables and appropriate tests

In this case the dependent variables are FDI and FPI, measured in amounts of dollars, and they have a continuous nature. The independent variable, governance environment, is also measured on a continuous scale, since the quality a country is assigned is given on a normal distribution from -2.5 to 2.5.3 Due to the nature of our variables regression analysis is the preferred choice. The objective is to examine certain causality in the quality of governance and the amount of FDI/FPI received, for which regression analysis is appropriate. In addition, a main advantage of this method is that with linear relationships between the dependent and independent variables, regression analysis shows optimal results (Globerman & Shapiro, 2002). Regression analysis allows us to test for this statistical significance as well as for the strength of the relationship. We are thus able to examine if changes in GE had an effect, either positive or negative, on the amounts of FDI and FPI received. Another reason for the adoption of regression analysis is because we intend to build on the research by Globerman and Shapiro (2002) and compare our results with theirs. Since a similar set of variables is deployed as these authors, the same advantages of regression analysis apply to our study.

2 _{Table retrieved from http://www-users.cs.umn.edu/~ludford/stat_overview.htm} 3

More detail on the scale and nature of the variables is presented further in the paper.

Dependent Variable

Categorical Chi Square t-test, ANOVA Independent

Variable

2.4 Data collection

Regression analysis requires data on FDI and FPI amounts for the countries used in the sample as well as data on governance quality. For the data on foreign direct investment and foreign portfolio investment we make use of data bases of the World Investment Report (2007) and the International Financial Statistics (IMF, 2007), respectively. These sources provide data that is readily accessible on a wide range of financial indicators. Furthermore, we shall make use of websites (e.g. GovIndicators Worldbank, UNCTAD) that focus specifically on institutions and institutional development. These websites provide a more in-depth analysis of governance related issues, for both developed and less-developed countries, created by Kaufman et al. (2006), which have also been used by Globerman and Shapiro (2002, 2002). Per country an analysis is provided for several years and supportive information and resources are given. Also available is an interactive platform that enables users to compare governance situation in different countries to one another or to compare for a single country the various indicators over several years.

The five-year time span has been based mostly on the availability of data. This was the largest time span between years data was found for on all of our variables. A larger time gap would have meant we had to exclude countries based on unavailability of either missing governance information or missing figures on FDI and/or FPI. The choice was made not to exclude more countries to maintain the sample size, with the consequence that the time span is only five years.

2.5 Country Sample

3. LITERATURE REVIEW

This chapter will focus on giving an answer to the three sub-questions posted previously. In doing so, the following is an account on what is known on the matter at hand and what different views exist on the importance of FDI and FPI determinants as well as the relation of both forms of foreign investment to institutional/governance quality. The purpose of the section is to convey what knowledge and ideas have been established on our subject and what their strengths and weaknesses are. At the end of this chapter the reader should have a clear image not only on the important factors that influence FDI and FPI that have been found by previous scholars, but also to understand our reasoning for continuing on this subject. In addition, the explanation is given why to adopt certain variables and why to exclude others for the sake of this analysis.

3.1 FDI and FPI determinants

In this section the focus will be on previous research to increase the understanding of the relations between the foreign direct and foreign portfolio investment and determinants of these international capital flows.

their model and they also find a statistically significant relationship. According to them large market size is expected to attract FDI because of economies of scale in production and distribution for products sold in the host market. In addition, larger markets may be associated with agglomeration economies that lower costs for all producers in that market. These advantages conceptually enhance the attractiveness of inward FDI. GDP also has a positive influence on the amount of foreign portfolio received by countries. Evidence shows, albeit less abundant than the relationship between GDP and FDI, that GDP also leads to more FPI. Portes and Rey (1999) who examine bilateral gross cross-country equity flows, show that such flows “depend positively on the size of a cross-country as measured by GDP.” In addition to that Martin and Rey (2004) further confirm the importance of market size and FPI received. They examined the size of economies as determinant for FPI, the determinants of assets return and the breadth of financial markets. Due to its importance we have to consider GDP in our analysis as a determinant for foreign direct and foreign portfolio investment.

In addition to the importance of country size, the relative wealth is also an important indicator in determining the amount of FDI according to Habib and Zurawicki (2002) and is measured by GDP/capita. Their reasoning is that a high GDP/capita reflects high consumption potential in the host country and, as such, should lead to attracting FDI. Globerman and Shapiro (2002) on the other hand come up with a different argument of why GDP/capita should provide other results. They claim that since productivity levels are highly correlated with wage rates, as well as with GDP per capita, all other things constant, higher wage rates will discourage inward FDI. In addition, it is not surprising that GDP per capita and relative wage rates are frequently either statistically insignificant or appear with the ‘wrong’ signs in FDI regression equations (Ibid.). Even though both scholars come up with opposing arguments for the effect of GDP/capita we adopt this measure into our analysis as well. When examining less developed countries the differences in wage rate and relative wealth might prove to be an important determinant for foreign investors.

situation in place (Faugere & Van Erlach, 2006). Although we do not focus on growth in GDP/capita we do find it to be important to examine the relation between FDI and GDP/capita because of a certain minimum level that has to obtained, according to the authors.

Other factors have also been investigated to prove that they too are important indicators in foreign investment received. Previous studies have identified factors such as physical infrastructure and human capital as determinants of foreign investment. Physical infrastructure is conventionally thought to include investments in the construction and maintenance of communications, transportation and utility networks. Human capital reflects less tangible investments in people, mainly in the form of education and health. The relations have been proved to be not significant or highly correlated with other indicators making the results difficult to interpret. According to Globerman and Shapiro (2002) they do not include such variables in their specification because they are highly correlated with governance infrastructure. According to these authors, this is not surprising since these measures are also measures of development outcomes that result from good governance. It is therefore not surprising that such measures and governance environment tend to be positively correlated (Globerman and Shapiro, 2002).

From the above examination it becomes clear that GDP as a measure of country size and GDP/capita as a measure of wealth are of importance in determining foreign direct investment. Other factors that have been utilized as important determinants in FDI and FPI amounts have proved to be less significant or difficult to interpret. We shall thus focus our attention solely on the two indicators that have been found in several scholars to be important indicators for FDI and FPI.

3.2 Governance and Foreign Direct Investment

The focus is on governance environment as a determining factor for FDI and FPI and what difference a change in such an environment might have on both forms of foreign investment. We look for the importance of governance environment on FDI.

La Porta, et al. (1998) has studied the rules and regulations of investor protection and the enforcement of these laws. They also investigate the origin of these rules based on the different law systems within a sample of 49 countries. They separate legal systems into common law countries and civil law countries. The latter being divided in French civil law and Scandinavian civil law countries. What they find is that countries that originate from common law systems have better mechanisms for investor protection than countries with a civil law origin; with French civil law countries among those with the poorest protection mechanisms is place. Furthermore, those countries which exhibit strong enforcement, have independent judiciary and legislation and thus provide better protection for investors are more favourable to attract FDI (La Porta, et al, 1998). Moreover it seems that a country lacking proper enforcement of property rights and where the risk of expropriation is high, firms prefer FDI as it is harder to expropriate due to its information intensity and its inalienability (Albuquerque, 2003).

Other studies have focused more specifically on the role of institutions and FDI flows. Daude & Stein (2004) look at the institutional quality of a country as a factor of attracting FDI. Different institutional dimensions appear to be important for investors’ decisions on where to invest. Especially, the predictability of policies, regulatory burden, enforcement of property rights and the level of commitment of the government all play a major role in deterring FDI flows. This is much in line with Benassy-Quere, Coupet & Mayer (2005) who find that public efficiency in a broad sense (tax systems, easiness to create a company, lack of corruption, transparency) serves as a major determinant for inward FDI. They highlight the importance of good institutions for increasing the amount of FDI particularly for lesser developed countries. These countries, according to the authors, should try to match the quality of their institutions to those of source countries in order for them to receive more FDI. With the attention on transition economies, Baniak, Cukrowsky and Herczynski (2005) found that, with the risk-averse nature of firms, legal and macroeconomic stability is a crucial determinant for the stimulation of FDI inflows.

model is used. They start with the likelihood a country is a recipient of FDI flows. What they observed was that those countries that “fail to achieve a minimum threshold of effective governance are unlikely to receive any U.S. FDI” (Globerman & Shapiro, 2002). In the second stage the main subject is governance infrastructure and the volume of FDI flows received. Again, governance infrastructure was found to be an important determinant explaining the volume of U.S. FDI flows received by countries. In addition, evidence also suggested that countries originating from English common law attracted more FDI than countries with other legal origins. Related to this research is their paper on the relation between governance infrastructure and inward and outward FDI flows for a sample of 144 countries. Once more they utilize the aggregated measure of governance as a determinant for FDI, which was found to be a good indicator for countries’ FDI flows both inward and outward. Particularly important is good political governance, which is characterized by policies promoting competition (domestically and internationally), as well as open and transparent legal and regulatory regimes, and effective delivery of government services (Globerman & Shapiro, 2002). Furthermore, the authors found evidence suggesting that the returns to investment (net FDI flows) are greater for developing and transition countries.

There is a positive relation between good governance environment and the amount of FDI received. Specifically less developed and developing countries would enjoy increased FDI with better institutional and governance environment. It appears that countries should have a minimum quality of governance in place to be a recipient of FDI and that increases (decreases) in governance quality will have a positive (negative) effect on the amount received.

3.3 Governance and Foreign Portfolio Investment

problem is much larger than it is with direct investors. To overcome this agency problem, FPI is dependent to a larger extent on other forms by which their investment is protected such as a well functioning governance environment. Daude and Fratzscher (2006) examine what they refer to as the ‘pecking order’ of different forms of foreign investment based on two key determinants of foreign investment: the importance of information frictions and the role of institutions. Regarding the first variable, FPI is found to be much less responsive towards information frictions than FDI, because of the stronger ownership implications of the latter one. As for the second variable, FPI is found to be much more sensitive than FDI to both market development (openness of the capital account and the development of the domestic financial sector) and to domestic institutional features (Daude & Fratzscher, 2006). For all the three proxies they use, degree of transparency, investor protection and corruption, the results are robust and highlight greater importance for FPI than for FDI on these institutional dimensions. In line with Albuquerque (2003) the authors state that FDI is less affected by the risk of expropriation whereas FPI is highly sensitive to this risk.

In addition, the magnitude of foreign portfolio investment is influenced by the level of corruption, which is not the case for FDI. Their findings are supported by previous work by Hausman and Fernandez-Arias (2000) that showed that countries that are rich and show low volatility, and countries that have good institutions and well functioning markets, receive more portfolio investment in relation to foreign direct investment. This could be because portfolio investment flows, due to their more liquid nature, seem to respond more quickly to changing circumstances, which occurs less in developed countries (Rueda-Sabater, 2000).

Interesting to mention is the paper by Fausten and Lake (2004) that focused on foreign investment composition and the governance environment in China. They hypothesized that the preferred mode of foreign investment was dependent on the financial development of China. Their suggestion was that China would receive more foreign direct investment in the initial phase of development, which would gradually change to larger amounts of foreign portfolio investment with the increased quality of institutions and governance. Even though their findings ‘loosely supported’ their hypotheses, we believe that their thinking was correct.

developed countries the lowest share (Daude & Fratzscher, 2006). This could be related to the lower quality of institutions in such countries since FDI is more likely than other forms of capital to take place in countries with missing or inefficient markets. In such settings, foreign investors will prefer to operate directly in stead of relying on local financial markets, suppliers, or legal arrangements (Loungani & Razin, 2001). Daude and Fratzscher (2006) conclude their research with the notion that a large share of foreign investment that comes through FPI is likely to signal well functioning domestic financial markets and foreign investors’ trust in domestic institutions. Where, on the other hand, a large share of FDI on total foreign investment may indicate a lacking quality of domestic institutions and financial markets.

As with FDI, the institutional and governance environment appears to be an important determinant of the amount of FPI countries receive. In some cases we have seen that certain institutional elements may be more important for foreign portfolio investors than for foreign direct investors. We have also seen that countries with sound institutional and governance environment attract more FPI than FDI, which is the case in developed countries. This is very interesting for our research since the countries we intend to focus on are not characterized by stability and these are countries where institutional and governance quality is not at such a high level as with developed countries.

4. LINEAR REGRESSION MODEL

In the following chapter, the model will be explained that will be used to test the relationships between the variables we have identified to be important for attracting FDI and FPI. From the previous chapter, we have come to see that besides the measurement of governance, a country’s GDP and GDP/capita should also be taken into account. We will now further elaborate on the specific data and resources from which we obtained the data and the justification of the country sample.

The objective is to find an answer to the question if there is a difference in the amount of FDI received by countries and FPI received by countries with changes in a country’s governance environment. In trying to find an answer to that question we make use of linear regression analysis. This type of analysis determines if there is a significant relation between a dependent variable and one or more independent variables; that is the degree of confidence that the true relationship is close to the estimated relationship (Sykes, 1993). In addition to the statistical significance of such a relationship, this method also helps to determine whether there is a positive relationship between the variables or if there is a negative one.

4.1 Model Specification

a) FDI = a + b1a GE + b2aGDP + b3aGDP/cap + e

and

b) FPI = a + b1bGE + b2bGDP + b3bGDP/cap + e

Where:

a = a constant term

b1a & b1b = the coefficient of GE for FDI and FPI respectively

b2a & b2b = the coefficient of GDP for FDI and FPI respectively

b3a & b3b = the coefficient of GDP/capita for FDI and FPI respectively

e = a noise term that reflects other factors’ influence

The regression analysis identifies whether changes occurred in the strength of the relationship between FDI and FPI and the independent variables between each point in time. In addition, to test our model we will also examine the ratios between FPI and FDI for the different years. By comparing these ratios, the variance of these figures and the standard deviation of these figures, we are able to see whether there has been a significant increase in FPI over FDI. This is in order to examine whether over time one form of foreign investment has increased over the other form based on the possible change in governance environment. If, for example, GE has increased and as a result the ratio between FPI and FDI has increased significantly, this would indicate a stronger influence of GE on FPI than FDI.

4.2 Measurement of FDI and FPI

data and makes it possible for us to use it in a regression model. To test for normality within regression a plot of the residuals will be used; the difference between the observed and the predicted dependent variable. Figure 2 provides an example of what such a plot should look like when data is normally distributed. In this example we have used the natural logarithm of FDI in 20014. It can be seen that the plot looks like a straight line, which it should if normality is attained.

Figure 2. Example of residual plot for Log FDI 2001 to test for normal distribution

4.3 Measurement of Governance

Because the governance environment serves as a basis, we will have to establish how the concept is measured. We have previously mentioned that we make use of the six indicators which are estimated by Kaufman et al. (2006). These indicators measure a range of aspects of a country’s governance structures consisting of voice and

4 _{For both years and for both forms of foreign investment we have performed the same technique. We}

only show this particular situation to present the reader with an idea of the appearance of such a plot. For all transformations the normality of the distribution has been attained.

Observed Value 12.5 10.0 7.5 5.0 2.5 0.0

Expected Normal Value 12.5

10.0

7.5

5.0

2.5

accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law and control of corruption (see appendix B for more details on each indicator). Their estimates are based on the aggregates of several other indicators, 31 to be exact, which are derived from a variety of sources such as BERI, DRI/McGraw Hill, the Heritage Foundation, and the World Bank. According to Kauffman et al. (2006) the premise behind this aggregation of this data into 6 governance indicators is that each individual data source provides an imperfect signal of some deep underlying notion of governance that is difficult to observe directly. They perform an unobserved components model (see Kaufmann, Kraaij and Mastruzzi, 2004) which, according to them, has the main advantage in that the aggregate indicators are more informative about unobserved governance than any individual data source. The problem however with using these indicators has been presented by Globerman and Shapiro (2002) who also operationalized governance environment based on the data presented by Kaufmann et al. They found that the variables show very large amounts of correlation as can be seen in the following table:

** Correlation is significant at the 0.01 level (2-tailed).

Table 2. Correlation matrix governance indicators 2001

This high correlation between the six indicators makes it difficult to use them all in a single equation (Globerman & Shapiro, 2002). In Appendix C (Table 3.) we have constructed the same correlation matrix of the governance indicators for the year 2006. Similarly, there is a high amount of correlation visible between each of the indicators with the others.

In order to circumvent this problem the authors use a technique to reduce the six indicators into a single measure that best captures the individual indicators. This method

is called principal component analysis (PCA). The PCA method aims at explaining as much variance as possible with the smallest number of factors. Such a factor is the newly constructed concept which the authors found as being their combined measure of governance. We perform the same procedure for our sample of less developed and developing countries in order to capture one “governance” measure from the original six indicators. In Table 3 we show that just like Globerman and Shapiro (2002) we also have one factor that best represents the original six indicators based on the amount of variance explained.

Component Initial Eigen values Extraction Sums of Squared Loadings

Total % of Variance Cumulative % Total

% of Variance Cumulative % 1 5.419 90.321 90.321 5.419 90.321 90.321 2 _{.232 3.872 94.193} 3 .223 3.716 97.910 4 _{.077 1.291 99.201} 5 .026 .431 99.632 6 _{.022 .368 100.000}

Extraction Method: Principal Component Analysis.

Table 4. Eigen values resulting from principal component analysis

It can be seen that with constructing one new concept from the original six, over 90% of the variance can be explained. This means that the combined new measure of the weight given to the six original indicators explains more than 90%. If there were to be a second new concept created only a mere 3% extra variance would be explained and so on. In following Globerman and Shapiro we are also able to use one measure of governance, which encompasses a wider range of original concepts, for our analysis.

4.4 Measurement of GDP and GDP/capita

high quality of governance or a very low quality (Kaufmann et al., 2006). These measurement levels stay the same after the transformation to one governance measure by the PCA method.

The independent variables GDP (market size of a country) and GDP/capita (relative wealth of a country) are also measured in US dollar denominations such as with our dependent variables. The figures on these variables were obtained from Worldbank (2007). Here the same problem was encountered with the dependent variable of the data not being normally distributed. Again we have taken the natural logarithm of these figures to attain normality, the same way we did for FDI and FPI.

The following table provides an overview of the variables, a short description of the variables and their sources where we obtained them.

Variables Description Source

FDI Foreign direct investment measured in US $ World Investment Report (2007) FPI Foreign portfolio investment measured in

US $

International Financial Statistics (2007) GE First principal component of governance

indicators developed by Kaufmann et al.

Kaufman et al. (1999) available at: http://www.worldbank.org/wbi/governance/

datasets.htm#dataset

VA Voice and accountability; measures freedom of press, civil liberties, political

rights etc.

Kaufmann et al. (1999)

PV Political stability and absence of violence; measures political violence, terrorism etc.

Kaufmann et al. (1999)

GOV Government effectiveness; measures bureaucracy, quality of policy formulation

etc.

Kaufmann et al. (1999)

RQ Regulatory quality; measures permission of private sector development, public

infrastructure etc.

Kaufmann et al. (1999)

RL Rule of law; measures contract enforcement, property rights etc.

Kaufmann et al. (1999)

CC Control of corruption; measures corruption among private and public officials etc.

Kaufmann et al. (1999)

GDP Gross domestic product measured in US $ Worldbank (2007) GDP/cap Gross domestic product per capita measured

in US $

Worldbank (2007)

5. RESULTS

When performing a regression analysis, a number of things are important to look for in analyzing the output. First of all we look at the statistical significance of the results retrieved. To draw conclusions of such a true relationship we consider a significance level of 0.05 to be significant. What is also of importance is the value of the R ² statistic. This is a measure of the extent to which the total variation of the dependent variable is explained by the regression; 0 being no amount of variation explained and 1 indicating all variance is explained. A low number of R ² may point to the fact that there are important factors which are not adopted in the model. The closer the R ² value is to 1, the better the variables in the model explain the variation. The coefficient (beta) shows the steepness of the regression line and it shows the direction of the line; +1 being a perfect positive relationship or -1 being a perfect negative relationship. The findings will be presented in such a way that we compare the results from the regression analysis for FDI to that of FPI starting with 2001 and then progressing to 2006.

From the multiple regression analysis for LogFDI in 2001 we find that governance environment and LogGDP are both statistically significant with values of 0.002 and 0.000 respectively. LogGDP/capita on the other hand shows no significant relation with its significance level well exceeding 0.05 at 0.913. In this case we cannot accept GDP/capita as a valuable indicator in determining FDI in 2001. The total variation explained (R ²) in this situation is 0.577, which indicates that a little less than half of the variation is not explained. The beta values for GE (0.299) and LogGDP (0.690) are both indicative of positive relationships. GDP however appears to have a stronger positive effect on foreign direct investment than does GE. In Appendix D the original output table can be seen for the case of FDI in 2001.

influence on the amount of FPI received than GE has. However, there is a stronger positive relation between GE and FPI in 2001 than for GE and FDI (0.391>0.299). The results or our regression analysis for 2001 are presented in the following table.

FDI 2001 R ² = 0.577

Variable beta Significance

GE 0.299 0.002

GDP 0.690 0.000

GDP/capita -0.010 0.913

FPI 2001 R ² = 0.790

Variable beta Significance

GE 0.391 0.001

GDP 0.788 0.000

GDP/capita -0.039 0.543

Table 7. Output results regression analysis FDI and FPI for 2001

For FDI in 2006 we see a similar pattern compared to 2001 in the significance levels for GE and LogGDP (0.001 and 0.000) as well as for LogGDP/cap which is yet again statistically insignificant at 0.265. We see that the R ² has increased as opposed to the same situation in 2001 to a value of 0.686 i.e. explaining almost 70% of the variation. Which is also in line with our previous findings are the beta values with GE at 0.264 and LogGDP at 0.794, once more showing a stronger positive influence on the amount of FDI received.

FDI 2006 R ² = 0.686

Variable beta Significance

GE 0.264 0.001

GDP 0.794 0.000

GDP/capita 0.091 0.265

FPI 2006 R ² = 0.878

Variable beta Significance

GE 0.355 0.000

GDP 0.862 0.000

GDP/capita 0.004 0.973

Table 8. Output results regression analysis FDI and FPI for 2006

If we compare these results for both investment types as well as for both years there are some remarkable things to be noticed. First of all comparing 2001 to 2006 for both types of foreign investment, it can be seen that the variation that is explained by the models is larger in 2006 for both FDI (0.686>0.577) as well as for FPI (0.878>0.790). From this it also becomes obvious that the variation that is explained by the model within each year is larger for FPI compared to FDI. What also becomes apparent is that it is GDP that has a stronger positive effect (beta values) on the amount of both foreign direct and foreign portfolio investment received, when compared to GE. In every situation in our analysis the beta value of LogGDP exceeded that of GE.

2,0000 1,0000 0,0000 -1,0000 -2,0000 G I2 0 0 6 1,0000 0,0000 -1,0000 -2,0000 R Sq Linear = 0,907

Figure 3. Changes in governance environment (GE) between 2001 and 2006

6. DISCUSSION

The previous chapter has presented various insights regarding foreign direct investment and foreign portfolio investment and the relation both forms have with a countries’ governance environment. Although, no observation could be made in changes in governance quality for the sample countries, some interesting findings did emerge from the analysis, which we will now interpret and put into perspective with the existing knowledge and literature.

The most important result from the analysis has been that the change in quality of governance environment for the entire group of less-developed and developing countries has been negligible. The fact that over this 5-year time span there have nearly been any changes in governance quality is in line with Williamson’s theory of “new institutional economics” where he states that the Level 2 design instruments, or “first order economizing” as he calls it, take decades or even centuries to change (Williamson, 2000). We have to come to a similar conclusion from the limited changes we have observed. Consequently, we argue with Boesen (2006) and his claim that institutions do change at a sometimes rapid pace. Even though this may undoubtedly be the case on certain occasions we have not been able to detect such changes from our analysis. His examples for some developing African countries may have shown rapid changes in institutional quality for the better. We have to acknowledge, however, that these countries, as well as other less-developed or developing countries, may change a single institutional aspect but the entire governance environment may not be affected by such a single occurrence.

As for the analysis on FPI, it could well be the case that these countries’ GDP/capita level is not high enough and as such does not provide a risk diminishing situation as was stated by Faugere and Van Erlach (2006). However, we can only theorize about that because we have no hard threshold on the GDP/capita level which has to be in place. Therefore, care should be taken with any statements on this matter. What was found was that both governance environment and GDP were statistically significant in relation to each type of foreign investment. This coincides with the literature where both variables are found to be important determinants of FDI and FPI.

7. CONCLUSION

The objective of this research was to seek an answer to the main question whether changes in governance quality in less developed and developing countries had a different effect on the amount of FDI received as opposed to the amount of FPI received by these countries. In order to do so a method of research was adopted similar to that of Globerman and Shapiro (2002), who use regression analysis to analyze FDI in- and outflow of countries based on their governance environment. Their research was extended by examining the difference between FDI and FPI on possible changes in a governance environment over a time span of 5 years between 2001 and 2006.

The differences in governance quality observed between these years were too small to draw any hard conclusions on. Based on that observation we cannot say whether changes in governance have different effects on the amount of FDI received or on the amount of FPI received by less developed and developing countries. We did find, though, that the regression models for FPI showed higher explanatory value than the models of FDI. This could indicate that governance environment and GDP are more important explanatory variables for FPI than for FDI.

However, it could also be that for FDI there are other factors, which we have not included in our model that explain the amount of FDI received. This is an interesting subject that deserves closer attention in future research, where more independent variables should be taken into account. Further research should also try to isolate the effects of changes in governance and other independent variables on the amounts of FDI and FPI. Whereas we have only tried to examine differences in changes of governance quality we were not able to come up with detailed explanatory evidence on the exact relations between the selected variables.

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APPENDICES

Appendix A

Less Developed and Developing countries

Latin America Asia Eastern Europe Africa/Mid. East

Argentina Bangladesh Bulgaria Cote d'lvoire

Bolivia China Croatia Egypt

Brazil Hongkong Cyprus Ghana

Chile India Czech Republic Israel

Colombia Indonesia Estonia Kenya

Costa Rica Kazakhstan Hungary Morocco

Ecuador Korea Latvia Namibia

El Salvador Malaysia Lithuania Nigeria Guatemala Pakistan Poland South Africa Honduras Philippines Romania Tanzania

Jamaica Singapore Russia Tunisia

Mexico Sri Lanka Slovenia Zambia

Paraguay Vietnam Turkey Peru

Trinidad & Tob. Uruguay

Venezuela

Appendix B

1. Voice and accountability (VA), the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and free media.

2. Political stability and absence of violence (PV), the perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including political violence and terrorism.

3. Government effectiveness (GE), the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.

4. Regulatory quality (RQ), the ability of the government to formulate and implement sound policies and regulations, which permit and promote private sector development.

5. Rule of law (RL), the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, the police, and the courts, as well as the likelihood of crime and violence.

6. Control of corruption (CC), the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests.

Appendix C

** Correlation is significant at the 0.01 level (2-tailed).

Table 3. Correlation matrix governance indicators 2006

Appendix D Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 _{,759(a) ,577 ,552 1,28269}

a Predictors: (Constant), CAP2001, GI2001, GDP2001

Coefficients(a)

Unstandardized Coefficients

Standardized

Coefficients t Sig.

Model B Std. Error Beta B Std. Error

(Constant) -2,316 1,624 -1,426 ,160

GI2001 _{,810 ,246 ,299 3,285 ,002}

GDP2001 ,909 ,120 ,690 7,548 ,000

1

CAP2001 _{-,013 ,123 -,010 -,109 ,913}

a Dependent Variable: FDI2001

Table 6. Original output data for FDI in 2001 with all independent variables