THE EFFECT OF COLONIAL TIES ON
CROSS-BORDER M&A FAILURE
Empirical proof from Africa
Leon Mol
S1712888
27-01-2014
Master Thesis International Business and
Management - Faculty of Economics and Business
- University of Groningen
ABSTRACT
Colonial ties continue to have an enduring effect on the political and economic relations between a former colony and its colonizer. However, the main outcome of this thesis for the M&A process is that it can be argued that being an acquiring firm from a country that was the former colonizer in the country of the target firms does not lower the probability of M&A failure. In addition, arguably the effect of colonial ties has decreased since the colonies have been independent for an increasing period of time. This thesis was written with the aim of researching whether colonial ties have an influence on the failure rate of cross-border mergers and acquisitions of France and Great Britain in their former colonies in Africa. Using the theory of institutional distance, it was hypothesized that countries with colonial ties have a lower M&A failure rate because of a smaller institutional distance. Data from the Zephyr database was used to collect all completed and failed cross-border M&As in the sample. Logistic regression was used to calculate whether colonial ties had a significant
contribution in predicting the probability of M&A failure. The results indicated that colonial ties did not decrease the failure rate of M&As. To the contrary, in some models the countries with colonial ties had a significant higher failure rate than the countries without colonial ties.
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Table of Content
1. INTRODUCTION ... 1
2. THEORY ... 4
2.1 Cross-border merger & acquisition failure... 4
2.2 Institutional distance ... 5
2.3 Colonialism ... 7
2.4 Research model ... 10
3. DATA ... 12
4. METHOD ... 14
4.1 Variables en model construction ... 14
4.2 Method assumption ... 16
5. RESULTS ... 18
5.1 Descriptive statistics ... 18
5.2 Logistics regression results ... 20
6. DISCUSSION ... 26
7. CONCLUSION ... 30
7.1 Implications for practice ... 30
7.2 Implications for theory ... 30
7.3 Future research and limitations ... 31
1. INTRODUCTION
Recent military involvement of France in its former colonies, Mali and the Central African Republic, fuelled the debate on what exactly the role is that France, as a former colonizer, plays in the current affairs of its former colonies. France its interventions, requested and unrequested, in the domestic affairs of its former colonies have always been of interest to scholars from the political sciences. However, in my opinion this relationship has more, not yet researched areas of ties between a former colony and colonizer that are also of relevance to business transactions and the economy of these countries.
The Western economies are still growing at a very slow rate or are even contracting in the years that have passed since the start of the global financial crisis in 2008 (OECD, 2013). On the other hand, has technological progress made it possible for firms to compete in foreign markets at lower costs (Baldwin, 2006). These developments have as a consequence that in today’s globalizing world the growth of multinational enterprises (MNEs) depends more and more on its global operations, especially in high growth economies. Foreign direct investment (FDI) is an investment to acquire a lasting management interest, 10 per cent or more of voting stock, in a firm operating in an economy other than that of the investor (World Bank). FDI is one of the most important vehicles for MNEs to enter a new market.
Africa is often dubbed as the final frontier in business, and because of its wealth of natural resources has always been of interest to resource-seeking MNEs. However, the continent is also becoming more attractive for market-seeking MNEs in recent years. Due to the steadily rising income levels in most countries on the continent, the total gross domestic product (GDP) of Africa has tripled in the last decade (Ernst & Young Report, 2013). FDI in Africa has grown with a compound rate of almost 20% since 2007 and has remained mostly unaffected by the global financial crisis (Ernst & Young Report, 2012).
Institutional economists are advocates of the importance that a country its context has on the range of possibilities an economy has and thus its performance (North, 1990). Institutional distance has proven to be a compelling conceptual tool in explaining firm and country developments. Bae and Salomon (2010) argue that institutional distance impacts the relative attractiveness of country markets, the trade-offs among foreign market entry strategies, the management of subsidiaries abroad, and ultimately, firm performance. According to these studies, following the new
institutional economics as advocated by North (1990) and conceptualized by Kostova (1996), the concept of institutional distance is likely to be of influence on M&A success. To conceptualize institutional distance a number of dimensions are used: political, regulatory, economic, cultural and cognitive dimensions (Bae and Salomon, 2010).
With the exception of Liberia and Ethiopia, all countries in Africa have in common that they have been colonized by a European country. The colonial ties between former colonizer and former colony are found to have an enduring effect on the current (economic) relationship between these countries (Grier, 1999; Gardinier, 2000). The former colonizers France and Great Britain are especially interesting for a research into colonial ties and whether this influences the failure rate of M&As in Africa. France and Great Britain both ruled over a large number of colonies in Africa for a prolonged period of time. This implies that many institutions, like the regulatory framework and economic institutions have been transplanted from the colonizer to the colony. Using colonial ties as a subset of institutional distance, this research aims to investigate what the effect is of colonial ties on the failure of M&As in former colonies.
There are several reasons why the concept of colonial ties can serve as a proxy for institutional distance. Colonial ties are an important factor for the regulatory dimension of institutional distance. La Porta, Lopez-de-Silanes and Shleifer (2008) state that legal tradition in a country typically is implemented through conquest and colonization. Moreover, Acemoglu, Johnson and Robinson (2001) argue that the effects of the institutions implemented by colonizers in their colonies have had an enduring effect on the economic performance of these countries. Therefore, considering the status of Africa as an increasingly popular destination of FDI and location of M&As, this research aims to empirically establish whether colonial ties are of influences on the failure rate of M&As in Africa.
This thesis is structured in the following way: in the theory section the existing theory on M&A failure will be reviewed, along with reviews of institutional distance, the history of colonialism and its impact on economic relations and business transactions between countries. Lastly, the
2. THEORY
2.1 Cross-border merger & acquisition failure
In the research field several concepts have been identified to influence M&A failure. These can be ordered into three separate types of causes: organizational causes, deal-specific causes and institutional causes. All will be reviewed in this section. M&A failure is of importance to
international business research, since an average of 45% of all M&A are abandoned (Cartwright and Schoenberg, 2006).
Organizational causes
Organizational causes are factors within either the target or acquiring firm that influence the likelihood of M&A failure. The attitude the top management of a target firm has towards the takeover bid is regarded as the most important reason for M&A failure (Jensen, 1988). When top-management of the target firm is opposed to the takeover this will increase the possibility of a failure significantly. Moreover, when the acquiring firm is larger than the target firm the likelihood of success is larger than when the acquirer is smaller than the target firm (Martynova and
Renneboog, 2008). Furthermore, when the acquiring firm already owns five per cent or more equity in the target firm the likelihood of a successful M&A increases as well (Jeon and Ligon, 2011). Data on an increase of ownership share is available and thus will be included in the analysis. Data on firm size is not given for a large enough number of deals to make an analysis, while data on the attitude of top management is not available in the database. Therefore, these variables are not included in the model.
Deal-specific causes
Institutional causes
Institutions and institutional distance have shown to be of influence on the probability of M&A failure. Dikova, Rao Sahib and Van Witteloostuijn (2010) researched the relationship between institutional distance and M&A failure. As in this thesis, the study of Dikova et. al. (2010) conceptualized M&A failure as an M&A that did not reach the completion phase. One of the outcomes of their study was that institutional distance has a profound effect on the failure of an M&A. The more institutionally distant the acquiring and target firm were, the higher the number of M&A failures. This effect was established for both formal and informal institutions. Very and Schweiger (2001) underscore the importance of informal institutions such as trust on the failure of M&As in a country: the lower the trust the higher the probability of M&A failure they found.
2.2 Institutional distance
The concept of institutional distance first emerged in the literature in 1996 when Kostova developed the construct. Institutional distance is the extent of similarity or dissimilarity between the regulatory, cognitive, and normative institutions of two countries (Kostova, 1996). Since then the framework of institutional distance has been used to explain various types of firm behaviour (Gray, 1996; Kostova and Zaheer, 1999; Xu and Shenkar, 2002).
In the study of institutional distance various dimensions can be employed, however, to get a complete measure all dimensions must be taken into consideration. A complete picture of institutional distance is made up of several dimensions that are categorized under a political, regulatory, economic, cultural, and cognitive pillar (Bae and Salomon, 2010).
The political dimension refers to the effectiveness of governmental and political institutions in securing property rights and enforcements of contracts. The regulatory dimension measures how effective the rules are enforced in a country. It is closely related to the political dimension and often these two dimensions are operationalized as one construct, the regulatory pillar (Eden and Miller, 2004). Legal origin has been used as a proxy for the political dimension of institutional distance. This adds to the relevance of the concept colonial ties, since La Porta et. al. (1998) displayed that colonialism was an important way how countries got their legal system. As legal systems were transplanted from the colonizing country to the colony. These legal systems have remained in place until present day. The economic distance dimension is based on the size of an economy, membership of a trade-block and also whether countries share historical links. This again
the Kogut and Singh (1988) index. Cognitive distance is focused on the structures, frames, routines and scripts used by individuals in society to judge and to assign meaning to a phenomenon and to solve problems (Bae and Salomon, 2010). However, in many studies the cultural and cognitive dimensions are operationalized as one construct. Bae and Salomon (2010) cite numerous studies explaining cross-border trade and investment by using commonalities in language, religion and history (colonial ties) as a proxy for cultural distance. This further underlines the applicability of colonial ties as a concept related to institutional distance.
Additionally, several studies have researched the relationship between institutional distance and various other concepts, such as: bilateral trade flow, firm performance and M&A survival. De Groot, Linders, Rietveld and Subramanian (2004) found that having a similar institutional framework, hence less distance, promote bilateral trade by an average 13%. Kostova and Zaheer (1999) found that a larger institutional distance between target and acquiring firms leads to a lower performance of the firm in the host country. Chan, Isobe and Makino (2008) found similar results on the
relationship of institutional distance between home and host country and local firm performance. Abovementioned studies both found a negative correlation between an increase in institutional distance and (successful) economic activity. However, there is also support for an inverted U-shape between institutional distance and firm survival (Gaur and Lu, 2007). The authors theorize that with a moderate level of institutional distance a firm can take advantage from this institutional distance, for example if the host-country offers better property rights protection than the home country. A firm is said to make use of institutional arbitrage when it is able to take advantage from the location advantages in the host-countrythat arise from institutional distance. As the institutional distance between the home country firm and the host country firm increases from small to medium, the survival chances of subsidiaries improve, but when the distance becomes too large, the survival chances deteriorate. Differences in institutional endowments are an important determinant for differences in country-specific advantages. However, there is a cut-off point; this is when the costs of institutional distance are larger than the benefits of institutional arbitrage. At this point the costs associated with unfamiliarity with the environment outweigh the benefits offered by the country-specific advantages. Consequently, a large institutional distance will have a negative effect on firm performance (Kostova and Zaheer, 1999;Gaur and Lu, 2007).
2.3 Colonialism
Definition of colonialism
Colonialism has many definitions and the term is often used ambiguously, therefore when mentioning colonialism in this thesis, the following concept as defined by Osterhammel (2005) is meant:
Colonialism is a relationship of domination between an indigenous (or forcibly imported) majority and a minority of foreign invaders. The fundamental decisions affecting the lives of the colonized people are made and implemented by the colonial rulers in pursuit of interests that are often defined in a distant metropolis. Rejecting cultural compromises with the colonized population, the colonizers are convinced of their own superiority and of their ordained mandate to rule (2005: p. 16).
Colonies can be classified according to three main types; exploitation colonies, maritime enclaves and settlement colonies (Osterhammel, 2005). The exploitation colonies had as a purpose the economic exploitation of the colony with a small number of migrants from the colonizer. The maritime enclaves served to secure trading routes and were a means for indirect economic penetration of a hinterland. The settlement colonies involved a large inflow of migrants from the colonizer who would permanently settle in the country. In this type of colony, social, cultural and religious life was cultivated under pressure of the mother country.
History of colonialism
The history of colonialism can be divided into two phases. The first phase started in the fifteenth century with the age of discovery of the Americas and afterwards of all other corners of the world. The Spanish, Portuguese, British and French had settlement colonies in the Americas together with exploitation colonies in the Caribbean. Colonial rule lasted for the longest period of time in Central and South America, under Spanish and Portuguese colonial rule. The colonies in the Americas were settler colonies, with a large influx of people from the mother-country. A consequence of this type of colony was the elimination of native societies while the labour of the native society was not used (Wolfe, 1999). This is illustrated clearly in the colonies in the Americas where the native inhabitants were dispersed to another place or killed and African slaves were brought in to carry out the labour. Evidence of this settler colonialism is still prevalent in the Americas, with large shares of the
During this first phase of colonialism which lasted from circa 1500 to about 1830, the colonies in Africa and Asia served as maritime enclaves and trading posts. The European powers did not hold large territories outside the trading posts and there was not a large inflow of migrants from the mother country. The wars of independence in the Americas that concluded at around 1830 resulted in almost all colonies in the Americas gaining independence. In reaction to these losses the
European powers shifted their attention towards Asia where these countries already had trade posts. The result of this pivot to Asia was that around 1870 colonial rule had been implemented in Indochina, the Dutch East Indies, and British India. These events can be seen as a precursor to the second phase of colonialism.
The interest in Africa increased when European explorers returned from Africa with stories of large reserves of natural resources on this continent (Osterhammel, 2005). The second phase of
colonialism started because of a combination of recent advances in technology and medicine in addition to a fierce political and territorial rivalry between European countries. This lead to Africa becoming the focal point of colonial interest for the European powers (Betts, 1966). African colonies took over the role that the colonies in the Americas had as a source of raw materials and ground to produce crops for export. This finalized the process of transition from trading posts to exploitation colony, using local labour and resources to produce for the colonizing country. However, there was no inflow of migrants from the colonizing country as happened in the Americas: in 1900 the population of colonies in Africa consisted of less than ten per cent European settlement (Jones, 2007).
Colonial history in Africa
sustenance to export for external profits to the benefit of the colonizer (Worger, Clark, and Alpers, 2010). See appendix A for maps depicting how Africa was divided before and after the scramble of Africa and after the First World War.
French versus British colonial rule in Africa
According to literature there were some interesting differences in the way the French and the British administered their colonies (Seidler, 2001; Osterhammel, 2005; Jones, 2007). Economic institutions are considered the most important determinant for long-term economic growth (Acemoglu, Johnson & Robinson, 2005). The authors state that this entails the enforcement of property rights and equality of opportunity for all people and equality before the law. The economic growth for former British colonies in Africa is significantly higher than that of former French
colonies Grier (1999). This is partly explained by the level of education the colony had at
independence, which is a consequence of the way a colonizer structured the education in a colony. The higher level of literacy and level of education in the British colonies compared to the French colonies is a testament of the higher level of human capital in the British colonies at time of
independence. The French had the dream of one united empire and administered their colonies in a centralized manner and didn’t allow the colonies to engage in free trade, creating a monopoly for French firms in the colonies (Lee and Schultz, 2012). The British pursued a more trade oriented and less assimilation focused policy, allowing for more decentralization and flexibility in the colonies. (Levine, 2013). This difference in centralization vs. decentralization and monopoly by French firms vs. openness to world trade resulted in the development of more efficient institutions in former British colonies in Africa and consequently better economic performance after independence (Grier, 1999).
Furthermore, both colonizers sent missionaries to their colonies to preach the word of God, for the French this was Christian Catholicism and for the British Christian Protestantism. Acemoglu et. al. (2001) found that colonies where the largest religion was Protestantism had higher levels of income than countries where any other religion was the largest religion.
Therefore, since British colonies developed institutions that are better able to deal with market exchanges and with a more efficient protection of investors and property owners it is expected that the number of failed M&As will be lower in British Africa than in Françafrique.
Contemporary effects of colonialism on business and economy
The study of Srivasta and Green (1986) found that colonial ties are a significant determinant for the intensity of total trade between countries. This effect is enduring, even after the colonies obtained independence. According to Srivasta and Green (1986) this finding is not surprising since firms of the former colonizer are generally well represented in the former colony and, in many cases close political ties still exist between both nations. A limitation of these findings however is that this research uses trade data from 1977 and most former African colonies obtained independence between 1960 and 1976 (Osterhammel, 2005) and therefore colonial ties per se were still very strong at the time.
Another enduring effect of colonialism is the legal system that has been implemented by the colonizer. Economists have recognized that efficient economic institutions, i.e. those that secure property rights, are conducive to good economic performance (Djankov,. Glaeser, La Porta, Lopez-de-Silanes, and Shleifer, 2003). The primary difference is between two schools of law, common-law and civil-law. In the negotiation process for independence the colonizers often secured special rights and corporate deals with their former colonies (Michalopoulos and Papaioannou, 2011). This strengthens the belief that firms from the former colonizer have an advantage in business dealings in a former colony.
Bertocchi and Canova (2002) analysed GDP growth data for former colonies in Africa for the years 1960-1988. One of the outcomes of this study was that having France or Great Britain as colonizer did make a difference for growth. Colonies under the rule of these two colonizers achieved higher economic growth after independence than colonies of other European countries.
2.4 Research model
level of human-capital in British colonies it is expected that British firms have a lower failure rate in their former colonies than French firms in their former colonies.
France and Great Britain were the two largest colonial forces in Africa and have had a sufficiently large corporate presence in Africa over the years. Furthermore, these two former colonizers have ruled for a long time in many colonies so that there has been a substantial time to transplant
institutions. Two countries were chosen to extend possible generalizability of the results. The failure rate of cross-border M&A failure will be analysed in these two countries former colonies in Africa. Former colonized countries by France in Africa are referred to as: Françafrique 1. Former colonized
countries by Great Britain in Africa are referred to as: British Africa 2. Moreover, a restriction on the
data is that a country has to be colonized for more than forty consecutive years by the same colonial power. The reasoning behind this time span is that institutions take time to build up and the time frame of forty years is an average between the time span of thirty and fifty years used in other studies (Jones, 2007; Seidler, 2011). To test whether colonial ties lead to a lower M&A failure rate there has to be a reference group. The group rest of the world (ROW) are the countries that have no colonial ties with the sample of colonized countries but did have M&As in one or more of the countries in the sample of former colonies.
Based on the theory currently available in the field, the following research question has been formulated:
Does having colonial ties result in a lower cross-border M&A failure rate?
Consequently, in order to answer this research question the following hypotheses are formulated:
Hypothesis 1. The failure rate of M&As in Françafrique between French firms and Françafrique firms will be lower than M&As between ROW firms and Françafrique firms.
Hypothesis 2. The failure rate of M&As in British Africa between British firms and British Africa firms will be lower than M&As between ROW firms and British Africa firms.
Hypothesis 3. The failure rate of M&As between French firms and Françafrique firms will be higher than the failure rate of M&A between British firms and British Africa firms.
1 The term Françafrique was introduced by the president of Ivory Coast (1960 – 1993) Félix Houphouët-Boigny and is used in current day media to refer to relations between France and its former colonies in Africa. (Al-Jazeera, BBC, Le Monde, New York Times).
3. DATA
In order to make the variable M&A failure measurable, data from the Zephyr database is used (Zephyr M&A database, 2013). This database records all M&A activities in three categories namely: rumoured, announced and completed. When an M&A does not have a completed date in the database it is considered to have failed. The announcement and completion phase are considered the second and last step in the M&A process (Boone and Mulherin, 2007). All M&As that are publicly announced are considered in the database. After the M&A is announced the firms enter into
negotiation to reach deal completion, this can take several months (Dikova, et. al., 2010).
The number of failed M&As is calculated by subtracting the number of announced M&As with the number of completed M&As in the sample period. The validity of taking this measure to serve as a proxy of M&A failure is based on studies of Dikova et. al (2010) and Erel, Liao and Weisbach (2012) in which M&A failure is operationalized by measuring the M&As that did not progress past the announcement phase.
Table 1: Target countries for M&A in sample
Source: Adapted from Jones, 2007
British Africa Date of colonization Date of independence Françafrique Date of colonization Date of independence Botswana 1885 1966 Algeria 1830 1962 Ghana 1821 1957 Benin 1894 1960
Kenya 1920 1963 Burkina Faso 1919 1960
Nigeria 1900 1960 Cameroon 1919 1960 South Africa 1848 1964 Central African Republic 1910 1960 Sudan 1909 1956 Chad 1920 1960
Uganda 1894 1962 Congo Republic Of 1910 1960
Tanzania 1920 1960 Ivory Coast 1882 1960
4. METHOD
4.1 Variables en model construction
In order to find conclusive support for the research question, that countries with colonial ties have a lower M&A failure rate than countries without this relationship, the existence of a colonial effect must be found. Regression analysis is used to test whether the percentage of M&A failure between countries with colonial ties are significantly lower than for countries without this relationship. According to binary logistic regression the dependent variable should be coded 1 if the event occurs. Therefore, the dependent variable is coded as 1 for M&A failure and 0 for M&A completion. The independent variable, colonial ties, is a dichotomous variable as well and accordingly it is coded as 1 when there are colonial ties. Thus, France and Great Britain are coded as 1 in their former colonies and the countries from the rest of the world group are coded as 0.
To test the robustness of the independent variable, control variables are added to the model to ensure that a possible significant relationship between the independent variable and the dependent variable is not the result of a variable that is not included in the model. The control variables are: GDP size, GDP growth, intellectual property rights protection, corruption control and financial openness to foreigners. The GDP variables are compiled from World Bank data, the other control variables are from the institutional profiles database of the actionable governance
indicators data portal (World Bank). The GDP variables have been included since it is expected that GDP size and GDP growth have an influence on the failure rate of M&As. The numbers that are entered in the model for GDP size and GDP growth are the averages over the sample period, thus from 1997 until 2012. In addition, strictly regulated intellectual property right protection is
conducive of economic growth, therefore it is included as a control variable since it is expected that countries that have efficient intellectual property right protection have a lower M&A failure rate. Moreover, the control of corruption in a country is included to control for the expected effect that countries with a low control of corruption have a higher M&A failure rate. The control variable financial openness measures the degree to which a country is open to foreign capital. It is expected that a high degree of openness of foreign capital leads to a lower failure rate of M&As, therefore this control variable is added to the model.
based on geographic distance and not on the seven dimensions of Bae and Salomon (2007), rendering it not useful as a control variable in the model for this thesis. Moreover, the institutional profiles database of the World Bank offers a possibility to calculate the institutional distance for country pairs. However, individual scores on all indicators in this database have to be taken
together and compared to that of the other country in a country pair. Unfortunately, the restricted time for this master thesis prevented the calculation of institutional distance, since there are a total of around 400 country pairs in the various samples.
After the number of completed and failed M&As in the sample has been established, a regression analysis will be performed to measure whether colonial ties are a significant predictor in explaining the probability of M&A failure. To perform the regression analysis, a logistic regression is better suited than a linear regression, since the dependent variable is a binary dependent variable and a linear regression might calculate incorrect estimates (Hosmer and Lemeshow, 2000). Discriminant analysis could perform the regression as well, however, logistic regression is necessary since the independent variable and the control variables are a mix of categorical and continuous data (Burns and Burns, 2008). Logistic regression analysis measures what a ‘1' increase in the independent variable and control variables has on the probability of group membership (failure). In other words: the independent variable and the control variables are used to estimate the probability that an observation is member of the failure group. See formula 1 for the regression equation stating the full model.
logit(p) = a + 𝛽1𝑐1 + 𝛽2𝑓2 + 𝛽3𝑔𝑠3 + 𝛽4𝑔𝑔4 + 𝛽5𝑓𝑜5 + 𝛽6𝑝𝑟6 + 𝛽7𝑐𝑐7 (1)
Where:
p = the probability that a case is in a particular category a = the constant of the equation
𝛽 = the coefficient of the predictor variables
c = colonial ties f = failure gs = GDP size gg = GDP growth fo = financial openness
4.2 Method Assumptions
The assumption tests for logistic regression are not extensive. The independent variable does not need to be: normally distributed, linearly related, nor of equal variance (Burns and Burns, 2008). Linearity between the dependent and independent variables is not needed because a non-linear log transformation is applied to the predicted odds ratio. However, a criterion of logistic regression is that every case must be mutually exclusive and thus can only be in one group (Burns and Burns, 2008). This means that if one deal involves the acquisition of two entities in the same country or another country, this deal can only be included once in the sample. Moreover, this refers to the fact that the error terms need to be from independent sampling. The sample satisfies this condition because each observation occurs on one point in time. Lastly, the requirement is satisfied that the ratio of observations to independent variable must be at least ten to one. Other method
assumptions are discussed in more detail below. Internal consistency
Cronbach’s Alpha is calculated to ensure that variables that are a combination of several indicators have internal consistency reliability. Three control variables are composites of multiple indicators from the World Bank institutional development dataset. These variables are financial openness, property rights protection and corruption control. All variables have a value of Cronbach’s Alpha above the (α = 0.80), which is classified as good according to Gliem and Gliem (2003) with an average of (α = 0.85). Appendix B offers the full details of Cronbach’s Alpha calculated for these variables.
Multicollinearity
Multicollinearity is tested by assessing the variance inflation factor (VIF) for each variable. Testing for multicollinearity is important because the risk of including a variable that has multicollinearity issues is that standard errors are being reported as too large and thus give imprecise information or underestimate the effect that a variable has on the dependent variable (Field, 2013).
same concept. In the model France vs. Great Britain in British Africa, the variable GDP size also had multicollinearity issues. Following above mentioned reasoning this variable was dropped from the model as well. The results of the multicollinearity tests are presented in appendix C.
Model fit
5. RESULTS
5.1 Descriptive statistics
Three models have been created in order to test the hypotheses. Françafrique, in which French M&As are compared with M&As of firms from the rest of the world in former colonies of France in Africa. British Africa, in which British M&As are compared with M&As of firms from the rest of the world in former colonies of Great Britain in Africa. Lastly, a model in which French M&As in Françafrique are compared with British M&As in British Africa. Each model thus has two groups of interest in which the following values of the independent- and control variables are recorded in the descriptive statistics tables below: mean, standard deviation, minimum and maximum value. The control variable GDP size is measured in billion U.S. dollars. In addition, appendix E offers a correlation table of each model.
Françafrique
The descriptive statistics for Françafrique in table 2 indicate that French firms have not been able to make use of the fact that France has less institutional distance to their former colonies than other countries. The failure rate of M&As of French firms in Françafrique is higher than that of firms from the rest of the world. Furthermore, the largest difference between the two groups is that French firms pursue M&As in countries with a higher GDP than firms from the rest of the world.
Table 2. Descriptive statistics M&As in Françafrique
France Rest of the world
Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max.
Failure ,28 ,45 ,00 1,00 ,26 ,44 ,00 1,00 GDP Growth 3,53 1,46 1,50 7,21 3,66 1,31 1,50 7,21 GDP Size 33,05 36,43 2,44 106,11 28,31 34,62 1,45 106,11 Financial Openness 2,66 ,69 1,00 3,60 2,64 ,72 1,00 3,60 Property Rights Corruption Control 1.41 1,70 ,44 ,55 ,25 1,00 1,75 2,50 1,32 1,70 ,49 ,55 ,25 1,00 1,75 2,50 British Africa
Table 3. Descriptive statistics M&As in British Africa
Great Britain Rest of the world
Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max.
Failure ,24 ,43 ,00 1,00 ,24 ,43 ,00 1,00
GDP Growth 3,43 1,51 -1,82 6,61 3,87 1,48 -1,82 6,61
GDP Size 173,04 92,96 6,76 229,17 154,26 98,45 6,76 229,17
Financial Openness 2,69 ,69 1,00 4,00 2,61 ,77 1,00 4,00
Corruption Control 2,09 ,43 1,00 3,00 2,05 ,47 1,00 3,00
France vs. Great Britain
The comparison between French M&As in Françafrique and British M&As in British Africa in table 4 illustrates that in their respective former colonies British firms indeed have a lower failure rate. In addition, there is a large difference in the average GDP size of the countries, with the average GDP size of British Africa being far larger than that of Françafrique.
Table 4. Descriptive statistics French M&As in Françafrique and British M&As in British Africa
France Great Britain
Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max.
Failure ,28 ,45 ,00 1,00 ,24 ,43 ,00 1,00
GDP Growth 3,53 1,46 1,50 7,21 3,43 1,51 -1,82 6,61
GDP Size 33,05 36,43 2,44 106,11 173,04 92,96 6,76 229,17
Financial Openness 2,66 ,69 1,00 3,60 2,69 ,69 1,00 4,00
Corruption Control 1,70 ,55 1,00 ,50 2,09 ,43 1,00 3,00
Although not stated as a hypothesis, when analysing the data and comparing the failure rates of French and British M&As in various samples, interest was provoked to compare these two countries on different levels. Therefore, the failure rate of British M&As in the British Africa sampleand French M&As in British Africa are compared, in addition to the failure rate of French M&As in Françafrique and British M&As in Françafrique.
Great Britain vs. France in British Africa
sample in table 5, it was found that French firms have a much lower M&A failure rate than British firms in British Africa. Moreover, French firms attempt M&As in British Africa in countries that score on average higher on all other variables, GDP growth, financial openness and corruption control than the countries in which British firms attempt M&As in.
Table 5. Descriptive statistics British and French M&As in British Africa
Great Britain France
Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max.
Failure ,24 ,43 ,00 1,00 ,11 ,32 ,00 1,00
GDP Growth 3,43 1,51 -1,82 6,61 3,70 1,06 3,20 6,61
Financial Openness 2,69 ,69 1,00 4,00 2,88 ,64 1,00 4,00
Corruption control 2,09 ,43 1,00 3,00 2,21 ,25 1,00 3,00
France vs. Great Britain in Françafrique
The failure rate of French M&As and British M&As in the Françafrique sample are compared in table 6. It was found that British firms have a much lower M&A failure rate than French firms in
Françafrique. On the other hand, French M&As in Françafrique score higher on all other variables GDP growth, financial openness and corruption control than the British M&As in Françafrique.
Table 6. Descriptive statistics French and British M&As in Françafrique
France Great Britain
Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max.
Failure ,28 ,45 ,00 1,00 ,11 ,32 ,00 1,00 GDP Growth 3,53 1,46 1,50 7,21 3,16 1,42 1,50 7,21 GDP Size 33,05 36,43 2,44 106,11 26,49 36,47 2,26 106,11 Financial Openness 2,66 ,69 1,00 3,60 2,56 ,87 1,00 3,60 Property Rights Corruption Control 1,41 1,70 ,44 ,55 ,25 1,00 1,75 2,50 1.37 1,63 0.47 ,47 0.25 1,00 1.75 2,50
5.2 Logistic regression results
significant influence on the probability of an M&A being a failure or success. The effect size is determined by the EXP(B), which reflects how much the probability of a failure is affected by an increase of ‘1’ in the independent or a control variable. The EXP(B) value is interpreted in the following way: when the value is larger than one there is an increased probability of failure, while a value smaller than one indicates a decreased probability of failure. For each sample two models are presented, model 1: including the control variables and the constant, and model 2: including the control variables, the independent variable and the constant.
Françafrique
For the sample of Françafrique the following was hypothesized: Hypothesis 1. The failure rate of
M&As in Françafrique between French firms and Françafrique firms will be lower than M&As between ROW firms and Françafrique firms. The failure rate of M&As of French firms in Françafrique is higher
than that of firms from the rest of the world, although this is not a significant contributor to the prediction of M&A failure as can be seen in table 7. GDP growth (p = .020) and financial openness (p
= .031) make a significant contribution to the prediction of the dependent variable in both models.
An increase of ‘1’ in GDP growth and financial openness leads to a higher probability of failure of M&As in Françafrique of (Exp(B) = 1.48) and (Exp(B) = 1.72) times.
Table 7. Regression results in Françafrique
France and ROW
Model 1 Exp(B) Model 2 Exp(B)
Control Variables GDP Growth ,392** (,167) 1,480 ,390** (,167) 1,477 GDP Size ,007* (,004) 1,007 ,007 (,004) 1,007 Property Rights -,419 (,406) ,658 -,433 (,408) ,648 Financial Openness ,544** (,252) 1,724 ,544** (,252) 1,723 Corruption Control -,569 (,354) ,566 -,566 (,354) ,568 Independent variable Colonial ties Constant Observations (N) -2,685** (1,378) 237 ,068 ,163 (,364) -2,698** (1,338) 237 1,177 ,067
British Africa
Regarding the British Africa sample the following relationship was predicted: Hypothesis 2. The
failure rate of M&As in British Africa between British firms and British Africa firms will be lower than M&As between ROW firms and British Africa firms. The descriptive statistics of British Africa in table
3 showed that there was a large difference in the average GDP size of the countries in which firms from Great Britain and firms from the rest of the world attempted M&As. As table 8 indicates GDP size also makes a significant contribution to the prediction in both models (p = .016). However, the effect this control variable has on the prediction of M&As failure was very small (B = .000). Colonial ties makes no significant contribution in the prediction of M&A failure.
Table 8. Regression results in British Africa
Great Britain and ROW
Model 1 Exp(B) Model 2 Exp(B)
Control Variables GDP Growth ,042 (,048) ,959 -,042 (,167) ,958 GDP Size ,000** (,000) 1,000 -,000** (,004) 1,000 Financial Openness -,122 (,126) ,885 -,122 (,126) ,885 Corruption Control ,284 (,177) 1,328 -,284 (,177) 1,328 Independent variable Colonial ties Constant Observations (N) -,887** (,364) 1239 ,413 -,005 (,165) -,882** (,368) 1239 ,995 ,414
France vs. Great Britain
Concerning the M&As of French and British firms in both their respective former colonies the following was hypothesized: Hypothesis 3. The failure rate of M&As between French firms and
Françafrique firms will be higher than the failure rate of M&A between British firms and British Africa firms. Table 9 indicates that the independent variable colonial ties makes a significant contribution
to the prediction (p = .043). However, since both France and Great Britain have colonial ties to the countries in the sample, the variable colonial ties does not indicate whether colonial ties exist. Moreover, the variable acts as a way to differentiate between M&AS attempted by French and by British firms. As the value of colonial ties rises with ‘1’ (from France to Great Britain) the likelihood of failure is (Exp(B) = 2.6) times higher, this is contrary to the hypothesized direction. Meaning that M&As of British firms in their respective former colonies are more likely to fail than French M&As in their former colonies. In addition, in both models the variable financial openness makes a
significant contribution to the prediction (p = .002). As the value of financial openness rises with ‘1’ the likelihood of failure is (Exp(B) = 2.4) times higher. Moreover, in both models the variable GDP size was significant (p = .002), however the coefficient was very small (B = -.006).
Table 9. Regression results Françafrique and British Africa
France and Great Britain
Model 1 Exp(B) Model 2 Exp(B)
Control Variables GDP Growth -,009 (,088) ,991 -,031 (,087) ,969 GDP Size -,004** (,002) ,996 -,006*** (,002) ,994 Financial Openness ,607*** (,228) 1,834 -,861*** (,268) 2,366 Corruption Control -,449 (,342) ,639 -,569 (,350) ,566 Independent variable Colonial ties Constant Observations (N) -1,273* (,676) 319 ,280 ,963** (,475) -2,089*** (,789) 319 2,620 ,124
Great Britain vs. France in British Africa
The regression results in table 10 display that the variable colonial ties makes a significant
contribution to the prediction of the dependent variable (p = .059). As the value of colonial ties rises with ‘1’ (from France to Great Britain) the likelihood of failure in the British Africa sample is (Exp(B) =
2.4) times higher. Hence, in British Africa, M&As of British firms are more likely to fail than M&As of
French firms. While it would be expected that because of the smaller institutional distance, British firms would have a lower M&A failure rate than French firms.
Table 10. Regression results in British Africa
Great Britain and France
Model 1 Exp(B) Model 2 Exp(B)
Control Variables GDP Growth ,015 (,087) 1,015 ,027 (,088) 1,027 Financial Openness ,095 (,274) 1,100 ,119 (,279) 1,126 Corruption Control -,618 (,438) ,539 -,571 (,442) ,565 Independent variable Colonial ties Constant Observations (N) -,309 (,710) 319 ,734 -,871* (,460) -1,266* (,869) 319 2,389 ,282
France vs. Great Britain in Françafrique
The regression results in table 11 indicate that in this sample, GDP growth makes a significant contribution to the prediction of M&A failure in both models of (p = .060). As the size of GDP increases, the likelihood of failure is (Exp(B) = 1.9) times larger. In addition, the variable financial openness makes a significant contribution to the prediction in both models of (p = .068). As the financial openness increases with ‘1’, the likelihood of failure is (Exp(B) = 2.7) times higher. These two effects are observed in both models. Although the descriptive statistics displayed that the failure rate of British M&As was much lower than that of French M&As in Françafrique, the corresponding variable colonial ties did not proof to be a significant variable in the prediction of the dependent variable.
Table 11. Regression results in Françafrique
France and Great Britain
Model 1 Exp(B) Model 2 Exp(B)
Control Variables GDP Growth ,737** (,343) 2,089 ,657* (,349) 1,929 GDP Size -,010 (,011) ,990 -,011 (,011) ,989 Property Rights 1,235 (,999) 3,439 1,086 (1,012) 2,962 Financial Openness 1,041* (,548) 2,831 1,009* (,554) 2,744 Corruption Control -1,085 (,696) ,338 -1,026 (,696) ,358 Independent variable Colonial ties Constant Observations (N) -6,278 (2,806) 73 ,002 ,461 (,746) -6,354 (2,819) 73 1,586 ,002
6. DISCUSSION
This thesis had as its aim to research whether colonial ties have an effect on the failure rate of M&As. Specifically of interest were the M&As between a target firm from a former colony and an acquiring firm from the former colonizer. It was hypothesized that firms from France and Great Britain had a smaller institutional distance to firms in the target countries, by being the former colonizer, than firms from other countries. Moreover, building on theory that a greater institutional distance increases M&A failure, it was expected that M&As involving firms from countries with colonial ties had a smaller probability of M&A failure.
The analysis of the data resulted in some surprising findings. For both the Françafrique sample as the British Africa sample colonial ties were not a significant predictor of M&A failure. The findings in this thesis fail to offer support that having colonial ties reduces M&A failure; however, some control variables had a significant effect on predicting the probability of M&A failure. Shortly after
independence the economic ties between the former colonizer and colony were still very strong as Srivasta and Green (1986) showed. However, as mentioned before, their data was from shortly after the colonies obtained independence, while the data in this thesis is from 35 to 50 years after
independence. Moreover, since their independence, the former colonies have increasingly opened up to the world economy. They have forged ties with an increasing number of countries and thus decreased dependency on the former colonizer. Hence, it is likely that the effect of colonial ties has diminished, as is also confirmed by the results of the analysis conducted in this thesis.
For the Françafrique sample a higher GDP growth and financial openness significantly increase the probability of M&A failure. When countries grow faster this will likely coincide with a greater inflow of foreign capital, increasing the number of attempted M&As in the country. The number of
attempted M&As is strongly influenced by the global economic climate, when there is a higher GDP growth, more M&As are attempted. Appendix F offers the volume of global cross-border M&As over the last years. As these countries do not have well developed economic institutions, the failure rate of M&As remains high. Moreover, because of this economic growth firms are willing to take more risks and the probability of M&A failure rises. A possible explanation why this effect is only apparent in the Françafrique samples and not in the British Africa samples could be that the countries in British Africa are more developed, illustrated by their greater GDP size, and therefore probably have more effective economic institutions. The control variable financial openness had a significant positive effect on the probability of M&A failure in all Françafrique samples. An
increase of M&A initiatives while the institutions remain of the same quality, resulting in a higher failure rate of M&As.
A potential explanation why in the British Africa sample colonial ties did not have a significant effect on M&A failure could be that there are several countries with more or less the same institutional distance to the countries in the British Africa sample as Great Britain has. Countries as the United States, Canada, Australia and South Africa share the same language and law system as Great Britain and are themselves former colonies of Great Britain. Therefore, the effect of colonial ties for Great Britain could have been reduced since countries with a similar distanceto the countries in British Africa are in the rest of the world group of the sample. In order to test whether this is the case M&As of firms from the United States, Canada, Australia and South Africa were removed from the ROW part of the sample and formed a new group with the M&As conducted by British firms. This group is then compared to the new smaller rest of the worldgroup. The descriptive statistics in table 12 showed a failure rate of 26% for Great Britain plus the United States, Canada, Australia and South Africa, and of 22% for the rest of the worldgroup.
Table 12. Descriptive statistics in British Africa
Great Britain (plus the United States, Canada, Australia Rest of the world and South Africa)
Mean Std. Dev. Min. Max. Mean Std. Dev. Min. Max.
Failure ,26 ,44 ,00 1,00 ,22 ,42 ,00 1,00
GDP Growth 3,63 1,65 -1,82 6,61 3,94 1,29 -1,82 6,61
GDP Size 157,70 92,96 6,76 229,17 158,88 95,97 6,76 229,17
Financial Openness 2,67 ,75 1,00 4,00 2,58 ,75 1,00 4,00
Corruption Control 2,07 ,46 1,00 3,00 2,05 ,45 1,00 3,00
Regression analysis revealed that also in this different configuration the variable colonial ties does not have a significant effect, with the corresponding values shown in table 13. As in the original configuration of the British Africa sample, GDP size has a small (B = -.006) yet significant effect (p =
.002) in both models. These findings offer no support that a possible effect of colonial ties on M&A
Table 13. Regression results in British Africa
Great Britain (plus the United states, Canada, Australia and South Africa) and ROW
Model 1 Exp(B) Model 2 Exp(B)
Control Variables GDP Growth ,042 (,048) ,959 -,030 (,136) ,970 GDP Size ,002** (,001) ,998 -,002** (,001) ,998 Financial Openness -,122 (,126) ,8942 -,151 (,126) ,860 Corruption Control ,284 (,177) 1,328 -,289 (,178) 1,336 Independent variable Colonial ties Constant Observations (N) -,884** (,364) 1239 ,413 ,185 (,136) -1,000*** (,377) 1239 1,203 ,368
*** p < 0.01 level, ** p < 0.05 level, * p < 0.10 level
The comparison between France and Great Britain in their respective former colonies showed that in Françafrique both the overall failure rate of M&As and the failure rate of M&As of French firms were higher than the overall failure rate of M&As in British Africa and of M&As of British firms in British Africa. However, this was not significant, to the contrary, British M&As in British Africa were significantly more likely to fail than French M&As in Françafrique. It was expected that because of the more market-oriented and more efficient British institutions (Grier, 1999) the failure rate of British M&As in British Africa would be lower. An explanation why this effect was not found could be that the transplantation of the effective British institutions has not been as effective in former colonies as assumed. Kymlicka (1995) argues, that most of the time it is not sufficient to transplant an institution, rather institutions need translation to fit the local environment in order to be effective. As this was not the case in the former British colonies, the institutions in the countries of British Africa might not be as effective as previously assumed.
subsidiary survival (Gaur and Lu, 2007). In British Africa French firms have a larger institutional distance than British firms, yet a lower M&A failure rate. Moreover, in Françafrique British firms have a larger institutional distance rate than French firms, yet also a lower M&A failure rate. This supports an extension of the concept of institutional arbitrage to the theory on M&A failure. As a moderate rather than a small institutional distance reduces the probability of M&A failure. Jeon and Ligon (2011) found support that when an acquiring firms already owns a five per cent or larger stake in the target firm, the probability of the M&A being a success rises. This was also tested in our sample, however the results were inconclusive. In the Françafrique sample M&As of firms that already had such a stake in the target firm had a failure rate of 29% while the overall failure rate in the sample was 26%. On the other hand, in the British Africa sample M&As of firms that already had a five per cent or larger stake in the target firm had a failure rate of 19% while the overall failure rate in the sample was 24%. Thus, in the Françafrique sample possessing stock of five per cent or more in the target firm does not decrease the failure rate of an attempted M&A in the same firm, while in the British Africa sample having stock in the target firm does lower the failure rate.
7. CONCLUSION
7.1 Implications for practice
The implications this thesis has for management should be interpreted carefully. As mentioned before, there are many factors that influence whether a firm attempts an M&A and whether an M&A is successful or not. What this thesis did contribute to practice is that regarding M&A failure, being an acquiring firm from a country that has colonial ties to the country of the target firm does not decrease the probability of the M&A failing. The fact that French and British firms have the highest number of attempted M&As in their former colonies is in line with the expectation that former colonizers would have a larger economic presence in their former colonies than other countries. Thus firms from France and Great Britain favour investing in these countries more than firms from other countries; however, they are less successful than firms from other countries in these former colonies. In addition, M&As of French and British firms are more successful in other countries than their former colonies. The implication than is that even if firms have a smaller institutional distance due to colonial relations firms should assess M&A on the merits of the deal itself and do not expect any benefits from the fact that the target firm is located in a former colony. Moreover, if managers of firms from countries with colonial ties are not aware of this, they put the firm at risk of engaging in irrational firm behaviour by attempting M&As in former colonies and expecting benefits because of colonial ties while these benefits will befall them.
7.2 Implications for theory
7.3 Future research and limitations
For future research it would be interesting to conduct a similar research in other former colonies, for example in South America or in Asia, to see how failure rates of M&As by former colonizers in those countries compare to the results found in this thesis. In addition, it would be interesting for future research to explore how exactly colonial ties influence the institutional distance between two countries. The theory section of this thesis argued that colonial ties have an enduring influence and continue to be a relevant explanatory factor for economic performance of countries. It would be interesting to expand research on this topic and explore how colonial ties continue to effect business dealings of firms to this day. This thesis has tried to explore this effect of colonial ties in the current day international business world.
Regarding the evidence this thesis offers on the relationship between institutional distance and M&A failure an important limitation has to be mentioned. The countries included in the rest of the world group range from neighbouring countries of the target countries to countries from the other side of the world. Consequently, there are countries in the rest of the world sample that have a smaller institutional distance to the target country than the former colonizer has. For example, Zimbabwe is part of the rest of the world group since there are firms from Zimbabwe that have conducted M&As in South Africa, one of the target countries. However, Zimbabwe has a smaller institutional distance to South Africa than Great Britain. This could mean that by including M&As of Zimbabwean firms in South Africa, the assumption that Great Britain has a smaller institutional distance than the rest of the world group is weakened. Therefore, in future research on this topic it would be beneficiary to subdivide the sample of the rest of the world countries in various
References
Acemoglu, D., Johnson, S., & Robinson, J. A. 2001. The Colonial Origins of Comparative Development – An empirical investigation. American Economic Review, 91(5): 1369-1401. Acemoglu, D., Johnson, S., & Robinson, J.A. 2005. Institutions as a Fundamental Cause of Long-Run Growth. In Aghion, P., & Durlauf, S. N. 2005. Handbook of Economic Growth, Volume 1, Part A, Pages 385–472.
Bae, J.H., & Salomon, R. 2010. Institutional distance in international business research. Advances in International Management, 23: 327–349.
Baldwin, R. 2006. Globalisation: the great unbundling(s)”, Chapter 1, in Globalisation challenges for Europe, Secretariat of the Economic Council, Finnish Prime Minister’s Office, Helsinki.
Bates T. W., & Lemmon M. L. 2003. Breaking up is hard to do? An analysis of termination fee provisions and merger outcomes. Journal of Financial Economics, 69, 469-504.
Bertocchi, G., & Canova, F. 2002. Did colonization matter for growth? An empirical exploration into the historical causes of Africa’s underdevelopment. European Economic Review, 46(10): 1851–1871. Betts, R. F. 1966. The Scramble for Africa: Causes and Dimensions of Empire. Boston: Heath. Boone, A. L., & Mulherin, J. H. 2007. How are firms sold? The Journal of Finance, 112(2): 847–875. Cartwright, S., & Schoenberg, R. 2006. Thirty years of mergers and acquisitions research: Recent advances and future opportunities. British Journal of Management, 17: s1–s5.
Chan, C. M., Isobe, T., & Makino, S. 2008.Which country matters? Institutional development and foreign affiliate performance. Strategic Management Journal, 29(11): 1179–1205.
Dikova, D., Rao Sahib, P., & Van Witteloostuijn, P. 2010. Cross-border acquisition abandonment and completion: The effect of institutional differences and organizational learning in the international business service industry, 1981–2001. Journal of International Business Studies, 41(2): 223-245. Djankov, S., Glaeser, E., La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. 2003. The New
Comparative Economics, Journal of Comparative Economics, 31(4): 595-619.
Eden, L., Miller, S. R. 2004. Distance matters: Liability of foreignness, institutional distance and ownership strategy. In Hitt, M. A., & Cheng, J. L. C. Theories of the Multinational Enterprise: Diversity, Complexity and Relevance. Emerald Group Publishing Limited, 187-221.
Erel, I., Liao, R. C., & Weisbach, M. S. 2012. Determinants of cross-border mergers & acquisitions. Journal of Finance, 67(3): 1045-1082.
Ernst and Young 2012 Africa by numbers – Assessing market attractiveness in Africa. Ernst and Young (2013) Ernst and Young’s Africa attractiveness survey.
Field, A. P. 2013. Discovering statistics using IBM SPSS Statistics (4th edition). London: Sage
publications.
Gardinier, D. E. 2000. France and Gabon since 1993: The Reshaping of a Neo-Colonial Relationship. Journal of Contemporary African Studies, 18(2): 225-242.
Gaur, A. S., & Lu, J. W. 2007. Ownership strategies and survival of foreign subsidiaries: Institutional distance and experience. Journal of Management, 33(1): 84–110.
Gliem J. A., Gliem, R. R. 2003. Calculating, interpreting, and reporting Cronbach's alpha reliability coefficient for Likert-type scales. Midwest Research to Practice Conference in Adult, Continuing, and Community Education: 82–8.
Grier, R. M. 1999. Colonial Legacies and Economic Growth. Public Choice, 98(3): 317-35. Groot, H. L. F. de, Linders, G. M., Rietveld, P., & Subramanian, U. 2004. The institutional determinants of bilateral trade patterns. Kyklos, 57(1): 103–123.
Hitt, M. A., King, D., Krishnan, H., Makri, M., & Schijven, M. 2009. Mergers and acquisitions: overcoming pitfalls, building synergy, and creating value. Business horizons, 52(6): 523-529. Hofstede, G. 2001. Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. California: Sage Publications.
Hosmer, D. W., & Lemeshow, S. 2000. Applied logistic regression. New York: Wiley. Jensen, M. C. 1988. Takeovers: Their Causes and Consequences. The Journal of Economic Perspectives, 2(1): 21-48.
Jeon, J. Q., & Ligon, J. A. 2011. How much is reasonable? The size of termination fees in mergers and acquisition. Journal of Corporate Finance, 17(4): 959–981.
Jones, P. 2007. Did the Colonial Powers Pick the Economic Winners? Unpublished doctoral dissertation, Vassar College, New York.
Kostova, T. 1996. Success of the transnational transfer of organizational practices within multinational firms. Unpublished doctoral dissertation, University of Minnesota.
Kostova, T., & Zaheer, S. 1999. Organizational legitimacy under conditions of complexity: The case of the multinational enterprise. Academy of Management Review, 24(1): 64-81.
Kymlicka, W. 1995. Multicultural citizenship: A Liberal Theory of Minority Rights. Oxford: Oxford University Press.
La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. W. 1998. Law and finance. Journal of Political Economy, 106(6): 1113-1155.
La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. 2008. The Economic Consequences of Legal Origins. Journal of Economic Literature, 46(2): 285-332.
Lee, A., & Schultz, K. A. 2012. Comparing British and French Colonial Legacies: A Discontinuity Analysis of Cameroon. Quarterly Journal of Political Science, 7(4): 365‐410.
Levine, P. 2013. The British Empire: Sunrise to sunset. Oxford: Taylor & Francis
Martynova, M., & Renneboog, L. 2008. A Century of Corporate Takeovers: What Have We Learned and Where Do We Stand? Journal of Banking and Finance, 32(10): 2148-2177.
Mayer, T. & Zignago, S. 2011. Notes on CEPII's distances measures: The GeoDist database. CEPII Working Paper 25 -12-2011,Centre d'Etudes Prospectives et d'Informations Internationales. Michalopoulos, S., & Papaioannou, E. 2011. The Long-Run Effects of the Scramble for Africa. Working Paper no. 17620, National Bureau of Economic Research, Massachusetts.
North, D. C. 1990. Institutions, institutional change, and economic performance. Cambridge: Cambridge University Press.
Osterhammel, J. 2005. Colonialism: A theoretical overview. New Jersey: Markus Wiener Publishers.
Rugman A. M., & Verbeke, A. 1992. A note on the transnational solution and the transaction cost theory of multinational strategic management. Journal of International Business Studies, 23(4): 76 1-772.
Srivastava, R. K., & Green, R. T. 1986. Determinants of Bilateral Trade Flows. The Journal of Business, 59(4): 623-640.
Very, P., & Schweiger, D. M. 2001. The acquisition process as a learning process: Evidence from a study of critical problems and solutions in domestic and cross-border deals. Journal of World Business, 36(1): 11–31.
Worger, W. H., Clark, N. L., & Alpers, E. A. 2010. Africa and the West - Volume 2 from colonialism to independence, 1875 to present. New York: Oxford university press.
Wolfe, P. R. 1999. Settler Colonialism. London: Cassell. Online sources:
Châtelot, C. Au bon souvenir de la Françafrique. Le Monde, 09-05-2013 http://www.lemonde.fr/idees/article/2013/05/09/au-bon-souvenir-de-la-francafrique_3174091_3232.html
GDP Growth. 15-12-2013. http://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG GDP Growth. 10-10-2013. www.oecd.org
GDP. 15-12-2013. http://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG Haski, P. The Return of Françafrique. New York Times, 21-07-2013
http://www.nytimes.com/2013/07/22/opinion/global/the-return-of-francafrique.html?_r=0 Institutional profiles database- Actionable governance indicators data portal, Worldbank. 01-11-2013 http://www.agidata.org/Site/SourceProfile.aspx?id=21
Melly, P. The cosy relations between France and Africa. BBC, 13-09-2011 http://www.bbc.co.uk/news/world-africa-14898197
The French African Connection. Aljazeera, 23-08-2013
http://www.aljazeera.com/programmes/specialseries/2013/08/201387113131914906.html
Burns, R. P., & Burns, R. A. Business Research Methods and Statistics Using SPSS. California: Sage Publications, 11-2008. http://www.uk.sagepub.com/burns/chapters.htm
APPENDICES
Appendix A1: Africa before the Scramble for Africa
Source: Pearson Education, Inc.
Appendix A2: Africa after the Scramble for Africa
a. Appendix 1c: Africa after first world war Source: Michigan State University
Appendix A3: Africa after the First World War
Source: The New Society for the Diffusion of Knowledge
Appendix B: Internal consistency
Financial Openness
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted VAR00001 9,9231 16,154 ,531 ,435 ,849 VAR00002 9,6538 15,115 ,560 ,441 ,843 VAR00003 8,8462 13,335 ,700 ,538 ,807 VAR00004 8,8846 14,026 ,711 ,834 ,804 VAR00005 9,0000 12,880 ,801 ,870 ,777 Corruption Control
Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted VAR00001 5,5000 3,780 ,588 ,436 ,801 VAR00002 5,2308 3,785 ,527 ,366 ,821 VAR00003 5,0000 2,720 ,653 ,568 ,782 VAR00004 5,0385 2,678 ,866 ,751 ,655
Property Rights Protection
