Transitions of power mark an inflection point in any society. They come about in all forms—elections, successions, coups, and conflicts—but in each case, it is an instance of a country embarking on a new path. In the field of development economics, it is thus essential to understand how the level of success of these power transitions impact the development of the nation. Specifically, the authors of this paper set out to determine to what extent change in foreign direct investment flows can be explained by the level of success of a transition of power. We conclude that maintaining or increasing good governance practices during a transition of power is a significant explanatory factor for changes in Foreign Direct Investment (FDI) and discuss the potential policy implications.
Transitions of power are a fragile moment in which governance can take an improving or deteriorating path. This paper varies from the existing literature on the impact of the perceived quality of governance on Foreign Direct Investment (FDI) flows by introducing the question of transitions of power (Rodríguez-Pose and Cols 2017, 64). Thus, it will research how their level of success can explain changes in FDI flows. This is an especially pertinent question on the African continent, which lags behind the rest of the world in most development indicators and has endured many transitions of power. It will first review the literature used to construct the model, describe the methodology, explain and discuss the results, and finally, conclude with some policy recommendations.
The work of Cols and Rodríguez-Pose on the role of quality of governance in the distribution of FDI in sub-Saharan Africa provides a starting framework for our discussion (Rodríguez-Pose and Cols 2017, 64). The authors identify the determinants of gross FDI flows in 22 sub-Saharan African countries over the period from 1996 to 2015. This paper focuses on measuring changes in FDI flows based on transitions of power in 38 African countries between the years 2000 and 2017.
Foreign Direct Investment
Since the mid-1980s there has been a steady increase in global FDI, of which developing countries were the first to benefit from. FDI in these countries recovered much faster after the 2008 financial crisis than in developed countries, accounting for 43 percent of the global share in 2015 (Rodríguez-Pose and Cols 2017, 65). However, this increase is focused mostly in Asian and Latin American countries. Even though in absolute terms recent flows in FDI have increased in Africa, in relative terms they have declined, and the continent remains the lowest recipient in the world (Onyeiwu and Shrestha 2004, 90). The existing economic literature attributes this to perceived riskiness of doing business on the continent, especially due to political instability (Asiedu 2002, 114; Onyeiwu and Shrestha 2004, 90; Rodríguez-Pose and Cols 2017, 70; Ajayi 2006, 8), lack of economic freedom in some countries (Onyeiwu and Shrestha 2004, 90), lack of adequate infrastructure (Ajayi 2006, 8; Rodríguez-Pose and Cols 2017, 64), and weak governance (Adeleke 2014, 127), among other factors. FDI is given to countries with “good institutions”, defined by Cols and Rodríguez-Pose as having “a credible and effective legal system, and being less corrupt” (Rodríguez-Pose and Cols 2017, 79).
Transition of Power
As characterized by Osaghae, a transition of power is seen as the interval period between one regime and the next (Osaghae 1995, 187). Thus, a successful transition of power is a change in regime that maintains or increases governmental functionality. The effectiveness of governance throughout a period of transition of power will be studied in order to understand how the government functionality affects the distribution of FDI. As taken by Cols and Rodríguez-Pose, this paper will use five indicators of good governance developed by Kaufmann, Kraay, and Mastruzzi and the World Bank: political stability and absence of violence, government effectiveness, regulatory quality, rule of law, and control of corruption (Kaufmann, Kraay, and Mastruzzi 2008, 1; Rodríguez-Pose and Cols 2017, 69-70). We will not be using the sixth indicator, voice and accountability, which is the World Bank’s variable measuring democracy (“Voice and Accountability Indicator,” n.d.), as a measure of whether a transition was successful. For the purpose of this paper, we define successful transition in terms of day-to-day functionality of the government rather than of democracy itself. The model however does control for this sixth indicator. Further details are discussed in the Methodology section.
There are other factors mentioned in the literature that affect the attraction of FDI in African countries. This paper focuses on three factors: change in natural resource endowments, democratic transitions, and changes in market size to control for effects on the attraction in FDI not caused by the good governance indicator.
Natural resources play an important role in African wealth, thus affecting the distribution of FDI (Rodríguez-Pose and Cols 2017, 71). According to the literature, the quantity and availability of natural resources affects the attraction of investment. Countries with poor availability of these resources draw little FDI (Deichmann et al. 2003, 29), whereas countries in the oil and mining industries are traditionally the largest recipients of FDI (Ajayi 2006, 6; Anyanwu 2011, 8).
Since the collapse of many authoritarian regimes in the 1990s, many African countries have undergone political transformation leading to democratization (Gibson, Hoffman, and Jablonski 2015, 2). A question studied in the literature is whether FDI is attracted to more corrupt and less democratic countries or vice versa. Gossel demonstrates that if there is a weak democracy in sub-Saharan Africa, investors use corruption as a ‘helping hand’, while with more democratic capital, corruption is used as a ‘grabbing hand’ (Gossel 2018). Asiedu and Lien show that democracy facilitates FDI in countries where natural resources
comprise a low proportion of their exports, but democratization has a negative impact on FDI in countries whose exports are dominated by natural resources (Asiedu and Lien 2011, 109).
The role of market size is debated in the literature. Some authors argue that small markets find it more difficult to attract foreign investors (Jenkins and Thomas 2002, 54; Asiedu 2006, 74-75). However, Asiedu adds that countries with small markets can attract FDI by improving their institutions (Asiedu 2006, 66). Rodríguez-Pose and Cols conclude that market size is insignificant in explaining FDI attraction, stating that even the largest markets in sub-Saharan Africa remain too small to influence investment decisions (Rodríguez-Pose and Cols 2017, 77).
Methodology and Data
Constructing a Good Governance index: In order to answer our research question, how the level of success of a transition of power impacts foreign direct investment in African countries, we had to create a unit of measurement for transition success. We specifically define “success” as maintaining or increasing functionality of government. With this in mind, we constructed a “good governance” variable as a measure of government functionality throughout a period of transition of power. We do this by utilizing variables from the Worldwide Governance Indicators (WGI) from the World Bank to construct an index that reflects the functionality of government in a given country. We use the indicators Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption (see Appendix 1). These indicators were originally constructed by the World Bank by surveying experts on each country each year and asking them to rate the country on the given indicator on a -2.5 (weak) to a 2.5 (strong) scale. We maintained this scale, and constructed our Good Governance index, which averages the five indicators on this scale.
We exclude a sixth World Bank indicator, Voice and Accountability, from our Good Governance index. We are not seeking to establish a relationship between democracy, which is a specific form of government, with FDI inflows within this paper, but instead are looking at the general structural stability of government after a transition of power at the top. Therefore, this paper is consciously not utilizing democracy as an indicator of transition success. While the authors of this paper certainly value democracy as a virtue and human right, whether the transition was democratic or not is not explicitly reflective of the government’s functionality after a transition. Thus, given that the fundamental question of this paper is how successful transitions impact foreign direct investment, we do not include it in our Good Governance index variable. We do however control for how democratic the transition was, which allows us to separate how democracy affects FDI as well as how government functionality affects FDI. This has important policy implications, which are expanded upon in our discussion section.
Calculating change in quality of governance: As per the study design, we define our independent variable as the change in governance quality during the time of transition. To calculate this change, we average the Good Governance index in the two years after the transition of power, as well as averaging the Good Governance index in the two years prior to the transition of power. Averaging these variables is intended to minimize the effect of outlier years that, for one reason or another, may have had an isolated event that impacted governance in the single calendar year. We then subtract the Good Governance index in the two years prior to transition from the Good Governance index in the two years after the transition.
We argue that an effective transition should raise or at least maintain the prior Good Governance index. That is, a successful transition should not create political instability, foment violence in the country, impede government effectiveness or its ability to regulate, inhibit the government’s ability to maintain rule of law, nor increase corruption. Therefore, a successful transition should have a positive, zero, or negligibly negative score in our independent variable. On the other hand, an unsuccessful transition where institutional quality is not maintained is expected to have a negative score in our independent variable.
To measure FDI, we utilize the World Bank’s database of FDI Net Inflow as a percentage of national GDP. With the aim to both control for temporary shocks and maintain consistency with the independent variable, FDI as a percentage of GDP is averaged in the two years prior to the transition as well as in the two years after the transition. The pre-transition average is then subtracted from the post-transition average to create a measurement of net change in FDI as a percentage of national GDP .
Scope of Analysis
This paper specifically focuses on transitions of power on the African continent. Accordingly, the 54 countries of Africa as designated by the World Bank are our dataset . We focus on transitions between the years from 2000 to 2017 as defined by the Brookings Institute (see Appendix 2). We chose this time frame due to both availability of data as well as world events. The earliest year that we have consistent WGI Scores is 1998. Consequently, it is not possible to have a change of Good Governance index for any transition occurring prior to 2000 due to insufficient data. We also cut transitions occurring after 2017. This was done to remove the effect that the COVID-19 pandemic would have on our data. It has been well-established that the pandemic had significant effects on FDI, which would significantly interfere with our measurements of how the level of success of a transition of power was impacting FDI (Zhenwei Qiang et al. 2021). While the pandemic’s effect on FDI is an important field of study, it is beyond the scope of this paper.
Selecting the Transitions
The most difficult part of selecting transitions is defining when the transition occurred. This is a messy business; after all, if transitions were clean-cut, there would be little reason to study how they impact FDI. Our conditions for selecting transitions to measure are not perfect, but they are, in our opinion, the most effective method to create a dataset that generates a large enough sample size, captures when a transition occurred, and does not double-count moments of instability within a given country. To that end, our conditions for inclusion are as follows:
- The prior Government was in place for more than two years prior to the transition. The averages we use for governance and investment are for the two years prior to the transition of power. Therefore, we want to be measuring the success of transition away from just the prior government, not multiple prior governments. In essence, we believe that to measure the level of success of a transition, there must be a clear government that has been in place for enough time that, by measuring the change in the independent variable, we are measuring the change from that government specifically.
- In a period of multiple transitions, we measure the two years after the first transition. Unlike for governments prior to the transition, we did not eliminate examples where there were multiple governments in quick succession post-transition. Instability is a sign of a bad transition, so we treat multiple transitions in quick succession as part of one larger transition in the country. It is not a perfect indicator, as governments do have agency in their decision-making, so one government post-transition may be more effective than another in attracting FDI inflows. Nevertheless, as a macro variable, we believe this is suitable in measuring governance during a transition period. As a result of condition 1., it will only be considered a “new” transition if a government has been in place for two years, and then is transitioned away from.
- There must be a government before a new government comes in. This may seem obvious, but there is not always a clear governmental entity before a new government takes over. Unfortunately, this makes it impossible to measure transition of power, because it is not a true transition. In our sample, this concerns both South Sudan and Somalia. South Sudan became independent in 2011, and thus there was no “prior” government to compare it to. Somalia was considered a failed state throughout the 1990s, and thus the creation of the Transitional National Government in 2000 with international intervention is not defined as a “transition” of power (Menkhaus 2007, 74). With no independent government prior to these years, it was not possible to measure levels of change of governance or FDI inflows. Hence, we exclude both from the viable sample.
- There must be sufficient data. Unfortunately, we are constrained by the level of data that the World Bank has available, and in consequence, we cannot account for transition periods where we have no data. This was most present in accounting for changes in natural resource wealth. Angola did not provide data during the transition of 2017, nor did Libya during the transition of 2011. This is a limitation, as both were going through a tumultuous transition, given the Luanda Leaks regarding corruption in the oil sector in Angola and the Libyan Civil War in 2011.
The three control variables that we account for in our regression analysis were democratic transition, change in resource wealth, and changes in market size. Democratic transitions were particularly important for us to account for as a control variable, because it was not included in the Good Governance index we created for aforementioned reasons. Certainly, we had to make sure that the Good Governance index was not a spurious variable that could be explained by how democratic the transition was. Hence, we use the WGI variable for democracy (titled “Voice and Accountability”) within a country as the control variable for democracy. This indicator is on the same scale as the other WGI variables and we use its score for the specific transition year.
We also account for change in resource wealth. The literature is clear that resource wealth can cause an FDI “bonanza” (Toews and Vézina 2022, 1046). We thus wanted to make sure that large swings in resource wealth (such as the discovery of new oil) were not driving the changes of FDI, instead of how effective the transition was. The methodology is the same as in the good governance index variable, averaging resource wealth in both the two years before and the two years after the transition and subtracting the prior number from the post-transition number.
Lastly, we account for change in market size. Given the disagreements in the literature, we felt it was important to factor this in, in case it was explanatory. The methodology is the same as for the WGI indicators, averaging GDP in both the two years before and the two years after the transition and subtracting the prior number from the post-transition number.
The regression model is the following:
- FDI is net change in FDI as a percentage of national GDP from the 2 years prior to the transition to the 2 years after.
- Good.gov is change in good governance index from the 2 years prior to the transition to the 2 years after.
- Res.wth is change in resource wealth from the 2 years prior to the transition to the 2 years after.
- Gdp.ind is change in GDP (our account for market size) from the 2 years prior to the transition to the 2 years after.
- Dem.ind is the score of the Voice and Accountability variable of WGI indicators for the year of the transition.
- i is the country.
- t is the year of transition.
Table 1 below shows the model’s results.
- Good Governance is significant at 0.01 level.
As shown in Table 1, our independent variable, a constructed Good Governance index based on political stability and absence of violence, government effectiveness, regulatory quality, rule of law and control of corruption, shows a positive and significant relationship at the 0.01 significance level to explain net change in FDI as a percentage of national GDP. Accordingly, we can observe a positive trend in Figure 1 where the level of success of a transition of power positively impacts FDI flows. On the one hand, successful transitions (those with a positive change in governance score) can either attract more FDI (in a few best cases), stabilize it, or not suffer a significant drop. On the other hand, unsuccessful transitions (those with a negative change in governance score) show a general downwards trend; that is, the less successful, the more the negative change in FDI flows. Overall, our results mirror those of Rodríguez-Pose and Cols concerning the importance of institutional quality to determine FDI (Rodríguez-Pose and Cols 2017, 79).
In other words, the success of transitions in increasing or maintaining political stability, quality of public services, quality of policy formulation and credibility, promotion of private sector development, and confidence in their rule of law, is generally associated with better results in FDI flows (or at least maintaining the pre-transition level).
2. Democracy score is not significant.
Consistent with our argument of democracy’s ambiguous relationship with FDI, the democracy score is not significant to explain changes in FDI inflows from pre- to post-transition (see Table 1). This gives us stronger confidence in our variable of good governance in transitions of power as being determinant to FDI inflows instead of whether they are democratic or not.
Given that the data for this score is extracted from Voice and Accountability from the WGI, our result should resemble that of Cols and Rodríguez-Pose which shows a negative association for this indicator with FDI inflows (Rodríguez-Pose and Cols 2017, 74). We also get a negative association but it is not significant.
One explanation is that Voice and Accountability seems to “exert a long-lasting influence in FDI inflows” (Rodríguez-Pose and Cols 2017, 77). Since our analysis focuses on net change in short-term FDI inflows, two years before and after the transition, the model might not be able to capture the long-term effect of democracy.
3. Change in resource wealth and market size have no significant effects.
While resource wealth was important to control for, it is unsurprising that it is not significant given the sample size. In such a relatively short period, there tends not to be huge swings in resource wealth unless there is a new source of oil or minerals, meaning that it may be hard to see how the change in resource wealth would impact change in FDI flows. We know, based on the literature, that resource wealth does promote FDI flows in the aggregate (Rodríguez-Pose and Cols 2017, 74; Anyanwu 2011, 8; Ajayi 2006, 8; Deichmann et al. 2003, 5-6). Nonetheless, our model accounts for change in endowment rather than wealth stock. Hence, taking into account the size of our sample, the change in resource wealth does not appear to be an explanatory factor for changes in FDI flows during transitions of power in our sample set.
Changes in market size were also found to be insignificant in our sample. We wanted to be sure to account for any significant changes in market size, to ensure that large swings in GDP were not driving changes in FDI. However, our data does not suggest that this is a determinant factor. There are two possible explanations for this. The most intuitive one, in our view, is that there is not a significant effect of changes in size of the market on changes in FDI. This is consistent with Rodríguez-Pose and Cols’s findings, arguing that even commodity-rich countries have markets that are too small to influence investment decisions (Rodríguez-Pose and Cols 2017, 74). The fact that most “foreign firms export their products outside of the countries where they invest in and out of sub-Saharan Africa” also substantiates this claim (Rodríguez-Pose and Cols 2017, 78) . Thus, due to the markets’ scale and mode of operation, changes are also irrelevant. However, another explanation is that, in our limited sample, there were no large changes in market size that would make certain economies disproportionately attractive or unattractive to invest in.
Considering that previous literature shows that high-quality governance matters for FDI (Adeleke 2014, 130; Rodríguez-Pose and Cols 2017, 78), we believed that transitions were a weak point that we could use to showcase the impact of changing governance. In this inflection point for any country, governance can either decrease, increase, or stay the same. Thus, comparing the pre-transition and post-transition levels is key to understanding the effect of good institutions in development. Our data backs up our hypothesis, as good governance is the only significant explanatory variable of changes in FDI flows that we observe. Notwithstanding, there are limitations to our approach.
Firstly, there are fair questions to be asked as to whether the World Bank’s World Governance Indicators are the best measure of the success of a transition. In our opinion, the data on good governance is largely private-sector oriented. Thus, the authors of this study may not fully agree with their metrics for what defines “effectiveness” of a transition inasmuch as it does not consider more measures of welfare or democracy. This is beyond the scope of our paper, as the data we used from the World Bank provided an effective, albeit rough, picture of how successful the transitions in our dataset were. The bias towards private investors’ views is adequate because this data is associated with FDI flows. Despite this, further research would do well to do a deeper dive into what exact factors most explain the success of a transition.
Secondly, regarding data quality, we would have preferred to have a larger sample size. With World Bank data being available only after 1998, as well as instances of incomplete data, we were able to account for 72 transitions on the African Continent. As we saw in the results section, outliers had a large effect that, with more data points, could have been better accounted for. Since this is not survey data, we can only include as many data points as actually occurred. Thus, it is an inherent limitation of our study.
Moreover, our model does not allow us to include countries in which there were no previous governments. This refers to South Sudan and Somalia. As explained, these cases do not amount to a transition of power. Nevertheless, this means that we were unable to account for the effect on FDI of new governments known for their political instability and ineffective governance (Gavin 2022; UN News 2022). Their inclusion would have been interesting to prove our point that decrease in governance negatively affects FDI flows. An additional issue with the data is that poor reporting on natural resources (i.e. Angola and Libya) did not allow us to include this information on the model.
Thirdly, since we accounted for net change in FDI before and after the transition and not the percentage change with regards to the global average, we could not measure the effect of recessions. However, since the 2007-2008 Financial Crisis meant “only a small hiccup” (Rodríguez-Pose and Cols 2017, 64), we believed it would not substantially affect our model. This is also the reason why we avoided including the COVID-19 pandemic period, with the last transition measured occurring in 2017, so the last post-transition year measured would be 2019.
Another measurement issue we have encountered is that two years may be too short of a time frame to measure the long-term effects of policies on FDI. This can be for two main reasons: (1) long periods of transition in which the new government has not been in power long enough to alter the course and perceptions of policies; and (2) investors’ time to react to the new government and increase or decrease its confidence in it.
Finally, we could have included other controls such as macroeconomic stability (i.e., the inflation rate), as investors may see a restraint or a reason to disinvest due to a high inflation rate. Our reason not to include it is that, in our view, the regulatory quality indicator already captures this effect. This is because the indicator “reflects perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development,” according to the WGI (See Appendix 1) (“WGI 2022 Interactive” 2022). Given that a high inflation rate tends to be related with a lack of sound policies, the effect of a lack of macroeconomic stability on investment is already covered by the indicator.
The same argument can be made for the inclusion of other variables such as human capital, capital controls, ease of doing business, infrastructure, or trade openness in the model. The list can be infinitely long, and further research would do well in examining their relationship with FDI. However, in our case, we believed that the WGI already captured perceptions on some of these variables (capital controls, ease of doing business, infrastructure, etc.), so we would run the risk of possible collinearity as well as duplicity of information.
Despite the discussed limitations in data availability, we are confident that our paper contributes to the existing literature on the determinants of FDI flows, particularly in developing contexts. As mentioned above, the intention is to open a new segment of the research by looking at how changes in good governance affect investment (as a measure of development).
Our findings indicate that effective governance has a significant impact on determining FDI flows in periods of transition. This matters in terms of policy because it means that new governments, during the transition period, should focus on preserving or, ideally, improving the quality of institutions to maintain a steady and sustainable flow of investments. Additionally, at least in the short term, democracy is not a relevant factor to attract private investors. We also find no significant relationship with change in market size and in resource wealth in transition intervals.
In our paper, good governance is a combination of political stability, quality of public services, promotion of private sector development, quality of contract enforcement and control of corruption. As we have demonstrated, these qualities should not merely be striven for as a moral virtue to serve a given population, but rather, have a real impact on a country’s ability to attract resources through FDI flows. We thus aim to offer a direction for all kinds of governments, regardless of ideological differences, to ensure functioning institutions. This can be particularly timely due to current trends of democratic backsliding in the world.
The case of West Africa is particularly relevant to our findings, where new governments have been working towards more policies that enhance trade liberalization and diminish corruption and have been seeing a simultaneous upsurge in FDI flows (Zhenwei Qiang et al. 2021). Additionally, the new African Continental Free Trade Area (AfCTA) provides a framework for current governments to harmonize regulatory barriers and lower the cost of doing business (Morgan, Farris, and Johnson 2022, 5). Once the previous government has done so, the existence of the free trade area may constrain subsequent governments to continue these policies.
Despite these advancements, important issues remain such as high crime rates and political violence, corruption, weak regulatory quality, and poor contract enforcement (Sobrinho and Thakoor 2019; “Foreign Direct Investment (FDI) in South Africa - International Trade Portal” n.d.). Consequently, new governments would do well to focus on improvements after a transition, rather than maintaining these previous conditions. This can be done by working on controlling corruption, improving the rule of law and ensuring legal transparency, among others. In this manner, they could increase the opportunities and incentives for private investment within their borders.
Whether they are newly elected governments, successions, conflicts, or coups d’état, transitions constitute an inflection point when quality of governance can improve or deteriorate. Hence, creating or maintaining effective transitions is key to ensure development. While our results are specific to the African continent, they may provide a framework for emerging countries in general. Further research on this subject would be a valuable contribution to the literature.
*This article was edited by Afsana Khan (Princeton University) and Kylar Cade (IE University).
Maria Fossas is a first year Master student in International Development at Sciences Po Paris, with concentrations on Global Economy and Diplomacy. She holds a BA in Global Studies from Universitat Pompeu Fabra in Barcelona. With prior professional experience in international business in Africa, her research interests focus on private sector development, the role of institutions, inclusive growth and the linkages between trade, investment and development.
Jack Moore is a first-year Master’s of International Development student at Sciences Po’s Paris School of International Affairs. He is a graduate of the University of North Carolina as a Morehead-Cain Scholar with Phi Beta Kappa honors. He is specifically interested in encouraging renewable energy investment in the developing world. In his spare time, you can find him running along the Seine, practicing his French, or watching Tar Heel football and basketball.
Alexandra Tomlinson is a first year Master student in International Development at Sciences Po, with a focus on health and gender. With previous experience in the agricultural sector as well, her research interests are mainly project management and impact evaluation.
 There was internal discussion amongst the authors as to how best to measure FDI inflows. We are aware that there is a danger of endogeneity by using FDI as a percentage of national GDP, because GDP can also be impacted by a successful or unsuccessful transition. Unfortunately, the only alternative data available was net gross change in FDI, and this presents problems of its own; specifically, larger economies will by their nature have bigger swings in FDI, even if it is the same percentage as a smaller country. Consequently, if we had used this, it would have given greater weight to the transitions of larger economies
in our data. Furthermore, we were unable to measure percentage change in net FDI inflows, as some countries had a negative net FDI inflow, due to foreign disinvestment. We were unaware of a method in which to code for change on a percentage basis for the lowest level of FDI inflow not being zero. For that reason, despite the worries of endogeneity from measuring change in FDI Net Inflows as a percentage of national GDP, we saw it as the best path forward given data availability.
 The World Bank currently does not classify Western Sahara as a sovereign nation.
 We also ran a regression testing whether market size in general impacts changes in FDI flows, to make sure the size of the economy did not impact the relationship of good governance and FDI flows. Once again, this was found to be insignificant.
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