Foreign Direct Investment in Less Developed Countries: Do Institutions Still Matter? Evidence for Central African Countries


This paper analyses the FDI flows determinants in less developed countries with evidence in Central African countries. We mention that if institutions matter in attracting FDI flows; this is not only due to good institutions or political regime types as focused in economic literature but also due to economic sectors which must be considered as investors decision procedure.

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Mantsie, R. (2023) Foreign Direct Investment in Less Developed Countries: Do Institutions Still Matter? Evidence for Central African Countries. American Journal of Industrial and Business Management, 13, 93-106. doi: 10.4236/ajibm.2023.132007.

1. Introduction

1.1. Consideration and View

The foreign direct investment (FDI) flows are usually analyzed as a result of Institutions and to a large economic view as an offshoot of institutions’ quality as one can mention infrastructures quality. Among institutions, we can quote Governance mode, property rights protection, corruption and so on. In infrastructures, we mention Energy power, routes, manpower ability, etc. This is to lose that one of the roles of institutions leads to correct the market failures or coordination commitment problems that sometimes disturb the basic type of economic interactions.

This work underlines that the relationship between institution and FDI must take into account not only institutions, but also the economic sector where FDI are allocated as proposed by Farrell, Remes, & Schulz (2004) . The aim of this paper is to say economic sector matters in the process of attracting FDI. Political regime options and institutions also do as mentioned by Demirhan & Masca (2016) but they depend on economic sector which is the decision booster.

Central African countries analyzed are to be characterized by their similarity as raw materials producers, economies’ level of development and geographic proximity. The charts of investments are like to be the same.

This paper is organized as follows. We review next the related literature dealing with institution and FDI in that context. In the second section, we present the model. In section three we present the results on FDI allocation, institution and sector determinants. Section four discusses the results and concludes.

1.2. Brief Review of Literature

The FDI has been analyzed by many authors as one of the growth determinants for developing countries. Those flows increased in Africa until the big wall fell in East Europe in 1990s. According to UNCTAD (2008) these remain the most important part of the foreign capital. As to say, FDI provides in the emerging country not only plants and capital but also knowledge, technology, skills and abilities to become competitive (Sachs & Warner, 1995; Rodrik, 1996) .

These advantages do not occult the fact mentioned by parts of economists who argued that FDI can be seen as a compromising result (Evans 1979) of multinational and power in less developed countries (O’Donnell, 1988; Haggard, 1990) . It is asserted that an authoritarian power will be an attractive determinant of FDI (Resnick, 2001; Tuman & Emmert, 2004) . The way is to see with Lipsey (2002) that FDI offshoots abilities in the statement country. According to its importance, we have to question the determinants which guide FDI flows to a country.

A certain economic point of view asserts the relation between FDI benefit countries is not clear (Freeman & Oostendorp, 2000) . Another view mentions that this link depends on the nature of institutions (North & Weingast, 1989) or on regime types of economic and property rights (Olson, 1993) . In this way, Harms & Ursprung (2002) and Jensen (2003) concluded to a positive impact of democracy in attracting FDI.

The relationships between institutions and FDI have pointed to the nature of the political regime and its effects on FDI (Haggard, 1990; Lipset, 1960; Olson, 1993; Resnick, 2001; Li & Resnick, 2003) and in a large stand (Henisz, 2002) . The main debate focused on economic literature dealing with the link between foreign enterprises and authoritarian political systems (Oneal, 1994; Pandya, 2006) . As mentioned by Haggard (1990) , such regimes generate more business transaction by securing property rights than democratic systems. The opposite view can be noticed by Olson (1993) and before all by Lipset (1960) who argued that democracy protects more property rights by providing political stability.

As tested by Resnick (2001) in the cases of 19 developing countries from 1971 and 1993, in Latin America, Asia, and the Caribbean between negative effect of democracy on FDI is real (see for example (Ross, 2001, 2006) ). These results have been enforced by Tuman & Emmert studies on Latin American countries in 2004 when they study found that authoritarian regimes receive more FDI than democracies in the case of US investments. A neutral position would be adopted by Li & Resnick (2003) who concluded on mitigating effects of democracies on FDI as did Büthe & Milner (2008) .

So, the relationship between institutions and growth has been differently considered (Kobrin, 1982) . But the lack was the manner of considering institutions and their measurement. Institutions environment can be estimated as the bureaucracy. The level of corruption is taken to proxy this part of institutions given by environment. In the same way, we can mention civil liberties as determinant of institutions in promoting economic growth (Kormendi & Meguire, 1985; Levine & Renelt, 1992) . Bahati & Mbithi (2022) comparing Central and East Africa flows of FDI arrives at a diversity of determinants and specificities

Property rights also analyzed as part of institutions indicators (Pejovitch, Furubotn, Keefer and al.). The evidence of Economic freedom-growth and Democracy-growth is also discussed but their effects are no more evident (Malesky, 2008; Morrison, 2009) . Political institutions can also be taken as part of institutions influencing FDI and growth. They are analyzed to explain the relation between institutions and FDI. Different reasons are pointed to explain why FDI is oriented to LDC (UNCTAD 1998) . We can mention among missing factors are access to raw material, markets expansion, economic costs reduction.

It is known that LDC abound in natural resources but haven’t enough financial capacity and knowledge to exploit their resources (Smith, 2004) . This leads foreign partner or investors as mentioned FDI to exploit these resources. In the same way, FDI can be oriented to access a foreign market. In the presence of cost transaction or in a trade barriers situation, it is preferable for a firm to establish one’s activities in a country. Costs of transaction, barriers to entry, competition lead to FDI location in a country.

This paper feared a voice to know FDI is attracted by setting up institutions quality which leads investors to make up their choice for a country or another one. So, institutions stimulate FDI and make them able to realize investments programs. We mention also FDI is allocated where raw material exists and capital is profitable. So, the sector will be suggested to be considered as one of the determinants in defining FDI location.

It is known that the Central African countries abound in raw materials and have all the same charts of investments like taxation code, investments incentives, capital transfer regime and so on. It is also known that foreign capital flows differ from one country to another when political regime types differed. Before adopting democracy as means of governance in 1991, FDI flows in these countries looked like to be an offshoot of economic sectors not due to governance institutions. Do institutions still matter?

2. The Model

2.1. The Structure of the Model, Data and Research View

The model is log X = β 0 + β 1 log x 1 + β 2 log x 2 + + β n log x n + μ t

With μt as the error and log is the log means.

The basis variables are chosen to analyze the Flows of FDI growth in Central African countries. Data sources are from World Bank, IMF/SFI statistics, BEAC data, UNCTAD, Zone franc Reports, Gastil index as resumed in Table 1.

The rate of FDI grow this available from 1978 to 2009 combining IMF, BEAC and Zone franc reports on economic and financial statements. Trade openness is taken from Trade Statistics and UNCTAD data, when Capital openness results from Zone franc and BEAC reports for several years. At this level, we have to mention that capital openness is a proxy as we adapted freedom of transfer as mean of measurement. Economic Growth and inflation are both available on Zone franc and BEAC reports as on IMF and SFI Statistics, while Economic sector comes from Zone franc and BEAC Statistics.

The main difficulty of the study is to measure institutions in the empirical tests. Broadly defined by multidimensional feature of a socioeconomics space, we use proxy of institutional characteristics.

We retain the rate of FDI growth (RFDI) as a variable depending on Political Regime Type (PRT), Trade openness (TO), Property rights (PRI), Capital Openness (Cop), the rate of Inflation (INF), Energy Rents (ER), Mineral Rents (MR) and Economic Sector (ES).

The model to be tested is:

log RFDI = β 0 + β 1 log PRT + β 2 log TO + β 3 log PRI + β 4 log Cop + β 5 log INF + β 6 log ER + μ t (1)

Table 1. Determinants of FDI flows rates.

In order to test the model and decipher institutions and economic sector on FDI flows separately, we’ll distinguish one part relationship between institutions and FDI and another part Economic sector and FDI flows. In this way we will introduce Mines Rents (MR) and Economic Sector, as:

log RFDI = β 0 + β 1 log PRT + β 2 log TO + β 3 log PRI + β 4 log Cop + β 5 log INF + β 6 log ER + β 7 log MR + β 8 log ES + μ t (2)

2.2. Country FDI and Selected Raw Materials

We map in Table 2 a selected view of sector structure of raw material and FDI flows. We note that according to UNDP and World Bank publication, those countries are badly listed in governance statement and doing business repertory. We have to mention to before initiating a look like democracy process in 1991, those countries were all governed by authoritarian parties pro liberal or socialist. FDI never depends on Bad or good governance but on investment sector.

In Table 2, we note that FDI exists in all the countries without consideration with nature of institutions like structure of governance (political or economical), property rights but extends to all the economic sectors as Oil sector, Copper, precious metal, diamond and so on. This leads to discuss the basis for the establishment or FDI attractiveness as a function of the institutions quality or any other distribution of governance in mineral-rich countries for which other determinants make it possible to capture the said investments, such as yields or the low cost of production factors.

Table 2. Raw materials allocation in selected central African countries.

Cc = Cacao, Cf = Coffee, Cp = Copper, Ct = Cotton, D = Diamond, M = Precious Metal, O = oil, T = Timber, L = Liberal, A = Authoritarian. *Superior to 8% of GDP.

3. FDI Allocation, Institution and Sector Determinants

3.1. Institutions and FDI Allocation

The relationship between institutions and FDI allocation are usually analyzed as aggregated flows of FDI. We have to mention two points of view: first, in fact, investors found sector of investment, its pay back in constraint of production costs. Second, if we observe the pattern of Exports of these countries or the structure of their budget, more that 80 ùù of their Export and public resources come from extractive product were FDI play a prominent role.

We quote that, if it is real that investors decide to implant FDI in accordance with political institutions, the positive effect of political institutions on FDI flows do not influence FDI but create a first level of decision procedure. This means, the positive effect of political institutions on FDI do not create the decision of implanting FDI, the FDI is implanted when the sector matters.

Table 3 reveals that means square are not far different and there is no high dispersion among variables.

To conduct our study, we will distinguish CEMAC countries from Angola and DR Congo. This consideration is due to the fact CEMAC countries belong to a same monetary zone and Angola has its own money (Kwanza) so does DR Congo with Franc Congolais.

We note that, referring to Table 4; test results for CEMAC zone lead to assert that institutions due to property rights and Political Regime Type do not directly affect FDI flows. But Capital and Trade Openness do. This means that in the fields of FDI investors have enough guarantees with miner countries while contracting. The Political Regime Type or the nature of property rights does not affect investors’ decisions once mines contracts concluded. Another explanation can also be seen as Capital and Trade Openness affecting FDI efficiency and trying to be a good institutions’ substitution.

We also note according to Table 4 Capital and Trade Openness do affect FDI flows. This means investors decision process can be influenced by institutions as

Table 3. Variables description.

Table 4. Tests results for CEMAC zone.

CEMAC zone regroup Cameroon, Chad, Congo Republic, Central African Republic, Equatorial Guinea, Gabon, in a monetary zone. Corrected standard errors in parentheses. (*) (**) Significance levels: 5% and 10%.

the capital transfers regime, Trade or economic freedom and so on but, those are more incentive structures than real institutions broadly speaking.

The same conclusion can be established for Angola and DR Congo as reveal Table 5 and Table 6.

As we know, the pattern of exchange and public finances resources in these countries are influenced by raw material extraction where FDI are the most important foreign capital flows. We can test FDI flows due to sector determinants.

The determinants of FDI flows in CEMAC zone given by institutions do not affect directly FDI level but partly. This truly means institutions as political regime, property rights do not have enough evidence on FDI flows, but Capital

Table 5. Tests results for Angola.

Corrected standard errors in parentheses. (*) (**) Significance levels: 5% and 10%.

openness quite does. This conclusion widely asserts early result obtained by (Kobrin, 1987) , Rajan & Marwah (1998) and more closely Ross (2008) concluded to the same on FDI decision process.

3.2. Economic Sector and FDI Allocation

We mention that the first sector, the primary one, broadly changed from 1978 to 2009. By the way Gabon and Congo boosted their Exports by Oil extraction in 1980-1984 and further. The same impact was observed in FDI flows in 1990 in Angola and Equatorial Guinea by 2000 and in Chad in 2005.

This study makes easy to understand the indicators of FDI attractiveness in some developing countries with high commodity endowments. It argues that some FDIs are not only due to traditional attractiveness criteria, but also the

Table 6. Tests results for Congo D R.

Corrected standard errors in parentheses. (*) (**) Significance levels: 5% and 10%.

return aspect or the anticipation of future improvements in governance or institutions can be emphasized as a future bet on investment in a world of uncertain institutions.

Initial FDI has better explanation in taking into account sector contribution. Such an approach leads to see that FDI changed from equation column 1 to 2. For example, in addition of economic sector Capital Openness, Property rights, Political Regime Type and energy rents, representing institutions got another impact on FDI. Trade Openness and Inflation have inverse sense. This means their influence is more mitigate.

To be more realistic, we can distinguish FDI influence by sector. The second and the third ones changed so slowly we hypothesized them as unmoved. To be more explicit, we analyze sector effects on FDI by testing its growth in relation with FDI weight per sector. Table 7 mentions the tests results.

Table 7. Tests results for central African countries.

Corrected standard errors in parentheses. (*) (**) Significance levels: 5% and 10%.

Change in property rights impacted more in second and third sectors than its does in primary sector where FDI flows are more important. As we mention this sector is the prominent one which provides more 80% of public finance resources in these countries.

In the first column we consider FDI flows without economic sectors and it appeared that institutions influence them partly. When introducing sectors, effects of FDI changed for institutions determinants.

Freedom Change never influences total FDI flows but it does for primary and second sectors, not for the third one. The same conclusion can be advanced for Change in trade openness which reveals FDI investors have guarantees for their resources when investing. Second and third sectors are less impacted.

According to economic sectors, FDI depends on both institutions and sectors; this is to say, it will be profitable to consider both institutions and sectors as correlated determinants of FDI in Central African countries.

4. Conclusion and Recommendations

We have attempted to examine to what extend the effects of institutions and economic sectors can influence FDI flows in Central African countries. We found that, in the similar economic characteristics, institutions effects have got some evidence on FDI flows but this is not enough to explain FDI determinants; economic sectors also do and this might be considered as FDI flows incentives.

Table 8. Panel data analysis.

Corrected standard errors in parentheses. (*) (**) Significance levels: 5% and 10%.

According to Table 8, the evidence suggests that FDI flows depend on both institutions and economic sector. This implies economic authorities and politics in those countries have to improve new means of decision in FDI seeking.

First, they have to improve both good institutions and sectors incentives to stimulate FDI flows;

Secondly, new advantages in catching FDI flows must be built. This simply means as there is similarity in economic characteristics, investments charts, raw materials, Central African countries must be built capacity in the field of infrastructures like power, routes, communications and so on;

At least, Central African countries’ deciders have to take into account new means of improving FDI flows, raw materials are not enough to explain FDI concentration in the fields of Mines. Institutional capacity buildings can offshoot second and services sectors which look like to be abandoned.

Conflicts of Interest

The author declares no conflicts of interest regarding the publication of this paper.


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