Location Theory, Business Climate

and Foreign Direct Investment in Africa

Preliminary Draft

Mars, 2007

Noomen LAHIMER

Université Paris- Dauphine

Centre de Recherche : EURIsCO

noomenla@yahoo.fr

Abstract:

Africa has known a failure in attracting FDI comparing to other developing countries. Weak

Business Climate is presented as the most important argument to explain this failure. This

paper tries to investigate definitions and origin of the Business Climate Concept. Then, it puts

the emphasis on its relation with Foreign Direct Investment. The empirical section uses a

panel data with fixed effect estimation applied on 25 African countries. The estimated fixed

effect is an FDI indicator when they can rely on everything except for their natural resources

and market size. Thus, it represents a Business Climate indicator. Then we examine the

impact of Human Capital, Institution quality and Geographical factors on the Business

Climate of African countries. We find out that policies matters for Africa FDI attractiveness

and that education and openness to trade have positive and strong effect on African Business

Climate.

JEL Classification: F23, O55

2

Introduction

Many theories have been used in order to explain investment location decisions. The

most cited determinants are cost factors, transport factors, market factors, labour factors as

well as tax regimes and regulations. Generally speaking, we can include all of them into

one concept: the Business Climate. Many countries, States, public officials and

businessmen have placed emphasis on “The Business Climate” concept as a fundamental

factor in attracting industry and promoting growth (Plaut and Pluta, 1983). However, the

definitions and components of this concept are elusive and ambiguous due to the

divergence of interests between economic and political actors. World Bank Development

Report (2005) insists on the role of Business Climate as a bridge between firms’ interests

and country economic development through the improvement of institutions and social

stability. As far as firms are concerned, Business Climate is considered as an inevitable

component of attractiveness. Its evolution is crucial for firm’s operations success or

failure. The Business Climate is also felt by the country chosen by firms. The location

decision of a single firm may exert a little real impact on an area, but the sum of many

decisions over time is tangible and potent.

Moreover, new internationals theories give an important place for Business Climate as

a fundamental comparative advantage that stimulates globalization of production. Indeed,

international firms’ mobility is being easier and easier. Foreign Direct Investments (FDI)

are attracted by several factors such as market size and natural resources. Business

Climate is also one of the most important FDI determinants. Usually, international

organizations and Multinational Firms (MNFs) establish a sort of short-list of countries

where investment is the most convenient. Generally, this list is constructed on the basis of

countries’ Business Climate. The FDI – Business Climate relation is crucial for countries

development and attractiveness. However, FDI are also attracted by exogenous factors

such as natural resources endowment. Those factors do not depend on government

decisions and institutions’ quality, and then they cannot be incorporated into the Business

Climate components. Hence, isolating the FDI endogenous part would be essential to

compare Business Climate of several countries. An important methodological question is:

how can we isolate empirically the Business Climate explicative part of FDI? Most of

recent empirical studies have tried to estimate the effect of Business Climate on FDI

inflows. However, our paper tries to construct an inverse method that consists in

estimating a Business Climate index with respect to FDI strategy.

3

In the African case, the relationship between FDI and Business Climate is less clear.

Indeed, more than half of the world’s cobalt and manganese and over the third of bauxite

are located in Africa. Thus, most MNFs implementations are solely driven by natural

resources availability. This suggests that African attractiveness is largely determined by

an “uncontrollable” factor (Asiedu, 2003) and that Business Climate effect is marginal in

this region. Some empirical studies, in particular Morrisset (2001) and Asiedu (2003),

pointed out that .African countries can also attract FDI through their Business Climate.

They conclude that institutions, education and stability matter in Africa as in other regions

in the world.

This paper uses panel data and aims at two important purposes. First, we look for

estimating a Business Climate indicator in order to create an African rating index through

fixed effect estimation. Second, we seek to test empirically Business Climate determinants

such as macroeconomic and political instability, infrastructure, education and openness in

order to check whether our Business Climate estimator is robust and whether Africa is

different from other regions.

The paper is organized as follows: Section 1, overviews Business Climate definitions

and determinants and emphasises on the historical evolution of this concept. Section 2

reviews the theoretical relation between FDI and Business Climate while section 3

describes the estimation method and defines the data and the explanatory variables.

Finally, section 4 presents the empirical results concerning Business Climate estimation

and determinants.

1. Business Climate Concept: Origin and Definitions:

Business climate origin backs up to the sixties in United States. The increase of

competition between Western States and Eastern States created the need for an index to

compare attractiveness across States. Northern States knew, also, a decline in most of their

important industries. Thus, public politics sought to understand factors motivating

investment flows (Erikson, 1987).

The first comparison of the Business Climate was based on labour costs and taxes.

This way appeared rapidly as inefficient to explain capital flows. Strasma (1959)

examined factors motivating investment decision. He found that income per capita and

property laws are very important. He also found, that taxes regime had effect on

4

investment decision if only two different states had identical characteristics in terms of

attractiveness. He concludes that taxes effect on states attractiveness is marginal.

During the 70th, the energetic crises figures out a new attention on commodities and

transport costs and had putted the location theories (Weber, 1929; Isard, 1956; Smith,

1981) into new issue: international mobility and international trade. Investment decision

was influenced by new international factors as expressed in the H.O.S model in term of

cost, transport and commodities availability and comparative advantages. Those,

Multinational Firms expressed the need of a new synthetic index describing the

attractiveness of each region. This index should represent the “business climate” of a

region and should allow investor to make an exhaustive comparison.

The weakness of the simple general indicators comparison, push consulting groups to

find a new way of ranking regions. The first business climate study was done by “Fantus

Company’s State Ranking of Business Climate in 1975” (Atkinson, 1990). Forty height

American States were classified taking into consideration: taxes, labour costs, life quality,

and demographics characteristics. Then, all these factors were grouped in a single index

called “Business Climate Index”. The Fantus’s ranking meat with great response in all

American States. Obviously the bad ranked States made a strong criticize on this business

Climate Index; however the results were largely accepted. Since, many consulting groups

have tried to construct their own Business Climate index where the most famous was the

“Alexander Grant and Company index”. Each of those studies had its strongest and

weakest characteristics. The efficiency of the business climate index depended on the

factor on which we focus.

Economic literature describe business climate as an elusive and ambiguous concept. It

is a multifaceted concept and there is no agreement among different economic and social

actors. It is very difficult to give an exhaustive and precise business climate definition

given disagreement over location factors. Erickson (1987) gave one of the most relevant,

precise and concise definition:

« Business Climate is: the sum total of a place’s human and capital

resources including infrastructure, public policies, and attitude that affect

the formation and operation of a business enterprise »

This definition reveals the global aspect of the concept. It’s composed of all factors

that can affect directly or indirectly firm activity. Hence, it can take form of geographical

factors, cost factors, social factors or even political factors.

5

As mentioned before, initially, the Business Climate concept was developed to

compare American States. However, the idea of ranking regions or countries is very

important for multinational firms and for International Organizations. World Development

Report (2005) set a general review of the Business Climate with focusing on its

determinants in developing countries and on its effects on economic growth and poverty

alleviation. The World Bank defines the Business Climate as:

“The Investment Climate1 reflects the many location-specific factors that

shape the opportunities and incentives for firms to invest productively,

create jobs, and expand. A good Business Climate is not just about

generating profits for firms—if that were the goal, the focus could be

limited to minimizing costs and risks. A good Business Climate improves

outcomes for society as a whole. That means that some costs and risks are

properly borne by firms. And competition plays a key role in spurring

innovation and productivity and ensuring that the benefits of productivity

improvements are shared with workers and consumers.”

The World Bank’s report insists on government role and on the importance of

competitiveness as major business climate factors. It orders out also, the significance of

Business Climate not only for firms but also for the whole society as a determinant of

economic prosperity.

The following diagram shows clearly the Business Climate component in interaction

with firm and country environment. It shows also the importance of the connection

between business climate, economic growth and economic development. Business climate

looks as an inevitable bridge between firms (local and international) and economic and

social country development.

Country attractiveness relies first on cost factors, risks and competitiveness. All these

factors are endogenous to States. Second, government policies and their behaviour are

decisive for international investors. MNFs will look into the government credibility and

stability before deciding implementation or not. Finally, some factors are completely

exogenous to politic deciders such as climate, distances, geography…Market factors and

consumer’s preferences are partially independent from government behaviour. Both can

not be enhanced without life quality and investment condition improvement.

1 We consider the Investment Climate and the Business Climate as the same concept since both concerns the

investment conditions.

6

Source: World Bank Development Report 2005: A better Business Climate for Everyone

After defining Business Climate concept, it is crucial for our study to establish its

relation with FDI determinant. It seems clearly that combination of some location factors

promote domestic investment. The question here is to know whether business climate has

the same effect on foreign investment or not? World Bank and UNCTAD’s reports, figure

out that a good Business Climate is on the whole favourable to country international

attractiveness. Meanwhile, this depends largely on MNFs strategy. FDI has many ways of

international investment each one aiming a precise objective and needs a different location

factors. The effect of Business Climate’s effect will, in that way depends on FDI strategy.

In the following section we will examine this relation taking into consideration FDI

strategy.

2. FDI Strategy and Country Business Climate

Basically, there are three multinational firms strategy: natural resources strategy,

horizontal (market seeking) and vertical strategy.

FDI aiming at exploiting the natural resources, worry marginally about the conditions

of investment of the host countries. The released revenue, for example by the oil

exploitation, is generally sufficient to cover the costs related to the risks factors, bad

governorship and regulation (Sachs and Warner, 1995). A relevant example so is the

abundance of FDI in a country such as Nigeria where the conditions of investments are

hardly unfavourable and political and social instability, are quasi-permanent. In the same

way, it is shown in the literature that the effect of this type of FDI on the development is

7

very weak because of their strong capital intensive intensity, their geographical bulk-

heading and their weak externalities on local economy.

The horizontal FDI generally aims at exploiting market opportunities (Michalet, 1999).

The bond of this type of FDI with the Business Climate is more complex. Firstly, we can

presume that, in the same way that for the natural resources, the revenue released by the

market could be sufficient to cover risks and dysfunctions of the country host intrinsic

conditions. Secondly, MNFs which aims at exploiting the internal market are in the search

of a not very competing climate to be able to impose their monopoly. Within this

framework two cases can be posed: (I) The MNF can play as leader on the domestic

market and impose thereafter its monopoly by drawing up entry barriers; (II) in the case of

existence of local companies (formal or informal) which to operate in the sector of the

MNF, the latter will use its advance on technological, financial, managerial and

commercial techniques to crowd-out local competitors and to be strongly established on

the domestic market. An Business Climate promoting competition is not necessary, and, a

priori, inciting for this type of FDI. Thirdly, the constitution of a carrying market is often

posterior to the existence of a good Business Climate. In this case the relation between

FDI and Business Climate is certainly positive but indirect. A market with strong

consumption potential can be the result of an exogenous economic growth, i.e., resulting

for example from exploitation abundant natural resources (exp.: FDI in Golf countries). In

this case, also, Business Climate matters only slightly to the MNFs. location choice.

Nevertheless, the quality of the life, a minimum level of labour quality and cost and a

political, economic and social stability is decisive for the establishment of this kind of FDI.

The third type of FDI, is the vertical strategy. This strategy aims at benefiting from the

costs advantages, proximity and agglomeration offered by host countries. MNFs distribute

their chain of value in order to internalize production and to reduce the costs while

profiting from certain advantages of proximity. Generally, they re-export the final or

intermediate products towards mother company or international markets. It is clear that

beyond cost advantages, economic policy and social stability are essential to the operation

of these companies. A good regulation facilitating international trade is an inciting factor

with the establishment of this kind of FDI. The quality of infrastructures, the tax system

and the existence of a competing environment can play an important role in the process of

selection of the site. Indeed, this type of FDI is entirely and exclusively depending on the

quality of the Business Climate with the attributes which one defined in the theory of

8

location in preceding section. It should be announced, in addition, that vertical strategy

FDIs can evolutes to a horizontal diversification in the case the domestic market becomes

enough promoter.

Figure 1: FDI, Market size and Natural Resources.

KenyaMalawi

Morocco

NigerTogo

Malaysia

Algeria

Cote d'Ivoire

Egypt,

Gabon

GhanaMadagascar

Mali

Nigeria

SenegalSouth Africa

Tunisia

ZambiaBrazil

India

Mexico

Thailand

Singapore

-8

-6

-4

-2

0

2

4

6

8

10

12

-10 0 10 20 30 40 50 60 70 80

NR

GDPPG

Source: Author, World Development Indicators (2005)

Figure 1, represents a distribution of a set of countries in terms of: Natural Resources

endowment, market size and FDI inflows. The bubble size indicates level of FDI inflows

(%GDP). We observe that countries are concentrated basically in two separate regions: the

first represents countries with high growth rates. They attract market seeking FDIs. The

second is in the right side, and it’s composed largely by African countries which attract

FDI due to their Natural Resources. Countries, with a medium natural resources

endowment (or low) and with a medium economic growth market and which attract a

large amount of FDI are likely to have a good business climate. Thus, countries which are

concentrated in the middle of the graph, namely: Singapore, Morocco, Tunisia, Thailand

and Malaysia should have better business climate than other countries. Some Sub-

Saharan Africa countries should also have better business climate than other developing

countries. In one hand, Zambia and Madagascar are two countries without a huge Natural

Resources endowment and without a big market size evolution; however they still attract a

relatively important amount of FDI. We conclude that these countries attract FDIs

basically because they promote a good Business Climate. In the other hand, Nigeria and

Algeria, does not have an important market evolution. They attract FDI mainly through

natural resources. Nigeria is one of the most important oil world producer and the same

9

for Algeria for natural gas. Hence, the Business Climate of these two countries is

relatively low.

In short, we can say that country attractiveness depends on the existence of natural

resources, a large market size and a good Business Climate. Among these factors, only the

Business Climate is endogenous to the politicians (at least partially). FDI attracted by

location factors (and not of possession or internationalization as defined by Dunnnig )2 are

thus explained mainly by the Business Climate concept. This one, depends on the

infrastructure, education, quality of life, stability, openness, the competition environment,

the taxes regime…These constitute essential and intrinsic conditions to the host country.

Nevertheless, it would be useful to define a method in order to estimate the Business

Climate. This method should be at the same time alternative and complementary to

existing index. It should take into account location theory. In the following section, we

will try to explore an econometric method, which will enable us to compare, in ex post,

the Business Climates of several countries while based on the FDI determinants

3. Estimation Method

We present an econometric method to estimate an indicator of the business climate in

a panel of developing countries. The basic idea is very simple. It is based on the

explanation of FDI strategies provided by Michalet (1999) and on the analysis carried out

on their determinants by Morriset (2001).

According to Michalet, FDI are attracted by: natural resources, market opportunities,

or/and by Business Climate. This attractiveness depends on the three strategies explained

before. That wants to say that the part of the FDI not explained by the natural resources

and the size of the market is inevitably explained by the business climate. This last

depends on the factors of location in particular in term of infrastructure, education, labour

cost and productivity, stability… but also of geographical factors such as the proximity,

the existence of littoral or not…Thus, it would be, interesting to isolate this part of FDI,

explained exclusively by the business climate. In other words, that will enable us to

explain the difference of FDI inflows received by two different countries having the same

level of natural resources and market sizes. Distinguishing this part of the FDI will be able

to constitute thereafter a way of comparison of business climates. We can explain this

method by the following: FMNs have a rational behaviour searching for maximization of

profit, minimization of the costs and prospecting of progress. In order to get this purpose,

2 As defined by theory OLI of Dunning.

10

MNFs elaborate their choices. Hence, the chosen host country is likely to have the better

quality of Business Climate, all things being equal. Thus, it would be convenient to find a

method exhaustive to work out this purpose.

Morisset (2001) presents a method which makes possible to isolate the part of the FDI

explained by business climate. Indeed, Morriset try to prove that African countries can

attract FDI differently than while counting on their natural resources and their local

market. He constructed, on the base of location theory, an indicator which made possible

to eliminate the effect of market size (measured by the GDP) and from the natural

resources3, on FDI inflows. According to Morrisset (2001) this calculation makes possible

to eliminate the exogenous factors from the analysis of the FDI determinants. He deduced

the Business Climate indicator on the basis of the following algebraic relation:

(1) ( )

i

i

i i

FDIBC

GDP NR=

×

Where FDIi are FDI nets inflows in a country i; GDPi is Gross Domestic Product

of a country i; and NRi is the natural resources of a country i (indicated by the primary

and secondary sector production minus manufacture production).

BCi allowed catching African and Asian attractiveness independently from their

exogenous factors. Thus, it can reflect not only institutional variables such as:

democracy, corruption, country risk, but also many structural variables such as

infrastructure, transport costs, and human capital quality. Morriset (2001) results shows

that African countries attract also FDI through their Business Climate. Good

government, improvement of education and infrastructure and low administrative

barriers matter for African FDI. He concluded that of Africa policies also matters (and

not only natural resources). Admittedly, this is a very interesting method, nevertheless,

we can address some criticize.

The first criticize we address to Morrisset (2001) concerns the elasticity of FDI to

natural resources and to market variation. He assumes that this elasticity is equal to one.

That can be acceptable if the panel of countries is strongly homogeneous but not in

heterogeneity case. The differences in term of geography, institutions, and network let

3 The total value of the natural resources in each country is considered as being the sum of primary sectors and

secondary, less the manufacturing sectors. Source; World Bank Development Indicators and the Statistical

Report/ratio of the UNCTAD 2002

11

the elasticity of FDI relatively to the two chosen measures not equal to one and changes

from country to another and from period to period.

The second criticize, concerns the fact that Morrisset (2001) considers Business

Climate as a fixed proportion of FDI in all periods. This assumption implies a certain

rigidity of MNFs behaviour in front of economic changes and international markets.

Globalisation, competitiveness, and the power of information imply a firm adaptability

and a certain production and commercialisation flexibility. In consequent, fixed

proportions affected to markets seeking indicator and natural resources indicators is not

an acceptable assumption (They may change, if for example international oil prices

change).

Our study is inspired from Morrisset (2001). If we realize an FDI explanatory model

and we introduce only two explanatory variables: a market indicator and a natural

resources indicator, than the constant of the regression would be the non explained FDI

part. Thus the constant would represent an Business Climate index.

In a set of a panel data, this report would be more convenient. Indeed, a panel with

countries heterogeneity should have fixed effect specificity. Thus the fixed country effect

can be assimilated to the country Business Climate.

The model would take the following form:

(2) , 1 , 2 , ,( ) .i t i i t i t i tFDI LOG GDP NRα β β ε= + + +

Where :

• FDIi,t are FDI net inflows of country « i » for year « t » (%GDP) .

• LOG( GDPi,t) is the logarithm of the GDP of country « i » for year “t”. It

indicates the domestic market size.

• NRi,t is a Natural Resources indicator and measured by the sum of primary and

secondary sector value added minus manufacture value added (%GDP).4

• iα is the fixed effect estimated by the model. It indicates the Business Climate

of a country “i” for the chosen period.

4 This measure is also used by Morriset (2001). We also test, a different Natural Resources Indicator which is the

non- manufacture exports but this measure did not give significant results.

12

We have a sample of 25 African Countries5. We select data for 5 years each country

and for seven period from 1970 to 2004 from WDI (2005).

The first estimation step is to realize the fixed effect test. In the case we accept the

fixed effect assumption that proves the existence of an intra-group variance. Within

estimator (or LSDV) allows to avoid this problem and to find non- biased and exhaustive

results taking into account the intra- group variance. The fixed effects values would

indicate structural differences between countries Business Climate.

4. Results and Interpretations:

In the following section, we will check conformity between theories we have

developed before and empirical results.

First, the test for fixed effect figures out the existence of heterogeneity between

countries. Hence we conclude, as predicted, that Africa is not a homogeneous region; each

country has its specific structural and geographical condition. The heterogeneity depends

broadly on colonial history, geographical conditions, regional integration, political regime,

natural resources availability… Haussman test, figures out the non existence of random

effects6. These two tests mean that our sample has an intra-country variance and let us

chose the within (with fixed effect) estimator.

Second, the Market size’s coefficients is estimated and found to be negative but non-

significant in all periods except for two periods: 1970-1974 and 1975-19807. These

exceptions are not due to a market incentive factors but to political reasons and related to

the evolution of African term of trade: indeed, the seventies were the postcolonial African

period. Thus, after 1973, the oil and non- oil producer countries have profited from the

high international prices of raw materials by increasing exports. This was accompanied

by a rise of flows of international assistance and aid (thanks partly to the cold war). Hence,

African market looked virtually as attractive but the reality is quite different (Akyüz and

Gore, 2001; Collier and Gunning, 1999). International flows were attracted by temporarily

expectations and political reasons and not by the perspective of long- run market growth.

5 The small number of countries is due to data availability. In the first step of estimation we consider Africa as a

whole in order to compare North African and Sub-Saharan Africa countries. While, in the second step of

estimation we include only SSA countries in our panel, since the purpose of the paper is to study SSA Business

Climate. 6 That is due to result of the small number of years chosen: avoid time heterogeneity.

7 Where the market size coefficient is positive and significant

13

Table 1: Estimation Results for all Periods (1970- 2004)

Périodes Within

Estimator

FDI/GDP Fishers Test for

Fixed Effect

Test of

Haussmann for

Random Effect

Log(GDP) -0,0062 (0,4045)

2000-2004 NR/GDP 0,1992

(0,007)***

2.98 (0.0001)***

1.95 (0.3776)

Log(GDP) -0,0196 (0,4127)

1995-1999 NR/GDP 0,1283

(0,1475)*

3.85

(0.0001)***

0.57

(0.7522)

Log(GDP) -0,0063 (0,4786)

1990-1994 NR/GDP 0,0264

(0,507)

6.02

(0.0001)***

0.47

(0.7892)

Log(GDP) 0,00053 (0,9271)

1985-1989 NR/GDP -0,0036

(0,9046)

11.79 (0.0001)***

0.41 0.8143

Log(GDP) -0,0053 (0,5987)

1980-1984 NR/GDP 0,0821

(0,1423)*

4.32

(0.0001)***

0.22

(0.8960)

Log(GDP) 0,0252 (0,0194)**

1975-1979 NR/GDP 0,0615

(0,4292)

2.18

(0.0041)***

4.61

(0.0998)

Log(GDP) 0,0112 (0,154)*

1970-1974 NR/GDP -0,0027

(0,9463)

2.12 (0.0062)***

1.74 (0.4186)

While as predictive by the literature, Natural Resources have a positive and strongly

significant coefficient in all periods (except for the 1970-1974)8 . Market indicator seems

not having effect on African FDI inflows. This confirms the idea that African countries

attract FDI for the most part through natural resources. The positive effect of explicative

variables on FDI reduces the fixed effects levels. This is obvious, because countries which

attract a large amount of FDI due to their exogenous factors are not likely to have a good

Business Climate9.

Now we consider fixed effect as a business climate10 indicator (the non explained

determinants of FDI). Then, we will rank countries using their respective fixed effect.

Nevertheless, to appreciate the fixed effect utility, we must use it as a relative and not an

absolute indicator since it determines the structural differences between the countries in

8 We will make a larger attention on disparities between periods in the following paragraph.

9 Exp.: Nigeria figures in the short list most African countries attractiveness due to oil. However the Investment

Climate in Nigeria is not attractive due to wars, corruption, weak institutions… 10 We do not make difference between “Investment Climate” and “Business Climate” as defined by the World

Bank Development Report.

14

our panel. The fixed effect value is calculated in the base of the heterogeneity of the used

sample.

Table 2 figures out a country rating based on fixed effect estimation, with a

comparison to other country risks and business climates indexes.

We observe that all countries fixed effects are positive. This is a very important result.

Indeed, the common idea is that Africa can’t attract FDI else then counting on its natural

resources endowment. Our results orders out the importance of Business Climate as an

FDI motivation and basically vertical FDI location. As Morriset (2001) we confirm that

institution, labour quality and costs, infrastructure and other business climate factors

matters also for African countries

Table 2 shows that countries which attract the more FDI are not, necessary, the better

ranked. Nigeria, Ghana and Congo Republic receive many FDI inflows in order to exploit

natural resources (especially oil and minerals). Using the average of five years FDI/GDP,

these countries are respectively ranked as the seventh, the sixth and the second, however

in term of fixed effect ranking they are in the bottom of the list. These countries did not

promote a relatively good Business Climate and suffers from instabilities problems. The

Top five countries, is very representative and corresponding to ICRG and investment

profile ratings. South Africa is the first country in our rating. At the same time, it’s the

fourth in term of ICRG and the first in term of competitiveness index. Since the abolition

of the Apartheid regime in 1991and the first democratic election in 1994, South Africa has

liberalized the economy. Government has enacted economic reforms that made it easy for

foreign capital to flow in and out. It also, performed well on various surveys of

competitiveness and the business environment. Finally the government has managed to

make macroeconomic indicator stable and favourable to international investment and

trade. Despite, the so called “failure” of South Africa to attract a FDI relatively to the rest

of developing countries (China, Brazil..) it still one of the most attractive site in Africa.

15

Country

FIX

ED

EFFECT

(CI)

Rank

Average

FDI/GDP(%

)

(2000-2004)

FDI

Rank

ICRG

Index

ICRG

Rank

Inv.

Profile

Index

Inv.

Class

Competitiveness

Index

Compt.

Rank.

Transparency

Index

Transp.

Rank

South Africa

0,147

1

0,15

18

68,8

4

10,5

3

5,3

1

4,3

9

Swaziland

0,135

2

1,31

1

- -

11,5

2

5,1

3

5,3

2

Tunisia

0,132

3

0,77

3

72,8

3

8

12

4,5

5

5,1

4

Morocco

0,109

4

0,13

19

75

2

9

6

4,4

7

3,5

15

Côte d’Ivoire

0,109

5

0,45

8

55,8

16

6

17

22

22

Zambia

0,108

6

0,75

4

53

19

6

18

4,1

14

4,5

5

Egypt

0,107

7

0,24

13

66

6

6,5

16

4,4

6

..

1

Zim

babwe

0,104

8

0,06

22

37

21

6

19

4,1

15

4,5

6

Senegal

0,098

9

0,29

12

64,8

9

8

11

4,3

9

3,9

12

Madagascar

0,092

10

0,43

9

61,5

12

8

9

4,2

10

3,5

16

Kenya

0,087

11

0,17

16

65,8

7

9

5

5,2

2

4,2

10

Botswana

0,080

12

0,22

14

79,3

1

11,5

1

4,1

12

5,1

3

Mali

0,072

13

0,68

5

58,5

14

7,5

13

3,8

16

4

11

Burkina Faso

0,067

14

0,18

15

53,7

18

9

4

20

20

Malawi

0,062

15

0,30

11

54

17

8

10

4,2

11

3,5

17

Algeria

0,061

16

0,16

17

66,3

5

8

8

3,5

17

3,6

13

Congo Rep.

0,057

17

1,03

2

60,8

13

8,5

7

23

23

Ghana

0,054

18

0,67

6

62,8

10

7

14

4,3

8

3,6

14

Cameroon

0,051

19

- 24

62

11

6,5

15

4,1

13

4,4

7

Nigeria

0,047

20

0,54

7

57

15

3,5

21

4,7

4

3,4

18

Burundi

0,040

21

0,33

10

22

22

19

19

Gabon

0,039

22

-0,17

25

65,3

8

25

24

4,3

8

Rwanda

0,033

23

0,09

21

24

24

18

24

Congo Dem

. 0,020

24

0,11

20

47

20

6

20

25

25

Central Africa

0,010

25

0,02

23

23

23

21

21

Table 2: Comparison between Estim

ated Fixed

Effect and Some Business Climate Indexes (2000-2004).

Source: ICRG: Intern

ational Country Risk Guide and W

orld Bank Developmen

t Indicators (2002Investmen

t Pro

file Index, Competition Index and Transparency Index: World Bank Developmen

t

Rep

ort (2005): “ A better Business Climate for Every one”

16

If we look into the chosen indexes (ICRG, Investment profile, Competition and

Transparency)11 we see that there is a disparity between ratings. For example Côte

d’Ivoire is a risky country. It does not have a good investment profile (the 15th) but it is

well rated in term of competition. Our Business Climate estimator represent in that way, a

sort of combination between all these indexes with other location. That is why, Cote

d’Ivoire is ranked in the fifth position with Fixed Effect Rating despite its bad ICRG

rating12.

In the top five countries short list, we have two from the top five FDI best attractive

countries (Tunisia and Swaziland) and one from the top ten (Cote d’Ivoire). Hence, these

African countries are likely to receive more vertical FDIs than others. Tunisia and

Morocco, for example are two specialized countries in textile and electronic industry.

Tunisia, has promoted since two decades a special policies to attract FDI in labour

intensive industries. Therefore, politicians created many free zones with special taxes

regimes in order to attract MNFs. As Morriset (2001) we can conclude that African

countries can attract FDI according to their Business Climate and not only natural

resources. However, this observation must be putted into perspective that: four from the

top five countries do not have the same structural conditions as the others. Tunisia and

Morocco are North African countries with a quite different economic organisation and

system than Sub- Saharan Africa. They do not suffer also, from geographical

disadvantages and benefit from Europe market proximity. The education and social

factors are more adapted to globalization than it is in Sub- Saharan Africa. South Africa is

also a special case in term of business climate.

The second estimation step consists on the calculating of the fixed effect among

different period. We take a large period: from 1970 to 2004 and we devise it into seven

small periods of five years each13. We estimate, using the same method, the fixed effect of

each country (Within). Thus we construct a fixed effect variable which illustrates the

Business Climate evolution in African countries since 1970. Using different period

estimation is crucial for Business Climate estimation. As we specified before, Business

Climate is not a rigid concept. Also, FDI inflows do not have the same market and natural

resources elasticity among all period. Estimating fixed effect in several periods can show

11 Source : World Development Report (2005) :

12 This is due to civil war and instability.

13 Seven periods : (1970-974) ; (1975-1979) ; (1980- 1984) ; (1985-1990); (1990-1994);(1995-1999) ; (2000-

2004)

17

us the difference between countries in attracting FDI in different periods, and includes

international change in terms of commodities prices, international chocks and world

economic growth.

Figure 2: Evolution of Business Climate (Fixed Effect) Index for selected countries (1970-2004)

-0,8

-0,6

-0,4

-0,2

0

0,2

0,4

0,6

1970 1975 1980 1985 1990 1995 2000

BWA

CIV

CMR

NGA

TUN

ZAF

Source: Fixed Effect Calculated by author; 1970 is representative for period 1970-1974; 1975 is

representative for period 1975-1980; 1980 is representative for period 1980-1985; 1985 is

representative for period 1985-1990; 1990 is representative for period 1990-1995; 1995 is

representative for period 1995-2000; 2000 is representative for period 2000-2004

Figure 2 shows the evolution of Business Climate in the selected African countries.

First, we observe that Africa had a worst Business climate in the seventies. As mentioned

before, the seventies is the postcolonial period and it is characterized by an “anti- white”

economic and political behaviour. Many African countries has nationalized industries and

adopted a political economy of import substitution accompanied with a denigration of all

colonial country aspects (Collier and Gunnig, 1999). In addition, one could explain the

failure of Africa to translate the investments boom of the sixties to a growth process, by

the fact that there was not within countries a political good-will, and an institutional

follow-up allowing the stimulation of the domestic saving and the reform of the

agricultural sector (Savvides, 1995). The investment of the sixties in Africa was the result

of exogenous elements and was followed by a degradation of the structural business

climate.

During the eighties, the Business Climate has knew a little improvement with respect

to the seventies but has decreased quickly in the second eighties period. The Structural

Adjustment recommended by the World Bank, was applied since the beginning of the

18

eighties and has aimed to correct the errors made out in the seventies concerning

agricultural reforms and the improvement of administrative efficiency. Since 1984 one

observed an improvement of the agricultural outputs materialized by the rise of the

volume of production and the increase in agricultural exports. However, this reversal was

only sufficient to stop the decline of the agricultural production per capita. And in spite of

the increase in agricultural exports the balance of payment of the Sub- Saharan African

countries continued to worsen. The agricultural growth rates were higher during the

seventies than for the period post- 1984 (Structural Adjustment Plan Period), especially in

the countries with low density of the population (Akyüz and Gore, 2001). At the end, the

politics of Structural Adjustment have succeeded to disengage the State from the process

of capital accumulation, but did not succeed in creating another form of promoting

accumulation. This analyse justifies the decrease of the Business Climate index, during

eighties.

From 1990 to 1999, the world economy knew a fast and globalized economic growth.

This was followed by an increase of FDI inflows to Developing Countries, especially to

Asian countries. Thus, World Bank and UNCTAD reports insisted on the fact that Africa

failed to attract FDI as the rest of Developing Countries. However, our results figure out

that during that period African Business Climate went better. The divergence between

international organisation interpretations and our results can be explained through two

arguments: (i) First, the comparison between African countries and the rest of Developing

Countries must be putted in the perspective of market and natural resources considerations:

If we take into concern African contribution to world economy, we can say that this

region attracted an important amount of FDIs. (ii) Second, if Africa attracted more FDI

than in the last decade, it is due to an improvement of its Business Climate since their

natural resources and market did not change too much over that period.

The last estimation step of our model aims to look into business climate determinants

in Africa. We use the constructed data of Business Climate (the estimated Fixed Effect)

over the seven chosen periods. Hence we have seven business climates estimation for each

country. Then we collect data for explicative variables for the same periods. This model

is very important for our study. It will test whether Business Climate is determined by

endogenous or exogenous variables or both. It will be an important way to answer the

question: do Africa can be able to improve its business climate throw economic and social

policies?

19

We choose to test three kinds of variables:

(i) First we test human capital determinant of business climate. Variables such

education and infant mortality are usually used in the empirical literature to test

human capital capability. Education indicates the labour quality and the

importance of human capital in government expenditure. Infant mortality is a

variable representing government expenditure in health, quality of life and

poverty alleviation. Finally, we test Human Development Index (HDI) because

it combines a group of human capital indicators such as life expectancy and

nutrition indicator. In addition, HDI index is described by Amarytha Sen as the

best exhaustive indicator to explore population poverty.

(ii) Second we test stability and infrastructure variables: we consider

LOG(TRADE) as an openness indicator and a stability variable. We use the

sum of import and export per GDP us most of empirical literature. We assume

that a country with more openness is likely to have better institutions quality

and better economic stability. Also, VARINFLA14 is an indicator of internal

financial stability. Moreover, we test the number of telephone per 1000

habitant as an infrastructure indicator like Easterly and Levine (1997). Finally,

we test RURAP, the percentage of rural population as indicator of migration,

industrialization and poverty since the industrialization is always followed by

migration to urban cities and since poverty is basically a rural phenomenon.

(iii) Third we test selected exogenous variables. These variables are completely

independent of political decision or institution quality but they are an

inseparable component of the country business climate. We select first, a

geographical variable (COTIER). It indicates if a country is landlocked or not

(landlocked = 0; not landlocked =1). UNCTAD and many empirical studies

pointed out that landlocked countries are less likely to receive FDI or to be

open to trade than others. Then we test COLON as an indicator of what was the

colonial country. This variable is important to distinguish between French and

British ex- colonies. Last, we test ETHN, as an indicator of the ethno-linguistic

fragmentation.

14 We use the variation of inflation rather then the level to explore more the stability prices rather then the

amplitude.

20

(iv) In the last regression we include all variables in a way to test their coefficient

robustness in term of sign and significance.

We choose the GMM estimation method to avoid endogeneity problems especially

between explanatory variables and instrumental variables.

Table 3: Business Climate Determinants

GMM estimator; Number of Countries: 21; Number of Periods: 7

(1) BC and Human Capital Var.

(2) BC and

Stability and

Infra. Var

(3) BC and

Exogenous Var.

(4) BC and

all Var.

EDUS 0,0021

(0,0330)*** 0,0138

(0,0000)***

HDI 0,474

(0,0000)*** 0,2633 (0,1000)*

INFANTM -0,0026

(0,0000)***

GDPPG -0,0201

(0,0000)*** -0,0173

(0,0007)***

VARINFLA

-6,46E-05 (0,0000)***

-2,97E-05 (0,0000)***

TEL

0,0027 (0,0002***)

-0,0077 (0,0002)***

Log(TRADE)

0,0985 (0,0000)***

-0,0648 (0,1414)

RURAP

-0,0064 (0,0000)***

-0,0006 (0,6208)

COTIER

0,138436 (0,0021***)

0,0633 (0,2476)

COLON

0,008906 (0,7845)

0,0406

(0,0598)*

ETHN

-0,019531 (0,7387)

-0,1755 (0,0585)*

CG

0,0004 (0,8741)

R² 0,175 0,056 -0,121 0,033

D-W 1,83 1,59 1,33 1,65

J-Stat 0,22 0,17 0,37 0,22

Table 3 figures out estimations results concerning Business Climate determinants. We

display three columns each one for one category of determinant.

Human capital indicators have, all of them, the predicted sign and significance.

Education has positive and significant coefficient and those in the first and the forth

regression. Grier (2001) found that domestic investment and education are jointly

endogenous. He found out that a one percent increase in primary and secondary

21

educational attainment raises investment by 23% and 20%, respectively. This is in

confirmation with our results. Hence, we can conclude that it is robust and very important

for African business climate. Also, an improvement of the HDI index implies an increase

of the BC index. In addition, a decrease of infant mortality is synonymous of health and

quality of life condition. It is also a result of an improvement of nutrition quality and

availability. Hence, it has the expected effect on Business Climate. Our results point out

that, human capital is very important, even, for African Business Climate. Admittedly,

Africa is basically a natural resources attractive continent, but we find that business

climate matters and depend strongly on human capital stock and quality. Education is very

important for Business Climate improvement because, it is a way to escape poverty, to

improve productivity and to create a collective social capital which permits better

institution and longer stability.

Column (2) shows results concerning stability and infrastructure indicators. We find

that TRADE has a positive and significant effect on Business Climate and by the way on

FDI. This goes in conformity with all the previous empirical studies: Asiedu (2003) tested

the effect of openness/FDI and found that it has a positive and significant effect; Morrisset

(2001) shows that openness to trade is a determinant factor for FDI inflows and for

African countries business climate. This result is very important not only as a Business

Climate determinant but also as an answer to the question whether FDI and Trade are

complement or substitute. Theoretically, horizontal FDI are substitute to trade when

vertical FDI are complement. Natural resources FDI are likely to be complement with

trade because MNF which seek to exploit oil or mineral product aims generally to export

output into international market. Our method permits to isolate the vertical part of FDI,

the one complement to trade. In addition, countries with low trade barriers are likely to

have low barriers to FDI and tend to be more attractive to MNFs (Lall, 2000)

VARINFLA which indicates the variation of inflation and by the way financial

stability has the predictive effect and still significant even for the fourth regression.

Asiedu (2001) using the lag of inflation rate found also that it has a negative effect on FDI

inflows. However, the simple lag of inflation does not indicate necessary the prices

instability because a given country can have a high level of inflation without big

variations among years. In this case we may describe the country as stable where it is not!

In column 3, we test also the infrastructure indicator. We found that it has the expected

positive effect on business climate. Meanwhile, putting all variables together, TEL loses

22

its positive effect and the coefficient sign become negative. We deduce that infrastructure

by itself is not a robust variable and it is correlated with other instrumental variables such

as government consumption. In contrary, Grier (2001) found that Infrastructure has one of

the strongest effects on investment and education in its model. Low infrastructure

countries have 28 percent less secondary schooling attainment, and 45 percent less

investment, than countries with average infrastructure levels. Note that we tested also the

rural population indicator and found that it was negatively correlated with country

business climate.

As World Bank 2005 report indicates, geo-political and social factors are very

important for a country Business Climate. We test in column (3) three indicators: ETHN

shows the level of ethno linguistic fragmentation. Data are provided from Easterly and

Levine (1997). We find out that this variable has a negative effect on business climate and

so on FDI. Ethnic diversity is usually correlated with a weak pro- poverty policy, with a

weak education, political and social instability and inadequate infrastructure. Political

economic models point out that polarised society have more difficulty to put up

development policies which aim to create public goods such as institution, infrastructure

and education (Alesina and Tabellini, 1989; Alesina and Rodrik, 1994). Easterly and

Levine (1997) think that the more is ethnic diversity the more official discriminations

against minority are likely to be established. Hence, Ethno linguistic disparities act as a

negative factor on country Business Climate. Our results confirm this idea. Indeed, we

find out that its coefficient is negative and significant in the fourth regression but not in

the third. Yet, it is not significant when putting only geo-political variables but that is due

to the fact that geo-political variables can’t have a strong effect on business climate when

putted alone. We deduce that ethno- linguistic fragmentation is certainly a negative

Business Climate component but it is not as important as education or political stability.

In addition, education and other institutional variables are negatively affected by social

disparities and that creates a problem of endogeneity between explanatory variables.

Easterly and Levine (1997) found out the same endogeneity problem. Also, they found

that an increase by one point of ethno- linguistic indicator imply a decrease of growth of

GDP per capita of almost 30%. This result is valid for African countries as other

Developing countries.

The second purely exogenous variable is a geographic one. COTIER indicates whether

country is landlocked or not. It is usually mentioned in the geographical models that not

23

landlocked countries are likely to be more open to trade and more attractive to FDI. Grier

(2001), testing the relation between education and investment in Sub- Saharan Africa,

found that geographical indicators have mixed effects. Indeed, he figured out that

landlocked countries are likely to have less education levels than others. While, countries

with tropical climate have better human capital that those with moderate climate.

However, the effect of geographical indicators on investment appears only if we exclude

educational variables. Our model we find out a similar result. Indeed, COTIER has a

significant and positive effect on Business Climate, if only if, we include human capital

variables. Also, we test the relationship between colonial history and current business

climate levels by including a French colonial dummy in the third and fourth equation that

is equal to 1 for countries which used to be French colonies. Contrary to Grier (2001) who

argued that ex-British colonies have higher educational levels on average, we find out that

ex-French colonies are likely to have better Business Climate. This can be due to the fact

that French colonial system aimed to build infrastructure such as roads, hospitals,

ports…in order to facilitate trade and network with African countries.

In the last column we test all variables putted together. The results point out that the

most important African Business Climate determinant is relative to human capital. This is

very important because we have seen before that education is also correlated with

institutional factors and geographical factors. Hence, African countries which are able to

have more open economy and which have development human capital programs are likely

to have better Business Climate.

World Bank Development Report (2005) identified in addition to tested variables

other important Business Climate component. Thus, we can add to this study other

explicative variables such as taxes regimes, wage rates, productivity, war or democracy

indicators and administrative indicators. These factors are also very important for country

Business Climate; meanwhile, human capital and stability factors still the most important.

They constitute a sort of entry barrier to international investor. If a country is instable

or/and do not have a sufficient human capital, it can’t be attractive to vertical FDI.

A survey was conducted by UNCTAD in 1999/200015. It covered 63 large

multinational firms from the database of the top 100 MNFs of UNCTAD. Respondents

were asked to cite the factors that have a negative impact on FDI to Sub Saharan Africa.

49% of the MNFs respondents found that corruption is the most negative factors on Sub-

15 Cited in Asiedu (2003)

24

Saharan Africa. The second negative factor was “the lack of access to global market”.

Nevertheless, Only 24% of the respondents declare that “Tax regulation” has a negative

effect on African Business Climate and the same percentage concerning “FDI regulation”.

This confirms our assumption that human capital and openness are more important than

taxes and regulations in the MNFs decision process.

Hence, in addition to other exogenous form of FDI, African countries can attract more

vertical FDIs like the Asian case. This consists a very important result because literature

on development insists that vertical FDI have better effect on domestic investment and

economic growth than other FDI strategies (Agosin and Mayer, 2000; Blömstorm and al ,

2000).

Conclusion:

This paper examines two important issues. First, we define the Business Climate

concept and find that it is strongly related to location theory (mainly the government

policies determinants). Thus, we establish a theoretical relation between Business Climate

and MNFs mobility which allows the construction of an empirical model.

The panel data with fixed effects estimation gave us a country investment rating

independently from natural resources endowment and market size. Our results show that

countries such as Nigeria which offers a large market and/or natural resources are not the

better ranked in terms of Business Climate whereas countries such as Tunisia, South

Africa, Swaziland and Morocco are perceived as the countries with most attractive

investment environment.

Second, to understand the Business Climate determinants in Africa, we construct an

econometric analysis where the independent variable was the estimated fixed effect and

the explicative variables were inspired from location, geographical and institutional

theories. We find that the most important Business Climate determinants are human

capital factors, namely education. Social indicators such as ethno- linguistic fragmentation

and geographical indicators such as the dummy for landlocked countries are significant

only in the regression including human capital variables. We deduce that exogenous

factors are not able alone to explain the African development failure. An instable and

landlocked country is likely to have a lesser educational level than other countries and

consequently a worst Business Climate but a landlocked country with a good human

capital may have a good business climate. In addition, we find that openness to trade is a

25

very important factor for countries’ attractiveness. This confirms the World Bank

ideology which affirms that the more an economy is open to trade the more it will attract

FDI and then stimulate economic growth. Our results let us conclude that African

Business Climate is not different from other world regions. Policy makers can improve

their countries’ attractiveness by investing in public goods such as education and by

putting lower barriers to trade.

To resume, we can say that, in the long run, better business climate would attract

more diversified FDI and more labour and technological intensive investment. Moreover,

FDI theory focused on the positive effect of FDI on host countries through externalities,

spillovers and technology transfers. This could be a very important contribution to African

economic growth and to poverty alleviation. Hence, an interesting idea for further studies

would be to test the existence of a virtuous circle between FDI, Business Climate and

economic growth.

26

BIBLIOGRAPHIE:

Agosin M. R. et R. Mayer : (2000) “ Foreign Investment in Developing

Countries, Does it Crowd in Domestic Investment”; N°146;

UNCTAD

Akyüz Y. and Gore C. (2001) : « African Economic Development in a

Comparative Perspective » ; Cambridge Journal of

Economics 2001, 25, 265-288

Alchian, A. (1950): “Uncertainty, Evolution, and Economic Theory” The

Journal of Political Economy. 58 (3): 211-211

Asiedu E. (2003): “Foreign Direct Investment to Africa: The Role of

Government Policy, Governance and Political Instability”

University of Kansas; Department of Economics

Asiedu, E (2002). “On the Determinants of Foreign Direct Investment to

Developing Countries: Is Africa Different? ” World

Development, 30 (1), 107-19.

Atkinson, R. (1990): “Understanding Business Climate Studies: Their Use

and Validity” Economic Development Review 8 (1): 46-49

Barro, R.J et Sala-i-Martin, X. Economic Growth ; New York, London, Mc

Graw- Hill

Barrow C. (1998): “State Theory and the Dependency Principle: An

Institutional Critique of the Business Climate Concept”;

Journal of Economics Issues, Vol XXXII No 1 March 1998

Bende- Nabende, A. (2002) « FDI determinants in Sub- Saharan Africa : A

Cointegration Analysis », The University of Birmingham ;

Bjorvatn K., H.J. Kind et H. K. Nordâs “The Role of FDI in Economic

Development”

Blomstrom, M. et Kokko, A. « FDI in Host Countries : A review of the

Empirical Evidence » WP N° 1747 World Bank

Buckley P. et CLEGG J. (1991);“ Multinational enterprises in less

developped countries“ ; New York;.

Caves R.E (1983) « International corporation, the industrial economy of

foreign direct investment » Economica, Paris ;

Collier P. and Gunning J. W.: « Explaining African Economic

Performance »; Journal of Economic Literature, Mars 1999

Easterly W. et Levine R.(1997): “ Africa’s Growth Tragedy: Policies and

Ethnic Division”; The Quarterly Journal of Economics, Vol.

112, No 4 (Nov., 1997), 1203- 1250

Erickson, R. (1987) : “Business Climate Studies: A Critical Evaluation”

Economic Development Quarterly, 1 (1):62-71

Grier, M. (2001): « Spillover Effects of Investment and Education in Sub-

Saharan Africa »; Department of Economics, University of

Oklahoma.

27

Helpman E., Marc J. Melitz et Stephen R. Yeaple; (2003) « Export Versus

FDI » ; NBER Working Paper 9439;

Hernandez- Cata E; (2002) “Raising Growth and Investment in Sub-

Saharan Africa: What Can Be Done?” IMF Policies

Discussion Paper;

Isard W. and Peck J. M. (1954) : “Location Theory and International and

Interregional Trade Theory”; The Quarterly Journal of

Economics, Vol. 68, pp. 97-114

Jenkins C. et L. Thomas (2002): “Foreign Direct Investment in Southern

Africa: Determinants, Characteristics and Implication for

Economic Growth and Poverty Alleviation”.CSAE

CREFSA

Kjell B. Nordal (2001):“Country risk, country risk indices, and valuation

of FDI: A real options approach”; Foundation for Resaerch

in Economics and Business Adminisatration;

Markusen J. R. et A. J. Venables, (1995) « Multinational Firms and The

New Trade Theory. » NBER Working Papers, 5036,.

Michalet C. A. (1997) “Strategies of multinationals and competition for

foreing direct investment”; FIAS

Morrisset (2001). “Foreign Direct Investment to Africa: Policies also

Matter” , Transnational Corporation, 9 (2), 107-125.

Noorbakhsh and Paloni (2001). “Human Capital and FDI Inflows to

Developing Countries: New Empirical Evidence,” World

Development, 26 (7), 1593-1610.

Plaut T. and Plut J. (1983): “Business Climate, Taxes and Expenditures,

and State Industrial Growth in the United States”; Souther

Economic Journal, Vol. 50, N°1, pp. 99-119

Predohl A. (1928) « The theory of location in its relation to General

Economics » ; The Journal of Political Economy, Vol. 36,

N°3, pp. 371-390

Richardson J. D. (1971) «On ‘going abroad, the firm’s initial foreign

direct investment decision»The Quarterly Review of

Economics and Business; N° 11

Rodrik, Dani (1998). “Trade Policy and Economic Performance in Sub-

Saharan Africa” NBER Working Paper No 6562.

Sachs and Warner (1995): “Natural Resource Abundance and Economic

Growth” NBER

Smith, D. (1981). Industrial Location: An Economic Geographical

Analysis, 2nd ed. New York

United Nations Center for Trade and Development (1999). Foreign Direct

Investment in Africa: Performance and Potential. New

York: United Nations Publication.

28

United Nations Industrial Development Organization UNIDO (2003):

“African Foreign Investment Survey 2003: Motivation,

Perception and Future Implication »