Location Theory, Business Climate
and Foreign Direct Investment in Africa
Preliminary Draft
Mars, 2007
Noomen LAHIMER
Université Paris- Dauphine
Centre de Recherche : EURIsCO
[email protected]
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
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.
2
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
3
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.
4
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.
5
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
6
very weak because of their strong capital intensive intensity, their geographical bulkheading 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
7
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.
12
Singapore
10
8
6
Mexico
GDPPG
4
0
-2
Tunisia Egypt,
India
Nigeria
Ghana
Brazil
Algeria
Madagascar
Zambia
South Africa
Gabon
Morocco
Senegal
Mali
10
20
30
40Kenya Malawi
50
60
70
80
Thailand
2
-10
Malaysia
0
Togo
Niger
-4
-6
Cote d'Ivoire
-8
NR
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 SubSaharan 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
8
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.
9
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)
BCi =
FDI i
(GDPi × NRi )
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
10
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:
FDI i ,t = α i + β1 LOG (GDPi ,t ) + β 2 NRi ,t + ε i ,t .
(2)
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
•
α i 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.
11
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 nonsignificant in all periods except for two periods: 1970-1974 and 1975-1980 7 . 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
12
Table 1: Estimation Results for all Periods (1970- 2004)
Périodes
2000-2004
Within
Estimator
FDI/GDP
Log(GDP)
-0,0062
NR/GDP
0,1992
(0,4045)
Fishers Test for
Fixed Effect
Test of
Haussmann for
Random Effect
2.98
(0.0001)***
1.95
(0.3776)
3.85
(0.0001)***
0.57
(0.7522)
6.02
(0.0001)***
0.47
(0.7892)
11.79
(0.0001)***
0.41
0.8143
4.32
(0.0001)***
0.22
(0.8960)
2.18
(0.0041)***
4.61
(0.0998)
2.12
(0.0062)***
1.74
(0.4186)
(0,007)***
1995-1999
Log(GDP)
-0,0196
NR/GDP
0,1283
(0,4127)
(0,1475)*
1990-1994
Log(GDP)
-0,0063
NR/GDP
0,0264
Log(GDP)
0,00053
NR/GDP
-0,0036
Log(GDP)
-0,0053
NR/GDP
0,0821
(0,4786)
(0,507)
1985-1989
(0,9271)
(0,9046)
1980-1984
(0,5987)
(0,1423)*
Log(GDP)
1975-1979
0,0252
(0,0194)**
NR/GDP
0,0615
Log(GDP)
0,0112
NR/GDP
-0,0027
(0,4292)
1970-1974
(0,154)*
(0,9463)
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 climate 10 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.
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.
9
13
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.
14
Average
Inv.
FIXED
FDI ICRG ICRG
Inv. Competitiveness Compt. Transparency Transp.
Profile
EFFECT Rank FDI/GDP(%)
Rank Index Rank
Class
Index
Rank.
Index
Rank
(CI)
(2000-2004)
Index
0,147
0,15
68,8
10,5
5,3
4,3
1
18
4
3
1
9
0,135
1,31
11,5
5,1
5,3
2
1
2
3
2
0,132
0,77
72,8
8
4,5
5,1
3
3
3
12
5
4
0,109
0,13
75
9
4,4
3,5
4
19
2
6
7
15
0,109
0,45
55,8
6
5
8
16
17
22
22
0,108
0,75
53
6
4,1
4,5
6
4
19
18
14
5
0,107
0,24
66
6,5
4,4
..
7
13
6
16
6
1
0,104
0,06
37
6
4,1
4,5
8
22
21
19
15
6
0,098
0,29
64,8
8
4,3
3,9
9
12
9
11
9
12
0,092
0,43
61,5
8
4,2
3,5
10
9
12
9
10
16
0,087
0,17
65,8
9
5,2
4,2
11
16
7
5
2
10
0,080
0,22
79,3
11,5
4,1
5,1
12
14
1
1
12
3
0,072
0,68
58,5
7,5
3,8
4
13
5
14
13
16
11
0,067
0,18
53,7
9
14
15
18
4
20
20
0,062
0,30
54
8
4,2
3,5
15
11
17
10
11
17
0,061
0,16
66,3
8
3,5
3,6
16
17
5
8
17
13
0,057
1,03
60,8
8,5
17
2
13
7
23
23
0,054
0,67
62,8
7
4,3
3,6
18
6
10
14
8
14
0,051
62
6,5
4,1
4,4
19
24
11
15
13
7
0,047
0,54
57
3,5
4,7
3,4
20
7
15
21
4
18
0,040
0,33
21
10
22
22
19
19
0,039
-0,17
65,3
4,3
22
25
8
25
24
8
0,033
0,09
23
21
24
24
18
24
0,020
0,11
47
6
24
20
20
20
25
25
0,010
0,02
25
23
23
23
21
21
15
Source: ICRG: International Country Risk Guide and World Bank Development Indicators (2002Investment Profile Index, Competition Index and Transparency Index: World Bank Development
Report (2005): “ A better Business Climate for Every one”
Table 2: Comparison between Estimated Fixed Effect and Some Business Climate Indexes (2000-2004).
South Africa
Swaziland
Tunisia
Morocco
Côte d’Ivoire
Zambia
Egypt
Zimbabwe
Senegal
Madagascar
Kenya
Botswana
Mali
Burkina Faso
Malawi
Algeria
Congo Rep.
Ghana
Cameroon
Nigeria
Burundi
Gabon
Rwanda
Congo Dem.
Central Africa
Country
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) :
This is due to civil war and instability.
13
Seven periods : (1970-974) ; (1975-1979) ; (1980- 1984) ; (1985-1990); (1990-1994);(1995-1999) ; (20002004)
12
16
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)
0,6
0,4
BWA
0,2
CIV
0
CMR
1970
1975
1980
1985
-0,2
1990
1995
2000
NGA
TUN
-0,4
ZAF
-0,6
-0,8
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
17
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?
18
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.
19
(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.
EDUS
HDI
INFANTM
GDPPG
(2) BC and
Stability and
Infra. Var
(3) BC and
Exogenous Var.
0,0021
0,0138
(0,0330)***
(0,0000)***
0,474
0,2633
(0,0000)***
(0,1000)*
-0,0026
(0,0000)***
-0,0201
-0,0173
(0,0000)***
(0,0007)***
VARINFLA
TEL
Log(TRADE)
RURAP
-6,46E-05
-2,97E-05
(0,0000)***
(0,0000)***
0,0027
-0,0077
(0,0002***)
(0,0002)***
0,0985
-0,0648
(0,0000)***
(0,1414)
-0,0064
-0,0006
(0,0000)***
(0,6208)
COTIER
COLON
ETHN
0,138436
0,0633
(0,0021***)
(0,2476)
0,008906
0,0406
(0,7845)
(0,0598)*
-0,019531
-0,1755
(0,7387)
(0,0585)*
0,0004
CG
R²
D-W
J-Stat
(4) BC and
all Var.
(0,8741)
0,175
1,83
0,22
0,056
1,59
0,17
-0,121
1,33
0,37
0,033
1,65
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
20
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
21
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
22
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 1999/2000 15 . 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 Sub15
Cited in Asiedu (2003)
23
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
24
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.
25
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