Foreign direct investment in non-landlocked Africa countries (página 2)

In summary, the empirical findings show that financial
development, balance of payment, trade openness, domestic
savings, inflation and economic growth are the main determinants
of FDI inflows to non-landlocked countries of Africa excluding
the Lusophone countries. On a comparative basis between the
Arabophones and Francophones countries, the result shows that the
financial development, balance of payment, and trade openness are
the main determinants of the FDI inflows to both regions
identified with linguistic approach. However, infrastructure
development, domestic investment and short-term infrastructure
development are also found to be important additional
determinants of FDI inflows to Francophones countries. Although
the contemporaneous domestic investment, infrastructure
development and domestic savings did not have statistical
significant on FDI inflows to Arabophones countries, these
variables were found to be critical determinants of FDI to
Arabophones in the long-run and statistically
significant.

Conclusion

This paper assesses the effect of some determinants of
foreign direct investment (FDI) inflows of non-landlocked Africa
countries using a linguistic approach. It covers the period from
1980 to 2010 and employs an unbalanced panel dynamic ordinary
least square method of analysis. A theoretical review is first
undertaken to elucidate the relationship between the selected
macroeconomic variables used in the study and foreign direct
investment inflows. The inclusion of the FDI"s determinant
variables in the model was based on the push and pull factors as
well as some macroeconomics variables that investors use as a
yardstick in measuring profit destination for
investment.

The contemporaneous trade openness was found to have
positive significant to foreign direct investment inflows to
Arabophones, Francophones and non-landlocked countries excluding
Lusophone countries. Infrastructure development has a negative
effect on FDI inflows to Francophones countries and the same
effect on FDI inflows to Arabophones in the long-run.

The result shows that economic growth and inflation have
a positive effect on FDI inflows to Arabophones and Francophones
countries in the models that captured them as dummies. However,
an FDI inflow decreases to Francophones as a result of an
increase in the level of financial development but increases to
Arabophones under the same condition. It implies that FDI
investors attracted to Arabophones may be associated with market
seeking investors while the investors attracted to Francophone
were both the resource seeking and nonmarket seeking investors.
Consequently, FDI investors in non-landlocked Africa countries
excluding the Lusophone are market seeking investors in general.
This inclusion was based on effect financial development, balance
of payment and trade openness effect on FDI inflows to the
recipient (non-landlocked Africa countries).

The paper recommends that policy makers in the
Francophone countries should adapt promotional policies to
attract some types of foreign direct investment which are willing
to convert the primary resource to finished product and regulate
others. Policies should be aimed at putting in place an ideal
model based on the national goal of the country to screen foreign
direct investment applications so as to ascertain their
productivity level. The paper strongly recommends that policies
aimed at encouraging the foreign investors to reduce their level
of profit expatriation. This can be done by providing an
efficient financial system, investment more on infrastructure
development and maintain a stable inflation rate in these
regions.

The study has shown that Arabophones members except
Mauritania countries are part of the northern Africa, which is
the highest recipient of FDI inflows in Africa to date (UNCTAD,
2010). This performance can be deduced from the effect of
contemporaneous financial development and long-run domestic
investment on foreign direct investment inflows to Arabophones
and it is consistent to theory. On this remark, the paper
recommends that although contemporaneous domestic investment has
a positive effect on FDI inflows to Francophone, the member
countries should retrospect various polices adopted by
Arabophones and incorporate that in their future policy
adaptation where applicable. Its recommendation was also based on
the result that language was not a significant determinant of FDI
in non-landlocked Africa countries excluding the Lusophone member
states.

The foremost constraint was the problem of
unavailability of some important variables from the selected
countries which were detrimental to FDI inflows to the
non-landlocked countries.

Additional limitations are insufficient funds which have
restricted the chance of directly assessing the data from the
individual country database and the delinquent associated with
using different sources of secondary data. This problem may
result in either overestimation or underestimation of the
variables used in the model estimation. The current paper has
made a substantial contribution to the literature by using a
panel rather than the commonly used cross-country studies.
However, future studies should focus more comparative analysis
including both linguistic and directional approaches, more
importantly, a rigorous comparative analysis of a cross-sectional
study of expectation and motives of foreign direct investors and
the recipients in Africa.

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Mrpresident2002

[1] FDI is an investment made to get hold of
a long-term management interest (at least 10 percent of voting
stock) in a business enterprise operating in a country other
than that of the investor’s country of residency (World
Bank, 1996). FDI may take the form of either
“Greenfield” investment or merger and acquisition
(M&A), and the latter entails, the acquisition of existing
investment rather than new investment. It includes not only
M&A and new investment, but also reinvested earnings and
loans and similar capital transfer between parent companies and
their affiliates (Adeolu, 2007).

[2] A first generation of models has analyzed
the properties of panel-based unit root tests under the
assumption that the data is independent and identically
distributed (i.i.d.) across individuals.

[3] If t- statistic is significant which has
a corresponding p-values less than 1% as represent with one
asterisk (*) and p-value less than 5% as represented with two
asterisk (**) . It implies that t-statistic is significant and
the conclusion is that null hypothesis is rejected or panel
data has no unit root. Otherwise if t-statistic does not have
any asterisk implies that it is not significant then conclusion
is that do not reject the null hypothesis or panel data has
unit root

[4] The rule of thumb stipulates that if the
correlation is approximately to 0.9 and it is likely that
multicollinearity is present between the variables in question.
It also implies that if the variables are of very important, it
then means that two separate models have to be estimated
incorporating the variable one after the other. That is to
capture their effect on the dependent variables otherwise drop
one of the variables.

[5] Hausman diagnostic test was employed to
determine the proper specification of the model. It is of
paramount importance to know whether the model is to be
specified under fixed effect estimate or random effect
estimation and as well to solve the endogeneity problems
amongst the explanatory variables. The test statistic of the
Hausman test is asymptotically distributed as chi-square such
that if the Hausman test statistic is large and significant,
you reject the null hypothesis of random effect specification
and specified a fixed effect estimate. The null hypothesis is
tested to find the existence of correlation between the
stochastic error term and explanatory variables. If the
correlation does not exist, implied that the probability value
associated to the test was insignificant, then do not reject
the null hypothesis, then the model will be specified using
random effect estimation, otherwise the proper estimate is
fixed effect estimate.