Economic Determinants of Foreign Direct Investment Inflow in Cameroon

Sonkey Louis Ntu¹ and Miracle Lobe^2*
*Correspondence: Miracle Lobe, Department of Economics and Management Sciences, University of Bamenda, University of Bamenda, Cameroon, Email:

Keywords

Foreign direct investment • GDP • Inflation • Trade openness • Gross fix capital formation

Introduction

Prior to the mid-1980s, Cameroon's policies were aimed to show that the public sector plays a substantial role in economic development when compared to the private sector. After the 1980s, however, major government reforms such as foreign investment encouragement, privatisation, and liberalisation were implemented. Growth and development would not be fostered, according to, unless emerging countries with abundant natural resources polished their endowments. He explained that citizens struggle to achieve their level of development due to a high marginal propensity to consume and, as a result, a low level of savings. According to him, a low level of savings leads to a low rate of capital formation, which is linked to a high rate of poverty. Kumo makes this point. Multinational Enterprises (MNEs) transfer capital, technological knowledge and management to the local corporations, it was projected that their existence in Cameroon would advance the trade, economic growth and industry situation of the country [1].

This study was therefore aimed at investigating the Economic Determinants of Foreign Direct Investment (FDI) inflow in Cameroon. The work therefore embarked on answering the question “What are the Economic Determinants of Foreign Direct Investment (FDI) inflow in Cameroon?” In achieving this, the Ordinary Least Square (OLS) estimation technique was employed to estimate the coefficients of the variable in the model, with data from world bank development indicator [2]. On the basis of the OLS results obtained from the FDI model, Gross Fix Capital Formation, Gross Domestic Product, and Household Consumption positively affect the inflow of foreign direct investment in Cameroon and were all statistically significant. By implication, an increase in these variables, would lead to an increase in foreign direct investment inflow in Cameroon ceteris paribus. Though Inflation, Openness to Trade and Government Expenditure also had a positive relationship in attracting the inflow of FDI in Cameroon, their coefficients were not statistically significant [3].

Literature Review

Many researchers as shown above have made extensive studies regarding the determinants of FDI inflows and concluded that inward FDI determinants does not consider any boundary because it flows from regions to regions and/ or countries to countries that are known for their features such as good fiscal policy, political stability minimum security risk, quality infrastructure, low cost of skilled labour, attractive market, higher rate of return and ease of doing business. Amna analyzed the impacts of FDI and the inflation on the economic growth of Pakistan by using time series data from 1981 to 2010. A multi regression technique was used to estimate the model. According to the results, FDI has a positive and significant impact on economy whereas the inflation has a negative contribution in the Cameroon’s economy [4]. Globerman and Shapiro examined 144 industrialized and emerging countries between 1995 and 1997 with the main objective to investigate the impact of institutional infrastructure on both FDI inflows and outflows. They made use of the resulting indices such as the Human Development Index (HDI), Environmental Regulation Indices (ERI) and kaufmann Governance Infrastructural Indices (GII).

In order to run their regression using the OLS technique, they had to control factors such as taxation, labour cost, openness, instability of exchange rate and GDP. At the end of the study, they realize that GDP and openness has a positive role to play on a global scale. Hence, concluded that regulatory environment, rule of law and graft variables have economic significance as the determinants of FDI inflows. In addition to this, Ali, Fiess and MacDonald discussed similar questions as Globaberman and Shapiro as per whether institutions matter for FDI inflows [5]. This was demonstrated by using a panel of 69 economies over the years 1981-2005 and dataset obtained from World Bank that breaks down the inflows of FDI in to primary, manufacturing and services sectors. They estimated their models with a panel random effects model while controlling factors such as inflation, top marginal tax rate, GDP per capita, openness and tariffs. At the end, their result confirmed that institutional quality is a robust determinant of inward FDI under different specifications in the services and the manufacturing divisions. However, in the primary segment, there is no robust influence of institutions on inward FDI. Finally, it was concluded that in terms of the size and consequence of the coefficient, property rights institutional variables are known to be the most relevant factors when associated with other variables such democracy, social tension, corruption and political instability [6].

Vijayakumar, Sridharan and Rao uses panel least square method with fixed impact to analyze the factors that controls FDI inflows in China, Russia, South Africa and Brazil between 1975 and 2007. According to them the possible factors of FDI inflows to these economies are labour cost, infrastructure, market size, gross capital formation and exchange rates. Due to their analysis, they establish out that growth prospect measured by industrial production, economic steadiness measured by rate of inflation and trade openness are concluded to be statistically insignificant and therefore economically less vital as determinant factors of FDI inflows in these economies. Inflation rate increase in host country reduces FDI as it erodes the value of the profits made by foreign firms. Low inflation reduces nominal interest rates and consequently pushes down the cost of capital for foreign investors. On the contrary, noted that it is possible that inflation in the host country can have a positive impact on FDI inflows on condition that it does not exceed a certain threshold level. To summarize the review of literature, economic factors play a positive and significant role on FDI inflows in many advance countries. Nevertheless, many studies have neglected to investigate the determinants of FDI inflow in developing countries particularly in middle income developing country like Cameroon. Therefore, this study seeks to fill in this gap and hence adding to the literature on the determinants of FDI inflows [7, 8].

Data collection: The basis of our analysis is on time series data. The data used in this study was collected from secondary sources. Data for the study is collected from World Bank data base known as World Development Indicators. The data run from 1984 to 2018 making it a 34 years’ study [9, 10].

Model specification: FDI affects the growth of many economies in the world; therefore, the study seeks to determinants the role played by economic factors such as trade openness, inflation, government spending, tax policy, consumption, gross fix capital formation and GDP in attracting FDI in Cameroon. The model introduced in this study therefore captured such independent variables that are relevant in bringing FDI in Cameroon and also on the bases of data availability. However, the choices of the inclusion of the variables in the models were based mostly on empirical, as well as, theoretical considerations [11, 12].

On the basis of the justifications of the inclusion of variables in this study, the FDI model is specify as follows:

FDI=f (GDP, INFLA, GE, GFKF, TAX, CONS, OPEN) ….………… ……...……………… (3.1)

The function above shows a relationship between Foreign Direct Investment (FDI), with Gross Domestic Product (GDP), Inflation (INFLA), Government Expenditure (GE), Gross Fix Capital Formation (GFKF), Tax Policy (TAX), Household Consumption (CONS). The above associations between the dependent and the independent variables show that there exists a relationship as such. In therefore transforming this in to an econometric model, a stochastic error term is introduced. In the econometric sense, the model is specified in its a priori as follows:

FDIt=β0+β1GDPt+β2INFLAt+β3GEt+β4GFKFt+β5TAXt+β6CONSt +β7OPENt+ɛ............(3.2)

• Is foreign direct investment,

• Represents real GDP per capita which indicates economic growth rate in Cameroon,

• INFLA represent inflation rate in the economy,

• GE represent Total Government Expenditure,

• GFCF is Gross fixed capital formation,

• TAX represent Tax policy existing in the economy,

• CONS is Household Consumption, and

• OPEN represent Trade Openness between Cameroon and the world.

ß1, ß2, ß3, ß4, ß5, ß6 and ß7 are the coefficient of GDP, INFLA, GE, GFCF, TAX, CONS, and OPEN respectively. ß0 is the constant term and ɛ is the disturbance term [13, 14].

Our a priori expectation is as follows: β0 ≠ 0, β1, β3, β4, β6 and ß7>0 while ß2 and ß5<0

Estimation techniques: This study seeks to investigate the contributions or effects of FDI on the economic growth in Cameroon. This study therefore employed the Ordinary Least Square (OLS) technique for the estimation of the parameters of the model specified above. This is because it possesses the Best Linear Unbiased Estimator (BLUE) property and has been widely used in literature. Unbiased per this content implies that the estimated coefficient is a true representation of the population parameter and it is also said to have the minimum variance among all other estimators rendering it efficient [15]. The Ordinary Least Square technique of estimation is used when the dependent variable is continuous and not a discrete choice variable. Our model that follows a time series (t) is an example of a continuous variable. The Ordinary Least Squares (OLS) method results how much each independent variable affects the dependent variable, holding other independent variables constant [16, 17].

Stationarity test of variables

The results above Table 1 describe the statistical relationship between the dependent variable and the independent variables. The test was conducted at the 5% level of significance given a 95% confident level of the results [18]. The null hypothesis of each variable will be tested and the decision role of either rejecting or do not rejecting the null hypothesis is: “If the P-Value for a variable is less than your significance level (<0.05), the sample data provide enough evidence to reject the null hypothesis for the entire population implying that the data favor the hypothesis that there is a non-zero correlation. Changes in the independent variable are associated with changes in the response at the population level (dependent variable). This variable is statistically significant and probably a worthwhile addition to your regression model [19,20].

On the other hand, a P-Value that is greater than the significance level (>0.05), it indicates that there is insufficient evidence in your sample to conclude that a non-zero correlation exists that is, changes in the independent variables cause no change in the dependent variable and as such, the null hypothesis is not rejected [21, 22]. From the OLS results, the probability value of Inflation is 0.1396 and is greater than the level of significance (0.05) implying that there is an insignificant relationship between Inflation and FDI inflows in Cameroon. Although there is a positive relationship between inflation and FDI inflow in Cameroon because the sign of the coefficient of inflation is positive, this relationship is statistically insignificant at the 5% level of significance. The null hypothesis is not rejected. The coefficient of inflation is 7.546892 indicating that an increase of 1 unit in the rate of inflation will increase by 7.546892 units the inflow of FDI in Cameroon. The sign of the coefficient is however contrary to my priori expectation sign for this variable [23, 24].

Also, Gross Fix Capital Formation (GFKF) shows a positive relationship with FDI inflow in Cameroon as the sign of the coefficient of GFKF is positive. However, the probability value (0.0132) is less than the level of significance (0.05) indicative of a positive and statistically significant relationship. The coefficient of GFKF is 47.83600 indicating that a unit increase in GFKF will increase FDI inflow in Cameroon by 47.83600 and this result is highly significant at 5% level of significance, implying that this variable is very important in estimating this model and the sign of the coefficient is in line with the expected priori sign and the null hypothesis is rejected. Again, the coefficient of Government Expenditure (GE) is positive indication a positive relationship with FDI inflow in Cameroon. The probability value of GE is 0.1539 which is greater than the level of significance at the 5%. The coefficient of GE is 19.14851 indicating that a unit increase in GE will increase the inflow of FDI by 19.14851.

This result is positive but statistically insignificant at 5% level of significance, implying that GE is not a good variable to be used in the model. The sign of the coefficient of GE is in line with the priori sign of this study and null hypothesis is not rejected. The coefficient of GDP is positive, which implies that there is a positive relationship between GDP and FDI inflow in Cameroon. This means that an increase in GDP will lead to an increase in FDI and a decrease in GDP will result to a decrease in FDI [25, 26]. The coefficient of GDP is 0.000421 indicates that an increase in GDP by 1 unit will lead to an increase in the inflow of FDI by 0.000421. Units this effect is statistically significant at 5% level of significance since the P-Value of GDP (0.0333) is less than the level of significance (0.05). The sign of the coefficient is consistent with the a priori expectation which shows there is a positive relationship between GDP and FDI. Thus, GDP is an important policy instrument to use in influencing the inflow of FDI in Cameroon. The null hypothesis is rejected. OPEN in the same trend has a positive relationship with FDI inflow in Cameroon. The coefficient of OPEN is 2.917767 indicating that a 1 unit change in OPEN will increase the inflow of FDI by 2.917767. This result is statistically insignificant at the 5% level of significance as the probability value of 0.4059 is greater than the level of significance. The result is in line with the expected priori sign. Openness to trade is therefore not a good variable to be included in this model and the null hypothesis is not rejected [27, 28].

Contrarily, there exist a negative and insignificant relationship between Taxes and FDI inflow in Cameroon because the sign of the coefficient is negative. This relationship is however statistically insignificant since the probability value of taxes (0.6280) is greater than the 0.05 at the 5% level of significance. This implies that increases in tax rate will lead to decrease in FDI inflow in Cameroon. The coefficient of taxes (-1.867028) means that for every decrease in taxes by 1 unit will attract 1.867028 units of FDI in Cameroon. The sign of the coefficient is in line with our priori expectation sign. Taxes are not a good variable to be added in this model and our null hypothesis is not rejected. Household Consumption in the same trend has a positive relationship with FDI inflow. The coefficient of Consumption is 8.31E-11 indicating that a 1 unit change in CONS will increase the FDI by 8.31E-11 units. This effect is statistically significant at 5% level of significance. This is so because the probability value of CONS (0.0287) is less than the level of significance (0.05). The sign of the coefficient is consistent with the a priori expectation which shows there is a positive relationship between CON and FDI. Thus, CONS is an important policy instrument to use in influencing the inflow of FDI in Cameroon. Therefore, the null hypothesis is rejected [29].

The coefficient of the constant -1054.810 indicates the intersect which implies that if all the independent variables under study were considered to be zero or not to have any effect on the dependent variable (FDI), FDI will be -1054.810 in the model and it is statistically significant at 5% level of significance since the probability value of 0.303 is less than 0.05. To conclude, the table above shows the model fit of the variable. The value for R-square Adjusted indicates the degree of variations in FDI inflow in Cameroon captured by variations in the variables used in the model. From the result above, the value of R-square is 0.644503 and R-square Adjusted is 0.521863 indicating that 52.19% variation in the inflow of FDI in Cameroon is attributed to the changes (variations) in the variables included in the model while 47.81% variations in FDI inflow in Cameroon is caused by variables not included in the model. However, the overall model is statistically significant at the 5 percent level of significance as the F-test probability value of 0.001316 is less than the level of significance (0.05). Therefore, the null hypothesis was rejected and it was concluded that, Economic factors significantly contributes to the inflow of FDI in Cameroon [30].

Discussion

This study was aimed at investigating the effects of Economic factors on Foreign Direct Investment (FDI) inflow in Cameroon. On the basis of the OLS results obtained from the FDI model, Gross Fix Capital Formation, Gross Domestic Product, and Household Consumption positively affect the inflow of foreign direct investment in Cameroon and were all statistically significant. By implication, an increase in these variables, would lead to an increase in foreign direct investment inflow in Cameroon ceteris paribus. Though Inflation, Openness to Trade and Government Expenditure also had a positive relationship in attracting the inflow of FDI in Cameroon, these results were not statistically significant and were not good variables to be included in the study meanwhile taxes had a statistically insignificant result and a negative relationship with FDI inflow in Cameroon [31].

We therefore reject the null hypothesis that Economic factors have no significant effect in influencing the inflow of Foreign Direct Investment (FDI) in Cameroon. The significance of this result could possibly be attributed to high anticipations by foreign investors on the economic prosperity of Cameroon and the fact that the government of Cameroon enacted laws and degrees such as the provisions in the 1990 investment code, Heavily Indebted Poor Countries (HIPC) initiative (amongst others) and the 1994 devaluation which encouraged international trade and led to trade surpluses. The finding contrary to analysed the impacts of FDI and the inflation on the economic growth of Pakistan by using time series data from 1981 to 2010. A multi regression technique was used to estimate the model. According to the results, FDI has a positive and significant impact on economy whereas the inflation has a negative contribution in the Cameroon’s economy. Inflation has a significant effect in attracting the inflow of FDI in Cameroon. The significant relation between inflation and FDI could be a stimulate to investment as a result of high prices depending on the level of inflation rate in the country. Noted that it is possible that inflation in the host country can have a positive impact on FDI inflows on condition that it does not exceed a certain threshold level.

Who Expanded the literature beyond these adopting nation’s specific macroeconomic indicators by increasing their sample size among countries and provided the first empirical study to our knowledge to go deep into the international trade influence of inflation targeting. The results show that inflation targeting is significant in attracting FDI cash flows. The attraction is slightly stronger for developed nations than for developing nations. However, when the developing nations are split between upper- and lower-middle incomes we do find inflation targeting to attract more FDI for the lesser developed nations. Also, the positive and significant relationship gross fix capital formation and inflow of FDI was further comfirmed by Vijayakumar, Sridharan and Rao uses panel least square method with fixed impact to analyse the factors that controls FDI inflows in China, Russia, South Africa and Brazil between 1975 and 2007. According to them the possible factors of FDI inflows to these economies are labour cost, infrastructure, market size, gross capital formation and exchange rates. Due to their analysis, they establish out that growth prospect measured by industrial production, economic steadiness measured by rate of inflation and trade openness are concluded to be statistically insignificant and therefore economically less vital as determinant factors of FDI inflows in these economies.

The study also portrays a negative relationship between Tax and FDI. This result is however confirmed by De Mooij provide useful overviews. After removing outliers, they calculate a mean value tax elasticity of -3.3, suggesting that a 1 percent reduction in the host country rate of tax on capital would increase total FDI inflows by 3.3 percent. Studies of the impacts of other forms of taxation on FDI are scarce. Egger and Radulescu examine labor tax impacts on the location of foreign subsidiaries and find that both the capital income tax rate and the constructed labor income tax rate have a negative relationship to the prevalence of subsidiaries or branches of foreign owned corporations. Also find evidence that indirect taxes (taxes other than payroll and corporate income taxes) depress FDI. Finally, as expected, the coefficient of trade openness is positive implying that more trade liberalisation will attract many more investors into the national territory. However, no significant relationship could be established between this variables and foreign direct investment inflow.

Conclusion

As developing countries aim at meeting the millennium and sustainable development goals, Cameroon’s policy makers should design and implement fiscal and monetary policy to enhance the country’s attractiveness as a recipient country for FDI by making sure that these policies are acceptable to foreign investors. Success in attracting foreign capital inflows would accelerate the accumulation of the country’s capital stock, thus setting the stage for the progressive structural transformation of the country’s economy from a largely agriculture-based economy to a growing economy with expanding industrial and service sectors capable of absorbing the existing labor surplus and of reducing unemployment and poverty by improving the living standards of its people. Also, Cameroon government, using monetary and fiscal policies should enact plans to reduce the taxation policy in the economy, maintain a favourable and stable rate of inflation and trade so as to easily attract FDI in the economy. Above all, the government should improve the business environment by eliminating bribery and corruption as well as the degree of underground economy that can discourage foreign investors and reduce the inflows of FDI.

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