Modelling the synergy between fiscal incentives and foreign direct investment in Ghana

Abstract

Purpose

The purpose of the paper was to investigate the role of fiscal incentives in driving foreign direct investment (FDI) inflows into the Ghanaian economy based on data from 1975 to 2017 with the Eclectic paradigm as the theoretical basis. FDI inflows was the dependent variable whiles trade openness, corporate tax rate, exchange rate and market size were the independent variables with corporate tax rate as the main explanatory variable of interest.

Design/methodology/approach

The autoregressive distributed lag (ARDL) bounds test technique was employed to investigate Cointegration in the model. The results showed the presence of cointegration among the variables.

Findings

The results revealed that corporate tax rates have a significant negative impact on FDI inflows into the Ghanaian economy in the long run and significant positive impact on FDI inflows in the short run. In the context of Ghana, the positive short-run relationship observed is attributed to the lag effect of tax policy on FDI inflows.

Research limitations/implications

One obvious limitation of the research is that, it does not identify the specific foreign businesses that are more deserving of a low corporate rate and to what extent can that boost FDI inflows in Ghana. Another limitation is that the data analyzed in the paper is exclusively for Ghana and the findings may not be generalized for other countries.

Practical implications

Based on the research findings, it is recommended that the Ghana Revenue Service (GRA) restructures the corporate tax regime in the country to deal with the policy lapses. It is also recommended that low corporate rates should be maintained especially in respect of foreign companies that are into the production of goods and services for which indigenous companies in Ghana have a comparative disadvantage in order to drive FDI into the Ghanaian economy.

Originality/value

This paper is unique for providing up to date and dynamic insights into the tax incentive and FDI nexus in the Ghanaian context.

Citation

Abille, A.B., Mpuure, D.M.-N., Wuni, I.Y. and Dadzie, P. (2020), "Modelling the synergy between fiscal incentives and foreign direct investment in Ghana", Journal of Economics and Development, Vol. 22 No. 2, pp. 325-334. https://doi.org/10.1108/JED-01-2020-0006

1. Introduction

A foreign direct investment (FDI) takes place when an investor establishes foreign business operations in a foreign country (Chen et al., 2019). There has been intense competition among developed and developing countries to attract FDI in recent years. This competition for FDI is due to the fact that foreign capital creates employment and economic growth, augments the productive capital of a country, promotes transfer of technology and skills to the host country and hence helps alleviate poverty, among other benefits (Obeng, 2014). In the past decades, many nations especially developing nations have been making frantic efforts directed toward the attraction of FDI. The expectation is that FDI would contribute positively to economic growth of the host nation (Ugwu, 2018). FDI can be viewed as assets, which augment other investment streams and make a distinguishing contribution to the growth process of a country (Asante and Gyasi, 2000). With the low level of savings that characterized emerging markets, i.e. developing economies like Ghana, FDI can be a very useful alternative to boosting the productive capacity of such economies, which will lead to growth and job creation (Majavu and Kapingura, 2016). These expected inherent gains in FDI inflows have led to competition for FDI inflows among various countries especially developing countries. Generally, this competition usually presents a herculean task for African emerging markets due to the common image that Africa can be a high-risk investment region (Gumo, 2013).

To this end, these economies usually go the extra-mile to put various measures in place to be adjudged as business friendly destinations. Notable among these measures includes the liberalization of the economy, provision of guarantee on repatriation of profit, tax incentives and provision of critical infrastructure as well as cheap labor (Chakrabarti, 2001). Among these measures, tax incentives by far have been a common place for most governments as it provides direct relief to firms and place them in a strategic position thus facilitating their performance and their stay in business. Relief takes the form of personal allowance, investment allowance, loss relief, roll-over relief, pioneer relief and exploration relief, to mention but a few (Peters and Kiabel, 2015).

FDI is necessary for promoting development in emerging market countries like Ghana and could benefit from fundamental research. The role of FDI is deemed one of the contributory pillars of economic growth (Halil Kukaj, 2016). The contributory role of FDI inflows in the economic development of Ghana cannot be overemphasized. The data shows that over the past decades, there has been consistent progressive increase in FDI inflows into the Ghanaian economy. For instance, according to the Ghana's Balance of Payments database, the net inflows of FDI into the country have fluctuated between $18,260,970 in 1976 and $3,485,333,000 in 2016. Clearly, this shows an upward trend and considering the most recent data available, it even reinvigorates further the importance of this particular indicator to Ghana's development.

Per the records of the World Bank as quoted by the Ghana Investment Promotion Centre (GIPC), in 2012 Ghana recorded FDI inflows of about 8.09% of GDP. Additionally, Provisional FDI figures from January to September, 2018 hit 1.3 billion dollars representing 100% of the value recorded same period in 2017, being the value of projects registered with the Centre (GIPC) by foreign investors. There are opposing opinions available in literature regarding the extent to which FDIs can derive economic growth in developing countries like Ghana. However, FDIs have a straight consequence on local and regional economic growth by contributing to capital accumulation as well as enabling innovation and technology transfers to the beneficiary country (Halil Kukaj, 2016).

Considering the significant role of FDI in the economic growth of developing economies such as Ghana, it is imperative that the government of Ghana commits to the formulation of policies that would serve as incentives for foreign investors in order to derive FDIs into the economy. As a guide to the Ghanaian government and the Ghana Revenue Authority (GRA) in policy formulation in this regard, an empirical study that examines the impact of corporate tax rates on FDI inflows will be very critical and this study seeks to achieve this.

2. Theoretical and empirical background

2.1 Theoretical framework

Many theories justify the critical role FDI inflows play in promoting the growth of an economy and the benefits a company stands to gain in undertaking foreign investment. Notable among these theories is the Eclectic paradigm which illustrates the motivation for foreign investment in three main ways, namely, ownership advantage, locational advantage and internalization of multinational enterprises, MNEs (Dunning, 2001). The ownership advantage allows competition in the market despite the difficulties of being a firm and the main elements include trademark, production techniques and return to scales. The locational advantage focuses on benefits such as raw materials, labor, market size, tax and tariff regulations that makes one country more eye-catching site for FDI relative to other countries whereas internalization of MNEs is linked with trade that makes coopted dealings via FDI more effective.

This study is particularly located within the ambit of the locational advantage of the eclectic theory of investment and seeks to do so within the context of Ghana with particular emphasis on tax incentives. There is no doubt that the primary motive for most multinational companies that engage in foreign investment is to make profit and as such the business environment of the host country seeking to attract FDI is of utmost importance (Dunning, 2001). Regarding the locational advantage of the Eclectic paradigm, Caves (1971) opined that the size and growth of domestic markets, the availability of cheap and skilled labor, quality infrastructure and institutions as well as the macro policies of the host governments definitely exert influence on market-seeking foreign investors.

Another component of the Eclectic paradigm is the Internalization concept which is essentially about the motivation for transnational companies to embark on FDIs. The concept was initially proposed by Coase (1934) in a domestic perspective and Hymer (1976) in a transnational perspective. In the words of Hymer (1976), the transnational enterprises come about due to the market inadequacies that occasion a deviation from a perfect competitive final product market. Hymer (1976) argued regarding the effect of asymmetric information on foreign firms with respect to local firms, unequal treatment by host governments and currency threat as also observed by Lorraine and Eden (2004). In a nutshell, the locational advantage and the Internalization concepts of the Eclectic paradigm of FDI seeks to drum home the fate of foreign companies' vis-à-vis local companies in terms of information advantage and possibly deliberate discrimination by governments of host countries. The import of this theory is very crucial for this study considering that this study centers on the role fiscal incentives play in attracting FDI inflows into an economy and for that matter the Ghanaian economy.

2.2 Empirical reviews

The review of empirical literature on the subject relating to the role fiscal incentives play in attracting FDI is very consequential for this study. Considering that FDI is a very critical factor of economic growth, an appraisal of the germane empirical literature will reveal the knowledge gap to be addressed and thereby providing an impetus for a study like this. The following therefore constitutes some of the empirical literature that exists on this subject matter, especially those literatures that employed the ARDL and/or Vector Error Correction (VECM) dynamic models to assess the extent to which tax incentives attract FDI inflows to host countries.

To begin with, employing the ARDL, Lodhi (2017) analyzed the impact of tax incentives on Investment in Pakistan from 1990 to 2014. FDI and domestic investment were the dependent variables whiles corporate tax rates and tariff rates were the independent variables. The findings revealed that corporate tax rate is significantly negatively associated with domestic investment and FDI inflows in Pakistan in both the short and long runs. It was therefore recommended the government of Pakistan streamlines the corporate tax rates and tariffs in order to drive investment to Pakistan.

Also, in a study to identify the determinants of FDI inflows into the South African economy Majavu and Kapingura (2016) applied the VEC model to a set of variables such as GDP, trade openness, inflation, exchange rate, corporate tax as well as FDI as the dependent variable. The empirical results showed that these variables are important drivers of FDI inflows into the South African economy with corporate tax exerting statistically significant negative influence both in the short and the long runs.

Furthermore, Obeng (2014) studied the effect of corporate tax on sector specific investment in Ghana, namely, mining, manufacturing and service sectors, using the Johansen Cointegration technique and quarterly data from 1986 to 2012. Variables used in the study were real effective exchange rate, corporate tax, consumer price index, tangible exports of the sectors and investments into the various sectors. The paper found that corporate tax influences FDI inflows into those sectors. The paper therefore recommended that authorities should keep a low company tax rate in order to drive more FDI into the country.

Additionally, Peters and Kiabel (2015) examined the extent to which tax inducements could drive foreign investors to Nigeria using data drawn from the Central Bank of Nigeria and the World Development Indicators. The researchers employed a multiple regressions and static error correction modeling to the data. The empirical results revealed that FDI responds negatively to corporate taxes. The researchers recommended that focus should be shifted from reliance on tax incentives to other incentives strategies such as stable economic reforms and stable political climate.

Finally, in an exploration over a 19 year period, Etim et al. (2019) ascertained the outcome of cost-centered and profit-centered tax strategy incentives on FDI in Nigeria. For the study, secondary data were sourced from the CBN and World Bank database. Multiple regression techniques were used in analyzing the data. The findings revealed that though the cost-centered tax policy incentives had much potent effect on FDI relative to profit-centered tax policy incentives, there was no significant correlation between cost-centered tax policy incentives and profit-based tax policy incentives and FDI in Nigeria. It was therefore suggested that non-tax incentive interventions should be pursued by authorities as an essential supplement to the tax policy incentives in order to drive FDI inflows into Nigeria.

3. Research methodology

3.1 Estimation strategy

To effectively analyze the association between FDI inflows and its driving factors including tax incentives, data on the variables were sourced from the Ghana Statistical Service (GSS) and the World Development Indicators (WDI) over the period 1975–2017. The ARDL model was set up drawing on the outcome of the stationarity test which suggest that the variables under consideration are not stationary at levels and hence are integrated of orders I (0) and I (1). The import of the stationarity test results is that, applying simple OLS to the data involving these variables will deliver a spurious outcome. The generalized form of the ARDL (p, q) model is given by;

(1)Yt=βoi+∑i=1pλiYt−i+∑i=0qαiXt−i+εt

where Y_t is the dependent variable (i.e. FDI), X_t is a vector of independent variables with α_i as the vector of coefficients of the independent variables, p and q are the ideal lag length for the regressand and the regressors respectively and εt is the stochastic error term.

To model both the short run and the long run forms of the ARDL model based on the outcome of the bounds test, the model in Equation (1) was formulated as follows:

(2)ΔFDIt=αO+∑i=1pα1iΔlnFDIt−i+∑i=iqα2iΔlnGDPt−i+∑i=iqα3iΔCTRt−i+∑i=1qα4iΔlnTRADEt−i+∑i=iqα5iΔlnEXCHt−i+ λECTt−1+εt

where Equation (2) is the operational form of the generalized ARDL model specified in Equation (1) where α₁ to α₅ are the short-run coefficients and λECTt−1 is the long-run representation in the model with λ as the error correction term.

3.2 Diagnostic tests

The data collected on these variables were subjected to a unit root test to establish the stationarity properties and/or order of integration among the variables in order that the appropriate model can be adopted for estimation to avoid the danger of producing a spurious result. In this regard, the Augmented Dickey Fuller (ADF) test approach was adopted to achieve this. Also, the bounds test was employed to ascertain the existence of long-run relationships among FDI and its causative factors. Aside from that other diagnostic tests like heteroscedasticity and autocorrelation that can undermine the robustness of the findings were also performed.

4. Empirical findings and discussions

4.1 Results for the unit root test

The unit root test was conducted using the Augmented Dickey Fuller test approach and the results are presented in Table 1.

From Table 1, it can be seen that, most of the variables are not statistically significant in their level form as seen by their low ADF test statistics in absolute terms. This points to the non-stationarity of these variables, but for GDP ruling out the possibility of integration of order I (0) among the variables at level form. This is a signal that applying OLS to these variables in their level form will produce spurious results (Sakyi et al., 2016).

However, at first difference, all the variables were stationary at the 5% level of significance. This is because the null hypothesis of the existence of unit root is rejected for all the variables at their first difference form. This suggest that all the variables are integrated of the same order I (1). This scenario of a mixture of variables integrated of orders zero and one calls for the adoption of the ARDL model specified above.

4.2 Autoregressive distributed lag bounds tests

This test is employed to test for the existence of long-run relationships between the dependent and the independent variables. The results are reported in Table 2.

The results of the bound test are shown in Table 2. The hypothesis statement underlying this test is:

H0.

There is no long-run relationships between corporate tax rates and FDI inflows in Ghana.

H1.

There exist long-run relationships between corporate tax rates and FDI inflows in Ghana.

From the results, since the F-statistic for the bounds test of 5.635 lies above the upper bound at even the 1% level of significance, we reject the null hypothesis. What this decision means is that, there exist long-run relationships between the explanatory variables and the regressand. This implies that, the explanatory variables, especially the corporate tax rate do predict variations in the dependent variable even in the long run.

4.3 Analysis of results from the autoregressive distributed lag model

The Autoregressive Distributed Lag (ARDL) cointegrating and long-run form was employed in estimating the model. The statistical significance of the coefficients of each independent variable for both the short run and the long run was then tested on the basis of the following hypothesis statement.

H0.

Insignificant

H1.

Significant

At the 5% level therefore, the decision rule is not to reject H0 if the probability value of a variable exceeds the level of significance, otherwise H0 is rejected. The signs and magnitude of these coefficients were also identified in the context of the a priori expectations, the theoretical foundation and the findings of empirical literature on the subject matter.

4.4 Long- and short-run coefficients

The long- and short-run coefficients of the ARDL model are presented in Table 3.

From Table 3, it can be seen that trade openness albeit insignificant, exerts positive influence on FDI inflows into the Ghanaian economy in both the short and the long runs in accordance with the a priori expectations and the eclectic paradigm theoretical foundation of this study. A finding which is consistent with the findings of Majavu and Kapingura (2016) who found trade openness to impact positively on FDI inflows in South Africa. It is also supported by the findings of Chakrabarti (2001) who found a robust positive correlation between trade openness and FDI inflows. The insignificance of the coefficients is attributed to the nature of the trade regulations in Ghana. Indeed, until recently, the processes to clear goods at Ghana's ports were a rigorous one and this could have really affected the country's trade openness position. However, with the recent introduction of the paperless port system, Ghana's trade openness position is expected to improve significantly going forward.

Furthermore, the results from the table show that exchange rate, though statistically insignificant, negatively affects FDI inflows into Ghana both in the long run and in the short run. Its insignificance is attributed to the fact that, Ghana has enjoyed relative exchange rate stability in recent times and that investors are also driven by other factors such as the political atmosphere, availability of cheap labor and the infrastructural base of Ghana to invest in the country. This negative correlation between exchange rate and FDI inflows corroborates the predictions of the eclectic paradigm of FDI. It is also supported by the findings of Drogendijk and Martín (2015) in which study exchange rate affects FDI inflows negatively.

The results from the table further indicate that market size, with real GDP growth as the proxy affects FDI inflows positively in the short run and negatively in the long run although with statistically insignificant coefficients. The positive long-run observation is supported by the a priori expectations and the predictions of the eclectic theory of FDI as market size is one of the important locational advantages in the theory. Empirically, the finding is also supported by the work of Iamsiraroj and Doucouliagos (2015) who confirmed a robust positive correlation between economic growth and FDI inflows as well as Ho (2016) who established a positive but statistically insignificant relationship between FDI inflows and market size in fast emerging economies like Brazil, China, Russia, India and South Africa.

The final and the most important variable of interest in the table is the corporate tax rate which appears to influence FDI inflows negatively in the long run and positively in the short run in Ghana with statistically significant coefficients. This implies that, an increase in the corporate tax rates will lead to an increase in FDI inflows into Ghana in the short run but will eventually lead to a fall in FDI inflows in the long run. The long-run indication is in accordance with the a priori expectations and the theoretical foundations of this study with the short-run findings contracting against the a priori expectations as well as the theoretical predictions of the eclectic paradigm of FDI upon which this study is based. The negative long-run correlation found between FDI inflows and the corporate tax rate is also corroborated by the empirical findings of Obeng (2014) who found a long-run negative relationship between FDI inflows and the corporate tax rate in Ghana. It is also supported by the findings of Majavu and Kapingura (2016) who identified the corporate tax rate to be an important long-run determinant of FDI inflows into the South African economy. It is further in sync with the findings of Lodhi (2017) who empirically established a long-run negative influence of the corporate tax rates on FDI inflows into Pakistan. In the context of Ghana, the positive short-run relationship observed between FDI inflows and the corporate tax rates is attributed to the lag effect of tax policy on FDI inflows, in that a change in the corporate tax rate does not immediately influence FDI inflows and deter investors since most investors would normally compare their profit margins to the loss in revenue as a result of high corporate tax rates before drawing back on their investments. Based on these findings, it is recommended that, the Ghana Revenue Service (GRA) restructures the corporate tax regime in Ghana in order to deal with policy lapses. It is also recommended that low corporate rates should be maintained especially in respect of foreign companies that are into the production of goods and services for which indigenous companies in Ghana have a comparative disadvantage in order to drive FDI into the Ghanaian economy.

Finally, the ECM coefficient of −0.562 implies that the model adjusts to equilibrium at a speed of about 56% per period following short-run shocks. Therefore, shocks in this model are expected to disappear after the second year. This coefficient is statistically significant as the p-value is lower than the 5% level of significance.

4.5 Diagnostics tests

This section presents the results of the various residual diagnostic tests. Specifically, it reports on Serial Correlation and Heteroscedasticity.

Table 4 presents the diagnostic results of the model by comparing the probability values of the various F-statistics to the 5% level of significance. The model diagnostic tests done by the study were against issues of serial correlation and heteroscedasticity. Referring to the results of Breusch–Pagan–Godfrey test of serial correlation and heteroscedasticity in Table 4, it shows that there is no serial correlation or heteroscedasticity present. This is shown by the higher P-values of the F-statistics at the 5% level of significance. Thus, we fail to reject the null hypothesis of no Autocorrelation and Heteroscedasticity.

5. Conclusions

This study aimed at investigating the impact of fiscal incentives on FDI in Ghana. The dependent variable in the study was the FDI variable and the independent variables were fiscal incentives measured with corporate tax rates, market size as measured by the level of real GDP, trade openness and exchange rate. The study found a negative and significant long-run effect of corporate tax rates on FDI inflows but a significant positive short-run effect. The study further found that all the other independent variables such as trade openness, market size and exchange rate although statistically insignificant in influencing FDI inflows in Ghana, conforms to the a priori expectations and the predictions of the eclectic paradigm of FDI in sign.

The implication of this study for practice is that it acts as an empirical basis for the Ghana Revenue Service (GRA) to restructure the corporate tax regime in Ghana in order to deal with policy lapses. It also highlights the need for the authority to maintain low corporate rates targeted at non-indigenous companies that are into the production of goods and services for which the indigenous companies have comparative disadvantage in order to attract FDI into the Ghanaian economy. However, the results of the research should be interpreted against some limitations. For instance, the paper did not identify the specific foreign businesses that are more deserving of a low corporate rate and to what extent can that boost FDI inflows in Ghana. With Ghana as a signatory to the Economic Partnership Agreement (EPA) and a member of the most recently adopted African Continental Free Trade Agreement (AFCFTA), a future study that identifies the segment of foreign companies that deserve low corporate rates would be helpful in directing the GRA to enact corporate tax policies that would not make Ghana a potential dumping place for goods and services that can be produced domestically.

Table 1

Augmented dick fuller units root test (ADF)

Variables	Levels		First difference
	Intercept	Intercept and trend	Intercept	Intercept and trend
LnFDI	−1.2607	−2.5712	−6.4021**	−6.2546**
RGDP	−4.7237**	−5.2155**	−7.3642**	−7.2426**
CTR	−1.7002	−1.0038	−6.023**	−6.9189**
EXCH	−2.1167	1.7853	−4.4437**	−4.0539**
LnTRADE	−1.2382	−1.8149	−5.9409**	−5.9112**

Source(s): Author's computation using Stata

Note(s): (**) denotes statistical significance at 5% level of significance

Table 2

ARDL bounds test

Test statistic	Value	K
F-statistic	5.635	4

[I_0]	[I_1]	[I_0]	[I_1]	[I_0]	[I_1]	[I_0]	[I_1]
L1	L1	L_05	L_05	L_025	L_025	L_01	L_01
2.450	3.520	2.860	4.010	3.250	4.490	3.740	5.060

Source(s): Author's computation using Stata

Table 3

Long and short runs coefficients of the ARDL model

D.LnFDI	Coeff.	Std.Error	t-statistic	p > t	[95%Con	Interval]
ECM(-1)	−0.562	0.117	−4.820	0.000	−0.800	−0.324
Long-run Coefficients
LnTRADE	0.011	0.013	0.890	0.382	−0.015	0.037
EXCH	−0.116	0.509	−0.230	0.821	−1.152	0.921
RGDP	0.011	0.108	0.100	0.918	−0.209	0.231
CTR	−0.350	0.061	−5.780	0.000	−0.474	−0.227
Short-run Coefficients
LnTRADE
D1	0.025	0.015	1.610	0.118	−0.007	0.056
EXCH
D1	−0.680	0.842	−0.810	0.425	−2.394	1.034
RGDP
D1	−0.013	0.047	−0.290	0.777	−0.109	0.082
CTR
D1	0.104	0.036	2.890	0.007	0.031	0.177
Cons	7.272	1.652	4.400	0.000	3.907	10.637

Source(s): Author's Computation using Stata

Table 4

Diagnostic tests

Breusch-Pagan-Godfrey test	F-Statistic	p-Value
Heteroscedasticity	1.157152	0.3627
Serial correlation	1.554587	0.2231