Foreign capital inflows, trade openness and output performance in selected sub-Saharan African countries

This study empirically examined the dynamic impact of foreign capital inflows and trade openness on output performance and national productivity in 31 selected countries in sub-Saharan Africa (SSA) between 1985 and 2018. The study employed random effects and fixed effects models to estimate the coefficients. However, the results from the two models portray similar behaviors. Both estimates revealed a significant relationship between output performance and the independent variables. This suggests that the macroeconomic variables examined are good explanatory variables for analyzing the determinants of output performance and national productivity in the SSA region. The study further found that foreign capital inflows, trade openness and inflation rate have a positive and significant influence on output performance and national productivity. In contrast, exchange rate and interest rate exhibited a negative and significant relationship with such output performance. This result implies that policymakers in SSA countries must formulate policies that can successfully ensure trade openness and promote foreign capital inflows so as to stimulate national productivity and boost output performance in the region. Therefore, it can be concluded that foreign capital inflows and trade openness affect the industrial sector in contributing to output performance and national productivity in the SSA countries.


INTRODUCTION
Eradicating poverty and promoting employment through sustainable growth of industrial output production are among the fundamental goals of the United Nations' Sustainable Development Goals (SDGs) to be reached by 2030 (United Nations, 2020). In achieving these objectives, foreign capital inflows (FCI), trade openness (TO) and the development of the industrial sector have been identified as one of the key strategic plans to be promoted in the SSA countries. The plan is to create employment, increase domestic savings, encourage foreign investment, export promotion and boost industrial output production through innovation and infrastructural development (Nurunnabi et al., 2020). Unfortunately, over the last two decades, the region experienced the worst economic performance on record when compared to other regions of the world. For example, the region is threatened with high levels of unemployment, poverty, sluggish output growth and challenges of diversifying their economies in achieving industrialization and export growth.
The SSA region recorded its dawdling growth rate in 2015, the first time since 1998. IMF's Regional Economic Outlook for Africa (2016) showed that the economic growth rate in SSA fell from 5.1% to 3.4%, from 2014 to 2015. In a study conducted in SSA, Wilfred and Bokana (2017) also established that the real Gross Domestic Product (GDP) of the region recorded an increase of 1.1%, from January to March in 2016. However, in the third quarter, the authors found an equivalent 1.0% decrease in the real GDP. According to the IMF, the GDP and export growth of the countries in the SSA region decreased from 2.9% to 1.4%. The inability to diversify the economy, enhance trade liberalization and development of the critical sector (like the industrial sector) have been hypothesized to be one of the major reasons why the SSA region is experiencing such a low economic growth and performance. Moreover, the IMF World Economic Outlook (2021) projection further revealed that the recovery rate in SSA region is likely to lag behind the rest of the world with an aggregate growth rate of 3.6% over the 2020-2025 period as compared to the rest of the world which is put at 14%. Within the period, the income gap based on real GDP per capita between the SSA region and the rest of the world is projected to grow wider.
In view of the forgoing, there is a need to investigate whether foreign capital inflows and trade openness affect the industrial sector in contributing to output performance and national productivity in the SSA region. While several studies have revealed that there is overwhelming evidence that more economies that are open experience high growth rates than less open ones. Nonetheless, as cited by Gwartney et al. (2009) and Murinde (2009), there are some countries in the SSA region that are open but still struggling to attract foreign capital inflows and hence, have slow growth rates. In view of this puzzling, this study seeks to examine the dynamic impact of foreign capital inflows and trade openness on output performance and national productivity in SSA countries.

LITERATURE REVIEW
Empirical analyses of foreign capital inflows and trade openness and their comparative impacts on output performance and national productivity in SSA countries make sense and they are relevant based on the premise that they are properly related to the means through which a country can accelerate economic development. Empirical studies that summarize the relevance and nexus of foreign capital inflows, trade openness and output performance are hereby reviewed. Yaoxing (2010)  Related to the studies discussed above, Ayodele Folorunso et al. (2019) demonstrated that economic growth was conditional to foreign capital inflows in Nigeria but failed to establish a link between trade openness and the economic growth in the country. These results do not only prove that foreign capital inflows are important for the economic growth in SSA but also emphasize that SSA has been dependent on foreign investors. A study conducted by Shaibu (2014) demonstrated that in the regime of trade openness, foreign capital inflows would cause a significant positive influence on economic growth, thus offering an empirical backing for the transformation theory that trade policy and capital inflow are complementary and growth-enhancing. In a similar development, Asamoah et al. (2019) investigated the empirical role of institutional factors and the nexus among trade openness, FDI, and economic growth in sub-Saharan African (SSA) countries and revealed an effect of FDI and trade openness on economic growth and a positive effect of institutions on trade openness.
In Ethiopia, Abebaw (2019) employed a time series data from 1992 to 2018 to analyze the influence of macroeconomic variables on the output growth of industrial sectors. The authors demonstrated a long-run association between industrial output growth and inflation rate, lending rate and trade. Both lending rate and trade were found to have a negative impact on industrial output growth, while inflation had a positive impact. The study recommended that "government has to keep lending rate to the level that could be amenable for firms and maintaining the trade balance; via manipulating the export and import".  2021), on the other hand, looked at the impact of FCI on agricultural growth and poverty reduction in developing countries. Therefore, none of these studies covered the focus area (industrial sector) and the scope (trade openness, foreign capital inflows and industrial output) that are currently investigated. It is in this vein that this study attempts to contribute to this area by investigating the dynamic impact of the foreign capital inflows and trade openness on output performance and national productivity in selected SSA countries.

Model specification
This paper employs the augmented Cobb-Douglas production function to model the dynamic relationship that may exist between foreign capital inflows, trade openness and industrial output performance and national productivity in the SSA countries. The choice of this method is informed from its ability to handle multiples input in its generalized form in producing certain level of output and that the model does not self-initiate distortion data and results.
Given the above reasons for employing the augmented Cobb-Douglas production function in this study, the theory is systematically linked to an economy aiming to increase the level of foreign capital inflows, reducing poverty, create employment, promote export and boost productivity using the two types of factors of production (reproductive and non-reproductive economy). This is based on the assumption that the SSA countries use the same factors of production and the same technology in production of similar goods and services. It is further based on the assumption that there are constant returns to scale in which doubling the input will lead to doubling the output and a competitive free international trade among all the countries. The theoretical model illustrates that output is a function of labor, capital or technology (total factor productivity). Consequently, the augmented Cobb-Douglas production function as given by Roubalová and Viskotová (2019) can be presented in the following form for SSA countries: where Y it is total output in country i at time t, which is measured by the real value of all the goods produced in a country; A it is the level of technology in country i at time t, and popularly called total factor productivity. A it is assumed in the equation as a constant as parametric efficiency. L it is labor input in country i at time t, operationalized as the total man-hours of a country over a particular time range. K it denotes the input of physical capital in country i at time t, measured as the real value of all equipment, machinery and buildings at a point in time. Β and α respectively represent the output elasticity of capital and labor. Available technology is used to determine the values of B and a. Hence, the proportion of labor and capital substitution can vary.
Since the marginal product of labor and capital is always positive, this function permits returns to scale by summing β and α (Roubalová & Viskotová, 2019). On the condition that (β + α) = 1, the Cobb-Douglas production theory demonstrates constant return to scale. This implies that, by doubling the usage capital K it and labor L it (input), the output Y it will double proportionally. On the other hand, if (β + α) > 1, it suggests increasing return to scale, and if (β + α) < 1, it implies a decreasing return to scale.
A corresponding form of equation (1) is a linear function of the model where the three variables are transformed into a logarithms form given as: where Y it , L it and K it denote output, labor and capital, respectively; c io is a constant parameter and A it is Total Factor Productivity (TFP) or other factors not captured by labor and capital (also considered as unconventional inputs or level of technology). The other variables not captured by labor and capital (unconventional inputs and level of technology) include foreign direct investment (FDI), gross foreign capital inflows (GFCI), trade openness (TO), foreign portfolio investment (FPI), exchange rates (EXC), inflation (INF) and interest rates (IN). Therefore, it is assumed that TFP is a function of foreign direct investment, gross foreign capital inflows, trade openness, foreign portfolio investment, exchange rates, inflation and interest rates over a particular period of time t which is given by: By inserting A it in equation (3) into equation (1), the following Cobb-Douglas production function is obtained: Following Omar and Hussin (2015, p. 102), the linear form of equation (4) can be given as follows: where Y it is industrial output production and national productivity in SSA countries; c i is a constant term;

Brief definition of variables
This study employs annual data that were collected from the SSA countries from 1985 to 2018. The variables are drawn from similar studies like Cinar and Nulambeh (2018) and Ayirikame (2021), as well as theoretical model using the Cobb-Douglass production function. Those variables are briefly discussed below.

• Output (Y)
This is the production variable, and it represents a dependent variable in the model developed for this study. This variable was included in the model because the industrial sector significantly contributes to economic growth and assists to achieve specific objective like employment creation and economic growth.

• Foreign direct investment (FDI)
This is a form of direct business ownership or investment in one country by an entity based in another country. FDI is a form of foreign capital, which aims at accelerating economic development (Todaro & Smith, 2012).

• Foreign portfolio investment (FPI)
This is another form of foreign capital inflows aimed at accelerating economic development. It deals with investment in a grouping of assets such as stocks, bonds, and cash equivalents (Otiwu, 2018).

• Gross foreign capital inflow (GFCI)
GFCI is the sum of FDI and FPI as a ratio or percent of GDP. The gross foreign capital inflow is included in this paper because dealing with each component of capital flows in disaggregated forms may sometimes be misleading because the volatility in capital flows may be dampened by the changes in another component (Chakraborty, 2006).

• Inflation (INF)
This variable is included to capture macroeconomic instability in the production processes or the economy as posited by Okonkwo et al. (2015) and Sahoo (2017). In addition, the variable will assist this study to establish the trade links among the SSA countries and with the rest of the world, as well as how prices attract foreign capital inflows, level of investment and output production in the economy.

• Interest rate (IN)
This variable represents the cost of borrowing and it allows this study to measure the process through which it is used to control inflation in the economy. For example, if inflation is high, central banks increase repo rate which eventually reduces the money supply in the economy and thus helps in curbing inflation (vice versa).

• Trade openness (TO)
Trade openness is simply the ratio or sum of a country's export and import. In this paper, trade openness as a percentage of GDP, i.e. (Imports + Exports) is employed, and this is in line with Wiredu et al. (2020). It is included in the study to see its impact on output performance.

• Exchange rate (EXC)
The inclusion of this variable in the model allows the study to investigate how variations in the value of the US Dollar affect selected variables in the SSA countries as posited by Bacchetta and Van Wincoop (2000). The SSA country's currency against the US dollar is used in this study because, as posited by Rodrik (2006), US is the most industrialized country in the world and their currency is the most traded in the foreign exchange market.

Data sources
The panel data for the SSA countries used in this paper was extracted from the databases International Financial Statistics (IFS) of IMS and the WDI

Estimation technique
Following the empirical studies of Wilfred and Bokana (2017) and Wiredu et al. (2020), this paper employs the fixed effects model (FEM) and random effects model (REM) to investigate the dynamic impact of foreign capital inflows and trade openness on output performance and national productivity in SSA countries.
Supposing the panel fixed effects and random effects regression model for the SSA countries is specified as follows: where Y it is the industrial output production and national productivity in SSA countries; β io is the constant term; i denotes individual country in the SSA countries; X 1 -X n and Y i are explanatory variables (for every i = 1……n); β 1 -β P represent coefficient of the explanatory variables in the model; and µ it is the error terms.

ESTIMATION RESULTS
The behavior of data in terms of its stationary status has implications on the validity of results.
Therefore, this paper begins by conducting a descriptive summary statistic to determine the behaviors of the data and their interaction in the model. Thereafter, a stationarity (testing for unit roots) of the dataset is carried out in order to prevent spurious results. Finally, the fixed effects and random effects analyses were conducted. Table 1 presents an overview of the data set using the raw data of the variables. As shown in Table 1 quence following the normal distribution series. Given the probability value of each of the variable from the Jarque-Bera statistics, the study rejects the null hypothesis of a normal distribution because the probability values are highly significant. Given this observation, the study conducts a unit root test to prevent spurious results.

Results of summary statistics
The result of the correlation matrix as contained in Table 2 shows a strong relationship among the variables. For example, the study discovers a strong relationship between the independent variables (GFCI, FDI, FPI, TO, EXC, INF and IN) and the dependent variable (Y). The implication of this is that those vari-ables have impacts on output growth or performance and national productivity in SSA countries.

Panel unit root results
Prior to the estimation of the results, the study tested for the stationarity of the datasets. Three different stationary tests comprising Im, Pesaran and Shin (IPS), Augmented Dickey-Fuller (ADF) and Levin, Lin and Chu (LLC). As shown in Table  3, six variables (GFCI, FDI, FPI, Y, INF and IN) were stationary at 5% with both intercept and trend, while the other two variables (TO and EXC) were stationary at first differencing (I(1)).   Table 3. LLC, IPS and Augmented ADF unit root tests a)

The fixed effects test results
Tables 4 and 5 present the regression results for estimating the impact of selected factors on industrial output and national productivity using panel FEM and REM, respectively. The results from the two models portray similar behaviors. At 5% level, all the variables in the two models significantly affect output production. This suggests that these macroeconomic variables are good explanatory variables for analyzing the determinants of industrial output performance and national productivity in the SSA region. It is an indication that they determine industrial output performance and national productivity among the SSA countries.
Based on the regression results, it is observed further that under the two models, the coefficients of gross foreign capital inflows, foreign portfolio in- On the other hand, exchange rate and interest rate have a negative impact. This is an indication that exchange rate instability and an increase in interest rate will decrease industrial output performance and national productivity in the region.
Given the above results, the SDGs 2030 fundamental's goals of eradicating poverty and promoting employment through sustainable growth of   industrial output production can be achieved with a concerted efforts to promote foreign capital inflows, trade openness and the development of the industrial sector in the SSA countries. The strategic plans to develop and promote the key macroeconomic variables in the model will help to create employment, increase domestic savings, encourage capital flows, export promotion (remove trade restrictions and high tariffs) and boost industrial output production and national productivity among the SSA countries.  (2017), "the adoption of fixed effects model is premised upon justification that it can handle heterogeneity effect that may influence the outcome of our findings". However, all the significant variables in the RE model were also significant in the FE model. The size of the coefficients and their signs of the variables in both models were relatively similar. Therefore, confirm the earlier assertion that foreign capital inflows and trade openness affect the industrial sector in contributing to output performance and national productivity in the SSA region.

CONCLUSION
Foreign capital inflows, trade openness and the development of the industrial sector have been identified as one of the key strategic plans to eradicating poverty and promoting employment in the SSA. Unfortunately, over the last two decades, the region experienced the worst economic performance on record when compared to other regions of the world. Therefore, this study examined the dynamic impact of foreign capital inflows and trade openness on industrial output performance and national produc-  tivity in the SSA countries. Annual data from 1985 to 2018 was used for the study. The study employed panel fixed effects and random effects models to analyze the data.
The results based on both the FE and RE models revealed that gross foreign capital inflows, FDI, trade openness, foreign portfolio investment and inflation positively affected industrial output performance and national productivity in SSA countries. This result implies that an increase in foreign capital inflows, trade openness and inflation stimulate the industrial output performance in the SSA region. On the other side, the results demonstrated that exchange and interest rates had a negative impact, suggesting that an increase in interest and exchange rates will decrease industrial output performance in the SSA region. The study concludes that FCI and trade openness affects the industrial sector in contributing to output performance and national productivity in the SSA countries.
The significant policy implication emanating from the findings is that policymakers in SSA countries have to formulate policies that can successfully promote foreign capital inflows and ensure trade openness. Policies towards managing a good combination of domestic investment and foreign capital inflows, as well as trade openness, must be formulated in order to boost output performance and national productivity in the SSA countries. As a policy recommendation, SSA countries should commit to creating viable economic environments that will entice foreign investors. This can be achieved through the promotion of trade and investment by establishing pragmatic and sound economic policies and strengthening both economic and policy institutions, which can help in taking full advantage of the gains from foreign capital inflows and trade openness in the SSA region in order to boost industrial output performance and national productivity.