Evaluating Government Consumption
Expenditure Effect on Current Account in Nigeria
Ephraim Ugwu^{1}, Phillip Nwosa^{2}, Christopher Ehinomen^{3}
Abstract: This study evaluates the effect of government consumption expenditures on the current account in Nigeria covering the periods from 1980 to 2019. The study answered the question, does government consumption expenditure affect the current account in Nigeria? Employing the Autoregressive Distributed Lag (ARDL) bound cointegration testing approach for evaluation, the unit root test results show a mixed order of stationarity. The ARDL bound test result shows that there exists a longrun relationship among the variables. The estimated coefficients of the longrun relationship are positive and statistically significant for the consumption expenditure, LOG (GCON), and the growth rate of GDP (GDPGR), at a 5% significant level. This shows that an increase in the government consumption expenditure results in a decrease in the current account balance of Nigeria. The coefficient of the budget deficit, DEFICIT shows a positive sign, indicating that government budget deficit leads to a current account deficit, thus supporting the twin deficit proposition. The study, therefore, recommends that the Federal Government of Nigeria should reduce the level of borrowing as this would reduce debt service payment.
Keywords: Government consumption; Current account; Bound cointegration; ARDL; Nigeria
JEL Classification: B22; C13; F32; H50; N47
1. Introduction
There had been several debates among scholars on the interaction effect between fiscal policy and balance of trade. Among the scholars include, Ahmed (1987) that there exists a negative relationship between increases in expenditures of the government and the balance of trade in the 18th and 19th centuries. Baxter (1995) that as the final consumption expenditures increase by 1%, it results in a 0.5% decline of the current account balance. The views of the neoclassical economists are that government consumption expenditures on goods and services affect both output and investments positively while spending based on worked hours negatively affect the two variables (see Baxter & King, 1993). While, Oseni and Onakoya (2013) were of the view that issuance of bonds by the government, raises the rate of interest, leading to higher consumption expenditure as a result of the wealth effect. Highinterest rate leads to currency appreciation, and a loss in competitiveness sets in, coupled with a higher marginal propensity to consume, leads to deterioration of the current account (Oseni & Onakoya, 2013).
On the other hand, Abbas, BoughaHagbe, Fatas, Moun, and Valleso (2011) stated that the question most economies have asked over time is, how has the adjustment of fiscal policy resulted in resolving problems relating to external balances? The continuous deterioration of the government budget, as well as trade deficit in most of the advance and emerging economies in the 1980s and 2000s, brought attention to the twin deficit hypothesis (Abbas, 2020). The hypothesis states that as the economy suffers fiscal shocks as a result of an increase in government expenditure or reduction in taxes, leading to a budget deficit, also results in a trade deficit. This implies that there is a positive correlation between budget deficit trade deficits (Abbas, 2020).
Government consumption expenditure is the values of both goods and services utilized by various agencies, departments, and institutions of governments, in the provision of goods and services to the population (Cavallo, 2005). These types of goods and services which include, national defense, administrative activities, are not easily provided by private business owners. On the other hand, the current account balances of countries are the differences between an economy’s export and imports of goods and services, as well as income. It also includes the differences between an economy’s national income and domestic investments and consumption. A greater amount of local expenditure especially in the advanced economies is mainly government consumption expenditures (Cavallo, 2005).
In Nigeria, the government’s final consumption expenditure in 2003 was 23.926% of the Gross Domestic Product (GDP). In 2013, the Nigerian government spent a total of 41.6 billion dollars, thus placing the country 38th in the global rankings and a share of the global consumption expenditures to 0.31%. The final consumption expenditures in 2015 and 2016 were 11.897% and 15.116% respectively. The final consumption expenditures as a percentage of the GDP in 2017, was 4.6% of the GDP and 22.3 billion US dollars, in 2018, about 33.16% of the GDP (The World Bank, 2019). Figure 1 below shows the Nigerian government consumption expenditures from 1980 to 2019.
Figure 1. The Government Consumption Expenditures of Nigeria from 1980 2019
From the figure, it could be seen that consumption expenditures of Nigeria were on a constant increment from 1980; it, however, decreased between 1987 and 1990. From the figure, the consumption expenditures of the government continued to increase on a higher scale from 2004 to 2019. The current account balance in 2000 was US$7.01 billion, in 2005, US$25.57 billion, and in 2008 US$29.34 billion (Sanni, Musa & Sani, 2019). There was a decline in 2011 to the tune of US$10.75 billion and in 2014 to US$1.28 billion. This drastic decline was attributed to higher import bills and deficits in both the services and income accounts of the country. As a result of a drop in the prices of crude oil, in 2015, the country recorded a deficit of US$15.44 billion and in 2016, there was a surplus of US$2.72 billion (Sanni, et al, 2019). However, in the second quarter of 2020, the current account revised from 4.9% of the GDP to 3.4%, thus moving in line with the balance of trade decline during the periods. During the second quarter of 2020, the country’s balance of trade declined negatively from 1.2% of the GDP to 4.0% (Proshare report, 2020). Figure 2 below shows the current account balance (CA) in Nigeria from 1980 to 2019:
Figure 2. The Current Account Balance of Nigeria from 1980 2019
A look at the figure of the country’s current account showed a record low in the 1980s as the figures are close to negative. The figure showed an upward spike in the country’s current account from 1981 to 1996, with a surplus for Nigeria in the 1990s. The figure showed the current account balance to be fluctuating in the period from 2000 to 2010; also, the country recorded a deficit in 2015 and a surplus in 2016 2018, and 2019 respectively.
Studies on the effect of government consumption expenditure had been conducted widely and yet no consensus was reached among scholars. Among the scholars include Kim and Roubini (2003) which showed that there exists a twin divergence for the US economy instead of a twin deficit. However, Ravn, SchmittGrohe, and Uribe (2012) noted that fiscal shocks reduce the current account for four industrialized economies including the US. And a study by Monacelli and Perotti (2007) for some Organisation of Economic Cooperation and Development (OECD) countries, noted a deteriorating balance of trade as a result of an increase in public expenditure and a little effect in the case of the US economy. Enders, Müller, and Scholl (2011) on the other hand argued that there is a possibility of having either twin deficit or twin divergence differences as a result of trade price elasticity. Though some institutions in support of a twin deficit approach push for fiscal consolidation in order to decrease the current account deficit, there is still a question on fiscal consolidation credibility in correcting imbalances in the current account in a situation where there exists a twin divergence phenomenon (Abbas, 2020).
As studies on the effect of fiscal policy on current account balance continued to attract debates among researchers without conclusive evidence, theoretical debates on current account balances explaining variations in fiscal measures had centered on macroeconomic models. Among the models include the Mundell–Fleming, and Ricardian Equivalent models. In the Mundell–Fleming approach, fiscal deficit causes current account deficit, while the Ricardian equivalent hypothesis posits that deficit financing, either through reduced taxes or by issuing bonds does not change the present value wealth of individual households, since both temporarily reduced taxes and issuance of bonds represent future tax liabilities (Kim, 1995; Oseni & Onakoya, 2013).
Following the twindeficit hypothesis, it is expected that the recorded fiscal deficit is accompanied by a huge current account deficit (Kim & Roubini, 2004). On the other hand, the Keynesian principle suggests that increases in fiscal deficit as a result of expenditure increment, households will be compelled to utilize the additional income to boost consumption, thereby causing national saving, both public and private to decline (Ekundayo, 2011). The implication of this is that the country would resort to borrowing unless the local investment activities decrease enough to offset the shortfall in the saving rate. Nonetheless, the Keynesian approach centered on the fact that there is a positive interaction effect between fiscal deficits and private consumption, implying that higher deficit results in higher private consumption expenditures. This viewpoint however may not be realistic according to Briotti (2005), based on the literature on the expansionary effect of fiscal consolidation.
It, therefore, becomes crucial to understand the effect of government consumption on current account dynamics in Nigeria, as the performance of the economy in the recent past has been discouraging. For instance, since the Nigerian government embarked on the Structural Adjustment Programme (SAP), geared towards liberalization of the economy, it has in practice led to a decline of the economy, and further worsened the current account imbalances (Oseni & Onakoya, 2013). Thus understanding current account dynamics, might lead to a mitigation of these effects; though it is still unclear what the current account determinants are, and also, not yet if the imbalances are sustainable. Equally, the burden of debt service repayments has also contributed to the huge current account deficits of the country. As an importdependent economy, consumption expenditures which constituted a greater part of the total expenditures, and a greater share of the total output, have resulted in a huge trade deficit for the country. This study, therefore, tends to answer the following questions: how do government consumption expenditure shocks affect current account balance in Nigeria? What are the other variables that affect the current account balance in Nigeria? The overall objective of this research is therefore to evaluate the effect of government consumption expenditure shocks on the current account in Nigeria.
2. Literature Review
In the literature, it is argued that that there are opposite effects of the consumption expenditures on goods and hourly worked on key macroeconomic variables which include, private investment and the total output. These variables are the key determinants of the current account (Cavallo, 2005). The NeoClassical school posits that there is a positive effect between expenditures on goods, output, and investment; and a negative effect between hourly work (Baxter & king, 1993; Finn, 1998). However, Baxter (1995) noted that expenditures on hourly worked, are smaller in magnitude than the goods expenditures on the current account. According to the author, a 1% increase in the hourly worked, decreases the current account to 0.5% of the GDP.
Studies on fiscal policy effects on current account balance according to Abbas et.al. (2011) include effect on consumption, tradable goods demand, and investment. A large part of the local demand for goods is always accounted for by the government, thus depending on the propensity of import, a change in the demand for import by the government leads to a movement in the balance of trade. Also, changes in the rate of exchange affect the current account by altering the relative prices of nontradable goods (Abbas et.al. 2011). An increased government spending on nontradable goods like real estate sectors or services can lead to exchange rate appreciation, thereby tilting forward private consumption and production away from tradable goods. Other channels through which fiscal policy affects the current accounts include the country’s risk premia and rate of interest (Abbas et.al, 2011).
2.1. Government Expenditures as a Measure of the Size of Government
In the literature, there exist several ways through which the size of government is measured. According to Alesina, Glaeser and Sacerdote (2001), these measures are typically based on, either total expenditure of the government, or general consumption expenditures. The authors were of the view that the relative measure of the government size is the expenditure ratio of government and that depicts how the government utilizes local resources. However, Leonard (1986) argued that the budget might not actually state clearly, the true size since it may not account for the government ‘quiet size’ activities. The government’s role in an economy, therefore, goes beyond the collection of revenues and spending (Leonard, 1986).
2.2. A Cross Country Study on Government Consumption Expenditure
Crosscountry studies on government consumption expenditure show that in 2013, the Nigerian government spent a total sum of 41.6 billion dollars on consumption expenditures. This amount brings the country on par with other countries like Greece 41.6 billion dollars, the Czech Republic 41 billion dollars, Ireland 40.6 billion dollars, Algeria 39.7 billion dollars, Malaysia 42.3 billion dollars, and Portugal 43.1 billion dollars respectively. Also, the country’s consumption expenditures far exceeded that of the neighboring countries. For instance, consumption expenditures for countries like Cameroun in the same year 2013, was 3.4 billion dollars, Chad 2.6 billion dollars, the Republic of Niger, 1 billion dollars, and the Republic of Benin 0.93 billion dollars respectively. As a percentage of the GDP, Nigeria’s consumption expenditures in 2015 and 2017 were 5.94% and 4.6% respectively. The consumption expenditures as a percentage of the GDP in 2017 for Ghana was 8.8%, Niger 15.8%, and Cameroun 11.5% respectively (The World Bank, 2019).
3. Empirical Literature
Bhavesh and Prabheesh (2017) investigate macroeconomic and external factors that affect current account balance in India from 1997 to 2012. The study shows that the twin deficit hypothesis that fiscal deficit reduction ameliorates the current account deficit applies. Işık, Yılmaz, and Kılınç (2017) evaluate the relationship between current account balance and credit to firms in 26 OECD countries from 2005 to 2015. The study results indicate that credit to households and firms has a negative effect on the current account balance in the short run while credit to firms and government has a positive effect in the long run. Klemm and Iakova (2013) investigate growth following investment and consumptiondriven current account crises for industrialized countries. The results show that a deficit reversal that follows investment boom is identified with better growth than those following consumption booms. The study finds that large current account deficits are a result of consumption or nonproductive investment booms. On the examination of the effect of fiscal policy on Nigeria’s current account, Oseni and Onakoya (2013) using the Structural Vector Auto Regression (VAR) model approach, show that expansionary fiscal policy has a positive effect on the output and exchange rate and negatively impacts the current account balance.
3.1. Limitations of the Previous Studies
From the reviewed literature, it is evident that since a study by Cavallo (2005) for the US economy, few studies had been conducted on the effect of government consumption expenditure on the current account of countries. Most studies had either focused on how macroeconomic variables affect current accounts (see Bhavesh & Prabheesh, 2017; Işık et al, 2017; Klemm & Iakova, 2013; Oseni &Onakoya, 2013; Nickel & Vansteenkiste 2008). A recent study on government expenditure and current accounts by Abbas (2020) evaluated the twin deficit approach for the US economy. Thus, it is evident that few studies had been conducted for emerging and developing economies. This study, therefore, fills the gap in the literature by extending the work from 1980 to 2019, using an ARDL estimation procedure.
4. Methodology of Research
4.1. Data analysis method
The study adopts an Auto Regressive Distributive Lag (ARDL) model approach for evaluation. The current account balance is the dependent variable, while government consumption expenditures, budget deficit, gross domestic product, and interest rate are the independent variables. The model for the effect of government consumption expenditures on current account in Nigeria is therefore specified as follows:
_{ (1)}
where
CA = The current account balance
GCON = The Government consumption expenditure
GDPGR =The growth rate of Gross Domestic Product
INTR = Interest rate
DEFICIT = government budget deficit
In order to establish a linear relationship between the dependent variable and the independent variables, the econometrics model is therefore specified as follows:
_{ }_{ }(2)
where
= Error term
= the constant term
‘s = the parameters to be estimated
For a statistical reason the variables are transformed into linlog equations as follows:
_{ }(3)
4.2. Method of Result Evaluation
This study utilizes the Augmented DickeyFuller (ADF) test for the stationarity test. This is because, the Auto Regressive Distributed Lag (ARDL) bound test procedure is conducted based on the assumption that, the variables under consideration are either integrated of order zero or order one. Hence order of integration was determined using the ADF test procedures. The null hypothesis that guided the test is stated as follows: H0: β=0 (β has a unit root); H1: β upper critical bound, H0 is rejected and concludes that the variables under consideration are cointegrated, otherwise, it is not accepted. However, if Fstatistic ≥ lower critical bound ≤ upper critical bound, then the decision becomes inclusive. If the null hypothesis of no cointegration is rejected, a vector errorcorrection model (VECM) is therefore estimated (Narayan & Narayan, 2006). The VECM model is therefore specified as follows:
where
Δ = Difference operator
𝜀𝑡 = Stochastic term
Conducting ARDL bound test, an Ordinary Least Square (OLS) is estimated firstly in order to establish if there exists a longrun relationship between the variable under consideration. The test is based on an FStatistic for the joint statistical significance of the lagged variables. The null hypothesis of no cointegration ( ) is evaluated using the Pesaran et.al. (2001) procedure. The underlining assumption is therefore stated as follows: if the Fstatistic is > upper critical bound, H0 is rejected and concludes that the variables under consideration are cointegrated, otherwise it is not accepted. However, if Fstatistic ≥ lower critical bound ≤ upper critical bound, then the decision becomes inclusive. If the null hypothesis of no cointegration is rejected, a vector errorcorrection model (VECM) is therefore estimated (Narayan & Narayan, 2006). The VECM model is therefore specified as follows:
where:
ECM = The error correction term
𝜆 = the error coefficient
4.3. Presentation and Analysis
The descriptive statistics for the variables under consideration are therefore presented in table 1 below:
Table 1. The Descriptive Statistics

CA 
GCON 
GDPGR 
INTR 
DEFICIT 
Mean 
2.916950 
3.667327 
18.80231 
6.275542 
613.4903 
Median 
2.462145 
2.084226 
6.419219 
6.959583 
102.5900 
Maximum 
20.73932 
9.448340 
550.5400 
11.06417 
32.05000 
Minimum 
6.289509 
0.911235 
7.060000 
0.316667 
4913.820 
Std. Dev. 
5.590810 
2.809908 
86.35847 
2.785681 
1148.532 
Skewness 
1.046099 
0.861125 
6.056597 
0.555914 
2.381948 
Kurtosis 
4.412237 
2.282249 
37.80187 
2.515798 
7.965212 
JarqueBera 
10.61951 
5.802180 
2263.166 
2.451020 
78.91340 
Probability 
0.004943 
0.054963 
0.000000 
0.293608 
0.000000 
Sum 
116.6780 
146.6931 
752.0923 
251.0217 
24539.61 
Sum Sq. Dev. 
1219.029 
307.9277 
290853.6 
302.6407 
51445929 
Observations 
40 
40 
40 
40 
40 
From table 1 above, the descriptive statistics indicated that from 1980 to 2019, four of the variables under study showed averaged positive mean values and one variable, DEFICIT indicates a negative mean value, all with 40 observations. The standard deviation indicated that the highest standard deviation is recorded by the variable DEFICIT, while the least standard deviation is recorded by variable INTR. The JarqueBera (JB) test of normality for the variables under consideration revealed that four of the variables are significant at a 5% level.
4.4. Correlation
In order to ascertain the degree of relationship between the current account, government consumption expenditure, the growth rate of GDP, the interest rate, and budget deficit, a correlation is therefore conducted. The result in table 2 below, it shows that there exists a positive relationship between the current account and the independent variables. The relationship shows GCON (42%), GDPGR (16%), INTR (13%), and DEFICIT (08%) respectively.
Table 2. The Correlation Matrix

CA 
GCON 
GDPGR 
INTR 
DEFICIT 
CA 
1.000000 
0.429179 
0.165047 
0.133535 
0.087661 
GCON 
0.429179 
1.000000 
0.099005 
0.318045 
0.378987 
GDPGR 
0.165047 
0.099005 
1.000000 
0.163225 
0.077115 
INTR 
0.133535 
0.318045 
0.163225 
1.000000 
0.353169 
DEFICIT 
0.087661 
0.378987 
0.077115 
0.353169 
1.000000 
4.5. Unit Root Test
The results of the Augmented DickeyFuller (ADF) unit root test obtained are presented in table 3 below as follows:
Table 3. The ADF Unit Root Test Results
Variable 
Level difference 
Prob. 
First difference 
Prob. 
Order of integration 
CA 
2.810097 
0.0663 
5.967427 
0.0000** 
I(1) 
GCON 
2.669140 
0.0887 
5.915466 
0.0000** 
I(1) 
GDPGR 
6.160989 
0.0000** 


I(0) 
INTR 
2.136564 
0.2321 
6.536317 
0.0000** 
I(1) 
DEFICIT 
6.007475 
0.0000** 


I(0) 
Note: * , ** and *** denote 1% ,5% and 10% critical values respectively 
From table 3 above, the results showed that two of the variables, CA, GCON, and INTR are stationary at the first difference I(1) at 5% significant levels in the ADF test procedure. The other two variables, GDPGR, and DEFICIT are stationary at the level difference I(0) at 5% significant levels in the ADF test procedure respectively. Therefore, since there exists a mixed order of stationarity among the variables, an ARDL model Procedure is therefore conducted. OtengAbaiye & Frimpong (2006) stated that instead of utilizing the Johanson cointegration approach which requires that all variables are integrated of order one I(1), an ARDL that incorporates variables that are I(0) and I(1) are therefore utilized.
4.6. Auto Regressive Distributed Lag (ARDL), Bound Testing Approach
The study tries to establish whether there exists a longrun relationship among the variables under study by conducting a bound cointegration test procedure. An Fstatistic to test the longrun relationship is therefore computed. An automatic lag length of ARDL ARDL (2, 4, 1, 0, 0) is adopted. The result of the ARDL bound cointegration test is presented in table 4 below:
Table 4. The ARDL Bound Test Result
Null Hypothesis: No longrun relationships exist 

Test Statistic 
Value 
k 
Fstatistic 
7.210474 
4 
Critical Value Bounds 

Significance 
I0 Bound 
I1 Bound 
10% 
2.45 
3.52 
5% 
2.86 
4.01 
2.5% 
3.25 
4.49 
1% 
3.74 
5.06 
The ARDL bound test result from table 4 above indicated that the F Statistic value is greater than the critical value bounds at both 1%, 5%, and 10% significance levels respectively. We can see that the value of 7.210474 is higher than 2.86 and 4.01 critical values at 5% significant levels. The hypothesis of no longrun relationship is therefore rejected. Thus it showed that the ARDL model estimated is proven to determine the longrun slopeestimated coefficients and the shortrun dynamicestimated coefficients. Hence there exists a longrun relationship between CA, GCON, GDPGR, INT, and DEFICIT.
4.7. Testing for the Long Run Relationship
The longrun model for the relationship between consumption expenditures and the current account is therefore presented as follows:
Table 5. The Long Run Coefficients Result
Variable 
Coefficient 
Std. Error 
tStatistic 
Prob. 
LOG(GCON) 
2.010212 
1.062763 
1.891495 
0.0707 
GDPGR 
0.428390 
0.154150 
2.779054 
0.0104 
INTR 
0.005125 
0.222177 
0.023065 
0.9818 
DEFICIT 
0.000786 
0.000646 
1.216984 
0.2354 
C 
1.124287 
1.717884 
0.654461 
0.5190 
The results showed that the estimated coefficients of the longrun relationship are positive and statistically significant for LOG (GCON) and GDPGR at the 5% level. The positive coefficient of the variable LOG(GCON) implied that the consumption expenditure contributed significantly to the decrease in the current account of Nigeria in the long run. The finding conforms to the study by Cavallo (2005) that consumption expenditures of the governments overestimate its role while accounting for current account movement. The estimated results showed that the coefficient of the growth rate of GDP (GDPGR) indicates a positive sign and is significant statistically. Thus there exist a positive relationship between the GDPGR and the current account in Nigeria. This suggests that as the income increases, it results in an increase in spending by the households on imported consumable goods. The implication is that it results in a current account deterioration. The finding is consistent with the findings of Tarawalie (2014) that there exists a positive relationship between the current account deficit and the real GDP for Sierra Leone. The coefficient of the DEFICIT indicates a positive sign and is insignificant statistically at a 5% significant level. The positive coefficient showed that a government budget deficit leads to a current account deficit, thus supporting the twin deficit proposition. The finding goes in line with studies conducted by Onafowora, and Owoye (2006) for Nigeria and that of Tarawalie (2014) for Sierra Leone. However, the monetary policy variable, interest rate shows a negative sign and is insignificant statistically. The results conform to the findings of Corsetti, Meier, and Müller (2006) that the rate of interest responded negatively for the US economy as against the theoretical prediction of positive response.
4.8. The Estimated Short Run ARDL Regression Model
The ARDL (1, 4) is selected based on the Akaike information criterion.
Table 6. The Short Run Error Correction Dynamics
Variable 
Coefficient 
Std. Error 
tStatistic 
Prob. 
D(CA(1)) 
0.388433 
0.148153 
2.621837 
0.0149 
DLOG(GCON) 
4.539311 
1.760108 
2.578995 
0.0165 
DLOG(GCON(1)) 
0.366517 
2.219855 
0.165108 
0.8702 
DLOG(GCON(2)) 
3.470234 
2.215205 
1.566552 
0.1303 
DLOG(GCON(3)) 
2.279325 
1.893102 
1.204016 
0.2403 
D(GDPGR) 
0.067215 
0.143681 
0.467805 
0.6441 
D(INTR) 
0.005098 
0.220935 
0.023072 
0.9818 
D(DEFICIT) 
0.000781 
0.000671 
1.165255 
0.2554 
ECM(1) 
0.994725 
0.172116 
5.779403 
0.0000 
Rsquared = 0.770424 Fstatistic = 7.321873 Prob(Fstatistic) = 0.000025 Adjusted Rsquared = 0.665202 DurbinWatson stat= 2.001526 
Table 5 above indicates that the shortrun errorcorrection term result ECM(1) from the ARDL model estimate is negative as expected with a value of 0.994725 and is statistically significant. This implies that there is a possibility for cointegration and therefore the existence of a longrun relationship among the variables. We can therefore conclude that the gap between the longrun equilibrium value and the actual value of the dependent variable CA is corrected with the speed of adjustment equal to 0.99 percent annually. It also showed that there exists a backward move towards equilibrium.The coefficient of determination indicates a value of 0.770424 and the adjusted with a value of 0.665202. This shows that 66% of variations in the dependent variable (CA) are explained by independent variables. The Fstatistics results indicate that the overall model is significant with a value of Prob(Fstatistic)= 0.000025; while the DurbinWatson (DW) statistics value of 2.001526 indicates the absence of serial correlation in the model under consideration.
4.9. Diagnostic Test
Under the diagnostic tests conducted, the Normality test results are presented in figure 3 below, shows that the average mean value is 2.96e16 and a median value of 0.280477. The maximum value is 4.223925 and the minimum value is 7.014235. Evidence from the Jarque – Bera (JB) test indicates that the null hypothesis is therefore rejected and the error terms of the model are normally distributed.
Figure 3. The Normality Test Result
Equally, the serial correlation and Heteroskedasticity tests results as presented in table 7 below, shows that the null hypotheses of no serial correlation are accepted and the Heteroskedasticity test results indicate that the error term of the variables is homoscedastic.
Table 7. The Diagnostic Tests Results
BreuschGodfrey Serial Correlation LM Test: 


Fstatistic 
1.193896 
Prob. F(2,22) 
0.3219 
Obs*Rsquared 
3.524736 
Prob. ChiSquare(2) 
0.1716 
Heteroskedasticity Test: BreuschPaganGodfrey 

Fstatistic 
1.135632 
Prob. F(11,24) 
0.3785 
Obs*Rsquared 
12.32355 
Prob. ChiSquare(11) 
0.3398 
Scaled explained SS 
4.749205 
Prob. ChiSquare(11) 
0.9427 
4.10. Stability Test
The stability test procedure is conducted using the Cumulative Sum of Recursive Residuals (CUSUM) and the Cumulative Sum of Squares of Recursive Residuals (CUSUMSQ) in line with Durbin, Brown and Evans (1975). To ascertain if the ARDL estimated results are stable, the CUSUM and CUSUMSQ test results are presented in figures 4 and 5 below:
Figure 4. The CUSUM test result
Figure 5. The CUSUM of Squares Test Result
From the figures 4 and 5 above, the critical bounds within the straight lines are significant at 5% level. The CUSUM and CUSUMSQ tests with a blue lines are equally within the area restricted by the lines; thus, the null hypothesis for CUSUM and CUSUMSQ are rejected and the conclusion is that the estimated models are effective with stable recursive residuals.
5. Conclusion and Policy Recommendations
This study contributes to the body of knowledge by evaluating the interaction effect between government consumption expenditure and current account in Nigeria covering the periods from 1980 to 2019. It is noted that Consumption expenditures, such as goods and services used by agencies and departments of the government cannot be economically produced by business enterprises. Examples are public administration and defense. This study particularly evaluated government consumption expenditures on goods and services to ascertain its effect on the current account in Nigeria. Thus, the study answered the question, does government consumption expenditure affect the current account in Nigeria? The stationarity test results for the variables indicate a mixed order of stationarity among the variables. The bound cointegration test results are proven to determine the longrun slopeestimated coefficients and the shortrun dynamicestimated coefficients. The shortrun errorcorrection term result ECM(1) from the ARDL model estimate is negative and is statistically significant. This implies that there is a possibility for cointegration and therefore the existence of a longrun relationship among the variables. Based on the findings of the study, the policy recommendations are as follows: The Federal Government of Nigeria should reduce the level of borrowing as this would reduce debt service payment affecting the country’s current account balance. There should be more funds allocated to sectors that create employment opportunities for the teeming population.
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1 Lecturer 1, Federal University OyeEkiti, Nigeria. Corresponding author’s: ephraim.ugwu@fuoye.edu.ng.
2 Senior Lecturer, Federal University OyeEkiti, Nigeria, email: philip.nwosa@fuoye.edu.ng.
3 Associate Professor, Federal University OyeEkiti, Nigeria, email: christopher.ehinomen@fuoye.edu.ng.