THE NEXUS BETWEEN THEEXTERNAL SECTOR AND INFLATION IN NIGERIA, 1985 -2018

The interaction between different economies in the global market could have impact on their key economic variables. Hence, this study set out to examine the impact of the external sector on a key economic variable in Nigeria being Inflation. The study utilized time series data from 1985 to 2018 which was subjected to Augmented Dickey Fuller Test. The next step was to subject the data to an ARDL cointegration test. The result showed that in the short run and long run external sector variables do not have any significant impact on inflation in Nigeria. The paper suggests that money supply and fiscal policy should be used to control inflation in Nigeria.

The interaction between different economies in the global market could have impact on their key economic variables. Hence, this study set out to examine the impact of the external sector on a key economic variable in Nigeria being Inflation. The study utilized time series data from 1985 to 2018 which was subjected to Augmented Dickey Fuller Test. The next step was to subject the data to an ARDL cointegration test. The result showed that in the short run and long run external sector variables do not have any significant impact on inflation in Nigeria. The paper suggests that money supply and fiscal policy should be used to control inflation in Nigeria.

…………………………………………………………………………………………………….... Introduction:-
Inflation is a concern to government's, businesses, and individuals. To the ordinary man, inflation is seen as a rise in the general price level in society (Arjun, 2014, p.67).Why would an ordinary man be familiar with the rise in the price level in the economy? This is because he is also a functioning man within the society. To function, he interacts at different levels which leads him to engage in transactions or financial and social discussions.
Firms, industries, and households are also affected by prices in their daily activities. A rise in the price of transportation can affect the final cost of raw materials and the cost of an individual's daily expenditure. Specifically speaking, higher prices can erode business profit, amplify losses, and reduce the disposable income of households. Basically, higher prices (inflation), has the potential to affect society to a large extent.
One of the major roles of any government is to ensure economic stability. Inflation, GDP (Gross Domestic Product) and exchange rate act as barometers that enable any government to determine the level of economic stability in the country.The major economic barometer that is of interest to this paper is inflation. For a government to stabilize inflation, it is important that the government understands what triggers inflation in both the theoretical and realistic sense as it relates to their country.
There are avariety of theories on the causes and impacts of inflation on the economy. One of the pronounced theories in this regard is Fishers 'Quantity theory of money'. Fisher recognizes that money supply has a direct impact on inflation. Therefore, the higher the money supply, the higher the inflation rate and vice-versa. However, money supply also has its own origins. It could be done through fiscal policy where government expenditure and open market operations are used to control money supply. It can also be done through monetary policy where the central bank manipulates the interest rate, direct lending to banks and the banks reserve to determine money supply.

Inflation
The desire of any government is for stability of its economy. When prices in an economy are stable it allows for proper economic planning by firms, household, and government. Inflation is a key economic indicator. It tells us the rate of increase in the general price level of an economy over time. Inflation is measured in different forms. It could either be the consumer price index (CPI), the rate of increase in the CPI (inflation rate) or PCE (Personal consumption expenditure). In Nigeria the CPI and the inflation rate are the common measures used for policy making.

Theoretical Framework
Fishers' quantity theory of money was propounded in the year 1911 in his paper with Brown titled 'The purchasing power of money'. The theory states that the general price level of goods and services in the society is proportionally related to the money supply in the economy (Fisher 1911).According to this theory, if the money supply in the economy should double, then the price level in society should also double. Equation 1 below can be used to further explain Fishers' quantity theory of money: MV = PT ……………….. (2.1) Where: -M is the quantity of money in existence.
-V is the velocity of money (number of times money changes hands) -P is the average price level.
-T is the volume of trade. V and T are assumed to be constant. This means that M and P have a directly proportional relationship. Equation 1 above also shows fishers perception of the relationship between the demand and supply of money. The left side of the equation being 'MV' tells us that money supply depends on the volume of money in circulation and 1153 the number of times the money changes hands. The right side of the equation tells us that money demand depends on the average price level and the volume of trade in the economy.
Theoretically speaking, it is expected that increase in money inflow from the external sector should lead to an increase in the inflation rate in Nigeria and vice-versa. This forms the basis of the null hypothesis of this paper.

Empirical Literature Review
There is a vast literature on the relationship between the external sector variables and the inflation rate in Nigeria. In this section of the paper, we are going to review some of the literature available.
Mustafa (2019) examined the relationship between foreign direct investment (FDI) and inflation in Sri Lanka between the years 1978 and 2017. The study employed the Johansen cointegration analysis technique. The result showed the existence of a long run relationship between inflation and FDI. The nature of this relationship is negative meaning that a rise in FDI, would lead to a fall in the inflation rate in Sri Lanka. A causality test carried out in the analysis showed a one-way causal relationship from FDI to inflation. This implies that FDI can be used to control inflation in Sri Lanka.
Aderemi et al (2020) carried out an empirical investigation into 'The determinants of foreign direct inflows in Nigeria' between the years 1990 and 2017. Data sourced from the World bank and the CBN statistical bulletin were analysed using the ARDL regression technique. The study found market size, exchange rate and GDP growth rate to be the major drivers of FDI in Nigeria. This study also agrees with Mustafa (2019) as it discovered the existence of a negative relationship between inflation and FDI in Nigeria. The paper concludes that inflation discourages foreign direct investment and encourages the Nigerian government to work on reducing its inflation rate to attract more foreign direct investment.
A different angle to the relationship between inflation and FDI is presented by Kelvin and Oliver (2019). They studied the relationship between inflation and FDI then related it to economic growth. Their study was on 'Moderating the effects of inflation on foreign direct investment and economic growth in Nigeria'. The aim of the study was to determine the impact of inflation on FDI in Nigeria between the years 1981 and 2017. The study employed the Johansen cointegration technique to determine the long run relationship between inflation and FDI. The results shows that the relationship betweeninflation and FDI is non-linear. It was also discovered that when inflation was at 2.8 per cent and lower, there was a positive relationship between FDI and growth and vice-versa. This paper therefore advises that government policy should target maintaining the inflation rate at a maximum rate of 2.8%.
Trade openness is one of the variables that is also identified in this paper as an external sector variable.Musibau (2017) studied the relationship between trade openness and inflation in Nigeria between the years 1980 to 2015. The study was done using the Autoregressive Distributed Lag (ARDL) method of analysis. The result of the bounds test showed the presence of a long-run relationship between trade openness and inflation in Nigeria. The nature of this long-run relationship is positive. As the Nigerian economy becomes more open to trade in the long run there would be a rise in the inflation rate and vice-versa. The result also showed a totally opposite situation in the short run. In the short run there is a negative relationship between inflation and the trade openness. As the Nigerian economy becomes more open to trade, there is a fall in the inflation rate in the short run.
A similar study was done in India by Megha and Qamar (2020) where they used the ARDL method of analysis to investigate the relationship between trade openness and inflation. Time series data covering the period of 1974 to 2016 was used for the analysis. The result showed the presence of a positive relationship between inflation and trade openness in India. Therefore, the more open the economy is to trade, the more inflation there will be in the economy. The aim of the paper was to test the Romer's hypothesis which state that there is a negative relationship between inflation and trade openness. This paper by Megha and Qamar (2020) clearly negates the Romer hypothesis.
Another key external sector variable identified is the exchange rate. Abiodun et al (2016), carried out a research titled 'Exchange rate pass-through to inflation in Nigeria'. The aim of thier paper was to check if the persistent fall in the naira caused by both intentional devaluation by the Nigerian government and the effects of the interaction of demand and supply in the foreign exchange market, would lead to inflation in Nigeria. The study utilized the 1154 Johansen cointegration test to check for the existence of long-run relationship between inflation and exchange rate. It went on to carry out a vector error correction mechanism which showed that there is no pass-through of exchange rate into inflation. The result of the analysis showed that exchange rate influences imports and not inflation. Sanam and Fetullah (2017) also investigated the relationship between the exchange rates and inflation in Iran. Time series data that was used in this research covered the years 1976 to 2012 and was analysed using the Hendry method. Quarterly data covering 1997 third quarter to 2011 fourth quarter was also analysed using the VAR (Vector Autoregression) method. The results showed the existence of a direct relationship between inflation and the exchange rate in Iran. Therefore, the higher the exchange rate, the higher the inflation rate and vice-versa. The result of the analysis also showed that money supply has more influence on the inflation rate in comparison with the exchange rate.
The final external sector variable that is key to this paper is trade balance. Muhammed and Muhammed (2015) investigated the impact of financial development on trade balance in Pakistan.The aim of the investigation was to determine the nature of the relationship between financial development, trade balance, exchange rate and inflation. Time series data was used for this research which was subjected to a unit root test. The result of the unit root test suggested that the ARDL method of analysis should be applied in the paper. The regression result showed the presence of a positive relationship between inflation and trade balance in both the short run and in the long run.
The dynamics of inflation rate, exchange rate and trade balance in Uganda was analysed by Zelealem and Jacob (2018). The aim of the analysis was to determine the nature of the relationship between inflation and the exchange rate and how it affects trade balance in Uganda. The time series data used in this paper was subjected to the ARDL regression technique. The results showed that in the long run, inflation and real depreciation had no impact on trade balance. The ECM was generated to determine the short run result which showed that inflation has no impact on trade balance in the short run. The study suggests to policy makers that actions targeted at controlling the inflation rate and exchange rate will have no impact trade balance in Uganda.
The theoretical foundation of this paper hypothesizes that an increase in money supply should lead to an increase in the inflation rate. This implies that the inflow of funds from the external sector should lead to an increase in the inflation rate. The literature reviewed which covers both Nigeria and other countries has showndifferent results for different countries where some agree, and others disagree with the theoretical foundation of this paper. This inconsistency between the theoretical framework and the literatures reviewed gives further justification for this research.This paper will now go on to investigate the situation specific relationship that exists between the external sector and inflation in Nigeria between the years 1985 and 2018.

Methodology:-
This section is going to explain the data collection and analytical method that is used to analyze the impact of the foreign sector on inflation rate in Nigeria. This section lays out the empirical steps to be followed in this study.

Model Specification
The analytical framework is derived from the quantity theory of money in which an increase in money supply will lead to an increase in the rate of inflation in an economy. Going by this theory, if there is an increase in money supply in the country due to the activities in the foreign sector, then there will be an increase in the rate of inflation within the country. It is based on this theoretical framework that the following model is specified:

Method of Data Analysis:-
This study will adopt the Auto-Regressive Distributed Lag (ARDL) regression technique for this analysis. The technique was developed by Pesaranet al (2001). The ARDL/Bound is unique when compared to other analysis techniques as it can be applied in the event that there are mixed stationarity levels or orders of integration (i.e. I(0) and I(1). It is also efficient in small samples and generates both the short and long-run. The following steps below will be used to carry out the ARDL technique. Granger and Newbold (1974) observed that running regressions without analyzing the unit root will lead to spurious results. It is therefore advisable for empirical studies that unit root analysis be applied before running regressions. For the purposes of this paper, the Augmented Dickey-Fuller approach (Dickey and Pantula, 1987) will be used to test for unit root. This method of unit root testing has control for serial correlation in the model and performs well asymptotically.

Unit Root Test
There are three strands to unit root testing using the ADF approach. This paper will adopt the complete version with trend and intercept as is seen below: 3) When conduction the unit root test the following hypothesis are used: 0 ; p=0: Y has a unit root. 1 ; ρ<0 Y does not have a unit root. The test will be carried out at 5% significance level.

Co-integration Test
After getting the results of the unit root test, the next step to take is to check if the relationship among the variables being analyzed have a long run relationship. The econometric method of checking this is called co-integration test. The ARDL model makes used of the 'Bounds approach technique' which was developed by Pesaran et al (2001) to examined co-integration among the variables within the model. The ARDL/Bound testing model is specified below as follows: 1156 ∆ is the vector of the first difference of the dependent variables; ∆ −1 is the lag values of the difference of the dependent variables; −1 are the first lag of the independent variables; is the short run coefficient; is the long run coefficient; is the summation sign; is the error term.
The F-statistics generated by the bounds test is compared with the upper and lower bounds outputs at a 5% probability level (Pesaran et al 2001). If the F-statistics is greater than the upper critical bound the null hypothesis of no co-integration is rejected. However, if the F-statistics is lower than the lower bound then we cannot reject the null and there is no co-integration in the model. When the F statistics is between the upper and lower bound then the cointegration test is said to be inconclusive and therefore the short run and long run results should be analyzed.

Empirical Results and Discussions:-
The results of the empirical analysis will be discussed in this section of the paper.

Descriptive Statistics
The statistical properties of the regression data are examined using descriptive statistics. This analysis tells us the different statistical properties of the data to enable us to determine if the data can be used for regression analysis. The results of the descriptive statistics of the different variables are presented below: There are 34 (thirty-four) observations in the table above. Inflation has a mean of 17.3% per annum, a maximum and minimum value of 75.40% per annum and 0.69% per annum respectively.

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As it is shown in Table 4.1 above, we also see that there are 34 annual exchange rates between the years 1985 and 2018. These exchange rates have a mean of 99.88 Naira to the American dollar. The maximum annual official exchange rate for the same period is 306 Naira to the American dollar; and the minimum annual official exchange rate is 0.89 naira to the American dollar.
Foreign direct investment has a mean of 298 million American dollars per annum between the years 1985 and 2018. The maximum foreign direct investments that has been received by the Nigerian government between the years 1985 to 2018 is 884 million American dollars and the minimum foreign direct investment that the Nigerian government has received between the years 1985 to 2018 is 193 million American dollars.
Trade openness has a mean of 50% between the years 1985 and 2018. The maximum value for trade openness between those years is 81% and the minimum value for trade openness between those years is 21%.
Finally, Trade Surplus has a mean of eleven billion, five hundred million dollars between the years 1985 to 2018. The minimum value being a trade deficit of nine billion, two hundred and fifty million dollars only. The maximum value with the same period is eighty-five billion and three hundred million dollars only.

Unit Root Test Results
The unit root test was conducted with both the Augmented Dickey-Fuller (ADF) test. This test is used to check for the existence of trend in the data using trend and intercept. The results are presented in the table below: The result presented in table 4.1 above shows that only FDI is stationary at level I(0) after being subjected to the Augmented Dickey-Fuller unit root test, while INFR, EXCH, TOP and TS are not stationary at level. This is because the calculated statistics for FDI is greater than the critical values at both 5% and 10% level of significance integrated at order I(0). However, the calculated statistics for INFR, EXCH, TOP and TS are less than their associated critical values at both 5% and 10% level of significance which means that these variables are not stationary. Shrestha and Bhatta (2018) suggest that taking the first difference of a non-stationary variable can make it stationary. Therefore, the next step is to proceed to take the first difference of the variables that were not stationary at level. This is seen in the table 4.2 below:  The result of the bounds test shows that the calculated F-statistics of 3.029607 is in-between the lower and upper bound at 10% and lower than the lower bound at both 5% and 1%. This result suggests that both results for the short-run and long-run will be presented to understand the relationship between the external sector and inflation in both the short-run and the long-run.This paper now proceeds to estimate the long-run model. The table above shows the long run results on the relationship between inflation and the external sector. In the table we see that Exchange rate has a negative relationship with inflation. A rise in the exchange rate (the lower the value of the naira) will lead to a fall in the inflation rate and vice-versa holding all factors constant. A 1% increase in the exchange rate will cause inflation rate to fall by 0.12%. However, this negative relationship between exchange rate and the inflation rate in insignificant in the long run.
Foreign direct investment also has a negative and insignificant relationship with inflation during the period under review. The result on FDI above implies that in the long run, a 1% increase in foreign direct investment will lead to a (1.47E-09) % decrease in the level of inflation in the economy in the period under review.
In the table above, we can see that Trade Openness has a negative and insignificant relationship with inflation in the long run. This implies that for a 1% increase in trade openness in the economy will lead to a fall in the inflation rate by 0.116077% in the period under review.
From the table above, we can see that the relationship between Trade Surplus and inflation in the long run is negative and insignificant. The implication is that a 1% increase in Trade Surplus will lead to a (-2.55E-10) % decrease in the inflation rate.
The results in table 4.4 generally tells us that in the long run there is no significant relationship between the different variables which together make the external sector and inflation. Therefore, in the long run the external sector is insignificant in determining the inflation rate in Nigeria.
We will now proceed to examine the short-run relationship between inflation and the external sector. The short run effects of the Nigerian external sector in the inflation rate in Nigeria is presented in Table 4.5. From this table we can see that in the short run, the external sector variables that affect inflation in Nigeria are only, trade openness and trade surplus. The result shows that in the short run, trade openness has a negative but insignificant relationship with inflation. Therefore, in the short tun, a 1% increase in trade openness will lead to a decrease in inflation by approximately 0.25%.
The result also shows that in the short run there is a negative and significant relationship between inflation and trade openness after one-year lag. Therefore, a 1% increase in trade openness will lead to an approximately 0.59% fall in inflation rate after one-year lag.
There is also a negative but insignificant relationship between trade openness and inflation after two days lag. For a 1% increase in trade openness, there will be a 0.34% decrease in inflation after a two-year lag.
Trade surplus has a positive and insignificant relationship with inflation. This implies that a 1% increase in trade surplus will lead to a (3.63E-11) % increase in the inflation rate.
The coefficient of the Error Correction mechanism (CointEq (-1)*) is negative and statistically significant. The coefficient of the error correction mechanism is appropriately signed and significant. The absolute value of the coefficient, -0.62830, implies that the speed of adjustment of the model to the long run equilibrium value is approximately 6% within the year.

Post Estimation Test
We use post estimation tests to check the integrity of the analysis:

Accepted
The results of the post-estimation tests are presented in table 4.6 above. The results show that the estimated residuals of the model are normally distributed. Serial correlation test also shows that there is no presence of serial correlation among the error terms. Heteroskedasticity test supports the acceptance of the null hypothesis at 0.05 level of significance. Therefore, there is no evidence of heteroskedasticity among the estimated error terms. In figure 4.1 below, we see the result of the CUSUM test. The test shows that themodel is within the 5% significance level which is desirable.

Implication of Results
From the results discussed above, the external sector does not have any significant impact on inflation in Nigeria. It therefore implies that inflation cannot be controlled by policies affecting the external sector variables in Nigeria. Theoretically, as prescribed by the quantity theory of money, inflation should be controlled using money supply. It is therefore implied that using money supply to control inflation in Nigeria should be considered as the external sector variables are not significant to explaining inflation in Nigeria.

Conclusion and Recommendations:-Conclusion:-
The general objective of this paper is to examine the relationship that exists between the external sector and inflation in Nigeria. The specific objective is to determine if there is a long-run relationship between the external sector variables and inflation in Nigeria within the years 1985 to 2018.
To achieve these objectives the study engaged ex-post facto research design using Nigeria's data obtained from the World Bank covering the time of 1985 to 2018. The foundational empirical test carried out on the data was the Augmented Dickey-Fuller test. The results of the Augmented Dickey Fuller test informed the used of the Autoregressive Distributed Lag (ARDL) bounds test to check for the existence of long-run relationship. The next step was to present the short-run and long-run results from which the error correction mechanism was designed. It was found that in both the short-run and long-run there is no significant relationship between external sector variables and inflation in Nigeria. It is therefore imperative to conclude from the results that the external sector has no significant impact on inflation in Nigeria. Going by the theoretical framework of the quantity theory of money, this paper would urge the Nigerian government to utilize domestic money supply and fiscal policy to control inflation in Nigeria.