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                                            Australian Finance & Banking Review; Vol. 4, No. 1; 2020  
                                                                               ISSN 2576-1196   E-ISSN 2576-120X 

           Published by Centre for Research on Islamic Banking & Finance and Business, USA 
 

        9 
 

Test of Monetary Approach to Balance of Payments in West Africa Monetary 
Zone 

 
 

Foluso Ololade Oluwole 
Department of Banking and Finance 

Adekunle Ajasin University, Akungba Akoko; Ondo State, Nigeria 
E-mail: foluso.oluwole@aaua.edu.ng 

 
John Adebayo Oloyede 

Department of Banking and Finance 
Ekiti State University; Ado Ekiti, Ekiti State, Nigeria 

E-mail: ololadefo81@gmail.com 
 
 
Abstract 
This research tested the monetary approach to Balance of Payment in developing countries of West Africa in order to affirm 
whether the specified relationship in the approach depicts correctly the actual behaviour of the economies. Time series and cross-
sectional data that ranges from 1970 – 2016 were used. The empirical results of the fixed effect model established a significant 
positive relationship between net domestic credit, interest rate and exports; an insignificant positive relationship between capital 
movements, imports, income and the dependent variable. Exchange rate, however, had a significant negative relationship with the 
net foreign assets, while inflation had an insignificant but negative relationship with net foreign assets. The pairwise causality 
tests indicated a unidirectional relationship between exchange rate, net domestic credit and net foreign assets while the other 
variables move independently and cannot granger cause net foreign assets. Hence, the study concludes that the Polak model is 
valid in the West Africa Monetary Zone despite the fact that they are no more operating a fixed exchange rate system. The study 
suggests that the attention of the monetary authorities and the governments should not only be on decreasing the money supply 
in the economy, since an increase in net domestic credits has a positive impact on the net foreign assets provided it is channeled 
towards domestic production.  
 
Keywords: Balance of Payment, Foreign Exchange, Monetary Approach, Current Account Deficit, Money Supply.   
 
JEL Codes: E42, F31, E12, F32, E51.  
 
1. Introduction 
It has been observed over time among developing countries that there is a prevalence of persistence current account deficit which 
is a major cause of concern because, maintaining a healthy and stable balance of payment and promoting trade drives rapid 
economic growth. Therefore, the management and sustenance of balance of payment (BOP) equilibrium is of great importance 
for developing countries to pursue (Boateng and Ayentimi, 2013; Umer, 2010; Ogiogio, 1996 and Obionna,1998). An 
examination on the problem of BOP imbalances by Martin (2014) revealed that out of the 66 poorer developing counties (low 
income and lower middle-income countries), 52 had a current account deficit. The current account deficits in these states are 
common than in other groups of nations due to the great effect of external factors that cannot be influenced and it is also a sign 
of the endeavours of countries with less capital to accelerate economic development by means of net capital imports. 

Also, despite the relatively extensive body of theoretical and empirical literature on this subject matter, there are only a 
few comprehensive studies that empirically analyse the effect of macroeconomic variables of the polak model on the BOP 
position of West African countries. For example, Stephen and Njuyuna (2000) applied the old Polak model to Kenya, pointing 
out that the behavioural equation of the Polak model ignores the other determinants of money balances like interest rate, 
inflation and wealth. It assumed that changes in domestic credit have no effect on the determinants of money demand. The study 
is also in conformity with the work of (Nwakama, 2013; Duasa, 2005; Ajayi, 2014; Tijani, 2004; Johnson, 1976; Aghevli and 
Khan, 1977; Connolly and Taylor, 1976; Humphrey, 1976, 1977; Musa 1976). The monetary approach also assumed a fixed 
exchange rate regime. The definitional equation also treated export as being determined exogenously, which is only realistic if the 
exchange rate is fixed. Once an exchange rate is flexible, it becomes endogenous (Khan, 2008). Adamu and Itsede (2010), 
however, in their study of monetary approach to BOP in West Africa monetary zone, filled the above gap by including other 
determinants of money demand like inflation and interest rate but ignored the effect of exchange rate volatility on BOP as a 
control variable that the monetary authority should also focus on, in addition to the net domestic credit (Polak 1997).  

mailto:foluso.oluwole@aaua.edu.ng
mailto:ololadefo81@gmail.com


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This sparked off the emergence of an empirical research and better evidence to validate the monetary approach in resolving 
the BOP crisis in the selected West African countries through the modified Polak model. In view of this, the study tends to 
investigate the relationship between BOP, proxy as net foreign assets and some macroeconomic variables in the selected 
countries. The investigation is an attempt to examine the extent to which the monetary theory approach explains the observed 
behaviour of BOP problem of West African countries that operates the floating exchange rates. 

 
2. Literature Review 
The application of Polak model to Namibia was also carried out by Fleermuys (2005). The monetary approach to Namibia’s 
BOP was tested on the basis of quarterly data covering the period 1993 to 2003, in which Net foreign assets is a function of 
economic growth, inflation, interest rate and net domestic credit using the Engel-Granger approach to long run estimation to test 
whether BOP is a monetary phenomenon on the long run. It was found out that the BOP in Namibia is not a purely monetary 
phenomenon because only inflation and domestic credit have a significant relationship with net foreign assets. The study thus 
concluded that the monetary authorities should pay special attention to domestic credit and to also achieve sufficient economic 
growth through money demand to correct the balance of payments deficit. This conforms with the works of Menzie and 
Eswar,2002;  Dausa, 2005; Makin, 2005; khan, 2008; Boateng and Ayentimi (2013); Iyoboyi and Mufutau (2014); Shuaib, 
Augustine and Frank ,2015 

The study conducted by Braima and Korsu (2013) tested whether the balance of payments of Sierra Leone is a 
monetary phenomenon, using aggregate annual data for Sierra Leone from 1970 to 2010. A reserve flow model was estimated. 
Due to the inherent tendency of non-stationary of macroeconomic variables and their attendant spurious effects on time series 
regression estimates, tests for stationary of the variables were carried out. Given the existence of non-stationary in the variables, 
which were however found to be stationary under linear combination (were co-integrated); an error correction model was 
estimated. The result showed that the balance of payments of Sierra Leone is a monetary phenomenon, driven by changes in 
domestic credit, the price level, exchange rate and interest rate. Domestic credit, interest rate and the price level have negative 
effects on the balance of payments of Sierra Leone while the exchange rate has a positive effect. However, the importance of the 
price level is felt with a delayed impact. According to them, the policy implication is that monetary policy operations that are 
consistent with low and stable inflation, domestic credit restraint and exchange rate depreciation are important for improvement 
of the BOP of Sierra Leone, with low and stable inflation being more useful for medium term objective.  Supporting these views 
are the works of Aghevli and Khan, 1977; Dhliwayo, 1996; Tijani, 2004; Imoisi,2012; Umoru and Odjegba (2013); Ajayi, 
2014. 
 For a cross country study in Africa, Taiwo (1992), using Bayesian posterior odds ratio, sampled ten (10) African 
countries from 1960-1990, to assess their BOP crisis. He concluded that about 50 percent of the countries sampled were 
experiencing a fundamental disequilibrium in their current and capital accounts. He noted that the economic crisis facing most 
African countries is multi-dimensional, and must not in any way be compared with the BOP predicament that they are facing. 
The view of Nyong and Obafemi (1995) and that of Arewa and Nwakama(2013) are that government needs to look beyond 
the issue of money supply in solving the BOP issues.  

Most of the studies reviewed above view balance of payment problem as a monetary phenomenon and not a real 
phenomenon while some have mixed results. It is also noted that a lot of work has been done on the developed countries and 
developing countries.  Despite the application of the monetary approach, even by the IMF to various countries, they are still  
experiencing deficits in their balance of payment position. Using various models by different authors, and the conventional 
theories, there is need to carry out this study on the African countries, most especially the West African countries whose external 
sector has undergone profound changes over the years viewed from the trend of their BOP position.  Most of these countries run 
current account deficits alongside low levels of investment and economic growth, which may not be beneficial to them on the 
long run.  The study, however intends to investigate the validity of the assumption that BOP deficits or surplus in the West 
African countries, is a monetary phenomenon, using the modified Polak model (Polak, 1997).  
 
3. Methods 
The research design for this study is the correlation research design as the model focuses on the relationship between credit 
expansion and change in foreign assets and its effect on the BOP. The key variable according to the model which the authorities 
could control is the domestic credit creation. 
 
3.1 Model Specification 
To test the efficacy of the monetary approach on balance of payment proxy as net foreign assets, the equation in a functional 
form is given as: 
 
NFA = f (NDC, CM, EXP, INC, MCIP, INF, INT). 



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The modified version of the Polak model as in Yotzov (2001), Adamu and Itsede (2010), Wioletta (2013) with the inclusion 
of exchange rate as an additional policy variable to the net domestic credit was tested in the usual equation as: 
 
NFAit =a0 + a1NFAIt -1 + a2 EXPit + a3CMit + a4INCit + a5NDCit + a6MCPIit + a7EXCHit + a8INF + a9 INT + nit + µi 

 
Where,     NFA = net foreign assets 
  EXP = value of exports 
  NDC = net domestic credits 
  INC = Real income 
  CM = capital movements 
  INT = interest rate 
  INF = inflation rate 
  MCIP = share of imported goods and services relative to price level 
  EXCH = exchange rate  
  a0  = intercept 
  a1 – a8 = are the coefficient of the parameter estimates 
  nit = country specific factor 
  ui = is the error term 
 
3.2 A Priori Expectation 
It is expected that the coefficients of domestic credit, price index, interest rate, and inflation will be negative while exchange rate, 
income, exports and imports will be positive. Theoretically, it is expected that low exchange rate will encourage importation and 
this will worsen the balance of payment position. Also, the growth of GDP will increase when exports exceed import which 
basically improves BOP. When there is inflation in an economy, people tend to rely on imported goods whose price does not 
change, therefore bringing about unfavourably BOP.   

Mathematically: a1, a3 a5, a6 ˃ 0 while a2, a4, a7 and a8 ˂ 03.4 
  
3.3 Estimation Techniques 
The choice of estimation depends on the specification of model, the nature of the available data and the purpose of the model. 
The fixed effects model takes into account the panel structure of the data and assumes that the individual heterogeneity among 
the countries is captured by the intercept. The intercept of the model does not vary over time i.e. it is time invariant. Therefore 
the model was estimated using the panel fixed effect model. Different diagnostic tests were also conducted to check the validity 
of the model. The panel unit root to test the level of stationary, the panel co-Integration to guide against spurious regression and 
the Hausman tests to determine whether the fixed or the random effect would be suitable for the model under study. 
 
3.4 Sources of Data 
Annual time series data covering the period of 1970 – 2018 were sourced to test the Polak model of the monetary approach to 
BOP in the West African Monetary Zones (Ghana, Gambia, Guinea, Liberia, Nigeria and Sierra Leone). These data were 
sourced from secondary sources which include: the IMF’s International Financial Statistics, West Africa Monetary Institute 
(WAMI) database, World Development Indicators, Organisation for Economic Community Development (OECD) data base. 
However, the data for guinea was not all available and so; the analysis was based on the other five countries, excluding Guinea 
 
3.5 Statistical Definition of Variables 
For the purpose of the study under review, the following definitions are adopted: 

▪ Net Domestic Credit (NDC): is defined as the sum of the net claims on the central bank and claims on other sectors 
of the economy measured in local currency unit. 

▪ Income (Y): is identified as the gross domestic product (GDP) rate annual percentage, that is the annual percentage 
growth rate of GDP at market prices based on constant local currency. 

▪ Net Foreign Assets (NFA): represents the nets foreign assets held by monetary authorities and deposit money banks, 
less their foreign liabilities measured in current local currency.  

▪ Exports (X): The export value index was used; that is, the current value of exports converted to US dollars and 
expressed as a % of the coverage for the base period (2000). 

▪ Capital Movements (CM) covers the net capital inflows of the non-banking sector.  
▪ Import (MCPI): This is measured as the annual growth rate of imports of goods and services based on constant local 

currency, aggregate based on constant 2010 US dollars. 



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▪ Exchange rate (EXCH):  The official exchange rate was used, calculated as an annual average based on monthly 
averages (local currency units relative to dollars).  

▪ Interest rate (INT): this represents the deposit interest rate measured by the rate paid by commercial banks for 
demand, time and savings deposit. 

▪ Inflation rate (INF): inflation was measured by the annual growth rate of the GDP implicit deflator, that is, the ratio 
of GDP in constant local currency. 
 

4. Results 
4.1 Descriptive Statistics 
Table 1. Descriptive Statistics 
 

 NFA NDC MCIP INT INF INC EXPT EXCH CM 

 Mean  3.83E+11  5.93E+11  15.95938  13.01391  19.35887  3.336903  1.86E+11  268.7881  1.73E+11 

 Median  21389119  1.05E+09  11.76600  12.47208  11.59316  4.168448  13316120  2.084538  46642816 

 Maximum  8.72E+12  1.96E+13  96.26080  35.75917  178.7003  106.2798  5.70E+12  4524.158  6.55E+12 

 Minimum -4.22E+11 -3.14E+08 -54.34199  1.833333 -35.83668 -
51.03086 

-115138.3  0.000102 -9.24E+08 

 Std. Dev.  1.50E+12  2.46E+12  27.13448  6.112069  24.21256  11.27003  6.01E+11  841.9288  8.27E+11 

 Skewness  4.274297  5.802849  0.128018  0.988401  3.012703  2.545981  6.428859  3.634825  6.006569 

 Kurtosis  20.66077  38.08141  2.654650  4.457101  15.02110  36.48484  53.48722  15.59943  40.05378 

 Jarque-Bera  3593.160  12743.71  1.724998  56.28831  1687.581  10706.85  25333.28  1974.872  14161.45 

 Probability  0.000000  0.000000  0.422106  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000 

 Sum  8.58E+13  1.33E+14  3574.901  2915.115  4336.386  747.4663  4.16E+13  60208.53  3.88E+13 

 Sum Sq. Dev.  5.04E+26  1.35E+27  164190.4  8330.696  130733.3  28324.05  8.06E+25  1.58E+0
8 

 1.52E+26 

 Observations  224  224  224  224  224  224  224  224  224 

Source: Researcher’s Computation 2019 
 

From table 1, the mean results of all the variables showed a significant value, the median and maximum equally 
revealed a significant value while the minimum descriptive statistics of Net Foreign Asset (NFA), Net Domestic Credit (NDC), 
MCIP, Inflation (INF), Real Income (INC), Export (EXPT), and Capital Movements (CM) revealed negative minimum 
contributions meanwhile Interest Rate (INT) and Exchange Rate (EXCH) reported positive contributions.  

From Skewness statistic, it indicated that all the variables were positively skewed, while Kurtosis statistic displayed that 
all variables were leptokurtic (fat tailed) in nature. The Jarque-Bera statistic value showed significant contributions. However, the 
descriptive analysis revealed that the variables were normally distributed with 224 observations.  
 
4.2 Panel Unit Root Result 
The unit root test was carried out using the Im, Perasan and Shin Methos. The results are presented in table 2 to table 4 
 

Table 2. Im, Pesaran & Shin Unit Root Test at Level   
 

Variable Statistic Prob.  

NFA 3.76907 0.9999 Non-Stationary 

NDC 3.63730 0.9999 Non-Stationary 

MCIP -2.39857 0.0082 Stationary 

INT -0.05629 0.4776 Non-Stationary 

INF -3.64146 0.0001 Stationary 

INC -6.37563 0.0000 Stationary 

EXPT -1.04578 0.1478 Non-Stationary 

EXCH 1.84191 0.9673 Non-Stationary 

CM -4.10924 0.0000 Stationary 

Source: Researcher’s computation (2019) 
 

          



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Table 3. Im, Pesaran & Shin Unit Root Test at First Difference 
 

Variable Statistic Prob  

NFA -8.35293 0.0000 Non-Stationary 

NDC -10.3402 0.0000 Non-Stationary 

INT -10.0086 0.0000 Non-Stationary 

EXPT -5.80371 0.0000 Non-Stationary 

EXCH -7.00957 0.0000 Non-Stationary 

Source: Researcher’s computation (2019). 
 

           Table 4. Order of Integration 
 

Variable Order of Integration 

NFA I(1) 

NDC I(1) 

MCIP I(0) 

INT I(1) 

INF I(0) 

INC I(0) 

EXPT I(1) 

EXCH I(1) 

CM I(0) 

Source: Researchers’ computation (2019) 
 

Table 2, 3 and 4 revealed Im, Pesaran and Shin (IPS) Panel Unit Root test, which was employed to test for the stationarity 
of the variables. The results were presented in level and first difference at 5% significance level. The result showed that MCIP, 
INF, INC and CM were stationary at level while other variables such as NFA, NDC, INT, EXPT and (EXCH) became 
stationary only after first differencing at 5% alpha level of significance. This implies that the variables retained shock for short 
period, after which they let go and this necessitated the use of Panel Auto-regressive Distributed Lag (P-ARDL).  
 
4.3 Lag Selection Criteria 
The Likelihood Ratio test (LR), Final Prediction Error criteria (FPE), Akaike Information Criterion (AIC), Schwarz 
Information Criterion (SC) and Hannan-Quinn Information Criteria (HQIC) were applied for the selection of lag length. The 
Criteria suggestion is then presented below for the estimation of the Panel ARDL.  
 
Table 5. Lag Length Selection Criteria 
 

 Lag LogL LR FPE AIC SC HQ 

0 -28868.59 NA   4.7e+110  280.3649  280.5103  280.4237 

1 -27101.08  3363.405  3.6e+103  263.9911   265.4450*  264.5791 

2 -26953.74  267.5031  1.9e+103  263.3470  266.1095  264.4642 

3 -26698.42   441.2406*   3.5e+102*   261.6545*  265.7255   263.3010* 

Source: Researchers’ computation (2019) 
 

The results indicated that Likelihood Ratio (LR), Final Prediction Error (FPE), Akaike Information Criterion (AIC), 
Schwarz Criterion (SC) and Hannan-Quinn Criterion (HQ) predicted 3, 3, 3, 1, and 3, lag respectively. The study then selected 
the lag length of Schwarz Criterion being the minimum lag length and for the nature of the data.  
 
4.4 Results of the ARDL 

         Table 6. Autoregressive Distributed Lag (ARDL) Model 
 

Variable Coefficient Std. Error t-Statistic Prob. 

C 1.330945 3.437045 0.387235 0.6990 

NFA(-1) 0.638765 0.067898 9.407745 0.0000 



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EXPT -0.275808 0.111102 -2.482475 0.0325 

NDC -0.513939 0.165061 -3.113628 0.0096 

INC 0.021686 0.063919 0.339270 0.7347 

CM -0.256245 0.070942 -3.612036 0.0184 

INTR 0.145507 0.141922 1.025257 0.3064 

INF -0.039398 0.030838 -1.277555 0.2028 

EXCH 0.086458 0.023829 3.622582 0.0162 

MCIP 0.061339 0.028177 2.057866 0.0213 

R-Squared = 0.75 Adj. R-Squared = 0.74 F-Stat. = 64.888 Prob.(F-Stat.) = 0.000 
Source: Researcher’s Computation 2019 

 
The result of the autoregressive distributed lag (ARDL) was presented in Table 6. From this result, it was discovered 

that a direct linear relationship exist between net foreign asset and net foreign asset at lag one [NFA (-1)], income (INC), 
interest rate (INTR), exchange rate (EXCH) and MCIP while, an inverse relationship was observed between the net foreign 
asset (NFA) and export (EXPT), net domestic credit (NDC), (CM), inflation rate (INF) of the countries during the period 
under study. The statistical significance of the estimated parameters of this model was examined using the standard error test and 
the probability value.  

This result shows that one percent increase in net foreign asset at lag one, net foreign asset at lag two income, interest 
rate, exchange rate and MCIP will lead to 64, 17, 2, 15, 9 and 6 percent increases in net foreign asset while, one percent increase 
in value of export, net domestic credit, capital movement and inflation rate will cause the net foreign asset to reduce by 28, 51, 
26 and 4 percent respectively in West Africa. Using standard error test, it was revealed that 0.319, 0.086, 0.138, 0.257, 0.128, 
0.043, 0.031 which are greater than 0.068, 0.067, 0.111, 0.165, 0.071, 0.024 and 0.028 respectively for NFA(-1), NFA(-2), 
EXPT, NDC, CM, EXCH and MCIP. The same result is obtained using probability value as the prob. values of the estimated 

parameters 0.000, 0.011, 0.033, 0.009, 0.018, 0.016 and 0.021 ˂ 0.05 the probability of the error margin. Thus, it implies the 
statistical significant of the estimated parameters in determining the net foreign asset of the West African countries. The R-
square value 0.75 revealed that 75 percent variation in the net foreign asset of the West Africa countries under consideration can 
be explained by the lags value of the net foreign asset, export, net domestic credit, income, capital movement, interest rate, 

inflation rate, exchange rate and MCIP. The probability of F-statistic 0.000 ˂   0.05 shows the statistical significant of the 
autoregressive distributed lag model in balance of payments in the West African Monetary Zone countries using monetary 
approach. 
 
4.5 Hausman Result 
To determine the appropriate estimator between fixed effect and random effect the Hausman test was employed. Hausman Test 
compares fixed effect with random effect. If the Hausman test is insignificant (Prob > Chi2 greater than .05), then the fixed 
effects model will be used and vice versa. The result is therefore presented in table 4 
 

    Table 8. Hausman Result  
 

Test Summary Chi-Sq. Statistic Chi-Sq. d.f. Prob.  

Period random 29.989784 8 0.0002 

Source: Researchers’ computation (2019) 
 

Table 8 presents the result of Hausman test which revealed that the chi-square value is 29.9898 and its P-values were 
0.0002. The result showed that there is enough evidence to reject the null hypothesis of no substantial difference between fixed 
effect estimates and random effect estimates. The test revealed that fixed effect estimator is the most efficient and consistent 
during the study period. 
 
4.6 Panel Fixed Effect Result 

         Table 9. Panel Fixed Effect 
 

Variable Coefficient Std. Error t-Statistic Prob.   

C -2.62E+11 1.66E+11 -1.580263 0.1159 

NDC 0.522071 0.024154 21.61458 0.0000 

MCIP 5.44E+08 2.07E+09 0.262241 0.7935 

INT 2.70E+10 1.23E+10 2.195278 0.0295 



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INF -1.61E+09 2.95E+09 -0.544249 0.5870 

INC 2.62E+09 5.12E+09 0.512333 0.6091 

EXP01 0.377186 0.135740 2.778729 0.0061 

EXCH -2.75E+08 95571584 -2.882570 0.0045 

CM 0.009342 0.084638 0.110371 0.9122 

 Effects Specification   

Period fixed (dummy variables)  

R-squared 0.807372   

Adjusted R-squared 0.748795   

F-statistic 13.78308   

Prob(F-statistic) 0.000000    

Source: Researcher’s computation (2019) 
 

Table 9 revealed the panel fixed effect which showed that the difference in beta coefficient of the variables have 
different contributions to Net Foreign Asset in developing countries. In this result, using the beta coefficient, NFA is negative at 
constant of -2.62 and its P-values were 0.1159. This means that when all variables are held constant, there will be a negative 
variation up to the tune of 2.62 units in NFA which implies that there is insignificant and negative effect of the independent 
variables to NFA at constant. 

The result further showed that the regression coefficient of NDC was 0.522 and its P-value was 0.0000. This implies 
that NDC has positive and significant effect on NFA in developing countries.  The coefficient of MCIP was 5.44 and its P-
values were 0.7935 and this implies that MCIP has a positive and insignificant effect on NFA. The regression coefficient of 
INT in NFA was 2.70 and its P-values were 0.02095.  

The panel fixed effect equation showed that INT has a positive and significant effect on NFA. The regression 
coefficient of INF in NFA was -1.61 and its P-values were 0.5870. The result showed that INF has a negative and insignificant 
impact on NFA. The coefficient of INC was 2.62 and its P-values were 0.6091 and this implies that INC has a positive and 
insignificant effect on NFA. The regression coefficient of EXPT in NFA was 0.377 and its P-values were 0.0061. This showed 
that EXPT has a positive and significant effect on NFA. The regression coefficient of EXCH in NFA was -2.75 and its P-
values were 0.0045. The result showed that EXCH has a negative and significant impact on NFA and the regression coefficient 
of CM in NFA was 0.009 and its P-values were 0.9122. The result showed that CM has a positive and insignificant effect on 
NFA in the developing countries during the study period. 

The result equally revealed that the coefficient of the regression which is the coefficient that depicts the estimated 
coefficient appears to be good while standard error and the values of t-statistic were equally presented in table 4.8. The results of 
other important statistical tools revealed that the coefficient of determination (R2) representing 80.7%, the adjusted R-square 
75.9%, and the entire regression test is statistically significant including the F-test with P-values 0.0000 at 5% significance level.  
 
4.7 Summary and Implication of Findings 
The empirical proof gathered in this study has been to establish the fact that increased domestic credit, exports, and imports 
improves the BOP position contrary to the postulates of the monetary approach to balance of payment theory that increased 
money supply causes a distortion in the balance of payment position of a country. The reason could be the fact that the 
increased domestic credit expansion was able to boost the production, increased domestic output and more demand for inputs 
including imports. So, the economy was able to grow at a rate faster enough to absorb the rate of expansion in the net domestic 
credit which could have led to increased money supply and excess demand for goods and services. 

Furthermore, the increase in exchange rate and inflation worsened the BOP position of these WAMZ countries. 
Normally, exchange rate ought to improve the BOP as it will reflect in currency appreciation, discouragement of imported goods 
and increased demand for domesticated goods.  
 
5. Conclusion and Recommendations 
This study assessed and investigated the impact of the monetary variables on the balance of payments of the West Africa 
Monetary Zone countries. The focus was to investigate the validity of the theoretical proposition of the monetary approach, 
rooted in Polak model, to the theory of BOP in a floating exchange rate system. 

From the study, it has been confirmed to a large extent that the monetary approach is valid in explaining the BOP 
position of the WAMZ countries despite the fact that they are no more operating under a fixed exchange rate system as 
propounded by the theory. The objectives of the WAMI have not been achieved by the member countries, in terms of single 
digit inflation rate, positive real interest rate, real exchange rate stability and efficient level of foreign reserves. 
The study thus recommended that:  



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▪ The attention of the monetary authorities and the government should not only be on decreasing the money supply in 
the economy since an increase in net domestic credits has a positive impact on the net foreign assets provided it is 
channelled towards domestic production. This will eventually have a positive increase on exports and if supported by a 
policy of ban on importation, the BOP position will improve.  

▪ The inclusion of exchange rate in the Polak model is also relevant since it has a direct effect on both imports and 
exports. Out of all the variables examined, exchange rate and net domestic credits have major impacts on the net 
foreign assets, therefore there is need for the monetary authorities and the governments to critically pay attention to 
the movements in exchange rate. Exchange rate adjustment could also be used as a policy tool because of its impact on 
imports, exports and even settlement of external debts 

▪ There is also a need for stability in the economies and for investors not to be scared of investment, the economy need 
to be politically and socially stable. A suitable and positive environment gives birth to thriving investment which in 
turn improves the balance of payment. 

 
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