A stable money demand function as noted above is crucial for the conduct of efficient and effective monetary policy since it helps policy-analysts in ascertaining the liquidity needs of a given economy·at any point intime. As a result of this, a number of studies have been geared towards understanding the factors that affect the demand for money and its stability over time.
For the purpose of this study, the literature review will pay particular attention to developing countries that share similar demographie and economie characteristics with The Gambia.
However, studies done in other places will also be reviewed especially if the quantification method adopted is robust and hence capable of giving reliable estimates.
J eroen J.M.Kremers and Timothy D. Lane estimating the demand for narrow money in the European Monetary System in 1990 used real income, inflation, interest rate and the exchange rate of the European currency unit vis-à-vis the U.S.$. The long-run relationship between the variables was stable and well determined: a unit income elasticity, negative elasticities with
strength of the ex change rate. Short-run fluctuations in the demand for real money could also be expressed as a stable function of changes in real income, changes in interest rates, and disequilibrium feedback from deviations of the real ERM money stock from its desired long-run position. An interesting feature of their model was the relatively rapid elimination of such disequilibria as opposed to findings of prior works on individual countries, which found slow er adjustment response-- theoretically implausible. If this could be confirmed by other robust analyses, it would be a strong case for monetary integration, as the policy implication is that management of monetary po licy would be more effective in the group than each of the countries taken in isolation. The efficacy of monetary control and hence inflation in the CF A zone countries seems to lend sorne support to their hypothesis /finding. Their money demand function is specified below:
M1 = f (TI, RS, LR, e, GDP) where
M1 =real demand for narrow money TI = Rate of inflation
RS = short-term interest rate.
e = nominal exchange rate
GDP = real gross domestic product LR = long -term interest rate
Their justification for using the short term interest rate was that since M1 was held largely for transactionary purposes, the time horizon relevant for decision regarding the amount held should as a matter of fact be short. Consequently, the long-term interest rate was later dropped from the madel, resulting in better results. The consumer priee index was used to deflate nominal money and also to find. the rate of inflation. The government bond yield was also taken as a measure of long-term interest rate and used in a second equation.
They first determined whether the residuals from the static regression (on the levels) of the ERM money stock (M1) on the general priee level (Il), real GDP, the interest rate (RS) and the exchange rate (e), were stationary. According to the authors, the main idea behind cointegration is simply to study the behaviour of variables moving apart in the short-run but brought together again by market forces or government po licy, or a combination of bath, in the longer-run. It is noted that, a set' of variables each 1 (1 ), is cointegrated if a linear combination of them is 1 (0) i.e.
if they move together in the long-run.
Following the procedure recommended by Engle and Granger (1987), the lagged residuals from the equation of the levels, called EC1_1, was included in a dynamic madel (the error-correction madel) as a representation of feedback toward the long-run money demand equilibrium. As noted earlier, the coefficient on the error-correction feedback term was found to be large (-0.95) compared with estimates of earlier econometrie work on individual countries. It implies a mean lag of about one month in the response of real money balances to real incarne, indicating more rapid adjustment at the ERM level than usually found at the national level. Even though this
study was done in industrialized country-situations, it is relevant in terms of the methodological approach adopted, which this study intends to replicate.
In his study in Kenya in 1992, Oshikoya also estimated the demand for money function in order to determine the role of the real interest rate. The real demand for money was regressed on real GDP; real deposit rate, ratio ofprivate investment to GDP and the demand for money lagged one period. This function was used to test the validity of the hypothesis that high real interest rates increased the incentives to save by means of bank deposits and also the complementarity between money and capital.
To sum up, it can be said that the estimated result on savings rate provided a mild support for the financial liberalization hypothesis i.e. an increase in the real deposit rate raises the saving rate.
The demand for money function, which was included because of the postulate that higher real interest rates increase the incentive to save by means of bank deposits, showed a negative and statistically insignificant sign for the period of study. He found that higher real interest rates increase the availability of domestic credit in banks by regressing the ratio of credit to the private sector to GDP on deposit rate, logarithm of real per capita income and lagged value of credit.
The result showed that real deposit rate exerts a small and positive, but insignificant correlation with credit.
A study conducted in Kenya that is more useful and applied recent econometrie technique was that of Christopher S. Adam in September 1992. The period covered the second quarter of 197 4 to the second quarter of 1989 and the stability of the demand for narrow mo ney was tested over the sample period. The cointegration approach was also adopted by the study and the coefficients
were estimated using Ordinary Least Squares technique. He also used the real interest rate, GDP, the real exchange rate and the lagged dependent variable. Adam was able to demonstrate that the slight parameter instability revealed in the recursive plots were not very significant. He concluded in the following modest words "in the spirit of the methodology described here we conclude by leaving the model a hostage to fortune. The adequate performance of this specification against such a battery of diagnostic tests is a necessary, but not sufficient condition for accepting the model. These tests are simply designed criteria, and ultimately the model can be maintained only to the extent that it continues to explain out-of-sample data and to encompass rival models "(Adam 1992,P.42)7
In 1995, Peninah W. Kariuki also investigated the impact of interest rate liberalization on financial savings in Kenya from the period 1968-1990 for M2 and 1973-1990 for the M3 definition. The money demand function was specified in the following logarithmic form:
LnMt = b0+ b1l~Yt + b2lndt + b3lnpinv + b4lnMt-l +Ut
where
Mt= real broad money (m2) Y =real GDP
pin v = ratio of private investment to GDP d = real deposit rate
Mt_1= lagged dependent variable, and ut= error term
7 AERC Special Paper 15, 1992
The inclusion of real GDP derives from the monetary theory, which postulates that the demand for desired real money balances is a positive function of a scale variable like real income, while the other variables derive from the Mckinnon-Shaw hypothesis. The impact of the real deposit rate was found to be negative and insignificant while real GDP was found to exert a very significant positive impact on the demand for real money balances. When the broader definition ofmoney was introduced i.e. adding non-bank financial institutions (NBFis) deposits to M2, the real interest rate impact became positive but still insignificant.
Kariuki concluded that in the 1980s in Kenya, sorne fiscal policies as well as the depreciation of the shilling could have discouraged domestic savings. He went further to explain that interest income earned on deposits with commercial banks, NBFis and building societies remained liable to tax and this effectively reduced the real return to savers. Again the depreciation of the shilling against the major hard currencies meant that the increases in deposit rates were not high enough to encourage saving domestically. He suggested that sorne other determinants, perhaps even non-economie facto'rs might have been downplayed in the model. However, the coefficient of determination of 97% suggests a high explanatory power of the variables used and as such we suspect spurious correlation. Applying stationarity and cointegration tests could have given better and more reliable estimates.
Rungsun Hataiseree and Anthony Phipps (1996) of the University of Sydney did a study on the relationship between money and income using both the M1 and Mz defmitions of the latter. Their study was also inspired by the belief that structural changes in many economies during the 1980s, particularly financial deregulation, cast doubt on the interpretation of monetary
39
aggregates and their relationship with economie activity. These developments created considerable debate about the stability and predictability of the money supply-income relationship, and caused many central banks to de-emphasize monetary aggregates and rely on a
wider range of variables as indicators of monetary policy (Hataiseree and Phipps, 1996, p.389).
Monetary aggregates were used as intermediate targets and indicators ofmonetary policy.
However, they believed that the financial innovation and deregulation of the late 1980s in Thailand might have affected the behaviour of the money-income relationship. They also employed cointegration and error correction models.
A series of studies were conducted in Pakistan in arder to determine the key variables that explain the demand for money. However, these earlier studies paid less attention to testing the stability of the money demand function. Only Khan (1980, 1982a) and Ahmed and Khan (1990) have examined the stability of the function using the Chow test and varying parameter technique respectively. Khan (1980, 1980a) using the Chow test and covering the period 1959/60-1977178 in Pakistan, found the money demand function to be stable over the period. On the other hand, Ahmed and Khan (1990) employing the varying parameter technique over the period 1959/60-1986/87 found the money demand function to be stable till 1980/81, but became unstable thereafter. Their conclusion was that the instability might have been due to the institutional changes in the banking sector such as the introduction of partial interest-free banking and the change in the exchange rate regime from fixed to dirty floating during the early 1980s. Even though they made very useful attempts, their failure to test the stationary properties of the time-series data was a major shortcoming. It has now become widely accepted that most time-series
data used in economie analysis are non-stationary in nature. A regression of one non-stationary series on another can give rise to spurious correlation/regression problem leading to incorrect statistical inferences8. The non-stationarity problem can be resolved by differencing the data, but in so doing, one may lose potentially interesting information about the long-run equilibrium relationship between economie variables. As a result of this, the study conducted by khan and S.S. Ali, which made great strides in surmounting this problem, is to be preferred and served as a major source of inspiration for this study.
Khan and Ali (1997) took advantage of recent advances in the area of time series analysis, development of new dynamic modeling approach, encapsulated in the cointegration and error correction models. The basic idea of cointegration is that if two or more variables are cointegrated then it confirms the existence of a long-run relationship between these variables and that the variables can be legitimately used in an error correction model. They estimated the demand for money function in Pakistan by employing cointegration and error correction models from the period 1972 to 1992. They used the two monetary aggregates (M1 and M2 definitions) as dependent v~ables and real incarne, real and nominal interest rates, and the inflation rate as explanatory variables. The Dickey-Fuller (DF) and Augmented Dickey-Fuller (ADF) tests were used which showed that all the variables were integrated of order one. It should be noted that all the variables were in logarithmic form. Having established the order of integration, they proceeded to test for cointegration using the Engle-Granger approach. The results showed that changes in the financial sector have rendered the narrow monetary aggregate unstable and unpredictable in the long-run. On the other hand, broad monetary aggregate exhibited stable
8 For more theoretical postulates on this phenomenon, see technical annex 2 41
long-run relatio~ship with real income, real interest rate and inflation. They did not also find any short-run deviations from the long-run path for broad money during 1972-1992. Their conclusion was that the structural changes in the financial sector after 1989, especially interest rate liberalization, did not affect the stability of the broad monetary aggregate, perhaps because the move from one financial regime to another was more cautious and graduai. The policy implication, according to their findings and interpretation, was that M1 may not be used for policy purposes, rather the Bank of Pakistan should concentrate on the use of M2 as a policy variable. Another policy implication was that the process of financial liberalization, which started in 1989, should proceed at a moderate pace in order not to render the money demand function unstable.
The income elasticity ofbroad money demand, the study found, was in the neighbourhood of 1.1 which suggests that the demand for money has been rising at a rate more or less proportional to the changes in income growth. The coefficient of the real interest rate was very low, positive but significant. According to them, the positive sign of the real interest rate was an indication that the Pakistani economy had experienced financial repression during the sample period. The rate of inflation was statistically significant with the expected negative sign.
CHAPTER THREE
METHODOLOGY
3.0 Introduction
In this chapter we present the specification and estimation of the demand for money and the real domestic savings functions in order to investigate the effect of the real interest rate on each of the functions from the period 1973 to 1997. We begin by testing the time series data for all the dependent and explanatory variables to establish first of all the order of integration of the series as elaborated upon below.