Long–and Short–Run Determinants of Demand for Money and its Stability in the
Gambia: An Empirical Investigation
Kebba Jammeh
Research Paper submitted in fulfillment of the Honours Requirements for the
Bachelor of Science in Economics
1
Department of Economics and Management Sciences
University of the Gambia
March, 2012
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Approval
I certify that I have supervised this research project and I am of the opinion that it meets the
acceptable standards of scholarly work and is adequate in quantity and quality as a research
project for the fulfillment of Honors requirements for the Bachelor of Science in Economics.
……………………………………………….
Prof. Jan Sture Gunnarsson
(Supervisor)
This research project is submitted to the Department of Economics and Management Sciences
and is accepted as the fulfillment of the Honours Requirements for the Bachelor of Science in
Economics.
………………………………………….
Mohammed Jammeh
Ag. Head of Department of Economics
and Management Sciences
3
Dedication
This thesis is dedicated to my sister, brothers and our parents.
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Acknowledgments
I would like to register my sincere appreciation to my supervisor, Prof. Jan Sture Gunnarsson,
for his wholehearted support and time during the course of writing this Thesis. I am also greatly
indebted to Mr. Yaya S. Jallow whose encouragement and expert advice helped pilot this paper.
Under his tutelage, I had also been inspired towards contributing to the frontiers of knowledge.
I would also like to record my sincere thanks to Dr. Momodou Mustapha Fanneh for his
intellectual and material contributions which supplemented the necessary ingredients to
making this thesis a product of extensive research.
I would specially like to express my profound gratitude to Mr. Bai Madi Ceesay, Mr. Lamin
Camara, Mr. Alhagie Fadera, Mr. Abdou Kadrie Ceesay and Madam Amie Kolleh Jeng for their
understanding and constructive suggestions after reading the first draft of this paper. My
thanks go to Mr. Hassoum Muhammed Loum whose brotherly advice and words of
encouragement made me realized that ‘when the going gets tough, the tough get going’. Very
importantly, my special acknowledgement goes to Mrs. Amie Tunkara, Ms. Saffiatou Sanneh
and Mr. Samba Bah for their support. I would also convey my heartfelt gratitude to Ms. Fatou
Sillah who has helped me a lot in the search for up-to-date and relevant information. I also
gratefully acknowledge the authors of all the articles that provided me a wealth of useful
information and the reliable scientific basis for this paper. Above all, I am grateful to the
Almighty God for His grace, wisdom and knowledge He granted onto me and mostly
importantly for making me know these great people. Words are indeed inadequate for me to
express the enormousity of my oceanic gratitude to all those who have contributed towards the
successful completion of this thesis. May God bless and strengthen you all.
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Abstract
The objective of this paper is to empirically examine the long–and short-run determinants of
demand for money and its stability in the Gambia using quarterly time series data from 1993:I
to 2008:IV. The Johansen cointegration test shows the existence of a long-run equilibrium
relationship between money demand, income, interest rate, inflation rate and exchange rate.
However, the short-run dynamic model did not confirm the existence of this relationship in the
short-run. The estimated long-run money demand function shows that money demand in the
long-run has a positive relationship with income and exchange rate, and a negative relationship
with interest rate and inflation rate. The estimated long-run income elasticity of money
demand is greater than one, which implies that money can be considered a luxury in the
Gambia (Valadkhani, 2008). Furthermore, the ECM model shows that although these variables
are important determinants of money demand in the Gambia in the long-run, they are not
significant drivers of money demand in the short-run. Hence, the transactional, precautionary
and speculative motives of money demand hold in the Gambia only in the long-run. Moreover,
the asset-substitution phenomenon also holds only in the long-run while the currencysubstitution phenomenon does not exist in the Gambia.
The Impulse Response Function (IRF) shows that a percentage increase in real income increases
money demand by 2.4 percent after one year and die down to 2.1 percent in the second year,
while a percentage shock in interest rate reduces money demand by 0.023 percent in the first
year and 0.043 percent in the second year. The error correction factor shows that about 2.9
percent of the disequilibrium in real money demand is corrected by short-run adjustment
within a quarter. Furthermore, the ECM stability test shows that inflation is not purely a
monetary phenomenon in the Gambia because money demand is not stable during the period
under study. Thus, monetary authorities in the Gambia should be flexible in the use of broad
money supply as an intermediate target because money supply targeting may not translate to
changes in interest rates due to the instability of money demand. An alternative policy option
of targeting interest rates rather than money supply may improve the outcome of monetary
policy in the Gambia.
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Table of contents
Approval.................................................................................................................................................. 3
Dedication ............................................................................................................................................... 4
Acknowledgments ................................................................................................................................... 5
Abstract .................................................................................................................................................. 6
List of Figures…………………………………………………………………………………….………………………….…………..9
List of Tables……………………………………………………………………………………….……………………………………10
CHAPTER 1 ............................................................................................................................................ 11
Introduction .......................................................................................................................................... 11
1.1 Background of the study .................................................................................................................. 11
1.2 Problem Statement.......................................................................................................................... 12
1.3 Research Objective .......................................................................................................................... 13
1.4 Significance of the Study .................................................................................................................. 14
1.5 Research Hypotheses....................................................................................................................... 15
1.6 Scope of the Study ........................................................................................................................... 15
CHAPTER 2 ............................................................................................................................................ 16
Literature Review .................................................................................................................................. 16
2.0 Introduction .................................................................................................................................... 16
2.1 Theoretical Framework .................................................................................................................... 16
2.1.1 Quantity Theory of Money Demand........................................................................................ 17
2.1.2 Liquidity Preference Theory of Money Demand ...................................................................... 18
2.1.3 Portfolio Theory of Money Demand........................................................................................ 20
2.1.4 Inventory Theory of Money Demand…….…………………………………………………………………………….….21
2.2 Empirical Evidence ........................................................................................................................... 23
CHAPTER 3 ............................................................................................................................................ 26
Financial Sector Development and Trend Analysis of Board Money Demand in the Gambia ................... 26
3.0 Introduction .................................................................................................................................... 26
3.1 Financial Sector Development.......................................................................................................... 26
3.2 Trend Analysis of Broad Money Demand in the Gambia…………………………………………………….28
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CHAPTER 4 ............................................................................................................................................ 30
Methodology......................................................................................................................................... 30
4.0 Introduction .................................................................................................................................... 30
4.1 Model specification and Definition of Variables ............................................................................... 30
4.2 Dataset and its Source ..................................................................................................................... 31
4.3 Pre-estimation tests: Unit Root and Cointegration Tests .................................................................. 32
4.4 Estimation Technique: Error Correction Model………………………………………………………………..………………34
4.5 Post-estimation techniques: Impulse Response, Variance Decomposition and Stability Tests ........... 35
4.6 Expected Results…………………………………………………..……………………………………………………………36
CHAPTER 5 ............................................................................................................................................ 38
Analysis and Interpretation of Results ................................................................................................... 38
5.0 Introduction .................................................................................................................................... 38
5.1 Unit Root and Johansen Cointegration Tests Results ........................................................................ 38
5.2 Estimated Long-run Money Demand Function ................................................................................. 40
5.3 Estimated Short-run Money Demand Function…………..…………………………….……………………………….......42
5.4 Impulse Response and Variance Decomposition Tests Results………………………………………………..……….43
5.5 ECM Stability Test Result…………………………………………………………………….……………………………………….….45
CHAPTER 6 ............................................................................................................................................ 47
Conclusion and Recommendations ........................................................................................................ 47
6.0 Introduction……………………………………………………………………………………………………………………….……………47
6.1 Conclusion…………………………………….……………………………………………………………………………………47
6.2 Recommendations……………………………………………………………………………………………………………..49
References ............................................................................................................................................ 51
Appendix ............................................................................................................................................... 55
Declaration............................................................................................................................................ 64
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LIST OF FIGURES
Figure A1: Annual Growth Rate and Share in GDP of the Financial Sector in the Gambia…………27
Figure A2: Trend of Broad Money Demand In the Gambia from 1990 to 2010…………………………28
Figure A3: The Graph of Log Real GDP at Level…………………………………………………………………………60
Figure A4: Graph of Interest Rate at Level………………………………………………………………………………..60
Figure A5: Graph of Log Real Broad Money Balance at Level……………………………………………………61
Figure A6: Graph of Inflation Rate at Level……………………………………………………………………………….61
Figure A7: Graph of Log Exchange Rate at level……………………………………………………………………….62
Figure B1: Graph of Cumulative IRF for ECM model…………………………………………………………………63
* Impulse factor= Real income and Response factor= Real money demand
Figure B2: Graph of Cumulative IRF for ECM model…………………………………………………………………63
* Impulse factor= Interest rate and Response factor= Real money demand
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LIST OF TABLES
Table B1: Summary Statistics of the variables in the model……………………………………………………..55
Table B2: Correlation Matrix of the variables in the model………………………………………………………55
Table B3: Augmented Dickey Fuller Test Results………………………………………………………………………55
Table B4: Results from Johansen Cointegration Test………………………………………………………………..56
Table B5: Results from the estimated Long-run money demand function and the Ramsey RESET
Test ……………………………………………………………..…………………………………………………………………..……..56
Table B6: Results of the Lag Selection-order criteria………………………………………………………………..56
Table B7: Regression results of the error-correction model of money demand equation..……….57
Table B8: Result of the cumulative Impulse Response Function and FEVD……….………………………57
*Impulse factor= Real income and Response factor= Real money demand
Table B9: Result of the Cumulative Impulse Response Function and FEVD……………………………….58
*Impulse factor= Interest rate and Response factor= Real money demand
Table B10: Result of Lagrange-multiplier test……………………………….……………………………….…………58
Table B11: Result of Jarque-Bera test……………………………….……………………………….…………………….58
Table B12: Result of Eigenvalue stability condition……………………………….………………………………….59
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Chapter 1
INTRODUCTION
1.1 Background of the study
Studies on the demand for money and its stability has long remained in the domain of rigorous
investigation dating back to the period when it helped in eliminating the problems associated
with the barter system. The demand for money plays a central and very crucial role in
macroeconomic analysis as it serves as the core link between the monetary and the real sector
of an economy. Goldfeld (1994) noted that the relationship between the demand for money
and its main drivers is an important building block in macroeconomic theory and is a crucial
component in the conduct of monetary policy. Theories on the determinants of money demand
and its stability has attracted debates in the academic circle dating back to the period when
Irving Fisher implicitly put forward the earliest theory of money demand in his quantity theory
of money. The stability of the money demand function also has crucial implications on the way
the central bank carries out its monetary policy under a monetary targeting framework. A
stable money demand function is prerequisite for any policy-driven change in monetary
variables to have predictable effect on output, interest rate and ultimately prices through the
transmission mechanism of monetary policy. A stable money demand function also provides
empirical evidence that money supply targeting is an effective monetary policy option to
controlling inflation and effective demand.
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During the last decade, the Central Bank of the Gambia (CBG) has been using various monetary
policy instruments to control inflation and effective demand. The CBG had been following an
interest rate targeting regime by using its Bank Rate as a monetary instrument to control
inflation and effective demand. The CBG reduced the Bank Rate from 29% in 2003 to 9% in
2007, but was raised to 10% at the end of 2007 to check effective demand and inflationary
pressures on the economy. The Bank Rate has since then remained at 10%. However, with the
introduction of the Monetary Policy Committee (MPC) Policy Rate, the Bank Rate has become
ineffective and non-operational. The MPC then started using the CBG rediscount Rate as its
policy instrument. The CBG raised its rediscount rate by one percentage point from 14% to 15%
in June 2007, and further to 16% in October 2008 to counter emerging inflationary pressures on
the economy. The rediscount rate since then remain unchanged until December 2009 when the
MPC reduced it by two percentage points to 14% due to the declining trend of inflation rates.
Currently, the CBG follows a monetary regime using broad money – defined as M21– as the
intermediate target and reserve money as the operating target in order to achieve its policy
objectives which are price stability and real economic growth. The CBG uses control
instruments such as the statutory minimum reserve requirement and open market operations
to regulate the quantity of money in the economy.
1.2 Problem Statement
Controlling inflation to a single digit has long been a policy objective for the Gambian
government. The Government of the Gambia through the Central Bank of the Gambia does
1
M2 is the sum of M1 and Quasi money. While M1 is the sum of currency in circulation outside banks and demand
deposits, Quasi money is the sum of saving deposits and time deposits.
12
alter monetary aggregates to achieve this policy objective. The specification of an appropriate
money demand function is vital in determining the optimum quantity of money to be supplied
in an economy. Effective monetary policy implicitly assumes a stable money demand function.
However, if the relationship is not stable, money supply targeting might not be an effective
policy option for controlling inflation. Thus, the problem of this thesis is to explain the long–and
short-run determinants of money demand and its stability in the Gambia because
understanding the main drivers of money demand is crucial in understanding the transmission
mechanism of monetary policy in the Gambia.
1.3 Research Objectives
The main objective of this thesis is to examine the long–and short-run determinants of broad
money demand and its stability in the Gambia from 1993 to 2008. This is because so far there is
little that is known on the stability and determinants of demand for broad money in The
Gambia. Thus, the fundamental objectives of this paper, among other things, are:
A. To provide an empirical investigation on both the long–and short-run determinants of
broad money demand in the Gambia. This will help to provide answers to vital
macroeconomic questions such as; do changes in real income affect the demand for
money in the Gambia? If yes, what is its magnitude? How does money demand in the
Gambia response to changes in the opportunity cost of holding it? Does the assetsubstitution phenomenon holds in the Gambia? Moreover, how does domestic money
demand adjust when the Dalasi depreciates? Does the currency-substitution
phenomenon or the wealth-effect hypothesis hold in the Gambia?
13
B. To estimate how money demand responds to changes in interest rate and income, since
the sensitivity of money demand in the Gambia to these two variables determines the
slope of the Gambian LM Curve
C. To evaluate the stability of broad money demand in the Gambia during the period under
study. This is because the recession in 2003 was a potential source of money demand
instability as inflation was as high as 20 percent accompanied with a sharp depreciation
of the Dalasi by 100 percent within a year.
D. To provide recommendations that would help improve monetary management in the
country.
1.4 Significance of the Study
A correctly specified money demand function is very important in the determination of the
optimal way in which the Central Bank formulates and conducts its monetary policy to ensure
that it supplies the optimum quantity of money for the stabilization of the economy. Moreover,
the stability of the specified money demand function is also fundamental if monetary targeting
is to have any predictable effect on the ultimate purposes of the policy which are price stability
and real economic growth. Among the importance of this thesis is that it evaluates the stability
of the money demand function which could help to determine if inflation is purely a monetary
phenomenon in the Gambia and to ascertain the effectiveness of monetary policy in the
Gambia as a policy tool. Moreover, the paper will also provide vital information that could help
in tracking both interest rates and money stock. This is essential because it will help in assessing
the impact of monetary policy in the Gambia. Furthermore, this research is significant because
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it will add up to the limited available literature on the Gambian economy and hence will provide
information for those students or researchers who may want to further explore this
relationship in the Gambia.
1.5 Research Hypotheses
The working hypotheses of this paper are presented below and they are differentiated by the
number of asterisks associated with each hypothesis.
H0* Real income has no effect on the demand for money in the Gambia
H0** Interest rate has no effect on money demand in the Gambia
H0*** Inflation has no effect on money demand in the Gambia
H0**** Exchange rate has no effect on demand for money in the Gambia
H0*****Money Demand is not Stable in the Gambia
1.6 Scope of the Paper
Following this Introduction as Chapter 1, Chapter 2 presents a review of literature on both the
theoretical and empirical evidence. Chapter 3 presents the financial sector and a trend analysis
of broad money demand in the Gambia. While Chapter 4 discusses the methodology used in
this study, Chapter 5 presents the analysis and interpretation of the results obtained using the
methodologies mentioned in Chapter 4. Finally, Chapter 6 highlights the conclusion and
recommendations on monetary management in the Gambia.
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Chapter 2
LITERATURE REVIEW
2.0 Introduction
This chapter presents a review of literatures on the theoretical and empirical fronts for both
developed and developing economies as well as the Gambia.
2.1 Theoretical Framework
The theory of money demand has been in the forefront of academic debates for many years.
The earliest theory of money demand was implicitly put forward by Irving Fisher when he laid
the quantity theory of money demand. Fisher (1911) argued that the demand for money is
solely a function of income. Keynes (1936) in his liquidity preference theory of money demand
argued that people demand money for transactional, precautionary and speculative motives.
He argued that money demand depends on both income and interest rate. Portfolio theories of
money demand treat money like any other asset and used the assets’ demand theory to derive
the money demand theory. They argued that people hold money as part of their portfolio of
assets because money offers different combination of risk and return than other assets.
Inventory theories of money demand postulate that money demand for transactional motives
have a positive relationship with income and a negative relationship with nominal interest rate
earned on alternative assets. The Baumol-Tobin model is the most well-known inventory
theoretic approach model. A cursory look at these theories is presented below.
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2.1.1 Quantity Theory of Money Demand
The earliest theory of money demand was implicitly put forward by Irving Fisher when he laid
the foundation of the Quantity Theory of Money. The quantity theory of money demand is
explained using the equation of exchange. According to the old Fisher equation of exchange,
the demand for money in an economy is solely a function of the volume of transaction in an
economy. In other words, people demand money solely for transaction purpose and the more
money people need for transactional purpose, the more money they will demand. This
relationship between money demand and the level of transaction is expressed in the equation
below:
Where,
is the quantity of money balances;
price level and
is the transactional velocity of money;
is the
is the volume of transactions. Fisher (1911) argued that people demand
money only for transactional purpose and the demand for money is inelastic to interest rate
changes. This equation was later modified by the Cambridge School and they presented a
slightly different version of the old equation by replacing
with . The modification is due to
the fact that there is a problem inherent with the original Fisher equation because the number
of transactions in an economy is difficult to calculate. Hence, output
transaction
is used as a proxy for
because the more an economy produces, the more goods and services are bought
and sold. With this modification by the Cambridge economists, the equation of exchange
becomes:
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This equation is transformed into the Quantity Theory of Money Demand by solving for the real
money balance
and thus rewriting the equation as:
Equilibrium in the money market is where the quantity of real money supplied
to the demand for real money balance
and
is also equal to
is equals
which is constant
reflecting institutional and technological features of the economy which are stable in the short
run. This now gives us the quantity theory of money demand as:
Thus, the quantity theory of money demand function shows that the demand for real money
balance is solely a function of real income and this relationship is stable over time.
2.1.2 Liquidity Preference Theory of Money Demand
Keynes in his famous book “The General Theory of Employment, Interest and Money” identified
three motives why people demand money: the transactional motive, the precautionary motive
and the speculative motive. Keynes developed a more general and realistic theory of money
demand than Irving Fisher in his liquidity preference theory. Contrary to Fisher, Keynes believed
that the demand for real money balances depends on both interest rate and income. According
to Keynes (1936), the volume of transactions is positively related with income and if income
increases, the demand for real money balances also increases for transactional and
precautionary motives. Moreover, Keynes argued that money demand for speculative motives
18
is interest rate elastic because interest rate is the opportunity cost of holding money. Hence,
the Keynesian money demand function is expressed as:
According to the model above, the demand for real money balance is a function of income and
nominal interest rate. Money demand is positively related with income and inversely related
with interest rates. Keynes further argued that the velocity of money
is not constant but
instead it is positively related with interest rates which fluctuate considerably.
Moreover, the liquidity preference function implicitly captures the effect of inflation on the
money demand. This can be demonstrated by introducing the Fisher equation, which states
that nominal interest rate is the sum of the real interest rate and expected inflation, into
liquidity preference function. The Fisher effect is written as:
The Fisher equation states that there is a one-to-one relationship between expected inflation
and nominal interest rates. This now gives us the Keynesian money demand function that
captures the effect of inflation on real money demand as:
This equation implies that the demand for real money balance also depends negatively on the
expected rate of inflation. Inflation rate positively influence nominal interest rate and nominal
interest rate is the cost of holding money. This explanation gives us a more sophisticated
explanation of money demand than the quantity demand of money theory because it shows
19
that money demand is an increasing function of income and a decreasing function of both
interest rate and expected rate of inflation.
2.1.3 Portfolio Theories of Money Demand
Portfolio theories of money demand provide a microeconomic explanation of money demand
which emphasize the function of money as a store of value. Portfolio theories of demand for
money emphasize that people hold money as part of their portfolio of assets because money is
one asset among several and it offers a different combination of risks and return than other
assets. Friedman (1956) and Tobin (1958) formulated the most well-Known portfolio theoretic
approach models. Portfolio theories of money demand treat money like any other asset and
used the assets’ demand theory to derive the money demand theory. According to these
theories, the demand for money should be a function of the risk and return offered by money
and by the alternative assets that households can hold instead of money. Moreover, it should
also be a function of wealth, since the size of wealth determines the amount of the portfolio to
be allotted between money and the alternative assets. This version of money demand can be
expressed as:
Where
is the expected return on stock/equity,
expected return on money,
is the expected return on bonds,
is the expected inflation rate and
is the
is the permanent income
which is used as a proxy for wealth. According to portfolio theories, since the demand for assets
increases as wealth increases, the demand for money is also positively related with permanent
20
income because higher wealth means larger portfolio. The three main assets identified by
proponents of portfolio theories of money demand were bonds, stocks and goods; and they
argued that the incentive to hold money depends on the attractiveness of these assets
comparing to holding money. Expected returns on these assets are negatively related with the
demand for money. As
or
increases, money demand declines because it becomes less
attractive to hold money comparing to stock or bond holding. Furthermore, an increase in
expected inflation
also reduces money demand because money became less attractive as its
real value depreciates over time. Mankiw (1997) highlighted that from the viewpoint of
portfolio theories of money demand, the liquidity preference function of money demand is just
a useful simplification of the general theory of money demand because firstly it uses real
income
as a proxy for real wealth
and secondly only the nominal interest rate on money is
included while ignoring the returns on other alternative assets.
2.1.4 Inventory Theories of Money Demand
Another microeconomic theory of money demand is the inventory or transaction theories of
money demand because they emphasize the role of money as a medium of exchange. Inventory
theories of money demand consider the demand for money for transactional motives. The
Baumol-Tobin model is the most well-known inventory theoretic approach model. Baumol
(1952) and Tobin (1956) explicitly formulated a transactions demand for money in an inventory
theoretic approach that provides a microeconomic explanation of money demand by analyzing
the costs and benefits of money holding. The cost of holding money is the forgone interest and
the benefit of money holding is liquidity. According to this theory while agents receive income
21
periodically for instance monthly, they make transactions at a constant rate over the period.
The agent can decide to hold his entire income to make his daily transactions or save his entire
income in an interest-bearing savings account or other interest-earning assets. However, there
is a trade-off between the costs of holding his income – interest cost
cost
– and the transaction
of converting interest-bearing assets into money. Thus, the optimal strategy is to hold a
portion of his income as money and another portion in interest-bearing assets. The BaumolTobin model postulated that the optimal average money demand is given by:
Where;
rate,
is the cost of converting interest-bearing assets into money,
is the price level and
is the nominal interest
is income. Therefore, the Baumol-Tobin model postulates
transactional money demand to have a positive relationship with income and a negative
relationship with nominal interest rate earned on alternative assets. Moreover, the transaction
cost of converting wealth between interest-bearing assets and money also has a positive
relationship with money demand. If transaction cost declines, for example the introduction of
Automatic Teller Machines, more wealth is held in the form of interest-bearing assets and less
in the form of money. Thus, according to the Baumol-Tobin model the income elasticity of
money demand and the interest rate elasticity of money demand are
and – , respectively.
This implies that average money demand should increase by 5 percent when income increases
by 10 percent and average money demand should decline by 5 percent when interest rate
increases by 10 percent. Inventory theories of money demand provide a microeconomic
22
explanation of the liquidity theory of money because they show that money demand is
positively related with income and negatively with interest rates.
2.2 Empirical Evidence
On the empirical front, there is a large body of literature documenting the determinants and
stability of money demand in both developed and developing economies. This large body of
literature on the topic could be divided into two generations. The first generation of this
literature is the pre-1974 literature and the second generation is the post-1974 literature. This
is because the earliest researches on the demand for money that were conducted before 1974
work reasonably well in estimating money demand and they concluded that the money
demand function is stable over time (Tomori, 1972 and Goldfeld, 1973). However, during the
post-1974 era the consensus that the demand for money is stable started to fall apart. In the
United States, the estimated money demand functions over-predicted actual money demand,
M1, which according to Goldfeld (1976) led to ‘the case of the missing money’ because actual
money demand were lower than the estimated money demand. Whereas, the estimated
money demand functions over-predicted actual money demand in the US, money demand
equations under-predicted actual money demand in the United Kingdom (Artis and Lewis,
1974). The break-down of these money demand functions was partly explained by great
financial innovations such as electronic funds transfer which altered the working definition of
money even though the official definition did not change. The 1973 Arab oil embargo resulting
to oil prices hike, higher inflation rates and sharply higher interest rates also contributed to the
instability of such money demand functions.
23
However, currently the stability of money demand remains controversial because different
researchers reached at different conclusions on the stability of money demand in different
economies. Sriram (2009) evaluated broad money demand in the Gambia using an ECM model
and monthly observations from 1988:1 to 2007:2. He found that there appeared to be a longrun relationship between real money balance, real GDP, interest rates on deposits at the
commercial banks, yields on Treasury bill, and expected inflation; but the relationship was not
stable. He argued that foreign-influence variables such as foreign interest rates and expected
depreciation were not significant determinants of real money demand in The Gambia.
Tomori (1972), pioneering empirical estimation of money demand in Nigeria, used OLS and
annual data from 1960 to 1970 and concluded that income is a significant variable that
explained variation in money demand regardless of the definition of money adopted. He
further argued that this relationship is stable by running a separate regression for the period
1960 to 1966, and comparing the coefficients with the coefficients obtained from the full
sample. Akinlo (2006) found that there exist a cointegrating relationship between broad
money, income, interest rates and exchange rates in Nigeria. He further tested the stability of
the function using an Autoregressive Distributed Lags Model (ARDLM) which revealed that the
relationship is somewhat stable. Moreover, Kallon (1992) estimated the money demand
function in Ghana using quarterly data from 1966:1 to 1986:4, and found that the money
demand function in Ghana was stable. On the other hand, Andoh and Chappell (2002)
estimated money demand in Ghana and tested if there was a structural break using annual data
from 1960 to 1996. Their study revealed that there was a structural break of the Ghana’s
money demand function in 1983.
24
Furthermore, Hamori (2008) empirically analyzed the money demand function in the SubSaharan African region using a non-stationary panel data analysis for 35 countries based on
annual data from 1980 to 2005. His findings revealed that there exists a cointegrating
relationship of the money demand function in the Sub-Saharan African region over the period
under study regardless of whether M1 or M2 is used as a measure of money supply. Similarly,
Narayan and Seema (2009) studied the demand for money function from a panel of 5 South
Asian countries using data spanning 1980 to 2000. They found that there exist an equilibrium
relationship between money demand and its determinants both for individual countries and for
the panel. Using diagnostics testing tools, they found that the money demand functions of all
these economies are stable except for Nepal.
Valadkhani (2008) estimated the long- and short-run determinants of money demand in six
countries in the Asian-Pacific region as a function of real income, interest rate spread 2, inflation
rate, real effective exchange rate and the US real interest rate using panel data (1975-2002). He
found that the long-run income elasticity is greater than unity and both the currency
substitution and capital mobility hypotheses hold only in the long run.
From this empirical evidence, it could be seen that variables such as income and inflation rate
are important determinants of demand for money in developing countries while foreign
exchange and foreign interest rates are less important determinants of money demand.
Moreover, the mixed conclusions on the stability of money demand in different economies
might be attributed to the fact that the factors that affects money demand vary in accordance
to the realities of different economies.
2
The difference between the deposit and lending rates
25
Chapter Three
FINANCIAL SECTOR DEVELOPMENT AND TREND ANALYSIS OF BROAD MONEY
DEMAND IN THE GAMBIA
3.0 Introduction
This chapter presents the Gambia’s financial Industry and a trend analysis of broad money
demand in the Gambia between 2000 and 2010.
3.1 Financial Sector Development
The Gambian financial system is small and under-developed. There are no merchant banks; no
stock markets and the capital markets are underdeveloped. Like most nations, the Central Bank
of the Gambia (CBG) is at the apex of the financial system of the country which is the institution
charged with the responsibility of regulating the financial and monetary system in the Gambia.
The sector is dominated by commercial banks, accounting for 97 percent of the sector’s total
assets. The industry continues to show signs of resilience as it recorded an annual growth rate
of 6.4 percent between 2001 and 2010, and contribute on average about 3.2 percent of GDP.
The growth trend of the financial sector and its contribution to GDP from 2001 to 2010 is
shown in Figure A1. From Figure A1, it can be seen that the contribution of the financial sector
to GDP has not been changing much. However, growth in the industry has been volatile with a
sharp growth from 2007 to 2008 which was mainly driven by the influx of commercial banks
into the country during that period.
26
-10
0
10
20
30
Figure A1: Annual Growth Rate and Share in GDP of the Financial Sector in the Gambia
2000
2002
2004
2006
2008
2010
TIME
Annual Growth Rate (%)
Share in GDP (%)
Data Source: Ministry of Finance and Economic Affairs, Republic of the Gambia.
Commercial banking in the country is highly concentrated with the three largest banks
accounting for more than 60% of total assets, although their share has declined over the years.
Despite the large number of commercial banks in the country, financial intermediation is still
low with a loans-to-deposits ration as low as 0.4 which also influences demand for money. This
is because government securities which have low default risk and high yield are very attractive
to commercial banks. In January-June 2010 and 2011, Treasury Bills accounted for 92.3% and
93.0% of Commercial Banks investment respectively (The Gambia Macroeconomic Bulletin,
2011).
27
3.2 Trend of Broad Money Demand in the Gambia
Monetary policy in the Gambia continues to focus on containing inflation at a single digit,
maintaining exchange rate stability and a viable external position. To sustain this single digit
inflation rate target, the CBG target broad money growth at about 12½ percent during 2010 by
limiting reserve money growth to 9.5 percent during the year (The Gambia Macroeconomic
Bulletin, 2011). Figure A2 shows that the growth trend in broad money (M2) has generally been
increasing between 1990 and 2010. On the supply side, broad money supply recorded a growth
of 21 percent in June 2010, compared to 21.2 percent a year ago. This growth was supported by
9.6 percent growth in currency in circulation outside banks, 14.1 percent growth in demand
deposits, 15.9 percent growth in savings deposits and significant growth of 45.3 percent in time
deposits.
0
5000
m2
10000
15000
Figure A2: Trend of Broad Money Demand in the Gambia from 1990 to 2010
1990
1995
2000
time
2005
2010
Data Source: Central Bank of the Gambia
28
On the demand side, this 21 percent increase in broad money supply was substantially driven
by a 5.9 percent growth in net foreign assets and 27.1 percent growth in net domestic assets
over a year. Domestic credits increased by 23.7 percent from D6.9 billion in June 2009 to D8.6
billion in June 2010, sustained by 28.4 percent growth in government borrowing and 29.6
percent growth in credits to the private sector, while credits to public entities declined by 15.8
percent over one year. The increasing trend of broad money demand shown in Figure A2
illustrates that people want to hold more money for their transactional, precautionary and
speculative purposes.
29
Chapter 4
METHODOLOGY
4.0 Introduction
This chapter presents a bird’s-eye view of the model and estimation techniques used in this
paper as well as the dataset and expected results.
4.1 Model Specification and Description of Variables
The general specification of money demand in most macroeconomic literature postulates
money demand as a function of income and interest rates. However, the conventional money
demand function is extended by introducing exchange rate to take account of the currencysubstitution hypothesis and inflation rate to take account of the asset-subsistution hypothesis.
The inclusion of inflation also has its theoretical foundation from the portfolio theoretic
approach models discussed in
. Mundell (1963) also suggested the exchange rates
to be included in the standard money demand function to take account of the currencysubstitution phenomenon. A similar approach was used by Sriram (2009) and Bahmani-Oskooee
and Chi Wing Ng (2002). However, both models were modified by excluding interest rates on
deposits and foreign interest rates from the models of Sriram (2009) and Bahmani-Oskooee and
Chi Wing Ng (2002) respectively. Against this background, this paper postulates an open
economy money demand function which relates real money balance as a function of real
30
income, interest rates, inflation rate and exchange rate, and can be econometrically presented
as:
Where
is real broad money demand,
transactions and precautionary demand for money,
to capture speculative demand for money,
asset-substitution hypothesis and
is the real GDP as a proxy to capture
is the interest rate on T-bills as a proxy
is the inflation rate as a proxy to capture the
is the nominal dollar-to-dalasi exchange rate as a proxy to
capture the currency-substitution phenomenon.
4.2 Dataset and its Source
The dataset used in this paper was obtained from the IMF Statistical Appendix of The Gambia
1990 and 2008 reports and the CBG database. The variables used are nominal broad money
demand (M2), Consumer price index (2004 base period), real GDP at 1974/75 price, 91-Day Tbills rates, CPI inflation rates, and the dalasi-to-dollar exchange rate. The real money demand
was computed by dividing the nominal money demand (M2) with average prices (CPI). M2 was
used as a measure of money demand because according to De Brouwer and Subbaraman
(1993, p.10) a broader measure of money is more appropriate for modeling purposes because
it: a) is less distorted by financial deregulation and innovations; and b) has a more reliable
relationship with income. M2 and GDP are measured in millions of dalasi, interest rates and
inflation rates are in percentage. All variables are at their end period rates. The variables are all
31
in quarterly frequencies except GDP. Hence, the Denton method of disaggregation was used to
convert the annual figures of GDP into quarterly frequencies. The Denton was applied because
it has the ability to disintegrate the annual data into quarterly frequencies in such a way that
the sum of the quarterly frequencies will also be equal to the annual figure. Moreover, the
dataset stretches from 1993 first quarter to 2008 fourth quarter, giving a total of 64
observations.
4.3 Pre-estimation Tests: Unit Roots and Cointegration Tests
Several pre-estimation tests were conducted before undertaking any regression analysis. The
unit root and cointegration tests are very important pre-estimation tests that are often used to
circumvent the inherent limitations of traditional models as well as avoid spurious regression
result (Hendry, 1986).
The objective of these tests is to examine the properties of the time
series used in this paper in order to avoid a nonsensical regression. Nonsense or spurious
regression arises when an OLS regression is estimated with non-stationary variables and
residuals. The Augmented Dickey-Fuller (ADF) test is employed to test whether the variables
used in the estimation are stationarity or not. The test is performed by augmenting each
variable with its lags. The number of lags to be used in all the pre-estimation and estimation
models in this paper is determined by using the Alkaike Information Criterion (AIC). The
maximum lag length is chosen based on the minimum AIC criterion. The ADF test in this study is
conducted by including a constant only and a constant and with a time trend. The test could be
estimated with the following regression:
32
Where
term,
is the individual variable at time ,
is the constant,
,
is a pure white noise error
is the number of lags which should be large enough to ensure that
the error terms are white noise and small enough to save degree of freedom,
variable in quarters and
is the trend
. The equations above are the ADF with a constant and time
trend, and ADF with only a constant. In each case, the null hypothesis is that
; which
means that there is unit root or the time series is nonstationary. The alternative hypothesis is
that
; this means that the variable is stationary, using a Tau ) statistics. At ninety-five
(95) percent confidence level, if the p-value is less than or equals to 0.05, we reject the null
hypothesis otherwise we do not reject the null hypothesis that the variable is nonstationary.
Among the rich menu of pre-estimation techniques, unit root test is the first pre-estimation test
employed in this study because it is prerequisite for cointegration test. Cointegration test is
used to determine if there exists an equilibrium or long-run relationship between two or more
variables. If two or more variables are non-stationary but a linear combination of them is
stationary, then the variables are said to be cointegrated. In this paper, the Johansen
cointegration technique is used to examine the existence of an equilibrium relationship
33
between money demand and its determinants. The Johansen cointegration model is a VARbased test and it is presented as:
is an (n x 1) vector of endogenous variables and
is also an (n x 1) vector of white noise
error term, where n is the number of all the variables used in this paper. The rank of the matrix
coefficient
indicates the long run relationship among the variables. Full rank r = n means that
the variables are cointegrated. Rank r = 0 means that the variables are not cointegrated and
reduced rank where r lies between zero and n means that there are r cointegrating vector
among the variables. According to (Bashier and Dahlan, 2011) this technique is preferred to the
two-step Engle-Granger procedure because it can test for multiple cointegrating vectors.
Johansen developed two test statistics – trace eigenvalue statistics and maximum eigenvalue
statistics. In the trace test, the null hypothesis is that there are r cointegrating vectors and the
alternative hypothesis is there are n cointegrating vectors. On the other hand, the maximum
eigenvalue test tests the null hypothesis of r cointegrating vectors against the alternative
hypothesis of r +1 cointegrating vectors.
4.4 Estimation Techniques: Error Correction Mechanism (ECM)
An ECM model is employed to estimate money demand in the Gambia. The ECM technique has
been the dominant estimation technique used in estimating money demand in most literatures.
Therefore, we estimate money demand and evaluate its stability in the Gambia using a similar
34
technique. An ECM model helps us to study the short-run dynamics in the relationship between
money demand and its determinants. After testing for the existence of a long-run relationship
between money demand and its determinants using the Johansen cointegration test, the error
correction model enables us to reconcile the short-run behavior of money demand with its
long-run behavior. The ECM model is specified as:
Where:
Where
is the error correction term, it is the residual from the cointegrating equation,
is the error correction coefficient and
are the estimated short-run coefficients. The error
correction coefficient works to push short-run money demand disequilibrium back towards its
long-run equilibrium and its shows the speed of this adjustment. Our interest in the ECM model
is the error correction coefficient, the Impulse Response Function (IRF), the Forecast Error
Variance Decomposition (FEVD) and the stability test.
4.5 Post-estimation Techniques: Impulse Response Function, Forecast Error
Variance Decomposition and Stability Test
The post-estimation techniques employed in this paper are the IRF, the FEVD and the stability
test. The IRF measures the percentage change in the response variable due to a percentage
change in the impulse factor. In this paper, the IRF test is conducted using money demand as
the response variable, and income and interest rates as the impulse factors. Hence, the IRF in
this paper measures the percentage change in money demand due to a percentage in either
35
interest rates or income. The FEVD measures the percentage of the variation in the response
factor that is explained by a percentage shock in the impulse. In other words, the FEVD in this
paper measures the percentage of the variation in real money demand that is explained by a
percentage shock in either interest rate or income. The ECM stability test is also very important
in this study. This test was used to determine if the relationship between money demand and
its determinants in the Gambia were stable during the period under study. Rapid expansion of
and innovations in the financial sector, high inflation rate, sharp depreciation of the Dalasi, a
recession or the combination of these factors are factors that might cause money demand
instability. Interestingly, these macroeconomic disequilibria where experienced in the country
during the period under study. For instance during the recession in 2003, inflation was as high
as 20 percent accompanied with a sharp depreciations of the Dalasi by 100% within a year.
4.6 Expected Results
The expected sign and magnitude of the coefficient of the real income (income elasticity of
money demand) has a very interesting meaning. If
applies; if
, then the quantity theory of money
, the Baumol-Tobin inventory theoretical approach is applicable; and if
, money can be considered as a luxury (Valadkhani, 2008). A prior, we expect the sign of
real income to be positive. This is because as real income increases, people demand more
money for their transactional and precautionary motives. We also expect the signs of all the
other explanatory variables except exchange rates to be negative. The coefficient on interest
rate is expected to be negative because it measures the real cost of holding money. If the
interest rates on savings accounts, time-deposits accounts or T-Bills increase, people would be
36
willing to hold less money at their disposal. The magnitude of the coefficient of interest rates
which is the interest elasticity of money demand is also very central in the debate over whether
fiscal or monetary policy is a more powerful policy option in an economy. A low coefficient
implies that monetary policy has a greater effect on output than fiscal policy while a high
coefficient value imply that fiscal policy has a larger effect on output than monetary policy,
ceteris paribus. The coefficient on inflation rate is also expected to be negative since an
increase in inflation reduces the incentive to hold money. The rate of inflation serves as a proxy
to measure the return on real assets as an alternative to holding domestic currency. Nachega
(2001) argued that in developing countries where interest rate ceiling and capital controls
prevail, assets substitution is likely to be between money and physical assets rather than
between money and financial assets. The sign of the coefficient on exchange rates is
unspecified because exchange rate depreciation may increase or reduce domestic money
demand. According to Bahmani-Oskooee and Chi Wing Ng (2002) variation in the foreign
exchange rate may have two effects on domestic money demand, which are the wealth effect
and the currency-substitution effect. Exchange rate depreciation may be perceived as an
increase in wealth by wealth holders in foreign economies which may leads to an increase in
money demand. However, exchange rate depreciation may cause expectation of further
depreciation. This will lead to a reduction in domestic demand of money because people are
given enough reasons to hold less domestic money in order to avoid the associated capital loss.
The sign of the coefficient will eventually be determined by the predominant effect.
37
Chapter 5
Analysis and Interpretation of Regression Results
5.0 Introduction
This chapter deals with the analysis and interpretation of the findings of this thesis. The chapter
is divided into five sections. Section 5.1 reports the results obtained from the pre-estimation
tests. Section 5.2 presents the results of the estimated long-run money demand function. The
results of the short-run money demand function are presented in Section 5.3. Section 5.4 shed
light on the IRF and FEVD results, and Section 5.5 presents the ECM Stability test.
5.1 Unit Root and Johansen Cointegration Tests Results
Before any formal unit root test was conducted, we plotted all the variables used in this paper
in order to have initial glue about the properties of the variables. Figure A3 to A7 [in the
Appendix] show a visual plot of all the variables. The Augmented Dickey-Fuller (ADF) test of unit
root shows that all the variables in the model are stationary at first difference with the
exception of interest rate and inflation rate which were stationary at their levels. The
econometrics result of the ADF test is presented in Table A1. These results show that the null
hypothesis of unit root at level cannot be rejected for money demand; income and exchange
rate at 95 percent confidence level while the null hypothesis of unit root at level for interest
and inflation rates can be rejected. The numbers of lags are included in the estimation in order
to eliminate the possibility of autocorrelation in the error terms.
38
Table A1: Augmented Dickey Fuller Test Results
No. of
Lags
Variables
Intercept Only
Levels
First
Difference
Intercept and Trend
Levels
First
Difference
Log Real M2
5
0.9666
0.0160
0.1726
0.0831
Log GDP
2
0.9981
0.0078
0.4397
0.0114
91-Day T-Bills rate
4
0.0171
0.0000
0.0679
0.0000
CPI inflation rate
2
0.0000
0.0000
0.0596
0.0000
Log Forex
6
0.8268
0.043
0.5446
0.0521
Given that interest and inflation rates are stationary at their levels, and real money demand,
real income and exchange rate are stationary at their first differences, we proceeded to
determine whether there is a long-run cointegrating relationship among these variables. The
trace statistics and the maximum eigenvalue statistics revealed the existence of at least four
cointegrating vectors between real money balance and its determinants. The result is shown in
Table A2.
Table A2: Results from Johansen Cointegration Test
Eigenvalues
(lambda)
.923607
Ho:
rank<= (r)
r
0
H1:
Maximum lambda statistics
(rank<=(r+1))
159.45558
Trace Statistics
(rank<=(p=5))
232.12859
.59072856
1
55.389354
72.673008
.23113812
2
16.296324
17.283655
.01276239
3
.79636058
.98733066
.00307542
4
.19097007
.19097007
39
This signifies that there is a long-run relationship between money demand, income, interest
rate, inflation rate and exchange rate in the Gambia.
5.2 Estimated long-run money demand function
Given the evidence that the variables in the specified money demand model have a long-run
relationship as shown by the Johansen cointegration technique, our next step is to estimate
how the demand for money responds in the long-run to changes in its determinants. The
econometrics result of the estimated long-run money demand function is shown in Table A3.
Table A3: Result of the estimated Long-run money demand function
Number of obs = 63; R-squared = 0.9900; Adj R-squared = 0.9893; Prob > F
= 0.0000
The coefficients of the estimated long-run money demand model are consistent with a prior
expectation and theoretical postulations regarding signs, and they are all statistically significant.
The result shows that a percentage increase in real income will in the long-run increase real
money demand by about 1.823%. Real income has the expected sign; hence it shows that the
transactional and precautionary motives of money demand hold in the Gambia in the long-run.
Its magnitude also has an interesting implication because it indicates that money can be
considered as a luxury in the Gambia because the income elasticity of money demand is greater
than one (Valadkhani, 2008). Interest rates has its expected sign (-0.005) which means that a
40
one percent increase in interest rate will in the long-run lead to a decline in real money demand
by about 0.005%. This effect is statistically significant at 95 percent confidence level and it is
very important because it shows that in the long-run people also hold money in the Gambia for
speculative reasons.
Inflation rate also has its expected sign (-0.013) which shows that a percentage increase in
inflation rate will in the long-run leads to a decline in money demand in the Gambia by about
0.013%. This finding is in conformity with Nachega (2001) who argued that in developing
countries where interest rate ceiling and capital controls prevail, assets substitution is likely to
be between money and physical assets rather than between money and financial assets. This
means that physical assets are substitutes of money in the Gambia and thus, inflation leads to a
shift from money holding to asset holding. Suggesting that demand for money also has
implications for portfolio decisions in the Gambia. The coefficient of exchange rate (0.579)
shows that the currency-substitution phenomenon does not hold in the Gambia. The positive
estimated coefficient on exchange rate is consistent with the fact that depreciation of domestic
currency raises the domestic currency value of an individual’s foreign assets, and if this is
perceived as an increase in wealth, then money demand would increase (Arango and Nadiri,
1981). This means that the wealth-effect of currency depreciation dominates the currency
substitution-effect of currency depreciation in the Gambia in the long-run which postulates that
money demand increases in the Gambia when the dalasi depreciates. The wealth-effect could
be attributed to the fact that remittances play a very crucial role in the Gambian economy. A
depreciation of the dalasi may be perceived as an increase in wealth because it raises the
domestic value of dollar inflows which would increase money demand in the Gambia.
41
An Adjusted R-squared of 0.9893, used to measure the goodness-of-fit of the estimated
model, indicates that the model explain about 99 per cent of the long-run behavior of money
demand in the Gambia. This is similar to the findings of Valadkhani (2008) who also found that
real income, interest rate spread, inflation rate, real effective exchange rate and the US real
interest rate explained about 99 percent of the long-run variation of demand for money in six
Asian-Pacific countries. The Ramsey RESET test was also employed to determine if the model
has omitted a relevant variable and it indicates that the model is correctly specified [Result
shown in the Appendix].
5.3 Estimated Short-Run Money Demand Function
Another experiment in this paper is to examine the short-run dynamics of the variables within
an error correction model (ECM) given the evidence that the variables in the money demand
function model are cointegrated. The ECM model shows how the model adjusts to the long-run
equilibrium implied by the cointegrating equation. The ECM model shows that although the
independent variables used in the model are important determinant of money demand in the
Gambia in the long-run, they are not necessarily important determinants of money demand in
the short-run. The result from the ECM also shows that the error correction mechanism (ECM)
which is the residual from the cointegrating equations has its expected negative sign (.0290569) but statistically insignificant (0.787). The absolute value of the coefficient of the
error-correction term indicates that about 2.9 percent of the disequilibrium in the money
demand function is corrected by short-run adjustment within a quarter. This suggests that
following short deviations, 2.9 per cent of adjustment to the long-run are corrected within one-
42
quarter period either by market mechanism, government intervention or combinations of both.
The coefficient indicates that the speed of adjustment in the money demand function is
relatively low in the Gambia.
The adjusted R-squared of 0.5142, used to measure the
goodness-of-fit of the estimated short-run money demand function, indicates that the model
fairly explain about 51 percent of the short-run behavior of demand for money in the Gambia.
The result is shown in Table B7 [in the Appendix].
5.4 Impulse Response Function and Variance Decomposition Tests Results
The IRF was also implemented to single-out the effect of a percentage change in one of the
impulse factors on the response variable. The IRF test is conducted in this paper using real
income and interest rate as the impulse variables, and real money demand as the response
variable. This is because we want to estimate how money demand responds to changes in both
interest rate and income. These two variables were selected as the impulse factors due to their
strong theoretical backup. From the econometrics result shown in Table A4, the IRF reveals a
positive relationship between money demand and real income, and a negative relationship
between money demand and interest rates. The result shows that a percentage increase in real
income increases money demand by 2.4 percent after one year and die down to 2.1 percent in
the second year. Furthermore, the IRF also reveals that a percentage increase in interest rate
reduces money demand by 0.023 percent after one year and 0.043 percent in the second year.
The relative small change in real money demand due to a percentage change in interest rates
give evidence that domestic assets holders in the Gambia still prefer to hold money to
43
themselves rather than investing in interest bearing monetary assets which is attributed to the
cash-based nature of the Gambian economy.
Table A4: Result of the Cumulative Impulse Response Function
Step
Real Income
Interest Rate
0
0
0
1
.881385
-.000622
2
.375368
-.006525
3
.563695
-.016104
4
2.4492
-.022739
5
3.07514
-.026437
6
2.7019
-.03063
7
2.18506
-.036375
8
2.10806
-.042618
From the reported results shown in Table A5, the FEVD was also used to measures the
percentage of the variation in money demand that is explained by a percentage shock in either
income or interest rate. The FEVD result shows that 8.1 percent of changes in real money
demand are explained by a percent change in real income after one year and this diminishes to
6.7 percent after two years. The FEVD result also illustrates that 0.8 percent of changes in real
money demand are explained due to a percent change in interest rate in the first year and this
lessen to 0.5 percent in the second year. The relatively small proportion of the variation in
money demand that is explained by a percentage shock in interest rates is attributed to the
cash-based nature of the Gambian economy.
44
Table A5: Result of the Forecast Error Variance Decomposition
Step
Real Income
Interest Rate
0
0
0
1
0
0
2
.001439
.000737
3
.030066
.000966
4
.081423
.008145
5
.080092
.008221
6
.068097
.006539
7
.06435
.005601
8
.06765
.00512
The Lagrange-multiplier (LM) test was also employed to determine the presents of serial
autocorrelation between the residual. As shown in Table B10 [in the appendix], there is no
serial autocorrelation between the residual at any lag, up to lag two. Based on the Jarque-Bera
(JB) normality test, multivariate normality of all the variables in the model cannot be rejected.
5.5 ECM Stability Test Result
The ECM Stability test was also used to find out if demand for money is stable in the Gambia
during the period under study. As shown in Table B12 [in the Appendix], the stability test shows
that the relationship between demand for money and its determinants was not stable in the
Gambia during the period under study which is consistent with the conclusion of Sriram (2009).
The instability of the money demand function implies that inflation is not purely a monetary
phenomenon in the Gambia. EMPU (2009) found that inflation in the Gambia is not purely a
45
monetary phenomenon because money supply is not an important determinant of inflation.
Thus, the instability of the money demand function found in this paper shows that money
supply targeting is not a reliable policy option to controlling inflation since shocks in money
demand also influence the LM curve which destabilizes money supply targeting. The instability
of the money demand function could not also be associated with macroeconomic disequilibria
in 2003 when inflation was as high as 20 percent accompanied with a sharp depreciation of the
Dalasi by 100 percent within a year. This is because a dummy variable was used to test
whether there was a structural break in 2003 but we found out that demand for money was
instable prior to and after 2003.
46
Chapter 6
Conclusion and Recommendations
6.0 Introduction
This chapter is divided into two sections. Section 6.1 presents the conclusion and Section 6.2
highlights the policy recommendations based on the findings highlighted on this Thesis.
6.1 Conclusion
A correctly specified money demand function is very important in the determination of the
optimal way in which the central bank formulates and conducts its monetary policy, whether it
follows a monetary regime of money supply targeting or interest rates targeting. The stability of
money demand is prerequisite for any policy-driven change in monetary variables to have
predictable effect on output, interest rate and ultimately prices through the transmission
mechanism of monetary policy. This paper examines the long–and short-run determinants of
money demand and its stability in the Gambia using quarterly time series data from 1993:I to
2008:IV. The Augmented Dickey-Fuller test clearly indicated that all the variables in the
specified money demand function are stationary at first difference except interest rate and
inflation rate which were stationary at their levels. The Johansen cointegration test shows that
there is a long-run equilibrium relationship between real money demand, real income, interest
rates, inflation rate and exchange rate in the Gambia. The estimated long-run money demand
function shows that money demand in the long-run have a positive relationship with income
and exchange rate, and a negative relationship with interest rate and inflation rate. The
47
estimated long-run income elasticity of money demand is greater than one, which implies that
money can be considered a luxury in the Gambia. Moreover, the error correction model which
captures short-run dynamics of money demand shows that although these variables are
important determinant of money demand in the Gambia in the long-run, they are not
significant determinants of money demand in the short-run. Hence, the transactional,
precautionary and speculative demand of money holds in the Gambia only in the long-run.
Likewise, the asset-substitution phenomenon also holds only in the long-run, which implies that
domestic assets holders in the short-run do not view holding of real assets as an attractive
alternative to monetary assets during periods of high inflation but as time passes by they tend
to modify this view and start to view real assets holding as an attractive alternative to monetary
holding because of the inflationary psychology developed. The insignificant effect of interest
rate on money demand is evidence that domestic assets holders in the Gambia still prefer to
hold money to themselves rather than investing in interest bearing monetary assets which is
attributed to the cash-based nature of the Gambian economy. In addition, the currencysubstitution phenomenon does not hold in the Gambia. The wealth-effect of currency
depreciation dominates the currency substitution-effect of currency depreciation in the Gambia
in the long-run which might have arisen due to the crucial role remittances play in the Gambian
economy. Thus, to answer the working hypotheses of the thesis presented in Section 1.5 of the
Introduction, we conclude that real income, interest rate, inflation and exchange rate have
effect on demand for money in the Gambia. Moreover, demand for money is not stable in the
Gambia.
48
Furthermore, the error correction factor shows that about 2.9 percent of the disequilibrium in
money demand is corrected by short-run adjustment within a quarter. This suggests that
following short deviations, 2.9 per cent of adjustment to the long-run are corrected within onequarter period either by market mechanism, government intervention or combinations of both.
The Impulse Response Function shows that a percentage increase in real income increases
money demand by 2.4 percent after two years while a percentage increase in interest rate
reduces money demand by 0.043 percent after two years. Moreover, the ECM stability test
shows that money demand is not stable in the Gambia during the period under study. Hence,
the Central Bank of the Gambia should be flexible in the use of broad money supply as an
intermediate target because money supply targeting may not translate into changes in interest
rates due to the instability of money demand.
6.2 Recommendations
Based on the specified money demand function, in conducting monetary policy in the Gambia,
monetary policy makers in the Central Bank of the Gambia (CBG) should consider real income,
interest rate, inflation rates and exchange rates as key policy factors. Monetary authorities
should also be cognizant of the fact that inflation is not purely a monetary phenomenon in the
Gambia because the money demand function is not stable. Thus, a monetary policy which only
targets money supply is not a reliable policy option to controlling inflation because money
supply targeting may not translate into changes in interest rates due to adjustments or the
instability of money demand a phenomenon which could be associated with Keynes’s liquidity
traps. The CBG should therefore adopt an interest rate targeting regime because interest rate
49
targeting is an alternative policy option that could improve the outcome of monetary policy in
the Gambia. Paul Samuelson in support of this approach noted that “God gave us two eyes so
we can keep one on the money supply and the other on interest rate”. In interest rate
targeting, the CBG should use instruments of monetary policy to set interest rates at levels that
it deems would be consistent with low inflation and continued economic growth. However, the
CBG should be aware that there is no straight - Jacket policy instrument to control inflation and
effective demand and should use a mixture of policy options in conducting monetary policies.
50
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54
APPENDIX
PART A1
Table B1: Summary Statistics of the variables in the model
Variable
Log Real M2
Log GDP
Interest rate
Inflation
Log Forex
Obs.
64
64
64
63
64
Mean
36.49258
-.4606271
16.95516
1.314513
2.76691
Std. Dev.
21.6073
.2025934
5.383732
2.022264
.4665733
Min
13.21817
-.727833
12
-4.84386
2.174752
Max
81.68407
-.0575475
31
5.910915
3.509454
Table B2: Correlation Matrix of the variables in the model
Log Real M2
Log GDP
Interest rate
Inflation rate
Log Forex
Log Real M2
1.0000
0.9777
0.1693
0.1420
0.8837
Log GDP
Interest rate
Inflation
Exchange rate
1.0000
0.1126
0.1685
0.8698
1.0000
0.3031
0.4907
1.0000
0.2984
1.0000
Table B3: Augmented Dickey Fuller Test Results
No. of
Lags
Variables
Log Real M2
Log GDP
91-Day T-Bills rate
CPI inflation rate
Log Forex
5
2
4
2
6
Intercept Only
First
Levels
Difference
0.9666
0.0160
Intercept and Trend
First
Levels
Difference
0.1726
0.0831
0.9981
0.0171
0.0000
0.8268
0.4397
0.0679
0.0596
0.5446
0.0078
0.0000
0.0000
0.043
0.0114
0.0000
0.0000
0.0521
55
Table B4: Results from Johansen Cointegration Test
Eigenvalues
(lambda)
Ho:
rank<= (r)
r
0
1
2
3
4
.923607
.59072856
.23113812
.01276239
.00307542
H1:
Maximum lambda statistics
(rank<=(r+1))
159.45558
55.389354
16.296324
.79636058
.19097007
Trace Statistics
(rank<=(p=5))
232.12859
72.673008
17.283655
.98733066
.19097007
Table B5: Results from the estimated Long-run money demand function and the Ramsey
RESET Test
Real M2
Coef.
Std. Err.
T
P>t
Log GDP
Interest rate
Inflation rate
Log Exchange
rate
_cons
F( 4, 58) =
1439.08
1.822544
-.0049575
-.0127306
.5794709
.1177146
.0024716
.0042127
.0585384
15.48
-2.01
-3.02
9.90
0.000
0.050
0.004
0.000
2.754004
.1825855
Prob > F R-squared
= 0.0000
0.9900
[95%
Interval]
1.586913
-.0099049
-.0211632
.4622935
15.08
0.000
2.38852
= Adj
R- Number of obs = 63
squared =
0.9893
Conf.
2.058176
-.0000102
-.0042979
.6966483
3.119489
* significant at 5 percent
Results for Ramsey RESET Test
Ramsey RESET test using powers of the fitted values of lpm2
Ho: model has no omitted variables
F(3, 55) =
31.61
Prob > F =
0.0000
Table B6: Results of the Lag Selection-order criteria
Lag
0
1
2
3
LL
-252.265
62.0496
121.914
158.714
LR
Df
P
0.000
0.000
0.000
FPE
.069631
2.8e-06
6.4e-07
3.2e-07
AIC
8.68695
-1.42541
-2.91233
-3.61744
HQIC
8.74194
-1.1505
-2.41749
-2.90267
628.63
119.73
73.602
16
16
16
4
182.431
47.433*
16
0.000
2.6e-07*
-3.87902*
-2.94432*
SBIC
8.8278
-.721161
-1.64468
1.78639*
-1.48457
56
Table B7: Regression results of the error-correction model of money demand equation
Coef
-.0290569

-.3553059
-.4951452
-.2673922
.8125127
-.9739894
1.433838
-.000591
-.0031625
-.0019006
-.0142546
-.0001515
-.0026822
.2924242
.4008054
.0395493
cons
.0378087
Log likelihood = P>chi2=
273.0351
0.0003
Std. Err.
.1077249
.194202
.1674684
.1683449
2.368355
4.118918
2.570943
.0052543
.0052938
.0052416
.0216771
.0242572
.0049296
.1579699
.1618347
.1710921
.0148168
Rsq=0.5142
Z
-0.27
-1.83
-2. 69
-1.59
0.34
-0.24
0.56
-0.11
-0.60
-0.36
-0.66
-0.01
-0.54
1.85
2.48
0.23
2.55
chi2=
44.45388
P>|z|
[95% Conf. Interval]
0.787
-.2401939 .1820802
0.067
-.7359348 .025323
0.003
-.8233772 -.1669133
0.112
-.5973423 .0625578
0.732
-3.829379 5.454404
0.813
-9.04692
7.098942
0.577
-3.605118 6.472794
0.910
-.0108891 .0097072
0.550
-.0135381 .0072131
0.717
-.0121739 .0083727
0.511
-.056741
.0282318
0.995
-.0476948 .0473918
0.586
-.0123441 .0069797
0.064
-.0171911 .6020395
0.013
.0836152 .7179956
0.817
-.2957851 .3748837
0.011
.0087683 .0668491
AIC=
- SBIC
HQIC
6.238479
=
- =
3.104567 5.015127
Table B8: Result of the cumulative Impulse Response Function and FEVD
Step
(1)
(1)
Cirf
Fevd
0
0
0
1
.881385
0
2
.375368
.001439
3
.563695
.030066
4
2.4492
.081423
5
3.07514
.080092
6
2.7019
.068097
7
2.18506
.06435
8
2.10806
.06765
*Impulse factor= Real income and Response factor= Real money demand
57
Table B9: Result of the Cumulative Impulse Response Function and FEVD
Step
(1)
(1)
Cirf
Fevd
0
0
0
1
-.000622
0
2
-.006525
.000737
3
-.016104
.000966
4
-.022739
.008145
5
-.026437
.008221
6
-.03063
.006539
7
-.036375
.005601
8
-.042618
.00512
*Impulse factor= Interest rate and Response factor= Real money demand
Table B10: Result of Lagrange-multiplier test
Lag
chi2
1
22.6533
2
24.4559
H0: no autocorrelation at lag order
Df
25
25
Prob > chi2
0.59780
0.49317
Table B11: Result of Jarque-Bera test
Equation
chi2
Df
Prob > chi2
D_lpm2
0.335
2
0.84590
D_lgdp
2.280
2
0.31978
D_irate
173.994
2
0.00000
D_infl
5.651
2
0.05927
D_lforex
39.619
2
0.00000
ALL
221.879
10
0.00000
58
Table B12: Result of Eigenvalue stability condition
Eigenvalue
Modulus
1
1
1
1
1
1
1
1
7053378 + .3536431i
.789028
.7053378 - .3536431i
.789028
.7477387 + .1018127i
.754638
.7477387 - .1018127i
.754638
.3533548 + .6576239i
.746545
.3533548 - .6576239i
.746545
-.07562946 + .7384904i
.742353
-.07562946 - .7384904i
.742353
-.6861313 + .129883i
.698316
-.6861313 - .129883i
.698316
-.3672004 + .4458319i
.577583
-.3672004 - .4458319i
.577583
-.4065421 + .1694841i
.440456
-.4065421 - .1694841i
.440456
.1563731 + .3582525i
.390893
.1563731 - .3582525i
.390893
The VECM specification imposes 4 unit moduli.
59
PART A2
-.4
-.6
-.8
1993q1
1997q1
2001q1
year and quarter
2005q1
2009q1
15
20
25
30
Figure A4: Graph of Interest Rate at level
10
lrgdp
-.2
0
Figure A3: The Graph of Log Real GDP at level
1993q1
1997q1
2001q1
year and quarter
2005q1
2009q1
60
3.5
2.5
3
lrm2
4
4.5
Figure A5: Graph of Log Real Broad Money Balance at level
1993q1
1997q1
2001q1
year and quarter
2005q1
2009q1
2005q1
2009q1
-4
-2
0
infl
2
4
6
Figure A6: Graph of Inflation Rate at level
1993q1
1997q1
2001q1
year and quarter
61
2
2.5
lforex
3
3.5
Figure A7: Graph of Log Exchange Rate at level
1993q1
1997q1
2001q1
year and quarter
2005q1
2009q1
62
PART A3
Figure B1: Graph of Cumulative IRF for ECM model
orderb, lgdp, lpm2
3
2
1
0
0
2
4
6
8
step
Graphs by irfname, impulse variable, and response variable
* Impulse factor= Real income and Response factor= Real money demand
Figure B2: Graph of Cumulative IRF for ECM model
orderb, irate, lrm2
0
-.01
-.02
-.03
-.04
0
2
4
6
8
step
Graphs by irfname, impulse variable, and response variable
* Impulse factor= Interest rate and Response factor= Real money demand
63
Declaration
I declare that this research project is the outcome of my own investigations, except where
otherwise stated. Other sources are acknowledged by footnotes giving explicit references.
Kebba Jammeh
Signature: …………………
Date: …………………….
64