TeachersFirst - an Edutech Presentation at TEDx Lagos by Chinenye Mba-Uzoukwu
Thesis
1. UNIVERSITY OF ZIMBABWE
FACULTY OF SOCIAL STUDIES
DEPARTMENT OF ECONOMICS
DISSERTATION TOPIC:
DETERMINANTS OF DOMESTIC SAVING IN ZIMBABWE: A MACROECONOMIC
ANALYSIS (1980-2008)
SUBMITTED BY:
TAFADZWA TOMU
(R117815N)
THIS DISSERTATION WAS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS OF THE BACHELOR OF SCIENCE HONOURS DEGREE IN
ECONOMICS
APRIL 2015
2. i
DEDICATION
I dedicate this dissertation to my father in heaven (JEHOVAH and his son JESUS CHRIST) for
his wisdom, knowledge and power of life to complete this project. To my parents (Mr Brilliant
Tomu and Mrs Selina Tomu) for their love, financial, and spiritual support. To my siblings
Blessed, Tinashe, Vimbai, and Kupakwashe for their spiritual support and believing in me.
3. ii
ACKNOWLEDGEMENTS
I would like to express my profound gratitude to my supervisor Mrs E Rwavheya (Depart of
Economics: UofZ) for her unconditional and interminable supervision notwithstanding her
busy schedule. She played a pivotal role in laying the foundation of this research work and
heightening my self-esteem until the completion of this dissertation. Mr D Ndedzu (Depart of
Economics: UofZ) who gave me mettle and helped to produce a presentable piece of work
through his rich ideas and the entire department personnel for their invaluable support through
out the whole BSc. Hons. Progamme, l candidly thank you!
I extend my earnest gratefulness to friends who are numerous to mention by names, and the
Tomu family who gave me the audacity, prodigious ideas and financial sustenance to produce
this satisfactory piece of work. I am greatly indebted to my fellow students/friends: Trevor
Tinarwo, Tinotenda Bvumai, Wayne Mhishi, Gabriel Kunguma, Caleb Ndedzu and the rest of
the 2014 Economics students who provided me with much needed data in this project. Last but
not least, thanks to ZAFM (Kuwadzana Branch) for their prayers and support. Thanks guys!
May God Bless You All!!
Tafadzwa Tomu
University of Zimbabwe
April 2015
4. iii
ABSTRACT
The study examined the determinants of domestic saving in Zimbabwe for the period between
1980 and 2008 using an Ordinary Least Square technique (OLS). The results showed that four
out of five examined dependent variables were significant. Gross domestic product (GDP)
growth and financial liberalisation were found to be statistically significant and positively
affecting domestic saving. Contrary to the McKinnon-Shaw (1973) hypothesis and the Buffer
stock (1992) model of saving, both depositor’s interest rate and unemployment were found to
be statistically significant, however, with negative impact on domestic saving. Population
growth was found to be statistically insignificant in the model. From this study it was
recommended to maintain manageable interest rates by monitoring inflation rate in real terms.
The researcher also suggested for the alleviation of financial restrictions and deregulation of
interest rates while ensuring reasonable bank charges. The study showed that there is need for
the government to formulate policies that will reduce formal unemployment as well as
introducing long-term profitable projects that will enhance people’s incomes, which will
subsequently increase prospects for saving.
5. iv
Table of Contents page
CHAPTER ONE ......................................................................................................................1
Introduction and Background ................................................................................................1
1.0 Introduction......................................................................................................................1
1.1 Background of the study..................................................................................................2
1.2 Problem statement............................................................................................................4
1.3 Objectives of the research................................................................................................4
1.4 Research questions...........................................................................................................5
1.5 Hypotheses of the study...................................................................................................5
1.6 Justification of the study..................................................................................................5
1.7 Organisation of the study.................................................................................................5
CHAPTER TWO .....................................................................................................................6
Literature Review ....................................................................................................................6
2.0 Introduction......................................................................................................................6
2.1 Theoretical Literature Review .........................................................................................6
2.2 Empirical literature ..........................................................................................................8
2.3 Conclusion .....................................................................................................................11
CHAPTER THREE...............................................................................................................12
Methodology...........................................................................................................................12
3.0 Introduction....................................................................................................................12
3.1 Model Specification.......................................................................................................12
3.2 The empirical model ......................................................................................................13
3.3 Definitions and Justification of Variables......................................................................13
3.4 Data Sources ..................................................................................................................15
3.5 Descriptive Statistics......................................................................................................15
3.6 Stationarity tests.............................................................................................................15
3.7 Estimation procedure .....................................................................................................15
6. v
3.8 Diagnostic tests..............................................................................................................15
3.9 Conclusion .....................................................................................................................16
CHAPTER FOUR..................................................................................................................17
Estimation and Presentation of Results...............................................................................17
4.0 Introduction....................................................................................................................17
4.1 Descriptive statistics ......................................................................................................17
4.2 Stationarity test ..............................................................................................................17
4.3 Multicolinearity test.......................................................................................................18
4.4 Regression results and Diagnostic tests results..............................................................19
4.5 Interpretation of Regression results ...............................................................................20
4.6 Conclusion .....................................................................................................................21
CHAPTER FIVE ...................................................................................................................22
Summary and Policy Recommendations .............................................................................22
5.0 Introduction....................................................................................................................22
5.1 Summary of the study....................................................................................................22
5.2 Policy recommendations................................................................................................22
5.3 Suggestions for further studies.......................................................................................23
REFERENCES.......................................................................................................................24
APPENDICES........................................................................................................................26
Appendix1: Raw data used ..................................................................................................26
Appendix 2: Augmented Dickey Fuller Stationarity results................................................27
Appendix 3: Correlation Matrix...........................................................................................31
Appendix 4: Regression Results..........................................................................................31
Appendix 5: Histogram Normality Test ..............................................................................32
Appendix 6: Autocorrelation ...............................................................................................32
Appendix 7: Heteroskedasticity...........................................................................................32
Appendix 8: Model Specification with Ramsey RESET test ..............................................32
7. vi
LIST OF FIGURES
Figure 1: Trends of Domestic Saving between 1980 and 2012.................................................3
LIST OF TABLES
Table 1: Descriptive statistics..................................................................................................17
Table 2: ADF unit root test results...........................................................................................18
Table 3: Correlation Matrix .....................................................................................................18
Table 4: Regression results......................................................................................................19
Table 5: Diagnostic Tests.........................................................................................................19
8. vii
LIST OF ACRONYMS
ADB African Development Bank
ADF Augmented Dickey Fuller
ARDL Autoregressive Distributive Lag model
BLUE Best Linear Unbiased Estimators
BP test Breusch-Pagan Heteroskedasticity test
D After Differencing
ECM Error Correction Model
ESAP Economic Structural Adjustment Program
FDI Foreign Direct Investment
GDP Gross Domestic Product
LCH Life Cycle hypothesis
JB test Jarque-Bera normality test
LM test Lagrange Multiplier Serial Autocorrelation test
MPC Marginal Propensity to Consume
MPS Monetary Policy Statement
OGM Overlapping Generations model
OLS Ordinary Least Square
RBZ Reserve Bank of Zimbabwe
RESET Regression Specification Error Test
SME Small to Medium Enterprises
USA United States of America
ZIMPREST Zimbabwe Program for Economic and Social Transformation
9. 1
CHAPTER ONE
Introduction and Background
1.0 Introduction
Saving mobilization has been receiving a great deal of attention from policy makers in developing
countries. Apparently, many economies are drifting away from relying on foreign aid by favouring
domestic funds for growth and development projects, which creates less dependence on other
countries (Bristy 2014). The Solow growth model posits that in order to grow, new investments
are necessary and the funds that are demanded for investment come from savings. Hence, every
economy must save a certain proportion of its national income (Todaro and Smith, 2012).
To promote domestic savings, it is very prudent to understand the nature of national saving
behaviour, which is critical in designing effective policies to boost investment in capital formation
(Kudaisi, 2013). Furthermore, the relationship between saving and the level of growth rate of
national income is an indispensable aspect to underscore the need for analysing the determinants
of domestic saving in greater depth. Singh, (2008) found a long run relationship between saving
and investment, implying that increases in savings will increase investment while Abdel and
Mohamed, (2003) found that investment in physical capital is linked to economic growth. Higher
saving rates are positively related to higher income growth, a fact that has been taken as proof of
existence of both virtuous cycles of saving and prosperity, and poverty traps of insufficient saving
and stagnation (Loayza et al., 2000).
Macroeconomic and microeconomic theories explain some of the factors that may influence
domestic savings. The life cycle hypothesis (LCH) by Modigliani et al., (1954) posits that
demographic structure and income determine the rate of saving while the overlapping generations
model (OGM) by Diamond, (1965) introduces population growth and income growth as other
determining factors. The McKinnon and Shaw hypothesis (1973) assumes a saving function that
responds positively to depositor’s interest rate and real income growth. Last but not least, the
buffer stock model by Carroll, (1992) postulate that savings are affected by uncertainty in
unemployment and inflation.
From 1980 to 2012, average domestic saving in Zimbabwe was US$668 727 475.9 (World Bank,
2014). Since 2004, domestic savings performed poorly as they fell from $134 147 687.2 in 2003
to negative US$150 416 942.6 in 2004 (World Bank, 2014). Up until 2012, domestic savings
remained in the negative with the worst recording of a negative US$1 511 370 572 in 2011. Poor
performance in domestic savings emanated from poor macroeconomic environment and poor and
inconsistent policies, which heavily affected saving mobilisation. Hence, the Reserve Bank of
10. 2
Zimbabwe (RBZ, 2014) in its monetary policy statements (2009-2014) resolved to stabilize the
financial system by monitoring banks to boost depositors’ confidence and increase savings.
Ensuing these changes, the objective of this study is to examine the determinants of domestic
savings in Zimbabwe from 1980 to 2008. Time series Econometrics will be used to analyse these
determinants. The findings will be used for policy recommendations to improve domestic savings
in Zimbabwe.
1.1 Background of the study
Between 1980 and 1990, domestic savings in Zimbabwe, performed remarkably well with an
average amount of US$1 177 930 376 (World Bank, 2014). This performance necessitated a stable
performance in investment that was indicated by an average of 17.28% gross capital formation as
a percentage of GDP and consequently, the economy grew by an annual average of 3.5%. This
was coupled with a high population growth rate of 3.69% and the net result was a marginal
increase in per capita income, which further supported a stable pattern in domestic savings, as
published by African Development Bank, (ADB, 1999). During the same decade, the Money and
Finance Commission was proposed as a policy reform, but it was never implemented (Ndlovu,
2013).
In 1991, the government embarked on an Economic and Structural Adjustment Program (ESAP)
that aimed at establishing a market oriented policy environment in which the financial sector was
liberalized and interest rates were deregulated.ter the implementation of ESAP, depositor interest
rate increased to an average of 26.5% as compared to an average of 9.7% from the previous decade
and savings increased to an average of US$1 275 551 984 from US$1 177 930 376 (World Bank,
2014). However, perhaps to a drought that occurred in 1992, domestic saving fell from US$1 366
977 280 in 1991 to US$741 263 850 in 1992 while GDP per capita fell from $805.13 to $614.82
respectively as domestic consumption increased (World Bank, 2014). Generally, domestic saving
continued performing well during the course of the decade, despite the failure of ESAP in 1995.
Prior to year 2000, the government, realized the need to stabilize exchange rates, reducing interest
rates and targeting low inflation by introducing the Zimbabwe Program for Economic and Social
Transformation (ZIMPREST 1998-2001) in 1998. Under this policy reform, a 6% GDP growth
rate, 3.4% per capita income growth and 4.4% growth in consumption was expected. These goals
were to be achieved with the expectation that saving and investment will be 23% of the GDP
(ADB, 1999). Despite these reforms, domestic saving started to fall in 2000 perhaps due to a fall
in GDP per capita as unemployment increased from 6% in 1999 to 8.8% in 2001, and continued
rising up to 94% in 2008 (World Bank, 2014).
11. 3
The introduction of the land reform programme in 2001 contributed to the deterioration of the
macroeconomic environment, thereby contributing to negative saving and reduction in investment
that was recorded during the course of the decade. In 2002, inflation rate increased from 76.71%
to 140.06% and continued increasing to 302.12% in 2005 (World Bank, 2014). The highest
inflation rate of 231000000% was recorded in 2008. During the same period, GDP fell from US$5
727 591 778 in 2002 to US$4 415 702 801 in 2008 (World Bank, 2014). The government
introduced the indigenization policy in 2007, which was accompanied by low investment as
investors feared for their resources; a situation that hindered economic growth prospects and hence
saving continued in the negative up to a worst recording of negative US$1 511 370 572 in 2011.
Figure 1 shows the trend of gross domestic saving since independence in 1980. From 1980, the
pattern shows that gross domestic savings were increasing until 1988 which recorded the highest
amount of US$1 725 665 217. In 1992, there was a sharp fall in savings from US$1 366 977 280
to US$741 263 850.4 because of a drought and soon after, domestic savings increased to US$1
602 214 726 in 1996. As the economy started to face many economic challenges, such as
previously discussed, there was a fall in savings, which proceeded to negative savings of US$150
416 942.6 in 2004 and further dropped to negative US$1 511 370 572 in 2011. Possibly, there is
strong evidence to attribute this low performance to poor and inconsistent policy reforms that
resulted in low investment, low national incomes, and therefore low domestic savings.
Notwithstanding considerable influences of the macroeconomic environment and policy reforms
on saving mobilisation in Zimbabwe, demographic patterns may conceivably explain the
fluctuations in savings. From 1980 to 1999, the population grew annually by an average of 3.69%
-2E+09
-1.5E+09
-1E+09
-5E+08
0
500000000
1E+09
1.5E+09
2E+09
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
DOMESTICSAVINGS
YEAR
Domestic Savings in Zimbabwe (1980-2011)
Figure 1: Trends of Domestic Saving between 1980 and 2011
Source; Author's computation from the data collected from World Bank (2014)
12. 4
whilst life expectancy was 60.84 years on average and there was a growth in savings (World Bank,
2014). Savings continued performing well in the second decade, regardless of the fall in life
expectancy to an average of 53.69 years whilst population growth dropped to 1.97% (World Bank,
2014). From 2000 to 2012, population growth further decreased to an average of 0.79%, while life
expectancy reduced to 45.76 years and there was a fall in savings (World Bank, 2014).
1.2 Problem statement
Due to an economic recession in 2004, the RBZ introduced diverse initiatives to tackle severe and
persistent liquidity crunch that resulted in insufficient funds to support key sectors of the economy.
One of the proposed solution to curb liquidity crunch and to stimulate economic growth was
mobilisation of domestic savings, which would encourage investments through operative credit
channels (RBZ, 2013). Following this proposition, Zimbabwe experienced negative savings,
which fell from US$134 147 687.2 in 2003 to negative US$947 611 265 in 2008. Perhaps, this
was owing to low economic growth rate and low depositors’ rates, which were 79.70% on average,
between 2000 and 2008 (World Bank, 2014). The situation necessitated high lending rates of an
average 228.75% between 2000 and 2008 as compared to 31.71% in the previous decade, which
further deterred economic growth due to limited availability of loanable funds. These dramatic
changes in interest rates, domestic savings, and macroeconomic conditions exacerbated the
liquidity crunch. As a consequence, the economy of Zimbabwe has been realising low saving
owing to low national income, low liquidity because of low savings, resulting in limited funds for
investment and again low income, low saving and liquidity shortages. The successive deepening
of liquidity shortages has resulted in a chronic “vicious liquidity cycle” that call for special
attention.
The vicious liquidity cycle raises numerous questions on the impact of government policies (such
as interest rate policy, GDP growth policy) and non-policy variables (demographic variables) on
sources of liquidity such as domestic savings and what determines savings mobilisation in
Zimbabwe. Perhaps, from the policy perspective, there are serious problems about the size and
the effects of policy variables. What would be the most effective policy in raising domestic
savings? Hence, this study seek to assess the determinants of savings in Zimbabwe.
1.3 Objectives of the research
The overall objective of this study is to assess the determinants of domestic savings in Zimbabwe.
The specific objectives are to:
Establish the effect of depositor’s interest rates on domestic saving in Zimbabwe
Determine the impact of GDP growth on domestic saving in Zimbabwe
13. 5
1.4 Research questions
The study is guided by the following research questions;
What is the effect of depositor’s interest rate on domestic savings in Zimbabwe?
What is the impact of GDP growth on domestic saving in Zimbabwe?
1.5 Hypotheses of the study
In order to achieve the specific objectives, the study shall test the following hypotheses;
Depositor’s interest rates have a positive impact on domestic saving in Zimbabwe.
GDP growth has a positive impact on domestic saving in Zimbabwe.
1.6 Justification of the study
Given the importance of investments to advance economic growth, the use of foreign direct
investments (FDIs) in promoting economic projects, often create unjustified dependence on other
countries, although domestic savings are less risky and can be easily sourced. These factors are
critical and they have motivated policy makers and researchers to examine the behaviour of
savings in their respective countries. This research will provide better knowledge on the behaviour
of domestic savings in Zimbabwe and will contribute to the literature of savings behaviour in
developing economies.
1.7 Organisation of the study
The rest of the study is structured as follows; Chapter Two will elaborate on the literature review
on saving behaviour. Chapter Three will present the methodology that was employed in achieving
the objectives of this study. Chapter Four will give an analysis and interpretation of the results
obtained, while Chapter Five will provide a summary of the findings and policy
recommendations.
14. 6
CHAPTER TWO
Literature Review
2.0 Introduction
Since saving mobilisation is becoming a major concern in developing nations, it has drawn
attention to many economic theorists across the world. Theories concerning saving behaviour have
been proposed by various schools of thought and some of these have been empirically tested using
economic data. Various empirical studies have also been done in different countries with the
motive to establish the potential determinants of savings. This chapter will highlight some of these
theories as well as some results of the empirical studies.
2.1 Theoretical Literature Review
Saving theory is for the most part built around an individual household and then generalized to
the economy. At the micro level, theories of saving explain how economic agents are likely to
respond to changes in income growth and demographic structure of the household as they attempt
to smoothen their consumption pattern. Similarly, macroeconomic policies like interest rate
growth and inflation targeting, impose their effects on the savings behaviour of the entire economy
by inducing economic agents to either increase saving or not.
Modigliani et al., (1954) developed the Life Cycle Hypothesis (LCH) that relates to spending and
saving habits of households as they try to smoothen their consumption pattern over the course of
their lifetime. The hypothesis begins with the observation that income tends to fluctuate
systematically over the course of a person’s life and that personal saving behaviour is crucially
determined by one’s stage in the life cycle (Sachs and Larrian, 1993). Younger people tend to
have consumption needs that exceed their income. Their needs tend to be mainly for education
and housing, and thus having little savings because of high marginal propensity to consume
(MPC) out of the income earned. During the working age, earnings generally rise, enabling debts
accumulated earlier in life to be paid off whilst accumulating savings because of lower MPC and
a higher propensity to save. At retirement age, MPC is very high and consumption is financed by
savings accumulated during the working years and from transfers that the older people receive
from a government’s social security system and from their children (Sachs and Larrain, 1993).
However, the more generous a social security system, the less a household must save during its
working period to provide consumption during its retirement period.
Diamond (1965), developed an overlapping generations model (OGM) which is a two stage life
model. The model postulate that in an economy with a stable distribution of young and old people
and in which there is no per capita income growth and no overall population growth, the savings
15. 7
of the young tend to be offset by the dissaving of the old. In this case, even if the young generation
is saving for retirement, the aggregate saving in the economy is zero, because the older generation
is dissaving at the same rate. However, most economies are characterized by a positive population
growth and an increasing income per person due to technological improvements in the production
process. Thus, each generation is richer than the previous one implying that young savers are
generally more plentiful and richer than the old dissavers. In aggregate, savings exceed dissavings,
and such economies show an overall positive rate of saving. Faster growing economies tend to
show a higher aggregate saving rate because of their demographics, with younger savers being
more numerous and richer than the old dissavers. Hence, the higher the proportion of the retired
ages, plus the very young to the working population, the lower its aggregate savings.
Mackinnon and Shaw (1973) developed a hypothesis that analyse the benefits of financial
liberalization in developing economies and the impact of reducing financial repression on the
domestic financial system. The hypothesis assumes a saving function that responds positively to
both real interest rates on deposits and the real rate of growth in output. The model predicts that
low interest rate produces a bias in favour of current consumption and against future consumption
(Gemech and Struthers, 2003). This may cause economic agents to reduce savings below the
optimum level while potential lenders may engage in relatively low yielding direct investment
instead of depositing money in banks. Repressing the financial system limits financial savings and
such policies may cause shifts in the saving function that reflects depositors’ reactions to changes
in the regulatory environment. Conversely, liberalising the financial sector in developing countries
will result in higher savings rate through favourable interest rates. Higher savings would finance
a higher level of investment, leading to higher economic growth. McKinnon and Shaw (1973),
argued that raising interest rate ceiling deters entrepreneurs from undertaking all low yielding
investments that are no longer profitable at higher real interest rates. Hence, the average returns
to or efficiency of aggregate investment increases. The output growth rate raises in the process so
further increasing savings.
Carroll (1992) developed the Buffer Stock model of Savings, which assumes that economic agents
hold assets so that they can shield their consumption against unpredictable fluctuations in income,
inflation, and unemployment. Typically, the model predicts that drastic fluctuations in
household’s income are more associated with spells of unemployment. The buffer stock model
assumes an impatient economic agent whose saving behaviour emerges from a precautionary
saving motive. If wealth is below the desired level, fear will dominate impatience and the
economic agent will try to save, while when wealth is above the desired level, impatience will be
16. 8
stronger than fear and consumers will plan to dissave. Carroll (1992) argued that unemployment
and inflation expectations are important in predicting savings because when consumers become
more pessimistic about unemployment, their uncertainty about future increases, so their desired
buffer stock of savings will increase. They will increase their savings to build up wealth toward
the new target. Thus, the economic agents will adjust their consumption downwards gradually.
Nonetheless, consumption smoothing as assumed by LCH (1954) depends on access to
unconstrained borrowing and lending, which may be hindered by the existence of liquidity
constraints and low real interest rates on current savings thereby preventing households to move
resources across periods. Therefore, the McKinnon-Shaw (1973) hypothesis argues for the
alleviation of financial restrictions to allow real interest rates to rise towards their competitive
equilibrium. However, economic agents in developing countries are less responsive to interest rate
changes, especially in times of high inflation. Furthermore, due to macroeconomic instability
which cannot be diversified away by risky pooling within households, household incomes in
developing countries are more uncertain. Thus, the precautionary saving motive may be more
important in developing countries as postulated by the buffer stock saving model (1992),
notwithstanding the importance of other theories and their assumptions on explaining saving
behaviour. But what seems to be clear from the theory of precautionary saving appears to be
difficult to prove empirically since expectations are not easy to quantify and thus estimates of the
extent of precautionary saving may differ between researches. However, precautionary saving
may play an indispensable role in intertemporal decision making.
2.2 Empirical literature
The following studies review the observations and different methodological approaches that were
employed in studying saving behaviour in various countries with the aid of economic theory.
Wachtel, (1977) used time series data from 1955 to 1974, to investigate the relationship between
inflation, uncertainty, and saving behaviour in America. Ordinary least squares with quarterly
savings flow was employed in the study. Wachtel, (1977) discovered that a high savings rate
observed in the USA since the mid-1960s were related to inflation and uncertainty. The study
concluded that when households are uncertain about inflation, they reduce borrowing, cut on their
consumption and increase savings. These results support the buffer stock model of savings that
postulated an increasing savings function due to high inflation and uncertainty. However, the
applicability of the buffer stock model to developing countries may differ due to differences in
stages of development as compared to developed.
17. 9
Having discovered a considerable controversy about the role of financial factors as determinants
of savings in developing countries, Gupta (1987) analysed the impact of financial intermediation
and interest rate on aggregate savings. The study employed a pooled time series technique on
panel data for twenty-two Asian and Latin American countries from 1967 to 1976. The results
indicated that there was no clear support for the effect of either interest rates or financial
intermediation in Latin America. However, some qualified support was found in Asia on the
impact of interest rates, but none in Latin America.
Owing to the increasing demand for funds, which were mainly borrowed from external sources in
Malaysia, Thanoon and Baharumshah (2003) examined the determinants of gross domestic
savings. A multivariate cointegration and error correction model was applied on annual data for
the period 1960 to 2000. The study revealed that economic growth, foreign direct investment,
dependency ratios, and interest rate had an impact on national savings. The outcomes showed that
the McKinnon-Shaw (1973) hypothesis holds only in the long run and that the short run savings
to interest rate relation runs contrary to this hypothesis.
After financial sector reforms were introduced in Pakistan, Awan et al., (2010) tested the validity
of the McKinnon-Shaw (1973) hypothesis. An auto regressive distributive lag model (ARDL) was
employed on annual data from 1973 to 2007, to analyse the long run and short run association
among the depositor’s interest rate, financial liberalisation, economic growth, terms of trade and
real remittances. The findings indicated that real interest rate, financial liberalisation, and
economic growth affect savings positively in the long run while terms of trade and real remittances
had a negative impact. The study confirmed the McKinnon and Shaw hypothesis in that allowing
market forces to determine real interest rates could exert a positive effect on growth rates and real
interest rate rise towards their competitive equilibrium. This would increase savings in such an
economy.
Contrary to the findings of Awan et al., (2010), Khoso et al., (2011) used time series data between
the period of 1976 and 2009 to analyse the impact of population growth on savings in Pakistan.
The study was prompted by dramatic changes in demographics, which are the major determinants
of variations in savings according to the LCH (1954). A non-linear multiple regression model was
used and the results showed that per capita income and discount rate had a negative effect on
savings due to the economic downturn and high inflation. Life expectancy had a negative effect
on savings, leaving more room to question the validity of the LCH (1954) findings by Modigliani
and Ando (1963) that people would continue to save because of longer than expected longevity.
18. 10
Due to wide fluctuations and deteriorating savings ratio in Ghana that was below the sub-Saharan
regional level of savings in Africa, Larbi (2013) studied the determinants of private savings. A
residual-based test for cointegration was employed on annual data from 1970 to 2010. The study
showed that financial liberalisation, per capita income and inflation had a positive and significant
relationship with private savings. Larbi (2013) suggested that financial liberalisation would give
financial institutions room for improved packages of increased savings. Additionally, pursuing
economic growth policies vigorously would improve incomes and hence people’s capacity to
save.
Kudaisi (2013) investigated the determinants of domestic savings in West Africa by employing
an OLS model on panel data from 1980 to 2006. The study was prompted by differences in savings
rate across the African region and the need to understand how policy and non policy variables
affect the saving rate in West Africa. Seemingly, the findings contradicted with the LCH (1954)
and OGM (1965) as growth in GDP and dependency ratio were found insignificant. Financial
development and inflation had a positive impact and they supported the McKinnon-Shaw (1973)
and Buffer stock (1992) models respectively. Moreover, government budget surplus was found to
be statistically significant and positively affecting domestic savings. Kudaisi (2013) concluded
that the establishment of new and more sophisticated financial markets and adoption of new
instruments are crucial in increasing savings rate.
In Ethiopia, Ayalew (2013) investigated the long run and short run determinants of domestic
savings on a time series data for the period 1970 and 2010. The researcher employed an
autoregressive distributed lag (ARDL) bounds model. The results showed that the growth rate of
income, budget deficit ratio, and inflation was statistically significant in both the short run and
long run. Contrary to the McKinnon-Shaw (1973) hypothesis, depositing interest rate, financial
depth, and the current account deficit ratio was insignificant. The results underscored the need for
raising the level of income in a sustainable manner, minimising the adverse impacts of budget
deficit, and creating a competitive environment in the financial sector.
In Bangladesh, Bristy (2014) studied the saving behaviour by decomposing the aggregate saving
trend in urban and rural sector to shed more light on saving behaviour in the long run and short
run horizons. Using time series data for the period of 1980-2012, the researcher employed a
cointegation test and vector correction model. The outcomes indicated a great deal of diversity
between urban and rural sector. Deposit rate was the only factor that stimulates depositors to save.
Higher volatility regarding income, banking facilities and inflation would influence savers to
increase interest-bearing deposits. The results confirmed the buffer stock savings model in that
19. 11
people have a precautionary saving motive. When people are not certain about future
unemployment and inflation, they will increase their desired buffer stock of savings. As a result,
people would cut on their consumption expenditure and save for the future
As a result of the high incidence of poverty, declining levels of disposable income and weak
financial system, Ehikioya and Mohamed (2014) carried out an econometric analysis on the
determinants of private domestic savings in Nigeria using time series data from 1981 to 2012. An
integration and error correction mechanism was employed in the study. Results indicated that
income per capita, inflation rate, terms of trade and financial deepening were statistically
significant in Nigeria’s private savings. Ehikioya and Mohamed (2014) suggested that there is a
need for proper financial development and tightening the monetary and fiscal policy in order to
fight inflation. Furthermore, government expenditure should be tied to specific viable economic
projects in order to increase income, which had a direct effect on savings.
In summary, the empirical literature supported the McKinnon-Shaw (1973) hypothesis, which
assumed a saving function that responds positively to financial liberalisation and real rate of
growth, and the buffer stock model (1992) that assumed uncertainty about inflation and
unemployment as determinants of savings. Furthermore, support was found on both the OMG
(1965) and LCH (1954), which postulated that demographic structure and population growth
affects saving behaviour as well. Nevertheless, there was no clear agreement on the impact of
depositor interest rates as, in some studies, it was found insignificant and or contradicting the
McKinnon-Shaw (1973) hypothesis. Except in Malaysia and Pakistan, all the theories were
significant in both the short run and the long run. Growth in income, demographic structure,
financial liberalisation, interest rates, and inflation rate were found to be the major determinants
of saving. Therefore, both economic theory and empirical literature have shed more light on the
various factors that influenced saving mobilisation in different economies and this compelled the
motive to test the pertinence of the literature review in the context of Zimbabwe, in order to
achieve the overall objective of this study. The major determinants from the empirical and
theoretical literature were considered in model specification in Chapter Three.
2.3 Conclusion
This chapter has highlighted the literature review on savings behaviour and its determinants.
Theoretical literature as well as empirical literature was discussed. Chapter Three will present the
methodology that was used in this study.
20. 12
CHAPTER THREE
Methodology
3.0 Introduction
This Section presents the methodology that was employed in analysing the data in Chapter Four.
The presentation provides definitions and justification of the exogenous and endogenous
variables, as well as the expected priori signs for the exogenous variables. The method of data
collection, sources of data, and the estimation procedure, including diagnostic tests are discussed
as well.
3.1 Model Specification
The model for domestic saving is derived from both micro and macro theories as well as the
empirical evidence discussed in Chapter Two. Life Cycle Hypothesis and Overlapping Generation
Model hypothesized savings as a function of a nation’s demographic structure, growth in income,
population growth, and dependency ratio. The McKinnon-Shaw postulated a saving function that
responds positively to both real interest rates on deposits and the real rate of growth in output.
Lastly, the Buffer Stock Model of Savings assumed that uncertainty in inflation and
unemployment has a shock on the saving behaviour of the people. Therefore, from theory and the
empirical evidence saving is a function of;
Saving = f (per capita income growth, GDP growth, dependency ratio, life expectancy, population
growth, interest rate on deposits, inflation, financial liberalisation, and unemployment)
The error correction model (ECM) was the most preferred technique from the empirical studies
as it is used to determine time series data short-run deviations from long-run equilibrium.
However, ECM is applicable only between variables that are integrated of the first order and
cointegrated. Owing to the fact that many time series are not cointegrated, a linear regression
(OLS) model was employed to test the relationship between domestic savings and its determinants
borrowing from the model by Chinweuba and Sunday (2014), which models Savings=f (GDP,
depositor interest rate, broad money, inflation rate). The model that was employed in this study
excluded broad money supply and inflation, and introduces unemployment, GDP growth,
population growth, and financial liberalisation.
21. 13
3.2 The empirical model
The following model was estimated;
= + + ℎ + + ℎ + +
Where;
DSt = Gross domestic savings as a percentage of GDP
UNEt = Unemployment rate
Pgrwtht = Population growth rate
DEPRt = Depositors interest rates
GDPgrtht = GDP growth
FINt = Financial liberalization
= constant term βi (i= 1,2…5) = Slope coefficients µt = error term (with zero mean and constant
variance)
Where: µ ̴ N(0, ) implying that µ follows a normal distribution. The assumption ensures that
each observation is equally reliable, so that the estimates of the regression coefficients are efficient
and tests of hypothesis about them are not biased (Salvatore and Reagle, 2002).
3.3 Definitions and Justification of Variables
Gross domestic savings (DSt)
Gross domestic saving is calculated as gross domestic product less final consumption expenditure.
According to the McKinnon-Shaw (1973), increasing savings may finance a higher investment,
leading to higher economic growth. This assertion is supported by the loanable funds theory,
which postulates that the demand for loanable funds comes from savings. These funds are invested
in capital formation and thus, leading to economic growth.
Unemployment rate (UNEt)
Unemployment rate is the share of the labour force that is without work, but available for and
seeking employment. Carroll (1992) argued that unemployment expectations are important in
predicting savings because once consumers become more pessimistic about unemployment, their
uncertainty about future increases, so they forego current consumption and increase savings.
Accordingly, an economic agent is supposed to adjust its target buffer stock by increasing saving
(dissaving) if unemployment uncertainty increases (decreases). Alexandar (2012) found an
22. 14
inverse relationship between unemployment and domestic saving. However, based on theory, a
positive sign was expected between unemployment and domestic saving.
Population growth (Pgrwtht)
Population growth is the exponential rate of growth of the total population from year (T-1) to T,
expressed as a percentage. Diamond (1965) argued that in an economy with a stable distribution
of young and old people and in which there is no overall population growth, the saving of the
young tend to be offset by the dissaving of the old. This implies that population growth is essential
in increasing saving. Khoso (2011) found that Population growth had a positive impact on savings.
A positive relationship was expected between population growth and domestic savings.
Depositor’s interest rates (DEPRt)
Deposit interest rate is the rate paid by commercial or similar banks for demand, time, or savings
deposits. The McKinnon-Shaw hypothesis (1973) assumed a saving function that responds
positively to both real interest rates on deposits. The higher the interest on deposits, the higher the
savings since depositor’s rate is an opportunity of holding cash in liquid. Empirical studies in
Chapter Two concluded that interest rates are insignificant except for Awan et al., (2010) and
Bristy (2014) who found a positive relationship. However, a positive relationship was expected
between depositor’s interest rate and domestic savings.
GDP growth (GDPgrtht)
GDP growth is the annual percentage growth rate of gross domestic product (GDP) at market
prices. The McKinnon-Shaw (1973) hypothesis assumed that a saving function should respond
positively to the real rate of growth in output (GDP or national income). Thanooon
andBaharumshah , (2003), Awan et al., (2010), and Ayalew (2013) found a positive relationship
between GDP growth and domestic saving. Thus, following these studies, a positive sign was
expected between GDP growth and domestic saving.
Financial liberalization (FINt)
Financial liberalization is the removal of any sort of regulation on the financial sector of a nation.
FINt is a dummy variable taking two values, that is, 1 (one) for liberalization and 0 (zero) for
otherwise. McKinnon and Shaw (1973) argued that liberalising the financial sector will result in
higher savings rate through favourable interest rates and conversely repressing the financial
system limits savings, which thwarts economic development. Awan et al (2010), Kudaisi (2013),
23. 15
and Larbi (2013) found a positive relationship between financial liberalisation and domestic
savings. A positive sign was expected between financial liberalisation and domestic saving.
3.4 Data Sources
The study used data that were collected from Zimbabwe Statistic Agency (ZIMSTATS), African
Development Bank (ADB), and the World Bank. Except for unemployment and financial
liberalisation, the data for domestic savings, population growth, depositor interest rate, and GDP
growth were collected from the World Bank. Unemployment data were obtained from
ZIMSTATS while financial liberalisation information was extracted from the ADB publications.
3.5 Descriptive Statistics
Some descriptive statistics were discussed in this study. Measures of central tendency such as the
mean and the median were summarised. In addition, measures of variation that include standard
deviation, range, and kurtosis were summarised as well.
3.6 Stationarity tests
Stationarity tests were done to factor out the trend component in time series data. A stationary
time series is a process that has mean, variance, and covariance that do not depend on time. If the
series is non-stationary, spurious results are obtained. The Augmented Dickey Fuller (ADF) test
was employed to test for stationarity, which states that is the ADF test value is less than the critical
values then the variable in stationary. A method of differencing was used to stationarize the data
after the ADF test was applied.
3.7 Estimation procedure
To examine the determinants of domestic savings in Zimbabwe, the study used time series data
from 1980 to 2008. The Ordinary Least Square (OLS) technique was employed to estimate the
coefficients (βs). The OLS method generates estimates that are Best Linear Unbiased Estimators
(BLUE) and minimize the sum of squared residuals only when its basic assumptions are satisfied.
These assumptions include; linearity, normality, full rank, homoscedasticity, non-autocorrelation,
exogeneity of dependent variables and exogenously generated data (Greene, 2002).
3.8 Diagnostic tests
Multicolinearity test was performed using a pairwise correlation method to examine whether the
explanatory variables depend on each other using a correlation matrix. When two or more
explanatory variables in the regression model are highly correlated, it may be difficult to isolate
their individual effects on the dependent variable (Salvatore and Reagle 2002). An absolute value
24. 16
above 0.8 would indicate high correlation between variables and the solution was to drop one of
the variables.
A histogram normality (Jarque-Bera) test (JB) was employed to test for normality, which ensures
that the estimates of the regression coefficients are efficient and tests for hypothesis about them
are not biased. However, according to Greene, (2002) estimations can proceed even if errors are
not normally distributed since the normality assumption is unnecessary and inappropriate addition
to the regression model.
The Breusch-Pagan test (BP) was carried out to test for the presence of heteroskedasticity, which
exists when the variance of the error term is not constant. The test was necessary to avoid
misleading confidence intervals due to high standard errors in the presents of heteroskedasticity.
The problem is associated with both cross sectional and time series data.
To test for autocorrelation between successive errors in time series data, a serial correlation LM
test (LM) was employed. If the error in one period is correlated with the error in the previous
period, the data will exhibit first order autocorrelation. Autocorrelation is common in time series
data as the observation follows a natural orderly through time. The consequences of
autocorrelation are similar to those of heteroskedasticity.
To test the fitness of the model, the coefficient of determination (Rsquared-R2) was employed,
which measures the variations in the dependent variable as explained by variations in the
explanatory variables. Regression Specification Error Test (RESET) was employed to detect the
omitted variables and incorrect functional form and the F-Test was used to test the significance of
the whole model.
3.9 Conclusion
This chapter has presented the methodology that was applied in estimating the empirical model in
Chapter Four. The following chapter will present and analyse the results that were obtained using
the techniques that were proposed in this chapter.
25. 17
CHAPTER FOUR
Estimation and Presentation of Results
4.0 Introduction
This section presents the empirical results following the methodology that was proposed in
Chapter Three. Descriptive statistics will be presented, followed by stationarity tests, regression
results and diagnostic tests. Finally, the section will interpret the results.
4.1 Descriptive statistics
Table 1 presents descriptive statistics of the variables that were used in this study.
Table 1: Descriptive statistics
Table 1 shows a summary of descriptive statistics for 29 observations on domestic saving,
unemployment, population growth, depositor’s interest rates, GDP growth, and financial
liberalisation. Domestic saving (as a percentage of GDP) has a large standard deviation implying
greater variations in domestic saving, which is not favourable for the economy. Domestic saving
is negatively skewed which shows that its mean is less than the median. Thus, there was a fall in
domestic saving in periods at the end of this study. Domestic saving is not normally distributed
about its mean, since a probability value of 0.0018 for Jarque-Bera is less than 0.05. Despite the
violation of the normality assumption on domestic savings, the estimated parameters are still
BLUE since all other assumptions are met (Greene, 2002).
4.2 Stationarity test
The ADF unit root test was used to test for stationarity of the variables at 1% and 5% levels of
significance in the study. The test showed that GDP growth, Financial liberalization, and domestic
savings were stationary at first difference, I(1). Depositor’s interest rates, unemployment were
stationary at second difference, I(2). Lastly, population growth was found to be stationary at third
Variable DSt UNEt Pgrwtht DEPRt GDPgrtht FINt
Mean 11.24904 19.25276 2.061575 41.71073 0.601783 0.275862
Median 15.81878 9.200000 1.924602 18.59833 1.439615 0.000000
Maximum 22.08206 94.00000 3.995295 233.6000 14.42068 1.000000
Minimum -21.46003 5.000000 0.107875 3.520833 -17.66895 0.000000
Std. Dev. 10.73253 24.81800 1.418033 57.01914 7.698229 0.454859
Skewness -1.453993 2.218774 -0.025488 2.292375 -0.558530 1.002972
Kurtosis 4.416937 6.429326 1.542069 7.397568 3.224241 2.005952
Jarque-Bera 12.64411 38.00463 2.571530 48.76656 1.568548 6.056094
Probability 0.001796 0.000000 0.276439 0.000000 0.456451 0.048410
Sum 326.2221 558.3300 59.78567 1209.611 17.45171 8.000000
Sum Sq. Dev. 3225.241 17246.13 56.30286 91033.11 1659.357 5.793103
Observations 29 29 29 29 29 29
26. 18
difference I(3). Table 2 shows the results of the ADF unit root test at first difference, second
difference and third difference.
Table 2: ADF unit root test results
Variable Dickey
fuller test
Critical
value at
1%
Critical
value at
5%
Critical
value at
10%
Order of
integration
Conclusion
DSt -7.245741 -4.339330 -3.587527 -3.229230 I(1) *stationary
UNEt -4.776019 -4.416345 -3.622033 -3.248592 I(2) *stationary
Pgrwtht -3.719464 -4.394309 -3.612199 -3.243079 I(3) **stationary
DEPRt -6.007211 -4.440739 -3.632896 -3.254671 I(2) *stationary
GDPgrtht -4.872692 -4.394309 -3.612199 -3.243079 I(1) *Stationary
FINt -24.947546 -4.339330 -3.587527 -3.229230 I(1) *Stationary
(*) indicates stationarity at 1%, (**) indicates stationarity at 5%
4.3 Multicolinearity test
The sample correlation coefficient was calculated and the results indicated that no correlation
greater than the absolute value of 0.8 was observed amongst the explanatory variables and thus,
no serious problem of multicolinearity existed. Table 3 shows the correlation matrix for a
multicolinearity test that was carried out.
Table 3: Correlation Matrix
Variable DUNEt DPgrwtht DDEPRt DGDPgrtht DFINt
DUNEt 1.000000
DPgrwtht -0.027316 1.000000
DDEPRt -0.153733 0.077175 1.000000
DGDPgrtht 0.006773 -0.225415 -0.242932 1.000000
DFINt 0.065826 -0.174417 0.109007 -0.219924 1.000000
27. 19
4.4 Regression results and Diagnostic tests results
Table 4 shows the regression results that were obtained using E-views 7
Table 4: Regression results
(*) shows 1% level of significance, (**) shows 5% level of significance
The regression results in Table 4 shows that unemployment, depositor’s interest rates, GDP
growth, and financial liberalisation were statistically significant. Financial liberalisation, GDP
growth, and unemployment had the expected signs. Population growth was not significant in the
model. R-squared value of 0.749323 implied that 74.93% variation in domestic savings is
explained by variations in unemployment, depositor’s interest rates, GDP growth, and financial
liberalisation. It also shows that the model was of good fit since the R-squared value was above
0.5. The F-probability value is 0.000019 less than 0.01 thus, we may conclude that the whole
model was significant at 1% level of significance.
Table 5: Diagnostic Tests
Table 5 shows diagnostic test results that were carried out using 0.05 as the decision rule. A
histogram Normality-test (JB test) was carried out and a Jarque-Bera p-value 0.617298 showed
that the errors were normally distributed. This was supported by a kurtosis value of 3.106189,
which is above (3) three. The serial correlation LM test (LM test) was employed to test for
autocorrelation and a p-value of 0.0791 greater than 0.05 indicated the absence of autocorrelation.
The Breusch-Pagan test (BP test) was used to test for heteroskedasticity and a p-value of 0.9938
Dependent variable; DSt
Variable Coefficient Std. Error t-Statistic Prob.
DUNEt -0.195628 0.058267 -3.357450 0.0031*
DPgrwtht -23.75001 15.10359 -1.572475 0.1315
DDEPRt -0.051666 0.011324 -4.562358 0.0002*
DGDPgrtht 0.375243 0.104752 3.582200 0.0019*
DFINt 4.302601 1.847776 2.328529 0.0305**
C -0.532909 0.702361 -0.758740 0.4569
R-Squared = 0.749323 Adjusted R-Squared = 0.686654 Prob(F-Statistic) = 0.000019
Test type P-value Decision at 0.05
Normality Test (JB test) 0.617298 Normally Distributed
Autocorrelation (LM test) 0.0791 No Autocorrelation
Heteroskedasticity (BP test) 0.9938 Homoskedastic
Model Specification (RESET) 0.4601 Correctly Specified
28. 20
greater than 0.05 signified homoskedasticity. Lastly, a Ramsey (RESET) test was carried out to
test for model misspecification and a p-value of 0.4601 showed that the model was correctly
specified.
4.5 Interpretation of Regression results
Unemployment rate (UNEt) was found to be statistically significant at 1 % level in the model with
a negative coefficient of -0.195628. This showed that a unit increase in unemployment will result
in a 0.195628 units fall in domestic saving for the period under study. However, the result
contradicts the Buffer Stock saving theory (1992), which assumes that savings must increase as
uncertainty about unemployment increases. The results are the same with what Alexander (2012),
found on the relationship between savings and unemployment. It is argued that economic agents
that face a high risk of unemployment may be disposed to save for precautionary motives, it might
nonetheless show a small prospect of actually being able to save (Alexander, 2012). The focal
point is that in the event of unemployment, economic agents anticipate having insufficient funds
after purchasing necessities and the effect is called the “expected income effect” due to the risk of
unemployment.
Depositor interest rate (DEPRt) was found to be statistically significant at 1% level with a negative
coefficient of -0.051666. The variable had an unexpected sign and contradicting the McKinnon-
Shaw (1973) hypothesis, which assume a saving function that responds positively to depositor’s
interest rates. The result indicated that a unit increase in depositor’s interest rate will result in a
0.051666 units fall in domestic saving, holding other things constant. The outcome supported
Khoso (2011) who found similar results in Pakistan. Perhaps, this was explained by the fact that
when inflation goes up, depositor’s fear that the interest they are paid won’t buy as much in the
future because inflation is driving costs higher, a situation that was prevailing during the period
under study in Zimbabwe.
GDP growth (GDPgrtht) was found to be statistically significant at 1% level with a positive
coefficient of 0.375243. This indicated that, other things remaining constant, a unit increase in
economic growth will result in a 0.375243 units increase in domestic saving. The outcome is
consistent with theory and supports Kudaisi (2013) who found a positive relationship between
domestic saving and GDP growth in the West African region.
Financial liberalisation (FINt) was found to be significant at 5% level of significance with a
positive coefficient of 4.302601. The result showed that the existence of financial liberalisation
increases domestic saving by 4.302601 units. The result supported Awan et al., (2010) who found
a positive relationship between domestic saving and financial liberalisation in Pakistan. The result
29. 21
is also consistent with the McKinnon-Shaw (1973) hypothesis, which argues for the alleviation of
financial restrictions in developing countries like Zimbabwe.
4.6 Conclusion
In summary, unemployment, depositor’s interest rates, GDP growth, and financial liberalization
were found to be significant variables that determine domestic saving in Zimbabwe. Population
growth was found to be statistically insignificant in the model. Policy recommendations and areas
of further study are subject of matter in Chapter Five.
30. 22
CHAPTER FIVE
Summary and Policy Recommendations
5.0 Introduction
Chapters One to Three necessitated the presentation of the results in Chapter Four, which
subsequently lead to the conclusion and policy recommendations to be drawn in this chapter.
5.1 Summary of the study
The specific objective of the study was to determine the impact of the depositor’s interest rate on
domestic saving in Zimbabwe using time series data for the period 1980 to 2008. Eviews 7
statistical package was used for regression analysis. The results obtained showed that depositor’s
interest rate, unemployment, GDP growth, and financial liberalisation were the factors that
explained domestic saving in Zimbabwe for the period under study. The results indicated that
GDP growth confirmed the pattern of effects as hypothesized and supported the McKinnon-Shaw
(1973) which states that savings should respond positively to real rate of growth in output.
However, the hypotheses that both depositor’s interest rate and unemployment had a positive
influence on domestic saving may be rejected.
5.2 Policy recommendations
There was a rapid increase in both the depositor’s and the lending interest rates between 2000 and
2008. However, the depositor’s interest rate trend shows an anomalous pattern, despite its average
increase during the period under study. The increase in the depositor’s interest rate is attributed to
increasing inflation that ended up in hyperinflation (231000000% inflation rate in 2008). As a
result, savers were induced to draw down their saving accounts for the fear that the interest they
were paid would not buy as much in future because inflation was driving costs higher.
Additionally, the inefficiency of the financial system drew people’s attention to the reality that
their savings were no longer secured in banks. Therefore, people in Zimbabwe become more
reluctant to save even at higher interest rates and thus reducing saving.
To promote savings in Zimbabwe, the government should adopt an interest rate regime that
promotes manageable depositor rates and as well maintaining low inflation rates in real terms that
will reduce uncertainty in future returns. Furthermore, the RBZ should alleviate financial
restrictions and allow market forces to determine real interest rates that will allow interest rates to
move towards their competitive equilibrium. Alleviating financial restrictions should be supported
by creation of a competitive financial system that is very innovative, which can produce new
financial products and increase savings by reducing travel cost and other related banking costs.
The RBZ should also ensure that all the bank charges are equitable, which can encourage people
31. 23
to save more. The government should vigorously aim to reduce formal unemployment by creating
an efficient and effective labour market information system to enhance labour market analysis and
human resources development and utilisation. The system should be able to disseminate
information about job opening to better match workers and jobs. The government should also
introduce public job training programs to help workers that are displaced from declining and or
closing industries to get the skills needed for jobs in growing industries. The government should
review the regulatory framework as well as dispensing funds to encourage the growth of small to
medium enterprises (SMEs) which will promote employment creation. The government should
avail adequate resources for economic empowerment projects across all age groups (inclusive of
people living with disabilities, women and youths) that will increase their incomes. High
employment means more income, low dependency ratios, and increased prospects for saving. The
government should formulate policies that will attract investors, and this may allow physical
capital inflows and new technologies for building a globally competitive economy. To achieve
this goal, the government should improve the ease of doing business in Zimbabwe by revising the
business regulatory framework and avoid unnecessary investment policy reversals.This will
reduce deterrence to new investments and hence promote economic growth.
5.3 Suggestions for further studies
Limited availability of data on depositor’s interest rates constrained the study to cover for the
multicurrency regime period that was adopted since 2009; hence, the study can be improved to
cater for the multicurrency regime. Furthermore, the study failed to establish the short run
deviations from the long run equilibrium due to the inapplicability of the error correction model
(ECM). Hence, the study will improve if this method is applied. Despite the results obtained on
the relationship between domestic saving and economic growth, a study can be carried to test the
causality between these two variables using cointegration test and Granger Causality technique.
32. 24
REFERENCES
Abdel, M., and Mohamed, W., (2003), The impact of foreign capital inflow on savings, investment
and economic growth rate in Egypt: An econometric analysis Scientific Journal of King Faisal
University Vol. 4 No. 1
African Development Bank (1998), Zimbabwe (1999-2001) Strategic plan
Alexander, A., (2012), Precautionary saving and the influence of unemployment insurance on
saving behaviour Wirtschafts
Awan, U. R., Munir, R., Hussain, Z., and Sher, F., (2010), Rate of interest, Financial liberalisation
and domestic savings behaviour in Pakistan International Journal of Economics and Finance
Ayalew, A. H., (2013), Determinants of domestic saving in Ethiopia: An autoregressive
distributed lag bounds testing approach Journal of Economics and Internationa finance
Bristy, H. J., (2014), Saving Behaviour of Bangladesh International Review of business Research
papers Vol. 2 No.2
Carroll, D. C., (1992), The Buffer Stock Theory of saving: Some Macroeconomic Evidence Board
of governors of the federal reserve system
Chinweuba, T. E., and Sunday, C. O., (2014), Determinants of private domestic saving in Nigeria
(1970-2010) Journal of Economics and Sustainable Development
Diamond, P., (1965), National Debt in a Neoclassical Growth Model American Economic Review
Ehikioya, L. I., and Mohammed, I., (2014), An econometric analysis of the determinants of private
domestic saving in Nigeria (1981-2002) International Journal of Humanities and Social Sciences
Gemech, F., and Struthers, J., (2003), The McKinnon-Shaw hypothesis: Thirty years on: A review
of recent developments in financial theory
Greene, W. H., (2002), Econometric Analysis. 5th Eddition. Prentice-Hall
Gujarati, D. N., (2003), Basic Econometric. McGraw-Hall
Gupta, L. K., (1987), Aggregate Savings, Financial International, and Interest rate The Review of
Economics and Statistics
Khoso, Y. M., Bhutto, A. N., Khatri, V., Choithani, S., and Butt, F., (2011) The Impact of
population growth on savings: A case of Pakistan
33. 25
Kudaisi, V. B., (2013), Saving and its determinants in West Africa countries Journal of Economics
and Sustainable Development
Larbi, D. A., (2013), The long run determinants of private domestic savings in Ghana: A
cointegration approach Journal of Economics and Sustainable Development
Loayza, N., Hebbel, S. K., and Serven, L., (2000), Saving in developing countries: An overview
The World Bank Economic Review
Ndlovu, G., (2013), Financial Sector Development and Econmic Growth: Evidence from
Zimbabwe International Journal of Economic and Financial Issues
Reserve Bank of Zimbabwe (2014) Monetary Police statements 2009-2014
Sachs, J., and Larrian, B., (1993), Macroeconomics in the global economy. Prentice Hall
Salvatore, D., and Reagle, D., (2002), Theory and Problems of Statistics and Econometrics. 2nd
Eddition. McGraw-Hill
Singh, T., (2008) Testing the saving-investment correlation in India: An evidence from single-
equation and system estimators Economic Modelling Vol 25
Thanoon, A. M., and Baharumshah, Z. A., (2003), Determinants of gross national saving in
Malaysia: A macroecomic analysis 1960-2000 Giadano Dell-Amore foundation
Todaro, P. M., and Smith, C. S., (2012), Economic development. 11th Edition. Addison-Wesley
Watchel, P., (1997), Inflation, Uncertainty, and Saving Behaviour since the Mid-1950s
Ecploration in Economic Research. NBER
World bank (2014)
Zimstats, (2014)
