determinants of saving among the zambian middle...

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Determinants of saving among the Zambian middle class:

The banking employees’ perspective

A research report presented to:

The Graduate School of Business

University of Cape Town

In partial fulfillment of the requirements of the

Masters of Business Administration Degree

By John Chundu

February 2017

Supervisor: Dr Abdul Alhassan

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Plagiarism Declaration

1. I know that plagiarism is wrong. Plagiarism is to use another’s work and pretend that it

is one’s own.

2. I have used the APA convention for citation and referencing. Each contribution to, and

quotation in, this submission from the work(s) of other people has been attributed, cited and

referenced.

3. I certify that this submission is my own work.

4. I have not allowed, and will not allow, anyone to copy my work with the intention of

passing it off as his or her own work.”

Date: February 2017

Student Name: John Chundu

Exam no. 821

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ACKNOWLEDGEMENTS

Someone once said, “Life should not be a journey to the grave with the intention of arriving

safely in a pretty and well preserved body. Rather, to skid in broadside in a cloud of smoke

thoroughly used up, totally worn out and loudly proclaiming ‘Wow! What a ride!!’”. This

is how I feel at the end of my MBA journey - thoroughly used up and totally worn out!

However, I leave the MBA a more confident, energised and stronger person than when I

started. I would not have completed this journey (which I have, by the way, thoroughly

enjoyed!) without the help and support of many people.

I would like to express my gratitude to my supervisor, Abdul Latif Alhassan, for sharing his

knowledge and continued input during the course of this research.

I wish to acknowledge my appreciation to my fellow MBA modular class of 2015/2016

especially my syndicate group and to Mary Lister and Michele Snyders at GSB for their

support and assistance in various ways to make my journey a success.

Special thanks go to my beautiful wife Mika and the children: Natasha, Zewelanji and Lusa

including my nephew Bupe for their encouragement, sacrifice and prayers in the last two

years.

Lastly, I am grateful to God for enabling me undertake this journey.

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ABSTRACT

The purpose of this study was investigate whether financial literacy, availability of credit or

ethnic / cultural background were factors pertinent to sustaining and increasing saving

among the Zambian banking employees or not. This is in recognition of the importance that

saving plays in the economic development of a given country and the apparent sluggish

growth of saving among individuals and households in Zambia. The study employed a

questionnaire as a tool for collection of data from 100 employees within the banking

industry.

In analysing these factors, a statistical analysis software tool called Megastat v11.0 was used

to run regressions and test hypotheses relevant to the study. The study found that financial

literacy was a factor influencing saving behaviour while availability of credit and ethnic /

cultural background were not. The findings will help policy makers, bankers and investment

managers to design interventions that encourage saving through fiscal policy formulation,

introduction of innovative saving products and access to saving and investment information.

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GLOSSARY OF TERMS

Gross national savings (GNS) ratio - an indicator of how much a country saves and is

calculated by deducting the country’s final consumption expenditure from gross national

disposable income (which consists of personal and household savings, business savings and

government savings but excludes foreign saving) expressed as a percent of gross domestic

product (CIA, 2016).

Household – a group of persons who eat and live together and may comprise of several

members or in some cases, only one member (Central Statistical Office, 2016).

Middle class - an ambiguous social classification, broadly reflecting the ability to lead a

comfortable life. The middle class usually enjoy stable housing, healthcare and educational

opportunities (including college) for their children, reasonable retirement and job security,

and discretionary income that can be spent on vacation and leisure pursuits (Kharas, 2010.

p.7).

Saving – residual between income and current consumption (Browning and Lusardi, 1996.

p.1798).

Savings – accumulated value of past saving sometimes referred to as wealth (Blanchard &

Sheen, 2009. p.663)

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TABLE OF CONTENTS

PLAGIARISM DECLARATION II

ACKNOWLEDGEMENTS III

ABSTRACT IV

GLOSSARY OF TERMS V

TABLE OF CONTENTS VI

LIST OF TABLES IX

LIST OF FIGURES IX

CHAPTER ONE 1

1 INTRODUCTION 1

1.1 CONTEXT OF THE STUDY 1

1.1.1 PROBLEM STATEMENT 5

1.2 JUSTIFICATION OF THE RESEARCH 6

1.3 RESEARCH QUESTIONS 8

1.5 LIMITATIONS OF THE STUDY 8

1.6 ASSUMPTIONS 9

1.7 ETHICS 10

1.8 ORGANIZATION OF THE THESIS 11

CHAPTER TWO 12

2 LITERATURE REVIEW 12

2.1 INTRODUCTION 12

2.2 DEFINITIONS 12

2.3 THEORETICAL FRAMEWORKS OF SAVING 13

2.4 EVIDENCE OF SAVING FROM LITERATURE 14

2.4.1 INFLUENCE OF CULTURAL FACTORS ON SAVING BEHAVIOUR 14

2.4.2 CULTURAL FACTORS 14

2.4.3 PROPOSITION 1 16

2.4.4 ROLE OF FINANCIAL LITERACY IN SAVING 16

2.4.5 FINANCIAL LITERACY 16


2.4.7 EFFECT OF CREDIT AVAILABILITY 18

2.4.8 CREDIT AVAILABILITY 18

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2.5 CONCLUSION OF LITERATURE REVIEW 21

2.5.1 PROPOSITION 1: 21



CHAPTER THREE 22

3 RESEARCH METHODOLOGY 22

3.1 INTRODUCTION 22

3.2 RESEARCH METHODOLOGY / PARADIGM 22

3.3 RESEARCH DESIGN 24

3.4 STUDY POPULATION AND SAMPLE 26

3.4.1 POPULATION 26

3.4.2 SAMPLE AND SAMPLING METHOD 26

3.5 THE RESEARCH INSTRUMENT 28

3.6 PROCEDURE FOR DATA COLLECTION 29

3.7 DATA ANALYSIS AND INTERPRETATION 31

3.8 CONSISTENCY MATRIX 32

CHAPTER FOUR 35

4 RESEARCH FINDINGS, DISCUSSION AND INTERPRETATION 35

4.1 INTRODUCTION 35

4.2 OBJECTIVE 1 36

4.3 OBJECTIVE 2 41

4.4 OBJECTIVE 3 48

CHAPTER FIVE 53

5 RESEARCH CONCLUSION AND RECOMMENDATION 53

5.1 INTRODUCTION 53

5.2 CULTURAL FACTORS AND SAVING 53

5.3 FINANCIAL LITERACY AND SAVING 54

5.4 CREDIT AVAILABILITY AND SAVING 54

5.5 RECOMMENDATIONS 54

5.6 PROPOSED FUTURE RESEARCH 55

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REFERENCES 56

APPENDICES 61

APPENDIX A: ETHICS CLEARANCE 61

APPENDIX B: NOTICE TO RESPONDENTS 62

APPENDIX C: INSTRUCTIONS FOR DISTRIBUTION OF QUESTIONNAIRE 63

APPENDIX D: RESEARCH INSTRUMENT 64

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LIST OF TABLES

Table 1: Comparative summary of qualitative and quantitative research approaches……23

Table 2: Banking employees per occupational category and by province………………..27

Table 3: Profile of respondents…………………………………………………………....27

Table 4: Results from the pilot test of questionnaire…………………….………………..28

Table 5: Survey delivery platforms……….………………………………………………30

Table 6: Consistency matrix…………..…………..…………………………………….…33

Table 7: Paired observations - saving when growing up and currently save………………39

Table 8: Regression analysis - Discuss money with kids………………………………….40

Table 9: Paired observations for hypothesis 2 under simulation 1……………………..…43

Table 9: Paired observations for hypothesis 2 under simulation 2…………………..……44

Table 11: Mean vs hypothesized value…………………………………………………...51

LIST OF FIGURES

Figure 1: Gross national savings ratio and gross domestic product movements from 1980

to 2015…………………………………………..………………………………………….3

Figure 2: Relationship between savings, budget deficit or surplus and economic growth ..4

Figure 3: Individual & household savings as a component of total savings ....…….……...6

Figure 4: Household debt and personal saving rate…………………….………………....19

Figure 5: The Survey process……………………………………………………..………25

Figure 6: Province from where respondent comes from…………………………………..36

Figure 7: Regression between province and saving behaviour……………………………37

Figure 8: Regression between growing up and currently save……………………………..38

Figure 9: Regression between last expenditure knowledge and saving……………………41

Figure 10: Regression between budget skills and saving account…………………………42

Figure 11: Q 17 Interest rate - Numeracy………………………………………………….45

Figure 12: Q 18 Inflation…………………………………………………………………..46

Figure 13: Q 19 Risk diversification………………………………………………………47

Figure 14: Regression between credit availability and saving…………………………….48

Figure 15: Regression between high debt service ratio and saving………………………..49

Figure 16: Responses to whether access to credit hinders saving or not…………………..50

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CHAPTER ONE

1 INTRODUCTION

This chapter sets the context under which the phenomenon being investigated is found. It

discusses the motives and importance of saving. The problem statement, research questions

and objectives including the justification and limitations of the study are also explored. The

chapter concludes by looking at the assumptions made and ethical issues surrounding the

study. The structure of the thesis is also outlined in this chapter.

1.1 Context of the study

The Republic of Zambia is a landlocked, resource rich country in Southern Africa with

massive mineral endowments and agricultural potential. It is geographically large and

sparsely populated with 15.5 million people. It has capitalised on these factors and is now a

lower middle-income country that experienced robust growth in the past decade. It was

among the 10 fastest growing economies in Sub Sahara Africa in 2012 (Central Statistical

Office, 2016; De La Fuente, Murr & Rascon, 2015).

Zambia inherited a free economy and a multi-party political system at the time of its

independence from Britain in October 1964. At the time, it was a relatively wealth country

with gross domestic product per capita of US$238 compared to that of South Korea which

stood at US$120 (World Bank, 2016a; 2016b). However, in 1969, Zambia nationalised or

acquired a major stake in all foreign owned companies in the so-called Mulungushi

economic reforms. This effectively introduced a mixed type of economy where the state and

the private sector were all participants in the economy. While the private sector was free to

be involved in the running of the economy, the State was a major player in the running of

the economy through state owned enterprises. The introduction of a one party state system

of government in 1972 followed the Mulungushi economic reforms. With no opposition

parties or politically active civil society groups to provide checks and balances to

Government’s management of national economic and political affairs, the economic

fortunes began to deteriorate. By 1990, South Korea GDP per capita stood at US$6642

surpassing that of Zambia’s which was at USD$404 clearly indicating the different paths

taken by the two respective countries towards their political and economic development

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(World Bank, 2016a; 2016b). This deterioration led to increased political activism in the

country culminating in the re-introduction of multiparty politics and free economy in 1991.

The State privatised most of the state owned companies and opened up the economy. After

implementing an austerity economic programme recommended by the International

Monetary Fund (IMF), the country’s economy began to grow. From a negative growth of -

13.1% in 1994, the country has been on an upward growth trajectory save for 1998 when

the country registered a negative economic growth of -0.4 (figure 1). Average annual growth

between 2001 and 2012 was about 6%. The growth has somewhat tempered in light of a

recent slump in the copper prices, Zambia’s main foreign exchange earner with the economy

growing by 3.5% in 2015.

Underpinning this economic performance has been the emergence and growth of the

Zambian middle class. This economic growth has enabled unprecedented public and private

infrastructure development in roads, hospitals, schools, housing and shopping malls to take

place. Up and until 2008, Zambia depended on the Brentwood institutions (IMF and World

Bank) for financing most of her public infrastructure development. However, since the last

programme ended in 2011, the country has been funding a large part of its public

infrastructure from domestic borrowing and lately, in the last 3 years, from issuance of

sovereign bonds. So far, two bonds have been issued amounting to US3 billion. However,

financing of public infrastructure through external borrowing as the case has been by

issuance of sovereign bonds has exposed the country to vagaries of external economic

factors outside the control of the country.

As alluded to earlier, domestic and external borrowing has been financing both private and

public infrastructure. Domestic borrowing has been possible due to the increasing national

savings in the last decade as measured by the GNS ratio. A negative GNS ratio indicates

that the overall economy is spending more income than it earns, thereby drawing down

national wealth (dis-saving) while a positive number is a good indicator of the general

financial wellbeing of the economy in terms of its ability to deal with internal and external

uncertainties without having to borrow for consumption. There was a meteorite increase in

the GNS ratio in Zambia during the period 2001 to 2015. As seen in figure 1, the GNS ratio

increased from about 3.2% in 2001 to 31.1% in 2015 reaching a peak of 41.3% in 2006 just

before the eruption of the 2007/8 financial crisis. GNS ratio dropped to 26.3% in 2008,

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before returning to around 38.3% in 2011. Since then, the ratio has been fluctuating between

31 – 37% ranges. Compared to many developing countries, Zambia is still among the top

savers. According to Economic Watch (2016), Zambia was 21st on the world rankings in

saving in 2015 at 31.1% while the average world GNS value for the same period was 17.5%.

Fig. 1. Gross national savings ratio and gross domestic product movements from 1980 to2015. Source:

International Monetary Fund, World Economic Outlook Database, April 2016 and Author’s own

computations.

Importance of saving

Saving has been an area of interest to economists since economics was organised and

recognised as a science given the role it plays in the economic development of a nation.

Most literature on saving however, can be traced back to 1950s with work done by Solow

and Swan where they showed the interrelationship between savings, capital formation,

technological progress and economic growth (Blanchard & Sheen, 2009). Other works

include the Life Cycle hypothesis and Permanent Income hypothesis propounded by Franco

Modigliani and Richard Brumberg and Milton Friedman respectively (Browning & Lusardi,

1996; Friedman, 1957). Kazmi and Bilquees (1993) argue that... “Savings provide the most

important economic link between the past, present and future of a country. An adequate rate

of national saving is regarded as an essential condition for achieving targets in the

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investment and growth” (p1313). Savings are used for domestic investments, which in turn

impacts economic growth. Posner and Bovbjerg (1995) illustrate this relationship in figure

2 in their study of the impact of USA national budget deficit on savings in which they argued

that deficits in the end affect economic development where such deficits are financed by

private savings thereby negatively affecting private investments, which are key to long-term

economic development.

Figure 2: Relationship between savings, budget deficit or surplus and economic growth

Adapted from “Budget Policy and The Long Run Future” by P.L. Posner and B.D. Bovbjerg,1995,

In Proceedings of the Annual Conference on Taxation Held under the Auspices of the National Tax

Association-Tax Institute of America p. 72

Later studies, such as the one conducted by Cohn and Kolluri (2003), buttress this argument

by stating that…“saving is the ultimate source of physical capital formation and plays a

fundamental role in determining the “wealth of the nation” (p.1199). The importance of

savings in the economic growth / development of a given country, however, remains a hotly

debated issue among economists and scholars. While most of them acknowledge that there

is a positive link between national savings and economic growth, the causality issue is far

for settled (de Laiglesia & Morrison, 2008).

Households are responsible for a substantial part of the saving in both industrial and

developing countries (Schmidt-Hebbel, Webb & Corsetti, 1992). Households play a key role

in capital formation and economic development through savings. Various studies

investigating variables that may affect household savings have been conducted over time.

According to Jongwanich (2010), there is correlation between economic growth and

increase in household savings. As the economy grows, an increase in household savings

rises reflecting better economic conditions that may entail more disposable income.

Non-federal savings

Federal deficit / surplus

Private investment

GDP National savings

Capital (plant & equipment)

Productivity

Labour

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Without increased savings, the country will resort to external borrowing that will make the

country vulnerable to external financial and economic shocks. For example, an increase in

the lending interest rates in external borrowings may result in an increase in the loan

repayments leading to a reduction in resources available for other investments. The higher

the GNS ratio the less vulnerable the country is to external financial and economic shocks.

Countries that have demonstrated sustained economic growth, as the case is with South

Korea, can also be shown to have relatively high GNS ratios indicating that sustainable GNS

ratio is correlated to sustainable economic growth (Jongwanich, 2010). GNS for South

Korea has averaged 32.5% for the period from 1980 to 2015 (World Bank, 2016a). A

country’s GNS ratio, in relation to other countries, can act as a barometer for measuring

economic growth (Obi, Wafure, & Menson, 2012).

Motives for saving

Individuals and households have different motive for saving. According to Kasilingam &

Jayabal (2011), however, there are four saving motives emphasised by neo-classical

economists. These include “the desire 1) to maintain consumption in the face of income

fluctuations, particularly during retirement; 2) to prepare for income shocks and other

emergencies (precautionary saving); 3) to transfer wealth to future generations (bequest

motive); and 4) to purchase consumer durables and to spend for children education and

vacation (target saving)” (p.68). The ability to save is a function of one’s income and

willingness to save. InterMedia (2016) citing a Zambia 2015 Finscope study on financial

inclusion found that Zambians perceive savings as of critical importance and save to afford

their needs, and as a reserve when in need of emergency funds. Despite the perceived

importance however, the study found that Zambians have difficulties to make ends meet and

may not often have any additional income at the end of a month though they do not fall

completely behind on expenses.

1.1.1 Problem Statement

Personal and household savings are not growing at a rate that would sustain the economic

development the nation aspires to achieve. While the GNS ratio for Zambia has been rising,

personal and household savings, which is part of the components used in the calculation of

GNS ratio, has not been growing in proportionate to the overall growth as seen in figure 3

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and the underlying causes contributing to this need to investigation. Individual and

household savings as a percentage of total savings stood at 27% in 2005. By the end of 2015,

the contribution of individual and household savings to total savings had plummeted to

19.5%. According to the World Bank (2016b), the GNS ratio for Zambia stood at 31% in

2015 but projected to decline to 26% in 2016 indicating the need for the country to sustain

or increase the GNS ratio. However, in a country where 54.4% of the population lives below

the poverty line (Central Statistical Office, 2016), it is questionable whether the country can

sustain the current levels of GNS ratio.

Figure 3: Individual & household savings as a component of total savings

Source: Bank of Zambia (2016) and Author’s own computations

The middle class of any society plays a key role in the economic development of its society

(Kharas, 2010). With the steady growth of the Zambian economy over the last decade, a

robust middle class has emerged of which banking employees are part. It is critical therefore,

to understand the determinants of saving amongst this segment of the middle class.

1.2 Justification of the Research

This study is significant in two ways. In the first instance, the study would help policy

makers, bankers and investment managers to design interventions that:

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Can help in sustaining or increasing the GNS ratio through fiscal policy formulation

and introduction of innovative products

Encourage accessibility to savings and investment information.

Change people’s cultural perspectives, customs and behaviours by making savings

and investments desirable.

In order to design policies to promote investments and saving, it is imperative to understand

determinants to saving. The study was aimed at investigating whether or not identified

variables or factors were pertinent to sustaining and increasing savings among the Zambian

middle class for sustained economic growth. In this context, it is investigative research.

In the second instance, this study was meant to contribute to the body of knowledge in the

focus area of this study. While there is abundant literature on the subject for other countries

or groups of countries, there has been a dearth of literature in the case of Zambia. There are

few studies sighted by this researcher on this subject. One report was for the period from

1998 to 2004 that investigated whether interest rates, income and inflation were variables

that influenced national savings or not. This is the period when the country experienced

declining personal and household savings. These studies, however, found that the three

variables were not correlated (Mususu, 2006).

In another study, Maimbo and Mavrotas (2008) identified foreign exchange liberalisation,

HIV/Aids pandemic, absence of rural financial savings institutions, parastatal sector

reforms, poor state of economy, bank closures during the period from 1995 to 1998 and

increase in property for private and commercial purposes as factors affecting savings

mobilisation in Zambia. However, these factors may not apply in the current environment

given the strides recorded in the social, economic and financial spheres of the Zambian

society. For example, the HIV Aids pandemic has largely been contained and HIV Aids

prevalence rates are declining while public sector reforms have abated since the last IMF

program ended in 2011. The Zambian economy has also shown steady growth in the last ten

years.

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1.3 Research questions

The research sought to answer the following primary question: “What are the determinants

of saving among the Zambian banking employees?” Literature review suggested that

among the various factors that influence individual and household saving was culture,

financial literacy and credit availability. These factors were examined to see if they were

determinants of saving among Zambian banking employees. The following sub questions/

statements were critical in helping to answer the primary question of the research:

1. Is the saving culture (a habit of saving one’s income) a function of one’s cultural

upbringing?

2. Is there a relationship between financial literacy and saving?

3. Is credit availability a hindrance to saving?

1.4 Research objectives

The main objective of the study was to examine the determinants of saving among banking

employees in Zambia. Based on the research questions, the objectives included;

1. To examine the effect of ethnic background on saving behaviour of Zambian

banking employees.

2. To assess the relationship between financial literacy and saving.

3. To examine the effect of credit availability on saving.

1.5 Limitations of the study

Savings is a broad economic activity. Domestic savings comprise of Government, corporate

and personal/household savings. The scope of the research only covered personal and

household savings. Government and corporate savings were not in the scope of the research.

Further, given that the GNS ratio is derived from what is captured in the country’s official

accounting books, the research was restricted to formal savings as in the form of bank

deposits. Informal savings did not form part of the study.

The research focused on the determinants of saving among the Zambian middle class. The

key focus area within the middle class category was the banking employees. Only Zambia

banking employees were included in the study. Non - Zambia banking employees were

excluded. Further, the research was conducted among banking employees working within

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Lusaka City and as such may not be representative of the entire banking employee

population. However, considering that most studies on saving to some extent is affected by

inaccurate or lack of data, it was apparent that focusing on one specific sub segment of the

population located within a particular geographical area, could be of great help in

understanding the complex relationship between saving rate and its determinants (Ozcan,

Gunay & Ertac, 2003).

Other limitations to this research included the following situations:

1. Limited time within which to complete the research, which may lead to inaccurate or

wrong findings. This was mitigated by limiting the sample size and targeting a

population that has adequate understanding of the phenomenon being investigated.

2. Where there was non-response from some participants or where they were not willing

to participate in the study and therefore not being able to get representative set of data

from which conclusions could be drawn. This limitation was mitigated by targeting a

bigger sample than would have been required for this research.

3. Researcher’s bias. This limitation was mitigated by ensuring that the questionnaire was

tested on a pilot basis before being applied to the study sample.

4. Non-probability sampling approach adopted making the sample to be non-

representative. This limitation was mitigated by :

Taking samples from 14 out of 18 banks operating in the country.

Adopting a stratified approach by taking samples from different categories of

staff. For the purposes of this research, three categories of staff were identified

namely: clerical, managerial and executive staff. Further, the questionnaire was

distributed across a wide spectrum of staff in each category (operations, sales,

finance etc.) to avoid the possibility of having respondents from the same unit

1.6 Assumptions

The following assumptions were made in relation to the research.

1. By focusing on banking employees to study the phenomenon, it was assumed that

the participants had sufficient knowledge and understanding of financial and

economic fundamentals in the market/economy for them to be able to clearly

articulate answers to questions posed to them.

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2. Since the study was limited to the banking employees within Lusaka City, the sample

was not fully representative of the banking staff population. However, by choosing

a sample from the country’s capital city that interacts and serves a diverse customer

base, they held rich information about the phenomena I was investigating and it was

assumed that their responses to survey questions would be representative of the

population being studied.

3. Ethnic groupings from one province / region of the country were assumed to

culturally homogenous due to their proximity to each other.

1.7 Ethics

University of Cape Town stipulates that all research involving human subjects be evaluated

and approved by Commerce Faculty Ethics in Research Committee prior to collection of

data to ensure that the researcher was in ethical compliance with regard to their study. The

research proposal was evaluated and approved by the University’s committee and an

approval letter can be found under Appendix A. Ethical considerations were looked at from

various angles of responsibility to which the researcher has ethical obligations – society,

environment, subjects and practice of science. One ethical consideration was the danger of

disclosure of subject’s personal and organisational data in the process of collection of data.

The researcher paid close attention to the research instrument and the structure of data

collection methods to ensure that such danger was mitigated. Data was masked so that it did

not reveal who the respondent was.

Another ethical consideration made at the beginning of data collection was on the use of

paper in the production of reports and disseminating the research instrument. It is a known

fact that trees are used to manufacture paper and that trees are critical in the reduction of the

carbon footprint. Consideration was made to cut use of paper to the minimum by utilising

electronic means of data collection and storage of reports. However, due to the slow

response rate experienced in receiving data electronically, about 50% of the data was

collected through physical distribution of the questionnaire which method saw an

improvement in the response rate.

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Consideration was also made not to use deception or manipulation in conducting the study

or during collection of data. There was a temptation of not informing respondents of their

right to consent or refuse to participate in the study during data collection for fear of not

getting the anticipated sample size. However, respondents were notified through an

introduction letter accompanying the survey instrument as to their rights in relation to this

study. (See Appendix B).

1.8 Organization of the thesis

The research is be structured as follows.

Chapter 1 deals with the introduction or background context within which the study is set.

It will discuss the purpose of the study, the importance and motives of saving and the main

problem the study is trying to address. This chapter will further discuss the research

questions, limitation to the study, assumptions and ethics associated with the study and a

definition of terms used in the study.

Chapter 2 will discuss the theoretical framework of saving and results of the literature

review conducted on the following determinants of saving: availability of credit, cultural

factors and financial literacy.

Chapter 3 discusses methodology adopted to conduct the research. This includes a

discussion of research design, population and sample sampling methods and research

instrument used and procedure for data collection.

Chapter 4 analyses the data collected and the findings. The analysis of data will be

accompanied by a discussion of the findings.

Chapter 5 will conclude, make recommendations and suggest future research. References

and appendices will follow chapter 5.

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CHAPTER TWO

2 LITERATURE REVIEW

2.1 Introduction

This chapter surveys literature in individual and household savings to determine whether

cultural factors, financial literacy and availability of credit are determinants of saving

behaviour among Zambian banking employees. It will cover areas such as the definitions

relevant to the topic; determinants of savings and summary of literature review.

2.2 Definitions

Browning and Lusardi (1996) define saving as “simply the residual between income and

current consumption” (p.1798). Blanchard & Sheen (2009) differentiate the various types

of saving by stating that saving is a sum of private and public saving. Private saving is saving

by consumers comprising of individuals, households, corporates or firms and is equal to

income minus taxes and expenditure. Public saving is residual of taxes minus government

expenditure. The main thrust of this study was about private saving and in particular,

individual and household saving. The definition of saving for purposes of this study is that

adopted by Browning and Lusardi (1996): the residual between income and expenditure for

individuals and households. The definition adopted provides an easy and simple

understanding of an otherwise complex topic.

Expanding further on the definition by Browning and Lusardi, Chauke (2012) posits that

saving is a long-term or short-term decision about what to do with residual income after

expenditure and that it is a function of income, expenditure, tax, interest rates, inflation, the

banking system, family structure, investment opportunities and political stability.

F(S) = {Y, E, T, ir, r, Bs, Fs, I, Ps}

Where; Y=Income, E=Expenditure, T=Tax Rate, ir=Interest rate, r=Inflation, Bs=Banking

System, Fs=Family Structure, I=Investment Opportunities and Ps=Political Stability.

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2.3 Theoretical frameworks of saving

There are two most well-known theories of private saving (Uremadu, 2009). The first one

is the Permanent Income Hypothesis (PIH) propounded by Friedman (1957) where he

explored the relationship between consumption and income. Friedman theorised that income

comprised of two components: permanent and transitory, where permanent income

consisted of factors an individual or household regards as sources of wealth and transitory

income being other income acquired by chance or accident hence not permanent. Similarly,

consumption comprised of permanent and transitory consumption where the permanent

component consisted of factors that were permanent in nature such as rent or food and

transitory component being consumption specific to a particular individual or household

such as an unusual illness or an opportunity to make a specific purchase. He further proposed

that transitory income by its very nature (chance or accidental income) does not have an

impact on consumption. Meghir (2004) sums up the basic hypothesis posited by Friedman

by stating, “Individuals consume a fraction of this permanent income in each period and

thus the average propensity to consume would equal the marginal propensity to consume.

The propensity itself could vary with a number of factors, including the interest rate and

taste shifter variables, or could reflect uncertainty” (p.294). Consumers base their

consumption habits on long-term view of an income measure and may borrow to meet

immediate consumption needs in anticipation of future income (Meghir, 2004).

Understanding income and consumption patterns of individuals or households has

implications on saving.

The second one is Life Cycle Model (LCM). The life cycle model of consumption originally

proposed by Modigliani and Blumberg (1954) and Ando and Modigliani (1963) is the

dominant framework in economics for analysing aggregate consumption and saving

behaviour (Palumbo, 1999). LCM is modelled built around the consumption / savings

behaviour of the householder. According to Ando and Modigliani (1963), householders

spread their lifetime consumption over their lives by accumulating savings during earning

years and maintaining consumption levels during retirement. Age structure is likely to

influence income as during childhood period, the householder earns less money but

consumes relatively large amount of goods thereby saving less in this period. The

householder saving becomes positive as householder grows and reaches a certain age but

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becomes a dis-saver once he retires and, income drops to a level below consumption. This

implies that over and above income and real interest rates, savings behaviour can vary

systematically from individual to individual according to age structure. In summary,

according to Jongwanich (2010), “the basic LCM model postulates that the savings

behaviour of the householder is determined by current income (Y), income growth (GY),

real interest rates (r) and population structure (P)” (p.968). This is illustrated in the following

equation:

S = f(Y,GY,r,P)

Saving (S) is a function of Y, GY, r and P. An increase in the Y and GY variables tend to

increase private saving while the effect of r is inconclusive (Jongwanich, 2010). The effects

of P have been alluded to above.

2.4 Evidence of saving from literature

2.4.1 Influence of cultural factors on saving behaviour

Literature suggests that cultural factors can affect someone’s saving behaviour. There is

need to investigate whether this phenomenon exists among Zambian banking employees as

a determinant of saving.

2.4.2 Cultural factors

Among several definitions of culture, Telleria (2015) defines culture as “a set of values,

principles and standards shaping and conditioning our behaviour, usually biased towards

the existence of tradition” (p.257). In seeking to understand social phenomena like low

saving rates, Shepherd and Stephens (2010) argue that one needs to pay attention to the role

of culture. They posit that “an integrated cultural approach that considers the ongoing

interdependence between the behaviour and psychological processes of the individuals and

their sociocultural context is essential for social scientists who seek to explain behaviour

like low saving rates and for policy makers who seek to design interventions to change

behaviours” (p.353). Gatina (2014) notes that cultural diversity can play a key role in

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explaining the level of saving in a country. This is because as people move from place to

place, they carry along with them customs and traditions from their place of origin that may

affect their behaviours including that of saving.

To explain international disparities in saving rates, cultural effects has been one of the

variables that suggested accounting for such disparities (Carroll, Rhee & Rhee, 1994).

However, there are difficulties associated with testing a hypothesis premised on national

culture using cross-country aggregate data, as it (culture) is an unobservable variable

(Carroll et al., 1994).

According to studies conducted by Carroll et al (1994) on immigrants to Canada, they found

no evidence to support the view that cultural effects are a determinant in saving rates across

countries. Their study examined whether cultural factors have any influence on the saving

behaviour by comparing saving habits of migrants to Canada from countries with different

saving rates. However, they admit that their findings may be inconclusive as data used only

reported the immigrants’ place of origin in broad terms and the sample size was small.

Other studies appear to support the view that culture affects saving rates. In a study of

immigrants to United Arab Emirates conducted by Al-Awad and Elhiraika (2003) using

household survey data covering 3206 households, they found that migrants from India and

Pakistan in particular had higher saving rates in comparison to others despite having

relatively low incomes. This finding suggests that saving behaviour may vary across

migrants from different places of origin. Perhaps what could help in understanding this

finding is that Al-Awad and Elhiraika (2003) studies departed from those by Caroll et al

(1994) and others in a number of ways. Firstly, they used a large sample (3206 households);

secondly, migrants come to UAE for finding a job and accumulating savings. Thirdly, there

is little or no assimilation between migrants and nationals. This researcher, however,

disagrees with the conclusion of Al-Awad and Elhiraika. By their own admission that

migrants come to UAE to find a job and accumulate savings, one can argue that the increase

in saving is due to precautionary motives than to cultural factors.

In a recent study conducted in Australia, Gatina (2014) found evidence that cultural effects

affected saving rates. Data from the Household, Income and Labour Dynamics in Australia

(HILDA) Survey to obtain personal characteristics of individuals and country data from the

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World Development Indicators of the World Bank was used for this study. The study

examined determinants of household saving rates of Australian residents and whether a

difference exists in saving behaviour between Australian-born and foreign-born individuals.

Further, sampling was restricted to immigrants to test whether a home-country effect existed

on their saving habits. The study then compared the saving rates of immigrants to the saving

rate in their respective home country. This examination revealed that immigrants in

Australia save less in comparison to their native-born counterparts.

2.4.3 Proposition 1

Ethnic or cultural background of individuals or households affects saving behaviour.

2.4.4 Role of financial literacy in saving

It is important to examine the role of financial literacy as an enabler or disabler of saving if

action is required to make any interventions necessary to promote a saving culture.

2.4.5 Financial Literacy

The importance of financial literacy in saving or financial behaviour is available in literature

(Huston, 2010; Beckmann, 2013; Klapper, Lusardi & Panos, 2013). The mortgage crisis,

high household bankruptcy rates and consumer over indebtedness experienced in the recent

economic recession have catapulted financial literacy to prominence to a point where it has

the attention of public policy makers (Huston, 2010). After recognising the absence of a

definite definition of financial literacy, Huston (2010) defines it as…. “Measuring how well

an individual can understand and use personal finance-related information” (p.306).

Although financial literacy and financial knowledge is used interchangeably, Huston (2010)

argues that there is a difference stating that “financial knowledge is an integral dimension

of, but not equivalent to, financial literacy” (p.307).

In order to make sound financial decisions, financial literacy is an important component of

this process (Lusardi, Mitchell & Curto, 2010). Knowledge on banking products, interest

rates and other financial instruments can help boost savings. However, knowledge of

savings and investments was low in some studies conducted (Lachance & Cloutier, 2009;

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Tang & Peter, 2015) hence the need for financial education. To test knowledge of basic but

fundamental financial concepts, there are three questions asked for this purpose (Lusardi et

al., 2010). The first two questions test the knowledge about inflation and interest to see if

one possesses basic financial numeracy while the third evaluates one’s knowledge of risk

diversification, a crucial factor in making an informed investment decision.

Lachance & Cloutier (2009) undertook a study to evaluate young adults’ knowledge,

practices and attitudes towards savings and investments by sampling 966 young adults in

the province of Quebec, Canada. Their findings showed that knowledge about savings and

investments was rather low. Lusardi (2008) postulates that low financial literacy levels and

lack of financial information affect the ability to save and to secure a comfortable retirement.

Beckmann noted that individuals, who are financially literate, are more likely to save using

more than one interest-bearing saving instrument and invest in pension funds. Financially

literate individuals are likely to perform better in terms of saving money, budgeting and

controlling expenditures (Yu, Wu, Chan & Chou, 2015). To the contrary, financial illiteracy

can affect the ability of someone to better financial decisions on savings and investments

(Tang & Peter, 2015).

Examining the impact of saving behaviour in Romania using internationally comparable

indicators, Beckmann (2013) concluded that financial literacy has a positive impact on

saving. The analysis, based on data from the Euro Survey of the Austrian Central Bank,

covered ten countries in Central, Eastern, and South-Eastern Europe (Albania, Bosnia and

Herzegovina, Bulgaria, Croatia, Czech Republic, FYR Macedonia, Hungary, Poland,

Romania, and Serbia). Klapper et al., (2013), however, argue that “correlation between

financial literacy and behaviour does not mean causation and that it is important to find a

causal link” (p.3906). This is due to challenges in obtaining an exogenous source of

variation in financial literacy.

According to Lusardi et al, (2010), there is an association between each of the following

and financial literacy: gender, educational attainment and peers. They found that men were

more financially literate than women while young people with mothers with a college degree

were financially literate compared to their counter parts whose mothers did not have college

degrees. These findings are consistent with other recent studies which found, gender,

financial experience, financial education and parents’ financial experience as some of the

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variables that have been found to be key to financial knowledge among the young (Yu et al,

2015; Tang & Peter, 2015).

2.4.6 Proposition 2

Financial literacy contributes to sound financial decisions and can affect the individual’s

ability to save and invest.

2.4.7 Effect of credit availability

The easy with which one can access credit may affect saving for precautionary motives.

Credit availability therefore is a variable to study as to whether it is a determinant of saving

or not.

2.4.8 Credit availability

The effect of availability or non-availability of credit on households has been an area of

interest for many researchers. From literature reviewed, credit can affect household saving

in a negative or positive way. Jongwanich (2010), through an in-depth case study of

Thailand during the period 1960 to 2004 examined possible determinants of household and

private savings behaviour. The study found that inflation, an increase in economic growth

and terms of trade, all had a significant positive impact on private and household savings

rates. In contrast, availability of credit tended to reduce private and household saving rates.

The study concluded that when households could borrow freely against future cash flows,

savings rate tended to reduce. The relaxation of consumer borrowing constraints affords

households an alternative source of funds they can use to meet precautionary saving motive

(Glick & Lansing, 2011). Deaton (1991) had earlier put it differently stating that

“precautionary motives interact with liquidity constraints because the inability to borrow

when times are bad provides an additional motive for accumulating assets when times are

good” (p.1222).

Glick & Lansing (2011) studied the relationship between household credit and personal

saving in the US. By studying changes in the saving rate from the mid-1960s to 2010, they

established that changes over time in the availability of credit could explain 90% of the

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variances in the savings rate. The era of expanding credit availability for individuals and

households that contributed to a dramatic increase in financial leverage as measured by the

household debt to personal disposable income ratio coincided with a period of declining

saving rates. The study found that saving rate is negatively correlated with the household

debt ratio (see figure 4).

Personal saving rate (left scale)

Household debt/ disposable income

(right scale)

14 % %

12

10

8

6

4

2

0

60 65 70 75 80 85 90 95 00 05 10

140

130

120

110

100

90

80

70

60

50

Year

Figure 4: Household debt and personal saving rate

Source: Adapted from Glick & Lansing (2011)

In recent studies conducted in the US by Carroll, Slacalek and Sommer (2013) and using

historical data over a 45-year period, they found strong evidence that credit availability was

one of the factors driving US household saving. They theorised that three factors affect

saving and that these might vary substantially over time. In the first instance, since the

precautionary motive diminishes as wealth rises; the saving rate is a declining function of

market resources. In the second instance, because an expansion in the credit availability

reduces the target level of wealth, looser credit conditions lead to lower saving. Lastly, an

elevated unemployment risk results in greater saving as a precautionary measure. They

conclude by arguing that “the relentless expansion of credit supply between the early-1980s

and 2007 (likely largely reflecting financial innovation and liberalization), along with higher

asset values and consequent increases in net wealth (possibly also partly attributable to the

credit boom) encouraged households to save less out of their disposable income” (p. 25).

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Easy availability of credit manifests itself in rising household debt. Hence, there is no

incentive for households to save.

In contrast to availability of credit, non-availability of credit can force households to save

more at present in order to make lump sum payments in future. The resultant effect of such

behaviour is an increase in savings. Non-availability of credit are because of imperfect credit

market conditions. Jappelli and Pangano (1994) claim that if household cannot access the

amounts they want to borrow, aggregate saving will be higher than in markets with perfect

credit conditions. Using data from 19 countries (including all the main OECD countries),

they tested whether or not the liquidity constraints helped to explain the international

differences in national saving rates, as articulated in the overlapping generational model and

whether or not the effect of growth on saving is greater where liquidity constraints are more

pervasive. They introduce the concept of forced saving where for example a mortgage credit

provider stipulates that the borrower contribute a certain amount of the loan value before

the mortgage disbursement. This results in an increase in household saving. Jappelli and

Pangano’s findings are supported by Ozcan et al (2003) who state that “borrowing

constraint, if tight, can prevent people from borrowing extensively, thereby possibly

inducing them to save for contingencies and for the purchases of houses, cars, etc” (p.1408).

Deidda (2014) investigated this phenomenon in Italy. Using a 3-year (1989–1993) pooled

cross section of the Bank of Italy Survey of Household Income and Wealth (SHIW) data,

the study found that precautionary savings and non-availability of credit are complementary.

Households that face simultaneously both liquidity constraints and uncertainty have a

stronger precautionary motive to save than unconstrained ones. However, Carroll (2001)

argues contrary to the view that liquidity constraints induce households to save by stating

that “precautionary saving motive can generate behaviour that is virtually indistinguishable

from that generated by a liquidity constraint, because the precautionary saving motive

essentially induces self-imposed reluctance to borrow (or to borrow too much)” (p.32).

2.4.9 Proposition 3

Credit availability reduces the precautionary saving motive thereby affecting the level of

saving.

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2.5 Conclusion of Literature Review

Culture, financial literacy and credit availability are among determinants of saving

suggested in literature. Below is a presentation of a summary of the review on these three

determinants.

Cultural factors: Studies on the effect of cultural factors on saving have yielded different

results with some suggesting that there is a positive effect while some have been

inconclusive. The fact that some studies have shown a positive effect while others are

inconclusive demonstrates the complexity of measuring cultural factors as a determinant.

Nevertheless, it may still be relevant in explaining differences in saving rates among

different cultural identities.

Financial literacy: The level of an individual’s financial literacy affects their performance

in terms of saving money, investing, budgeting and controlling costs. High financial literacy

affects these behaviours positively while the opposite happens with low financial literacy.

Gender and educational attainment are linked to financial literacy with women showing

lower financial literacy in comparison to men while higher financial literacy increases with

educational attainment.

Credit availability: Where credit is easily available and no credit constraints exist, studies

have shown that there is a negative impact on saving. There is less motivation to save as

saving is easily replaced by debt. Credit is a fall back measure to saving.

2.5.1 Proposition 1:

Ethnic or cultural background of individuals or households affects saving

behaviour.


Financial literacy contributes to sound financial decisions and can affect the

individual’s ability to save and invest.


Credit availability reduces the precautionary saving motive thereby affecting

the level of saving.

Table 6 also summarises the literature review in form of a consistency matrix.

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CHAPTER THREE

3 RESEARCH METHODOLOGY

3.1 Introduction

This chapter covers the research methodology paradigm and design, study population and

sample, the research instrument, procedure for data collection, analysis and data

interpretation and limitations. The purpose is to provide information in the manner the

research was conducted to arrive at the conclusions made.

3.2 Research methodology / paradigm

There are mainly two domains of research from literature namely quantitative research and

qualitative research (Adams, Khan & Raeside, 2014). Mixed research is a methodology that

combines both qualitative and quantitative approaches to research. In defining quantitative

research, Adams et al. (2014) write, “quantitative research refers to the type of research that

is based on the methodological principles of positivism and neo-positivism, and adheres to

the standards of a strict research design developed prior to the actual research. It is applied

for quantitative measurement and hence statistical analysis is used” (p.6). On the other hand,

they describe qualitative research as the type of research that uses a number of

methodological approaches based on different theoretical principles such as

phenomenology, Social Interactionism and hermeneutics and uses non-statistical methods

of data collection and analysis. It describes reality as lived by the respondents and aims at

exploring social interactions.

One assumption of a quantitative methodology is that the researchers approach the study in

an impersonal way and as a result, their personal views / experience or that of their study

subjects does not affect their expert interpretation of data (Leacock, Warrican & Rose,

2009). For this study, a quantitative approach was used to examine the determinants of

saving. This was based on the underlying assumptions of quantitative traditions (deductive

reasoning) and the research questions that rendered themselves towards a quantitative line

of enquiry.

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Table 1 illustrates the differences between quantitative and qualitative research and provides

a useful summary to the underlying approach, data collection and analysis of both research

approaches.

Table 1: Comparative Summary of Qualitative and Quantitative Research Approaches

Qualitative Research Quantitative Research

Uses an inductive form of reasoning :

develops concepts, insights and

understanding from patterns in the data

Uses a deductive form of reasoning :

collects data to assess preconceived

models, hypotheses and theories

Uses an emic perspective of inquiry :

derives meaning from the subject’s

perspective

Uses an etic perspective : the meaning

is determined by the researcher

Is idiographic : thus aims to understand

the meaning that people attach to

everyday life

Is nomothetic : aims to objectively

measure the social world, to test

hypotheses, and to predict and control

human behaviour

Regards reality as subjective Sees reality as objective

Captures and discovers meaning once

the researcher becomes immersed in

the data

Tests hypotheses that the researcher

starts off with

Concepts are in the form of themes,

motifs and categories.

Concepts are in the form of distinct

variables

Seeks to understand phenomena Seeks to control phenomena

Observations are determined by

information richness of settings, and

types of observations used are

modified to enrich understanding

Observations are systematically

undertaken in a standardised manner

Data is presented in the form of words,

quotes from documents and transcripts

Data is presented by means of exact

figures gained from precise

measurement

The research design is flexible and

unique and evolves throughout the

research process. There are no fixed

steps that should be followed and

cannot be exactly replicated

The research design is standardised

according to a fixed procedure and

can be replicated

Data is analysed by extracting themes Data analysis is undertaken by means

of standardised statistical procedures

The unit of analysis is holistic,

concentrating on the relationships

between elements, contexts, etc. The

whole is always more than the sum

The unit of analysis is variables which

are anatomistic (elements that form

part of the whole)

Source: Denzin & Lincoln (2000); Neuman (1994) as adapted from April, 2004 (p.77)

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3.3 Research Design

Leacock et al., (2009) identified the following commonly used research approaches: case

studies; survey studies; correlational studies; causal – comparative studies; historical studies

and; experimental studies. Given the dearth of literature on the subject in the Zambian

context, the research was designed in such way as to obtain data directly from respondents.

As such, a survey study approach was used. In survey studies, data is collected from a select

group of persons in order to answer questions about beliefs, feelings and opinions or test a

hypothesis (Leacock et al., 2009)

One criticism about this approach is the use of a questionnaire that is a self-reporting

instrument as a means of data collection. Leacock et al., (2009) argue that such instrument

“may lead to the collection of data that is distorted by perception, personal experience, and

the passage of time or outright deliberate misrepresentation of the facts” (p 57). It also

suffers from the “garbage in, garbage out” if it is not properly formulated (Adams et al.,

2014).

However, despite the criticism of this approach, the researcher preferred it due to the limited

time the researcher had to undertake the study and the quantitative nature of the study which

meant that data could be compiled and analysed in a shorter period compared to qualitative

approach. Further, by using a questionnaire distributed via email, the researcher facilitated

completion of questionnaire without influencing the outcome.

To address the criticisms of the survey approach alluded to earlier; the survey process as

described in figure 5 was adopted.

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The Survey Process

Design

Purpose

Support from Literature

Sample Selection

Delivery Method

Write the Questions

Form of Response

Layout

Pilot the survey

Make iterations —

Re-pilot?

Administer the survey

Data Entry

Coding and Storage

Media Missing Data

Analysis

Report

Figure 5: The Survey Process. Source: Adapted from Adams et al., 2014. p.119

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3.4 Study population and sample

3.4.1 Population

The general study population was the Zambian middle class. However, for the purposes of

this study, the specific study population was the banking employees who within this market

are a sub-segment of the middle class. The specific study population was further limited to

banking employees living in Lusaka City. The country boasts of 19 commercial banks. All

19 commercial banks are represented in Lusaka City. However, one bank was recently

placed under the direct supervision of the Central Bank due to its insolvency and inability

to meet financial obligations as they fell due and was excluded from the population.

As at end of 2015, there were 7999 banking employees across the country of which 5522

were based in the Lusaka area representing 69% of the total banking employees (Bank of

Zambia, 2016). Only Lusaka based bank employees formed a population from which a

sample for study was drawn. This is because the researcher believed that such a sample

contained rich information about the phenomenon being investigated (Leacock et al.,

(2009). Availability and proximity of a large slice of the banking employee population to

the researcher also played a key role in the decision. Table 2 provides an overview of where

the entire banking employee population is located.

3.4.2 Sample and sampling method

The researcher aimed to distribute a total of 270 questionnaires by distributing 15

questionnaires (see Table 3) to each of the 18 banks. In the end, however, the sample was

drawn from bank employees from 14 banks out 18 due time constraints. Non-probability

sampling approach was used for this study. In non-probability sampling, the selection of

sample units or categories depend on the researcher’s personal judgement. According to

Adams et al. (2014), this approach has a weakness of not being representative due to the use

of the researcher’s personal judgement in coming up with a sample. As a result, the findings

of the study may not be valid.

The weakness identified by Adams et al. above were mitigated by:

Taking samples from most of the banks (14 out of 18 banks) operating in the country

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Adopting a stratified approach by taking samples from a broad spectrum of staff.

For the purposes of this research, three categories of staff were identified namely:

clerical, managerial and executive staff (see Table 3).

Table 2: Banking employees per occupational category and by province

Source: Bank of Zambia (2016). Financial and Other Statistics Booklet

Table 3: Description of respondents

Description of respondents Number to be sampled

Clerical staff (normally unionised) 90

Managerial staff (as per criteria of the specific bank) 90

Executive staff (as per criteria of specific bank) 90

Table 4b: Employment in Banks by Occupational Category and Province, 2015

Occupational Category Lusaka Central Copperbelt Eastern Southern Luapula Western Northern North/W Muchinga Numbers

Executive Management 128 0 0 0 0 0 0 0 0 0 128

Senior Managers 454 3 30 3 4 4 1 3 5 2 509

Managers 839 17 125 14 33 5 9 13 15 9 1,079

Credit 389 0 1 0 0 0 0 0 0 0 390

Treasury 91 0 0 0 0 0 0 0 0 0 91

Finance 117 0 0 0 0 0 0 0 0 0 117

Risk and Compliance 56 0 1 0 0 0 0 0 0 0 57

Operations 675 12 108 13 28 3 1 4 6 3 853

Others 1,048 46 248 36 76 15 19 22 28 15 1,553

Clerical and general staff 1,725 129 598 141 234 47 66 96 125 61 3,222

Total 5,522 207 1,111 207 375 74 96 138 179 90 7,999 Source: Commercial Banks

Table 5: Annual Employment in Commercial B a n k s by Province, 2006 - 2015

Province 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Lusaka 1,111 927 1,003 3,729 4,052 4,064 4,750 5,078 5,273 5,522 Central 27 40 28 134 133 130 133 152 170 207 Copperbelt 411 521 306 813 843 823 870 931 1,015 1,111 Eastern 51 100 6 135 132 132 147 147 168 207

Southern 125 194 52 289 297 322 335 332 346 375 Luapula 6 8 7 36 48 46 51 51 63 74 Western 9 9 9 71 62 52 57 75 80 96 Nor thern 23 488 28 141 135 146 151 105 124 138 Nor thwestern 7 12 185 89 106 97 106 143 154 179 Muchinga 67 72 90 Total 1,770 2,299 1,624 5,437 5,808 5,812 6,600 7,081 7,465 7,999 Note: Data for Access Bank,African Banking Corporation, Investrust, ZANACO and Finance Bank were not available for 2006 to 2008.

*Muchinga Province was formed in 2011 hence data for earlier periods are not available

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3.5 The research instrument

A questionnaire was used as a research instrument (see Appendix D). Youngman as cited in

Bell and Waters (2014) listed seven types of questions commonly used by researchers using

this instrument namely: verbal/open, list, ranking, grid, scale, category and quantity. For

this research, a closed questionnaire, one in which a question is asked and a respondent

chooses the answer from a number of options provided, was used to gather data on the

phenomenon studied (Leacock et al., (2009). The questionnaire contained some of the types

of questions identified by Youngman (Bell & Waters, 2014). The advantage of using this

type of questionnaire is the easy to collate and code data while allowing for uniform

measurement thereby providing greater reliability (Leacock et al., (2009).The key, however,

is a proper construction of the questionnaire. The questionnaire included classification and

targeted questions. Classification questions were meant to provide more data with regard to

potential respondents while target questions addressed research questions relevant to the

study. The questions in the questionnaire were derived from the literature review conducted

(see Table 6).

Prior to being administered, the questionnaire was tested among a select group 10 banking

employees. 40% response rate was obtained from questionnaires distributed electronically.

Questions and a summary of the results from the pilot test are contained in Table 4. Feedback

from responses received was used to refine the research instrument.

Table 4: Results from the pilot test of the questionnaire

No. Clarity sought on questionnaire Response from pilot test respondent

1. How long did you take to complete the

questionnaire?

Between 10 – 15 minutes

13 minutes

10 minutes

15 minutes

2. Were the questions in the questionnaire

clear?

Questions were clear

90% clear

Some questions were ambiguous

e.g. one asking about salary per

month: is it gross or net salary?

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3. Were the questions in the questionnaire

difficult or hard to answer?

Had to thick twice on section D &

E

Some take time to understand, can

be made easier.

Q19 is technical, other the rest are

ok

4. Is there any feedback or comment you

would like to give on the

questionnaire?

send to credit team who see

patterns of borrowing

include religion as a factor to

investigate

provide boxes for ticking instead

of manually making the response

However, Adams et al., (2014) allude to the fact that this type of research instrument has,

among the others, one disadvantage namely that of low response rate which in some cases

may be as low as 20%. The researcher aimed to collect a minimum of 100 responses hence,

a high number of questionnaires was distributed to mitigate the low response rate.

3.6 Procedure for data collection

According to Adams et al., (2014), a researcher can choose between, mail questionnaires,

face to-face interviews, email/web questionnaires, telephone and. peer dissemination as

survey delivery platform. The delivery platform initially preferred by this researcher was

the email platform. To solicit a high response rate, the questionnaire was distributed through

the Human Resource (HR) Directors of respective banks. Instructions on how to distribute

the questionnaire were included to provide guidance to HR Directors in order to mitigate

weaknesses identified with the non-probability sampling approach used (See Appendix C).

However, due to the low response rate experienced in the early stages of data collection

using this approach, peer dissemination was also used which approach was further

augmented with physical distribution of questionnaires. Data was collected using

questionnaires electronically or physically distributed. An introduction letter explaining the

purpose of the research and outlining the rights and responsibilities of the respondents and

the researcher respectively accompanied each questionnaire sent out. The delivery platforms

are compared in Table 5.

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Table 5: Survey delivery platforms (adapted from Adams et al, 2014. P.122)

Delivery

Platform

Who

Completes—

Surveyor or

Surveyed

Cost Length of

Questionnaire

Response

Rates

Comment

Household Either Expensive Can be long High Not advisable for a student

approach—safety issues

and too time consuming,

no compulsion for

householders to reply

Street Surveyor Medium Short Medium Concern as to the validity

of responses and those

surveyed tend to be self-

selected—so are they

really representative?

Telephone Surveyor Medium Short Depends on

culture

In the UK, student-based

telephone surveys of

individuals do not appear

to illicit a very high

response rate but in Hong

Kong they do. Can work

for company-based

surveys—but little detail is

given and not of a

confidential nature.

Email / web Surveyed Cheap Short Low Reliability concerns—can

be multiple responses.

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Companies pay little

attention to these

Mail Surveyed Cheap Variable Low For individuals need a

reply paid envelope—not

required for companies.

Customer Either Medium Medium Variable Usually requires

permission of retailer.

Part of an

institution or

organisation

Surveyor Cheap Medium High Can have high response

rates if the surveyed think

that it is advantageous to

them. But can be biased

responses as the

respondents try to portray

their position to their

superiors.

3.7 Data analysis and interpretation

A statistical analysis software tool, Megastat v11.0 was used to run regressions used to

analyse the data collected. Descriptive statistics were also used in conjunction with

regressions. For ethnic / cultural factors questions that indicated willingness to save were

incorporated in the questionnaire. According to Al-Awad & Elhiraika (2003), “willingness

to save is assumed to depend primarily on cultural factors” (p.141). Three questions that

have become standard survey questions for assessing financial literacy (Beckmann, 2013)

were included in the questionnaire. The questionnaire also contains questions that collected

detailed information on the saving behaviour, which were utilized to study whether financial

literacy was correlated with the saving behaviour of Zambian bankers. Credit availability

phenomenon was also analysed using regression and descriptive statistics.

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3.8 Consistency Matrix

Table 6: Consistency matrix

Research problem: Personal and household savings are not growing at a rate that would sustain the economic development the nation

aspires to achieve.

Sub-problem Literature Review Hypotheses or

Propositions or

Research

questions

Source of data Type of

data

Analysis

The objective of this

sub question is to

examine whether

someone’s cultural

upbringing can

influence saving

behaviour or not.

Zambia is an ethnically

diverse country

comprising of about

seventy-three tribal

groups.

Carroll, C. D.,

Rhee, B. K., &

Rhee, C. (1994).

Al-Awad, M., &

Elhiraika, A.

(2003). Gatina, L.

(2014). Shepherd,

H. R., & Stephens,

N. M. (2010).

Ethnic or cultural

background of

individuals or

households affects

saving behaviour.

I make voluntary contributions on top of

my mandated monthly pension contributions

(7). I currently save or put money away (8).

I always think about life after retirement (9).

How often did your parents / relatives or

friends speak to you about money when you

were growing up? (14), How often do you

discuss money issues with your kids? (15)

How often do you support your siblings or

parents financially? (16).

Ordinal Quantitative:

Descriptive

statistics;

Regression

analysis Copyright UCT

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aspires to achieve.


Propositions or

Research

questions


data

Analysis


sub question is examine

whether financial

literacy as a variable

has an impact on

individual and

household saving.

Beckmann, E.

(2013). Tang, N.,

& Peter, P. C.

(2015). Klapper,

L., Lusardi, A., &

Panos, G. A.

(2013. Lachance,

M. J., & Cloutier,

J. (2009). Lusardi,

A., Mitchell, O. S.,

& Curto, V. (2010)

Financial literacy

contributes to

sound financial

decisions and can

affect the

individual’s ability

to save and invest

I know how much money I spent last month

(1). I am happy with my financial /

budgeting skills (2). I own shares / trade on

the stock exchange (3). I have an Investment

/ savings account (4). I know the interest

rate(s) I pay on my loan(s) (5). I have an

insurance life Cover and or retirement

annuity (6). Suppose you had K100 in a

savings account and the interest rate was 2%

per year. After 5 years, how much do you

think you would have in the account if you

left the money to grow? (17). Imagine that

the interest rate on your savings account was

1% per year and inflation was 2% per year.

After 1 year, would you be able to buy more

than, exactly the same as, or less than today

with the money in this account? (18). Do

you think that the following statement is

true or false? Buying a single company

stock usually provides a safer return than a

stock mutual fund (19).

Discrete;


Descriptive

statistics;

Regression

analysis

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aspires to achieve.


Propositions or

Research

questions


data

Analysis


question is to examine

whether easy access to

credit hinders

individuals and

households from saving

or not.

Glick, R., &

Lansing, K. J.

(2011). Carroll, C.,

Slacalek, J., &

Sommer, M.

(2013). Deaton, A.

(1991). Jappelli,

T., & Pagano, M.

(1994)

Credit availability

reduces the

precautionary

saving motive

thereby affecting

the level of saving.

I do not wait for store sales promotions; I

buy today when I need it (10). I have

borrowed in the last 24 months (11). I have

taken on too much debt (Debt service ratio -

Monthly loan repayments / Monthly income

after tax / NAPSA/ Pension) > 50%) (12). I

think easy access to credit (loans) hinders

saving (13)


Descriptive

statistics;

Regression

analysis

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CHAPTER FOUR

4 RESEARCH FINDINGS, DISCUSSION AND INTERPRETATION

4.1 Introduction

This chapter presents the findings of the research objectives based on the data collected. The

findings are analysed using statistical analysis software tool (Megastat v11.0) and followed by a

discussion of the analysis.

How and from where was data sourced?

Initially, the researcher aimed to distribute a total of 270 questionnaires by distributing 15

questionnaires (see Table 3) to each of the 18 banks. This target was not achieved however. The

researcher only managed to distribute a total of 203 questionnaires to 14 of the 18 banks

representing a coverage rate of 77.8%. 4 banks were not covered due to time constraints within

which to collect the data. 100 responses were collected from the total number of questionnaires

distributed representing 49.3% response rate. Responses were received from all the 14 banks to

which the questionnaire was distributed to. According to Leacock et al., (2009), a minimum sample

of 100 is acceptable as it is untenable to anticipate a 100% response rate and also given the limited

time available for any particular research.

Research objectives


employees in Zambia. Based on the research questions, the objectives included;

1. To examine the effect of cultural / ethnic background on saving behaviour of Zambian

banking employees.

2. To assess the relationship between financial literacy and savings.

3. To examine the effect of credit availability on savings.

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4.2 Objective 1

We have to acknowledge the assumption that the ethnic / cultural background as an independent

variable is measured by province. It is assumed that people of the same province will exhibit

homogeneous saving patterns. These provinces depict the cultural grouping as well as the common

background. Figure 6 shows frequencies of the respondents from the various ethnic groups

categorised into provinces.

Figure 6: Provinces from where respondent come from

As observed from figure 6, the largest number of respondents came from Eastern province making

up 23% while lowest number was from North western and other parts of the world outside Zambia

(3%).

To determine the relationship between the ethic / cultural background and the saving behaviour, a

regression was run between the observed responses on provinces against the observed responses on

whether someone has a savings account or investment account (Q4).

From figure 7 below, we observe that the regression line is almost horizontal or flat. This implies

that there is weak or no significant relationship between the cultural /ethnic background and saving

Province

1. Lusaka

2. Central

3. Southern

4. Western

5. Eastern

6. Muchinga

7. Northern

8. Luapula

9. Copperbelt

10. North

Western

11. Other

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pattern. The coefficient of determination R² = 0.0139, is too small and almost zero, which suggests

that relationship between the two factors is almost zero.

This phenomenon can be justified in that people move and merge up in urban areas and their cultural

ties may be broken by close association with other people of different tribal groups hence making

up the whole country a homogeneous grouping.

Figure 7: Regression between province and saving behaviour

Hypothesis 1

H0: Ethnic or cultural background of individuals or households does not affect saving behaviour.

H1: Ethnic or cultural background of individuals or households significantly affect saving behaviour

To test this hypothesis, the following testing questions were evaluated and run into the analysis

software: (the number in bracket indicates the question tag on the questionnaire)

1. I make voluntary contributions on top of my mandated monthly pension contributions (7).

2. I currently save or put money away (8).

3. I always think about life after retirement (9).

4. How often did your parents / relatives or friends speak to you about money when you were

growing up? (14).

y = 0,0671x + 3,2211R² = 0,0139

0

1

2

3

4

5

6

0 2 4 6 8 10 12

INV

/SA

VIN

GS

Province

REGRESSION BETWEEN PROVINCE AND SAVING BEHAVIOUR

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5. How often do you discuss money issues with your kids? (15).

6. How often do you support your siblings or parents financially? (16).

The regression was run between dependent variable probe 2 (I currently save or put money

away) and independent variable probe 4 (How often did your parents / relatives or friends speak

to you about money when you were growing up?)

Figure 8: Regression between saving when growing up and currently save

Figure 8 highlights the regression relationship between the exposure to saving at time of growing

up through discussion and an individual’s current savings behaviour. The relationship is weak (flat)

and R² = 0.0057 which is almost zero implying that there is no significant relationship between the

two factors. The individual’s current saving behavior has nothing to do with their upbringing.

Alternatively, how often the parents or relatives or friends speak to an individual about money or

investments when they were growing up has little to do with their saving pattern.

This situation may explain the reason why an individual from a rich family may shockingly lead a

reckless life of abandon when let alone in adulthood, while an individual from irresponsible parents

or families may have good saving habits and prosper economically when they lead their own life

after leaving their families. Furthermore, it also explains the reason why different individuals

brought up from the same identical family will fair differently in saving habits.

y = 0,0783x + 3,1846R² = 0,0057

0

1

2

3

4

5

6

0 1 2 3 4 5 6

MA

KE

SA

VIN

GS

SAVINGSGROWINGUP

REGRESSION- SAVINGS WHEN GROWING UP AND CURRENT MAKING OF SAVING

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Hypothesis testing results

When the hypothesis test was run on paired observations between saving when growing up against

current saving, the results yield was as summarised in the table 7.

Please note the following:

- Since the anchoring scale was in ascending order with positive at 5 and negative at 1, the

hypothesised value was set at 5 (5 - always talked to about saving, 5 - strongly agree making saving)

- Decision rule is that if p value is greater than 0.05, accept null, if p value is less than 0.05 reject

null and accept the alternative hypothesis test.

- Since the value of n is large enough, we use z test and not t test.

Table 7: Paired Observations - saving when growing up and currently save

Hypothesis Test: Paired Observations

5.000 hypothesized value

2.750

mean

SAVINGSGROWINGUP

3.400 mean MAKESAVINGS

-0.650 mean difference (SAVINGSGROWINGUP - MAKESAVINGS)

1.866 std. dev.

0.187 std. error

100 n

-30.28 z

1.0000 p-value

-1.016

confidence interval 95.%

lower

-0.284

confidence interval 95.%

upper

0.366 half-width

At 95% level of significant on both upper and lower tails, the p value is greater than the critical

0.05, since p value is 1.00. This means that we fail to reject the null hypothesis, instead we reject

the alternative which states that there is a significant effect of individual cultural background and

the current savings behaviour. Hence we can conclude at 95% certainty that there is no significant

effect of individual’s cultural and ethnic background on their current saving behaviour.

The other regression was run to find out the relation between individual who was brought up in

some cultural pattern and if they continued to impart the same on their children.

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Independent variable: How often did your parents / relatives or friends speak to you about money

when you were growing up? (14),

Dependent variable: How often do you discuss money issues with your kids? (15)

Table 8: Regression Analysis – discuss money with kids

r² 0.026

Adjusted r² 0.016

r

-

0.162

Std. Error 1.347

n 100

k 1

Dep. Var. Discuss money with kids

ANOVA table

Source SS df MS F p-value

Regression 4.7864 1 4.7864 2.64 .1075

Residual 177.7236 98 1.8135

Total 182.5100 99

At 95% significant level, we still accept the null hypothesis that there is there is no relationship

between an individual being often talked to about money when growing up and them telling their

children about money when grown up.

These findings run contrary to studies conducted in other countries suggesting that there is a

correlation between cultural factors and saving (Carrol et al, 1994; Al-Awad & Elhiraika, 2003;

Gatina, 2014). What is perhaps striking with these studies is that they involved migrants while this

study involved subjects from different parts of Zambia. Migrants from other countries may have

distinct cultural behaviours different from the host countries whereas different ethnic / cultural

groupings within a country may not be distinct in their cultural norms or behaviours due to close

proximity to one another and forging of a national identity.

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4.3 Objective 2

The objective was to examine whether financial literacy as a variable has an impact on individual

and household saving. To address this objective the following were the probes from the respondents.

The dependent variable was saving habit on bank employees while the independent variables were

measured by a number of variables listed below.

Financial Literacy measures:

- I know how much money I spent last month (1).

- I am happy with my financial / budgeting skills (2).

- I own shares / trade on the stock exchange (3).

- I know the interest rate(s) I pay on my loan(s) (5)

Individual savings measures

- I have an Investment / savings account (4).

- I currently save or put money away (8).

Simulation 1: A regression was run between the probes: “I know how much money I spent last

month” (1) financial literacy measure and “I currently save or put money away” (8). The results

yielded are shown in figure 9.

Figure 9: Regression between last expenditure knowledge and saving

y = 0,2446x + 2,495R² = 0,0429

0

1

2

3

4

5

6

0 1 2 3 4 5 6

MA

KE

SA

VIN

G

LASTEXPEND

REGRESSION LAST EXPENDITURE KNOWLEDGE AND MAKING SAVING

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Figure 9 highlights the regression relationship between the last month knowledge and an

individual’s current saving behaviour. The relationship shows some positive upward trend with

slope of 0.2446 and R² = 0.04 which slightly higher away from zero. This implies that there is some

significant relationship between the two factors. The individual’s current saving behavior has

something to do with the financial literacy in terms of accountability of their previous expenses.

Alternatively, the more conscious an individual is to spending the more they become thrift for the

consequence period.

This may explain the reason why individuals who maintain simple book keeping and have some

literacy on financials are likely to be thrifty and invest or save than individuals with no

accountability for periodical expenses. In reality, a person who spends on drinking may not save

partly because they unconsciously spend while drunk and may not remember exactly how much

lump sum was spent.

Simulation 2: A regression was run between probes: “I am happy with my financial / budgeting

skills” (2) and “I have an Investment / savings account” (4). The results yielded are shown in figure

10

Figure 10: Regression between budget skills and saving account

Figure 10 highlights the regression relationship between the individual’s budgeting skills, a measure

of financial literacy an individual’s willingness to maintain an investment or savings account. The

relationship shows a significant positive upward trend with slope of 0.3464 and R² = 0.08 which

y = 0,3464x + 2,4996R² = 0,0827

0

1

2

3

4

5

6

0 1 2 3 4 5 6

AC

CS

AV

ING

BUDGETSKILL

REGRESSION BUDGET SKILLS AND SAVING

ACCOUNT

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slightly higher away from zero and R = 28% (explained proportion of the dependent variable as a

result of independent variable). This implies that there is some significant relationship between the

financial literacy measured in terms of budgetary skills and an individual maintain a savings or

investment account. The individual’s financial literacy is positively related to saving. Alternatively,

the higher the budgeting skills an individual has, the more they become thrifty and have investments

Hypothesis 2

We test the second hypothesis based on the variables discussed in Simulation 1 of objective two.

H0: Financial literacy does not contribute to sound financial decisions and cannot affect the


H1: Financial literacy significantly contributes to sound financial decisions and greatly affect the


- Since the value of n is large enough, we use z test and not t test.

- We set hypothesis value at 5.00

- Decision rule is that if p value is greater than 0.05, accept null, if p value is less than 0.05

reject null and accept the alternative hypothesis test.

Table 9: Paired observations for Hypothesis 2 under Simulation 1

Since p value (0.00) is less than 0.05 we reject the null hypothesis that financial literacy does not

contribute to sound financial decisions and cannot affect the individual’s ability to save and invest.

Instead, we accept the alternative hypothesis and conclude that financial literacy significantly

contributes to sound financial decisions and greatly affect the individual’s ability to save and invest.



3.090 mean BUDGETSKILL

3.570 mean ACCSAVINGS

-0.480 mean difference (BUDGETSKILL - ACCSAVINGS)

1.567 std. dev.

0.157 std. error

100 n

-34.98 z

0.00 p-value (two-tailed)

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Hence we deduce that conducting financial literacy programmes to adults and including bank

employees can contribute significantly to saving improvements. People can make decisions if well

informed and appreciate the need to save. This gives the added reason banks or microfinance

lending institutions engaged in administering group loans or small and medium enterprises

financial empowerment may do well to first educate the would be borrowers on budgeting skills

and saving for better investment. This will make the debtors to be financially viable and prudent on

revenues.

Simulation 2 on hypothesis 2

- value of n is large enough, we use z test

- We set hypothesis value at 5.00


reject null and accept the alternative hypothesis.

The variables run are last expenditure knowledge and individual making some savings away

Table 10: Paired observations for Hypothesis 2 under Simulation 2

In reference to Table 10, at 95% significant level, we reject the null hypothesis that financial literacy

does not contribute to sound financial decisions and cannot affect the individual’s ability to save

and invest, instead we accept the alternative hypothesis and conclude that financial literacy

significantly contributes to sound financial decisions and greatly affect the individual’s ability to

save and invest.



3.700 mean LASTEXPEND

3.400 mean MAKESAVINGS

0.300 mean difference (LASTEXPEND - MAKESAVINGS)

1.636 std. dev.

0.164 std. error

100 n

-28.73 z

0.00 p-value (two-tailed)

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Hence we can establish that a person’s knowledge and consciousness of their expenses as well as

other measures of literacy, affect the saving behaviour. The higher the financial accountability, the

higher the saving for an individual.

Descriptive statistics for questions 17, 18 and 19

According to Lursadi et al, (2010), there are three questions that are normally asked to test financial

literacy. These questions were included as Question 17, 18 and 19 in the questionnaire. The results

are depicted in figures 11 to 13 respectively. The results showed that the level of financial literacy

declined with the complexity of the subject being tested indicating perhaps the need for intervention

in such areas.

Figure 11: Q17 - Interest Rate (Numeracy).

Frequency Distribution - Quantitative

ACCAFTER5YRS cumulative

lower upper midpoint width frequency percent frequency percent

0.0 < 1.0 0.5 1.0 0 0.0 0 0.0

1.0 < 2.0 1.5 1.0 82 82.0 82 82.0

2.0 < 3.0 2.5 1.0 6 6.0 88 88.0

3.0 < 4.0 3.5 1.0 6 6.0 94 94.0

4.0 < 5.0 4.5 1.0 0 0.0 94 94.0

5.0 < 6.0 5.5 1.0 6 6.0 100 100.0

100 100.0

0

10

20

30

40

50

60

70

80

90

Perc

ent

ACCAFTER5YRS

Histogram

Series1

1. More than

K102

2. Exactly

K102

3. Less than

K102

4. Do not

know

5. No answer

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This question tested whether respondents were familiar with interest rate calculation. 82% answered

this question correctly while the other 18% got it wrong, did not know the answer or refused to

answer.

Figure 12: Q18 – Inflation

77% respondents answered correctly to Question 18 which sort to find out if respondents were

familiar with inflation and its effect on savings or investment. 23% answered wrongly, did not know

or did not answer.


1PERCENTINT cumulative


0.0 < 1.0 0.5 1.0 0 0.0 0 0.0

1.0 < 2.0 1.5 1.0 7 7.0 7 7.0

2.0 < 3.0 2.5 1.0 2 2.0 9 9.0

3.0 < 4.0 3.5 1.0 77 77.0 86 86.0

4.0 < 5.0 4.5 1.0 6 6.0 92 92.0

5.0 < 6.0 5.5 1.0 8 8.0 100 100.0

100 100.0

0

10

20

30

40

50

60

70

80

90

Per

cent

1PERCENTINT

Histogram

Series1

1. More than

today

2. Exactly the

same

3. Less than today

4. Do not know

5. No answer

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Figure 13: Q19 – Risk diversification

Only 66% answered question 19 correctly with the rest not knowing the answer, answering wrongly

or ignoring it completely.

Previous studies (Lusardi, Mitchell & Curto, 2010; Yu, Wu, Chan & Chou, 2015) have shown that

that financial literacy is a determinant of saving and this study goes a long way to argument such

position. However, as Klapper et al., (2013) argue, “correlation between financial literacy and

behaviour does not mean causation and that it is important to find a causal link” (p.3906). For bank

employees, this may be by default given that bank employees have access to financial literacy

information by virtue of their employment the financial industry. Further, many bank employees

have bank accounts opened wherein they receive their salaries and or make savings.


TRUEFALSE cumulative


0.0 < 1.0 0.5 1.0 0 0.0 0 0.0

1.0 < 2.0 1.5 1.0 7 7.0 7 7.0

2.0 < 3.0 2.5 1.0 68 68.0 75 75.0

3.0 < 4.0 3.5 1.0 18 18.0 93 93.0

4.0 < 5.0 4.5 1.0 7 7.0 100 100.0

100 100.0

0

10

20

30

40

50

60

70

80

Perc

ent

TRUEFALSE

Histogram

Series1

1. True

2. False

3. Do not

Know

4. No

answer

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4.4 Objective 3

The major aim of this objective was to examine whether easy access to credit hinders individuals

and households from saving or not. The major assumption on this objective was that as more

credit facilities are accessed, the individual will have more liability obligations to meet, leaving

them with very little if none for saving.

To address this objective the following were the probes from the respondents. The dependent

variable was saving habit on bank employee while the independent variables were measured by a

number of variables listed below

Credit availability measures

- I have borrowed in the last 24 months (11).

- I have taken on too much debt (Debt service ratio > 50%) (12).

- I think easy access to credit (loans) hinders saving (13)

Savings measures

- I have an Investment / savings account (4).

- I currently save or put money away (8).

Simulation1: A regression was run between the probes: “I have borrowed in the last 24 months”

as measure of credit facility and “I currently save or put money away”. The results yielded are

shown in figure 14.

Figure 14: Regression between credit availability and saving

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Figure 14 highlights the regression relationship between the individual’s easy access to credit

facility and saving. The relationship shows a significantly weak positive upward trend with slope

of 0.0907 and R² = 0.0095 which is almost zero and R = 10% (explained proportion of the dependent

variable as a result of independent variable). This implies that there is weak or no relationship

between the availability of or easy access to credit facilities and individual’s saving.

In expansion, we will deduce that a person who appreciates saving will continue with the saving

behavior despite the availability of credit, and will be within their debt service ratio. It is a decision

a person willingly makes whether to go for a loan or not.

Simulation2: A regression was run between the probes: “I have taken on too much debt (Debt

service ratio > 50%)” as measure of credit facility and “I currently save or put money away”. The

results yielded are shown in figure 15.

Figure 15: Regression between high debt service ratio and saving

Figure 15 above highlights the regression relationship between the individual’s debt ratio and

saving. The relationship shows a significantly negative upward trend with slope of -0.1834 and R²

= 0.0329 which is further away from zero and R = 57% (explained proportion of the dependent

variable as a result of independent variable). This implies that there is an inverse relationship

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between an individual’s debt ratio and individual’s saving. The higher the debt ratio, the lower the

saving due to less surplus money for saving.

Hence it is not advisable to let individuals exceed the threshold borrowing ratio. This reduces their

financial viability and the marginal propensity to save (MPS).

When the respondents were asked “I think easy access to credit (loans) hinders saving”, in a five

continuum anchor rating from strongly disagree (1) to strongly agree (5), the results were as shown

in figure 16.

Figure 16: Responses to whether access to credit hinders saving or not

The majority of respondents (33%) said they strongly agree that easy loan access hinders savings,

followed by 24% on agreeing that easy access hinders savings. While 11% were indifferent to the

opinion, a total of 32% categorically felt easy access does not hinder savings. Statistically, this is a

significant value to depict that easy access to loans may not have an effect to dissaving.

Hypothesis 3

We now test the third hypothesis based on the variables discussed in objective three. To recap, the

hypothesis is stated below.

1. strongly

Disagree

2. Disagree

3. Neither

Disagree

nor agree

4. Agree

5. Strongly

agree

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H0: Credit availability has no effect on the precautionary saving motive thereby affecting the level

of saving

H1: Credit availability has a significant effect on the precautionary saving motive thereby affecting

the level of saving

Note the parameters set below

- value of n is large enough, we use z test

- We set hypothesis value at 3.00, since hinders is from neutral 3 to 1strongly disagree,

- This is one tailed, since it is hinders


reject null and accept the alternative hypothesis.

Table 11: Mean vs. Hypothesized Value

Hypothesis Test: Mean vs. Hypothesized Value


3.300 mean EASYLOANACCESS

1.418 std. dev.

0.142 std. error

100 n

2.12 z

.9828 p-value (one-tailed, lower)

We notice that p value is greater than the critical 0.05. Hence we accept the null hypothesis and

conclude that credit availability has no effect on the precautionary saving motive thereby affecting

the level of saving at 95% certainty level.

While many studies (Jappelli & Pangano, 1994; Jongwanich, 2010; Carroll, Slacalek & Sommer,

2013) conducted in developed countries have concluded that there is a relationship between

availability of credit and saving, it does not appear to be the case with this study. From the findings,

the results show that credit availability does not discourage saving. It is generally accepted that

availability of credit in a developing country like Zambia, is a source of investment and savings.

Most bank employees borrow to increase their net worth by acquiring landed properties. As

observed in figure 12, the finding however, agree with Glick & Lansing (2011) study that found

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that saving rate is negatively correlated with the household debt ratio in the US in that there is a

negative relationship between high debt ratio and savings. Hence the way forward is to make the

credit available but be cautious to limit the individual borrowing ratio.

Hence we can establish that a person’s knowledge and consciousness of their expenses as well as

other measures of literacy, affect the saving behaviour. The higher the financial accountability, the

higher the saving for an individual.

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CHAPTER FIVE

5 RESEARCH CONCLUSION AND RECOMMENDATION

5.1 Introduction


employees in Zambia. There are many determinants of saving but this dissertation investigated three

of these possible determinants namely: availability of credit; financial literacy; and ethnic / cultural

factors. A regression model and descriptive statistics were used to analyse the data to arrive at

conclusions presented in this chapter. The study was designed to help policy makers, bankers and

investment managers to craft interventions that:

Could help in sustaining or increasing the GNS ratio through fiscal policy formulation and

introduction of innovative saving products

Encourage accessibility to saving and investment information.

Change people’s saving cultural perspectives, customs and behaviours by making saving

and investment desirable.

By using Megastat V11.0 software to run regressions and testing hypotheses in chapter four, the

following conclusions have been made.

5.2 Cultural factors and saving

Statistical evidence showed that there was no correlation between ethnic or cultural factors and

saving. This may be attributed to the fact that different ethnic / cultural groupings within a country

even if they come from different provinces may not be distinct in their cultural norms or behaviours

due to close proximity to one another and forging of a national identity. Saving motives appear to

be the driving force to fostering a saving culture. The motives transcend cultural barriers hence the

evidence seen from findings.

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5.3 Financial literacy and saving

There was evidence to suggest that financial literacy is a determinant of saving among banking

employees and that financial literacy significantly contributes to sound financial decisions and

greatly affect the individual’s ability to save and invest. Information about financial products,

ability to budget and an understanding of risk and reward can help an individual or household to

make informed decisions about their money and investment opportunities.

5.4 Credit availability and saving

Evidence showed that availability of credit did not impact saving in a negative way. Some banking

employees who had access to credit also demonstrated that they were able to save. However,

evidence also showed that there was regression relationship between the individual’s debt ratio and

saving. The relationship shows a significantly negative upward trend implying that an individual

with a high debt service ratio has less funds to invest or save.

5.5 Recommendations

Given the importance of saving in any given economy, it is important that savings are encouraged.

Going by the findings of this study and in the spirit of the design of the study as alluded to in the

introduction section of this chapter, the following are recommended:

5.5.1 Encourage culture of saving by intensifying financial literacy education targeting all sectors

of the economy and different age groups within society. Hitherto, there has been

concentration of financial literacy training / programme to the National Literacy Week.

Financial literacy activities also tend to be skewed to school going children to the exclusion

of other groups within the society.

5.5.2 Zambian Government to consider abolition or reducing withholding tax on interest on

individual or household investments in Govt. bonds and treasury bills.

5.5.3 Lending institutions to cap the debt service ratio to enable individuals or households save

surplus funds.

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5.5.4 Banks should innovate by coming up with savings products that can encourage and

attract savers.

5.6 Proposed future research

Given the dearth of literature on this subject within the Zambian context, there are many areas yet

to be explored. It is proposed that the following could be examined:

Determine whether saving behaviour is different between males and females

Consider the role of religion in saving and whether religion can influencing saving

investigate whether education is a determinant of saving

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APPENDICES

Appendix A: Ethics clearance

Graduate School

orBUSINESS UNIVERSITYOF CAPETOWN

GSB/MBA/ETHICS/001

John Chundu

Graduate School of Business, University of Cape Town

[email protected]

Prof Ralph Hamann

GSB Research Director

Research Chair (UCT ACDI)

T: +27 (0)21 406 1503

E: [email protected]

Cape Town, 19 January 2017

Dear John,

RE: ETHICS APPROVAL

Thank you for submitting your ethical clearance application for your research on “Determinants of saving

among the Zambian middle class: The banking employees’ perspective”.

This is to confirm that your application has been assessed by the GSB’s Ethics in Research Committee according

to the rules and norms of the University and Commerce Faculty, and that it has been approved.

Please note that if you make any substantial change in your research procedure that could affect the experiences

of the participants, you must submit a revised protocol to the Committee for approval.

We wish you all the best for your research.

Kind regards

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Appendix B: Notice to Respondents

This questionaire is being conducted by an MBA student at the Graduate School of Business,

University of Cape Town. The intention of this study is to contribute to the body of literature by

examining and understand the determinants of saving among the Zambian banking employees.

The research has been approved by the Commerce Faculty Ethics in Research Committee and is

conducted for academic purposes to fulfil the requirements of the Masters in Business

Administration degree programme.

You will not be requested to supply any identifiable information to ensure anonymity of your

responses. All information from this questionaire will be kept confidential, consolidated and not

linked to individual responses. Your participation is voluntary and you have the right to withdraw

from this research at anytime. Further, you have the right to refuse to answer any questions you feel

are not appropriate. Only the researcher will have access to completed questionnaires. The

questionaires will be deleted or shreded upon completion of the research, submission and

acceptance of the report to the University.

The questionaire will take between 10 – 15 minutes to complete and should be returned to the

researcher by xxxxxx using the email address indicated below.

Should you have any questions regarding this research, please feel free to contact the researcher at:

[email protected] or Mobile phone no. +260 xxx xxxxxx

Thank you in anticipation.

John Chundu

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mailto:[email protected]

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Appendix C: Instructions for distribution of questionnaire

Please follow the distribution pattern in the table. To avoid the possibility of having respondents

from the same unit, please distribute the questionnaire across a wide spectrum of staff (i.e.

operations, sales, finance etc.). Non-Zambian banking staff do not qualify for this study.

Profile of respondents

Description of respondent type Number to be sampled

Clerical staff (as per criteria of your bank) 5

Managerial staff ( as per criteria of your bank) 5

Executive staff ( as per criteria of your bank) 5

For easy follow up / reminders by the researcher, keep details of staff to whom the questionnaire

will be sent and share the said details with the researcher.

Thank you!

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Appendix D: Research Instrument

Instructions on how to complete questionnaire

Section A: For each row, please select what is applicable to you.

Section B, C, D & E: Select the choice or answer that suits you the best.

Return questionnaire to [email protected] once completed.

Section A

No. Classification 1 2 3 4 5

a. Gender Male Female Other

b. Age (years) < 25 26 - 35 36 - 45 46 - 55 > 55

c. Marital Status Married Single Divorced Co-habiting

d Number of children 0 1 2 3 >3

e. Educational Level Grade 12

Certificate

Professional

certificates

Diploma Bachelor’s

Degree /

Masters/Phd

Other

f. Monthly Gross Salary

Range (ZMW)

< 10000 10001 - 20000 20001 - 35000 35001 -

50000

> 50000

g. Level in organisation Clerical Managerial Executive

h. Total indebtedness (ZMW

& foreign currency bank

loans - reported in ZMW)

< 100000 100001 -

300000

300001 -

600000

600001 -

900000

>900000

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mailto:[email protected]

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i. Province of your tribal grouping

1. Lusaka

2. Central

3. Southern

4. Western

5. Eastern

6. Muchinga

7. Northern

8. Luapula

9. Copperbelt

10. North Western

11. Other

Section B

No. Questions Strongly

Disagree

Disagree Neither

disagree nor

agree

Agree Strongly

agree

1 2 3 4 5

1 I know how much money I

spent last month

2 I am happy with my

financial / budgeting skills

3 I own shares / trade on the

stock exchange

4 I have an Investment /

savings account

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5 I know the interest rate(s) I

pay on my loan(s)

6 I have an insurance life

Cover and or retirement

annuity

7 I make voluntary

contributions on top of my

mandated monthly pension

contributions

8 I currently save or put

money away

9 I always think about life

after retirement

10 I do not wait for store sales

promotions, I buy today

when I need it

11 I have borrowed in the last

24 months

12 I have taken on too much

debt (Debt service ratio:

Monthly loan repayments /

Monthly income after tax

+ NAPSA + Pension >

50%)

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13 I think easy access to

credit (loans) hinders

saving

Section C

No. Question Never Once a while Sometimes Often Always

1 2 3 4 5

14 How often did your

parents / relatives or

friends speak to you about

money or investments

when you were growing

up?

15 How often do you discuss

money issues with your

kids? (Skip question if you

have no kids).

16 How often do you support

your siblings or parents

financially?

Section D

No. Questions More than

K102

Exactly K102 Less than

K102

Do not

Know

No

Answer

1 2 3 4 5

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17 Suppose you had K100 in

a savings account and the

interest rate was 2% per

year. After 5 years, how

much do you think you

would have in the account

if you left the money to

grow?

No Question More than

today

Exactly the

same as today

Less than

today

Do not

know

No answer

1 2 3 4 5

18 Imagine that the interest

rate on your savings

account was 1% per year

and inflation was 2% per

year. After 1 year, would

you be able to buy more

than, exactly the same as,

or less than today with the

money in this account?

More than

today

Exactly the

same as today;

Less than

today

Do not

Know

No Answer

Section E

No. Question True False Do not Know No Answer

1 2 3 4

19 Do you think that the

following statement is true

or false? Buying a single

company stock usually

provides a safer return than

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a stock mutual fund (i.e. a

collection of stocks and or

bonds).

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