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2025 

 

An Assessment of factors influencing 

retirement saving among youth in Nairobi 

County, Kenya. 

 

 
 
Toroitich, Cherop 
Strathmore Business School  
Strathmore University 

 

 

Recommended Citation 

Toroitich, C. (2025). An Assessment of factors influencing retirement saving among youth in Nairobi County, 

Kenya [Strathmore University]. http://hdl.handle.net/11071/15957 

 
 
 
 
 

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http://hdl.handle.net/11071/15957
http://hdl.handle.net/11071/15957


 

 

AN ASSESSMENT OF FACTORS INFLUENCING RETIREMENT SAVING 

AMONG YOUTH IN NAIROBI COUNTY, KENYA 

 

 

 

 

 

CHEROP TOROITICH 

MPPM 2019: 123793 

 

 

 

 

 

A Dissertation Submitted in Partial Fulfilment for the Degree of Master of Public Policy and 

Management at Strathmore University 

 

 

 

 

May 2025



i 

 

DECLARATION 

I declare that this work has not been previously submitted and approved for the award of a 

degree by this or any other university. To the best of my knowledge and belief, the thesis 

contains no material previously published or written by another person except where due 

reference is made in the proposal itself.  

 

Cherop Toroitich 

MPPM: 123793 

Signature:                    Date………21/05/2025………………… 

 

This proposal was reviewed and approved for examination by: 

Dr. Thomas Kibua 

Signature:                Date:………21/05/2025…………………



ii 

 

ABSTRACT 

This study examined the factors influencing retirement saving behaviour among youth in 

Nairobi County, Kenya, and their implications for reducing old-age poverty. Despite economic 

growth and improved financial inclusion over the years, retirement savings among the youth 

remain critically low. This is largely due to unemployment, informal employment, financial 

illiteracy, and a focus on short-term consumption needs. The research was guided by the life-

cycle hypothesis and the theory of planned behaviour and aimed to assess how socioeconomic, 

psychosocial, and institutional factors affect youth retirement saving practices. To achieve 

these objectives, the study employed a mixed-method approach. Quantitative data was 

collected from youth respondents, and qualitative insights were drawn from interviews with 

policymakers and financial service providers. Socioeconomic factors such as income level, 

education, and employment type emerged as significant predictors of saving behaviour. In 

contrast, family obligations were found to have a negative impact on the ability to save. 

Psychosocial factors, particularly financial literacy and future orientation were positively 

associated with saving, although risk attitude was statistically insignificant. Institutional factors 

such as awareness of pension schemes, access to financial services, and trust in financial 

institutions also significantly influenced saving behaviour. The findings underscore the need 

for a multifaceted approach to improve youth retirement saving. Key recommendations include 

strengthening financial literacy through education, expanding digital pension platforms for 

informal workers, and revising policy frameworks to encourage voluntary contributions. This 

study provides a foundation for future research and policy action to build a savings culture and 

address the risk of old-age poverty among Kenya's youth. 

  



iii 

 

TABLE OF CONTENTS 

DECLARATION .............................................................................................................................. i 

ABSTRACT ..................................................................................................................................... ii 

LIST OF TABLES .......................................................................................................................... vi 

LIST OF FIGURES ....................................................................................................................... vii 

LIST OF APPENDICES ............................................................................................................... viii 

DEFINITION OF TERMS ............................................................................................................. ix 

ACKNOWLEDGMENTS ............................................................................................................... x 

DEDICATION ................................................................................................................................ xi 

CHAPTER 1: INTRODUCTION .................................................................................................... 1 

1.1. Introduction ........................................................................................................................... 1 

1.2. Background to the Study ....................................................................................................... 1 

1.2.1. Retirement saving .......................................................................................................... 3 

1.2.2. Factors influencing retirement saving behaviour among the youth ............................... 3 

1.3. Statement of the Problem ...................................................................................................... 4 

1.4. Research objectives ............................................................................................................... 5 

1.4.1. General Objective .......................................................................................................... 5 

1.4.2. Specific Objectives ........................................................................................................ 6 

1.5. Research questions ................................................................................................................ 6 

1.6. Significance of the study ....................................................................................................... 6 

1.7. Scope of the study ................................................................................................................. 8 

CHAPTER 2: LITERATURE REVIEW ......................................................................................... 9 

2.1. Introduction ........................................................................................................................... 9 

2.2. Theoretical literature ............................................................................................................. 9 

2.2.1. Life cycle hypothesis ..................................................................................................... 9 

2.2.2. Theory of planned behaviour. ...................................................................................... 11 



iv 

 

2.3. Empirical literature ............................................................................................................. 12 

2.3.1. Socio-Economic Factors Influencing Retirement Saving Behaviour .......................... 12 

2.3.2. Psychosocial Factors Influencing Retirement Saving Behaviour ................................ 14 

2.3.3. Institutional Factors Influencing Retirement Saving Behaviour ................................. 15 

2.3.4. Summary of reviewed literature .................................................................................. 16 

2.3.5. Research gaps .............................................................................................................. 17 

2.4. Conceptual Framework ....................................................................................................... 22 

2.5. Operationalization of variables ........................................................................................... 23 

CHAPTER 3: RESEARCH METHODOLOGY ........................................................................... 26 

3.1. Introduction ......................................................................................................................... 26 

3.2. Research Philosophy ........................................................................................................... 26 

3.3. Research Approach ............................................................................................................. 27 

3.4. Research Design ................................................................................................................. 27 

3.5. Population of the Study ....................................................................................................... 28 

3.6. Sampling and Sample Size ................................................................................................. 29 

3.7. Data Collection methods ..................................................................................................... 33 

3.7.1. Data Collection Procedure ........................................................................................... 33 

3.8. Reliability and validity of instruments ................................................................................ 34 

3.8.1. Reliability .................................................................................................................... 34 

3.8.2. Validity ........................................................................................................................ 35 

3.9. Data analysis ....................................................................................................................... 36 

3.9.1. Quantitative Data Analysis .......................................................................................... 36 

3.9.2. Qualitative Data Analysis ............................................................................................ 37 

3.10. Ethical considerations ....................................................................................................... 37 

CHAPTER 4: DATA ANALYSIS AND FINDINGS ................................................................... 38 

4.1. Introduction ......................................................................................................................... 38 



v 

 

4.2. Response Rate ..................................................................................................................... 38 

4.3. Demographic Data .............................................................................................................. 39 

4.4. Descriptive Statistics ........................................................................................................... 46 

4.4.1. Psychosocial factors affecting retirement savings behaviour among youth ................ 46 

4.4.2. Institutional factors affecting retirement savings behaviour among youth .................. 48 

4.4.3. Retirement planning knowledge and behaviour .......................................................... 50 

4.5. Inferential Statistics ............................................................................................................ 53 

4.5.1. Socioeconomic factors affecting retirement savings behaviour among youth ............ 54 

4.5.2. Psychosocial factors affecting retirement savings behaviour among youth ................ 55 

4.5.3. Institutional factors affecting retirement savings behaviour among youth .................. 56 

CHAPTER 5: DISCUSSIONS, CONCLUSIONS AND RECOMMENDATIONS ..................... 57 

5.1. Introduction ......................................................................................................................... 57 

5.2. Discussion of the findings ................................................................................................... 57 

5.2.1. Socioeconomic Factors and Retirement Saving Behaviour ......................................... 57 

5.2.2. Psychosocial Factors and Retirement Saving Behaviour ............................................ 58 

5.2.3. Institutional Factors and Youth Participation in Retirement Saving ........................... 59 

5.3. Conclusions ......................................................................................................................... 60 

5.4. Recommendations ............................................................................................................... 60 

5.4.1. Policy recommendations .............................................................................................. 60 

5.4.2. Practical Recommendations ......................................................................................... 61 

5.5. Suggestions For Further Studies ......................................................................................... 62 

5.6. Limitations of the Study ..................................................................................................... 63 

CHAPTER 6: REFERENCES ....................................................................................................... 64 

 



vi 

 

LIST OF TABLES 

Table 2.1: Summary of Reviewed Literature and Identified Gaps .......................................... 19 

Table 2.2: Definition and measurement of variables ............................................................... 23 

Table 3.1: Population of Nairobi sub counties ......................................................................... 28 

Table 3.2: Calculated Sample Size .......................................................................................... 30 

Table 3.3: Sample size per sector per subcounty ..................................................................... 31 

Table 3.4: Reliability test results ............................................................................................. 35 

Table 4.1: Response Rate ......................................................................................................... 38 

Table 4.2:Proportion of savings by age group ......................................................................... 40 

Table 4.3: Average monthly savings by Education Level ....................................................... 41 

Table 4.4: Education Level and Retirement Saving Participation ........................................... 42 

Table 4.5: Marital status and number of dependents of respondents ....................................... 42 

Table 4.6: Employment Status and Retirement Saving Participation ...................................... 43 

Table 4.7: Income level and number of years worked of respondents .................................... 44 

Table 4.8: Income Level and Retirement Saving Participation ............................................... 44 

Table 4.9: Descriptive statistics for psychosocial factors ........................................................ 47 

Table 4.10: Descriptive statistics for institutional factors ....................................................... 49 

Table 4.11: Reasons for not thinking of retirement saving ...................................................... 50 

Table 4.12: Respondents' anticipated retirement age ............................................................... 51 

Table 4.13: Correlation Analysis ............................................................................................. 53 



vii 

 

LIST OF FIGURES 

Figure 2.1: Conceptual Framework ......................................................................................... 22 

Figure 4.1: Number of respondents by sub county .................................................................. 39 

Figure 4.2: Respondents' Gender ............................................................................................. 40 

Figure 4.3: Employment status of respondents ........................................................................ 43 

Figure 4.4: Respondents' financial situation ............................................................................ 45 

Figure 4.5: Financial priorities of respondents ........................................................................ 45 

Figure 4.6: Perceived barriers to retirement savings ............................................................... 48 

Figure 4.7: Proportion saving for retirement ........................................................................... 51 

Figure 4.8: Reasons for not saving for retirement ................................................................... 52 

Figure 4.9: Extent of Retirement Savings Knowledge ............................................................ 52 

Figure 4.10: Retirement saving methods ................................................................................. 53 

 

  



viii 

 

LIST OF APPENDICES 

Appendix 1: Introduction Letter .............................................................................................. 71 

Appendix 2: Survey Questionnaire .......................................................................................... 72 

Appendix 3: Key Informant Interview Guide .......................................................................... 80 

Appendix 4: SU -ISERC Approval .......................................................................................... 82 

Appendix 5: NACOSTI License .............................................................................................. 83 



ix 

 

 DEFINITION OF TERMS 

Financial Literacy The ability to understand and effectively use various financial skills, 

including personal financial management, budgeting, and investing. 

 
 

Informal 

Employment 

Work that is not regulated by formal contracts or covered by labour 

legislation, often lacking social protection and pension benefits. 

 
 

Life-Cycle Hypothesis 

(LCH) 

An economic theory suggesting individuals plan consumption and 

savings behaviour over their lifetime to maintain a stable standard of 

living. 

 
 

Pension Scheme A structured program that enables individuals to contribute toward a 

fund that provides income upon retirement. 

 
 

Retirement Benefits 

Authority (RBA) 

The regulatory body established under the Retirement Benefits Act 

to supervise, regulate, and promote retirement schemes in Kenya. 

 
 

Retirement Saving The act of setting aside financial resources during one’s working life 

to ensure income security during retirement. 

 
 

Theory of Planned 

Behaviour (TPB) 

A behavioural theory that explains how attitudes, social norms, and 

perceived control influence an individual’s intention to perform a 

behaviour. 

 
 

Youth Individuals aged between 18 and 35 years, as defined by Kenya’s 

national youth policy. 

 

  



x 

 

ACKNOWLEDGMENTS 

I wish to express my sincere gratitude to everyone who supported me throughout the course of 

this academic journey. I extend my deepest appreciation to my family for their unwavering 

love, encouragement, and patience. To my dear husband, thank you for your constant support, 

understanding, and belief in me even during the most demanding phases of this journey. Your 

encouragement kept me going when the road became tough. Above all, I give thanks to God 

for the strength, grace, and clarity of purpose that carried me through. 

  



xi 

 

DEDICATION 

This work is lovingly dedicated to the memory of my beloved “twin” Chebet Toroitich. Though 

you are no longer physically present, your spirit has remained with me every step of the way. 

Your unwavering belief in me, your laughter, and your light continue to inspire and strengthen 

me. This achievement is a tribute to the bond we will always share. 

To my dear husband, thank you for your love, patience, and steadfast support. Your 

encouragement has been my anchor throughout this journey. 



1 

 

CHAPTER 1: INTRODUCTION 

1.1. Introduction 

This chapter introduces the study by presenting the background and rationale behind examining 

retirement saving behaviour among youth in Nairobi County, Kenya. It begins by 

contextualising the issue of old-age financial insecurity and the global and local challenges 

related to youth participation in pension systems. The chapter further outlines the statement of 

the problem, research objectives, and research questions, followed by the significance and 

justification of the study. It also details the scope, limitations, and organisation of the thesis. 

Collectively, these elements provide a comprehensive foundation for understanding the 

purpose and structure of the research. 

1.2. Background to the Study 

Old-age poverty and financial insecurity in retirement are growing global concerns, particularly 

as populations age and traditional support systems erode. According to the United Nations 

(2015), nearly half of all people of retirement age globally do not receive a pension. In 

developing countries, pension systems are especially vulnerable, often covering only a small 

fraction of the population (Lyons et al., 2018). These challenges reflect the evolving and often 

fragile nature of social protection systems, especially across Africa, where pension 

infrastructure is still maturing. Rapid urbanisation, shifting demographics, and economic 

transitions have compounded the complexity of ensuring long-term financial security, 

especially for vulnerable populations (ILO 2022). 

Historically, many African societies, including Kenya, relied on informal social protection 

structures primarily extended families to support the elderly (Cohen et al., 2006). However, 

urbanisation, modernisation, and changing family dynamics have significantly weakened these 

informal systems, leaving many older adults without support and perpetuating cycles of old-

age poverty. In response, governments have established formal retirement systems to reduce 

reliance on family and public resources. 

In Kenya, the formal retirement system was introduced in 1965 with the establishment of the 

National Social Security Fund (NSSF) under Cap 258 of the Laws of Kenya. Initially designed 

as a provident fund, the NSSF was later restructured into a defined contribution scheme through 

reforms in 2013. Despite these changes, NSSF continues to face challenges such as low 



2 

 

coverage, especially among informal sector workers, limited investment diversity, and delays 

in benefits disbursement factors that undermine its effectiveness in securing old-age income 

(World Bank, 2023; Cytonn Investments, 2024). 

To strengthen regulatory oversight, the Retirement Benefits Authority (RBA) was established 

in 1997. Over time, the Authority has introduced reforms to improve scheme governance and 

compliance. Nevertheless, the pension system remains limited in reach and inclusivity. 

Informal workers remain largely excluded, and uptake of voluntary contributions among youth 

is low. These gaps have resulted in persistently low participation rates, especially among young 

people, further increasing the risk of future old-age poverty (RBA, 2023). 

Kenya's demographic profile underscores the urgency of addressing youth retirement 

preparedness. Over 60% of the population is aged between 18 and 35 years; a group that holds 

immense economic potential for the country. However, studies show that Kenyan youth are 

poorly prepared for retirement (Safari et al., 2021). Many lack the knowledge, motivation, and 

attitudes necessary to cultivate long-term saving habits. 

Several barriers contribute to this trend. Youth often prioritise immediate financial needs such 

as education, housing, and family support, leaving little room for retirement savings. This 

behaviour reflects a broader poor saving culture in Kenya, which, if left unaddressed, could 

translate into widespread dependence and poverty in later life (Enwealth, 2022). Financial 

planning and early savings are, therefore, critical to ensuring long-term financial security. As 

Hershey & Mowen (2000) argue, inadequate pre-retirement planning is a key contributor to 

economic challenges in retirement. 

Further complicating the situation is the structure of Kenya’s labour market. According to 

IPSOS (2020), a large proportion of Kenyan youth work in the informal sector or gig economy, 

which often falls outside the formal pension system. This makes it difficult for many young 

people to access or contribute to retirement savings plans. Despite these challenges, there is 

limited data on how Kenyan youth perceive and prioritise retirement savings. 

Existing studies on saving behaviour tend to focus on either economic or demographic factors 

(Yusof & Sabri, 2017). They often neglect the influence of psychosocial and institutional 

dynamics. A more holistic understanding of these interconnected factors is essential to design 

effective policy interventions. In the Kenyan context, research that integrates socioeconomic, 



3 

 

psychosocial, and institutional dimensions is urgently needed to inform inclusive policies that 

promote a saving culture and improve retirement preparedness among youth.  

1.2.1. Retirement saving  

Retirement refers to permanent withdrawal from paid working life (Denton & Spencer, 2009). 

It is normally associated with exit from employment at defined retirement age but can also be 

performed prior to attaining the prescribed age due to a variety of reasons (Atchley, 1982). 

Upon retirement, individuals who have saved and planned accordingly can access their 

retirement benefits savings and use it as a source of income post work life. The retirement 

benefits can take various forms of payments which include a lump sum- where the retiree gets 

full access to their entire benefits; pension- where a retiree gains access to a percentage of their 

benefits upon retirement and receives smaller subsequent payments on a regular basis. 

Retirement benefits are therefore  necessary to help alleviate  old age poverty (Stewart & 

Yermo, 2009) . 

Recent statistics from the Retirement Benefits Authority reveal that only about 20% of Kenya's 

working population participates in formal retirement schemes (Retirement Benefits Authority, 

2024). The situation is particularly dire among Kenyan youth, where participation rates are 

even lower. This low participation rate is concerning given that Kenya's old age dependency 

ratio is projected to increase significantly in the coming decades, potentially creating a 

substantial social and economic burden. Retirement planning is therefore necessary to equip one 

with the necessary skills and abilities required to ensure adequate retirement preparedness and 

savings that will eventually lead to reduced old age poverty. 

1.2.2. Factors influencing retirement saving behaviour among the youth 

Studies by Foster (2017), Indapurkar et al. (2024), and Xie et al. (2023) indicate a knowledge 

gap when it comes to retirement planning and saving among young people. Many young people 

have been noted to have inadequate knowledge on basic financial concepts, investment options 

and the importance of early retirement savings for their retirement security. This has resulted 

in poor retirement savings decision making and financial insecurity in the retirement years. 

Compounding this challenge with high costs of living makes it challenging for Kenyan youth 

to save for retirement. 

The high cost of living in Nairobi, coupled with irregular income patterns and unemployment 

challenges, creates immediate financial pressures that often override long-term saving 



4 

 

considerations. Youth frequently prioritize immediate needs and short-term investments over 

retirement saving, creating a significant gap in their future financial security (IPSOS, 2020). 

The current pension system structure may not adequately address the needs and circumstances 

of young workers, particularly those in the informal sector. Complex registration processes, 

minimum contribution requirements, and limited flexibility in pension products can discourage 

youth participation (World Bank, 2023). 

The rapid growth of financial technology (fintech) in Kenya, particularly mobile money 

services like M-PESA, has created new opportunities for retirement saving. These innovations 

have the potential to increase financial inclusion and make retirement saving more accessible 

to youth. However, the impact of these technological advances on youth retirement saving 

behaviour remains understudied (FSD Kenya, 2021). 

The Kenyan government has implemented various policies aimed at enhancing retirement 

security and promoting saving. The recent reform of the NSSF Act in 2013 and initiatives to 

expand pension coverage to informal sector workers demonstrate policy commitment to 

addressing retirement security (World Bank, 2023). However, the effectiveness of these 

policies in encouraging youth participation in retirement saving schemes requires further 

evaluation. 

1.3. Statement of the Problem 

Globally, increased life expectancy has highlighted the urgent need for robust retirement saving 

practices to mitigate old-age poverty. In Kenya, this challenge is particularly acute, as only 3% 

of the elderly population receives a regular pension income (Kakwani et al., 2006). Despite 

notable economic growth and financial sector expansion in recent years, a significant 

proportion of Kenyan youth remain inadequately prepared for retirement. This lack of 

preparedness poses a growing threat to their future financial security and risks compounding 

the burden on families and public support systems. 

Prior studies underscore the importance of early retirement planning and saving in achieving 

financial stability in old age (Hershey & Mowen, 2000; Yusof & Sabri, 2017). However, youth 

in Kenya particularly those in Nairobi continue to face significant structural and behavioural 

barriers. These include high unemployment rates, irregular income, high living costs, and 

competing financial priorities. The situation is further complicated by Kenya’s labour market 

composition, where over 80% of the workforce operates in the informal sector and lacks access 



5 

 

to formal retirement arrangements (Paklina, 2018). With youth comprising more than 70% of 

the national population, the exclusion of this demographic from pension systems signals a 

looming crisis. 

Although the Retirement Benefits Authority (RBA) has introduced reforms to expand 

coverage, current data show that only about 20% of Kenya’s working population participates 

in formal retirement schemes (RBA, 2023). This coverage is even lower among youth, who are 

often unaware of or excluded from institutional pension products. Social shifts such as 

urbanisation and weakening family safety nets have further diminished traditional old-age 

support mechanisms (Cohen et al., 2006; Thuku, 2013). These developments make personal 

retirement planning more essential than ever. 

Previous studies have examined economic and demographic factors influencing saving 

behaviour (Fan et al., 2021; Githui & Ngare, 2014). However, few have comprehensively 

explored how socioeconomic, psychosocial, and institutional factors interact to shape 

retirement saving behaviour among youth in Kenya. Notably, the role of psychosocial variables 

such as financial literacy, future orientation, and motivation remains underexplored in this 

context (Ibeme, 2014). Additionally, institutional barriers such as rigid contribution structures 

and inadequate policy incentives continue to discourage participation (The National Treasury, 

2023). 

This study, therefore, addresses a critical research gap by investigating the interplay of 

socioeconomic, psychosocial, and institutional factors influencing retirement saving behaviour 

among youth in Nairobi County. By building on previous work while extending it to include 

underexamined variables, the study aims to inform inclusive policies and interventions that can 

foster a savings culture and enhance long-term financial security for Kenya’s youth. 

1.4. Research objectives 

1.4.1. General Objective 

The overall objective of this research was to examine the factors influencing retirement saving 

behaviour among the youth in Kenya and their implications for old age poverty mitigation. 

 

 



6 

 

1.4.2. Specific Objectives 

The specific objectives of the study were to: 

i. Evaluate the impact of socioeconomic factors (income levels, employment status, 

education, and family obligations) on retirement saving decisions among youth in 

Nairobi County. 

ii. Determine the relationship between psychosocial factors and retirement saving 

practices among youth in Nairobi County. 

iii. Examine the influence of institutional factors (access to formal financial services, 

pension scheme features, and regulatory framework) on youth participation in 

retirement saving programs in Nairobi County. 

While retirement saving is influenced by various factors including cultural, economic, and 

policy related dynamics, this study focused on socioeconomic, psychosocial, and institutional 

factors due to their strong theoretical grounding and practical relevance in the Kenyan context. 

Socioeconomic conditions affect the ability to save, psychosocial traits shape saving intentions, 

and institutional factors influence access and trust in retirement saving mechanisms. Together, 

these dimensions offer a comprehensive and policy-relevant lens for understanding youth 

saving behaviour, especially within urban and informal employment settings 

1.5. Research questions  

To achieve the general objective, this study addressed the following questions. 

i. How do socioeconomic factors (income levels, employment status, education, and 

family obligations) impact retirement saving decisions among youth in Nairobi County. 

ii. To what extent do perceptions and attitudes determine retirement saving practices 

among youth in Nairobi County. 

iii. To what extent do institutional factors (access to formal financial services, pension 

scheme features, and regulatory framework) influence youth participation in retirement 

saving programs in Nairobi County? 

1.6. Significance of the study 

This study provides a multidimensional understanding of the factors influencing retirement 

saving behaviour among youth in Kenya, focusing on the intersection of socioeconomic, 

psychosocial, and institutional variables. It is significant for theory, policy, and practice. From 



7 

 

a theoretical standpoint, the research contributes to the academic body of knowledge by 

integrating and empirically applying the Life-Cycle Hypothesis and the Theory of Planned 

Behaviour. While most existing studies in Kenya concentrate narrowly on financial literacy, 

this research broadens the scope to include behavioural intent and institutional factors such as 

access to pension products and trust in financial systems. By doing so, it fills a knowledge gap 

and offers contextualised evidence on youth saving patterns in an environment characterised 

by high informality and economic precarity. The findings thus enhance the explanatory power 

of the two frameworks when applied in developing country settings. 

From a policy perspective, the study provides valuable insights to support the development of 

inclusive, evidence-based strategies and regulatory frameworks aimed at promoting early and 

consistent retirement saving behaviour among youth. This includes informing the work of the 

Retirement Benefits Authority (RBA), the National Treasury, and other key policy actors. The 

findings highlight the importance of implementing youth-targeted financial education, mobile-

enabled pension solutions, simplified registration procedures, and incentive-based mechanisms 

such as tax reliefs and government matching contributions. These insights are particularly 

crucial in addressing the long-term risk of old-age poverty and improving the standards of 

living among future retirees. 

Practically, the study offers useful recommendations to pension and provident scheme 

providers on how to structure retirement saving products that are attractive and accessible to 

the youth. It highlights the need for flexible contribution mechanisms, trust-building measures, 

transparent communication, and simplified onboarding processes. In doing so, it guides 

providers in adopting best practices that resonate with young savers. Furthermore, the study 

has implications for financial educators, curriculum developers, and civil society actors, 

reinforcing the need to incorporate retirement planning into secondary and tertiary education 

as part of a broader strategy to instil a savings culture from an early age. 

Overall, the study’s findings present an in-depth understanding of the complex dynamics 

influencing retirement saving behaviour among youth and provide actionable 

recommendations for improving financial inclusion, supporting policy reforms, and guiding 

institutional innovation in Kenya’s pension landscape.. 



8 

 

1.7. Scope of the study 

The study focused on the factors influencing retirement savings among the youth in Nairobi. 

Nairobi was chosen by the researcher as the area of study due to its evolving socioeconomic 

landscape and being the largest urban centre in the country. Nairobi also has the highest number 

of Kenyan youths seeking employment and economic opportunities. The diversity of the 

neighbourhoods offered by the geographical location creates varying socioeconomic and 

psychosocial conditions that influence retirement saving behaviours making it suitable for the 

study. The scope of the unit of analysis of the study was  employed Kenyan youth. The scope 

of the research instrument was limited to semi-structured questionnaires and Key Informant 

Interviews (KIIs). The scope of the respondents of the study was therefore Nairobi youth 

working in both formal and informal employment. In the context of this study, youth was 

regarded as employed persons aged 18 to 35 years as defined by (Constitution of Kenya, 

Chapter 17, Article 260 (2010). 



9 

 

CHAPTER 2: LITERATURE REVIEW 

2.1. Introduction 

This chapter reviews the literature on the retirement savings and factors that determine 

retirement saving patterns. The chapter will begin with the theoretical review of theories and 

empirical literature that underpin this study which form the basis of establishing a conceptual 

framework. 

2.2. Theoretical literature 

2.2.1. Life cycle hypothesis 

The life-cycle hypothesis was developed by Franco Modigliani in 1957. The hypothesis is an 

economic theory that explains how people manage their spending and saving throughout their 

lives. It suggests that individuals aim to maintain a stable level of consumption by borrowing 

during periods of low income and saving during times of high income. Accordingly, it infers 

those individuals plan their consumption, saving, and dissaving behaviour with a mind to 

smoothen out changes in their lifestyles over the course of their lifetimes (Fan, Stebbins, & 

Kim, 2021).  

The life-cycle hypothesis assumes that people earn majority of their income during their 

working years. Further, it assumes that consumers are logical, forward-thinkers and proactive 

planners. This means that people will plan accordingly during their working age to ensure 

wealth accumulation. Wealth accumulation according to Franco Modigliani follows a hump-

shaped curve where it is assumes that individuals have a low saving rate when younger as there 

have less income; high rate of saving when middle- aged/ working age as they earn more 

income and low rate of savings when old (Hayes, 2021). Another assumption is that individuals 

will maintain the same level of consumptions by saving when their income is high and 

borrowing when income is low. The theory suggests that savings are corelated to income levels 

where it assumes that those with more income will save more while those with less income will 

save less. Additionally, it assumes that those with higher income are considered to be more 

financially savvy and are more likely to make better financial decisions as compared to those 

that have less disposable income. 

 



10 

 

In practice, people vary greatly in their consumption habits which are subject to erratic 

fluctuations across periods of relative success and hardship. There are also several factors that 

modulate old age poverty. These include positive structural factors such as government welfare 

programmes for retirees and negative structural factors such as the economic effects of 

pandemics. They also include positive sociocultural factors, such as private cash transfers and 

care from relatives as well as negative sociocultural factors such as an unexpected need to care 

for relatives (Kwan & Walsh, 2018). Such factors are distinct from the individualistic economic 

activities of borrowing, saving and dissaving advocated by Modigliani as the core of lifestyle 

stability. The life-cycle theory is, therefore, less useful as a descriptive model of lifetime 

consumption behaviour and is better used to identify the considerations useful to retirement 

planning during employment instead.  

The life cycle theory has also faced criticisms due to its assumptions that may not be reflective 

on today’s society. It assumes that people are rational and forward thinkers; however, this is 

not the case as individuals have been shown to be poor planners. Additionally, they lack the 

discipline to prioritise their spending vis a vie savings. It also assumes that people do not work 

during old-age and that wealth generated is depleted during this stage of people’s life. This is 

not the case as individuals have been shown to have an attachment to wealth and a reluctance 

to spend. Further, it has been observed that the elderly do not fully retire from employment 

with many choosing to work during retirement. They also do not run down the wealth they 

have accumulated but rather save up with the intention of bequeathing to the next generation. 

Additionally, people may not have intentions to save where a governments have provided 

social security (Pettinger, 2019). 

Despite all the criticisms of the life-cycle hypothesis, Deaton (2005) argues that it is an essential 

theory that informs on issues such as provision of private and public social security, the impact 

of demographic shifts on national savings, the significance of savings in economic growth, and 

the factors influencing national wealth. It also provides a guide on how individuals should 

prioritize spending and saving where it encourages borrowing during low income phase and 

saving during high income cycles (Mpaata et al., 2020). 

The life-cycle hypothesis can be observed in saving for retirement as it is assumed to be part 

of a normative lifecycle. This is viewed in individuals who save during their earning period to 

be able to afford a similar lifestyle upon retirement. Majority of those in formal employment 

save for their retirement through an employer-sponsored program where contributions are 



11 

 

directly remitted from wages. However, those in non-formal working arrangements with an 

irregular income are often observed to save less towards their retirement savings. 

This theory directly informs the first and third objectives of the study. The first objective 

explores how socioeconomic factors like income, education, and employment type influence 

retirement saving. According to the hypothesis, these are critical determinants because they 

impact an individual's capacity and motivation to save during high-income years. The third 

objective, which examines institutional factors, also aligns with the life-cycle hypothesis 

framework. Institutional arrangements such as pension access, policy incentives, and trust play 

a significant role in determining whether individuals, especially those in informal employment, 

can participate in retirement saving during their peak earning years. This theory therefore 

supports the research objectives hypothesis that demographic and socio-economic and policy 

factors have an influence on retirement savings. 

2.2.2. Theory of planned behaviour. 

The theory of planned behaviour was developed by Icek Ajzen in 1985 and is aimed at 

understanding human behaviour. It builds upon the theory of reasoned action, suggesting that 

individuals make rational and well-thought-out decisions to engage in certain behaviours by 

assessing the information they have. It states that three factors affect individual behaviour, and 

they include positive or negative attitude toward actual behaviour, subjective norms, and 

perceived behavioural controls. Therefore, an individual's intention to engage in a behaviour 

becomes stronger when they have a more positive attitude toward it, perceive greater social 

approval, and feel a higher sense of control over their actions (Kimiyagahlam et al., 2019). 

The theory of planned behaviour can be summarised into six main influences on an individual’s 

behaviours. These include attitudes, intention to act, subjective norms, social norms, perceived 

authority, and perceived control over behaviour (LaMorte, 2022). In the context of saving, 

Rahmawati & Asandimitra (2018) found that social environment have an impact on saving 

behaviour. This is because individual background such as experience, knowledge, age, and 

gender have an influence on their behaviours. Additionally, subjective norms such as social 

pressure also influence saving intentions. She et al. (2023) found that financial knowledge is 

positively related to retirement attitude which in turn had a positive relationship towards 

retirement planning.  



12 

 

Criticism of the theory of planned behaviour argue that it is limited by its assumptions. The 

theory bases it assumption that individuals act rationally which is not the case. Additionally, it 

does not take into consideration the economic and environmental factors that may influence a 

person’s behaviour. Furthermore, the theory assumes that individual have all the resources and 

opportunities available to make successful behavioural action. It also assumes that decision 

making is linear and does not take into consideration that can change over time (LaMorte, 

2022). 

The theory of planned behaviour model provides a basis for a comprehensive measure of 

retirement planning. In considering the factors, this theory supports the second objective of the 

study, which investigates the influence of psychosocial factors specifically financial literacy, 

attitudes toward saving, and future orientation on retirement saving behaviour. The theory of 

planned behaviour provides a framework for understanding how behavioural intent is formed 

and how it translates into action i.e. saving. The theory is especially relevant in the Kenyan 

youth context, where saving for retirement often competes with more immediate financial 

needs and limited behavioural reinforcement. It explains why even financially capable 

individuals may not save if they lack motivation, face social discouragement, or feel that saving 

is outside their control due to external constraints. 

In this regard, the theory of planned behaviour enhances the study’s behavioural dimension by 

illustrating how individual cognition and social influences shape retirement planning decisions, 

beyond purely economic considerations 

2.3. Empirical literature 

This section presents a critical review of empirical studies that explore the socio-economic, 

psychosocial and institutional factors influencing retirement saving behaviour. It adopts a 

funnel approach, beginning with global studies, narrowing to other developing countries, and 

concluding with evidence from Kenya. The review identifies the methodologies used in each 

study, outlines their geographic scope, and provides an analytical critique of their findings, 

limitations and policy relevance. 

2.3.1. Socio-Economic Factors Influencing Retirement Saving Behaviour 

At the global level, Lusardi and Mitchell (2011) conducted a series of surveys across the United 

States and Europe using cross-sectional data from the Health and Retirement Study (HRS) and 



13 

 

Financial Literacy Surveys. Their econometric analysis showed that individuals with higher 

education, stable income and full-time employment were more likely to plan for retirement. 

These findings support the Life-Cycle Hypothesis, which assumes people smooth consumption 

over their lifetime. The strength of their work lies in the breadth of datasets and rigorous 

modelling. However, the assumption of rational decision-making and formal income structures 

limits its relevance for populations with irregular earnings and weak social protection systems. 

In Indonesia, Rahmawati and Asandimitra (2018) used a structured questionnaire to collect 

data from 100 respondents in Surabaya, applying multiple linear regression to test the impact 

of income and self-efficacy on saving behaviour. While their study provided useful behavioural 

insights, the limited sample size and urban-only setting reduce generalisability. Similarly, 

Gunu and Tsado (2012) conducted a descriptive survey in Kwara State, Nigeria, to assess 

knowledge and participation in Nigeria’s contributory pension scheme. They identified low 

income and irregular employment as key deterrents. Their study offered practical insights but 

lacked robust statistical controls, weakening causal interpretation. 

In South Africa, Tustin and Strydom (2015) employed a comparative survey across formal and 

informal urban settlements. Their stratified random sampling approach highlighted stark 

differences in saving patterns, attributing them to job informality and limited employer-

sponsored pensions. While comprehensive, the study’s primary limitation was its lack of 

psychological or institutional variables. 

In Kenya, Githui and Ngare (2014) used a quantitative research design with structured 

questionnaires distributed among Nairobi’s informal sector. Their regression analysis found a 

strong positive relationship between income level and retirement planning. Similarly, Gitau, 

Njuguna and Otsola (2011) surveyed formal sector workers in Nairobi, using descriptive and 

inferential statistics to link employment tenure and financial training to saving outcomes. These 

studies offer useful local insights. However, they focus predominantly on formal employees, 

lack longitudinal depth, and do not explore how informal workers adapt to income volatility. 

According to an Enwealth (2022) pension report, economic burdens from dependents and 

competing saving priorities significantly undermine pension uptake. The study’s strength is in 

its wide geographic coverage and integration of qualitative and quantitative findings. Still, it 

does not apply statistical controls to test specific relationships or explore youth-specific 

dynamics. 



14 

 

These findings suggest that income stability, employment formality, and financial capacity are 

central to retirement saving. However, most existing studies rely on cross-sectional methods, 

do not target youth, and fail to examine informal sector dynamics, which dominate Kenya’s 

labour market. 

2.3.2. Psychosocial Factors Influencing Retirement Saving Behaviour 

A study by Hershey and Mowen (2000) using structural equation modelling based on data from 

the United States Retirement Confidence Survey, found that individuals with high financial 

literacy and future orientation were more likely to save. Their theoretical grounding in the 

Theory of Planned Behaviour allowed for rigorous modelling of behavioural constructs. 

However, the reliance on U.S. data and assumptions of financial access limit its application to 

developing contexts. 

Ismail (2013) conducted a survey of 385 university students in Malaysia, using regression 

analysis to explore the influence of social norms and peer influence on saving. While the study's 

youth focus is commendable, the student-only sample may not reflect broader socioeconomic 

diversity. In Uganda, Mpaata et al. (2020) applied a cross-sectional survey to staff at five public 

universities. Their ANOVA analysis showed that staff exposed to financial education had 

higher saving discipline. The study linked psychological traits to institutional exposure, but it 

lacked disaggregation by age and did not address informal employment. 

In Kenya, Githui and Ngare (2014) incorporated questions on financial literacy and behavioural 

beliefs in their survey of informal workers in Nairobi. They found that individuals with basic 

financial knowledge were more likely to engage in long-term financial planning. Similarly, 

Gitau, Njuguna, and Otsola (2011) reported that only 5.7% of respondents enrolled in 

registered pension schemes demonstrated comprehensive pension literacy. Additionally, 

Gathiira et al. (2019), using a mixed-method approach, found that goal setting and social 

reinforcement enhanced retirement preparedness in Nyeri County. While these studies offer 

valuable insights, they remain largely descriptive and do not evaluate the impact of specific 

interventions. 

The reviewed studies suggest  that psychosocial traits such as financial knowledge, future 

orientation, and peer norms significantly shape saving behaviour. Yet most empirical work in 

Kenya and similar contexts fails to combine these factors with structural or policy variables. 



15 

 

Furthermore, few studies measure behavioural change over time or assess the impact of 

targeted education interventions. 

2.3.3. Institutional Factors Influencing Retirement Saving Behaviour 

At the international level, the OECD (2016) used comparative policy reviews to show that 

participation in pension systems increases when transparency, regulatory oversight, and 

incentives are in place. However, these findings are based on countries with stable financial 

systems and may not address the fragmented regulatory landscapes seen in Africa. 

In Ghana, the National Pensions Regulatory Authority (NPRA 2020) conducted stakeholder 

interviews and surveys to examine the challenges hindering pension uptake among informal 

sector workers. Their findings pointed to low enrolment rates, largely attributed to limited 

awareness and poor alignment between pension products and the needs of informal workers. 

This underscores a critical gap in market segmentation and product design that fails to 

accommodate the irregular income patterns typical in informal employment. 

In Nigeria, Ilesanmi and Olayemi (2018) used descriptive survey methods to explore pension 

participation among youth. They found that distrust in pension providers was a major barrier, 

rooted in bureaucratic inefficiencies and negative service experiences. While the study 

identifies important structural constraints, its reliance on descriptive analysis limits its ability 

to establish how institutional trust interacts with other variables such as financial literacy or 

income stability. 

Similarly, Tustin and Strydom (2015) examined South Africa’s hybrid pension schemes 

through a comparative survey of formal and informal sector workers. Their results revealed 

that weak implementation and insufficient outreach to younger demographics significantly 

hindered youth engagement. Despite highlighting institutional shortcomings, the study did not 

disaggregate findings by age or socio-economic status, which weakens its capacity to inform 

targeted interventions. Together, these studies provide useful insights into the institutional 

challenges affecting pension participation in African countries. However, many lack strong 

research methods. Most do not use advanced analysis techniques like predictive modelling, and 

few explore how factors such as trust, access, and communication work together to influence 

youth saving behaviour. As a result, their findings offer limited guidance for designing pension 

systems that effectively meet the needs of young people. 



16 

 

In Kenya, Aluodi et al. (2017) conducted a survey among pension contributors and found that 

individuals with access to formal pension schemes were more likely to save. However, the 

study sample primarily consisted of salaried workers, limiting its applicability to informal 

sector participants. A study by Enwealth (2022) identified several practical barriers to pension 

uptake, including complex documentation requirements, inadequate customer service, and 

limited integration with mobile platforms. Similarly, Githui and Ngare (2014) emphasised the 

impact of mistrust arising from past mismanagement of pension funds, which further 

discourages youth from participating. While these studies offer valuable insights into structural 

challenges, they fall short of examining how trust, access, and financial literacy collectively 

shape retirement saving behaviour. 

The reviewed studies indicate that institutional access, trust in financial systems, and the design 

of pension services are critical factors in influencing retirement saving. However, most 

empirical research in Kenya and similar contexts remains largely descriptive and does not 

adequately explore how institutional reforms impact youth, particularly those in informal 

employment. Additionally, there is limited empirical testing of mobile-based or digital pension 

innovations, despite their increasing relevance in expanding access and engagement among 

younger populations. 

2.3.4. Summary of reviewed literature 

The reviewed literature demonstrates that retirement saving behaviour is shaped by a complex 

interplay of socio-economic, psychosocial, and institutional factors. Two key theories underpin 

this understanding. The Life-Cycle Hypothesis (Modigliani, 1957) emphasises the role of 

income, employment, and forward planning, suggesting that individuals save during high-

income periods to maintain consumption in later life. However, this model assumes rational 

behaviour and income stability, which are often absent in contexts like Kenya where informal 

employment is widespread. Consequently, the model’s assumptions limit its relevance for low-

income earners and young people with irregular income streams. 

To address these behavioural dimensions, the Theory of Planned Behaviour (Ajzen, 1985) 

provides a complementary perspective. It posits that saving behaviour is influenced by 

individual attitudes, perceived social norms, and the perceived ability to act. This theory 

explains why even financially capable individuals may not engage in retirement saving if they 

lack motivation, face peer pressure, or perceive external constraints beyond their control. It is 



17 

 

particularly relevant for youth, who may prioritise short-term financial needs and lack 

consistent behavioural reinforcement. 

Empirical studies affirm that income stability, formal employment, and financial literacy are 

key predictors of retirement saving across both developed and developing countries. However, 

much of this evidence is drawn from formal sector contexts and cross-sectional designs, 

limiting its applicability to youth and informal workers. In Kenya, studies reveal that youth 

participation in retirement saving remains low, with limited access to pension products, 

inadequate service delivery, and deep-seated mistrust in pension providers continuing to hinder 

engagement. 

While behavioural traits such as future orientation, goal setting, and peer influence are 

positively linked to saving, these are often studied in isolation from structural constraints. Very 

few studies integrate psychological and institutional factors in a unified model. Moreover, there 

is limited use of longitudinal or experimental approaches, which restricts understanding of 

behavioural change over time or in response to specific interventions. 

Across both theory and practice, a consistent message emerges: improving retirement saving 

among youth requires addressing both behavioural intent and structural opportunity. Most 

existing research mainly describes patterns. It does not use advanced analysis, and rarely tests 

practical solutions like digital pension plans, financial reminders, or peer-based education 

programmes. This gap is especially critical in developing countries, where economic 

vulnerability, low trust, and fragmented financial systems reduce participation in long-term 

saving schemes. 

These findings highlight the need for research that focuses on youth and considers their 

economic, behavioural, and institutional challenges . Such research is key to creating pension 

solutions that are practical, inclusive, and suited to Kenya’s changing job and financial 

environment. 

2.3.5. Research gaps 

A review of the empirical literature reveals several important gaps. These gaps relate to both 

the content and design of existing studies. They also highlight missed opportunities to examine 

youth saving behaviour in settings like Nairobi. Using the framework developed by Miles 



18 

 

(2017), seven distinct gaps can be identified in the literature. These gaps help justify the current 

study. 

First, there is a clear population gap. Most studies focus on adults in formal employment. 

Youth, especially those working informally, are often left out. For example, Gitau, Njuguna 

and Otsola (2011) focus on scheme members with regular jobs. Study by Enwealth (2022) 

presents national data, but it does not explore saving behaviour among young people in 

informal settings. This creates a blind spot in understanding a population that faces high levels 

of income insecurity and long-term financial vulnerability. 

Second, there is an empirical gap. While several studies provide descriptive insights, few offer 

strong empirical testing. Most do not use robust data to evaluate the relationship between 

financial literacy, trust, access, and saving outcomes. For example, Gathiira et al. (2019) and 

Aluodi et al. (2017) provide helpful observations, but they stop short of testing these 

relationships in a structured way. A lack of rigorous empirical work limits our ability to draw 

firm conclusions or inform policy. 

Third, there is a methodological gap. Many of the reviewed studies use simple survey methods 

and cross-sectional designs. For example, Rahmawati and Asandimitra (2018) rely on a small 

sample in a single city. These approaches do not support causal inference. They also fail to 

show how saving behaviour may change over time or in response to interventions. There is a 

need for more advanced methods such as multi-variable regression, mixed methods, or 

longitudinal approaches. 

Fourth, there is a knowledge gap. There is limited information on how young people make 

financial decisions under conditions of uncertainty. Studies such as Mpaata et al. (2020) and 

Ismail (2013) highlight the role of peer influence and education. However, they do not explain 

how these behavioural factors interact with broader issues such as product design or 

institutional trust. In Kenya, there is little research on how mobile money and digital platforms 

affect retirement saving among youth. 

Fifth, there is a theoretical gap. Many studies use traditional models such as the Life-Cycle 

Hypothesis or the Theory of Planned Behaviour. These models assume stable incomes and 

access to formal employment. Yet, most Kenyan youth work in informal jobs with 

unpredictable earnings. Applying these theories without adjustment fails to reflect the financial 



19 

 

realities faced by many young savers. There is a need to rethink or adapt theory to better match 

local conditions. 

Sixth, there is an evidence gap. The literature includes some conflicting results. For instance, 

Enwealth (2022) suggests that people want to save but are held back by low incomes. In 

contrast, Githui and Ngare (2014) argue that lack of knowledge is the bigger problem. These 

contradictions point to the need for further investigation. It is important to test how economic 

and behavioural factors work together to influence saving. 

Finally, there is a practical knowledge gap. Most studies do not lead to practical action. While 

regulators such as the Retirement Benefits Authority promote financial literacy, these 

programmes are not always informed by evidence. Few studies assess the impact of digital 

pension tools or simplified registration systems on saving behaviour. Bridging this gap requires 

research that produces recommendations relevant to both policy and practice. 

In light of these gaps, this study focuses on youth in Nairobi County. It includes informal sector 

workers who are often overlooked in retirement research. The study uses a mixed-method 

approach to explore the interaction of socio-economic, behavioural, and institutional factors. It 

also tests how these factors shape saving decisions. The goal is to generate findings that are 

both empirically sound and useful for designing products and policies that support youth 

retirement saving in Kenya 

Table 2.1: Summary of Reviewed Literature and Identified Gaps 

Author(s) Focus of Study Methodology and 
Findings

Knowledge 
Gaps

Focus of the Current Study 

Modigliani 
(1957) 

Life-cycle savings 
and consumption 
behaviour 

Theoretical; saving 
increases in high-
income years to 
smooth lifetime 
consumption 

Neglects 
institutional and 
social influences 

The current study draws on 
Modigliani's theory to explore 
how income and employment 
affect saving behaviour among 
youth in informal employment 
settings. 

Ajzen (1985) Planned 
behaviour theory 
for decision-
making 

Theory 
development; 
intentions influenced 
by attitudes, norms, 
and control 

Ignores economic 
and policy 
constraints 

The current study uses Ajzen's 
model to examine how financial 
literacy, attitudes, and perceived 
control influence youth saving 
intentions in Kenya. 



20 

 

Author(s) Focus of Study Methodology and 
Findings

Knowledge 
Gaps

Focus of the Current Study 

Lusardi and 
Mitchell 
(2011) 

Financial literacy 
and retirement 
planning in the 
US and Europe 

Cross-sectional 
econometric survey; 
education and 
employment 
increase planning 

Assumes 
rationality and 
stable income, 
lacks informal 
sector 
perspective 

Building on Lusardi and 
Mitchell, this study extends the 
analysis of financial literacy 
and employment to informal 
youth in Nairobi. 

Rahmawati 
and 
Asandimitra 
(2018) 

Income and self-
efficacy in 
retirement saving 
in Indonesia 

Regression on 
structured 
questionnaires; 
income and self-
confidence predict 
saving

Small urban 
sample, limits 
generalisation 

The current study builds on 
Rahmawati and Asandimitra by 
applying self-efficacy and 
income constructs to youth 
saving behaviour in a low-
income Kenyan context.

Gunu and 
Tsado (2012) 

Pension 
awareness and 
participation in 
Nigeria 

Descriptive survey; 
low income and 
mistrust reduce 
participation 

No robust 
statistical control, 
weak inference 

This study responds to Gunu 
and Tsado by investigating how 
trust and income barriers affect 
pension participation among 
youth in the informal sector.

Tustin and 
Strydom 
(2015) 

Saving behaviour 
in formal vs 
informal sectors 
in South Africa  

Comparative 
stratified survey; 
informal work 
weakens saving 
patterns 

Lacks 
behavioural and 
institutional 
variables 

The current study addresses gaps 
identified by Tustin and 
Strydom by integrating 
behavioural and institutional 
variables in the analysis of 
Kenyan youth.  

Githui and 
Ngare (2014) 

Income and 
saving behaviour 
in Nairobi’s 
informal sector 

Quantitative 
regression; income 
linked positively to 
retirement saving 

Focuses on 
formal sector, no 
longitudinal data 

Expanding on Githui and 
Ngare, the current study focuses 
on informal youth in Nairobi 
and incorporates recent 
economic changes. 

Gitau, 
Njuguna and 
Otsola (2011) 

Employment and 
pension training 
among Nairobi 
workers 

Descriptive and 
inferential statistics; 
tenure and training 
support saving 

Ignores informal 
worker dynamics 

The current study extends Gitau 
et al.'s findings by incorporating 
informal employment and 
examining the behavioural 
drivers of youth saving. 

Enwealth 
(2022) 

Barriers to 
pension uptake in 
Kenya 

Mixed-method; 
documentation, 
service, and digital 
access as barriers 

Descriptive only, 
lacks youth focus 
and causal insight

This study builds on Enwealth's 
findings by investigating 
practical access barriers for 
informal youth and testing 
behaviour-based solutions. 



21 

 

Author(s) Focus of Study Methodology and 
Findings

Knowledge 
Gaps

Focus of the Current Study 

Hershey and 
Mowen (2000) 

Behavioural traits 
and saving 
confidence in the 
US 

Structural 
modelling; future 
orientation and 
literacy improve 
saving 

Formal-only 
context, limited 
Low & Middle 
Income Countries 
relevance 

The current study applies 
Hershey and Mowen's 
behavioural insights to a youth-
specific, informal Kenyan 
context to evaluate saving 
readiness. 

Ismail (2013) Social norms and 
saving among 
Malaysian 
students 

Regression; peer 
norms affect saving 
behaviour 

Unrepresentative 
sample, narrow 
scope 

Expanding on Ismail's findings, 
this study examines the impact 
of peer norms on saving 
behaviour among youth outside 
the formal education system. 

Mpaata et al. 
(2020) 

Financial 
education and 
saving among 
Ugandan 
university staff 

Cross-sectional 
ANOVA; financial 
education improves 
saving discipline 

No youth focus, 
lacks behavioural 
analysis 

The current study builds on 
Mpaata et al. by focusing on the 
effects of financial education on 
retirement saving behaviour 
among youth in Kenya. 

Gathiira et al. 
(2019) 

Goal setting and 
saving behaviour 
in Nyeri County, 
Kenya 

Mixed-method; goal 
setting boosts 
preparedness 

No experimental 
design, 
descriptive 

This study adopts Gathiira et 
al.'s focus on goal-setting but 
applies it to youth in Nairobi's 
informal economy using a more 
analytical approach. 

Aluodi et al. 
(2017) 

Access to 
pensions and 
saving behaviour 
in Kenya 

Survey; access to 
formal pensions 
increases saving 

Salaried bias, 
excludes 
informal sector 

Expanding on Aluodi et al., this 
study investigates access and 
trust issues among informal 
sector youth rather than salaried 
employees. 

Ilesanmi and 
Olayemi 
(2018) 

Trust and 
participation in 
pensions in 
Nigeria 

Descriptive survey; 
mistrust and poor 
service reduce 
participation 

No modelling or 
youth-specific 
analysis 

This study addresses gaps in 
Ilesanmi and Olayemi by 
modelling the interaction 
between trust, financial literacy, 
and pension uptake among 
youth. 

OECD (2016) Policy and 
regulation impact 
on pension 
participation 

Policy review; 
transparency and 
incentives increase 
engagement 

Limited 
applicability to 
fragmented 
systems 

The current study uses OECD 
policy lessons to inform youth-
focused recommendations that 
respond to fragmented 
regulatory realities in Kenya. 



22 

 

 

2.4. Conceptual Framework 

Independent Variable     Dependent Variable 

The study sought to examine factors that influence retirement saving of youth. The dependent 

variable is retirement saving. The independent variables include socio-economic factors: 

income levels, employment status, education, family obligations, financial literacy; 

psychological factors: attitudes, motivation, future time perspective; institutional factors: 

access to formal financial services, pension scheme features and regulatory frameworks. 

Predications were made to demonstrate the relationship between the factors as shown on figure 

2.1.   

 

Socio-Economic 
Factors 
(income levels, 
employment status, 
education, family 
obligations, financial 
literacy) 

Psychological Factors 
(attitudes, motivation, 
future time 
perspective) 

Institutional Factors: 
(access to formal 
financial services, 
pension scheme 
features, and 
regulatory 
frameworks) 

Retirement saving 
among youth 

(Adequate savings, 
investment 

diversification) 

Figure 2.1: Conceptual Framework 



23 

 

2.5. Operationalization of variables 

The following framework (Table 2.2: Definition and measurement of variables) describes the 

variable and measurements that was used in the study. 

Table 2.2: Definition and measurement of variables 

VARIABLE DEFINITION MEASUREMENT 

Dependent 

Variable 

Retirement 

saving 

Savings set aside for 

retirement 

Average monthly savings 

in Kenya shillings 

Socio- 

Economic 

factors 

Age Number of years lived Ordinal variable 

Gender Classification of 

individual as male 

female or other 

Binary variable 

Marital status Relationship status  Categorical Variable 

Education Highest level of 

education attained  

Categorical Variable 

Dependents Individual that relies on 

the survey participant 

Number of individuals who 

rely on the survey 

participant 

Income Amount of money 

earned by an individual 

Average monthly income 

in Kenya shillings 

Employment 

type 

Classification of an 

individual’s work status

Binary variable 

Occupation 

period 

Span of time during 

which an individual is 

actively engaged in 

employment 

Number of years worked 



24 

 

VARIABLE DEFINITION MEASUREMENT 

Employment 

sector 

Classification of 

employment sector 

Binary variable 

Saving rate Proportion of income 

that is saved 

Monthly saving as 

percentage of income  

Saving approach Methods used to save Categorical Variable 

Savings as part 

of household 

Budget 

allocation 

Savings as a priority in 

household budget 

allocation each month 

Likert Scale 

Psychological 

factors 

Financial 

literacy 

Rating of knowledge 

needed to make 

informed financial 

decisions 

Likert scale 

Financial goals Retirement saving as 

priority financial goal 

Likert scale 

 

Retirement 

saving 

Retirement Saving 

activity  

Binary variable 

Retirement 

saving rate 

Proportion of income 

that is retirement 

savings 

Monthly retirement savings 

as percentage of income 

Retirement 

saving plan 

Type of retirement 

saving plan 

 Categorical Variable 

Financial risk 

tolerance 

Financial risk tolerance 

level 

Likert scale 



25 

 

VARIABLE DEFINITION MEASUREMENT 

Retirement 

saving 

challenges 

Challenges/ barriers to 

saving for retirement 

Identified key challenges to 

saving for retirement 

Saving 

motivation 

Mindset/beliefs/feelings 

that individuals hold 

towards retirement 

saving. 

Key motivators to save or 

not save for retirement 

Institutional 

Factors 

Retirement age 

policy 

Retirement age as 

factor to start planning 

and saving early. 

Likert Scale 

Tax incentives Extent to which 

measures provide for 

favourable participation 

in retirement saving 

Likert Scale 

Availability of 

public and 

private pension 

plans 

Perceptions that 

individuals hold 

towards retirement 

saving in public or 

private pension plans 

Motivation towards saving 

in public or private pension 

plans 



26 

 

CHAPTER 3: RESEARCH METHODOLOGY 

3.1. Introduction 

This chapter examines the methodology that was used in this study. The chapter looked into 

the research philosophy, research approach, research design, population sample, data 

collection, data analysis and ethical considerations. 

3.2. Research Philosophy 

Research philosophy refers to the assumptions that guide the development of a study and 

contribute to the generation of new knowledge (Saunders et al., 2015). According to Saunders 

et al. (2015), these assumptions can be categorised into three types: ontological, which relate 

to the nature of reality; epistemological, which concern how knowledge about that reality can 

be acquired; and axiological, which address the researcher’s values and how they may 

influence the research process. 

This study followed a positivist research philosophy. This is because positivism is anchored to 

the view that real knowledge is gained from observations that involve measurements which are 

trustworthy (Collins, 2010). Additionally, positivism relies on a deductive method where a 

researcher has to verify a priori hypotheses using factual data, deriving relationships between 

causal and explanatory factors (Park et al., 2020). This made the philosophy appropriate for 

this researcher as it sought to establish the relationship between socioeconomic, psychological 

and institutional factors and the impact on retirement savings among the youth in Nairobi, 

Kenya. This way, the research would establish which factors were enablers or impeded 

retirements saving among the youth. 

Researchers who have employed the positivist approach to studies argue that knowledge should 

be developed objectively without the biases and beliefs of the researcher influencing the study 

(Park et al., 2020). In order to achieve the truth, Hansen (2004) suggests separating the 

researcher from the study’s participants through dualism and objectivity. This is done through 

research protocols to reduce biases in studies. 

Positivist research philosophy limits the researcher to data collection only and interpreting the 

data in an objective manner. Positivist research relies solely on quantifiable and measurable 

observations that can be statistically analysed for generalisation, interpretation, and knowledge 

production (Yee & Khin, 2010). Given these characteristics, it was an appropriate approach for 



27 

 

this study. Moreover, the researcher was distinct from the participants to achieve objectivity in 

its findings. 

3.3. Research Approach 

Given the research philosophy adopted by the study, a mixed method approach was employed. 

This involved the use of both qualitative and quantitative data to assess the factors influencing 

retirement saving behaviours among youth in Nairobi County, Kenya. Creswell (1999) 

explains that a mixed-method approach, particularly in policy research, enables researchers to 

gain an in-depth understanding of complex phenomena through quantitative data and to 

validate or elaborate on findings using qualitative insights. Similarly, Rossman and Wilson 

(1985) argue that mixed methods enable researchers to examine problems from multiple 

perspectives. This approach allows for the application of diverse methodologies that are better 

suited to addressing the varied needs of stakeholders. As a result, mixed methods offer more 

balanced and comprehensive solutions compared to single-method designs. 

For the quantitative part, the study undertook a cross-sectional survey to examine the 

relationships between socio-economic, psychological and institutional factors and how they 

influence retirement savings among the youth. On the other hand, qualitative data was gathered 

using unstructured interview guides. However, the study acknowledges certain limitations 

inherent in the chosen methodology, including reliance on self-reported data, which may be 

subject to recall bias or social desirability effects, and the cross-sectional design, which restricts 

the ability to draw causal inferences from observed relationships. 

3.4. Research Design 

A study’s research design is the blueprint on how data will be collected from a target 

population. According to Creswell & Creswell (2018), there exists three main mixed methods 

research designs: the convergent design, the explanatory sequential design, and the exploratory 

sequential design. This study adopted the explanatory sequential design. Both qualitative and 

quantitative data are collected and analysed separately. The results are then merged and 

interpreted to compare whether they confirm the phenomenon under study or not.   

The study was cross-sectional in nature and utilised an explanatory design. This design allows 

researchers to collect both quantitative and qualitative data by first collecting quantitative data 

and analysing it and then collecting qualitative data to explain further the quantitative results 



28 

 

(Ivankova et al., 2006). This design was better suited for this study because it gave a general 

representation of the research problem and more qualitative data was used to give in-depth 

insights to explain the research problem. In this case, the quantitative data was used to show 

the relationship between socio-economic, psychological and institutional factors with regard to 

their influence on retirements saving behaviour among the youth in Nairobi. With the 

correlation between the variables under study, qualitative data from industry experts and 

policymakers was used to explain further how these factors influence retirement savings 

behaviour among the youth. 

3.5. Population of the Study 

The study population for this research was Kenyan youth aged between 18-35 years as 

prescribed by the Kenyan constitution, and who reside in Nairobi County working in the formal 

or informal sector. The 2019 census report placed Nairobi County at 4,397,073 with youth 

making up 2,154,266 of the population (KNBS, 2019). The focus on youth in this study of 

retirement saving behaviour in Kenya is highly significant from demographic, economic, 

developmental, and policy dimensions. Kenya’s population is estimated to be youthful with at 

least 70% of the population being under 35 (KNBS, 2019). This implies that in the future, there 

will be a significant impact on national economic stability on social welfare systems at the 

point of the youth retiring. The youth are therefore a significant demographic for this study in 

identifying how to alleviate possible old age poverty in coming years while ensuring national 

economic stability on social welfare systems. 

The research employed stratified sampling to generate the target population of the study. This 

means using the administrative boundaries of subcounty level. The table 3.1 shows the total 

population of the Nairobi sub counties. 

Table 3.1: Population of Nairobi sub counties 

Subcounty 2009 Census Population 2019 Census Population Proportion of 
Population

Dagoretti 294,222 434,208 10%

Embakasi 663,211 988,808 22%

Kasarani 525,624 780,656 18%



29 

 

Subcounty 2009 Census Population 2019 Census Population Proportion of 
Population

Njiru 283,449 626,482 14%

Westlands 247,102 308,854 7%

Kamukunji 220,659 268,276 6%

Starehe 159,709 210,423 5%

Mathare 193,416 206,564 5%

Lang'ata 178,282 197,489 4%

Makadara 160,434 189,536 4%

Kibra 212,261 185,777 4%

The total population of Nairobi County is 4,397,073 people according to the 2019 Population 

Census. Given that 49% of the population is made up of the youth between 18 -34 years, it 

implies that this research study would be targeting a population of 2,154,566 youth. It is 

important to note that there are no studies documenting the number of youths engaged in both 

formal and informal employment hence this target population. 

3.6. Sampling and Sample Size 

In determining the population sample, the sample size for this study was determined using 

(Cochran, 1977) formula as follows: 

𝑛
𝑁

1 𝑁 𝑒
 

Where: 

𝑛  Sample size 

𝑁  Target population size (2,154,566 youth in Nairobi County) 

𝑒  Margin of error 

Consequently, 

𝑛
2,154,566 

1 2,154,566 0.05
 399.8 



30 

 

Assuming a confidence level of 95% and a margin of error of 5%, the sample size was 

determined to be 400 participants. To achieve the number of respondents making up the sample 

size (400 youth), this study employed proportional allocation of the sample size to each of the 

strata (subcounty). Table 3.2 shows the number of respondents expected from each subcounty. 

Table 3.2: Calculated Sample Size 

Subcounty 2019 Census 

Population

Proportion of 

Population

Allocated Sample 

Size

Embakasi 988,808 22% 90

Kasarani 780,656 18% 71

Njiru 626,482 14% 57

Dagoretti 434,208 10% 39

Westlands 308,854 7% 28

Kamukunji 268,276 6% 24

Starehe 210,423 5% 19

Mathare 206,564 5% 19

Lang'ata 197,489 4% 18

Makadara 189,536 4% 17

Kibra 185,777 4% 17

The sampling procedure included all the 11 sub counties within Nairobi County. The sample 

included a further stratification of socioeconomic status was undertaken as follows: 

i. Higher socioeconomic status: Parts of Westlands, Langata, and portions of 

Dagoretti North. 

ii. Middle-income areas: Parts of Kasarani, Embakasi East, and Roysambu 

iii. Lower-income areas including Mathare, Kibra, parts of Embakasi West, and 

Kamukunji. 

With regard to the formal and informal sectors, the study used findings from a working paper 

by KIPPRA (Okara & Obiero, 2018) that shows: 

i. Formal sector employment: More prevalent in central business districts and 

commercial hubs like Westlands, Central Business District (in Starehe sub-county), 

and industrial areas in Embakasi.  



31 

 

ii. Informal sector employment: Widespread throughout the county but particularly 

concentrated in areas like Gikomba (Kamukunji), Githurai (between Roysambu and 

Kasarani), and various markets in Embakasi and Eastlands areas.  

iii. Self-employment: Distributed across all sub-counties but with different 

characteristics - high-end professional services in wealthier areas like Westlands 

and Kilimani, and small-scale entrepreneurship in middle and lower-income areas. 

A control group of youth who are not in gainful employment were surveyed as a part of the 

sample size to compare the factors affecting retirement saving among the youth with gainful 

employment and those without. This was important to the study to determine whether gainful 

employment does or does not influence retirement saving among the youth.  

After the socioeconomic and sectoral stratification, the study adopted simple random sampling 

to select the eligible respondents for the study from the sub counties in Nairobi. This means 

that every individual had an equal chance of being selected to participate in the study. To get 

to the actual number required per sub county, the study considered proportional allocation after 

socioeconomic stratification of the sub counties (20% came from the formal sector, 20% came 

from the informal sector, 20% came from self-employed – formal sector, 20% from the self-

employed informal sector while the remaining 20% came from those who are unemployed) as 

shown on table 3.3. The selection considered gender (targeting 50% male and 50% female 

participants) and age brackets (33.3% for each of the 3) to allow for representation of the target 

population. 

Table 3.3: Sample size per sector per subcounty 

Subcounty Allocated 

Sample 

Size 

Formal 

sector 

employment

Informal 
sector 
employment

Self-
employed 
- Formal 
sector 

Self-
employed 
-
Informal 
sector 

Unemployed

Embakasi 90 18 18 18 18 18 

Kasarani 71 14 14 14 14 14 

Njiru 57 11 11 11 11 11 

Dagoretti 39 8 8 8 8 8 

Westlands 28 6 6 6 6 6 



32 

 

Subcounty Allocated 

Sample 

Size 

Formal 

sector 

employment

Informal 
sector 
employment

Self-
employed 
- Formal 
sector 

Self-
employed 
-
Informal 
sector 

Unemployed

Kamukunji 24 5 5 5 5 5 

Starehe 19 4 4 4 4 4 

Mathare 19 4 4 4 4 4 

Lang'ata 18 4 4 4 4 4 

Makadara 17 3 3 3 3 3 

Kibra 17 3 3 3 3 3 

 

To validate and give further insights on the retirement savings behaviour among the youth in 

Kenya, the study sought to collect data from at least twelve key informants who included 

financial institutions and policymakers in pension and retirement benefits bodies in Kenya. 

This was to give further insights into the unique social, economic, and institutional contextual 

factors that influence retirement savings behaviour among the young people in Kenya. 

Purposive sampling was used to identify key informant participants based on their expertise, 

willingness and availability. The key informants included  policymakers from Retirement 

Benefits Authority (RBA)  and National Social Security Fund (NSSF); and financial providers/ 

pension administrators from Association of Kenya Insurers (AKI), Enwealth Financial 

Services, Liaison Financial Services. Further, a snowball sampling technique was adopted 

where the first group of respondents enlisted future participants from their circle of associates. 

An interview schedule was carried out by the researcher until the point of saturation (when 

additional participants to the study do not yield new insights or perspectives) was reached. 

According to Hennink & Kaiser (2022), there are no adequate sample sizes known for 

saturation. However, the researchers concluded that saturation can be achieved in a narrow 

range of interviews of between 9 to 17 participants. This study realised that after 9 interviews, 

there were no new insights or perspectives that were being added to the phenomenon under 

study and thus completed the interviews after 11 key informants.  



33 

 

3.7. Data Collection methods 

To comprehensively examine the factors influencing retirement saving behaviours among 

Kenyan youth, this study used a semi structured questionnaire as the primary data collection 

tool. The questionnaire was designed to have Likert scales and closed ended questions to collect 

quantitative data on the factors influencing retirement saving behaviours among youth in 

Nairobi County, Kenya. This approach allowed participants to express their opinions 

objectively. Moreover, the quantitative data gained allowed for statistical evaluation to identify 

any patterns and trends among the variables. Open ended questions were added to the semi 

structured questionnaire to allow participants to give their perceptions and insights regarding 

the research questions. The questionnaire was digitised and administered using tablets/ 

smartphones in order to maximise efficiency of data collection and analysis and full cross-

tabulation of information about retirement saving among the youth in Kenya. 

In addition to the survey, an unstructured interview guide was developed to gather qualitative 

insights from experts and policymakers on the factors influencing retirement saving behaviour 

among the youth. Unstructured interview guides gave flexibility to the respondents to explore 

emerging themes and further insights that would guide the study. The key informants, among 

them RBA, NSSF, Association of Kenya Insurers, Enwealth Financial Services and Liaison 

Financial Services were identified from key literature review sources and the researcher used 

purposive and snowballing techniques to identify and locate them. 

3.7.1. Data Collection Procedure 

The researcher received the required approvals from Strathmore University and NACOSTI 

before the data collection exercise. The second process of the data collection exercise involved 

the researcher having an introduction letter of the researcher and the participant informed 

consent outlining the purpose of the study for the respondents (targeted youth, financial service 

providers and policymakers in the field of pension). Given the sample size and time constraints, 

the researcher used research assistants who helped with the data collection exercise. The 

researcher identified, interviewed, selected, engaged and trained research assistants who were 

residents of or very well versed with the sub counties under study. The researcher trained the 

research assistants in the data collection methodology and administered the questionnaire 

together with them after receiving the consent to collect data from the targeted respondents 



34 

 

A pilot study was conducted before the main data collection exercise to test the validity and 

reliability of the questionnaire items. Necessary recommended corrections were made before 

rolling out the main data collection. 

For respondents who wanted to self-administer the questionnaire, they were given up to two 

weeks to fill in the questionnaire. Follow ups were made via emails and phone calls to make 

sure that the respondents completed filling the questionnaires. Throughout the data collection 

process, ethical standards were strictly adhered to. These included confidentiality and 

anonymity of respondents, strict adherence to the Data Protection Act of Kenya (2019), and 

respect of all respondents. 

Data was collected from at least 350 youth within Nairobi and 11 key informants who included, 

policy makers, pension providers/ administrators and financial providers/educators. The 

researcher collected the primary data in April 2025.   

3.8. Reliability and validity of instruments 

To guarantee the reliability and validity of data collection instruments, the use of standardised 

tools was crucial in maintaining objectivity and consistency. Ensuring high research quality 

requires employing a well-established and dependable data collection method, selecting a 

sample size that accurately represents the target population, and implementing a rigorous and 

systematic data analysis procedure. By adhering to these principles, the research produced 

credible and meaningful findings that contribute to a more accurate understanding of the 

subject matter (Mugenda & Mugenda, 1999).  

3.8.1. Reliability 

To ensure the reliability of the survey questionnaire, a pilot study was conducted with a sample 

drawn from the population under the study. The purpose of the pretest was to allow the 

assessment of the validity and gauge the consistency and stability of the questionnaire. The 

respondents involved in the pretest were separate from those who took part in the main study, 

contributing to the external validity of the research. Moreover, any ambiguities and 

inconsistencies identified by the pilot study were used to adjust the questionnaire.  

Internal consistency reliability was determined using statistical measures-Cronbach’s alpha 

coefficient. This analysis evaluated the extent to which the items in the questionnaire are 

interrelated and measure the same construct consistently. A strong relationship with a  



35 

 

Cronbach’s alpha value of more than 0.70 therefore indicated good internal consistency 

(Tavakol & Dennick, 2011). 

Table 3.4: Reliability test results 

Scale Number of 
Items 

Cronbach's 
Alpha 

Interpretation 

Financial Literacy 5 0.82 Good reliability
Risk Attitude 4 0.78 Acceptable 

reliability 
Future Orientation 4 0.81 Good reliability
Trust in Financial 
Institutions 

3 0.73 Acceptable 
reliability 

Retirement Planning 
Behaviour 

6 0.85 Good reliability 

Note: Alpha values > 0.7 indicate acceptable reliability, > 0.8 indicate good reliability 

 

Table 3.4 shows the results of the diagnostic test that was conducted. The results indicate that 

all the statements had a Cronbach’s alpha value that was greater than 0.7, indicating internal 

consistency within the questionnaire hence reliable data. 

3.8.2. Validity 

Validity refers to how well a study accurately measures the specific concept that research is 

attempting to examine. It’s a crucial concept that ensures that study findings are credible, 

accurate and that the measurement tool is relevant and is suitable for its intended purpose.  

Shadish et al., (2002, p.34) further infers that “without validity, research results can be 

misleading, leading to incorrect conclusions and potentially flawed applications.”  

Content validity by experts of the topic under study was used to examine whether this study 

comprehensively covers the concepts to be measured. Content validity according to Creswell 

& Creswell (2018) ensures that the assessment tool used in a study represents the concept under 

review. The experts panel assessed the clarity, relevance, and appropriateness of each 

questionnaire item, providing valuable insights to enhance its content and ensure alignment 

with the research objectives. Further, pilot testing was undertaken to assess performance of the 

measurement tool where feedback was analysed for suitability and  any other  issues to be 

reviewed to enhance content validity as recommended by (Tan, 2014). 



36 

 

3.9. Data analysis 

The data analysis process involved clean-up of collected data, synthesis, analysis, and 

interpretation of both qualitative and quantitative data using an appropriate statistical analysis 

program. The quantitative data that was collected was analysed using IBM’s SPSS software 

version 25 while qualitative data was analysed using thematic coding. 

3.9.1. Quantitative Data Analysis 

For quantitative data, descriptive and inferential statistical analysis was used for this study. 

Descriptive statistical analysis was employed to provide an overview of the demographic 

characteristics of the respondents and key variables. The study used frequencies and 

percentages for categorical variables (socio-economic variables, saving methods, enablers and 

barriers to retirements savings, among others); measures of central tendency and dispersion 

including mean, median, mode, variance and standard deviation for continuous variables (age 

at planned retirement, percentage of income supporting dependents, years in employment, 

number of dependents, percentage contribution to retirement savings, financial literacy score, 

risk tolerance score, etc.); cross-tabulations to examine relationships between variables and 

identify patterns that might not appear in simple frequency distributions. These cross-

tabulations may include demographic variables versus retirement saving behaviour (for 

example education level versus contribution proportion to retirement savings), psychological 

factors versus saving behaviour (“I find it difficult to sacrifice current consumption" × 

proportion currently saving for retirement) and institutional factors versus saving behaviour 

(financial education received × percentage currently saving for retirement). Statistical testing 

was employed on the cross tabulations to ensure statistical significance. For this study, the Chi-

Square test was used to determine if the observed distributions were significantly different from 

expected distributions. 

Further to descriptive statistical analysis, inferential statistical methods was applied to the 

quantitative data to explore relationships and patterns within the data. Chi-square tests were 

used to examine associations between demographic variables and retirement saving behaviour 

while correlational analysis was used to examine relationships between continuous variables. 

ANOVA and t-tests were used to compare means across different groups in the study v