Journal of Economics, Finance and Business Analytics
2023; 1(2): 11- 25
http://www.quantresearchpublishing.com
ISSN: 3006-0745 (Online)
Effectiveness of Financing Strategies for Provision of
Affordable Housing in Kenya
Daniel Mutongi Amuyunzu1*, Abdifatah Ogle 2, Beatrice Abura3, Julia Ngososei4, Justin Nderitu5,
Lydia Ngigi6, Salvatory Capis7, Hilda Mugendi8
1,2,3,4,5,6,7,8 Management, Kenya School of Government, Nairobi, Kenya
Email address:
daniel.mutongi@gmail.com (Daniel Mutongi)
*Corresponding author
Suggested citation to this article:
Amuyunzu., D.M., Ogle, A., Abura, B., Ngososei, J., Nderitu, J., Ngigi, L., Capis, S., Mugendi, Hilda (2023). Effectiveness of financing
strategies for the provision of affordable housing in Kenya. Journal of Economics, Finance and Business Analytics, 1 (2), 11 -25
Received: 12 01, 2023; Accepted: 12 15, 2023; Published: 12 21, 2023
Abstract: The provision of affordable housing in Kenya is critical given the urbanization and immigration in towns. The
study sought to assess the effectiveness of financing strategies for affordable housing units in Kenya. The independent
variables under study included; the influence of home ownership savings Plan/Mortgage, public-private partnership, direct
government financing and employer-assisted housing approach on the provision of affordable housing units in Kenya. The
targeted population were top and middle-level management of public and private institutions involved in the provision of
affordable housing including property developers, mortgage companies, National Housing Corporation, Nairobi City County
and the Ministry Department of Housing and Development in Nairobi Kenya. The total target population for the study was 100
top and middle-level management employees. The sample size was 86 with the study adopting purposive and stratified random
sampling. Questionnaires were used to obtain relevant data which was analysed using SPSS to obtain descriptive and
inferential statistical analysis. The study revealed that increased uptake of home ownership savings plans and mortgages leads
to improved provision of affordable housing units. The study also noted that increased adoption of public-private partnership
programs has led to an increase in the provision of affordable housing. The study also revealed that increased direct
government funding towards the provision of affordable housing has enhanced the same. Finally, the study noted that increased
participation of employers in the employer-assisted housing approach has improved the provision of affordable housing units.
The study recommends that the government should regulate the interest charged on mortgages to reduce the cost of funding for
affordable housing. Additionally, real estate developers should partake in public-private partnership programs to reduce the
risks involved in the provision of affordable housing units. Finally, employers should directly develop housing units that
benefit their employees.
Keywords: Homeownership Savings Plan, Public Private Partnership, Direct Government Financing, Employer Assisted
Housing, Provision of affordable housing
1. Introduction
Housing is regarded as a system made up of shelter and the supporting basic infrastructure required by man. It is a basic
human need in every society and is considered a fundamental right of every individual (Gan et al., 2017). The right to housing
is embedded in various international instruments including the United Nations Human Rights Declaration of 1948, the
International Covenant on Economic, Social and Cultural Rights of 1966 and the Istanbul Declaration and Habitat Agenda of
1996. The Universal Declaration of Human Rights gives one of the basic human rights as the right to a decent standard of
living, central to which is access to adequate housing (United Nations General Assembly (UNGA), 1948). The achievement of
the right to a decent standard of living needs the provision of affordable housing units to the global population. The
12 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
affordability of housing units is not only about the cost of buying a home; it needs to account for operation and maintenance
costs, accessibility of workplace and social infrastructure. UN-HABITAT defines affordable housing as housing which is
adequate in quality and location and does not cost so much that it prohibits its occupants from meeting other basic living costs
or threatens their enjoyment of basic human rights (Raswol, 2019). Affordable housing is housing that incorporates all essential
and fundamental costs and meets the needs of low and medium-income families (Woo, 2018).
Globally, the provision of affordable housing has been of concern. According to UN figures, only 13% of the world's cities
have affordable housing (UN-HABITAT, 2016). In 2014, McKinsey estimated that 330 million urban households were living in
substandard housing or were financially stretched by housing costs (McKinsey Global Institute, 2014). This is projected to rise
to nearly 440 million households, or 1.6 billion people, by 2025 and 2.5 billion people by 2050. In the United States, the
increasing appeal of major urban centres has brought on an unprecedented housing affordability crisis. Even more urban
households are burdened by rents or mortgage payments that take up a large fraction of their income. The share of cost-
burdened renters in the United States has risen from 23.8% in the 1960s to 47.5% in 2016. Over this period, the median home
value rose 112%, far outpacing the 50% increase in the median owner income (Fishman, 2018). Bhanot, Khaire, Kalro and Jha
(2020) argue that most productive cities in the US are smaller than they should be because of a lack of affordable housing
options. In Europe, the availability of adequate affordable housing has become a key issue, affecting the lives of millions of
European citizens. Housing costs are the single highest expenditure item for households, with about a quarter of the total
households' budget in 2015 (Poggio & Whitehead, 2017). In 2015, 11.3% of the EU population lived in households that spent
40% or more of their equalized disposable income on housing. Low-income households face higher overburden rates: in 2015,
33% of the households that had an income below 60% of the median faced housing cost overburden. While social and
affordable housing providers continue to offer rents significantly lower than the market, these providers are under increasing
pressure to respond to growing demand. The number of households on waiting lists is increasing across Europe (Czischke &
van Bortel, 2018). In the Philippines, the housing industry strongly believes that every Filipino family has the right to live with
dignity in the comfort of their own home, irrespective of their economic status. The industry in the Philippines strives to
eliminate the deficit of 3.9 million in the housing sector by the year 2030. Therefore, the country has generated and mobilized
funds for end-user financing, improved the regulatory environment for housing development and implemented a
comprehensive government housing subsidy for targeted groups. Namely, the country has vigorously pursued the low-cost,
socialized and economic housing unit (Jones & Stead, 2020). In India and China, nearly a quarter of the population lives in
informal settlements. Based on the median, cities in less developed countries are found to be 28% less affordable than cities in
more developed countries (Kallergis, et al., 2018). In Indonesia, where about 70 per cent of the total workforce is in the
informal sector i.e. noncredit-worthy enterprises (Dewita, Burke & Yen, 2020), the vast majority of low-income housing is
self-help housing, which is incremental housing based on financial ability. To address the housing need in the country, the
government embarked on multi-story low-income rental housing, unique purpose houses, quality improvement of self-help
housing and neighbourhood improvements, and the establishment of housing microfinance institutions and secondary
mortgage facility corporations (Susilawati, 2018).
The majority of developing countries still face acute affordable housing deficits. In the developing countries of Africa,
almost every country is experiencing a housing shortage that in most cases is growing. According to UN-Habitat (2011),
estimates of housing deficits for the period 2001- 2011 indicated that over 60 million new dwellings needed to be constructed
to accommodate the rapidly growing number of new urban households in Africa. The condition of housing in these countries is
also very poor, with the majority of people living in slums and informal settlements. A UN-Habitat global audit on slums in
2001 showed that 3 out of 10 inhabitants living in urban areas were slum dwellers. Among the regions of the world, Sub-
Saharan Africa has the highest slum growth rate of 4.53% per annum and also the highest proportion of slum dwellers at 61.7%
in 2010 (UN- habitat, 2016). The reasons for the inadequate supply of affordable housing and poor housing conditions in
developing countries in Sub-Saharan Africa are due to a combination of poor policies and the limited resources available to
meet the investment needs of rapid urban population growth. In Nigeria, making housing accessible and affordable to the urban
population has been a continuous struggle for the government of Nigeria, both at the Federal and State levels. The shortage of
affordable housing has created urban slums and overcrowding in the cities. The government of Nigeria has made various
efforts to increase the supply of housing in Nigeria (Oni-Jimoh, Liyanage, Oyebanji & Gerges, 2018). However, from 1962 to
1996, the achievement rate was just 17 per cent, and the shortfall was over half a million housing units. In 2001, the total
number of housing units in Nigeria was 15,221,000 (UN-Habitat, 2016) while in 2006, the total housing stock was 28,197,085
units (NPC 2010). It was estimated that by 2020, the country's housing needs would be 102,111,081 units (Onibokun, 1990).
As of 2015, the country's housing deficit was estimated at 17 million units (Saidu & Yeom, 2020). Therefore, there is a need to
produce 800,000 per annum against the current 100,000 per annum produced. In South Africa, a middle-income country in
Africa, affordable housing has been a challenge to the existence of a large housing deficit. However, there have been
significant government efforts towards addressing the same. Since 1994, the government's efforts have resulted in the building
of 2.8 mn units by 2015 (approx. 133,000 units annually). The housing deficit reduced from about 3.0 million units in 1994 to
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 13
about 2.1 million units, out of a population of 57.3 million people as of 2018 (Butcher, 2020). While the South African
Government has made significant steps in providing housing for the low-income segment, the underserved segment in South
Africa is the middle-income population who earn more than the USD 295.0 threshold for subsidies but not enough to service a
mortgage and thus a lot more needs to be done to address the shortage (Riazi & Emami, 2018). In Ghana, over the years
housing units have been independently delivered either by the government through the State Housing Corporation or the State
Construction Corporation. Emphatically, this has not contributed to the growth of the Ghanaian housing market compared to
other African peers including Nigeria and South Africa (UN-Habitat, 2016). Notwithstanding, the current housing deficit in
Ghana is estimated at 1.7 million deficits, which requires 170,000 housing units per annum over the next decade (MWRWH,
2016). This suggests that the unilateral effort from the government cannot bridge the housing gap; hence a collective effort
with private developers is vital. Although, in the last couple of years, some measures including a drafted national housing
policy have been undertaken by the Ghana government, the pace at which affordable housing projects are procured by local
housing authorities has been very slow (UN-Habitat, 2016).
In the Kenyan context, affordable housing would be units that can be afforded by individuals who earn Kshs 50,000 and
below per month, which is 74.4% of persons employed in the formal sector in Kenya. According to the National Housing
Corporation, Kenya has a cumulative housing deficit of 2 million units growing by 200,000 units per year being driven mainly
by rapid population growth of 2.6% p.a compared to the global average of 1.2%, and a high urbanization rate of 4.4% against a
global average of 2.1% (Kieti, 2020). Supply, on the other hand, has been constrained with the Ministry of Housing estimating
the total annual supply to be at 50,000 units per year. Notably, the Ministry indicates that 83.0% of the existing housing supply
is for the high-income and upper-middle-income segments, with only 15.0% for the lower-middle and 2.0% for the low-
income population. While 74.4% of Kenya's working population requires affordable housing, only 17.0% of the housing
supply goes into serving this low to lower-middle-income segment. Kenya's first medium-term goal (2009-2012) of the Vision
2030 strategy had a target of increasing housing production from 35,000 units annually to 200,000 units for all income levels.
However, the Kenyan Government delivered approximately 3,000 units only during that period, compared to a target of
800,000 houses, according to the World Bank Economic Update of 2017 (Arucy, 2019). In recent times, the government of
Kenya has stepped up efforts to bridge the deficit in affordable housing provision. Under the big four agenda, the government
plans to deliver 1 million units over the next 5 years out of which, 20.0% will be social housing while 80.0% will be affordable
housing (Gardner, et al., 2019). The Kenyan Government intends to offer affordable housing at Kshs 0.8 mn to Kshs 3.0 mn
per unit, at lower interest rates of up to 5.0% and longer mortgage tenors of up to 30 years. The affordable housing programs
will cater for individuals earning an income of between Kshs 9,700 and Kshs 36,600 per month, at 5.0% interest and a 30-year
tenor. So, the unit prices, if they can be achieved are clearly within the affordability bracket of below Kshs. 50,000 per month
income, assuming two income earners but assuming 1 income earner, the maximum house price would be Kshs. 1.8 million. If
produced, these houses would be affordable (Kimani & Karugu, 2020).
Housing is a crucial component of the economic competitiveness of a country. Well-planned housing at affordable costs,
when combined with essential services, affords dignity, security and privacy to the individual, the family and the community as
a whole (GoK, 2017). According to the Kenya Vision 2030 report, Kenya needs 200,000 housing units annually, a third of
which is required for urban dwellings (Gardner, 2019). To achieve this feat, the Government of Kenya has sought to address
affordable housing needs through various initiatives. The key interventions have included the formulation of Sessional Paper
No. 5 on the Housing Policy of 1966/67, The National Strategy of the year 2000, Sessional Paper No. 3 of June 2004 on
National Housing Policy for Kenya, a policy statement on Public Private Partnerships of 2009 and enactment of the PPP act
2013, The vision 2030 development plan and more recently, the Big four agenda with affordable housing as one of the agenda
(Kimani, 2020). Despite these interventions, Kenya's housing sector is characterized by an inadequate supply of affordable
housing. According to the National Housing Corporation, Kenya has a cumulative housing deficit of 2 million units growing
by 200,000 units per year being driven mainly by rapid population growth of 2.6% p.a and a high urbanization rate of 4.4%.
Supply, on the other hand, has been constrained with the Ministry of Housing estimating the total annual supply to be at 50,000
units per year (Gardner, 2019). Notably, the Ministry indicates that 83.0% of the existing housing supply is for the high-income
and upper-middle-income segments, with only 15.0% for the lower-middle and 2.0% for the low-income population. While
74.4% of Kenya's working population requires affordable housing, only 17.0% of the housing supply goes into serving this low
to lower-middle-income segment. The deficit in affordable housing units is largely filled by the growth in slum dwellings and
the continued self-construction of poor-quality traditional housing (Arucy, 2019). The challenges of access to affordability
housing continue to affect low-income and lower-middle-income households in Kenya (Gardner, 2019). According to KNBS
(2019) in their KNHS report the renting households spend more than 30% of their income on rent monthly. These households
are considered cost-burdened and may have difficulty affording necessities such as food, clothing, transportation and medical
care. Additionally, the supply of rental and owner-occupier housing stock for the low and lower-middle-income categories of
households is not commensurate with demand (Nthule, 2019). The private developers, driven by the commercial viability of
the projects, have focused on the upper middle- and high-income segments leaving out the lower middle- and low-income
categories (GOK - Vision 2030, 2013). The huge affordable housing deficits begs the need for better financing strategies for
14 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
the provision of adequate affordable housing units in Kenya hence the current study. Given the high demand for affordable
housing against a constricted supply of the same, there is a need for better financing strategies for the provision of adequate
affordable housing units in Kenya. The current study sought to create a solution to the financing problem for affordable
housing by assessing the effectiveness of various financing strategies for the provision of affordable housing units in Kenya.
1.1 Research Objective
The main objective of the study was to assess the effectiveness of financing strategies in the provision of affordable housing
units in Kenya. Specific Objectives included:
1. To examine the influence of home ownership savings plans and mortgages on the provision of affordable housing
units in Kenya.
2. To establish the influence of public-private partnership programs on the provision of affordable housing units in
Kenya.
3. To determine the influence of direct government financing programs on the provision of affordable housing units in
Kenya
4. To analyze the influence of the employer-assisted housing approach on the provision of affordable housing units in
Kenya.
2. Literature Review
2.1 Financing Strategies for Affordable Housing
The reasons for inadequate supply of affordable housing and poor housing conditions globally are due to a combination of
poor policies and the limited resources available. Adequate financing structures and funding are critical to addressing the
affordable housing challenge. Several financing strategies have been adopted globally and locally in Kenya including home
ownership savings plans/mortgages, Public-private partnership programs, direct government financing programs and
employer-assisted housing financing approach (Kallergis, et al., 2018).
2.1.1 Homeownership Savings Plan/Mortgage Financing
Globally, Home Ownership Savings Plans, also referred to as Contractual Savings for Housing (CSH) schemes, are defined
as a contractual agreement between a financial institution and a customer that grants the customer the right to obtain a
preferential mortgage after a minimal saving period (Fuster, Arundel & Susino, 2019). Home Ownership Savings Plans
(HOSPs) are also defined as tax-sheltered savings plans created to enable individual depositors to save for home acquisition or
development. Depending on the contractual agreement and the laws of a country, these savings can be used for land
acquisition, housing construction, home improvement, or to purchase a new home. Globally, they are characterized by
contractual deposits, tax deductions for mortgage interest payments tax exclusion for capital gains for owner-occupier
residential property, government subsidies, and direct provision of homeownership loans for low and middle-income
households (Power, 2017). A homeownership savings plan is a savings account for individuals who desire to save towards
home ownership. Home ownership savings plan established under the Income Tax Act of a country for instance Income Tax
Act (Cap470) of the laws of Kenya. The Income Tax Act cap 470 of Kenya defines a Home Ownership Savings Plan (HOSP)
as a savings plan established by an 'approved institution' and registered with the commissioner for Income Tax for receiving
and holding funds in trust for depositors. It is a tax-sheltered savings, plan whose main objective is to enable individual
depositors to save for home acquisition or development. As per Section 22C (8) of the Income Tax Act, an ‘approved
institution’ means a bank or financial institution registered under the Banking Act (Cap. 488), an insurance company licensed
under the Insurance Act (Cap. 487) or a building society registered under the Building Societies Act (Cap. 489) (Arucy, 2019).
2.1.2 Public-Private Partnership
Public Private Partnership is another critical financing strategy for the provision of affordable housing units. The Canadian
Council for Public-Private Partnerships, (2003) defines PPP as a cooperative venture between the public and private sectors,
built on the expertise of each partner, that best meets clearly defined public needs through the appropriate allocation of
resources, risks and rewards (Kavishe, Jefferson & Chileshe, 2019). When viewed as a continuum PPPs span a spectrum of
models that progressively engage the expertise or capital of the private sector (CCPPP, 2003). At one end is total public
ownership under the traditional contracting methods, while at the other end, there are arrangements that are publicly
administered but within a framework that allows for private finance, design, building, operation and possibly temporary
ownership of an asset. Sani, Sani and Ahmed (2018) on the other hand view PPP as a contractual agreement formed between a
government agency and a private sector entity that allows for greater private sector participation in the delivery of public
infrastructure projects. Public Private Partnerships (PPPs) have been used in both developed and developing countries as a
means of delivery of affordable housing. Sani, Sani and Ahmed (2018) identified the Netherlands, United Kingdom (UK) and
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 15
Ireland as the countries with the deepest PPP experience in the housing sector. By the year 2007, in the UK, affordable housing
PPPs accounted for 2.1% of the value of all PPP projects amounting to 1.269 billion pounds. It is important to note that the
successful PPP projects for affordable housing in the UK involved a measure of subsidy, Jones and Stead (2020) gave two
examples; in Plymouth Grove, a remodelled estate the government contributed 37.8 million pounds in subsidy while in
Stanhope regenerated housing estate 26.7 million pounds was contributed by government in subsidy. Other first-world
countries that have accomplished PPPs for delivering affordable housing include; the USA, Canada, and Australia (Payne,
2009).
2.1.3 Direct Government Financing
Direct government financing is government funding at national, state and local levels that uses market mechanisms to
influence the supply of affordable housing. These include direct provision of housing by the government or assistance
programs to the private sector such as tax incentives, grants or exemptions, facilitating debts and debt guarantee programs for
the construction of affordable homes. (Kimani & Karugu, 2020). The government can directly finance affordable housing
through public housing programs, rental assistance programs and homeownership assistance programs. Public housing
programs receive funding primarily through the central government and are managed and operated by public housing
authorities for the production of decent and affordable rental accommodations for families with limited incomes. The
government finances the construction of these units with tenant rent payments expected to cover operating and maintenance
costs (Gan, 2017). Rental assistance programs include both subsidized housing production and tenant assistance programs.
Supply-side rental assistance programs focus on producing and maintaining housing units that are earmarked for occupancy by
low- and moderate-income households. Whereas demand side rental assistance programs focus on directly helping low-income
renters obtain decent rental housing. Kallergis (2018) noted that homeownership assistance programs mostly through improved
access to mortgage credit; and efforts to further expand homeownership. Government programs that expand the availability of
mortgage credit and help families overcome barriers to home buying have done much more to advance homeownership among
low- and moderate-income households than programs that expand the supply of affordable housing (Riazi & Emami, 2018).
Homeownership assistance has demand-side and supply-side components. The main supply and demand categories involve the
provision of mortgage credit. Supply-side mortgage credit interventions (housing finance, regulation, and mortgage market
innovations) facilitate the flow of mortgage credit in a systemic fashion, while the demand-side approaches (tax preferences
and homeowner education and counselling) focus on reducing the individual borrower cost of mortgage credit and/or
improving the odds that an individual can obtain mortgage credit (Saidu & Yeom, 2020).
2.1.4 Employer Assisted Housing
Employer-assisted housing strategy has been accepted globally as s strategy for financing affordable housing. According to
Barry and Roux (2019), Employer Assisted Housing refers to any housing program rental or homeownership that is financed or
is in some way assisted by an employer. Employer Assisted Housing (EAH) is a flexible tool that can be tailored to work in
different community contexts and to support various equitable development goals. EAH has been used to provide extra benefits
to employees, without directly increasing wage rates. Employers working in partnership with their communities help to address
affordable housing shortage resulting in a stable workforce and healthy economy. The assistance can be modelled as financial
assistance, service provision, or facilitation assistance or the employer can provide development assistance (Collinson, Ellen
and Ludwig, 2019). According to Johnson (2020), common types of employer assistance include Down payment assistance in
the form of grants or forgivable loans to employees. Extending low or zero-rated construction financing to employees.
Donation of land for construction to employees. Helping employees obtain affordable housing through down payment and
closing cost assistance. Deferred loan to a new housing development that provides capital to a project resulting in lower
payment and reduced costs. EAH is a crucial component that has contributed towards closing the housing gap and therefore
brings down the total costs. Arucy (2019) noted that EAH programs reflect the many ways through which companies strive to
meet the housing needs of their workforce and to balance those needs against business objectives. In Kenya, EAH dates back
to the colonial era when both the government and private employers provided housing to core employees. For instance, Kenya
Railways constructed its first housing project for its employees before independence. The initial EAH projects were driven by
the need to house the employees close to the workplace (Gardner, et al., 2019).
3. Methodology
3.1 Research Paradigm and Approach
The research onion model groups research philosophies into distinct fields as follows realism, pragmatism, positivism, and
interpretivism (Melnikovas, 2018). The study used the positivist research paradigm. Positivism is mainly characterized by the
search for causalities as well as consistencies in discernable and observable reality. The approach suits this study in that the
researcher aims to assess the effectiveness of financing strategies for the provision of affordable housing units in Kenya. In
addition, this approach is suitable for exploring and understanding meanings that people ascribe to the specific human or social
16 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
phenomenon that in this case is financing strategies for the provision of affordable housing units. The most suitable study
design to be adopted was explanatory research. The design was fit for this study as it aimed to describe how effective financing
strategies for the provision of affordable housing units in Kenya are. The design facilitated the investigation of the causal
association between financing strategies and the provision of affordable housing units. Therefore, explanatory research was
suitable to explain the effectiveness of financing strategies for the provision of affordable housing.
3.2 Population and Sampling
The target population of the present study were top and middle-level management of public and private institutions involved
in the provision of affordable housing including property developers, mortgage companies, National Housing Corporation,
Nairobi City County and the Ministry Department of Housing and Development in Nairobi Kenya presented in Table 1.
Table 1: Target Population
Population Group
Target Population
Percentage
Ministry of Land Housing and Urban Development
65
20.63
PPP UNIT at Treasury
36
11.43
National Housing Corporation
47
14.92
Nairobi City County
22
6.98
Mortgage Providers/Commercial Banks
25
7.94
Property Developers (Listed and Non listed)
68
21.59
Contractors
52
16.51
Total
315
100.00
The study opted for the formulae by Kothari (2012) to determine the sample size. The formula was adopted due to its
efficiency in determining the sample size by recognizing the error of picking a sample whose attributes do not correspond to
the attributes of the population with the error being between 1% to 10%. The sample size of 86 was proportionately distributed
according to the proportion of the stratum in the population in Table 2.
Table 2: Target Population
Population Group
Target Population
Percentage
Sample Size
Ministry of Land Housing and Urban Development
65
20.63
18
PPP UNIT at Treasury
36
11.43
10
National Housing Corporation
47
14.92
13
Nairobi City Council
22
6.98
6
Mortgage/housing Savings Plans firms
25
7.94
7
Property Developers
68
21.59
19
Contractors
52
16.51
14
Total
315
100.00
86
The sampling technique to be used for the study was purposive and stratified random sampling. The researcher identified
participants likely to provide rich data concerning the topic of interest. Participants are perceived to be knowledgeable about
the effectiveness of financing strategies for the provision of affordable housing units. The decision to use top and middle-level
management in the study is informed by their knowledge about the effectiveness of financing strategies for the provision of
affordable housing units. The study also adopted stratified random sampling where the population was divided into
homogenous strata of public sector housing implementing agencies and private stakeholders as indicated in Table 2. Thereafter,
samples were drawn randomly from each sampling unit to give every member of the population an equal chance of being
selected, therefore, avoiding biases.
3.3 Data Collection
The current study utilized a survey strategy to effectively explore the phenomenon under study. A survey questionnaire was
used to obtain relevant data from the selected participants and was developed using a set of close-ended statements with
predefined answer options. Questionnaires are suitable here to better understand the attitudes, views, and perspectives of the
respondents. To encourage participants to respond to the survey, the researcher kept it relevant and made the questions specific.
Besides, the researcher informed participants about the study's purpose and the anticipated benefits. The survey questionnaires
were anonymous to further encourage participants to respond without fear of being intimidated. Besides, the participants were
asked to become part of the survey and provided with the consent form where they were required to confirm their inclusion in
the current study. All of them participated of their own will and were provided with different instructions before participating
in the research. Thus, a consent form ensured that willing respondents participated in the survey. The researcher gained access
to the respondents by initially contacting the management of the selected public and private institutions in Kenya. They were
contacted via email to introduce the research study, primary purpose, and state anticipated significance and planned
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 17
procedures. Upon approval, the researcher gained access to the employee's information, including email addresses, with the
human resource personnel's assistance. An email was generated for the selected employees, describing the research study. A
consent form was also attached along with the link for the survey questionnaire. Content validity was used to determine the
validity of the research instrument was facilitated through expert comments (Heale & Twycross, 2015). The researcher used a
measure of internal consistency to determine the reliability of the questionnaires where Cronbach alpha was generated and a
value equal to or greater than 0.7 was considered reliable.
3.4 Data Analysis
Once data has been collected, the next stage entails analysis of the collected data to make sense of it. Since the study
collected quantitative data using questionnaires, it follows that quantitative data analysis was used for data analysis to make
sense of it (Mishra et al, 2019). The researcher began by familiarizing and screening the obtained data thereafter the data was
coded and entered into a computer with the assistance of Statistical Social Package for Social Science (SPSS.24) software.
Data analysis involved both descriptive and inferential statistical analysis. The descriptive analysis included statistical tools
such as frequency, standard deviation, mean, and normality tests. Descriptive statistics entail an explanation of data using
proportions, mean, median, quartiles, and standard deviation. These tests are useful as they facilitate a better understanding of
the gathered data. Therefore, the application of descriptive statistics in the current study was appropriate as helped in
summarizing the obtained data and organising it for further analysis (Mishra et al, 2019). Besides, data was analyzed
quantitatively through Pearson correlation and multiple regression analysis presented in equation (1).
Y = β0 +β1X1+ β2X2+β3X3 +β4 X4+ɛ......................................................................................................................................... (1)
Where: Y is the dependent variable provision of affordable housing
β0= Intercept term
β1, β2, β3 and β4 are the coefficients.
X1 = Home ownership savings Plan and Mortgage
X2= Public-private partnership programs
X3= Direct government financing programs
X4= Employer-assisted housing approach
ɛ = Error term
3.5 Ethical Considerations
All studies that use humans as their subjects should adhere to the established ethical standards to achieve the reliability and
validity of the findings (Park &, 2016). The researcher observed key ethical considerations since the study involved human
participants. Different appropriate measures were taken to fulfil the ethical requirements for the current research study. First,
the researcher upheld the principle of informed consent where all the respondents were informed about the study's purpose and
how their data was to be used. Additionally, the informed consent form highlighted that their participation was voluntary and
that they could withdraw from the process at will without any consequences. To protect the anonymity of the participants,
pseudonyms were used to represent each participant rather than their actual names to ensure that they were not easily identified
(Park & Park, 2016). Next, the researcher ensured confidentiality and data security. The questionnaire did not ask for personal
information, apart from demographic data. As such, identifiable details about participants were not included in the final report.
Moreover, the researcher stored all raw data in a password-protected folder on the personal computer. Only the researchers had
full access to the data. The filled questionnaires were stored for at least three years.
4. Results
4.1 Background Information
The researcher emailed 83 questionnaires to the respondents of which 71 were returned while adequately filled for analysis.
This gave a response rate of 82% and was therefore adequate for analysis as given by Mugenda and Mugenda (2009) who held
that a response rate of 70% and above is adequate for survey study. The study also examined the reliability of the
questionnaires used in the study. The researcher used a measure of internal consistency to determine the reliability of the
questionnaires where Cronbach alpha was generated and a value equal to or greater than 0.7 was considered reliable. The
research revealed that all the variables had a reliability greater than 0.7 implying that the questionnaires were reliable for data
collection. The research also sought to collect data on demographic variables including Employers of respondents, years of
experience and gender. Regarding the employer of the respondents, the respondents were distributed across different employers
as presented in Table 3. Gender showed that 52 (73.23%) of the respondents were males with the remaining 19(26.76%) being
18 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
females. Finally, regarding the experience level of the respondents, 48 (67.6%) of the respondents had an experience level of
11 years and above. The remaining respondents had an experience level of 10 years and below.
Table 1: Demographic Characteristics
Variable
Category
No
Percentage
Employer
Ministry of Land Housing and Urban Development
16
22.53
PPP UNIT at Treasury
8
11.26
National Housing Corporation
12
16.90
Nairobi City County
4
5.63
Mortgage Providers/Commercial Banks
5
7.04
Property Developers (Listed and Non-listed)
14
19.71
Contractors
12
16.90
Total
71
100.00
Gender
Male
52
73.23
Female
19
26.76
Total
71
100.00
Experience
less than 5 years
8
11.27
5-10 years
15
21.13
11-15 years
38
53.52
Over 15 years
10
14.08
Total
71
100.00
4.2 Descriptive Analysis of Study Variables
The study also sought to present a descriptive analysis of the study variables. The study variables examined included home
ownership savings Plan/Mortgage, public-private partnership programs, direct government financing programs, Employer-
assisted housing approach and Provision of Affordable Housing. The study relied on descriptive statistics measures such as
mean and standard deviation.
Table 2: Home Ownership Savings Plan and Mortgage
Statements on Home Ownership Savings Plan and Mortgage
Mean
Std. Deviation
A mortgage or home ownership savings plan is a useful financing strategy for home ownership in Kenya
4.35
.678
Mortgages are priced fairly in the market.
4.34
.608
Mortgage providers regularly sensitize people to their products.
4.32
.604
Mortgage Repayment Periods are well structured.
4.17
.507
A mortgage or home ownership savings plan is a useful financing strategy for home ownership in Kenya
4.07
.543
Every working class can afford a mortgage.
3.90
.419
Overall Mean Score
4.19
0.55
Table 4 presents the data analysis regarding responses to statements on home ownership savings plans and mortgages. The
responses to the statements have been ordered from the most supported to the least supported statement based on the mean
score per statement. The most supported statement was that a mortgage or home ownership savings plan is a useful financing
strategy for home ownership in Kenya with a mean score and standard deviation tending to the strong agreement (M= 4.35 and
SD= .678) implying that a home saving plan and mortgages are useful financing strategy for the provision of affordable
housing. The least supported statement was that every working class could afford a mortgage as depicted by mean score and
standard deviation of (M= 3.90 and SD= .419) implying that not every working class can afford mortgages. The overall mean
score was M= 4.19 implying that generally home ownership savings plan and mortgages was a useful strategy for the provision
of affordable housing.
Table 3: Public-Private Partnership Program
Statements on Public Private Partnership Program
Mean
Std. Deviation
Public Private Partnerships distributes the risks associated with affordable housing provision
4.54
.651
The cost of capital in the PPP finance structure motivates the private party to deliver on time.
4.45
.693
The Government has sensitized its people on PPP
4.38
.799
There are enough PPPs involved In the Housing Sector
4.17
.507
The PPP Model Provides Affordable Housing Development Capital
4.13
.419
Injection and Recovery of PPP Capital is well regulated in Kenya
4.01
.423
Overall Mean score
4.28
.582
Table 5 presents the findings regarding responses on the statements about public private partnership strategy for financing
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 19
affordable housing in Kenya. The responses to the statements have been ordered from the most supported to the least supported
based on mean score. The most supported statement was that Public Private Partnerships distribute the risks associated with
affordable housing provision as depicted by the mean response score (M= 4.54) tending to strong agreement and narrow
standard deviation (SD=.651). The finding means that the PPP financing strategy for affordable housing helps in distributing
risks associated with the provision of affordable housing in Kenya. The least supported statement was that injection and
recovery of PPP Capital is well regulated in Kenya as depicted by the mean score (M= 4.01) of agreement and standard
deviation of (SD= .423). The response implies that although the PPP is well-regulated, there are avenues for improvement. The
overall mean score was (M=4.28) that is agreement implying that the private Partnership financing strategy for affordable
housing was critical in Kenya.
Table 4: Direct Government Financing Programs
Statement on Direct Government Financing Programs
Mean
Std. Deviation
Direct Government provision of affordable housing is not sustainable
4.37
.660
The government has put in place proper legislation to govern the housing sector.
4.35
.612
Government officers in critical installations are provided with Government Houses.
4.31
.646
Government financing is increasing with the increasing demand for affordable housing
4.27
.608
The government allocates enough funds in its budget for the construction of affordable housing for the citizens.
3.96
.429
Overall Mean Score
4.252
.591
Table 6 presents the responses to the statement regarding direct government financing programs. The responses have been
ordered from the most supported to the least supported based on mean response score. The most supported statement was that
direct government provision of affordable housing is not sustainable as depicted by the mean response score (M=4.37) tending
to strong agreement and narrow standard deviation of SD= .660. The response implies that the government should not be
directly involved in the provision of affordable housing in Kenya but rather should do it through other avenues. The least
supported statement was that the government allocates enough funds in its budget for the construction of affordable housing for
the citizens as shown by a mean response score of (M= 3.96) and narrow standard deviation of .429. The response means that
government financing for affordable housing projects is not adequate. The overall mean score was 4.252 implying that direct
government as another financing strategy for affordable housing in Kenya was relatively dominant in Kenya.
Table 5: Employer-Assisted Housing Approach
Statement on Employer-Assisted Housing Approach
Mean
Std. Deviation
Employers assisted housing approach is sustainable means
4.28
.659
Most Employers have helped set up Housing Investment corporations for staff.
4.27
.774
Many Employers have an internal Housing Scheme that provides House Development loans for staff.
4.21
.827
Government Employees are Paid an occupier allowance if they stay in their own Houses.
4.20
.749
Many employers have partnered with banks and set up affordable housing Products for staff.
4.20
.668
Overall Mean Score
4.23
.735
Table 7 presents the findings on the variable employer-assisted housing approach in financing affordable housing in Kenya.
The responses to the statements about the employer-assisted housing approach have been arranged from the most supported to
the least supported based on mean score. The most supported statement was that the employer's assisted housing approach is a
sustainable means for financing affordable housing in Kenya as depicted by the mean score (M= 4.28) of agreement and
narrow standard deviation (SD = .659). The least supported statement was that many employers have partnered with banks and
set up affordable housing products for staff as depicted by mean response score and standard deviation (M= 4.20 and
SD=.668). Additionally, the overall mean score was (M= 4.23) meaning that in general, employer-assisted housing programs
for financing affordable housing in Kenya were effective.
Table 6: Provision of Affordable Housing
Statements on Provision of Affordable Housing
Mean
Std. Deviation
The number of affordable housing units developed in Kenya has been increasing every year
4.38
.704
Government Regulation of the Mortgage and Housing Finance Sector has improved the construction of more Housing
Units.
4.37
.541
Legislation of the PPP Models has led to an increase in investors venturing into the Affordable Housing Sector.
4.31
.575
The inclusion of Housing into the Government's Big Four agenda has unlocked substantial funding from the Exchequer.
4.23
.721
Employers who have established Internal Housing Schemes experience less Employee Turnover.
3.99
.463
The use of PPP has enabled the timely delivery of affordable housing
3.87
.455
The housing units developed in Kenya are accessible to those who need them.
3.58
.654
Overall Mean Score
4.10
.587
20 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
Table 8 depicts the responses to the statements regarding the variable provision of affordable housing. The responses were
ordered from the most supported to the least supported based on mean score. The most supported statement was that the
number of affordable housing units developed in Kenya has been increasing every year as depicted by the mean response score
(M=4.38) tending to a strong agreement and standard deviation (SD= .704) around the mean. The least supported statement
was that the housing units developed in Kenya are accessible to those who need them as depicted by the mean response score
(M=3.58) and standard deviation (SD= .654) around the mean. The finding implies that affordable housing units developed are
not always made accessible to those who need them for renting or ownership. The overall mean score was (M= 4.10) which
was tending to agreement implying that the respondents were generally in agreement that affordable housing in Kenya was on
the right course.
4.3 Correlation Analysis
The research also examined the association between financing strategies for affordable housing (home ownership savings
Plan/Mortgage, Public-private partnership programs, direct government financing programs and employer-assisted housing
approach) and provision of affordable housing in Kenya. Pearson correlation coefficient was adopted at a 5% level of
significance. The value of the Pearson correlation coefficient is usually between 0 and 1 where 0 implies no correlation and 1
implies perfect correlation. Correlation between 0.1- 0.3 is a weak correlation, 0.4- 0.6 is a moderate correlation, 0.7- 0.9 is a
strong correlation. The value of the Pearson correlation coefficient can be positive or negative where a positive correlation
implies a direct relationship and a negative correlation is an inverse relationship. The findings are presented in Table 9.
Table 7: Bivariate Pearson Correlation Coefficient
X1
X2
X3
X4
Y
X1
Pearson Correlation
1
.474**
.305**
.608**
.708**
Sig. (1-tailed)
.000
.005
.000
.000
N
71
71
71
71
71
X2
Pearson Correlation
.474**
1
.231*
.710**
.780**
Sig. (1-tailed)
.000
.026
.000
.000
N
71
71
71
71
71
X3
Pearson Correlation
.305**
.231*
1
.141
.116
Sig. (1-tailed)
.005
.026
.121
.168
N
71
71
71
71
71
X4
Pearson Correlation
.608**
.710**
.141
1
.687**
Sig. (1-tailed)
.000
.000
.121
.000
N
71
71
71
71
71
Y
Pearson Correlation
.708**
.780**
.116
.687**
1
Sig. (1-tailed)
.000
.000
.168
.000
N
71
71
71
71
71
**. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed).
X1= home ownership savings Plan/Mortgage, X2= Public-private partnership programs, X3= direct government financing programs, X4= employer-assisted housing
approach and Y = is provision of affordable housing
Table 9 presents the bivariate Pearson correlation between financing strategies for affordable housing (home ownership
savings Plan and Mortgage, Public-private partnership programs, direct government financing programs and employer-assisted
housing approach) and provision of affordable housing in Kenya. The correlation between homeownership savings Plan and
Mortgage and provision of affordable housing was positive, strong, and statistically significant (r= .708, p-value .000). The
positive correlation between home ownership savings plan, mortgage, and provision of affordable housing implies that an
improvement in the uptake of home ownership savings Plan and Mortgage is accompanied by improved provision of
affordable housing units in Kenya. When, Kenyans wishing to own homes can get access to ownership savings plans and
mortgages, and then their ability to acquire affordable housing units is improved greatly. The correlation between Public-
private partnership programs and the provision of affordable housing was positive, strong, and statistically significant (r = .780,
p-value = .000). The positive correlation between public-private partnership programs and the provision of affordable housing
implies that increased adoption of public-private partnership programs by the government and real estate developers is
accompanied by the improved provision of affordable housing units. Public-private partnerships are associated with improved
efficiencies hence more of those contracts can only mean increasing the number of development of affordable housing units.
The relationship between direct government financing programs and the provision of affordable housing was positive, weak,
and not statistically significant (r = .116, p-value= .168). The positive correlation between direct government financing
programs and the provision of affordable housing implies that increased government funding directed at affordable housing
leads to improved provision of such housing. However, the correlation implies that direct government financing of affordable
housing units is associated with inefficiencies that are common with government-led projects. Finally, the correlation between
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 21
the employer-assisted housing approach and the provision of affordable housing was positive, strong, and not statistically
significant (r = .687 and p-value = .000). The direct relationship between the employer-assisted housing approach and the
provision of affordable housing implies that employers have a role to play in the provision of affordable housing to their
employees. Improved uptake of this initiative by employers can only mean improving access to affordable housing for the
employees on ownership or rental terms.
4.4 Regression Analysis
The study further examined the effectiveness of financing strategies for the provision of affordable housing units in Kenya.
The research adopted multivariate regression analysis with financing strategies as the independent variable and the provision of
affordable housing as the dependent variable. The study findings are presented in Tables 10, 11 and 12.
Table 8: Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.884a
.781
.768
.23525
a. Predictors: (Constant) are X1= home ownership savings Plan/Mortgage, X2= Public-private partnership programs, X3= direct government financing programs, X4=
employer-assisted housing approach
Table 10 presents the model summary where the value (R= .884) is the overall correlation between financing strategies
(home ownership savings Plan/Mortgage, Public-private partnership programs, direct government financing programs,
employer-assisted housing approach) and provision of affordable housing in Kenya. The coefficient of determination (R2
= .781) shows that financing strategies including home ownership savings Plan/Mortgage, Public-private partnership programs,
direct government financing programs and employer-assisted housing approach explain 78.1% of the variation in privation of
affordable housing in Kenya. The remaining variation of 21.9% of the provision of affordable housing is explained by other
unobserved variables that were not part of the current study. The findings imply that the financing strategies of concern to the
researcher including home ownership savings plan and mortgage, public-private partnership programs, direct government
financing programs and employer-assisted housing approach contribute greatly to the provision of affordable housing in
Kenya.
Table 9: Analysis of Variances
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
13.009
4
3.252
58.769
.000b
Residual
3.653
66
.055
Total
16.662
70
a. Dependent Variable: y= Provision of Affordable Housing
b. Predictors: (Constant), X1= home ownership savings Plan/Mortgage, X2= Public-private partnership programs, X3= direct government financing programs, X4=
employer-assisted housing approach
Table 11 presents the Analysis of Variances (ANOVA). The table shows that financing strategies including home ownership
savings Plan/Mortgage, Public-private partnership programs, direct government financing programs and employer-assisted
housing approach have a significant influence on the provision of affordable housing in Kenya (F = 58.769 and P-Value
= .000< .05). The study finding implies that the financing strategies of concern to the researcher including home ownership
savings Plan and Mortgage, Public-private partnership programs, direct government financing programs and employer-assisted
housing approach have a major contribution to the provision of affordable housing in Kenya. The study therefore concludes
that the financing strategies examined in the current were effective in the provision of affordable housing units in Kenya.
Table 10: Regression Coefficients
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
.394
.435
.905
.369
X1
.602
.095
.479
6.332
.000
X2
.218
.081
-.167
2.710
.009
X3
.002
.121
-.002
.020
.984
X4
.702
.099
.593
7.115
.000
a. Dependent Variable: Y = Provision of Affordable Housing
b. X1= home ownership savings Plan/Mortgage, X2= Public-private partnership programs, X3= direct government financing programs, X4= employer-assisted housing
approach
22 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
Table 12 shows the regression coefficients for the causal effect relationship between homeownership savings Plan/Mortgage,
Public-private partnership programs, direct government financing programs, employer-assisted housing approach and
provision of affordable housing in Kenya. The influence of home ownership savings Plan and Mortgage on the provision of
affordable housing was positive and statistically significant (β1= .602, t = 6.332 and p-value = .000). The positive influence of
home ownership savings Plan/Mortgage on the provision of affordable housing implies that the increased uptake of home
ownership savings plans and Mortgages by one unit has enhanced the provision of affordable housing in Kenya by .602 units.
When citizens contribute towards affordable housing schemes, they can easily get ownership of affordable houses in Kenya.
They can also access mortgages for the construction of affordable housing units. The influence of Public-private partnership
programs on the provision of affordable housing was positive and statistically significant (β2= .218, t = 2.710 and p-value
= .009). The positive effect of public-private partnership programs on the provision of affordable housing signifies that
improving public-private partnership by one unit leads to improved provision of affordable housing units by .218 units. The
finding further implies that increased use of PPP has enhanced the provision of units by spreading the risks associated with
public projects as well as faster development of affordable houses. The influence of direct government financing programs on
the provision of affordable housing was positive but not statistically significant (β3= .002, t = .020 and p-value = .984). The
positive influence of direct government financing programs on the provision of affordable housing implies that increasing
direct government funding by one unit leads to enhanced provision of housing units by .002 units. The increased funding from
by government through the Ministry of Housing and Development has led to increased development of affordable housing for
the citizenry in Kenya. The effect however was not significant implying that financing of affordable housing units through
direct government funding is not sustainable and is riddled with inefficacies. Finally, the influence of the employer-assisted
housing approach on the provision of affordable housing was positive and statistically significant (β4= .702, t = 7.115 and p-
value = .00). The direct influence of employer-assisted housing approach on the provision of affordable housing implies that
improving employer-assisted housing approach adoption by one unit has enhanced provision of affordable housing in Kenya
by .687 units. Further, the study finding implies that when employers embrace the employer-assisted housing approach, they
make it easy for their employees to get access to affordable housing units on rent or ownership. The model was thus estimated
as
Y = .394 + .602X1+ .218 X2+.002 X3+.702X4..........................................................................................................................(ii)
Where: Y is the dependent variable provision of affordable housing, X1 = home ownership savings Plan/Mortgage, X2=
Public-private partnership programs, X3= direct government financing program and X4= employer-assisted housing approach.
5. Discussion
The study sought to examine the influence of home ownership savings Plans and Mortgages on the provision of affordable
housing units in Kenya. The correlation analysis revealed that the correlation between homeownership savings plan and
Mortgage and provision of affordable housing was positive and statistically significant (r= .708, p-value .000). The regression
analysis revealed that the influence of home ownership savings plan and mortgage on the provision of affordable housing was
positive and statistically significant (β1= .602, t = 6.332 and p-value = .000). The result of the study agrees with Kohl (2018)
who showed that homeownership savings plans are associated with higher homeownership rates, more encouraging mortgage
regimes and a bigger housing acquisition. The study sought to establish the influence of Public-private partnership programs
on the provision of affordable housing units in Kenya. The correlation analysis showed that the correlation between Public-
private partnership programs and the provision of affordable housing was positive and statistically significant (r = .780, p-value
= .000). Regression analysis also revealed that the influence of Public-private partnership programs on the provision of
affordable housing was positive and statistically significant (β2= .218, t = 2.710 and p-value = .009). The findings are in
congruence with a study by Ojwang (2015) who found that the risk allocation, private capital, delivery time and cost savings in
a Public Private Partnerships model of procurement influence the provision of affordable housing in Nairobi County, especially
for the lower and middle-income groups. The study also sought to determine the influence of direct government financing
programs on the provision of affordable housing units in Kenya. The correlation analysis revealed that the relationship between
direct government financing programs and the provision of affordable housing was positive, weak and not statistically
significant (r = .116, p-value= .168). The regression analysis showed that the influence of direct government financing
programs on the provision of affordable housing was positive but not statistically significant (β3= .002, t = .020 and p-value
= .984). The government finances the construction of these units with tenant rent payments expected to cover operating and
maintenance costs (Gan, 2017). Rental assistance programs include both subsidized housing production and tenant assistance
programs. Finally, the study sought to analyze the influence of the employer-assisted housing approach on the provision of
affordable housing units in Kenya. The correlation analysis revealed that the correlation between the employer-assisted
housing approach and the provision of affordable housing was positive and statistically significant (r = .687 and p-value
= .000). Regression analysis results showed that the influence of the employer-assisted housing approach on the provision of
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 23
affordable housing was positive and statistically significant (β4= .702, t = 7.115 and p-value = .00). The findings are in
agreement with Muturi (2013) who established that employer-assisted housing projects have enhanced provision of affordable
housing units to employees in the civil service.
6. Conclusions
The first objective sought to examine the influence of home ownership savings Plans/Mortgages on the provision of
affordable housing units in Kenya. The study revealed that the influence of home ownership savings Plan/Mortgage on the
provision of affordable housing was positive and statistically significant. The study therefore concluded that the uptake of a
home ownership savings Plan/Mortgage enhances the provision of affordable housing units in Kenya. When citizens contribute
towards affordable housing schemes, they can easily get ownership of affordable houses in Kenya. They can also access
mortgages for the construction of affordable housing units. The second objective sought to establish the influence of Public-
private partnership programs on the provision of affordable. The influence of Public-private partnership programs on the
provision of affordable housing was positive and statistically significant. The study thus concluded that the positive effect of
public-private partnership programs on the provision of affordable housing signifies that improving public-private partnerships
leads to improved provision of affordable housing units. The finding further implies that increased use of PPP has enhanced
the provision of units by spreading the risks associated with public projects as well as faster development of affordable houses.
The third objective sought to determine the influence of direct government financing programs on the provision of affordable
housing units in Kenya. The study showed that the influence of direct government financing programs on the provision of
affordable housing was positive but not statistically significant. The research thus concluded increasing direct government
financing programs leads to improved provision of affordable housing units. The increased funding from by government
through the Ministry of Housing and Development has led to increased development of affordable housing to the citizenry in
Kenya. The effect however was not significant implying that financing of affordable housing units through direct government
funding is not sustainable and is riddled with inefficacies. The fourth objective sought to analyze the influence of the
employer-assisted housing approach on the provision of affordable housing units in Kenya. The study showed that the
influence of the employer-assisted housing approach on the provision of affordable housing was positive and statistically
significant. The study therefore concluded that improving the employer-assisted housing approach results in improved
provision of affordable housing units. Further, the study finding implies that when employers embrace the employer-assisted
housing approach, they make it easy for their employees to get access to affordable housing units on rent or ownership. Given
the positive influence of home ownership savings plans and mortgages on the provision of affordable housing units, the study
recommends that the availability of homeownership savings Plans/Mortgages should be improved by real estate firms. The
government of Kenya should regulate the interest charged on mortgages to encourage the availability of low-cost funding for
the benefit of developers and real estate firms. The influence of Public-private partnership programs on the provision of
affordable housing was positive and statistically significant. Based on the findings, the study suggests to the government to
continue funding the provision of affordable housing units to the citizenry through the Public Private Partnership programs.
The study also recommends that the private sector including real estate developers should aggressively partake in public-
private partnership programs to reduce the risks involved in the provision of affordable housing units. The influence of direct
government financing programs on the provision of affordable housing was positive but not statistically significant. Based on
the findings, the study suggests that the government should reduce their direct funding to the provision of affordable housing
units given the inefficiencies associated with direct government involvement. However, the government can improve funding
through other means like public-private partnerships. The study finally revealed that the influence of the employer-assisted
housing approach on the provision of affordable housing was positive and statistically significant. The study thus recommends
that employers should actively participate in the provision of affordable housing units by directly developing housing units that
benefit their employees. Additionally, they can guarantee their employees mortgage facilities for the development of housing
units. The current study was an assessment of the effectiveness of financing strategies for affordable housing units in Kenya.
The study was thus limited to four financing strategies for the provision of affordable housing units. Future studies should
therefore examine other financing strategies that were not part of this study for instance the real estate traded funds through the
capital market.
Conflicts of Interest
“The authors declare no conflicts of interest.”
References
24 Amuyunzu et al.: Effectiveness of financing strategies for the provision of affordable housing in Kenya
[1] Arucy, K. (2019). Affordable Housing Policy in Kenya: The Big Four Transformation Agenda 2017–2022. Management and Economic
Journal, 593-596.
[2] Barry, M., & Roux, L. (2019). Hybrid governance and land purchase strategies in a state-subsidized housing project in a rural South
African town. Survey review, 51(369), 492-501. https://doi.org/10.1080/00396265.2018.1482674
[3] Butcher, S. (2020). Appropriating rent from Greenfield affordable housing: developer practices in Johannesburg. Environment and
Planning A: Economy and Space, 52(2), 337-361. https://doi.org/10.1177/0308518X19895278
[4] Bhanot, D., Khaire, M., Kalro, A., & Jha, S. K. (2020). Affordable housing finance companies in India: how do they ‘differently ‘serve
the underserved? Housing Studies, 35(3), 537-566. https://doi.org/10.1080/02673037.2019.1614538
[5] CAHF (2016). Understanding Kenya’s Housing Finance Market, Housing Finance in Africa Yearbook 2015, 4(January).
[6] Collinson, R., Ellen, I. G., & Ludwig, J. (2019). Reforming housing assistance. The ANNALS of the American Academy of Political
and Social Science, 686(1), 250-285. https://doi.org/10.1177/0002716219877801
[7] Czischke, D., & van Bortel, G. (2018). An exploration of concepts and policies on 'affordable housing ' in England, Italy, Poland and
The Netherlands. Journal of Housing and the Built Environment, 1-21. https://doi.org/10.1007/s10901-018-9598-1
[8] Dewita, Y., Burke, M., & Yen, B. T. (2020). The relationship between transport, housing and urban form: Affordability of transport and
housing in Indonesia. Case Studies on Transport Policy, 8(1), 252-262. https://doi.org/10.1016/j.cstp.2019.01.004
[9] Fishman, R. (2018). The Global Crisis of Affordable Housing: Architecture Versus Neoliberalism. Architectural Design, 88(4), 22-29.
https://doi.org/10.1002/ad.2317
[10] Fuster, N., Arundel, R., & Susino, J. (2019). From a culture of homeownership to generation rent: housing discourses of young adults
in Spain. Journal of Youth Studies, 22(5), 585-603. https://doi.org/10.1080/13676261.2018.1523540
[11] Gan, X., Zuo, J., Wu, P., Wang, J., Chang, R., & Wen, T. (2017). How affordable housing become more sustainable? A stakeholder
study. Journal of Cleaner Production, 162, 427-437. https://doi.org/10.1016/j.jclepro.2017.06.048
[12] Gardner, D. A. V. I. D., Lockwood, K. E. I. T. H., Pienaar, J. A. C. U. S., & Maina, M. I. R. I. A. M. (2019). Assessing Kenya’s
affordable housing market. Centre for Affordable Housing Finance in Africa (CAHF), available at http://bit. ly/31WXBtY.
[13] Jones, A., & Stead, L. (2020). Can people on low incomes access affordable housing loans in urban Africa and Asia? Examples of
innovative housing finance models from Reall’s global network. Environment and Urbanization, 32(1), 155-174.
https://doi.org/10.1177/0956247819899557
[14] Johnson, R. W. (2020). Financial Challenges at Older Ages and the Implications for Housing Options. Generations, 2020.
[15] Kallergis, A., Angel, S., Liu, Y., Blei, A., Sanchez, N., & Lamson-Hall, P. (2018). Housing affordability from a global perspective.
Lincoln Institute of Land Policy.
[16] Kavishe, N., Jefferson, I., & Chileshe, N. (2019). Evaluating issues and outcomes associated with public–private partnership housing
project delivery: Tanzanian practitioners’ preliminary observations. International journal of construction management, 19(4), 354-369.
[17] Kenya National Bureau of Statistics (2015). Basic Report on Well-Being in Kenya. https://doi.org/10.1080/15623599.2018.1435154
[18] Kieti, R. M. (2020). Affordable Housing in Kenya. Africa habitat review, 14(1), 1677-1687.
[19] Kimani, S. K., & Karugu, J. (2020). Strategic Approaches and Delivery of Affordable Housing in Nairobi City County, Kenya.
International Journal of Business Management, Entrepreneurship and Innovation, 2(1), 17-35.
[20] Kohl, S. (2018). The political economy of homeownership: a comparative analysis of homeownership ideology through party
manifestos. Socio-Economic Review. 0 (0,1–26 https://doi.org/10.1093/ser/mwy030
[21] McKinsey Center for Business and Environment and C40 Cities, (2017). Focused Acceleration: A Strategic Approach to Climate
Action in Cities to 2030. Retrieved from https://www.mckinsey.com/~/media/McKinsey/ Business%20Functions/Sustainability%20
[22] Muturi, M.(2013). Employer-assisted housing addressing accessibility and affordability for civil servants in Kenya. (Unpublished
Masters Thesis, UoN).
[23] Ojwang', P. (2015). The influence of public-private partnerships finance on the provision of affordable housing: the case of Nairobi
County, Kenya. (Unpublished Master’s Thesis, UON)
[24] Oni-Jimoh, T., Liyanage, C., Oyebanji, A., & Gerges, M. (2018). Urbanization and meeting the need for affordable housing in Nigeria.
Housing, Amjad Almusaed and Asaad Almssad, IntechOpen, 7(3 S1), 73-91.
[25] Poggio, T., & Whitehead, C. (2017). Social housing in Europe: legacies, new trends and the crisis. Critical Housing Analysis, 4(1), 1-
10.
[26] Power, E. R. (2017). Housing, home ownership and the governance of ageing. The Geographical Journal, 183(3), 233-246.
https://doi.org/10.1111/geoj.12213
[27] Raswol, L. M. (2019). Neighborhood Sustainability Evaluation Based on UN-Habitat… Principles: Case Study Masike and Avro City
in Duhok. Al-Rafidain Engineering Journal (AREJ), 24(1), 26-34.
[28] Riazi, M., & Emami, A. (2018). Residential satisfaction in affordable housing: A mixed method study. Cities, 82, 1-9.
https://doi.org/10.1016/j.cities.2018.04.013
[29] Saidu, A. I., & Yeom, C. (2020). Success criteria evaluation for a sustainable and affordable housing model: a case for improving
household welfare in Nigeria Cities. Sustainability, 12(2), 656. http://dx.doi.org/10.3390/su12020656
[30] Sani, M., Sani, A., & Ahmed, U. S. (2018). Exploring factors affecting implementation of public-private partnership housing projects in
Bauchi State, Nigeria. Traektoriâ Nauki= Path of Science, 4(3).
[31] Susilawati, C. (2018). Housing policy and social development in Indonesia. Housing policy, well-being and social development in Asia
(Routledge Studies in International Real Estate), 226-249.
[32] UN General Assembly. (1948). Universal Declaration of Human Rights, 10 December 1948, 217 A (III), available at:
http://www.refworld.org/docid/3ae6b3712c.html, article 25 (1)
[33] UN-HABITAT (2011). Public-private partnerships in housing and urban development. UN-HABITAT, Nairobi, pp 6, 8
[34] UN-HABITAT, 2016. Only 13% of the World's Cities Have Affordable Housing – According to New Research. [Online] Available at:
https://unhabitat.org/only-13-of-worlds-citieshave-affordable-housing-according-to-new-research/
[35] Woo, K. H. (2018). Affordable Housing Policy in Penang State of Malaysia. Global Encyclopedia of Public Administration, Public
Policy, and Governance, 1-5. https://doi.org/10.1007/978-3-319-31816-5_3671-1
Journal of Economics, Finance and Business Analytics 2023; 1(2): 11-25 25
[36] Heale, R., & Twycross, A. (2015). Validity and reliability in quantitative studies. Evidence-based nursing, 18(3), 66-67.
https://doi.org/10.1136/eb-2015-102129
[37] Melnikovas, A., 2018. Towards an explicit research methodology: Adapting research onion model for future studies. Journal of Futures
Studies, 23(2), pp.29-44. 10.6531/JFS.201812_23(2).0003
[38] Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical
data. Annals of cardiac anaesthesia, 22(1), 67.
[39] Park, J., & Park, M. (2016). Qualitative versus quantitative research methods: Discovery or justification? Journal of Marketing
Thought, 3(1), 1-8.
[40] Rutberg, S., & Bouikidis, C. D. (2018). Focusing on the fundamentals: A simplistic differentiation between qualitative and quantitative
research. Nephrology Nursing Journal, 45(2), 209-213.
[41] Suresh, K. P., & Chandrashekara, S. (2012). Sample size estimation and power analysis for clinical research studies. Journal of Human
Reproductive Sciences, 5(1), 7.
[42] Taherdoost, H. (2016). Sampling methods in research methodology; how to choose a sampling technique for research. How to Choose
a Sampling Technique for Research (April 10, 2016).
