THE EFFECT OF FINANCING SOURCES ON REAL ESTATE

DEVELOPMENT IN KENYA

JOSEPH KAMAU MWATHI

A RESEARCH PROJECT SUBMITTED IN PARTIAL

FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE IN FINANCE OF THE UNIVERSITY OF

NAIROBI

2013

ii

DECLARATION

This research project is my original work and has not been presented for examination in

any other University.

Signature: ________________________ Date: _______________________

Joseph Kamau Mwathi

Reg No: D63/72514/2012

This research project has been forwarded for examination with my approval as the

University supervisor.

Signature: ________________________ Date: _______________________

Mr.James M Karanja

School of Business, University of Nairobi.

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ACKNOWLEDGEMENTS

I wish to thank The Almighty God for giving me a gift of life to write this work. I wish

to express my gratitude to my supervisor Mr. James M Karanja forhis professional

guidance in research methodology and motivation that enabled me to compile this

project. I also extend gratitude to my classmates whose presence offered me the

psychological motivation and need to learn.

Finally, I thank my family for supporting me throughout my studies.I can’t express my

gratitude in words for my family, whose unconditional love has been my greatest

strength.

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DEDICATION

I dedicate this project to my wife Florence Wanjiru, children Jackie, Gideon and Esther

,friends and colleagues at my work place,the school of business and administration at

the University of Nairobi for being a strong pillar stone throughout my Msc

Financecourse.Without their love and support this project would not have been made

possible. I have been deeply humbled by the knowledge acquired and support accorded

to me during my studies at the university.

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ABSTRACT

The purpose of this study was to establish the sources of financing real estate in Kenya. In specific terms the study reviewed whether financing in the real estate originates from; mortgage financing, savings, venture capital and equity financing.This study also employed descriptive survey design since it is conducted to describe the present situation, what people currently believe, what people are doing at the moment and so forth. The population of this study wasall the real estate firms in Nairobi. This study used secondary data for five years. Data was analyzed using Statistical Package for Social Sciences (SPSS) and results were presented in frequency tables and charts. The data was then analyzed in terms of descriptive statistics like frequencies, means and percentages. The findings indicated that mortgage financing is the most used source of financing, with equity and venture capital being the least source of financing used. The findings also indicated that there is a significantly positive relationship between mortgage financing and real estate development. However the findings recommended that to increase use of equity and venture capital as a source of financing will require businesses to sell their ideas to people who have money to invest.Equity and venture capital financing can be a good source of financing but with combining them with other sources of financing. Further research should be on the effects of sources of financing in unsuitable economic conditions, political instability and a global economic crisis and internal and external factors that affect the decision on sources of financing for real estate firms in Kenya. Carrying out this study will analyze decisions on the best methods to source for finances during such times and will also analyze critical factors that managers ought to consider in order to make their decision on sources of financing yield successful results.

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TABLE OF CONTENTS

DECLARATION ........................................................................................................ ii

ACKNOWLEDGEMENTS ....................................................................................... iii

DEDICATION ........................................................................................................... iv

ABSTRACT ................................................................................................................ v

LIST OF TABLES ..................................................................................................... ix

LIST OF FIGURES .................................................................................................... x

LIST OF ABBREVIATIONS .................................................................................... xi

CHAPTER ONE ......................................................................................................... 1

INTRODUCTION ...................................................................................................... 1

1.1 Background of the Study ................................................................................. 1

1.2 Research Problem ........................................................................................... 8

1.3 Research Objective ........................................................................................10

1.4 Value of the Study .........................................................................................10

CHAPTER TWO .......................................................................................................12

LITERATURE REVIEW ..........................................................................................12

2.1 Introduction ...................................................................................................12

2.2 Theoretical Review ........................................................................................12

2.3 Empirical Review ..........................................................................................14

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2.4 Summary .......................................................................................................24

CHAPTER THREE ...................................................................................................26

RESEARCH METHODOLOGY ..............................................................................26

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

3.2 Research Design ............................................................................................26

3.3 Population .....................................................................................................27

3.4 Sample ...........................................................................................................27

3.5 Data Collection ..............................................................................................28

3.6 Data Processing .............................................................................................28

CHAPTER FOUR......................................................................................................31

DATA ANALYSIS, RESULSTS AND DISCUSSION ..............................................31

4.1 Introduction ...................................................................................................31

4.2 Descriptive Results ........................................................................................31

4.3 Model Results ................................................................................................34

4.4 Summary and Interpretation of Findings ........................................................36

CHAPTER FIVE .......................................................................................................39

SUMMARY , CONCLUSION AND RECOMMENDATIONS ...............................39

5.1 Summary .......................................................................................................39

5.2 Conclusions ...................................................................................................40

5.3 Policy Recommendations ...............................................................................42

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5.4 Limitations of the study .................................................................................43

5.5 Suggestions for Further Research ...................................................................43

REFERENCES ..........................................................................................................45

APPENDICES ............................................................................................................52

Appendix I: Secondary Data Collection Template ....................................................52

Appendix II: List of Real Estate Firms .....................................................................55

Appendix III: Data ...................................................................................................58

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LIST OF TABLES

Table 4.1: Descriptive Statistics for Real Estate Financing ...........................................32

Table 4.2: Model Fitness ..............................................................................................35

Table 4.3: Analysis of variance (ANOVA) ...................................................................35

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LIST OF FIGURES

Figure 4. 1: Trend analysis in financing .......................................................................33

Figure 4. 2: Trend analysis in Units developed by Real Estate Firms ............................34

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LIST OF ABBREVIATIONS

ABS Australian Bureau of Statistics

CBK Central Bank Supervision

CMBS Commercial Mortgage-Based securities

KPDA Kenya Property Developers Association

REIT Real Estate Investment Trusts

RMBS Residential Mortgage Backed Securitization

SSA Sub- Saharan Africa

ULI Urban Lands Interest

ULT United Learning Trust

1

CHAPTER ONE

INTRODUCTION

1.1 Background of the Study

The development of the housing sector is widely recognized as an integral part of

economic development. In addition to the large share that the housing sector occupies in

the economy, its importance also arises from the positive externalities and spillover

effects, and its impact on the social and political climate, issues of particular importance

in developing countries. In most countries, and increasingly so in emerging economies,

housing represents a large proportion of a household’s expenditure and takes up a

substantial part of lifetime income. Usually, it is the largest asset owned by households.

The backward and forward linkages to land markets, durable goods manufacturing and

development of labor markets with depth and mobility further underscore the

significance of this sector, particularly in the process of economic transition (Bardhan&

Edelstein, 2007).

According to Zhu (2006) it is also widely understood that the provision of housing

services depends upon a well functioning housing finance system. Indeed, without a

properly functioning housing finance system that operates in an allocationally and

operationally efficient manner, the “real” housing market would be sub-optimal.

Moreover, similarly to the housing markets, the housing finance system has beneficial

spillover effects on the entire financial system with far-reaching consequences for

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economic development. Increasing emphasis is therefore being placed in developing and

transitioning countries on the reform of real estate finance and mortgage markets.

1.1.1 Financing sources

Mortgage is a loansecured by real property through the use of a mortgage note which

evidences the existence of the loan and the encumbrance of that realty through the

granting of a mortgage which secures the loan. A mortgage market is important for the

process of capital accumulation in a developing economy, and is critical to enhancing

the depth and reach of the financial markets. Since housing is the primary tangible asset

of a developing or transitioning economy, it can then also be used as collateral to borrow

funds in order to carry out productive capital investment. Mortgage debt accounts for a

large proportion of household debt and, through secondary markets and securitization,

supports the efficient functioning of financial markets. Housing finance, as well as other

real estate finance, are vital elements both in the development of a dynamic housing

sector as well as a growing and deepening financial sector. In addition to creation of

more lending channels, more investment channels are opened up as well for both

institutional and individual investors, leading to more complete and efficient markets

(Goodhart, 2003).

Sources of financing corporate real estate and the utilization, techniques and motivations

involved in leasing real estate by manufacturing and service corporations have been

investigated by Redman and Tanner. These researchers found out that significant

sources of funds to acquire real assets for production and distribution were operating

cash flows rather than external sources. Leasing was a common technique to finance and

3

acquire assets, allowing for managerial flexibility and tax-sheltering benefits and

creating off-balance sheet financing (Redman and Tanner, 1989).

Funds for real estate development in Ghana are acquired through diverse sources. Some

are obtained through the debt finance with some relatively few banks in the country

giving financial support to real estate developers provided all requirements are fulfilled.

Surveys throughout the country also indicate the persistence of informal financing

methods such as the use of homeowners’ own sweat equity, barter arrangements and

remittances from abroad , (Debrahet al., 2002 and Erguden, 2002). The loans acquired

are given on short, medium and long terms repayment period with interest rates charged

on them. There are various forms of funding that can be considered by real estate firms

in Ghana. Some of these are bonds, mortgage facilities stocks investment trusts,

merchant and commercial banks and mortgage companies. Moreover, there are other

forms of financial relieve that are being enjoyed by real estate developers. Trade

crediting involves the delay of payment of creditors beyond the normal period, high

purchasing system enables a company to enjoy a full use of goods or equipment but

avoids initial full sum payment.

1.1.2 RealEstate Development

Direct new expenditures in the construction industry or in other real estate related

industries stimulate the economy and generate jobs. Since a substantial portion of

generated income is plowed back into the economy, there is an additional multiplier

effect. This is true of any industry. However, since the real estate industrial sector

cluster is largely a non-tradable industry (i.e. most of the output and inputs associated

4

with the industry stay, and are from within the confines of the domestic economy), there

is little leakage out of the country. The localized and domestic nature of real estate

therefore leads to a much larger multiplier effect than would be expected for more

tradable sectors. While construction, home maintenance and repairs, power and

transportation directly affect the economy, the extensive nature of downstream and

upstream linkages of real estate, from the finance sector to the furniture/consumer goods

sector, from infrastructure (roads, bridges, public works) to superstructure (commercial

space/retail, industrial, etc.) further impact the national economy. A given amount of

expenditure in the real estate industry (vis-à-vis other sectors) tends to support larger

numbers of jobs in the economy (Jaffee and Levonian, 2008).

Though real estate is considered a “local” business activity, the national residential and

nonresidential/ commercial real estate markets are essential for the development of

nationally integrated economic markets in general. A national economic market implies

a free flow of capital, labor and resources within the borders of a nation-state, and the

development of a national market for housing and other real estate resources is critical in

facilitating national markets in goods, services and factors. The experience of several

countries shows that regional disparities and distorted development are the norm if real

estate markets are regionally segregated and segmented. Whether firms respond to

investment opportunities in various parts of the country or whether people follow jobs, a

rapidly responsive market in commercial construction and support services, in the

development of hotels, rental housing and homes for sale, can lead to a more efficient

and geographically mobile labor market (Bardhan& Edelstein, 2007).

5

1.1.3 Effects of Financing Sources on Real Estate Development in Kenya

In some countries the purchase of an entry-level home, often subsidized in some form,

has served as a stepping stone for upward social and economic mobility. As observed by

Bardhan, Datta, Edelstein and Kim (2003), the Singapore housing market, for example,

is characterized by the coexistence of a dominant public sector and a small, growing

private sector with relatively higher quality housing. While accounting for the impact of

the former on the latter, they find that an increase in the rate of change of public housing

resale prices has an important and significant positive impact on the sales of private

residential units. The underlying mechanism for this effect is that occupants of the

subsidized public sector flats are allowed to sell their flats after a certain period, subject

to some restrictions, and capital gains from the sale proceeds provide a substantial

portion of the down payment in the purchase of new, more expensive, private

apartments. This tandem of private-public activity lends a helping hand to upwardly

mobile households, and the larger social and economic value created far outweighs the

resources expended in the public sector housing subsidies (Bardhan, Datta, Edelstein

and Kim, 2003).

Laibson (1998) developed simulation theory and examined the extent to which markets

enable the provision of housing finance across a wide range of countries. Housing is a

major purchase requiring long-term financing, and the factors that are associated with

well-functioning housing finance systems are those that enable the provision of long-

term finance. The theory stated that countries with stronger legal rights for borrowers

6

and lenders (through collateral and bankruptcy laws), deeper credit information systems,

and a more stable macroeconomic environment have deeper housing finance systems.

Pottow (2007) in structural- form theory documented the evolution of mortgage finance

in SSA (Sub- Saharan Africa) to determine what steps need to be taken to extend it to

the middle-class, to enable them to address their housing needs to the extent of their

affordability. The theory revealed that there have been a number of problems when it

came to the delivery of formal housing finance amongst most, if not all the countries.

1.1.4 Real Estate Sector in Kenya

According to KIM journal (Nov-Dec 2007) vision 2030, it is estimated that over 80% of

Kenyan population will have migrated from rural areas, meaning that that shelter is one

of their basic needs. Presently, slum dwellers are1/3 of the urban dwellers population

whereby Kenya’s Kibera slum is one of the largest dwelling in Africa yet only

approximately three million people are urban dwellers. Hence as more rural urban

migration occurs more houses, well constructed must be built to combat slum uprising

problem.

The real estate industry must be supported and it will have to grow at a faster pace that it

currently does. The Kenya industry is benefiting from economic growth of the country

and the inflow of foreign aid is being regarded as a very promising venture. The

government is also heavily investing in this industry in various ways such as the

inclusion of the ministry of housing in the government body, availing of funds to the

7

housing ministry; enforcement of laws to do urban planning, regulatory laws in license

permits (Homes Expo Kenya, 2012)

Nairobi is a prime market in a major way especially because of infrastructural

development and market interest. Investors are being attracted by the city’s potential to

offer high returns on the property market. There is also a notable high demand

especially in the high-end market, which is expected to grow even more as interest rates

come down. To give you a clearer picture, the City Council of Nairobi approve an

estimated 12,000 residential and commercial building plans each month. But with the

formation of county governments, there’s bound to be more keen interest in real estate

development in other towns (Homes Expo Kenya, 2012).

It is also worthy to note that in some segments such as luxury real estate it has been

observed by analysts that the cities of Nairobi and Mombasa are global trailblazers.In

terms of growth, Kenya’s real estate market is still superior in comparison to her peers

in the region. Although the rest of East Africa is also making considerable headway with

much improved infrastructure and renewed interest by developers to build and sell more

in trying meet the growing demand in both residential and commercial property

segments. Growth drivers are quite similar across the region with factors such as rapid

urbanization, modern household formations, regional economic growth, improved

government policies among others (Kamau, 2011).

Kenya has a well-developed construction and building industry with readily available

quality engineering, building and architectural design services. The industry is currently

on an upward trend, due to the implementation of programmes such as the Urban

8

Transport Infrastructure plan. The increase in population and rural to urban migration

has presented numerous opportunities for investors, especially in the housing sector.It is

projected that Kenya will have a population of over 60 million people by the year 2030

and more than 50% of them were living in urban areas, creating a huge demand for new

housing units. It is estimated Nairobi alone requires approximately 150,000 new housing

units per year against a maximum construction of about 10,000 units per year (Mbugua,

2004).

1.2 Research Problem

In recent years the population of Kenya has steadily increased, resulting to the urban

population in Nairobi to a record of 3 million, whereby all these people need shelter,

hence the real estate industry is doing well and contributing to the economy (Nuri,

Erbas& Frank Nothaft, 2002). Despite recent indication that the real estate business in

Kenya is performing well, there is evidence that certain challenges still persist. These

include amongst others, social, economic, cultural, legal and personal factors. This has

led to stalled projects and unoccupied complete properties. This being an important

industry that makes enormous contribution to the Kenyan economy, there are some gaps

in the literature that ought to be filled, these includes: the available literature has not

indicated ways in which real estate enterprises can be empowered to compete on equal

levels with established businesses and also where the booming housing development is

the city has been sourcing its financing (Mwangi, 2002)

A studies conducted byLustigand Nieuwerburgh (2005) and Kamau (2011) indicate

thatthere is growing competition for funding of real estate development due to

9

competing needs for using the same funds to finance other productive sectors of the

economy. The studies indicate the existence of shortage of long term funds which are

mainly required to finance housing projects due to banks preferring short term

financing. The Central Bank Supervision report of 2012 indicates long term funding

mismatch which further complicates the funding mechanisms of long term projects in

the real estate sector (CBK, 2012).

Michuki (2010) did a study on the existence of Real Estate Investment Trusts (REITS)

needs by institutional investors at the Nairobi Securities Exchangeand concluded that

investors would invest in REITs if they were to be introduced at the exchange and

therefore confirming that REITs needs do exist among institutional investors at the NSE.

Wahome (2010) conducted a study to establish the effects of mortgage financing on

performance of the firms and concluded that mortgage financing is influenced by market

and financial factors which includes increase investment and improve profitability of the

firm, improvement of risk management, attraction' of more customers ,promotion of

innovations, market penetration, diversification of investment and encountering

competitions in the market lowering of interest on Treasury bond, Kenya financial laws

require bank to have less cash in reserve and high interest from mortgage, creating of

wealth and Improving savings. The objective of the study was to establish the

relationship between factor influencing mortgage financing and performance of

mortgage institutions in Kenya. This has left limited finance for long term projects and

hence the need to investigate the financing source of the current growth of real estate in

Kenya. Based on this well informed research gap, this study, therefore, examines the

sources of real estate financing in Kenya.

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1.3 Research Objective

The key objective of this study was to establish the source of financing real estate in

Kenya. In specific terms the study reviewed whether financing in the real estate

originates from; mortgage financing, savings, venture capital and equity financing.

1.4 Value of the Study

The findings of the study will be useful to the stakeholders and players in real estate

industry. The study was expected to reveal the key sources of financing real estate

developments and the findings will be key pointers to potential investors on where and

how to raise funds from.

The government will be able to appreciate the limitations that face real estate financiers

and developers. Such appreciation will inform policy change for the improvement of the

sector with an objective of making it more productive and hence creating more

employment and contribute meaningfully to the national economy. The Government

will also understand the incentives that are required in order to direct more funding by

banks to the real estate sector.

Future researchers will have a reference point from the information gathered that will

contribute to understanding the financing sources for the real estate sector. It forms a

basis for and stimulates research in order to develop a better understanding of factors

influencing investment finance in the real estate industry.

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Venture capitalists and equity capitalists will appreciate the financing gaps in the real

estate sector in Kenya. Based on the findings of the study it is able to target particular

projects and segments within the sector for their maximum returns on their investments.

12

CHAPTER TWO

LITERATURE REVIEW

2.1 Introduction

This chapter discussed theories relevant to the study. Literature related to the study is

also reviewed with the aim of identifying literature gaps.

2.2 Theoretical Review

This section contains review of theories relevant to the study.

2.2.1 Simulation theory

The theory was developed by Laibson (1998) and examines the extent to which markets

enable the provision of housing finance across a wide range of countries. Housing is a

major purchase requiring long-term financing, and the factors that are associated with

well-functioning housing finance systems are those that enable the provision of long-

term finance.

The theory further states that countries with stronger legal rights for borrowers and

lenders (through collateral and bankruptcy laws), deeper credit information systems, and

a more stable macroeconomic environment have deeper housing finance systems. These

same factors also help explain the variation in housing finance across emerging market

economies such as Kenya. Across developed countries, which tend to have low

13

macroeconomic volatility and relatively extensive credit information systems, variation

in the strength of legal rights helps explain the extent of housing finance.

To a certain extent, a statistical comparison of the loan-to-value and loan-to-income

ratios can provide a good indication of the risks that owner-occupiers run in financing

their own home. At the same time, this kind of comparison ignores the causes of the

risks, namely the volatility or uncertainty of future interest rates, house prices and

changes in income. It also disregards the main mortgage characteristics, the cost of

taking out a mortgage, and the direct and indirect subsidies, including interest

deductibility, factors that have a big influence on the real costs and risks for

homeowners.

2.2.2 Structural Form theory

This theory was formulated by Pottow (2007). It documents the evolution of mortgage

finance in SSA (Sub- Saharan Africa) to determine what steps need to be taken to

extend it to the middle-class, to enable them to address their housing needs to the extent

of their affordability. The theory revealed that that there have been a number of

problems when it came to the delivery of formal housing finance amongst most, if not

all the countries,

These problems are a record of macroeconomic instability, an adverse institutional, legal

and regulatory environment which has resulted in inefficient, collateralization of

housing assets, a poor record of public sector housing banks, building societies and

other specialist housing lenders in that most have been destroyed due to poor

14

management and a lack of funds and limited availability of long-term funding sources to

carry out intermediation that would spread the cost of a house over a relatively long

period of time.

Arising out of this dismal history is a move to revive and introduce mortgage lending

into a number of countries. Moreover, as part of the move to straighten out financial

markets, a number of consultants have been sent into SSA countries to begin

documenting the specific problems of each country as well as to make recommendations

on how to address them. Development agents, in particular, are also putting forth

recommendations on what is required to ensure financial market development and

capital market investment necessary to entice the private sector into the delivery of

housing finance.

2.3 Empirical Review

Housing is for many households around the world both the largest expense and the most

important asset. For all householdit is an important determinant of quality of life. For the

majority in developed countries, and for some in emergingmarket economies, housing is

adequate. But a significant proportion of the world’s population does not have access to

adequateand affordable housing. According to UN-Habitat (2005), roughly one billion

people, or one-third of the world’s urbanpopulation, live in slums. And a well-

functioning housing market influences not only shelter concerns. At a basic level,

acountry’s housing sector can improve public health (by reducing the likelihood of

outbreaks of disease), stimulate economicgrowth (through its own job creation, but also

15

as workplaces for home-based entrepreneurs), and have important social con sequences

(by influencing crime reduction and citizenship).The best housing sectors should enable

the adequate provision ofshelter across all segments of the population.

While there are many aspects to the housing market (discussed below), it can be argued

that the provision of housing finance is a binding constraint that must be addressed

before the market can sustainably provide adequate housing. Even in the best of

environments, housing is a major purchase—average home prices typically ranging

from 4 times annual income in developed countries to 8 times annual income in

emerging economies (Ball, 2003)—that is affordable only when payments can be spread

out over time. Absent a well-functioning housing finance system, for manythe market-

based provision of formal housing will be neither adequate nor affordable. Other

housing or housing financesolutions are possible—such as subsidies and the outright

provision of public housing—but these can be unsustainable (Quigley,2006)

While housing finance is a vital component of a well-functioning housing system, to

date there has not been a systematicanalysis of the depth of housing finance across a

broad set of countries.In fact, as far as we know, no formal cross-countrystudy of the

size of the housing finance market exists. Existing international housing finance studies

tend to be descriptive andhighly informative, but lack any formal empirical analysis and

often focus on one or more country case studies. Diamond and Lea (2002) evaluate the

housing financesystems of five countries. Chiquier et al. (2004) include case studies of

eight emerging market economies. Low et al. (2003),the Mercer Oliver Wyman study,

focus on eight countries in Europe. Hegedus and Struyk (2005) present case studies on

16

seventransition economies and Germany and tabulate housing finance statistics. Chiuri

and Jappelli (2003) analyze 14 developed countries (with an emphasis on loan-to-value

ratios). Allen et al. (2004) include a short section on mortgage markets in 17developed

countries. Renaud (2005) includes a presentation of data on 45 countries, the broadest

set of countries available. All of these studies are important, but none formally studies

why some countries have larger mortgage markets thanothers and none includes formal

empirical analysis.

Chinese commercial real estate financing meet the same problem as that of real estate, but

the problem is more complicated. As commercial real estate differentiates real estate in the

characteristics that commercial real estate needs long development period, large investment,

long payback time, high- stake and high-return, the financing of commercial real estate is

much more difficult. Nowadays, the primary options of commercial real estate financing are

bank loans and self-financing only takes a small share in contrast. However, based on risk

consideration, banks stipulate strict rules of loans both in amount and time to commercial

real estate developers. According to some relevant statistics, it shows that 70%-80% capital

of Chinese commercial real estate developers comes from bank loans, and in some cities it

even reaches 90% (Han,2007). According to an investigation of China business association

in 2006, more than 80% of the investment capital of shopping mall of all whole countries

comes from banks. Therefore, in development of commercial real estate, the financing

channels are limited, which meanwhile results in substantial risk on banks.

In the 1940s, there was already commercial real estate in America. With several

decades’ development, American commercial real estate has become mature in the

whole process like inviting investment, financing and operating. In America, the

17

developers of commercial property not only consider the sale of the properties, but also

the operation of the properties, they would have detailed plan about the development,

operation, management and so on. Most developers would choose to possess the

properties after they develop them, which can reduce the risk of investors because the

developers of commercial real estate would not only consider development of these

properties, but also the operation (Jiang,2007). This is different from China’s

commercial real estate. In China, the developers usually develop to sell, not to possess

because to develop commercial real estate needs large amount of money and the current

financing system of China cannot let developers possess the properties too long, their

70%-80% capital come from banks and these loans are usually short-term, they need to

get the funds back as soon as possible. In America, 10% of the capital for developing

commercial real estate comes from banks, 90% of the capital comes from the

developers’ own fund and other funds from investors. The low proportion of bank

financing and high proportion of other funds financing reduce the risk of developers

(Jiang,2007).

The financing of US commercial property market is different from that of real estate

market in aspects of participants, financing structure, securitization ratio or the quality

of bank loans. According to Moody, up to 2007, the market value of American

commercial real estate was 5.3 trillion US Dollars; the proportion of market value of

commercial properties is 36.6% for offices, 24% for apartments, 22.1% for retail, 15.3%

for industrial properties, 2% for hotels and so on. According to Deloitte, the financing

structure of American commercial real estate is 50% for bank loans, 25% for CMBS

18

(commercial mortgaged-based securities) issuing, 10% of loans from insurance

companies and 15% from other sources.

Compared to real estate financing, American commercial real estate financing has the

following characteristics. Firstly, the main participants are institutional investors, the

main source of capital comes from the institutional investors like banks, insurance

companies, pension funds, and the borrowers are developers, builders and investors.

However, for residential real estate, the borrowers are the main individuals who will buy

the houses. Secondly, the leverage is high. According to RREEF and ULT (urban lands

interest), up to the end of 2008, the whole leverage of commercial real estate was about

60%. Thirdly, the developers of commercial real estate would re-finance when the debt

becomes due. As the development and the operation of commercial real estate need a

long time, so more financing is needed to satisfy the need for capital (Ge, 2010).

In big aspects, the financing of American commercial real estate is divided into debt

financing and equity financing (Ge, 2010). For equity financing, there are private equity,

which means that individuals have the equity of the listed real estate companies; and

public equity, which is REITs. According to the estimation of ULI, up to the end of

2008, the proportion of the two equity financing is 80% and 20% separately. REITs

financing develops very well in America, so far there are more than 200 trust companies

trading in the exchanges. In America, there are 85% equity REITs, 15% mortgage

REITs and 5% hybrid REITs (Yang, 2009). In America, REITs is always in the form of

stock company, the company issue stocks to attract the money of investors and then they

19

will hire specialized institutions to manage the products and money, the institutions will

get the interest of real estate investment indirectly and the management fee of REITs.

For debt financing, according the statistics of Federal Deposit Insurance Corporation, up

to the end of 2009, the total amount of debt for American commercial real estate is 3.4

trillion dollars, 50.3% for commercial banks and saving institutions, 20.7% for CMBS,

CDO, and the other for other institutional investors. The debt financing is divided into

private debt, which is bank loans, and public debt, which is CMBS. Bank loans accounts

about 50% of the debt of commercial real estate. There are some characteristics that are

different from loans for residential houses. Firstly, most loans are from regional and

community banks or institutions.

Secondly, the rate of violation is usually lower than that of residential mortgages

(Ge,2010). The CMBS financing is frequently used in the financing of commercial real

estate, the advantages of CMBS make it very popular in the commercial real estate

financing. Firstly, the complexity is lower compared to RMBS (residential mortgage

backed securitization), commercial real estate loan can always avoid the risk of

advanced repayment (It is always about 10 years.). Secondly, the securitization rate is

lower compared to residential real estate. Thirdly, the degree of scatter is lower

compared to RMBS (Ge,2010)

Since the Asia financial crisis, ABS has had great development in some Asian countries,

especially in Hong Kong. ABS can transfer the illiquid real estate to liquid securities

and then sell to investors, the investors own creditors’ rights of securities instead of

owning the right of real estate. This is very useful for real estate development as real

20

estate is an illiquid, the investment is huge, the development cycle is long, the liquidity

is poor, the securitization of real estate can change the situation, real estate securities can

exchange in the stock market. In Hong Kong, the transformation of capital and assets is

very smooth, the financial market and the real estate promote mutually (Wang & Hu,

2004).

Bank loans are the main source of real estate developers. In the whole capital chain,

bank loan account for at least 55%, some even more than 90% (Han,2008).Bank loans

almost go through every part of the development process, including land reserve, real

estate developing, selling and buying.

The mezzanine debt is senior to the original equity but junior to the bank, hence, viewed

to reside in the middle. Mezzanine financing is generally used to fill the gap between

low-risk collateralized debt obtained from traditional lenders and higher-risk equity

interests. Unlike a traditional bank loan, a mezzanine lender does not hold real assets of

a company as collateral but instead has an indirect link to the company's equity in the

case of default. In other words, mezzanine lenders most often gain an equity ownership

in real estate or the financed project, if borrowers default (Bean, 2008).

Mezzanine financing is well-developed in developed countries. It is estimated that there

are more than 100 billion dollars investing in mezzanine fund (Liu&Song, 2007). The

main investors were insurance companies in the early stage, and gradually mainly with

fund companies and commercial banks. Fund companies account for 70% and

commercial banks 20% (Sun, 2005). Many banks like Goldman, Deutsche Bank and

Bank of America Merrill Lynch have set up mezzanine investment fund. As mezzanine

21

financing products have good liquidity and low fluctuation, it has great attraction to the

institution investors like insurance companies, commercial banks, investment banks,

hedge fund and pension fund. Mezzanine financing is a mature asset class. In the

alternative assets class of institution investors, mezzanine asset accounts for 5%, and the

current interest is 12%, the total annual average return rate of investment is 18-20%, the

mortgage period is 5-7 years.

Mezzanine financing has been widely used in emerging market. FMO has been

providing mezzanine financing for small and medium companies for developing

countries such as China, Indonesia, Thailand and Brazil. Also Value Partner has

invested more than 100 small and medium enterprises in China (Liu 1&Song, 2007).

There is great potential in Asia market. The economic development, enterprises upgrade

and market reform increases the demand for venture capital, which creates a good

opportunity for the development of mezzanine financing. The main demand in

mezzanine financing focuses on infrastructure, industrial and commercial areas. The

small and medium enterprises have great demand for mezzanine capital for the

development.

There is a positive relationship between operating assets (fixed assets) and long-term

debt in Ghana. Ghanaian banks with a higher proportion of operating assets are financed

by long-term debt capital, (Amidu, 2007). This could be due to the fact that higher

proportions of banks’ operating assets denote less operating risk; therefore, the banks

may not be exposed to more risk from the use of more long-term debt capital. There is

also a negative relationship between size and long-term debt, (Amidu, 2007). This

22

suggests that smaller banks, due to their limited access to equity capital market tend to

rely on long-term debt for their financing requirements. However, long-term debt

structure is positively and statistically related to operating assets (Amidu, 2007). More

than 87 per cent of the Ghanaian banks’ assets are financed by debts, of this, short-term

debts appear to constitute more than three quarters of the capital of the banks (Amidu,

2007). This highlights the importance of short-term debt over the long-term debt in

Ghanaian banks’ financing. Empirical evidence suggests that profitability, corporate tax,

growth, asset structure and bank size are important variables that influence banks’

capital structure.

Better corporate frameworks benefit firms through greater access to financing; lower

cost of capital, better performance and more favorable treatment of all stakeholders

Claessens et al. (2002). Firms with well-established corporate governance structures are

able to gain easier access to debt financing at lower cost since such firms are able to

repay their debt on time (Abor, 2007). This suggests that the ability of the firm to access

debt capital at lower cost could be dictated to a large extent by how the market gauges

its corporate governance system. Easier access to debt capital at lower cost, ultimately

leads to improved company performance.

Countries with a developed housing finance system tend to experience lower

construction costs and the use of housing assets to support broader investment

opportunities through formal institutional frameworks (Blasko and Sinkey, 2005). The

financial market is critical to the development process for real estate developers and

investors, (Miles et al, 2000). There are suggestions that poor access to private external

23

finance relates to demand-side problems, particularly a lack of information about

available sources, rather than a lack of available credit (Fraser, 2004). Generally, there is

a gross persistence of informal financing methods throughout Ghana. Residential

property owners in Ghana as in most developing countries use their own sweat equity,

barter arrangements and remittances from abroad to build their houses (Debrahet al,

2002 and Erguden, 2002).

In Ghana, lack of access to long term capital is a major barrier to real estate delivery.

Even though the government policies recognizes the private sector’s dominant role in

housing provision, the banks have short term funding and unable to lend on medium or

long-term bases, thus crippling the real estate industry (Adjonyoh, 2007).

Kamau (2011) did a study on the factors that influence investment in the real estate

industry in Nairobi. The research design employed by the study was descriptive research

and targeted all licensed real estate enterprises in located in Nairobi. The researcher

used questionnaires to collect data and analyzed data using SPSS .The study findings

indicated that all the real estate investment firms work towards reducing the housing

deficit in the city of Nairobi which currently stands at 410 house units a day, the study

also concluded that although deregulation of this sector is a necessary condition for

revival of a healthy real estate investment sector, deregulation cannot by itself ensure

that a full range of real estate investment accommodation is provided.

24

2.4 Summary

Based on the literature reviewed, it is evident that there are various source of real estate

financing and it depends on the circumstances surrounding a project. It has also been

revealed that there is no one best or worst financing option. Project financing option also

depends on the structure and the risks associated with the project. It is therefore

important to seek to appreciate the real estate financing options available in Nairobi,

Kenya.Studies conducted byLustig and Nieuwerburgh (2005) and Kamau (2011)

indicate that there is growing competition for funding of real estate development due to

competing needs for using the same funds to finance other productive sectors of the

economy. The studies indicate the existence of shortage of long term funds which are

mainly required to finance housing projects due to banks preferring short term

financing.Several studies have been done but there is paucity in Kenya. Michuki (2010)

did a study on the existence of Real Estate Investment Trusts (REITS) needs by

institutional investors at the Nairobi Stock Exchangeand concluded that investors would

invest in REITs if they were to be introduced at the exchange and therefore confirming

that REITs needs do exist among institutional investors at the NSE. Wahome (2010)

conducted a study to establish the effects of mortgage financing on performance of the

firms and concluded that mortgage financing is influenced by market and financial

factors which includes increase investment and Improve Profitability of the firm,

improvement of risk management, attraction' of more customers ,promotion of

innovations, Market Penetration, diversification of investment and encountering

competitions in the market lowering of interest on Treasury bond, Kenya financial laws

require bank to have less cash in reserve and High interest from Mortgage, creating of

25

wealth and Improving savings. However the studies did not address the sources of real

estate financing in Kenya.

26

CHAPTER THREE

RESEARCH METHODOLOGY

3.1 Introduction

This chapter contains research design, population, sample and data analysis. The chapter

also covers the research ethical issues to be observed. Research methodology is the

architecture or the layout of the research framework. According to Polit and Hungler

(2003) methodology refers to ways of obtaining, organizing and analyzing data.

3.2 Research Design

Research design is an outline of research study which indicates what the researcher will do

from writing the hypothesis and its operational implications to the final analysis of data.

A research design is the arrangement of conditions for data collection and analysis of

data in a manner that aim to combine relevance to research purpose with economy in

research procedure (Kothari, 2004). Research design constitutes decision regarding

what, why, where, when and how concerning an inquiry or a research study (Sekaran,

2011). Research design can be thought of as thelogical master planof a research

thatthrows light on how the study is to be conducted. It shows how all of the major

partsof the research study– the samples or groups, measures, treatments or programs,

etc–work together in an attempt to address the research questions. Research design

issimilar to an architectural outline. The research design can be seen as actualization

oflogic in a set of procedures that optimizes the validity of data for a given

27

researchproblem. According to Yin (2003) the research design serves to "plan,structure

and execute" the research to maximize the "validity of the findings".

This employed descriptive survey design. Descriptive survey conducted described the

present situation, what people currently believe, what people are doing at the moment

and so forth (Baumgartner, Strong and Hensley 2002). According to Kothari (2004),

descriptive survey design includes surveys and fact finding enquiries of different kinds.

The major purpose of descriptive research design is description of the state of affairs as

it exists at present (Kothari 2004).

3.3 Population

Burns and Grove (2003) and Mugenda and Mugenda (2003) describe population as all

the elements that meet the criteria for inclusion in a study. Population is therefore the

entire group of individuals, events or objects having a common observable

characteristic. The population of this study was all the real estate firmsregistered by

Kenya Property Developers Association (KPDA). The real estate developers registered

by Kenya Property Developers Association (KPDA) are sixty nine in number.

3.4 Sample

According to Polit and Beck (2003), a sample is a proportion of population to be

researched, while Kothari (2004) defines a sample as the selected respondent

representing the population. The study sample comprised of all real estate firms

registered by Kenya Property Developers Association (KPDA). This means that a

census was employed in order to include all 69 real estate firms. The sample was drawn

28

from the offices of the 69 firms in Kenya.

3.5 Data Collection

Secondary data was utilised in this study. This means that all the study variablesutilised

quantitative data. Data for real estate development was secondary data which was

sourced from the Kenya economic survey of year 2013. This included the number of

houses built in the span of five years (2008- 2012). Data for the independent variables

was gathered from the banks’ annual report. To compile the data, a secondary data

collection template was used.

3.6 Data Processing

Data Analysis is the processing of data to make meaningful information (Sounders,

Lewis and Thornhill, 2009). Burns and Grove (2003) define data analysis as a

mechanism for reducing and organizing data to produce findings that require

interpretation by the researcher. According to Hyndman (2008) data processing involves

translating the answers on a questionnaire into a form that can be manipulated to

produce statistics. This involves coding, editing, data entry, and monitoring the whole

data processing procedure.

After data was collected, it was prepared in readiness for analysis by editing, handling

blank responses, categorizing and keying into Statistical Package for Social Sciences

(SPSS) computer software for analysis. SPSS was used to produce frequencies,

29

descriptive and inferential statistics which helped to derive conclusions and

generalizations regarding the population.

3.6.1 Analytical Model

Multiple linear regression modelwasused to analyze the data using statistical package

for the social sciences (SPSS) version 20. A linear multiple regression modelwasused to

measure the relationship between the independent variables and the dependent variable

which are explained in the model. The regression model helps to explain the magnitude

and direction of relationship between the variables of the study through the use of

coefficients like the correlation, coefficient of determination and the level of

significance. Analysis of data using regression model has been used previously by

Aduda (2011) in a studywhich investigated the relationship between executive

compensation and firm performance in the Kenyan banking sector. Also Ngugi (2001)

used a regression analysis in a study on the empirical analysis of interest rates spread in

Kenya while Khawaja and Mulesh (2007) used regression analysis to identify the

determinants of interest rates spread in Pakistan. The multiple linear regression model

that was adopted for the study is as follows:

Y= a + β1X1+ β2X2+ β3X3+ β4X4+

Where: Y = real estate development units (Units are the projects for development). X1 =

mortgage finance, X2 = savings, X3 = Venture capital and X4= equity finance. In the

model a is the constant term while the coefficient β1 to β4are used to measure the

30

sensitivity of thedependent variable (Y) to unit change in the explanatory variable (X1,

X2, X3&X4). is the error term which captures the unexplained variations in the model.

31

CHAPTER FOUR

DATA ANALYSIS, RESULSTS AND DISCUSSION

4.1 Introduction

The chapter represents the results of the data collected. Descriptive statistics and model

results were presented. The chapter also includes the results interpretation and summary

of the findings.

4.2 Descriptive Results

This section presents the descriptive results where the measures of central tendency and

trend analysis are presented.

4.2.1 Measures of Central Tendency

Results in table 4.1 indicate that the lowest number of real estate units developed by the

firms was 6 while the maximum was 29. The average number of units developed

throughout the years was 16.66. The analysis also show that the lowest percentage

amount of mortgage financing by the real estate firms was 0.30 and the highest

percentage amount of mortgage used for financing was at 0.82. On average the

percentage mortgage financing used by real estate firms through years; 2008 to 2011

was 0.63.

32

Savings incorporated for financing of real estate’s indicated a minimum percentage of

0.05 and a maximum of 0.42. The average percentage amount of savings used for

financing was at 0.186. Results indicate that 0.000 was the minimum percentage amount

of venture capital used in financing real estates and 0.20 was the maximum venture

capital used. The average presented a 0.036 use of venture capital financing.Financing

through equity capital represent a minimumpercentage amount of 0.00 equity used and a

maximum of 0.53 equity used. The firms used an average percentage amount of 0.12

equity capital financing.

Table4.1: Descriptive Statistics for Real Estate Financing

Financing Type

Minimum Maximum Mean Std.

Deviation

Real Estate

Development Units 6 29 16.66 5.436

Mortgage (Debt

Financing) 0.3 0.82 0.6382 0.09463

Savings 0.05 0.42 0.1867 0.06837

Venture Capital 0 0.2 0.0537 0.04752

Equity Capital 0 0.53 0.1238 0.07926

4.2.2 Annual Trends of the financing options

Figure 4.1 indicates that debt as a source of financing for real estate firms have

gradually increased from year 2008 to 2012. The increase may be explained by low

interest rates charged and fair terms and conditions on borrowing.

33

Results also indicate that trend in savings as a source of financing was inconsistent.

From year 2008 to 2009 there was a gradual decrease with an increase in 2010, 2011

and a slight decline in 2012. This may be as a result of real estate firms using mortgage

financing more than savings.

Trend in venture capital as a source of financing revealed a gradual decrease from year

2008 to 2012. This can be explained by interest of few venture capital firms to finance

real estates. Results in Figure 4.1 shows that there was a slight increase in equity capital

as a source of financing in year 2009, followed by a gradual drop from in the following

years.

Figure 4. 1: Trend analysis in financing

54%59%

64%70%

73%

21%17% 17% 19% 19%

9% 6% 6% 3% 2%

16% 18%13%

9%6%

0%

10%

20%

30%

40%

50%

60%

70%

80%

2008 2009 2010 2011 2012

Perc

enta

ge F

inan

cing

Time in Years

Mortgage (debt)Financing

savings

venture capital

equity capital

34

The trend in units developed by real estate firms indicates an increase throughout the

years; 2008 to 2012 .This increase can be as a result of rise in demand for housing which

is triggered by changes in income level, consumer and investors preference.

Figure 4. 2: Trend analysis in Units developed by Real Estate Firms

4.3 Model Results

This section presented the model results. Result in table 4.2 indicates that the goodness

of fit of the model was adequate. This is reported by an r squared of 0.409 which means

that 40.9% of the variation in real estate development is explained by savings, venture

capital, mortgage and equity capital are substantial to explain real estates’ sources of

financing. This further implies that 59.1% of the variation in real estate development

units is explained by other factors not captured in the model.

11.3814.19

16.1419.71

21.86

0.00

5.00

10.00

15.00

20.00

25.00

2008 2009 2010 2011 2012

Aver

age

Num

ber

of u

nits

de

velo

ped

Time in years

35

Table 4.2:Model Fitness

Indicator Coefficient

R 0.64

R Square 0.409

Adjusted R Square 0.386

Std. Error of the Estimate 4.261

An Analysis of Variance (ANOVA) results in table 4.3 indicates that the overall model

was significant. This was supported by a p value of 0.000. The ANOVA results

demonstrated that the sources of financing that is equity capital,venture capital, savings

and mortgageare good predictors of real estate units’ development.

Table 4.3: Analysis of variance (ANOVA)

Indicator Sum of Squares df Mean Square F Sig

Regression 1258.464 4 314.616 17.332 0.000

Residual 1815.193 100 18.152

Total 3073.657 104

Table 4.4 presents regression of coefficient results which indicates that is a positive

relationship between mortgage financing and real estate units’ development. The results

also indicate the relationship was significant since the reported p value 0.009 was less

36

that the critical value of 0.05. Results further indicate that all the other sources of

finance had an insignificant effect on real estate development.

Table4.4: Regression Coefficients

Variable Beta Std. Error t Sig.

Constant -26.456 21.14 -1.251 0.214

Mortgage Financing 55.98 21.108 2.652 0.009

Savings 21.195 22.311 0.95 0.344

Venture Capital 26.283 22.645 1.161 0.249

Equity Capital 16.21 21.437 0.756 0.451

4.4 Summary and Interpretation of Findings

The minimum number of units that were developed by the real estate firms were 6 while

the maximum number of units developed were 29. The overall mean number of real

estate units’ development was 16.66. The results also show that there was a positive

trend in the number of units presented. This is as a result of increase in urbanization

which results to the rise in demand of housing and commercial buildings. The rise in

demand of residential and commercial housing supports structural form theory

developed by Pottow (2007) which explains the steps to be taken by firms to address

housing needs to the extent of their affordability. Rise in urbanization results to building

of more residential and commercial facilities by real estate firms to take advantage of

37

the increasing markets. Therefore real estate companies take in account the source of

financing that will yield more units development throughout the years

Results indicate that the real estate development has a minimum of 0.30 and a maximum

of 0.82 mortgage financing. On average, the mean number mortgage financing used by

real estate firms was 0.6. Mortgage is the most used source for financing and

investment.Trends also show that mortgage as a source of financing for real estate firms

gradually increased from year 2008 to 2012. The increase may be explained by low

interest rates charged and fair terms and conditions on borrowing. In addition good

products offered such as short term construction loans, long term financing of

commercial and residential properties increased the use of mortgage source of financing.

The findings also relates to the empirical study of Hans (2007) on Chinese commercial real

estate financing where bank loans finance most real estate units development some relevant

statistics, it shows that 70%-80% capital of Chinese commercial real estate developers

comes from bank loans, and in some cities it even reaches 90%.

Savings as a source of financing was represented by a maximum percentage of 0.42 and

a mean percentage of 0.18. There was an inconsistent trend in savings as a source of

financing with high proportions in years 2010 and 2011. Savings may not be fully

substantial in setting up real estate units as the costs involved in the same are too high.

Small percentage of savings may be used together with other forms of financing such as

mortgage or equity or venture capital.This finding relates to a study done by RREEF and

ULT where most American commercial real estate financing comes from institutional

investors, banks, insurance companies, pension funds, and the borrowers are developers,

38

builders and investors. This shows that acquiring financing from other sources other

than mortgage or personal savings is relevant in real estate developments.

The minimum percentage of Venture capital was 0.00 while the maximum was 0.20

with an overall mean of 0.036 and an average risk (standard deviation of 0.04).This

means that the use of venture capital by real estate firmsdoes not deviate much from the

average. From the trends it is also evident that venture capital as a source of financing

gradually decreases throughout the years. This is because venture capital firms expect a

business to be able to return their investment not only with interest, but with a large

profit. Descriptive statistics show that the risk associated with venture capital is 0.04

which is very low for venture capitalists to have the motivation to invest.

The minimum percentage financing through equity capital was 0.00 and a maximum of

0.53. The firms used an average proportion of 0.12 equity capital as a source of

financing. Trends in equity source of financing shows that there was a slight increase in

equity capital in year 2009, followed by a gradual drop in the following years.

Financing through equity capital is almost the same as venture capital only that venture

capital is providing finance to high risk and high potential new companies.Investing

cash in business revolves around risk and reward, the higher the risk the higher the

returns. The risk represented by standard deviation was of 0.729, this means that there

was a high variance in the use of venture capital and that there was a variation in

investors being interested in buying stock or shares in such companies.

39

CHAPTER FIVE

SUMMARY , CONCLUSION AND RECOMMENDATIONS

5.1 Summary

This section summarizes the results of the study. Chapter one discussed the problem

statement and the objectives of the study. The study aimed to determine the effect of

financing sources on real estate’s development in Kenya.

Chapter two discussed the literature review, that is, the theories supporting the

study.The discussed theories were simulation theory and structural form theory with

empirical evidence of the study given. Chapter three presented the research

methodology. The chapter discussed the type of research design, population, sample,

data collection/instruments to be used and data analysis.

Chapter four presented the findings. Regression analysis was carried out to determine

the relationship between the different sources of financing to real estate developments in

Kenya.Results indicated that there is a positive relationship between mortgage financing

and real estate units development. The relationship was also significant as mortgage

financing was significant in explaining real estate development in Kenya as the reported

p value of 0.009 is lower than the critical value of 0.05.

40

Results also indicate that the goodness of fit was adequate as it reported an r squared of

0.409 which means that 40.9% of the variations in real estate development units was

explained by variables that such as savings, venture capital, mortgage and equity capital

are substantial to explain real estates’ sources of financing. An Analysis of Variance

(ANOVA) indicated that the overall model was significant. This was supported by a p

value of 0.000. The ANOVA results demonstrated that the sources of financing that is

equity capital,venture capital,savings and mortgage are good predictors of real estate

units’ development.

5.2 Conclusions

The study concluded that mortgage financing in the years 2008 to 2011 have gradually

increased. This may be explained by the variety of products that mortgage firms have

and the low interest rates associated with the loans. Housing finance in Kenya has a

variety of loans which is flexible to individuals and more especially to real estate firms.

For example from their website the project finance, offers a varietyof multi development

loans which is quite advantageous for developing real estate’s firms in Kenya.

Multi development loans include commercial properties where the loan under this

approach is tailored to development of building for sale to clients upon completion of

construction.The principal amount on the said loan is not payable during the

construction period but payable after completion.The repayment is linked to the sale of

completed developments. Another product is the build to rent residential, were the loan

is available for developers to build many units for rental income.Loan repayment is done

41

after completion of construction and occupation of the rental space over an agreed

period of time.From the various advantages listed on mortgage financing it is then

prudent to make conclusions from the study that mortgage financing is the most

preferred source by most investment firms.

It is also possible to conclude that savings contributes a smaller percentage in financing

real estate’s development. The advantage of using savings to start up or expand in

housing or commercial units for real estate firms is the ability to have control on the

business. It is relatively rare for businesses to have sufficient savings to completely

finance projects. This has to go with other sources of financing to make the projects

development a success.

Venture capitalists consist of individuals or companies with interests to invest in a

business with a strong growth potential and high risks. In reality, individuals or informal

venture capitalists may be more interested in investing in smaller businesses than

institutional venture capitals. In real estate development in Kenya, venture capital is not

extensively used as a source of financing. The trend shows that venture capital from

year 2009 to 2011 decreased gradually which may be as a result of investment firm

owners who do not want to relinquish control over their business in exchange of money

for units development. Venture capitalists also look at the risk level of the company

before making an investment in the real estate firm, which as evidenced from the

standard deviation in the results most real estate firms have a low risk. The declining

trend in equity capital as a source of financing is also explained the same way as venture

42

capital financing. The lower the risk the less attracted the investors will be, as high risks

presents high potential of a firm thus higher return.

The trend in venture capital and equity capital source of financing can also be explained

by liquidity of the investment. If a company is privately owned,selling the stock in that

company may be more difficult than selling the shares of a public firm since buyers

have to be privately sourced. In addition real estate’s that finally achieve the growth

objective tend to raise the price of their stock and take it public in order to let investors

cash out. The latter may happen if the company pays very low dividends thus

demotivating potential investors in the company.In a nutshell equity and venture capital

financing can be a good source of financing but with combining them with other sources

of financing.

5.3 Policy Recommendations

To increase use of equity and venture capital as a source of financing requires

businesses to sell their ideas to people who have money to invest. Careful planning can

help convince potential investors that the company is competent and that there is a high

potential in growth in future.

Mortgage firms should also increase more products with long term financing

incorporated. The study also recommends that owners of real investment firms should

relinquish some of their ownership rights to potential investors for them to invest. As

when an investor puts his or her money in an investment there is a hard work from their

side so as to generate more profits which later increases their dividends.Real estate firms

43

should also increase their dividends as their profits grow to increase investors

motivation and avoid the potential ones moving out of the company.

5.4 Limitations of the study

One of the limitations of the study was that the study did not consider the effects of

political crisis especially in year 2007/2008 post election violence which affected the

returns of most real estate firms especially when people were forced to move out of

areas deemed to be unsafe as a result of the violence.

The study did not analyze internal and external factors that affect real estate firms when

deciding on the various sources of financing. Perhaps, competition,performance of the

company, operating efficiency could have influenced the decision on financing.The

study also failed to look at whether corporate bonds would act as a source of financing

for real estates.

5.5 Suggestions for Further Research

Suggested areas of study should be on internal and external factors that affect the

decision on sources of financing for real estate firms in Kenya.This will analyze critical

factors that managers ought to consider in order to make their decision on sources of

financing yield successful results.

Further studies should also include the effects of sources of financing in unsuitable

economic conditions,political instability and a global economic crisis.This study will be

able to come up with decisions on the best methods to source for finances during such

44

times.Studies can also be done on corporate bonds to assess whether it is a reliable

source of financing for real estate’s or other companies in Kenya.

45

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APPENDICES

Appendix I: Secondary Data Collection Template

The following statement relates to how real estate firms finance their projects. Indicate

the agreeable percentage on how you finance yourproject by placing a tick (√)

against.This would cover a period of five years.

Year 2008

No Finance Type Percent

1 Mortgage Financing

2 Savings

3 Venture Capital

4 Equity financing

Others, Please specify.......................................................................................................

Year 2009

No Finance Type Percent

1 Mortgage Financing

2 Savings

3 Venture Capital

4 Equity financing

Others, Please specify.......................................................................................................

53

Year 2010

No Finance Type Percent

1 Mortgage Financing

2 Savings

3 Venture Capital

4 Equity financing

Others, Please specify.......................................................................................................

YEAR 2011

No Finance Type Percent

1 Mortgage Financing

2 Savings

3 Venture Capital

4 Equity financing

Others, Please specify.......................................................................................................

YEAR 2012

No Finance Type Percent

1 Mortgage Financing

2 Savings

54

3 Venture Capital

4 Equity financing

Others, Please specify.......................................................................................................

55

Appendix II: List of Real Estate Firms

1. Active Homes

2. Afriland Agencies

3. Ark Consultants Lt

4. Barloworld Logistics (Kenya) Ltd

5. Betterdayz Estates

6. British American Asset Managers

7. Canaan Properties

8. Capital City Limited

9. CB Richard Ellis

10. Colburns Holdings Ltd

11. Coral Property Consultants Ltd

12. Country Homes and Properties

13. Crown Homes Management

14. Crystal Valuers Limited

15. Daykio Plantations Limited

16. Double K Information Agents

17. Dream Properties

18. Dunhlill Consulting Ltd

19. East Gate Apartments Limited

20. East Gate Apartments Limited

21. Ebony Estates Limited

22. Economic Housing Group

23. Elgeyo Gardens Limited

24. Fairway Realtors And Precision Valuers

25. FriYads Real Estate

26. Gimco Limited

27. Greenspan Housing

28. Hajar Services Limited

29. Halifax Estate Agency Ltd.

56

30. Hass Consult

31. Hewton Limited

32. Homes and lifestyles

33. Housing Finance

34. Jimly Properties Ltd

35. Jogoo Road Properties

36. Josekinyaga Enterprises Ltd

37. Josmarg Agencies

38. Karengata Property Managers

39. Kenya Prime Properties Ltd

40. Kenya Property Point

41. KilifiKonnection

42. Kiragu&Mwangi Limited

43. Kitengela Properties Limited

44. Knight Frank Limited

45. KusyombunguoLukenya

46. Land & Homes

47. Langata Link Estate Agents

48. Langata Link Ltd

49. Lantana Homes

50. Legend Management Ltd

51. Lloyd Masika Limited

52. MamukaValuers (M) Ltd

53. Mark Properties Ltd.

54. MarketPower Limited

55. Mentor Group Ltd

56. Merlik Agencies

57. Metrocosmo Ltd

58. Mombasa Beach Apartments

59. Monako Investment Ltd

60. Muigai Commercial Agencies Ltd.

57

61. Myspace Properties (K) Ltd.

62. N W Realite Ltd

63. Nairobi Real Estates

64. Neptune Shelters Ltd

65. Oldman Properties Ltd

66. Oloip Properties

67. Ounga Commercial Agencies

68. Raju Estate Agency Limited (REAL)

69. Tysons Limited

58

Appendix III: Data

Real

Estate Year

Mortgage

Financing

(debt

financing) Savings Venture Capital

Equity

Capital

Total

Financi

ng

Real Estate

units

Firm1 2008 0.49 0.15 0.16 0.2 1 12

2009 0.5 0.17 0.18 0.15 1 10

2010 0.55 0.19 0.19 0.07 1 15

2011 0.57 0.22 0.21 0 1 23

2012 0.63 0.25 0.07 0.05 1 27

Firm2 2008 0.67 0.21 0.08 0.04 1 6

2009 0.69 0.22 0.09 0 1 12

2010 0.7 0.15 0.11 0.04 1 16

2011 0.72 0.1 0.14 0.04 1 25

2012 0.73 0.15 0.12 0 1 29

Firm3 2008 0.53 0.19 0.1 0.18 1 8

2009 0.62 0.2 0.11 0.07 1 12

2010 0.65 0.21 0.12 0.02 1 17

2011 0.68 0.22 0.1 0 1 19

2012 0.67 0.21 0.1 0.02 1 28

Firm4 2008 0.55 0.21 0.07 0.17 1 10

2009 0.59 0.27 0.09 0.05 1 16

2010 0.62 0.28 0.1 0 1 20

2011 0.63 0.28 0.09 0 1 23

59

2012 0.65 0.2 0.13 0.02 1 24

Firm5 2008 0.59 0.14 0.11 0.16 1 11

2009 0.6 0.15 0.12 0.13 1 14

2010 0.65 0.16 0.13 0.06 1 16

2011 0.67 0.17 0.14 0.02 1 18

2012 0.67 0.18 0.15 0 1 19

Firm6 2008 0.52 0.21 0.12 0.15 1 6

2009 0.53 0.22 0.13 0.12 1 10

2010 0.55 0.23 0.14 0.08 1 12

2011 0.59 0.24 0.15 0.02 1 13

2012 0.6 0.25 0.15 0 1 18

Firm10 2008 0.53 0.14 0.07 0.26 1 7

2009 0.58 0.15 0.12 0.15 1 11

2010 0.66 0.18 0.16 0 1 14

2011 0.71 0.22 0.07 0 1 18

2012 0.74 0.24 0.01 0.01 1 20

Firm11 2008 0.65 0.11 0.07 0.17 1 11

2009 0.67 0.21 0.08 0.04 1 12

2010 0.69 0.22 0.09 0 1 13

2011 0.7 0.15 0.15 0 1 15

2012 0.72 0.1 0.16 0.02 1 19

Firm12 2008 0.48 0.26 0.2 0.06 1 6

2009 0.5 0.27 0.21 0.02 1 9

2010 0.54 0.15 0.25 0.06 1 10

2011 0.53 0.17 0.26 0.04 1 20

60

2012 0.55 0.18 0.27 0 1 22

Firm13 2008 0.63 0.14 0.03 0.2 1 16

2009 0.65 0.16 0.06 0.13 1 24

2010 0.67 0.19 0.08 0.06 1 20

2011 0.68 0.2 0.05 0.07 1 24

2012 0.69 0.21 0.09 0.01 1 25

Firm14 2008 0.59 0.29 0.06 0.06 1 13

2009 0.6 0.3 0.07 0.03 1 16

2010 0.65 0.12 0.08 0.15 1 18

2011 0.68 0.19 0.09 0.04 1 21

2012 0.69 0.2 0.1 0.01 1 26

Firm15 2008 0.61 0.16 0.08 0.15 1 10

2009 0.62 0.18 0.08 0.12 1 18

2010 0.63 0.19 0.11 0.07 1 19

2011 0.65 0.2 0.13 0.02 1 23

2012 0.69 0.21 0.07 0.03 1 27

Firm16 2008 0.53 0.21 0.09 0.17 1 16

2009 0.59 0.22 0.1 0.09 1 16

2010 0.6 0.23 0.11 0.06 1 17

2011 0.61 0.24 0.12 0.03 1 18

2012 0.62 0.25 0.13 0 1 22

Firm17 2008 0.48 0.24 0.14 0.14 1 14

2009 0.49 0.26 0.15 0.1 1 15

2010 0.51 0.27 0.16 0.06 1 17

2011 0.53 0.28 0.14 0.05 1 20

61

2012 0.55 0.29 0.15 0.01 1 22

Firm18 2008 0.63 0.1 0.09 0.18 1 12

2009 0.62 0.2 0.1 0.08 1 17

2010 0.64 0.21 0.13 0.02 1 19

2011 0.65 0.21 0.14 0 1 24

2012 0.66 0.22 0.12 0 1 26

Firm19 2008 0.48 0.22 0.12 0.18 1 9

2009 0.49 0.24 0.14 0.13 1 11

2010 0.5 0.28 0.15 0.07 1 13

2011 0.52 0.29 0.16 0.03 1 16

2012 0.55 0.3 0.15 0 1 22

Firm20 2008 0.58 0.1 0.1 0.22 1 19

2009 0.6 0.12 0.13 0.15 1 9

2010 0.64 0.13 0.14 0.09 1 25

2011 0.66 0.15 0.16 0.03 1 23

2012 0.67 0.16 0.17 0 1 20

Firm21 2008 0.42 0.21 0.19 0.18 1 13

2009 0.45 0.23 0.2 0.12 1 23

2010 0.5 0.24 0.21 0.05 1 8

2011 0.51 0.26 0.22 0.01 1 15

2012 0.52 0.29 0.19 0 1 15

Firm22 2008 0.63 0.1 0.09 0.18 1 16

2009 0.62 0.16 0.11 0.11 1 18

2010 0.65 0.19 0.12 0.04 1 20

2011 0.67 0.2 0.13 0 1 21

62

2012 0.68 0.18 0.14 0 1 10

Firm23 2008 0.5 0.03 0.09 0.38 1 10

2009 0.55 0.06 0.11 0.28 1 14

2010 0.65 0.08 0.13 0.14 1 16

2011 0.7 0.11 0.14 0.05 1 18

2012 0.72 0.13 0.15 0 1 20

Firm24 2008 0.45 0.14 0.06 0.35 1 14

2009 0.53 0.16 0.1 0.21 1 11

2010 0.59 0.19 0.12 0.1 1 14

2011 0.61 0.2 0.13 0.06 1 17

2012 0.61 0.22 0.16 0.01 1 18