DETERMINANTS OF INVESTMENT IN REAL ESTATE IN KENYA
Real estate is a booming business currently in Kenya. Many investors ventures into the business with different motives. The rate at which Kenyans are shifting to real estate investment prompted me to research the determinants of investment in real estate. I sought to research microeconomic, macroeconomic, and other factors which drive investment in real estate. The real estate sector in Kenya is growing at a higher rate because of the belief that investment in real estate is worthwhile due to its expensive prices and continuous rental incomes (obong’o, nyakundi & mogwambo, 2016).
1.2 Background of the study
This study seeks to establish the determinants of investment in real estate in Kenya. Housing plays a vital role in revitalizing the growth of any country’s economy, with housing provision being the key indicators of development (Ireri 2010). Real estate is dominated by the private sector in the market outdoing what the government has done in the last decade. According to Brueggeman and Fisher (2005) real estate is defined as property consisting of land, minerals, buildings, water and natural resources that may be contained on the estate. The primary goal of any investor in real estate property development is to maximize profit in the shortest time possible (Muthama 2012).
Financial world experienced a turning point in the year 2008 according to (AMF, 2008). Real estate suffered from the decision made by the financial agent on the capital market involved in the united subprime crisis. The crises arose in the mid of 2007 which become clearer that the trade market performance prospects have been lower. The banks in America begun providing money supply to credit risk households with an aim of financing real estate acquisition.
Due to decline in the real estate business in united states of America, reports indicate that the unemployment misfortunes as well as declining buyer spending by 2009 have greatly influenced all land speculations classes negatively particularly retail properties. The land esteem in US tend to move in cycles thus reflecting the general economy. The joblessness rate increased while wage level diminished which led to increase in dispossession of the home loan advance. Properties emerged in the market but few people can bear the cost of the property.
Indian real estate is one of the most recognized sectors globally. It is projected to grow at 30% over the next decade. Real estate comprises of four sub sector that is commercial, retail, hospitality and housing. Real estate growth is attributed to the demand for office space and also urban and semi-urban accommodations. Construction industry is ranked among the 14 major sectors in terms of indirect, direct and induced effects (Kapila 2014).
According to Real Estate 2020 report, it highlights global trends and makes prediction on real estate industry in Africa. The report asserts that there is drive for growth in the real estate industry in Africa. According to World Bank, Africa is the continent with the youngest population. Therefore, Africa’s young population will drive demand for real estate. Her will be continued urbanization, an expansion of the current cities and rise of new cities.
In South Africa, real estate market size is projected to have an increase to US dollars 180 billion by the year 2020.Housing sector in South Africa contributes 5.6% of the country’s GDP. The market size of the housing sector is also expected to have an increase at annual growth rate of 11.2%. Apparently, real estate has emerged second active sector and raises US dollars 1.2 billion from private equity investors for the last 10 months (Norbert 2014).
Nigerian real estate sector is growing faster than the average G.D.P at a rate of 8.7% and is now the sixth largest sector in the economy. This has been achieved by a growing middle-class driving demand for a residential property, development and retail, industrial and commercial real estate development. The real estate market in Nigeria presents opportunities as well as number of specific risks for property investors.
The Kenyan market of real estate property are made up of all classes of property ranging from single house family to multi-house families, agricultural land, commercial land, go-down and warehouses, office space, retail shops and shopping complexes (masika, 2010).Compared to other industries, real estate industry undergoes constant evolution and the key driver of this evolution in commercial and residential properties are rural-urban migration in Kenya as well as global (kimani et al, 2016). Therefore, there are important factors that determine the investment in real estate in Kenya.
1.2.1 Economic growth
Economic growth has created a conducive environment for development of real estate investment. Housing plays a greater role in providing one of the basic needs to its population, that is shelter. Real estate is a crucial sector to a growth plan of the country especially in addressing ever increasing urban population resulting from among other factors rural-urban migration it contributes, lack of it may limit the growth of the economy (norman, 2011). Friedman hypothesis on income from real estate suggests that people are likely to change their desired consumptions if house prices influence their target life time wealth.
Investors shift their investment according to investment theory. Real estate risks is moderate, given that it offers better returns making hence investors will prefer investing this sector hence large population gets accommodation (Markowitz, 1958).
According to (Ho & wong, 2008) in Hong Kong suggested that there’s a direct relationship between economic growth and real estate investment as they were evaluating the impact of house prices on local demand found that housing market augment significantly to domestic demand.
Kenya’s economy according to IEA & IPAR (2000), has been erratic with the lowest being negative 0.8% recorded in 1992. However, kenya economy since year 2000 has not bleached sub-zero line. The highest GDP registered over two decades is 7.0% in the year 2007, unfortunately political events that took place in the country early months of 2008 following a contested general election, the country’s economy slumped to 1.5% in that year. Kenya recover ten years later, having recorded 5.8% growth as the highest since 2007. The economic growth has fluctuated at an average of 4.6% annually. The (Kenya national bureau of statistics, 2019) estimated the GDP growth to be 5.6%.
Prices-Analysts agree that asset prices are determined by the market, particularly by the supply and demand theory. Price theory states that, the most optimal market price for any good or service is the point at which the benefit gained from those who demand the entity meets the seller’s marginal cost. Aggregate demand is the total demand for goods and services in an economy at a given price. Higher prices decrease the demand for any particular good or service as they erode the purchasing power of disposable income and vice versa (Baumol & Blinder, 2011).
The relationship between the amount that the output firms are willing and able to supply and the prices of economy, determined in the long run by changes in patent laws, technology, conventions of the market place and others is known as aggregate supply (McEachern, 2011). Supply and demand guide the real estate prices.
Interest rates- An interest rate is the rate at which borrower pay interest for the use of money from the lender (Brigo & Mercurio, 2006). Trends in interest rates influence greatly on the affordability of houses as well as the demand for new houses and resales of homes. Borrowing becomes expensive when the rate of interest increases. This results in high mortgage repayments thus reducing the affordability and also the demand for property (Kgert and Mihaljek, 2007).
Inflation– Inflation plays a major role in real estate investment decision and it also influence the purchasing power of money. Consumers price index (CPI) is used to measure rate of inflation in an economy which detects the changes in retail prices of goods and services purchased by the household (Liow, Ibrahim and Huang, 2005). Inflation is categorized into two, the expected and unexpected inflation rate. The difference between actual and expected rate is known as unexpected inflation rate. Economic risk and a risk premium could be the genesis of unexpected inflation. Residential house prices in industrialized countries are affected by the inflation (Zhu, 2004).
1.2.2 Population
Population is the total number of persons inhabiting a country, city, or any district or area. Total demand for property is determined by population size and changes in the structure of the population caused by migration and long-term changes in the birth and death rates. Borowiecki (2009) indicated that residential house price changes were most sensitive to population growth in Switzerland housing economy. Another determinant is employment growth. Case and Shiller (1990) study showed that changes in employment levels were effective in predicting house prices in US.
1.3 Statement of the problem
Investment in real estate has been on the upsurge in Kenya mostly in urban areas. Kenya is attracting real investors due to its fast-growing GDP, secure financial returns, prime location for real estate investors and property market. The climate for investment in the country is strong with flowing in from markets in line with its economic blue print (Gatauwa & murunga, 2015).
The Kenyan government has envisioned its development blue print of 2030 to providing affordable housing for Kenyan citizens. Several strategies have been employed by the government in order to achieve its plans. These strategies include lower interest rate to facilitate uptake of credit which spurs private sector investment in the real estate, staff mortgage rates review as well as motivating the pension schemes to invest in the real estate. The prove the seriousness on how the sector is very important, the government has listed housing sector as among its big four agenda.
The expatriate’s number in Kenya has risen up recently due to international companies settling down in the country. This has led to increase in demand for residential real estate, with employees looking for accommodation near work (Knight Frank, 2015). The demand signals an environment for quick investments in large real estate developments. The population has also been on the increase which increases the demand for housing (World Bank, 2017).
Huge deficit in housing being experienced in Kenya is what is fueling growth in real estate sector. The urban population in Kenya is growing at an average rate of 4.2% resulting to a demand of about 250000 new housing units every year (Mutai, 2016). Due to the population of Kenya growing exponentially against the planned carrying capacity, mushrooming of slums within main estates or makeshift structures on public land for schools and hospitals or play grounds has recently been on the rise. Most of the estates are either crowded or unaffordable to most of the Kenyans. In these crowded estates, access to social facilities including access roads during emergencies is limited. Despite the increasing demand for public housing and increasing opportunities for investors to invest in residential real estates, real estate developers have been on the rise (Hass consult, 2016). Most estates in Kenya experience high demand for housing, while available units are unaffordable to most of its citizens especially the middle class seeking to own homes due to rising prices. It’s on this background that the current study sought to critique the effects of both micro and macro factors on investment in real estate in Kenya
Traditional economic theory assumes that people are rational agents who make their decision intentionally to take advantage of the opportunities available to the them. Investors always think of themselves as logical and rational. Most of the investors considers expected return from the investment and economic stability of the country before deciding to invest.
1.4 Purpose of the study
The purpose of the study is to investigate the determinants of investment in real estate in Kenya, a case of Housing finance corporation (HFC) and registered property companies in Nakuru.
1.5 objectives of the study
1.5.1 general objective
The general objective of this study is to determine the factors influencing investment in real estate in Kenya.
1.5.2 specific objective
The study sought to address the following specific objectives:
- To examine micro factors’ influence on investment in real estate in Kenya
- To determine the macro factors’ influence on growth of investment in real estate in Kenya.
- To obtain the challenges faced by investing in real estate in Kenya.
1.6 research question
The study is guided by the following research questions:
- What is the influence of micro factors on investment in real estate in Kenya?
- What is the influence of macro factors on investment in real estate in Kenya?
- What are the challenges facing investment in real estate in Kenya?
1.7 Justification for the study
The study will provide relevant knowledge and information that will help real estate developers, financial institution and real estate investors. In addition, the document will help Kenyan government particularly to come up with regulations and policies which will promote real estate enhancement. The study also, purposes to increase knowledge of the borrowers in real estate financing as well as providing an opportunity for borrowers to enlarge their portfolios and to unravel real estate tax loopholes that increase cashflows. The study also will help academician and researchers
1.7.1 To investors
The investors of the real estate will benefit from the information provided from the research that can be used to make decision. The investment advisors and financiers will get equipped with findings so as to offer more informed quality advise to the investors. In addition, the findings of the research will enable the investors comprehend the trends in housing both in short and long run.
The results will help investors understand other factors that influence the real estate investment for instance corruption, political instability and the natural catastrophe within Kenyan soil.
1.7.2 To researcher
The study will add more information to the knowledge body on the determinants of the real estate investment in Kenya. The other benefit is that academician and researchers conducting studies on real estate investment will get information as a literature review.
1.7.3 to policy makers and regulators
The government and regulatory bodies benefit from the study by creating awareness on the factors influencing investment in real estate. Such factors include financial factors (taxation, interest rate, inflation, credit uptake, mortgage), economic factors (demand and supply, GDP, direct foreign investment) and other factors (political, corruption, insecurity natural calamity) hence formulate appropriate regulatory framework for enhancing the real estate industry.
1.8 scope of the study
This study will be conducted at housing financing corporation (HFC) Nakuru county because HFC is a non-banking financial company which engages in the principal business of financing acquisition or houses construction which includes developing plots of land for construction of new houses
1.9 limitation of the study
Financial constraint– inadequate fund impedes the researcher’s efficiency when sourcing for the relevant materials, literature or information as well as data collection process for instance interview, internet and questionnaire.
Time constraint-the researcher sacrifices his time by engaging simultaneously in this study with other academic work. As a result of this the researcher will have to cut down on the time devoted for research activity.
The data that will be obtained from HFC may not be accurate because it is only one institution
1.10 assumption of the study
There is a negative perception about real estate. Public tend to assume that real estate is costly hence many fears to venture into the business. The perception has led the mighty and financial stable individuals undertake the business of real estate. Therefore, have put into consideration the facts that anyone can invest in real estate regardless of the financial status if a good plan is made as well as the investor is determined.
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
This chapter explains the findings by various researchers on the determinants of investment in real estate. The chapter begins with a theoretical review, then empirical review, the research gap and finally conceptual framework. The theoretical review presents related theories to the determinants of investment in real estate while empirical review presents a review of studies done on the determinants of investment in real estate. The research gap indicates diverse gaps in the empirical literature while the conceptual framework presents the hypothesized relations between independent and dependent variable.
2.2 General overview of literature
Real estate being an immovable permanently fixed asset to one location includes land as well as anything that exists on the land (Badmus, Yusuff & Alli, 2017). Real estate refers to land and physical property or improvements that are fixed to the land which includes landscaping, buildings fencing, houses wells, mining right under the land. Residential lots as well as vacant land and the houses, decks, outbuildings, fixtures within the boundaries of the property are all real estates. Also, mobile houses, modern construction method and technology are part of real estate. Real estate from the time immemorial has proved to an excellent profit source through the increase in the value of the property over time (Finnih, 2017). Real estate is a basic need for an individual, corporate, family and government. population increase, production increase, quality increase in living will directly correlate to the demand.
Real estate has classification known as land uses. It can be commercial, industrial, residential, office, hospitality, recreation, sports, shopping mall, medical, education, transportation, rural, urban etc (Oyedele, 2018). Generally, investors tend in real estate with an aim of generating higher rate of returns on investment. Yield is what determines the rate of return on investment because it is an important way of gauging income on an investment in future. Property yield is essential in real estate investment as growth rate of capital are not the same for the similar investment amount on different land uses in the similar property market. what matters in real estate investment is the return that one will obtain in the future.
Real estate in Kenya is unprofessional, unorganized as well as underfunded (Agbola & Olatubar, 2003). That is why many projects have been abandoned and collapses of building. Real estate sector has higher deficit in Kenya and that is why the government is encouraging private developers to venture into the business (national housing corporation 2019).
The products of real estate in Kenya are expensive as well as unaffordable by majority of the residents. The average price of constructing single room is between ksh.500000 and ksh.550000 depending on labor, finishing and location. The average wage per month in Kenya is Ksh. 15000. Therefore, the minimum wage earner will take average of 12 years saving in order to buy a house. That is the reason why most Kenyans believe that real estate investment is for the rich and therefore unaffordable to an ordinary man. What drives the investment in real estate in Kenya is demand and supply. The higher demand for a kind of house in a particular location with no proportional increase in supply, the cost of the house will rise and when the supply increases without the corresponding demand, the cost or prices declines.
In Kenya, people tend to think that industrial, office and commercial land use will yield higher than residential or recreational land uses. The assumption may not be true because real estate markets and real estate products are different. Investors consider the payback periods analysis of yields and valuation before settling on a particular type of real estate. The investors always use SWOT, SMART & PESTLES analysis when considering risk analysis. Economic environment, political environment, social environment, legal environment, technological environment, physical environment or location of investment as well as safety and security must be analyzed before investing in real estate.
The investors consider SWOT (strength, weaknesses, opportunities, and threats). Also, the project must be SMART (specific, measurable, achievable, reviewable and timely). The factor considered majorly before making decision is the property location. In addition, there are features or iconic that attract value of properties. For instance, industrial area location, city Centre, office hub, recreational parks, schools, police stations and market sparks appreciation rate of investment properties. Infrastructure provision such as tarmac roads security, electricity, piped water parks, convenient shopping centers are also factors believed to boost yield of an area. Also, sanitation systems, bus station, land fill and cemetery existence attract investment while environmental hazards discourage investors.
There’s a pattern that real estate development follows called model. In Kenya, development takes place along the road especially tarmacked roads in outskirts of cities. Development of Real estate can be concentric circle as stated by (burgess, 1925). The model proposes that city zones extends outward by highways and railroads.
The available type as well as infrastructures in an area determines the appreciation rate of real estate in the area. Security plays an important role in procurement of real estate in cities, towns and sustainable houses. Innovation and new development in real estate is slow in the industry because of long gestation period.
2.7 Theoretical framework
There are several theories explaining the factors influencing investment in real estate. Publications and books regarding the investment in real estate are abundant and some related topics appears in more than one document.
Tobin’s q theory
According to this Tobin’s q theory, the expected future rise in income results in an increase in the current consumption. The comparable analysis in real estate is that growth in housing demand leads to home buyers’ willingness to give money for the increased prices which give rise to marginal return in real estate investment making it more attractive for investors. This insinuates that as the real estate prices increases, investment in the sector will increase leading to an increased supply of units in the market. The investors ability as well as willingness to pay higher prices is motivated by the future expected income or if there is a rise in the number of potential home owners demanding for housing which ultimately increase house prices. As a result, the increase in demand for real estates is triggered by expected future increase in income. Therefore, an increase in real estate prices will push up investment in the housing sector. Tobin’s theory highlights the concept of user cost which is essential in analyzing determinants of investment in real estate. This concept causes swings in the demand curve for real estate prices. The theory explains that the cost of purchasing a house decreases as the interest rate on mortgage declines thus increasing the ability of a home owners to buy bigger real estate property. This suggests that mortgage rate reduction leads to increase in the demand real estate property, in addition, increases comparative higher prices demand as well as increased investment in real estate market. The backbone of this is that it relies majorly on the future anticipated income hence triggers the increase in the price of houses as well as increased investment in residential. This theory captures the significance of investment in real estate, lending rates, GDP and other macro factors in the real estate market.
A theory advanced by stahl, (1985) is used in micro factors analysis which is closely related to Tobin q theory. It explains in detail the user cost element by taking the expected rate of change in the real capital assets price. In context of real estate, the expected change rate in the housing price can be influential in the shifts in demand for housing. If potential home owners anticipate rice in prices at the real estate, the user cost goes down, leading to an increased demand. The housing prices will go up while investment in the real estate sector will also increase. If the investors expect the real estate investment to be good, then there will be an increase in building materials demand as well as land demand for new dwellings thus, triggering the prices of real property to rise rapidly which increases the number of properties in the real estate market.
Financial constraint influences the real estate demand according to this. The lenders play critical role of easing credit availability as well as credit uptake, which can enable afford to own property without undergoing financial constraints. This implies that financial capacity of a country increases the real estate demand, a higher price in real estate property and increased investment in real estate. From this theory, changes in the user cost triggers the growth in the residential estate prices caused by expectations and elimination of constraints in the financial market. earlier studies indicate that the real estate functions well as theorized by the Tobin q. the supply for real property stock responds to the demand for real properties in the market. (Githae, 2017) while utilizing Tobin q theory found that growth in housing prices can be attributed to increase in expected future income and increase in construction cost Similarly, Kaijser (2014) found a positive relationship between housing investment and Tobin q in the long run but not explained in the short run.
2.7.1 The Economic Theory of Demand and Supply
Studies carried out by (Tsatsaronis &Zhu, 2004)and (Hou, 2010), based on the premise which explains that, the interaction of the market forces in an uncontrolled economy, demand and supply determines the price at which properties ought be exchanged from one hand of the housing price divide by the factors of demand which include employment, interest rates, population growth, household income, household formation, income tax policy as well as renting house cost while the supply factors are cost of construction which include land cost, material cost, labor cost and the investment in the existing premise (Tsatsaronis&Zhu, 2004).
(Tsatsaronis&Zhu, 2004), stated that the factors of demand and supply that are driving the real estate prices have a shorter-term influence or a long-term influence. The factors that influence housing demand over a long period are growth in disposable income of household, tax system features that encourages home ownership compared to other ways of accumulating wealth, gradual shift in population and the interest rate average level. The real estate stock is restrained from growth in short run due to a number of factors such as planning length and construction phases as well as the land planning schemes inertia.
Land availability for residential housing affects house prices which constrains the supply responsiveness. Zoning rules, slow administrative procedures, building regulations that cumbersome restricts the amount of developable land thus affects the delivery speed of the housing units on supply side (Girouard et al., 2006). In addition, the sudden rise in interest rate increases cost of housing which results to lower demand for housing, house price growth slows which may lead to decline in house price (Himmelberg, Mayer &Sinai, 2005). The interplay between these fundamental factors of demand and supply settle at an equilibrium price.
This theory is crucial in this study because it addresses theoretical population variable on the demand side as well as construction costs variable on the supply side.
2.7.2 Malthusian Theory of population
This theory was developed by Thomas Robert Malthus which states that human population grow in exponential manner for instance, the population doubles in each cycle as opposed to production of food that grows in arithmetic rate for instances, food production grows in a repeated addition of a uniform increment in each uniform interval of time. Food output may likely to increase in a series of twenty year intervals in the arithmetic progression 1,2,3,4,5,and so on, while population has ability to increase in in the geometric progress in such as 1,2,4,8,16… this arithmetic food growth scenario together with geometric human population projects a future of population when no more resources to survive on (Weil and Wilde, 2010).
This theory is clearly depicting on what will happen when the population grows exponentially particularly in urban areas proving that house supply will be short thus push prices of housing higher.
2.7.3 The trade-off model
The assumption of this model is that growth in income influences the willingness rate among families to substitute for less expensive land from time to time. (Muth, 1959) stated that trade off model explains the predominance of quality real estate investment in the city environs as a tradeoff the access to central location and households space demand. There are two aspects in this model, that is travel cost versus space as well as tradeoffs in the multiple nucleus city.
Space versus travel cost theory explicates that when the distance to workplace is low the household is ready to pay maximum costs in terms of rent (Balchin, Bull & Kieve, 1995). This theory implies that the rich will always live closer to the central business district while the poor live in the cheaper outer regions of the city. The opposite is however true, with lower income houses living close to the places of work as they seek to minimize their transport expenses. These areas will thus be more densely populated. The rich will seek to move out of congested areas as the income grows. The rich relocates to expensive affluent property in the outer regions of the city. (Balchin and Kieve,1982) found out that this theory is valid to some point. As individuals moves distant from the central business district, the value of residential properties tend to decrease since land further away has lower business use. According to (Blair,1995) alludes to there being an optimum location. This arises due to the opportunity cost of commuting. Households tends to move from point A to point B as they seek cheaper and spacious land given the income rising. The theory is limited in that it does not explain residential locations preferences in areas with multiple central business districts and areas where the distribution of income is not localized. Due to inability to explain the preferences in areas with multiple districts, Blair sought to refine the model further to provide for the Multiple Nuclear City. Development in infrastructure in the multiple Nuclear cities in Kenya has led CBD cease being the key access point in most cities. Thus, the assumption of lower transport costs to the CBD may cease to hold for many households with these new job distributions. As such, there may even be instances where cost of residential real estate near the CBD may come down. There have been developments in the recent past and locations other than the central business district have become very prevalent for commercial uses.
According to Evans (1985) states that increase in income levels, the households with higher income outbids the households with lower income regardless of the location whether it is near or far from the CBD because of their higher purchasing power. The higher income households are also indifferent about location as they can readily pay the higher transport as well as higher housing costs. Highways have also decreased transport costs by making locations far away from the CBD more accessible than some areas closer to the CBD (Balchin, Bull & Kieve, 1995).
The filtering down theory
This theory was developed by Wilbur Thompson in the year 1968 (Thompson, 1968). This theory sought to explicate how social economic groups end up occupying a certain neighborhood. Burgess become the first to forward this theory while he was carrying out a study in Chicago. He noted that as the higher income households left homes near the city Centre for housing units further away, the vacated housing units were usually occupied by lower income households. Since a housing unit has a relatively long useful life, it is possible that it will be used by several households over this time. Over the years, the house will be passed down to households with lower income levels (Mills & Hamilton, 1994). This can be explained by the fact that when incomes rise, the demand for housing also rises. People will satisfy this demand by buying newly constructed houses. This new house will usually be located further away from the commercial Centre since that is where land will be available. In Kenya, there are several estates or neighborhoods that moved from higher-income to lower-income households over the years. But as the years have moved, these areas are being occupied by the upper- middle class as new affluent neighborhoods. Thus, as per the theory the returns of a house will change over time both in terms of rent and capital gains.
2.3 Review literature based on objective one
This section will discuss prior literature on the micro economic factors in the real estate investment. prior studies reveal that the drivers of the real estate investment include infrastructure, location and building characteristics.
Infrastructural facilities
Infrastructure is referred to a basic facilities and services that allow for effective functioning of the society such as communication system, roads, water, post offices, schools and sewage treatment power lines among others. According to Ajibola, Awodiran and Salu-Kosoko (2013) from the study conducted on the impact of infrastructure on real estate property cost in unity estate in Lagos. The study showed that social amenities such as electricity, roads, water are ranked as the most essential infrastructural facilities facilitating the effective functioning of an estate. Study conducted by (Gatauwa and Murungi, 2015) on the infrastructure development and real estate values in Meru County. The study revealed that basic facilities that may lead to higher residential property values include improved social amenities, good road network, improved educational systems, presence of commercial centers and industries. The provision of these infrastructural facilities is considered to be the drivers of demand and changes in real estate prices.
Adebayo (2012) conducted a study and revealed that infrastructural facilities are one of determinants of the returns on real estate investment, the consideration of which leads to high property values and its absence affects neighborhood prices and causes dissatisfaction among residents. Capital investment on infrastructure development is a key driver that may reduce the production and labor costs, leading to high profitability, increased output level, employment which in turn effects on the economic growth across the African continent hence leading to improved living standards reducing poverty index.
A well-established transport network is among the infrastructural facilities that attracts higher property values ensuring a positive net of return on investment in real estate investment (Heise, 2009). Due to development projects in today’s mobile society like the development of the bypasses and the primary linkages are highways. In selecting real estate property, most individual’s essential determinant that influences the selection of a property initially included the neighborhood environment, job accessibility, ease of access to shopping malls and recreational centers and proximity to other social amenities basis (Olujimi & Bello, 2014). In this study, Olujimi and Bello (2014) found that infrastructural facilities played a very crucial role in the determination of rental values by contribution of 30.50% of the decision-making process in choosing a residential real estate in Lagos. Security measures such installation of a burglary proof in all windows and provision of wall-fence round the building were to be very important when selecting a residential estate. Other determinants that influences rental values include, watch day-security, water supply, drainage channel and refuse disposal services and watch night security services. The variables for electricity, kitchen and access road had no significant relationship with the determination of rental values.
The degree of provision of infrastructural facilities may vary from one location to the other and from building to building. The expansion of the highway system has had a great effect on regional, national, and local economies in ensuring lesser travelling time and travelling costs. Past studies done suggest that transport networks and quality of the environment, characteristics of the surrounding neighborhood are crucial determinants of residential property prices and rental values. (Boucq and Stratec, 2011) conducted a study on the influence of rail transport infrastructure on property prices in France established that development of infrastructure leads to property gains in the long run. However, the improvement of transport network can also lead to a decrease in the values of properties and rent if the accessibility of the properties adjacent to the roads network is made easier. In the United Kingdom (UK), John (2006) investigated the impact of new transport infrastructure on property values in the South Yorkshire. Findings from the study reveal that anticipation of the construction of a super tram led to an increase in residential buildings leading to an increase in return on investment. Social amenities also influence return in investment in residential buildings. Gallimore, Fletcher and Carter (2011) proposes considerations that a residential property user may be prepared to pay for a high value comparative to another. Facilities such as accessibility to job, shopping malls, water and electricity supply. Nubi (2003) found that social amenities affect occupancy and returns on investment in residential buildings. These social amenities consist of real estate investment, basic facilities such as pipe-borne water and electricity, waste disposal, drainage systems, roads networks, educational facilities, sewer lines, health facilities, institutional structures such as police post and communications systems, post office, fire brigades and banking halls. The value of real estate is derived from its utility by the users, and it has therefore no value if it is not effectively demanded or scarce. It therefore has significance only if it fulfills its intended purpose of satisfying the user’s needs and desires. According to Kuye (2002) reveals that it is a man’s collective desire and determination to own property that gives rise to value. The capacity of a property to fulfill a man’s needs and desires together with its degree of scarcity and utility compared with others makes man to ascribe value to it. Another factor influencing return in investment and occupancy in residential buildings is education infrastructure (Omboi, 2011). Though the relationship between public schools and property values may not be directly ascertained, several studies argue that quality of school has a positive and a direct relationship with house prices. Barrow and Rouse (2012) found that, holding other factors constant, houses in locations with good quality schools have higher prices compared to the ones located near average or poor performing schools. Gatauwa and Murungi (2015) study similarly like the above studies found that the factors that lead to higher property prices in the real estate sector include developed social amenities, enhanced transport networks, industries, commercial center, and expanded educational institutions
Locational factors
Real estate is property that is uniquely different made up of land and buildings occupying a geographically distinct location on the earth’s surface. However, because of its fixed location, properties have the same common external influences. (Barry and Rodriguez, 2004), reveals that in the real estate industry, there are three important value determinants. These determinants are “location, location, and location.” Visibly, this is so redundant and not illustrating it. Beside population, economical factors and financial factors, there are other factors which determines investment in real estate such determinants are corruption, politics and security. Basically, identical residential properties located in different neighborhoods can have vastly different prices (Adebayo, 2006).
According to (Barrett and Blair, 2001) reveals that the location aspects have indirect economic factors that determines the demand and supply of real estate investment. These determinants include geographical factors such as zoning and ground condition, topography, accessibility, utilities, neighborhood, traffic, parking, proximity to social amenities, transportation linkage and traffic, impact on government services, socio economic level and environmental impact. These locational factors determine residential property prices and are constraints to be overcome in the real estate market. These indirect economic factors are therefore the essential factors in the development market and the most critical factors in the real estate investment markets In the United Kingdom, (Svets, 2010) reveal that apart from the demand for the attributes of the dwelling units themselves influences real estate prices, the area in which the properties are located plays a very critical role selecting a type of a real properties. Accessibility of a location is a relationship between the time and distance taken to access linkages to transportation networks, other neighborhoods and social amenities Harold and Leonard (2005) propose that locations further away may have more attractive features and amenities, despite their higher commuting cost and time. Frequently, most properties in a neighborhood have the same or highly similar locational relationships with common origins and destination.
The neighborhood is influenced by the neighboring community. Different areas respond to its own local demands for urban space (John, 2006). In his study most urban areas include high end and upper income households who tend to live further away from the CBD, while lower income families continue prefer to live closer to the CBD’s nearer to employment centers. Those who use public transportation or those who prefer not to use their cars during working days are very keen on distance to CBD compared to those who own cars (Gallimore, Fletcher & Carter, 2011). Accessibility to shopping malls, schools, sports facilities, distance from public transportation are considerations taken by those who are to serve by their availability. Notably, urban apartment inhabitants prefer to be within convenient walking distance to public transportation to minimize on travelling cost and time. On the other hand, inflation, interest rate and profitability, are also important factors in determining general level of value at any given point in time. Households categorize themselves in terms of their tastes and preferences, income levels, social and economic activities and beliefs (Boucq & Stratec, 2011). Consequently, the factors such as their age, education and income levels, size of household availability and cost of borrowing must be assimilated in affecting the types of housing and the values. The above average income earners will hunt for a part of the city that offers leisure facilities, social amenities, parks and convenient form of public transportation and infrastructure (Green, 2005). This shows that the proximate and relevant influences on the property are related to the same influences operating on other properties in the neighborhood.
Building characteristics
According to (Ajilowo, Olujimi and Bello, 2009) their study on the effects of infrastructural facilities on the rental values of residential property in Nigeria reveals that rental values of residential real estate were significantly determined by infrastructural facilities. The study found that the installation of boundary walls, a burglary proof windows and the provision of wall-fence round the real estate property played a significant role in pricing of the investment. The fundamental infrastructural facilities available in the residential property include electricity, water supply, road access, drainage channel, refuse disposable facility, security factors such as alarms internal fittings like sanitary and electrical fittings, spacious windows, burglary proofing windows and doors, joinery works, floor and wall finish and kitchen fittings.
A study contacted in Malaysia, Isa et al. (2014) on green attributes affecting investment returns for green buildings reveals that green real estate investment strategy provides a new investment option to property investors with more leverage compared to traditional approaches. The ecofriendly and cheap materials used in green buildings are progressively replacing the conventional buildings. This can be attributed to the fact that green building provides high occupancy, higher rents high appraisal values, cost savings lower utility costs. The impacts of energy and water efficiency have the potential to generate a positive economic effects and sustainable site planning management. Barry and Rodriguez (2004) conducted a study on the effects of building characteristics on return in investment in Residential Real Estates in India. The study used a cross-sectional study design and the target population was real estate developers. They found that the building characteristic’s such as security, cleanliness, layout, interior and exterior design had a significant influence on occupancy rate and hence return in investment.
Building cost
Building cost is amount paid which include, site overheads, labour, materials, land, finance cost, equipment or plants, professional fees, head office cost, profit and statutory fees approval of building plans. These costs and construction cost overrun are well documented according to (Mbachu and Nkado, 2004). Cost overrun has an impact on project budget and final price of the real estate property. The developer will realize less return on investment while the end user will have to pay more on rent or buying price. Akanni et al. (2014) conducted a study on implication of rising in the building materials cost, the study revealed that the high building materials cost affects the final price of the building including rental income. Exchange rate, power cost and fuel supply, legislation variation and government policies are factors affecting the rising cost of building materials. In addition, variation in development cost determines the cost of building since it can result in scheme abandonment and reduction in volume of building production.
2.4 Review literature based on objective two
2.4.1 Real estate investment and macro-economic factors
According to (romkaew, 2014) conducted a study which revealed that there’s a direct association between the economic situation, real estate industry and the general economic activity of the nation. The significant economic indicators are building and construction activities, real wage and per capita income GDP, unemployment rate, personal savings and investments. A study by (Barrett and Blair 2001) revealed that its possible to split the economic factors depending on their origin or impact into the demand and supply sides of the economy. Population and source of occupation, community income and distribution are the demand side of the economy. Competitive environment, the current and intended amount of supply in properties are the supply side.
A study conducted by (Yang et al., 2014) revealed that returns in global property markets are profoundly correlated with the fundamental economic variables such as economic growth, GDP and inflation while study conducted by Ling and Naranjo (2003) reveals that unexpected inflations, real interest rate, term structure of interest rate and growth in consumption as regular determinants of real estate returns. (Hekman, 2001) revealed that GDP have great effects on prices and returns of real estate market while unemployment rate had no significant effect on returns. comparably, unemployment rate was found had no significant impact on returns in real estate.
A study conducted by (Kofoed-Pihl, 2003) on the macroeconomic determinants of United States Commercial Real Estate returns reveals that long term interest rate and unemployment had a negative influence on returns in US real estate market while the GDP influences returns positively over time. The outcome of the study reveals that inflation had a weak relationship with returns on investment. According to (Barrett and Blair, 2001) revealed that real estate industry has a strong relationship with inflation. Compared to other assets that have higher depreciation rate, property tends to rise in prices because of the firm re-sale market. The rate at which property prices increases is greater than the general increase in price level. The expectation of future inflation is just as essential as inflation, with the investors ready to buy properties which has low rates of return with future expectation of inflation in order to gain from capital appreciation and rental growth. Changes in interest rates tend to affect growth in a country’s economy with the real estate market being greatly impacted by changes in the interest rate term structure. Investors intensifies the borrowing cost because of the rising interest rate which will in turn discourage investment due to less disposable income. High interest rates slow down the economy hence reducing the demand for new homes uptake as well as the supply of new housing units in the market. Material and labor costs consort that a high interest rates causes the construction costs rise due to developers get funding from banks to build. Both demand and supply of property markets are greatly affected by the interest rates. A study by (Wofford, 2002) illuminates how property taxes tremendously affects individual’s ability to make decisions on the property ownership as well as the types and timing of development. Taxation changes influences properties reducing future revenues expected from capital appreciation, which investors could expect from selling them in the future. Investors can take the changes in property taxes into account by changing the assessment value of a house to establish a higher value of the same property. This will help in deciding how much to pay so as to capitalize those taxes into the values of properties. Therefore, the economic factors affect generally the performance of property markets.
A study conducted in Kenya by (Nzalu, 2013) evaluating the determinants of real estate investment reveals that, GDP growth, interest rate variation, as well as growth in inflation are significant determinants of real estate returns. A study by (karoki,2013) to assess the determinants of real estate prices in Kenya, revealed that there exist a positive relationships interest rates as well as with GDP and negative significant relationship between residential real estate prices and level of money supply. The study revealed that interest rates have greater influence on property prices, then GDP as well as level of money supply. Macro-economic variables explain growth in real properties price. Despite the study revealed a direct positive relationship between residential real estate prices and inflation rates, the relationship was found to be weak. The movement in house prices indicate a general rise in property prices over time hence the trend is expected to continue. Even without significant changes in the variables, the result of time is that house prices go up. in addition, this indicates that the real estate market is significantly stable.
Karoki (2013) conducted a study on the determinants of residential real estate prices in Kenya using data collected from publications in financial institutions and the government including monthly secondary data for a period of eight years spanning from 2005 to 2012. The study revealed that there are positive relationships with GDP, significant negative relationship between residential real estate prices and interest rates and level of money supply. The results show that Interest rates have the most significant impact on real estate properties, then GDP together with the level of money supply. The limitations of the study are that macroeconomic determinants only were used in analysis hence it did not show the influence of location. This finding contradicts the study conducted by (Ochuodho, 2011) who deliberately dropped the GDP and Inflation rate Variable from the model as an indication that they are among the significant economic fundamentals that support residential house prices. From his findings, a positive relationship existed between house prices and inflation implying an increase in rate of inflation will have a positive impact on house prices. According to (Kibunyi, 2015) conducted a study on the determinants of the investment in Kenya. The findings indicate that there is a positive relationship between house prices with diaspora remittance, GDP, lending rates, construction cost as well as loans to real estate sector. Inflation had a negative relationship with house prices. The cointegration tests results indicated unstable relationships for diaspora remittances and building costs while GDP and NSE index had a stable long-run relationship with house prices. The results show higher orders of integration using fractional integration, for the house price series compared with the other variables, though the study is indifferent about the existence of a house price bubble. No causal relationships between investment and diaspora remittances from granger causality tests. However, two-way causalities between house prices and GDPNSE Index and building cost.
Demographics are the population data that describes race, gender, migration patterns, age and population growth composition. The growth of population puts pressure on housing demand and hence push prices up.
(Taltavull, 2003), explained that population growth has strong significance in the rise of house price.
The population is among the determinants of real estate investment, Gabriel et al. (1999) migration of people to urban plays role in explaining difference in house prices and house price dynamics across nation. Study carried out by Gabriel found out that net migration is a major factor in the performance of urban centers. Capozza et al. (2004) recognized the importance of relative economic performance, finding that faster growth in both population and real income is associated with more serial correlation in real estate investment. In the past ten years, Kenya has experienced significant migration to urban because of marketization, industrialization, urbanization (Tunon, 2006).
Internal migration is considered as an influential factor of real estate investment in cities via its influence on urban population growth (Chen and Guo, 2010). In addition, the study found that there is a positive relationship between population and housing. According to Zheng and Kahn (2010), population has a positive effect on housing price among cities. A larger population should generate a higher housing demand which will increase housing price.
Government regulation
Real estate in Kenya is governed by the enacted by laws from both the national government and county government which are efficient. Both governments have issued rules and regulations on the choice of materials to be used in the construction. Rules of building or codes always specify the material type, material quality, space size, tolerance level and class of services. (Gichunge, 2001) conducted a study and revealed that building codes provide no specifications for the local materials but it covers only the conventional materials. The authorities sometimes come up with a stringent by laws that can make the users of the building suffer due to building material cost that are unaffordable hence no consideration of whether the investment will be viable or not. According to (Keivani & Werna, 2011) study reveals that County governments have a guide developed for use by Physical Planning Department before granting any approval and construction of buildings. Ground coverage, the zone, area covered, minimum area in hectares allowed, plot ratio and type of development. Reviews are being made regularly on building rules to allow for more development. Also, the building regulation determines the building material cost and the specific types of buildings in an area to be put up. The National Construction Authority approves the enacted regulations (Ambreena, 2014).
Challenges facing real estate investments sector
Several challenges like increased supply and competition, inadequate and the high cost of funds, together with the lack of affordable land in the past years are being faced by the real estate investors. 2019 annual market report from Cytonn Investments indicate that mortgages had reduced due to the interest-rate capping, with the number of active accounts dropping at the end of December. There’s a decline in real estate investment despite the interest rates capping, financial institutions are becoming risk averse to avail funds.
Kenya bankers association (KBA) on available house price index indicates that Kenya was faced by a number of challenges in year 2018. The developers and private sectors are struggling to sell properties at the initially projected prices due to slowed down market. There is scarcity of the land to develop hence its cost of development become high. According to (cytonn, 2018) study reveals that land prices have grown by a six-year compound annual growth rate of 17.4 per cent on average. A study conducted by (Danny,2012) reveals that that unemployment was a major challenge in real estate development as one cannot afford to own a property without a source of income. (Vontello and Williamson, 2001) reveals that real estate investment requires large amount of capital which worsens during economic crisis where and employment level stagnates, borrowing cost increases as well as purchasing power declines.
The building cost and return in investment are influenced government policies such as digitization of the lands ministry, fifty percent off on corporate taxes for any developer producing over one hundred affordable residential properties annually, Innovative financing solutions such as Mortgage Liquidity Facility (MLF) for instance the National Housing Development Fund (NHDF), the Kenyan Mortgage Refinancing Company (KMRC), the National Housing Development Fund (NHDF). In addition, taxation policies such as 10% withholding tax of the rental income is among the government policies which influences the cost of building and the return in investment in Kenya.
According to KNBS statistics, the household disposable income in Kenya has been on rise. This indication shows that households spends more on basic needs such as shelter. The emerging evidence indicates that since the introduction of interest rate capping, the commercial banks have shifted their interest to large corporate borrowers and the government with aim of avoiding risky borrowers. Despite the GDP being on rise, the effects on growth has also begun to suffice. According to (comptrollers’, 1998) found out that initially high interest rates were perceived by investors as the major challenge in real estate development which implies that the borrowing cost is a barrier to potential developers and investors. High interest rates lower the market liquidity of real estate by enhancing the attractiveness of other alternative investments. Real estate market in Kenya operates in cycle similar to other market which starts after general election and end with the following general elections. A study conducted by (Gichunge, 2015) reveals that 2017 elections impacted real estate in that it slowdown in uptake of real properties leading to drop in prices. The implications of this is that the market had been influenced by the political uncertainty that was there. Kenya industrial base dwindle due to harsh operating environment which caused the Kenya industrial base. Underdeveloped transport infrastructure, corruption, power unreliability and land crisis are factors that have contributed heavily to challenges facing real estate investment.
Research gap
A review of literature established that majority of factors influencing house prices studies have concentrated on developed economies with less focus in developing economies such as Kenya. Moreover, findings from literature show that housing prices studies at different timings produced contradictory results. As a result, the current study aimed at assessing the influence of macro and micro factors on housing prices. A review of literature has established that most studies on housing prices have focused on the influence of macro factors on house prices. The current study extended the analysis of both the micro and macro factors. The micro and macro factors were from previous studies. Additionally, methodologies in data analysis differed as most studies employed VAR model to establish relationship between independent and dependent variables. The current study used the VEC model to establish both long and short run effects of macro variables on growth in house prices. Previous studies that analyzed micro factors mostly did a primary data collection while the current study used secondary data and did a stepwise regression. The current study also captures shocks experienced in the economy during and after regime change at the ballot as captured in time series data beyond 2014 contrary to most studies done. Lastly, the current study sought to desegregate the different segment in residential real estate market by income levels while previous study generalized findings across the housing market.
conceptual framework
The conceptual framework gives an idea of the association between the variables informing the investigations and helping achieving the goals. In this study, the dependent variable is investment in real estate and independent variables include lending rates, inflation, GDP, foreign exchange, total remittance, construction cost and prices are macro-economic factors. Government policies, building cost, building characteristics and location are micro economic factors. Corruption, security and politics are other factors that determines the investment in real estate. This study seeks to analyze how the independent variables relate with the dependent variable.
Modermmmmm
2.8.1Operationalization of variables
This section describes how the researcher will measure the independent variables which include financial factors (mortgage loan), economic factors (inflation rate, interest rate and infrastructure) and other factors (political influence, corruption and government policies). The dependent variables are real estate investment.
2.7.1 Micro factors
Location is vital when making decision on investment. Location refers to particular position or area a property is situated. Proximity and accessibility are sometimes used interchangeably (Fanning and Stephen, 1994). Land economies pioneers view distance as the locational heart analysis. There are attributes identified by the scholar (segal, 1997) when assessing the desirability of a real estate investment location, such are the virtual features of a neighborhood such as infrastructures, residential buildings, socio economic activities of the people living in the neighborhood, public services like the quality of schools, roads and recreational facilities. It also includes the quality of the environment and ease of access to the neighborhood. According to (Pollakowski, 2016) reveals that real estate investment are determined by accessibility properties and neighborhood attributes of the location. Environmental factors such as amenities, parks, locality, as well as levels of neighborhood security are considered. According to (Amatete, 2016) measured location in terms of accessibility from the main roads (distance and type of roads), availability of social amenities (water, electricity, police station of police post, churches and schools), physical neighborhood environment (surrounding buildings and infrastructure) and income level of people living in the area. Primary data was obtained by administering questionnaires to real estate agents, managers, and developers. Building characteristics involves general building characteristics such as the age of a building, the floor space and total occupants found in a building. It can also refer to occupancy level which is the rate at which a building is occupied in a given period. Other scholars look at level of distribution of floors whether they are below or above grade and the usage of floor spaces. Characteristics of the site also constitute to building characteristics such the topology where it is situated. The external attributes such exterior walls and other facilities such generators, solar heaters, bore holes are part of the building characteristics. It also constitutes suitable architectural designs, quality of finishes Neighborhood refers to the physical area surrounding a building. It could also refer to the style of architecture of houses that stand out like the roof types, sizes of the houses and many more.
2.7.2 Macro factors
GDP, interest rate, as well as Inflation rate from the previous studies are the macro economic factors (Ouma, 2011), (Karoki, 2013), (Kibunyi, 2015). The cost of borrowed fund is known as interest rate. Interest rate is the payment for the risks involved in lending as well as the expense of the current spending power (Mudida, 2009). GDP refers to the measure of the total value of domestic production for the entire domestic economy.
Inflation rate is the increase in the market prices which erodes purchasing cost of a typical consumer over time. Inflation increase level in general prices. Gross domestic product and inflation rate is the obstinate rise in general price levels of goods and services as a result of high costs of production costs (cost-push), and the demand-pull which takes place when the aggregate supply is persistently exceeded by the aggregate demand at the current prices (Mudida, 2009) employment rate for the last five years. Inflation and interest data are obtained from Central Bank of Kenya on quarterly basis. Diaspora remittance are funds by nationals of a country generated in other countries. Recently, diaspora remittance has been on the leading to their recognition as an important contributor to the country’s growth and development. According to study by (Andrews 2010) reveals that there is a relationship between real estate investment and interest rate. A study by (Kibunyi, 2015) reveals that there is a positive relationship between real estate investment and diaspora remittances. Diaspora remittances data was obtained from Central Bank of Kenya (CBK) on quarterly basis.
Building cost is measured in terms of materials cost used in building and land buying cost. Data for construction cost is limited and therefore the study used the Building cost Index data obtained from KNBS as a proxy for cost of construction.
Legal frameworks related to real estate investment include zoning, building codes and standards, taxation, land use controls and county government by-laws. Land use controls on real estate investment have a significant effect which type of dwellings construction of real property. Their enactment and enforcement by the local government dictates on rules and regulations that govern urban planning. They set standards that prevents uncontrolled buildings, unfinished houses which prevents haphazard development of dwellings and therefore protects investors from unexpected demolitions and in other cases buildings collapsing
Chapter three
Research design and Methodology
3.1 introduction
This chapter will discuss in detail the research design and methods to employ in answering the objectives of the study as stated in chapter one. Study design, location, population of the study, sampling procedure, sample size, instruments that will be used, their validity, method of analyzing data and ethical consideration.
3.2 research design
According to (ogula, 2011) research design is a planning and conducting a study strategy. This study adopted both exploratory as well as causal effect approach in examining the impact of microeconomic environment on investment in real estate as well as how macroeconomics factors impacts real estate investment in Kenya. Primary and secondary data will be collected on specific variables as captured in the conceptual framework. Macroeconomic data will be collected as captured on conceptual framework on quarterly basis making the study longitudinal in nature. The exploratory approach allowed for gathering quantitative data that will be subjected to empirical analysis. Econometric and descriptive analysis will be done.
3.3 location of the study
The research will take place in Nakuru county. Ten registered property companies, property developers and housing finance corporation are selected for the study.
3.4 Population of the study
Population of the study is the entire group of people, events, or things of interest that the researcher will investigate (borg et al, 2007). In addition, (kasom 2006) explains that the population of study is the aggregate of all cases that conform to designated sets of specification to which the study general results. The researcher intends to administer questionnaire to registered property companies as well as housing finance corporation (HFC).
3.5 sampling procedure and sample size
3.5.1 sampling procedure
According to (orodho, 2008) Sampling is the process of acquiring a proportion of a unit from the selected individuals as the representative of that people. Sample should be hundred percent when the population is small. When the sample population is large, the more study findings represents the target population. This study requires cross-sectional data for micro-economic analysis while time series data will be gathered for macroeconomic analysis. Cross sectional data will be collected from the real estate agents, property managers as well as sales representatives.
3.5.2 sample size
According to study conducted by (kothari, 2004) states that sample size has to be large enough to be a true representative of the universe population. (Creswell, 2006) stated that sample size should be able to provide relevant and enough information on the population to be analyzed efficiently. (Cochran, w.g, 1977) come up with a formula for determining a proportional sample size.
N=Z squared.pq/E squared
where n is the desired sample size of the respondents real estate investors, property developers and managers among others in kenya, z is the standard normal deviate at the required confidence level and is found in the Z-table, p is the proportion in the target population estimated to have characteristics of interest, q is 1- p, and e is the desired level of precision. p will be adopted as the unknown estimate of the respondent proportion Third objective will be addressed by the registered. Therefore, all the registered development companies will the target population to address challenges faced in the real estate investment companies
3.6 instrumentation (data collection instruments)
Questionnaires is the instrument that will be use in data collection from the sample population. Questionnaires makes process efficient due to its simplicity when analyzing and interpreting (McMillan, 2006). It enables the researcher to know what is required and how to measure the variables of interest. questionnaires are low in cost.
3.6.1 pilot study
Questionnaire pilot testing will be done to expose the questionnaires’ weakness. Careful preparation of the questions will be done in accordance with the objectives of the study to prove its effective in collecting the relevant information.
3.6.2 validity of the instrument
The ability to generalize the outcome of a study to other settings are known as validity. It’s the extent to which the study investigates what it claims to investigate and report what exactly happen in the field (mason, 2002). Generally, validity explains the degree to which the instrument of the research collects the necessary information. The aim of this measure is to assess whether there’s a gap between the data that will be collected and the information that will be sought (serem, boit & Wanyama 2013). validity seeks to assess the strength of the relationship between the variables. The validity of the instrument research will only be guaranteed via pre-test study. The objective of the study will be realized after receiving the feed feedback of the study and then revise the tool if need be. If the instrument validity produces a consistent data, then it will be acceptable to be used on the entire population. Also, the research supervisor’s opinion will count in validating the questionnaire as long as the instrument meets the research objectives.
3.6.3 reliability of the instrument
According to (Mugenda and Mugenda, 1999), stated that reliability is a degree to which an instrument of research yields the same data after many trials. reliability is a demonstration that study operations such as procedures of collecting data can produce same results repeatedly. The research instruments reliability can be achieved by pre-visiting the area under study to establish the reliability of the study. A test-retest method will be adopted to measure the reliability of the study. Test-retest can be obtained through administering test twice over a period of time to a group of individuals. Time 1 & 2 be correlated to evaluate stability test over time.
3.7 data collection procedure
As a researcher, I will personally distribute structured questionnaires to real estate investors, real estate agents and sales representatives with an aim of addressing objective one and capturing micro factors influencing real estate in Kenya. Secondary data will be required on macro-economic factors (lending rates, GDP, diaspora remittance, inflation rate, foreign exchange rate, growth in house prices, real estate building cost index) from available published literature, KNBS, financial statement, World Bank journals, CBK as well as Real Estate annual reports to address objective two. Development companies will address objective three through questionnaires. This will take place after the researcher is given data collection letter from the kabarak university to support the authenticity of the study and remove doubt from the respondent’s mind.
3.8 data analysis
Data analysis is the process of bringing order, structure as well as meaning to a large quantity of information collected. Primary as well as secondary data will be analyzed statistical package for social sciences (SPSS) and Stata. Descriptive statistics and inferential analysis will be done on Quantitative data collected and findings presented in the results section. Transformation of raw data into a form that will provide information which describes a set of factors in a manner that will make them easy to understand and interpret is known as descriptive statistics. Descriptive statistics that will be recorded include mean, percentages, frequencies and standard deviation. Cross sectional data will be subjected to normality as well as collinearity tests and a factor analysis technique will be used to determine the relationship between micro factor and investment in real estate.
Time series data will be subjected to statistical tests such as Pearson correlation tests, Philip Perron test, Johasen and Juselius test as well as granger causality tests. These tests are necessary in determining the relationship that exist amongst the variables in the dataset before specifying our regression models. Pearson Correlation test will be used to find out the strength and direction of the relationship between the dependent variable and its covariates in the regression. Philip Perron test will be used for stationarity check (unit root test) in the data and Granger Causality will be applied on data to find out the effect-causality relationship on selected time series variables.
3.8.1 Model specification
Factor analysis will be carried out on the overall model but the number of observations may not be enough for the segment analysis, therefore the study will use regression as expressed in the following equation.
Y = β0 + β1X1 + β2X2 + β3X3
Y=investment in real estate (dependent variable)
β0=constant term
β1, β2, β3 …. Βn, =beta coefficient
3.9 Ethical consideration
Ethics refers to philosophy branch which deals with one’s conduct as well as guiding one’s behavior. During the research process, the team will maintain high level of ethics. Researcher will make sure that the participation will be voluntary in order to encourage high response rate, this will be made per potential participant. Therefore, the major ethical consideration that will be uphold is anonymity and responsibility of researcher, privacy and confidentiality as stated by (Mugenda & Mugenda, 1999).
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