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DEMAND FOR ACCOMMODATION IN KENYATTA UNIVERSITY AND ITS
IMPACT ON STUDENT BUDGET.
BY
SYLVESTER MWANIKI KIRERU.
K24/0314/2008
KENYATTA UNIVERSITY
SCHOOL OF ECONOMICS
SUBMITTED TO: DR.EMMANUEL MANYASA
A RESEARCH PROJECT SUBMITTED TO THE DEPARTMENT OF APPLIED
ECONOMICS IN PARTIAL FULFILLMENT FOR THE REQUIREMENT OF THE
AWARD OF A BACHELORS DEGREE IN ECONOMICS AND STATISTICS
DECEMBER 2011
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DECLARATION
This project is my original work and has never been presented for an award of a degree in any
other university.
Signature............................................. Date........................................................
SYLVESTER MWANIKI KIRERU
K24/ 0314/ 2008
The Research Project has been submitted for examination with my approval as the course
instructor.
Signature........................................... Date....................................................
DR. EMMANUEL MANYASA
LECTURER: DEPARTMENT OF APPLIED ECONOMICS
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ACKNOWLEDGEMENT.
I would like to thank the following without whose assistance I would not have been able to complete
this research project; Mr. Elijah Kipkurui Yangon, Mr. John Barongo, Mr. Joab Kitiyo, Mr. Tony Kimathi
and last but not least Dr. Emmanuel Manyasa. I truly thank you all from the bottom of my heart.
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Table of ContentsDECLARATION .......................................................................................................................................... ii
ACKNOWLEDGEMENT. .......................................................................................................................... iii
CHAPTER ONE: INTRODUCTION ........................................................................................................... 1
1.1. Background ................................................................................................................................... 1
1.2. Statement of the Problem .............................................................................................................. 1
1.3. Research Questions ....................................................................................................................... 2
1.4. Objectives of the Study ................................................................................................................. 2
1.4.1. General objective .................................................................................................................. 2
1.4.2. Specific Objectives ............................................................................................................... 2
CHAPTER TWO: LITRATURE REVIEW ................................................................................................. 3
2.0 Introduction..................................................................................................................................... 3
2.1 Theoretical Literature...................................................................................................................... 3
CHAPTER THREE. ..................................................................................................................................... 6
3.1Theoretical framework. ....................................................................................................................... 6
3.2 Model specification ............................................................................................................................. 6
3.3Definition of variables. ......................................................................................................................... 7
3.4. Data Analysis. ..................................................................................................................................... 7
CHAPTER FOUR......................................................................................................................................... 9
DATA ANALYSIS, PRESENTATION AND INTERPRETATION .......................................................... 9
4.0 Introduction......................................................................................................................................... 9
4.1 Descriptive Statistics. .......................................................................................................................... 9
4.2 Descriptive Qualitative Analysis. ....................................................................................................... 10
4.3 Correlation Coefficient Analysis. ....................................................................................................... 15
Regression. .............................................................................................................................................. 17
4.4 Model summary. ............................................................................................................................... 17
CHAPTER FIVE. ....................................................................................................................................... 20
5.1 Introduction. ..................................................................................................................................... 20
5.2 General information.......................................................................................................................... 20
5.3 Hypothesis Testing. ........................................................................................................................... 20
5.4 Limitations of the study. ................................................................................................................... 20
5.5 Recommendations of the study. ....................................................................................................... 20
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5.6 Further Areas of Research. ............................................................................................................... 21
5.7 Conclusion. ........................................................................................................................................ 22
APPENDIX................................................................................................................................................. 23
Questionnaire. ........................................................................................................................................ 23
REFERENCES. .......................................................................................................................................... 24
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CHAPTER ONE: INTRODUCTION
1.1. BackgroundKenyatta University had been steadily increasing admission to its various degree courses.
This had been as a result of not only an increase in the demand for higher education but also
government policy which favored higher enrollment in all the public universities so that,
they could provide manpower with the required skills to propel Kenya to middle income
economy status by the year 2030.
In large part, this had been met by not pegging admission to university on the available bed
capacity. This had resulted in large number of K.U students missing out on accommodation
as demand outstrips supply and as a result the university granted accommodation on a first
come first serve basis.
More money gives you more command over goods and services, Wronski et al (1968). Since
these students have to spend a higher proportion of their budgets on accommodation, the
amount left over should buy a lower quantity of goods and services meaning these students
receive lower utility from their disposable budgets than if they were residing in the
university halls of residence.
This was replicated in all the other six public universities as admission was increased
without an increase in the university accommodation. The policy therefore did not consider
the extra expense incurred by these students when they are forced to seek accommodation
outside the university.
1.2.
Statement of the ProblemWith admission in K.U rising every academic year and accommodation only marginally so a
significant proportion of students were left with no choice but to seek accommodation
outside the K.U campus. The cost of accommodation at these private hostels was much
higher than the cost of accommodation at the university. The purpose of this study was
therefore is to find out what impact residing off campus had on the student budget.
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1.3. Research QuestionsThe following research questions arise from the research problem.
Was there a significant relationship between demand for accommodation and studentbudget in Kenyatta University?
What had been the impact on student budget of not pegging admission on availableaccommodation?
What steps were be taken by K.U management to bridge the gap between demandand available accommodation?
1.4. Objectives of the Study1.4.1. General objective
In line with the research questions, the general objective of this study was to establish
whether there was a significant relationship between demand for accommodation and the
student budget and to assess the impact on student budget of not pegging admission on
available accommodation with a view of recommending measures to bridge the gap
between student admission and available accommodation.
1.4.2. Specific Objectives(i) To test whether there was a significant relationship between demand for
accommodation and the student budget.
(ii) To establish the impact on student budget of not pegging admission on availableaccommodation.
(iii) To determine what steps had to be taken by K.U management to bridge the gapbetween student admission and accommodation.
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CHAPTER TWO: LITRATURE REVIEW
2.0 Introduction
Theoretical literature proposes that there is a positive relationship between income and demand
i.e. an increase in income leads to an increase in demand. Empirical literature on the other hand
says that accommodation is a key consideration for students who usually have a limited earning
capacity while studying. For this reason, purpose built accommodation can often be unaffordable
for many students.
This chapter reviews both the theoretical literature on demand and income and empirical
literature on demand for student accommodation.
2.1 Theoretical Literature
Colander (1993) and Mudida (2003) point to a positive relationship between income and
demand. An increase in income leads to an increase in demand and decrease in income leads to a
decrease in demand.
Schiller (1983) meanwhile says that changes in consumer income have the same kind of effect as
changes in tastes. He asserts that the shape and position of the demand curve depends on income
as well as on tastes.
Whitehead (1980) meanwhile says that family income is decisive as to whether a commodity is
demanded or not. He furthers states that even so called impulse buying is usually within the
familys budget or income.
Miller (1978) says that peoples role as consumers depend critically on their ability to consume.
The ability to consume depends on their income-that is, on how much money they have to spend.
He further states that no matter what a persons income is, however, spending income that
decisions are made all the time. It requires that the person as a consumer decide what to buy,
how much to buy, where to buy it, and how much time to spend obtaining information about the
appropriate consumer choices to be made.
Lipsey (1971) points to four hypotheses about the factors that influence household demand and
about the direction that these factors take. He says that the households demand for a commodity
is influenced by the price of that commodity. Usually the higher the price, the lower will be the
quantity demanded. The households demand for a commodity is influenced by the size of its
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income. In most cases the demand for will increase as the price of a second commodity
increases. A households demand for a commodity is influenced by the tastes of its members.
Moore (1973) also points to a very large number of forces that may be expected to influence the
quantity of any commodity demanded. Those few singled out for analysis as most important are
called the determinants of demand. The chief of these are the price of the commodity, the prices
of other commodities, the level of income and wealth, and tastes and preferences.
Hague (1968) also says that consumers will normally buy more of a commodity if its price falls
and less if its price raises, assuming, of course, that consumers money income remains constant
when the price change occurs.
Samuelson (1973) talks of the law of downward sloping demand. When the price of a good is
raised (at the same time all other things are held constant), less of it is demanded. Or, what is the
same thing, if a greater quantity of a good is put on the market, then- other things being equal- it
can only be sold at a lower price. He further states that this law is in accordance with common
sense and has been known in at least a vague way since the beginning of recorded history. When
the price of wheat is sky high, only rich men will be able to afford it; the poor will have to make
do with coarse rye bread, just as they still must do in poorer lands. When the price is still high
but not quite as high as before, persons with moderate who also happen to have an especially
great liking for white bread will now be coaxed into buying some wheat.
Miller (1982) points to relative prices and how consumer buying decisions depend on relative,
not absolute prices. At higher relative prices, a lower quantity will be demanded than at lower
prices, other things being equal.
McConnell and Bruce (1996) point to several levels of analysis as the foundation of the law of
demand. The first is that common sense and simple observation are consistent with the law of
demand. The second is that in any given period of time each buyer of a product will derive less
satisfaction or benefit or utility from each successive unit consumed. Consumption is subject to
diminishing marginal utility. The third is that the law of demand can be explained in terms of
income and substitution effect.
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2.2 Empirical Literature.
This section borrows heavily from Stonnington City Council student accommodation study 2006.
The study was undertaken to inform the city of Whitehouse on the current student population
residing in the municipality, the supply of purpose built student accommodation and the
forecasted demand for more facilities Stonning City Council found out that the factors that affect
the student housing market are export industry considerations, ethnicity and culture of students,
housing type and location and affordability.
On affordability, the study found out that wealth, a major factor in an international students
oversees experience can dictate which type of institution they attend and where they live.
The study also found out that transport adds an additional expense to their (students) daily living
and impacts on what they can afford to pay in rent.
Canton and Blom (2004) point to student difficulties in financing university education and these
students have to apply for financial assistance. They also point out high college premium in
Mexican Universities and limited physical capacity in public universities.
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CHAPTER THREE.3.0Methodology.
3.1Theoretical framework.This study adopted price theory as it theoretical framework.
R=F(Y, T, P)
Where R=Rent paid by students
Y=Student budget
T=Transport Cost
P=Place of accommodation
3.2 Model specification
The study assumed the multivariate regression model. Rent paid by students was considered as
the dependent variable. Student budget, transport cost and place of accommodation were
considered as independent variables. The study assumed a linear relationship between the
dependent variable and the independent variables. The study also assumed an inverse
relationship between the rent paid by students and the student budget, transport cost and place ofaccommodation.
Where R=Rent paid by students
Y=Student budget
T=Transport Cost
P=Place of accommodation
E=randomly distributed error term
Then the model was being written as;
D (P) =o+1T+2P+3Y+E
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Where;- 0 is the intercept of the regression equation while 1 2 3 are coefficients while the E
is a randomly distributed error term.
3.3Definition of variables.
Transport cost.
This was the amount incurred by students as they commuted to and from Kenyatta University.
Place of accommodation.
This was the place of residence of students as they carried on their studies at Kenyatta
University.
Student Budget.
This was the income of students while they carried on their studies at Kenyatta University.
Error term
This is also known as disturbance term, or noise. This variable captured all other factors which
influenced the dependent variable R other than the regressors Y, T, and P.
Study Area.
The study covered then following areas: Kahawa Wendani, Kahawa Sukari, K.M, Ruiru,
Roysambu, Clayworks, Allsopps, Kasarani and Kariobangi South. All of them were areas where
nonresident student were known to reside.
Sample size and sample design.
To achieve the objectives of the study, the study assumed the following methodology.
Simulation (field research) study was carried out in Kenyatta University to obtain primary data.
This was through questionnaires and interviews. The study covered 30 nonresident students due
to limited time available and limited resources.
3.4. Data Analysis.
Simulation was carried out to analyze the relationship between demand for accommodation and
the student budget. The study covered the period between September and December 2011. In
data analysis, Data was collected using questionnaires and sorted to check for completeness and
clarity. The items collected were coded, edited and data was then analyzed qualitatively using the
Statistical Package for the Social Sciences (SPSS) version 16.0.
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Data collected was processed, coded and analyzed to facilitate answering the research objectives
and questions.
In addition to descriptive statistics, I employed correlation and regression analyses. Before
applying regression analysis, the validity and reliability of the research instrument were
examined using correlation analyses, t-test and ANOVA appropriately. A correlation analysis
was used to examine the relationship between demand for accommodation and the student
budget, transport cost and place of accommodation. Regression analysis was also employed to
look at relationship between demand for accommodation and the student budget, transport cost
and place of accommodation.
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CHAPTER FOUR.
DATA ANALYSIS, PRESENTATION AND INTERPRETATION
4.0 Introduction.
This chapter presented and discussed data analysis that related to the research objectives. The
raw data collected was coded, tabulated and analyzed. This enabled me to draw proper
conclusions easily and without hassle. The results are as below:
4.1 Descriptive Statistics.
N Minimum Maximum Mean Std. Deviation
Rent30 2700.00 7000.00 4110 1186.51910
Transport30 .00 2000.00 713.67 565.38350
Budget30 8700.00 30900.00 15595 4779.13622
Age30 19.00 29.00 22.7 1.93248
Valid N (list wise)30
Rent paid.
The minimum rent paid was KES 2700 every month while the maximum rent paid was KES
7000 every month. The mean rent paid was KES 4110 every month.
Transport Cost.
The minimum transport cost was KES 0 every month while the maximum transport cost was
KES 2000 every month. The mean transport cost was KES 713.67 every month.
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Student Budget.
The minimum student budget was KES 8700 every month while the maximum student budget
was KES 30900 every month. The mean student budget was KES 15595 every month.
Age.
The minimum age was 19 years while the maximum age was 29 years. The mean age was 22.7
years.
4.2 Descriptive Qualitative Analysis.
Sex.
Frequency Percent Valid Percent Cumulative Percent
Male 22 73.3 73.3 73.3
Female 8 26.7 26.7 100.0
Total
30 100.0 100.0
In the study 73.3% of the sampled respondents were male while 26.7% of the sampled
respondents were female.
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Kahawa Wendani
0 represented the percentage of students that did not live in Kahawa Wendani.
1 represented the percentage of students that lived in Kahawa Wendani.
As in the table above, 33.3% of the respondents lived in Kahawa Wendani.
KM (Kilometer Moja).
Frequency Percent Valid Percent Cumulative Percent
0 26 86.7 86.7 86.7
1 4 13.3 13.3 100.0
Total 30 100.0 100.0
0 represented the percentage of students that did not live in KM.
1 represented the percentage of students that lived in KM.
As in the table above, 13.3% of the respondents lived in KM.
Frequency Percent Valid Percent Cumulative Percent
020 66.7 66.7 66.7
110 33.3 33.3 100.0
Total30 100.0 100.0
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Ruiru
Frequency Percent Valid Percent Cumulative Percent
026 86.7 86.7 86.7
14 13.3 13.3 100.0
Total30 100.0 100.0
0 represented the percentage of students that did not live in Ruiru.
1 represented the percentage of students that lived in Ruiru.
As in the table above, 13.3% of the respondents lived in Ruiru.
Roysambu.
Frequency Percent Valid Percent Cumulative Percent
0 29 96.7 96.7 96.7
1 1 3.3 3.3 100.0
Total 30 100.0 100.0
0 represented the percentage of students that did not live in Roysambu.
1 represented the percentage of students that lived in Roysambu.
As in the table above, 3.3% of the respondents lived in Roysambu.
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Kahawa Sukari
Frequency Percent Valid Percent Cumulative Percent
0
22 73.3 73.3 73.3
18 26.7 26.7 100.0
Total30 100.0 100.0
0 represented the percentage of students that did not live in Kahawa Sukari.
1 represented the percentage of students that lived in Kahawa Sukari.
As in the table above, 26.7% of the respondents lived in Kahawa Sukari.
Clay Works.
Frequency Percent Valid Percent Cumulative Percent
0 29 96.7 96.7 96.7
1 1 3.3 3.3 100.0
Total 30 100.0 100.0
0 represented the percentage of students that did not live in Clay Works.
1 represented the percentage of students that lived in Clay Works.
As in the table above, 3.3% of the respondents lived in Clay Works.
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Kariobangi South.
Frequency Percent Valid Percent Cumulative Percent
0 29 96.7 96.7 96.7
1 1 3.3 3.3 100.0
Total 30 100.0 100.0
0 represented the percentage of students that did not live in Kariobangi South.
1 represented the percentage of students that lived in Kariobangi South.
As in the table above, 3.3% of the respondents lived in Kariobangi South.
Allsopps.
Frequency Percent Valid Percent Cumulative Percent
029 96.7 96.7 96.7
11 3.3 3.3 100.0
Total30 100.0 100.0
0 represented the percentage of students that did not live in Allsopps.
1 represented the percentage of students that lived in Allsopps.
As in the table above, 3.3% of the respondents lived in Allsopps.
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4.3 Correlation Coefficient Analysis.
The Table below showed the Correlation Coefficient of the explained variable against the
explanatory variables and the explanatory variables against the explanatory variables.
Rent Budget Transport Age Sex Wendani Sukari KM Ruiru Roysambu Clayworks Allsopps
Age -.202 .024 .000 1
Sex.040 -.032 -.178
-
.381*1
Wendani .339 .134 -.160 .037 -.107 1
Sukari -.212 -.273 -.362* -.222 -.023 -.426* 1
KM -.373* -.276 -.355 .010 .207 -.277 -.237 1
Ruiru
-.247 -.011 .352 .268 -.015 -.277 -.237 -.154 1
Clayworks
.301 .249 .430* .029 -.112 -.131 -.112 -.073 -.073 -.034 1
Allsopps
.301 .107 .162 -.068 .308 -.131 -.112 -.073 -.073 -.034 -.034 1
Age is 20.2% negatively related to rent paid and 2.4% positively related to student budget. The
sex of the students is 4% positively related to rent paid, 3.2% negatively related to student
budget, 17.8% negatively related to transport cost and 38.1% negatively related to the age of
students. Kahawa wendani is 33.9% positively related to rent paid by students, 13.4% positively
related to the student budget, 16% negatively related to transport cost, 3.7% positively related to
the age of students and 10.7% negatively related to the sex of students. Kahawa Sukari is 21.2%
negatively related to rent paid by students, 27.3% negatively related to student budget, 36.2%
negatively related to transport cost, 22.2% negatively related to the age of students, 2.3%
negatively related to the sex of students and 42.6% negatively related to Kahawa Wendani. KM
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is 37.3% negatively related to the rent paid by students, 27.6% negatively related to the student
budget, 35.5% negatively related to transport cost, 1% positively related to the age of students,
20.7% positively related to the sex of students, 27.7% negatively related to Kahawa Wendani
and 23.7% negatively related to Kahawa Sukari. Riuru is 24.7% negatively related to the rent
paid by students, 1.1% negatively related to the student budget, 35.2% positively related to the
transport cost, 26.8% positively related to the age of students, 1.5% negatively related to the sex
of students, 27.7% negatively related to Kahawa Wendani, 23.7% negatively related to Kahawa
Sukari and 15.4% negatively related to KM. Clayworks is 30.1% positively related to the rent
paid by students, 24.9% positively related to the student budget, 43% positively related to the
transport cost, 2.9% positively related to the age of students, 11.2% negatively related to the sex
of students, 13.1% negatively related to Kahawa Wendani, 11.2% negatively related to Kahawa
Sukari, 7.3% negatively related to KM, 7.3% negatively related to Ruiru and 3.4% negatively
related Roysambu. Allsopps is 30.1% positively related to the rent paid by students, 10.7%
positively related to the student budget, 16.2% positively related to the transport cost, 6.8%
negatively related to the age of students, 30.8% positively related to the sex of students, 13.1%
negatively related to Kahawa Wendani, 11.2% negatively related to Kahawa Sukari, 7.3%
negatively related to KM, 7.3% negatively related to Ruiru, 3.4% negatively related to
Roysambu and 3.4% negatively related to Clayworks.
From the above correlation results there was no multi-collinearity between the explained and the
explanatory variables and between the explanatory variables and the explanatory variables.
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Regression.
4.4 Model summary.
Model R R Square Adjusted R Square
Std. Error of the
Estimate
1 .812a .659 .451 878.97045
a. Predictors: (Constant), Ksouth, Age, Clayworks, Allsopps, Roysambu, KM, Ruiru, Sukari, Sex, Budget, Transport
From the above table the regression results showed that 65.9% of the variations in rent paid is
explained by variations in student budget, transport cost and place of residence.
Regression Coefficients.
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Model
Unstandardized Coefficients
Standardized
Coefficients
T Sig.B Std. Error Beta
1 (Constant) 6395.934 2705.261 2.364 .030
Budget (Y) .113 .055 .454 2.030 .057
Transport(T) -.488 .742 -.233 -.658 .519
Age(A) -143.463 110.213 -.234 -1.302 .209
Sex(X) -126.123 474.159 -.048 -.266 .793
Sukari(SK) -839.620 468.935 -.318 -1.790 .090
KM -1350.983 608.530 -.394 -2.220 .039
Ruiru(RU) -696.159 769.247 -.203 -.905 .377
Roysambu(RY
)60.600 1286.073 .009 .047 .963
Clayworks(C
W)1413.132 1343.592 .217 1.052 .307
Allsopps(AS) 1410.776 1105.933 .217 1.276 .218
Ksouth(KS) -100.102 1435.381 -.015 -.070 .945
a. Dependent Variable: Rent
D(R) = 6395.934 +0.454Y- 0.233T- 0.234A- 0.048X- 0.318SK- 0.394KM - 0.203RU +0.009RY + 0.217CW +0.217AS-
0.015KS
If you increase the student budget by one percent, rent paid increases by 0.454%. For every one
student increase in Roysambu, Clayworks and Allsopps, the rent paid increases by 0.009%,
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0.217% and 0.217% respectively. Female students pay 4.8% lower rent than their male
counterparts.
For every one unit increase in transport cost and age of students, rent paid decreases by 0.233%
and 0.23% respectively.
For every one student increase in KM, Kahawa Sukari, Ruiru and Kariobangi South, rent paid
decreases by 0.394%, 0.3185%, 0.203% and 0.015% respectively.
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CHAPTER FIVE.
5.1 Introduction.
This chapter aims at giving a general overview of the findings of the research project, test of
hypothesis, limitations of the study, give recommendations of the study and suggest further areas
of research.
5.2 General information.
The study found out that the minimum rent paid was KES 2700 per month while the maximum
rent paid was 7000 per month. The study also found that the maximum transport cost was KES
2000 per month with a mean of KES 713.67. On the student budget the study found out that the
minimum student budget was KES 8700 per month while the maximum student budget was KES
30900 with a mean of KES 15595. The study also found out that the minimum age was 19 years
while maximum age was 29 years. The mean age was 22.7 years. 73.3% of the respondents were
male while 26.7% of the respondents were female. On the place of residence the study found out
that 33.3% of the respondents lived in Kahawa Wendani, 13.3% in KM, 13.3% in Ruiru, 26.7%
in Kahawa Sukari, 3.3% in Clayworks, 3.3% in Kariobangi South and 3.3% in Allsopps.
5.3 Hypothesis Testing.
The study found out that indeed there was a significant relationship between the student budget
and demand for accommodation in Kenyatta University. This was consistent with both the
theoretical and empirical literature and also consistent with common sense beliefs.
5.4 Limitations of the study.
The limitations of the study were accuracy of data on student budget and transport cost from the
nonresident students. There was also limited time available for carrying out this research project.
5.5 Recommendations of the study.
The government should institute a policy whereby a certain percentage of students, sat75% should be housed on campus.
In order to relieve pressure on government finances in the area of student housing,student living accommodation should be financed through loans with the government
financing a certain proportion of it, say a third.
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K.U should employ the services of an Estate Agent to undertake a feasibility study of thebest avenues of raising loans from the many mortgage establishments, Insurance
Companies, the Provident Funds and banks.
Design for student hostels should be more modest, simple and functional, so that they canbe within the means of students.
The university should identify a suitable location for the provision of private hostelswhich will eventually be integrated in the universitys Master Plan.
Students who are the most important stakeholders must be involved in the determinationof fair rent before the commencement of construction work.
The university should contract private developers who would build hostels on a BuildOperate Transfer model.This would be for a period of at least 25 years.
5.6 Further Areas of Research.
The purpose of this study was to investigate the determinants of demand for accommodation in
Kenyatta University and its impact on the student budget. Given the financial and time
constraints the study could not reach each and every nonresident student to find out their specific
demand characteristics. Sampling was therefore employed to achieve the objectives of the study.
Researchers interested in studying the various characteristics of student accommodation could
therefore focus their energies on the following areas:
If the state of sanitation in private hostels in and around Kenyatta University affects thedemand for accommodation.
The determinants of the supply of hostels in and around Kenyatta University. The economic impact of the Thika Superhighway on the demand for accommodation in
Kenyatta University.
The economic impact of the Thika Superhighway on the supply for accommodation inKenyatta University.
The impact of the existing rules and regulations of the Nairobi City Council on the supplyfor accommodation in and around Kenyatta University.
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5.7 Conclusion.
It is clear that increasing admission to Kenyatta University without a corresponding increase in
available bed space has a significant impact on the student budget. Students have no choice but
to seek accommodation at private hostels at great expense to not only themselves but to those
who support them financially. Appropriate corrective measures as recommended above should
therefore be taken to relieve some if not all the financial burden that falls on these nonresident
students.
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APPENDIX.
Questionnaire.
I am a Kenyatta University student carrying out a research project to be submitted to the
department of Applied Economics in partial fulfillment of the requirement for the award of the
degree of Bachelor of Economics and Statistics. This questionnaire aims at analyzing the impact
on the student budget of not pegging accommodation on the available bed space. The data
provided will be useful in providing information that will help solve this challenge. The
information you shall provide will be confidential and will be used only for the purpose of this
research project.
I kindly urge you to help by filling in this questionnaire so as to make this study a success.
PART ONE.
1. Sex. Male Female
2. What is your date of birth? (dd/mm/yy)
3. What is your marital status?
Single Married
PART TWO.
1. Where do you live while studying at Kenyatta University?
2. Why do you prefer to live there?
Close proximity to K.U Friends also live there Nice spacious rooms Privacy
Other Reason(s)
3. Given a choice would you live somewhere else? Yes No
4. If yes, where and why would you live there?
............................................................................
............................................................................................................................................................
5. How much do you pay as rent every month?
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6. Do you pay for water? Yes No
7. If yes, how much do you spend in a month? ................................................................................
8. Do you pay for electricity? Yes No
9. If yes, how much do you spend in a month? .
10. How much do you spend on food in a week?.
11. How much do you spend on airtime in a week?
12. How much do you spend on entertainment in a week, i.e., when you go out to drink, to dance
etc.
13. How much do you spend on transport in a week? ..................................................................
14. How much do you spend on burning movies, music etc. in a week? .
15. How much do you spend on shopping in a week? ..
16. Do you incur any other expenditure in a week? Yes No
17. If yes, how much is this expenditure?
18. How much do you spend on clothes in a month? ...
19. Do you save? Yes No
20. If yes, how much do save in a month?
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