demand for accommodation in kenyatta university and its impact on student budget_3

8/2/2019 Demand for Accommodation in Kenyatta University and Its Impact on Student Budget_3

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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).


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.


020 66.7 66.7 66.7

110 33.3 33.3 100.0

Total30 100.0 100.0


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Ruiru


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.


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


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.


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.


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.


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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