Identification of regularities in the development of the baby economy as a co...
CAUSES OF WAGE DIFFERENTIALS IN UGANDA
1. KYAMBOGO UNIVERSITY
FACULTY OF ARTS AND SOCIAL SCIENCES
DEPARTMENT OF ECONOMICS AND STATISTICS
P.O. BOX 1 KYAMBOGO
EMAIL: enconomics@kyu.ac.ug
THE CAUSES OF WAGE DIFFERENTIALS IN UGANDA
A CASE STUDY OF MINISTRY OF LANDS, HOUSING
AND URBAN DEVELOPMENT
BY
WESIGYE ALEX
REG NO. 11/U/6826/BEE/PE
A RESEARCH REPORT SUBMITTED TO THE DEPARTMENT OF
ECONOMICS AND STATISTICS IN PARTIAL FULLFILLMENT
FOR THE REQUIREMENT OF THE AWARD OF BACHELOR
OF ECONOMICS AND STATISTICS DEGREE OF
KYAMBOGO UNIVERSITY
OCTOBER, 2014
2. i
Declaration
I WESIGYE Alex, hereby declare that this is my original work and has not been submitted
for any award of a degree or diploma in any university or institution of learning.
3. ii
Approval
This is to certify that this research report by WESIGYE Alex entitled “The causes of wage
differentials in Uganda” has been compiled under my supervision and is now ready for
submission to the Department of Economics and Statistics.
4. iii
Dedication
This work is dedicated to my lovely Father the late lieutenant Wesigye Amos Murangira,
my dear Mother Mrs. Ngaronsa Rose, my beloved uncle Mr. Tumwine David, my
cherished friend Ms. Muzaki Christine. And to all my friends and family who have helped
me in my studies.
GOD Bless you all.
5. iv
Acknowledgement
I give thanks to the LORD JESUS CHRIST of Nazareth; my GOD, LORD and SAVIOR for
HIS Wisdom, Knowledge, Understanding, Insight and Finances among others that HE
has Graciously given me throughout the production of this report.
I surely wish to extend my SINCERE gratitude to my supervisor Mr. KATO FREDRICK for
his mentorship, guidance and supervision throughout the process of compiling this
report.
Finally I thank my uncles Mr. Keneth Muhwezi and Mr. Martin Rwenzigye for their
unfailing love and support towards my education.
And never forgetting Mr. Tumwine David for being a good father and paying all my
educational fees. No words can fully express how grateful I am sir.
May GOD abundantly bless you.
6. v
List of Acronyms/Abbreviations
SPSS Statistical Package for Social Scientists
SRS Simple Random Sampling
MS Microsoft Office
OLS Ordinary Least Squares Estimation method
MLHUD Ministry of lands, housing and urban
development
MPS Ministerial policy statement
FY Financial year
MWLE Ministry of Water, Lands and Environment
MWHC Ministry of Works, Housing and
Communication
ANCOVA Analysis of covariance
Ugx Uganda Shillings
7. vi
Abstract
The study aimed at finding the causes of wage differentials. Wage differentials refer to a
difference in payment among workers with different skills working in the same industry,
or workers with similar skills working in different industries or regions. Wage
differentials in Uganda have worsened the income inequality and lead to industrial strikes
in the country, which in turn affect the GDP and the whole economy.
A sample of 70 respondents was taken and this was specifically employees in the
Directorate of Physical Planning and Urban Development of the Ministry of Lands,
Housing and Urban Development.
A Simple Random Sampling technique was used to select the respondents. The researcher
used questionnaires to obtain the required information from the respondents.
The researcher used both quantitative and qualitative data in his analysis and
presentation of findings was done using tables. The analysis in this report was done using
Eviews 3.1 and SPSS statistics 17.0 with a 95% confidence interval for the results obtained.
The researcher also gave a clear explanation regarding the results in a way of pointing out
the meaning of each important component of the regression equation. From this result it
was realized that 88.6% of the variation in wages was explained by differences in gender,
educational level and working experience. While Educational level and working
experience had significant effects on wages, gender had no significant effect on wages.
8. vii
Table of Contents
Declaration................................................................................................................................ i
Approval ................................................................................................................................... ii
Dedication............................................................................................................................... iii
Acknowledgement ...................................................................................................................iv
List of Acronyms/Abbreviations ..............................................................................................v
Abstract ....................................................................................................................................vi
Table of Contents................................................................................................................... vii
List of Tables ............................................................................................................................ix
CHAPTER ONE......................................................................................................................... 1
1.0 Introduction......................................................................................................................... 1
1.1 Back ground of study............................................................................................................ 1
1.2 Statement of the Research Problem....................................................................................3
1.3.0 General objective...............................................................................................................3
1.3.1 Specific objectives..............................................................................................................3
1.4 Research hypothesis ............................................................................................................3
1.5 Scope of the study................................................................................................................3
1.6 Significance of the study .................................................................................................... 4
CHAPTER TWO........................................................................................................................5
LITERATURE REVIEW.............................................................................................................5
2.0 Introduction ........................................................................................................................5
2.1 Gender and Wages...............................................................................................................5
2.2 Training/ Educational level and wages ............................................................................. 6
2.3 Wages and working Experience..........................................................................................7
2.4 Summary of literature review............................................................................................ 8
CHAPTER THREE.................................................................................................................... 9
RESEARCH METHODOLOGY................................................................................................ 9
3.0 Introduction ....................................................................................................................... 9
3.1 Research Design.................................................................................................................. 9
3.2 Data Types and Sources ..................................................................................................... 9
3.3 Sample Selection and Size.................................................................................................. 9
3.4 Data Collection Method.................................................................................................... 10
3.5 Data Analysis ..................................................................................................................... 10
3.6 Limitations..........................................................................................................................11
CHAPTER FOUR..................................................................................................................... 12
DATA ANALYSIS, INTERPRETATION AND PRESENTATION........................................... 12
4.0 Introduction...................................................................................................................... 12
10. ix
List of Tables
Table 1: Table Showing Gender Distribution of the Respondents---------------------------12
Table 2: Table Showing Age Distribution of the Respondents------------------------------12
Table 3: Table Showing Marital Status of the Respondents----------------------------------13
Table 4: Table Showing Regression Results----------------------------------------------------14
11. 1
CHAPTER ONE
1.0 Introduction
This chapter presents the background information of the study, problem statement,
objectives of the study, research hypotheses, scope of the study and significance of the
study as explained below.
1.1 Back ground of study
Wage is an economic reward to the factor of production called labour. Wage differentials
refer to the variation in wage structures paid to labour. Wage structures are the relative
prices of the labour that are utilized to allocate labour to its most productive and efficient
use and to encourage human capital development in the area of educational training,
mobility and job search yielding high returns. Wages are also the prices that compensate
workers for undesirable job characteristics.
Under conditions of perfect competition, the identical workers doing the same type of
jobs would get the same wages. However, in the real world, it is seen that different wages
are paid to workers because of several factors which include; workers differ in quality,
skill and training; jobs differ, some are dangerous, and others are pleasant, some require
more education and training than others; some institutional factors cause imperfections
in the labor market such as discrimination against black race in America, women in many
parts of the world, scheduled castes and scheduled tribes in India. The above arguement
explains only some of the factors causing differences in wages , the differences in natural
abilities, differences in non-monetary benefits, pleasant atmosphere, freedom to choose
one’s work schedule as in case of some other factors account for wage differentials. (Dr.
H. L. Ahuja, 2012)
Even though the female labor force participation in the Soviet Union was higher than in
Western countries (For 1960 - 1988: Austria - 60.7%, France - 72%, Italy - 54.2%, Ireland -
44.7%, Portugal - 67.4%, Soviet Union around 90%), throughout its history women were
regarded as a “specific labor force and occupational segregation was a lived reality.
According to C. G. Ogloblin (1999), protective legislation restricted women’s employment
in jobs that were considered dangerous or physically demanding and encouraged their
entrance into jobs that suit their biological and psychological peculiarities and their
moral ethical temperament. Women hence ended up in such sectors as Education,
healthcare, trade, food and light industry, while men were mostly concentrated in the
heavy industry, mining, construction and engineering. Such segregation was one of the
12. 2
main forces that drove the gender wage gap in the Soviet Russia. This was due to the fact
that in the centralized wage system, where market forces did not interfere, earnings
within sectors were determined by the perception of a certain sector’s productivity,
laboriousness and social usefulness. Since Marxist ideology considers the productive
sphere (manufacturing) superior to the unproductive one (services, office jobs), the blue-
collar wages always tended to be higher than the white-collar wages. Women in Russia
were highly concentrated in the white-collar jobs therefore their earnings were on
average lower than those of men throughout the whole Soviet Union’s history.
Nevertheless, occupational segregation was not the only contributor of the wage gap
during the soviet times, as labor market discrimination, even though forbidden by law,
was well set afoot and contributed in big measure to wage differentials. Ogloblin (1999)
writes: “Since household and family responsibilities were explicitly treated as women’s
domain, women often chose to sacrifice career interests to family responsibilities.
Furthermore, since both creativity and authority were identified with men, women who
tried to pursue managerial or professional careers encountered subtle but effective
resistance to their promotion” His text suggests that glass ceilings were present in the
Soviet Union and deeply rooted in people’s perceptions of women’s role and gender
norms. Newell and Reilly (2000) similarly mention that, despite high labor force
participation, women held few senior positions mostly due to two reasons: first, since
Russia never went through the revolution in gender relations that took place in the West,
the slow but fundamental shift in household division of labor did not happen; second
and as a consequence, working women had to carry a double burden as the domestic
duties remained entirely on their shoulders leaving them with less time to pursue a
career.
A. McAuley (1981), on the other hand, identifies an additional reason for the persistence
of wage gaps in Russia - the "differential participation" of women. Differential
participation is the idea that women worked shorter hours than men and in some sense
supplied less labor. McAuley (1981) mentions that this was mostly due to the fact that
domestic work was viewed as being almost exclusively women’s responsibility.
This research therefore intents to look at the causes of wage differentials in Uganda
through the Ministry of Lands, Housing and Urban Development (MLHUD). According
to MLHUD’s Ministerial Policy Statement FY2013/14 (pg2-15), the Ministry employs
numerous personnel of different professions such as Statisticians, Economists,
sociologists, drivers, physical planners, office attendants, geographers, records assistants,
surveyors, engineers and development analyst among others who earn different wages.
This therefore enticed the researcher to investigate the causes of wage differentials.
13. 3
1.2 Statement of the Research Problem
The Employment Act 2006 states that “every employer shall pay male and female equal
remuneration for work of equal value”. A good example is the Uganda Public Service
salary structure which is based on the principle of equal pay for work of equal value. In
this case jobs considered to be equal value are grouped together on the same salary scale
for equal pay. MLHUD Ministerial Policy Statement FY2013/14 (pg2-15) reveals the basic
pay of MLHUD employees. The wages clearly differ from employee to employee.
Different occupations earn different pay, some personnel of same occupations as well
earn different wages and employees of the same level of education also earn different pay.
Therefore, searching for the reasons of wage differentials has important social and
economic worth because it will help in realizing wage equality.
1.3.0 General objective
The purpose of the study is to examine the major causes of wage differentials in Uganda.
1.3.1 Specific objectives
(i) To find out whether wages depend on training/educational level.
(ii) To assess the relationship between gender and wages.
(iii) To ascertain the relationship between working experience and wages.
1.4 Research hypothesis
(i) Ho: Wage does not depend on educational level.
Ha: Wage depends on educational level.
(ii) Ho: There is no significant relationship between Wage and Gender.
Ha: There is a significant relationship between Wage and Gender.
(iii) Ho: There is no significant relationship between Wage and Working
Experience.
Ha: There is a significant relationship between Wage and Working Experience.
1.5 Scope of the study
The study focused on the aspect of causes of wage differentials in Uganda; a case study of
MLHUD. The study was conducted by taking sample statistics particularly wage,
educational level, age bracket, working experience and gender of employees of MLHUD.
The research covered the period of the financial year 2013/14. MLHUD consists of three
14. 4
(3) sub sectors namely: Lands, Housing and Urban Development. The Ministry is
responsible for providing policy direction, national standards and coordination inter alia,
on all matters concerning Lands, Housing and Urban Development. The Ministry is also
responsible for reviewing and putting in place policies and laws to ensure sustainable
land management promote sustainable housing for all and foster orderly urban
development in the country. It is located Plot 13 - 15 Parliament Avenue, century house
Kampala Uganda.
1.6 Significance of the study
The study will help policy makers in identifying the major causes of wage differentials so
as to make appropriate policies. This study will also be of great significance to
academicians because it will provide a foundation for other academic purposes. The
study findings will aid the government and other agencies in initiating a process of
revising the labor market so as to accommodate the new and emerging challenges that
must be addressed. The study also will help other researchers on the related topic by
providing them with literature to be used in their reviews.
15. 5
CHAPTER TWO
LITERATURE REVIEW
2.0 Introduction
This section contains the review of literature related to the study based on the works of
other scholars. The study focuses on the causes of wage differentials in Uganda with
MLHUD as a case study.
2.1 Gender and Wages
According to Dr. H. L. Ahija (2012), Institutional factors such as discrimination on the
basis of sex among others make labor markets imperfect and give rise to wage
differentials. In many countries, women are paid less than men for the same work.
According to consad research corp, 2009), one of the main reasons why women interrupt
their careers is motherhood: specifically, bearing and raising children. Thus, explanatory
factors relating to motherhood generally are included in statistical analyses investigating
the gender wage gap. In the recent past, several researchers have conducted studies that
have focused expressly on the relationship between motherhood and women's earnings.
[Anderson, Binder, & Krause, 2003; Budig & England, 2001; Dey & Hill, 2007; Johnson,
2008]
Budig and England report that, in their baseline analysis, having children is associated
with a 7.3 percent reduction in the wages of mothers. After the effects of the mothers'
absence from the labor force and their consequent diminished accumulation of pertinent
experience are taken into account statistically, however, the reduction in wages is
decreased to 4.7 percent. Then, after accounting statistically for job characteristics that
might be especially appealing to mothers, such as part-time status or flexible work
schedules, the reduction is decreased further, to 3.7 percent.
A study by Ssebagala (2007) found out that difference in wages between men and women
averaged around 39% (with men at the higher end of the scale). More recently, the
Ministry of Finance, Planning and Economic Development (2009) established that there
is a female disadvantage in the Ugandan labour market. It revealed that the average
monthly wage of women is about 30% less than the average wage of men.
16. 6
2.2 Training/ Educational level and wages
According to Dr. H. L. Ahija (2012), the first important factor that causes wage
differentials in workers and therefore wages earned by them is that various workers differ
in skills/training.
He considered wage of computer engineers and unskilled workers. To become a
computer engineer, one requires a lot of education and training to acquire the skills.
On the other hand, unskilled workers do not have to spend time and money for
obtaining education and training.
The result is that not only demand for computer professionals is high but also supply is
relatively small. As illustrated below
Panel A Panel B
Y Y S2
Wage rate Wage rate D2
D1 D1 S1
W1
W2
D1
S1
N1 S2 N2 D2
0 Number of unskilled workers X 0 X
Number of computer engineers
Source: Modern Macroeconomics Theory and Application (Dr. H. L. Ahija, 2012).
According to Dr. H. L. Ahija (2012), Panel A shows the determination of wages for skilled
workers. The demand for computer engineer is D1D1 is high and supply S1S1 is relatively
low.
The wage rate for computer engineers is determined by these demand and supply curves.
0W1 which is much higher than wage rate 0W2 of the unskilled workers as shown in Panel
B.
D2D2 represents demand for unskilled labor which is low and supply for them is depicted
by S2S2 is relatively large. Therefore the wage rate of unskilled laborer is low, it should be
noted again that demand for unskilled worker is small because of lack of skill, education
17. 7
and training. Their Marginal Productivity is low and their supply is large because those
who cannot spend time and money in acquiring education and training can get
employment as unskilled workers. It is thus clear that the differences in wages can be
explained by the demand-supply analysis.
According to Dewett and Varma (2000), Wages depend on the level of efficiency for
example one industry may require a higher level of efficiency which is acquired by
education and training followed by practical experience involving heavy expenditures.
Wages in such industry will naturally be higher than in an industry where no such is
needed. For example the reward for a banker who has taken three years to learn his job is
bound to be greater than that of a cleaner who is fit to start his work after just briefing
him or her.
According to N.Mankiw (2002), Firms use educational attainment as a way of sorting
between high-ability and low-ability workers. Education makes workers more productive
and increasing education levels for all workers will increase productivity and thereby
wages.
Most often people who have high educational qualifications earn more wages as
compared to those with low qualifications. More educated people are considered to have
high expertise and more productive at work.
According to N. Mankiw (2002), Education raises wages because firms (demanders of
labor) are willing to pay more for the highly educated because they have higher marginal
products and Workers (suppliers of labor) are willing to pay the costs of education only if
there is a reward for doing so.
2.3 Wages and working Experience
According to Christian. D, Meghir.R (2003), the returns to experience for skilled workers
can be substantial. In the first place, 2 years of work, following formal training, wages
grow at 7% and then at 6% a year. The returns decline thereafter, but even in the longer
run experience leads to a wage growth of 1.2% a year.
For the unskilled workers, there are substantial returns in the first two years (10% and
8%) but they become effectively zero beyond three years. In addition to this growth due
to experience, the wages of unskilled workers also grow early on via improved job
matches achieved by job mobility.
18. 8
2.4 Summary of literature review
Wage differentials are inevitable differences in skills, talents, physical efforts, industries,
risks, responsibilities, age, and educational levels among others
The complete elimination of wage differentials would require all workers to be
homogenous; all jobs would have to display identical monetary advantages and
disadvantages; there must be perfect knowledge and mobility of labor.
19. 9
CHAPTER THREE
RESEARCH METHODOLOGY
3.0 Introduction
This section gives an overview of various procedures and methods which will be used by
the researcher. The methods and procedures include research design, types and sources
of data, sample selection and size, data collection methods, data analysis and the
limitations encountered in the study.
3.1 Research Design
A research design is a systematic plan to study scientific problem. The researcher used a
descriptive design, which is a method of collecting information by interviewing or
administering a questionnaire to a sample of individuals. It can be used when collecting
information about people’s attitudes, opinions, habits, or any of the variety of education
or social issues. The researcher used quantitative and qualitative research methods.
Quantitative methods were applied to by the researcher especially where figures were
availed for analysis and qualitative methods in cases where information was not in
figures. Descriptive design helps to describe phenomena, defines what the thing is, how
often it occurs and so helping the researcher to get a sense of something. However the
design cannot prove what causes phenomena and takes a lot of time to study
3.2 Data Types and Sources
The researcher used cross-sectional data; this data type was collected once in the study
and primary data, a type where information is obtained directly from first-hand sources
by means of surveys, observation or experiment. The primary data is advantageous
because it is unbiased, basic and original information is obtained was gotten from the
respondent for themselves.
3.3 Sample Selection and Size
The researcher used probability sampling technique of simple random sampling (SRS). A
simple random sample is one drawn in such a way that all possible samples of the same
size have the same probability of being the selected sample. The technique is cheap,
simple and easily applied to a small population and ensures bias is minimized because
20. 10
samples are chosen randomly. The researcher used a sample of 70 respondents from
MLHUD.
3.4 Data Collection Method
Self-administered questionnaires were used. The questionnaires were open-ended, where
the respondents answered by supplying a response, by entering a number, a word or a
short text; closed ended, where the respondents were asked to tick the chosen answer
from a multiple set of answers and contingency questions, which involved filter questions
that directed the respondents to answer a relevant set of specialized questions and
instructs others respondents to skip to another question. Self administered
questionnaires minimized interviewer’s bias and the respondent was given enough time
to answer the questions.
3.5 Data Analysis
The data collected were entered, coded and edited in Microsoft Office Excel 2007 to
ensure accuracy, completeness and relevancy.
Data analysis was done in SPSS Statistics 17.0 and Eviews 3.1 which are statistical
packages. An ANCOVA model of a Log-linear functional form was run by OLS method as
shown below;
LogWi = β0 + β1Gi + β2Li + β3Xi + εi
Where;
LogW= Logarithm of Monthly wage.
G= Dummy for Gender.
L= Dummy for Educational level.
X= Working experience.
β0 - β3 = Coefficients of the variables.
ε = the error term.
The error term includes those factors that are considered to affect wages such as location
of the job, age, risk of the job, talent, ability, efficiency, work effort, bargaining power,
responsibility at work, seniority, chance, human capital and marginal productivity of
labour.
21. 11
Output presentation, interpretation of results and drawing of final conclusions were
done in Microsoft Office Word 2007.
3.6 Limitations
Time factor. There was inadequate time for the whole research process since it was done
concurrently with internship.
Finances needed for printing, Binding and information search among others were also
inadequate as the researcher had to meet the costs.
Some respondents gave inappropriate and irrelevant responses in the questionnaires
while some filled the questionnaire partially.
Some respondents were too reluctant to fill the questionnaire. This slowed down the
process of data collection.
22. 12
CHAPTER FOUR
DATA ANALYSIS, INTERPRETATION AND PRESENTATION
4.0 Introduction
In this chapter, the researcher analyses, presents and interprets the findings of the study.
The findings are based on primary data obtained using questionnaires. The presentation
was done using tables; data analysis was done using SPSS and EVIEWS.
4.1 Demographic Presentation and Interpretation
Table 1: Table Showing Gender Distribution of the Respondents
Gender Frequency Percent Cumulative Percent
Female 25 35.7 35.7
Male 45 64.3 100.0
Total 70 100.0
Source: primary data
From the above table, 25 out of the 70 respondents were females which represent about
35.7% while 45 out of the 70 respondents were males constituting 64.3%. This means that
males were more willing to respond to the study.
Table 2: Table Showing Age Distribution of the Respondents
Age bracket Frequency Percent Cumulative Percent
18-30 5 7.1 7.1
31-40 20 28.6 35.7
41-50 23 32.9 68.6
51-60 22 31.4 100.0
Total 70 100.0
Source: primary data
23. 13
From the above analysis, it is shown that 5 out of the 70 respondents are in the age
bracket of 18-30 constituting 7.1% of the sample size. 20 out of 70 respondents are in the
age bracket of 31-40 constituting 28.6%, 23 out of the 70 respondents are in the age
bracket of 41-50 which constitutes 32.9% and 22 out of 70 respondents are in the 51-60
age bracket constituting 31.4%.
Table 3: Table Showing Marital Status of the Respondents
Marital status Frequency Percent Cumulative Percent
married 39 55.7 55.7
Single 25 35.7 91.4
widowed 6 8.6 100.0
Total 70 100.0
Source: primary data
As shown in the above table, 39 out of 70 respondents were married constituting 55.7% of
those interviewed, out of the 70 who responded 25 were single representing 35.7% and 6
out of the 70 respondents were widowed which constituted 8.6% of the respondents.
24. 14
4.2 Presentation of ANCOVA Regression Analysis.
Table 4: Table Showing Regression Results
Dependent Variable: LOGWAGE
Method: Least Squares
Date: 08/30/14 Time: 00:43
Sample: 1 70
Included observations: 70
Variable Coefficient Std. Error t-Statistic Prob.
C 11.63940 0.161865 71.90809 0.0000
DMALE 0.091284 0.071477 1.277112 0.2063
DBACHELORS 1.640921 0.150887 10.87519 0.0000
DDIPLOMA 1.071867 0.175005 6.124783 0.0000
DMASTERS 1.870854 0.135178 13.83995 0.0000
DUACE 0.474132 0.202537 2.340960 0.0225
DUCE 0.201554 0.155888 1.292942 0.2008
EXPERIENCE 0.018487 0.003763 4.913175 0.0000
R-squared 0.885712 Mean dependent var 13.26580
Adjusted R-squared 0.872809 S.D. dependent var 0.759357
S.E. of regression 0.270816 Akaike info criterion 0.332459
Sum squared resid 4.547173 Schwarz criterion 0.589430
Log likelihood -3.636058 F-statistic 68.64131
Durbin-Watson stat 1.501437 Prob(F-statistic) 0.000000
Source: primary data
25. 15
Regression Equation;
LOGWAGE = 11.6393992 + 0.0912844822*DMALE + 1.64092065*DBACHELORS +
1.071867417*DDIPLOMA + 1.870853859*DMASTERS + 0.4741317745*DUACE +
0.2015541534*DUCE + 0.01848652537*EXPERIENCE
From the above table;
The benchmark category is Female and PLE
The regression coefficient (11.63940) for C shows the average logWage for the benchmark
category and is about Ugx 11.64. This is statistically at 5% level of significance since the p-
value (0.000) <0.05. Thus keeping other factors constant, the average logWage of a
respondent who are females or with PLE educational level is about Ugx11.64.
The coefficient (0.091284) for dummy for males shows that keeping other factors
constant, the average logwage of males is higher by about Ugx 0.09 than those of females.
But this is statistically insignificant at 5% level of significance since the p-value
(0.263)>0.05.
The coefficient (1.640921) for dummy for bachelors implies that keeping other factors
constant, the average logwage of people with bachelors’ degree is higher by about Ugx
1.64 than those of PLE. This is statistically is significant at 5% level of significance since
the p-value (0.000) <0.05.
The coefficient (1.071867) for dummy for Diploma shows that keeping other factors
constant, the average logwage of diploma holders is higher by about Ugx 1.07 than those
of PLE. This is statistically significant at 5% level of significance since the p-value (0.000)
<0.05.
The coefficient (1.870854) for dummy for masters implies that keeping other factors
constant, the average logwage of masters’ degree holders is higher by about Ugx 1.88 than
those of PLE. This is statistically significant at 5% level of significance since the p-value
(0.000) <0.05.
The coefficient (0.201554) for dummy for UCE means that keeping other factors constant,
the average logwage of Ordinary level leavers is higher by about Ugx 0.20 than those of
PLE. But this is statistically insignificant at 5% level of significance since the p-value
(0.2008) >0.05.
26. 16
The coefficient (0.474132) for dummy for UACE shows that keeping other factors
constant, the average logwage of Advanced level leavers is higher by about Ugx 0.47 than
those of PLE. This is statistically significant at 5% level of significance since the p-value
(0.0225) <0.05.
The coefficient (0.018487) for working experience means that, keeping others factors
constant a unit increase in working experience on average increases logwage by about
Ugx 0.02. This is statistically significant at 5% level of significance since p-value (0.000) <
0.05
The value (0.885712) of the R-squared implies that from the model 88.6% of the
variations in wages are explained by differences in gender, educational level, working
experience and age groups. This is a good fit for the model.
This signifies that the remaining 11.4% of the variations in wages are explained by all
factors in the error term which included age, location of the job, risk of the job, talent,
ability, efficiency, work effort, bargaining power, responsibility at work, seniority, chance,
human capital and marginal productivity among others.
The Prob (F-statistic) 0.000000<0.05 for F-statistic (68.64131) implies that the overall
coefficients of the model are statistically significant at 5% level of significance.
27. 17
CHAPTER FIVE
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
5.1 Summary
The study had a main objective as the causes of wage differentials and was specifically
carried out on employees of MLHUD. Both male and female employees were involved in
this study and this gave results which are in this summary.
The study reveals that male employees contributed easily to the study than their female
counter parts taking 64.3% of the 70 respondents as shown in table 1
The study as well reveals that the biggest number of respondents were in the 41-50 age
bracket taking 32.9% and 51-60 age bracket with 31.4% of the 70 respondents as shown in
table 2
The findings further show that most of the employees were married with 55.7% and the
singles constituted 35.7% of the 70 respondents.
More so the findings found out that gender had an insignificant effect on wage while
educational level and working experience had significant effects on wage.
The findings based on the regression analysis revealed that 88.6% of the variations in
wage are explained by differences in gender, educational level, and working experience.
There are other factors which have not been considered in the study but also cause wage
differentials which account for the remaining 11.4% of the variation in wages.
5.2 Conclusions
Based on the findings, out of the three causes of wage differentials used in the study
namely gender, working experience, and educational level, the first variable is
insignificant in influencing wages of most employees with educational level and working
experience seen to have significant effect on wages. This means that looking at the entire
employees’ population, working experience and educational level are the major causes of
wage differentials.
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Much as the study focused mainly on these causes namely gender, working experience
and educational level, it is worth to mention that there are other causes of wage
differentials which have not been looked at in this study by the researcher such as luck,
bargaining power, age, work effort, ethnicity and therefore these offer areas for further
studies.
5.3 Policy Recommendations
The Government of Uganda need to fix a minimum wage for all employees in the labor
market to curb down the problem of differences in earnings by workers.
There is need to formulate a defined wage structure for formal employment for all
employers to based on qualifications, working experience and scope of work among
others. Determinants of wages should be clear to everyone.
There is need to introduce free education for all citizens to enable workers to get the
necessary educational level to eligible for higher paying jobs.
The government of Uganda should adopt teaching techniques aimed at exposing
students to practical training and hands on experience in order to enable them to link
theory to practice in the real world so as to meet the labor market demands.
There is need for a further study to be conducted on The Impact of Wage Differentials on
the Economy of Uganda.
29. 19
References
Modern Microeconomics Theory and Application, Revised Edition by Dr.
H.L.Ahuja.
Elementary Economic Theory, Millennium Edition by K.K.Dewatt, J.D
Varma.
Modern Labor Economics Theory and Public Policy, 6th
edition Ronald G.
Ehrenberg, Robert Smith.
Economics in Context by Susan Grant, Chris Vidler.
Labour market in the long run by Osman Zaim /lect15os.ppt.
Principles of microeconomics by Gregory Mankiw, second Canadian
edition, 2002 Nelson.
www.mlhud.go.ug/aboutus.html.
Ministry of Lands, Housing and Urban Development sector strategic plan
for statistics 2007/2008-2011/12.
Ministerial policy statement Ministry of Lands, Housing and Urban
Development FY 2013/14.
The Review of Economic Studies Limited; Wages, Experience and Seniority
by Christian Dustmann and Rostas Meghir, University College London,
Institute for Fiscal Studies and CEPR, Nov 2003.
Newell, A.; Reilly, B. (2001). "The Gender Pay Gap in the Transition from
Communism: Some Empirical Evidence". Economic Systems 25 (4): 287–
304. doi:10.1016/S0939-3625(01)00028-0. edit
Ogloblin, C. G. (1999) "The Gender Earnings Differential in the Russian
Transition Economy. Industrial and Labor Relations 52(4): 602-634.
Katz, K. (2001) Gender, Work and Wages in the Soviet Union. A Legacy of
Discrimination Palgrave. ISBN 0-333-73419-9.
McAuley, A. (1981) Women's Work and Wages in the Soviet Union. George
Allen & Unwin. London. ISBN 0-04-339020-X.
Ogloblin, C. G. (1999) "The Gender Earnings Differential in the Russian
Transition Economy. Industrial and Labor Relations Review Vol. 52, No 4.
(p. 604).
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Apendix1: Questionnaire
Dear Respondent,
I am WESIGYE ALEX a third year student of Kyambogo University carrying out a
research on the causes of wage differentials in Uganda with a case study of Ministry of
Lands, Housing and Urban Development
I kindly request you to respond to these questions as you can and in their applicability.
The research is meant for academic purposes for me to be awarded a Bachelor of
Economics and Statistics Degree of Kyambogo University. The information that you will
provide will be treated with utmost confidentiality.
TICK OR FILL IN WHERE NECESSARY
SECTION ONE: DEMORGRAPHIC CHARACTERISTICS
Qn 1. Gender
(i) Male
(ii) Female
Qn 2. Age
(i) 18-30
(ii) 31-40
(iii) 41-50
(iv) 51-60
Qn 3.Education level
(i) None (ii) PLE (iii) UCE (iv) UACE
(v) DIPLOMA (vii) BACHELORS (viii) MASTERS
Others specify………………………………………………………………....................................
Qn 4.Maritual Status
(i) Married
(ii) Single
(iii) Widowed
Qn 5. Occupation…………………………………………………………………………………..
31. 21
Qn 6. For how long have you worked in the above company? (Years)………………
SECTION TWO: SOCIO-ECONOMIC STATUS
Qn 7.Are you paid on monthly basis?
(i) Yes
(ii) No Skip Qn8 to Qn9
Qn 8. Your monthly wage is UGX...................................................................................
Qn 9.For how many hours do you work per week..........................................................
Qn 10.Your hourly wage is UGX………………………………………………………...................
SECTION THREE: ATTRIBUTES TO THE STUDY
Qn 11. Are all workers paid the same wage?
(i) Yes
(ii) No
Qn 12. If no why do workers in earn different wages based on
(i) Age
(ii) Bargaining Power
(iii) Ethnicity
(iv) Working Experience
(v) Occupation
(vi) Educational level
(vii) Gender
(viii) Trade unions
Others specify…………………………………………………………………………
Qn 13. How do you think that this difference affect your work/motivation?
…………………………………………………….……………………………………………………………………………
…………………………………………………………………………………………………………………………………
Qn 14. what can be done to improve the above?
………………………………………………….………………………………………………………………………………
……………………....................………………………………………………………………………………………..
Thanks for your time, GOD Bless you!!
