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Women and Unemployment in Bahir Dar City, Ethiopia: Determinants and

Consequences

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American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS)
ISSN (Print) 2313-4410, ISSN (Online) 2313-4402
© Global Society of Scientific Research and Researchers
http://asrjetsjournal.org/

Women and Unemployment in Bahir Dar City, Ethiopia:

Determinants and Consequences

Wubante Ayalew Dessie

Debre Birhan University, Debrebirhan, Ethiopia

Email: webeayalew@gmail.com

Abstract

Even if women make up half of the world’s population, their contribution to measured economic activity,
growth, and well-being is far below its potential. Besides, employment of women in economic sectors has
important effect on their life, family and the country as a whole. However, the gap between women and men in
paid employment remains wide in many parts of the world. These issues of women encompassing determinants
and consequences of unemployment on them are not well articulated. Thus, the main objective of this study was
to examine the socio-cultural and demographic determinants of employment status of women and the
consequence of unemployment on women in Bahir Dar City, Amhara region. To carry out this study, mixed
research approach specifically convergent parallel design was used. To investigate this, primary and secondary
data sources were utilized. Additionally, questioner and in-depth interview were used as the data gathering
instruments for quantitative and qualitative respectively. Besides, 388 respondents were selected by using
simple random sampling technique for quantitative technique and 11 participants were selected by purposive
sampling technique for qualitative technique. The analytical techniques used in this study were descriptive
statistics such as frequency of tables as well as cross tabulation and binary logistic regression for quantitative
data and thematic way of data analysis for qualitative one. The descriptive statistics result showed that 61.1 %
were employed where as 38.9 %were unemployed. In view of that training skills obtained, family size and
household headship were found to be the significant determinants of women’s employment status. Moreover ,
poor living standard and dependency, domestic violence, unwanted marriage and unwanted pregnancy, low
level of social participation (isolation ), hopelessness and anxiety (stressful life) , addiction by intoxication of
alcohol and other forms of drug, less satisfaction in marital life , divorce , prostitution , allowing to be the victim
of sexually transmitted disease like HIV-AIDS, increasing future shocks were found to be the consequence of
unemployment on women in the study area .Furthermore, the study has discovered that it is still not easy for
many women to enter the formal labor market even though the situation has altered over time. Thus, the major
challenge encountering the present government of the city is how to address this issue.

Keywords: Unemployment; gender; women; gender division of labor and discrimination.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

1. Introduction

Women make up half of the world’s population, but their contribution in economic activity, growth, and well-
being is far below its potential, with serious macroeconomic cost. Contrary to this, women employment in
economic activities has several valuable effects for women and their families in particular and the economy in
general. Despite significant improvement in recent decades, labor markets across the world remain divided
along gender lines, and progress toward gender equality seems to have delayed. In many countries, distortion
and discrimination in the labor market hamper women’s options for paid work, and female representation in
senior positions and entrepreneurship remains low [41].

Besides, as far as social networking is concerned, there is a significant gender disparity across the world.
Women carry the burden of housework, which limits their time in developing social networks and in improving
their employment prospects. Therefore, the nature of women work obliges them to spend less time in social
networking as compare to that of their counter parts [28].

Likewise, gender unemployment gaps are at least as important as the gaps in other labor market outcomes.
Unemployment is not necessarily affecting the majority of the population in the same way. Thus, the impact of
unemployment on women is more serious than men in different contexts [11].Unlike the case for most men,
women’s unpaid labor in productive activities is extremely imbricate in the patriarchal temperament or nature of
the household and its property, and therefore a material articulation of their lack of social freedom and
independence in the overall economy and society [49].The continued mediation of a large part of women’s
productive/economic labor and incomes derived from such unpaid labor by the household represents conditions
of both economic dependence and patriarchal domination in the lives of these women workers [36].

Moreover, when both paid and unpaid works are accounted for women and men spend analogous amounts of
time working on an average day. Women’s ability to participate in the labor market is constrained by their
higher allocation of time to unpaid work. On average, women spend twice as much time on household work as
men and four times as much time on childcare thereby freeing up time for male household members to
participate in the formal labor force [59].

Owing to these facts, women contribute substantially to economic welfare through large amounts of unpaid
work such as child-rearing and household tasks, which often remains unseen and unaccounted for in GDP
[41].Gender inequalities in the labor market can also be seen in terms of earnings differentials. Evidence shows
that women are paid less than men for equivalent work. Women’s earnings range from a low of around 50
percent to around 85 percent of men’s earnings. In some countries the ratio has fallen, in others it has raised, in
some there is no consistent rise or fall [70].

However, concern regarding marginalization of women in employment has engaged those involved in women’s
studies since its inception in the 1970s. In the 1960s, before the advent of specialized women’s studies, female
work participation had been declined, but generally thought to be a transitory phenomenon as the economy
moved from subsistence agriculture and household industry to modern industry. The advances of the women’s

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

movement, the enactment of laws forbidding sex discrimination, increases in female enrollment in higher
education and professional schools, the steady increase in women’s labor force participation, and reductions in
gender stereotyping in both education and employment all contributed to this trend [71].

In line with these, the Copenhagen conference (1980) recognized that women would be given equal access to
education, health, employment opportunities in order to achieve equality, development and peace throughout the
world. Relieving restraint to women's labor market participation; whether through legislation or provision of
substitutes for women's time spent on domestic work (for example, child care) may help to break the link
between female headship and poverty [46].

Contrary to these, unemployment has an impact on family cohesion, level of poverty and it results in different
social problems like civil war, violence, prostitution, breakup of families and alcoholism due to hopelessness. It
is accompanied by bad occupational prospects and impending economic deprivation, placing the well-being of a
future family at risk [63].

Also, unemployment is often psychologically and financially devastating for those who experience it and for
those who are dependent upon them. There is substantial evidence of the negative health effects for the
unemployed person. In economic terms, unemployment is a major loss of valuable productive resources with all
that implies for economic growth and the standard of living of the whole community. The impacts are not
evenly spread. Particular parts of the community are more severely affected than others, exacerbating problems
of inequality within metropolitan areas and between the cities and some regional areas [71].

Generally, at a global level, female unemployment is higher compared to that of male unemployment. They also
suffer from a difference in the quality of employment in comparison to men. Vulnerable employment which
comprises contributing family workers and own account workers (as opposed to wage and salaried workers) is
more widespread for women than men [38].

In most developing countries in general, and in sub-Sahara Africa in particular, the worst-affected groups in job
crisis are women, young people, the disabled and the elderly. Women’s unemployment problems arise from a
variety of factors including cultural prejudices, educational difference between men and women and a lack of
marketable skills [39]. Unemployment (mainly as an urban phenomenon) and underemployment continue to be
serious social problems in Ethiopia despite some improvements in recent years [50].

Similarly, the Ethiopian economy has witnessed tremendous improvement in the labor market; however,
unemployment remains widespread in urban areas. Policies need to address the poor labor market conditions for
women in both the rural and urban areas as well as implement strategies which benefit the rising number of
educated youth and women entering the labor market [15].

Currently, there are encouraging trends in Ethiopia with regard to female participation in education and the labor
force. However, women representation in the formal sector and in professional and managerial jobs is not
comparable with that of men. Unemployment and underemployment are more prevalent among women than
men. As noted earlier, it is also true that more of the employed women are concentrated in the informal

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

economy. To deliver successful results in terms of improving women's labor force participation and improve
their presence in the formal sector, the government should focus on skill development, access to productive
resources and social and economic protection through institutional support [56].

To sum up, unemployment is more of a problem of women than that of their counterparts. This issue dictates the
researcher to consider the determinants and consequences of unemployment of women in Bahirdar town as part
of Ethiopia. The existing circumstance motivates for improving the labor market participation of women. For
this rationale, there is a need to examine the determinants and consequences of unemployment of women. In line
with this, the objective of this study is to study the determinants and consequences of unemployment of women
in the study area. The examination is accomplished in the course of a review of relevant literature and findings
on some demographic and socio-cultural determinants of women employment status and the consequence of
unemployment on women.

1.1. Objectives

General Objective of the Study

The general objective of this research is to study the determinants and consequences of unemployment of
women in Bahir Dar City.

Specific Objectives

 To examine the demographic as well as socio-cultural factor that determines women employment
status.
 To investigate the social, economic and psychological consequences of unemployment on women in
the study area.

2. Materials and methods

2.1. Description of the Study Area

The Metroplolitican area of Bahirdar is found in the Bihar Dar Zuria Woreda of the previous administration. It is
specifically located in the central part of Amhara National Regional State encircling the periphery of Lake
Tana’s Southern tip. The Metroplolitican area of Bahir Dar stretches some about 25 km radius from the center
of Bahir Dar City proper. It includes the surrounding three small urban centers such as Zegie in the North West,
Meshenti in the South, and Tis Abay in the East. The approximate geographical coordinates of Bahir Dar
Metroplolitican area is between 11o2’.-11o39’North latitude and 37o15’-37o 40’East longitude.

Bahir Dar is one of the leading tourist destinations in Ethiopia, with a variety of attractions in the nearby Lake
Tana which is the source of Blue Nile River. The city is known for its wide avenues lined with palm trees and a

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

variety of colorful flowers. In 2002 it was awarded the UNESCO Cities for Peace Prize for addressing the
challenges of rapid urbanization. Based on 2007 Censuses conducted by central statistics agency of Ethiopia
(CSA), this city has a total population of 221,991. The annual population growth rate is also estimated to be
5.5%.

From this total population 108,456 and 113,535 were men and women respectively. The ethnic composition of
the city shows that 96.2% of the residents are Amhara, 1.1% Tigre, 1.1 Oromo%. 0.3% Agaw and 0.2%
Guragie. This shows the dominance of Amhara ethnic group in the area .In addition; there are different religious
groups in the city. The 2007 census report shows that 89.7% of the residents are orthodox Christian, 8.5% Islam,
1.6% protestant 0.04% catholic and the remaining are from traditional and other [12]. See below figure 1.

Figure 1: The ethnic composition

2.2. Research Approach

According to author [21] noted that, there are four schools of thought about knowledge claims. Those are
positivism, constructivism, advocacy participatory, and pragmatism. Constructivists develop subjective
meanings of their experiences-meanings directed toward certain objects or thing. Accordingly, advocacy
participatory claims specific issues needed to be addressed that speak to important social issues of the day,
issues such as empowerment, inequality, oppression, domination, suppression, and alienation

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

However, the researcher’s world view is pragmatic paradigm. The rational for selecting this from other
paradigms is that the researcher wants to investigate the consequence of unemployment on women’s life and
determining demographic and socio-cultural barriers for employment of women. For this purpose, pragmatic
paradigm is well suited since their maxim postulated that the meaning of some thing is to be determined by the
experience or practical consequence of belief in or use of the expression in the world. They are consequence
oriented and problem centered. The issue of unemployment of women has been discussed by other researchers
but the researcher need to see this in Bahir Dar City due to that the researcher doesn’t accept the existence of
one universal truth rather it depends on the practical experience of the situation.

2.3. Research Strategy

In mixed research approach, the researcher used convergent parallel design/concurrent procedures. It occurs
when the researcher uses concurrent timing to implement the qualitative and quantitative strands during the
same phase of research process. In a concurrent study, the quantitative and qualitative data collection may be
presented in separate sections, but interpretation combines the two forms of data. In this design, the investigator
collects both forms of data at the same time during the study and then put together the information in the
interpretation of the overall. Also, in this design, there is larger data collection procedure in order to analyze
different questions [21].

2.4. Data Sources

Primary and secondary data sources have been used for this study. Primary data’s were obtained from in-depth
interview and questionnaire. On the other hand, secondary sources were collected from published as well as
unpublished books.

2.5. Data Gathering Instruments

The data gathering instruments of this study were in-depth interview for qualitative study and questionnaires for
quantitative study.

2.5.1. In-Depth Interview: - This instrument was used to gather deep information about the issues undertaken.
In-depth interviewing is a qualitative research technique that involves conducting intensive individual
interviews with a small number of respondents to explore their perspectives on a particular idea, program, or
situation. In-depth interviews are useful when you want detailed information about a person’s thoughts and
behaviors or want to explore new issues in depth [13].

Hence, the researcher opted to use this for qualitative technique so as to investigate the social, economic and
psychological consequence of unemployment on women by their own voice.

3.5.2. Questionnaires: Close ended questionnaire was used. Questionnaires allow the researcher to find out
information such as facts, attitudes and opinions. They are a simple way to gather short responses to questions
from people.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

2.6. Sampling Techniques

The researcher used purposive sampling technique for selecting the participants’ of in-depth interview. In
purposive sampling, sampling is done with a purpose in mind. We usually would have one or more specific
predefined groups we are seeking. Purposive sampling can be very useful in situations where you need to reach
a targeted sample quickly and where sampling for proportionality is not the primary concern. With a purposive
sample, you are likely to get the opinions of your target population, but you are also likely to overweight
subgroups in your population that are more readily accessible [3].

On the other hand, the researcher used simple random sampling for selecting the respondents of quantitative
technique. Here, the participants of the qualitative study have been incorporated in randomly selected
respondents. We are making random sampling when the process, through which we choose the sample,
guarantees that all the possible samples that we can take from the population have the same probability of being
chosen, this is, all the elements of the population have the same probability of being chosen to belong to the
sample[43].

2.7. Sample Size

The sample size for in-depth interview was 11 participants. On the other hand, for quantitative study, 388
respondents were selected by using simple random sampling technique out of 13,647 women in the study area.

2.8. Sampling Procedure

Bahir Dar City administration has 17 kebeles; according to the current administration system. This kebeles
clustered in to nine groups as follows : Keble (7,17),(1,2,12),(8,9,10),(11), (4,5,6),(3,15),(13),(14),(16). The
researcher has selected Keble 11 because there are high numbers of unemployed women in that Kebeles when
the researcher compares its unemployment level with that of other kebeles. According to the Keble
administration, there are 1889 unemployed women in that Keble.

The study populations were women who are within labor force as economically active population. The
interviewees and respondents were selected from the total number of women who are within the labor force of
the kebeles, hence would have difference in their life experiences. The study has seen a comprehensive picture
of the lives of women through their own voices. Interview has been conducted with unemployed women those
who are within the labor force.

When we come to quantitative research method, respondents have been selected randomly. The researcher has
adopted the mathematical formula below for determining the sample size for quantitative data [53].

n= N

1 + N (e) 2

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

Where, N is the total women, and e is the error or confidence level

The conventional confidence level of 95% used to ensure a more accurate result from the sample. Based on this,
the error term would equal to 0.05. Using the total Population of 13,647 and error margin of 0.05, the sample
size has been calculated as follows:

n=13,647

1+13647(0.0025) = 388

Hence, out of the total population of 13,647 unemployed women, sample size of 388 respondents was taken.

2.9 Trustworthiness for Qualitative Section

Trustworthiness is seen as strength of qualitative research. It used to suggest determining whether the findings
are accurate from the standpoint of the researcher, the participants, or the readers of an account. In ensuring trust
worthiness, the following strategies have been employed for this study project. The investigator have employed
rich and deep explanation to convey the findings by examining evidence from the sources and utilize it to
construct a reasonable explanation for themes which have been provided by the investigator .

2.10. Validity and Reliability for Quantitative Section

A data collection instrument's reliability is interpreted as the consistency with which it measures the target
attribute and concerns a measure of accuracy. In order to ensure reliability of the instrument in this study, the
majority of the variables adopted from the research conducted by authors [52] and [48].

Additionally, a pilot study was conducted for some new variables recommended by Mesifin. This involved
testing the actual tool on a small sample taken from the general population. A week before execution of the
study, the actual questionnaire was administered to 20 female 15-65 years of age in the study area , in order to
ensure the questions were clear. After analyzing this, questions which were not clear were rephrased to ensure
that appropriate responses would be obtained in the future.

On the other hand, Validity of an instrument concerns the extent to which the research measures what it asserts
to measure without bias or distortion. To test the validity of the instrument, a copy of the questionnaire was
submitted to the known researcher to examine whether the number and type of items in the questionnaire
measured the Concept or construct of interest (content validity). Generally, questions in the tool were developed
based on findings from previous studies and the literature reviewed.

2.11. Ethical Considerations

The researcher first has requested permission from those in authority in the study area. As well, the researcher
asked the voluntariness of participants and respondents. Data collection was continued after introducing the
participants about the research objectives and proceeds after gaining their informed consent verbally.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

Participants and respondents have been invited to a small room that ensures their privacy and confidentiality.
The researcher has guaranteed the right to ask questions and secure the respondents as well as participants’
privacy. Moreover, the researcher has not pointed out the names of the participants and respondents of the study.

3. Results
3.1. Quantitative results :
3.1.1. Descriptive statistics

Figure 2: Education status of respondents

Figure 3: Respondents employment status

Note: all other variables carried out like these. Please refer the appendix:

3.1.2. Cross tabulation on the relationship between dependent variable (women employment status)
and demographic as well as Socio-cultural status of respondents (the independent variables). The Pearson
Chi-square statistics was used as a measure of association at 95% confidence level. See table three in the
Appendix.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

A. Marital status and women employment status

Marital status Employed Unemployed

Unmarried 15 10
Married 177 100
Divorced 23 22
Widowed 20 19
2
Chi-square(x ) =5.025

P=0.285

The Chi square result showed that, there was no association between marital status and women employment
status (p=0.285). Marital status has no significant contribution for women’s labor market participation.

B. Age and women employment status

Variables Employment status with frequency

Age group Employed Unemployed
15-29 93 69
30-44 105 59
45+ 39 23
2
chi-square(x ) =1.604

p=0.448

The Chi-square results showed that, there was no association between age of respondents and women
employment status (p=0.44). Age has no role on women’s participation in the labor.

Note: all other variables carried out like these. Please refer the appendix:

3.1.3. Multivariate analysis (Binary logistic regression results).

Table four: Binary logistic regression results. For further, see table four in the appendix.

Variables B Exp(B) SIG 95%(CI)

Household headship
Wife 0769 2.16 0.015 1.7-3.10

(0.315)
Husband 0.890 2.43 0.002 1.4-4.31

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

(0.292)
Both 1.00
Education status
No education 0.133 1.14 0.84 0.306-4.25

(0.671)
Primary 0.095 1.10 0.88 0.303-4.0

(0.657)
Secondary 0.141 0.86 0.83 0.238-3.16

(0.66)
Territiary 1.00
Training obtained
Yes -0.604(0.26) 0.547 0.022 0.32-0.91
No 1.00
Access of credit
Yes -0.33 (0.289) 0.716 0.249 0.40-1.06
No 1.00
Exposure to mass media
Always -0.3 (0.291) 0.76 0.346 0.43-1.34
Sometimes -0.352 (0.288) 0.73 0.22 0.40-1.23
Not exposed 1.00
Family size
More than five -2.970 (1.060) 0.051 0.005 0.06-0.4
Less than five 1.00

R2=442.473

N=388

Note: Standard error in parenthesis.

A. Goodness of Fit Test

The Hosmer-Lemeshow”s test is one of the recommended tests for overall fit of a binary logistic regression
model. This goodness-of-fit statistic is used to assess the fit of a logistic regression model.

Accordingly, results of Hosmer - Lemeshow”s goodness of fit test showed that the binary logistic regression
was better model than other forms of regression in establishing association between the dependent and
independent variables of the study in Bahir Dar City (p=0.171) since in binary logistic regression, Hosmer-

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

Lemeshow”s Goodness-of-Fit test is good fit in accepting Ho where as bad fit in accepting H1. See table five in
the appendix.

B.House Hold Head Ship and Women Employment Status

The binary logistic regression result indicated that, there was significant relationship between household
headship and women employment status. Compare to a women with a household headed both by woman and
man, the odds of being unemployed for a woman with male headed household higher by a factor of 2.435;
similarly the odds of being unemployed is 2.157 times higher for a woman with a female headed household
compared to a woman with household headed both by woman and man. Thus, house hold headship has a role in
women employment status and a household which had ahead of both male and female having equal power was
preferable.

C.Training and Women Employment Status

The binary logistic regression result showed that , there was significant relationship between training skills
obtained and women employment status .Untrained women were less likely to be employed compare to that of
women with any form of training including business skill training and technical and vocational training at a
factor of 0.547. Hence, training play pivotal role in women employment status.

D. Family Size and Women Employment Status

The binary regression result implied that, there was significant relationship between family size and women
employment status. Women who had family size less than five were less likely to be unemployed at the factor of
0.051 compare to that of family size more than five. Therefore, family size has role in women employment
status.

On the other hand , the binary logistic result showed that ,exposure to mass media , education status of
respondents and access of credit had no statistically significant relation with women employment status at
P=0.34,0.84,0.24 respectively .

3.2. Qualitative Results

3.2.1 Consequences of Unemployment on Women

Accordingly, interviewees of the study were asked to explore the social, economic and psychological
consequence of unemployment. Based on the interviewees, the following are the main consequence of
unemployment on women.

Consequently , unemployment has several negative effects on women such as poor living standard and
dependency, domestic violence, unwanted marriage and unwanted pregnancy, low level of social participation
(isolation ), hopelessness and anxiety (stressful life),over thinking , addiction like intoxication of alcohol and

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

other forms of drug, less satisfaction in marital life , divorce , prostitution , allowing to be the victim of sexually
transmitted disease like HIV-AIDS, increasing future shocks in Bahir Dar City, Ethiopia .

 Some examples of case studies on domestic violence: Increases in male unemployment are associated
with declines in domestic abuse while female unemployment increases the incidence of domestic abuse which
encompassed under domestic violence that resulted in physical and psychological damage [5].

In line with this, one of the interviewee who is in the age of 31 depicts that:

Last week, my husband has been upset due to disagreements with his colleagues and I asked him what was
wrong with you? I have repeated this question, is there anything wrong? Unfortunately, my husband has given
me one box with small stone. Hahah! “Keshengo biretta mistune gebto meta”. Have you seen my face that
looks like not normal due to the force exerted from him during that time? However, I didn’t like to exposed it to
other people even to the police because he is the main bread winner of the household; without him our life is
dark since I cannot generate income to afford my families’ need. The only solution that I had in my hand is
accepting him as he is. Am so sorry! I have exposed many secrets of my life but what if he would reject me? I
don’t like to surface other things beyond this! Please don’t disturb my life!

As to the interviewee, unemployment allows women to be powerless, voice less which in turn to be subjugated
by their husband. This circumstances that women experiencing lead to violation of women’s right.

Similarly, another interviewee who is in the age of 35 having three kids said that:

My husband always frighten me for abandonment (rejection) and beyond that he beats me and I experience
humiliating things (insulting), confinement to home (lack of freedom) and withholding money (unreleased). I
have no power to move any place even to my families’ house without the permission of my husband. Hoff! I have
lost my freedom beyond that he try to kick me in any case that I have tried to give response to his question equal
with him. Am so sorry! Crying……..

According to the interviewee, unemployed women experience restriction of their freedom and they may lose
their physical appearance in case their husband getting upset. Thus, unemployment allows women to be
exploited by their counterparts.

In addition, another interviewee who is in the age of 40 with two kids stated that:

In my day to day ,life slapping or hitting, kicking or dribbling, beatings with any object are very common and I
accept it as day to day life because I had no chance to refuse it. When I express this I have remembered one
thing, one year ago when we were discussed on family issues my husband getting upset and tried to hit me but I
was refused, and said that why you tried to kick or hit me in all cases that disagreements occurred, However ,
he has threaten me that he would reject me in the near future . Soon after that time, I accept all things as it is
rather than asking why questions because I have no answer what if he would reject me.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

Generally, as to the interviewees, unemployment allows women to experience humiliating things and beating
with any object. Beyond this it prohibits them to experience women’s freedom to move from one place to
another place. From these, one can conclude that, unemployment leads women to be the victim of domestic
violence.

 Another case study on Unwanted Marriage and Unwanted Pregnancy: Unemployment allows
women to have unwanted marriage which may result from unwanted marriage. As to interviewees of the study ,
most of the time unemployed women conduct marriage with whom don’t like to marry to satisfy their immediate
needs . They marry even sugar daddy for their well-being in spite of their intrinsic to marry them. As a result,
they experience unwanted pregnancy.

In view of that, one of the interviewee who is in the age of 30 said that:

From the very beginning I was not interested to marry my husband but I have conducted marriage with him.
This is because of the fact that I had no enough resources to lead my life properly like that of my friends. Right
now, my husband forced me to give birth but I don’t like to have a child in this situation. However, I would not
refuse his order because I had no power to do so. To tell you honestly, life is very challenging for me. Now, I am
experiencing unpleasant life.

In line with this, another interviewee who is in the age of 28 of Pointed out that:

Frankly speaking, marrying and living with a husband without love leaded life to be very unpleasant. At the
beginning my family forced me to marry him since I have failed in grade ten during that time. At that moment,
the only option that I had, was accepting my family’s interest and conducting marriage with my husband but
after a passage of time he forced me to give birth since he loves a child so much but I was not interested to give
birth due to the fact that I had no money and other resources that for myself. Nevertheless, I did not refuse to do
so. Now I am 6 months pregnant and I will give birth after three consecutive months.

Generally, from this finding one can deduct that, unemployment leads women to experience unwanted marriage
which results in unwanted pregnancy. This in turn leads women to live unpleasant and miserable life.

4. Conclusion

The study found that women unemployment is still persisting in Bahir Dar City. Accordingly, providing
technical and vocational training for women is very critical for their labor market participation. Training and
skill development plays fundamental role in active labor market policies since it enables the unemployed
women to acquire skills or knowledge that will help them actively participate in the labor market .Training
makes women to be active and competent to do whatever any activities outside their home. Thus, training play
pivotal role in employment of women, as a trained woman is more likely to be equipped, skilled and access jobs
than the untrained.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

Additionally, family planning is very important for women labor market participation. High number of family
creates difficulty for women to be active participant in the labor market by creating workloads due to various
domestic activities. Reducing the number of family members through planning play key role for women’s labor
market participation since it deduce women’s burden of their family. Thus, the number of family members can
determine women’s participation in the labor market equal to that of their counter parts.

More ever, household headship has vital role for women labor force participation. A family which had headship
of men and women is very fine for women labor market participation since it allows women to have equal
power with that of their husbands to do whatever they want including searching and accessing job opportunities
. As a result, a woman with the household headed by both man and women is preferable for women’s labor
market participation. This allow women to have less family burden and better decision making power to
participate in the productive activities and communities roles .

On the other hand, unemployment has several interconnected negative effects on women through making their
life unpleasant and hopeless. As a result, unemployed women experience many ups and downs because of the
fact that they face scarcity of economic resources that determines their social life as well as psychologically
wellbeing.

Thus, providing different different opportunities such as job and training for unemployed women could reduce
the burden that they experience due to unemployment. Furthermore, the study has discovered that, it is still not
easy for many women to enter the formal labor market even though the situation has altered over time.

Hence, the challenge encountering the present government of Bahir Dar City is to address this problem.

Acknowledgement

I would like to express deepest gratitude to all individuals who have made significant contribution to this thesis.

First and foremost, I would like to thank our omnipotent God who never let me down. Secondly, my greatest
gratitude is to my advisor, Dr. Chalachew Getahun, for his professional and insightful suggestions and kind
understanding. He has devoted a lot of time for reading and commenting my work to bring it into completion.
Additionally, my appreciation and heartfelt thanks go to Bahir Dar City administrator including Keble eleven
administrators for their cooperation. Moreover, I would like to acknowledge the contributions of the participants
and respondents for this study. More to the point, my special thanks go to the staff of Institution of Gender for
their cooperation with work. My appreciation and heartfelt thanks go to my lovely classmates for their
encouragement and continuous love. Furthermore, special and sincere appreciation goes to my lovely family for
their encouragement, support and unconditional love. Also, I would like to give appreciation for Debere Birhan
University which provides me this golden opportunity. Last but not least, I would like to sincerely thank each
one of you for your continued support and cooperation in whichever small way.

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

References

[1] Afzal, A., and Bibi, A. 2012. ‘‘Determinants of married women labor force participation’’. Descriptive
analysis .Wah Cantt: University Of Wah. Academic Research journal 2(1), 321 -324. Available
http://www.savap.org.pk/journals/.
[2] Ahn, N., Garcia, J., Ramon, B., Jimino, J. F. (2004). ‘‘European network of economic policy
research’’. Madrid. Spain. Available www.sopol.at/get_file.php.
[3] Albandoz, P. J., and Barreiro, L. P. Population and sample and Sampling techniques. Seville:
University of Seville, 2001.
[4] American Psychological Association*.‘‘Psychological effect of unemployment and under
employment’’: American psychological Association. March 03, 2014 from. http://www.a,a.org
[5] Anderberg, D., Rainer, H., Wald worth, J., and Wilson, j. Unemployment and domestic violence: Theory
and Evidence: University of Bonn. Germany. (2013). http://ftp.iza.org.
[6] Assaad, R., Elthmaidi, F., and Ahmed, A. (2000). The determinants of women employment status in Egypt:
International food policy research institute. United States of America. Available
http://ageconsearch.umn.edu.
[7] Barwell, R. Age structure and the UK unemployment. London: Bank of England. United Kingdom. 2011.
[8] Beggs*. ‘‘Types of unemployment’’. March, 2014, http://economics .about .com.
[9] Beyerstein, L*. ‘‘Prostitution and Unemployment benefits’’. April, 2014, from http://majikthise type pad
.com.
[10] Bernard, A*. ‘‘Unemployment dynamics among Canada’s youth’’: Canadian minister of industry.
Canada. Retrieved April 14, 2014, from http://www.statcan.gc.ca/pub.
[11] Bicakova, A. (2012). Gender unemployment gaps in the EU: Blame the family. Praque: Academic
Science of Charles University. Czech Republic. 2012,62-63..
[12] Birhanu Alene, Getachew Tsegaye, Taye Zinale, Wubante Fetene, Zelalem Yirga. Bahir Dar City profile:
Bahirdar University. Bahir Dar. Ethiopia, 2012.
[13] Boyce, C., and Neale, P. 2006. ‘‘Conducting in-depth interview’’: A guide for designing and conducting in-
depth interview for evaluation input: Path finder international.13/2,124-27 Available
http://www.cpc.unc.edu.
[14] Brauns, H., Markus. G. and Stefani. Education and unemployment: patterns of labor market entry in France,
United Kingdom and West Germany. 1999.
[15] Broussard, H., and Tsegaye Gebremedin. ‘‘Youth unemployment’’, masters, Ethiopian country study.
Sussex: University of Sussex. UK. 2012.
[16] Btang*. ‘‘Causes and Consequences of unemployment’.’ Internet http://www.the peak time’s world press.
[17] Budria, S., and Pereira, T. P. The contribution of vocational training to employment, job related skills and
productivity: Madeira: Madereia University. German. 2008. 405-407.
[18] Bushey, H*. ‘‘Unemployment among married couples’’ .Unemployment continuous to plaque families in
today’s tough job market: Center for American progress. , 2010.
[19] Contreras, D., and Plaza, G*. ‘‘Cultural factors in women’s labor force participation in Chile’.’ (2010).
[20] Crabtree, B and Miller, W. ‘‘Doing qualitative research. Newyork’’: Sage publications. (1992).

29
 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

[21] Creswell, J. ‘‘Research Design: Qualitative, Quantitative and Mixed Methods

’’. Sage Publications. (2003).
[22] Desta Solomon. 2008. ‘‘Research study on women entrepreneurs association in Ethiopia’’: Center for
African women empowerment. 16/5.45-49 www.enterprise-development.org.
[23] Doyle, C., Kavanagh, P., Metcal, T., and Levin, T*. ‘‘Health impact of unemployment’’ .Ireland: Institute
of public health in Ireland. 2005.
[24] Eiselen, R., and Tinauys.U ‘‘analyzing survey data using spss’’ Johannesburg:
University of Johannesburg. South Africa.2005.
[25] European Commission. 2010. Education and long term unemployment. Retrieved on 04, 2014, from
http://www.europian commission .com.
[26] Fischer, S., A. ‘‘mixed methods research’’: southeastern university. (ND)
[27] Fitzenberger, B., Wnderlich, G., Schnabel, R. ‘‘Gender gap in labor market participation and
employment’’, A cohort analysis for West Germany. Mannheim University. 2001.
[28] Floro, S., Valodia, I., and Komatsu, H. ‘‘Gender dimension of social networking, unemployment and
underemployment’’ what time use data reveal. Washington: American university.USA. 2008.
[29] Geddes, M., Robinson, M., and Lockyer*. ‘‘literature review pertaining to the employment of women in
north western Ontario’’. Ontario: Government of Canada. Canada. 2000. Internet: www.docstoc.com.
[30] Geoff, R *. ‘‘Consequence of unemployment’’. 2011 Internet: http://www.tutor.2u.net/blog/index.
[31] Gezahege Ayele, Hayat Yusuf. ‘‘Enabling the private sector to contribute to the education of urban youth
unemployment in Ethiopia’’. MA thesis .Addis Abeba: Addis Abeba University .2010.
[32] Habtamu Wondimu, Hirut Tefete, Konjit Ketetew, and Yusuf Abdi*. ‘‘Gender and cross culture dynamics
in Ethiopia’’: Addis Abeba university. Internet: March 21, 2014, from www.tandfonline.com.
[33] Hasset, A. K., and Searle, G*. ‘‘Testimony before the joint economic committee long term unemployment:
consequences and solutions’’.American enterprise institute of public policy research. USA. Internet: April
23, 2013, www.policyuncertainty.com/app/Hasset.
[34] Hirut, T*. ‘‘Violence against women from gender and cultural perspective reflections’’ .documentation on
the forum on gender. Addis Abeba .Ethiopia. Internet: April 01, 2014.preventgbvafrica.org/wp-
content/uploads/2013/10/panosreflect7.pdf.
[35] ILO Bureau of Statistics*. ‘‘Measurement of employment, unemployment and underemployment’’ internet:
February 12, 2014, http://www.geostat.ge/cms/site.
[36] Indri an, M., and Neetha, N*. ‘‘Gender dimensions: employment trends in India’’. 1993-94 to 2009-
2010. New Delhi. Internet: 2014, www.jppc.ro/reviste.
[37] International Labor Organization*. ‘‘Labor flexibility and employment and income security in
Ethiopia’’. Geneva. Switzerland. Retrived Aprile 3, 2014, from http://www.rrojasdatabank.
[38] International Labor Organization. ‘‘Growth-employment-poverty reduction linkages’’: a framework for
recovery and accelerated progress towards the Millennium Development Goals.
Economic Report on Africa. Internet: April 04, 2014. From Http://books.google.com.et/books
[39] International Labor Organization.
‘‘Global employment trends for Women’’.Geneva. Switzerland. 2012. http://www.ilo
[40] International Labor Organization*. ‘‘Global employment trends for Youth’’. Geneva. Switzerland. Internet:

30
 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

March 11, 2014, from http://www.rcsa.

[41] International Monterey fund*. ‘‘Women, work and the economy’’ : Macroeconomic gains from gender
equality. 2013. Internet: www. Inf.org/external /pubs.
[42] Jacob, O. ‘‘Causes of unemployment of the youth’’’, MA thesis, Case study of Manyana village in busa
district: Makerere University. 2011.
[43] Kothari, R.C. Research methodology. Methods and techniques. Jaipur: New age international.
University of Rajasthan, India,2004,79-84
[44] Krogh, E., Hansen, T., Wendt, S., and Elkjaer, M*. ‘‘Promoting employment of women as strategy for
poverty reduction’’. Paris: OECD. France. 2009. Internet: www.oecd.org/dac/poverty.
[45] Kumar, S .M*. ‘‘Gender discrimination and women’s development in India’’: Chikkaiah
Naicker collage of Erode. 2008. Internet : Mpra.ub.uni muenchen.de.
[46] Lawrence, H., Christian, P., Chizuru, N., Agus, Q., and Alison, S*. ‘‘Food security and nutrition division
bias’’. Washington DC: Food policy research institute. USA. 1996. Internet: http://www.ifpri.org/site.
[47] Leahy, L. R*. ‘‘Unemployment and anxiety’’. Newyork: American institute for cognitive theory.USA.
2009. Internet: www.abct.org/docs.
[48] Mahelewel, C*. ‘‘Factors associated with women unemployment in South Africa’’. 2009, internet:
http://www.statssa.gov.za/is:2009.scientific.
[49] Marshall, k*. ‘‘Converging gender roles. Statistics of Canada’’. Canada. 2006. Internet :
http://statcan.gc.ca/pub
[50] Martha Kibru. ‘‘Employment challenges in Ethiopia’’. MA thesis. Addis Abeba: AddisAbeba University.
Ethiopia. 2012.
[51] Meager, N. ‘‘the role of training and skills development in active labor market policies’’ .Brighton:
University of Sussex. UK. 2008,11-16.
[52] Mesifin. ‘‘Determinant of women unemployment in Ethiopia’’. MA thesis. Addis Abeba
University. Ethiopia. Unpublished. 2012..
[53] Meron Hailesilasie. The role of micro finance in empowering women in Addis Abeba, MA thesis: Addis
Abeba University, Ethiopia, 2007.
[54] Mincer. C*. ‘‘Education and the unemployment of women’’. Newyork: National bureau of economic
research working paper. 2014 internet: www.nber.org/papers/w3837.
[55] Minister of Education of Ethiopian. Economics for grade eleven. Addis Ababa: Minister of Education.
Ethiopia,2006,123-27
[56] Minister of Labor and Social affair of Ethiopia. (2009). National employment policy of Ethiopia.
AddisAbeba. Ethiopia, 2009,57-63.
[57] Nanayakkara, A.G. Employment and unemployment in Serilinka. Trends, issues and options Serilinka:
Department of census and statistics Colombo, 2004, 90-112
[58] National Suicide Prevention Coalition. 2010. Unemployment, financial problems and suicide. Available
http://parecovery.org/service.
[59] Ollikainen, V. ‘‘Gender differences in unemployment in Finland’’.Jyvas kyla : University of
Jyvaskyla. Finland. 2006.
[60] Onwuegbuzie, J. A., and leech, N. 2005. ‘‘On becoming a pragmatic researcher’’: the importance of

31
 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

combing qualitative and quantitative research Methodology .Rutledge: International journal of social
research methodology, 5(1), 375-387. Retrieved April, available files.eric.ed.gov/full text.
[61] Perrons, D. ‘‘Women and gender equity in employment’’. Pattern progress and challenges in London:
London school of economics. UK. 2009.
[62] Pettinger. 2010. Measurement of unemployment, and summery of types of unemployment. available 2014
http://www.economic help .org.
[63] Schmitt, C. ‘‘Gender specific effects of unemployment on family formulation’’. Across national
perspective. Berlin: Germen institute of development studies. Germen .2008.
[64] Sharme, A. ‘‘Wellbeing of youth: impact of unemployment’’: World science publisher.
United States. 2012.
[65] Stark, O., and Fan, S. ‘‘the prospect of migration, sticky wages, and educated unemployment’’ .Bonn:
Center for development studies: University of Bonn. Germany. 2011.
[66] Stevens, C. 2009. Green jobs and women workers employment, equality and equity: International labor
organization foundation for sustainable development. Available http//www.sustinable labour.org.
[67] Suda, C. 2002. ‘Gender disparities in Kenyan labor market’’. Implication for poverty reduction: University
of Nairobi. Kenya. 11(3), 301-321. Available, http://www.njas.helsinki.fi/pdf-files.
[68] United Nation Development Program*. ‘’Poverty, unemployment and social exclusion incase
of Croatia. Croatia’’. 2006, http://www.undp.
[69] US Department of labour*. ‘‘Unemployment, race, gender and marital status’’: State University. 2006.
Available 2014 from http://jops.state university .com
[70] Wach, H., and Reeves, H. ‘‘Gender and Development’’. Prepared for department for international
development (DFID) for its gender mainstreaming intranet resources. Sussex: Sussex institute of
development studies.UK. 2000.
[71] Wotton, B*. ‘‘Gender differences in occupational employment’’. Monthly labor review. 1997. Available
http://stats.bls.gov.

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APPENDIXES

Appendix-I: Questionnaires on Demographic and Socio-Cultural Status of the Respondents

Dear, Respondents,

The purpose of this study is to assess the possible determinants of employment status of women and its social,
economic and psycholological consequence on them in Keble eleven of Bahir Dar City with the view to have
comprehensive understanding and making possible suggestions about it. This questionnaire constitutes the first
part of data collection activity. The objective of this questionnaire is to gather background information and
socio-cultural factors which determine women’s employment statues.

Note: It is important that you answer each item as thoughtfully and frankly as possible and your responses are
highly valuable and will be used for research purpose only.

 Please answer all questions;

 You do not need to write your name on the questionnaires ;
 All the information that you may provide will be held confidential;
 Please circle the letter of your answer for choice part and write your answer in space provided for
others.
Thank you for your kind cooperation!!!!

Part I: Demographic characteristics of the respondents

1. How old are you? -----------------

2. What is your current marital status?
A. Single C. Divorced
B. Married D. Widowed
3. Total Number of family members? ------------------
4. Number of children less than five years of age --------------------
5. Sex of household head? A. male B. female C. both
6. House number------------------------------------
I. Socio- cultural factors or statues of the respondents
7. Highest level of education attained (in years)-------------------
8. What is your current employment status?
A. Employed B. Unemployed
9. What is your husband’s highest level of education attained (in years)? ------------------
10. Do you prepare food for your family? A. yes B. no
11. Do you perform Bearing and caring of the child? A. yes B. no

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12. Do you carry out cleaning including home and cloth? A. yes B. no
13. Do you make housekeeping and family health care? A. yes B. no
14. Did you obtain any form of training? A. Yes B. No
15. Do you have access to credit services? A. Yes B. No
16. How often have you been exposed to any mass media? -------------------------------------
17. Did you experience any insult or inappropriate remarks in recruitment for employment? A. yes
B. no
18. Did you face any unwanted invitation or request in recruitment for employment? A. yes B. no
19. Have you seen any job specifications which are not essential to carrying out the prescribed duties e.g.
Minimum weight or height? A. yes B. no
20. Did you experience any unwanted physical contact in recruitment for employment? A. yes B. No

Appendix-II: Interview Guiding Questions for Unemployed Women

Dear, interviewees, this in-depth interview guide are designed to obtain information on the social, economic as
well as psychological effects of unemployment on women in Keble eleven of Bahir Dar City. To realize this
objective and objective and reliable information is highly demanded.

Thank you in advance!!!!!!

I. Socio-demographic information of the interviewee

Personal data (back ground information): Age -----Marital statues -----Education statues ---- House number ------
----Date of interview--------------------Who is the head of the family --------------How many family members do
you have? ---------------------------

II. In-depth interview guiding questions on social, economic and psychological consequence of
unemployment on women.
1. What is your means of generating income or means of survival?
2. Who is the breadwinner or main economic provider of the household?
3. Would you express your feeling as you are unemployed?
4. Did you experience any shortage or lack of basic necessities like food, shelter, cloth?
5. Did you experience financial constraints?
6. Do you have any credit that need to be returned?
7. What is your experience in relation to alcoholism or any other forms of addiction?
8. What role or statues do you have in the society?
9. How do you express your participation in social sphere? Did you experience isolation?
10. How do you convey your marital life?
11. Did you experience prostitution, unwanted marriage, unwanted pregnancy, women trafficking?
12. Did you experience domestic violence like marital rape, beating, and insulting by husband?

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13. How do you articulate your decision making role in the household affairs?
14. How do you express your safety or protocol?
If any other than these………………………………………………?

Thank you in advance!!!!!!!!!!

List of tables:-

Table 2: Demographic and socio-cultural characteristics of respondents

Variable Frequency Percent

Age group of respondents
15-29 162 41.8
30-44 164 42.3
45+years 62 16.3
Marital status
Unmarried 25 6.4
Married 277 71.4
Divorced 45 11.6
Widowed 39 10.1
Family size
Less than five 373 96.7
More than five 14 3.6
Child less than five years of age
No child 213 54.9
1-3 175 45.1
More than four 0 0
House head ship
Wife 110 28.4
Husband 155 39.9
Both 121 31.2
Education status
No education 101 26.0
Primary 138 36.2
Secondary 126 33.1
Territory 16 4.2
Husband’s education status
No education 34 8.8

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Primary 103 26.5

Secondary 68 17.5
Territory 42 10.8
Food preparation
Yes 371 95.6
No 15 3.9
Child care
Yes 230 59.3
No 152 39.2
Cleaning (house and cloth)
Yes 365 94.1
No 21 5.4
Training skills obtained
Yes 159 41.0
No 229 59.0
Access of credit service
Yes 106 27.3
No 280 72.2
Exposure to mass media
Always 127 32.7
Sometimes 131 33.8
No exposure 117 30.8
Insulting in recruitment
Yes 86 22.2
No 301 77.6
Unwanted invitation
Yes 93 24.0
No 295 76.0
Irrelevant job specification
Yes 106 27.3
No 282 72.7
Unwanted physical contact
Yes 17 4.4
No 371 95.6

Source: Own survey data, 2014

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Table 3: Chi square results of dependent and independent variables

Variables Employment status with frequency

Age group Employed Unemployed
15-29 93 69
30-44 105 59
45+ 39 23
2
chi-square(x ) =1.604

p=0.448

Marital status Employed Unemployed

Unmarried 15 10
Married 177 100
Divorced 23 22
Widowed 20 19
2
Chi-square(x ) =5.025

P=0.285

Family size Employed Unemployed

Less than five 1 0
More than five 235 151
2
Chi-square(x ) =13.311

P=0.000

Child less than five years Employed Unemployed

of age
No child 130 107
0ne up to three 107 68
More than four 0 0
2
Chi-square(x ) =0.000

P=0.982

House head ship Employed Unemployed

Wife 61 49
Husband 82 73
Both 92 29
2
Chi-square(x ) =17.166

P=0.000

Education status Employed Unemployed

No education 65 50
Primary 83 57

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Secondary 75 38
Post secondary 10 3
2
Chi-square(x ) =8.150

P=0.043

Husband education status Employed Unemployed

No education 21 13
Primary 61 42
Secondary 38 30
Post secondary 32 10
2
Chi-square(x ) =4.963

P=0.175

Food preparation Employed Unemployed

Yes 224 147
No 11 4
2
Chi-square(x ) =1.016

P=0.313

Child care Employed Unemployed

Yes 133 97
No 102 50
2
Chi-square(x ) =3.329

P=0.068

Cleaning Employed Unemployed

Yes 220 145
No 15 6
2
Chi-square(x )=1.037

P=0.303

Family care Employed Unemployed

Yes 227 144
No 10 7
2
Chi-square(x ) =0.038

P=0.845

Training obtained Employed Unemployed

Yes 117 42
No 120 109
2
Chi-square(x ) =17.714

P=0.000

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Access of credit Employed Unemployed

Yes 78 28
No 153 123
2
Chi-square(x ) =9.903

P=0.002

Exposure to any mass media Employed Unemployed

Always 81 49
Sometimes 86 53
No exposure 59 47
2
Chi-square(x ) =8.128

P=0.017

Insulting in recruitment Employed Unemployed

Yes 58 28
No 178 123
2
Chi-square(x ) =1.939

P=0.164

Unwanted invitation in Employed Unemployed

recruitment
Yes 64 29
No 173 122
2
Chi-square(x ) =3.078

P=0.079

Unwanted job specification Employed Unemployed

Yes 73 33
No 164 118
2
Chi-square(x ) =3.719

P=0.054

Unwanted physical contact Employed Unemployed

in recruitment
Yes 12 5
No 255 146
2
Chi-square(x ) =0.676

P=0.411

Source: Own survey data, 2014

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Table 4: Multivariate analysis (binary logistic regression results)

Variables in the Equation

Variables B S.E. Wald df Sig. Exp(B) 95% C.I.for
EXP(B)
Lower Upper
Houshead 9.865 2 .007
houshead(1) .769 .315 5.969 1 .015 2.157 1.164 3.998
houshead(2) .890 .292 9.275 1 .002 2.435 1.373 4.319
traning(1) -.604 .265 5.209 1 .022 .547 .325 .918
Yeducatio .911 3 .823
yeducatio(1) .133 .671 .039 1 .843 1.142 .306 4.259
yeducatio(2) .095 .657 .021 1 .885 1.100 .303 3.990
Step 1a
yeducatio(3) -.141 .660 .046 1 .830 .868 .238 3.167
accessofcridit(1) -.333 .289 1.330 1 .249 .716 .406 1.263
Exposurtomassmedia 1.633 2 .442
exposurtomassmedia(1) -.275 .291 .890 1 .346 .760 .430 1.344
exposurtomassmedia(2) -.352 .288 1.500 1 .221 .703 .400 1.235
familygrouped(1) -2.970 1.060 7.851 1 .005 .051 .006 .410
Constant 2.383 1.270 3.521 1 .061 10.837
a. Variable(s) entered on step 1: houshead, traning, yeducatio, accessofcridit, exposurtomassmedia,
familygrouped.

Table 5: Hosmer lemshow goodness of fit test

Step Chi-square Df Sig.

1 11.583 8 .171

Omnibus Tests of Model Coefficients( combined effect

of variables
Chi-square df Sig.
Step 49.625 10 .000
Step 1 Block 49.625 10 .000
Model 49.625 10 .000

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 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2015) Volume 8, No 1, pp 14-41

Model Summary
Step -2 Log Cox & Snell R Nagelkerke R
likelihood Square Square
1 442.473a .127 .172
a. Estimation terminated at iteration number 5 because
parameter estimates changed by less than .001.

Table 6: Back ground information of the interviewees of the study

No- Age Education status Marital status Family size Number of kids
1 40 Primary Married 4 2
2 35 No education Married 5 3
3 29 Secondary Divorced 1 0
4 31 Primary Married 3 1
5 34 Primary Married 4 2
6 30 Primary Married 3 1
7 28 Primary Married 2 0
8 32 No education Married 5 3
9 42 Primary Divorced 2 1
10 36 Primary Widowed 3 2
11 33 Primary Married 3 1

41

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