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. 14 http://asrjetsjournal.org/ American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 15 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 16 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 17 http://en.wikipedia.org/wiki/Lake_Tana http://en.wikipedia.org/wiki/Lake_Tana http://en.wikipedia.org/wiki/Blue_Nile American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 18 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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. 19 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 20 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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. 21 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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. 22 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 Chi-square(x 2 ) =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 chi-square(x 2 ) =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 (0.315) 2.16 0.015 1.7-3.10 Husband 0.890 2.43 0.002 1.4-4.31 23 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 (0.292) Both 1.00 Education status No education 0.133 (0.671) 1.14 0.84 0.306-4.25 Primary 0.095 (0.657) 1.10 0.88 0.303-4.0 Secondary 0.141 (0.66) 0.86 0.83 0.238-3.16 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- 24 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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 25 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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. 26 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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. 27 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) 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. 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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 33 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 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? 34 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 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 35 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 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 36 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 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 chi-square(x 2 ) =1.604 p=0.448 Marital status Employed Unemployed Unmarried 15 10 Married 177 100 Divorced 23 22 Widowed 20 19 Chi-square(x 2 ) =5.025 P=0.285 Family size Employed Unemployed Less than five 1 0 More than five 235 151 Chi-square(x 2 ) =13.311 P=0.000 Child less than five years of age Employed Unemployed No child 130 107 0ne up to three 107 68 More than four 0 0 Chi-square(x 2 ) =0.000 P=0.982 House head ship Employed Unemployed Wife 61 49 Husband 82 73 Both 92 29 Chi-square(x 2 ) =17.166 P=0.000 Education status Employed Unemployed No education 65 50 Primary 83 57 37 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 Secondary 75 38 Post secondary 10 3 Chi-square(x 2 ) =8.150 P=0.043 Husband education status Employed Unemployed No education 21 13 Primary 61 42 Secondary 38 30 Post secondary 32 10 Chi-square(x 2 ) =4.963 P=0.175 Food preparation Employed Unemployed Yes 224 147 No 11 4 Chi-square(x 2 ) =1.016 P=0.313 Child care Employed Unemployed Yes 133 97 No 102 50 Chi-square(x 2 ) =3.329 P=0.068 Cleaning Employed Unemployed Yes 220 145 No 15 6 Chi-square(x 2 )=1.037 P=0.303 Family care Employed Unemployed Yes 227 144 No 10 7 Chi-square(x 2 ) =0.038 P=0.845 Training obtained Employed Unemployed Yes 117 42 No 120 109 Chi-square(x 2 ) =17.714 P=0.000 38 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 Access of credit Employed Unemployed Yes 78 28 No 153 123 Chi-square(x 2 ) =9.903 P=0.002 Exposure to any mass media Employed Unemployed Always 81 49 Sometimes 86 53 No exposure 59 47 Chi-square(x 2 ) =8.128 P=0.017 Insulting in recruitment Employed Unemployed Yes 58 28 No 178 123 Chi-square(x 2 ) =1.939 P=0.164 Unwanted invitation in recruitment Employed Unemployed Yes 64 29 No 173 122 Chi-square(x 2 ) =3.078 P=0.079 Unwanted job specification Employed Unemployed Yes 73 33 No 164 118 Chi-square(x 2 ) =3.719 P=0.054 Unwanted physical contact in recruitment Employed Unemployed Yes 12 5 No 255 146 Chi-square(x 2 ) =0.676 P=0.411 Source: Own survey data, 2014 39 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 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 Step 1a 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 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 1 Step 49.625 10 .000 Block 49.625 10 .000 Model 49.625 10 .000 40 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2014) Volume 8, No 1, pp 14-41 Model Summary Step -2 Log likelihood Cox & Snell R Square Nagelkerke R 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