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             \author[1]{Kokobe Seyoum  Alemu}

             \affil[1]{  Ambo university}

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\date{\small \em Received: 10 February 2015 Accepted: 28 February 2015 Published: 15 March 2015}

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\begin{abstract}
        


The research study evaluated owner manager characteristics as a determinant of MSE growth. On this, analysis of variance was carried out to examine the variation in the growth of MSEs with respect to the variation in each of the independent variables. As two dependent variables were used to measure growth in this study, the result shows different statistical value for both of them. The ANOVA and t-test result indicates, there is a significant variation on the growth of MSEs in relation to the variations of gender, work experience and family back ground if growth is measured using asset growth. If growth is measured using employment growth, the deference in experience and family back ground brings difference in growth. But the result shows there is no significant difference in growth with respect to the difference in education level whether it is measured with asset or employment growth.

\end{abstract}


\keywords{MSES, small firms, micro enterprises, entrepreneurship, ethiopia.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
icro and small enterprise (MSE) sector is highly diversified sector and plays a predominant role in the economy of developing countries. The MSE enterprises are being considered as engines of economic growth worldwide. One of the most important roles of MSEs in this context includes poverty alleviation through job creation. The developed as well as developing countries are taking extreme benefits from MSEs and that are capable to accelerate the economy of any country (Jasra, 2011). It plays considerable responsibility in providing further employment and conversion of economy.\par
Given the importance of the micro and small enterprise sectors to GDP and to national employment in most developing countries like us, it is important to consider what sorts of policies might be undertaken to foster expansion of this sector. In order to address this issue it is helpful to better understand the factors involved in the growth of MSEs. Some businesses grow more than the others. Again, some business grows while others perish within a short period of time. So this gives us the implication of the fact that there is something that those businesses have and others don't. Even if some of the researchers on the area see growth as a natural phenomenon in the evolution of the firm, most of the peoples on the area see growth as a Author : Lecturer and Researcher, Ambo University, Ethiopia. e-mail: kokseyoum@yahoo.com consequence of some embedded characteristics (Mervi and Jyrki, 2007; Qureshi et al, 2012; \hyperref[b0]{Hansen and Hamilton 2011;}\hyperref[b11]{Federico et al, 2008;}\hyperref[b12]{Serazul, 2012;} {\ref woldie et al., 2008;}\hyperref[b19]{Rahel, 2010;}\hyperref[b9]{brown et al. 2004}). But, all of those researchers will agree on the contribution of owner/ manager to business growth. In MSE most of the time the owner of the business will became the manager of the business. The rationale to include the entrepreneurs' profile perspective is that MSEs, compared with large companies, are characterized by a strong emotional connection between the owner and the firm (Chan and Foster, 2001). Thus, certain characteristics of the entrepreneur will strongly influence not only the type of firm that will be created but also the way it will be managed \hyperref[b17]{(Qureshi et al., 2012)}. So, the attitudes and abilities of the business owner have an important impact on small firm growth and will be reflected in strategic choices and the ways in which he or she operates the business for future success  {\ref (Papadaki and Chami, 2002)}.\par
Many of those empirical studies have tended to focus on the relationship between the characteristics of the owner/manager and firm growth. Within the broad category of owner-manager characteristics, Woldie et al.,  {\ref (2008)} suggests five elements which are likely to influence growth, these are: Age, Gender, Education, Previous work experience and family back ground of the owner managers. According to Lucas' theory, the variation in levels of business acumen is the major determinant of business growth which does mean that difference in education level and experience about the business under consideration will have a direct impact in business decision and MSE growth. Alternatively, as proposed by \hyperref[b3]{Ishengoma and Kappel (2008)}, the major determinant of business growth is the differing taste for risk among individuals in which females are risk averse than males in making business decision.\par
The purpose of this paper is to explore how owner manager characteristics may affect MSE growth in Ethiopia 1  Abstract-The research study evaluated owner manager characteristics as a determinant of MSE growth. On this, analysis of variance was carried out to examine the variation in the growth of MSEs with respect to the variation in each of the independent variables. As two dependent variables were used to measure growth in this study, the result shows different statistical value for both of them. The ANOVA and t-test result indicates, there is a significant variation on the growth of MSEs in relation to the variations of gender, work experience and family back ground if growth is measured using asset growth. If growth is measured using employment growth, the deference in experience and family back ground brings difference in growth. But the result shows there is no significant difference in growth with respect to the difference in education level whether it is measured with asset or employment growth.\par
that attention paid to owner manager characteristics as a role it play in MSE growth. Moreover, it is believed that, in effort to help mushrooming of MSEs, especially by establishing business incubators, academicians can provide consultancy service to MSEs through such researches. Last but not least, the knowledge of the effect of owner manager characteristics on MSE growth will allow proprietors not only to learn their true efficiency level but also to increase their firms' efficiency by means of investing in their own human capital or cut their level of investment if it has no effect. 
\section[{II.}]{II.} 
\section[{Literature}]{Literature}\par
Even if there is a disagreement on level of digits between the government and some international institution like World Bank and International Monetary Fund, everybody agrees that there is a fast growth in Ethiopia for the last nine years. As the country lacks large industries, the contribution of MSE to this growth is undeniable. That is why the government of Ethiopia gave greater attention to the promotion and development of MSEs, especially for women as a strategy for poverty alleviation and increasing for employment creation. But those policies of the government failed to address those factors responsible for the graduation of MSE. Despite the countries heterogeneity with regard to MSEs composition and level of growth, the centrality of MSE in the process of economic development is by now widely recognized and essentially beyond debate. In addition, the MSE sector may serve as an entrepreneurial training ground in which tomorrow's business leaders can find success and gain valuable experience (A. \hyperref[b15]{McPherson and Rous, 2010)}.\par
In the world, there is no commonly accepted definition of micro and small enterprises. Depending on the prevailing realties and objectives, each country has its own definitions. Based on the purpose for which the identification is required different definitions have been instituted by researchers in the same country at different point of time. Thus, the definition of MSEs may be based on persons employed, annual growth of sales, fixed capital invested, or a combination of the above criteria. In Ethiopia the demarcation between micro and small enterprise was made based on the capital employed and number of employees. Again the demarcation depends on the sector of the business whether it is industry or service.\par
There are dozen researches on the area in developed countries and only a little is known in developing countries like Ethiopia. Present descriptive evidence from several countries suggests that small-firm growth differs according to a number of proprietor characteristics \hyperref[b19]{(Rahel, 2010;} {\ref woldie et al., 2008;} {\ref Hansen and Hamiltan, 2011;}\hyperref[b12]{Serazul, 2012;}\hyperref[b17]{Qureshi et al., 2012)}. The vast majority of those researchers conclude that owner/ manager profile like education level, age, family back ground, gender and previous work experience will have much impact on MSE growth. The conclusions of those variables are summarized as follows III. 
\section[{Age of Owner/Manager and its}]{Age of Owner/Manager and its}\par
Influence on Growth\par
Available theoretical discussion explaining the influence of the age of the owner/manager advocates for the younger owner/manager; the argument here rests on the fact that the younger owner/manager has the necessary motivation, energy and commitment to work and is more inclined to take risks \hyperref[b18]{(Doern, 2009;} {\ref Jasra et al, 2008)}. The logic is that the older owner/manager is likely to have reached his/her initial aspiration. It is also suggested in the literature that younger individuals may be more willing to assume risks and grow their business. Following Federico et.al argument, a younger individual may have a higher need for additional income. The burden of supporting a family and meeting mortgage payments generally declines with age (woldie et al., 2008). An older individual who continues to be the owner-manager of a small firm is more likely to have reached his/her initial aspirations. However, while younger individuals have more motivation to expand their business they also may have fewer financial resources and fewer networks. The limited empirical evidence suggests that the ownermanager's age tends to be negatively related to growth (A. .\par
Hypothesis 1: There is significant relationship between the age of the owner/manager and the level of growth attained; consequently, firms run by younger owner/managers tend to have a higher growth probability than those run by their older counterparts IV. Gender of the Owner/Manager and its Influence on Growth\par
The previous analysis suggested that maleheaded MSEs are likely to expand more rapidly than ones operated by females \hyperref[b17]{(Qureshi et al.,2012;} {\ref Coad et al.,2008)}. The survey results indicated that femaleheaded MSEs generally grew at an average rate of only about 7\% per year, while those headed by males grew at approximately 11\% per year  {\ref (Woldie et.al.,2008)}. One of the explanations for this difference is that enterprises owned by women are often concentrated in more slowly growing sectors. Even when controlling for other variables such as sector and location, however, enterprises owned by women grew at a significantly slower rate. Possible explanations for these gender differences include such factors as the dual domestic and productive responsibilities of women, or possible differences in the business objectives of females and males.\par
Females may also be more risk-averse than their male counterparts, reflecting their responsibilities for maintaining the welfare and perhaps even the survival of the household. This may lead them to use any available funds for diversification into new activities rather than for an expansion of existing ones \hyperref[b2]{( mead et al.,1998;}\hyperref[b9]{Brown et al., 2004;} {\ref Akoten et al., 2006)}.\par
Akoten et al, (2006) provide an insightful analysis of many of the challenges constraining women's opportunities for MSE growth. All too often, women face asymmetrical rights and obligations limiting their labor mobility and burdening them with disproportionate household responsibilities. Due to gender-specific roles and time constraints, even university-trained women may choose to weave tapestries within the household. Temporal discontinuities in women's ability to work frequently leads to a loss of economic skills, and at times even lowers career and educational aspirations. Women in some countries face greater problems with in numeracy, illiteracy, and a lack of business skills. In addition, women commonly have unequal access to markets. Studies have shown that men travel farther geographically than women to buy inputs, enabling them to enjoy lower prices and higher quality  {\ref (Bwisa et al., 2011)}. Men also sell in multiple markets more frequently than women, allowing them additional growth opportunities. As a result of such factors, women frequently focus their MSEs on a relatively narrow range of industries. It has been proposed in the literature that women may have fewer opportunities to develop relevant experiences may have fewer networks to get assistance and may have greater difficulty in assembling resources \hyperref[b12]{(Serazul, 2012)}. There is some evidence that banks may impose more stringent requirements on women business owners in regard to collateral for loans, and therefore limit their ability to grow \hyperref[b9]{(Brown et al., 2004)}. Women may also be more family oriented and be less keen in pursuing economic goals related to expansion of the firm \hyperref[b12]{(Serazul, 2012)}. \hyperref[b0]{Hansen and Hamilton,(2011)} found that being female had a negative impact on the growth of small ventures but had no impact on the survival of the firm.\par
Hypothesis 2: There is significant relationship between the gender of the owner/manager and firm growth; male-owned/managed firms exhibit higher growth than female-owned/managed firms.\par
V. 
\section[{Formal Education of Owner/Manager and its Influence on Growth}]{Formal Education of Owner/Manager and its Influence on Growth}\par
In the past it was generally been believed that small business owners would be less likely to have pursued a formal education than those holding managerial positions in larger organizations, as individuals "followed in their father's footsteps. There is no question as to the fact that basic education enhances the overall quality of the owner/manager by providing him/her with basic numeric and literacy skills, thus increasing the chance of survival  {\ref (Tiruneh,2011;} {\ref Jasra et al.,2011;} {\ref woldie et al.,2008}). Literature's discuss on the educational level of the owner/manager tends to be split into two schools of thought. Some studies state that the fact that a manager has a higher education degree or even a postgraduate degree seems to stimulate the growth of the firm, thus having an impact on both survival and growth. The converse argument is that owner/managers of MSEs who had degrees generally achieved lower rates of growth than those less well educated \hyperref[b4]{(Reid and Xu, 2009)}. The link between owner-managers' education and firms' performance as well as growth is addressed in the economic literature. One among the categories of human capital effects on firms' competitiveness is allocative effect. This effect is related to owner-managers' education, in that those with a relatively higher level of education have a greater ability to efficiently allocate resources to more productive lines of business and to select profit maximizing inputs/combinations \hyperref[b11]{(Federico et al.,2008)}. Qureshi et al., (2012), emphasize the role of entrepreneurial/business education in the growth/performance of the firm. They argue that a firm whose management has business/entrepreneurial education is likely to perform better than those without managers with these types of education. Loan providers use owner-managers' education levels as an indication of the latter's ability to utilize resources to generate profit and be able to meet their obligations. Thus, firms with relatively more educated owners are likely to have more access to external finance. Hypothesis 3: There is significant relationship between the educational qualification of the owner/manager and the level of growth attained; growth is higher in firms where the owner/manager has a college or university degree and above. 
\section[{VI. Previous Experience and its Influence on Growth}]{VI. Previous Experience and its Influence on Growth}\par
Any development practitioner or businessperson can attest that MSE owner/managers acquire a substantial amount of skills and knowledge while operating their firms. Such work experience proves to be highly important for developing capabilities within MSEs, as entrepreneurs with more years of work experience typically have faster-growing MSE. For example, one empirical study found that Kenyan entrepreneurs with at least seven years of work experience expanded their firms more rapidly than those without such experience \hyperref[b18]{(Doern, 2009)}. While the 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XV Issue IV Version I Year ( ) C benefits of on-the-job experience are frequently mentioned, the importance of prior work experience may be even more helpful, especially if that experience came within the same sector or in micro to small-sized enterprises. An empirically rigorous study of high-growth entrepreneurs provides telling insights about the importance of skills and business contacts gained during past employment (Tiruneh, 2011). Among Latin American and East Asian entrepreneurs, contacts were found to be a key benefit of work experience, helpful in identifying business opportunities, obtaining financing and other resources, and alleviating management challenges \hyperref[b9]{(Brown et al., 2004)}. Other developing regions, such as Africa, are characterized by a systematic lack of opportunities to gain relevant work experience.\par
A study carried out by Serazul, (2012) found that MSE owner/managers with little experience at the start-up phase could have problems remaining solvent with an increase in expenditure in relation to their earnings. Nichter and gold mark, (2005) in their study found no relationship between prior MSE experience and firm growth. Coad, (2008) found reasonable evidence indicating a negative relationship between being unemployed before starting a business and subsequent business growth. Knowledge gained from industry experience provides the entrepreneur with certain key competencies and inside information needed to recognize and exploit opportunities. Through work experience, people develop information and skills that facilitate the formulation of entrepreneurial strategy, the acquisition of resources, and the process of organizing. Industry experience is also important in reducing risks and uncertainty. Thus, industry experience is expected to be associated with entrepreneurial orientation (woldie et al. 
\section[{, 2008).}]{, 2008).}\par
Hypothesis 4: There is significant relationship between the previous experience of the owner/manager and firm growth; growth is positively influenced by previous experience of the owner/managers, especially those who have prior MSE experience.\par
VII. Family Back Ground / Family who Owned a Business/ Coad, (2008) discusses the importance of the entrepreneur's family background in instilling the need for achievement, the need for independence and control of an unstructured environment, and patterning later modes of behaviour. One important dimension of family background, which seems to affect entrepreneurial outcomes, is business history. Entrepreneurs born into business families are more likely to have positive attitudes toward risks, be prepared in part by the family's accumulated business experience and have links with the family's age-old ties and business networks. A family's business background is also a source of previous work experience, another influential personal life experience. This characteristic is probably more critical in developing countries like Ethiopia, given the relative strength and cohesiveness of the family unit in such countries. Therefore, family business history is expected to be related to higher levels of entrepreneurial orientation. Approximately three-quarters of MSE owners have some family connection with business ownership, with men being much more likely to 'inherit' a business than women. Individuals who have business owning parents are much more likely to pursue their own business ventures than those who do not \hyperref[b1]{(Davidsson et al., 2002)}. In addition, he further says, spouses of micro or small business owner are more likely to be business owners themselves than those who have employed spouses.\par
A number of studies have shown that entrepreneurs are more likely to be from families in which the parents owned a business. It is assumed that young individuals develop knowledge of what is involved in running a business (Krasniqi, 2012), and that they are more likely to perceive entrepreneurship as a viable career choice. There is indeed some empirical evidence to suggest that coming from an entrepreneurial family background increases the likelihood of survival (woldie et al., 2008). However, there is little evidence on the impact of family background on the growth prospects of an entrepreneurial venture. One study has found no relationship between entrepreneurial background and growth of a small venture (Hansen and Hamilton, 2011). Hypothesis 5: Growth is higher for businesses whose owners during childhood had close family membersparents or siblings -that were entrepreneurs. 
\section[{VIII. Methodology}]{VIII. Methodology}\par
The aim of this research is to explore the influence of the owner/manager characteristics on the growth of the firm. Utilizing a self administered questionnaire, data were collected from two sub-cities of Addis Ababa, where a large number of MSEs are located, namely: Addis ketema sub-city and Arada subcity. The sample for this survey consisted of 99 MSE owner/managers. Questionnaires are good research methods as they yield information about the past and present and offer the best means of obtaining standardized stimuli  {\ref (Woldie et al., 2008)}.\par
The data collected from the self administered questionnaire were analyzed by using descriptive statistics based mainly on frequency distribution and percentage value. In addition, ANOVA test and t-test were used to check the relation between dependent and independent variables. The ANOVA test is used when there are more than two alternatives. The t-test is used for variables having two alternatives to check whether Many different variables have been used to measure the firm's growth. Employment, sales, and total asset are mostly used as growth measurement in literature. This shows that, there is little agreement in the existing literature on how to measure growth, and scholars have used a variety of different measures. In measuring growth, although theoretically alternative measurement tools such as growth rate of sales or profits could give more precise results, in practice they are not as credible as the employment and asset growth measure because of entrepreneurs' hesitation to report the true values of their sales and profits. This hesitation, which leads to measurement errors, makes the employment and asset-based measure preferable in studies considering enterprise growth. Again, employment growth is relatively easy for respondents to remember and that is uncontaminated by price changes. Moreover, job creation may be an important social goal, and policies to support MSE's are frequently justified on their supposed employment effects. But the use of employment or asset criteria could also depend on the sector under study. For highly capitalized firms, such as those belonging to certain manufacturing subsectors, variation in assets would be a more accurate measure of growth than variation in the workforce. But, this criterion cannot be used in the service sector, which is more labor-intensive. Therefore, this paper used both employment 2   IX. Findings from the Research and asset growth as a growth measure. Employment Growth is the difference between average employment at inception and current average employment; whereas total asset growth is the difference between the total asset at the current and total asset at the beginning plus unpaid amount of debt.\par
The study sample consisted of 99 MSEs in which large number of them is owned by females. This is because of the fact that; in our country; as the number of females in formal education is less in number, most of them are participating in the business. The numbers of females joining government offices are very much less due to their less participation in formal education and business is their best area of selection. That means women in developing countries like us have a strong tendency to enter the MSE sector, in part because of ease of entry and their limited access to alternate opportunities. Again females are good from marketing point of view than males as they have a natural ability to attract and negotiate customer. Therefore, it is perhaps not surprising to see more number of females in business area than males in this country. 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XV Issue IV Version I Year ( ) As it is indicated in the above t-test table result, 38 MSEs in this study are owned/ managed by male owners. In terms of growth performance, enterprises run by male individuals' shows an average asset growth of 2.55*10 5 and employment growth of 4.74 during their operation time. The remaining 61, MSEs involved in this study are owned/ managed by female individuals. In terms of performance MSEs in this category shows on average asset growth of 1.14*10 5 and employment growth of 2.84 . Concerning both, asset and employment growth, the mean growth is larger for the male category. These suggest, therefore, that enterprises with a male owner/ manager exhibit greater likelihood of having higher growth than enterprises whose owner/ manager is females. Possible explanations for these gender differences include such factors as the dual domestic and productive responsibilities of women, or possible differences in the business objectives of females and males, or education difference between females and males in which most of the time in our country females do not go to school for cultural reason. Again, females may also be more risk-averse than their male counterparts, reflecting their responsibilities for maintaining the welfare and perhaps even the survival of the household. The table above shows 13 enterprise owner/ managers of this study have an education status of no schooling which means that they did not join formal education in their life time. Enterprises owned/managed by individuals with no education level have an average asset growth of 2.64*105 and employment growth of 5 in their whole life till now.C\par
The other 19 enterprise owner/ managers of this study have an education status of elementary school which means that they have been in a formal education for some years with a maximum of grade 8. Enterprises owned/ managed by peoples with this level of education have an asset growth of 1.80*10 5 and employment growth of 1.58 in their life time Again the other 42 enterprise owner/manager of this study have an education status of high-school which means that their maximum level of education is to grade 12 starting from grade 9. Enterprises owned/ managed with peoples of this level of education have a total asset growth of 1.17*10 5 and employment growth of 3.24 during their operation\par
The remaining 25 MSEs involved in this study are owned/ managed by individuals having an education level of collage/ university status. This educational status category of the owners/manager includes those who join college or university to have further education. This category includes those owners/managers having diploma or first degree and above. Regarding performance of the enterprises in this category of the educational level of the owners/manager of the enterprises; on average they showed an asset growth of 1.96*10 5 and employment growth of 4.88 since their establishment.\par
Over all, the result shows that education does not have such implication on asset and employment growth as expected. It is not surprising to see such things in our country in which most of the educated peoples are not involved much in business. In our country the more peoples are educated, the more they are far from business and they consider it as a minor activity left for jobless people which most of the time is the uneducated part of the society. The no schooling part develops those businesses from scratch and knows everything about the business environment due to enough experience for the industry. Again even if they are not educated they have passed whole of their life in business and they know what to do than many of the educated person who is new in the area. So this knowledge of the area may make them develop more when compared with more educated parties. Again the education level attained by the educated parties may not be related with the activity they are undertaking. Even if lacks of education have negative implication on business growth, the result of this study shows that mean asset and employment growth is higher for no schooling.\par
Concerning the employment growth the possible reason that no schooling category has high growth is due to the fact that they are uneducated, they should have to work through others that they should hire many employees which are appropriate for the position and this may increase the number of employees at their organization. The third variable considered in this study as the success factor for growth of MSEs is the age of the owner/ manager of the enterprises. To examine the variation in the growth of the enterprises in different age categories, the sample is grouped into four age groups as depicted in the table above. In many studies it is stated that, the young have high probability of business development and as peoples become older their energetic effort to develop their business will decrease. In this study what is needed to be known is which category of this young age particularly have a high probability of business growth and which older part have a least growth. From where this least growth starts will be answered after business owners are categorized in to four age groups.\par
As it is indicated in the table, from the total sample taken 10 enterprises are possessed by owners/manager with the age of less than or equal to 25. This category is the youngest of all the listed categories. When we look at the growth of those MSEs in this age category on average they show an asset growth of 95,700 and employment growth of 5 from the time of establishment to to-date.\par
The The other variable in this study is the owner/manager experience 3   The third category of MSEs in this table shows that 34 enterprises are included under this category and in the business industry which is expected to create variations on the growth of MSEs operating in Addis Ababa.\par
From the above, 20 owner/ managers of MSEs in this study have less than 5 years work experience in any other field either being employed in other organizations or working in their own independent enterprises before the current one. In terms of growth those 20 enterprises owned/ managed by individuals with less than 5 years work experience demonstrates an average asset growth of 17,817 and employment growth of -15.\par
Again the same table shows that, 28 MSEs are owned/ managed by owners which have a prior management experience of between 5 to 10 years. With respect to the growth of those enterprises in this category on average they show an asset growth of 29,493 and employment growth of 1.29 during their operation owned/ managed by individuals with a work experience of 10 to 15 years. Concerning growth those business with in this category have an average asset growth of 249,726 and employment growth of 5.91.\par
The remaining 17 MSEs in this study are owned/ managed by individuals who have a prior work experience of more than 15 years. The growth of the enterprises in this category shows that they have an asset growth of 410,744 and employment growth of 7 starting from the beginning to to-date.\par
This shows that the increase in the owner/manager experience will increase the average growth of those enterprises. This is because of the fact that owner managers having an experience before, knows different tactics of solving problems. Again the liability of newness does not affect experienced individuals. As they know what is happening in the area, they may have special techniques in using an opportunity and decreasing a threat. The negative value of employment growth of those businesses within the age range of less than 5 years shows that, there is high probability that those businesses are unstable and go out of business at that stage. But small businesses passing this stage have high probability of growth. The fifth variable of this study is the family back ground of the owner/ manager. This deals with whether the owner/ manager have a family who participate in business before. Having being born from business families would have relation to the performance of MSEs and determine their success in the business environment they are working in. As shown on the above table, 53 MSEs are owned/ managed by individuals whose families are in the business before. When we look at the growth of MSEs in this category, it shows an average asset growth of 2.58*10 5 and employment growth of 4.72 during their life time.\par
On the other hand, from the same table you can see that, 46 sample enterprises in this study are owned/ managed by individuals whose families didn't participate in businesses. That is their families have been participating in another activity which is different from business. Looking to the performance of the enterprises in terms of the asset growth, on average they show a 6.53*10 4 and in terms of employment it shows 2.24 during their operation.\par
Generally from this statistical data, those enterprises owned/managed by individuals whose owners is from business family perform better in terms of growth compared to those possessed by individuals whose owners are from non business family. The possible reason is that, being coming from families that have exposure for business will decrease the liability of newness as he/she grows with families always talking about business. Again, those individuals may have learned to expect difficulties and be less disheartened in the face of unfavourable events. 
\section[{X. Hypotheses Testing}]{X. Hypotheses Testing}\par
The following ANOVA and t-test result is used to identify whether those variables are determinates or not. The above table shows that, the Asset growth is significantly different with the gender of the owner/ managers (t=2.638, df=97, p=0.010). So, with respect to the asset growth the hypothesis which states that, there is significant difference on the MSE growth operated by owners with different gender can be accepted. The result indicates there is a significant difference on the asset growth of MSE run by male and female.\par
Again with respect to employee growth, the above analysis suggested that there is no statistically different employment growth between male-headed and female headed SMEs (t=1.287, df=97, p=.201). Even if the average employment growth for male headed (4.74) enterprises are larger when compared with female headed (2.84) enterprises there is no significant difference in employment growth for both of them. The survey results indicated that male and female-headed MSEs generally grew at insignificant difference. With respect to the employment growth the hypothesis which states that, there is a significant difference on the MSE growth operated by owners with different gender is rejected\par
To sum up about the gender variable as one factor that contribute to the growth of MSEs, the t-test provide table with different results. In terms of asset growth gender is statistically different for male and females. But, for employee growth it is statistically insignificant for the difference in the gender of owner/ manager. Based on this it can be concluded that, gender is not the determinants for growth, if growth is measured by employee growth and is the determinants of growth if growth is measured by using asset growth. The above table shows that, the asset growth among different educational levels is not statistically different (F=1.97, df=3, 95, p=0.315) and at the same time employment growth is not statistically different for the difference in education level (F=0.968. df=3, 95, p=0.411). The ANOVA result suggests that there is a weak relationship between the owner/ manager educational level and the asset and employment growth. The result suggested that educational attainment of the owner /manager has no effect on MSE growth. Such findings may suggest that enrolment in formal schooling is a poor measure of skill creation, or that creating skills without opportunities to use them does not foster economic growth.\par
As a result the hypothesis of the study which states that, there is a significant difference on the asset/employment growth of MSE in relation to the difference on the education level of the owner/manager is rejected. Even so the ANOVA result shows that there no significant relation between the educational level of the owner/ manager and the MSE growth, the mean asset/employment growth is high for no schooling part of the educational level which includes those individual who didn't join formal education  Hence, the hypothesis of this study which states, there is significant difference on the performance of enterprises in relation to the owner/ manager age will be rejected. That means age of the owner manager does not affect business growth But, the result of asset growth shows that there is a significant difference between asset growth and age of owner/ manager (F=1.479, df=3, 95, P=0.000). This shows that having young owner/ manager do have a significant effect on asset growth. Those businesses whose the owner/ manager is young grow more than the others.\par
Hence, the hypothesis of this study which states, there is significant difference on the performance of enterprises in relation to the owner/ manager age will be accepted. That means being young have an effect on asset growth.\par
To conclude, the age of the owner/ manager is the determinants of growth if growth is measured by asset growth but is not the determinants of growth if the growth is measured by using employment growth. This is to mean that those businesses owned/ managed by young individual have a large asset growth but have no effect on employee growth. Irrespective of the age of owner/ manager, the employment growth is almost similar. The above ANOVA table shows that the owner manager experience have a direct relation to both asset and employment growth (F=6.063 and 14.930, df=3,95, P=0.001 and 0.000). That means statistically there is a significant relation between the owner/manager experiences and business growth. This is to mean that businesses owned/managed by experienced people will As a result, the hypothesis of this study which states, there is a significant difference on MSE growth with the difference in experience is accepted for both asset and employment growth. To conclude the ANOVA result, the table shows us that owner/ manager experience is the determinants of MSE growth. The above t-test result shows that businesses owned/managed by individuals who is from a family member that owned a business at childhood has a positive effect and statistically significant for asset growth (t=3.832, df=97, P=.000). But the t-test for employee growth shows that the result is statistically insignificant. That means coming from families within business industry have no effect on employment growth. Some reason set for this is that being from business family may contribute to the successful start-up of MSEs, but not necessarily to its growth, when more specific skills necessary to managing growth may be required. Now, based on the above t-test result the hypothesis of this study that states, there is a significant difference on the growth of enterprises with respect to the difference in the family back ground of the owner is accepted if growth is measured by using asset or rejected if growth is measured by employee growth. To conclude the result of the above t-test table MSEs owned/ managed by individuals who came from business family is the determinants of business growth if growth is measured by using asset growth and not a determinant if growth is measured by using employee growth. 
\section[{XI. Conclusion}]{XI. Conclusion}\par
Numerous studies have tried to identify the determinants of firms' growth, mainly in order to isolate those factors which would allow us to distinguish the successful businesses of tomorrow from those which will fail to grow. Ideally, this would allow the implementation of better-targeted economic policies, since growing firms greatly contribute to the creation of jobs and wealth. Nevertheless, the bulk of such research tends to concentrate on MSEs in developed countries; very limited studies have provided such research on MSEs in Africa. To the best of my knowledge, this paper is the first to quantitatively investigate the relationship between MSE growth and owner/ mangers characteristics in our country; Ethiopia and it will fill this gap of knowledge.\par
In this study, while some of the findings support commonly held beliefs, others suggest that some popular concepts regarding small business growth may need to be re-examined. The study supports the idea that, there is a significant variation in the growth of MSEs operating in this town with respect to the gender, experience and family back ground differences if asset is used as a growth measurement. That means the variation in those variables will result in the variation of growth if the measurement of growth is asset growth. But the study shows there is no significant difference between MSE growth with respect to the variation in the level of education of the owner/ managers whether the growth is measured by using asset growth or employment growth. The study found no evidence to support a common perception linking formal higher education with higher incidence of business success and growth.\par
The statistical result for the second dependent variable that is employment shows, there is a significant variation in the growth of MSE with respect to experience and family back ground, if growth is measured using employment growth. With respect to this variable, the statistical result shows there is no difference in growth between MSE with respect to the difference in gender and age of the owner / manager.\par
Based on the finding, as enterprises owned/ managed by individuals with high previous experience shows better growth; stakeholders of the sector should work on preparing training programs so that they can share experience with one another especially to those entering into the sector without any previous business background. Again education level which is expected to have an effect on MSE growth doesn't affect growth here. This is because of the fact that the education system of the country is more of theory based than practical. So it is good if the education system of the country is practical rather than a theory based and other subjects about business should be given at lower grades that everybody who joins school can get it.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
  \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.17607142857142857\textwidth}P{0.12142857142857141\textwidth}P{0.32785714285714285\textwidth}P{0.06071428571428571\textwidth}P{0.16392857142857142\textwidth}}
Employment growth\tabcellsep Male\tabcellsep 38 4.74\tabcellsep 7.232\tabcellsep 1.173\\
\tabcellsep Female\tabcellsep 61 2.84\tabcellsep 7.090\tabcellsep .908\\
asset growth\tabcellsep Male\tabcellsep \multicolumn{2}{l}{38 2.55E5 312419.567}\tabcellsep 50681.146\\
\tabcellsep Female\tabcellsep \multicolumn{2}{l}{61 1.14E5 217739.999}\tabcellsep 27878.750\end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.3786026200873362\textwidth}P{0.09279475982532752\textwidth}P{0.20414847161572053\textwidth}P{0.17445414847161572\textwidth}}
\multicolumn{3}{l}{Education status of owner/manager Asset growth}\tabcellsep Employment growth\\
no schooling\tabcellsep Mean\tabcellsep 263950.00\tabcellsep 5.00\\
\tabcellsep N\tabcellsep 13\tabcellsep 13\\
elementary\tabcellsep Mean\tabcellsep 180471.05\tabcellsep 1.58\\
\tabcellsep N\tabcellsep 19\tabcellsep 19\\
high-school\tabcellsep Mean\tabcellsep 116745.71\tabcellsep 3.24\\
\tabcellsep N\tabcellsep 42\tabcellsep 42\\
collage/university\tabcellsep Mean\tabcellsep 195676.16\tabcellsep 4.88\\
\tabcellsep N\tabcellsep 25\tabcellsep 25\\
Total\tabcellsep Mean\tabcellsep 168237.62\tabcellsep 3.57\\
\tabcellsep N\tabcellsep 99\tabcellsep 99\end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.42229299363057327\textwidth}P{0.25175159235668787\textwidth}P{0.08662420382165606\textwidth}P{0.08933121019108281\textwidth}}
Age of the owner /manager\tabcellsep \tabcellsep \multicolumn{2}{l}{Asset growth Employment growth}\\
\tabcellsep \multicolumn{2}{l}{Mean 95,700.00}\tabcellsep 5.00\\
less than 25\tabcellsep N\tabcellsep 10\tabcellsep 10\\
greater than or equal to 25 and less than35\tabcellsep \multicolumn{2}{l}{Mean 271,305.07 N 54}\tabcellsep 4.54 54\\
greater than or equal to 35 and less than 45\tabcellsep \multicolumn{2}{l}{Mean 19,940.00 N 25}\tabcellsep 2.20 25\\
greater than or equal to 45\tabcellsep \multicolumn{2}{l}{Mean 54,955.00 N 10}\tabcellsep .30 10\\
Total\tabcellsep \multicolumn{2}{l}{Mean 168,237.62 N 99}\tabcellsep 3.57 99\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.85\textwidth}}
Year\\
Volume XV Issue IV Version I\\
( ) C\\
Global Journal of Management and Business Research\end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.12202970297029701\textwidth}P{0.22301980198019802\textwidth}P{0.03787128712871287\textwidth}P{0.10099009900990098\textwidth}P{0.2524752475247525\textwidth}P{0.11361386138613862\textwidth}}
\tabcellsep \multicolumn{2}{l}{Group Statistics}\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Family ownership of\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep business\tabcellsep N\tabcellsep Mean\tabcellsep \multicolumn{2}{l}{Std. Deviation Std. Error mean}\\
Employment growth\tabcellsep Yes\tabcellsep 53\tabcellsep 4.72\tabcellsep 6.640\tabcellsep .912\\
\tabcellsep No\tabcellsep 46\tabcellsep 2.24\tabcellsep 7.590\tabcellsep 1.119\\
asset growth\tabcellsep Yes\tabcellsep 53\tabcellsep 2.58E5\tabcellsep 302604.984\tabcellsep 41565.991\\
\tabcellsep No\tabcellsep 46\tabcellsep 6.53E4\tabcellsep 166525.236\tabcellsep 24552.807\end{longtable} \par
 
\caption{\label{tab_4}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.1537542662116041\textwidth}P{0.0667235494880546\textwidth}P{0.08703071672354948\textwidth}P{0.04351535836177474\textwidth}P{0.16535836177474403\textwidth}P{0.09863481228668942\textwidth}P{0.17696245733788393\textwidth}P{0.05802047781569966\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{T-test for Equality of Means}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{95\% Confidence Interval of the}\\
\tabcellsep \tabcellsep \tabcellsep Sig. (2-\tabcellsep Mean\tabcellsep Std. Error\tabcellsep \multicolumn{2}{l}{Difference}\\
\tabcellsep \tabcellsep t Df\tabcellsep tailed)\tabcellsep Difference\tabcellsep Difference\tabcellsep Lower\tabcellsep Upper\\
\multicolumn{2}{l}{asset growth Equal variances assumed}\tabcellsep \multicolumn{2}{l}{2.638 97 .010}\tabcellsep 140663.735\tabcellsep 53316.168\tabcellsep 34845.901\tabcellsep 246481.569\\
Employment growth\tabcellsep Equal variances assumed\tabcellsep \multicolumn{2}{l}{1.287 97 .201}\tabcellsep 1.901\tabcellsep 1.477\tabcellsep -1.030\tabcellsep 4.831\end{longtable} \par
 
\caption{\label{tab_5}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{P{0.48571428571428565\textwidth}P{0.04047619047619047\textwidth}P{0.20238095238095236\textwidth}P{0.12142857142857141\textwidth}}
ANOVA Table\tabcellsep \tabcellsep \tabcellsep \\
Sum of\tabcellsep \tabcellsep Mean\tabcellsep \\
Squares\tabcellsep Df\tabcellsep Square\tabcellsep F Sig.\end{longtable} \par
 
\caption{\label{tab_6}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.5709302325581396\textwidth}P{0.0872093023255814\textwidth}P{0.033720930232558136\textwidth}P{0.08837209302325581\textwidth}P{0.02558139534883721\textwidth}P{0.02558139534883721\textwidth}P{0.018604651162790697\textwidth}}
\tabcellsep \multicolumn{2}{l}{ANOVA Table}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep Sum of\tabcellsep \tabcellsep Mean\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Squares Df}\tabcellsep Square\tabcellsep F Sig.\\
Employment growth * age of the owner /manager\tabcellsep Between Groups\tabcellsep (Combined)\tabcellsep 224.797\tabcellsep 3\tabcellsep 74.932\tabcellsep 1.479 .225\\
\tabcellsep \multicolumn{2}{l}{Within Groups}\tabcellsep \multicolumn{2}{l}{4811.526 95}\tabcellsep 50.648\tabcellsep \\
\tabcellsep \multicolumn{2}{l}{Total}\tabcellsep \multicolumn{2}{l}{5036.323 98}\tabcellsep \tabcellsep \\
asset growth * age of the owner /manager\tabcellsep Between Groups\tabcellsep \multicolumn{2}{l}{(Combined) 1.304E12}\tabcellsep \multicolumn{3}{l}{3 4.348E11 7.356 .000}\\
\tabcellsep \multicolumn{2}{l}{Within Groups}\tabcellsep \multicolumn{3}{l}{5.615E12 95 5.910E10}\tabcellsep \\
\tabcellsep \multicolumn{2}{l}{Total}\tabcellsep \multicolumn{2}{l}{6.919E12 98}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{The above ANOVA results indicated that there is}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{no significant difference in employment growth of}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{different MSEs owned/managed by peoples in different}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{age level (F=7.356, df=3, 95, P=0.225). That is, the}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{relation between owner /manager age and employee}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{growth is not statically different. Holding other business}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{and owner characteristics constant, being young, does}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
not seem to affect employee growth performance.\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.48571428571428565\textwidth}P{0.04047619047619047\textwidth}P{0.20238095238095236\textwidth}P{0.12142857142857141\textwidth}}
ANOVA Table\tabcellsep \tabcellsep \tabcellsep \\
Sum of\tabcellsep \tabcellsep Mean\tabcellsep \\
Squares\tabcellsep Df\tabcellsep Square\tabcellsep F Sig.\end{longtable} \par
 
\caption{\label{tab_8}Table 9 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{10} \par 
\begin{longtable}{P{0.06101485148514851\textwidth}P{0.2103960396039604\textwidth}P{0.08626237623762377\textwidth}P{0.004207920792079208\textwidth}P{0.06522277227722773\textwidth}P{0.09257425742574257\textwidth}P{0.10099009900990098\textwidth}P{0.1556930693069307\textwidth}P{0.07363861386138613\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{95\% Confidence Interval of the}\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Sig. (2-\tabcellsep Mean\tabcellsep Std. Error\tabcellsep \multicolumn{2}{l}{Difference}\\
\tabcellsep \tabcellsep t\tabcellsep Df\tabcellsep tailed)\tabcellsep Difference\tabcellsep Difference\tabcellsep Lower\tabcellsep Upper\\
Employment growth\tabcellsep Equal variances assumed\tabcellsep \multicolumn{2}{l}{1.733 97}\tabcellsep .086\tabcellsep 2.478\tabcellsep 1.430\tabcellsep -.360\tabcellsep 5.316\\
\tabcellsep Equal variances not assumed\tabcellsep \multicolumn{2}{l}{1.716 90.199}\tabcellsep .090\tabcellsep 2.478\tabcellsep 1.444\tabcellsep -.390\tabcellsep 5.346\\
asset growth\tabcellsep Equal variances assumed\tabcellsep \multicolumn{2}{l}{3.832 97}\tabcellsep .000\tabcellsep 192212.696\tabcellsep 50157.321\tabcellsep 92664.299\tabcellsep 291761.094\\
\tabcellsep Equal variances not assumed\tabcellsep \multicolumn{2}{l}{3.982 82.949}\tabcellsep .000\tabcellsep 192212.696\tabcellsep 48275.997\tabcellsep 96192.805\tabcellsep 288232.588\end{longtable} \par
 
\caption{\label{tab_9}Table 10 :}\end{figure}
 			\footnote{According to the Ethiopian MSE development Strategy, Micro enterprises are business with less than 5 employees and capital of less than 100,000 birr. Again Small enterprises are business with employees of 6-30 and capital of less than 1.5 million birr.} 			\footnote{© 2015 Global Journals Inc. (US)} 			\footnote{© 2015 Global Journals Inc. (US) 1} 			\footnote{Workers here includes even working owners (entrepreneurs), since job creation for owners may be equally as valuable, from a social point of view, as jobs created for others. On the other hand, unpaid family helpers are excluded, both because their relationship is more frequently part-time and casual (as well as unpaid), and because they cannot be reliably measured. Employment is defined as the sum of regular workers, contract workers, and working entrepreneurs.} 			\footnote{Experience here includes the work done by the owner/manager other than this position held. It is the total number of years the person spent on work.} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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