Keywords

Entrepreneurial Training, Startup Capital, and Promote Youth Employments.

Introduction

Recently, youths’ unemployment is a hot issue and becomes the main socio-economic problem all over the world. It creates several economic, political, psychological, and social problems in the across the world especially in developing countries. Hence Youth unemployment is the most critical challenges and hottest issues that need priorities in several African countries despite the helpful economic development rates experienced over the previous period. There are various pointers that shows this development has not created enough and dressed employment opportunities for the youth in developing countries specifically for Africa. These Inadequate employment occasions that hastily growing young labor force can lead to social unrest and political instability (Ministry of Gender, Labor and Social Development, 2018). The difficulties tackled by young people in most developing countries for finding work are recognized to limited skills mismatches and limited or no work experience. As a result, most African youth engage in low quality informal sector jobs.

Unemployment among youths is very critical issues and most challenges of many African countries. Investigators and politicians alike consider entrepreneurship to be portion of the solution to the increment of youth unemployment rates. To solve this problems, the integration of young people into the labor market is significant objectives of all over the world and specifically, it is a key policy issue of the Ethiopian Employment Scheme. In Ethiopia, joblessness is a serious concern where almost two-thirds of the population is younger than 25 years. Indeed, Ethiopia has one of the highest urban unemployment rates at about 50 per cent of the youth labor force (Fox & Kaul, 2018; ILO, 2014). Joblessness of these young people results in increasing crime rates and violence, dependence on family, low self-esteem, poor social adaptation, depression and loss of confidence (Karlan & Valdivia, 2011)

The government of Ethiopia has recently start to pay due attention to youth employment concerns by taking vital actions to transform the youth workforce into productivity and job-creation schemes. However, the government of Ethiopia still unable to reduce unemployment rate. These results as a big burden of improving the economy of the country. According to a survey in 55 urban areas, joblessness was projected at 41.3% and the prevalence of joblessness was 45.5% and 35.7% for females and males respectively (Bauer, 2011a). To overcome such challenges and one ways to minimize joblessness is giving awareness for youth about business. To do this, Entrepreneurship training programs that combine training with finance have more effect on rising self-employment via start-up capitals as well as enhancing business performance and practices (Cho & Honorati, 2014; de Mel et al., 2014). Entrepreneurs are more likely to persist self-employed if they have access to a second capital grant (Mayuran, 2016) Programs which deliver training for entrepreneurs regularly embrace other involvements such as micro-finance, grants, internships or mentorship (McKenzie & Woodruff, 2014).

Various studies had been conducted on unemployment and its challenges in Ethiopia. For examples the studies of (Alemnew, 2014; Cho & Honorati, 2014; Eyasu, 2016; Tsegaw, 2019) reveals that young unemployment increase in high rates because of low job creation and increasing environmental threats Marina J Mayer. (2011). However, no more in-depth study and concrete data on entrepreneurial training, and start-up capitals. While the general facts are clear, the specific promoting youth employment through entrepreneurship trainings, and start-up capital have received little research attention Cao & Shi (2021).

A pre-survey taken by the investigator in the study area from the workers of micro and small business enterprise office shows that, there is a quick increase unemployment and this raises many socio-economic problems in the Bale Gasger distinct. Long-term unemployment always results in causing political instability financial hardships, poverty, homelessness, crime, frustration and many other problems like breakdown and family tension, social isolation, loss of confidence and self-esteem, All these lead to the erosion of a healthy society. Even though they face many problems, in Bale gasger district. Thus, this study intends to fill this gap by investigating the effect of entrepreneurship training and startup capital on promoting youth employment in Bale Gasger distinct Belitski et al. (2021).

Accordingly, the subsequent parts of this paper are structured as follows: following the introduction section, an overview of entrepreneurship training and startup capital and extensive literature review of variables used in this study and hypothesis development was addressed in section two. Section three outlines the methodology part and data used, whereas section four portrays the result and discussion part of the study. The final part of this paper, section five contains the conclusion and implications for further research Choudhry et al. (2012).

Literature Review

Overview of Related Literature Review

Entrepreneurship training programs frequently the goal of remaining and aspirants of entrepreneurs, so the rate of business start-up after the involvement is an pointer of success (Duguma & Tolcha, 2019; Nkechi et al., 2012). The Whole, start-up rates are uncertain in the short-term and generally disperse over the long-run. Two studies find that the control group ultimately catches up with the treatment group in terms of setting up a novel business (de Mel et al., 2014; Gine & Mansuri, 2019; McKenzie & Woodruff, 2014).

Across the world, different governments and organizations have taken initiative to help the youth in entrepreneurship. The Prince’s Trust Enterprise Programmed in Britain, for example, was set up for young people who have a business idea they want help to explore, are aged 18-30 and are unemployed or working less than 16 hours per week. Services provided by this program include; Advice on employment options, business skills training, business planning support, start-up loan funding, ongoing support from a volunteer business mentor, access to specialist support, including free legal services and, if one wants to start a business, access to a wide range of free and discounted products and services (Fox & Kaul, 2018; ILO, 2014).

According to research done by (Kithae et al., 2013) Entrepreneurship training was found to have had a substantial impact on performance of entrepreneurs. Further, constant monitoring was found necessary to make the skills learnt be translated into more practical work. Even though, they were not able to translate their leant skills due to inadequate finance and lack of monitoring. Entrepreneurs trained were mostly in the trade sector, aged with no formal education and were sole proprietors and all employees agreed that training program is beneficial to their business function Minola et al. (2021). The empirical information resulted from analyzing the data obtained from the SMEs, suggests that manager's, enterprise's and external characteristics affect the demand for training, and training has a positive impact on SMEs performance including profit, revenue and size. Findings revealed that there was a significant and positive relationship between training, and manager's characteristics, enterprise's characteristics and external characteristics (Akmaliah et al., 2013; Mayuran, 2016; Montgomery et al., 1998).

Affect Entrepreneurship training on promoting youth employment

Entrepreneurship training plans are more operative with respect to improving business knowledge and better business practices (de Mel et al., 2014). There was a helpful outcome on business practices in the meta-analysis of 37 programs, particularly amongst existing small businesses(Cho & Honorati, 2014). Other studies witnessed that enhancements in terms of finances and asset managing is vital issues in business (Gine & Mansuri, 2019). Furthermore, these improvements were viable over the long-term(de Mel et al., 2014). In addition, entrepreneurship training is valuable for female entrepreneurs because it enhances their self-confidence and logic of self-empowerment (Bauer, 2011b; Rauth Bhardwaj, 2014).

The impact of entrepreneurship training programs can be magnified by combining training with finance, as such programs are more effective in terms of fostering self-employment and as well as helping entrepreneurs to improve business performance and operations (Cho & Honorati, 2014; de Mel et al., 2014). A study in Chile finds that training which incorporate a second capital grant are more effective in terms of promoting self-employment in the long-term (Mayuran, 2016).

H1: Entrepreneurship training has a positive and significant effect on Promoting Youth Employment.

Effects of startup capital on promoting youth employment

The evidence shows that a package of training and finance is further effective for enhancing the whole contributions in labor market activities than training alone The mixtures of training and finance brings constructive labor market outcomes for the youth and social support heirs, but not for women (Cho & Honorati, 2014). Additionally, (de Mel et al., 2014) detect that business training alone does not increase profits, sales, or capital stock of current firm owners, or change the number of hours the owners spend working in their businesses. However, the combination of training with cash grants had a helpful effect on young unemployment(de Mel et al., 2014).

Accessing credit facilities has been well-known as a key component for small and medium enterprises to flourish in their initiative to build fruitful capacity, to strive, to generate jobs and to donate to poverty alleviation in developing countries. Youth entrepreneurs, especially, face a lot of challenges in accessing finances for their business both as start up, seed capital and finance expansion of the businesses.(Gine & Mansuri, 2019; Montgomery et al., 1998) According to (Akhuemonkhan et al., 2013; Kithae et al., 2013). There is inadequate access to financial resources offered to smaller enterprises compared to larger business firms and the consequences for their growth and development. Another crucial financial problem faced by SMEs is managing sales and debtors (Nkechi et al., 2012)

H2: Startup capital has a significant effect on Promoting Youth Employment.

Conceptual Framework

The dependent variable is employment while the independent variables are: start-up capital, and training and the following are the conceptual frame work of this study shows in Figure 1.

The study was used a mixed of qualitative and quantitative research approach. Mixed methods method is one in which the investigator inclines to base knowledge maintain on practical grounds and the study used this method due to the evidence gathering engages both numeric information as well as writing information so that the finishing binder signifies both quantitative and qualitative information. In addition, the study was used descriptive and explanatory research design to analyses data and obtain adequate information about realities of the study. A descriptive research explains and reports the way things are and tries to define things as possible behavior, attitudes, values and features and this is why the researchers needs to use descriptive research design. In this case that, the researcher was also used to examine the relationship between entrepreneurship trainings, start-up capital factors and youth employment by using explanatory research deign.

Target Population and Sample Size

Population to refer to the proposed population enclosed by a study in a specific geographical area such as country, region and town in terms of age group and gender. Accordingly, the target populations of this study were all employees of public servant at bale gasger distinct. Therefore, from those employees the researcher was select sample of respondents. Since the population size for this research was limited in number 196, all target populations were included in the study using census method. Therefore, the study was conducted on 196 employees those were a target population from the study area through total enumeration with a census method Shita & Dereje (2018).

Sources of Data and method of data collection

The main source of data was from both primary and secondary sources. Primary data were collected through questioners and interview; questionnaire is prepared for the youth in general which is the major primary source. In addition to this, the secondary sources of data were used to strengthen the primary sources. Secondary source of data was collected. The method of data collection was survey method; survey research method was for this research because it is an appropriate method for measuring respondent’s opinion and attitude. The data collection tool that was used to gather data from sample respondents is questionnaire and interview. In addition to the questionnaires, the researcher was prepared informative interview questions too purposively. The interview was used based on the assumption that the participants’ perspectives are meaningful, and they have the knowledge in the area, and able to make precise points, and their perspective affects the success of the research Brieger & Gielnik (2021).

Method of Data Analysis

To assess the collected data, some kinds of statistical methods including descriptive statistics and inferential statistics (multiple regressions) were used. Furthermore, descriptive are applied for frequencies, and percentage value was computed using SPSS (23). Then the data were analyzed and interpreted within necessary information collected from respondents. The analysis and interpretation are based on the respondent’s responses and stated by simple and clear sentences to express the qualitative data and quantitative data. The quantitative data were mainly expressed by using table and chart, percentage, mean values and rank order whereas the data collected through interviews and documents were analyzed qualitatively concurrently to strengthen the analysis of the questionnaires. In this study, multiple linear regression models were used to achieve research objectives. The basic objective of using multiple linear regression analysis was to because of there is cause and effects between dependent and independent variables of this study. According to Gujarati (1995) defines a regression function as follows:

Υ = β 0+ β 1Χ1+ β 2Χ2+ β 3Χ3 +β 4Χ4…+ β n Χn+ ui

Where

Y is the dependent variable (employment)

βn is the coefficient of independent variables.

Xn is independent variables (startup capital, and entrepreneurial training)

Ui is error term.

Validity and Reliability of Research Instruments

Validity is a measurement characteristic that describes the ability of a research instrument or tool to measure what it was intended to measure. In this study, validity of instruments is ensuring by using simple language when constructing instruments for respondents to understand easily. Questionnaires were pre-tested by potential expert. It was examined and checked by consultant and other experts who have knowledge about the study issue. Reliability is a measure of the degree to which a research instrument yields consistent results or data the same way each time it is used under the same condition with the same subjects. The reliability of the instrument was measured by using Cronbach’s alpha test.

Ethical Considerations

They are actions taken to assure the safety and rights of participants are not violating whatsoever. These considerations are therefore usually made to ensure that research involving human or living thing subjects is carried out following high ethical standards. These standards include voluntary participation, informed permission, and confidentiality of information, ambiguity to research participants and approval from relevant authorities such as independent review boards (IRBs) to conduct the research study. In this study, participants were voluntarily allowed to participate and prospective research participants was fully informed on procedures, benefits, and risks involved in the research after which they were voluntarily asked to fill informed consent forms to participate. They were a guarantee of confidentiality of the information and to ensure this was achieved participants were not asked to give their names or indicate anything on the research instruments that could be used to identify or link them to the study documents or reports.

Result Presentation and Analysis

Introduction

In this chapter, both descriptive and explanatory data analysis and procedures are presented. The data analysis follows the phases discussed in chapter three (under research design and analysis methods). The first phase involves editing, coding and the tabulation of data. The main aim of this chapter was presenting the primary and secondary data that was collected during this study. These data were collected in order to answer the main objective of the study. The data was then checked for possible erroneous entries and corrections made appropriately. This chapter deals with results and discussions of the data that are classified into two sections. In this study, both quantitative and qualitative methods of analysis were employed and the report was organized in a way to answer research questions raised in this research sequentially. The data were entered by using SPSS version 23 and the results of the descriptive analyses are presented first, followed by the explanatory analysis.

Descriptive Statistics

Effect of entrepreneurship training

The analysis is based on the assumption (Zedatol, 2009) comparison bases of mean score for five point Likert scale instruments is used to compare the mean value. According (Zedatol, 2009) mean score 3.80 and above is consider high, 3.40-3.79 is moderate and 3.39 and below is low satisfaction. Therefore, the fairness perceptions of the performance appraisal practices in the study considered by the above thresholds. The study required to found the Effect of entrepreneurship training on promoting youth employment at Bale gasger. The findings of the study were discussed below Table 1.

Table 1 Effect of Entrepreneurship Training on Promoting Youth Employment
Descriptive Statistics
	N	Mean	Std. Deviation
Effect of entrepreneurship training on promoting youth employment.	196	4.4082	.64588
Lack of business plan preparation skills to convince micro finance institution.	196	3.9082	.95635
Entrepreneurship training is the most important solution  to youth unemployment.	196	4.3265	.74800
Entrepreneurship training has enabled youth to get away from home of poverty.	196	2.9694	.97617
Entrepreneurship training has enabled me improve my economic status.	196	4.0918	1.33272
Entrepreneurship training has contributed directly and indirectly to development of community.	196	4.5765	.49537
Received any training on entrepreneurship from any organization is help full	196	4.587	.8023
Training will have very good chance to find employment	196	4.3112	1.00260
Valid N (listwise)	196

The respondents’ views on the Effect of entrepreneurship training on promoting youth employment at Bale gasgar had varied agreeing on table above 4.1: For the case of Effect of entrepreneurship training on promoting youth employment, a mean of 4.4082 and std. deviation of 0.64588, for the case of Lack of business plan preparation skills, a mean of 3.9082 and std. deviation of 0.95635 and for the case of Entrepreneurship training is the most important solution to youth unemployment, a mean of 4.3256 and std. deviation of 074800. For the case of Entrepreneurship training has enabled youth to get away from home of poverty a mean of 2.9694 and 0.97617. For the case of Entrepreneurship training has improve economic status, a mean of 4.0918 and std. deviation of 0.1.33272, for the case of Entrepreneurship training has contributed directly and indirectly to development of community, a mean of 4.5867 and std. deviation of 0.49537 and for the case of received any training on entrepreneurship from any organization, a mean of 4.587 and std. deviation of 0.8023 and for the case of Training will have very good chance to find employment a mean of 4.3112 and 1.00260.

From the above result the researcher found that, the majority of the respondents strongly agreed that received any training on entrepreneurship from any organization is helpfull.in the case of Bale gasger and Entrepreneurship training has contributed directly and indirectly to development of community.

Effect of Startup Capital

The study required to found the Effect of startup capital on promoting youth employment at Bale gasger. The findings of the study were discussed below Table 2.

Table 2 Effect of Startup Capital on Promoting Youth Employment
Descriptive Statistics
	N	Mean	Std. Deviation
Startup capital is the most important solution  to youth unemployment	196	3.4184	1.31986
Lack of trust by guarantors to guarantee the youth enterprises	196	4.2959	.80012
Fear of collateral requirement from lending institutions on SMEs	196	4.5561	.72460
Startup capital has enabled affiliated youth to get out of poverty	196	4.5765	.49537
Lack of sufficient collaterals required by financiers	196	4.5510	.49866
Valid N (listwise)	196

The respondents’ views on the Effect of entrepreneurship training on promoting youth employment at Bale gasgar had varied agreeing on table above 4.2: For the case of Startup capital is the most important solution to youth unemployment, a mean of 3.4184 and std. deviation of 0.1.31986, for the case of Lack of trust by guarantors to guarantee the youth enterprises, a mean of 4.2959 and std. deviation of 0.80012, for the case of Fear of collateral requirement from lending institutions on SMEs, a mean of 4.5561 and std. deviation of 0.72460. for the case of Startup capital has enabled affiliated youth to get out of poverty, a mean of 4.5765 and.0.49537and for the case of Lack of sufficient collaterals required by financiers, a mean of 4.5510 and std. deviation of 0.49886.

From the above result the researcher found that, the majority of the respondents strongly agreed that Startup capital has enabled affiliated youth to get out of poverty in the case of Bale gasger and Fear of collateral requirement from lending institutions on SMEs is another problem due to Lack of sufficient collaterals required by financiers.

Effect of Youth Employment

The study required to found the Effect of promoting youth employment at Bale gasger. The findings of the study were discussed below Table 3.

Table 3 Promotion of Youth Employment
Descriptive Statistics
	N	Mean	Std. Deviation
Employment increases self-confidence of youth	196	4.4847	.86218
Employment decline dependence of youth on their  family	196	4.4643	.94665
Employment reduce depression of youth	196	4.1633	1.06885
Employment of youth can calm down political instability	196	4.0408	.91616
Employment increase income of youth	196	4.3367	.77053
Valid N (listwise)	196

The respondents’ views on the Effect of entrepreneurship training on promoting youth employment at Bale gasgar had varied agreeing on table above 4.3: For the case of Employment increases self-confidence of youth, a mean of 4.4847 and std. deviation of 0.86218, for the case of Employment decline dependence of youth on their family, a mean of 4.4643 and std. deviation of 0.94665, for the case of Employment reduce depression of youth, a mean of 4.1633 and std. deviation of 1.06885. For the case of Employment of youth can calm down political instability, a mean of 4.0408 and 0.91616 and for the case of Employment increase income of youth, a mean of 4.3367and 0.77053

From the above result the researcher found that, the majority of the respondents strongly agreed that Employment increases self-confidence of youth in the case of Bale gasger followed by Employment decline dependence of youth on their family.

Correlational Analysis

In this portion of the analysis bivariate Pearson correlation coefficient has been castoff to observe the association between the dependent and independent variable. According to (Robert, 2008), Pearson correlation coefficients ranges between -1 and +0.1, when 0 indicates no association between, -1.00 shows a perfect negative relationship and +1.00 specifies a perfect positive relationship. For intermediate values the study uses Pall ant (2010) guideline to conclude the strength of the correlation, less than 0.1 show weak correlation, small correlation for value 0.1 to 0.29; medium/moderate for 0.3 to 0.49; and large for 0.50 to 1.00) shows in Table 4.

Table 4 Correlations of Startup Capital, Entrepreneurial Training and Youth Employments
Correlations
		Youth employments	Entrepreneurship training	Startup capital
Youth employments	Pearson Correlation	1	0.935**	0.929**
	Sig. (2-tailed)		0.000	0.000
	N	196	196	196
Entrepreneurship training	Pearson Correlation	0.935**	1	0.980**
	Sig. (2-tailed)	0.000		0.000
	N	196	196	196
Startup capital	Pearson Correlation	0.929**	0.980**	1
	Sig. (2-tailed)	0.000	0.000
	N	196	196	196
**. Correlation is significant at the 0.01 level (2-tailed).

The above Table 4. illustrates the correlation in between independent and dependent variables. Accordingly there is a positive and significant relationship in between entrepreneurship and promoting youth employment (r = .935, N = 196, p<0.001 ) and there is a positive and significant relationship in between startup capital and promoting youth employment (r=0.929, N=196, p<0.001) but there is no relationship in between strategic planning and sustainable business practices.

Regression Analysis

Through a correlation analysis it is identified that there is a significant relationship between the Startup capital, Entrepreneurial training and mentoring and promoting youth employments. To what extent the variance in the dependent variables will be explained by the independent variable is discussed here.

The above Table 5 depicts model summary. Accordingly, a highly significant relationship (p=0.001) between the dependent variable and the linear combination of the predictor variables as indicated by R (0.937). The coefficient of determination (R square) is a measure of how good prediction of the criterion variable that can be selected by knowing the predictor variables. Accordingly, 87.8% of the variation in the dependent variable was explained by the set of the above independent variables. However, R- squared measures the proportion of the variation in the dependent variable explained by independent variables, irrespective of how well they are correlated to the dependent variable. This is not a desirable property of a goodness of – fit statistic. Conversely, adjusted R – squared provides an adjustment to the R- squared statistic such as an independent variable that has a correlation to dependent variable increases adjusted R- squared and any variable without a strong correlation will make adjusted R- squared decrease. Therefore, to see the success of the model in the real world adjusted R- squared more preferable than R- squared (Burns & Burns, 2008). Accordingly, adjusted R- squared, the variation is explained by the regression of dependent variable on the combined effect of all the predictor variables is 87.6%. Hence, generally speaking, the independent variables (such as startup capital, and entrepreneurship training.) can predict the dependent variable (youth employments) by 87.6%.

Table 5 Model summary
Model Summaryb
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics					Durbin-Watson
					R Square Change	F Change	df1	df2	Sig. F Change
1	.937a	.878	.876	.30459	.878	692.723	2	193	.000	.089
a. Predictors: (Constant), startup capital, entrepreneurship training
b. Dependent Variable: youth employments

The analysis of variance (ANOVA) in the above Table 6 provides statistics about the overall significance of the model being tested. The significant value which is also P-Value in the model is 0.000 which indicates the independent variable in the model explains the dependent variable. From the ANOVA (Analysis of variance) table shown above, it is possible to describe that, from the total observation value (146.439), the regression model explains majority of the observation (128.534). The remaining (17.905) is not explained by the model. Hence, it is possible to deduce that regression explains most of observations while the other observations are explained by extraneous variables. Mean square of the model (regression) represents the average amount of variation explained by the model is 64.267 and mean square of the residual is 0.093 which is the average amount of variation explained by extraneous variables (the unsystematic variation). The F ratio (692.723) which indicates that a measure of the ratio of the variation explained by the model and the variation explained by extraneous variables. Hence, the value of F is large enough to conclude that the set of independent variables as a whole are contributing to the variance of promoting youth employment and therefore, the model represents actual practice of the business operators under study.

Table 6 Anova
ANOVAa
Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	128.534	2	64.267	692.723	0.000b
	Residual	17.905	193	0.093
	Total	146.439	195
a. Dependent Variable: youth employments
b. Predictors: (Constant), startup capital, entrepreneurship training

The above Table 7 illustrate the coefficient of the variables. The un standardized coefficient of an independent variable (also called B or slope) measures the strength of its relationship with the dependent variable (youth employments); this means, the variation in the youth employments corresponds to the variation in the independent variables (such as: Entrepreneurship training and Startup capital). A coefficient of 0 means that, the dependent variable does not consistently vary as the independent variables vary. In this research model, the coefficient for the Entrepreneurship training is 0.676; and the coefficient for Startup capital is 0.419. So, for a certain variation in each independent variable as stated above, there was a consistent variation in the youth employments. That is, Entrepreneurship training predict youth employments by 67.6%, and the Startup capital predicts the youth employments by 41.9%.

Table 7 Coefficient of Variables
Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	-0.301	0.160		-1.881	0.061
	Entrepreneurship training	0.676	0.140	0.608	4.818	0.000
	Startup capital	0.419	0.158	0.334	2.646	0.009
a. Dependent Variable: youth employments

The standardized beta (β) coefficient column also showed that the contribution that an individual variable makes to the model. The beta weight is the average variation the dependent variable (youth employments) increases when the independent variables (Entrepreneurship training and Startup capital) increase by one standard deviation (all other independent variables are held constant). Thus, the largest influence on youth employments is from the Entrepreneurship training (.608), and the next is Startup capital (.334). The table which is illustrated above further shows that all the explanatory (independent) variables included in this study except strategic planning can significantly explain to the variation on the dependent variable at 95% confidence level. That means in other words, a unit intervention by Entrepreneurship training can enhance youth employments by 60.8% being other things remain constant and a unit intervention made by Startup capital enhances(affects) youth employments by 33.4% being other things held constant.

Table 8 presents the coefficient of regression between entrepreneurship, startup capital and Promoting Youth Employment. It shows that the regression result at a confidence interval level of 95% with standardized data coefficients. The standardized beta coefficient column reveals the role that an individual variable makes to the model. The beta weight is the average volume of the dependent variable which rises when the independent variable increases by one standard deviation (all other independent variables are held constant). By comparing them, the most effective variable is Entrepreneurship training having a standard coefficient of (Beta 0. 608) followed by startup capital (Beta 0.334), and it can be concluded all variables under this study have a significant role for the Promoting Youth Employment. Therefore, all the hypotheses should have accepted and are analyzed:

Table 8 Discussion of Hypotheses
Hypothesis	Beta Value	Sig	Result
Hypothesis 1 (H1): Entrepreneurship training has a positive and significant effect on Promoting Youth Employment.	0.608	0.00	Positive, Significant Accepted
Hypothesis 2 (H2): startup capital has a significant effect on Promoting Youth Employment.	0.334	0.009	Positive, Significant Accepted

Hypothesis 1(H1): There are effects and positive correlation (p<0.05) between entrepreneurship, and Promoting Youth Employment as perceived by worker’s respondents. Result: P=0.00 and B is positive, hypothesis 1 is accepted and the null hypothesis is safely rejected, thus entrepreneurship has a significant effect on the performance of employees in promoting youth employment.

Hypothesis 2(H2): There are effects and positive correlation (p<0.05) between startup capital and Promoting Youth Employment as perceived workers’ respondents. Result: P=0.009 and B is positive, hypothesis 2 is accepted and the null hypothesis is safely rejected, thus startup capital has significant effects on employee performance and promoting youth employment.

Conclusion and Recommendations

The main objective of this study was to examine promoting youth employment through entrepreneurship training, and start-up capital. To achieve its objective, the study has employed descriptive research design and exploratory research design. The study employed descriptive statistics such as mean, frequency and percentage for descriptive analysis and used inferential statistics such as correlation and multiple linear regression models. In the model promoting youth employment were taken as the dependent variable and start-up capital, and entrepreneurship training variables were taken as independent variables.

The study revealed that startup capital has a lion share contribution in promoting youth employment and in the study area majority of the youth face challenges on the access to finances from financial institutions which hinders performance since good financial management is critical to the success of any business, and without it, a business can be set for failure from the start. Based on the findings, the study concludes that entrepreneurial training is conducted to enhance the youth employment. A lot of young people mention that there are no multiple alternatives to create their own businesses to solve their temporary problem and lack of opportunities challenges of youth unemployment of the bale gasger Woreda. The finding

revealed that graduate expectation of a smooth and rapid transition from school to work, attitude towards work, and low level of initiative keep youth away from being proactive in starting their own businesses. Most young people's dissatisfaction with the current policy of youth because the government failed to create opportunities and empowering youth in multidimensional, the situation is aggravated particularly for women and migrants of young people from rural-urban, to address the problem of youth unemployment. A comprehensive strategy of employment creation seeks to promote job creation in the public, private sector, and also in terms of promoting self-employment and entrepreneurship.

The finding from correlation analysis shows Startup capital is the most correlated variable with youth employments (with the r value of 0.552) and it was followed by Entrepreneurial training (with the r value of 0.539) To sum up relationship between the entrepreneurship training, and start-up capital and youth employment were strong and positive relationship and the results of regression analysis observed that entrepreneurship training, mentorship, and start-up capital and youth employment has a significant positive effect on the youth employment.

Based on the finding of the study the following recommendation is forwarded;

1 The study found that comparatively those graduated from higher education institutions becomes more unemployed. Hence, the government and concerned bodies should review job market laws and regulation in order to promote educated youth to be employed in the formal sector which can help them to contribute their role for their country. Moreover, emphasis should be given when departments are opened; a detailed study is required in order to make a match between the demand and supply of education since mismatch between individuals acquired skill and knowledge with the market demand.

2 Government should have to create favorable business environment in corporation with the society and other potential organizations by constructing cluster and shade on eye catch area. The government, on the other hand, should support organizations which come up with entrepreneurship training programs and enhance production of books, trade journals and seminars to empower entrepreneurs.

3 Micro finances institution be supposed to have to minimize their interest rates, service charge and advance saving of 10%, enhanced to give continuous advice, supervision and counseling the MEs at start up, growth and maturity stage, create trust worthiness between the institution and customers and open satellite branch at cluster level.

4 Stakeholders are supposed to have to develop training programs and courses aimed at unemployed youth’s. This will ensure that the MEs owners are equipped with adequate business knowledge and experience for them to run successful businesses.

Funding: Funding: “Not applicable.” The study has not funding support from anybody. There is no external funding source for this study.

Conflict of Interest: The authors do not have any sort of conflict of interest. The author declare that they have no competing interests.

Authors’ Information

Abebe Ayalew got his BA degree in 2016 from Ambo University, Faculty of Business and Economics, Department of management. After serving for two consecutive years in Ambo university, he did MBA (masters of business administration) degree in Jimma University, College business and economics in 2019. His MBA graduation was endorsed in the senate meeting Septembers 17. 2020 and he scored the CGPA 3.84 out of 4.00 and he got a very good score on his master’s thesis. Now a time he is teaching at Ambo University, college of business and economics and doing different research and community services in the university. He had on publication on sustainability journal. The title of the article is why socially responsible, determinant factors of organizational performance the case of Dangote cement factory in Ethiopia.

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Received: 06-May-2022, Manuscript No. AEJ-22-11256; Editor assigned: 09-May-2022, PreQC No. AEJ-22-11256(PQ); Reviewed: 18- May-2022, QC No. AEJ-22-11256; Revised: 23-May-2022, Manuscript No. AEJ-22-11256(R); Published: 27-May-2022