Entrepreneurship is a worldwide phenomenon with economic growth across the globe that is rendered by the emergence of new and innovative business start-ups. Thus, the main objective of this research was to model the impact of entrepreneurial attitudes on self-employment intention among final year engineering students in Bahir Dar Institute of Technology, Debre Markos University and University of Gondar, Ethiopia, in 2017. To achieve the objective of the study, a survey research approach was employed. Questionnaire and interview were the instruments used, and stratified sampling technique was adopted to select 921 respondents from a population of 4327 final year undergraduate engineering students in 2016/2017 academic session. To analyze the data, descriptive statistics, chi-square test, principal component factor analysis, and binary logistic regression analysis were employed. The descriptive result revealed that about 57.4% of the students had an intention to be self-employed while 42.6% do not have an intention. The principal component factor analysis was used to reduce the set of variables by grouping variables with similar characteristics together and generates new variables (factors). These methods help the researchers to transform the number of correlated variables into a smaller number of uncorrelated variables. The logistic regression analysis was performed to investigate the effect of the predictor variables on self-employment intention status of students. The results showed that entrepreneurial education/training and entrepreneurial attitudes significantly predicts students' selfemployment intention. Accordingly, information and opportunity seeking, creativity and problem solving skills, achievement and instrumental readiness, self-confidence and self-esteem, goal setting, entrepreneurship education/training, business-owned family background, prior business experience with family, access to finance/capitals for startup, and networking and professional contacts were found to be significant predictors at 5% level of significance. These factors had positive relationship with self-employment intention at 5% level of significance. In the meanwhile, demographic factors (such as age, gender, and marital status) and socio-economic factors (such as parents' occupation, colleagues' business background, means of finance, discouragement by external environment, and clear future business idea) are not significant predictors at 5% level of significance. The study recommends that the government as well as the universities should design programs that facilitate entrepreneurship to change the mindset, attitude, and intention of those students who do not have knowhow about entrepreneurship as a future career.

In recent years, entrepreneurship has become an important issue due to national economic development and the contribution of society. Data with a hierarchical structure received more attention and occur frequently in social science, public health and epidemiological researches. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. Traditional logistic regression is inappropriate when data are hierarchically structured. Therefore, this study presents multi-level Bayesian logistic analysis for entrepreneurial intention of students using classical and Bayesian approach. The descriptive result revealed that about 57.4% of the students had an entrepreneurial intention while 42.6% do not have an intention. The results also showed that entrepreneurial education/training and entrepreneurial attitudes significantly predicts students' entrepreneurial intention at 5% level of significance. The model results indicate that the effects of the selected variable on entrepreneurial intention vary across university. By failing to take into account the clustering within university (level 2), Bayesian multilevel effects are not taken into consideration in modeling, the β coefficients in multilevel logistic model using classical approach are distorted somewhat in both directions either in over or under direction. This study also evaluates and compares the behavior of maximum likelihood and Bayesian estimators to investigate the relationship between covariates and the response. Both point and interval estimation performances were investigated. The results revealed that lower standard errors of the estimated coefficients in the Bayesian logistic regression approach as compared to classical approach. Moreover, the results revealed that the length of the Bayesian credible interval is smaller than the length of the maximum likelihood confidence interval for all factors. In order to identify the most plausible method between Bayesian method and maximum likelihood estimation of the data, AIC, BIC and DIC are adopted in this paper. The result of the study depicts that the Bayesian method performs better and more efficient than maximum likelihood estimation. The study recommends that the government as well as the universities should design programs that facilitate entrepreneurship to change the mindset, attitude, and intention of those students who do not have knowhow about entrepreneurship as a future career.

Recently, entrepreneurship has been given serious devotion due to its importance on economic growth, job creation, sources of innovation and productivity. So, this paper aims to identify the determinants of entrepreneurial intention of engineering graduating students in Ethiopia. Stratified sampling technique was employed and data were collected via questionnaire from 921 students from the target population. The study utilized regression statistics to analyze the data. The data used for this study is hierarchally structured and hence multilevel binary logistic model was used to identify the relationship between predictor and outcome variables by taking into account both level-1 (students' characteristics) and level-2 (universities characteristics) in regression relationships. The model result founds that personal attitude, perceived educational and relational support are the significant predictors of entrepreneurial intention of students at 5% level. The policymakers should facilitate entrepreneurship trainings to change attitude of students and strength the cooperation between students and fund raisers.