BAYESIAN APPROACH TO IDENTIFY PREDICTORS OF WOMEN UNEMPLOYMENT IN URBAN ETHIOPIA

Abstract

Background: Despite promising growth, unemployment is high and is one of the socioeconomic problems in Ethiopia. Moreover, it is higher for females compared to males. The aim of this study is to identify the determinants of unemployment status of women in urban Ethiopia. Method: The data for this study was obtained from the 2011 Ethiopia Demographic and Health survey. A sample of 5,274 women in urban Ethiopia was included in the study. Descriptive statistics and Bayesian logistic regression methods were used to analyze the data. Results and Conclusion: Out of the 5,274 women considered in the analysis, 2,712 (51.42%) women were unemployed and 2,562 (48.58%) women were employed. The results of Bayesian logistic regression indicated that Age, religion, number of household, education level, literacy, mass media, wealth index, pregnancy, number of living children and marital status significantly affect the unemployment status of women in urban Ethiopia.