Statistical Modeling of Women Employment Status at Harari Region Urban Districts: Bayesian Approach

Abstract

Women have always faced a number of disadvantageous gaps in the labour market; the status of women at the labour markets throughout the world has not substantially narrowed gender gaps in the workplace. Many women in developing countries are domestic workers or informal factory workers, while others are unpaid workers in family enterprises and family farms. Agriculture is the primary sector of women's employment; Sub-Saharan Africa is among regions with the highest proportion of women employment in the agriculture sector. This research was conducted on 274 sampled households with the objective to determine the factors associated with women's employment status and to examine whether the estimated parameters for logistic regression model adopting Bayesian and maximum likelihood estimation approaches are similar or not. The research revealed that about 144 (52.6%) of sampled women were unemployed that is, they were not involved in any activity for earning during the data collection. The inferential analysis using both Bayesian and Maximum likelihood estimation schemes indicated that, pregnancy, age, education level, husband/partner occupation, marital status, family size, training opportunity and a child less than 5 years old had statistically significant (p < 0.05) effect on employment status of women. The maximum likelihood estimates and Bayesian estimates with non-informative prior do not have considerable difference.

Geographical variation and determinants of women unemployment status in Ethiopia; A multilevel and spatial analysis from 2016 Ethiopia Demographic and Health Survey data

“…Unemployment was lower among pregnant women than among non-pregnant women. This finding is consistent with earlier research [ 1 , 19 , 33 ], which found that pregnant women were less likely than non-pregnant women to work in a given year.…”

“…Unemployment was higher among women under the age of 25 than among older women. This finding is consistent with a study done in Urban Districts, Harari Region, Ethiopia [ 1 ], Halaba town, SNNPR, Southern Ethiopia [ 34 ], Ethiopia [ 19 ] and Sahiwal District, Pakistan [ 2 ] which found that women in the youngest age group studied are most influenced by unemployment.…”

“…Women who lived alone were more likely than widowed or divorced women to be unemployed. A study in Ethiopia’s Harari Region [ 1 ], Ethiopia [ 19 , 32 ], and Pakistan’s Sahiwal District [ 2 ] supports this conclusion. Female-headed families had a lower unemployment rate than male-headed households.…”

“…Globally, the rate of unemployment is higher among women than it is among men. The quality of employment is also disparate among men and women [ 1 – 3 ].Women, for instance, account to 38.8 percent of all labor force participants. However, women rather than spend more time on unpaid work such as childcare and housework.…”

“…Prior studies investigated the determinants of women’s unemployment in small urban areas [ 1 , 10 , 18 ], though only on individual-level factors [ 1 , 10 , 18 ]. At the community-level, unemployment among women is affected by factors, such as residence, media exposure, region and cluster (enumeration area) [ 19 , 20 ].…”