Abstract:
This study investigates the determinants of rural-to-urban migration, focusing on individual and
household characteristics, such as age, sex, education level, marital status, and family size,
access to information, occupation, unemployment, and housing conditions. The research employs
a logistic regression model to predict the likelihood of migration and uses Spearman’s rank
correlation analysis to explore the relationships between variables. The findings indicate that
age, education level, marital status, unemployment, and housing conditions are significant
predictors of rural-to-urban migration. Specifically, younger individuals and those with higher
education levels are more likely to migrate, as they seek better job opportunities and living
conditions in urban areas. Unemployment plays a crucial role, as individuals facing job scarcity
in rural areas tend to migrate to urban centers in search of employment. Also this study
identified unemployment, age, education as critical determinants of rural –urban migration in
Holeta. Logistic regression revealed unemployed individual had 8.3x higher odds for migrating
(Or=8.3,p<0.01,while higher education reduced migration odds by 58%(OR =0.42,P<0.01).
Younger migrants (21-30 years) dominated the flow (48%), with males comprising 87% of
respondents. access of information significantly deterred migration (OR=0.096, p<0.05),
additionally, the study highlights the importance of access to information and family size in
shaping migration decisions. The lack of access to information in rural areas is a major barrier
to migration, while smaller family sizes tend to encourage migration, as individuals face fewer
familial obligations. The results provides valuable insights for policymakers seeking to
understand migration patterns and formulate strategies to address urbanization challenges,
especially in terms of employment, housing, and education.
