Sociodemographic Determinants and Types of Employment in Tanzania: Evidence from Integrated Labour Force Survey Data

Abstract

This study scrutinises the link between sociodemographic factors and types of employment in Tanzania, leveraging data from the 2020-2021 Integrated Labour Force Survey collected by the Tanzania National Bureau of Statistics. Age, gender, education, and geographical area (rural or urban) are analysed for their influence on employment outcomes. The Integrated Labour Force Survey dataset, offering a national representative sample, forms the foundation for this research, facilitating a comprehensive investigation of employment types and sociodemographic characteristics. Two analytical techniques are employed – cross-tabulation analysis and the Chi-Square test of independence – allowing for exploring employment distribution across sociodemographic categories and the significance of the observed relationships. A key finding is the predominance of self-employment across all education levels, ages, gender and regions, with a subtle rise in wage employment correlating with higher education. Rural areas predominantly rely on self-employment, indicating their economic reliance on agriculture and small businesses. Urban areas show increased wage employment, indicating a wider array of job opportunities. Gender disparities are evident, with self-employment slightly more common among men while women engage more in unpaid work, reflecting traditional gender roles. Age-related analysis reveals a tendency for self-employment to increase, suggesting older individuals shift towards entrepreneurship, while unpaid work is more common among the younger population. Although the study design identifies associations, not causality, it offers more profound insights into the intricate relationship between sociodemographic characteristics and employment types in the Tanzanian context. This research enriches our understanding of Tanzania’s employment landscape, underlining the importance of sociodemographic determinants in shaping types of employment in the population.