Publication: Tanzania Jobs Diagnostic
Tanzania has just entered a phase of growing dependency rates that will put pressure on job creation so that the larger number of dependents do not fall into poverty. However, the new millions of jobs that will be needed in the next decade is only part of the challenge. It is important to create better jobs. An economy that produces plenty of good jobs is the most direct way to continue the trajectory toward lower poverty rates. Challenges to creating more and better jobs for the poor and vulnerable groups stem from both labor demand and supply issues. On the demand side, large firms in a few sectors dominate. Possibly because of that dominance, micro and small firms find it difficult to grow and provide new jobs. Firms’ relatively restricted market access may also be a crucial factor in explaining comparative low productivity and employment. Trade expansion and a well-connected economy would address issues of comparative low-productivity and employment. On the supply side, urban areas have high unemployment. In rural areas, underemployment is on the rise. The fall in unemployment rates may be largely explained by discouraged workers withdrawing from the labor force. Where there is willingness to work—like with women and young workers—disparities in the access to quality employment is an obstacle. Finally, the rise in educational attainment was insufficient to address labor market challenges likely due to the fall in the quality of education. The objective of the Jobs Diagnostic (JD) is to identify the main challenges to job creation and to improve the quality and inclusiveness of employment. The JD is a data-driven exercise that looks at macroeconomic and demographic factors, as well as labor supply and demand to pinpoint the main constraints for a jobs-rich growth path. The fact that JDs are data-driven allows for international comparisons based on standardized datasets.The JD covers three main areas: macro and demographic trends, labor supply, and labor demand. The first section looks at the relationships between employment growth, labor productivity, and economic growth to set the macro context to later examine labor supply and demand. The second section cover labor supply. It aims to identify trends in labor supply to understand the population’s needs for employment, the unemployment challenges, underemployment, and waged and informal employment. These trends include working-age population (WAP), labor force, and inactivity. Once identified, international comparisons are based on a global harmonized household database (International Income Distribution Dataset— ‘I2D2’). The labor supply section in JDs employs a set of harmonized variables that are comparable across countries and time. The third section covers labor demand. It aims to identify the links between sectoral productivity, size, age, and other characteristics to assess the constraints for employment growth, productivity, and wages. Firm-level datasets such as Enterprise Surveys, (which allow for some international benchmarking), or censuses of enterprises are used to do this. The demand for labor is derived from the production of goods and services by entrepreneurs to meet the demand for products in an economy. The analysis also highlights who gets the jobs created in the economy and what variables determine earnings and employment. A JD analyzes a country’s economic transformations in relation to other experiences. There are three important aspects of such transformation: Structural transformation (the movement of labor across sectors); Spatial transformation (or “urbanization”; the movement of labor across places); and Organizational transformation (or “formalization”; the movement from informality to formal work, and from self to waged employment). A JD also identifies the characteristics of individuals that can access jobs in the economy, and those who are left behind.
“Petracco, Carly; Sanchez-Reaza, Javier. 2018. Tanzania Jobs Diagnostic. Jobs Series;No. 16. © World Bank, Washington, DC. http://hdl.handle.net/10986/31384 License: CC BY 3.0 IGO.”