CEEG Seminar Series: Determinants of gender differences in employment among youth in the cities of Beira and Maputo

IGM Seminar Series

CEEG Seminar Series: Determinants of gender differences in employment among youth in the cities of Beira and Maputo

Wed, 9 March 2022

On Wednesday 9 March 2022, Paul Jasper, researcher at Oxford Policy Management (OPM), and Ivan Manhique, Independent consultant, will present a recent study in progress entitled 'Determinants of gender differences in employment among youth in the cities of Beira and Maputo'.

The seminar is part of the CEEG Seminar Series, organized under the Inclusive growth in Mozambique (IGM) programme. The seminars offer a forum to share and discuss ongoing research on topics related to the work of the IGM programme and to foster a culture of research at the faculty and at UEM in general. The sessions are open for all and are held in Portuguese.

The seminars take place at the Faculty of Economics of the University of Eduardo Mondlane (UEM). It is a public event open to everyone. The presentation will be given in Portuguese.

About the study

Employment rates among young Mozambicans show a great difference between men and women. This study investigates the determinants of this difference using panel data from a survey among young people in the cities of Beira and Maputo. The study uses two methodologies. First, based on a literature review, the authors define a list of 'theoretical' variables as possible determinants and apply the Oaxaca-Blinder decomposition of the gender gap. Second, they apply a Machine Learning Methodology using all the information from the survey to estimate which are the most statistically important variables in determining employment among young people.

Theoretical results indicate that women do much more housework, which explains a large part of the difference in employment. On the other hand, fertility or social norms do not have predictive power. These results imply that programs that promote a more balanced division of roles in terms of domestic tasks can help young people to seek income opportunities outside the home.

Preliminary results from the Machine Learning Methodology confirm that gender is one of the most important variables to determine the state of young people's economic activity. The results of the difference between men and women are still ambiguous, not showing a clear sign of influences of some very strong variables.

The presentation will end with a description of the next steps in the study.