Neoliberalism, marginalization and the uncertainties of being young: The case of Egypt

Abstract

This study highlights the general context of neoliberalism in the Middle East and North Africa (MENA), and its influence on young people’s life chances. It is mainly concerned with understanding the extent to which socio-economic variables, like education and family income levels, impact youth marginalization. Through analysing the case of Egypt, this study argues that education is indeed a predictor for developing a young person’s life chances. However, a family’s income level is even more important. If a family’s income level is low, then the opportunity for continuing education is also low. If a young person is able to attain university level education, their chances of obtaining employment opportunities is tied to their family’s income levels and networks rather than to their education level per se. A family’s income levels on the other hand are influenced by the structure of neoliberalism in general, and neoliberalism amalgamated with authoritarianism, corruption and crony capitalism in particular.

Keywords:

• Neoliberalism
• authoritarianism
• inequality
• Middle East and North Africa
• youth
• Egypt

Disclosure statement

No potential conflict of interest was reported by the author.

Acknowledgements

I would like to thank Daniela Pioppi and Cristina Paciello for coordinating the Power2Youth project. I would also like to thank Alia Alaa El Din for helping out with the regression models. The qualitative fieldwork would not have been conducted without Hatem Zayed, Batoul al Mehdar, Rana Gaber and Alia Alaa El Din. I would also like to thank Åge A. Tiltnes and Jon Pedersen for carefully reviewing a previous version of this article and providing me with most helpful comments. I would like to thank the four blind peer reviewers for helpful comments on the earlier version of the paper. Kathryn Cabral Vallis helped with the editing process.

Notes

1. For more information on this programme see: http://plp.eg/ar/%D8%A7%D9%84%D8%A8%D8%B1%D9%86%D8%A7%D9%85%D8%AC-%D8%A7%D9%84%D8%B1%D8%A6%D8%A7%D8%B3%D9%8A-%D9%84%D8%AA%D8%A3%D9%87%D9%8A%D9%84-%D8%A7%D9%84%D8%B4%D8%A8%D8%A7%D8%A8-%D9%84%D9%84%D9%82%D9%8A%D8%A7/

2. The numbers here are based on the IDSC report, nevertheless, the analysis is mine, since the report has read these numbers in a different manner, and from a pro-government perspective.

3. ’Uneducated’ does not only refer to young people who have not entered the education system, but it also refers to those who have dropped out before completing their primary school.

4. In the questionnaire this question encompassed 5 values for income levels: high, above average, average, below average, low. For the purposes of this model I this nominal variable into a dichotomous variable, whereby all youth who reported to have below average and low household income levels were given the value 1. In the remainder of the paper, income levels refer to young people’s economic self-classification of their household income levels.

5. The initial question in the questionnaire asked young people about the main reason for not working during the past month. Here, 42 per cent said they were students; 36 per cent said they were housewives or conducting domestic work, 15 per cent said they did not find a job, 2 per cent did not want to work, 1 per cent did not work for medical reasons and 4 per cent did not work due to social restrictions. I turned the 15 per cent who did not find a job into a dichotomous variable – unemployed vs. the rest who answered that they have not been working in the past 12 months.

6. I did the same with the variable entitled ‘housewife’. Here, I turned the 36 per cent who answered that they did not work in the past 12 months, due to domestic work or being housewives into another dichotomous variable – housewife vs. the rest who answered that they have not been working in the past 12 months.

7. See for instance Tables 1 and 2.