the same reason, we excluded youths who had already completed a university degree or above from the regressions. This included 75 observations from the pooled sample, as well as 50, 7, and 18 observations from Ethiopia, Malawi, and Nigeria, respectively. These exclusions were made to address the issue of perfect collinearity, as these individuals all shared the common aspiration of furthering their education beyond the current level, making them collinear with the dependent variable. We also controlled for the following variables: Age, Started working 23-25 years, Secondary education, Working in agriculture, Own account worker, Consumption Quintiles, Urban area. Results for these variables were either not statistically significant or not discussed in the analysis. Full results are available under request.

**Table 2. Youths’ aspiration to work in STEM-related jobs, marginal effects from logit regressions.**

|**Main variables**|**Pooled sample**|**Ethiopia**|**Malawi**|**Nigeria**|
|---|---|---|---|---|
|**Characteristics of theyouths**|||||
|Youth is female|-0.054**|-0.071*|-0.06**|-0.074|
||(0.028)|(0.038)|(0.03)|(0.046)|
|19-22 years|-0.109***|-0.113**|-0.089**|-0.117***|
||(0.03)|(0.055)|(0.036)|(0.044)|
|23-25 years|-0.147***|-0.166***|-0.044|-0.167***|
||(0.033)|(0.059)|(0.054)|(0.046)|
|Educational gap|0.116***|0.118***|0.066*|0.102*|
||(0.031)|(0.041)|(0.04)|(0.052)|
|Started working 15-18 years|-0.046|-0.302***|-0.079*|0.048|
||(0.038)|(0.111)|(0.047)|(0.055)|
|Started working 19-22 years|-0.146**|-0.086|-0.181**|-0.162|
||(0.069)|(0.103)|(0.074)|(0.115)|
|Youth likelihood to reach the dream job (self-efficacy)|-0.05*|-0.091*|-0.097***|-0.032|
||(0.03)|(0.051)|(0.03)|(0.061)|
|Job that family and friends regard highly|0.120***|0.221***|0.03|0.055|
||(0.033)|(0.05)|(0.047)|(0.051)|
|**Characteristics of the household**|||||
|Quintile 2|0.084*|0.037|-0.037|0.112*|
||(0.044)|(0.076)|(0.056)|(0.065)|
|Observations|2,688|881|873|934|

Note. Results are presented in margins and clustered standard errors in parentheses. Individual-level survey weights used. Statistical significance at: *** p<0.01, ** p<0.05, * p<0.1. Enumeration areas fixed effect included. The Educational gap is measured as the difference between aspiration to complete university or higher degree and the current education of the youth at the time of the interview. We also controlled for the following variables: Started working <14 years, Started working 23-25 years, Interesting job to do, Working in STEM related jobs, Size of the HH, and Urban area, Consumption Quintiles 3, 4 and 5. Results for these variables were either not statistically significant or not discussed in the analysis. Full results are available under request.

**Regarding aspirations to migrate, we find that female youths generally have lower aspirations to migrate compared to their male counterparts.** Specifically, female youths are 11.6% less likely to express a desire to migrate than their male peers. This pattern is in line with the literature (i.e., Migali and Scipioni, 2019) and consistent across all the countries examined, although there are some variations. For example, in Nigeria, the gender difference is more pronounced, with female youths being 16.8% less likely to aspire to emigrate to another country ( **Table 5** ).

**Additionally, our analysis reveals that aspirations to migrate tend to decline with age.** In Malawi, youths aged 23-25 years are 10.8% less likely to express a desire to migrate compared to the youngest age group, which includes those aged 15-18 years ( **Table 4** ). When considering

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