threshold significantly divergent from one's initial conditions, aspirations cease to exhibit a meaningful correlation with enhanced outcomes. This phenomenon may be attributed to the onset of frustration or other complex factors at play (Janzen, et al., 2017; Ross, 2019; Bloem, 2021).

# **3. Methods**

# **3.1. Data and Survey Instruments**

Recent surveys targeting youth have incorporated questions aimed at understanding their career aspirations and life goals amid the backdrop of the COVID-19 crisis. The ‘Youth Aspirations and Employment Module’ was designed based on household surveys<sup>2</sup> and implemented in World Bank's Living Standards Measurement Study (LSMS) High Frequency Phone Surveys (HFPS) in Ethiopia, Malawi and Nigeria<sup>3</sup> to collect information about (i) education history, including the level of education already achieved (note that in multi-topic household surveys, some of this information is partially captured within the Education Module), (ii) work history, such as the age at which respondents began working, their previous work experiences, and sources of income, (iii) future plans, which encompass intended activities following the completion of education or training programs, and (iv) career aspirations, covering desired occupations, role models, adherence to social norms, and interest in migration.

Understanding youth aspirations can be complicated due to measurement issues. Firstly, all empirical measures of aspirations rely on self-reported survey questions. Secondly, the measures of aspirations may vary in the underlying concepts they capture. While most authors agree on aspirations being multidimensional, the specific survey questions used to capture them differ in formulation, potentially yielding diverse results and policy implications. A key distinction among survey questions is whether respondents are asked about their aspirations without any constraints or limitations (Roy, et al., 2018; Ross, 2019; Favara, M., 2017).

This analysis examines three key dimensions (i) educational aspirations, which were assessed using the question ‘ _Imagine you had no constraints and could study for as long as you liked or go back to school if you have already left. What level of formal education would you like to complete?’_ ; (ii) occupational aspirations, determined through the question ‘ _When you are about 30 years old, what job or "dream" job would you like to be doing?’_ ; and (iii) migration aspirations, gauged by asking _‘Would you consider leaving your community to look for better job opportunities?’_

> 2 The ILO SWTS questionnaire (2009), Module 2; the World Bank Young Basotho's Aspirations and Challenges Survey (2019); and Young Lives, Round 4, Ethiopia (2013-2014).

> 3 <mark>World Bank. Ethiopia - High Frequency Phone Survey 2020-2023. Ref: ETH_2020-2023_HFPS_v13_M. Dataset downloaded from h</mark> <u>ttps://microdata.worldbank.org/index.php/catalog/3716</u> <mark>on January 2, 2024; Malawi National Statistical Office (NSO) (Government of Malawi). Malawi - High-Frequency Phone Survey 2020-2024 (HFPS-COVID-19 2020-2024). Ref: MWI_2020-2024_HFPS_v18_M. Downloaded from</mark> <u><mark>https://microdata.worldbank.org/index.php/catalog/3766</mark></u> <mark>on January 2, 2024; National Bureau of Statistics. Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020-2021, Phase 1. Dataset downloaded from</mark> <u>https://microdata.worldbank.org/index.php/catalog/3712</u> <mark>on January 2, 2024.</mark>

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