Social factors in the management of youth participation in the labor market in Asia: Justification of causal dependencies

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The study aims to determine social factors in the management of youth participation in the labor market in Asia based on causal analysis. The information base involves youth employment and youth working-age population by education levels, rural/urban areas, marital and disability status, time arrangement, and job contract. The sample covers 14 countries the ILO assigned to the Asia group for 2012–2021. Correlation analysis identifies dependencies between social factors and youth employment and determines their nature and strength, considering time lags when this influence becomes maximally significant. Granger causality analysis contributes to the establishment of causal dependencies within identified relationships. The greatest causal effect on youth employment is identified for educational level (basic educational level is a cause of positive changes in youth employment level in four countries, and youth employment level is a cause of growth of basic educational level in eight countries, including three countries with bidirectional causality, mostly with strong/very strong strength without lag). Quantitative indicator of youth working-age population by gender influences youth employment in Azerbaijan, Israel, the Philippines, and Thailand (from moderate to strong strength with lag from 0 to 2 years), by marital status – in Cyprus, Georgia, Korea, and Thailand (mostly very strong, time lag – from 0 to 2 years), by social factor of disability – in Shri-Lanka and Mongolia (very strong with 1-year time lag). The results can be used to form directions for managing youth participation in the labor market to improve social, educational, and youth policy.

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    • Table 1. Assessment of dependency between youth employment and youth working-age population differed by four aggregate education levels, gender, and area
    • Table 2. Assessment of dependency between youth employment and youth working-age population differed by disability, marital status, working time arrangement, and job contract
    • Table 3. The estimation of Granger causality in the case of the first sample’s country (Azerbaijan)
    • Table 4. The cross-country generalized results of the Granger causality test
    • Conceptualization
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