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Abstract
Since the 1970s, the Philippines has faced a persistent skills mismatch, producing more college graduates than the economy can absorb. This has led to lower wages, decreased job satisfaction, reduced productivity, and higher turnover rates. Addressing this issue requires a well-functioning Labor Market Information System (LMIS). This study contributes to the Technical Education and Skills Development Authority Skills Anticipation and Prioritization of Skills Requirements (SAPSR) Framework, which helps identify skills needs. The study highlights valuable existing data sources and LMIs but points out significant areas for improvement in data collection, capability building, and institutional arrangements. The paper offers recommendations for enhancing the LMIS and SAPSR through partnerships, skills taxonomy, more detailed data collection, and collaboration with other initiatives like PhilJobNet and the Philippine Skills Framework. Training to utilize emerging data sources and qualitative and quantitative methods is also emphasized to ensure long-term success.
Introduction
Skills mismatch is defined as a discrepancy between the skills available in the labor market and those sought by employers or firms. It manifests in various forms, including skills gaps, skills obsolescence, skills shortages, vertical mismatch, and horizontal mismatch (ILO 2020). Mismatch occurs due to incomplete and imperfect information (Říhova 2016). Prior research indicates that information deficits lead to mismatches between vocational specialization choices and labor market outcomes, particularly in the face of unanticipated labor market changes (Borghans et al. 1996). The authors concluded that enhanced public labor forecasts are crucial for guiding students in their career choices.
Prolonged skills mismatch adversely impacts individuals, firms, and the economy as a whole. At the individual level, overqualification is associated with wage penalties and lower job satisfaction (e.g., Sánchez-Sánchez and McGuinness 2015). At the firm level, skills mismatch can lead to decreased productivity, underinvestment in innovation, and higher employee turnover rates (ILO 2020). When aggregated, these effects result in diminished economy-wide productivity, reduced national competitiveness, and higher unemployment and underemployment rates (Říhova 2016).
While skills mismatch is an inherent issue stemming from incomplete and imperfect information (Říhova 2016), its negative effects can be mitigated through a well-functioning labor market information (LMI) system. LMI can be defined in various ways. A comprehensive definition is offered by Schmillen (2019, p.2), who explains that it "includes any quantitative or qualitative information and intelligence on...