Construction of the “Specialization – Employment Sector” Correspondence Matrix Based on Microdata

The purpose of the study. To develop a reproducible methodology for constructing a correspondence matrix between broad groups of higher education specializations and employment sectors for use in forecasting labor demand in the Russian economy. The tool is designed to fill a methodological gap in analyzing structural imbalances between the education system and the labor market by providing a quantitative assessment of graduate distribution across industries based on their field of study.

Materials and methods. The study is based on microdata from the Russian Longitudinal Monitoring Survey – Higher School of Economics (2004 – 2024), comprising 52,916 observations of respondents with higher education. A procedure is proposed for consolidating diploma occupations (ISCO-2008 classifier) into ten broad specialization groups according to the Russian nomenclature and aggregating thirty original industry categories into sixteen meaningful groups. A matrix of graduate distribution across sectors is constructed, concentration indexes (Herfindahl index) and profile employment have been calculated. The methodology is tested using cohort analysis across five periods for obtaining a diploma (2000–2004, 2005–2009, 2010–2014, 2015–2019, 2020–2024).

Results. A reproducible correspondence matrix “specialization – employment sector” is formed, enabling the transformation of graduate supply forecasts by field of study into estimates of the sectoral structure of new highly educated personnel. Persistent linkages are identified: medical graduates predominantly work in healthcare (72% on average), engineering graduates - in industry (31%), and teaching staff – in the education sector (60%). Contrasting trends are observed: increasing concentration of engineers in industry (from 28% to 44%), a restoration of the profile employment of IT specialists (from 6% to 25%), declining share of medical professionals in healthcare (from 68% to 60%), and high volatility in teacher employment. For broad-field specializations (social sciences, humanities), reduced diversification and the formation of employment clusters in trade, public administration, and education are documented. Herfindahl index values range from 0.12 (mathematical sciences) to 0.53 (healthcare), confirming varying degrees of sectoral attachment across specializations.

Conclusion. The proposed tool can be integrated into labor demand forecasting systems, including for adjusting university admission targets and developing career guidance programs. The matrix serves as a bridge between graduate supply forecasts and estimates of their sectoral distribution. Alongside persistent traditional links between training and employment, graduate career paths are increasingly diversifying, calling for a reassessment of curriculum planning and mechanisms linking education to the labor market. Study limitations include potential subjectivity in mapping ISCO-2008 codes to Russian specialization groups and the confounding of cohort, age, and period effects. Future research may focus on analyzing the impact of artificial intelligence development and deployment on labor trajectories.

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