ANALYSIS AND MATHEMATICAL MODELING OF DISTRIBUTION OF ENGINEERING AND TECHNICAL SPECIALTIES GRADUATES OF PENZA STATE UNIVERSITY

Background. The growing demand for skilled personnel to implement technological innovations and develop infrastructure underscores the relevance of analyzing and numerically modeling the distribution of graduates in engineering and technical specialties (ETS). Therefore, it is essential to conduct regular monitoring of the demand and supply of ETS in the labor market to respond adequately to changes and ensure the availability of necessary personnel for the successful development of businesses. This helps identify shortages or surpluses of specialists in specific fields, optimizes educational programs, and ensures that graduates' training meets labor market requirements. In the context of digitalization and the transition to sustainable development, it is crucial to effectively utilize resources to cultivate the engineering potential of the country. The aim of this study is to develop appropriate mathematical models for simulating the distribution of graduates from the Penza State University (PSU) engineering programs. Materials and methods. Statistical analysis methods, econometric modeling, and economic-mathematical modeling are employed. Results. In the context of rapid changes in the labor market and the growing need for highly qualified personnel, the distribution of graduates of engineering and technical specialties is of particular importance. Based on foreign and domestic models of the labor market, three mathematical models have been developed to analyze the distribution of graduates of engineering and technical specialties at PSU. These models serve as a tool for forecasting the number of bachelors, specialists and masters who will look for work after graduation. Using the constructed mathematical models and the results of previous related studies, an average forecast for the distribution of PSU ITS graduates in the transition period "study-work" until 2028 has been formed. Conclusions. The results obtained not only allow for forecasting the distribution of graduates but also assess the potential imbalance between demand and supply of specialists in this field. These data highlight the necessity of enhancing the prestige of technical specialties and the relevance of engineering education. The successful development of research activities and industry, as well as the high-tech service sector, becomes critically important for the reindustrialization of Russia's economy.