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The article aims to describe the role of training and examines the impact on the wages of university and college graduates.

We use nationwide administrative data on university and college graduates in 2019. The population includes 1.3 million observations, of which 222,000 (∼16%) received training after graduation from an educational institution (from July 2019 to 2022). We used OLS and the “difference-in-differences” methods to estimate the returns to training. Estimates obtained using the DID method turned out to be several times smaller because they consider unobserved characteristics (abilities).

We obtained several key findings. First, the participation of graduates in training is high, despite their recent education. Second, undergoing training is conditional on the existence of wage returns. The results show a wage premium of 17.8% (OLS method) and 2.0% (DID method). Third, graduates from nonselective universities (with low state exam score) try to participate more actively in training to acquire missing knowledge and skills. The wage premium for graduates from nonselective universities is 19.1% (OLS method) and 5.1% (DID method). Fourth, there is a high return to training for graduates from socially relevant fields (education and healthcare), where training is regular and mandatory.

This paper is one of the first to estimate the involvement and returns to training for graduates using nationwide administrative data in Russia.

This paper aims to determine the influence of various enterprise characteristics on on-the-job training. The paper focuses mainly on identifying the influence of a firm’s innovative activity, technological capacity for manufacturing and product market competition on its likelihood of having a training program and on training intensity.

The authors administered a firm-level survey to a sample of 2,000 Russian enterprises. This survey includes questions about on-the-job training and key information about the companies’ activities. Probit and ordered probit estimates are used in the statistical analyses.

The results indicate that an enterprise’s provision of training is determined largely by firm-specific factors, such as its innovative activity, technical and technological state of manufacturing and product market competition. The authors adopt two widely used measures of training: incidence and intensity. Innovative activity and the technical and technological state of manufacturing are decisive factors in explaining a firm’s provision of training, as they have a strictly positive effect on both the incidence and the intensity of training. Product market competition has a positive effect on the incidence of training and a negative effect on the intensity of training.

This paper is original because it assumes that the process of deciding whether to implement a training program at an enterprise and the corresponding proportion of employees involved in training is built on the presupposition that the training intensity decision is made in two stages. This paper is the first to present estimates of on-the-job training intensity based on data from Russian enterprises.

The paradigm of school-to-work transition is changing, with an increasing number of students combining work and study. Furthermore, there exists some mixed evidence for the impact of student employment on future earnings and employment likelihood. The purpose of the present paper is to examine additional evidence that would shed light on the pros and cons of student work as a function of its type (i.e. whether or not it matches the student's field of study). We also discuss practical implications for specialists who facilitate the transition of graduates to the job market.

This is a quantitative study based on the National Statistical Survey of Graduate Employment (SGE) conducted by the Russian Federal State Statistic Service (Rosstat) in 2016. Statistical methods of data analysis were used (logistic regression, Mincer equations). The analysis is based on two dependent variables as follows: data on graduates' employment and their monthly earnings.

We show that student work is a predictor of higher employment chances for both university and vocational college graduates. Moreover, the highest employment chances are associated with student work that is well-matched to the field of study. As for earnings, the greatest returns are again associated with work related to education. Jobs unrelated to education significantly correlate with earnings only for university graduates.

An important limitation of the present research is that it estimates the effects of student employment over a rather short-term period by using data on employment just after graduation and only starting salaries. These findings evoke the need for further study of graduate competencies and the process of their acquisition.

Our findings suggest some directions for education development. The results can be used to analyze governmental and other stakeholders' initiatives in the field of vocational and higher education.

The research results can be used by a wide range of stakeholders interested in the employment of graduates as a source of data for designing measures for improving graduates' employability.

Our study obtained data on the impact of student work on later employment. Tertiary graduates get returns from all work experience, while VET graduates earn more only if their student employment was consistent with their field of study.