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Russian human capital and its components: labour market implications

Priority areas of development: economics, sociology, management

Present report initiates the project dedicated to the studies of Russian human capital that will be conducted by the Centre for Labour Market Studies of NRU HSE in 2019-2021. Set of studies comprising present report were carried out in 2019 and cover different aspects of such productive elements of Russian human capital as non-cognitive skills and social traits as well as their effect on various labour market indicators.

The report presents the results of the studies of various aspects of non-cognitive skills in Russia, such as the distribution of non-cognitive skills in various groups of the Russian population, wage differences between categories of workers with respect to their tenure, the impact of non-cognitive skills on public-private wage gap, dynamics of interregional differences in wages and its causes, as well as the use of specific non-cognitive skills in the workplace and their impact on wages and other labour market indicators in the OECD countries.

Goal of researchis the comprehensive study of non-standard components of human capital in Russia and their effects on the labour market.

Methodology of the surveyscombined both descriptive procedures - comparison of the mean values, distributions and ratios, the estimation of correlation and transition matrices - as well as the use of more sophisticated techniques based on the estimation of various types of the Mincer wage equation, multinomial logit regressions, decomposition of time and cohort effects in wage distribution, Oaxaca-Blinder decomposition of the public-private wage gap, decomposition of the Theil inequality index in various categories of the population and extreme bound analysis.

Empirical base of the research is largely provided by the Russia Longitudinal Monitoring Survey – Higher School of Economics (RLMS-HSE) covering the period of 2000-2018. Microdata of the Survey of Occupational Wages for 2005-2015 by Federal State Statistics Service (Rosstat) were also used together with the data on the aggregated regional statistics prepared by Rosstat. Cross-country analysis of age-wage profiles was carried out on the basis of the micro data from the labour force survey of the Statistical Committee of the Republic of Armenia, the Life in Kyrgyzstan Survey, panel data from The Ukrainian Longitudinal Monitoring Survey, as well as the micro-data from the European Union Statistics on Income and Living Conditions (SILK) by Eurostat. Comparison of indicators of the use of non-cognitive skills in OECD countries was carried out on the basis of the World Bank Skill towards Employment and Productivity (STEP) survey and the OECD International Assessment of Adult Competencies (PIAAC) data.

Results of research demonstrate that the overall level of non-cognitive skills, analyzed using a variety of indicators (Big Five classification, locus of control, time and risk preferences) is very low. The analysis is consistent with the main findings of foreign studies which attributed high average values of the majority of non-cognitive skills to higher educated, managers and representatives of skilled occupations, residents of large cities, those with good health. Higher level of non-cognitive skills appears to characterize Russian informal employment as well. Self-employed, informal employees, as well as, in some cases, irregular workers, demonstrate higher average values of risk-loving, prefer future gains rather than present consumption and have an internal locus of control.

Level of implementation,  recommendations on implementation or outcomes of the implementation of the results

Results included in this report can be used in the development of policies on economic and education. They also have a number of implications for the evolution of the theory and methodology of the human capital analysis. They provide new empirical results on the state of Russian employment, contributing to the understanding of its current dynamics. The results obtained can be also used in the labour economics, economics of education and social policy courses.


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