Munich Personal RePEc Archive

Digital Skills: Classification, Empirical Estimates of the Demand

Kapelyuk, Sergey and Karelin, Iliya (2023): Digital Skills: Classification, Empirical Estimates of the Demand.

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We provide a review of the various approaches used in the literature to classify digital skills. Utilizing this classification, we conduct an empirical analysis to estimate the demand for digital skills and the wage premium for digital skills in the Russian labor market. Our study uses an extensive dataset of 8 million vacancies posted on the Unified Digital Platform "Work in Russia" from 2018 to 2022. The uniqueness of this dataset lies in the specification of wage data in over 99 percent of the vacancies. The demand for digital skills is determined through the automated processing of employer requirements outlined in job postings. We explore the advantages and limitations of different indicators of digital skills demand and suggest the ratio of vacancies requiring digital skills to the labor force as the most appropriate measure. The findings reveal substantial regional differentiation in the employer’s demand for all groups of digital skills in Russia. Regions with a higher level of economic development tend to have increased requirements for digital skills. Digital skills are more frequently required in regions characterized by higher economic development and those with a focus on natural resources. Of the federal districts, the North Caucasian Federal District stands out with a substantially lower demand for digital skills. A positive wage premium is associated only with advanced and professional digital skills.

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