Using Open Data Online Vacancies in Comparison with Official Statistics to Monitor and Forecast Labor Market Dynamics

Digitalization of labor processes and the growing popularity of online platforms open up new opportunities for monitoring and forecasting labor market dynamics. However, the issues related to the representativeness of online vacancies data, their timeliness and completeness remain unresolved. The scientific interest of the study lies in the development of approaches to the integration of data from online sources with official statistics, which will improve the accuracy of forecasting and promptness of labor market assessment. In traditional labor market analysis, vacancies are used to measure labor market tensions and can signal the presence of imbalances in the labor market, when supply and demand do not match each other (in terms of qualitative characteristics, geographically, etc.). The purpose of the article is to compare the data of online vacancies and official statistics to develop approaches to monitoring and forecasting labor market dynamics. The article gives an example of implementation of labor market monitoring based on big data and comparison of online vacancies data with the sources of official statistics. The main sources of data for comparison were Rosstat and hh.ru (open vacancy data). The author's methodology of aggregation of vacancy data into groups of professional spheres and professions based on official classifiers, as well as methods of calculation and estimation of salary levels were used in the comparison. As a result of the study, it was revealed that the obtained and aggregated data of the online job search portal hh.ru reliably correlates with the official quarterly and monthly statistics on the dynamics of the number of open vacancies and salaries. Finally, we discuss methods of forecasting labor market dynamics using machine learning methods based on open big data. According to the authors, the possibility of correlating the dynamics of the indicators of online portals with official statistics of enterprises could complement the methodology of labor market monitoring and increase the reliability of forecasts.