Abstract

In article we propose a method for the analysis of long time series data of the Monitoring of Labor Protests. This database has been accumulating data on labor protests in Russia since 2008. During 156 months data were collected on 3,951 protests by Russian workers. The article describes the need to control labor protests, the features of the current legal regulation of labor conflicts. The peculiarity of the Russian situation is that the state bodies register only “legal” strikes, ignoring the numerous protest actions of workers undertaken in other forms. Therefore, it is necessary to study their dynamics in order to identify trends that are not visible using conventional analysis. The main difficulty in identifying trends is the high variability of the source data. The article proposes a method for smoothing data and the rate of change of the smoothed function at each point, which makes it possible to find criteria for determining periods of growth and decline in the protest indicator. This makes it possible to calculate periods, their duration, intensity, average rate of growth or decline. In addition to analyzing the overall dynamics, the proposed method allows to study subsamples, for example, of different sectors, and compare them obtaining comparable estimates. The article compares three sectors – industry, transport and healthcare – that accounted for 75% of all protest actions of workers in 2020.

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