Forbes reviewed the findings of a study by Margarita Kropocheva, Researcher at the Gaidar Institute's Mathematical Modeling of Economic Processes Department. The article “The relationship between industrial robots, labor shortages, and labor productivity in Russian regions” has been accepted for review by a scientific journal.
The study is based on an analysis of Rosstat statistics from 2023 on the number of industrial robots by Russian region. The leaders in terms of robot density are the Kaluga, Samara, Leningrad, and Tula regions, with 60, 41, 40, and 28 industrial robots per 10,000 workers, respectively, which is explained by the concentration of large machine-building enterprises. At the same time, the outsiders are the Republic of Komi, Crimea, and the Stavropol Territory, where specialization in mining, tourism, and agriculture is not very susceptible to robotization. The author noted that the complete picture for the country is limited, as data on some enterprises is confidential.
In her work, the expert assessed how achieving the target of 123,000 industrial robots by 2030 (required for the national project “Means of Production and Automation”) will affect the labor market. According to calculations, in this case, average labor productivity in manufacturing will increase by 25.1%, and average wages for skilled workers will grow by 11.5%, all other things being equal.
The estimates obtained regarding the relationship between robotization and wages should be interpreted with caution, Margarita Kropocheva noted. First, the analysis is based on a still limited data set. Second, the identified relationship may be two-sided: “the estimate of robot density may be biased if robot installation and worker wages influence each other.” On the one hand, the introduction of robots can stimulate employee income growth. On the other hand, average wage levels may also influence firms' decisions on automation: rising labor costs may reduce the relative cost of introducing robots.
Nevertheless, the results of the calculations show an improvement in the situation of manufacturing workers in regions where industrial robots are being introduced more actively. According to the expert, this connection arises from increased profits, output, and competitiveness of enterprises through automation. In addition, the effect may reflect the complementarity of workers and robots: in conditions of labor shortages, the introduction of robots may be accompanied by more active recruitment of employees.
Margarita Kropocheva also additionally assessed the impact of the level of robotization on average wages in the manufacturing industry without dividing them by qualifications. “The estimates obtained when all control variables were included turned out to be statistically insignificant, which indicates a correlation between the introduction of robots and the wages of manual laborers,” she noted.
The expert also confirmed that in conditions of record low unemployment (around 2.2–2.3%) in Russia, robots primarily fill vacant jobs. The calculations revealed a significant negative correlation: the lower the unemployment rate in a region (and, consequently, the greater the labor shortage), the higher the density of robotization there. At the same time, as Margarita Kropocheva noted, it may be more important for business not the absolute level of unemployment, but the relative position of the region: “For example, if industrial enterprises are located in different regions, management may direct funds for the robotization of production primarily to those divisions that are located in regions with lower unemployment, as they experience a greater labor shortage,” the expert concluded.