The analysis of technical efficiency of Russian retail companies in 2019–2023

Abstract

This paper studies the technical efficiency of Russian retail companies from 2019 to 2023 using stochastic frontier analysis (SFA) with the Battese and Coelli (1995) model. The authors employ a translogarithmic production function for estimations. The dependent variable is company revenue, and the production factors are the average number of employees, fixed assets, and assets less fixed assets, along with year-specific dummies. We model the mean distribution of the inefficiency component as a function of company age, total assets, and the regional Herfindahl–Hirschman index, calculated using a sample from the SPARK database. The results of our analysis show that labor makes the largest contribution to revenue growth, with increasing returns to scale, albeit close to constant. Revenue increased annually throughout the period under study. Average technical efficiency in the industry exhibits an inverted-U-shaped relationship with firm age and size. Technical efficiency declined significantly during the pandemic but showed steady growth in subsequent years.