Subject The article addresses differences in payment for labor, using the Russian data. Objectives It analyzes the most sensitive aspects of Oaxaca–Blinder decomposition. Methods The study employs linear regression and Oaxaca–Blinder decomposition. Results The paper demonstrates the sensitivity of decomposition to the choice of suitable average counterfactuals, which variation may change the total effects of Oaxaca–Blinder decomposition. The most effective option is to include a subgroup dummy variable in the model specification. There may be discrepancies in the decomposition results for different approaches to the choice of the omitted dummy category. Conclusions The method of normalized regression enabled to reflect all categories of dummy variables in the decomposition, and unify the results.
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