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OaxacaBlinder decomposition of wage inequality: Sensitivity analysis on Russian data

Vol. 18, Iss. 11, NOVEMBER 2019

Received: 21 October 2019

Received in revised form: 5 November 2019

Accepted: 19 November 2019

Available online: 29 November 2019

Subject Heading: THEORY OF FINANCE

JEL Classification: C31, D63

Pages: 24682484

https://doi.org/10.24891/fc.25.11.2468

Ovchinnikov V.N. Financial Research Institute of Ministry of Finance of Russian Federation, Moscow, Russian Federation
vyacheslav_ovchinnikov_1993@mail.ru

https://orcid.org/0000-0001-9786-3299

Subject The article addresses differences in payment for labor, using the Russian data.
Objectives It analyzes the most sensitive aspects of OaxacaBlinder decomposition.
Methods The study employs linear regression and OaxacaBlinder decomposition.
Results The paper demonstrates the sensitivity of decomposition to the choice of suitable average counterfactuals, which variation may change the total effects of OaxacaBlinder 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.

Keywords: differentiation, income, regression, decomposition

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