SFeDu

DETERMINANTS OF WAGE INEQUALITY IN MODERN RUSSIA

TERRA ECONOMICUS, , Vol. 17 (no. 3),

The purpose of this study is to assess the contribution of various factors to the differentiation of the wage level of Russian citizens belonging to different income groups over time. The study is based on the data provided by two RLMS surveys by the Higher School of Economics for 2004 and 2017. To assess the contribution of factors to the wage level of the various quintile income groups of population in different periods, we used the construction of OLS and conditional and unconditional quantile regressions. Further, on the basis of the developed regressions using the methods of decomposition by R. Oaxaka and A. Blinder and unconditional quantile by S. Firpo, we evaluated the contribution of various factors to the wage differentiation of quantile groups of the Russian population for the two years under study. The study revealed that wage differentiation was primarily determined by the effect of market valuation, while the effect of the composition of the characteristics of the labor force had a much smaller impact on it. Salaries of urban and rural residents leveled off. The remuneration of representatives of the budget and agrarian sectors of the economy gradually approached the average level. Higher education added a lower wage premium. However, high-paid workers did not face this kind of devaluation of a higher education diploma. Finally, we found a tendency to increase the fine for belonging to the informal sector of the economy, although the number of such workers has hardly changed in recent years. The results can be useful when conducting a social policy aimed at reducing the income inequality of Russian citizens.
Citation: Ovchinnikov, V. N., and Malkina, M. Yu. (2019). Determinants of wage inequality in modern Russia. Terra Economicus, 17(3), 30–47. DOI: 10.23683/2073-6606- 2019-17-3-30-47


Keywords: wage; differentiation; inequality; factor decomposition of income; regression; conditional and unconditional quantile

References:
  • Aaberge, R., Eika, L., Langørgen, A., & Mogstad, M. (2018). Local governments, in-kind transfers,
    and economic inequality. Discussion Papers №888, Statistics Norway Research department,
    November.
  • Behr, A., & Pötter, U. (2010). What determines wage differentials across the EU? The Journal
    of Economic Inequality, 8(1), 101–120.
  • Blinder, A. (1973). Wage Discrimination: Reduced Form and Structural Estimates. Journal
    of Human Resources, (8), 436–455.
  • Burdetta, K., Carrillo-Tudel, C., & Coles, M. (2016). Wage inequality: A structural decomposition.
    Review of Economic Dynamics, 19, 20–37.
  • Chernozhukov, V., Fernandez-Val, I., & Melly, B. (2009). Inference on Counterfactual Distribution.
    Centre for Microdata Methods and Practice, Institute for Fiscal Studies, CeMMAP
    working papers, 81. DOI: 10.2139/ssrn.1235529.
  • Ciminelli, G., Ernst, E., Merola, R., & Giuliodori, M. (2019). The composition effects of taxbased
    consolidation on income inequality. European Journal of Political Economy, 57,
    107–124.
  • Cotton, J. (1988). On the Decomposition of Wage Differentials. Review of Economics and
    Statistics, 70(2), 236–243.
  • DiNardo, J., Fortin, N., & Lemieux, T. (1996). Labor Market Institutions and the Distribution
    of Wages, 1973–1992: A Semiparametric Approach. Econometrica, 64(5), 1001–1044.
    Firpo, S., Fortin, N., & Lemieux, T. (2009). Unconditional Quantile Regressions. Econometrica,
    77(3), 953–973.
  • Firpo, S., Fortin, N., & Lemieux, T. (2018). Decomposing Wage Distributions Using Recentered
    Influence Function Regressions. Econometrics, 6(2), 1–40.
  • Fortin, N. (2008). The Gender Wage Gap among Young Adults in the United States: The Importance
    of Money vs. People. Journal of Human Resources, 43(4), 884–918.
  • Fortin, N., Lemieux, T., & Firpo, S. (2010). Decomposition Methods in Economics. NBER.
    Working Paper Series, 16045, pp. 1–92.
  • Gimpelson, V. E., & Kapelyushnikov, R. I. (2013). Is it Normal to be Informal? HSE Economic
    Journal, 17(1), 3–40. (In Russian.)
  • Gorlin, Y. M., & Lyashok, V. Y. (2018). Tax Incentives in Russia and Other Countries: Critical
    Analysis. Financial Journal, (6), 34–46. (In Russian.)
  • Kapeliushnikov, R. (2017). Inequality: How not to primitivize the problem. Voprosy Ekonomiki,
    (4), 117–139. (In Russian.)
  • Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis,
    91(1), 74–89.
  • Koenker, R., & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33–50.
    Lazaryan, S. S., & Chernotalova, M. A. (2017). Global Risk of Rising Inequality. Financial
    Journal, (3), 34–46. (In Russian.)
  • Lukiyanova, A. (2013). The impact of informality on earnings inequality: Unconditional
    quantile regressions. Applied Econometrics, (32), 3–28. (In Russian.)
  • Machado, J., & Mata, J. (2005). Counterfactual Decomposition of Changes in Wage Distributions
    Using Quantile Regression. Journal of Applied Econometrics, 20(4), 444–465.
  • Malkina, M. Yu. (2017). Contribution of various income sources to interregional inequality
    of the per capita income in Russian Federation. Equilibrium. Quarterly Journal of
    Economics and Economic Policy, 12(3), 399–416.
  • Mincer, J. A. (1974). The Human Capital Earnings Function, pp. 83–96 / In: J. A. Mincer.
    Schooling, Experience, and Earnings (Human behavior and social institutions). Natonal
    Bureau of Economic Research, Inc., 152 p.
  • Neumark, D. (1988). Employers’ discriminatory behavior and the estimation of wage discrimination.
    Journal of Human Resources, 23(3), 279–295.
  • Oaxaca, R. (1973). Male-Female Wage Differentials in Urban Labour Markets. International
    Economic Review, 14(3), 693–709.
  • Okamoto, M. (2011). Source decomposition of changes in income inequality: the integralbased
    approach and its approximation by the chained Shapley-value approach. Journal
    of Economic Inequality, 9, 145–181.
  • Reimers, C. (1983). Labor market discrimination against Hispanic and black men. Review of
    Economics and Statistics, 65(4), 570–579.
  • Woo, J. (2011). Growth, income distribution, and fiscal policy volatility. Journal of Development
    Economics, 96, 289 –313.
Publisher: Southern Federal University
Founder: Southern Federal University
ISSN: 2073-6606