Wage arrears and the distribution of earnings in Russia
The increase in wage inequality in Russia during its transition process has far exceeded the increase in wage dispersion observed in other European countries undergoing transition. Russia also has an extremely large incidence of wage arrears. We analyse to what extent wage arrears affect the wage distribution and measures of wage inequality in Russia. We present counterfactual distributions, derived from a variety of different methods, which suggest that conventional measures of earnings dispersion would be some 20 to 30 per cent lower in the absence of arrears. We then go on to show how wage gaps at various points in the pay distribution across gender, education, region and industry are influenced by a failure to allow for wage arrears. Using our counterfactual estimates we show, for example, that the median gender wage gap would be around twenty-five points higher than the actual gap that we observe. Similarly, the counterfactual ratio of mean graduate pay to mean pay of those with primary education is around twenty points lower than observed. We show that the parameters of the counterfactual wage distributions are very similar to the parameters of the observed wage distributions of those not in arrears. This means that for those wishing to study aspects of wage differentials and inequality in Russia, it may be feasible to use the subset of those not in arrears and still get close to the true population parameters.
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absence of arrears Actual No OLS analysis arrears distribution coefficient of variation conditioning on pre-treatment construct counterfactual wage counterfactual distributions counterfactual estimates counterfactual wage distributions differentials DiNardo Distribution of Earnings earnings dispersion earnings distribution Earnings in Russia earnings inequality Economic Employed and fully entropy estimates based experiencing wage arrears Firm gender wage gap Gini coefficient Heckit JMP DFL Heckman Heriot-Watt University incidence of wage individual inequality in Russia IZA Discussion Papers JMP DFL Match Kernel density Kluve labor economics labour market level of wages logit matching estimator Median monthly wage distribution n/a n/a paid in full parameters Potential Control pre-treatment history predicted wage propensity score estimates propensity score matching Quintile random real monthly wage Real Wa9e regression residual rise in inequality RLMS sample period sectors suggest Table treatment Universities of Heidelberg unobserved heterogeneity Urals VCIOM Wa9e 000 Roubles Wadsworth and Acquisti wage equation wage inequality workforce World Bank