High Economic Inequality in Russia? Measurement Issues, Indicators and Evaluation

Abstract

The correct choice and adequate interpretation of the methodology for measuring inequality are important for understanding the specifics and depth of economic inequality in Russia. This article discusses the main inequality indicators used in Russia and applied in international studies. The first part of the article presents the estimates of inequality in Russia according to official statistics (Rosstat) and considers alternative estimates provided by international organizations and researchers. Special attention is paid to inequality indicators and a number of methodological aspects of measurement that need to be considered when making calculations. The author shows how selected indicators and the data used affect the assessment of inequality. She also provides inequality estimates based on accumulated wealth and discusses the specifics of income inequality in Russia, namely the presence of “heavy” distribution tails. The second part presents a comparison of income inequality in Russia and other countries based on OECD data. According to most indicators, Russia belongs to the group of countries with moderately-high income inequality (above the average OECD level). However, considering additional income inequality estimates (e.g., the incomes of the richest decile based on wealth data and tax statistics according to the estimates of Credit Suisse and Thomas Piketty) Russia is a world leader in inequality. In order to obtain an objective picture of inequality, it is necessary to evaluate it simultaneously in several dimensions. In addition to standard indicators of income differentiation (such as the Gini coefficient and decile coefficient), it is important to take into account a number of other indicators that reflect the specifics of income distribution in Russia, in particular, the presence of heavy tails. Of particular interest are indicators which account for such distribution specifics (e.g., the Palma coefficient) and which are sensitive to changes in income among the poor (e.g., Atkinson index, the average logarithmic deviation).