Reliable inferences on income and wealth distributions and their heavy-tailedness properties is crucial for estimation of inequality measures. Robust inequality measurement is of great importance for the analysis of the effects of income and wealth disparity on economic markets and their development, including the changes in demand curves and the implied market equilibria over time. Emerging economic markets are likely to be more volatile than their developed counterparts and subject to more extreme external and internal shocks. The higher degree of volatility suffered by these economies leads to the expectation that heavy-tailedness properties and distributions of key variables in these markets, including income and wealth, may be different from those in developed economies.
This paper focuses on robust analysis of distributions and heavy-tailedness characteristics for data on income and wealth for the world, Russia and post-Soviet Central Asian economies. Among other results, using the recently proposed robust tail index inference methods, the paper provides estimates of heavy-tailedness parameters for income and wealth in the markets considered, and their comparisons with the benchmark values that are well established for distributions of these variables in developed economies. The paper further provides applications of the obtained estimation results to inference on income inequality, and discusses applications of the empirical results in the analysis of the relation between inequality and consumer demand, and their implications for economic equilibrium.
The results point to interesting and somewhat surprising similarities between the distributional characteristics and heavy-tailedness properties of income and wealth distributions in some of the economies considered and those in the developed markets. Distributions of many variables of interest in developed economic and financial markets, including income and wealth, exhibit heavy tails as in the case of Pareto or power laws. Many commonly used income and wealth inequality measures are very sensitive to extremes and outliers generated by these distributions due to their heavy-tailedness properties.
Finally, the paper finds that the emerging and developing economies are likely to be more volatile than their developed counterparts and subject to more extreme external and internal shocks. The higher degree of volatility leads to the expectation that heavy-tailedness properties and distributions of key variables in these markets, including income and wealth, may differ from those in developed economies.