Multiproduct Model Decomposition of Components of Russian GDP
In this paper, we explore the relationship between informality and earnings inequality using the data from the Russia Longitudinal Monitoring Survey (RLMS-HSE) for 2000–2010. We determine that during the entire period, earnings inequality was substantially higher in the informal sector. Informality increases earnings polarization, widening both tails of the earnings distribution. Nonetheless, inequality has declined in both formal and informal sectors. In the formal sector, changes in the distribution of monthly earnings between 2000 and 2010 were primarily generated by changes in the distribution of hourly earnings. In the informal sector, reduction of variation in monthly earnings went through two channels: declining differences in hourly rates and considerable compositional shifts within the informal sector. The results point to the importance of distributional analysis of earnings gaps and explicit accounting for the sector choice.
In this paper I study and compare the earnings distributions for formal and informal workers using the data from the RLMS HSE survey for 2000-2010. I find that during the whole period earnings inequality was significantly higher in the informal sector than in the formal sector. Informality has statistically significant impact on the distribution of earnings, but its contribution is much smaller than the effects of other variable such as gender, education, region, and settlement type. Earnings inequality dramatically decreased in both sectors over the 2000-2010 period. In the formal sector the changes in the earning distribution were mainly generated by the changes in the distribution of hourly earnings. In the informal sector the reduction of inequality went through two channels: differences in both hourly rates and hours of work were declining. This reflects several underlying forces: a declining share of workers without permanent job and low barriers between the sectors (as inequality decreased by similar amount in both sectors). In fact, one third of the overall decline in the variance of logs over the 2000-2010 period is due to workers without permanent employment.
The author applied the decomposition method LMDI to investigate the factors that influences the energy intensity of power generation in Russia. The analysis allows to determine the connection between energy intensity of power generation and both technical and structural changes in electricity and heat production.
Inequality is a part of the economic reality of any society. It is also a constant focus of attention of academic community, from time to time becoming a matter of heated social and political debates. Social scientists consider the growth of income inequality as one of the major socio-economic risks posed by globalization. Inequality issues have acquired a particular importance in connection with the market transition of post-socialist countries, including Russia, where the ‘starting point’ of transformation was the centrally planned economy. The characteristic feature of the transition process has been a sharp increase in income inequality. In the late 1980s Russia, along with the Scandinavian countries was in the group of states with a low level of income inequality. At present, the scale of inequality in Russia is comparable to economies of Latin America. This note aims to provide a comprehensive analysis of income inequality in Russia for the period since the beginning of market reforms. The sources of data are both official macro-statistics and independent sociological surveys.
An approach to the construction of a stabilizing feedback for linear time variant systems is considered. This approach is based on a heuristic isolation of two simplified subsystems of lower dimension. For these subsystems, stabilizing regulators are constructed and then combined into a composite regulator. This paper generalizes the results obtained earlier, which can lead to a significant expansion of the scope of composite control. This is illustrated by a number of examples.
The paper studies the evolution of individual- and household-based non-employment rates in Russia using data from the RLMS HSE for 1994–2016. Following [Gregg and Wadsworth, 2008], I estimate disparities between individual- and household-level measures and compare actual household workless rates with counterfactuals based on a random distribution of work. I find that the Russian labor market is characterized by a low, albeit growing, rate of household joblessness: about 6% of the working-age population live in households where no other adults work. Inequality in the distribution of work is also low and declining. Generally, work is distributed equally among households and in some years more (!) equally than if it were distributed randomly. Equality is achieved primarily due to very high employment rates among two-adult households. Conditioning on characteristics, we distinguish several types of households that face “excessive” non-employment, i.e. for these types of households actual non-employment rate is higher than the counterfactual prediction based on their socio-demographic characteristics. These are households without university graduates, couples without children in which one of the spouses is above official retirement age, working-age couples living with adult children, and working-age single adults without children. The paper assesses various underlying driving factors for the dynamics of household nonemployment. The decomposition results reveal that there are a number of factors at play. Demographic shifts – reduction of average household size and expanding share of single-adult households – were identified as the main driver of growing household joblessness. Labour market factors – changes in individual employment rates, especially deterioration of permanent jobs – also exerted a sizable effect. These trends were partly offset by improvements in the distribution of work among households.