2018. vol. 22. No. 4

The paper discusses the composition and dynamics of low paid workers whose hourly wages do not exceed two thirds of the median value. Using RLMS-HSE data for 2002–2016, we analyze how the size and the composition of low-paid employment, and the likelihood of being low-paid have changed over time. Our findings suggest that the size of the group has decreased from 30 до 24% of the total employment over the study period, while the chances of being low paid are significantly higher for those who have lower level of education, who are employed in low skilled jobs, and who reside outside large cities. However, the main focus of the study is on the earnings mobility of low paid workers. The key question is whether the low paid state is a dead-end and a long-term trap or is it just a stepping stone towards the high pay group? In order to answer this question, we apply a dynamic random effects multinomial logit-model, which allows to control for unobserved heterogeneity and to account for initial conditions problem. The study demonstrates high degree of structural dependence: two out of three low paid workers cannot exit this state over the year. This trap effect is stronger for women than for men. Though the stepping stone effect is also present, it is much weaker and relates to only one out of four low paid workers.

Studies on job search in Russia regularly raise the problem of separating seekers from non-seekers and forming a sample for empirical analysis of job search. Different researchers provide different solutions to the problem, but there are two main approaches to constructing a sample. The first one is to use data only on registered unemployment, the second approach is to use data from surveys that include questions on whether a respondent is searching for job and is ready to start working after receiving an acceptable offer. This paper provides estimates of an empirical job search model that explains both decision whether to seek a job or not and a probability of a successful search. That decision is unobservable and may not coincide with answers that individuals give during the survey. The model is estimated using data from Russian Longitudinal Monitoring Survey (RLMS-HSE) for the 2000–2014 period. According to obtained estimates, most of the non-employed may be considered as job seekers. The results not only provide a new insight into economic activity of non-employed but also show a possibility to significantly enhance information base for empirical studies on job search.

Economic access to food, in contrast to the Doctrine of Food Security, involves providing the population with food, regardless of the source of its origin. The situation with the economic access in Russia as a result of the impact of sanctions and embargoes has complicated and conditions have been created for its regular monitoring, both at the country level and at the level of individual regions. The paper analyzes the conceptual apparatus and the main methodological approaches to assessing economic access. The article presents a method for quantifying the economic access to food, which takes into account the effects of absolute income, food prices in the country and the region, the balance of the diet of the consumer, or the national or local share of food expenditures. An empirical assessment of the economic access in Russia and its subjects has been carried out. The values of the indicator of economic access for Russia as a whole demonstrate a fairly stable situation. The results made it possible to identify a number of factors that ensure an increase in the economic access to the population, including income, the level of prices for basic food products. Indirect influence on the economic access can have the share of the agrarian sector in the economy of the region and the share of small farms in the structure of agricultural production. Methodical development is intended for the governing board.

We conduct a statistical study of the global trade slowdown relative to industrial production after the global financial crisis of 2008–2009 and the revival of the global trade in 2017. We aim to decompose the overall effect by geographical and commodity dimensions, that is, to determine the contribution of regions, major countries and aggregated commodity groups to the global trade slowdown and revival. Calculation scheme implies the two-way analysis, both from the demand and the supply side (imports and exports, respectively), and relies on the customs data. The focus on merchandise trade is confirmed by the fact that the growth rates of world imports and exports in constant prices for services decreased much less after the crisis of 2008–2009 than for goods. We analyze the dynamics of world trade relative to the dynamicsof industrial production, not GDP, due to the very high volatility of trade to GDP. The data comes from the Netherlands Bureau for Economic Policy Analysis, WTO, World Bank, OECD, FAO andthe Chatham House Resource Trade Database. The key feature of the proposed scheme is aligning data on international trade growth for largest countries from different sources with CPB data for the world as a whole.

The results of the study show that the slowdown in global exports was largely associated with emerging economies of Asia (and, primarily, China), Japan, Germany and the US, while the slowdown in global imports reflected the drop in demand in China and other emerging economies of Asia, the Euro Area, Russia and Brazil. The revival of global exports was driven by China,Japan, Netherlands, South Korea and Mexico, and the revival of world imports boils down to the demand growth in China, India and Russia. Unlike the global trade slowdown, the revival of the world trade was critically concentrated in emerging countries, while the Euro Area has practically not experienced the revival. An important role in the global trade slowdown was played by China and its reorientation to the domestic market after the crisis of 2008–2009. In terms of commodity structure of global trade, the slowdown was almost entirely associated with non-resource goods.

The results can be used to refine the forecasts of the global merchandise trade growth by accounting for the contribution of the major countries more accurately.

This article is devoted to estimating the Phillips curve on the regional panel data for Russia, that allows to understand the degree of regional heterogeneity of the main macroeconomic indicators.

Using the generalized method of moments, the hybrid Phillips curve and its partial cases (adaptive expectations-augmented and neokeynesian) are estimated in this paper. The results show that among three model’s modifications the hybrid model with the output gap and forward-and back-looking expectations is the most fitting to real data. Thus, we can assume that inflation expectations in Russia include both adaptive and rational components.

At the same time, the Phillips curve with the unemployment rate incorrectly describes the regional panel data. We associate this result with the specifics of regional labor markets and divide the regional sample into clusters by the indicators of income and unemployment, which gives the formation of three clusters: 1) with high income per capita, high level of the economically active population and low unemployment, 2) with low income per capita, low level of the active population and high unemployment, 3) with middle values of each indicator.

The results of the model estimation show that the Phillips curve does not describe the data on the sample of «rich» regions, which is explained by the natural and climatic conditions in these regions and/or by specific state premiums. At the same time, inflation and unemployment in regions with low and/or moderate incomes are adequately described by the Phillips curve. The obtained results allow to understand more deeply the mechanisms of pricing in the Russian regions, the specific features of labor markets and the formation of macro variables at the regional level.

After the recent debt crisis governments of many developed and developing countries turned to the use of financial repression as a way of government spending financing along with explicit capital taxation. Financial repression can be considered as an implicit tax on capital, be cause it leads to the outflow of resources from investment to the government debt. We question what type of government spending financing is better: explicit or implicit tax on capital (financial repression). The criterion is the minimization of consumption crowding out effect in the steady-state where government spending can be of three types. We propose a Ramsey model mo­dification with financial repression and three types of government expenditures: wasteful, productive and one in the utility. There are two instruments of financial repression: artificial increase in debt demand and lowered government debt yield. We find that regardless of government spending type, the choice of the government, which guarantees maximum level of consumption or minimum crowding out in the steady state, is explicit tax on capital in the absence of financial repression (in the form of artificial increase in debt demand). The higher is artificial debt demand the bigger is the direct outflow of capital to the government debt and less is the average interest of savings, while increase in the explicit capital tax rate affects only the savings yield. However, increase in the explicit tax on capital and lowering debt yield leads to the same crowding out effect.