This paper tests covered interest parity at Russian money market over period of 2010-2014 and studies scale and sources of deviations from it. We use both offered and actual interbank interest rates for four different terms. Average deviations from the parity vary between 8 and 105 basis points depending on rates and terms. We test credit risk, turbulence and monetary policy as explanation of these deviations and assessed them quantitatively. For example, one standard deviation change in credit risk is responsible for 50 per cent of the average deviation from parity compared to 72 per cent due to monetary policy spread and (minus) 22 per cent due to turbulence for one week offered rate spread. Risk and turbulence effects grow with maturity and higher for actual rate spreads.

The present paper extends the traditional Dixit and Stiglitz set-up by introducing consumers’ workers’ heterogeneity into a general equilibrium model of monopolistic competition. The model obtains a closed-form solution for a symmetric equilibrium and shows how the market outcome depends on the joint distribution of consumers’/workers’ taste and labor productivities. In contrast to the traditional framework, our model predicts that the short-run equilibrium price may vary with the number of firms, demonstrating both anti- and pro-competitive behavior, which is in accordance with economic intuition and empirical evidence. Proposed approach is also capable to explain variability of the long-run equilibrium markups, which is observed empirically. Unlike the standard CES model, where markups are constant, in our setting the equilibrium markups depend on the covariance of tastes and productivity

We develop a monopolistic competition model with two sectors and heterogeneous agents who self-select into entrepreneurship, depending on entrepreneurial ability. The effect of market size on the equilibrium share of entrepreneurs crucially hinges on properties of the lower-tier utility function for differentiated varieties -- its elasticity of substitution and its Arrow-Pratt index of relative risk aversion. We show that the share of entrepreneurs, and the cutoff for self-selection into entrepreneurship, can increase or decrease with market size. The properties of the underlying ability distribution largely determine how income inequality changes with market size.

The transition to market economic systems in the countries of Central and Eastern Europe and the former Soviet Union involves fundamental shifts in the sectoral allocation of resources, in particular, dramatic changes in employment structures. Development of services in Russia turns to be more impressive than in many other transitional countries. This paper uses the Baumol-Fuchs model of the service sector expansion to estimate underdevelopment of services in Russia prior the transition and measure the progress in catching-up that has taken place thus far. Based on the Russian Longitudinal Monitoring Survey (1994-2000) empirical analysis demonstrates that sectoral variation in the difference between withdrawal from and entrance to the labor force is the main reason of changing distribution of labor. For job-to-job transitions low quality of current job matches, tenure effects and labor market segmentation are the most important explanation of inter-sectoral labor mobility.

The paper documents the changes in the size of the wage distribution in Russia over the period 1994–2003. Developments in wage inequality varied a lot by sub-periods: overall wage inequality stayed stable in 1994–1996, then it jumped following the 1998 crisis and remained at higher levels for three years. In 2002 the trend reversed again and in the course of a single year wage inequality fell back to the level of the mid-1990s. We find that evolution wage inequality was largely driven by changes in the upper end of the wage distribution. Decomposition of wage inequality by population sub-groups shows that inequality has been higher for men, younger and low-educated workers, and rural inhabitants. The structure of inequality did not change much over the period from 1994 to 2003. Demographic variables (mainly gender and region) explain the largest proportion of wage dispersion (over 40% of the explained variation and 15% of total variation). Nearly equivalent is the contribution of firm characteristics with industry affiliation of employer playing the leading role. Our results show that returns to education continued to rise at all percentiles of the wage distribution converging at the level of about 8–9% of wage increase for an additional year of schooling.