Abstract

In this paper we compare two types of models for forecasting Russia’s GDP under the structural breaks. We consider models that allow breaks in a deterministic trend, in which the dates of structural breaks set exogenously, and more flexible class of models – with a stochastic trend. We show that models with a stochastic trend demonstrate the best result in GDP growth rates forecasting for a year ahead. For shorter horizons, the best forecasting model is the error correction model with a break in the deterministic trend in the GDP level.

Abstract

The topic of the study is relevant due to the fact that abrupt changes in the economy and in the financial system, particularly those caused by the coronavirus pandemic, have changed all existing development forecasts. At the same time, a whole range of new risks for the financial system appeared. In this regard, the development of a forecast for the development of the financial sector in various scenarios, taking into account risks and opportunities, seems to be the most important task for the Russian economy. The purpose of the study is to develop a medium-term forecast for the development of the financial sector in the Russian Federation. The subject of this research is the dynamics of the development of the financial system of the Russian Federation in the medium term. The research method or methodology is based on the study of key current and retrospective data on the state of the financial sector of the Russian Federation, highlighting the most important risks for the financial sector and building a medium-term forecast. As a result of the work carried out, the key components of the budgetary sphere, financial and credit markets have been analyzed, and the impact of the deterioration in the external environment has been assessed. Thus, the work presents the assessments of the prerequisites for the forecast and developed three possible scenarios for the development of the financial sector in Russia. The scientific novelty of the research lies in producing unique forecasts for the development of the financial sector in Russia. The recommendations obtained as a result of the study indicate the need to develop mechanisms for responding to certain risks for the financial system, taking into account the possible consequences of such an impact presented in the forecast. The project was carried out as part of research work by the Laboratory for Structural Research of the IAER at the Russian Presidential Academy of National Economy and Public Administration in 2021.

Abstract

Empirical analyses on income and wealth inequality and those in other fields in economics and finance often face the difficulty that the data is heterogeneous, heavy-tailed or correlated in some unknown fashion. The paper focuses on applications of the recently developed t-statistic based robust inference approaches in the analysis of inequality measures and their comparisons under the above problems. Following the approaches, in particular, a robust large sample test on equality of two parameters of interest (e.g., a test of equality of inequality measures in two regions or countries considered) is conducted as follows: The data in the two samples dealt with is partitioned into fixed numbers

Abstract

Social and economic changes resulted in a transformation of youth’ values: the attitude towards higher education, granting both social status and, consequently, privileges in employment, became a history. However, the changes taking place in Russia, external to the vocational education system, may have a serious impact on the behavior of young people in the near future, especially young men, who will be more targeted to enroll in full-time higher education programs.