Objects of research are Russian economy’s specific sectors.
The aim of the research is development of new models in the framework of the system of models elaborated for analysis and forecasting of Russian economy and its separate sectors by the staff of the laboratory. These new models should correspond to changing economic environment of Russia. The models should be ready for both fundamental and applied researches running by researchers, students and PhD-students of NRU HSE.
Methodology of research combines econometric, general equilibrium and analytical approaches to modelling of contemporary economic processes in specific branches of Russian economy.
There were made some significant improvements during the current year. Some sectorial models of Russian economy have been modified. Financial sanctions and recession of Russian economy forced to take into account new economic reality and to check robustness of the previously developed models under new circumstances. There were developed some solutions to arisen problems including the following. Development of the model of the Russian banking system; modification of the complementary slackness condition approach for improvement of forecast power of a dynamic model; development of both the aggregating and heterogeneous consumer model; revealing of measure of influence of direct foreign investments in firms of Russian food industry; risk evaluation at Russian financial market; modelling of hidden incomes of Russian households; modelling of interregional migration in Russia based on municipal level statistic.
The main scientific results are the following
There was developed a dynamic bank model. The model was analytically solved, and main regimes were analyzed. New approach to complementary slackness conditions was proposed. The turnpike effect is revealed.
There was investigated an influence of de-seasoning procedures on statistical tests’ performance, namely, on unit root and cointegration tests. The conclusion is not to use de-seasoning procedures under unit root tests due to possible large bias. At the same time, de-seasoning procedures are allowable before modelling multivariable relations.
There were developed two dynamic models of aggregate consumers’ behavior. The first model based on the representative consumer approach, and it was solved analytically. The second model based on the concept of heterogeneous consumer. It was calibrated to the Russian data, and it demonstrates good forecast properties for different income stratas.
This year research continues examination of "fat tails puzzle" at Russian financial market. We implemented to Russian financial indices the method of Y. Gabovich (G-bounds approach) based on the rate of convergence in CLT to the normal distribution. It was shown that the G-bounds evaluate risk at financial markets more carefully than models based on VaR approach.
The analysis of FDI in Russian food firms revealed positive agglomeration effect on firms’ performance.
There was developed QUAIDS model with endogenous prices in order to reveal the consequences of countersanctions regimes on Russian consumers’ behavior. The results demonstrate changes in food demand.
The hidden incomes of Russian household were analyzed on RLMS data. The modeling revealed that the most shares of hidden outcomes characterizes the poorest strata.
The developed model of interregional migration in Russia showed that the average wages is the most influential by spatial factor. Moreover, the scheme of influence is different for different regions.
The foreign partners were
Maurel Mathilde, Centre d'économie de la Sorbonne
Maison des Sciences Economiques,http://centredeconomiesorbonne.univ-paris1.fr/bandeau-haut/membres/m-chercheurs/
Sasha Sardavar, Wienna University of Economics and Business,http://www.wu.ac.at/wgi/institut/team/forscher/sardadvar