Methodology: DEA estimators of total factor productivity and its components; Kalman filter to estimate potential output and output; SFA estimators of cost efficiency of Russian banks; Bayesian vector autoregression with identification for structural shocks; panel discrete choice models to construct leading indicators of government bond market shocks; spectral analysis with the method of inverse decomposition problem to extract cyclical components from economic series; nonlinear interpolation of spectrum to detect significant cyclical components; gravitation models estimated with Poisson quasi-maximum likelihood to estimate effects of trade integration between Russian regions and Eurasian Economic Union members. The analysis includes the use of statistical and illustrative techniques, as well as other analytical methods (cluster analysis, ranking etc).
Empirical base of research: The data we used include databases by Rosstat, Minfin, Bank of Russia, Ministry of Industry and Trade, Ministry of Economic Development, Federal Customs Service, industrial surveys compiled by IET, newspaper articles, official sources. Laboratory staff created a unique statistical database on Russian economy comprising over five thousand series and makes use of it for research purposes. Also we use the following databases: Cbonds-PRO RU (database on Russian corporate paper issuance), Loans-PRO (database on syndicated credit), BIR-Analytik (database on accounting reports of Russian companies) and several smaller databases.
Results of research:
- We conducted regular monitoring and research on development of Russian economy in 2013 for topics in industry, external trade, budget, as well as macroeconomic, monetary policy and banking topics. We developed scenarios for economic and social development in Russia both in short- and medium-term. Our research was focused on burgeoning crisis processes in main sectors of Russian economy, development of scenarios including uncertainty factors linked to oil prices and world economic growth, but also to government policy profile (which could be either stabilizing or proactive); each scenario was analyzed with roadmaps of exploratory macro forecast and then scenario quantification was performed.
- We estimate potential output growth and output gap for US, euro area, China, and Japan with a variety of multivariate Kalman filters. We detect structural breaks on post-crisis period for all countries with Chow test.
- Using DEA non-parametric production function method we estimate production possibility frontier for two samples (Russia and 1990 OECD members, and 100 largest economies). Properties of TFP estimates and its components for both samples are similar. We estimated the long-run impact of R&D on technological frontier component dynamics and other components and found that overall TFP model has lowest forecast errors.
- We made new estimates for impact of new goods on export volumes based on edge-cutting approaches to growth decomposition into extensive and intensive components. For Russian economy the impact was much lower thatn for the world economy, namely 6% of export growth against 20% in the world. We found that the growth input is the largest in chemical industry and machinery production. Consequently, these sectors need to be focused on for long-term government export stimuli purposes.
- We estimated probable impact of import substitution on industry basis by using world export specialization structure. We found that out of 15 leading import substitution activities 10 are inside machinery production. The highest potential for import substitution was found in chemical, food processing, textile and metallurgy industries.
- We developed the methods to estimate manufacturing trade growth potential in case of economic integration for the case of Eurasian economic union. We expanded gravity model of intra-country trade to include the economies Russian economy integrates with.
- We estimated exchange rate impact on corporate profits. We found that in case of efficient fiscal income redistribution could dampen depreciation effects for the real sector. Depreciation effects are the largest for mining industries and production of oil products, amounting to 1.3 bn dollars per 1% depreciation. Metals industry receives around 0.2 bn dollars per 1% depreciation. Other industries experience income decreases in case of depreciation, the sharpest in machinery production and services sector.
- An analytical framework was developed in order to trace the changes in the liabilities-to-assets transformation process within the Russian banking sector. First, it was revealed that those funds attracted for corporate lending have shifted from retail to corporate deposits. Second, it was shown that the channel of extracting extra-revenues by Russian banks has been transformed so that now banks issue new unsecured retail loans by exploiting longer term retail deposits instead of foreign liabilities previously used for that purpose. At the same time, the following two strong tendencies take place: (i) banks provide retail loans of maturity more than one year using retail deposits of the same maturity and (ii) banks allocate corporate deposits in reserve assets and government bonds. This observed segregation of retail and wholesale businesses threatens the Russian economy by the following stagnation because the expanding of corporate lending required for the Russian economy to recover met an obstacle in the form of insufficient use of retail deposits by banks as a major source for respective operations.
- A set of empirical models was developed in a panel framework to estimate both the signs and strengths of impacts that the market powers of Russian banks might have on their stability indicators over the period of 2005Q1-2013Q4. On the basis of these estimated models, it was proven the relevance of the tripod “market power — cost efficiency — greater stability” for majority of Russian banks. From the policy perspective, it was shown that, given the currently revealed highly volatile states of banks’ market powers, the Russian government and the Bank of Russia could, without any loss in banking sector stability, take the following steps. First, to gradually raise equity capitals of government-owned banks so that the share of the top-3 banks, i.e. Sberbank, VTB and Gazprombank, increase from the current 47% to 52% of banking system assets. Second, to facilitate the consolidation of banks by (i) gradually increasing the minimal levels of equity capital required from the currently operating financial institutions, which is 300 mln Rub from 2015, and (ii) stimulating M&As providing banks with the some kind of temporal softening of the regulatory required normative ratios. Third, to gradually decrease the insurance coverage guaranteed by the Russian Deposit Insurance Agency to private depositors since the currently observed crisis episodes begin to fade away and the Russian economy starts to recover.
- Stress test assessment based on leading indicators of government bond market stress led us to conclude that significant probability of stress is limited to one out of three scenarios, and the probability is still low. The main reason for stress in that scenario is still not the excessive debt burden but the complementary factors – mainly the corporate debt defaults.
- Some research on special topics was conducted, including research on employment and evolution of public-private partnerships for education and health in Russia.
- We published a number of regular research and outlooks, including “Trends of Russian Economy”, “Trends in the largest economies”, “Technology monitor for Russia and the world”, “Financial indicators”, and a number of regular monthly research reports
During the year, we performed reviews of main economic policy actions, including scenarios and forecasts made by Ministry of Economic Development, and developed scenarios for economic and social development in Russia based on the same assumptions. We analyzed Main directions of monetary policy devoting special attention to risks for monetary policy and banking system.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results
Implementation of research goals will allow to add to the quality of socioeconomic forecasting, including those for the purposes of anti-crisis policy. The results may serve as a base for policy advice in preparing large-scale decisions and long-term strategic official documents.
The materials prepared during the realization of the project were accepted by officials in Office of the President, Ministry of Economic Development, Ministry of Industry and Trade, Ministry of Education and Science.