Goal of research. The aim of the project is better understanding of factors, which influence the ability of industries of the Russian economy to diminish real costs of production. In other words, the project aimed to explain what could influence multifactor productivity growth. Subject for study was the Russian economy in the post-crisis period.
Methodology. Two groups of methods were implemented. The first is based on time series econometric methods, oriented on estimation of dynamic models using relatively short time series. The second group is non-parametric estimation of supply-side sources of growth, called “the neoclassical industry growth and level accounting”.
Empirical base of research. Main data sources are official statistics provided by the Russian Statistical Office (Rosstat), including unpublished disaggregated series, and information on details of official methodology for construction of some important indicators. In addition, some data from alternative sources was used, such as World KLEMS (www.worldklems.net) and WIOD (www.wiod.org) datasets.
Results of research. The first study within the project compares dynamics and structure of sources of economic growth at the level of industries both in Russia and in Central and East post transition economies, using industry growth accounting approach. It was found that the contribution of multifactor productivity (MFP) in growth rates of the Russian economy is not as large as it has been presented in the literature. According to the present study, MFP contribution explains only half of real value added of the Russian economy. It was also established that the contribution of capital input was more substantial in comparison with the literature. Next, industry-level structure of sources of growth is unfavorable for high growth in upcoming years, because the lion’s share of investments flows to the inefficient oil and gas sector. Finally, the most substantial source of MFP growth is financial and business services. However, its high performance seems to be a catch up growth from a very low initial (1995) level even in comparison with many CEE economies, rather than the innovations-driven one.
The second study of the project is focused on compilation of the time series of Supply and Use tables of the Russian economy starting from 1995. Main obstacle for this is the shift of the official statistics from the old Soviet industry classification OKONKh (the Old classification), which is inconsistent with any international industry classification scheme, to the new one OKVED (the New classification), which is harmonized with NACE 1.0. Moreover, the last detailed official set of benchmark SUT’s was compiled in the Old classification in 1995 with imputed SUT’s until 2003, while the next one, by 2011, will be published in the New classification in the end of 2015. So, the study is a step in the direction of imputations of SUT’s in years between the two official benchmarks.
The present study suggested the consistent scheme of transformation of the official SUT’s for 2003 in the Old classification into the New one, as well as compiling the SUT’s for 2004 and the following years.
Main peculiarities of this approach are the following.
- Use of many classification bridge matrices between the Old and the New classifications instead of just one, as in the literature.
- Application of RAS for measures of the first and the second sections of the Use table rather than the first, as it assumed in the classical version of RAS. This resolves the problem of exogenous definition of sums of rows of the first section, for which there is no information.
- Imputation of the series of SUT’s in the New classification provides an empirical base for development of economic policy, research, and representation of the Russian economy in databases for cross-countries comparison at the level of industries.
The third study analyzes the systemic risks of the Russian financial system. Urgency of this issue became clear in 2014, when due to economic sanctions borrowing conditions for Russian firms worsened. At the same time, risks of borrowing abroad rose. The study considers systemic risks in the financial system of Russia, taking into account existing international experience of evaluation of these risks. Using approaches, relevant for the case of Russia, the study builds measures of these risks. It was found out that the Russian banking sector is procyclical. This indicates the ability of the financial system to enhance real sector instability. All measures used provide evidence that systemic risks were substantial before the financial crisis (2007–2009) and remain high now.
The study unveils the relationship between financial flows and investments and physical capital accumulation in the Russian economy. For this we identify factors, which influence investment decisions of firms, and then to understand the role of internal and external (borrowed) funds in the investment process. Taking into account that Russia is a technology backward country, there is a room for catching up and convergence. That is why the nature of investment process is urgent.
The fourth study deals with existing data sources in Russian statistics, which provide the information base for research in inflation and growth. Unfortunately, the official Russian statistics data of macroeconomic dynamics do not fully match the requirements of modern research. In first years after transition these difficulties could be explained by transformation of the Russian statistics. However, with the time being many problems, which could be resolved, did not disappear.
The study discusses some issues of data supply for the analysis of Russian macroeconomic dynamics. It highlights what indicators of the Russian official statistics are worth of saving. For example, should the official statistics save annual data only or quarterly and monthly series are also worth of attention? For what periods should these series be saved? What level of disaggregation is the most appropriate for public access? What structure of data (time series or matrices) is the most convenient? What is a relevant form of publication of official methodologies? What of the whole set of statistical information, which is producing now, will survive in the future, taking into account a current practice of publication of official statistics? To what extent will it be relevant for future quantitative research? The study highlights serious shortcomings in all these issues.
The study considers current practices of compilation of long internally consistent time series. It discusses requirements to a relevant media for saving of this information, and suggests practical steps, which could improve the existing situation.
Level of implementation, recommendations on implementation or outcomes of the implementation of the results. The present project provides a unique empirical base for applied analytical studies and economic policy making. The Russia KLEMS dataset attracted interest of the Conference Board the Conference Board (http://www.conference-board.org/), Institute of Economies in Transition of the Bank of Finland BOFIT (http://www.suomenpankki.fi/bofit_en/bofit/Pages/default.aspx), OECD (http://www.oecd.org/) and the Vienna Institute for International Economic Studies (http://www.wiiw.ac.at/).
Results of this project can be used for economic policy making, improvements of the official statistics methodology and for teaching.
The laboratory also provides expert examination services for such government authorities as Economic Council of the President, the Bank of Russia, the Ministry of Economic Development, Rosstat, and the Interstate Statistical Committee of the Commonwealth of Independent States.