Current economic analysis, planning of budget revenues, supporting medium-term forecasts and economic policy measures require not only quarterly macroeconomic statistics that is widely used now but also retrospective and current data with a shorter step length. The article summarizes the techniques and practical experience of specialists from the Ministry of Economic Development of Russia in the reconstruction for these purposes of monthly series of macroeconomic indicators based on official statistics using quarterly accounts and higher-frequency indicators, as well as methods for their short-term estimation and forecasting. Disaggregation techniques for the time-series of high-frequency indicators, proposed by specialists in this field were used to reconstruct the monthly series of GDP components for the production account at prices of 2011. Issues concerning disaggregation technique are discussed in the article. The author proposes a method for restoring monthly series of GDP components at current prices, calculated using production account and income account. The actual trends of monthly changes in the main indicators, excluding the seasonal factor, are analyzed from the view of their susceptibility to the crisis phenomena of 2014-2017. This article presents main methods of short-term forecasting of macroeconomic indicators with account to their relationship map with the final demand and the growth of potential GDP. It is demonstrated that both approaches are linked by the representation of the «gap» through the cyclic component and other factors.

The authors review task definition, methodology and results of using qualitative research for testing capabilities and tools of official Rosstat statistics to measure the input of small businesses in achieving sustainable development goals (SDGs) in Russia. Summary analysis of results of the in-depth group focus interview (in groups of experts and small business owners) demonstrated that the sample survey of small businesses to measure indicators of UN SDGs aimed at their inclusion into the overall system of SDGs indicators in Russia is not only possible in the Rosstat system, but also appropriate, promising, seams methodologically sound and sensible, and also feasible, without significant increase in statistical load on small businesses.

This is a brief commentary on the article by G.O. Kuranov and R.F. Luk’yanenko «Study of Economic Dynamics and Validation of Growth Factors» that reviews some if its theses. For instance, it is noted that considering the importance of the subject of the article it deserves to be discussed in detail by experts in macroeconomics and econometrics. At the same time some ideas put forward in the article require specific clarification and consideration. They pertain in particular to including in the model such factors as growth of exports and increase of price on crude oil at the world market; the arguments in favour of including these factors are not convincing. It is noted that the number of persons employed used in the model to denote the labour input is not satisfactory because it does not reflect the degree of participation of employees in production, and the number of man-hours worked in production is a more adequate indicator.

This article presents the first part of the work devoted to the application of innovative approaches to  statistics on migration, their directions and priorities. It is focused on the emerging use of Big Data in measuring migration. It is concluded that in the foreseeable future, Big Data will find its niche among the sources of information on population movements. However, at present they can only be used for estimations of various forms of short-term population mobility and shifts in its spatial distribution at certain moments or periods of time. It is not possible to apply to the Big Data the criteria of a migrant and migration identification that are used in official statistics, first of all - the concept of place of usual residence. An important limitation is also the lack of different variables characterizing the structure of migration flows and stocks. It is concluded that Big Data is not yet suitable to become an alternative to the traditional sources of information for the production of reliable and comprehensive statistics on migration. The potential of the latest is far from being exhausted, but the current situation is characterized by a complex of problems that require implementation of advanced technological solutions. Positive anticipations dealing with possible improvement of the situation are associated with establishment of the population register of Russia.

An analysis of the dynamics of Uzbekistan’s external trade shows that it retains a number of problems that in the long run undermine goals of sustainable economic development. This is expressed not only in the negative rates of its growth in recent years, but also in the negative trade balance net of energy, devaluation waves that swept the main trade partners, low world prices for the main export commodities, weak degree of product and geographical diversification of exports, as well as the existence of institutional problems. For these reasons, it can be argued that Uzbekistan’s export sector remains vulnerable to external shocks.

In these uneasy conditions it seems relevant and timely to pinpoint key directions for reforming the external trade sector.The targeted liberalization of external trade which is already underway, the elimination of the numerous problems associated with export and import procedures, taking into account the world’s best practices, the combination of these efforts with an effective policy of attracting foreign direct investment, mainly to the manufacturing industries, are the key policy priorities in this regard. This research is devoted to a detailed statistical analysis of the abovementioned problems of Uzbekistan’s external trade, the remaining policy space in this direction, the possibilities to increase the share of non-primary goods in its structure, and the development of effective steps and measures for further diversification of the geography and product structure of the country’s exports, taking into account foreign experience and results of empirical research. With effective implementation of these and other steps, the country can create new industries with high competitiveness in the world market, thereby ensuring the diversification of production and exports of industrial goods with a high degree of processing.

This article reviews general issues of accounting of R&D intramural expenditures of an enterprise that first and foremost are related to the questions of expenditures accounting and accounting methodology that together generate the price of R&D.

Methodological framework for R&D accounting in line with the 2008 SNA methodology is analyzed. It recognizes R&D as capital formation because it leads to generating knowledge assets, importance of which for the firms and economics keeps growing, which should be reflected in the national accounts.

The author further examines statistical and mathematics aspects reflecting external and internal sources of R&D funding. External sources include funds of the founders, the state, financial and credit organizations and funds, and to the internal ones - net profit, accounts payable; general corporate means and others. Apart from that the paper describes in detail indicators of selected directions for R&D investment support as a foundation for efficiency of the national economy.

This article presents the analysis of methodological framework for sample survey of private subsidiary farms in 2011-2016. The author points out main shortcomings of the sampling method and errors that they led to. The paper proposes an observation method for private subsidiary farms calculated on the basis of standardized revenue.

In 2009 on the basis of data from the 2006 All-Russia Agricultural Census, the author together with his colleagues developed the technique and classified all types of farms that participated in the Census based on standardized revenue estimates. This work resulted not only in several suggestions related to farm classification but also in methodological considerations on the estimation of the volume of standardized revenue that will allow assessing the economic performance of farms until official statistics starts estimating and subsequently publishing data on revenue characteristics of the selected groups of farms or classes.

The author argues that the effect of an individual group on the general standard error for a stratified sample will be significantly less with a relatively small increase in stratified groups, and consequently the value of the average in the sample will be closer to its true value in the statistical population.

This article focuses on summarizing the results of the 8th traditional international scientific and practical conference that has been held by Saint-Petersburg State University of Economics biannually since 2004.

On 1-2 February 2018 representatives of the statistical community from Russia, France, Bulgaria, Belarus, Kazakhstan, Israel, Japan convened to discuss questions concerning «Statistics in the Digital Economy: Teaching and Applying».

The article reviews subject matter of the conference along with the content of several scientific reports. This paper discusses digital economy trends and Big Data tools in business and management, as well as questions of implementation of information and communication technologies in teaching statistics and economics.