Russian Federation: Report on Observance of Standards and Codes-Data Module

International Monetary Fund

doi:10.5089/9781455219940.002.A001

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Russian Federation

Report on Observance of Standards and Codes-Data Module

Author: International Monetary Fund

Publication Date:: 08 Mar 2011

eISBN:: 9781455219940

ISBN:: 9781455219940

Language:: English

Keywords:: ISCR; CR; Russia; information; state; Rosstat; budget execution data; balance of payments; IIP data meet SDDS periodicity; weight data; PPI index data; Correspondent banking; Government finance statistics; Monetary statistics; Budget execution and treasury management; Global

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The report covers national accounts, prices (consumer and producer prices), government finance, monetary, financial and international accounts (balance-of-payments and international investment position) statistics. Assessment of macroeconomic datasets was conducted using data quality assessment framework (DQAF). With the assistance of the Central Bank of Russian Federation (CBR), users’ survey was conducted. Users are satisfied with the methodological soundness, coverage, timeliness, and accessibility of official statistics, especially monetary and financial and balance of payments statistics. Based on the review, the mission has developed a set of recommendations.

Abstract

I. Overall Assessment

1. This Report on the Observance of Standards and Codes (ROSC)—Data Module is a reassessment of the exercise conducted in October 2003, using the International Monetary Fund’s Data Quality Assessment Framework (DQAF July 2003). The Report covers national accounts, prices (consumer and producer prices), government finance, monetary and financial, and international accounts (balance of payments and international investment position) statistics. The Federal State Statistics Service (Rosstat) compiles the national accounts (NA), consumer price index (CPI), and producer price index (PPI); the Ministry of Finance (MOF) and the Federal Treasury (Treasury) compile the government finance statistics (GFS); and the Central Bank of the Russian Federation (CBR) compiles the monetary and financial statistics (MFS) and international accounts.

2. The Russian Federation’s macroeconomic statistics are generally of high quality, reflecting a continuation of positive developments in statistical practices since the last mission in October 2003 that prepared the ROSC—Data Module. Significant improvements are underpinned by the adoption of a Statistics Law in 2007, which embodies internationally recommended principles and practices for official statistics. The agencies compiling macroeconomic statistics have made further progress in adopting international statistical methodologies and best practices. Nevertheless, areas for further improvement and refinement exist. The recent financial crisis and increased prominence of the G-20 (of which Russia is a member) pose challenges to Russia to further upgrade the quality of its macroeconomic statistics for a more extensive and detailed analysis of vulnerability and sustainability. Given the statistical improvements that are underway or planned by the compiling agencies, Russia is well placed to respond to these challenges.

3. Following the ROSC mission in 2003, Russia subscribed to the Special Data Dissemination Standard (SDDS) on January 31, 2005 and started posting its metadata on the Dissemination Standards Bulletin Board (DSBB) on the same date. Russia is in observance of the SDDS, meeting the specifications for coverage, periodicity, timeliness, and the dissemination of advance release calendars. In many cases, it exceeds the SDDS requirements for periodicity and timeliness. Russia uses a flexibility option on the timeliness of the data on central government operations. Appendix I provides an overview of Russia’s dissemination practices compared to the SDDS.

4. In applying the DQAF, the remainder of this section presents the mission’s main conclusions. The presentation is done at the level of the DQAF’s quality dimensions, by agency for the first two dimensions and across datasets for the remaining four.

5. Regarding prerequisites of quality, the responsibility for collecting, processing, and disseminating the macroeconomic statistics are clearly specified in the relevant laws governing the operations of the Rosstat, the MOF, the Treasury, and the CBR. Significant and important changes in the legal mandate of the Rosstat have taken place since the 2003 ROSC mission. These changes include the adoption of the Statistics Law, which gives Rosstat a clear mandate to coordinate all statistical activities in the federal statistical system and reduces duplication and promotes efficiency. In addition, a well documented and comprehensive Federal Plan of Statistical Operations is prepared, which details specific data that are produced, by which agency, and the release dates. Laws related to the confidentiality of the data have been strengthened and now avoid conflict with the criminal codes. Moreover, all agencies have robust internal security procedures to protect the data. The human, physical, and computer resources allocated to macroeconomic statistics are adequate, except for the national accounts. The number of Rosstat staff for the compilation of national accounts is inadequate, which limits possibilities to implement development work in national accounts. The CBR’s relevance assessment practices and quality management procedures provide a firm foundation for its statistical work program. The MFS, as well as the international accounts statistics programs and products, undergo quality reviews by the CBR senior management. The Scientific and Methodological Council of the Rosstat provides a forum for consulting on the quality of Rosstat’s existing statistics and to discuss emerging data requirements and the implementation of methodological improvements. The CBR maintains formal processes of consulting with external users of monetary statistics regarding their needs. The budget execution data and GFS are used for the design, monitoring, and assessment of fiscal policy. No systematic arrangements are in place at the MOF to obtain feedback from external users. All statistics compiling agencies demonstrate awareness of the importance of the quality of data.

6. Regarding assurances of integrity, officials and staff of the Rosstat, the MOF, the Treasury, and the CBR uphold high standards of professionalism, transparency, and ethical conduct in producing macroeconomic statistics. However, the Rosstat now is administratively under the Ministry of Economic Development. The legal statutes establish the Rosstat as an independent agency but in practice, its technical independence is weakened by the role of the ministry in the approval and decision-making process. Changes in the methods used to compile price indices and national accounts must first be approved by the ministry. Data compilers in the Rosstat, the MOF, the Treasury, and the CBR are competent and have actively participated in relevant statistics courses abroad and received on-the-job training. The CBR staff participated in international technical expert groups that contributed to the development of international statistical methodologies. Macroeconomic statistics are disseminated without political interference. Advance notice of major changes in statistical methodology, data sources, and statistical techniques is given to users. Clear ethical guidelines exist for staff of the statistics compiling agencies.

Regarding methodological soundness, all macroeconomic statistics generally follow international statistical standards, namely the System of National Accounts, 1993 (1993 SNA), international manuals for the CPI and PPI, Government Finance Statistics Manual 2001 (GFSM 2001), Monetary and Financial Statistics Manual 2000 (MFSM 2000), and Balance of Payments, Manual, fifth edition (BPM5). Methodological deviations exist in all datasets. The output of illegal activities is not in the scope of the Russian national accounts. The PPI does not include sales of production for export while the CPI does not include owner-occupied housing. The CPI has not adopted the internationally recommended Classification of Individual Consumption by Purpose (COICOP) to classify all items in the CPI. As regards the budget execution data, a number of areas for improvement have been identified. There are monthly and annual cash-based budget execution reports for the general government and its subsectors, but not for the consolidated central government. Expenditures by economic classification are compiled monthly on a cash basis but only disseminated annually on an accrual basis.¹ Debt is classified by currency in accordance with budget legislation, not residency. The budget execution data compiled and disseminated do not follow the presentation of the statements and tables of the GFSM 2001. Monetary statistics have a strong methodological foundation. Classification can be further enhanced by (i) separately identifying contra-entries to data on government’s monetary authorities’ functions; (ii) collecting and including data on financial derivatives at end-period market price/fair value; and (iii) reclassifying the CBR’s valuation adjustment and current year result (profit/loss) accounts in shares and other equity. Valuation of securities held to maturity and shares in the investment portfolio is not on market or fair value basis. The international accounts statistics also have a strong methodological underpinning. An area for improvement is the adoption of accrual principle for recording transactions and positions, specifically for other investment income flows of other sectors (nongovernment, nonfinancial sectors), and the positions of government loan liabilities and nontradable debt of other sectors, which are recorded on due-for-payment basis. The CBR has adopted a phased work program for implementing the Balance of Payments and International Investment Position Manual, sixth edition (BPM6) by end-2012.

7. The accuracy and reliability of macroeconomic statistics received high marks. The Rosstat has a comprehensive system of regular monthly, quarterly, and annual enterprise surveys. Source data for the compilation of GDP and price statistics are adequate. Benchmarking procedures of the quarterly data, volume measures of output and value added for the trade industry, and for taxes and subsidies on products need improvement. In general, source data for the compilation of price statistics are adequate and constantly reviewed for consistency over time and with related products. For GFS, source data for budget execution reports are comprehensive and timely. Statistical techniques could be improved by addressing two concerns: (i) statistical errors are corrected only in the period detected, not in the period they took place, and (ii) consolidation does not follow the GFSM 2001 approach. Source data for monetary statistics are broadly adequate and are subject to validation checks. Automated compilation techniques underpin efficient processing. The data sources for compiling the international accounts are broadly sufficient and are under continuous review. During the 2008 financial crisis, the CBR detected increasing levels and types of financial derivative transactions by banks. Accordingly, measures now are underway to widen statistical collections beyond foreign exchange derivative contracts. The use of statistical techniques to enhance coverage in areas including goods, reinvested earnings, and the direct investment flows and positions of enterprises under production-sharing agreements contribute to the reliability of the international accounts.

8. Serviceability of macroeconomic statistics is sound, with price statistics, MFS, and international accounts receiving excellent assessment in all elements. Periodicity and timeliness of all the datasets, except for the timeliness of data for central government operations, meet and in many cases exceed the requirements of the SDDS. The timeliness of central government operations does not meet the SDDS requirement, but the SDDS flexibility option is taken for this category. Source data used to compile macroeconomic statistics are routinely reviewed and are consistent across datasets. Revision policy in the national accounts needs improvement. Revisions of the quarterly data of the current year should be introduced.

9. Regarding accessibility, all datasets and metadata are available to the public through the websites of the Rosstat, the MOF, the Treasury, and the CBR. Users surveyed during the mission expressed a desire to have statistics available in Excel format and for an improved search engine in the websites given the huge volume of available information. As regards GFS, (i) data on the Treasury and the MOF websites are difficult to access; (ii) limited data are available in English; (iii) limited metadata are posted; and (iv) assistance to users is limited. Regarding price statistics, continuous time series of data at a detailed level for both the CPI and the PPI are not disseminated. CPI weight data have been published on the Rosstat website since 2006. Detailed expenditure data used to develop the CPI weights are also posted on the website. PPI weights are not published, but detailed data on total annual sales, which are used to develop weights for the PPI, are published by economic activity on the Rosstat website. In accordance with international best practices, PPI weight data at a detailed level (both current and historic) should be published on the Rosstat website and included in the PPI bulletins.

10. Section II provides a summary assessment by agency and dataset based on a four-point rating scale. This is followed by a summary of results of the users’ survey in Section III and staff recommendations in Section IV. Practices compared to the SDDS are summarized in Appendix I. The authorities’ response to this report and a volume of detailed assessments are presented in separate documents.

II. Assessment by Agency and Dataset

11. Assessment of the quality of six macroeconomic datasets—national accounts, consumer price index, producer price index, government finance, monetary, and balance of payments statistics—were conducted using the DQAF July 2003. In this section, the results are presented at the level of the DQAF elements and using a four-point rating scale (Table 1). Assessments of the prerequisites of data quality and the assurances of integrity (Dimensions “0” and “1” of the DQAF) are presented in Tables 2a—c. For each dataset, the assessment of methodological soundness, accuracy and reliability, serviceability, and accessibility (Dimensions “2” to “5” of the DQAF) are shown in Tables 3a—f.

Table 1.

Russia Data Quality Assessment Framework—Summary Results

Practice observed: Current practices generally meet or achieve the objectives of DQAF internationally accepted statistical practices without any significant deficiencies. Practice largely observed: Some departures, but these are not seen as sufficient to raise doubts about the authorities’ ability to observe the DQAF practices. Practice largely not observed: Significant departures and the authorities will need to take significant action to achieve observance. Practice not observed: Most DQAF practices are not met. Not applicable: Used only exceptionally when statistical practices do not apply to a country’s circumstances.

Table 1.

Russia Data Quality Assessment Framework—Summary Results

Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable
Datasets		National Accounts	Consumer Price Index	Producer Price Index	Government Finance statistics	Monetary statistics	Balance of Payments statistics
Dimensions/Elements		National Accounts	Consumer Price Index	Producer Price Index	Government Finance statistics	Monetary statistics	Balance of Payments statistics
0. Prerequisites of quality
0.1	Legal and institutional environment	O	O	O	O	O	O
0.2	Resources	LO	O	O	O	O	O
0.3	Relevance	LO	O	LO	LO	O	O
0.4	Other quality management	O	O	O	O	O	O
1. Assurances of integrity
1.1	Professionalism	LNO	LNO	LNO	O	O	O
1.2	Transparency	O	O	LO	O	O	O
1.3	Ethical standards	O	O	O	O	O	O
2. Methodological soundness
2.1	Concepts and definitions	O	O	O	LO	O	O
2.2	Scope	LO	LO	LO	LNO	O	O
2.3	Classification/sectorization	O	LNO	O	LO	LO	O
2.4	Basis for recording	O	O	O	O	LO	LO
3. Accuracy and reliability
3.1	Source data	O	O	O	O	O	LO
3.2	Assessment of source data	O	O	O	O	O	O
3.3	Statistical techniques	LO	O	O	LO	O	O
3.4	Assessment and validation of intermediate data and statistical outputs	O	O	O	O	O	O
3.5	Revision studies	LO	O	O	O	O	O
4. Serviceability
4.1	Periodicity and timeliness	O	O	O	LO	O	O
4.2	Consistency	O	O	O	LO	O	O
4.3	Revision policy and practice	LO	O	O	NA	O	O
5. Accessibility
5.1	Data accessibility	O	LO	LO	LNO	O	O
5.2	Metadata accessibility	O	O	O	LO	O	O
5.3	Assistance to users	O	O	O	LNO	O	O

Table 1.

Russia Data Quality Assessment Framework—Summary Results

Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable
Datasets		National Accounts	Consumer Price Index	Producer Price Index	Government Finance statistics	Monetary statistics	Balance of Payments statistics
Dimensions/Elements		National Accounts	Consumer Price Index	Producer Price Index	Government Finance statistics	Monetary statistics	Balance of Payments statistics
0. Prerequisites of quality
0.1	Legal and institutional environment	O	O	O	O	O	O
0.2	Resources	LO	O	O	O	O	O
0.3	Relevance	LO	O	LO	LO	O	O
0.4	Other quality management	O	O	O	O	O	O
1. Assurances of integrity
1.1	Professionalism	LNO	LNO	LNO	O	O	O
1.2	Transparency	O	O	LO	O	O	O
1.3	Ethical standards	O	O	O	O	O	O
2. Methodological soundness
2.1	Concepts and definitions	O	O	O	LO	O	O
2.2	Scope	LO	LO	LO	LNO	O	O
2.3	Classification/sectorization	O	LNO	O	LO	LO	O
2.4	Basis for recording	O	O	O	O	LO	LO
3. Accuracy and reliability
3.1	Source data	O	O	O	O	O	LO
3.2	Assessment of source data	O	O	O	O	O	O
3.3	Statistical techniques	LO	O	O	LO	O	O
3.4	Assessment and validation of intermediate data and statistical outputs	O	O	O	O	O	O
3.5	Revision studies	LO	O	O	O	O	O
4. Serviceability
4.1	Periodicity and timeliness	O	O	O	LO	O	O
4.2	Consistency	O	O	O	LO	O	O
4.3	Revision policy and practice	LO	O	O	NA	O	O
5. Accessibility
5.1	Data accessibility	O	LO	LO	LNO	O	O
5.2	Metadata accessibility	O	O	O	LO	O	O
5.3	Assistance to users	O	O	O	LNO	O	O

Table 2a.

Russia Assessment of Data Quality—Dimensions 0 and 1—Federal State Statistics Service

Table 2a.

Russia Assessment of Data Quality—Dimensions 0 and 1—Federal State Statistics Service

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The Rosstat is the official body entrusted by law for coordinating and overseeing the production and dissemination of the official statistics of the country. Significant and important changes in the legal framework of the Russian Federation Statistical System have taken place since the 2003 ROSC mission. Though the Rosstat’s authority is mandated through various pieces of legislation, the most critical pieces of legislation are the resolution No. 420 of the Russian Federation, Provisions on the Federal State Statistics Service, issued on June 2, 2008 and the Federal Law No. 282 F3, On Official Statistical Accounting and State Statistics System in the Russian Federation, issued on November 29, 2007. The latter document is in compliance with recommended legal frameworks for the regulation of countries’ statistical systems as advised by Eurostat, the United Nations, and the World Bank. This Law and other legal statutes provide assurances of confidentiality to data collected for statistical purposes. According to the Law, all official statistical activities shall be exercised in compliance of the Federal Plans of Statistical Operations to be prepared by the Rosstat in consultation with all other Federal agencies producing statistics. The plan assigns responsibility for compiling and disseminating the official statistics and includes detailed information describing the statistics to be compiled, their periodicity, and the dissemination deadlines.

Resources. The Rosstat expressed concern with difficulties recruiting and retaining young professionals due to low salaries, which could affect future work. The number of staff available for compiling the national accounts is inadequate to implement the regular work program, thus implying a serious constraint for undertaking developmental work. Price statistics staff are sufficient to support monthly compilation activities. Both the national accounts and price statistics programs have adequate financial and computing resources to support data compilation. Physical resources are currently under renovation.

Relevance. The Rosstat does not conduct user surveys but consultations with users of the CPI are conducted. The Scientific and Methodological Council provides a structured venue for consulting on the usefulness/quality of existing statistics and to discuss emerging data requirements and the implementation of methodological improvements. Members of this group include economists and statisticians from inside and outside of the Rosstat, as well as members representing major data users including other government ministries and trade unions.

Other quality management. Within the Rosstat, processes are in place to ensure the production of quality products. A written manual, detailing the data quality procedures of Rosstat, serves as a reference and guide for all staff.

Professionalism. Rosstat is subordinated to the Ministry of Economic Development. Statistics are produced on an impartial basis; however, the adoption of new methodologies requires the approval of the Ministry’s technical staff. This undermines the technical independence of Rosstat.

Transparency. PPI weights are not published. The relevant legal documents are posted on the website of the Rosstat. Products of the Rosstat are clearly identified as such. Significant changes in the methodology are announced to the general public in advance. There is no prior access by government officials to data before their release.

Ethical standards. Staff are made aware of the code of conduct to be observed during employment. The commitment to the observance of the codes has to be signed by employees at the time of accepting the terms and conditions of employment and anytime a new contract is issued due to changes in positions within the organization. A strong culture of professionalism and ethical standards precludes political interference.

Table 2a.

Russia Assessment of Data Quality—Dimensions 0 and 1—Federal State Statistics Service

0. Prerequisites of quality

1. Assurances of integrity

Table 2b.

Russia Assessment of Data Quality—Dimensions 0 and 1—Ministry of Finance

Table 2b.

Russia Assessment of Data Quality—Dimensions 0 and 1—Ministry of Finance

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The responsibility for compiling and disseminating budget execution data and GFS are clearly specified in laws and regulations. Only budget execution data are disseminated domestically; GFS are also compiled but are only reported to the IMF. The task of compiling and disseminating budget execution data and GFS is assigned to various MOF and Treasury units, and there is close communication among these units.

The confidentiality of information is protected by law. There are adequate legal and administrative provisions for collecting the information necessary for the compilation of budget execution reports and GFS.

Resources. The human, physical, and computer resources allocated to compiling budget execution data and GFS are adequate.

Relevance. The budget execution data and GFS compiled by the Treasury are the main sources of information for the design, monitoring, and assessment of tax and budget policy. There are no systematic arrangements in place to obtain feedback from external users of fiscal statistics.

Other quality management. The MOF and Treasury are fully aware of the importance of the quality of data, which is regularly emphasized by management. Particular attention is placed on the quality of accounting data. Formal processes to monitor the quality of data exist. A program for budget reform is well advanced, and includes changing accounting standards and procedures to meet international standards and best practice.

Professionalism. Independence in the compilation and dissemination of budget execution data is not supported by specific laws. However, an MOF executive order establishes the functions, responsibilities, and rights of the compiling units. It also establishes that fiscal statistics are to be based on accounting data and must be compiled in accordance with international standards.

Statisticians are free of political influence in the choice of the most appropriate data sources and methods, as well as statistical procedures, for compiling budget execution data and GFS.

Compilers are authorized to provide expert advice on technical aspects of budget execution reports. Press releases are issued in cases of misinterpretation of data by external users.

Transparency. The laws and regulations governing the compilation and dissemination of budget execution data and GFS are available to the public. No official or public agency outside of the MOF and the Treasury has access to budget execution data and GFS prior to their general dissemination. Budget execution data are released simultaneously to the general public, through the MOF’s and the Treasury’s websites.

The tables disseminated by the MOF and the Treasury identify the department responsible for their compilation. The tables disseminated by other agencies identify their source.

Ethical standards. The compilation and dissemination of budget execution data and GFS are governed by the provisions of legislation that establish standards of behavior. The staff is reminded periodically of the provisions of the legislation.

Table 2b.

Russia Assessment of Data Quality—Dimensions 0 and 1—Ministry of Finance

0. Prerequisites of quality

1. Assurances of integrity

Table 2c.

Russia Assessment of Data Quality—Dimensions 0 and 1—Central Bank of the Russian Federation

Table 2c.

Russia Assessment of Data Quality—Dimensions 0 and 1—Central Bank of the Russian Federation

0. Prerequisites of quality

1. Assurances of integrity

Legal and institutional environment. The CBR has the necessary legal mandate to collect, compile, and disseminate monetary and balance of payments statistics. The basis for this mandate is in the Constitution of Russia Federation and the Federal Law on the Central Bank of Russia (July 10, 2002, with amendments). Credit institutions are required to report to the CBR the necessary information on their activity, including accounting and statistical reports, as established by the CBR in accordance with the Federal Law on Banks and Banking Activity (December 2, 1990, with amendments). Statistical reporting is ensured through legal mandates, clear instructions for reporting, and efforts to reduce reporting burden. The Federal Law On Information, Information Technology, and Protection of Information of July 27, 2006 establishes requirements for protection of information, confidentiality, and penalties for infraction of the federal laws. Specific requirements for maintaining confidentiality of the individual reporter’s data are stipulated in the Federal Law on the Central Bank of Russia and Federal Law on Banks and Banking Activity. Data sharing and coordination within the CBR and with other official data producing agencies is effective; organization of information flows is documented in internal guidelines and in agreements with other agencies.

Resources. Staff, financial, and computing resources are adequate to carry out the CBR’s current statistical programs and plans. Staff engaged in statistical compilation programs have attended courses organized by IMF and participate in seminars conducted by other central banks and international organizations. Various measures are in place for fostering efficiency in the use of resources.

Relevance. The relevance of monetary statistics in meeting users’ needs is assessed through regular consultations with CBR departments involved in implementing monetary policy. Several fora for nongovernment users of monetary statistics enable them to express views on data dissemination (in terms of content and format), and a user survey is posted on the CBR’s website for both monetary and international accounts statistics.

Other quality management. Quality awareness at the CBR is at a high level. Internal and external audits underpin compliance with accounting regulations. The outputs of statistical programs undergo quality reviews by CBR senior management. Reported information is subject to validation checks at the collection and processing stages and a follow-up as called for. Timeliness of information is considered vital and, as necessary, estimates/preliminary data are disseminated.

Professionalism. Compilation of statistics, in terms of choice of data sources, methodology, and statistical techniques, reflects statistical considerations only and is supported by legal provisions. Professionalism of staff engaged in statistical compilation activities at the CBR is high. Hiring and promotion policies are based on the principle of professional competence, as reflected in CBR Provision 235P of July 25, 2003 (with amendments) and the Model Qualification Standards of Staff of the Central Bank of Russia. Staff actively participate in international working groups (e.g., the IMF’s Committee on Balance of Payments Statistics and the Experts Group to Review the MFSM 2000) and attend conferences. The CBR conducts regional training programs in external sector statistics and MFS. The CBR tracks the use of its data in the media. Cases of misinterpretation or misuse are brought to the attention of the publisher with a request to make appropriate corrections in its publication.

Transparency. The terms and conditions under which statistical work is undertaken are clearly stated in the CBR’s publications, including its website. There is no government access to the data prior to their release and release of data is not accompanied by ministerial commentary. The CBR General Economic Department’s responsibility for compiling statistics is clearly stated. Statistics included in CBR’s publications but compiled by other agencies carry appropriate attribution. Major changes in monetary statistics methodology are announced in advance in a press release posted on the CBR’s website. Advance notice of major changes in balance of payments methodology and source data are also provided. The CBR has already informed users of plans to implement BPM6 by end-2012.

Ethical standards. Rules of ethical conduct for the CBR staff are set out in the CBR Provision 235P (July 25, 2003, with amendments). Articles 90–92 of the Federal Law On the Central Bank of the Russian Federation regulate the range of activities that CBR staff may undertake so as to rule out conflict of interest.

Table 2c.

Russia Assessment of Data Quality—Dimensions 0 and 1—Central Bank of the Russian Federation

0. Prerequisites of quality

1. Assurances of integrity

Table 3a.

Russia Assessment of Data Quality—Dimensions 2 to 5—National Accounts

Table 3a.

Russia Assessment of Data Quality—Dimensions 2 to 5—National Accounts

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Russian national accounts statistics are compiled based on the 1993 SNA conceptual framework. Scope. The output of illegal activities is not in the scope of the Russian national accounts. The sequence of accounts from the production account and up to the capital account is compiled annually for the total economy and by institutional sector. Annual supply and use tables are compiled. Quarterly GDP is calculated based on the production and the expenditure approaches both at current prices and as volume measures (reference period = 2003). The delimitation of the units that form part of the economy, the production boundary, and the assets boundary, are broadly in accordance with the 1993 SNA guidelines. Classification/sectorization. Russian national accounts use the 1993 SNA classification of transactions, flows and institutional sectors. The classifications of economic activities, as well as the classification of products, are both based on the corresponding classifications used by the European Community (NACE Rev. 2, and CPA [Classification of Products by Activity], respectively). The household budget survey (HBS) is classified based on the internationally recommended classification—COICOP—but estimates of household consumption are still based on a national classification, although there are plans to introduce the COICOP classification with the dissemination of a revised series of national accounts in August 2010. General government consumption expenditure is classified using the Classification of the Functions of Government categories. Basis for recording. Most transactions are recorded on an accrual basis. Government data, available on a cash basis at the source, are adjusted to the accrual time of recording concept of the national accounts. Valuation principles used are in line with the 1993 SNA.	Source data. Source data are quite comprehensive. There are regular quarterly reports from enterprises, government records, primary data from the agriculture sector, and administrative records. Enterprise surveys cover all economic activities and have national representation. Large- and medium-sized enterprises are surveyed on a census basis, while small enterprises surveys are based on random samples. Although annual and quarterly HBS are conducted regularly, their results have limited use in the compilation of household consumption expenditure, which is mainly based on retail trade data and surveys on enterprises providing services to households. The enterprise surveys also collect data on investment on fixed assets and inventories (also available from annual balance sheets) and data on exports and imports of goods and services are available from the balance of payments statistics. Assessment of source data. Sampling errors and non-sampling errors are routinely assessed and appropriate techniques are used to deal with problems of non-response, which mainly affect the samples of small enterprises. Data are also checked for errors and inconsistencies through the use of a range of automated checks. Statistical techniques. The quarterly production accounts now are compiled at highly disaggregated levels of the industrial classification (for 148 main activities and 312 “pure” activities of the industrial classification). Output of the services of owner-occupied dwellings is not estimated in accordance with internationally recommended methodology. Estimates of volume measures are in general based on adequate methods although improvements are needed in the compilation of trade margins, taxes and subsidies on products, general government consumption, and changes in inventories. Quarterly deflators of imports and exports of services need improvements. Techniques to achieve consistency between quarterly and annual data are not adequate. Assessment and validation of intermediate data and statistical outputs. Output data derived from enterprise surveys are assessed against data on output from other primary and secondary sources, including data from the HBS. Consistency between data on GDP based on different approaches is achieved during the compilation of the annual supply and use tables. Revision studies. Rosstat does not conduct systematic revision studies. Data are normally revised only for the last two years. Revisions to the published figures are explained at the time the data are released. Less frequent revisions imply that changes of the historical series are thoroughly reviewed before the figures are released. Also, explanations disseminated with historical revisions of the series are more detailed than for regular revisions.	Periodicity and timeliness. Normally, the first quarterly GDP estimates are disseminated 80 days after the end of the reference quarter, thus meeting the timeliness and periodicity requirements of the SDDS. An exception occurred in the second quarter of 2009 for which quarterly GDP data were not released on time. Consistency. Discrepancies between the independent estimates of GDP by production and expenditure are kept at reasonably low levels. National accounts series based on the same methodology are available from the data related to 1995 (series of GDP by production are based on the same classification only from the data of 2003). For chain-linked volume measures, the discrepancy between the total and the sum of the components has become significant, which may require a change of the reference period. Revision policy and practice. Russia has in practice a clearly defined revision policy, but no revisions of the quarters of the current year are introduced before March of the following year. This practice poses difficulties and confusion to users as it introduces temporary inconsistencies between the national accounts and some of the source data subject to more frequent revisions. Quarters of previous years become final in the third year after the reference year.	Data accessibility. Long-term series of quarterly GDP in nominal and volume measures are posted on the Rosstat’s website. The data are readily accessible in Excel format. The English language version of the Rosstat website contains less information than the Russian site and is updated less frequently. Metadata accessibility. A document is available on sources and methods for compiling the national accounts statistics, but only in Russian and in hardcopy. In addition, notes in the publications and on the website explain the national accounts concepts and methodology used. Discrepancies with the international standards are noted in the metadata. Assistance to users. Detailed contact information is provided in the publications and on the website. A catalog of publications is available on the website and updated annually. Information is also provided on how to obtain the publications.

Table 3a.

Russia Assessment of Data Quality—Dimensions 2 to 5—National Accounts

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Russian national accounts statistics are compiled based on the 1993 SNA conceptual framework. Scope. The output of illegal activities is not in the scope of the Russian national accounts. The sequence of accounts from the production account and up to the capital account is compiled annually for the total economy and by institutional sector. Annual supply and use tables are compiled. Quarterly GDP is calculated based on the production and the expenditure approaches both at current prices and as volume measures (reference period = 2003). The delimitation of the units that form part of the economy, the production boundary, and the assets boundary, are broadly in accordance with the 1993 SNA guidelines. Classification/sectorization. Russian national accounts use the 1993 SNA classification of transactions, flows and institutional sectors. The classifications of economic activities, as well as the classification of products, are both based on the corresponding classifications used by the European Community (NACE Rev. 2, and CPA [Classification of Products by Activity], respectively). The household budget survey (HBS) is classified based on the internationally recommended classification—COICOP—but estimates of household consumption are still based on a national classification, although there are plans to introduce the COICOP classification with the dissemination of a revised series of national accounts in August 2010. General government consumption expenditure is classified using the Classification of the Functions of Government categories. Basis for recording. Most transactions are recorded on an accrual basis. Government data, available on a cash basis at the source, are adjusted to the accrual time of recording concept of the national accounts. Valuation principles used are in line with the 1993 SNA.	Source data. Source data are quite comprehensive. There are regular quarterly reports from enterprises, government records, primary data from the agriculture sector, and administrative records. Enterprise surveys cover all economic activities and have national representation. Large- and medium-sized enterprises are surveyed on a census basis, while small enterprises surveys are based on random samples. Although annual and quarterly HBS are conducted regularly, their results have limited use in the compilation of household consumption expenditure, which is mainly based on retail trade data and surveys on enterprises providing services to households. The enterprise surveys also collect data on investment on fixed assets and inventories (also available from annual balance sheets) and data on exports and imports of goods and services are available from the balance of payments statistics. Assessment of source data. Sampling errors and non-sampling errors are routinely assessed and appropriate techniques are used to deal with problems of non-response, which mainly affect the samples of small enterprises. Data are also checked for errors and inconsistencies through the use of a range of automated checks. Statistical techniques. The quarterly production accounts now are compiled at highly disaggregated levels of the industrial classification (for 148 main activities and 312 “pure” activities of the industrial classification). Output of the services of owner-occupied dwellings is not estimated in accordance with internationally recommended methodology. Estimates of volume measures are in general based on adequate methods although improvements are needed in the compilation of trade margins, taxes and subsidies on products, general government consumption, and changes in inventories. Quarterly deflators of imports and exports of services need improvements. Techniques to achieve consistency between quarterly and annual data are not adequate. Assessment and validation of intermediate data and statistical outputs. Output data derived from enterprise surveys are assessed against data on output from other primary and secondary sources, including data from the HBS. Consistency between data on GDP based on different approaches is achieved during the compilation of the annual supply and use tables. Revision studies. Rosstat does not conduct systematic revision studies. Data are normally revised only for the last two years. Revisions to the published figures are explained at the time the data are released. Less frequent revisions imply that changes of the historical series are thoroughly reviewed before the figures are released. Also, explanations disseminated with historical revisions of the series are more detailed than for regular revisions.	Periodicity and timeliness. Normally, the first quarterly GDP estimates are disseminated 80 days after the end of the reference quarter, thus meeting the timeliness and periodicity requirements of the SDDS. An exception occurred in the second quarter of 2009 for which quarterly GDP data were not released on time. Consistency. Discrepancies between the independent estimates of GDP by production and expenditure are kept at reasonably low levels. National accounts series based on the same methodology are available from the data related to 1995 (series of GDP by production are based on the same classification only from the data of 2003). For chain-linked volume measures, the discrepancy between the total and the sum of the components has become significant, which may require a change of the reference period. Revision policy and practice. Russia has in practice a clearly defined revision policy, but no revisions of the quarters of the current year are introduced before March of the following year. This practice poses difficulties and confusion to users as it introduces temporary inconsistencies between the national accounts and some of the source data subject to more frequent revisions. Quarters of previous years become final in the third year after the reference year.	Data accessibility. Long-term series of quarterly GDP in nominal and volume measures are posted on the Rosstat’s website. The data are readily accessible in Excel format. The English language version of the Rosstat website contains less information than the Russian site and is updated less frequently. Metadata accessibility. A document is available on sources and methods for compiling the national accounts statistics, but only in Russian and in hardcopy. In addition, notes in the publications and on the website explain the national accounts concepts and methodology used. Discrepancies with the international standards are noted in the metadata. Assistance to users. Detailed contact information is provided in the publications and on the website. A catalog of publications is available on the website and updated annually. Information is also provided on how to obtain the publications.

Table 3b.

Russia Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index

Table 3b.

Russia Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Generally, the concepts and definitions used in CPI compilation reflect international standards and best practices promoted in the CPI manual, CPI handbook, and 1993 SNA. Scope. Owner-occupied housing has been excluded from the CPI. The CPI represents all households in Russia. The CPI measures the change over time in prices of a fixed basket of goods and services representative of households residing in all areas throughout the Russian Federation. Classification/sectorization. The CPI is classified according to the All-Russian Classification of Products and not the internationally recommended COICOP. The Ministry of Economic Development denied Rosstat’s request to implement COICOP in 2008. Basis for recording. The prices used to calculate the CPI correspond to market prices paid by consumers (deducting discounts and rebates, and including all applicable taxes levied—VAT, excise, sales tax, and other indirect taxes).	Source data. The items and weights for the CPI market basket are derived from HBS data collected on an annual basis from 48,700 private households of all socioeconomic groups. Approximately 560,000 prices are collected each month from over 50,000 outlets in 266 urban areas. Assessment of source data. Price and product specification data collected for the monthly price survey as well as expenditure data collected for the HBS are verified and processed using internationally recommended procedures. Statistical techniques. All missing prices (including seasonal items) are imputed using observed price changes of other varieties in the same group. Replacement items and or varieties are introduced as needed. Quality adjustments are made using the overlap method wherever possible. Elementary aggregates are calculated using geometric means. Upper-level aggregates are calculated using the Two-Stage (Modified) Lasperyes. Assessment and validation of intermediate data and statistical outputs. Intermediate data are validated as needed. Revision studies. The CPI is final when first released. Studies are conducted to assess the effect of weight revisions and substitution on the index.	Periodicity and timeliness. The CPI is published on a monthly basis on the fourth and sixth workday after the end of the month, meeting SDDS requirements. An Express Release is issued on the fourth workday, while detailed data are available on the sixth workday. Consistency. The CPI is internally consistent. Revision policy and practice. The CPI is final upon its first release. The market basket items and weights are updated on an annual basis, with revised weights introduced in January of each year. Revisions to weights and methodologies are explained to users.	Data accessibility. Detailed time series data are not produced. Data are disseminated monthly in detail through various monthly publications and by electronic means (website, diskette, CD-ROM, and e-mail). The English language Rosstat website contains less content than the Russian site, and is updated less frequently. To meet SDDS specifications, a continuous index series on a common reference base (2000 = 100) is produced for the All Items index at the national level only. Time series data are not produced at a detailed level. Metadata accessibility. Detailed descriptions of the CPI metadata are available to users through the Rosstat website or by request in hardcopy. Assistance to users. Publications clearly identify how users can obtain additional details. A detailed list of staff contacts, telephone numbers, and e-mail addresses is available on the Rosstat website. A call center directs users on how to obtain additional information. The Rosstat operates a public bookstore and users can access a library of publications on the first floor of the headquarters in Moscow.

Table 3b.

Russia Assessment of Data Quality—Dimensions 2 to 5—Consumer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Generally, the concepts and definitions used in CPI compilation reflect international standards and best practices promoted in the CPI manual, CPI handbook, and 1993 SNA. Scope. Owner-occupied housing has been excluded from the CPI. The CPI represents all households in Russia. The CPI measures the change over time in prices of a fixed basket of goods and services representative of households residing in all areas throughout the Russian Federation. Classification/sectorization. The CPI is classified according to the All-Russian Classification of Products and not the internationally recommended COICOP. The Ministry of Economic Development denied Rosstat’s request to implement COICOP in 2008. Basis for recording. The prices used to calculate the CPI correspond to market prices paid by consumers (deducting discounts and rebates, and including all applicable taxes levied—VAT, excise, sales tax, and other indirect taxes).	Source data. The items and weights for the CPI market basket are derived from HBS data collected on an annual basis from 48,700 private households of all socioeconomic groups. Approximately 560,000 prices are collected each month from over 50,000 outlets in 266 urban areas. Assessment of source data. Price and product specification data collected for the monthly price survey as well as expenditure data collected for the HBS are verified and processed using internationally recommended procedures. Statistical techniques. All missing prices (including seasonal items) are imputed using observed price changes of other varieties in the same group. Replacement items and or varieties are introduced as needed. Quality adjustments are made using the overlap method wherever possible. Elementary aggregates are calculated using geometric means. Upper-level aggregates are calculated using the Two-Stage (Modified) Lasperyes. Assessment and validation of intermediate data and statistical outputs. Intermediate data are validated as needed. Revision studies. The CPI is final when first released. Studies are conducted to assess the effect of weight revisions and substitution on the index.	Periodicity and timeliness. The CPI is published on a monthly basis on the fourth and sixth workday after the end of the month, meeting SDDS requirements. An Express Release is issued on the fourth workday, while detailed data are available on the sixth workday. Consistency. The CPI is internally consistent. Revision policy and practice. The CPI is final upon its first release. The market basket items and weights are updated on an annual basis, with revised weights introduced in January of each year. Revisions to weights and methodologies are explained to users.	Data accessibility. Detailed time series data are not produced. Data are disseminated monthly in detail through various monthly publications and by electronic means (website, diskette, CD-ROM, and e-mail). The English language Rosstat website contains less content than the Russian site, and is updated less frequently. To meet SDDS specifications, a continuous index series on a common reference base (2000 = 100) is produced for the All Items index at the national level only. Time series data are not produced at a detailed level. Metadata accessibility. Detailed descriptions of the CPI metadata are available to users through the Rosstat website or by request in hardcopy. Assistance to users. Publications clearly identify how users can obtain additional details. A detailed list of staff contacts, telephone numbers, and e-mail addresses is available on the Rosstat website. A call center directs users on how to obtain additional information. The Rosstat operates a public bookstore and users can access a library of publications on the first floor of the headquarters in Moscow.

Table 3c.

Russia Assessment of Data Quality—Dimensions 2 to 5—Producer Price Index

Table 3c.

Russia Assessment of Data Quality—Dimensions 2 to 5—Producer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Generally, the concepts and definitions used in PPI compilation reflect international standards and best practices in the PPI manual and 1993 SNA. Scope. Production of export goods is not included in the PPI as recommended by the PPI Manual. The PPI covers all of the industries in mining, manufacturing, and utilities (electricity, gas, and water). The index covers goods manufactured in the Russian Federation that are sold on the domestic market. Classification/sectorization. In accordance with international recommendations, economic activities are classified using NACE Rev. 1.1, and products are classified using CPA. Basis for recording. Factory gate prices are obtained from a monthly survey of producers, which do not include taxes, transportation costs, insurance fees, and trade margins. Actual prices charged by producers are determined for a specific product and not for unit values.	Source data. The weights are based on the value of sales at current prices as reported by respondents in annual industry surveys. Representative products for pricing are selected by PPI staff at headquarters and supplemented by regional authorities. Approximately 30,000 prices are collected each month from 8,500 establishments. Assessment of source data. The source data on prices are constantly reviewed by the compilers for consistency over time and with related products. Statistical techniques. All missing prices (including seasonal items) are imputed using observed price changes of other varieties in the same group. Replacement items and/or varieties are introduced as needed. Quality adjustments are made using the overlap method wherever possible. Elementary aggregates are calculated using geometric means. Upper-level aggregates are calculated using the Two-Stage (Modified) Lasperyes. Assessment and validation of intermediate data and statistical outputs. PPI index data are validated by comparing these data with corresponding index data from the CPI. Revision studies. Studies are conducted to assess the magnitude of change between preliminary and final PPI data. Studies are also conducted on the effect of weight revisions and substitution on the index.	Periodicity and timeliness. The monthly PPI is disseminated within 10 days after the end of the reference month, thus exceeding SDDS requirements. Consistency. Checks are made with the relevant elements of the CPI to ensure the two series are consistent. Revision policy and practice. PPI data are provisional when first released. All data are noted as provisional and subject to revision. Data can be revised up to the end of December of the current year. All data are final in January of the following year. Revised data are footnoted and explained	Data accessibility. Detailed PPI weight data are not published. International best practices recommend that detailed weight data (current and historic) should be published and made available to all users. Data are disseminated monthly in detail through various monthly publications and by electronic means (website, diskette, CD-ROM, and e-mail). The English-language Rosstat website contains less content than the Russian site and is updated less frequently. To meet SDDS specifications, a continuous index series on a common reference base (2000 = 100) is produced for the All Items index at the national level only. Time series data are not produced at a detailed level. Metadata accessibility. Detailed descriptions of the CPI metadata are available to users through the Rosstat website or by request in hardcopy. Assistance to users. Publications clearly identify how users can obtain additional details. A detailed list of staff contacts, telephone numbers, and e-mail addresses is available on the Rosstat website. A call center directs users on how to obtain additional information. The Rosstat operates a public bookstore and users can access a library of publications on the first floor of the headquarters.

Table 3c.

Russia Assessment of Data Quality—Dimensions 2 to 5—Producer Price Index

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Generally, the concepts and definitions used in PPI compilation reflect international standards and best practices in the PPI manual and 1993 SNA. Scope. Production of export goods is not included in the PPI as recommended by the PPI Manual. The PPI covers all of the industries in mining, manufacturing, and utilities (electricity, gas, and water). The index covers goods manufactured in the Russian Federation that are sold on the domestic market. Classification/sectorization. In accordance with international recommendations, economic activities are classified using NACE Rev. 1.1, and products are classified using CPA. Basis for recording. Factory gate prices are obtained from a monthly survey of producers, which do not include taxes, transportation costs, insurance fees, and trade margins. Actual prices charged by producers are determined for a specific product and not for unit values.	Source data. The weights are based on the value of sales at current prices as reported by respondents in annual industry surveys. Representative products for pricing are selected by PPI staff at headquarters and supplemented by regional authorities. Approximately 30,000 prices are collected each month from 8,500 establishments. Assessment of source data. The source data on prices are constantly reviewed by the compilers for consistency over time and with related products. Statistical techniques. All missing prices (including seasonal items) are imputed using observed price changes of other varieties in the same group. Replacement items and/or varieties are introduced as needed. Quality adjustments are made using the overlap method wherever possible. Elementary aggregates are calculated using geometric means. Upper-level aggregates are calculated using the Two-Stage (Modified) Lasperyes. Assessment and validation of intermediate data and statistical outputs. PPI index data are validated by comparing these data with corresponding index data from the CPI. Revision studies. Studies are conducted to assess the magnitude of change between preliminary and final PPI data. Studies are also conducted on the effect of weight revisions and substitution on the index.	Periodicity and timeliness. The monthly PPI is disseminated within 10 days after the end of the reference month, thus exceeding SDDS requirements. Consistency. Checks are made with the relevant elements of the CPI to ensure the two series are consistent. Revision policy and practice. PPI data are provisional when first released. All data are noted as provisional and subject to revision. Data can be revised up to the end of December of the current year. All data are final in January of the following year. Revised data are footnoted and explained	Data accessibility. Detailed PPI weight data are not published. International best practices recommend that detailed weight data (current and historic) should be published and made available to all users. Data are disseminated monthly in detail through various monthly publications and by electronic means (website, diskette, CD-ROM, and e-mail). The English-language Rosstat website contains less content than the Russian site and is updated less frequently. To meet SDDS specifications, a continuous index series on a common reference base (2000 = 100) is produced for the All Items index at the national level only. Time series data are not produced at a detailed level. Metadata accessibility. Detailed descriptions of the CPI metadata are available to users through the Rosstat website or by request in hardcopy. Assistance to users. Publications clearly identify how users can obtain additional details. A detailed list of staff contacts, telephone numbers, and e-mail addresses is available on the Rosstat website. A call center directs users on how to obtain additional information. The Rosstat operates a public bookstore and users can access a library of publications on the first floor of the headquarters.

Table 3d.

Russia Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics

Table 3d.

Russia Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Budget execution data are compiled in accordance with national concepts and definitions, which can be linked to those of the GFSM 2001. The GFS reported to the IMF are compiled in accordance with the guidelines of the GFSM 2001. Scope. There are monthly and annual cash based budget execution reports for the general government and its subsectors, but not for the consolidated central government. Information on expenditures by economic classification is compiled monthly (cash basis) but only disseminated in an annual report on an accrual basis. Debt is classified by currency in accordance with budget legislation and not by residency. Classification/sectorization. The budget classifications for revenues, expenditures, financing, and debt follow national concepts and definitions. The data can be converted to GFSM 2001 format, but this requires knowledge of the methodology and access to some information not publicly available. Basis for recording. Transactions are recorded on a modified cash basis.	Source data. Comprehensive and timely source data covering the full range of flows and stocks are provided from administrative and accounting systems for all levels of government. Assessment of source data. There are no material gaps in the coverage or completeness of data collection. The accuracy of accounting data is continuously assessed. Statistical techniques. Errors are corrected in the period detected, not in the period they took place. Consolidation does not follow the GFSM 2001 approach. Assessment and validation of intermediate data and statistical outputs. The information reported by general government units is cross-checked with bank statements and other information in a regular manner. Revision studies. There are no revisions to budget execution data and GFS, because they are based on final data. Revisions to final budget execution data are rare, and occur only when an accounting error is detected. No studies of revisions are needed.	Periodicity and timeliness. The periodicity and timeliness of fiscal statistics meet or exceed SDDS requirements, except for the timeliness of statistics on central government operations for which a flexibility option is taken. Consistency. There is full consistency in budget execution data and GFS within the dataset, but not over time. Previous series are not adjusted to account for discontinuities. Budget execution data and GFS are consistent with other macroeconomic datasets at the source data level, but should also be reconciled at the output level. Revision policy and practice. The dissemination of the statistics follows a regular cycle known to users, and in several cases follows a schedule established by law. No studies of revisions are conducted because data are not revised.	Data accessibility. Data on the MOF’s and the Treasury’s websites are difficult to access, and limited data are available in English. The budget execution data and GFS are presented in a way that allows major aggregates and balancing items to be identified and related to detailed underlying data. Metadata accessibility. Concepts, scope and classifications are only available from legislation; no methodological notes are posted on the MOF website. Methodological differences with internationally accepted standards are not identified. There is a link in the MOF website to SDDS metadata. Assistance to users. Assistance to users is limited. No contact person for budget execution data, or catalogue of statistical products and services. Only the contact person for SDDS data is publicized on the IMF’s DSBB.

Table 3d.

Russia Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. Budget execution data are compiled in accordance with national concepts and definitions, which can be linked to those of the GFSM 2001. The GFS reported to the IMF are compiled in accordance with the guidelines of the GFSM 2001. Scope. There are monthly and annual cash based budget execution reports for the general government and its subsectors, but not for the consolidated central government. Information on expenditures by economic classification is compiled monthly (cash basis) but only disseminated in an annual report on an accrual basis. Debt is classified by currency in accordance with budget legislation and not by residency. Classification/sectorization. The budget classifications for revenues, expenditures, financing, and debt follow national concepts and definitions. The data can be converted to GFSM 2001 format, but this requires knowledge of the methodology and access to some information not publicly available. Basis for recording. Transactions are recorded on a modified cash basis.	Source data. Comprehensive and timely source data covering the full range of flows and stocks are provided from administrative and accounting systems for all levels of government. Assessment of source data. There are no material gaps in the coverage or completeness of data collection. The accuracy of accounting data is continuously assessed. Statistical techniques. Errors are corrected in the period detected, not in the period they took place. Consolidation does not follow the GFSM 2001 approach. Assessment and validation of intermediate data and statistical outputs. The information reported by general government units is cross-checked with bank statements and other information in a regular manner. Revision studies. There are no revisions to budget execution data and GFS, because they are based on final data. Revisions to final budget execution data are rare, and occur only when an accounting error is detected. No studies of revisions are needed.	Periodicity and timeliness. The periodicity and timeliness of fiscal statistics meet or exceed SDDS requirements, except for the timeliness of statistics on central government operations for which a flexibility option is taken. Consistency. There is full consistency in budget execution data and GFS within the dataset, but not over time. Previous series are not adjusted to account for discontinuities. Budget execution data and GFS are consistent with other macroeconomic datasets at the source data level, but should also be reconciled at the output level. Revision policy and practice. The dissemination of the statistics follows a regular cycle known to users, and in several cases follows a schedule established by law. No studies of revisions are conducted because data are not revised.	Data accessibility. Data on the MOF’s and the Treasury’s websites are difficult to access, and limited data are available in English. The budget execution data and GFS are presented in a way that allows major aggregates and balancing items to be identified and related to detailed underlying data. Metadata accessibility. Concepts, scope and classifications are only available from legislation; no methodological notes are posted on the MOF website. Methodological differences with internationally accepted standards are not identified. There is a link in the MOF website to SDDS metadata. Assistance to users. Assistance to users is limited. No contact person for budget execution data, or catalogue of statistical products and services. Only the contact person for SDDS data is publicized on the IMF’s DSBB.

Table 3e.

Russia Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

Table 3e.

Russia Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The analytical framework used for compiling monetary statistics is consistent with MFSM 2000. Scope. The coverage of the depository corporations survey comprises monetary authorities (consolidation of the CBR accounts and the data on monetary authorities functions undertaken by the central government) and all other depository corporations (including those with revoked licenses). Classification/sectorization. Classification and sectorization is largely consistent with MFSM 2000, except for the following: (i) financial derivatives are excluded from monetary data; (ii) contra-entries to data on government’s monetary authorities’ functions are not separately identified; and (iii) the CBR’s current year result (profit/loss) and valuation adjustment accounts are misclassified. Basis for recording. The basis for recording largely follows MFSM 2000 recommendations except that securities held to maturity and shares in the investment portfolio are not valued at market price or fair value. Accrued interest is incorporated in the outstanding amount of financial asset or liability	Source data. Accounting records of the CBR, data on the monetary authority functions undertaken by central government, and the accounting statements reported to the CBR by credit institutions form the basis for monetary statistics. Data are available on a timely basis and with sufficient detail for compiling monetary accounts that meet MFSM 2000 recommendations. Assessment of source data. Automated and manual assessments and validations of source data, as well as of the statistical outputs, are performed. Data issues are investigated. Statistical techniques. Data compilation is fully automated to minimize processing errors. Assessment and validation of intermediate data and statistical outputs. Automated and manual assessment of intermediate data is performed. Procedures are in place to investigate discrepancies in the intermediate data, classification, and sectorization errors. Data issues are investigated. Revision studies. Monetary statistics are based on accounting records that are not subject to estimation. Revision studies are routinely undertaken to examine the cause and magnitude of differences between preliminary, revised, and final data. It has been found that such differences are relatively small.	Periodicity and timeliness. Data for the analytical accounts of monetary authorities and the analytical accounts of banking sector meet the SDDS requirements for periodicity and timeliness. Consistency. Statistics are largely consistent within the dataset. Consistency checks at the level of accounting data are routinely carried out with government finance data, international investment position, and the balance of payments data. Revision policy and practice. The revisions policy and practice for monetary statistics are made public. Preliminary data are clearly identified, and reasons for revisions if due to methodological changes are explained.	Data accessibility. Monetary statistics are disseminated through the CBR’s monthly Bulletin of Banking Statistics (BBS, available from the Publications page on the CBR’s website) and also, by specific survey type, in web-based printable and Excel file formats, retrievable from the Statistics/Monetary and Financial Statistics page on the CBR’s website. Monetary statistics are presented in clearly structured tables which, in BBS, are supplemented with charts and graphs. Data from the Statistics page can be retrieved for the various user-selectable periods. Monetary statistics are released simultaneously to all users in accordance with the advance release calendar. Unpublished but nonconfidential data are provided to users upon request with the CBR management’s approval. Metadata accessibility. Comprehensive methodological notes are published in BBS and on the Statistics page of the CBR’s website. A link to the IMF’s DSBB is also provided and is clearly identified on the CBR’s website. Assistance to users. A contact point is provided on the Statistics /Monetary and Financial Statistics page for sending questions to the General Economic Department concerning monetary data. (A user survey questionnaire is also posted there.) The BBS contains telephone number and e-mail address for such contact. The CBR website also identifies staff responsible for answering questions about SDDS data. Publications, documents, and unpublished but non-confidential data are provided free of charge. A list of publications is posted on the CBR’s website.

Table 3e.

Russia Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The analytical framework used for compiling monetary statistics is consistent with MFSM 2000. Scope. The coverage of the depository corporations survey comprises monetary authorities (consolidation of the CBR accounts and the data on monetary authorities functions undertaken by the central government) and all other depository corporations (including those with revoked licenses). Classification/sectorization. Classification and sectorization is largely consistent with MFSM 2000, except for the following: (i) financial derivatives are excluded from monetary data; (ii) contra-entries to data on government’s monetary authorities’ functions are not separately identified; and (iii) the CBR’s current year result (profit/loss) and valuation adjustment accounts are misclassified. Basis for recording. The basis for recording largely follows MFSM 2000 recommendations except that securities held to maturity and shares in the investment portfolio are not valued at market price or fair value. Accrued interest is incorporated in the outstanding amount of financial asset or liability	Source data. Accounting records of the CBR, data on the monetary authority functions undertaken by central government, and the accounting statements reported to the CBR by credit institutions form the basis for monetary statistics. Data are available on a timely basis and with sufficient detail for compiling monetary accounts that meet MFSM 2000 recommendations. Assessment of source data. Automated and manual assessments and validations of source data, as well as of the statistical outputs, are performed. Data issues are investigated. Statistical techniques. Data compilation is fully automated to minimize processing errors. Assessment and validation of intermediate data and statistical outputs. Automated and manual assessment of intermediate data is performed. Procedures are in place to investigate discrepancies in the intermediate data, classification, and sectorization errors. Data issues are investigated. Revision studies. Monetary statistics are based on accounting records that are not subject to estimation. Revision studies are routinely undertaken to examine the cause and magnitude of differences between preliminary, revised, and final data. It has been found that such differences are relatively small.	Periodicity and timeliness. Data for the analytical accounts of monetary authorities and the analytical accounts of banking sector meet the SDDS requirements for periodicity and timeliness. Consistency. Statistics are largely consistent within the dataset. Consistency checks at the level of accounting data are routinely carried out with government finance data, international investment position, and the balance of payments data. Revision policy and practice. The revisions policy and practice for monetary statistics are made public. Preliminary data are clearly identified, and reasons for revisions if due to methodological changes are explained.	Data accessibility. Monetary statistics are disseminated through the CBR’s monthly Bulletin of Banking Statistics (BBS, available from the Publications page on the CBR’s website) and also, by specific survey type, in web-based printable and Excel file formats, retrievable from the Statistics/Monetary and Financial Statistics page on the CBR’s website. Monetary statistics are presented in clearly structured tables which, in BBS, are supplemented with charts and graphs. Data from the Statistics page can be retrieved for the various user-selectable periods. Monetary statistics are released simultaneously to all users in accordance with the advance release calendar. Unpublished but nonconfidential data are provided to users upon request with the CBR management’s approval. Metadata accessibility. Comprehensive methodological notes are published in BBS and on the Statistics page of the CBR’s website. A link to the IMF’s DSBB is also provided and is clearly identified on the CBR’s website. Assistance to users. A contact point is provided on the Statistics /Monetary and Financial Statistics page for sending questions to the General Economic Department concerning monetary data. (A user survey questionnaire is also posted there.) The BBS contains telephone number and e-mail address for such contact. The CBR website also identifies staff responsible for answering questions about SDDS data. Publications, documents, and unpublished but non-confidential data are provided free of charge. A list of publications is posted on the CBR’s website.

Table 3f.

Russia Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics

Table 3f.

Russia Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The international accounts are compiled according to the methodological standards of the IMF’s BPM5 Scope. The balance of payments and International Investment Position (IIP) broadly cover all transactions and positions of resident institutional units vis-à-vis the rest of the world. Classification/sectorization. Classification is in broad conformity with BPM5. The classification of services is broadly in line with the Manual on Statistics of International Trade in Services. Under other investment (in the national data presentation), breakdowns include line items that accord with national requirements (including to estimate capital flight). Basis for recording. The accrual principle for recording transactions and positions is not fully met. Other investment income flows of other sectors (nongovernment, nonfinancial), and the positions of government debt liabilities and nontradable debt of other sectors are recorded on a due-for-payment basis.	Source data. Broadly sufficient and under continuous review to ensure that the collection program remains comprehensive. However, source data on financial derivatives are limited to foreign exchange derivatives; procedures are in train to expand the scope of reporting by banks. Since 2003, additional data sources have been developed to enhance the quality of data on direct investment, securities, and remittances. The coverage of customs-based foreign trade statistics remains an issue, and the CBR uses adjustment techniques. Assessment of source data. Coverage of bank reporting stays current because it is integrated with the register maintained by the bank supervisory authorities. Completeness of the closed-type International Transactions Reporting System provides for comparison of reported transactions with changes in bank balances. Statistical techniques. Rigorous standards for minimizing coding, editing, and data processing errors are in place. Statistical techniques are used to enhance coverage in areas including goods, reinvested earnings, and the direct investment flows and positions of enterprises under production sharing agreements. Assessment and validation of intermediate data and statistical outputs. Results are checked against partner-country data, and are assessed for plausibility against domestic, regional and global economic trends. Revision studies. The source and magnitude of revisions are tracked and are used to fine tune the compilation of estimates and preliminary data, and to refine data collection programs.	Periodicity and timeliness. Balance of payments meets SDDS periodicity and timeliness requirements. IIP data meet SDDS periodicity and exceed SDDS timeliness. Consistency. Balance of payments data are internally consistent as annual data is the aggregate of quarterly data. Consistency is achieved with the IIP, and reconciliation tables are published for the full IIP (annual), and for international reserves and external debt (quarterly). Consistent BPM5-based time series dating back to 1994 are available. Revision policy and practice. The revisions policy and practice for all SDDS external sector data are made public. Preliminary data are clearly identified, and reasons for revisions are explained. A history of the revisions to international reserves data are posted on the CBR website.	Data accessibility. International accounts data, along with related data sets including direct investment, international reserves, external debt, and trade in goods and services are available in formats that meet diverse user needs. Most series provide additional information, including geographical and sectoral breakdowns. External sector statistics are announced on a pre-announced schedule in line with the SDDS. Metadata accessibility. The CBR has recently published a methodological publication on external sector statistics which should address user concerns that information on sources and methods are fragmented across the CBR website and hard copy publications. A link to the IMF’s DSBB is also provided and is clearly identified on the CBR’s website. CBR statistical publications also include detailed notes. Assistance to users. A contact point is provided on the Statistics page for sending questions to the CBR concerning the international accounts. The CBR website identifies staff responsible for answering questions on SDDS external sector data, and an online user survey is also posted there. Publications, documents, and unpublished but non-confidential data are provided free of charge. A list of publications is posted on the CBR’s website.

Table 3f.

Russia Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics

2. Methodological soundness	3. Accuracy and reliability	4. Serviceability	5. Accessibility
Concepts and definitions. The international accounts are compiled according to the methodological standards of the IMF’s BPM5 Scope. The balance of payments and International Investment Position (IIP) broadly cover all transactions and positions of resident institutional units vis-à-vis the rest of the world. Classification/sectorization. Classification is in broad conformity with BPM5. The classification of services is broadly in line with the Manual on Statistics of International Trade in Services. Under other investment (in the national data presentation), breakdowns include line items that accord with national requirements (including to estimate capital flight). Basis for recording. The accrual principle for recording transactions and positions is not fully met. Other investment income flows of other sectors (nongovernment, nonfinancial), and the positions of government debt liabilities and nontradable debt of other sectors are recorded on a due-for-payment basis.	Source data. Broadly sufficient and under continuous review to ensure that the collection program remains comprehensive. However, source data on financial derivatives are limited to foreign exchange derivatives; procedures are in train to expand the scope of reporting by banks. Since 2003, additional data sources have been developed to enhance the quality of data on direct investment, securities, and remittances. The coverage of customs-based foreign trade statistics remains an issue, and the CBR uses adjustment techniques. Assessment of source data. Coverage of bank reporting stays current because it is integrated with the register maintained by the bank supervisory authorities. Completeness of the closed-type International Transactions Reporting System provides for comparison of reported transactions with changes in bank balances. Statistical techniques. Rigorous standards for minimizing coding, editing, and data processing errors are in place. Statistical techniques are used to enhance coverage in areas including goods, reinvested earnings, and the direct investment flows and positions of enterprises under production sharing agreements. Assessment and validation of intermediate data and statistical outputs. Results are checked against partner-country data, and are assessed for plausibility against domestic, regional and global economic trends. Revision studies. The source and magnitude of revisions are tracked and are used to fine tune the compilation of estimates and preliminary data, and to refine data collection programs.	Periodicity and timeliness. Balance of payments meets SDDS periodicity and timeliness requirements. IIP data meet SDDS periodicity and exceed SDDS timeliness. Consistency. Balance of payments data are internally consistent as annual data is the aggregate of quarterly data. Consistency is achieved with the IIP, and reconciliation tables are published for the full IIP (annual), and for international reserves and external debt (quarterly). Consistent BPM5-based time series dating back to 1994 are available. Revision policy and practice. The revisions policy and practice for all SDDS external sector data are made public. Preliminary data are clearly identified, and reasons for revisions are explained. A history of the revisions to international reserves data are posted on the CBR website.	Data accessibility. International accounts data, along with related data sets including direct investment, international reserves, external debt, and trade in goods and services are available in formats that meet diverse user needs. Most series provide additional information, including geographical and sectoral breakdowns. External sector statistics are announced on a pre-announced schedule in line with the SDDS. Metadata accessibility. The CBR has recently published a methodological publication on external sector statistics which should address user concerns that information on sources and methods are fragmented across the CBR website and hard copy publications. A link to the IMF’s DSBB is also provided and is clearly identified on the CBR’s website. CBR statistical publications also include detailed notes. Assistance to users. A contact point is provided on the Statistics page for sending questions to the CBR concerning the international accounts. The CBR website identifies staff responsible for answering questions on SDDS external sector data, and an online user survey is also posted there. Publications, documents, and unpublished but non-confidential data are provided free of charge. A list of publications is posted on the CBR’s website.

III. Users’ Survey

12. To complement the assessment of the macroeconomic datasets done using the DQAFs, the mission elicited the views of selected users of the statistics. With the assistance of the CBR, a users’ survey was conducted, which generated 36 responses. Overall, users consider the quality of Russia’s macroeconomic statistics good. A majority of the users are satisfied with the methodological soundness, coverage, timeliness, and accessibility of official statistics, especially monetary and financial and balance of payments statistics. Users expressed a general need for improvement in the information about revisions to official statistics and availability of metadata for all macroeconomic datasets. In addition, the need for improvements in the coverage, level of detail, and timeliness of national accounts and government finance statistics were also identified. Several users noted need for more user-friendly websites. Finally, a large majority of respondents consider Russia’s official statistics to be of the same or better quality than those from other countries in the region.

IV. Staff’s Recommendations

13. Based on the review of Russia’s statistical practices, discussions with the data producing agencies, and responses from data users (see Appendix III of the Detailed Assessments volume), the mission has developed a set of recommendations. Priority recommendations are presented below while other recommendations are noted in Volume III of the report. They are designed to increase further Russia’s adherence to internationally accepted statistical practices, respond to data challenges as a G20 member country, and therefore enhance the analytical usefulness of Russia’s statistics. Some additional technical suggestions are included in the Detailed Assessments volume.

Institutional

Rosstat should be provided the technical independence to implement methodological improvements and changes without the approval of the Ministry of Economic Development.
Expand the data and metadata available on the English-language version of the Rosstat website to include all data and metadata available on the Rosstat’s main Russian-language website. Update the English-language version of the Rosstat website on a more regular and frequent basis to include the most current data available.

Cross-cutting

Update regularly the metadata on the DSBB, and post data on the National Summary Data Page as soon as data are released.

Support for vulnerability and sustainability analysis

Compile and disseminate the comprehensive instrument, currency, and maturity breakdown of the assets and liabilities in the CBR and credit institutions’ (other depository corporations) surveys. ²

National accounts

Revisions of quarterly GDP for the current year should be compiled and disseminated every time data for a new quarter is released.
Caution users not to make use of the first preliminary annual data to derive estimates for the last quarter of the year, thus avoiding misuse of the data.
Compile and disseminate a revised series of imputed rental of owner-occupied dwellings based on the internationally recommended methodology.
Improve quarterly benchmarking techniques. The use of the Denton method is recommended.
Calculate volume measure estimates of general government consumption expenditure as the sum of the cost component of production compiled in volume measures. Develop specific indices to deflate intermediate consumption and consumption of fixed assets.
Update the reference period of the chain-linked volume measures and indices to a more recent period.

Consumer price index

Include a rental equivalence component in the CPI market basket to represent the cost of owner-occupied housing.
Adopt COICOP to classify all items in the CPI to enhance international comparability of Russia’s CPI.
Compile and disseminate a continuous time series of data at a detailed level.

Producer price index.

Expand coverage of PPI to include export goods for price collection.
Disseminate PPI weight data at a detailed level (both current and historic) on the Rosstat website and in PPI bulletins.
Compile and disseminate a continuous time series of data at a detailed level

Government finance statistics

Disseminate the monthly cash based economic classification of expense table.
Compile and disseminate budget execution data for the consolidated central government.
Compile and disseminate monthly GFS summary statements and detail tables (including time series) in accordance with GFSM 2001 guidelines for the general government and its subsectors.
Use the residency criterion to classify debt as either domestic or foreign debt.
Make the MOF and the Treasury websites more user-friendly. Users should be able to access and download data with ease. Introduce a dedicated fiscal data dissemination page that brings together all budget-related data and documents.
Disseminate methodological notes, detailing concepts, sources, and methods used in the compilation of budget execution data and GFS on the MOF and the Treasury websites.
Make public a contact person and contact details, for users interested in requesting information on budget execution data.
Make available to the public a list of the statistical products and services provided by the MOF and the Treasury.

Monetary statistics

Separately identify contra-entries to data on government’s monetary authorities functions (as “of which” lines under the aggregates that include the contra-entries).
Collect and include in monetary statistics data on central bank and the other depository corporations’ positions on financial derivatives, at end-referenced period market prices/fair values.
Reclassify CBR’s valuation adjustment and current year result accounts in shares and other equity.
Value securities held to maturity and shares for investment at market price or market price equivalent.

International Accounts

Use account accrual method for recording (i) other investment income flows (interest) of other sectors; and (ii) position data on government loans and the nontradable debt of other sectors.
Include in the international accounts, data on all types of financial derivatives.
Develop quarterly IIP covering all sectors.

Appendix I. Russia: Practices Compared to the SDDS Coverage, Periodicity, and Timeliness of Data

Note: Periodicity and timeliness: (D) daily; (W) weekly or with a lag of no more than one week from the reference data or the closing of the reference week; (M) monthly or with a lag of no more than one month; (Q) quarterly or with a lag of no more than one quarter; (A) annually; and (…) not applicable. Italics indicate encouraged categories.

SDDS Data Category	Coverage (meets SDDS requirement)	Periodicity		Timeliness		Comments
SDDS Data Category	Coverage (meets SDDS requirement)	SDDS	Russian Federation	SDDS	Russian Federation
Real Sector
National accounts	Yes	Q	Q	1Q	3M
Production index/indices	Yes	M	M	6W (1M encouraged)	4W
Forward-looking indicators	(encouraged data category)	M or Q		M or Q	4W
Employment	Yes	Q	M	1Q	4W
Unemployment	Yes	Q	M	1Q	4W
Wages/earnings	Yes	Q	M	1Q	4W
Consumer price index	Yes	M	M	1M	4W
Producer price index	Yes	M	M	1M	4W
Fiscal Sector
General government operations	Yes	A	A	2Q	2Q
Central government operations	Yes	M	M	1M	2M	Timeliness Notes: Russia is availing itself of a flexibility option on the timeliness of the central government operations data.
Central government debt	Yes	Q	Q	1Q	1Q
Financial Sector
Analytical accounts of the banking sector	Yes	M	M	1M	1M
Analytical accounts of the central bank	Yes	M (1W encouraged)	M	2W (1W encouraged)	2W
Interest rates	Yes	D	D	…	1D for money market and treasury securities market rates, refinancing rate, and REPO and the CBR’s bond rate.
Stock market: share price index	Yes	D	D	…	1D
External Sector
Balance of payments	Yes	Q	Q	1Q	1Q
Official reserve assets	Yes	M (W encouraged)	W	1W	1W
Reserves template	Yes	M	M	1M	20D
Merchandise trade	Yes	M	M	8W (4-6W encouraged)	6W
International investment position	Yes	A (Q encouraged)	A	3Q (1Q encouraged)	2Q
External debt	Yes	Q	Q	1Q	1Q
Exchange rates	Yes	D	D	…	1D
Addendum: Population	Yes	A	A	…	7M

SDDS Data Category	Coverage (meets SDDS requirement)	Periodicity		Timeliness		Comments
SDDS Data Category	Coverage (meets SDDS requirement)	SDDS	Russian Federation	SDDS	Russian Federation
Real Sector
National accounts	Yes	Q	Q	1Q	3M
Production index/indices	Yes	M	M	6W (1M encouraged)	4W
Forward-looking indicators	(encouraged data category)	M or Q		M or Q	4W
Employment	Yes	Q	M	1Q	4W
Unemployment	Yes	Q	M	1Q	4W
Wages/earnings	Yes	Q	M	1Q	4W
Consumer price index	Yes	M	M	1M	4W
Producer price index	Yes	M	M	1M	4W
Fiscal Sector
General government operations	Yes	A	A	2Q	2Q
Central government operations	Yes	M	M	1M	2M	Timeliness Notes: Russia is availing itself of a flexibility option on the timeliness of the central government operations data.
Central government debt	Yes	Q	Q	1Q	1Q
Financial Sector
Analytical accounts of the banking sector	Yes	M	M	1M	1M
Analytical accounts of the central bank	Yes	M (1W encouraged)	M	2W (1W encouraged)	2W
Interest rates	Yes	D	D	…	1D for money market and treasury securities market rates, refinancing rate, and REPO and the CBR’s bond rate.
Stock market: share price index	Yes	D	D	…	1D
External Sector
Balance of payments	Yes	Q	Q	1Q	1Q
Official reserve assets	Yes	M (W encouraged)	W	1W	1W
Reserves template	Yes	M	M	1M	20D
Merchandise trade	Yes	M	M	8W (4-6W encouraged)	6W
International investment position	Yes	A (Q encouraged)	A	3Q (1Q encouraged)	2Q
External debt	Yes	Q	Q	1Q	1Q
Exchange rates	Yes	D	D	…	1D
Addendum: Population	Yes	A	A	…	7M

Beginning July 8, 2010 the Treasury began posting on its website monthly information on expenditures by economic classification on a cash basis.

In July 2010, the CBR has begun disseminating the currency breakdown in the banking survey.

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Russian Federation: Report on Observance of Standards and Codes-Data Module

Author: International Monetary Fund

Volume/Issue:: Volume 2011: Issue 056

Publisher:: International Monetary Fund

ISBN:: 9781455219940

ISSN:: 1934-7685

Pages:: 191

DOI:: https://doi.org/10.5089/9781455219940.002

Keywords
I. Overall Assessment
II. Assessment by Agency and Dataset
III. Users’ Survey
IV. Staff’s Recommendations

Foresee

SDDS Data Category	Coverage (meets SDDS requirement)	Periodicity		Timeliness		Comments
SDDS Data Category	Coverage (meets SDDS requirement)	SDDS	Russian Federation	SDDS	Russian Federation
Real Sector
National accounts	Yes	Q	Q	1Q	3M
Production index/indices	Yes	M	M	6W (1M encouraged)	4W
Forward-looking indicators	(encouraged data category)	M or Q		M or Q	4W
Employment	Yes	Q	M	1Q	4W
Unemployment	Yes	Q	M	1Q	4W
Wages/earnings	Yes	Q	M	1Q	4W
Consumer price index	Yes	M	M	1M	4W
Producer price index	Yes	M	M	1M	4W
Fiscal Sector
General government operations	Yes	A	A	2Q	2Q
Central government operations	Yes	M	M	1M	2M	Timeliness Notes: Russia is availing itself of a flexibility option on the timeliness of the central government operations data.
Central government debt	Yes	Q	Q	1Q	1Q
Financial Sector
Analytical accounts of the banking sector	Yes	M	M	1M	1M
Analytical accounts of the central bank	Yes	M (1W encouraged)	M	2W (1W encouraged)	2W
Interest rates	Yes	D	D	…	1D for money market and treasury securities market rates, refinancing rate, and REPO and the CBR’s bond rate.
Stock market: share price index	Yes	D	D	…	1D
External Sector
Balance of payments	Yes	Q	Q	1Q	1Q
Official reserve assets	Yes	M (W encouraged)	W	1W	1W
Reserves template	Yes	M	M	1M	20D
Merchandise trade	Yes	M	M	8W (4-6W encouraged)	6W
International investment position	Yes	A (Q encouraged)	A	3Q (1Q encouraged)	2Q
External debt	Yes	Q	Q	1Q	1Q
Exchange rates	Yes	D	D	…	1D
Addendum: Population	Yes	A	A	…	7M

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Abstract

I. Overall Assessment

II. Assessment by Agency and Dataset

III. Users’ Survey

IV. Staff’s Recommendations

Institutional

Cross-cutting

Support for vulnerability and sustainability analysis

National accounts

Consumer price index

Producer price index.

Government finance statistics

Monetary statistics

International Accounts

Appendix I. Russia: Practices Compared to the SDDS Coverage, Periodicity, and Timeliness of Data

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