Ukraine: Detailed Assessments Using the Data Quality Assessment Framework (DQAF)
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International Monetary Fund
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Publication Date:
19 Aug 2003
eISBN:
9781451839029
Language:
English
Keywords:
ISCR; CR; balance of payments; National bank of Ukraine; data category; central government; accounting data; consumer price index; producer price index; current price; Monetary statistics; Balance of payments statistics
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The data dissemination module of the Report on the Observance of Standards and Codes (ROSC) provides an in-depth review of Ukraine’s statistical system. The report provides an assessment of Ukraine’s data dissemination practices in relation to the IMF’s Special Data Dissemination Standard (SDDS), and the quality of the data disseminated using the Data Quality Assessment Framework (DQAF) developed by the IMF’s Statistics Department. It also assesses data quality for the national accounts, consumer and producer prices, government finance, monetary, and balance-of-payments statistics.

Abstract

The data dissemination module of the Report on the Observance of Standards and Codes (ROSC) provides an in-depth review of Ukraine’s statistical system. The report provides an assessment of Ukraine’s data dissemination practices in relation to the IMF’s Special Data Dissemination Standard (SDDS), and the quality of the data disseminated using the Data Quality Assessment Framework (DQAF) developed by the IMF’s Statistics Department. It also assesses data quality for the national accounts, consumer and producer prices, government finance, monetary, and balance-of-payments statistics.

Detailed Assessment Using the Data Quality Assessment Framework (DQAF)

The following detailed information on indicators of statistical practices in the areas of the national accounts, price, government finance, money and banking, and balance of payments statistics was gathered from publicly available documents and information provided by Ukraine’s officials. This information, which is organized along the lines of the generic DQAF (see Appendix II), was used to prepare the summary assessment of data quality elements, based on a four-part scale of observance, shown in Ukraine’s Report on the Observance on the Standards and Codes (ROSC)—Data Module.

I. National Accounts Statistics

0. Prerequisites of quality

0.1 Legal and institutional environment

0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified.

The national accounts compiled by the State Statistics Committee (SSCU) have a legal and institutional framework that supports statistical quality. The current Statistics Law of Ukraine—adopted by the Parliament on July 13, 2000 (No. 1922–III) and effective January 1, 2001—defines the roles and responsibilities of state statistical agencies. Decrees/resolutions/orders of the President and Cabinet of Ministers clearly specify the responsibility for collecting, processing, and disseminating national accounts.1

The system of national accounts and supporting infrastructure were established through a series of decrees/resolutions/orders of the President and Cabinet of Ministers. The first regulatory document concerning this was the resolution of the Cabinet of Ministers of December 28, 1992 (No. 727). It assigned the task of implementing the system of national accounts to the SSCU and allocated resources to hire an additional 12 staff. A later resolution of May 4, 1993 (No. 326) specified this task in terms of preparing estimates of annual and quarterly gross domestic product (GDP) on a regular basis. The Presidential Decree of November 6, 1997 (No. 1249/97) made the compilation of national accounts a routine task of the SSCU. It also delegated to the SSCU chairperson the right to set out the various departments of the SSCU. Accordingly, the SSCU chairperson has assigned to the head of the National Accounts Department the responsibility of collecting, processing, and disseminating national accounts in close collaboration with other departments/divisions of the SSCU.

Soon after the Presidential Decree of November 6, 1997 a medium-term program for reforming official statistics (1998–2002) was prepared and issued as a resolution of the Cabinet of Ministers of June 27, 1998 (No. 971). The program includes detailed tasks to be accomplished in the area of national accounts. A longer-term program is currently under preparation, which includes the main directions for developing national accounts for the following 10 years.2

The periodicity and timeliness of GDP estimates were established in the order of the Cabinet of Ministers of August 9, 2001 (No. 341–r).

0.1.2 Data sharing and coordination among data-producing agencies are adequate.

Data sharing and coordination among data producing agencies for compiling national accounts have legislative support and are implemented through protocols or agreements among these agencies and government regulations.

Procedures for inter-agency coordination to support the compilation of national accounts were first set out in a supplement to the resolution of the Cabinet of Ministers of May 4, 1993. The order of the Cabinet of Ministers of August 9, 2001 (No. 341–r) further strengthened these procedures, particularly in terms of the provision of the data to the SSCU according to predetermined time schedules. The order has legislative support in Article 7 of the Statistics Law that entitles the SSCU to use administrative data compiled by state and local authorities, as well as banking and financial statistics and balance of payments statistics compiled by the National Bank of Ukraine (NBU). The order instructs the NBU, State Treasury of Ukraine (STU), Ministry of Finance (MoF), and other ministries and data producing agencies to provide to the SSCU the data required for compiling national accounts on predetermined dates. For example, the NBU has to provide the annual data of commercial banks on interest income and interest payments to the SSCU within 30 days after the end of the accounting year, and monthly data within 20 days after the end of the reporting month. The annual data on the profit and loss statements of commercial banks and NBU have to be provided by the NBU to the SSCU by the end of May following the reporting year. The quarterly data on these statements have to be provided by the twenty-fifth day following the end of the reporting period. The annual data on the balance sheets of NBU and commercial banks have to be provided to the SSCU by the end of September following the end of the reporting period, and the quarterly data have to be provided within 75 days after the end of the reporting quarter. The preliminary annual balance of payments data have to be provided within 40 days after the end of the reporting year, and the quarterly data have to be provided within 75 days after the end of the reporting quarter.

Protocols between the SSCU and other data producing agencies formalize and elaborate the provisions of the above order. For example, a protocol with the Tax Inspection was agreed on February 18, 1997; another with the Ministry of Economy was agreed in February/March 2000; and yet another with the Ministry of Transport was agreed in June 2001.

In addition, inter-agency working groups have been set up for data-sharing purposes. The main purpose of these groups is to ensure proper understanding of the data required for compiling national accounts and to harmonize classifications, concepts, and definitions used by different data-producing agencies. For example, one such group coordinated by the SSCU and comprising representatives of the MoF, Ministry of Economy, STU, NBU, research agencies, and Cabinet of Ministers is working since September 25, 2001. The group was set up at the initiative of the SSCU in accordance with Article 12 of the Statistics Law, which requires the SSCU to effectively organize the exchange of information with other statistics-producing agencies, and the Presidential Decree of April 14, 1995 (No. 312/95), which establishes the SSCU as the coordinating agency for other data-producing agencies in the country.3

0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only.

The confidentiality of the respondents’ data is protected by legislation. Management is sensitive to issues regarding confidentiality of statistics and takes appropriate steps to ensure that respondents’ data are well-protected.

Articles 21 and 22 of the Statistics Law prohibit the SSCU to disseminate individual and confidential statistical information without prior permission of the respondent. The Articles forbid state and local authorities, citizens associations, officials, or private authorities from obtaining such information. However, other legislation—in particular, legislation regulating the work of law enforcement agencies—had not been fully harmonized with the new statistical law, which resulted in conflict and litigation. In all instances, the courts of law have supported the SSCU. At the initiative of the SSCU, appropriate amendments have been introduced to remove provisions in other legislation that contradict the statistical law.

Under Article 17 of the Statistics Law, the staff of statistical agencies is required to comply with the requirements for protecting confidential information. The access to confidential data by the staff is only for official purposes. Disclosure of confidential data by staff violates Article 20 of the Statistics Law and is punishable under the law on Administrative Violations (as amended on July 13, 2000 No. 1929-III). For individuals, the fine is 3–5 times the pre-tax minimum personal income. For registered economic units and entrepreneurs, the fine is 10 to 15 times the pre-tax minimum personal income. The fine is higher for repeated violations. Appropriate measures are taken to secure the premises of the SSCU and its computer network to prevent unauthorized access to confidential data. Confidential information stored electronically is password-protected. Different types of information are protected through different levels of security.

According to Article 18 of the Statistics Law, respondents are entitled to know the nature of the data being collected from them, the purpose of the data collection, and the ultimate use of the data.

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.

The SSCU is authorized by Article 13 of the Statistics Law to obtain the data it requires for its work, including accounting reports—as well as explanations of such reports—from central and local government authorities, banks, other data-reporting units, and individuals. The Article authorizes the SSCU to check the status of the data and the reliability of the information provided by the respondents. The respondents are obliged by Article 18 to provide the required data free to the SSCU. Officials, data-reporting units and individuals violating these requirements may be prosecuted and fined. Cases of nonresponse, provision of false, inaccurate, or untimely information are punishable with a fine of 3–5 times the pretax minimum personal income for individuals, and 10 to 15 times the pre-tax minimum personal income for legal units and entrepreneurs.

0.2 Resources

0.2.1 Staff, financial, and computing resources are commensurate with statistical programs.

The Department of National Accounts consists of the divisions of national accounts, sub-annual national accounts, consumption and capital formation accounts, production and income accounts, and supply-use tables. All 35 staff employed in these divisions have university degrees with specialization in subjects such as statistics, economics, information technology, and accounting. New staff undergo on-the-job training. Staff may also undergo general training in statistics at the SSCU’s Institute of Statistics, Accounting, and Audit.

More experienced staff have attended national accounts courses conducted by the International Monetary Fund (IMF) in Washington and Vienna, and other courses and seminars conducted by international agencies. The senior staff is highly professional and very well-acquainted with the System of National Accounts 1993 (1993 SNA).

The skills acquired by the experienced staff are in great demand by the NBU and other agencies. Often the staff has left for higher paying jobs to these agencies, and as a result, several of the current staff are new and require training. Nevertheless, staff, financial, and computing resources are adequate for compiling the current national accounts data series. However, the timely development of the full set of institutional sector accounts, including capital and financial accounts, will require additional staff. Also, the present staffing does not allow the annual compilation of comprehensive supply-use tables. Such tables in current and constant prices are required for analysis of the economic structure and allow consistency checks of the source data.

Although staff has access to computers that are connected to the SSCU’s local area network, several of these computers are an old vintage, which prevents the SSCU from introducing more state-of-the-art processing techniques. Specialized training of the staff in computing procedures would result in significant efficiency gains in the use of staff resources.

0.2.2 Measures to ensure efficient use of resources are implemented.

In recent years, the SSCU management has brought the organizational structure more in line with the requirements of a modern statistical system. The number of staff employed by the SSCU has been reduced from more than 21,000 to approximately 12,800. Of these, only 440 staff are employed at headquarters in Kyiv. Current orders of the Cabinet of Ministers forbid the hiring of additional staff. The Central Inter-Regional Department of Statistics (main Computer Center) employs an additional 300 staff. The rest of the staff work in the oblast, rayon, and city offices.4

The large number of staff employed at regional offices is partially explained by the methods of data collection, which continue to rely on full or very large counts and the corresponding data flow and management procedures. Although sample surveys have been introduced in several sectors, they are not yet universally applied, and the counts of statistical units typically remain very large (see 3.1.1). The data are processed and edited at various levels, which involves some duplication. For example, in the case of surveys of nonfinancial enterprises, the data are collected in the rayons, converted into electronic format and transmitted to higher levels (oblast or city, and main Computer Center in Kyiv). The main Computer Center receives both micro-level data and aggregated data from regional offices.

The data undergo logic and arithmetic checks at different levels, followed by checking of aggregate data again at the main Computer Center, and further checking by the respective SSCU divisions. Duplication of effort also arises from the replication of the SSCU’s organizational structure and tasks in the main Computer Center. To streamline these procedures the SSCU needs to accelerate the implementation of sample surveys, improve data flow management, and computerized data processing by centralizing the processing of primary data in the main Computer Center in Kyiv.5

Staff performance appraisal follows civil service law and regulations that apply throughout the government. Although appraisals are given at three-year intervals, the departmental managers have the discretion to review and set the bonus portion of staff salaries on the basis of their own judgment of staff performance. This is normally done once a year, but adjustments can be made at any time. The Department of Finance and Computation maintains data of each Department on staff utilization at headquarters in the main Computer Center and in the regions. Regional workload by program is routinely monitored on an informal basis via regular communication with regional office managers. Staff compensation comprises base salary, a performance-based bonus salary, and cash awards for meritorious service. The SSCU budgets the base and bonus salary by Department, and the level of bonus salary of individual staff is determined by the total annual bonus budget allocated to the Department and the level of staff performance. Awards for outstanding individual staff performance are made, with adequate justification, over and above the Departmental compensation budget. Appointment of new staff is on competitive basis. 6 New staff are appointed by the order of the SSCU chairperson.

0.3 Quality awareness

0.3.1 Processes are in place to focus on quality.

Management is sensitive to issues regarding the quality of national accounts statistics and encourages the adoption of procedures for quality checks during data collection, processing, and compilation (see 3.3 and 3.4, and footnote 5).

0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics.

Management views the system of national accounts as the conceptual framework for economic statistics (see 3.3.1). Reduced format supply-use tables are compiled annually since 1999, mainly for analytical purposes to identify major discrepancies (see 4.3.2).

Regional publications are reviewed quarterly by the headquarters staff, and recommendations are made on accuracy, format, and presentation (including use of graphics). Annual reviews of regional publications make recommendations on quantitative and descriptive content.

Presently, there is no body distinct from the SSCU that provides guidance on the quality of the statistical series and on strategies for improving data production. A high-powered Statistical Council attached to the office of the President, that existed some time ago, could be revived for this purpose.7 The Council could play an active advisory role and, when required, may examine issues in depth and make specific and detailed recommendations to the chairperson of the SSCU, in particular, regarding methodological issues, accuracy, and exhaustiveness of official statistics. It could be chaired by the chairperson of the SSCU and comprise representatives of enterprises, trade unions, ministries, regional statistical offices, academic/research institutions, etc. It could meet as required.

As the national accounts—in particular, annual and sub-annual GDP estimates—are used for a variety of purposes, they enjoy an active user base inside and outside the government. The staff of the National Accounts Department report that they receive several queries every month related to GDP issues. The staff undertakes periodic consultations with users of national accounts supplemented by informal contact (see 4.1.1).

0.3.3 Processes are in place to deal with quality considerations, including trade-offs within quality, and to guide planning for existing and emerging needs.

Management is aware of the trade-offs among the dimensions of quality, especially in the context of meeting users’ demand for national accounts data with high frequency. For example, it recognizes the need to economize resources by reducing the demand for detailed administrative data of local rayon, oblast, and city administrations, as well as by reducing the requirement to produce timely estimates of monthly GDP. Management is also aware that quality could be improved by reorienting the data collection effort within sampling frameworks (see also 0.2.2 footnote 5).

1. Integrity

1.1 Professionalism

1.1.1 Statistics are compiled on an impartial basis.

The SSCU is an independent organization financed through the government budget. According to the Presidential Decree of November 6, 1997 (No. 1249/97), the chairperson of the SSCU is appointed by the President on the recommendation of the Prime Minister, and reports to the President and the Cabinet of Ministers. The chairperson is responsible for ensuring professionalism in statistical activities. Article 5 of the Statistics Law provides the legislative basis for the professional independence of the SSCU. It forbids state and local authorities, officials, public associations, and other persons to interfere in the work of the SSCU. Nevertheless, official users have continued to exercise undue influence in determining the dissemination practices or revision policies of the national accounts. The SSCU also relies excessively on the authority of the Cabinet of Ministers and the President to implement the national accounts program.

Professionalism is promoted by the Civil Service Code, which provides for penalties for misuse of public property and confidential information by government employees. It also determines qualifications for the statistical and other job series needed for SSCU’s work program. Professional skills in statistics and economics are considered in determining the level of compensation and eligibility for promotion (see 0.2.2).

1.1.2 Choices of sources and statistical techniques are informed solely by statistical considerations.

Independence in the selection of the methodology, data sources, content, and format of the data disseminated by the SSCU is guaranteed by Articles 5, 7, 8, and 9 of the Statistics Law. The compilers of national accounts are free to choose the data sources with regard to quality, timeliness, costs, and the burden on respondents. The National Accounts Department reports no external interference in the conduct of its work in these respects. Through inter-agency protocols (see 0.1.2) the staff of the National Accounts Department has access to the data produced by the NBU, MoF, and Customs Inspection.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.

The SSCU is empowered by Article 13 of the Statistics Law to comment on misuse or misinterpretation of statistical information. When it has significant disagreements about the technical merits of public statements made about SSCU’s statistics, the SSCU communicates—either in print or via other appropriate public modality, or via direct private communication—with the issuers or authors of the statements in contention.

1.2 Transparency

1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

The Statistics Law is a public document and available to the public on the official website of the SSCU. Statistical publications provide information about the SSCU and how its products may be obtained.

1.2.2 Internal governmental access to statistics prior to their release is publicly identified.

Equal access to all data users is guaranteed by Article 14 of the Statistics Law. Accordingly, the data are released simultaneously to all interested parties.

1.2.3 Products of statistical agencies/units are clearly identified as such.

Data released to the public by the SSCU are identified as the SSCU product. Government publications of the SSCU’s data are required to properly attribute them to the SSCU.

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.

Advance notice of changes in methodology are provided in the medium-term and long-term programs of statistical development. The changes in methodology to be undertaken during the current year are described in the annual plan of the SSCU. The document is provided to major users and accessible to others.

1.3 Ethical standards

1.3.1 Guidelines for staff behavior are in place and well-known to the staff.

Employees of state-statistical bodies are required by Article 17 of the Statistics Law to protect confidential information from disclosure. Staff must commit to abiding by the Civil Service Code as a condition of employment (see 1.1.1).

2. Methodological soundness

2.1 Concepts and definitions

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

The 1993 SNA is the general framework for compiling national accounts.

2.2 Scope

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

The national accounts cover annual GDP in current prices and in prices of the previous year by economic activity and by expenditure components, the sequence of national accounts to the capital account (inclusive), and the rest of the world account to the capital account (inclusive). Also covered by the national accounts program are the compilation of quarterly GDP by production activities and by expenditure components at current prices and in prices of the same period of the previous year, and annual supply and use tables. Estimates of gross value added are compiled for 27 regions with breakdown by 30 production activities.

To delimit the constituent units of the economy, the 1993 SNA is followed in principle but may not be fully implemented because of source data constraints, e.g., lack of adequate coverage of residents working abroad. Territorial enclaves—such as embassies—are, in principle, in scope for national accounts and covered to the extent possible depending on data availability.

The definition of the production boundary follows 1993 SNA. In particular, the following items are included: own-account production of goods for own final consumption, output of goods for own-account fixed capital formation, mineral exploration, production of literary, or artistic originals. Illegal goods sold to willing buyers are not included in production. However, an independent estimate of unrecorded activities is incorporated in the GDP estimate (see 3.2.2). Because of nonavailability of accurate data, the following are presently partly included: the production of literary and artistic originals, and research and development on own account.

The definition of the asset boundary follows 1993 SNA. In particular, the following items are included depending on the availability of the data: defense-related assets that could be used for civilian purposes, agricultural work-in-progress, computer software, patents, and leases.

2.3 Classification/sectorization

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

The 1993 SNA is followed to classify institutional units and transactions. The new five-digit national industrial classification—the Classification of Types of Economic Activity—follows the General Industrial Classification of Economic Activities of the European Communities (NACE, Rev. 1, ver. 7) at the four-digit level. It was introduced in all surveys from January 1, 2001. Work is underway to introduce the national Classification of Products by Activity to classify products according to the industry where they constitute the principal product. The classification uses nine digits, of which the first six digits correspond to the (international) Central Product Classification. Household consumption expenditure is classified following the Classification of Individual Consumption by Purpose. Functions of government are classified following a national classification that follows the Classification of Functions of Government (COFOG). The Harmonized System was adopted on July 1, 2001 to classify transactions in international trade.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

Valuation rules, in principle, follow 1993 SNA. Output for own use is valued at equivalent market prices. Intermediate consumption is valued at purchasers’ prices. Nonmarket output of government and nonprofit institutions is valued at cost. Imports and exports are valued on a free on board (f.o.b.) basis. Balance of payments (BOP) transactions in foreign currency are converted by the NBU to local currency using the average weighted exchange rate on the day of transaction.

2.4.2 Recording is done on an accrual basis.

Transactions are recorded to the extent possible on an accruals basis. In particular, work-in-progress is recorded in the period it is produced, such as construction, rearing of cattle, and cultivation of orchards. Government-related transactions are recorded on cash basis, excluding taxes and wages.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.

Transactions between establishments of the same enterprise are recorded on a gross basis.

3. Accuracy and Reliability

3.1 Source data

3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions.

A comprehensive statistical register derived from the Unified State Register of Enterprises and Organizations (USREO) has recently become operational with assistance from Eurostat.8

The statistical register provides the basis for conducting annual and sub-annual surveys. It includes around 450,000 registered units that are classified using the new five-digit national industrial classification (see 2.3.1). Summary information (in Ukrainian and English) from the register is published regularly. The published information includes data on changes in the structure and number of the units covered with a breakdown by region, industry, and type of ownership. To update the statistical register, a special survey of 10,000 statistical units was conducted in 2000. The register is also routinely updated using information provided by enumerators, and by the tax register.

The source data for compiling national accounts come from the extensive survey program of the SSCU, supplemented with data from administrative and other sources (see 0.1.2). In 1999, the surveys supporting the national accounts program covered 88.9 percent of total output. The data for compiling GDP by economic activities came from almost 37,000 medium and large enterprises, 9 and 197,000 small enterprises. Mining and electricity, gas, and water production sectors had coverage of 99.5 percent and 92.8 percent of total output respectively. The coverage of the manufacturing sector was 92.8 percent, and of agriculture and forestry sector, 96.2 percent. The least coverage was in wholesale and retail trade, and in services amounting to 51.9 percent and 67.9 percent of total production in the sectors. In the latest annual data collection cycle of 2001, the number of medium and large enterprises covered has increased further to 47,489. The number of enterprises covered in the quarterly surveys ranged from 46,248 to 47,489.

The national accounts data for enterprises are collected mainly using two report forms. The data on production and production-related expenses, including changes in inventories, are reported on one form (1-predprinimatelstvo). The financial and balance sheet data are reported in a separate form (see 0.2.2 footnote 5). The data collected are sufficiently detailed to derive the main national accounts aggregates (gross output, intermediate consumption, fixed capital formation and changes in inventories).

Government finance statistics (GFS) are obtained on a monthly and annual basis from the STU. The data allow the measurement of output, intermediate consumption, fixed capital formation, and final consumption expenditure of government.

The first all-Ukrainian population census was conducted in 2001. It will be conducted once in 10 years. The new quarterly household survey—conducted since 1999—has comprehensive coverage, sound sample design, and editing and imputation procedures that adequately represent the universe. Raising factors are derived from the sample design. The surveys provide detailed information on expenditure, including purchases of goods and services, purchases of durable goods, consumption of goods from subsidiary plots, etc., as well as on sources of income, including wages, housing subsidy, other compensation, and sales of real estate and assets. The data are compiled within four to four and a half months after the end of the reference period.

The labor force survey is conducted on a quarterly basis since 1999. Prior to that, the survey was annual.

3.1.2 Source data reasonably approximate the definitions, scope, classification, valuation, and time of recording required.

Survey report forms have been revised significantly in recent years to bring them in line with the definitions, scope, and classification of national accounts data (see also 0.2.2). Source data are consistent with the time of recording (with the exception of GFS), and valuation of national accounts. The fiscal year of the government and enterprises is the calendar year.

3.1.3 Source data are timely.

Source data are timely. The data provided to the SSCU by other data-producing agencies follows predetermined schedules (see 0.1.2).

3.2 Statistical techniques

3.2.1 Data compilation employs sound statistical techniques.

Production approach procedures: Annual and quarterly estimates of gross output are compiled for most sectors at the two-digit level of the national classification from data reported by enterprises. The intermediate consumption estimates are compiled at the same level of detail. However, the dissemination of the data is by 38 economic activities for annual estimates, and by 10 economic activities for quarterly estimates.

The gross output of owner-occupied dwellings is valued as the estimated rentals that tenants would pay for similar accommodation. The concept of work-in-progress is correctly applied to growing crops, standing timber, stocks of fish, livestock reared for purposes of food, large construction projects, and output of large equipment. Estimates of consumption of fixed capital are derived from the data reported by enterprises on capital amortization. The data on government subsidies, revenue (excluding taxes), and expenditure, that are on cash basis, are not converted to an accruals basis. Changes in inventories are estimated with accounting for holding gains/losses. The GDP estimate for 2001 includes an adjustment for holding gains/losses of around 2 percent of GDP.

Volume measures of GDP are compiled at a disaggregated level. Production indices/volume data are used to extrapolate gross output of agriculture, mining, manufacturing, trade, construction, market and nonmarket services, etc. The volume index for agricultural production is a monthly Laspeyres-type index with 2000 as the base year. The data for compiling the index are from area surveys, census of livestock, and productivity data that are derived from spot surveys of agricultural production in rural areas (covering 0.44 percent of total cropped area). The volume index for manufacturing is compiled from data reported directly by enterprises in current prices and in constant prices of December 2000, which facilitates the direct calculation of volume growth rates. Although the concept of gross value added based on accrued sales at transactions prices has replaced older concepts involving the use of list prices, it is not known exactly how the enterprises arrive at constant price data nor about how they deal with new products or varieties. The current price output of construction is deflated using a construction price index with base 1991. The index is compiled from information on 92 cost item groups as reported by selected enterprises (contractors). Volume indices are used to extrapolate the gross output of transportation. The indices are compiled from data on freight volume and number of passengers. The previous period current price gross output of trade and restaurants is extrapolated using the index of aggregate sales of consumer goods. The index is compiled by deflating actual sales of goods with the corresponding sub-components of the retail price index (for retail trade), and producer price index (for wholesale trade). Output volume of trade margins is estimated by extrapolating the base-year-trade margins using volume extrapolators of sales (retail and wholesale trade). Gross output of market services, including social and cultural services, are deflated using corresponding sub-components of the consumer price index (CPI). Double deflation method is applied to housing and communal services using data from the aggregate supply-use tables. For science-related services, finance services, and nonmarket services, the employment index of the corresponding sectors is used for extrapolation. Net taxes and subsidies are extrapolated using volume indices of the respective sectors.

The SSCU plans to improve its methodology for compiling volume measures by compiling better volume indices, such as the index of manufacturing production by 410 manufacturing groups and 13 main sectors, and the use of alternative methods for calculating gross output at constant prices, for example, through deflation of values using producer price indices at the detailed level.10

Expenditure approach: The GDP estimates by expenditure components are derived independently.

The estimate of household final consumption expenditure is compiled by 12 main groups of goods and services—corresponding to the Classification of Individual Consumption by Purpose (COICOP). Estimates of government consumption expenditure and gross fixed capital formation are compiled following COFOG. Because of insufficient data, the expenses of residents abroad are not fully covered in household final consumption expenditure (also see 2.2.1). Estimates of gross fixed capital formation are compiled with a breakdown by machinery and equipment, construction and assembly, capital repairs, etc. Changes in inventories are distinguished by three main types of inventories (raw material, work-in-progress, and finished goods) and compiled from data reported directly by enterprises (see 3.1.1). Price indices/volume indices are used at a fairly disaggregated level to derive volume measures. Household final consumption expenditure is deflated using CPI of broad groups of goods and services. Government final consumption expenditure is extrapolated using employment data. Gross fixed capital formation is deflated using the price index of construction machinery. The data on equipment is deflated using the producer price index (PPI) for the corresponding group. However, the lack of proper quarterly export and import price indices reduces the quality of the volume measures of GDP by the expenditure approach.

Specific quarterly compilation techniques: There is no discrepancy between the preliminary annual estimate and the sum of the quarterly estimates because the estimates of the fourth quarter are derived as a residual, after routinely adjusting the first three quarters as revised and better data become available. This makes the fourth quarter estimate inconsistent with estimates of the first three quarters.11 Further, the coverage of the annual compilation is much larger than the quarterly compilations, as it also includes small enterprises. The quarterly data are not seasonally adjusted while the data indicate strong seasonality.

3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.

Despite the apparently large coverage of economic activities (see 3.1.1), there is a prevailing view that private activities are under-recorded. The problem is addressed by including an estimate of unrecorded activities in the GDP estimate, which is derived mainly from the reported data on trade turnover. The official estimate of unrecorded activities in 2000 is 20 percent of GDP. An estimate of the size of the informal sector is also calculated.

Most unrecorded activities are in construction, trade and transportation, food and light industry, medical, and education services. In construction, an estimate of unrecorded activities is compiled from the data from an experimental survey of garages, dachas, and private houses in villages. In retail trade, the main source of data is the special survey of specific markets—conducted since 1996—to collect information on sales of specific agricultural products. A similar survey is conducted for transportation since 2001 mainly to collect data on intra-city and inter-city transportation. Additionally, commodity balances are used to develop aggregate estimates of production of specific products, such as grain, meat, and milk by comparing the data from the production surveys with the trade turnover and/or household consumption data from the household surveys, and data from the census of livestock.

3.3 Assessment and validation of source data

3.3.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide planning.

Information is not available about sampling/nonsampling errors of surveys. Nonresponse is followed up and appropriate imputations are made. Report forms are reviewed by management and by the staff of the Methodology Division, who cooperate closely with the staff of the National Accounts Department, to ensure consistency of concepts and definitions across survey areas. Control over the source data is exercised through data checks. For example, there are seven controls to check the source data on manufacturing production, sales, employment, and expenditure on production. Information on these indicators is collected in two separate report forms, 1-Predprinimatelstvo (also see 0.2.2 footnote 5 and 3.1.1), and financial report form for enterprises, and the appropriate data are aggregated and compared. High value transactions are given attention. Administrative data, budgetary data, international trade data, and other data, used in the calculations, are routinely assessed for deviations from the trend and for errors.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Main intermediate data are validated against other information where applicable.

The data from the main sources used to compile national accounts are checked with other primary/secondary data sources where available.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

The deviations in data sources are investigated and adjusted accordingly.

3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated.

The statistical discrepancy between GDP by production activities and GDP by expenditure components is investigated (also see 4.3.1).

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes.

The revision to the final GDP estimate is generally small. However, the procedures for revising the data are not explained.

4. Serviceability

4.1 Relevance

4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

Users’ surveys are not conducted on a regular basis. Feedback is obtained from the users within the context of various working groups in which the SSCU participates (see 0.1.2) either officially or in an informal way. The National Accounts Department receives letters and calls most often from official users of the data in the MoF, Ministry of Economy, other ministries and government offices, research organizations, etc. (see 0.3.2). At the insistence of official users of the data, the SCCU provides detailed administrative data to the oblast, rayon, and city administrations. Management is in contact with international agencies and aware of international best practices in the dissemination of national accounts data. It intends to further refine the measurement of unrecorded activities and to compile and disseminate comprehensive supply-use tables. Management is also aware of the need to compile and disseminate consistent time-series data for the main national accounts aggregates, as well as to disseminate volume measures in relation to a fixed reference base, which are issues of particular concern to users (see 4.3.2).

4.2 Timeliness and periodicity

4.2.1 Timeliness follows dissemination standards.

The timeliness of quarterly data for the first three quarters is 95 days. The data for the fourth quarter are disseminated around four months after the end of the reference period and need to be made more timely to meet the Special Data Dissemination Standard (SDDS) requirements. The preliminary annual data are released within two months of the end of the reference period, and the final data are released within one year.

4.2.2 Periodicity follows dissemination standards.

Quarterly and annual data are compiled.12

4.3 Consistency

4.3.1 Statistics are consistent within the dataset.

The statistical discrepancy between GDP by production activities and GDP by expenditure components is usually less than 2 percent of GDP (before adjustment). The discrepancy is not shown explicitly and is removed through adjustments in the estimates of production activities and expenditure components that have weaker data sources.

The concepts and definitions for compiling quarterly GDP estimates are identical to those used to compile annual GDP estimates (see 3.2.1 on quarterly compilation techniques).

The analytical and reconciliation process of compiling the supply-use tables serves as a check on the consistency of the components of the system of national accounts.

4.3.2 Statistics are consistent or reconcilable over a reasonable period of time.

Consistent annual time series data for GDP are only available for the period 2000–01. Consistent current price quarterly data are only available from 2001. The time-series data for the period 1990–2000 are according to the old classification of economic activities.

As a result of the quarterly deflation methodology, quarter-to-quarter volume measures of GDP are not consistent. Volume measures of GDP are expressed in prices of the same quarter of the previous year and are inadequate for producing consistent quarterly time series and, in addition, produce volume measures that are not consistent with annual volume measures of GDP.

4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.

Total net lending/net borrowing estimated from the national accounts is consistent with the balance of payments data. The rest of the world accounts are compiled from the balance of payments. However, because of difference in the timing of release of the revised balance of payments and national accounts data, there could be differences in the two datasets (see 4.4.1).

The government sector accounts and government finance statistics are compiled from the same data sources, which include the central and local government budgets, the accounts of extra-budgetary funds, and financial statements from public enterprises. Estimates are made to convert taxes and wages from a cash to an accrual basis.

4.4 Revision policy and practice

4.4.1 Revision follow a regular, well-established, and transparent schedule.

The quarterly and annual data are revised once according to a predetermined schedule. However, the revision period of one year for national accounts does not permit the incorporation of the latest balance of payments statistics that are finalized after 15 months. Similarly, the quarterly national accounts are unable to use the latest results of the household survey that are prepared four months after the end of the reference quarter (see 3.1.1).

4.4.2 Preliminary data are clearly identified.

The preliminary data are identified. The revised data are disseminated with the same detail as the preliminary data.

4.4.3 Studies and analyses of revisions are made public.

In cases of major revisions, the sources of data revision are indicated to show the difference from the preliminary figures.

5. Accessibility

5.1 Data accessibility

5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

Although the national accounts data are published with various levels of disaggregation and the corresponding metadata are adequate, the data are not disseminated in time-series format, i.e., volume measures are not disseminated in relation to a fixed reference base. The data are catalogued to provide users with adequate information to locate them. A brief description of the data and changes in the data is provided. Annual growth rates and percentage shares of the data are shown.

5.1.2 Dissemination media and formats are adequate.

Quarterly estimates of GDP are disseminated in current prices and in prices of the same period of the previous year. The data are provided by 10 main types of economic activity. The final data have the same level of disaggregation as the preliminary data. The preliminary annual data are released through press release. The final annual data are released with maximum detail in a dedicated national accounts publication.

5.1.3 Statistics are released on a pre-announced schedule.

The data are released according to a pre-announced schedule.

5.1.4 Statistics are made available to all users at the same time.

Following the Statistics Law, the data are released to all users at the same time.

5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request.

Users may obtain nonpublished (but nonconfidential) data from the contact person for national accounts.

5.2 Metadata accessibility

5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

Brief documentation on methodology is provided with the release of quarterly data. More details are provided in the annual publication. The main provisions of statistical methodology are published.

5.2.2 Levels of detail are adapted to the needs of the intended audience.

Metadata are available at different levels of detail (brief notes, summary of methodology, and detailed explanation of the methodology).

5.3 Assistance to users

5.3.1 Contact person for each subject field is publicized.

A contact person for national accounts is available to provide assistance to users. The information about the contact person is not publicized.

5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available.

The catalogue of SSCU’s publications is available. The price of the publications is shown, and a contact telephone is provided to obtain further information.

Table 1.

Ukraine—Data Quality Assessment Framework: Summary of Results for National Account Statistics

(Compiling agency: State Statistics Committee)

Key to symbols: NA = Not Applicable; O = Practice Observed; LO - Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Not Observed; SDDS = Complies with SDDS Criteria

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II. Price Statistics (Consumer Price Index)

0. Prerequisites of quality13

0.1 Legal and institutional environment

0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified.

The current Statistics Law of Ukraine, adopted by the Parliament on July 13, 2000 (No. 1922-III) and effective January 1, 2001, defines the roles and responsibilities of state statistical agencies. Decrees/resolutions/orders of the President and Cabinet of Ministers clearly specify the responsibility for collecting, processing, and disseminating price statistics.

As defined by the Statistics Law, the state statistical agencies consist of a central executive agency, and territorial and functional statistical units established by this agency and subordinated to it. The current Statistics Law is a revised version of an earlier law, that was adopted in 1992. It was revised with a view to making Ukraine’s statistical legislation consistent with international best practices. The current law is supplemented by the Presidential Decree of April 14, 1995 (No. 312/95), which establishes the State Statistics Committee of Ukraine (SSCU) as the central executive agency for official statistics. Under Article 12 of the Statistics Law, the SSCU is, therefore, responsible for collecting, processing, aggregating, analyzing, disseminating, storing, and protecting statistical information. A further Presidential Decree of November 22, 1997 (No. 1299/97) mandated the development of an integrated system of statistics according to international standards and directed the Cabinet of Ministers to make legislative, regulatory, and financial arrangements to support the new statistical system.

0.1.2 Data sharing and coordination among data-producing agencies are adequate.

Price statistics are produced with data compiled within the SSCU’s Price Statistics Department, in cooperation with other SSCU’s departments, and do not directly require interagency cooperation.

0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only.

The legislative basis for protecting the confidentiality of the respondents’ data is strong. Management is sensitive to issues regarding confidentiality of statistics and takes appropriate steps to ensure that respondents’ data are well-protected.

Articles 21 and 22 of the Statistics Law state that the SSCU is prohibited to disseminate personal and confidential statistical information without prior permission of the respondent. The Articles forbid state and local authorities, citizens associations, officials, or private authorities from obtaining such information. However, other legislation—particularly, legislation regulating the work of law enforcement agencies—had not been fully harmonized with the new statistical law, which resulted in conflict and litigation. In all instances, the courts of law have supported the SSCU. At the initiative of the SSCU, appropriate amendments have been introduced to remove provisions in other legislation that contradict the statistical Law.

Under Article 17 of the Statistics Law, the staff of statistical agencies are required to comply with the requirements for protecting confidential information. The access to confidential data by the staff is only for official purposes. Staff, who disclose confidential data, are liable to punishment under Article 20 of the Law. Violation of this Article is punishable under the law on Administrative Violations (as amended on July 13, 2000 No. 1929-III). In cases of breach of confidentiality, fines may be imposed on individuals amounting to 3–5 times the pre-tax minimum personal income. For registered economic units and entrepreneurs, the fines are 10–15 times the pre-tax minimum personal income. The fines are higher for repeated violations. Appropriate measures are taken to secure the premises of the SSCU and its computer network to prevent unauthorized access to confidential data.

The consumer price index (CPI) data comprise publicly observable retail prices, and the weights comprise aggregated Household Living Conditions Survey (HLCS) data, protecting individual households’ identities from disclosure. Nevertheless, the CPI is a “mission critical” data series. The computer, on which CPI calculations are performed in the SSCU’s headquarters, is not connected to the local area network to lower the chance of infection by viruses and is password protected. The producer price index (PPI) data are confidential in the SSCU. The systems, on which the PPI microdata reside and on which the index is calculated, reside at the SSCU’s Computer Center and are protected not only with passwords but also with additional safeguards against physical access by unauthorized individuals.

According to Article 18 of the Statistics Law, respondents are entitled to know what primary data are being collected from them, for what purpose, and who will use them.

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.

Statistical reporting has adequate legislative and regulatory support.

According to Article 13 of the Statistics Law, the SSCU is authorized to obtain the data it requires for its work—including accounting reports, as well as explanations of such reports—from central and local government authorities, banks, other statistical units, and individuals.

The Article authorizes the SSCU to check the status of the data and the reliability of the information provided by respondents. Article 18 obliges the respondents to provide the required data free to the SSCU. Officials, statistical units, and individuals violating these requirements may be prosecuted and fined. Cases of nonresponse, provision of false, inaccurate, or untimely information are punishable with fines amounting to 3–5 times the pretax minimum personal income for individuals and 10–15 times the pre-tax minimum personal income for legal units and entrepreneurs. In practice, punishments are rarely applied.

0.2 Resources

0.2.1 Staff, financial, and computing resources are commensurate with statistical programs.

Overall numbers of staff appear adequate. Staff resources for the combined CPI, PPI, and construction price index programs comprising the SSCU’s Price Department were budgeted at the levels indicated in the table below:

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As shown, the current budgeting system routinely tracks staff resource allocation by individual price program in the central office headquarters and Computer Center units, but not in the regions, where an individual staff member may work on two or more programs at various times of the month.

Financial resources have improved recently with economic conditions. In addition to its resources from the government budget, the SSCU earns income from various sources through its “subordinated bodies,” which produce income from special tabulations of data, from publications sales, provision of computer and research services, and provision of specialized training in areas such as accounting.

Computing resources in the headquarters are adequate, comprising a local area network of Pentium personal computers with standard word processing and spreadsheet software.

Headquarters computing facilities are used to compile the CPI from 270 item indices, transmitted from each of the 27 regions each month, and to prepare tables and charts for dissemination of the CPI, PPI, construction, and the retail and communications/transport price indices. The budget is very limited for undertaking normal upgrades of hardware and software for the network, and its workstations. Maintenance of the headquarters’ network is the responsibility of the SSCU’s Department of Computation—a small headquarters unit distinct from the Computer Center—which handles large-scale data processing.

Receipt of CPI and PPI data from the regions is done via electronic mail to the Computer Center in Kyiv. This plus the maintenance of microdata for the PPI and the calculation of the PPI from a central database are undertaken at the Computer Center.

Computing resources in the regional offices are barely adequate. CPI short-term item indices are calculated in the regions each month either on computers or on calculators, and the results forwarded to headquarters in Kyiv. PPI data entry is done in the regions on old systems with limited memory, storage, and processor power using a custom-programmed application of the Clipper database management system (a clone of the dBase database programming language comparable in many respects to the current Microsoft FoxPro), which admittedly is well-adapted to older generation personal computers. PPI calculation in the Computer Center of the SSCU’s headquarters uses another custom Clipper program.

0.2.2 Measures to ensure efficient use of resources are implemented.

The SSCU’s Department of Finance and Department of Computation maintain data for each SSCU’s department on staff utilization at headquarters, in the computer center, and in the regions. The managers of the Price Statistics Department do not routinely use these data, since—as noted in 0.2.1—there is no detail on regional utilization of staff for the CPI, PPI, and other price index programs. Regional workload by program is routinely monitored on an informal basis, however, via regular communication with regional office managers.

Staff compensation comprises base salary, a performance-based bonus salary, and cash awards for meritorious service. SSCU budgets base and bonus salary by Department, and the level of bonus salary for individual staff is determined both by the total annual bonus budget allocated to the Department and the level of staff performance. Awards for outstanding individual staff performance are made, with adequate justification, over and above the Departmental compensation budget. Staff performance appraisal follows civil service law and regulations that apply throughout the government. Appraisals are given at three-year intervals. The infrequency of appraisals could make it difficult to recognize superior or remediate poor staff performance until a significant amount of time has passed. A flexible performance-based compensation scheme mitigates this inflexibility, however. Departmental managers have the discretion to review and set the bonus portion of staff salaries on the basis of their own judgment of staff performance. This is normally done once a year, but adjustments can be made at any time.

0.3 Quality awareness

0.3.1 Processes are in place to focus on quality.

There is at present no formal quality program. Management is sensitive to issues regarding quality of price statistics and encourages the adoption of procedures for quality checks during data collection, processing, and compilation. (see 3.3 and 3.4)

There have been ongoing quality improvement projects for price statistics as part of an overall inter-agency program on statistical improvement. The current Statistical Reform Program began in 1998 and ends in 2002. The next Statistics Development Program begins in 2003 and will run through 2007. Although budgetary resources have not been sufficient to implement all of the projects envisaged during the current program, price statistics have been significantly upgraded nevertheless. A CPI improvement project was undertaken during 2000–01 that significantly streamlined the CPI sample, reducing it from 475,000 price records per month to 275,000—without harming national sample coverage—and implementing the COICOP/HBS14 classification, used by Eurostat and derived from the international COICOP household expenditure classification. The PPI is in the midst of implementing Eurostat’s Standard Classification of Economic Activities within the European Communities (NACE) industry classification, derived from the International Standard Industrial Classification of all Economic Activities, Revision 3 (ISIC 3), and Classification of Products by Activity (CPA), derived from NACE product classification—during the first half of 2002—and is now being compiled with an improved central database application.

Data models for the CPI and PPI tend to implement consistency with the national accounts by design. The consumption weights of the CPI and the consumption of the household institutional sector in the national accounts are derived from the same household expenditure survey source. The output weights of the PPI derive from the same industrial survey source used to compile output in the national accounts and to produce the industrial production index. In light of this, reconciliations between the national accounts and price indices are not viewed as worth undertaking.

Time-series consistency is routinely examined monthly between the comparable components of the CPI and PPI. (See 4.3.2)

0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics.

Management views the system of national accounts statistics as the conceptual framework for economic statistics. Within this framework, report forms are reviewed by management and by the staff of the Methodology Division, who cooperate closely with the staff of the National Accounts Department, to ensure consistency of concepts and definitions across survey areas. The Methodology Division works with a small group of enterprises to test the report forms. The analytical and reconciliation process of compiling the input-output tables serves as a check on the quality and consistency of the components of the system of national accounts.

Reviews are undertaken of all unusual movements in the price data received at the regional and central office levels and are traced back to the reporter if necessary. For the PPI, personal visits are made twice a year to verify responses received principally by mail.

Regional office error performance in data collection for all price programs and in elementary index calculations is routinely tracked, and problems are addressed with regional managers.

The SSCU’s General Information Department checks all publications for accuracy regardless of frequency of release. Quarterly reviews are made of regional publications by the headquarters staff and recommendations made on accuracy, format, and presentation (including use of graphics). Annual reviews of regional publications make recommendations on quantitative and descriptive content.

Presently, there is no body distinct from the SSCU that provides guidance on the quality of the statistical series and on strategies for improving data production. A high-powered Statistical Council attached to the office of the President, that existed some time ago, could be revived for this purpose with appropriate modifications in its structure.15

As part of execution of the Presidential Regulation on the Observation of Prices and Tariffs, in effect for 2001–03, government policy users have been surveyed to provide their views on how well SSCU’s price statistics suit their needs and what additional or changed information they would like to see. There are no formal surveys of nongovernment users. As the CPI, in particular, is used for a variety of administrative indexation purposes however, it enjoys an active user base inside and outside the government. SSCU’s Price Department reports that it routinely receives 40–50 letters a month on price programs as a whole and received 543 letters on the CPI alone during 2001. The SSCU’s website is generating large volumes of electronic mail, and there are frequent telephone inquiries.

0.3.3 Processes are in place to deal with quality considerations, including trade-offs within quality, and to guide planning for existing and emerging needs.

Although SSCU’s price indices are required by regulation to be quite timely, with release by the tenth of the month following the reference month (see 4.2.1), the Price Statistics Department staff does not experience a conflict between timeliness and quality. All checks are routinely completed within the available processing and review window, which is said to allow some flexibility in the time allocated for regions to report to the central office.

1. Integrity16

1.1 Professionalism

1.1.1 Statistics are compiled on an impartial basis.

Article 5 of the Statistics Law ensures the professional independence of the SSCU as the central executive body for statistics. It forbids interference of State and local authorities, officials, public associations, and other persons in the work of the SSCU. The SSCU is an independent organization with its own set of financial accounts and identifiable seal. According to the Presidential Decree of November 6, 1997 (No. 1249/97), the chairperson of the SSCU is appointed by the President on the recommendation of the Prime Minister, and reports to the President and the Cabinet of Ministers. The chairperson is responsible for ensuring professionalism in statistical activities.

The civil service law determines staff recruitment qualifications for the statistical and other job series needed for SSCU’s work program. As noted in 0.2.2, staff compensation is determined by the individual level of accomplishment in meeting the objectives of the statistical work program. Professional skills in statistics and economics are considered in determining the level of compensation and eligibility for promotion.

1.1.2 Choices of sources and statistical techniques are informed solely by statistical considerations.

Articles 5, 7, 8, and 9 of the Statistics Law provide guarantees of independence in the selection of the methodology, data sources, content, and format of the data disseminated by the SSCU, and the SSCU’s Price Department reports no external interference in the conduct of its work.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.

SSCU is empowered by Article 13 of the Statistics Law to comment on cases of misuses or misinterpretation of statistical information. When it has significant disagreements about the technical merits of public statements made about SSCU’s statistics, SSCU communicates—either in print or via other appropriate public modality, or via direct private communication—with the issuers or authors of the statements in contention.

1.2 Transparency

1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

The Statistics Law is a public document and available to the public on the official website of the SSCU. Statistical publications provide contact information where more information about the data producing agency and its products can be found.

1.2.2 Internal governmental access to statistics prior to their release is publicly identified.

Article 14 of the Statistics Law guarantees equal access to all data users. Accordingly, the data are released simultaneously to all interested parties. The SSCU and its Price Statistics Department provide no access to anyone outside the SSCU to the price statistics SSCU publishes until they are released.

1.2.3 Products of statistical agencies/units are clearly identified as such.

All government publications of SSCU’s data are required to properly attribute them to SSCU.

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.

Advance notice of changes in methodology are provided in the programs of statistical development. The changes in methodology to be undertaken during the current year is given in the annual plan of the SSCU. This document is public and provided to major users. Although users also are informed via notes in the CPI methodological manual and annual bulletin of methodological changes after their implementation, no additional advance notice is given to users of pending changes in the monthly Express Report. An additional alert in the Express Report, just prior to implementation, would be advisable to ensure that users are advised in advance of methodological changes.

1.3 Ethical standards

1.3.1 Guidelines for staff behavior are in place and well-known to the staff.

Article 17 of the Statistics Law requires all employees of state statistical bodies to protect confidential information from disclosure. The Civil Service Code provides for penalties for misuse of public property and confidential information by government employees. Staff are informed by management of these regulations and must commit to abiding by them as a condition of employment.

2. Methodological soundness

2.1 Concepts and definitions

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

The concepts and definitions employed in the CPI fit within the requirements of the 1993 SNA and the guidance in Consumer Price Indices, An ILO Manual (1989).

2.2 Scope

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

The scope of the Ukrainian CPI broadly follows international practice in including almost all monetary consumption expenditure. However, it excludes transactions in used goods. No nonmonetary expenditure is covered. 17

2.3 Classification/sectorization

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

The Ukrainian CPI employs international expenditure classification standards. It uses the Eurostat COICOP/HBS expenditure classification, which derives from the COICOP. Its institutional sector coverage follows international practice, comprising the 1993 SNA household institutional sector except for certain conventional exclusions, namely: households residing in rural areas, persons living on military bases, and residents of hospitals and prisons. The CPI covers the urban population, which comprises about 68 percent of the total as of 2001.18

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

The CPI weights and prices use market (e.g., actual transaction) prices to value monetary consumption. The detailed product specifications attempt to include the most important price determining characteristics, in the judgment of the collector, of the elementary items or varieties included in the index. They may or may not be tracked in computerized databases to facilitate the detection of changes in detailed product specifications, depending on the computer resources of the regional office collecting the prices.

2.4.2 Recording is done on an accrual basis.

The weights and the base prices of the CPI cover the full reference year and the monthly price observations are distributed over the month and collectively refer to virtually the full month of collection, from the first through the twenty-fifth. The weights are based on the obligations households accrue in making goods and services transactions rather than the payments they make. The weights thus incorporate adjustments for payments arrears where relevant, as in the case of the communal utility services provided by municipalities, and incorporate the entire purchase value of items acquired on credit.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.

Not applicable, as used durable goods and owner-occupied housing are excluded.19

3. Accuracy and Reliability

3.1 Source data

3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions.

Source for CPI weights: The source for the CPI weights is the HLCS, which is comprehensive, frequent (quarterly), timely (eight-month processing lag), and employs international best practice in its design and compilation methodology. The sampling frame for the HLCS is based on the most recent available population census (1989), updated by vital statistics on births and deaths.20 It includes critical information for area sampling—such as accurate household addresses and variables such as income and household size that are correlated with total expenditure—and is considered a comprehensive and accurate list of households for sample selection. The HLCS uses a modern, multistage randomized area sample design in selecting households from the frame.

Source for CPI prices: The sampling frame for the first stage of the CPI price sample, in which a set of districts (rayons) are selected within each of the 26 regions (oblasts) other than Kyiv (which comprises a single district), meets international standards for comprehensiveness and applicability to the CPI. This “area frame” of districts is further stratified by population size before selection of the district sample. Total consumption expenditure would be a better measure of district size than population for stratification of the district frame by size and selection of districts within stratum. Like most CPI price surveys worldwide however, total expenditure data are not available for every district, and thus, their coverage is not comprehensive enough for sample selection. Based on past experience from CPI surveys worldwide, area population is statistically correlated with area total expenditure across areas, and population is thus a reasonably good proxy for the desired measure of district size. Like many other countries, Ukraine has no sampling frames available for the second stage of area sampling, in which retail outlets are selected for each of the 270 item groups, as well as the third stage, in which elementary items or varieties of goods and services are selected within each outlet.

Although at some stage the business register21 for retail enterprises might be used as a frame for the selection of retail outlets within district, the speed of business formation and dissolution in the retail sector mitigates the relevance of a register as a sampling frame for the CPI unless it is very current. Were it to be used, supplementary canvasses probably would be required within at least some of the selected districts in which too large a number of unproductive (e.g., closed or of undetermined location) sample “hits” of retail outlets were encountered. In addition, the register would not be able to differentiate among the product lines handled by retail establishments because such information is not collected on the register. Thus, register-based district samples of retail outlets would have to be “post-stratified” by product line and be sufficiently large to produce a regional (oblast) sample of establishments dealing in product lines covering the 270 item groups of the CPI. Use of the register, with supplementation as needed, would be a medium-term option for improving the practice of selecting the establishment sample, depending on SSCU’s success in keeping the register current within reasonable resource constraints and whether the register-based sample could be shown to produce more representative retail outlet samples by CPI item group than the current judgmental procedure.

In view of the recent streamlining of the CPI sample that reduced it by almost 60 percent to about 23,000 outlets and about 275,000 price records per month, it may be feasible to implement a “disaggregation” technique for probabilistically selecting product varieties (elementary items) within each outlet. Use of this technique would improve the representativeness of the sample of elementary items, at the cost of additional training for regional staff. It is thus a medium-term option subject to resource constraints and the priorities of SSCU’s overall statistical program.

Refinements in the outlet and elementary item sample such as those noted generally lead over time to further opportunities for optimizing and reducing the size of the national sample without sacrificing its representativeness or materially reducing the precision of the CPI in estimating the national level and rate of change in the prices faced by households. These additional reductions often are not achieved with proportional reductions in survey cost, however, owing to the increased cost per price record of selecting and maintaining the sample with the more systematic methods.

A final point regarding the CPI sample design is that the HLCS is large enough to produce sufficiently accurate weights only for Ukraine’s eight economic zones plus Kyiv, but not for all 27 regions. Hence, in the current CPI all regions in an economic zone are compiled with the same set of zone expenditure weights. The CPIs for regions within a zone are unique nevertheless because there are region-specific price samples. In view of this, Ukraine’s users inside and outside the government might find the nine-zone level CPIs to be almost as useful as the 27 regional CPIs produced now. Were this the case it would, in turn, enable a still smaller CPI sample. SSCU might use some of the regional staff resources released by this reduction in the number of establishments and elementary items in the sample to train the data collectors and allow them to implement the disaggregation methodology for selecting elementary items.

3.1.2 Source data reasonably approximate the definitions, scope, classification, valuation, and time of recording required.

The HLCS is representative of the entire population of households resident in Ukraine that is not institutionalized. Data are collected on consumer expenditures at purchasers’ prices and are properly aligned in time with the recall period of the survey.

The CPI price sample is representative of monetary transactions in urban areas for the goods and services used by households for consumption, with the exception of used goods.

3.1.3 Source data are timely.

The HLCS is continuous, producing quarterly information on household expenditures with a processing lag commendably short enough to permit the CPI weights to be updated annually with expenditure information for the previous year that is about eight months old.

The CPI sample is commendably timely, with a processing lag short enough to release the index within 10 days of the end of the reference month, exceeding SDDS requirements.

3.2 Statistical techniques

3.2.1 Data compilation employs sound statistical techniques.

CPI data compilation employs sound statistical techniques.

The goods and services detail of the weights of the Ukrainian CPI, comprising 270 items, is appropriate.

As noted in 2.4.2, the weights are compiled on an accrual basis, taking account of payment arrears and including the full purchase price of items acquired on credit.

The CPI is compiled in two stages. The first stage, performed in the regional offices, is to aggregate prices of the elementary items for the current and previous months into a price index for one-month change for each of the 270 item groups in each of the 27 regions. This calculation uses a ratio of averages or Dutot formula. The second stage, performed in the Price Statistics Department at headquarters, is to aggregate the 270 short-term price indices reported by each of the 27 regions into the national index. This calculation uses a modified Laspeyres formula.

There is an improvement that should be made to the methodology of calculating the item indices. The SSCU’s Price Department is aware of the issue but notes that its quantitative impact on the index is likely to be small at present because of the small expenditure weight of the item groups, mainly fresh fruits and vegetables, that are most affected.

The calculation of elementary aggregates does not carry forward imputed prices for elementary items that are temporarily missing due to seasonal unavailability and other short-term factors. As a result, for such items, the index is not “self-correcting” in the sense that the direct item group index for the period between the month of the last price observation and the month observation resumes is not the same as the item index actually calculated. The actually calculated item index is the product or chain of month-to-month changes between the month of last observation and the month observation resumes. The month-to-month chaining method will produce the same result as the direct index only if the prices of temporarily missing elementary items are imputed from month to month.

There are distinct advantages to the chaining method actually employed by SSCU in computing item indices—precisely in the case when there are temporarily missing items—because it effectively imputes the short-term price change of the item group to the prices of missing elementary items and produces smoother and arguably more accurate results than; for example, imputing the long term price change of the elementary item index from the index base period. However, it would be desirable to compute the elementary item indices by updating the imputed prices each month so they are “self-correcting” to ensure the most accurate long-term level of the item indices.

In the near term, correction of the item index imputation problem would involve training the 540 field staff and assuring they implement the revised calculation procedure. The Price Statistics Department observes that the size of this implementation problem is now logistically smaller with the reduced CPI sample than it would have been in the past. The Price Statistics Department also concurs that this problem could be handled entirely by computer if the CPI database were configured like that of the PPI, where all index compilation occurs in the central office using a unified database of elementary item price records.

Quality adjusted direct comparisons are not performed in the CPI when a replacement elementary item is substituted for another that has become unavailable or when the detailed specifications of a currently followed elementary item have changed. Instead, the new item is brought into the calculation of the short-term item index after two months of data are available. This is equivalent to an implicit quality adjustment if there are one or more months of overlap between the new and old items. New products are detected as a result of the normal sample replacement process, but there are no special efforts to scan for new products over and above replacement of permanently unavailable elementary items.

3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.

The CPI expenditure aggregate covers 97 percent of national accounts household consumption.

In view of its coverage, the CPI is the basis for the deflator for household consumption in the national accounts.

Household capital formation in the form of net acquisitions of dwellings is not covered in the CPI.

3.3 Assessment and validation of source data

3.3.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide planning.

A full range of measures of error is available in principle for the CPI weights, as they are estimated for each economic zone from the HLCS, which sample design and methodology permits calculation of standard errors on expenditure estimates and of the impact of the nonresponse adjustments included in the household survey sampling weights. The Department of Household Surveys routinely assesses the accuracy of the standard aggregates produced from the HLCS.

Regarding CPI prices, no sampling errors are available, as the CPI does not use a random-sampling design. Unusually large movements in item indices are traced back to the reporting retail outlet if necessary and verified. Verified prices and elementary indices are included in the index on verification or corrected if found to be in error. There are no procedures for eliminating unusually large movements in prices from the index.

There are administrative sources of the statistical price data used in the CPI, such as the rates charged for communal utility services, municipal transit fares, and so on. These data are presumed accurate and are not routinely checked, except on the occasion of unusually large price movements.

Attempts are made to keep the sample size large enough in covered urban areas so that prices are obtained for all 270 item groups in the CPI.

All CPI source data for expenditure weights and prices are consistent with CPI concepts regarding price and expenditure definition, valuation, reference periods, and classifications.

When the CPI weights are updated, they are reviewed both in terms of change in the weights and in terms of their differential impact on the index as compared with the old weights.

There are no formal and routine assessments of sample error or response and other nonsampling error, but there is attention given to turning around nonrespondents or slow respondents, and this knowledge is used to guide survey planning.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Main intermediate data are validated against other information where applicable.

Item indices from the CPI are routinely compared with similar product or industry indices from the PPI in SSCU’s annual publications.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

As noted, unusual movements in item indices are checked and traced back to the reporting outlet if necessary.

3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated.

The CPI is imputed in only one way, so that aggregation first by areas and then by items yields the same result as aggregating first by items and then by areas. There are, therefore, no discrepancies arising from different imputation schema.

The index weights are monitored annually, as the index is revised and the sample of outlets reallocated toward items whose share has significantly increased.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes.

The Ukrainian CPI is not revised once published. However, the impacts of weight updates are examined to inform development of price samples.

4. Serviceability22

4.1 Relevance

4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

The CPI and PPI enjoy an active user base and the Price Statistics Department receives a large number of contacts from users in and out of the government; though government users are a particular source of inquiries. The Department incorporates changes in its publications within its resource and confidentiality constraints to meet the most common user requests, and special tabulations are made in some cases. Although a recent Presidential Order on price statistics is aimed at facilitating—among other things—collaboration with users, there is no formal advisory group or users’ survey to assess the relevance of the price programs.

4.2 Timeliness and periodicity

4.2.1 Timeliness follows dissemination standards.

The CPI and PPI are released within 10 days of the end of the reference month, bettering the SDDS requirement that they be published within one month of the reference month.

4.2.2 Periodicity follows dissemination standards.

The CPI and PPI are monthly indices, as required by the SDDS.

4.3 Consistency

4.3.1 Statistics are consistent within the dataset.

The CPI and PPI are imputed in only one way, so that the order of aggregation does not affect the all items index. There are, therefore, no discrepancies arising from different imputation schema.

4.3.2 Statistics are consistent or reconcilable over a reasonable period of time.

The CPI and PPI are annually chained. Disaggregated data for the CPI for the months of August through July, with base of the year prior to August equal to 100, may be aggregated using the previous year weights to obtain higher-level aggregates and the all items index.

Owing to chaining, these aggregations are not exactly comparable between months with weights from different base periods.

The imputation of missing prices arising from seasonal availability and supply interruptions is not “self-correcting” because imputations are not carried forward on the monthly pricing forms by the regional office staff. The items affected by this now comprise about 1 percent of index weight, but the problem can be expected to become more serious as economic conditions improve.

4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.

Item indices from the CPI are routinely compared with similar product or industry indices from the PPI in SSCU’s annual publications. The oil and gas index for the PPI is compared with the oil and gas data of a major public oil and gas corporation.

4.4 Revision policy and practice

4.4.1 Revision follow a regular, well-established, and transparent schedule.

The index weights of both the CPI and PPI are updated annually with full year expenditure and output data, respectively, for the previous calendar year. The new weights are normally introduced with data published in the June Express Report each year for the PPI and the August Express Report for the CPI.

4.4.2 Preliminary data are clearly identified.

There are no revisions to published CPI or PPI data; published data are final.

4.4.3 Studies and analyses of revisions are made public.

Studies of the impacts of annual weight revisions are not disseminated in existing publications but would be appropriate for the annual CPI and PPI bulletins.

5. Accessibility23

5.1 Data accessibility

5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

Although a CPI index with December 1997 = 100 is published in the Government Courier every month, as required by a 1998 law on indexation of wage arrears, there is no table containing a time series of all of these monthly CPI values calculated with a given reference period. Constructing such a table requires a user to reference many monthly issues of the Courier. The CPI and the PPI annual bulletins contain a table showing the December values of these indices relative to December 1990, but there is no table for either index showing all of the months over the published period relative to December 1990 or some other given reference period. The lack of a long time series of five years or greater length, with a given reference base, does not meet international good practice for index publication.

The other analytical tables presented for the CPI and PPI are clear and present the change in the indices since December of the previous year, since the same month of the previous year, and since the previous month, as well as breakdowns by aggregates of goods and services. It should be noted that all of these tables for the all-items CPI and PPI could be generated from a single long time-series table.

5.1.2 Dissemination media and formats are adequate.

Data are transmitted simultaneously by mail, electronic mail, and fax to all interested parties.

5.1.3 Statistics are released on a pre-announced schedule.

An advance release calendar is available on the SSCU’s website.

5.1.4 Statistics are made available to all users at the same time.

Data are transmitted simultaneously by mail, electronic mail, and fax to all interested parties.

5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request.

Nonpublished special tabulations of data that satisfy SSCU’s disclosure requirements are available on request.

5.2 Metadata accessibility

5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

Methodology pamphlets on the CPI and PPI methodology have been produced and are in limited circulation within the government. A full methodology publication on major SSCU’s data series is in preparation for general release.

5.2.2 Levels of detail are adapted to the needs of the intended audience.

SSCU’s publications and on-request tabulations meet a wide range of user preferences regarding display of detail by region and by product for the CPI and by region, industry, and product for the PPI.

5.3 Assistance to users

5.3.1 Contact person for each subject field is publicized.

A contact person with telephone number is provided on the inside of every price statistics publication.

5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available.

SSCU publishes a comprehensive print catalogue of all of its publications.

Table 2.

Ukraine—Data Quality Assessment Framework: Summary of Results for Consumer Price Index

(Compiling agency: State Statistics Committee of Ukraine)

Key to symbols: NA = Not Applicable; O = Practice Observed; LO - Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Not Observed; SDDS = Complies with SDDS Criteria

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III. Price Statistics (Producer Price Index)

0. Prerequisites of quality24

0.1 Legal and institutional environment

0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified.

The current Statistics Law of Ukraine adopted by the Parliament on July 13, 2000 (No. 1922-III) and effective January 1, 2001 defines the roles and responsibilities of state statistical agencies. Decrees/resolutions/orders of the President and Cabinet of Ministers clearly specify the responsibility for collecting, processing, and disseminating price statistics.

As defined by the Statistics Law, the state statistical agencies consist of a central executive agency, and territorial and functional statistical units established by this agency and subordinated to it. The current Statistics Law is a revised version of an earlier law that was adopted in 1992. It was revised with a view to making Ukraine’s statistical legislation consistent with international best practices. The current law is supplemented by the Presidential Decree of April 14, 1995 (No. 312/95), which establishes the State Statistics Committee of Ukraine (SSCU) as the central executive agency for official statistics. Under Article 12 of the Statistics Law, the SSCU is, therefore, responsible for collecting, processing, aggregating, analyzing, disseminating, storing, and protecting statistical information. A further Presidential Decree of November 22, 1997 (No. 1299/97) mandated the development of an integrated system of statistics according to international standards and directed the Cabinet of Ministers to make legislative, regulatory, and financial arrangements to support the new statistical system.

0.1.2 Data sharing and coordination among data-producing agencies are adequate.

Price statistics are produced with data compiled within the SSCU’s Price Statistics Department in cooperation with other SSCU’s departments and do not directly require interagency cooperation.

0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only.

The legislative basis for protecting the confidentiality of the respondents’ data is strong. Management is sensitive to issues regarding confidentiality of statistics and takes appropriate steps to ensure that respondents’ data are well-protected.

Articles 21 and 22 of the Statistics Law state that the SSCU is prohibited to disseminate personal and confidential statistical information without prior permission of the respondent. The Articles forbid state and local authorities, citizens associations, officials, or private authorities from obtaining such information. However, other legislation—particularly, legislation regulating the work of law enforcement agencies—had not been fully harmonized with the new statistical law, which resulted in conflict and litigation. In all instances, the courts of law have supported the SSCU. At the initiative of the SSCU, appropriate amendments have been introduced to remove provisions in other legislation that contradict the statistical law.

Under Article 17 of the Statistics Law, the staff of statistical agencies is required to comply with the requirements for protecting confidential information. The access to confidential data by the staff is only for official purposes. Staff, who disclose confidential data, are liable to punishment under Article 20 of the law. Violation of this Article is punishable under the law on Administrative Violations (as amended on July 13, 2000 No. 1929-III). In cases of breach of confidentiality, fines may be imposed on individuals amounting to 3–5 times the pre-tax minimum personal income. For registered economic units and entrepreneurs, the fines are 10–15 times the pre-tax minimum personal income. The fines are higher for repeated violations. Appropriate measures are taken to secure the premises of the SSCU and its computer network to prevent unauthorized access to confidential data.

The CPI data comprise publicly observable retail prices, and the weights comprise aggregated HLCS data protecting individual households’ identities from disclosure. Nevertheless, the CPI is a “mission critical” data series. The computer, on which CPI calculations are performed in the SSCU headquarters, is not connected to the local area network to lower the chance of infection by viruses and is password protected. The PPI data are confidential in the SSCU. The systems, on which the PPI microdata reside and on which the index is calculated, reside at the SSCU’s Computer Center and are protected not only with passwords but also with additional safeguards against physical access by unauthorized individuals.

According to Article 18 of the Statistics Law, respondents are entitled to know what primary data are being collected from them, for what purpose, and who will use them.

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.

Statistical reporting has adequate legislative and regulatory support.

According to Article 13 of the Statistics Law, the SSCU is authorized to obtain the data it requires for its work—including accounting reports, as well explanations of such reports—from central and local government authorities, banks, other statistical units, and individuals. The Article authorizes the SSCU to check the status of the data and the reliability of the information provided by respondents. Article 18 obliges the respondents to provide the required data free to the SSCU. Officials, statistical units, and individuals violating these requirements may be prosecuted and fined. Cases of nonresponse, provision of false, inaccurate, or untimely information are punishable with fines amounting to 3–5 times the pretax minimum personal income for individuals, and 10–15 times the pre-tax minimum personal income for legal units and entrepreneurs. In practice, punishments are rarely applied.

0.2 Resources

0.2.1 Staff, financial, and computing resources are commensurate with statistical programs.

Overall numbers of staff appear adequate. Staff resources for the combined CPI, PPI, and construction price index programs comprising the SSCU’s Price Department were budgeted at the levels indicated in the table below:

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As shown, the current budgeting system routinely tracks staff resource allocation by individual price program in the central office headquarters and Computer Center units, but not in the regions, where an individual staff member may work on two or more programs at various times of the month.

Financial resources have improved recently with economic conditions. In addition to its resources from the government budget, the SSCU earns income from various sources through its “subordinated bodies,” which produce income from special tabulations of data, from publications sales, provision of computer and research services, and provision of specialized training in areas such as accounting.

Computing resources in the headquarters are adequate, comprising a local area network of Pentium personal computers with standard word processing and spreadsheet software. Headquarters computing facilities are used to compile the CPI from 270 item indices, transmitted from each of the 27 regions each month, and to prepare tables and charts for dissemination of the CPI, PPI, construction, and the retail and communications/transport price indices. Budget is very limited for undertaking normal upgrades of hardware and software for the network and its workstations. Maintenance of the headquarters’ network is the responsibility of the SSCU’s Department of Computation—a small headquarters unit distinct from the Computer Center—which handles large-scale data processing.

Receipt of CPI and PPI data from the regions is done via electronic mail to the Computer Center in Kyiv. This plus the maintenance of microdata for the PPI and the calculation of the PPI from a central database are undertaken at the Computer Center.

Computing resources in the regional offices are barely adequate. CPI short-term item indices are calculated in the regions each month either on computers or on calculators, and the results forwarded to headquarters in Kyiv. PPI data entry is done in the regions on old systems with limited memory, storage, and processor power using a custom-programmed application of the Clipper database management system (a clone of the dBase database programming language comparable in many respects to the current Microsoft FoxPro), which admittedly is well-adapted to older generation personal computers. PPI calculation in the Computer Center of the SSCU’s central office uses another custom Clipper program.

0.2.2 Measures to ensure efficient use of resources are implemented.

The SSCU’s Department of Finance and Department of Computation maintains data for each SSCU’s department on staff utilization at headquarters, in the computer center, and in the regions. The managers of the Price Statistics Department do not routinely use these data, since—as noted in 0.2.1—there is no detail on regional utilization of staff for the CPI, PPI, and other price index programs. Regional workload by program is routinely monitored on an informal basis, however, via regular communication with regional office managers.

Staff compensation comprises base salary, a performance based bonus salary, and cash awards for meritorious service. SSCU budgets base and bonus salary by Department, and the level of bonus salary for individual staff is determined both by the total annual bonus budget allocated to the Department and the level of staff performance. Awards for outstanding individual staff performance are made, with adequate justification, over and above the Departmental compensation budget. Staff performance appraisal follows civil service law and regulations that apply throughout the government. Appraisals are given at three-year intervals. The infrequency of appraisals could make it difficult to recognize superior or remediate poor staff performance until a significant amount of time has passed. A flexible performance-based compensation scheme mitigates this inflexibility, however. Departmental managers have the discretion to review and set the bonus portion of staff salaries on the basis of their own judgment of staff performance. This is normally done once a year, but adjustments can be made at any time.

0.3 Quality awareness

0.3.1 Processes are in place to focus on quality.

There is at present no formal quality program. Management is sensitive to issues regarding quality of price statistics and encourages the adoption of procedures for quality checks during data collection, processing, and compilation. (see 3.3 and 3.4)

There have been ongoing quality improvement projects for price statistics as part of an overall inter-agency program on statistical improvement. The current Statistical Reform Program began in 1998 and ends in 2002. The next Statistics Development Program begins in 2003 and will run through 2007. Although budgetary resources have not been sufficient to implement all of the projects envisaged during the current program, price statistics have been significantly upgraded nevertheless. A CPI improvement project was undertaken during 2000–01 that significantly streamlined the CPI sample, reducing it from 475,000 price records per month to 275,000—without harming national sample coverage—and implementing the COICOP/HBS classification, used by Eurostat and derived from the international COICOP household expenditure classification. The PPI is in the midst of implementing Eurostat’s NACE industry classification, derived from the ISIC 3, and CPA, derived from NACE product classification—during the first half of 2002—and now is being compiled with an improved central database application.

Data models for the CPI and PPI tend to implement consistency with the national accounts by design. The consumption weights of the CPI and the consumption of the household institutional sector in the national accounts are derived from the same household expenditure survey source. The output weights of the PPI derive from the same industrial survey source used to compile output in the national accounts and to produce the industrial production index. In light of this, reconciliations between the national accounts and price indices are not viewed as worth undertaking.

Time-series consistency is routinely examined monthly between the comparable components of the CPI and PPI. (See 4.3.2)

0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics.

Management views the system of national accounts statistics as the conceptual framework for economic statistics. Within this framework, report forms are reviewed by management and by the staff of the Methodology Division, who cooperate closely with the staff of the National Accounts Department, to ensure consistency of concepts and definitions across survey areas. The Methodology Division works with a small group of enterprises to test the report forms. The analytical and reconciliation process of compiling the input-output tables serves as a check on the quality and consistency of the components of the system of national accounts.

Reviews are undertaken of all unusual movements in the price data received at the regional and central office levels and are traced back to the reporter if necessary. For the PPI, personal visits are made twice a year to verify responses received principally by mail.

Regional office error performance in data collection for all price programs and in elementary index calculations is routinely tracked, and problems are addressed with regional managers.

The SSCU’s General Information Department checks all publications for accuracy regardless of frequency of release. Quarterly reviews are made of regional publications by the headquarters staff and recommendations made on accuracy, format, and presentation (including use of graphics). Annual reviews of regional publications make recommendations on quantitative and descriptive content.

Presently, there is no body distinct from the SSCU that provides guidance on the quality of the statistical series and on strategies for improving data production. A high-powered Statistical Council attached to the office of the President that existed some time ago could be revived for this purpose with appropriate modifications in its structure.25

As part of execution of the Presidential Regulation on the Observation of Prices and Tariffs, in effect for 2001–03, government policy users have been surveyed to provide their views on how well SSCU’s price statistics suit their needs and what additional or changed information they would like to see. There are no formal surveys of nongovernment users. As the CPI, in particular, is used for a variety of administrative indexation purposes however, it enjoys an active user base inside and outside the government. SSCU’s Price Department reports that it routinely receives 40-50 letters a month on price programs as a whole and received 543 letters on the CPI alone during 2001. The SSCU’s website is generating large volumes of electronic mail, and there are frequent telephone inquiries.

0.3.3 Processes are in place to deal with quality considerations, including trade-offs within quality, and to guide planning for existing and emerging needs.

Although SSCU’s price indices are required by regulation to be quite timely, with release by the tenth of the month following the reference month (see 4.2.1), the Price Statistics Department staff does not experience a conflict between timeliness and quality. All checks are routinely completed within the available processing and review window, which is said to allow some flexibility in the time allocated for regions to report to the central office.

1. Integrity26

1.1 Professionalism

1.1.1 Statistics are compiled on an impartial basis.

Article 5 of the Statistics Law ensures the professional independence of the SSCU as the central executive body for statistics. It forbids interference of state and local authorities, officials, public associations, and other persons in the work of the SSCU. The SSCU is an independent organization with its own set of financial accounts and identifiable seal. According to the Presidential Decree of November 6, 1997 (No. 1249/97), the chairperson of the SSCU is appointed by the President on the recommendation of the Prime Minister, and reports to the President and the Cabinet of Ministers. The chairperson is responsible for ensuring professionalism in statistical activities.

The civil service law determines staff recruitment qualifications for the statistical and other job series needed for SSCU’s work program. As noted in 0.2.2, staff compensation is determined by the individual level of accomplishment in meeting the objectives of the statistical work program. Professional skills in statistics and economics are considered in determining the level of compensation and eligibility for promotion.

1.1.2 Choices of sources and statistical techniques are informed solely by statistical considerations.

Articles 5, 7, 8, and 9 of the Statistics Law provide guarantees of independence in the selection of the methodology, data sources, content, and format of the data disseminated by the SSCU, and the SSCU’s Price Department reports no external interference in the conduct of its work.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.

SSCU is empowered by Article 13 of the Statistics Law to comment on cases of misuses or misinterpretation of statistical information. When it has significant disagreements about the technical merits of public statements made about SSCU’s statistics, SSCU communicates—either in print or via other appropriate public modality, or via direct private communication—with the issuers or authors of the statements in contention.

1.2 Transparency

1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

The Statistics Law is a public document and available to the public on the official website of the SSCU. Statistical publications provide contact information where more information about the data producing agency and its products can be found.

1.2.2 Internal governmental access to statistics prior to their release is publicly identified.

Article 14 of the Statistics Law guarantees equal access to all data users. Accordingly, the data are released simultaneously to all interested parties. The SSCU and its Price Statistics Department provide no access to anyone outside the SSCU to the price statistics SSCU publishes until they are released.

1.2.3 Products of statistical agencies/units are clearly identified as such.

All government publications of SSCU’s data are required to properly attribute them to SSCU.

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.

Advance notice of changes in methodology are provided in the programs of statistical development. The changes in methodology to be undertaken during the current year is given in the annual plan of the SSCU. This document is public and provided to major users. Although users also are informed via notes in the CPI methodological manual and annual bulletin of methodological changes after their implementation, no additional advance notice is given to users of pending changes in the monthly Express Report. An additional alert in the Express Report, just prior to implementation, would be advisable to ensure that users are advised in advance of methodological changes.

1.3 Ethical standards

1.3.1 Guidelines for staff behavior are in place and well-known to the staff.

Article 17 of the Statistics Law requires all employees of State statistical bodies to protect confidential information from disclosure. The Civil Service Code provides for penalties for misuse of public property and confidential information by government employees. Staff are informed by management of these regulations and must commit to abiding by them as a condition of employment.

2. Methodological soundness

2.1 Concepts and definitions

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

The concepts and definitions employed in the PPI fit within the requirements of the System of National Accounts 1993 (1993 SNA) and broadly follow internationally accepted good practices.

2.2 Scope

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

The PPI covers mining, manufacturing, and energy generation and distribution, as well as other utilities such as municipal steam generation (NACE groups C–E). It does not cover shipbuilding, aircraft production, and military production. This coverage is conventional though the PPI in principal covers all market output, including market services. For that reason, coverage of more market-service activities would be desirable.

The PPI’s output weights cover a full year and are compiled from a monthly industry survey by the Industrial Statistics Department.

Enterprises in free trade zones are covered.

2.3 Classification/sectorization

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

Classification of transactions and institutional units follows the 1993 SNA.

Classification of establishments by activity follows Eurostat’s NACE, Revision 1.

Classification of products follows Eurostat’s CPA.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

For each establishment, output produced in a given month is valued at the prices at which units are sold in that month by the establishment.

2.4.2 Recording is done on an accrual basis.

Output is booked in the month in which it is produced, the 1993 SNA accrual principle.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.

The Ukrainian PPI is weighted on a gross output basis, making it a highly useable source for compilation of national accounts volume indicators via deflation. There are no stage of processing indices produced, and thus no grossing or netting done on that score.

3. Accuracy and Reliability

3.1 Source data

3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions.

The data from the monthly industry survey that are used in the PPI—comprising a 50 percent cutoff sample by four-digit NACE industry plus a judgmental sample of small- and medium-sized establishments—cover 80 percent of the aggregate output of the covered industries.

Estimates of output and price indices are produced for four- or five-digit NACE, and five-digit CPA strata. There are weights at the elementary item level within establishment at a nine-digit level of detail, comprising the five-digit CPA plus four digits, to identify varieties of products. Regional PPI staff continuously consult with regional industry statistics staff to pick up new product varieties for incorporation into the index.

New groups of goods and services are picked up during annual updates of output (product) weights and during the process of replacing elementary items that are no longer available.

3.1.2 Source data reasonably approximate the definitions, scope, classification, valuation, and time of recording required.

The source data satisfy the criteria on this indicator to a reasonable approximation.

3.1.3 Source data are timely.

The weights are sufficiently timely to permit annual updates of the weights with previous year output data by June. The price data are sufficiently timely to release the index within 10 days after the end of the reference month, exceeding SDDS timeliness requirements.

3.2 Statistical techniques

3.2.1 Data compilation employs sound statistical techniques.

Sound techniques are employed. The index formula used is Laspeyres at all levels of aggregation. If there are no sales in a given month, the prices prevailing in the most recent month for which there were sales are used. This is conventional for PPIs, though arguments can be made for the same methodology employed in the CPI, which imputes the average price change in the same item group to elementary items with missing prices.

3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.

Not applicable.

3.3 Assessment and validation of source data

3.3.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide planning.

The source data for the weights are routinely assessed and made available by the Industry Statistics Department to the Price Statistics Department to guide planning of PPI compilation. Source data for prices are routinely assessed by the regional offices and the results made available to the Price Statistics Department. However, there are no formal and routine assessments of sample error or response and other nonsampling error, but there is attention given to turning around nonrespondents or slow respondents and this knowledge is used to guide survey planning.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Main intermediate data are validated against other information where applicable.

The PPI is compared with the CPI for comparable products between the CPA and COICOP classifications.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

Unusual movements in the index arising from large movements in particular sectors or from particular reporters are investigated and errors corrected. Explanatory tables are provided in the annual bulletin from which users can glean the sources of index change.

3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated.

Imputations for missing prices are done only one way—by product—for both product and industry price indices. As a result, both breakdowns of indices are consistent in producing the same all items index.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes.

The Ukrainian PPI is not revised once published. However, the impacts of annual weight updates are examined to inform development of price samples.

4. Serviceability27

4.1 Relevance

4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

The CPI and PPI enjoy an active user base, and the Price Statistics Department receives a large number of contacts from users in and out of the government; though government users are a particular source of inquiries. The Department incorporates changes in its publications within its resource and confidentiality constraints to meet the most common user requests, and special tabulations are made in some cases. Although a recent Presidential Order on price statistics is aimed at facilitating—among other things—collaboration with users, there is no formal advisory group or users’ survey to assess the relevance of the price programs.

4.2 Timeliness and periodicity

4.2.1 Timeliness follows dissemination standards.

The CPI and PPI are released within 10 days of the end of the reference month, bettering the SDDS requirement that they be published within one month of the reference month.

4.2.2 Periodicity follows dissemination standards.

The CPI and PPI are monthly indices, as required by the SDDS.

4.3 Consistency

4.3.1 Statistics are consistent within the dataset.

The CPI and PPI are imputed in only one way, so that the order of aggregation does not affect the all items index. There are, therefore, no discrepancies arising from different imputation schema.

4.3.2 Statistics are consistent or reconcilable over a reasonable period of time.

The CPI and PPI are annually chained. Disaggregated data for the CPI for the months of August through July, with base of the year prior to August equal to 100, may be aggregated using the previous year weights to obtain higher-level aggregates and the all items index. Owing to chaining, these aggregations do not obtain on any other time-series comparison.

4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.

Item indices from the CPI are routinely compared with similar product or industry indices from the PPI in SSCU’s annual publications. The oil and gas index for the PPI is compared with the oil and gas data of a major public oil and gas corporation.

4.4 Revision policy and practice

4.4.1 Revision follow a regular, well-established, and transparent schedule.

The index weights of both the CPI and PPI are updated annually with full year expenditure and output data, respectively, for the previous calendar year. The new weights are normally introduced with data published in the June Express Report each year for the PPI and the August Express Report for the CPI.

4.4.2 Preliminary data are clearly identified.

There are no revisions to published CPI or PPI data; published data are final.

4.4.3 Studies and analyses of revisions are made public.

Studies of the impacts of annual weight revisions are not disseminated in existing publications but would be appropriate for the annual CPI and PPI bulletins.

5. Accessibility28

5.1 Data accessibility

5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

There is no table containing a long, multi-year time series of monthly PPI values calculated with a given reference period. Constructing such a table requires a user to reference many monthly issues of the PPI bulletin. The CPI and the PPI annual bulletins contain a table showing the December values of these indices relative to December 1990, but there is no table for either index showing all of the months over the published period relative to December 1990 or some other given reference period. The lack of a long time series, of five years or greater length, with a given reference base, does not meet international good practice for index publication.

The other analytical tables presented for the CPI and PPI are clear and present the change in the indices since December of the previous year, since the same month of the previous year, and since the previous month, as well as breakdowns by aggregates of goods and services. It should be noted that all of these tables for the all-items CPI and PPI could be generated from a single long time-series table.

5.1.2 Dissemination media and formats are adequate.

Data are transmitted simultaneously by mail, electronic mail, and fax to all interested parties.

5.1.3 Statistics are released on a pre-announced schedule.

An Advance Release Calendar is available on the SSCU website.

5.1.4 Statistics are made available to all users at the same time.

Data are transmitted simultaneously by mail, electronic mail, and fax to all interested parties.

5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request.

Nonpublished special tabulations of data that satisfy SSCU’s disclosure requirements are available on request.

5.2 Metadata accessibility

5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

Methodology pamphlets on the CPI and PPI methodology have been produced and are in limited circulation within the government. A full methodology publication on major SSCU’s data series is in preparation for general release.

5.2.2 Levels of detail are adapted to the needs of the intended audience.

SSCU publications and on-request tabulations meet a wide range of user preferences regarding display of detail by region and by product for the CPI and by region, industry, and product for the PPI.

5.3 Assistance to users

5.3.1 Contact person for each subject field is publicized.

A contact person with telephone number is provided on the inside of every price statistics publication.

5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available.

SSCU publishes a comprehensive print catalog of all of its publications.

Table 3.

Ukraine—Data Quality Assessment Framework: Summary of Results for Producer Price Index

(Compiling agency: State Statistics Committee of Ukraine)

Key to symbols: NA = Not Applicable; O = Practice Observed; LO - Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Not Observed; SDDS = Complies with SDDS Criteria

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IV. Government Finance Statistics

0. Prerequisites of quality

0.1 Legal and institutional environment

0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified.

The responsibilities for collecting, processing, and disseminating government finance statistics (GFS) are specified in the Budget Code, enacted by the Parliament of Ukraine on June 21, 2001. Articles 58–62 specify the collection system for budgetary central government, and Article 80 relates to local government. Article 28 instructs the Ministry of Finance (MoF) to make the data available for publication. A formal agreement was signed on 30 March 2001 by the heads of the three agencies concerned, which allocated the responsibilities between the MoF, State Treasury of Ukraine (STU), and the State Statistics Committee (SSCU). This agreement gave the MoF the lead responsibility for GFS.

0.1.2 Data sharing and coordination among data-producing agencies are adequate.

The formal agreement of March 30, 2001 allocated to the STU responsibility for the primary collection and processing of the data, and initial dissemination to the Parliament, to the administrative users and to the MoF. The MoF monitors budget execution, approves the classifications used, and compiles tables for publication and reports for the IMF. The SSCU publishes GFS data in its own publications and uses them to compile government data for the national accounts. The sharing works well; the MoF is able to publish monthly data in 35 days at present and expects to be able to publish within the SDDS requirement of one month from the end of the reference period.

0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only.

Not applicable. No data are collected from public or private corporations or individuals.

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.

The authorities have been introducing a Treasury Single Account (TSA) in stages, through which all transactions pass and are coded appropriately. The coverage of the TSA is expected to be complete for central government from July 1, 2002. Local government revenues are already handled by the TSA; the next step, starting from January 1, 2004, is to cover local government expenditures. Until then, those budgetary institutions not covered by the TSA will provide their data in monthly reports. The Budget Code specifies the timing of reports and authorizes the MoF to determine their format and classifications. The code specifies penalties for noncompliance, but these have not so far been necessary.

0.2 Resources

0.2.1 Staff, financial, and computing resources are commensurate with statistical programs.

There are four members of staff in the GFS section of the MoF dedicated solely to producing the fiscal statistics, and a further four employed on other publication duties. Of the four, two have attended the IMF’s GFS courses in Washington and Vienna. The staff are all university graduates. The Human Resources Department of the MoF also provides training in general financial affairs. These staff are sufficient for current needs, but more resources would be needed to carry out the existing plans for future development.

In the STU headquarters and regions, there are some 14,500 staff, of which only 11 in the Department for Budget Reporting are dedicated solely to producing statistical reports. In the whole organization, there are about 10,000 computers, of which some 3000 are six years old or more. Many computers are shared, and working days staggered to make this possible. The extension of the TSA to cover local government expenditure transactions from the start of 2004 and the planned implementation of the new centralized ledger accounting system by end-2002 is estimated to require an increase in data input of about 40 percent and an increase of about 4,500 staff and computers. In the last year, STU took delivery of 5,000 computers. Sources of finance are the World Bank and the domestic budget. There is concern about the ability of STU to meet the targeted implementation dates for the TSA and the centralized accounting system taking into account the amount of work still to be done and the difficulty of operating an increasingly sophisticated system of accounting with a computer stock that is inadequate and aging.

0.2.2 Measures to ensure efficient use of resources are implemented.

Most of the costs of collecting and compiling data are inextricably part of the STU’s budget-monitoring task and cannot be separately identified. The people interviewed in STU were unaware of any regular monitoring of the efficiency of their operations. In advance of the radical change in methods arising from the introduction of the TSA and its extension to the finances of local government, and the concomitant large increase in staff, an efficiency review is necessary. Such a review would consider the needs of a modern system of budget management, and evaluate the outputs of the organization and their resource costs in that context.

0.3 Quality awareness

0.3.1 Processes are in place to focus on quality.

There is at present no formal quality program, but concern for quality is evidenced by recent developments in the MoF and their plans for improvement. Recent developments include the bringing of published classifications closer into line with GFS standards, the compilation of annual GFS data for the IMF, and the introduction of the TSA. Fiscal data are revised annually to take account of audited information. The ministry’s short- and medium-term plans include measures to implement GFSM 2001.

0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics.

Monthly data on expenditure are automatically validated in the STU’s computer database against amounts assigned. Detailed reports are issued to STU headquarters departments and oblasts for checking before release to MoF and SSCU.

0.3.3 Processes are in place to deal with quality considerations, including trade-offs within quality, and to guide planning for existing and emerging needs.

It is the responsibility of the MoF to review the data received from the STU system; identify deviations from GFS specifications; and correct them as far as possible, and if they cannot be corrected, to explain them to users.

1. Integrity

1.1 Professionalism

1.1.1 Statistics are compiled on an impartial basis.

Article 8 of the Budget Code requires the MoF to authorize budget classifications. The minister acts on the advice of his professional statisticians. Article 58 gives responsibility for designing reports on Budget execution to the STU in coordination with the MoF and the Accounting Chamber of Ukraine. A working group of senior members of these three agencies, chaired by the State Secretary of the MoF, supervises the compilation of fiscal statistics.

1.1.2 Choices of sources and statistical techniques are informed solely by statistical considerations.

Staff of the MoF and the STU is free from political or other influence in choosing the most appropriate sources and methods for compiling GFS.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.

The Head of the Financial and Economic Statistics Division can (and frequently does) respond publicly to erroneous interpretation of fiscal statistics. Explanatory material, to aid in the interpretation of the statistics, is provided to the mass media on request.

1.2 Transparency

1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

The terms under which the statistics are collected, processed, and disseminated are published in the Budget Code and the Budget Law, in the Government Courier (Uryadovy Courier).

1.2.2 Internal governmental access to statistics prior to their release is publicly identified.

No government ministers or officials have access to the data before their release.

1.2.3 Products of statistical agencies/units are clearly identified as such.

The MoF’s publications are clearly labeled as statistical publications, and the individuals involved in the publication are identified on the inside cover. Tables in the SSCU’s publications are attributed to the STU.

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.

The annual Budget Law specifies methodology for the forthcoming year, and consequent MoF orders elaborate the differences from the previous Law. However, such advance notices are aimed primarily at budget management and are not convenient to users of statistics.

1.3 Ethical standards

1.3.1 Guidelines for staff behavior are in place and well-known to the staff.

Staff are bound by the general rules applying to all public service staff, which are set out in the Civil Service Code. There are no special guidelines for behavior of staff involved in compiling and disseminating GFS.

2. Methodological soundness

2.1 Concepts and definitions

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

The fiscal statistics in general follow the concepts and definitions of A Manual on Government Finance Statistics, 1986 (GFSM 1986), but have moved towards the GFSM 2001 in adopting the revised COFOG and in treating privatization receipts as financing rather than revenue.

Plans for migration to the GFSM 2001 have been drawn up in the context of general plans for reform of the State Statistical System. The government has stated that the timing of the later stages of the plan is dependent on the provision of aid.

2.2 Scope

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

The monthly data published relates to budgetary central government, and quarterly statistics relate to budgetary general government. The coverage of the budget has varied over recent years, but in all years omits the transactions of the nonbudget pension fund and social security fund. Information on these funds is available on a quarterly basis but is not included in the published data on central or general government, which cover budgetary accounts. Published time series reflect the changes in coverage. The following table indicates the importance of the pension and social security funds:

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Source: Ministry of Finance

Includes Pension, Social Security, Unemployment, and Accident Funds

The development plan includes the compilation and publication of statistics on the full international definition of central, local, and general government.

2.3 Classification/sectorization

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

The economic classification of transactions and the classification of outstanding debt are consistent with the GFSM 1986. The functional classification from 2002 is consistent with the GFSM 2001 (from 1998 to 2001, GFSM 1986; previously a national functional classification). However, the revised COFOG has yet to be extended to local government. Payments in fulfillment of government guarantees on debt are treated as payments of debt charges. The GFS Division is aware of the detailed provisions of the GFSM 2001 in this area and will be considering individual cases in that context.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

Cash transactions reflecting actual prices are recorded in GFS.

2.4.2 Recording is done on an accrual basis.

The budgetary system, which provides the source data for GFS, operates on a cash basis. Expenditure is recorded when checks clear and revenue when checks paid into the bank. Thus, above the line transactions in GFS are automatically consistent with changes in bank deposits. Since 1998, data on arrears of revenue and expenditure (amounts receivable and payable)—classified by economic category and function—have been collected, so that estimates of accruals can be produced.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.

The practice is in line with international recommendations. The accounting rule underlying GFS in this respect is enforced by Budget Code Article 56(4).

3. Accuracy and Reliability

3.1 Source data

3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions.

The sources are government accounting data for government operations and the debt database of the State Debt Department (SDD).

The Budget Code (Article 58) authorizes the STU to obtain reports from all spending units, including extra-budgetary funds. The STU compiles very detailed summary reports from which the MoF compiles the fiscal statistics. The local government sector is also covered by the STU budget management system.

From 2002, the accounts are consolidated at the relevant level. Previously the coding of transfers did not distinguish the level of government, which was the counterpart payer or recipient, so that consolidation at the level of central or local government was not possible.

3.1.2 Source data reasonably approximate the definitions, scope, classification, valuation, and time of recording required.

The TSA and the budgetary management system have been introduced in stages. From July 1, 2002, all central government budgetary spending units should be covered. From January 1, 2004, local government expenditures should be covered under the TSA, while local government revenues are already handled by the Treasury. For the time being, local government summary tables are adjusted to COFOG by means of bridge tables. From 2003, following the planned implementation of the new centralized ledger accounting system, expenditure data would be aggregated automatically to provide GFS. However, revenue statistics will continue to be calculated by bridge tables in MSExcel spreadsheets.

The debt database of the SDD maintains outstanding debt at nominal values (as required by GFSM 1986) and in the original currencies but in sufficient detail to classify according to the GFS requirements by type of instrument and borrower. In providing debt-related data for fiscal statistics, revaluation to hryvnia is done outside the database.

3.1.3 Source data are timely.

The Budget Code (Articles 58–61) specify the timing of reports. This timing is consistent with SDDS standards and is met in practice.

3.2 Statistical techniques

3.2.1 Data compilation employs sound statistical techniques.

Data compilation is by way of aggregating accounting data, and no special statistical techniques are required. The compilation can be criticized for collecting data that are cumulative from the beginning of the year, but with cash data, the extent of revisions will be extremely small. The revisions between the first 12-month estimates for the year and the final audited annual data are of the order of 0.1 percent. These revisions are attributed to the final month.

3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.

The publication of data with coverage that changes over time to reflect the changing scope of the budget process satisfies the needs of monitoring the execution of the budget, but it is not generally useful. At the meeting to discuss the survey of users, some demand was expressed for series with a consistent coverage. The MoF’s publications contain very few time series, and most tables cover only the current year and one previous year. (see 4.3.2)

3.3 Assessment and validation of source data

3.3.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide planning.

Comparisons are made between the 12 monthly reports and the final audited data. However, the revisions between the first 12-month estimates for the year and the final audited annual data are small.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Main intermediate data are validated against other information where applicable.

The MoF does not compare or reconcile its data with other information. This is not relevant, as accounting information provides full coverage.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

The STU reconciles the treasury ledger accounts with the NBU bank accounts on a regular basis. However, aggregate data on net credit to government are not reconciled with monetary survey data, which raises an issue of consistency among data sources (see 4.3.3).

3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated.

The sources of revenue and expenditure data are, in principle, consistent with banking data, and any discrepancy in balancing the fiscal accounts would be investigated and resolved.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes.

Revisions are minuscule.

4. Serviceability

4.1 Relevance

4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

There are no formal surveys of user requirements, but staff are in frequent contact with users in meeting data requests. Budget sector statistics, using GFS consistent classifications, are used within the government itself to monitor the impact of the budget sector on fiscal policy and for fiscal analysis more generally. General government (and public sector) and GFS are mainly used for program development purposes within the annual budget process.

GFS, on the coverage and classifications of GFSM 1986, were compiled in 2001 for the first time—solely for publication in the IMF’s Government Finance Statistics Yearbook (GFSY)—and are not used or published in Ukraine.

In general, users appear to be largely unaware of the potential uses of GFS, and there is currently little demand for these statistics outside the government itself. In part, this may reflect the lack of complete and easily understandable GFS.

4.2 Timeliness and periodicity

4.2.1 Timeliness follows dissemination standards.

Timeliness largely meets SDDS standards. Subject to the exclusion of the pension fund and social security funds, monthly central government operations statistics are available approximately 25 days after the end of the reference period but only released to the general public after a lag of 35 days. Quarterly debt figures are published within 45 days. Annual operations data based on audited accounts are required by the Budget Code to be published by June 1, five months after the end of the year.

4.2.2 Periodicity follows dissemination standards.

Periodicity meets SDDS standards. Subject to the qualifications on scope, central government operations data are published monthly and annually, and general government operations data are published quarterly. Central government debt statistics are published monthly, quarterly, and annually.

4.3 Consistency

4.3.1 Statistics are consistent within the dataset.

The derivation system ensures consistency within the dataset.

4.3.2 Statistics are consistent or reconcilable over a reasonable period of time.

Data published for each year relate to the budget coverage in that year. Differences in scope or classification between the current and previous year are explained in the annual publication. They are also given in advance in Budget Laws and MoF Orders. However, breaks in series are not indicated on tables and can only be identified by working back through the publications of previous years.

4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.

While the STU reconciles treasury ledger accounts with the NBU bank accounts on a regular basis, there is no reconciliation of treasury data on net credit to government with information from the monetary survey.

4.4 Revision policy and practice

4.4.1 Revision follow a regular, well-established, and transparent schedule.

Revisions arise only from one source—the incorporation of audited annual accounts. This takes place in June each year.

4.4.2 Preliminary data are clearly identified.

The first estimate for the year—the 12-month estimate—is labeled as preliminary.

4.4.3 Studies and analyses of revisions are made public.

Revisions are minuscule.

5. Accessibility

5.1 Data accessibility

5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

GFS are available monthly but do not provide the equivalent coverage to that set out in the GFSM 1986 tables. The data formats are more suited to the short-term needs of monitoring the execution of the budget in the current year. Users would need to make a substantial effort to assemble the data required for broader fiscal analysis, and long-term analyses would be virtually impossible.

STU maintain databases of input and summary data. A separate database is opened for every year, reflecting the Budget Law for that year. These databases are accessible to STU headquarters’ staff as necessary. Detailed data is sent in the form of electronic reports to the MoF, SSCU, and the Ministry of Economy. Databases for earlier years are archived. The MoF is considering the creation of a database, which could be accessible to outside users as part of their development plans.

5.1.2 Dissemination media and formats are adequate.

Publications containing fiscal statistics are shown in the following table.

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Contains fiscal statistics and other macroeconomic indicators

Also contains commentary

The SSCU has a website, on which the fiscal data are irregularly posted. In addition, the MoF has recently set up a website, on which it publishes fiscal data. However, it is noted that the current procedures lead to a delay of two days after the release of data before they appear on the MoF’s website.

5.1.3 Statistics are released on a pre-announced schedule.

An advance release calendar (ARC) is disseminated on the website of the SSCU (www.ukrstat.gov.ua) but is not maintained current. The availability of the ARC will be publicized in the future in the MoF’s publication, Monitoring of Budget Execution.

5.1.4 Statistics are made available to all users at the same time.

Government operations data are released simultaneously to all interested parties (even to the MoF) in the monthly flash estimates, Preliminary Monitoring of Budget Execution, and in the monthly publication, Monitoring of Budget Execution, which are also disseminated on the website of the MoF (www.minfin.gov.ua).

The debt data are released simultaneously to all interested parties by publishing the quarterly bulletin, Analytical Papers on Government Debt, copies of which can be obtained on request from the MoF. In addition, the publication is posted on the MoF’s website.

5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request.

Unpublished (but nonconfidential) sub-aggregates are made available upon request. However, the availability of such data, and the terms and conditions on which they are made available, are not publicized.

5.2 Metadata accessibility

5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

Documentation exists in the form of Budget Code and Laws, but other than summary notes with the data in some of the periodicals, there is no documentation aimed specifically at the user, nor do the laws make specific reference to international standards, nor the accounting framework on which the statistics are based.

5.2.2 Levels of detail are adapted to the needs of the intended audience.

Not applicable.

5.3 Assistance to users

5.3.1 Contact person for each subject field is publicized.

Compilers in the MoF are named on the inside cover of MoF’s statistical publications. A general MoF telephone number and address are also given.

5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available.

The MoF produces no such catalogues.

Table 4.

Ukraine—Data Quality Assessment Framework: Summary of Results for Government Finance Statistics

(Compiling agency: Ministry of Finance)

Key to symbols: NA = Not Applicable; O = Practice Observed; LO - Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Not Observed; SDDS = Complies with SDDS Criteria

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V. Monetary Statistics

0. Prerequisites of quality

0.1 Legal and institutional environment

0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified.

The National Bank of Ukraine (NBU) is the sole official agency in charge of collecting, compiling, and disseminating monetary statistics. The legal authority of the NBU to request any information and data for monetary statistics purposes is stated in Articles 57 and 67 of the Law of Ukraine on the National Bank of Ukraine, No. 679-XIV of May 1999, as amended on January 10, 2002. Article 57 specifies that for the preparation of banking and financial statistics and for economic analysis, the NBU is entitled to obtain necessary information from government agencies and businesses of all types of ownership. Article 67 gives the NBU the authority to request any information from banks and financial institutions located on the territory of Ukraine and to define the forms and procedures for such reporting.

Article 68 of the NBU Law specifies that, in order to ensure transparency of banking operations, the NBU should issue a monthly statistical bulletin, Visnyk of the NBU, which is a monthly magazine dealing with various aspects of banking activities, publish the current banking information on monetary statistics (provided that these statistics do not relate to state and banking secrets), and provide monetary data in accordance with international treaties.

The Economic Department of the NBU is responsible for improvements in the statistical methodology, data collection, compilation, verification, processing, and dissemination of monetary and financial statistics, and for making the information public. The Monetary and Banking Statistics Division of the Economic Department receives the accounting data on the NBU, commercial banks, and financial institutions from the Accounting Department and Information Technologies Department. In addition, the Economic Department receives supplementary information from NBU’s various departments that is also utilized in the compilation of monetary statistics. All inquiries about monetary data are directed to the Economic Department’s Monetary and Banking Statistics Division.

0.1.2 Data sharing and coordination among data-producing agencies are adequate.

Within the NBU, there are arrangements in place to ensure the smooth flow of information between the Accounting Department, Information Technologies Department, NBU’s other departments, and the Economic Department’s Monetary and Banking Statistics Division. Banks’ and financial institutions’ balance sheet information and supporting schedules, used for the compilation of monetary and financial statistics, are also utilized by the General Banking Supervision Department and NBU’s other departments.

Data on reserve requirements, government securities statistics, and deposit and lending rates are calculated by the Monetary Policy Department of the NBU. Statistics on international reserves are compiled by the Foreign Exchange Regulation Department.

In preparing and disseminating data with regard to possible subscription to the SDDS, the Ministry of Finance (MoF), the State Statistics Committee of Ukraine (SSCU), and the State Treasury of Ukraine (STU) are also involved. Meetings are held between the various agencies when necessary.

0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only.

Monetary statistics do not disclose data of individual institutions or transactions. Confidentiality of individual information is protected by the NBU Law, the Statistics Law No. 2614–XII, and by the Law of Ukraine on Information No. 2657–XII. Articles 57 and 67 of the NBU Law forbid the publication or disclosure by the NBU of any statistical information having a private and personal nature, except for cases provided by the legislation of Ukraine.

On December 12, 2001, the Board of the NBU adopted the resolution on The Procedure of Handling Confidential Information in the NBU that approved (i) the regulation on the protection of confidential information in organizational units of the NBU, (ii) instructions on the procedure for the formation, processing, recording, storage, and use of documents, files, publications (including electronic documents), and other material data bearers of information that contain bank secrets and “not for publication” information in organizational units of the NBU.

Only authorized staff members of the NBU have access to the data of individual banks before they are aggregated and consolidated for publication. Procedures are in place so that data are consolidated and aggregated as necessary, so as to prevent individual disclosure. Access to the internal database is limited to the authorized staff; differentiated degrees of authorization give differential degrees of access to the data. Computers are password protected.

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.

Articles 57 and 67 of the NBU Law provide the legal basis for the collection of statistical information that supports the compilation of monetary statistics. The NBU is authorized to request directly, and collect statistical and other information necessary for performing regulatory and supervisory functions, from banks and financial institutions, and other subjects engaging in economic activity. The NBU is also authorized to investigate and supervise the accuracy of the statistical information provided by the concerned parties, and to request additional information and documents. Each report form and supporting schedules for collecting information from banks indicates the timeliness for submitting the requested information to the central bank. According to the Resolution of the Board of the NBU of May 26, 2000 No. 215 on the regulation on enforcement of measures against banks and other financial institutions for violating banking laws, failure to comply with the above-mentioned reporting requirements is punishable by a fine. The regulation determines that in case of submission of incorrect information and reporting, as well as failure to submit information, or in case of a late submission of required information, a fine would be imposed in the amount of 500 times the nontaxable minimum monthly income. In practice, the penalties have not been enforced; the NBU considers that nonresponse is not possible in practice because all banks and financial institutions have to be connected to the automated processing system for accounting information.

According to Article 69 of the Law on Banks and Banking Activity, all banks operating in Ukraine are also required to submit their annual balance sheets and income statements, along with the reports of their boards of directors and auditors to the NBU, after their general assembly meetings, and the reports of independent auditing institutions after the date of preparation.

0.2 Resources

0.2.1 Staff, financial, and computing resources are commensurate with statistical programs.

The Monetary and Banking Statistics Division has a total of 24 staff, 11 of which are professionals primarily devoted to the compilation of monetary statistics. Five of them are also responsible for statistical concepts and methodology, and the improvement of the coverage and accuracy of monetary data.

Employment in the Economic Department is competitive, and the number of staff with university degrees in economics, banking, or statistics is high. Besides on-the-job training, staff are given the opportunity to participate in courses conducted by the IMF (especially the Monetary and Financial Statistics training courses) and in seminars offered by central banks, such as that of Germany, France, England, Italy, the Netherlands, and Japan. In addition, staff has the opportunity to attend the internal training organized by the NBU. Staff turnover is not high.

Computer resources utilized in the collection and compilation of monetary statistics are adequate. The data collection system is highly computerized. All reporting financial institutions submit their returns through the Information Technologies Department, which performs validation checks on the data before releasing them to the next stage in the production cycle. The NBU’s and commercial banks’ balance sheets are available daily.

There are currently no budgetary constraints impeding data collection and compilation activities. However, in line with the considered expansion of the institutional coverage of monetary data and the compilation and presentation of flow of funds for the financial sector, as recommended by the new Monetary and Financial Statistics Manual (MFSM), it may be desirable to expand human and budget resources for the compilation of monetary and financial statistics.

0.2.2 Measures to ensure efficient use of resources are implemented.

The Economic Department management holds meetings with the staff on issues that need to be addressed for enhancing the policy vision of the managers and the understanding of the professional staff within the department.

In general, all programs in the NBU are subject to budget considerations and performance assessments. Budgeting of the NBU is done annually by the board of directors of the NBU every September, based on budget needs identified by NBU’s departments. The budget is approved by the NBU Council. Budget allocations are made for each department by the Financial Department. In accordance with the NBU Board Resolution of June 21, 2000, No. 255 “On the Attestation Procedure of NBU’s Civil Servants”, the NBU staff will be subject to performance assessment and review of job description once in 3–5 years. New technology for data processing and dissemination is always tested by computer and systems analysis experts.

0.3 Quality awareness

0.3.1 Processes are in place to focus on quality.

The NBU recognizes that official statistics must have the confidence of their users, and exercises quality control at every stage of data production and dissemination. The Economic Department and NBU’s other departments verifies that data reporting practices followed by the banks are consistent with the regulations, and have systems and procedures in place to ensure quality in the compilation process. Staff at all levels of the Economic Department participates actively in the review of data prior to publication.

The source data submitted by the reporting institutions to the Economic Department and NBU’s other departments are cross-checked for accuracy, and any discrepancies are investigated. Data reporting practices are set in line with the sector and financial instruments classification distinguished in the charts of accounts of the NBU and commercial banks, and supporting schedules for the collection of data. Validation procedures for assessing the plausibility or reasonableness of reported data are undertaken visually on a bank-by-bank basis. The Economic Department and NBU’s other departments consult with the reporting institutions to verify the data for possible misclassifications.

External auditing companies audit the financial statements of the NBU and commercial banks.

0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics.

The quality of the collection, processing, and verifying of statistics is monitored through cross-checks; for problems in collected data, reporting institutions are informed of discrepancies and guided by the staff of the Economic Department, Accounting Department, and the NBU’s other departments in reconciling them.

No formal surveys of users have been undertaken so far; however, users can contact the Economic Department, for instance through its website, and responses will be provided to all requests and questions. On average, in cooperation with the NBU’s other departments, the Monetary and Banking Statistics Division responds monthly to about 60 questions related to monetary data.

There is currently no other body outside the Economic Department that provides regular guidance on the quality of monetary statistics and on strategies for improving data production. Suggestions on improvements of monetary data and their publication are provided ad hoc by users of monetary statistics, in particular by the SSCU and the Ministry of Economy.

0.3.3 Processes are in place to deal with quality considerations, including trade-offs within quality, and to guide planning for existing and emerging needs.

A specific staff of the Economic Department is assigned the responsibility of monitoring developments and changes in financial markets, and works to improve the methodological soundness of the data taking into account new initiatives in the financial system. In accordance with the recommendations of IMF’s technical assistance missions, the Monetary and Banking Statistics Division is currently verifying and analyzing activities of investment and private pension funds for their possible inclusion in the coverage of monetary statistics.

There is a wide recognition of the trade-offs between data quality and timeliness. The production of monetary statistics is fully automated and includes a series of checks and validations at every stage of the production cycle. Timeliness is regarded as one of the most important dimensions of data quality in line with the SDDS requirements.

Meetings are held periodically with policy makers, mainly the NBU’s Monetary Policy and Foreign Exchange Regulation Departments and other data users, to identify any emerging data requirements. The NBU also invites users’ comments on the relevance and usefulness of the monetary statistics via its website. However, it would be desirable that the Economic Department establishes periodic surveys of users of the monthly Bulletin of the NBU, requesting their reaction on its usefulness and their needs for specific detail information disseminated in the bulletin.

1. Integrity

1.1 Professionalism

1.1.1 Statistics are compiled on an impartial basis.

The statutory provisions, under which the NBU compiles monetary statistics, are adequate to support its independence in conducting these functions. In this regard, Article 53 of the NBU Law stipulates that the NBU shall enjoy absolute autonomy in exercising the powers and carrying out the duties under its responsibility, as granted by this law.

Professionalism of the staff in charge of the compilation of monetary statistics is promoted by encouraging participation in lectures, conferences, and meetings with other professional compilers (e.g., the SSCU), other central banks, and international organizations.

1.1.2 Choices of sources and statistical techniques are informed solely by statistical considerations.

Choices of sources and statistical techniques are informed solely by statistical considerations.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.

The Economic Department of the NBU comments on erroneous interpretation of its statistics if deemed truly significant. The Economic Department seeks to prevent misinterpretation or misuse of monetary statistics by providing explanatory notes in its publications. In addition, the NBU management holds press conferences in cases of significant misinterpretations of monetary data.

1.2 Transparency

1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

The NBU Law, which constitutes the base for the compilation and dissemination of monetary data, is available on the NBU’s website. Up-to-date advance release calendars (ARCs) for Ukraine’s SDDS data categories are currently not available to the public. Drafts of the ARCs for SDDS financial sector data categories have been provided to the SSCU, and posted on SSCU’s website. However, the information provided by these ARCs does not meet SDDS requirements, as no-later-than dates are not updated the week prior the release of the data to identify a precise day of release.

Statistical publications provide addresses and telephone numbers of the NBU’s respective departments from which additional publications can be provided.

1.2.2 Internal governmental access to statistics prior to their release is publicly identified.

Data are released to the Administration of Ukraine’s President, Cabinet of Ministers, Ministry of Economy, and SSCU within about 20 days after the end of the reference month (about ten days prior to their release to the public), with indication that they can be used for internal analysis and cannot be published before the NBU disseminates them officially. However, there is not public awareness of such internal government access prior to the release of the data.

1.2.3 Products of statistical agencies/units are clearly identified as such.

The Economic Department of the NBU is identified as the source of the monetary statistics published in the monthly Bulletin of the NBU. The NBU does not directly request attribution when its statistics are used or reproduced, but the Bulletin of the NBU indicates that it should be used as a source of data in case of reproduced statistical information originally published in the bulletin.

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.

Advance notice is given in the case of major changes in the methodology and compilation of monetary data, such as the introduction of the new charts of accounts that serve as a primary source of monetary data. Other changes in data classification, source data, and statistical techniques are announced simultaneously with the release of the data. Also, if any interpretation is needed regarding changes in time series, explanation is provided as a note in the publication in which the change first takes place.

1.3 Ethical standards

1.3.1 Guidelines for staff behavior are in place and well-known to the staff.

Guidelines for staff behavior are set up in the NBU Law in Articles 65 and 66 and in the Law on Banks and Banking Activity, in Section 10, Articles 60, 61, and 62.

According to Article 65 of the NBU Law, officials of the NBU are prohibited from becoming members of managing bodies or shareholders of commercial banks and other financial institutions. Article 66 stipulates that officials of the NBU are prohibited from disclosing information that constitutes a service secret or is of confidential nature, and has become known to them in the performance of their duties even after the resignation from the NBU, except for cases provided for by the laws of Ukraine.

Articles 60, 61, and 62 of the Law on Banks and Banking Activity provide details on information considered as banking secrets, actions needed for their protection and procedures, and cases for their possible disclosure.

2. Methodological soundness

2.1 Concepts and definitions

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

The framework used by the NBU in compiling analytical accounts of the NBU (central bank) and analytical accounts of commercial banks (comprising resident banks that accept demand and other deposits) reflects concepts and principles that are, in general, based on the IMF’s Draft Guide to Money and Banking Statistics in International Financial Statistics (December 1984). The monetary survey is derived by consolidating the accounts of the NBU and commercial banks, and provides an analytical presentation of the intermediation role of the central bank and commercial banks.

The money aggregates compiled and disseminated by the NBU are (i) M0, comprising currency in circulation; (ii) M1, comprising and broken down into M0 and settlement and current accounts (enterprises, households, and nonbank financial institutions) in the national currency; (iii) M2, comprising and broken down into M1 and time deposits (enterprises, households, and nonbank financial institutions) in the national currency, and all deposits (enterprises, households, and nonbank financial institutions) in foreign currencies; and (iv) M3, comprising and broken down into M2 and client funds arising from banks fiduciary transactions and securities issued that are held by other domestic sectors than commercial banks. Other aggregates compiled and disseminated by the NBU are (i) domestic credit, disaggregated into credits to the general government (comprising central government and local governments; extrabudgetary funds are included in the corresponding level of the government), financial sector (excluding banks), private and public nonfinancial enterprises, and households, and (ii) data on the components of the net foreign position (in a table, Ukrainian Page in International Financial Statistics, that is published in the monthly Bulletin of the NBU).

Following the publication in September 2000 of the IMF’s MFSM, the NBU intends to revise its procedures and formats for collection, compilation, and dissemination of monetary statistics. In this connection, the NBU established a working commission that should introduce a harmonized use of System of National Accounts (SNA) and MFSM terminology in all normative acts relating to the financial sector.

The NBU is also conducting studies for an expansion of the coverage of depository corporations to include those nonbank financial institutions that may issue instruments that are considered as deposit substitutes, as well as a possible future compilation of a Financial Corporations Survey that would extend the coverage beyond the deposit-taking institutions covered in the monetary survey. However, this expansion of the coverage of monetary statistics is dependent on the appropriate legislation for various financial institutions other than commercial banks.

2.2 Scope

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

The depository corporations sector of Ukraine comprises the NBU and 154 active commercial banks (as of December 31, 2001). There are currently no branches of foreign banks operating in Ukraine. According to Article 2 of the Law of Ukraine on Banks and Banking Activity, “bank” means a legal entity that, under the NBU license, has an exclusive right to perform the following banking operations: (i) accepting deposits and funds belonging to households and legal entities, (ii) allocating these funds in their own name at their own risk, and (iii) opening and servicing accounts of individuals and legal entities.

The institutional coverage of monetary statistics includes the banks’ domestic headquarters and their domestic branches. Branches of Ukrainian banks operating abroad are excluded from the institutional coverage of monetary statistics.

The monetary aggregates exclude data of 35 commercial banks that are currently in the process of liquidation. While this procedure is not consistent with the recommendation of the MFSM, the Economic Department disseminates in the monthly Bulletin of the NBU and on its website a major sectoral breakdown of data on provided credits and accepted deposits of nonoperational banks as a memorandum item. Thus, users of monetary data are provided with information on the overall credits and deposits provided and accepted by the banking sector of Ukraine. The data on nonoperational commercial banks are based on special reports that are collected by the Liquidation Bank Division of the General Banking Supervision Department.

For analytical purposes, the new MFSM defines the Other Depository Corporations (ODC) sub-sector, which consists of all resident financial corporations (except the central bank) and quasi-corporations mainly engaged in financial intermediation, whose liabilities consist of deposits or financial instruments considered as deposit substitutes that are included in the definition of money. The national definition of broad money is thus fundamental to the methodology of the MFSM, in that it determines which units in the financial corporations sector are classified as the ODC. In Ukraine, commercial banks are currently the only deposit-taking financial institutions fulfilling both criteria that classify them as the ODC—that is, Ukrainian commercial banks are mainly engaged in financial intermediation and issue deposit liabilities that are included in the aggregate M3. Thus, the ODC’s survey—which is, in accordance with the MFSM, the major framework for compiling monetary statistics—for Ukraine would have the same coverage as the currently compiled and published analytical accounts of the banking sector.

In line with the other MFSM guidelines, the ODC’s sub-sector also should include, in the national definition of broad money, financial corporations other than banks that issue liabilities (accept deposits or issue instruments that are considered as their substitutes). It appears that particularly investment funds, private pension funds, and other corporations that issue securities that are sold to nonbank financial corporations are not at present included.

The definition of residency in monetary statistics is consistent with the fifth edition of Balance of Payment Manual (BPM5) and 1993 SNA. Branches of foreign banks in Ukraine would be regarded as residents, whereas branches of domestic banks abroad are classified as nonresidents.

2.3 Classification/sectorization

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

The NBU uses the residency criterion to distinguish between domestic and external accounts for the compilation of monetary statistics. The delineation between resident and nonresident institutional units is broadly consistent with the criterion in the BPM5, 1993 SNA, and MFSM.

The sectorization of the domestic economy by the NBU is principally in line with the MFSM. The sectoral classification of resident units recommended in the MFSM, for the purpose of compiling monetary statistics, refers mainly to the following sub-sectors: (i) central bank, (ii) other depository corporations, (iii) other financial corporations, (iv) central government, (v) state and local government, (vi) public nonfinancial corporations, (vii) other nonfinancial corporations, and (viii) other resident sectors.

In the detailed presentation of monetary data by the NBU, the following sectoral groupings of resident institutional units are distinguished: (i) central bank, (ii) commercial banks, (iii) nonbank financial institutions, (iv) general government, (v) nonfinancial public enterprises, (vi) nonfinancial private enterprises, (vii) households, and (viii) nonprofit organizations servings household.

In the analytical accounts of the central bank and the analytical accounts of the banking sector, claims on and liabilities to the central government and local governments are grouped together in the aggregate claims on and liabilities to the general government. This presentation of the banking sector’s position with the government follows the understanding that local governments are dependent on the central government’s redistribution of budget recourses, and therefore, their deposits should be excluded from the definition of money. Thus, the aggregate net claims on the general government is used rather than the aggregate net claims on the central government. In accordance with the current International Financial Statistics’ (IFS) presentation, the analytical accounts of the central bank and the analytical accounts of the banking sector also group together claims on private nonfinancial enterprises, households, and nonprofit organizations servings household into the aggregate claims on the private sector.

The principles underlying the classification of financial instruments in Ukraine’s monetary statistics are broadly consistent with international standards and, notwithstanding differences in terminology used, are generally consistent with the MFSM’s recommendations. Data on financial derivatives (other than foreign exchange swaps) are not available and therefore they are not included in monetary statistics. Securities repurchase operations are treated as collateralized loans. This treatment of securities repurchase operations is consistent with the MFSM recommendations.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

The general recommendation of the MFSM is that the valuation of financial assets and liabilities should be done on the basis of market prices or market price equivalents (fair values). The valuation of loans is an exception to this principle and loan values should be based on creditors’ outstanding claims without adjustment for expected loan losses. This amount comprises the outstanding principal plus any accrued interest and is referred to as the book value of a loan. Monetary gold and nonmonetary gold should be valued on the basis of the market price of gold. Holding gains and losses arising from changes in market values (or fair values) of financial assets and of outstanding liabilities should be recorded separately in a revaluation account.

The NBU’s and commercial banks’ accounting data and financial statements are prepared in accordance with the related Ukrainian legislation and requirements of the NBU Law and are based on the International Accounting Standards. Thus, monetary data compiled based on accounting records follow valuation principles recommended by the MFSM. In practice, the purchase of securities is recorded in their nominal value and separate accounts are used for recording unamortized premiums and discounts on securities held in banks’ portfolio. These accounting procedures enable calculation of market value of securities. The market value of securities is calculated from their nominal value by adding unamortized premiums and subtracting unamortized discounts on securities.

The NBU records its foreign equity shares at market value and revalues them at current exchange rates prevailing at the balance sheet date. Monetary and nonmonetary gold at the NBU is valued based on the price determined on international markets. Gold held by commercial banks is valued at prevailing market prices on the reporting date.

Consistent with the recommendations of the MFSM, the loan portfolio and deposits on the balance sheets of the banks are valued at book value. In line with the recommendations of the MFSM, loan valuation is not adjusted for expected loan losses. Provisions for expected loan losses are recorded as separate entries on the liability side of the balance sheets and included in the capital accounts in the analytical accounts of the central bank and the analytical accounts of the banking sector.

According to the MFSM, all stocks and flows denominated in foreign currency should be converted to national currency values at the market exchange rate prevailing at the time they are entered in the accounts. The midpoint between the buying and selling rate of exchange should be used, so that any service charge is excluded. In the monetary statistics of Ukraine, monetary data compiled by the Economic Department fully follow this principle. In line with the MFSM recommendations, holding gains or losses arising from changes in the exchange rates are classified into a special revaluation account.

The MFSM recommends that data be compiled on stocks and on each of the three flows components: transactions, revaluations, and other changes in the volume of assets. The NBU follows this principle only partially and compiles only information on transactions of loans. However, these data are not disseminated and are used only for NBU’s internal analysis.

2.4.2 Recording is done on an accrual basis.

In accordance with the accrual accounting principles recommended in the MFSM, interest due but not paid on financial instruments should be incorporated into the outstanding amount of the financial asset or liability, rather than being treated as part of other accounts receivable/payable. The accounting standards in Ukraine require interest to be accrued on a monthly basis. Monetary data compiled by the Economic Department separately identify accrued interest and include it into the underlying financial instrument.

In general, transactions are recorded at the time the transaction occurs by means of simultaneous electronic recording.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.

In line with the general principle of the MFSM, assets and liabilities of the NBU and commercial banks are collected and compiled on a gross basis. In line with the MFSM, claims on particular transactors are not netted against liabilities to those transactors. Data presented on a net basis, e.g., “foreign assets (net)” and “claims on general government (net),” in the monetary survey) are also shown with the underlying gross data.

In the monetary data disseminated in the monthly Bulletin of the NBU and on the NBU’s website, the data on financial assets and liabilities are aggregated into major categories (e.g., claims classified by debtors and deposits classified by creditors). The monetary survey is obtained by canceling out all outstanding claims and liabilities between the NBU and commercial banks, and between commercial banks themselves.

3. Accuracy and Reliability

3.1 Source data

3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions.

The source data for compiling the analytical accounts of the central bank and analytical accounts of commercial banks are the balance sheet records, supporting schedules of the NBU and commercial banks provided by the Accounting Department and Information Technologies Department, and data obtained from NBU’s other departments. The incoming data are continuously reviewed by the Accounting Department, the Economic Department, and NBU’s other departments to ensure full institutional coverage. The balance sheet records and supporting schedules capture, in principle, the full range of financial instruments and economic sectors. They provide sufficient detail to enable the classification of all financial instruments and economic sectors, as defined in the MFSM, and permit in-depth analyses and cross-checks.

The financial press is monitored for information on developments in financial markets that may be of relevance for the compilation of monetary statistics. In this context, reports may be prepared by the staff for information on financial instruments and markets. Meetings with financial market participants and the business community—to identify new developments that need to be taken into account in the compilation system of monetary statistics—are not common.

3.1.2 Source data reasonably approximate the definitions, scope, classification, valuation, and time of recording required.

Reported source data provide a reasonably good approximation to the concepts, definitions, scope, classifications, and recording principles for compiling sound monetary statistics. Positions of the NBU and commercial banks with counterparties that cannot be reasonably approximated or allocated to specific instruments or sectors are recorded in “other assets” and “other liabilities.” These amounts are small overall.

3.1.3 Source data are timely.

The data collection system allows the timely compilation of monetary statistics, which are released in the monthly Bulletin of the NBU. The accounting records of the NBU and commercial banks are available on a daily basis and provided by the electronic system to the Monetary and Financial Statistics Division. However, the final NBU monthly balance sheet is produced only about 15 days after the reference month because data on NBU’s internal organizations (mint factory, training center) are provided with a delay of about two weeks after the end of the reference month. The data of NBU’s internal organizations do not have any impact on the value of monetary aggregates, and therefore, in accordance with the SDDS requirements, the NBU would be able to disseminate the analytical accounts of the central bank, excluding internal organizations, within two weeks after the end of the reference month using daily accounting records that are considered as operational data.

3.2 Statistical techniques

3.2.1 Data compilation employs sound statistical techniques.

Balance sheet records and supporting schedules are provided by the Information Technologies Department of the NBU using an MSExcel format, and they include several checks within the data. The statistical techniques used to compile monetary statistics are automated. In processing source data, computerized files that incorporate macros are used to avoid processing errors. Procedures for data management are documented and assisted by the Information Technologies Department of the NBU.

3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.

Due to full computerization of accounting procedures of the NBU and commercial banks, nonreporting of active banks’ data for monetary statistics purposes is practically impossible. Adjustments to the data are made for positions with the IMF, using the exchange rate at the end of the reporting period instead of the “holding exchange rate”, which is the exchange rate at the end of the financial year, as used by the IMF’s Treasurer’s Department. The Economic Department does not calculate seasonally adjusted monetary data. However, it is examining methods recommended by Eurostat for calculating them.

3.3 Assessment and validation of source data

3.3.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide planning.

Queries regarding the balance sheet data and supporting schedules of the NBU and commercial banks are solved between the Accounting Department, the Economic Department, and NBU’s other departments. Balance sheet records and supporting schedules are revised to reflect changes in the chart of accounts of the NBU and commercial banks, and rarely modified to cover sector reclassifications and the needs of compilers. The Economic Department is authorized to make revisions only in the supporting schedules that have been primarily designed to collect statistical information for the compilation of monetary statistics.

If necessary, the Economic Department conducts meetings with the Accounting Department, which has the authority to introduce changes to the charts of accounts.

A designated staff of the Monetary and Banking Statistics Division monitors developments and changes in financial markets, which may affect the compilation of monetary statistics.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Main intermediate data are validated against other information where applicable.

If deemed necessary, the accuracy of the balance sheets and data in supporting schedules is checked against secondary data sources, such as with data collected by other NBU departments. In general, however, most queries concerning monetary statistics are resolved by the Monetary and Banking Statistics Division directly with the banks.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

The Monetary and Banking Statistics Division investigates statistical discrepancies and determines major factors that might be contributing to them.

3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated.

Large fluctuations in monetary or credit aggregates are rare and likely to occur only after a significant change in statistical methodology or source data. In those circumstances, upon the release of monetary statistics, the Monetary and Banking Statistics Division is likely to receive inquiries from data users and handle them directly. In the case of large and unexplained fluctuations in data series, the Monetary and Banking Statistics Division would investigate possible classification/sectorization errors by individual respondents.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes.

There is no mechanism in place to conduct routine revision studies; the NBU believes that they are not relevant for monetary statistics, as the data are considered final when first published. However, deviations, omissions, and other potential sources of problems in the data (e.g., erroneous sectorization of institutional units) are identified and investigated. The results of these ad hoc studies are not made available to the users.

4. Serviceability

4.1 Relevance

4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

There is no formally established process of regular consultation with policy departments, ministries, or representatives from the private sector or academia. The Economic Department conducts informal reviews of monetary policy needs with NBU’s departments, in particular with the Monetary Policy Department and Foreign Exchange Regulation Department, and with external users of monetary data through e-mail, telephone, and facsimile. The Economic Department regularly participates in international statistical meetings and seminars organized by international and regional organizations.

4.2 Timeliness and periodicity

4.2.1 Timeliness follows dissemination standards.

The analytical accounts of the central bank and the analytical accounts of the banking sector are available within about 20 days after the end of the reference month, after which they are sent to the IMF for operational use and for their publication in IFS. Both the analytical accounts of the central bank and the analytical accounts of the banking sector are disseminated with a lag of about 30 days after the end of the reference month when they are simultaneously released in the Bulletin of the NBU and the Internet website.

The NBU would be able to meet the prescribed SDDS criteria for the timeliness of the analytical accounts of the central bank and disseminate on the Internet website the preliminary central bank’s aggregates, namely the foreign positions, reserve money, and domestic credit, within two weeks after the end of the reference month. These aggregates would be based on daily accounting data that are available to staff of the Economic Department.

4.2.2 Periodicity follows dissemination standards.

The analytical accounts of the central bank and the analytical accounts of the banking sector are disseminated on a monthly basis, consistent with the specifications of the SDDS.

4.3 Consistency

4.3.1 Statistics are consistent within the dataset.

The central banks’ and commercial banks’ records for claims on, and liabilities to each other show usually only negligible discrepancies because of differences in the time of recording financial transactions and discrepancies in recording of accrued interest. A reconciliation of stock and flow data is not available, because flow data for monetary statistics are not compiled for all recommended components. However, NBU data on its claims on commercial banks show larger discrepancies (in the amount of 444 million hryvnia as of end-December 2001) when compared with commercial banks’ data on their liabilities to the NBU, mainly due to the classification of the NBU’s credit to a large bank that became inoperative. While NBU data classify this credit as claims on all commercial banks, data of the large inoperative bank are not included in data on commercial banks used in the compilation of monetary statistics.

4.3.2 Statistics are consistent or reconcilable over a reasonable period of time.

Time series are available in the electronic system managed by the Information Technology Department and on NBU’s website. When changes in source data, methodology, and statistical techniques are introduced, all time series are revised. Main breaks and discontinuities in the time series are explained in detail in attached notes/footnotes. Unusual changes in economic trends are explained by the Economic Department in the analytical part of the monthly Bulletin of the NBU. However, the consistency of Ukrainian monetary data is somewhat hampered by very frequent changes to the charts of accounts of the NBU and commercial banks, as well as by the exclusion of liabilities of banks in liquidation, which create breaks in monetary aggregates’ time series.

4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.

The Economic Department regularly checks the consistency of monetary statistics with balance of payments statistics. At present, consistency checks between GFS and monetary statistics are not conducted on a regular basis. The NBU publishes in the monthly Bulletin of the NBU information on holdings of government securities bought by the NBU and commercial banks on the primary market, which provide users of monetary and GFS with a partial indication on consistency of these two sets of data.

4.4 Revision policy and practice

4.4.1 Revisions follow a regular, well-established, and transparent schedule.

There is no formal revisions policy. Revisions are infrequent and are made when needed, based on the availability of more accurate data. Revised data are identified as such in the publications. Users are not informed that the NBU does not conduct routine data revisions.

4.4.2 Preliminary data are clearly identified.

Monetary data are considered final when first released. Since it is highly unlikely that data will be revised, Bulletin of the NBU does not include notes on the status of the monetary data (preliminary or final). Revised data are identified in publications, but users are not informed on causes of revisions.

4.4.3 Studies and analyses of revisions are made public.

Given the sporadic nature of revisions to monetary data, no studies and analyses are carried out routinely. However, errors and data shortcomings in the data reported by banks are the focus of internal analysis.

5. Accessibility

5.1 Data accessibility

5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

The presentation of monetary statistics by the NBU facilitates the interpretation of the data. The monthly Bulletin of the NBU, prepared by the Economic Department, covers developments in money markets, balance sheets of the NBU and commercial banks, money supply, and credits. Charts and tables are also disseminated in this report. Estimates are produced only for internal analytical purposes and are not disseminated.

There is so far no seasonal adjustment of monetary data. Studies on the methods, however, are under way.

5.1.2 Dissemination media and formats are adequate.

Monetary data are disseminated in hardcopy and in electronic formats to meet the needs of data users. Monthly time series within each year (since 1992) are also disseminated on the website of the NBU. More detailed data are disseminated in the monthly Bulletin of the NBU.

5.1.3 Statistics are released on a pre-announced schedule.

There is no publicly announced ARC for the monthly Bulletin of the NBU and for the dissemination of monetary data on the NBU’s website, but the Economic Department strictly follows an internal publication schedule, according to which the bulletin is to be published about 30 days after the end of the reference month.29 The users are aware of this schedule and expect the publication of the bulletin on this date.

5.1.4 Statistics are made available to all users at the same time.

Data are released simultaneously to all interested users, except for cases specified in 1.2.2. The publication of the monthly Bulletin of the NBU and the posting of monetary data on the Internet are simultaneous.

5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request.

Unpublished and nonconfidential data are made available upon request free of charge upon the authorization of senior staff of the Economic Department. If there is substantial demand, unpublished data may be disseminated with the permission of the Vice Governor, who is responsible for the Economic Department.

5.2 Metadata accessibility

5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

The Economic Department publishes in monthly Bulletin of the NBU a short description of all terms (sectors, instruments, monetary and credit aggregates, and net positions) used in the tables for monetary statistics. This description does not provide users with full information on the framework for the compilation and presentation of Ukrainian monetary statistics and important metadata details, such as concepts, scope of the data, accounting conventions, nature of the data sources, and compilation practices. No documentation on differences from internationally accepted standards and good practices is available.

5.2.2 Levels of detail are adapted to the needs of the intended audience.

As Ukraine’s authorities intend to subscribe to the SDDS in the near future, the Economic Department has prepared base page information for the data categories recommended by the SDDS for the financial sector and sent it to the IMF for review.

5.3 Assistance to users

5.3.1 Contact person for each subject field is publicized.

Prompt and knowledgeable service and support is provided to users of monetary statistics. The phone numbers and e-mail addresses of the NBU officials, responsible for the compilation of statistical data, can be found in the monthly Bulletin of the NBU. No brochures have been produced to educate users.

5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available.

Publications, documents, and other services are generally free of charge; however, private sector subscribers of the monthly Bulletin of the NBU and Visnyk of the NBU are charged for their subscription. A catalogue of publications is available on NBU’s website. Subscription transactions are executed through post offices or by the editorial staff of the NBU’s periodic publications. A list of periodic publications is disseminated on the website of the NBU.

Table 5.

Ukraine—Data Quality Assessment Framework: Summary of Results for Monetary Statistics

(Compiling agency: National Bank of Ukraine)

Key to symbols: NA = Not Applicable; O = Practice Observed; LO - Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Not Observed; SDDS = Complies with SDDS Criteria

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VI. Balance of Payments

0. Prerequisites of quality

0.1 Legal and institutional environment

0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified.

A decree of the Cabinet of Ministers of Ukraine of February 19, 1993, Revision No. KD93015 of October 4, 2001, on Foreign Exchange Regulation and Control, assigns responsibility for compilation of balance of payments to the NBU. In support of that, the Law of Ukraine on the National Bank of Ukraine (Law on the NBU) No. 679-XIV of May 20, 1999—as amended on January 10, 2002—clearly defines the responsibilities of the NBU for the compilation, processing, and dissemination of balance of payments data. According to Article 7 of the Law on the NBU, the NBU is responsible for the compilation, analysis, and forecast of the balance of payments. Section 12 of the law stipulates the roles and responsibilities of the NBU with regards to balance of payments. It includes Article 67, which provides the NBU with the authority to define forms and procedures of data reporting for the compilation of balance of payments statistics that are mandatory for all business entities, residents, and nonresidents. In addition, Article 68 of Law on the NBU stipulates that the NBU shall disseminate the statistics on balance of payments. Article 6 of the Statistics Law makes reference to the fact that the responsibility for the compilation of balance of payments compilation is assumed by the NBU. The Balance of Payments Division (BOPD) of the Economic Department of the NBU is responsible for establishing the statistical methodology, reporting forms, data collection, verification, processing, compilation, and dissemination of balance of payments data.

Working arrangements among government agencies that provide statistical data for balance of payments compilation are consistent with their assignments of responsibility.

0.1.2 Data sharing and coordination among data-producing agencies are adequate.

Both formal and informal arrangements are in place to promote data sharing and coordination among data-producing agencies. A joint resolution of the Cabinet of Ministers of Ukraine and the NBU on Balance of Payments Compilation No. 517 of March 2000 provides a detailed list of government agencies that must provide balance of payments source data to the NBU. This resolution is very detailed about the coverage, timeliness, and periodicity of data sets that must be provided.

Efficient coordination has been established with other departments of the NBU for the sharing of information on official reserves, registered foreign loans, and cross-checking of commercial banks’ account balances. The balance of payments compilers cooperate closely with the statisticians of the SSCU involved in the compilation of statistics on foreign direct investment, merchandise trade, and international trade in services, as well as with officials from the State Customs Committee of Ukraine (SCCU) and the MoF; the latter for government and government-guaranteed external debt statistics. NBU compilers also work in close cooperation with staff of the State Committee on Securities and Stock Exchange to monitor the market value of selected share holdings of domestic enterprises. While this coordination of activities promotes efficient data sharing between agencies, it is not done under the umbrella of formal committees. Nonetheless, staff has been successful in reaching agreements, which could later be formalized at higher levels of authority when required.

0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only.

Article 67 of the Law on the NBU stipulates that data provided by banks and other business entities shall not be disclosed, except for cases provided for by the legislation of Ukraine. The requirements of this article do not apply to aggregated statistical information, which is subject to publication by the NBU. On December 12, 2001, the Council of the NBU has adopted a resolution on The Procedures of Handling Confidential Information in the NBU that approves (i) the regulation on the protection of confidential information in organizational units of the NBU and (ii) the instructions on procedures for the collection, processing, recording, storage and use of documents, files, publications (including electronic documents), and other material that contain bank secrets and “not for publication” information handled in various organizational units of the NBU. In addition to general security procedures within the NBU, NBU staff—other than those of the BOPD—do not have access to completed survey forms or databases at the respondent level. Furthermore, the confidential data provided to the BOPD are not shared with other departments of the NBU.

Article 66 of the Law on the NBU on confidentiality prohibits employees from disclosing confidential information to which they have or had access, even after resignation from the NBU. Strong guarantees of confidentiality are also provided to respondents that provide data to the SSCU, which are used directly in balance of payments compilation or to assess the quality of balance of payments data collected by the NBU. The confidentiality of statistical information is protected by Articles 21 and 22 of the Statistics Law. In addition, the survey forms used by the SSCU include a note specifying that the data are confidential, the intended purpose of their use, and that the information will be disseminated in an aggregate basis only.

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.

The legal basis for reporting data is covered by a number of pieces of legislation. The Law on the NBU (Article 67) makes it mandatory for all enterprises to report data for the purpose of balance of payments compilation. Penalties for nonreporting, for the provision of unreliable data or the provision of data with delays are covered by the Statistics Law and by the Law on Administrative Violations. These two laws also cover delinquent respondents for inquiries conducted by the SSCU.

The NBU has adopted a number of initiatives to encourage reporting of data, principally by commercial banks. The Economic Department staff of the NBU has developed software to facilitate electronic reporting by banks and has assisted them in implementing this standard software. The NBU compilers are in regular contact with commercial banks to assist them in their monthly reporting of data. The SSCU statisticians from local or regional offices involved in the collection of balance of payments-related data regularly promote response by direct visits to enterprises and on-the-spot assistance to respondents for completing the survey forms.

0.2 Resources

0.2.1 Staff, financial, and computing resources are commensurate with statistical programs.

The BOPD is comprised of a staff of 24 employees that are responsible for the production of the monthly current account estimates (for monitoring purposes only), quarterly balance of payments estimates, and experimental international investment position (IIP) statistics that are intended for annual publication, while quarterly IIP are produced for monitoring purposes. In addition, selected staff of the BOPD participate in the preparation of balance of payments forecasts and macroeconomic analysis. Compilers are responsible for maintaining three data bases for balance of payments and IIP compilation.

The staff benefits from regular training, as visits to balance of payments compiling central banks are regularly organized for groups of three to five compilers to familiarize them with methods and techniques used by other agencies. The staff has the opportunity to attend internal training offered by the NBU. Staff retention is high.

The computer equipment is adequate and each staff is provided with a LAN-connected computer, which is replaced, on average, every two to three years. Banks’ reports are electronically transmitted and processed using a combination of in-house and off-the-shelf software, which incorporate automatic edits for the source data provided by banks and enterprises.

The human resources currently allocated for balance of payments and IIP compilation are adequate. However, the imminent decision to disseminate annual IIP—and the possibility that the responsibility for compilation and dissemination of quarterly external debt data would be assumed by either the BOPD or the Foreign Exchange Regulation Department of the NBU—would stretch these resources.

More important are the resource problems encountered by other agencies compiling selected source data for balance of payments. In particular, lack of resources implies that the SSCU cannot undertake a travelers’ survey, which would improve estimates of travel and shuttle trade.

0.2.2 Measures to ensure efficient use of resources are implemented.

Budgeting of the NBU is done annually by the board of directors of the NBU based on budget needs identified by the departments. Budgets are approved by the NBU Council. Budget allocations are made for each department by the Financial Department. In accordance with the NBU Board Resolution of June 21, 2000, No 255 “On the Attestation Procedure of NBU’s Civil Servants”, the NBU staff will be subject to performance assessment and review of job description once in 3-5 years.

The NBU has implemented a number of cost saving and response burden reducing initiatives. The electronic reporting by banks reduces the requirements for manual data entry to the forms completed for the direct reporting of enterprises and significantly reduces response burden for banks. Automatic edits have been implemented in the early phases of data processing. The quality of the website of the NBU, which includes detailed balance of payments information, reduces the need for disseminating paper publications while facilitating access to data users.

0.3 Quality awareness

0.3.1 Processes are in place to focus on quality.

There is at present no formal quality program. However, the recent history of decisions made by the higher management of the NBU, as well as senior balance of payments compilers, demonstrates that the NBU staff is sensitive to various dimensions of data quality. For example, following the ratification by the Parliament of Ukraine of the sale of Ukraine’s Black Sea fleet to the Russian Federation, a number of very large revisions had to be made to previous years’ data. The NBU management fully supported the staff decision to incorporate these revisions into the balance of payments. The Economic Department has recently revised its reporting forms and instructions used for the compilation of balance of payments and monetary statistics. When these changes will be introduced, the International Transactions Reporting System (ITRS) threshold for separately identifying individual transactions will be reduced to US$50,000 from US$250,000. This initiative should improve the accuracy of the classification of transactions into the balance of payments standard components.

0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics.

Article 16 of the Statistics Law provides for the mandatory approval by SSCU of methodologies and reporting forms used by the NBU to collect balance of payments data. As a result, all report forms used by the NBU are previously approved by SSCU, a process intended to verify the methodological correctness of the data collection procedures.

In addition to the electronic reporting of banks and automatic edits of source data, a number of other processes are in place to monitor the quality of the data. Bank reporting is regularly cross-checked with opening and closing balances reported to the Monetary and Banking Statistics Division. Follow-ups are done with banks for improperly classified transactions to ensure the quality of future reporting. Data on international transactions in services are crosschecked with survey information collected by the SSCU.

0.3.3 Processes are in place to deal with quality considerations, including trade-offs within quality, and to guide planning for existing and emerging needs.

A Cabinet of Ministers order of August 9, 2001 (No. 341–r) on Measures to Improve National Accounts Compilation in Ukraine has established a working group comprising staff of the Ministry of Economy, MoF, STU, State Tax Administration, NBU, and other government agencies and research institutes of Ukraine to assist in setting up the work program for improvements to national accounts and identify emerging data requirements. Compilers of the BOPD are active participants in this working group and, as such, informed of priorities for development of Ukraine’s system of national accounts and data concerns of major users of macroeconomic statistics of Ukraine. In addition, senior compilers of the BOPD are official participants in the regularly organized Seminars of Senior Forecasters of Ukraine. Attendance at these seminars allows staff to be kept aware of the emerging needs and statistical concerns of data users and consequently adjust their data products. In addition, compilers remain in close and regular contact with their main data users.

1. Integrity

1.1 Professionalism

1.1.1 Statistics are compiled on an impartial basis.

The statutory provisions under which the NBU compiles balance of payments statistics are adequate to support its independence in conducting these functions. In this regard, Article 53 of the Law on the NBU stipulates that any interference of the legislative and executive bodies or their officials in the exercise of the function of the NBU shall be prohibited. The Statistics Law also addresses the need for the professional independence of SSCU, which provides complementary data used for balance of payments compilation. Articles 5 provides the legislative basis for the professional independence of the SSCU.

The Economic Department of the NBU promotes the professionalism of its staff by ensuring regular participation of compilers in balance of payments courses provided by the IMF and, with the assistance of a TACIS-financed program, permitting regular visits to other balance of payments-compiling central banks to review the compilation systems established by those organizations.

1.1.2 Choices of sources and statistical techniques are informed solely by statistical considerations.

Decisions on various sources of data to be used for compiling the balance of payments are based solely on statistical considerations. The various source data used by the BOPD are constantly cross-checked, and discrepancies between source data lead to a review of the data sources used for compilation following meetings with providers of such data to discuss reasons behind the discrepancies. These meetings involve staff of the SSCU responsible for direct investment statistics, merchandise trade, and trade in services statistics, as well as staff of the SCCU, MoF and other data-producing agencies.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.

Balance of payments’ staff are entitled to comment on misuses of statistics. Bilateral discussions with major data users take place, as the need arises, to resolve any interpretation issues.

1.2 Transparency

1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

The Law on the NBU is published on the website of the NBU, both in Ukrainian and in English, while the Statistics Law in published on the website of SSCU (in Ukrainian). The first page of the balance of payments publication contains the list of senior compilers, with telephone and facsimile numbers, for users interested in obtaining more information.

1.2.2 Internal governmental access to statistics prior to their release is publicly identified.

Information on internal governmental access to balance of payments data are provided in the draft SDDS metadata that have been provided to the IMF’s Statistics Department for review. However, the balance of payments publication does not contain any note to that effect. The SSCU has prepared SDDS metadata for merchandise trade statistics that provide information on data access prior to release, and that are published on the SSCU’s website, both in Ukrainian and English.

1.2.3 Products of statistical agencies/units are clearly identified as such.

The balance of payments publication is clearly identified as a product of the NBU, and any organization that reproduces or uses these statistics must attribute the data to the NBU. A note to that effect is included in the publication. The NBU will make a claim whenever an organization quotes its statistics without attribution.

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.

The NBU revises the publication’s note on sources and methods immediately after the introduction of methodological changes, new data sources, or statistical techniques, but does not give users advance notice of such changes.

1.3 Ethical standards

1.3.1 Guidelines for staff behavior are in place and well-known to the staff.

The Law on the NBU provides clear guidelines to staff concerning conflict of interests, ethics, and confidentiality issues. Article 65 of the Law on the NBU stipulates that officials of the NBU are prohibited from becoming members of managing bodies or shareholders of commercial banks, and other financial institutions. Articles 66 stipulates that officials of the NBU are prohibited from disclosing information that constitutes a service secret or is of a confidential nature and has come known to them in the performance of their duties, even after resignation from the NBU, except for cases provided for by the laws of Ukraine.

2. Methodological soundness

2.1 Concepts and definitions

2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.

The concepts and definitions used by the BOPD broadly follow internationally accepted standards and are generally well supported by the compilation system established by the NBU. The balance of payments is compiled on the basis of the BPM5.

2.2 Scope

2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.

The scope is broadly consistent with the recommendations included in the BPM5. The NBU has implemented methodologies to measure imports and exports by individuals that are not recorded by customs authorities, the so-called shuttle trade. Shuttle trade imports are measured using a data model for imports and bilateral exchange of data with major trading partners for exports. However, the quality of these estimates could be improved by conducting a travelers’ survey. Compensation of employees and workers’ remittances are estimated from ITRS data. Often, such data source provide only partial coverage of these transactions and should be supplemented by a travelers’ survey, which would improve estimates of compensation of employees and, indirectly, assist in allocating ITRS’ estimates between compensation of employees and workers’ remittances. Finally, at present, there is no entry for reinvested earnings of foreign direct investment (FDI) enterprises, as the imputed flows measured using the SSCU’s quarterly FDI survey are not materially significant (US$1.5 million in 2001).

2.3 Classification/sectorization

2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.

The classification used for compiling and reporting the balance of payments follows the standard components presentation recommended in the BPM5. The financial accounts transactions are presented using the recommended institutional unit classification. Information on selected exceptional financing transactions is available upon request. However, the component details for current transfers are not provided, although total transfers are quite significant. In addition, inter-enterprises’ receivables and payables are recorded under other investment, other assets/liabilities, other sectors, short-term without a breakdown of these transactions between trade credits, loans between FDI enterprises, and other investment, as relevant. The SSCU’s survey form used for collecting these transactions does not request relevant instrument and currency breakdowns as well as additional information on write-offs for bad debts, which are all required for balance of payments purposes.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

Market prices are used to value flows and, to the extent possible, stocks. In the IIP, there are some limitations to the extent to which BOPD staff can measure the market value of liabilities in equity securities and direct investment, as many of these liabilities are nonlisted shares that are assessed based on historical values.

Up to 1998, there was some potential for deviations from the market prices valuation principle for exports and imports of goods, as barter trade was important, representing approximately 6–7 percent of total trade. However, this potential largely vanished, as barter trade was approximately 1.3 to 1.4 percent of total trade in 2000 and keeps declining. Even when barter trade was important, customs officers were responsible to ensure that customs documents correctly reflected market prices of traded goods.

The balance of payments of Ukraine is published in U.S. dollars. As such, transactions in hryvnia and non-U.S. dollar foreign currencies are converted to U.S. dollars using the average monthly official exchange rates of the NBU for monthly ITRS data reported by banks and enterprises. Merchandise trade data published by the SSCU are also denominated in U.S. dollars. The SSCU uses the daily exchange rate of the NBU to convert the values reported on declaration forms to U.S. dollars on the basis of the date of transaction reported on the forms.

Transactions on inter-enterprises’ receivables and payables—in the BPM5; other investment; other assets (liabilities); other sectors; short-term—are derived from stocks data on inter-enterprises assets and liabilities compiled by the SSCU. As no information is available on the currency of denomination of such assets and liabilities, they are assumed to be denominated in hryvnia, the currency in which they are reported. Thus, changes in these stocks data are measured in their reported currency and then converted into U.S. dollars to derive transactions in conformity with the BPM5.

2.4.2 Recording is done on an accrual basis.

The main data source for compiling balance of payments is a closed ITRS. As a result, transactions are recorded on a cash basis. However, the staff of the BOPD adjusts data to an accrual basis when differences are materially significant. Such adjustments are made for transactions on loan and debt securities liabilities, which are recorded on an accrual basis for transactions on principal and interest.

Customs basis trade data are recorded in accordance with the general trade system of recording customs declarations. Trade of goods not subject to customs declarations, such as energy and electricity, are recorded on an accrual basis using enterprise survey data. Services are recorded at the time they are paid, with the exception of major trade in services, such as the receipts for pipeline services and the renting of Sevastopol port facilities, as well as imputed payments for the provision of technical assistance, which are recorded on an accrual basis.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.

Current account transactions are recorded on a gross basis, while financial accounts are reported net for each of the standard components of the BPM5, as recommended. Investment income of FDI enterprises are recorded net of withholding tax and not gross, but this is not a materially-significant deviation from grossing/netting procedures; although the issue should be addressed by the BOPD staff.

3. Accuracy and Reliability

3.1 Source data

3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions.

The ITRS established by the NBU is a closed-bank reporting system supplemented by direct reporting of enterprises that have a bank account abroad, as well as by recourse to survey and administrative data. Source data provide a broadly adequate coverage of international transactions of Ukraine.

The BOPD staff collects monthly report forms from all commercial banks of Ukraine that maintain direct correspondent relations with nonresident banks and/or undertake operations in foreign currency. Banks report monthly transactions according to the standard BPM5 classification, by currency of denomination, country of transaction, and country of correspondent bank. Banks must classify all transactions, except those below the Hryvnia equivalent of US$20,000 whose purposes do not have to be clarified. However, practice shows that very few transactions are reported as unclassified. Banks are currently required to provide a copy of the payment order for transactions over a US$250,000 threshold. Payment order information is used by BOPD compilers to monitor the accuracy of the classification of transactions performed by commercial banks’ staff. However, as this threshold is relatively high, it has a negative impact on the accuracy of the classification of reported transactions. In addition, payment order information does not allow the identification of the resident party to the transaction, further reducing the monitoring of reported transactions. To address these issues, the Economic Department has suggested a reduction of the threshold for transactions requiring the provision of additional information about the resident party to the transaction as well as its identification using the Unified State Register of Enterprises and Organizations. Banks’ reporting is supplemented by direct reporting of enterprises for all enterprises that have a bank account abroad. According to the regulation on foreign exchange, enterprises must obtain an authorization from the NBU in order to open a bank account abroad. The BOPD is automatically informed of such request for authorization and uses this information to update the list of enterprises included in its direct reporting of enterprises. There are approximately 100 enterprises that must currently complete form 2–PB, which provides monthly information on all transactions carried out through these specified accounts of Ukrainian enterprises. The coding of these transactions is being performed by staff of the Economic Department.

Current Account

Goods: Trade in goods is largely derived from SCCU data compiled monthly from customs declarations. The SCCU tabulates these data and provides them to the SSCU, which supplements them using survey information on goods procured in ports and trade on energy, which are not subject to customs reporting. These trade data are provided to the staff of the BOPD who adjusts them to include repairs on goods and shuttle trade, using the SSCU’s survey information, as well as data on private imports of vehicles, which are not included in customs data. The source data used for the latter is customs information on the number of cars imported by individual and taxes collected on such imports. However, the recording of such imports would be improved if the SCCU would include the value of imported cars in the customs basis trade data it provides to the SSCU. Shuttle trade imports are derived using information from an annual commodity survey of open-air retail outlets conducted by the SSCU and estimated ratios of shuttle trade imports by type of commodities. The staff of the BOPD relies on bilateral exchange of information with compilers of the Russian Federation and Belarus to adjust exports for shuttle trade. The methodology for estimating shuttle trade could be improved with the use of a travelers’ survey. However, such survey is not currently conducted due to lack of resources within the SSCU, although the survey forms have been designed and the border points for conducting the interviews have been selected. Ultimately, shuttle trade estimates would benefit from the commodity balancing process that would take place using detailed supply and use tables compiled by the staff of the National Accounts Department of SSCU. Such detailed tables do not exist, but their implementation is included in the long-term plan of the SSCU.

Services: Trade in services are largely derived from the ITRS. ITRS data are supplemented with information from the freight adjustment made to convert cost of insurance and freight (c.i.f.) imports to a free on board (f.o.b.) basis. The results of a survey conducted in 2000 by the SSCU on freight and insurance payments on imports of goods is used to make this adjustment. The SSCU provides survey information on receipts for pipeline services provided to nonresidents. The staff of the BOPD uses the results of the quarterly survey on international services transactions of the SSCU on tourist firms and hotels, as well as ITRS information, to derive the travel component. In addition, staff carries out estimates of travel receipts and expenses based on immigration services’ statistics on the number of persons crossing the border, origins of trips, and assumptions on purposes of trips. These estimates are compared with those compiled from survey and ITRS data for monitoring and adjustment purposes. Provision of technical assistance, shown as a sub-component of other business services, is estimated using administrative data received from the Ministry of Economy. In addition, the other services components, which are derived from the ITRS, are regularly compared with the results of the quarterly international services survey of the SSCU to assess the reliability of the ITRS information. This survey covers 6,000 enterprises and provides estimates for exports of services close to those derived from the ITRS. However, the figures for imports of services from SSCU’s survey are lower than those from the ITRS, an indication that the coverage of the ITRS is superior to that of the SSCU’s survey. At present, there is no sharing with the SSCU of the list of enterprises that import services. After amending the ITRS with regard to the identification of the resident parties to international transactions, the NBU will be able to provide the SSCU with such information, which would be useful to update the business register maintained by the SSCU for its international services survey.

Income: Income transactions are largely derived from the ITRS. Adjustments are made to income on debt (interest) liabilities using information from the MoF on official external debt and guaranteed debt to adjust the recording on an accrual basis. Reinvested earnings of direct investment enterprises are not included, as these data are not materially significant. Dividends of direct investment enterprises are recorded net of withholding tax, and not gross, as recommended in BPM5. Staff of the BOPD has agreed to examine these data and report them on a gross basis and record the withholding tax as a current transfer.

Current transfers: Current transfers are derived from the ITRS for worker’s remittances and is based on administrative data, compiled by the Ministry of Economy, for technical assistance provided to Ukraine. Recourse to this data source is important, as Ukraine receives a significant amount of technical assistance.

Capital and Financial Account

Capital account

Capital transfers: The staff of the BOPD works in close cooperation with the staff of the MoF responsible for official external debt and is provided with information on debt forgiveness, which occurs in the instances of debt-restructuring agreements, and that are recorded under capital transfers in the capital account.

Financial Account

Direct investment: Direct investment statistics are derived from the ITRS and the results of the quarterly FDI survey conducted by the SSCU. The survey covers all direct investment enterprises in Ukraine, as it is mandatory to register as such, and most direct investors, although the coverage of the latter is not as complete. ITRS information is supplemented using survey information for investment in kind, which is not recorded by the ITRS; and for selected privatization receipts, which are not captured by survey information. However, the survey forms should be improved to allow the identification of loans granted by the direct investors to the direct investment enterprises.

Portfolio and other investment: Transactions on debt securities are adjusted to an accrual basis using information from the MoF. The MoF provides a detailed schedule of payments of interest and principal as well as actual disbursements for all the components of official external debt. This information is used to record all external debt transactions, whether portfolio investment (for bonds and notes) or other investment (for loans) on an accrual basis and arrears, when relevant, to the other investment; other liabilities; general government; short-term component of the financial account. ITRS information on transactions on equity securities liabilities for other sectors is regularly monitored with information available from the State Committee on Securities and Stock Exchange, or using other alternative sources of information, to confirm the classification of transactions as well as reported amounts. Finally, the ITRS information on the component other investment; other assets/liabilities; other sectors is supplemented by survey data from the SSCU on inter-enterprises receivables and payables. This monthly survey covers approximately 55,000 enterprises and provides separate information on stocks of receivables and payables with the rest of the world, broken down by CIS and other countries. Needed improvements to this survey are discussed in section 3.1.2.

Reserve assets: The data are provided by the Foreign Exchange Regulation Department of the NBU. In addition, this department has recently implemented the reporting format of the IMF’s Data Template on International Reserves and Foreign Currency Liquidity (Reserve Template), a mandatory requirement for SDDS subscription. The data have been compiled according to the Guidelines for a Data Template but not yet reviewed by the IMF. These data have not yet been disseminated to the public.

In addition to these data sources, the financial press is regularly monitored mostly to review the information publicly available on significant current and financial account transactions. This review allows the NBU to be more specific in the analysis it provides to data users by making reference to transactions that are not of a confidential nature.

3.1.2 Source data reasonably approximate the definitions, scope, classification, valuation, and time of recording required.

The data sources used by the NBU provide an adequate basis to approximate the definitions, scope, classification, and time of recording recommended in the BPM5. The major issues are the need (i) to lower the threshold for banks to provide payment order information that should also identify the resident party to the transaction; (ii) to regularly conduct a travelers’ survey; (iii) to revise the survey forms used for collecting information on inter-enterprises’ receivables and payables to include information on debt instruments, currency of denomination, debt maturity, and write-offs for bad debts, and; (iv) to separately identify FDI investor loans in the FDI survey forms. Notwithstanding these issues, the range of data sources used allow compilers to make the adjustments needed to broadly conform to the guidelines set out in BPM5.

3.1.3 Source data are timely.

The NBU receives timely ITRS data from all its reporting banks and enterprises. Timely reporting for the surveys conducted by the SSCU is ensured by direct follow-ups by staff of the over 600 local statistical offices and 27 regional offices. This extremely broad network of local offices and the close follow-ups conducted by SSCU staff guarantees almost 100 percent response rate for enterprise surveys conducted by the statistical office; although, in some instances, the business registers supporting these surveys are not current, leading to some under coverage of transactions.

3.2 Statistical techniques

3.2.1 Data compilation employs sound statistical techniques.

The ITRS of the NBU is a fully computerized system where opening and closing account balances of reporting banks are monitored monthly—on an individual bank’s basis—with account balances reported for the purpose of money and banking statistics. Any discrepancy is automatically investigated, and as needed, follow-ups are conducted with reporting banks. In addition, banks’ balances are also cross-checked with the report forms used to compile the IIP information collected by the BOPD. Such verifications are possible, as the ITRS is a closed system. The system also automatically identifies large transactions, which are compared with the payment order information that banks must provide for transactions above a certain reporting threshold. The NBU is addressing the main weakness of the current system by reducing the threshold for providing payment order information from US$250,000 to US$50,000. In addition, banks will be required to provide the enterprise unique identification number with the payment order information, allowing BOPD compilers to directly verify the reported information with the resident party to the transaction. The new bank report forms and instructions were submitted for discussion with the banks’ representatives that participated to the seminar “On the Role of the Banking System in Establishing an Information Base for the Compilation of Ukraine’s Balance of Payments”.

3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.

The methodology used for compiling shuttle trade estimates is based on the use of all available data sources. However, the staff of the BOPD is aware that these estimates could be improved by conducting a sample survey of travelers at selected border points.

3.3 Assessment and validation of source data

3.3.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide planning.

On a monthly basis, the reported account balances in the closed ITRS are compared to the banks’ balances reported for money and banking statistics, and the equality between debit and credit entries for neutral transactions is monitored.

The information compiled using the ITRS is compared with other data sources using established quality control and data verification procedures taking place during the quarterly compilation of the balance of payments. This monitoring applies to services by standard components as well as FDI income and equity capital transactions data using SSCU’s survey results. Such procedures are used to confirm the coverage and adequacy of the classification of the ITRS data. Any large transaction is monitored to verify the accuracy of the classification.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Main intermediate data are validated against other information where applicable.

High value financial accounts transactions are monitored using information from the financial press. High value portfolio investment transactions are cross-checked with information available from the State Committee on Securities and Stock Exchange, or using other alternative sources of information, to monitor reported share prices.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

Travel data compiled using information from the ITRS and survey information on revenues of tourist agencies and hotels are compared with estimates derived from a data model using immigration authorities’ counts of entries into Ukraine and assumptions on purpose of stay and average daily expenses. Nonetheless, travel estimates would benefit from the implementation of a travelers’ survey. ITRS data on FDI income and financial flows are regularly monitored using FDI survey information.

3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated.

Net errors and omissions are constantly monitored and movements in the series will lead to a review of the data. Bilateral comparison with individual CIS countries are done for merchandise trade. The staff of the NBU has examined the data from the Bank of International Settlements locational international banking statistics, and the amounts reported for Ukraine are negligible.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes.

Materially significant revisions to the data are highlighted using footnotes to the tables that describe the source and magnitude of the revision. While staff of the BOPD regularly conducts analysis of revisions, there are no published studies to review preliminary and final data and identify systematic source of errors or omissions. In addition, data users would benefit from the provision of detailed studies of the impact on previously published series of the annual revision process and recourse to new data sources. Such studies would enhance the transparency of the statistical process.

4. Serviceability

4.1 Relevance

4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.

There is no formally established process of consultation with government users or a user advisory group that would also include users from the private sector or academia, or a users’ survey. However, the inter-agency working group, established by the Cabinet of Ministers resolution on national account of August 9, 2001, instituted a process that allows BOPD staff to monitor the relevance of its data in meeting the needs of SNA compilers and obtain the views of other major data users that participate in this working group. In addition, the regular participation of BOPD staff in international meetings/seminars, such as the IMF-sponsored 2001 Coordinated Portfolio Investment Survey (CPIS) and seminars—recently held at the central banks of Austria, Germany, France, and Japan—promotes the relevance of statistics and the implementation of improved methodologies.

4.2 Timeliness and periodicity

4.2.1 Timeliness follows dissemination standards.

Ukraine’s balance of payments meets the timeliness requirements of the SDDS; it is compiled and disseminated quarterly. The data are first released on the website of NBU approximately 75 to 80 days after the end of the reference quarter. The Balance of Payments publication is available later and includes more detailed tables as well as analysis and notes on sources and methods.

Data on merchandise trade are disseminated monthly by the SSCU, no later than 45 days after the end of the reporting month; although these data are disseminated on a cumulative basis and not as discrete monthly series. Official reserve assets are disseminated within one week after the end of the reference month. The monthly Reserves Template and the annual IIP are not disseminated, although both data sets are currently compiled for the internal purposes of the NBU. 30

4.2.2 Periodicity follows dissemination standards.

The periodicity of the balance of payments, merchandise trade, and reserve assets meet the requirements of the SDDS. The Reserves Template and the IIP are not disseminated.

4.3 Consistency

4.3.1 Statistics are consistent within the dataset.

The concepts, definitions, and classifications for producing quarterly and annual balance of payments statistics are the same and broadly consistent with the recommendations included in BPM5. Whenever annual data sources are used to replace quarterly estimates/data sources, the quarterly series are benchmarked to the level of the annual series at the time of the annual revisions, which take place the fourth quarter of every year. The current year’s estimates and quarterly data for the previous year are subject to revisions at the time of the annual revision process.

The net errors and omissions component has been negative and large during 1997–99 but has significantly decreased in 2000 and 2001—a possible indication of better coverage of international transactions.

4.3.2 Statistics are consistent or reconcilable over a reasonable period of time.

Time series for the balance of payments are consistent since 1994—the first year the NBU started compiling and disseminating data. Component details for services transactions were increased in 2000, and such details were carried back to 1999, consistently with the two-year revision policy of the NBU. Any significant revisions to the series or exceptional transactions are explained using footnotes to the statistical tables, data confidentiality permitting. The analytical text in the publication provides an analysis of recent fluctuations in the series.

4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.

The balance of payments data are consistent with other macroeconomic data sets of Ukraine with one exception. Balance of payments data are a direct input to the external sector of the national accounts, but final annual revisions to the national accounts take place approximately 12 months after the end of the reference year, while those of balance of payments are made 15 months after the end of the reference year. The authorities should address the issue of this difference in the revision schedules for national accounts and balance of payments, which leads to inconsistencies between the two datasets. Merchandise trade data are compiled on a cumulative basis in the course of the year. Monthly trade data are revised once a year, in time for the production of the revised annual balance of payments estimates. Money and banking statistics and official external debt statistics are consistent with balance of payments.

4.4 Revision policy and practice

4.4.1 Revision follow a regular, well-established, and transparent schedule.

The revision cycle follows a long-established schedule; quarterly data are not revised until the publication of the fourth quarter data, at which time all quarters of the current and the previous year are subject to revision. However, this revision cycle is not clearly made known to the public, although major data users are generally aware of this schedule. The draft metadata provided to the IMF include a description of the revision policy and schedule, but have not yet been posted on the NBU’s website or included in the NBU’s publications.

Any change in methodologies is documented in the sources and methods section of the quarterly Balance of Payments publication of the NBU. The implementation of new data collection procedures follows an established schedule. For example, the BOPD staff has consulted banks concerning the revision of the threshold to provide detailed payment orders along with the information included in form 1-PB. Banks are informed that this change will be implemented following the adoption of a forthcoming resolution by the board of directors of the NBU stipulating the date when these new reporting rules would become effective.

4.4.2 Preliminary data are clearly identified.

The website of the NBU contains a note to the fact that quarterly data are provisional while data in time series format are “refined.” However, the Economics Department should seek to better inform the public about the fact that the quarterly data are preliminary and revised once a year, at the time of the publication of the fourth quarter’s data, as well as once more 12 months later.

4.4.3 Studies and analyses of revisions are made public.

The statistical tables included in the balance of payments publication and posted on the NBU’s website include footnotes highlighting and explaining major revisions. However, the BOPD does not prepare detailed analysis of revisions by standard components, including explanatory notes on the reasons as well as the sources of such revisions. Such analysis would enhance the transparency of the data revision process.

5. Accessibility

5.1 Data accessibility

5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

The presentation of the balance of payments included in the NBU’s publication follows the standard component presentation of the balance of payments. The publication includes a detailed set of statistical tables; aggregated and detailed balance of payments presentations in time-series format for the rest of the world and two main economic regions; supplementary tables on exports and imports of goods by major categories and for two main economic regions; supplementary tables on total exports and imports by country, and; occasional supplementary tables on barter trade, shuttle trade, or direct investment. However, an analytical presentation of the balance of payments is not published and separate tables showing the impact of debt rescheduling agreements are not provided.

The NBU and the SSCU have made some efforts to explain the differences that arise between the two different trade balances published by the two organizations: the NBU publishes the various adjustments made to the trade data disseminated by the SSCU, while the latter includes a note to its statistical tables that specifies that merchandise trade estimates exclude shuttle trade.

5.1.2 Dissemination media and formats are adequate.

The data are first released on the website of NBU approximately 75 to 80 days after the end of the reference quarter. This release is followed by a publication that provides an analysis of recent trends and a set of supplementary tables.

5.1.3 Statistics are released on a pre-announced schedule.

An advance release calendar (ARC) is not provided.31

5.1.4 Statistics are made available to all users at the same time.

The data are released simultaneously to all users using the website of the NBU.

5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request.

Few nonpublished sub-aggregates of balance of payments statistics are available. The NBU collects data by country and would be able to provide a more complete geographical breakdown of the balance of payments. However, as work on a cost-recovery basis is not a practice adopted by the NBU, the staff of the BOPD cannot respond to such requests, as they would be too costly to fulfill. Additional information on external debt, including exceptional financing transactions, could be provided upon request to the Economic Department. Supplementary details on direct investment by region of Ukraine, country of investor, industry, and type of transactions are available upon request to the SSCU. However, these data are not fully consistent with those included in the balance of payments, as the latter are supplemented by banks’ reporting and privatization receipts, when relevant. Additional details for merchandise trade on a customs basis are available upon request to the SSCU. When applicable, requests to the SSCU are processed on a cost-recovery basis.

5.2 Metadata accessibility

5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

The note on sources and methods included in the quarterly balance of payments publication provides documentation to that effect. However, this note does not specify that inter-enterprises’ receivables and payables are not broken down into trade credits, FDI loans, and others or that investment income is recorded net of withholding tax and not gross, as recommended in the BPM5.

5.2.2 Levels of detail are adapted to the needs of the intended audience.

The website and publication of the NBU respond to the needs of major data users.

5.3 Assistance to users

5.3.1 Contact person for each subject field is publicized.

The quarterly balance of payments publication includes the list of senior compilers and their area of specialization with a telephone and facsimile numbers where they can be reached. Staff can provide service and support in Ukrainian, Russian, and English.

5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available.

The website of the NBU provides—in Ukrainian and English—the list of the statistical publications available, which includes the quarterly balance of payments publication, available in Ukrainian and in a bilingual English-Russian format. The data on the website of NBU are available in Ukrainian and English.

Table 6.

Ukraine—Data Quality Assessment Framework: Summary of Results for Balance of Payments

(Compiling agency: National Bank of Ukraine)

Key to symbols: NA = Not Applicable; O = Practice Observed; LO - Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Not Observed; SDDS = Complies with SDDS Criteria

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APPENDIX I: Main Features of the Special Data Dissemination Standard (SDDS)

This section contains highly condensed descriptions of the Special Data Dissemination Standard (SDDS). More details on the SDDS can be found on the IMF’s Dissemination Standards Bulletin Board (DSBB) on the Internet at http://dsbb.imf.org.

Data dimension (coverage, periodicity, and timeliness)

  • The dissemination of 18 data categories, including component detail, covering the four main sectors of the economy, with prescribed periodicity and timeliness.

Access dimension

  • The dissemination of advance release calendars providing at least a one-quarter ahead notice of approximate release dates and at least a one-week ahead notice of the precise release dates.

  • The simultaneous release of data to all users.

Integrity dimension

  • The dissemination of the terms and conditions under which official statistics are produced and disseminated.

  • The identification of internal government access to data before release.

  • The identification of ministerial commentary on the occasion of statistical release.

  • The provision of information about revision and advance notice of major changes in methodology.

Quality dimension

  • The dissemination of documentation on statistical methodology and sources used in preparing statistics.

  • Dissemination of component detail and/or additional data series that make possible cross-checks and checks of reasonableness.

SDDS subscribers are required to:

  • Post descriptions of their data dissemination practices (metadata) on the IMF’s DSBB.

  • Summary methodologies, which describe data compilation practices in some detail are also disseminated on the DSBB.

  • Maintain an Internet website, referred to as the National Summary Data Page (NSDP), which contains the actual data described in the metadata, and to which the DSBB is electronically linked.

At the March 29, 2000 meeting of the IMF’s Executive Board, Directors approved the incorporation of a new SDDS data category on external debt. The transition period for implementing this data category expires in March 2003.

As a result of the IMF Executive Board’s Third Review of the SDDS in March 2000, IMF staff began monitoring observance of the Standard through NSDPs maintained on the Internet. Monitoring commenced at the beginning of July 2000 and is limited to the coverage, periodicity, and timeliness of the data, and to the dissemination of advance release calendars.

APPENDIX II: Data Quality Assessment Framework—Generic Framework

(July 2001 Vintage)

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The elements and indicators included here bring together the “pointers to quality” that are applicable across the five identified dimensions of data quality.

APPENDIX III: Users’ Survey

With the assistance of the authorities and as a complement to the mission’s own assessment of the quality of Ukraine’s statistics, a survey was conducted among users of macroeconomic statistics, including universities, research institutes, embassies, commercial banks, other private sector, and government agencies. Thirty responses were received, including 11 from universities/research institutes, 1 commercial bank, 5 private sector’s users, and 13 government agencies. The number of responses received was lower than that observed for ROSCs—Data Module conducted in other countries.

The respondents’ views on Ukraine’s statistics were generally positive. Respondents were most satisfied with the overall quality of the statistics, the underlying methodology, the periodicity of the data and its access. Largest dissatisfaction were recorded for the level of detail and coverage of the statistics and the availability of information about revisions and methodological descriptions. Listed below are the major concerns/issues that data users, who attended a users’ meeting organized by the mission, had raised concerning the data.

One of the main concerns of data users is the nonavailability of data in time series format-i.e., expressed in terms of a fixed reference period-for GDP, CPI, PPI, and industrial production index. Users also indicated that the publication of data on a cumulative basis, such as is the case for monthly merchandise trade, is not appropriate.

Users would also like to be provided with more detailed breakdowns of the SNA components and requested improvements to the deflation methodology of the GDP. Following annual revisions, users would like to be provided with revisions to the underlying quarterly series, as the latter are not readily available. There was also a demand for the compilation of input-output tables at a greater level of commodity/industry detail than what is currently done and for the implementation of a set of financial accounts. However, users recognized that the rapid implementation of the improvements they are demanding would require that additional resources be allocated for SNA compilation within the State Statistics Committee. They also indicated that the availability of monthly GDP and regional accounts statistics were two important features of the SNA of Ukraine. Finally, there was no users’ consensus as to what constitutes an appropriate trade-off between timeliness/accuracy-reliability of the national accounts. Some users indicated their preference for longer dissemination lags to support improvements in accuracy-timeliness, but others were satisfied with the current compromise, but requested that the data be more frequently revised.

Users supported the adoption of international standards and classifications, although the absence of retrospective adjustments to the time series following the implementation of new methodologies has created numerous difficulties to data users. This issue was mentioned for a number of data series, including GDP, industrial production index, merchandise trade, and GFS. Users also indicated the need for better explanations of the sources and impact of large revisions to balance of payments statistics.

Users were satisfied with the availability of data in electronic format, which are provided upon special request to the compiling agencies. However, users pointed out that the website maintained by the SSCU does not contain up-to-date information and does not allow the retrieval of data in electronic format. On the other hand, the NBU’s website was quoted as the best statistical website of Ukraine.

Users were concerned about the absence of up-to-date methodological notes for many macroeconomic data series, including GDP and GFS, and requested that updated notes more precisely describe the methods for compiling the data. For example, users had great difficulty reconciling GFS disseminated by the MoF with the government sector data included in the SNA and requested reconciliation items between the two data series. Similar reconciliation items were requested for balance of payments and merchandise trade statistics.

During the meeting, some users indicated that, while they felt that monetary statistics was the best set of macroeconomic statistics in Ukraine, they would require the dissemination of more detailed methodological notes on these statistics. They also suggested the provision of detailed data on interest rates by the NBU.

Users noted that the absence of coordination of the revision policies for the national accounts and balance of payments statistics creates difficulty for compilers and, as a result, users of statistics.

The absence of a national body to consider all statistical problems as a whole and advise on priority for improvements appeared as a problem to users and should be remedied. In that regard, some users indicated that the recent establishment of an inter-agency working group on national accounts should be beneficial to the further development of the SNA in Ukraine.

Complete survey responses are provided in Table 7 below, followed by a summary of respondents’ comments and suggestions.

Table 7.

Ukraine—Results of the Users’ Survey

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Comments and Suggestions of Users’ Survey

Areas for improvement to coverage:

  • Prices (2)

  • Measurement of active population

  • GDP deflators (2)

  • Finance statistics

  • External trade (2)

  • Payrolls

  • Paid services by type

  • Households’ incomes and expenditures

  • Regional statistics

  • Use of natural resources

  • Environmental protection

  • Small businesses

  • Investment

  • Structure of debt in arrears

Areas for improvement to level of detail:

  • More detailed industrial breakdowns

  • Sufficient level of detail by industry, especially breakdown of industrial production by type of activity

  • Regional accounts (3)

  • Business finance

  • Labor remuneration

  • Classification of traditional and new industries

  • Budget appropriations to healthcare institutions by region

  • SNA

  • Statistical reporting by selected agricultural businesses

  • Value added structure by quarters

  • Investment structure

Areas for improvement to periodicity:

  • SNA

  • Price indices

  • State Treasury reports

  • Regional statistics should be produced monthly

  • Annual periodicity of data release is adequate

  • Quarterly supply of data is enough

Areas for improvement to timeliness:

  • Compilation lag for revised annual GDP should be less than 12 months after reference year

  • Compilation period should be reduced to 30 days (2)

  • GDP for December and the fourth quarter

  • Sales of goods including by barter

  • Financial results of enterprises

Provision of an advance release calendar:

  • No information about such calendar

  • No public calendar of revisions to data series

Provision of information about revisions:

  • Revisions of annual GDP are not always accompanied by revisions of the quarterly indicators

  • Explanations on large revisions are not always available (2)

  • Official statistics of Ukraine are rarely revised due to the very high quality of the data

Access to official statistics:

  • No access to detailed breakdowns and revisions

  • Statistics are mainly disseminated in the forms of press releases

  • Insufficient data on the state budget execution

  • Relatively easy access to the data although some indicators are not released publicly

  • There is no easy access to external debt data and SNA

  • Required data are supplied in electronic format on special request (3).

Easy access to metadata and methodological notes:

  • The SSCU website must include methodological notes (now available only by request)

  • Not enough details about compilation methods for GDP assessment

  • Metadata are often insufficient or stale

  • Cannot find the methodological papers

Methodological issues:

  • Require more discrete data versus cumulative data

  • SNA does not use a fixed base year for constant price GDP components

  • Require improvements to the quality of GDP deflators

  • Labor market data are biased

  • NBU and SSCU use different methodologies for trade in goods statistics compilation

  • Computation of fixed assets is inadequate

  • Measurement of the shadow economy is an issue (2)

  • Lack of import/export prices

Assessment of Ukraine’s statistics:

  • As good as those of the other CIS countries (3) but lagging behind Eastern Europe (1)

  • Equal to that of Eastern Europe

  • Difficult to make the judgment

  • Russian statistics are better

  • Quality of the statistics is high although the ongoing revisions bring some uncertainty about accuracy of the data

  • Ukrainian statistics are of high quality and do not undergo frequent revisions

  • Average quality statistics but better than Russian or Polish

  • Adequate quality statistics

  • Good quality

  • Ukraine’s statistics are one of the best within the CIS

  • Quality of the statistics is quite satisfactory for Ukraine

  • Quality of the official statistics is insufficient

Suggestions:

  • Improve statistical methodologies (3)

  • Provide better access to the SSCU compilation methods for individual indicators (2)

  • Provide better access to statistics (6), especially in electronic format (2) and for budgetary spending units (1)

  • Provide more information on the data revisions policy

  • Show statistical discrepancies for GDP assessed by different approaches.

  • Improve compilation methods for GDP deflators (2)

  • Provide more detailed breakdowns of SNA (2)

  • Provide consistency between the NBU and SSCU estimates for merchandise trade (3)

  • Explain the links between government sector in the SNA and state budget reporting (4)

  • Improve estimates of the shadow economy

  • Make available IIP data

  • Improve consistency between production by industrial branches and value added data (2)

  • Improve compilation methods for the index of industrial production

  • Improve coverage of enterprises of all types of ownership.

  • Improve all areas of real sector statistics: industrial breakdowns, incomes and expenditures, value added, profit, employment, labor efficiency

  • Compute gross value added for the regions, cities, territories, urban agglomerations, economic regions, border zones

  • Compile regional statistics for all data categories (2)

  • Disseminate data on the state debt by maturity

  • Improve quality of the employment data by region

Number in parenthesis refers to the number of users providing similar views.
1

The current Statistics Law is a revised version of an earlier law that was adopted in 1992. It was revised with a view to making Ukraine’s statistical legislation consistent with international best practices. As defined by the Statistics Law, the state statistical agencies consist of a central executive agency and territorial units established by this agency and subordinated to it. The current law is supplemented by the Presidential Decree of April 14, 1995 (No. 312/95), which establishes the SSCU as the central executive agency for official statistics. Under Article 12 of the Statistics Law the SSCU is therefore responsible for collecting, processing, aggregating, analyzing, disseminating, storing, and protecting statistical information. A further Presidential Decree in November 22, 1997 (No. 1299/97) mandated the development of an integrated system of statistics according to international standards and directed the Cabinet of Ministers to make legislative, regulatory, and financial arrangements to support the new statistical system.

2

Based on the medium-term/long-term programs, the SSCU prepares annual plans that detail the activities to be undertaken during the year, including collection and processing of the specified data, publication, preparation of methodological documents, introduction of new classifications, etc., as well as the data to be provided to the SSCU by other data producing agencies. The annual plans are approved by the Cabinet of Ministers and agreed with other data providing agencies. The implementation of the medium-term program and annual plans is followed up through reports submitted to the SSCU by concerned agencies.

3

The SSCU also participates in several groups coordinated by other agencies, such as the group coordinated by the MoF comprising representatives of the SSCU, MoF, and STU. The group is working since December 3, 1997 (No. 18–29215) on issues related to government finance statistics (GFS) and the chart of accounts of enterprises.

4

Regional offices of the SSCU correspond to the administrative organization of the government. There are 25 offices at the oblast level, 2 city offices in Kyiv and Sevastopol, and 696 sub-offices in rayons.

5

Management is aware of the efficiencies to be gained from centralizing data processing in the main Computer Center in Kyiv, and steps have been taken to move in this direction. For example, two new report forms for nonfinancial enterprises (1-predprinimatelstvo and balance sheet information of enterprises) are processed in the main Computer Center. These forms were recently “unified” by combining several old report forms.

6

The annual turnover of staff is about 10 percent.

7

The Presidential decree of November 6, 1997 (No. 1249/97) allowed the establishment of an Advisory Council comprising the chairperson, deputy chairpersons, other senior officials of the SSCU, as well other persons approved by the Cabinet of Ministers.

8

The SSCU distinguishes between the USREO, which is an administrative register, and the statistical register. In accordance with Article 10 of the Statistics Law the maintenance of the USREO is the responsibility of the SSCU. The register records vital information about enterprises. It is compulsory for new enterprises to be registered in the USREO.

9

Following current legislation, medium and large enterprises are defined as those with 50 employees or more. For statistical purposes, different criteria for defining enterprises are used.

10

Following the order of the President (of November 19, 2001, No. 328/2001–rp), during 2002–2003, improved price and volume indices—including unit value indices for imports and exports—will be compiled following international best practices.

11

Improvements in methodology now allow compilation of fourth quarter estimates that are consistent with source data of the three previous quarters.

12

Rough monthly estimates of GDP are also compiled.

13

The data quality assessment for the consumer and producer price indices is the same for this section in view of the broad overlap between the two statistical programs on this dimension.

14

Household Budget Survey

15

To provide guidance in statistical activities the Presidential Decree of November 6, 1997 (No. 1249/97) allowed the establishment of an Advisory Council comprising the chairperson, deputy chairpersons, other senior officials of the SSCU, as well other persons approved by the Cabinet of Ministers.

16

The data quality assessment for the consumer and producer price indices is the same for this section in view of the broad overlap between the two statistical programs on this dimension.

17

The nonmonetary expenditures of households that are normally (but not universally) excluded from CPIs in international practice comprise—

  • household’s consumption of goods and services that they produce for themselves (production for own consumption) and are recognized within the production boundary of the 1993 SNA, and

  • households’ consumption of goods and services that are received as compensation in-kind by employees from their employers.

An exception to the first exclusion regarding production for own consumption, however, is the frequent (though not universal) international practice that CPIs cover the rental value of those dwellings that are owned by the households that live in them.

18

The population size measure for the actual CPI sample of areas is based on the 1989 census updated to 2000 with vital statistics. The urban population estimate for 2000 also was 68 percent of the total.

19

In the CPI, netting operations are used for constructing the weights for durable goods and, in certain circumstances, owner-occupied dwellings. Durable goods, other than dwellings, are considered by the 1993 SNA to be consumed when acquired and thus are treated on an acquisitions-less-disposals basis, as disposals must be treated as effectively reversing previously recorded consumption. In contrast, dwellings are considered by the 1993 SNA to yield services that are consumed over time, and thus provision is made for the consumption of these services as well as the accumulation of dwellings as a capital asset. The value of services from dwellings comprises the rentals paid for those services and capital formation in the form of dwellings comprises the acquisitions less disposals of dwellings.

20

The most recent census was completed in 2001 but was being processed during the mission and has not yet been incorporated into survey sample frames.

21

See national accounts statistics’ 3.1.1.

22

The data quality assessment for the consumer and producer price indices is essentially the same for this section in view of the broad overlap between the two statistical programs on this dimension.

23

The data quality assessment for the consumer and producer price indices is essentially the same for this section in view of the broad overlap between the two statistical programs on this dimension.

24

The data quality assessment for the consumer and producer price indices is essentially the same for this section in view of the broad overlap between the two statistical programs on this dimension.

25

To provide guidance in statistical activities the Presidential Decree of November 6, 1997 (No. 1249/97) allowed the establishment of an Advisory Council comprising the chairperson, deputy chairpersons, other senior officials of the SSCU, as well other persons approved by the Cabinet of Ministers.

26

The data quality assessment for the consumer and producer price indices is essentially the same for this section in view of the broad overlap between the two statistical programs on this dimension.

27

The data quality assessment for the consumer and producer price indices is essentially the same for this section in view of the broad overlap between the two statistical programs on this dimension.

28

The data quality assessment for the consumer and producer price indices is essentially the same for this section in view of the broad overlap between the two statistical programs on this dimension.

29

Following Ukraine’s subscription to the SDDS, an ARC is regularly updated on the NBU and SSCU websites.

30

Prior to SDDS subscription in January 2003, the NBU has started disseminating the Reserves Template and IIP on a regular basis.

31

Following Ukraine’s subscription to the SDDS, an ARC is regularly updated on the NBU and SSCU websites.

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Cover IMF Staff Country Reports
Ukraine: Report on the Observance of Standards and Codes — Data Module; Response by the Authorities; and Detailed Assessments Using the Data Quality Assessment Framework
Author:
International Monetary Fund
Volume/Issue:
Volume 2003: Issue 256
Publisher:
International Monetary Fund
ISBN:
9781451839029
ISSN:
1934-7685
Pages:
170
DOI:
https://doi.org/10.5089/9781451839029.002