Abstract
This Report on the Observance of Standards and Codes (ROSC) provides a review of Georgia’s data dissemination practices against the IMF’s General Data Dissemination System (GDDS), complemented by an in-depth assessment of the quality of the national accounts, consumer price index, producer price index, government finance, monetary, and balance-of-payments statistics. Georgia has made good progress in improving its statistics in a number of areas. Nonetheless, substantial shortcomings are present in some statistical practices and databases. Some of these shortcomings could be addressed with current resources.
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 Georgia’s officials. This information, which is organized along the lines of the generic DQAF (see Appendix I), was used to prepare the summary assessment of data quality elements, based on a four-part scale of observance, shown in Georgia’s Report on the Observance on the Standards and Codes (ROSC)—Data Module.
I. National Accounts
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 State Department of Statistics (SDS) is an independent government institution operating under the Law on Statistics No. 1071 of November 12, 1997. The Law authorizes the SDS to collect, process, and disseminate official statistics data about the socio-economic development of Georgia. The Law specifies that while government units and agencies may set up specialized statistical units and may undertake their own statistical surveys, these shall operate under the methodological guidance of the SDS. Other provisions of the Law ensure the consistency of methodology, comparability of statistics international standards, and sharing information with other countries and dissemination.
The compilation and dissemination of national accounts statistics are mentioned explicitly in the Regulation for the SDS No. 92 from February 28, 1998, approved by the President of Georgia. Article 5 of the Regulation provides that the SDS is the responsible agency for compiling the national accounts statistics. In addition to that, the President of Georgia has approved a State Program for Development of Statistics for 2001-2005. The compilation and dissemination of national accounts statistics are stated in the State Program.
0.1.2 Data sharing and coordination among data producing agencies are adequate
Article 11 of the Law guarantees the SDS access to data produced by legal entities, including the data produced by government ministries and the National Bank of Georgia (NBG). Important areas of statistics are covered by other agencies, such as the NBG, which compiles monetary and financial statistics; the Ministry of Finance (MOF), which is responsible for compiling government finance statistics; and the State Department of Customs (SDC), which compiles data on imports and exports of goods. The Law gives the SDS primary and coordinating roles in the development of the country’s statistical program.
There are written agreements between the SDS and the MOF, the NBG and the SDC covering the sharing of macroeconomic data, and the SDS management and staff are satisfied with the level of cooperation they receive from these agencies. There appears to be no evidence of major duplication of statistical effort among the various agencies. However, no regular contacts with other statistics producing agencies are maintained to take into account the respondent burden of the enterprises.
0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only
Confidentiality of the data reported to the SDS is guaranteed under Articles 7, 12, and 17 of the Law. The Law does not provide penalties for disclosure. The SDS is planning a new amendment to the Law with a provision for penalties for disclosure. The confidentiality aspect is potentially compromised to some extent as a result of the provisions of the Anti-monopoly Law. According to it, the State Anti-monopoly Service of the Ministry of Economy, Industry and Trade (MOEIT) can request confidential data from the SDS. The conflict between the two laws has not been resolved. In practice, there have been no breaches of the confidentiality of individual business statistics data.
Staff are required to keep individual data confidential, and they are also required to sign a declaration on joining the SDS that confirms awareness of this provision. Access to individual data is restricted to the appropriate staff. However, there are no special aggregation rules to ensure that unintended disclosure does not occur. Senior staff review the data before dissemination to make sure that confidential data is not disseminated.
0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage reporting
According to Article 11 of the Law, the SDS is authorized to request the information it deems necessary from all legal public and private institutions, as well as from individuals. All respondents must furnish the requested information accurately, in the format and time period determined by the SDS. The Code of Administrative Offences (1999) provides some penalties for nonreporting, but they are not considered effective by the management of the SDS. These penalties were mostly applied to newly registered legal entities for noncompliance with the required registration in the SDS Administrative register. In practice they were rarely applied for nonresponse to statistical surveys.
The SDS does not review systematically the response burden and contacts with respondents are very limited. In practice, the SDS headquarters and its regional offices make little effort to create goodwill among data providers.
0.2 Resources
0.2.1 Staff, financial, and computing resources are commensurate with statistical programs of the agency
The National Accounts Division has a staff of nine, which are not adequate for performing the current tasks. There is a high staff turnover—during the last two years seven people have left the division. The salaries of the staff are very unattractive (about US$20-30 per month) and significantly lower compared to similar job positions in other data producing agencies (15 times less than the salaries of the economists in the NBG). The qualifications of the staff are generally adequate. Three economists were trained in the Joint Vienna Institute (JVI) course in national accounts and one in a Eurostat course. No other formal training program in national accounts exists. Most knowledge of national accounts methodology is gained through experience and on-the-job training.
Computing resources are generally adequate. The computers are connected by a network. Hardware and software facilities are quite up to date.
There are significant budget limitations for the SDS to undertake its work program. In the last three years, the SDS has received only about 40-50 percent of the amounts budgeted. The financing of the key basic economic statistics surveys is dependent entirely on the donors aid such as the household budget survey and the labor force survey.
0.2.2 Measures to ensure efficient use of resources are implemented
Although the SDS management claims it gives high priority to the compilation of national accounts statistics, it does not make effective use of the scarce SDS resources for addressing the key data problems. The national accounts staff are often engaged in performing other statistical activities, such as participating in donor financed ad hoc survey projects.
0.3 Quality Awareness
0.3.1 Processes are in place to focus on quality
The SDS management recognizes quality as an important statistical principle. In order to ensure quality, the organization structure of the SDS includes a Statistical Research Institute and an Institute for Informatics and Telecommunications. The Statistical Research Institute is responsible for developing methodology and software solutions for statistical tasks. The Institute for Informatics and Telecommunications is responsible for development and implementation of information and analytical systems of the national statistics and harmonization of classification systems. A Scientific and Advisory Council was established in the SDS in 1997. Apart from the SDS staff, specialists from the MOEIT, the NBG, and academic institutions are, with others, members of the Council. The Council presents assessments and recommendations on the State Program of Statistical Activities, statistical surveys, the structure of the SDS, broad directions of development in the area of statistics and on training and re-training of staff. However, a separate plan for improving quality as such does not exist.
The mission statement of the SDS emphasizes the improvement and harmonization of statistical activities and the maintenance of independence, accuracy, relevance, integrity, timeliness, and professional standard of statistical information produced in Georgia.
0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics
There is no body that provides guidance on the quality of the national accounts statistics and on strategies for improving the statistics process. The two user surveys, conducted in the last two years, seek to obtain feedback on general dissemination issues and not on monitoring the quality of the disseminated national accounts data.
There are no systematic reviews undertaken to identify problems at the various stages of the data collection, processing and dissemination. Due to lack of resources, the SDS headquarter staff does not review the problems in collecting and processing economic data by the local offices.
0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs
The SDS management is aware of the tradeoffs among the dimensions of quality. However, the tradeoffs between timeliness and accuracy of the national accounts are not taken into consideration. Considerable time and effort of the national accounts staff are spent to meet the very tight timeliness requirement for the compilation of the flash quarterly and annual national accounts estimates instead on the preliminary and the final ones.
1. Integrity
1.1 Professionalism
1.1.1 Statistics are compiled on an impartial basis
The Law on Statistics defines the key principles and responsibilities in relation to the collection, processing, and dissemination of statistics in Georgia, with emphasis on international standards, definitions, authenticity, objectivity, and independence. Respondents are obliged to provide clear, objective, and timely data to the SDS, within the context of assured confidentiality of their data.
The Regulation of the SDS addresses the role of the SDS as an independent data producing agency. Professional competency plays a key role in the promotion practices in the SDS. Professionalism is also promoted by dissemination of methodological papers and participation in meetings of the International Statistics Institute, the International Association for Official Statistics, the International Association of Research of Income and Wealth, etc.
1.1.2 Choices of sources and statistical techniques are formed solely by statistical considerations
The SDS is independent in its determination of statistical methods and is required to coordinate the methods used by other statistics producing agencies. There has been no instance of ministerial interference in the choice of the statistical sources and methods. The SDS is free to determine the appropriate data sources and in practice the NAD chooses from a wide range of survey and administrative data from a variety of sources.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics
The SDS national accounts staff comment on erroneous interpretation or the misuse of statistics. The release of the preliminary annual and quarterly national accounts data is usually supplemented by explanatory material for the press to prevent misinterpretation. Also, the media are closely followed for any misuse or misinterpretation of 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 terms and conditions governing the collection of statistics are published in the Law on Statistics. These conditions—including the obligation to report, penalties for noncompliance, and confidentiality—are set out on collection forms and discussed at meetings with users and journalists, as appropriate. Statistics publications identify information about the SDS but not about its products.
1.2.2 Internal governmental access to statistics prior to their release is publicly identified
There is no information on who has access to data prior to release. The MOEIT, MOF, IMF and some other international organizations have access to the data as soon as they are available. The provision of national accounts estimates prior to release to those users is not made public.
1.2.3 Products of statistical agencies/units are clearly identified as such
Products of the SDS are clearly identified as such by its name and logo. The national accounts tables disseminated in the NBG’s publications identify the SDS as the source. However, the SDS does not mention in its publications that attribution should be made to it when its statistics are used or reproduced.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques
Advance public notice is given of the major changes in methodology, source data, and statistical techniques of the national accounts statistics in the hard copy publications.
1.3 Ethical Standards
1.3.1 Guidelines for staff behavior are in place and are well known to the staff
Ethical rules for staff are laid down in the Code of Conduct for Civil Servants. New staff are made aware of the code and the mission of the SDS when they join the department.
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
Georgian national accounts are based on the concepts and definitions recommended by the 1993 System of National Accounts (1993 SNA).
2.2 Scope
2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices
The minimum requirements for the scope of national accounts tables and accounts, established by the Intersecretariat Working Group on National Accounts, are not met. The SDS compiles and disseminates the following national accounts and aggregates:
Value added and gross domestic production or GDP (annual and quarterly) at current and constant (previous year) prices by activity;
Annual expenditure of GDP at current prices; and
Generation of Income Account (annually)
In addition, quarterly GDP estimates by the production approach at current and constant prices are compiled. Annual supply and use tables are compiled but not disseminated.
The national accounts cover the economic territory of the country. The residence criterion is defined in accordance with the 1993 SNA and the Balance of Payments Manual, fifth edition (BPM5). The Abkhazia and the South Ossetia regions are included in the economic territory of Georgia, but there are significant problems in receiving data from the constituent units.
Workers who work part of the year in the neighboring countries (mainly Russia) are included in the national accounts.
The production boundary is in accordance with the 1993 SNA. In particular, the scope of output measurement includes, among other things, the following items:
own-account production of goods for own-final consumption;
output of goods for own-account fixed-capital formation;
research and development on own account;
mineral exploration; and
production of computer software, entertainment, literary and artistic originals.
Illegal activities are not in the scope of output measurement.
The assets boundary is generally in accordance with the 1993 SNA. Among tangible assets, agricultural work-in-progress is included in the scope of the assets boundary. The defense related assets that could be used for civilian purposes and the valuables and historical monuments are not at present in the scope for estimating the assets boundary.
Among intangible assets, the following assets are included:
mineral exploration;
systems and standard applications computer software and databases;
entertainment, literary, or artistic originals;
patented entities; and
leases and other transferable contracts.
2.3 Classification/Sectorization
2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices
The classification and sectorization used in the compilation of the national accounts are in conformity with internationally recommended standards.
The 1993 SNA is followed in classifying institutional units, transactions, and other flows. GDP estimates by production approach are classified according to the General Industrial Classification of Economic Activities within the European Communities (NACE Rev. 1). The Classification of Products by Activities (CPA) is used for classifying products. Government expenditure is classified according to the Classification of the Functions of Government (COFOG) and individual consumption expenditure according to the Classification of Individual Consumption according to Purpose (COICOP). Foreign trade is classified according to the Harmonized System.
2.4 Basis for Recording
2.4.1 Prices used to value flows and stocks reflect actual or expected cash payments
The valuation rules used for recording flows and stocks are in accordance with the 1993 SNA. Market output is valued at basic prices. Output for own use is valued at equivalent market prices. Purchases are valued at purchaser’s values, that is, including trade and transport margins, net taxes on products, and nondeductible value added tax (VAT). If the VAT is deductible, it is not included. Total exports are recorded on an f.o.b. basis. Total imports are recorded on c.i.f. basis and valued on an f.o.b. basis using an estimate for insurance and freight by commodities. The authorities report that transfer prices have not been detected.
2.4.2 Recording is done on an accruals basis
In principle, enterprises are asked to provide data on an accrual basis in accordance with the recommendations of the 1993 SNA. The basic data for central government are on a cash basis. Expenditures of government for education are adjusted to an “accrual” basis by using the planned budget values for education instead of the cash data.
2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices
Transactions between establishments within 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
The SDS maintains a statistics register only for the nonfinancial enterprises and the Non Profit Institutions Serving Households (NPISH) sector. The register was established on the basis of administrative records (registrations of legal entities) and the annual survey of revenues and expenditures of enterprises. It is maintained with the information from that same survey. The register covers about 26,000 enterprises from the nonfinancial and NPISHs sector. It contains data on the main characteristics of the units (legal status, type of unit, activity, ownership, economic data, including number of employees). The coverage of the register is not considered exhaustive as there have been no economic censuses for decades.
The sources for the annual national accounts are the following: for the nonfinancial sector and the NPISHs—the annual survey of nonfinancial enterprises and NPISHs; for the general government—data on general government from the MOF; for the financial sector—data on depository corporations from the NBG; for the household sector—the household budget survey and ad hoc surveys used for estimation of the unincorporated activities of the households.
The main source of data for the compilation of the annual national accounts is the survey of revenues and expenditures of enterprises for the nonfinancial sector and the NPISHs. The survey is conducted for all activities—mining, manufacturing, electricity, agriculture, construction, wholesale and retail trade, transport and communications, hotels and restaurants, and services. The coverage of the total activities in terms of value added is poor. The coverage of industry (in terms of value added) is considered to be good; the coverage for transport and communications is satisfactory; while the coverage of retail trade, construction, catering, and services is considered to be poor. All enterprises are surveyed through complete enumeration, sample surveys are applied only for retail trade. Large enterprises (defined differently for different activities) are surveyed by a detailed questionnaire and their coverage seems to be good. Small and medium enterprises are surveyed by a simplified questionnaire. Data collected are sufficiently detailed to derive all key national accounts aggregates, namely output, intermediate consumption, fixed-capital formation, and changes in inventories.
The main deficiency in the data collection system of the SDS is that a significant number of statistical units, mostly unincorporated enterprises, are not surveyed systematically, but their activities are estimated by using administrative or other statistical data. Their share in GDP is about 37 percent. In agriculture, there are about 700 thousand household farms that account for about 20 percent of the GDP and they are not surveyed through a systematic annual survey. The same problems exist in retail trade, services, and construction.
The household budget survey (HBS) is a quarterly survey. About 3,300 households are surveyed quarterly. The sample is based on the population census in 1989 and the households are selected using stratified random sampling technique. The population sample was stratified for urban and rural areas. The sample is considered to be representative on both country and regional levels, and also to be representative of all socio-economic groups. Proper imputation techniques are used to handle nonresponse resulting from refusals. The response rate of the survey is good—about 85 percent of the households fill in the questionnaire. Grossing-up factors are derived scientifically, based on sample design. The expenditure items are based on the COICOP groups. Data collected are sufficiently detailed and cover purchases of consumption goods and services, purchases of durable goods, production (including for own-consumption), and own-account fixed capital formation. Purchases of valuables are also covered. In addition, data on employment in the informal sector are collected for the needs of the national accounts compilation.
Comprehensive government finance statistics are available on a monthly, quarterly, and an annual basis for (i) central government, (ii) local government, and (iii) the extra-budgetary funds. The data are compiled by the MOF. The local government data are not considered exhaustive. The MOF provides data on all defense related expenditures. Data on capital stock are not considered comprehensive. Detailed data are available to measure output, intermediate consumption, and final consumption expenditure of government.
Data for the commercial banks are received by the NBG. It is considered to be sufficiently detailed for the compilation of the national accounts aggregates.
Data for external transactions in goods and services are received from the SDS Balance of Payments Division. The quality of the data is poor, reflecting the poor quality of the source data provided by the State Department of Customs.
No establishment censuses have been conducted on a regular basis. The last agricultural census was conducted in 1985; a census only of the establishments in Tbilisi was conducted in 2001 with the financial support through Technical Assistance for the Commonwealth of Independent States (TACIS). The population census was carried out in January 2002.
The SDS collects monthly data (on a cumulative basis) on output and employment for the nonfinancial enterprises that are surveyed annually. The SDS staff considers the data from that survey as not quite reliable as the enterprises are requested to submit data to the SDS on the seventh day after the end of the month.
Ad hoc studies are conducted mostly at the request of, and are financed by, international organizations, mainly the European Commission. Recent examples are the survey of hotels, construction, education, etc.
3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required
Although the Abkasia and South Ossetia regions are included in the economic territory of Georgia, almost no source data are collected for the constituent units of the regions.
The SDS national accounts staff in cooperation with the enterprise economic statistics divisions design the annual survey of nonfinancial enterprises in order that the source data approximate the definitions, scope, valuation, and classifications required in the national accounts. The fiscal year of the state, and all establishments, is the calendar year, which limits inconsistencies in the time of recording. Generally compilers are well aware that concepts and definitions underlying source data may differ from those required by the national accounts, and make necessary adjustments. But it seems that the SDS may not have much insight into how the definitions are being followed—as the national accounts staff rely heavily on instructions in the questionnaires and assume that values employed by the enterprises themselves follow the 1993 SNA concepts and definitions.
3.1.3 Source data are timely
Most source data are available on a timely basis with the exception of the data from the annual survey of enterprises, which is available with some delays (three-four months). Price statistics and balance of payments statistics are compiled by the SDS and are available on a timely basis. Monetary and financial statistics and government finance statistics are also obtained on a timely basis.
3.2 Statistical Technique
3.2.1 Data compilation employs sound statistical techniques
Production approach
Estimates of output are compiled by economic activities at the four-digit level of the NACE.
Data on intermediate consumption is collected only through the annual survey. The annual flash and preliminary estimates of GDP are compiled using intermediate consumption derived from the previous year’s ratio to output. The estimates are compiled on a four digit level of NACE.
Concerning the techniques used to address specific issues of GDP compilation, the following can be noted:
The output of the owner-occupied dwellings is valued as the estimated rentals that tenants would pay for similar accommodation. The owner-occupiers were asked to make a self-assessment of such rentals.
The following items are included in the work-in-progress: growing crops, livestock reared for purposes of food, large construction projects, and output of large equipment.
Inventory data are used in the estimates of output and intermediate consumption. The questionnaires requested respondents to value opening and closing stocks of inventories at average prices of the year. Authorities consider that the respondents report according to these instructions, and that holding gains or losses on inventories do not enter the valuation of value added.
The estimates of consumption of fixed capital are based on the book-keeping values.
Government expenditure and revenue data, as well as taxes and subsidies on products, are valued on a cash basis.
The following should be noted regarding the estimates at constant prices:
The double indicator method is not used for compilation of value added of any activity.
Single deflation of value added is applied in industry (using PPI); construction (using the sub-group of CPI for building materials); transport and communications (using sub-groups of CPI); and services (using total CPI).
In agriculture, extrapolation of value added by volume indices is applied.
Volume measures of taxes and subsidies on products are estimated by deflation of the current values using the total CPI.
Output volume of trade margins is estimated by deflating the current values using sub-groups of the CPI.
The volume changes are measured using annual chain indices for the annual data and previous year base indices for the quarterly data.
The GDP estimates in current prices according to the expenditure approach are derived independently. In particular, independent estimates are compiled for household final consumption expenditure (at one digit level of COICOP); government final consumption expenditure (at one digit level of COFOG); gross fixed capital formation (by activities and types of assets); and changes in inventories (by activities).
Concerning the quarterly compilation techniques:
The quarterly estimates are compiled from cumulative data.
The quarterly estimates are derived from seasonally unadjusted source data.
No seasonal adjustment of the estimates is done.
3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques
The estimated share of the nonobserved economy in the Georgian 2001 GDP is about 33 percent. The SDS makes significant efforts to ensure the exhaustiveness of the GDP estimates. In order that all components of the nonobserved economy are included, the SDS uses the supply and use tables, the data from the household budget survey, other SDS surveys and administrative data. Estimates are made for underreporting (mainly based on comparing the employment data from the Labor Force Survey and the establishment survey); and undercoverage (based on a case-by-case study). For agriculture, the output and intermediate consumption is estimated on the basis of the commodity flows for agricultural goods as well as data on area planted, livestock numbers, and productivity.
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 is collected by the local statistical offices in the districts. No validation is done at the local offices. Hardcopy questionnaires are sent to the headquarters. The first validation of data takes place in the SDS headquarters. If data is considered inaccurate, the headquarter staff have to return the questionnaire to the local office for corrections. Due to lack of resources, staff from local offices are not able to keep contacts with the respondents and to assess or audit their data.
Headquarter staff validate the source data making use of the software and hardware available. High-value transactions are confirmed with respondents. Information for sampling errors is available only for the HBS, for all other surveys there is information about the nonsampling error. Source data are analyzed for underreporting and temporal consistency. Adjustments to source data are done for nonsampling errors.
The accuracy of the budgetary data, balance of payments data, and the price data is routinely assessed.
3.4 Assessment and Validation of Intermediate Data and Statistical Outputs
3.4.1 Main intermediate data are validated against other information where applicable
Intermediate data on major activities, mainly industry, are assessed against related indicators, such as volume and price trends.
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated
Assessments of potential discrepancies of major intermediate data are undertaken, and adjustments are made to remove the discrepancies. In particular, the following ratios are checked carefully: intermediate consumption/gross output, gross value added/gross output, consumption of fixed capital/gross output. In addition, the value added structure by industries is also checked for temporal consistency. Proper adjustments are made to remove the discrepancies.
3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated
The statistical discrepancy for 1999 GDP by production and GDP by expenditure approach is about 10 percent and it is shown explicitly. Supply and use tables (with a two year lag) are used to make the estimates more consistent. After the SUT are applied, the discrepancy is about 3 percent. No studies about the bias in the GDP estimates are performed.
3.5 Revision Studies
3.5.1 Studies and analysis of revisions are carried out routinely and used to inform statistical processes
The direction and magnitude of revisions between preliminary and final data are investigated, but there is no documentation of the sources of errors, omissions, and fluctuations in the data. The results of investigations and adjustments made in the statistical processes are taken into account in compiling the data for the subsequent periods.
4. Serviceability
4.1 Relevance
4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored
In general, the SDS assesses whether the economic statistics adequately responds to government needs. Consultations are made mainly with representatives of the government agencies and some academic institutions. The SDS has conducted two user surveys in the last two years. However, there is no advisory group or an established process to systematically assess the relevance of the existing national accounts data.
4.2 Timeliness and periodicity
4.2.1 Timeliness follows dissemination standards
The annual national accounts estimates are disseminated within the timeliness limit of six-nine months after the reference year recommended by the General Data Dissemination System (GDDS). A flash estimate of GDP in current and constant prices is available one month after the end of the year. The SDS publishes preliminary annual GDP figures at current and constant prices after four months. Final annual national accounts estimates in current and constant prices are available 13 months after the end of the year.
The SDS publishes quarterly GDP flash estimates (on a cumulative basis) in current and constant prices one month after the end of the reference period and preliminary estimates four months after the reference period.
4.2.2 Periodicity follows dissemination standards
The dissemination of annual GDP statistics meets the recommendations of the GDDS.
4.3 Consistency
4.3.1 Statistics are consistent within the dataset
There are some problems with the internal consistency of the national accounts estimates. The estimates for GDP by activity and expenditure components have a statistical discrepancy that is not quite stable over time. The estimates at constant prices are available only through the production approach. In the supply and use tables, supply of goods and services does not match total uses and is balanced through the changes in inventories.
The quarterly and the annual GDP estimates are consistent with one another from a conceptual point of view. The fourth quarter GDP cumulative estimates are equal to the annual estimates for the flash and preliminary annual GDP.
4.3.2 Statistics are consistent or reconcilable over a reasonable period of time
Annual national accounts estimates are available since 1990 and quarterly estimates are available since 1996. There are two breaks in the annual accounts: (i) the annual accounts are expressed in rubles from 1990 to 1992, in Georgian coupons from 1993 to 1994, and in Lari from 1995; (ii) the annual accounts are compiled according to the old classification of activities until 1996 and according to the NACE since 1996. Therefore, consistent time series for the annual estimates are available since 1996. However, historical annual series were not reconstructed back for changes in the methodology. The quarterly estimates are consistent over time. There are detailed methodological notes to explain the breaks in the national accounts time series for the changes in the classification. The SDS always explains in the analytical text of the national accounts publications any unusual changes in the economic trends.
4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks
The national accounts statistics are reconcilable with data on general government produced by the MOF. Consistency checks between the national accounts and the balance of payments are not possible, as the SDS compiles only Production and Generation of Income Accounts. Data on import and export of goods and services for the GDP by the expenditure approach is consistent with the balance of payments current account data.
4.4 Revision Policy and Practice
4.4.1 Revisions follow a regular, well-established and transparent schedule
The revisions of the national accounts estimates follow an established schedule, but the public is not well informed about it. The revision cycle is the following:
For the annual estimates of GDP by the production approach:
Flash estimate—one month after the reference period
Preliminary estimate—four months after the reference period
Final estimate—13 months after the reference period
The authorities do not follow a regular schedule for revisions of the GDP by expenditure approach.
The quarterly estimates are revised following the same pattern.
The SDS does not provide extensive documentation on its major revisions.
Generally, there are no major new source data to be incorporated in the national accounts estimates. However, new statistical techniques are sometimes introduced into the accounts without revision to earlier data and in this way breaks in the series are created.
4.4.2 Preliminary data are clearly identified
The flash, preliminary, and final estimates are clearly identified. Users are made aware that data are subject to revision. The revised data are disseminated with the same level of detail as those previously published.
4.4.3 Studies and analyses of revisions are made public
Major revisions of data due to changes in methodology are measured and explained in the press release when the revised data is being disseminated. The explanations do not include analysis of preliminary versus revised data for the major aggregates that were revised.
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 national accounts series is not commensurate with the users’ needs. The national accounts estimates are disseminated in the SDS Statistical Yearbook of Georgia (SDS Yearbook), the Monthly Statistical Bulletin and through press releases. Annual current price estimates and growth rates are published by economic activity at the one digit level of NACE and by major expenditure category, with a breakdown by household consumption, government consumption, and capital formation. The constant price estimates and the deflators of GDP are not published. The annual estimates are not disseminated at a detailed level; there are no shares, charts, and tables to facilitate the analysis. The final quarterly estimates are not published.
5.1.2 Dissemination media and formats are adequate
The annual and quarterly flash and preliminary estimates are disseminated first by a press release and later through the Monthly Bulletin. The final annual estimates are released only through the SDS Yearbook. There is no other way to access the released data. Longer time series are not accessible. The newly developed web page of the SDS does not contain any national accounts data.
5.1.3 Statistics are released on a pre-announced schedule
The annual flash and preliminary as well as the quarterly national accounts estimates are released according to a pre-announced schedule. The schedule is published each quarter and is available to the public. There may be some delays in the schedule due to the printing process of the hardcopy publications. The final annual estimates are not released according to a pre-announced schedule.
5.1.4 Statistics are made available to all users at the same time
There is a general perception that as soon as data is compiled, they are considered to be released and are available to anybody who requests them. Once the national accounts are ready, they are released first to the MOEIT, MOF, the NBG, and some international organizations. After two-three days they are released simultaneously to all other users. The press is not briefed in advance.
5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request
Unpublished but nonconfidential detailed data are made available to users upon request. The availability of these data is 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
There is not a detailed description of concepts, definitions, classifications, data sources, and statistical techniques used for the compilation of the national accounts estimates. The SDS has published a short description of the national accounts metadata. The SDS has disseminated a description on the measurement of the nonobserved economy in a hardcopy publication. No metadata is available on the newly created web page of the SDS.
5.2.2 Levels of detail are adapted to the needs of the intended audience
Metadata are not made available at different levels of detail.
5.3 Assistance to Users
5.3.1 Contact person for each subject field is publicized
All statistical releases and publications indicate the mailing address, telephone and fax numbers, and e-mail address of the SDS Publication Division and the specific divisions (including National Accounts Divisions) that are responsible for the compilation of the statistics. National accounts staff handle all enquiries and perovide assistance to users.
5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available
A list of publications is given in the SDS catalog of publications and in the web page and there is information on how they may be obtained. The cost of the publications is not stated.
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for National Accounts
(Compiling Agency: State Department of Statistics)
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for National Accounts
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Penalties for noncompliance are ineffective. | |||||
| 0.2 | Resources | X | Inadequate staff and financial resources, high staff turnover, unattractive salaries. | |||||
| 0.3 | Quality Awareness | X | No special body to provide guidance on quality of national accounts data. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | Internal government access to NA data prior to release is not publicized. | |||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | Volume measures of expenditure GDP are not compiled, only production and generation of income accounts are compiled. | |||||
| 2.3 | Classification/Sectorization | X | ||||||
| 2.4 | Basis for recording | X | General government transactions are recorded on cash basis. | |||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | Coverage of register is not comprehensive, poor coverage of trade and services, no census surveys have been conducted. | A Labor Force Survey and a Census of Agriculture are planned for 2003. | ||||
| 3.2 | Statistical techniques | X | Serious deficiencies in techniques for deriving constant price estimates. | |||||
| 3.3 | Assessment and validation of source data | X | No validation of source data by the local offices. | |||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | Supply and Use Tables are not sufficiently detailed to allocate the discrepancy of GDP between the two approaches. | |||||
| 3.5 | Revision studies | X | ||||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | No systematic review process to assess whether NA meet users’ needs. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | Historical series are not reconstructed. | |||||
| 4.4 | Revision policy and practice | X | Revision schedule is not publicized. | |||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | NA constant price estimates and deflators are not published, dissemination formats are not adequate, there is no set embargo date, data are not released simultaneously. | SDS plans to disseminate NA data through its web page. | ||||
| 5.2 | Metadata accessibility | X | Very limited documentation on sources and methods. | |||||
| 5.3 | Assistance to users | X | The cost of the publications is not stated. | |||||
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for National Accounts
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Penalties for noncompliance are ineffective. | |||||
| 0.2 | Resources | X | Inadequate staff and financial resources, high staff turnover, unattractive salaries. | |||||
| 0.3 | Quality Awareness | X | No special body to provide guidance on quality of national accounts data. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | Internal government access to NA data prior to release is not publicized. | |||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | Volume measures of expenditure GDP are not compiled, only production and generation of income accounts are compiled. | |||||
| 2.3 | Classification/Sectorization | X | ||||||
| 2.4 | Basis for recording | X | General government transactions are recorded on cash basis. | |||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | Coverage of register is not comprehensive, poor coverage of trade and services, no census surveys have been conducted. | A Labor Force Survey and a Census of Agriculture are planned for 2003. | ||||
| 3.2 | Statistical techniques | X | Serious deficiencies in techniques for deriving constant price estimates. | |||||
| 3.3 | Assessment and validation of source data | X | No validation of source data by the local offices. | |||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | Supply and Use Tables are not sufficiently detailed to allocate the discrepancy of GDP between the two approaches. | |||||
| 3.5 | Revision studies | X | ||||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | No systematic review process to assess whether NA meet users’ needs. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | Historical series are not reconstructed. | |||||
| 4.4 | Revision policy and practice | X | Revision schedule is not publicized. | |||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | NA constant price estimates and deflators are not published, dissemination formats are not adequate, there is no set embargo date, data are not released simultaneously. | SDS plans to disseminate NA data through its web page. | ||||
| 5.2 | Metadata accessibility | X | Very limited documentation on sources and methods. | |||||
| 5.3 | Assistance to users | X | The cost of the publications is not stated. | |||||
II. Consumer Price Index
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 State Department of Statistics (SDS) is an independent government institution operating under the Law on Statistics No. 1071 of November 12, 1997, and supplemented by an amendment in June 1999. The Law on Statistics authorizes the SDS to collect, compile, and disseminate official statistics about the socio-economic development of Georgia. The Law specifies that while government units and agencies may set up specialized statistical units and may undertake their own statistical surveys, these shall operate under the methodological guidance of the SDS. Other provisions of the Law ensure the consistency of methodology, comparability of statistical international standards, sharing information with other countries, and dissemination.
A decree by the Council of Ministers of Georgia on the State Service for Registering Prices and Tariffs No. 125, March 10, 1995, established the prices division as a separate unit of SDS responsible for price statistics.
The collection and compilation of consumer and producer price statistics are mentioned explicitly in Article 21 of the Regulation for the SDS No. 92 from February 28, 1998, approved by the President of Georgia. In addition to that, the President of Georgia has approved a State Program for Development of Statistics for 2001-2005. The compilation and dissemination of prices statistics are stated in the State Program.
0.1.2 Data sharing and coordination among data producing agencies are adequate
Article 11 of the Law guarantees the SDS access to data produced by legal entities, including the data produced by government ministries and the National Bank of Georgia (NBG). Important areas of statistics are covered by other agencies, such as the NBG, which compiles monetary and financial statistics; the Ministry of Finance (MOF), which is responsible for compiling government finance statistics; and the Customs Committee, which compiles data on imports and exports of goods. The Law gives the SDS primary and coordinating roles in the development of the country’s statistical program.
There are written agreements between the SDS and the MOF, the NBG and the Customs Committee covering the sharing of macroeconomic data, and the SDS management and staff are satisfied with the level of cooperation they receive from these agencies. There appears to be no evidence of significant duplication of statistical effort among the various agencies. No regular contacts with other statistics producing agencies are maintained to take into account the respondent burden.
0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only
Confidentiality of the data reported to the SDS is guaranteed under Articles 7, 12, and 17 of the Law. The Law does not provide penalties for disclosure. The SDS is planning a new amendment to the Law with a provision for penalties for disclosure. The confidentiality aspect is potentially compromised to some extent as a result of the provisions of the Anti-monopoly Law. According to this Law, the State Anti-monopoly Service can request confidential data from the SDS. The conflict between the two Laws has not been resolved. In practice, there have been no breaches of confidentiality of price statistics.
Staff are required to keep individual data confidential, and they are also required to sign a declaration on joining the SDS that confirms awareness of this provision. Access to individual data is restricted to the appropriate staff. There are no special aggregation rules to ensure that residual disclosure does not occur. Senior staff review the data before dissemination to make sure that confidential data are not disseminated.
0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage reporting
According to Article 11 of the Law, the SDS is authorized to request the information it deems necessary from all legal public and private institutions, as well as from individuals. All requested respondents must furnish the requested information accurately, and in the format and time period determined by the SDS. The June 1999 amendment of the Law provides some penalties for nonreporting, but they are not considered effective by the management of the SDS. These penalties were mostly applied to newly registered legal entities for noncompliance with the required registration in the SDS Administrative register. In practice they were not applied for nonresponse to statistical surveys.
The SDS does not systematically review the response burden, and contacts with respondents are very limited. In practice, the SDS central office and its regional offices make little effort to create goodwill among data providers.
Since consumer prices are collected by personal visit, response burden and noncompliance are not significant issues.
0.2 Resources
0.2.1 Staff, financial, and computing resources are commensurate with statistical programs of the agency
The Consumer Price Index (CPI) and Producer Price Index (PPI) are jointly compiled by nine staff in the central office in Tbilisi. In the Tbilisi regional office there are 20 price collectors who spend about 80 percent of their time on prices work. In the other four regional offices, there is a total of 18 price collecting staff. The relatively small amount of producer price collection undertaken outside of the five main Georgian cities is undertaken on a part time basis by other staff. These staff resources are considered to be adequate to perform the required tasks.
Remuneration is extremely low and uncompetitive, causing major problems in attracting and retaining suitable staff. It has been estimated that SDS salaries have fallen to about 7 percent of the 1988 levels in real terms.
The staff are well qualified and trained which helps them to handle the continuing change and improvements to the prices work. The nine central office prices staff have tertiary qualifications in economics; three of them have over 15 years of statistical experience each.
Ninety percent of the regional office price collectors have tertiary qualifications; some are engineers which is valuable for product specification.
Staff are trained internally on general statistical issues such as sampling, methodology, data control, etc., as well as specialized topics such as price index theory, maintenance of product quality, treatment of temporarily missing items, etc. Unfortunately, funding restrictions provide for very limited external training.
The director of the Prices Division attended the IMF seminars in Vienna (2002) and Kiev (1998) and found them extremely valuable. Unfortunately, there have not been opportunities for other SDS Prices Division staff to attend such courses; priority should be given to enabling other staff to participate in international training such as the U.S. Bureau of Labor Statistics course on price indices. Also, the director should attend the next International Labor Organization (ILO) meeting in 2003.
Computing resources are very inadequate. For example, the nine Central Office staff share three old personal computers, having to queue to get access; at least three additional machines are required. The situation in the regional offices is even worse; prices staff in one regional office do not have any machines.
Software for the CPI is based on MS Excel files provided by the IMF and upgraded locally; new software is being developed using MS Access which will be more flexible and will more readily handle changing product lists, release of unpublished data, etc.
The PPI software needs updating as it does not handle functions such as cross analyses and dissemination very well.
Communications systems are very poor and unreliable. There is no electronic data transfer of unit records from the regional offices to the central office for processing; the data have to be physically delivered by SDS staff from one location to the other. As a result, sometimes the pre-announced CPI and PPI publication release dates are not met.
Financial resources are very scarce and travel, course attendance, etc., is very restricted. There is even a shortage of stationery and other office consumables.
0.2.2 Measures to ensure efficient use of resources are implemented
As part of the planning process, the SDS management scrutinizes the work program each year and reviews priorities in developing its financing plan. As resource allocations are regularly less than those required for the planned work program, resource usage is regularly monitored.
It would be beneficial to compare resource usages in detail with other statistical agencies and undertake periodic reviews of working processes.
There are major untapped opportunities available from the greater use of computing technologies.
Within the Prices Division, measures to increase efficiency include the rationalization of collection forms, upgrading of software, exploring more efficient data transmission mechanisms, and the evaluation of methodologies and data compilation techniques with assistance from external experts
Opportunities are being taken, through the attendance at international meetings and training courses, and bi-lateral follow-up communication, to share experiences with other statistical agencies to assist in developing best practice.
0.3 Quality Awareness
0.3.1 Processes are in place to focus on quality
Senior management is sensitive to the dimensions of data quality: integrity, methodological soundness, accuracy and reliability, serviceability, and accessibility. In order to ensure quality, the organizational structure of the SDS includes a Statistical Research Institute and an Institute for Informatics and Telecommunications. The Statistical Institute is responsible for developing methodology and software solutions for statistical tasks. The Institute for Informatics and Telecommunications is responsible for development and implementation of information and analytical systems of the national statistics and harmonization of classification systems. A Scientific and Advisory Council was established in the SDS in 1997. Apart from the SDS staff, specialists from the Ministry of Economy, Industry and Trade, the University, the National Bank of Georgia, and the Institute of Economics are, with others, members of the Council. The Council presents assessments and recommendations on the State Program of Statistical Activities, statistical surveys, and structure of the SDS, broad directions of development in the area of statistics and on training and re-training of staff.
The mission statement of the SDS places emphasis on the improvement and harmonization of statistical activities and the maintenance of independence, accuracy, relevance, integrity, timeliness, and professional standard of statistical information produced in Georgia.
Before the CPI and PPI are released, rigorous output editing and credibility checks are undertaken, including cross-checking between CPI and PPI data sets. The SDS senior management clears the data before each month’s release.
0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics
There is no separate unit that provides guidance on the quality of price statistics and on strategies for improving statistical processes.
Nevertheless, regular meetings are held with users, particularly the National Bank of Georgia (NBG), which provides a mechanism for receiving external feedback.
There are no systematic reviews undertaken to identify problems at the various stages of collecting, processing and disseminating data.
0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs
The SDS management is conscious of the tradeoffs between the dimensions of data quality and timeliness. For example, a judgment was made to extend the due date for data reporting (in the case of monthly collections, from three-four days after the end of the reference period to seven-eight days) because it was assessed that the substantial improvement in the resultant data quality would exceed the disadvantages of a small reduction in timeliness.
User feedback is encouraged and improvement in data quality is taken into account in planning the forward work program.
1. Integrity
1.1 Professionalism
1.1.1 Statistics are compiled on an impartial basis
The Statistics Law defines the key principles and responsibilities in relation to the collection, processing, and dissemination of statistics in Georgia, with emphasis on international standards and definitions, authenticity, objectivity, and independence. Respondents are obliged to provide clear, objective, and timely data to SDS, within the context of assured confidentiality of their data.
As such, the SDS has complete independence and autonomy in the performance of its statistical responsibilities, and there is no scope for external interference in the compilation and dissemination of official statistics.
Price statistics are collected and compiled in an impartial manner by professional SDS staff who have tertiary qualifications and are trained in statistical techniques. The collection and compilation of prices statistics is undertaken according to international standards with the application of objective statistical judgment.
1.1.2 Choices of sources and statistical techniques are formed solely by statistical considerations
Choices about data sources and statistical techniques are based on professional statistical considerations. The weighting sources for the price indices are based on sound household and industrial surveys while the design of the price collections are based on statistical considerations such as efficiency, cost effectiveness, data reliability, and respondent burden. The statistical techniques employed conform to international standards.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics
The media are closely followed for any misuse or misinterpretation of data.
In instances where there has been a major misinterpretation of price indices, public comment has been made to rectify the situation (e.g., in respect of the impact of the introduction of cigarette excise tax).
Press conferences are conducted in association with major statistical releases. Regular meetings are held with specialist journalists where data and methodological issues are discussed. These processes reduce the likelihood of serious misunderstandings.
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 and conditions governing the collection of statistics are published in the Law of Georgia on Statistics. These conditions—including the obligation to report, penalties for noncompliance, and confidentiality—are set out on collection forms and discussed at meetings with users and journalists, as appropriate.
Statistical publications do not identify where more information about the data providing agency and its products can be found.
1.2.2 Internal governmental access to statistics prior to their release is publicly identified
While there is no explicit, intentional internal government access prior to release, in practice, the lack of specific public release times (i.e., embargos) and the fact that there are special delivery arrangements for selected government agencies, results in these agencies receiving the data prior to other users. These arrangements have not been publicly acknowledged.
1.2.3 Products of statistical agencies/units are clearly identified as such
Publications of the SDS are clearly identified as SDS products by the department’s name and logo. In cases where SDS data are released in another agency’s publication (e.g., price indices released in an NBG publication), the data are clearly sourced.
The SDS does not mention in its publications that attribution should be made to it when its statistics are used or reproduced.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques
Advance notice is given to users prior to the introduction of changes to methodology, sources, or techniques. This applies to the periodic reweighting of the price indices. This action reduces misunderstanding and results in greater acceptance by users of the changes.
1.3 Ethical Standards
1.3.1 Guidelines for staff behavior are in place and are well known to the staff
SDS operates under a solid legal framework which is being further strengthened in relation to confidentiality of data, penalties for noncompliance by providers, and penalties for offenses by SDS staff.
Staff are well informed of their responsibilities. The law of the civil service contains statements on the ethical standards required of civil servants and the SDS guidelines cover regulations on the handling of confidential data.
Induction training of new SDS staff emphasizes ethical standards.
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
IMF technical assistance in 1992 and 1997 assisted in the development of the current CPI. It is compiled according to ILO guidelines and Eurostat recommendations. The basic concepts and definitions for household consumption are consistent with the 1993 SNA.
The CPI covers price change of goods and services consumed by resident households. Expenditure weights are based on Household Budget Survey (HBS) data for 1996–97. The prices included in the index relate to goods and services which are fully specified in terms of both product characteristics and transaction characteristics.
The weighting pattern will be updated at the end of 2002 using the results of the 2001–2002 HBS.
2.2 Scope
2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices
The scope of the CPI is all resident households living in the five major urban areas. The population coverage relates to families of all sizes and income levels. The index covers marketed goods and services for final consumption purchase including purchases by unincorporated businesses.
Prices are collected for the five major urban areas only, and indices are compiled for each of the five cities. A separate weighting structure is used for Tbilisi; the other four cities share a common weighting pattern. Population based weights are used to aggregate the five city indices, with the weight for each city reflecting not only its own population but also that of surrounding smaller cities.
Own-account production of market goods for own final consumption is very important in Georgia and is included in the CPI weights.
Owner-occupied dwelling services are not currently included in the CPI.
2.3 Classification/Sectorization
2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices
International standards are followed in classifying consumption activity. The structure of the CPI is based on ILO guidelines as recommended through IMF technical assistance missions. Commodities are classified according to the Classification of Products by Activity (CPA).
The Classification of Individual Consumption by Purpose (COICOP), which is now used for the HBS, will be introduced with the next reweight of the CPI at the end of 2002.
Product descriptions and standards conform to definitions that provide for the collection of prices of transactions in the same products from month to month.
2.4 Basis for Recording
2.4.1 Prices used to value flows and stocks reflect actual or expected cash payments
The weights, and the prices, used in the CPI are based on actual market transaction prices, including any discounts, valued at purchasers’ prices inclusive of trade and transport margins and taxes on products. Actual market transaction prices are captured through a process of negotiation on the asking price, as necessary.
The specifications of products for pricing are rigorously defined to include all price determining characteristics to support pricing to constant quality. The product list is updated annually.
2.4.2 Recording is done on an accruals basis
Prices for goods and services are recorded on an accrual basis. Most are collected each month over the period between the 10th and the 20th of the month. The frequency of collection depends upon the volatility of the prices. Food, fuel, and gas prices are collected three-five times per month while postal, communications, and water prices are collected quarterly.
2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices
This is not applicable since used goods are not included in the CPI.
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 1996–97 Household Budget Survey, conducted with technical and financial assistance from the World Bank, was the data source for the calculation of the structure and weighting pattern for the current CPI. The HBS has been conducted on a continuous basis each quarter since 1996. 3,351 households are surveyed, on an eight-quarter rotation basis, with the dwelling being the collection unit.
A two-stage stratified sample is used, using the 1989 population census, progressively updated with new data from the 2002 census, as the frame. The objectives of the HBS are to provide macro-economic data and support the IMF’s poverty reduction program. The total quarterly sample size is 3,351 households, using 12 rotation groups. Each month 1,117 households are surveyed.
The response rate was about 85 percent in 1997-98, falling to 75-79 percent in 2000-01 and increasing towards 85 percent again from 2001–02 with the introduction of a revised collection and questionnaire strategy.
The surveys from 1996 to 2001 were based on an old Soviet classification; COICOP is being used from 2002.
Nonresponse is treated as follows:
(i) the weight for household refusals is allocated to other households in the same strata;
(ii) if no one is living at a selected address, the weight for that dwelling is deleted and the actual household weight is adjusted.
Household expenditure data valued at purchasers’ prices and classified by detailed COICOP commodity are produced from the HBS on a timely basis.
The geographic coverage of the HBS is the whole country. The market value of goods produced for own consumption is covered, though the rental value of owner occupied dwellings is not measured.
Two studies of consumption patterns derived from HBS results for periods after 1996-97 revealed that there were only minor shifts which didn’t justify CPI weight updates. However, the CPI weights will be updated at the end of 2002 based on 2001–2002 data to make them contemporary.
The consumer price survey collects prices for most goods and services on a monthly basis, by personal price collection. Volatile items, such as fresh fruit and vegetables, fuel and gas are collected three-five times per month while prices for regulated items such as communications and water are collected quarterly.
In principle, all consumer purchases are covered. The sample of outlets from which prices are collected is drawn from a list of markets, shops, and supermarkets developed from Retail Surveys. Eighty percent of foodstuffs have traditionally been purchased from farmers’ markets, though the trend is shifting towards increased sales through stores and supermarkets and the outlet sample will be updated accordingly.
The outlet samples are selected on a random basis from a list stratified by type of outlet, retail industry (depending on the type of products sold) and region (e.g., Tbilisi is divided into ten administrative regions).
In the case of informal market outlets, where the prices are collected from stalls, there have been problems in obtaining prices for identical products over time from the same outlet, though this has stabilized in recent times. That is, it is difficult to achieve rigorous specification pricing in such a retailing environment.
Given the estimates of the size of the nonobserved economy, there are reservations as to the effectiveness of the HBS and the price surveys in adequately reflecting this activity in the weights and prices of the CPI.
The appearance of new goods is monitored for inclusion in the basket, and advertisements and press articles are scrutinized.
3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required
HBS data are largely consistent with the definitions, scope, classifications, valuation, and timing of recording of the CPI.
3.1.3 Source data are timely
Detailed annual data are available from the continuous HBS two months after the end of the year. Consumer price quotes are normally available on a timely basis though there can be delays in transferring the data to the central office due to unreliable and unsophisticated communication systems and inadequate financial resources, sometimes resulting in the publication failing to meet its preannounced release date.
3.2 Statistical Technique
3.2.1 Data compilation employs sound statistical techniques
Expenditure estimates from the HBS for goods are produced at a sufficiently detailed level for effective use as CPI weights. However, services are currently less well-categorized. The introduction of COICOP will result in more detailed expenditure data for services, allowing for better coverage and representation in the CPI.
Weights are based on household consumption expenditure as defined in the 1993 SNA. Owner occupied dwelling services are not currently included in the CPI. Goods for own final consumption are covered and they are valued at market prices at the time of production. Land use by householders is particularly important in Georgia.
The CPI is built up from 296 index items of goods and services and progressively aggregated to eight main publication groups: Food, beverages and tobacco, Clothing and footwear, Rent, water, fuel and power, Household goods, Medical care, Transportation and communication, Recreation, education and culture, and Personal care and effects.
Elementary aggregate index numbers are calculated by deriving short-term ratios of average prices. The modified Laspeyres aggregation formula is used. The weighting base period is 1996-97 with the weights adjusted to the prices of December 1997, the price reference period for the current index.
Weights have been based on 1992, 1994, and 1996-97. As new weights have been introduced, link factors have been derived from a December index overlap, and applied to the time series to form a continuous historical series.
The standard practice in the case of temporarily missing prices is to impute using the current movement in the index at the next level of aggregation. If products disappear permanently, they are replaced. Prices for out of season products are repeated until new season prices are available.
In the case of quality change, efforts are made to identify product changes. However, the practice is to treat the changed product as a new item and splice out the associated price change, rather than directly estimate the value of the quality change.
The list of items is reviewed each year and new items added to the sample as appropriate.
3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques
The scope of the CPI is basically the same as that for household final consumption expenditure in the national accounts. The only difference in scope is that the CPI does not include imputed dwelling rent.
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 main source data for the CPI are (i) the continuous HBS which provides expenditure data by commodity and region for the CPI weighting pattern, and (ii) the monthly survey of retail prices.
HBS response rates are closely monitored and efforts are made to ensure they are acceptable. For example, when rates gradually declined between 1998 and 2001, the collection strategy and form were reviewed. Standard errors are continuously reviewed, and investigations undertaken to minimize errors. In particular, successive annual HBS data are compared and analyzed.
For the price collection, pre-determined product specifications are selected using judgmental sampling; therefore information about sampling errors is not available. Nonresponse is not an issue due to the high level of respondent cooperation and the use of personal price collection.
Long term analyses of price changes are undertaken. Relationships within groups and subgroups are studied, and any shifts identified and investigated, with a view to eliminating any errors. Individual prices are checked against external sources where possible.
Price ratios are calculated and products are clustered according to ranges to ensure consistency—outliers are investigated. Source data are analyzed for spatial and temporal consistency and corrected as necessary.
Close contact is maintained with the State commission for regulation on energy and communications charges for cross checking.
3.4 Assessment and Validation of Intermediate Data and Statistical Outputs
3.4.1 Main intermediate data are validated against other information where applicable
Price movements for consumer products are compared at consumer and producer level. The aggregate CPI and PPI movements have been nearly identical over the last six months.
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated
Large movements, and inconsistent movements between different series, are investigated. Exchange rate movements are analyzed and their impact on imported consumer goods evaluated. Prices of regulated items are verified.
3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated
Comparisons between the five regional indices are undertaken. Imputations are made on a consistent basis. The overall CPI for Georgia is calculated as an aggregate of the five regional indices and there are no discrepancies.
3.5 Revision Studies
3.5.1 Studies and analysis of revisions are carried out routinely and used to inform statistical processes
The CPI is final when first released and index numbers are not subsequently revised. However, in the eight year history of the CPI, there has been one instance of a revision to a monthly index due to an error in the timing of recording an increase in railroad tariffs.
When weights or methodology are revised, the index number series are not backcast and revised. Rather, the new series are linked onto the old series to form a continuous historical series.
Prior to updating the weights, a detailed analysis of shifts in the pattern of consumption is undertaken and major changes explained.
4. Serviceability
4.1 Relevance
4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored
There is ongoing consultation with users on price indices, especially with the major public policy organizations. Press conferences and briefings are held with journalists, through which feedback is obtained.
However, there is no formal user group, nor an established process of review to systematically assess how well users’ needs are being met.
Representatives of the SDS attend international meetings, within the constraints of the available financial resources.
4.2 Timeliness and periodicity
4.2.1 Timeliness follows dissemination standards
The timeliness of the price indices meets GDDS dissemination standards. The CPI is released ten days after the end of the reference month. However, there are additional lags before publications are available to users.
4.2.2 Periodicity follows dissemination standards
The CPI is released monthly and therefore meets GDDS dissemination standards.
4.3 Consistency
4.3.1 Statistics are consistent with the dataset
The CPI is internally consistent. The all-items CPI is invariant to the geographic or commodity classifications. See 3.4.3 above.
4.3.2 Statistics are consistent or reconcilable over a reasonable period of time
Continuous monthly, quarterly, and annual index series are maintained through processes of linking at the time new weights are introduced. CPI series go back to January 1994.
4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks
The CPI and PPI are constructed on a consistent basis, and are compatible with national accounts statistics to the extent that they adhere to 1993 SNA concepts and methods.
4.4 Revision Policy and Practice
4.4.1 Revisions follow a regular, well-established and transparent schedule
The CPI is not revised and the monthly index numbers are final when first released (note the one exception mentioned under 3.5.1 above). This policy is well known to the public.
Weights are updated on a regular basis, and product and outlet samples modified over time so they remain representative. However, the index series are not backcast and revised to reflect the new weights or samples. Rather, the new indices are linked onto the previous series to form a continuous historical time series. These are well established practices.
4.4.2 Preliminary data are clearly identified
This is not applicable as the index numbers are final when first released.
4.4.3 Studies and analyses of revisions are made public
This is also not applicable (see also 3.5.1 above).
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 CPI publication contains clear tables and charts. A reasonable amount of detail is published and it is in time series form. However, no analysis of current period changes is presented.
5.1.2 Dissemination media and formats are adequate
As soon as the data are finalized, they are considered to be released and are available to anyone who requests them.
Data are first released by fax and e-mail to selected organizations and subsequently to the media. The data are later released in a monthly SDS General Report and then in a more comprehensive specialist quarterly CPI publication.
The data are not currently released electronically.
5.1.3 Statistics are released on a pre-announced schedule
There is a pre-announced schedule of publication release dates (but not times), though, in practice, the dates are not always met. It is reasonably well known amongst users that the target release dates for the CPI is the tenth of the month following the reference month (subject to when weekends fall).
5.1.4 Statistics are made available to all users at the same time
In principle, all users have access simultaneously. However, the release mechanisms result, in practice, in selected government users and international organizations receiving the data before other users. The lack of a strict and well-publicized, embargo time (e.g., 10:00am) contributes to this inequitable treatment.
5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request
Nonconfidential, unpublished index numbers are made available on request. However, the availability of this service is not publicized, nor the terms and conditions that apply.
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 only metadata made available to the public is a very brief description of the CPI contained in the SDS Yearbook, which is completely inadequate.
5.2.2 Levels of detail are adapted to the needs of the intended audience
There is no concepts, sources, and methods document or other descriptive material about the CPI.
5.3 Assistance to Users
5.3.1 Contact person for each subject field is publicized
A contact person and telephone number is provided in the fax sent to public policy users and on the cover sheet accompanying the CPI publication. A prompt and knowledgeable service is provided to enquirers.
5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available
There is a catalogue of publications but it is not comprehensive and does not contain charges.
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Consumer Price Index
(Compiling Agency: State Department of Statistics)
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Consumer Price Index
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Penalties for noncompliance are ineffective. | |||||
| 0.2 | Resources | X | Computer and financial resources are inadequate. | |||||
| 0.3 | Quality Awareness | X | There is no separate unit to provide guidance on quality. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | The public is not made aware of dissemination practices that result in selected government agencies receiving access in advance of other users. Information on the agency and its products is not publicized. |
|||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | The CPI only covers major urban households. Owner-occupied dwelling services are not measured in the CPI. |
|||||
| 2.3 | Classification/Sectorization | X | ||||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | There are problems in achieving rigorous specification pricing in informal market outlets. The nonobserved economy may not be adequately reflected in the weights and price collections. | |||||
| 3.2 | Statistical techniques | X | Services commodities are not well categorized in the Household Budget Survey. Quality change assessment techniques need improving. |
|||||
| 3.3 | Assessment and validation of source data | X | ||||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | ||||||
| 3.5 | Revision studies | X | ||||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | There is no review process that systematically assesses whether the CPI is meeting users’ needs. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | ||||||
| 4.4 | Revision policy and practice | X | ||||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Data are not released electronically. There is no set embargo time. Data are not released simultaneously as government users receive data in advance of other users. | |||||
| 5.2 | Metadata accessibility | X | There is no adequate metadata documentation. | |||||
| 5.3 | Assistance to users | X | The catalogue of publications is incomplete and does not include charges. | |||||
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Consumer Price Index
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Penalties for noncompliance are ineffective. | |||||
| 0.2 | Resources | X | Computer and financial resources are inadequate. | |||||
| 0.3 | Quality Awareness | X | There is no separate unit to provide guidance on quality. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | The public is not made aware of dissemination practices that result in selected government agencies receiving access in advance of other users. Information on the agency and its products is not publicized. |
|||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | The CPI only covers major urban households. Owner-occupied dwelling services are not measured in the CPI. |
|||||
| 2.3 | Classification/Sectorization | X | ||||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | There are problems in achieving rigorous specification pricing in informal market outlets. The nonobserved economy may not be adequately reflected in the weights and price collections. | |||||
| 3.2 | Statistical techniques | X | Services commodities are not well categorized in the Household Budget Survey. Quality change assessment techniques need improving. |
|||||
| 3.3 | Assessment and validation of source data | X | ||||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | ||||||
| 3.5 | Revision studies | X | ||||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | There is no review process that systematically assesses whether the CPI is meeting users’ needs. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | ||||||
| 4.4 | Revision policy and practice | X | ||||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Data are not released electronically. There is no set embargo time. Data are not released simultaneously as government users receive data in advance of other users. | |||||
| 5.2 | Metadata accessibility | X | There is no adequate metadata documentation. | |||||
| 5.3 | Assistance to users | X | The catalogue of publications is incomplete and does not include charges. | |||||
III. Producer Price Index
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 State Department of Statistics (SDS) is an independent government institution operating under the Law on Statistics No. 1071 of November 12, 1997, and supplemented by an amendment in June 1999. The Law on Statistics authorizes the SDS to collect, compile, and disseminate official statistics about the socio-economic development of Georgia. The Law specifies that while government units and agencies may set up specialized statistical units and may undertake their own statistical surveys, these shall operate under the methodological guidance of the SDS. Other provisions of the Law ensure the consistency of methodology, comparability of statistical international standards, sharing information with other countries, and dissemination.
A decree by the Council of Ministers of Georgia on the State Service for Registering Prices and Tariffs No. 125, March 10, 1995, established the prices division as a separate unit of SDS responsible for price statistics.
The collection and compilation of consumer and producer price statistics are mentioned explicitly in Article 21 of the Regulation for the SDS No. 92 from February 28, 1998, approved by the President of Georgia. In addition to that, the President of Georgia has approved a State Program for Development of Statistics for 2001-2005. The compilation and dissemination of prices statistics are stated in the State Program.
0.1.2 Data sharing and coordination among data producing agencies are adequate
Article 11 of the Law guarantees the SDS access to data produced by legal entities, including the data produced by government ministries and the National Bank of Georgia (NBG). Important areas of statistics are covered by other agencies, such as the NBG, which compiles monetary and financial statistics; the Ministry of Finance (MOF), which is responsible for compiling government finance statistics; and the Customs Committee, which compiles data on imports and exports of goods. The Law gives the SDS primary and coordinating roles in the development of the country’s statistical program.
There are written agreements between the SDS and the MOF, the NBG and the Customs Committee covering the sharing of macroeconomic data, and the SDS management and staff are satisfied with the level of cooperation they receive from these agencies. There appears to be no evidence of significant duplication of statistical effort among the various agencies. No regular contacts with other statistics producing agencies are maintained to take into account the respondent burden.
0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only
Confidentiality of the data reported to the SDS is guaranteed under Articles 7, 12, and 17 of the Law. The Law does not provide penalties for disclosure. The SDS is planning a new amendment to the Law with a provision for penalties for disclosure. The confidentiality aspect is potentially compromised to some extent as a result of the provisions of the Anti-monopoly Law. According to this Law, the State Anti-monopoly Service can request confidential data from the SDS. The conflict between the two Laws has not been resolved. In practice, there have been no breaches of confidentiality of price statistics.
Staff are required to keep individual data confidential, and they are also required to sign a declaration on joining the SDS that confirms awareness of this provision. Access to individual data is restricted to the appropriate staff. There are no special aggregation rules to ensure that unintended disclosure does not occur. Senior staff review the data before dissemination to make sure that confidential data are not disseminated.
0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage reporting
According to Article 11 of the Law, the SDS is authorized to request the information it deems necessary from all legal public and private institutions, as well as from individuals. All requested respondents must furnish the requested information accurately and in the format and time period determined by the SDS. The June 1999 amendment of the Law provides some penalties for nonreporting, but they are not considered effective by the management of the SDS. These penalties were mostly applied to newly registered legal entities for noncompliance with the required registration in the SDS Administrative register. In practice they were not applied for nonresponse to statistical surveys.
The SDS does not systematically review the response burden and contacts with respondents are very limited. In practice, the SDS central office and its regional offices make little effort to create goodwill among data providers.
Since producer prices are collected mainly by personal visit, response burden and noncompliance are not significant issues.
0.2 Resources
0.2.1 Staff, financial, and computing resources are commensurate with statistical programs of the agency
The Consumer Price Index (CPI) and Producer Price Index (PPI) are jointly compiled by nine staff in the central office in Tbilisi. In the Tbilisi regional office there are 20 price collectors who spend about 80 percent of their time on prices work. In the other four regional offices, there is a total of 18 price collecting staff. The relatively small amount of price collection undertaken outside of the five main Georgian cities is undertaken on a part time basis by other staff. These staff resources are considered to be adequate to perform the required tasks.
Remuneration is extremely low and uncompetitive, causing major problems in attracting and retaining suitable staff. It has been estimated that SDS salaries have fallen to about 7 percent of the 1988 levels in real terms.
The staff are well qualified and trained which helps them to handle the continuing change and improvements to the prices work. The nine central office prices staff have tertiary qualifications in economics; three of them have over 15 years statistical experience each.
90 percent of the regional office price collectors have tertiary qualifications; some are engineers which is valuable for product specification.
Staff are trained internally on general statistical issues such as sampling, methodology, data control, etc., as well as specialized topics such as price index theory, maintenance of product quality, treatment of temporarily missing items, etc. Unfortunately, funding restrictions provide for very limited external training.
The director of the Prices Division attended the IMF seminars in Vienna (2002) and Kiev (1998) and found them extremely valuable. Unfortunately, there have not been opportunities for other SDS Prices Division staff to attend such courses; priority should be given to enabling other staff to participate in international training such as the US Bureau of Labor Statistics course on price indices.
Computing resources are very inadequate. For example, the nine Central Office staff share three old personal computers, having to queue to get access; at least three additional machines are required. The situation in the regional offices is even worse; prices staff in one regional office do not have any machines.
Software for the CPI is based on MS Excel files provided by the IMF and upgraded locally; new software is being developed using MS Access which will be more flexible and more readily handle changing product lists, release of unpublished data, etc.
The PPI software needs updating as it does not handle functions such as cross analyses and dissemination very well.
Communications systems are very poor and unreliable. There is no electronic data transfer of unit records from the regional offices to central office for processing; the data have to be physically delivered by courier or SDS staff from one location to the other. As a result, sometimes the pre-announced CPI and PPI publication release dates are not met.
Financial resources are very scarce and travel, course attendance, etc., is very restricted. There is even a shortage of stationery and other office consumables.
0.2.2 Measures to ensure efficient use of resources are implemented
As part of the planning process, the SDS management scrutinizes the work program each year and reviews priorities in developing its financing plan. As resource allocations are regularly less than those required for the planned work program, resource usage is regularly monitored.
It would be beneficial to compare resource usage in detail with other statistical agencies and undertake periodic reviews of working processes.
Within the Prices Division, measures to increase efficiency include the rationalization of collection forms, upgrading of software, exploring more efficient data transmission mechanisms, and the evaluation of methodologies and data compilation techniques with assistance from external experts
Opportunities are being taken, through the attendance at international meetings and training courses, and bi-lateral follow-up communication, to share experiences with other statistical agencies to assist in developing best practice.
0.3 Quality Awareness
0.3.1 Processes are in place to focus on quality
Senior management is sensitive to the dimensions of data quality: integrity, methodological soundness, accuracy and reliability, serviceability, and accessibility. In order to ensure quality, the organization structure of the SDS includes a Statistical Research Institute and an Institute for Informatics and Telecommunications. The Statistical Institute is responsible for developing methodology and software solutions for statistical tasks. The Institute for Informatics and Telecommunications is responsible for development and implementation of information and analytical systems of the national statistics and harmonization of classification systems. A Scientific and Advisory Council was established in the SDS in 1997. Apart from the SDS staff, specialists from the Ministry of Economy, Industry and Trade, the University, the National Bank of Georgia, and the Institute of Economics are, with others, members of the Council. The Council presents assessments and recommendations on the State Program of Statistical Activities, statistical surveys, and structure of the SDS, broad directions of development in the area of statistics and on training and re-training of staff.
The mission statement of the SDS places emphasis on the improvement and harmonization of statistical activities and the maintenance of independence, accuracy, relevance, integrity, timeliness, and professional standard of statistical information produced in Georgia.
Before the CPI and PPI are released, rigorous output editing and credibility checks are undertaken, including cross-checking between CPI and PPI data sets. The SDS senior management clears the data before each month’s data release.
0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics
There is no separate unit that provides guidance on the quality of price statistics and on strategies for improving statistical processes.
Nevertheless, regular meetings are held with users, particularly the National Bank of Georgia (NBG), which provides a mechanism for receiving external feedback.
There are no systematic reviews undertaken to identify problems at the various stages of collecting, processing, and disseminating data.
0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs
The SDS management is conscious of the tradeoffs between the dimensions of data quality and timeliness. For example, a judgment was made to extend the due date for data reporting (in the case of monthly collections, from three-four days after the end of the reference period to seven-eight days) because it was assessed that the substantial improvement in the resultant data quality would exceed the disadvantages of a small reduction in timeliness.
User feedback is encouraged and improvement in data quality is taken into account in planning the forward work program.
1. Integrity
1.1 Professionalism
1.1.1 Statistics are compiled on an impartial basis
The Statistics Law defines the key principles and responsibilities in relation to the collection, processing, and dissemination of statistics in Georgia, with emphasis on international standards and definitions, authenticity, objectivity, and independence. Respondents are obliged to provide clear, objective and timely data to SDS, within the context of assured confidentiality of their data.
As such, the SDS has complete independence and autonomy in the performance of its statistical responsibilities, and there is no scope for external interference in the compilation and dissemination of official statistics.
Price statistics are collected and compiled in an impartial manner by professional SDS staff who have tertiary qualifications and are trained in statistical techniques. The collection and compilation of prices statistics is undertaken according to international standards with the application of objective statistical judgment.
1.1.2 Choices of sources and statistical techniques are formed solely by statistical considerations
Choices about data sources and statistical techniques are based on professional statistical considerations. The weighting sources for the price indices are based on sound household and industrial surveys while the design of the price collections are based on statistical considerations such as efficiency, cost effectiveness, data reliability, and respondent burden. The statistical techniques employed conform to international standards.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics
The media are closely followed for any misuse or misinterpretation of data. In instances where there has been a major misinterpretation of price indices, public comment has been made to rectify the situation (e.g., in respect of the impact of the introduction of cigarette excise tax).
Press conferences are conducted in association with major statistical releases. Regular meetings are held with specialist journalists where data and methodological issues are discussed. These processes reduce the likelihood of serious misunderstandings.
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 and conditions governing the collection of statistics are published in the Law of Georgia on Statistics. These conditions—including the obligation to report, penalties for noncompliance, and confidentiality—are set out on collection forms and discussed at meetings with users and journalists, as appropriate.
Statistical publications do not identify 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
While there is no explicit, intentional internal government access prior to release, in practice the lack of specific public release times (i.e., embargos), and the fact that there are special delivery arrangements for selected government agencies, results in these agencies receiving the data prior to other users. These arrangements have not been publicly acknowledged.
1.2.3 Products of statistical agencies/units are clearly identified as such
Publications of the SDS are clearly identified as SDS products by the department’s name and logo. In cases where SDS data are released in another agency’s publication (e.g., price indices released in an NBG publication), the data are clearly sourced.
The SDS does not mention in its publications that attribution should be made to it when its statistics are used or reproduced.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques
Advance notice is given to users prior to the introduction of changes to methodology, sources, or techniques. This applies to the periodic reweighting of the price indices. This action reduces misunderstanding and results in greater acceptance by users of the changes.
1.3 Ethical Standards
1.3.1 Guidelines for staff behavior are in place and are well known to the staff
SDS operates under a solid legal framework which is being further strengthened in relation to confidentiality of data, penalties for noncompliance by providers, and penalties for offenses by SDS staff.
Staff are well informed of their responsibilities. The law of the civil service contains statements on the ethical standards required of civil servants and the SDS guidelines cover regulations on the handling of confidential data.
Induction training of new SDS staff emphasizes ethical standards.
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 monthly PPI has been compiled using 1993 SNA concepts for the recording and valuation of producer prices and the value weights.
The index is a gross sector output index, with weights based on industry gross output value data from the Enterprise Survey for 2001, valued at basic prices. The prices recorded relate to market transaction prices valued at basic prices, thus excluding trade and transport margins and taxes on products.
The prices are transaction prices, inclusive of any discounts applying (these are specified on the collection form), and any rebates. The product specifications for pricing cover both the product characteristics and the transaction characteristics.
2.2 Scope
2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices
The scope of the index is confined to the output of the Mining, Manufacturing and Electricity, gas and water sectors (i.e., General Industrial Classification of Economic Activities within the European Communities (NACE) Sections C, D, and E).
All resident market enterprises for the defined sectors, are in scope. For the sectors covered, production for own account use is not significant.
2.3 Classification/Sectorization
2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices
International standards are followed in classifying production activity. The classification of units and transaction conforms to 1993 SNA.
NACE is used to classify industries and the Classification of Products by Activity (CPA) to classify commodities.
Product descriptions and standards conform to definitions that provide for the collection of prices of transactions in the same products from month to month. The descriptions of the products allow for them to be uniquely classified to a CPA category.
2.4 Basis for Recording
2.4.1 Prices used to value flows and stocks reflect actual or expected cash payments
Consistent with 1993 SNA, the valuation of the PPI weights, and the prices, is basic prices. The value weights and the collected prices are based on actual market transaction prices, including any discounts, valued at basic prices and thus excluding any trade and transport margins and taxes on products.
The specifications of products for pricing are rigorously defined to include all price determining characteristics of both the product and the transaction to support pricing to constant quality.
2.4.2 Recording is done on an accruals basis
Prices for goods are recorded on an accrual basis with prices recorded for the period in which they are sold. The prices are all collected monthly and included in the index for that month.
2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices
This is not applicable as the PPI is a gross sector index and it is not categorized by Stage of Production.
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 Business Register is not adequate to provide a frame for the PPI price collection because it does not differentiate between operating and nonoperating enterprises and does not accurately reflect the type of industrial activity actually undertaken by businesses.
Therefore, the PPI uses a list of operating enterprises obtained each year from the quarterly Enterprise Survey conducted by the Industry Division of the SDS. The list relates to enterprises that actually operated continuously during the previous four quarters, categorized by industry, product, and value of output.
The PPI output weights are based on annual results from the Enterprise Survey covering Manufacturing, Mining and Electricity, gas and water.
The Enterprise Survey covers all large enterprises in the defined sectors, all enterprises that hire employees and a random sample of enterprises that do not hire employees (10 percent of the enterprises in an industry with a large number of enterprises). In fact, the survey covers 2,500 of the 3,000 operating enterprises, so coverage of output is extremely high. One of the reasons for this large sample is because of the need to produce regional statistics.
Nonresponse is minor, because the traditional businesses have been well organized since Soviet times. Estimation of a missing quarter’s observation can be readily undertaken on the basis of earlier quarters’ observations.
NACE is used as the industrial classification for the survey, and CPA as the commodity classification.
Calendar year results from the Enterprise Survey are available by mid-January.
The monthly producer price survey is based on a shuttle form covering the 12 months of the calendar year. At the beginning of each year, regional offices are provided with forms for the new sample of enterprises and fully specified products.
The sample of enterprises includes all major units, and a selection of the other units using cut-off sampling to maximize coverage. A minimum of 60 percent coverage is achieved for each industry. A total of 260 units is included in the PPI collection.
In most cases, the producer prices are personally collected by regional office staff. In particular, large enterprises and those that have had difficulties or misreported in the past, are visited. This assists in obtaining accurate and timely prices and reduces respondent burden. Prices for other enterprises, and those located in rural areas, are collected by mail.
Given the estimates of the size of the nonobserved economy, there are reservations as to the effectiveness of the enterprise survey and the price surveys in adequately reflecting this activity in the weights and prices of the PPI.
3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required
Enterprise Survey data are consistent with the definitions, scope, classifications, valuation, and timing of recording of the PPI. The producer prices collected match the requirements of a PPI. Both surveys collect data classified by NACE.
3.1.3 Source data are timely
Detailed annual calendar year data are available from the Enterprise Surveys by the middle of January. The producer prices are due on the fifth of the month following the reference month and are normally available on a timely basis though there can be delays in transferring the data to the central office due to unreliable and unsophisticated communication systems and inadequate financial resources, sometimes resulting in the publication failing to meet its preannounced release date.
3.2 Statistical Technique
3.2.1 Data compilation employs sound statistical techniques
Gross output value estimates from the Enterprise Survey are produced at a sufficiently detailed level for effective use as PPI weights. The PPI structure relates to 83 three-digit NACE Classes, 28 Groups, 16 Subsections and three Sections.
Elementary aggregate index numbers for CPA commodities are calculated by deriving short-term ratios of average prices. The modified Laspeyres aggregation formula is used. The weighting base period is 2000 with the weights adjusted to the prices of December 2001, the price reference period for the current index.
Weights are updated annually. As new weights have been introduced, link factors have been derived from a December index overlap, and applied to the time series to form a continuous historical series.
The standard practice in the case of temporarily missing prices is to impute using the current movement in the index at the next level of aggregation. If products disappear permanently, they are replaced.
No seasonal products have as yet been encountered in the current PPI. If they are, they will be repeated until new season prices are available.
In the case of quality change, efforts are made to identify product changes. However, the practice is to treat the changed product as a new item and splice out the associated price change, rather than directly estimate the value of the quality change.
The list of items is reviewed each year and new items added to the sample as appropriate.
3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques
Source data are consistent with the requirements of the PPI. The scope of the PPI relates to less than 20 percent of GDP, so any national accounts deflators would have the advantage of more complete coverage.
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 main source data for the PPI are (i) the quarterly Enterprise Survey which provides gross output value data by industry, commodity, and region for the annual PPI weighting pattern, and (ii) the monthly survey of producer prices.
Enterprise Survey response rates are traditionally very high, and estimation of missing quarterly observations can usually be readily undertaken by reference to previous quarters’ data. Coverage is so high that standard errors are not an issue.
In formulating the new PPI weighting pattern, the Enterprise Survey results are analyzed in detail each year, at a product level, and progressively through the commodity and industry hierarchy. Strict quality control is maintained and queries of coding and reporting undertaken. The old and new weighting structures are carefully compared and any significant shifts rationalized.
Personal interviews are conducted with the sample of enterprises to establish the monthly price collection. For each of the commodities to be priced from a given enterprise, the four most important specifications, in terms of sales value, are selected in consultation with the enterprise.
The monthly producer price collection has rigorous procedures aimed at minimizing errors. Price collectors immediately query price changes in the field and obtain reasons for changes. Nonresponse is not an issue due to the high level of respondent cooperation and the considerable use of personal price collection.
Long term analyses of price changes are undertaken. Relationships within groups and subgroups are studied, and any shifts identified and investigated, with a view to eliminating any errors. Individual prices are checked against external sources where possible.
Price ratios are calculated and products are clustered according to ranges to ensure consistency: outliers are investigated.
3.4 Assessment and Validation of Intermediate Data and Statistical Outputs
3.4.1 Main intermediate data are validated against other information where applicable
Price movements for domestically produced consumer products are compared at producer and consumer level. In aggregate, the CPI and PPI movements have been nearly identical over the last six months.
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated
Large movements, and inconsistent movements between different series, are investigated, especially for important commodities such as oil and coal.
3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated
The aggregate PPI is a single hierarchical Laspeyres aggregation of commodity and industry indices with no scope for statistical discrepancies.
3.5 Revision Studies
3.5.1 Studies and analysis of revisions are carried out routinely and used to inform statistical processes
The PPI is final when first released and index numbers are not subsequently revised.
When weights or methodology are revised, the index number series are not backcast and revised. Rather, the new series are linked onto the old series to form continuous historical series.
Prior to updating the weights, a detailed analysis of shifts in the pattern of production is undertaken and major changes explained.
4. Serviceability
4.1 Relevance
4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored
There is ongoing consultation with users on price indices, especially with the major public policy organizations. Press conferences and briefings are held with journalists, through which feedback is obtained.
However, there is no formal user group, nor an established process of review to systematically assess how well users’ needs are being met. Representatives of the SDS attend international meetings, within the constraints of the available financial resources.
4.2 Timeliness and periodicity
4.2.1 Timeliness follows dissemination standards
The timeliness of the PPI meets GDDS dissemination standards. The PPI is released 20 days after the end of the reference month. However, there are additional lags before publications are available to users.
4.2.2 Periodicity follows dissemination standards
The PPI is released monthly and therefore meets GDDS dissemination standards.
4.3 Consistency
4.3.1 Statistics are consistent with the dataset
The PPI is internally consistent. There is a single hierarchical index structure for the PPI based on one classification structure. See 3.4.3 above.
4.3.2 Statistics are consistent or reconcilable over a reasonable period of time
Continuous monthly, quarterly, and annual index series are maintained through processes of linking at the time new weights are introduced. PPI series go back to January 1997.
4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks
The PPI and CPI are constructed on a consistent basis, and are compatible with national accounts statistics to the extent that they adhere to the 1993 SNA concepts and methods.
4.4 Revision Policy and Practice
4.4.1 Revisions follow a regular, well-established and transparent schedule
The PPI is not revised and the monthly index numbers are final when first released. This policy is well known to the public.
Weights are updated on a regular basis, and product and outlet samples modified over time so they remain representative. However, the index series are not backcast and revised to reflect the new weights or samples. Rather, the new indices are linked onto the previous series to form a continuous historical time series. These are well established practices.
4.4.2 Preliminary data are clearly identified
This is not applicable as the index numbers are final when first released.
4.4.3 Studies and analyses of revisions are made public
This is also not applicable (see also 3.5.1 above).
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 PPI publication contains clear tables and charts. A reasonable amount of detail is published and it is in time series form. However, no analysis of current period changes is presented.
5.1.2 Dissemination media and formats are adequate
As soon as the data are finalized, they are considered to be released and are available to anyone who requests them.
Data are first released by fax and email to selected organizations and subsequently to the media. The data are later released in a monthly SDS General Report and then in a more comprehensive specialist quarterly PPI publication.
The data are not released electronically.
5.1.3 Statistics are released on a pre-announced schedule
There is a pre-announced schedule of publication release dates (but not times), though, in practice, the dates are not always met. It is reasonably well known amongst users that the target release dates for the PPI is the 20th of the month following the reference month (subject to when weekends fall).
5.1.4 Statistics are made available to all users at the same time
In principle, all users have access simultaneously. However, the release mechanisms result, in practice, in selected government agencies receiving the data before other users. The lack of a strict and well-publicized, embargo time (e.g., 10:00am) contributes to this inequitable treatment.
5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request
Nonconfidential, unpublished index numbers are made available on request. However, the availability of this service is not publicized, nor the terms and conditions that apply.
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 only metadata made available to the public is a very brief description of the PPI contained in the SDS Yearbook, which is completely inadequate.
5.2.2 Levels of detail are adapted to the needs of the intended audience
There is no concepts, sources, and methods document or other descriptive material about the PPI.
5.3 Assistance to Users
5.3.1 Contact person for each subject field is publicized
A contact person and telephone number is provided in the fax sent to public policy users and on the cover sheet accompanying the PPI publications. A prompt and knowledgeable service is provided to enquirers.
5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available
There is a catalogue of publications but it is not comprehensive and does not contain charges.
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Producer Price Index
(Compiling Agency: State Department of Statistics)
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Producer Price Index
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Penalties for noncompliance are ineffective. | |||||
| 0.2 | Resources | X | Computer and financial resources are inadequate. | |||||
| 0.3 | Quality Awareness | X | There is no separate unit to provide guidance on quality. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | The public is not made aware of dissemination practices that result in selected government agencies receiving access in advance of other users. Information on the agency and its products is not publicized. |
|||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | ||||||
| 2.3 | Classification/Sectorization | X | ||||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | The business register is not adequate as a frame for the PPI. The nonobserved economy may not be adequately reflected in the weights and price collections. | |||||
| 3.2 | Statistical techniques | X | Quality change assessment techniques need improving. | |||||
| 3.3 | Assessment and validation of source data | X | ||||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | ||||||
| 3.5 | Revision studies | X | ||||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | There is no review process that systematically assesses whether the PPI is meeting users’ needs. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | ||||||
| 4.4 | Revision policy and practice | X | ||||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Data are not released electronically. There is no set embargo time. Data are not released simultaneously as government users receive data in advance of other users. | |||||
| 5.2 | Metadata accessibility | X | There is no adequate meta data documentation. | |||||
| 5.3 | Assistance to users | X | The catalogue of publications is incomplete and does not include charges. | |||||
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Producer Price Index
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Penalties for noncompliance are ineffective. | |||||
| 0.2 | Resources | X | Computer and financial resources are inadequate. | |||||
| 0.3 | Quality Awareness | X | There is no separate unit to provide guidance on quality. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | The public is not made aware of dissemination practices that result in selected government agencies receiving access in advance of other users. Information on the agency and its products is not publicized. |
|||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | ||||||
| 2.3 | Classification/Sectorization | X | ||||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | The business register is not adequate as a frame for the PPI. The nonobserved economy may not be adequately reflected in the weights and price collections. | |||||
| 3.2 | Statistical techniques | X | Quality change assessment techniques need improving. | |||||
| 3.3 | Assessment and validation of source data | X | ||||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | ||||||
| 3.5 | Revision studies | X | ||||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | There is no review process that systematically assesses whether the PPI is meeting users’ needs. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | ||||||
| 4.4 | Revision policy and practice | X | ||||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Data are not released electronically. There is no set embargo time. Data are not released simultaneously as government users receive data in advance of other users. | |||||
| 5.2 | Metadata accessibility | X | There is no adequate meta data documentation. | |||||
| 5.3 | Assistance to users | X | The catalogue of publications is incomplete and does not include charges. | |||||
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
For budget monitoring and management purposes, the Ministry of Finance (MOF) collects and compiles data covering the operations of the consolidated central government (“State Budget”) under the provisions of the Law on Budget Systems and Powers (No. 249-IIs of May 29, 1999) and the annual budget laws. In 1998, the State Financial Statistics Department in the MOF assumed responsibility for compiling GFS covering the consolidated general government (and its subsectors). This Department was merged with the MOF’s Public Relations Department (PRD) in 2002. The PRD is now responsible (under the provisions of Bylaw No. 14 of February 11, 2002) for collecting, processing, and consolidating information on the state of the general government’s finances in accordance with the budget classification system as well as according to the government finance statistics (GFS) methodology (only for publication in the IMF’s Government Finance Statistics Yearbook or GFS Yearbook)1
The MOF’s PRD does not disseminate any GFS themselves, but:
provides summary monthly and annual data to the State Department of Statistics (SDS) for dissemination in their monthly bulletin, and their yearbook, respectively;2
provides summary monthly data (more aggregated than for the SDS) to the National Bank of Georgia (NBG) for publication in their bulletin;
provides data (according to decrees)3 to a specific list of individual users. These users are mostly international organizations and other government agencies;
reports monthly and annual GFS to the IMF’s Statistics Department for publication in the International Financial Statistics (IFS) and GFS Yearbook; and
provides data to any other user, if and when requested.
The multitude sets of data that the PRD has to compile creates an opportunity for confusion among users of Georgia’s fiscal statistics, as these data sometimes differ in methodology, coverage, or level of detail.
Although all information from the MOF should be disseminated through the PRD, fiscal data are sometimes provided directly to users by other departments in the MOF.
There appears to be a duplication of effort in the compilation of GFS, with the creation of the Fiscal Policy Department (FPD) in the MOF in early 2002. Under a Decree of the Minister of Finance, the Long-term Forecasting and Financial Statistics Division in this department has the responsibility to compile and disseminate GFS covering the general government and its subsectors.
By Decree of the Minister of Finance, the Debt Department is responsible for the compilation and dissemination of data on government debt.
0.1.2 Data sharing and coordination among data producing agencies are adequate
Formal and informal arrangements exist also for the exchange of data with other data producing agencies (both inside and outside the MOF):
Well-established arrangements ensure data sharing and coordination between the MOF and other data producing agencies, in particular with the SDS and NBG.
On a formal basis—through a letter signed by the Minister of Finance—data are obtained from other departments in the MOF, and other government agencies. The letter defines the characteristics of the data, the level of detail, the periodicity and timeliness, and the format of the data transmission.
No specific mechanisms exist to maintain close liaison between the PRD (or other MOF departments involved in data compilation) and the users of the fiscal statistics.
0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only
Confidentiality of individual responses is not generally an issue in GFS. The General Administrative Code (2181 of June 25, 1999) states that all general government units should make their information public (i.e., to any public or private sector entity) no later than ten days after the request, unless such information is declared as being secret according to the Law of Georgia on Official Secrecy (No. 455-Is of October 29, 1996). Users are not always aware that they have these “rights.”
0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage reporting
By decrees of the Minister of Finance, the source data producing departments4 in the MOF provide data to the PRD for GFS compilation. Mechanisms do exist for reporting of local government data to the Local Government Division in the MOF’s Budget Department. However, as these arrangements are not supported by specific laws, timely compliance by all local governments is a problem.5
The providers of source data (i.e., other MOF departments) are aware that their data are used by the PRD and other MOF departments for GFS compilation and dissemination.
0.2 Resources
0.2.1 Staff, financial, and computing resources are commensurate with statistical programs of the agency
A substantial lack of staff, financial, and computing resources has been a key factor hampering the strengthening of GFS compilation in the MOF.
Currently, three staff members in the PRD compile GFS.6 Generally, these staff members’ knowledge of the GFSM1986 (A Manual on Government Finance Statistics, 1986 or GFSM1986) methodology is very good, and one of them has attended the IMF’s GFS training course in the Government Finance Statistics Manual 2001 (GFSM 2001) methodology at the Joint Vienna Institute (JVI). All fiscal data compilation in the PRD is done on one computer. Knowledge of GFSM 1986 methodology in other MOF departments, such as the FPD, is also good.
In January 2002, a three-year United Nations Development Program (UNDP)-financed project was launched to strengthen the MOF’s statistical and data compilation capabilities. The main characteristics of this project are: the provision of new computer equipment and software; the establishment of an intranet-service within the MOF as well as, eventually, throughout the central government sector; and the creation of a central GFS database in the MOF. Currently, the intranet-service has been established but the new computers and software have not yet been installed due to technical problems. Plans for the creation of the GFS database have not yet been finalized and it is not certain which MOF department will take responsibility for maintaining this database.
As existing resources are generally insufficient for any improvements in the quality of the GFS currently being compiled and disseminated, prospects are very slim for any improvements that would include the migration to the GFSM 2001 methodology with current resources.
0.2.2 Measures to ensure efficient use of resources are implemented
There is no separate cost information on the compilation of budget execution data or GFS, as the allocation of resources is part of the overall management process of the MOF. The apparent lack of a single unit in the MOF responsible for GFS compilation suggests that resources could be used more efficiently.
0.3 Quality Awareness
0.3.1 Processes are in place to focus on quality
The fiscal data production process in the MOF focuses on the application of accounting rules on which the statistics are based. There are no surveys using estimates and quality control processes (e.g., for GFS compilation) have not been formally documented.
Often, GFS has to be compiled on very short notice, e.g., for use by the Minister of Finance or by Parliament. It is possible that the quality of these data could be compromised as a result of the time constraints involved.
0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics
The PRD verifies the quality of the monthly source data by comparing the data with those of the previous period (e.g., large changes in trends are investigated). The PRD also relies on the professional judgment of the staff working with the GFS data. Annual data on central government operations, as well as local government’s data, are audited by the Chamber of Control against published accounting standards, which mainly correspond to those used in the Soviet Era.
There are no systematic arrangements in place to obtain feedback from users of GFS on the quality of the statistics.
0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs
Tradeoffs between quality and timeliness, or between timeliness and the level of detail of GFS are not communicated to the users of GFS. A three-year UNDP-financed plan has recently been launched to improve overall data quality in the MOF. However, the successful completion of this plan will, among other things, be determined by the level of continuity/stability within the MOF. Previous plans to improve the overall quality of GFS have been less successful due to numerous and frequent changes in the organizational structure and executive management of the MOF.
1. Integrity
1.1 Professionalism
1.1.1 Statistics are compiled on an impartial basis
There are no specific laws that establish the professional independence of those responsible for GFS compilation, as fiscal data are compiled primarily for purposes of budget monitoring, fiscal policy analysis, and for reporting to international organizations under the budgetary laws. The GFS compilers cannot change any of the source data provided by the Treasury and Tax Departments, unless such changes are the result of revisions. In principle, reclassifications of source data according to GFS methodology are allowed, but currently all fiscal data compiled follow the annual budget laws.
Uncompetitive salaries in the public sector have had a detrimental effect on the recruitment of appropriately qualified staff in the MOF, and do not encourage the retention of experienced staff. Analytic work is very weak in the MOF and only a few methodological papers have been published—none by the GFS compilers in the PRD. No seminars or conferences have been held in the MOF to promote professionalism or to benefit from methodological and organizational developments elsewhere.
1.1.2 Choices of sources and statistical techniques are formed solely by statistical considerations
As use of GFS within Georgia is mostly limited to government, the data compiled and disseminated follow the annual budget laws. The data reported to the IMF for publication in the GFS Yearbook also accord with the annual budget laws, which differ in some significant respects from international standards (see Methodological Soundness in section 2 below). However, according to the PRD, they would be free to compile GFS that would correspond to the GFSM 1986 or GFSM 2001 methodologies, should they be required to do so. For some individual users, GFS are compiled according to a methodology that differs from the budget law.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics
Apart from international organizations, GFS use is very limited outside the government sector in Georgia. As GFS are officially disseminated on a very limited basis, comments on the misuse of statistics are not made regularly. Nevertheless, GFS compilers are allowed to provide expert advice on technical aspects of GFS or to respond to public misinterpretation of statistics. Data provided to the SDS and NBG for dissemination in their media are not accompanied by any explanatory material to avoid misinterpretation. Extensive explanatory material are provided by the MOF when the State Budget is tabled in Parliament.
1.2 Transparency
1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public
The current compilation of fiscal data takes place under the provisions of the Law on Budget Systems and Powers (No. 249-IIs of May 29, 1999) and annual budget laws, as it is done mainly for budget monitoring and management purposes. Information about this law, like all other government laws, is freely available to the public. However, the terms and conditions under which GFS (as opposed to budget execution data) are collected, compiled, and disseminated by the PRD are not readily available to the public. Also, it is not publicised that there are no restrictions on public access to GFS.
1.2.2 Internal governmental access to statistics prior to their release is publicly identified
GFS are published in the SDS and NBG dissemination media not later than two months after the end of the reference month. Prior to these publications, information on fiscal data/GFS flow freely among government agencies, and to individual users outside the government sector about three weeks after the end of the reference month. MOF staff also have access to preliminary fiscal data—within a week after month-end. These data are not available to other government agencies as they are “soft” numbers. The internal access to fiscal data/GFS before general release is not officially made public, although it is a widely known fact.
1.2.3 Products of statistical agencies/units are clearly identified as such
The GFS tables the PRD provides to the SDS for dissemination do not include a reference that the MOF is the source of these data, but in the accompanying text—drafted by the SDS—it is implied that the MOF is the source of the data. Elsewhere, the MOF is clearly identified as the source of the data.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques
Until now, there was no need for advance notice to the public of major changes in methodology, source data, and statistical techniques. However, the MOF was not aware of the need for such notices as a good international practice.
1.3 Ethical Standards
1.3.1 Guidelines for staff behavior are in place and are well known to the staff
There is no specific code of conduct for the compilation of GFS. However, all state employees are governed by a code of conduct according to the Law of Georgia on Public Service (No. 1022 of October 31, 1997), which also includes penalties for violations. This Law was disseminated to all staff when it was promulgated. When employees sign their employment contracts, they are referred to the existence of this law. The MOF is considering to develop a code of conduct for its staff, similar to the Tax Department’s Code of Conduct.
2. Methodological Soundness7
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
Compilation of both monthly and annual fiscal data follows the analytic framework prescribed by the annual budget laws. While the annual budget laws are generally consistent with the analytic framework of the GFSM 1986, their concepts and definitions of revenue, expenditure and lending minus repayments, and financing differ from the international standards in some significant respects. In the existing budget law (2002):
Revenue and grants include repayments of loans previously extended by government. According to the GFSM 1986, these repayments are classified as Lending minus Repayments. For local governments, proceeds from privatization are included as nontax revenue;
Lending minus repayments (“net lending”), which form part of total expenditure and net lending, are defined as amortization of foreign loans as are all disbursements of World Bank financed project loans;8
As a result of the treatment of amortization of foreign loans, foreign financing is defined on a gross basis (i.e., new borrowing only).
In all data compiled by the PRD, including those for publication in the IMF’s GFS Yearbook, these budget law definitions of revenue, expenditure and net lending, and financing are followed.
GFS compiled for some individual users (e.g., reporting to international organizations) follow in some respects the analytic framework that resembles the methodology of the GFSM 2001:
Current expenditure include interest payments on a commitments basis.
Sales of equity other than shares (privatization) are recorded below the line as a disposal of a financial asset (financing). The 2002 Budget Law follows this approach too.
The deficit/surplus is calculated on a commitments basis.
Financing and debt data are compiled only on a currency basis and, as mentioned, foreign financing data exclude amortization of foreign loans. The data on a currency basis broadly accord with international standards for determining residence (i.e., debt denominated in foreign currency is assumed due to nonresidents and debt denominated in domestic currency is assumed due to residents).
There appear to be no official plans to migrate to the GFSM 2001 framework or methodology.
2.2 Scope
2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices
The scope of GFS disseminated (in terms of government units covered) generally meets that recommended and encouraged by the GDDS. However, in terms of transactional coverage, GFS disseminated only broadly meets the GDDS recommendations. Monthly and annual GFS cover all the activities of all the general government units in Georgia, except for the own revenues (e.g., fees and charges) of central and local government spending agencies (and the corresponding expenditure from these sources) received in their “Special Accounts.” Starting with the 2002 budget, special accounts are included in the budget law, but monitoring them on a monthly basis is still problematic. Plans are to abolish special accounts in 2003.
Sufficient data on transactions between general government units are available to compile GFS for the consolidated general government, with the exception of transfers from the extrabudgetary funds to other general government units. The coverage of GFS is the same for preliminary and final data. GFS do not cover any quasi-fiscal activities of government.
The PRD compiles nearly 20 different sets of tables for its various users and, put together, data would be available for most of the tables included in the scope of the GFSM 1986. For the IMF’s GFS Yearbook, data are compiled for gross government debt (see Concepts and Definitions in section 2.1 above), which is in accordance with international standards. Government’s assumption of “historical loans”9 are not included in government debt, although it is acknowledged that such liabilities exist. Domestically, no data are disseminated on domestic government debt, and thus not total government debt.
2.3 Classification/Sectorization
2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices
The institutional sectors of government are defined in accordance with the 1993 System of National Accounts (1993 SNA).
In all cases, except for the data compiled for publication in the IMF’s GFS Yearbook, GFS tables compiled and disseminated in Georgia do not provide the same level of detail as required by international standards. The economic classification of expenditure and lending minus repayments differs significantly from international standards.
Revenue and grants: At an aggregate level, the classification of revenue and grants closely resembles the GFSM 1986 classification of revenue: a distinction is made between tax and nontax revenue. Tax revenues are classified as taxes on income and profits, value-added tax, excises, customs duties, and other taxes. Nontax revenues include repayments of government lending, property income, dividends from state enterprises, fines and penalties, and miscellaneous other nontax revenues.
Functional classification of expenditure and lending minus repayments: The functional classification of expenditure and “net lending” follows the COFOG included in the GFSM 1986.
Economic classification of expenditure and lending minus repayments: While the economic classification of expenditure and net lending closely resembles the GFSM 1986 categories, several items are not classified according to international standards:
Although transfers from central government to local governments include transfers for both current and capital purposes, all transfers to local governments are classified as current transfers.
Loans to the Tbilisi Municipality are classified as current transfers. According to GFSM 1986, these should be classified as Lending minus Repayments.
A separate expenditure item, Targeted Programs, is included in the economic classification of expenditure. According to international standards, these expenditures should be classified to the appropriate economic categories. The inclusion of this separate item greatly reduces the overall usefulness of the economic classification of expenditures.
All projects financed through the World Bank are classified as Lending minus Repayments, but most of them should be classified in the appropriate current and capital expenditure categories according to international standards.
Financing and Debt: Financing and debt data are classified by type of debt holder and debt instrument, according to the GFSM 1986 with the exception of “changes in cash balances,” which are classified as “other liabilities” (classification by type of instrument) in the GFS compiled by the PRD. According to international standards, the changes in these financial assets should be classified as Changes in Cash, Deposits, and Securities Held for Liquidity Purposes (GFSM 1986).
2.4 Basis for Recording
2.4.1 Prices used to value flows and stocks reflect actual or expected cash payments
Only cash transactions are recorded in the source data (and thus GFS), and these flows are valued on the basis of the amount of payments in cash.
In accordance with the GFSM 1986, debt liabilities are recorded at face value (i.e., the amount to be repaid at the end of the contract), rather than market value. Amounts denominated in foreign currency are converted to Georgian Lari using the official exchange rate for the end of each month, as provided by the NBG.
2.4.2 Recording is done on a cash basis
Revenue and expenditure data are based on cash received and paid, respectively, and financing data are also recorded on a cash basis, according to the GFSM 1986. For some purposes, financing data including foreign loans are shown, in line with interest, on a commitments basis. The latter is, in principle, closer to the methodology of the GFSM 2001.
2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices
Government finance transactions are correctly shown on a gross basis, but not all financing transactions are correctly recorded on a net basis. Tax refunds are correctly classified as (negative) revenue transactions.
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
Budgetary central government: Timely and comprehensive revenue, grants and domestic financing data are available from the NBG Treasury Account records. Timely data, but less comprehensive than revenue data, are available every month from the Treasury system. Both revenue, grants and expenditure data are only available on a cumulative year-to-date basis. No discrete monthly data are compiled in the source data. Timely and comprehensive foreign financing data are available monthly from the MOF’s Debt Department. Both domestic and foreign financing data are available on a monthly and a cumulative year-to-date basis. No data are available on spending agencies’ operations relating to their own revenues received in their “Special Accounts.” Starting with 2002, special accounts are included in the budget law, but monitoring them on a monthly basis is still problematic. Plans are to abolish special accounts in 2003.
Extrabudgetary Funds: Timely, but aggregated data are available on revenues and grants, expenditures and financing from the two extrabudgetary funds. Expenditure data of extrabudgetary funds do not identify transfers between them and other general government units to allow consolidation. The revenues and grants of all general government units identify grants from other general government units separately, allowing for consolidation.
Consolidated Central Government: Timely data, but limited to the details of extrabudgetary funds’ data, are available from the Treasury Department. No data are available on spending agencies’ operations relating to their own revenues received in their “Special Accounts.”
Local governments: Timely cumulative year-to-date and annual data on local governments’ revenues, expenditures, and financing are available from the Budget Department’s Local Government Division. While revenue data are quite comprehensive, as NBG Treasury Account records are used, these data exclude their own revenues, as well as some central government taxes collected by certain regions. Local government expenditure data are very aggregated.
For final annual data, the same sources, but as verified by the Chamber of Control, are used.
3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required
For compiling GFS, the source data broadly approximate the definitions, classifications, valuation, and time of recording according to the GFSM 1986, with significant exceptions listed below. In some respects, the methodology of the GFSM 2001 is followed (e.g., the treatment of privatization revenue). The scope of the source data is only broadly sufficient to analyze the operations of the general government in Georgia, as not all government operations are covered in the source data.
In the following cases, the source data deviate significantly from the international definitions and classifications standards:
The economic classification of expenditure in the source data does not reflect the definitions according to international standards (see Classification/Sectorization in section 2.3 above).
Local government data do not allow for an economic classification of expenditure, as the budget classification system used in the Soviet period (line-item classification) is still employed. A (broad) functional classification of their expenditures is, however, possible.
Data published on the outcome of the state budget (i.e., under financial accountability arrangements) are easily reconcilable with the GFS data, as GFS are compiled to correspond exactly with the year’s budget law (i.e., the data is exactly the same). For some users, GFS are compiled according to a methodology that differs from the annual budget law. These data are also easily reconcilable with data published on the annual outcomes.
3.1.3 Source data are timely
Source data for compiling GFS covering the general government (and it’s subsectors) in Georgia are extremely timely.
Budgetary central government data (cumulative year-to-date) are available within seven days after the end of the reference month. Preliminary annual data are available by January 31 (year-end is December 31), and final annual data are available before April 1.
Extrabudgetary funds’ data (cumulative year-to-date) are available ten days after the end of the reference month. Preliminary annual data are available by January 31 (year-end is December 31), and final annual data are reported to the Treasury Department by March 1.
Aggregated Local governments’ data (cumulative year-to-date) are available 15 days after the end of the reference month. Preliminary annual data are available by January 31 (year-end is December 31), and final annual data are reported to the Budget Department’s Local Government Division by March 1. The consolidated data for all local governments are available by about mid-April. Obtaining detailed local government data on a timely basis is problematic.
3.2 Statistical Technique
3.2.1 Data compilation employs sound statistical techniques
No statistical techniques are applied to compile GFS, and no estimates are made for data that are not available (such as activities in spending agencies’ “Special Accounts”).
3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques
Other statistical procedures are not employed in compiling GFS.
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
There are material gaps in the coverage/completeness of the data collection for some local government data, all government units’ own revenue sources and expenditures from these sources (see Scope in section 2.2 above), and details of the economic classification of expenditure of all general government units. Although the MOF is trying to address the local government data issue, there is not much that could be done to improve the situation, as they are bound by existing laws governing relations between central and local governments. Details on expenditure data are available in administrative records, but are provided on an ad hoc basis to GFS compilers and users, when requested. In other words, no systematic efforts are made to improve the availability of detailed central government source data.
There is an appropriate balance between accuracy and timeliness of the source data. Tradeoffs are made between timeliness and the level of detail available. Every year, preliminary data are replaced by final audited data. The most timely data are sufficiently accurate, but not always sufficiently detailed, for fiscal policy development.
The status of data (preliminary or final) is not always clearly identified in the source data tables. However, according to the MOF, all GFS compilers and users are aware that cumulative year-to-date data are preliminary. Preliminary annual data are indicated as such, and “if nothing is indicated” it means the annual data are final. Data are always corrected when revisions are made by the Treasury due to, e.g., more accurate information available—such instances rarely occur, though.
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 same GFS data are published in the SDS and MOF publications, as these data are provided by the MOF’s PRD. No validations of intermediate government finance data are carried out, as no similar data are published elsewhere. Instead, validation of GFS compilation is done against the original, unpublished source data (e.g., against the Treasury Department’s data provided to the PRD).
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated
Not applicable.
3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated
GFS are compiled from Treasury and NBG records, and outputs are verified against the original source data. Discrepancies between these data, which rarely occur, are assessed and investigated. After compilation, all GFS data are compared with the previous period to identify unusual trends, for which explanations are then obtained and documented internally. None of these explanations are officially published anywhere, but are provided to users within government, or available to any other GFS users, if requested.
If GFS is compiled from different sources, e.g., by using NBG records for revenues rather than Tax Department revenues, discrepancies occur in the data mainly due to different times of recording. Compilers are aware of the reasons for the differences and reconciliation is done as far as possible.
3.5 Revision Studies
3.5.1 Studies and analysis of revisions are carried out routinely and used to inform statistical processes
Two types of revisions are done to compiled GFS: (i) ad hoc corrections by the Treasury Department of preliminary monthly data due to, e.g., more accurate information, and (ii) about four to five months after year-end, when preliminary data are replaced by final, audited data (see also Revision Policy and Practice in section 4.4 below). GFS compilers in the PRD keep information on reasons for revisions to preliminary year-to-date data, and reasons for differences between preliminary annual data and final audited data are provided in the Chamber of Control’s reports.
4. Serviceability
4.1 Relevance
4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored
GFS use in Georgia is largely limited to users within government and international organizations. These data are available with sufficient timeliness to allow users to assess the degree to which government is achieving its stated fiscal goals and policies, as these data are according to the annual budget law framework. However, the methodological basis and aggregated classification structure is generally not sufficient to meet users’ needs for analytical purposes, as GFS are largely compiled on an aggregated basis and mainly for budget monitoring purposes, which differ from international methodological standards. This is especially the case for the GFS disseminated in the SDS monthly bulletin and in the NBG bulletin and on their website. In addition, no data on government debt are disseminated in these publications.
For sub-annual data, only cumulative year-to-date data are disseminated, i.e., no discrete monthly data are compiled.
Currently, the MOF has no specific measures in place to obtain direct feedback, on a regular basis, from users or potential users on the relevance of existing statistics. According to the General Administrative Code (No. 2181 of June 25, 1998), all government agencies should make their information public, and provide this information to any public/private entity within ten days after the request, unless such information is regarded as secret. Until now, the practice has thus been to provide information to users in the formats, timeliness, and periodicity requested (“Ask, and we will provide what is requested”). Thus, users’ needs are monitored indirectly, based upon the users’ initiative.
4.2 Timeliness and periodicity
4.2.1 Timeliness follows dissemination standards
The timeliness of official dissemination of GFS (i.e., in the SDS and NBG monthly bulletins) meets, and exceeds, those recommended by the General Data Dissemination System (GDDS) (see also Scope in section 2.2 above):
Preliminary cumulative year-to-date GFS, covering the general government (and its subsectors), are disseminated to the PRD’s list of users three weeks after month-end (some data, e.g., budgetary data, are disseminated within government before that time). These data are disseminated in the SDS monthly bulletin and in the NBG monthly bulletin and website about two months after the end of the reference month. (GDDS recommendation: quarterly central government aggregates within one quarter after the end of the reference period.)
Preliminary annual data covering the general government (and its subsectors) are disseminated to the PRD’s list of users about one and one half months after the end of the reference month (some data, e.g., budgetary data, are disseminated within government before that). These data are disseminated in the SDS monthly bulletin and in the NBG monthly bulletin and website about three months after the end of the reference year.
Final annual data covering the general government (and its subsectors) are disseminated to the PRD’s list of users about five months after the end of the reference month (some data, e.g., budgetary data, are disseminated budgetary data within government before that). These data are disseminated in the SDS Yearbook in the NBG monthly bulletin and website about six months after the end of the reference year. (GDDS recommendation: comprehensive annual central government data within six-nine months after the end of the reference period)
Monthly and annual data on government’s foreign debt are disseminated about a week after the end of the reference month in a local newspaper, as well as to other users within government and international organizations. Data on domestic government debt are only disseminated to users within government and to international organizations about two weeks after the end of the referencemonth. (GDDS recommendation: annual central government debt data within one-two quarters after the end of the reference period)
The timeliness of detailed local government data are sometimes problematic.
4.2.2 Periodicity follows dissemination standards
The periodicity of official dissemination of GFS (i.e., in the SDS and NBG monthly bulletins) meets, and exceeds, those recommended by the GDDS (see also Scope in section 2.2 above):
Cumulative year-to-date preliminary data for the budgetary central government, extrabudgetary funds, and local governments are disseminated every month (cumulative year-to-date) and annually. (GDDS recommendation: quarterly and annual central government aggregates. Annual general government aggregates are encouraged by the GDDS.)
Central government foreign debt data are disseminated monthly and annually (GDDS recommendation: annual central government debt data, with quarterly data encouraged.)
4.3 Consistency
4.3.1 Statistics are consistent with the dataset
GFS compiled by the PRD from consistent sources (e.g., those data compiled from the Treasury Department’s records on revenues, expenditure and financing) are internally consistent. The deficit/surplus is equal to financing (with an opposite sign) and major aggregates are equal to the sum of their components. Total expenditure and “net lending” according to the economic classification corresponds with that in the functional classification of expenditure. Domestic financing is consistent with the change in domestic debt, as these data are compiled from the same NBG sources. Foreign financing data, after taking into account amortization of foreign loans included in “net lending” and revaluations of foreign loans, are consistent with the changes in foreign debt. Transfers paid by one level of government are equal to transfers received by another level of government. However, lack of details in the extrabudgetary funds’ expenditure data do not allow for verification (or consolidation) of transfers from these funds to other levels of government.
GFS compiled from separate data sources, e.g., using the Tax Departments records on revenues rather than NBG bank account records will, by definition, show inconsistencies between the deficit/surplus and financing data. This is because the one source records data on a checks received basis, while the other is on a checks cashed basis. This statistical discrepancy is, therefore, equal to the amounts in transit. Inconsistencies also exist between expenditure data compiled from different sources.
Government foreign borrowing and amortization data are derived from the UNCTAD Debt Management and Financial Analysis System (DMFAS) used by the MOF to manage debt. Data on budgetary central government financial assets are derived from NBG records of cash holdings.
4.3.2 Statistics are consistent or reconcilable over a reasonable period of time
Compiled GFS follow the annual budget laws and inconsistencies over time can be ascribed to changes in this law. The PRD does not apply material changes to classification or methodological treatment to the GFS time series to ensure a consistent series, but is aware of all such changes. Reconciliation of data over a reasonable period of time could thus be done. No official explanations of changes in trends, etc., are disseminated with the data, but the PRD can explain them, if users inquire.
4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks
National accounts and balance of payments statistics are compiled by general government data that the MOF provides to the SDS, and monetary and financial statistics are compiled from NBG records. All these data are consistent or reconcilable with GFS.
4.4 Revision Policy and Practice
4.4.1 Revisions follow a regular, well-established and transparent schedule
Ad hoc revisions to cumulative year-to-date data are done when needed. However, as only cumulative year-to-date data are published, revisions to previous months’ data are not visible to users. Users of GFS published in the SDS monthly bulletin or NBG bulletin are not informed of revisions to historical data. The internationally accepted practice is to publish discrete monthly data, in addition to cumulative year-to-date data, and to clearly identify revisions to historical data.
Preliminary annual data are replaced by final audited data according to a regular, well-established and transparent schedule, as required by law.
4.4.2 Preliminary data are clearly identified
Preliminary data published in the SDS and NBG bulletins are not always clearly identified. Data provided by the PRD to individual users within government and international organizations, are identified as preliminary.
4.4.3 Studies and analyses of revisions are made public
Studies and analysis of revisions are not automatically made public. Reasons for revisions are investigated and documented by the PRD, and are only made public when individual users enquire about the reasons for the revisions.
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)
For all disseminated GFS, the presentation of the statistics are in general not adequate to allow proper interpretation and meaningful comparisons. Only the major aggregates and balancing items of GFS are published in the SDS and NBG publications—these GFS data do not cover any of the detailed classification tables set out in GFSM 1986. Annual time series data are only provided for a short period. GFS disseminated to individual users are more detailed, in accordance with their requests.
Only data on foreign government debt are disseminated domestically.
5.1.2 Dissemination media and formats are adequate
There is no dedicated GFS publication or website. The SDS and NBG dissemination formats are generally adequate, but only for aggregated GFS data. GFS are disseminated to individual users according to their requirements, usually by facsimile or e-mail.
5.1.3 Statistics are released on a pre-announced schedule
The dissemination policy relating to GFS is not publicized, although it is generally known among regular users when the data becomes available. There is no advance release calendar for the release of GFS, so the actual date of publication may vary according to circumstances.
5.1.4 Statistics are made available to all users at the same time
GFS are not made available to all users at the same time. Users within government and international organizations have access to GFS as soon as the data have been compiled. In principle, any other user who asks for such data at that time, could get these data too. Preferential access to GFS within government (i.e., before general dissemination) is not made public.
5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request
Unpublished but nonconfidential data are made available upon request. There is no fee for obtaining such data. This is done under the provisions of the General Administration Code, which provides that any user may obtain information from government agencies and this information should be provided within ten days after the request. However, the availability of such data, as well as the terms and conditions under which it is made available, is not publicized in GFS publications.
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
No separate metadata exist on the concepts, scope, classifications, basis of recording, data sources, and statistical techniques for compiling GFS. Nevertheless, the Budget Systems Law and annual budget laws contain some information on the concepts, scope, definitions, and basis of recording of government activities—GFS currently compiled follows these laws. The differences between internationally accepted standards and GFS compiled in Georgia are not annotated nor publicized.
5.2.2 Levels of detail are adapted to the needs of the intended audience
Apart from the Budget Systems Law instructions, no metadata exist on the sources, methods, and methodology for the compilation of GFS.
5.3 Assistance to Users
5.3.1 Contact person for each subject field is publicized
No contact person for GFS is publicized in the publications of the SDS or NBG. Individual users of GFS disseminated by the PRD know who to contact for enquiries. Otherwise, users contact either the PRD or any other MOF department for the specific data they require.
5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available
The MOF does not have any catalogues of publications, documents, or other services.
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Government Finance Statistics
(Compiling Agency: Ministry of Finance)
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Government Finance Statistics
(Compiling Agency: Ministry of Finance)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observe; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Two departments in MOF have been assigned responsibility for compiling GFS after most recent restructuring posing a risk of duplication of efforts; legal mandate/measures not fully adequate to ensure timely reporting of detailed data by all local governments. | |||||
| 0.2 | Resources | X | Staff and financial resources mostly insufficient for comprehensive GFS compilation; no resources for migration to GFSM 2001. | |||||
| 0.3 | Quality Awareness | X | GFS quality control processes have not been formally documented; short notice for data compilation has potential to compromise quality; tradeoffs between quality, timeliness, and degree of detail not communicated to users. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | Somewhat constrained by requirement of annual budget laws, and apparent insufficient recognition of user needs for detailed GFS that fully correspond to international standards. | |||||
| 1.2 | Transparency | X | Specific terms of conditions under which GFS are compiled, as well as approval process for publication, are not made public; not publicly identified that there are no restrictions on access to GFS; internal access to GFS is a widely-known fact, but this is not officially made public; MOF as compiler of GFS not always clearly identified. | |||||
| 1.3 | Ethical standards | X | - | - | ||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | Analytic framework generally GFSM 1986, but revenue, expenditure, and financing concepts & definitions not according to GFSM 1986, specifically expenditure definition, e.g., by inclusion of debt amortization; no official plans to migrate to GFSM 2001. | |||||
| 2.2 | Scope | X | GFS cover all general government units, but not all their transactions—own revenues and expenditures from these resources are, up to now, excluded. | |||||
| 2.3 | Classification/Sectorization | X | Classifications broadly according to GFSM 1986, except: lacking degree of detail for all tables; economic classification of expenditure include nonstandard items, and some current and capital expenditures, and amortization of foreign financing, classified as lending minus repayments. | |||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | Generally adequate, but no data up to now on spending agencies’ activities regarding own revenue sources; lack of details for extra-budgetary funds expenditure do not allow full consolidation of data; levels of detail and classifications of local government expenditures do not approximate classification required for GFS; lack of details to compile complete economic classification of expenditure (e.g., no breakdown readily available of subsidies and other current transfers). | |||||
| 3.2 | Statistical techniques | X | - | |||||
| 3.3 | Assessment and validation of source data | X | Gaps in the coverage/completeness of the data collection are assessed, but not much could be done to improve because of laws and/or lack of resources. | |||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | - | |||||
| 3.5 | Revision studies | X | - | |||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | Methodological basis and classification structure generally not suitable to meet users’ analytical needs. No measures in place to formally seek feedback from users on relevance and usefulness of statistics—feedback is obtained indirectly through individual user requests. | |||||
| 4.2 | Timeliness and periodicity | X | - | |||||
| 4.3 | Consistency | X | Data internally consistent. No consistent GFS time series exist because of budget law changes but it is feasible to compile such series; no explanations provided for inconsistencies, but aware of reasons, so can reconcile. | |||||
| 4.4 | Revision policy and practice | X | Only cumulative year-to-date data published every month, so revisions are not visible; preliminary data sometimes not clearly identified, studies and analysis of revisions only made public in response to individual user requests. | |||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Presentation of aggregated GFS in SDS and NBG publications not adequate to allow proper interpretation and meaningful comparisons; GFS not released on a pre-announced schedule; GFS not made available to users at the same time; nonpublished but nonconfidential data are made available to users upon request, but this is not publicized. | |||||
| 5.2 | Metadata accessibility | X | No metadata exist on GFS. | |||||
| 5.3 | Assistance to users | X | Contact person for each subject field not publicized. | |||||
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Government Finance Statistics
(Compiling Agency: Ministry of Finance)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observe; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Two departments in MOF have been assigned responsibility for compiling GFS after most recent restructuring posing a risk of duplication of efforts; legal mandate/measures not fully adequate to ensure timely reporting of detailed data by all local governments. | |||||
| 0.2 | Resources | X | Staff and financial resources mostly insufficient for comprehensive GFS compilation; no resources for migration to GFSM 2001. | |||||
| 0.3 | Quality Awareness | X | GFS quality control processes have not been formally documented; short notice for data compilation has potential to compromise quality; tradeoffs between quality, timeliness, and degree of detail not communicated to users. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | Somewhat constrained by requirement of annual budget laws, and apparent insufficient recognition of user needs for detailed GFS that fully correspond to international standards. | |||||
| 1.2 | Transparency | X | Specific terms of conditions under which GFS are compiled, as well as approval process for publication, are not made public; not publicly identified that there are no restrictions on access to GFS; internal access to GFS is a widely-known fact, but this is not officially made public; MOF as compiler of GFS not always clearly identified. | |||||
| 1.3 | Ethical standards | X | - | - | ||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | Analytic framework generally GFSM 1986, but revenue, expenditure, and financing concepts & definitions not according to GFSM 1986, specifically expenditure definition, e.g., by inclusion of debt amortization; no official plans to migrate to GFSM 2001. | |||||
| 2.2 | Scope | X | GFS cover all general government units, but not all their transactions—own revenues and expenditures from these resources are, up to now, excluded. | |||||
| 2.3 | Classification/Sectorization | X | Classifications broadly according to GFSM 1986, except: lacking degree of detail for all tables; economic classification of expenditure include nonstandard items, and some current and capital expenditures, and amortization of foreign financing, classified as lending minus repayments. | |||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | Generally adequate, but no data up to now on spending agencies’ activities regarding own revenue sources; lack of details for extra-budgetary funds expenditure do not allow full consolidation of data; levels of detail and classifications of local government expenditures do not approximate classification required for GFS; lack of details to compile complete economic classification of expenditure (e.g., no breakdown readily available of subsidies and other current transfers). | |||||
| 3.2 | Statistical techniques | X | - | |||||
| 3.3 | Assessment and validation of source data | X | Gaps in the coverage/completeness of the data collection are assessed, but not much could be done to improve because of laws and/or lack of resources. | |||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | - | |||||
| 3.5 | Revision studies | X | - | |||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | Methodological basis and classification structure generally not suitable to meet users’ analytical needs. No measures in place to formally seek feedback from users on relevance and usefulness of statistics—feedback is obtained indirectly through individual user requests. | |||||
| 4.2 | Timeliness and periodicity | X | - | |||||
| 4.3 | Consistency | X | Data internally consistent. No consistent GFS time series exist because of budget law changes but it is feasible to compile such series; no explanations provided for inconsistencies, but aware of reasons, so can reconcile. | |||||
| 4.4 | Revision policy and practice | X | Only cumulative year-to-date data published every month, so revisions are not visible; preliminary data sometimes not clearly identified, studies and analysis of revisions only made public in response to individual user requests. | |||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Presentation of aggregated GFS in SDS and NBG publications not adequate to allow proper interpretation and meaningful comparisons; GFS not released on a pre-announced schedule; GFS not made available to users at the same time; nonpublished but nonconfidential data are made available to users upon request, but this is not publicized. | |||||
| 5.2 | Metadata accessibility | X | No metadata exist on GFS. | |||||
| 5.3 | Assistance to users | X | Contact person for each subject field not publicized. | |||||
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 NBG is given the legal authority and responsibility for the collection of monetary and financial statistics in Article 56 of the Organic Law on the NBG of 1995. Article 56 gives the NBG authority for “collecting statistical reports, accounting data and other materials from banks and other financial institutions, other government agencies, and private companies and organizations.” Commercial Banks have the responsibility to prepare and submit to the National Bank of Georgia (NBG) reports, forms and details prescribed by the Law of Georgia on activities of Commercial Banks (LCB) of 1996, Article 29.
Article 68 of the Organic Law provides that the NBG may publish financial statements, reports, and studies on financial and economic issues as it shall deem appropriate.
The Macroeconomic Research and Monetary Policy Department (MRMPD) of the NBG is responsible for research on the statistical methodology, data collection, processing, and dissemination of monetary and financial statistics (MFS). Banks’ statistical data are collected by the Monetary Statistics and Information Division (MSID). NBG and commercial banks’ balance sheet data are submitted by the Accounting Department (AD) of the NBG to the MSID. All inquiries about monetary data are directed to the MSID.
0.1.2 Data sharing and coordination among data producing agencies are adequate
Compilation, production, and dissemination of monetary and financial statistics fall under the responsibility of the NBG. Within the NBG there are arrangements in place to ensure the smooth flow of information between the AD, the Banking Supervision Department (BSD), the Monetary Operations Department (MOD), the Foreign Exchange Department (FED), and the MSID. There is no centralized database. The data is shared among departments through e-mail.
The AD collects balance sheets data from commercial banks, while the BSD collects supervisory data. Money market interest rates related to government securities are collected by the MOD. Statistics on international reserves and Foreign Exchange Markets data are collected by the FED. The Monetary Policy Division (MPD) of the MRMPD compiles analytical accounts of the monetary authorities, commercial banks, and the depository corporations survey, which are then published by the MSID. In conclusion, the collection system within the NBG is highly disaggregated, having several departments involved in the process, which may prevent gains derived from a more centralized collection and compilation system. In particular, the MPD compiles analytical accounts of the monetary authorities, commercial banks, and the depository corporations survey for domestic dissemination and to report to the European II Department of the IMF, while the MSID is responsible for compiling information of the same nature (but with more detail) to report to the Statistics Department of the IMF. This arrangement does not encourage the resolution of methodological differences between the two sets of data.
0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only
The MSID does not disclose confidential data of individual institutions or transactions. Article 21 of the NBG’s Organic Law forbids the publication or disclosure by the NBG of any confidential information having a private and personal nature to an official authority or private body (paragraph 1). It also states that the above mentioned persons may disclose confidential information only to the Chamber of Control of Georgia (paragraph 2). Information on the operations of economic entities may be disclosed only pursuant to a proper court decision (paragraph 3).
Only authorized staff members of the NBG have access to 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 to prevent individual disclosure. Access to the internal database is limited to 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 reporting
Article 56 of the NBG’s Organic Law provides the legal basis for the collection of statistical information that supports the compilation of monetary and financial statistics. The NBG is authorized to request directly, and to collect statistical information on the financial system and other information necessary for the surveillance of developments in the economy from depository corporations, other financial corporations, and ministries. The NBG is also authorized to investigate and supervise the accuracy of the statistical information provided by the concerned parties, and to request additional information if needed. In line with Article 29 (paragraph 1) of the LCB, the NBG has determined in circulars and guidelines that reporting forms are required to be submitted to the NBG no later than five working days after the end of the reporting period. According to Article 30 of the LCB, failure to comply with the abovementioned reporting requirements is punishable by a fine and the NBG may suspend or restrict institutions’ operations in the event of nonresponse.
0.2 Resources
0.2.1 Staff, financial, and computing resources are commensurate with statistical programs of the agency
The MPD, which compiles analytical accounts of the monetary authorities, commercial banks and the depository corporations survey has a total of five staff, two of whom focus on compilation of monetary statistics.
The MSID, which is responsible for the compilation of the MFS requested by international organizations such as the IMF, the compilation of other MFS (detailed statistics on deposits and loans, interest rates statistics, exchange rate statistics, international investment position of credit institutions, credit cards statistics) and for the dissemination of MFS produced by all units within the NBG, has a total of eight staff, who are professionals exclusively devoted to the compilation of statistics. Three people focus on statistical concepts and methodology and the improvement of coverage and accuracy of MFS.
Staff of the MSID and two specialists of the MPD devoted to the compilation of MFS have university degrees in economics or statistics. The head of the MSID holds a Ph.D. in economics. Besides the on-the-job training, staff are given the opportunity to participate in courses conducted by international organizations, such as the IMF, and in seminars offered by central banks, such as the Deutsche Bundesbank, Bank of England, Banque de France, and Central Bank of Russia. Staff turnover is not high.
Computer resources utilized in the collection and compilation of MFS are adequate. The data collection system is highly computerized. All reporting commercial banks submit their returns through e-mail and are entered into a compilation system that performs validation checks on the data before the next stage in the production cycle. There are currently no budgetary constraints impeding data collection and compilation activities.
0.2.2 Measures to ensure efficient use of resources are implemented
MRMPD 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 NBG are subject to budget considerations and performance assessments. Budgeting of the NBG is done annually by the Board of the NBG every December. Departments identify their budget needs and make proposals to the Board. Budget allocations are made for each department by the Board. The AD of the NBG measures on a quarterly basis the cost-effectiveness of each unit. Reviews are conducted regularly by the AD in order to improve the work within each unit. New technology for data processing and dissemination is always tested by computer and system analysis experts.
0.3 Quality Awareness
0.3.1 Processes are in place to focus on quality
The NBG recognizes that official statistics must have the confidence of their users, and exercises quality control at every stage of data production and dissemination, although no explicit measures are undertaken to focus on quality overall. The MSID verifies that data reporting practices followed by the banks are consistent with the regulations, and has systems and procedures in place to ensure quality in the compilation process. All levels of the MSID participate actively in the review of data prior to publication.
The source data submitted by the reporting institutions to the MSID are crosschecked for accuracy, and any discrepancies are investigated. Data reporting practices are set by the MSID in line with the sector classification in the chart of accounts for commercial banks. Validation procedures for assessing the plausibility or reasonableness of reported data are undertaken both automatically and visually, on a bank-by-bank basis. The MSID consults with the reporting institutions to verify the data for possible misclassifications.
An external auditing company audits the financial statements of the NBG.
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 monitoring of statistics is monitored through crosschecks; for problems in collection, reporting institutions are informed and guided by the staff of the MSID.
No formal surveys of users are undertaken; however, users can contact the MSID, directly or through NBG’s website, and responses are provided to all requests and questions.
There is no other body outside the MRMPD that provides guidance on the quality of monetary statistics, and on strategies for improving data production.
0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs
The MSID monitors developments and changes in financial markets, and works closely on improving the methodological soundness of the data to take into account new initiatives and developments in the financial system. The MSID is currently considering and analyzing the inclusion of nonbank depository corporations and other financial institutions, such as insurance companies and pension funds, into monetary statistics.
There is a wide recognition of the tradeoffs between data quality and timeliness. The production of monetary statistics is expected to be fully automated in the nearest future. A new system for monetary data compilation and processing is in a testing stage and will include 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. To accommodate this in the event of delays in reporting, some data may be published as provisional.
Informal meetings are held periodically with policy makers and other data users to identify any emerging data requirements. The NBG also invites user comments on the relevance and usefulness of the monetary statistics via its website.
1. Integrity
1.1 Professionalism
1.1.1 Statistics are compiled on an impartial basis
The statutory provisions under which the NBG compiles monetary statistics are adequate to support its independence in conducting these functions. In this regard, Article 3 (paragraph 1) of the NBG Law stipulates that the NBG shall be independent in its operations. No legislative or executive body shall have the right to interfere in its activities, except in cases specified 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 State Department for Statistics), other central banks, and international organizations.
1.1.2 Choices of sources and statistical techniques are formed solely by statistical considerations
The compilation of monetary statistics is based on the balance sheets of the reporting institutions. The depository corporations survey includes the NBG and all commercial banks operating in the country, so there is no possibility to alter the results by changing the source of information or the size of the sample. The NBG and commercial banks utilize a common chart of accounts that conforms to international accounting standards, further minimizing the chances of misclassification.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics
The MSID of the NBG comments on erroneous interpretation of its statistics if deemed necessary. The MSID seeks to prevent misinterpretation or misuse of monetary statistics by providing explanatory notes in its publications and website.
1.2 Transparency
1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public
The NBG Law, which constitutes the base for the compilation and dissemination of monetary data is available on the NBG website and in hardcopy on request.
Statistical publications provide e-mail addresses and telephone numbers of the respective NBG department from which additional information can be provided.
1.2.2 Internal governmental access to statistics prior to their release is publicly identified
Following the approval of the data by the MRMPD, a limited number of senior NBG staff have access to data prior to their publication.
Governmental agencies, such as the Financial-Budgetary Committee of the Georgian Parliament, Ministry of Finance, and State Department for Statistics (SDS) have access to monetary statistics prior to their release to the public. The internal access is not made public (in the dissemination media) in terms of who has access and at what time in the compilation process access is given.
1.2.3 Products of statistical agencies/units are clearly identified as such
The MSID of the NBG is identified as the source of the monetary statistics published in the Monetary and Banking Statistics Bulletin (MBSB), which is published quarterly providing monthly information. The NBG does not formally explicitly request attribution when its statistics are used or reproduced.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques
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. Advance notice is given only in the case of major changes.
1.3 Ethical Standards
1.3.1 Guidelines for staff behavior are in place and are well known to the staff
The Code of Conduct for the Staff of the NBG provides broad ethical guidelines for employees of the NBG. New staff members are informed about the guidelines.
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 analytical framework used by the NBG in compiling sectoral accounts of the central bank and of the other depository corporations reflects concepts and principles that are based on the IMF’s Monetary and Financial Statistics Manual (MFSM). The depository corporations survey is derived by consolidating the accounts of the central bank and the other depository corporations, providing an analytical presentation of the intermediation role of the depository corporations. The monetary and credit aggregates identified in the depository corporations survey are (i) money supply M1 (currency in circulation and demand deposits); (ii) M2 (M1 plus time and savings deposits); and (iii) broad money or M3 (M2 plus residents’ foreign exchange deposits). Other aggregates identified in the depository corporations survey are (i) foreign assets (net); (ii) domestic credit (disaggregated by claims on central government (net), claims on local governments, claims on public nonfinancial corporations, claims on other resident sectors and claims on other financial corporations); and (iii) other items (net).
2.2 Scope
2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices
The depository corporations sector of Georgia comprises 25 commercial banks and two branches/subsidiaries of foreign banks operating in Georgia. According to the LCB of 1996, “Bank” means a legal entity licensed by the NBG that attracts deposits and uses them on its own behalf to conduct banking activities pursuant to applicable law. The institutional coverage of monetary statistics includes the banks’ domestic headquarters and their domestic branches, and domestic branches of foreign banks operating in Georgia. However, it does not include other depository corporations that are not banks according to the previous definition. Data on these nonbank depository corporations will be collected by the NBG in the near future through a department recently created within the NBG to supervise their activities. Currently, the size of these institutions is not significant if compared to the commercial banks.
Data on other financial corporations, such as insurance companies and pension funds, which are considered to be significant, are not covered in a financial corporations survey.
2.3 Classification/Sectorization
2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices
The NBG 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 Balance of Payments Manual, fifth edition (BPM5), 1993 SNA, and MFSM.
The sectorization of the domestic economy by the NBG 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 subsectors: (i) central bank; (ii) other depository corporations; (iii) other financial corporations; (iv) central government; (v) state and local government; (vi) public nonfinancial corporations; and (vii) other resident sectors.
In the monetary statistics compiled by the NBG, the following sectoral groupings of resident institutional units are distinguished: (i) central government; (ii) local governments; (iii) central bank; (iv) depository corporations (no public banks); (v) foreign depository corporations; (vi) other nonbank financial institutions; (vii) nonfinancial public enterprises; and (viii) other sectors. However, owing to their relatively small size, some financial instruments are not fully sectorized, such as securities other than shares and other equity, or even not identified, such as financial derivatives. In addition, estimation of accrual interest by counterpart sector for some financial instruments, where this information is not available, is not carried out.
2.4 Basis for Recording
2.4.1 Prices used to value flows and stocks reflect actual or expected cash payments
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.
The NBG’s financial statements are prepared in accordance with the related Georgian Legislation and requirements of the NBG Law, which is based on international accounting standards since 2001. Depository corporations record securities in line with the following procedures: (i) securities held to maturity are recorded at face value with discount/premium shown on the counter account; (ii) securities held for trading—at market prices; and (iii) securities held for sale—the same way as securities held to maturity but at the same time subject to revaluation.
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 sheet.
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. In the monetary statistics of Georgia, foreign assets and liabilities are recorded at the official exchange rate set at the Tbilisi Interbank Currency Exchange on a daily basis.
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. In Georgia, banks provide financial information on transactions for deposits and loans, which are largely the most important financial instruments (securities other than shares account for only 4.3 percent of total assets in April 2002). The NBG does not derive for monetary statistics purposes transactions from stock data.
2.4.2 Recording is done on an accruals 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 Georgia require interest to be recorded on a monthly basis. Interest arrears are recorded separately when past due.
The sectoral breakdown of accrued interests is not fully in line with the MFSM, since accrued interest has only been partially sectorized. Thus, values of accrued interest on loans and advances to the general government, public nonfinancial corporations, other depository corporations and other residents—as well as on their deposits—are separately identifiable from the chart of accounts. At the same time, values of accrued interest on loans and advances to—and the deposits of—various other sectors—namely, republican government, local government, resident and nonresident banks, other financial corporations, and private sector—are not separately identified. Accrued interest should be distinguished by the instrument, as well as by sector.
In general, transactions are recorded at the time the transaction occurs.
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 NBG, banks, and other financial institutions, 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 central government (net)” in the monetary and banking surveys) are also shown with the underlying gross data.
For the compilation of the sectoral balance sheets of the NBG and depository corporations, the data on financial assets and liabilities are aggregated into major categories (e.g., claims classified by debtors and deposits classified by creditors). The depository corporations survey is obtained by canceling out all outstanding claims and liabilities between the NBG and banks and between the banks.
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 sectoral accounts for the monetary authorities are the accounting records (balance sheets) of the NBG prepared by the AD on a daily basis. These reports are generated by an electronic general ledger system based on complete reporting. Source transactions are captured and the reports are generated from a predetermined classification of each account.
The basic data sources for the commercial banks are the balance sheets received every ten days. Items in these returns are derived from accounting records of commercial banks. The incoming data are continuously reviewed by the AD to ensure full institutional coverage. The reporting forms capture in principle the full range of financial instruments and economic sectors. They provide sufficient detail overall to enable the classification of all financial instruments and economic sectors, as defined in the MFSM.
3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required
The depository corporations survey is based on complete reporting by depository corporations. There is an ongoing effort at the NBG to use data sources that reasonably approximate the definitions, scope, classifications, time of recording, and valuation required to compile sound monetary statistics.
After the introduction of a new chart of accounts for commercial banks in 2001, which identifies most of the sectoral breakdown recommended by the MFSM, the NBG has been able to implement most of this sectorization scheme. Consequently, current monetary statistics show a distribution of credit by republican government, local government, nonfinancial public corporations, other nonfinancial corporations, and individuals. However, it is unclear where insurance companies, which constitute a rapidly growing subdivision of Georgia’s other financial corporations sector, are classified since the chart of accounts does not identify them separately. Statistical information on the sectors nonfinancial private corporations and households are only available for deposits held with, and loans granted by, banks. Source data do not provide information on financial derivatives and the full sectorization of less important financial instruments for Georgia, such as securities other than shares and shares and other equity.
3.1.3 Source data are timely
The data collection system allows the timely compilation of monetary statistics, which are released in the NBG’s quarterly MBSB (hard copy) and monthly Bulletin (electronic version on website). Core statistical data comprising the ten-day statement and selected liability items of the NBG, money supply, and selected balance sheet items of the banking system are processed within seven working days after the reference date, which are not released for public use.
The accounting records of the NBG are available on a daily basis, and provided by the AD to the MPD via e-mail. The returns of the banks are submitted on a ten-day basis to the AD and on a monthly basis to the MSID. The banks are required to submit via e-mail ten-day data on exchange market data or electronic transfers or remittances to the MSID. Monthly returns on loans and deposits are also submitted by banks to the MSID via e-mail.
The MSID and the AD conduct follow-ups with late respondents via telephone in order to collect information to meet publication deadlines.
3.2 Statistical Technique
3.2.1 Data compilation employs sound statistical techniques
Reporting forms are easy to complete for respondents (using MS Excel format), and they include several checks within the tables. New reporting forms are always pilot-tested with several respondents prior to their implementation. 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.
3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques
In cases where no return is received from a bank, the previous month’s balance sheet data are carried forward to calculate preliminary monetary aggregates and credit extended by the banking sector until a new return has been officially received and processed. Adjustments for missing observations are documented. The NBG does not calculate seasonally adjusted monetary data.
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 of the NBG are solved between the AD and the MSID. Bank reporting forms are occasionally revised to reflect changes in the presentation of accounting records, sector reclassifications, and the needs of compilers. The MSID is authorized to make revisions only in the reporting form that has been primarily designed to collect statistical information for the compilation of monetary statistics. If necessary, the MSID conducts meetings with the AD, which has the authority to introduce changes to the chart of accounts for commercial banks.
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 submitted by banks is checked against secondary data sources, such as statistical information on the banking system published by the MSID. In general, however, most queries concerning monetary statistics are resolved by the AD and the MSID directly with the banks by telephone or e-mail.
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated
The AD and the MSID investigate statistical discrepancies and determine 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.
3.5 Revision Studies
3.5.1 Studies and analysis of revisions are carried out routinely and used to inform statistical processes
Studies and analyses of revisions in source data, methodology, and compilation techniques are seldom done, although deemed not necessary owing to the high quality of the source data. Documentation on revisions, therefore, is not always available. Investigation results and adjustments made in a revision process are taken into account in compiling data for the subsequent periods.
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 policy departments, ministries, or representatives from the private sector or academia. However, the MSID, which is responsible for monetary and financial statistics, encourages and receives comments from users regularly.
4.2 Timeliness and periodicity
4.2.1 Timeliness follows dissemination standards
The analytical accounts of the central bank are prepared daily with a one-day delay, and within one week for the last day of the month. The data on banks, which cover all the prescribed components, are disseminated within one month after the reference period. Georgia is planning to join the IMF’s GDDS standards for data dissemination.
4.2.2 Periodicity follows dissemination standards
The analytical accounts of the central bank and of the banking sector are disseminated on a monthly basis.
4.3 Consistency
4.3.1 Statistics are consistent with the dataset
The central bank’s and commercial banks’ records for claims on, and liabilities to, each other show some discrepancies because of differences in the time of recording financial transactions. A reconciliation of stock and flow data is not possible, because flow data are not compiled for monetary statistics.
4.3.2 Statistics are consistent or reconcilable over a reasonable period of time
Consistent time series are available in electronic format on the NBG website. When changes in source data, methodology, and statistical techniques are introduced, 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 MSID in the MBSB.
4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks
The MSID periodically checks the consistency of the monetary statistics with balance of payments statistics. Consistency checks between government finance statistics and monetary statistics are conducted occasionally.
4.4 Revision Policy and Practice
4.4.1 Revisions follow a regular, well-established and transparent schedule
Usually monthly and ten-day data of commercial banks are final. In practice, revisions are rare and insignificant. However, banks may send revisions in their next return. Monthly data of the NBG are final. Revisions due to important changes in statistical methodology are explained in the related publication.
4.4.2 Preliminary data are clearly identified
Users are alerted when the initially published data for banks are preliminary (data are marked with “*”) and subject to revision. The revised data are disseminated in the same way, and at the same level of detail, as the preliminary data.
4.4.3 Studies and analyses of revisions are made public (see also 3.5.1)
Only major differences between preliminary and revised data are explained in a footnote.
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 NBG facilitates the interpretation of the data. The MBSB contains tables presenting data in a clear and user friendly layout. Estimates are produced only for internal analytical purposes, and are not disseminated.
5.1.2 Dissemination media and formats are adequate
Monthly monetary data are disseminated in hardcopy on a quarterly basis and monthly in the website of the NBG to meet the needs of data users. Upon request, historical time series are also disseminated in the electronic formats. The dissemination format (Acrobat files) is not user friendly. However, Excel files are sent to users on request.
The web page of the NBG is the only means of dissemination of monthly MFS in those months where the MBSB is not published in hardcopy. Therefore, the electronic dissemination through the web is the only dissemination media in two out of every three months.
5.1.3 Statistics are released on a pre-announced schedule
Monetary statistics are released according to the NBG’s special resolution no.112 of May 14, 1999. There is no advance release calendar for monetary statistics. A notice to this effect is published in the quarterly MBSB.
5.1.4 Statistics are made available to all users at the same time
Data are released simultaneously to all interested users. However, governmental agencies, such as the Financial-Budgetary Committee of the Georgian Parliament, Ministry of Finance, and SDS have access to monetary statistics prior to their release to the public.
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 when authorized by senior staff of the MSID. However, the availability and terms and conditions of this service are not made public. If there is substantial demand, unpublished data may be disseminated in publications with the permission of the Vice-President, who is ultimately responsible for statistics.
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 monetary statistics’ metadata documentation, including the concepts, classifications, data sources, characteristics, and definitions is not available. Development of the metadata documentation, however, is under way.
5.2.2 Levels of detail are adapted to the needs of the intended audience
Draft metadata are being prepared in accordance with IMF recommendations for GDDS participating countries.
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 statistics users. However, not all statistical releases identify specific individuals. The phone numbers and e-mail addresses of the NBG’s heads of departments and other specialists can be found in the “Contacts” section of the NBG’s website. No brochures have been developed to educate users. Names of people responsible for the preparation of published statistics, as well as contact e-mails are cited in the of MBSB.
5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available
Main statistical publications, documents, and other services are free of charge. A catalogue of publications is not available in hardcopy, although the NBG’s website lists the publications that are available to the public. Subscriptions are done by the MSID. Periodic publications are disseminated on the website of the NBG. Subscription to hard copies for certain publications such as the journal Bank are not free.
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Monetary Statistics
(Compiling Agency: National Bank of Georgia)
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Monetary Statistics
(Compiling Agency: National Bank of Georgia)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observe; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Compilation of monetary and financial statistics for surveillance and publication purposes is conducted separately by two divisions within the NBG. | |||||
| 0.2 | Resources | X | ||||||
| 0.3 | Quality awareness | X | No formal user surveys are undertaken to obtain feedback on data quality issues. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | The internal access is not made public in the dissemination media, although it is evident in the law. | |||||
| 1.3 | Ethical standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | Nonbank depository corporations are not covered by MFS, although are not very significant. | Collect information on the nonbank depository corporations by March 2003. | ||||
| 2.3 | Classification/Sectorization | X | Accrued interest not sectorized. | |||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | ||||||
| 3.2 | Statistical techniques | X | ||||||
| 3.3 | Assessment and validation of source data | X | ||||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | ||||||
| 3.5 | Revision studies | X | Revision studies are seldom carried out. | |||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | Lack of established process of consultation with users. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | ||||||
| 4.4 | Revision policy and practice | X | ||||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | The dissemination format (Acrobat files) is not user friendly. There is no advanced release calendar. | |||||
| 5.2 | Metadata accessibility | X | No documentation on metadata exists. | |||||
| 5.3 | Assistance to users | X | ||||||
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Monetary Statistics
(Compiling Agency: National Bank of Georgia)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observe; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Compilation of monetary and financial statistics for surveillance and publication purposes is conducted separately by two divisions within the NBG. | |||||
| 0.2 | Resources | X | ||||||
| 0.3 | Quality awareness | X | No formal user surveys are undertaken to obtain feedback on data quality issues. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | The internal access is not made public in the dissemination media, although it is evident in the law. | |||||
| 1.3 | Ethical standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | Nonbank depository corporations are not covered by MFS, although are not very significant. | Collect information on the nonbank depository corporations by March 2003. | ||||
| 2.3 | Classification/Sectorization | X | Accrued interest not sectorized. | |||||
| 2.4 | Basis for recording | X | ||||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | ||||||
| 3.2 | Statistical techniques | X | ||||||
| 3.3 | Assessment and validation of source data | X | ||||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | ||||||
| 3.5 | Revision studies | X | Revision studies are seldom carried out. | |||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | Lack of established process of consultation with users. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | ||||||
| 4.4 | Revision policy and practice | X | ||||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | The dissemination format (Acrobat files) is not user friendly. There is no advanced release calendar. | |||||
| 5.2 | Metadata accessibility | X | No documentation on metadata exists. | |||||
| 5.3 | Assistance to users | X | ||||||
VI. Balance of Payments 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 State Department of Statistics (SDS) is an independent government institution operating under the Law on Statistics No. 1071 of November 12, 1997, and supplemented by an amendment in June 1999. The Law on Statistics authorizes the SDS to collect, compile and disseminate official statistics data about the socio-economic development of Georgia. The Law specifies that while government units and agencies may set up specialized statistical units and may undertake their own statistical surveys, these shall operate under the methodological guidance of the SDS. Other provisions of the Law ensure the consistency of methodology, comparability of statistics to international standards, sharing of information with other countries, and dissemination.
The compilation and dissemination of balance of payments statistics are mentioned explicitly in the Regulations for the SDS No. 92 of February 28, 1998, approved by the President of Georgia. Article 12 of the Regulation provides that the SDS is the responsible agency for compiling the balance of payments statistics. In addition to that, the President of Georgia has approved a State Program for Development of Statistics for 2001–2005. The compilation and dissemination of balance of payments statistics are stated in the State Program.
Organizationally, the SDS consists of three tiers, the headquarters, thirteen regional offices and several local offices that are directly under the jurisdiction of the regional offices. The regional and local offices not only serve as conduits through which nationwide statistical surveys are administered by the headquarters but also collect statistics needed by regional administrative bodies as well as disseminate statistics of regional interest. The heads of some of the regional offices, such as that of the Administrative Region of Adjara are appointed by the head of the region with the consent of the Chairman of the SDS. In other regions, the local governors could exert considerable influence on the appointment of personnel in the regional and local offices.
The regional offices are thus answerable to both the regional administrative bodies and to the SDS headquarters. Under these arrangements, the statistics they collect are intended to meet needs at both the regional and national level. In practice, this may result in a situation in which the collection of statistics needed for national purposes (such as balance of payments statistics) is assigned a lower priority at the regional level than the collection of statistics needed at the regional level and not at the national level. This situation appears to suggest that the SDS lacks authority to set the priorities of the regional offices, and that the collection of balance of payments statistics has suffered as a result.
The dual allegiance of the regional offices combined with the distance from the headquarters and poor communication facilities could further weaken the ties between the headquarters and the regions. Such conditions could have an adverse effect on the efficacy of one of the main functions of the regional and local offices, such as the administration of surveys on behalf of the headquarters.
0.1.2 Data sharing and coordination among data producing agencies are adequate
Article 11 of the Law guarantees the SDS access to data produced by legal entities, including the data produced by government ministries and the NBG. Important areas of statistics are covered by other agencies, such as the NBG, which compiles monetary and financial statistics; the MOF, which is responsible for compiling government finance statistics; and the State Department of Customs (SDC), which compiles data on imports and exports of goods. The Law gives the SDS primary and coordinating roles in the development of the country’s statistical program.
There are written agreements between the SDS and the MOF, the NBG and the SDC covering the sharing of macroeconomic data, and the SDS management and staff are broadly satisfied with the level of cooperation they receive from these agencies. However, the agreement with the SDS requires only that the SDC provide a computer file of its trade statistics database, with no requirement for quality control by the SDC or that the SDC follow international standards for compiling trade statistics. The result is that the SDC Balance of Payments Division (BOPD) is obliged to commit resources to checking the SDC database for errors and inconsistencies (which should have been handled by the SDC software) and there are major gaps in coverage, valuation, and classification in the SDC database, in which there are significant deviations from international standards.
Apart from balance of payments estimates compiled for internal purposes by the NBG, there appears to be no evidence of major duplication of statistical effort among the various agencies. No regular contacts with other statistics producing agencies are maintained to take into account the respondent burden.
0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only
Confidentiality of the individual data reported to the SDS is guaranteed under Articles 7, 12, and 17 of the Law. The Law does not provide penalties for disclosure of individual data by staff. The SDS is planning a new amendment to the Law with a provision for penalties for disclosure. The confidentiality aspect is potentially compromised as a result of the provisions of the Anti-Monopoly Law, by which the Anti-Monopoly Department of the Ministry of Economy, Industry and Trade can request confidential data from the SDS. The conflict between the two Laws has not been resolved. In practice, there have been no breaches of the confidentiality of individual balance of payments data.
Staff are required to keep individual data confidential, and they are also required to sign a declaration on joining the SDS that confirms awareness of this provision. Access to individual data is restricted to the appropriate staff. There are no special aggregation rules to ensure that unintended disclosure does not occur in SDS publications. Senior staff review the data before dissemination to make sure that confidential data are not disseminated.
0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage reporting
According to Article 11 of the Law, the SDS is authorized to request the information it deems necessary from all legal public and private institutions, as well as from individuals. All requested respondents must furnish information accurately in the format and time period determined by the SDS. The June 1999 amendment of the Law provides some penalties for nonreporting, but they are not considered effective by the SDS. These penalties were mostly applied to newly registered legal entities for noncompliance with the required registration in the SDS Business Register. In practice, they were not applied for nonresponse to statistical surveys.
Because there are few statistical surveys of balance of payments statistics (currently confined to a survey of transportation services and a survey of inward foreign direct investment (FDI)), the BOPD has little experience in conducting surveys. Response to these surveys has been seriously constrained by the reluctance of SDS to use its legal authority to mandate respondents to complete them, and the BOPD has been unsuccessful in conducting statistical surveys on a voluntary basis.
0.2 Resources
0.2.1 Staff, financial, and computing resources are commensurate with statistical programs of the agency
There are eight staff members in the BOPD. The BOPD has suffered from heavy staff turnover; the loss of institutional memory caused by staff turnover has led to a deterioration in the quality of data produced. In the last seven years, there have been nine different heads of the BOPD either in an acting or permanent basis. Some of them had left for better paying jobs in other government agencies or the private sector while others were re-assigned to other divisions at the SDS. More recently, there has been some increase in resources. However, the inadequate remuneration of employees continues to be the major constraint preventing the retention of a core contingent of capable and trained balance of payments staff.
The BOPD is not sufficiently equipped with personal computers; of the five computers in the department, only two are of functional value. The lack of computers is further aggravated by the disproportionate use of computer time to service user requests, especially for trade data. Renumeration is extremely low and uncompetitive causing major problems in attracting and retaining suitable staff. It has been estimated that SDS salaries have fallen to about 7 percent of the 1998 levels in real terms.
0.2.2 Measures to ensure efficient use of resources are implemented
Internal processes exist within the SDS to measure overall resources used to compile statistics. Periodic reviews of budgeting procedures are undertaken to ensure that scarce resources are best employed in addressing major data problems or meeting new data priorities. However, the impact of these on the efficient use of resources in the collection and compilation of balance of payments statistics is not clear. Failure to use the legal mandate of the SDS to conduct balance of payments surveys has meant that resources have been unnecessarily applied in trying to conduct balance of payments surveys on a voluntary basis.
0.3 Quality Awareness
0.3.1 Processes are in place to focus on quality
Senior management is sensitive to the dimensions of data quality: integrity, methodological soundness, accuracy and reliability, serviceability, and accessibility. In order to ensure quality, the organizational structure of the SDS includes a Statistical Research Institute and an Institute for Informatics and Telecommunications. The Statistical Institute is responsible for developing methodology and software solutions for statistical tasks. The Institute for Informatics and Telecommunications is responsible for development and implementation of information and analytical systems of the national statistics and harmonization of classification systems. A Scientific and Advisory Council was established in the SDS in 1997. Apart from the SDS staff, specialists from the Ministry of Economy, Industry and Trade, the Tbilisi University, the National Bank of Georgia, and the Institute of Economics are, with others, members of the Council. The Council presents assessments and recommendations on the State Program of Statistical Activities, statistical surveys, the structure of the SDS, broad directions of development in the area of statistics and on training and retraining of staff.
However, these initiatives do not appear to have contributed to a discussion of quality awareness in balance of payments statistics.
0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics
The BOPD has identified problems at the various stages of data collection, but has not been able to resolve some of the major ones, such as difficulties associated with the conducting of balance of payments surveys on a voluntary basis. The BOPD has not established processes for the identification of problems that arise during the processing and dissemination of data.
Since 1998, the SDS has held meetings with data users to discuss the relevance of statistics. As a result of these initiatives, the SDS is aware of user dissatisfaction with the quality of balance of payments statistics, but has been constrained in its response by lack of resources. The user survey conducted by the mission indicated that there remains widespread user concern about the quality of balance of payments statistics.
0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs
There is recognition by senior management that there is a trade-off between the timeliness and the accuracy of the data. However, as the rather limited data sources available for balance of payments compilation are monthly or quarterly, this trade-off does not currently arise in the compilation of balance of payments statistics. If more comprehensive data sources such as annual statistical surveys are introduced, tradeoffs within quality will have to be addressed as resources are applied to the improved quality of annual data.
1. Integrity
1.1 Professionalism
1.1.1 Statistics are compiled on an impartial basis
The Law on Statistics underscores the importance of the professional independence of the SDS and identifies the SDS as an independent data producing agency. Professional competency plays an important role in the promotion practices in the SDS. Staff are encouraged to present seminars or share information on the work they have done, and, as opportunities arise, are sent abroad for training. Professionalism is promoted by the dissemination of methodological papers on balance of payments statistics.
1.1.2 Choices of sources and statistical techniques are formed solely by statistical considerations
The SDS is independent in its determination of statistical methods and is required to coordinate the methods used by other statistics producing agencies. There has been no instance of ministerial interference in the choice of the statistical sources and methods. The SDS is free to determine the appropriate data sources.
1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics
The SDS provides regular press briefings/technical commentary/explanatory materials in connection with the release of macroeconomic statistics. The media are closely followed for any misuse or misinterpretation of data. Informal discussions take place with data users and suppliers on the quality of data produced.
1.2 Transparency
1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public
The newly created web page of the SDS reproduces information on the terms and conditions under which data are collected, compiled, and disseminated. There is also summary information about the confidentiality of the individual responses. Statistics publications identify information about the SDS but not about its products.
The obligation to report data and the confidentiality provisions are spelled out in the survey forms used by the SDS. However, the survey forms indicate only some of the terms and conditions, such as the confidentiality provisions under which statistics are collected.
1.2.2 Internal governmental access to statistics prior to their release is publicly identified
There is no information made public on who has access to data prior to the date of the press release or relevant publication. It appears that, once data are finalized, they are sent to government and other privileged users before the date of the press release or relevant publication. This dissemination practice (who, what, and when) is not documented or published.
1.2.3 Products of statistical agencies/units are clearly identified as such
Products of the SDS are clearly identified by its name and logo. The balance of payments tables disseminated in the NBG’s publications identify the SDS as the source. However, the SDS does not mention in its publications that attribution should be made to it when its statistics are used or reproduced.
1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques
Users are not alerted in advance or at the time that major changes to balance of payments methodology, source data, and statistical techniques are made.
1.3 Ethical Standards
1.3.1 Guidelines for staff behavior are in place and are well known to the staff
Ethical rules are laid down in the Code of Conduct for Civil Servants. New staff are made aware of the Code and the mission of the SDS when they join the department.
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
Balance of payment statistics are compiled broadly in accordance with the guidelines set out in the IMF’s BPM5.
2.2 Scope
2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices
With one exception, the scope of balance of payments statistics is fully consistent with internationally accepted standards. The exception is the exclusion of reinvested earnings from the definition of direct investment income.
The balance of payments covers the economic territory of the country inclusive of Abkhazia and the South Ossetia Regions, and the interpretation of residence of entities and individuals follows BPM5.
2.3 Classification/Sectorization
2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices
The classification/sectorization system in Georgia’s presentation is broadly in accordance with the guidelines according to BPM5.
The classification of the current account comprises goods, services, income, and current transfers account. The sub-classification for goods does not separately identify goods for processing, repairs on goods, and nonmonetary gold. Transportation services comprise transportation of goods (including transit trade), passengers, and ancillary transportation services. The SDS classification of other services include travel, communications, freight insurance, business services, and government services; and exclude construction, nonfreight insurance, financial, computer and information, royalties and license fees, personal, cultural, and recreational services. Income comprises compensation of employees, direct investment income, portfolio income, and other investment income, which are each identified separately. Current transfers comprise, without separate identification, grants in cash and goods received by the government as part of official development assistance from foreign governments, workers’ remittances, withholding taxes, and contributions to international organizations.
The classification of the capital account comprises migrants’ transfers. Grants made in cash and goods as part of official development assistance for expenditures of a capital nature are not identified separately and are included with current transfers
The classification of the financial account comprises direct investment, portfolio investment, other investment, and reserve assets. Transactions related to direct investment are identified separately for direct investment in Georgia and abroad. However, there is no subclassification by instrument, such as equity capital, reinvested earnings, and other capital. Portfolio investment is classified only broadly into assets and liabilities without further breakdown by instrument or sector. Transactions in other investments are shown separately for assets and liabilities with subclassifications for instrument or sector. Reserve assets comprise monetary gold, special drawing rights, reserve position in the IMF, and foreign assets in the form of currency, deposits, and securities. Four sectors are identified, namely the monetary authorities, general government, banks, and other sectors. Other sectors comprise without separate identification, nonbank financial institutions, enterprises, and individuals.
2.4 Basis for Recording
2.4.1 Prices used to value flows and stocks reflect actual or expected cash payments
Transactions are valued at market prices. Data are collected either in Georgian Lari or the U.S. Dollar and currency conversion, when necessary, takes place at monthly or quarterly period average exchange rates according to the periodicity of the data sources. Actual rates are used when available. When flows are derived from stock positions as in the case of foreign exchange assets of the reserves or the assets and liabilities of commercial banks, adjustments are made to remove the effects of exchange rate fluctuations. In some instances, the rules of currency conversion have not followed BPM5 guidelines.
2.4.2 Recording is done on an accrual basis
Transactions are generally recorded on an accrual basis.
2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices
Current account items are recorded on a gross basis, while financial account items are recorded on a net basis, separately for the individual asset and liability components.
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 sources available for balance of payments compilation are inadequate. Potential data sources are not kept under continuous review, and very little attempt is made to monitor current balance of payments developments. It is only very recently that the BOPD has started monitoring the financial press for information on international transactions.
The data sources comprise mainly administrative data (data collected by other government agencies for their own purposes) and statistical surveys. The latter comprise a survey of transportation services and a survey of inward FDI. The source data for the various balance of payments data categories are as follows:
Goods: Data on trade in goods provided by the SDC are based on the Single Administrative Document (SAD) as the basis for recording imports and exports of goods. The SAD includes information on currency and exchange rates, mode and terms of transportation, and valuation based on both c.i.f. and f.o.b. basis. The SDC does not collect data on goods for processing, repairs on goods, procurement of goods in ports by carriers, nonmonetary gold, or imports of gas, and imports and exports of electricity. The SDC has not fulfilled commitments it has made to SDS to provide information and revised trade data on smuggled goods, such as cigarettes, oil products, alcoholic beverages, and other consumer commodities.
Transportation services: Transportation credits are derived from survey data and data supplied by pipeline companies. The survey is limited to public enterprises. Operators of private sector vehicles (trucks, vans, and long distance passenger buses), who may be either residents or nonresidents, have not been identified. While some estimates are made for these activities, they are not considered to be of good quality. Due to its geographical position, earnings from transit trade are an important constituent of transportation credit. Estimates for transit trade derived from data supplied by the railways, the pipeline and oil companies are of good quality. Data for other transportation services are not complete as data have not been obtained from some of the providers of these services.
Travel services: Travel credits have been estimated on the basis of the number of tourist arrivals and estimates made for the average expenditure of tourists. Average expenditure of tourists has been estimated from various sources such as interviews carried out at airports by the BOPD estimates based on a Technical Assistance for the Commonwealth of Independent States (TACIS)-assisted sample survey carried out in 1999 and 2000, and from survey data. All principal airports, seaports, railway stations, and border crossing points in Georgia were covered. Travel debits are calculated from data on travel abroad by residents of Georgia.
Communication services: Data for communication services are obtained from the Ministry of Communications.
Insurance services: No data sources have been developed for insurance services.
Other business services: There are some limited data sources provided by FDI enterprises.
Government services n.i.e.: Data are taken from MOF sources and a survey of foreign embassies in Georgia was conducted in 1997.
Other services: No data sources have been developed for other services (such as nonfreight insurance, construction services, royalties and license fees, financial services, computer and information services, personal, cultural, and recreational services).
Compensation of employees: The only data source is numbers of short-term workers abroad, broken down by host country.
Direct investment income: Direct investment debits are estimated from some limited data sources provided by FDI enterprises.
Portfolio investment income: The source data are banking returns sent to the NBG.
Other investment income: The data source for interest on government debt is the External Debt Management Unit of the Ministry of Finance. Interest arrears are shown as interest payments and contra entries are included in the financial account as short-term liabilities. Data on interest on reserves are provided by the NBG.
Current transfers: Data for transfers have been developed from various sources. Current transfer receipts consist of official development assistance (ODA), workers’ remittances and expenditures of nongovernment organizations (NGOs). Data on ODA are obtained from the Organization for Economic Cooperation and Development (OECD) database. Workers’ remittances are calculated on the basis of migration patterns and data from the household surveys. Expenditures of NGOs are estimated based on their number and nature of activities in Georgia. Data on current transfer debits consist of taxes paid to foreign governments by Georgia’s short-term workers. This is derived from the model used to estimate the compensation of short-term workers abroad. Debits attributed to workers’ remittances consist of earnings sent abroad for family support by expatriate workers including long-term technical personnel.
Capital transfers: Capital transfers are identified only for migrants’ transfers. Direct investment: There are currently no data sources for inward direct investment. The SDS survey of direct investment enterprises yielded poor results because of nonresponse.
Portfolio investment: The data comprise portfolio investment by banks obtained from the NBG.
Other investment: Data on bilateral and multilateral loans are obtained from the Debt Management Unit in the MOF. Data on disbursements of loans, principal repayments, interest payments, and arrears on interest and principal repayments are available from this unit and are provided regularly on a quarterly basis, or when needed by the SDS. Information on loan agreements and the rescheduling of loans are also available from this unit. Data on changes in foreign assets and liabilities of commercial banks are obtained from the NBG based on commercial bank returns. In calculating the entries for changes in the stock of foreign assets or liabilities, appropriate adjustments are made to remove the effects on stocks of revaluations due to exchange rate movements.
Estimates are made for trade credit liabilities and are based on the value of imports. No data are included for transactions of insurance companies and pension funds.
Reserve assets: Data for reserve assets are obtained from the NBG and consist of monetary gold, holdings of special drawing rights, reserve position in the IMF, and foreign exchange and other claims. Valuation changes are excluded in the flow data submitted by the NBG.
3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required
Although the BOPD uses a number of specific procedures to improve the coverage, valuation, and classification of source data, the procedures used are not always the most appropriate, and, in a number of instances of deficient source data, no procedures have been developed.
Goods: The BOPD makes a global adjustment to the Customs data on foreign trade for under-coverage and under-valuation by applying a simple grossing up ratio. This technique does not have any objective basis. The SDS has initiated trade data reconciliation with Armenia, Azerbaijan, and Turkey for 1998-99, but the necessary follow-up work was not completed. As a result, no techniques for adjusting Customs data were developed. Attempts were also started to adjust Customs data by using the partner country data available from the IMF’s Direction of Trade Statistics, but this work has not been completed.
The BOPD does not make any estimates of smuggled imports or exports of goods, such as cigarettes, petroleum and products, electronic goods, metal products, wood, drugs and arms. The results of a special survey done by the Household Budget Survey and Living Standards Division of the SDS on consumption of tobacco products for the year 1998 have not been used to adjust the Customs data for imports of cigarettes.
Transportation: For transportation debits for freight, a rule of thumb estimate of five percent of total value of imports c.i.f. is assigned. No attempt has been made to sample the data on valuation at c.i.f. and f.o.b. values in the SAD records.
Insurance: A rule of thumb estimate of two percent is made by the BOPD for insurance on freight. No attempt was made to use either the SAD records or by contacting the insurance companies or major importers. There is no reporting by insurance companies of their balance of payments transactions.
Travel: While data from the two TACIS assisted surveys provided useful data on travel credits, there were also certain shortcomings. Since both surveys were carried out in the fourth quarter of consecutive years, it was not possible to analyze the influence of seasonal factors on travel.
Transfers: Official development assistance received in the form of capital goods are not identified. Efforts could have been made to estimate these from Customs or MOF records as well as projects of an investment nature such as construction and utilities that were financed by official development funds.
Direct investment: Media sources have not been effectively used to monitor major direct investment activities.
Although the Abkhasia and South Ossetia Regions are included in the economic territory of Georgia, almost no source data are collected on balance of payments transactions.
3.1.3 Source data are timely
Administrative data obtained from the various ministries and agencies are timely. However, direct investment surveys have experienced a high nonresponse rate in spite of respondents being made aware of deadlines for reporting and follow-up procedures to ensure the timely receipt of respondents’ data. OECD data on transfers are not timely.
3.2 Statistical Technique
3.2.1 Data compilation employs sound statistical techniques
As the BOPD does not conduct large statistical surveys, computer processing is not utilized to edit and tabulate questionnaires.
3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques
Sound statistical procedures are not used for data adjustments and transformations.
The c.i.f./f.o.b. factor for valuing imports is based on a rule of thumb of five percent of the value of imports and is not estimated on the basis of a sample survey of transportation enterprises.
Estimates of shuttle imports are not made based on information from periodic surveys conducted at major border points on goods carried by organized and nonorganized traders. Data are not extrapolated on basis of the monthly volume of shuttle traders identified by customs and immigration authorities. In Tbilisi and other major cities in Georgia, there are distinct markets where the shuttle traders have their retail outlets. These outlets have not been surveyed to estimate their sales or to calculate the f.o.b. import prices of goods imported by shuttle traders.
Adjustments are not specifically made for underestimation of imports and exports on the basis of partner country data. As in the case of shuttle trade, these estimates are part of a global estimate for the under coverage and under valuation of the Customs trade data and is not specifically identified.
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
Verification of relational data (e.g., reserve assets and interest income or changes in the stock of external debt and net financial flows related to external debt), and trend analysis to detect inconsistencies in the source data or errors in compilation are not routinely performed.
3.4 Assessment and Validation of Intermediate Data and Statistical Outputs
3.4.1 Main intermediate data are validated against other information where applicable
Very little monitoring of the media is performed for information on international transactions relating to trade, services, transfers, direct investment, and other financial flows.
3.4.2 Statistical discrepancies in intermediate data are assessed and investigated
The behavior of series is usually not crosschecked with related series or indicators. Reported data on investment income payments and receipts are not regularly assessed in relation to the corresponding stock data in the international investment position statistics. Data on freight earnings are not regularly assessed in relation to the value/volume of the trade flows. The reported financial data are not reconciled with changes in the corresponding stock data collected for external debt and for other elements of the international investment position. However, data on travel-related transactions are analyzed in relation to information compiled by the immigration authorities on the numbers of international travelers entering/leaving the country.
3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated
Net errors and omissions are not analyzed to monitor developments in their size or sign.
Bilateral trade comparisons have been done with major partner countries. However, follow-up actions were not taken to resolve the discrepancies that were identified. External debt data are not routinely compared with the Joint Bank for International Settlements (BIS)-IMF-OECD-World Bank Statistics on External Debt or the BIS locational international banking statistics.
3.5 Revision Studies
3.5.1 Studies and analysis of revisions are carried out routinely and used to inform statistical processes
The direction and magnitude of revisions between preliminary and final data are not investigated. Studies on fluctuations in the data, including the source of errors and omissions, are not carried out routinely.
4. Serviceability
4.1 Relevance
4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored
Specific actions are not taken to ensure that the balance of payments statistics continue to address issues of concern to users of statistics. There is no established process of consultation with users either in the government or the private sector. Feedback is received from the IMF on a regular basis on the relevance of existing data. Informal feedback is also received occasionally from the NBG. However, there is no established process of periodic review to assess whether the program meets the needs of users of balance of payments statistics. Users’ surveys have not been conducted to assess the relevance of published balance of payments statistics data. SDS regularly participates in international statistical meetings and seminars organized by international and regional organizations.
Although balance of payments statistics are compiled according to the classification and sectorization recommended in BPM5 (see section 2.3.1) these details are only available to users on request and their availability is not made public. Only a very summary classification and sectorization for balance of payments statistics is provided in SDS publications.
4.2 Timeliness and periodicity
4.2.1 Timeliness follows dissemination standards
Annual balance of payments data are disseminated within four months after the end of the reference period. Quarterly balance of payments data are disseminated within a quarter after the end of the reference period. However, there may be some additional lags before publications are available to users (which would be remedied by the use of the SDS website for the release of data).
4.2.2 Periodicity follows dissemination standards
The SDS compiles quarterly and annual balance of payments statistics, thereby exceeding the GDDS requirements.
4.3 Consistency
4.3.1 Statistics are consistent with the dataset
The concepts, definitions, and classifications for developing quarterly balance of payments data are the same as those for the annual data. Annual data are derived from quarterly and are not subsequently revised and, therefore, are consistent. However, the net errors and omissions in the annual data are large and exhibit significant fluctuations, which indicates a lack of consistency between years in the balance of payments estimates.
4.3.2 Statistics are consistent or reconcilable over a reasonable period of time
Consistent balance of payments series are not available for an adequate period of years. When new source data, methodology, or statistical techniques have been introduced, historical revisions have not been made. Major changes in methodology and unusual changes in economic trends have not been documented, and no analysis is included in the regular balance of payments publications.
4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks
The balance of payments statistics are consistent with the national accounts, government finance, and monetary statistics.
4.4 Revision Policy and Practice
4.4.1 Revisions follow a regular, well-established and transparent schedule
Revisions to balance of payments statistics do not have an established schedule and are not identified in the published statistics. Explanations and analysis of the revisions are neither published nor available in internal documents of the SDS.
4.4.2 Preliminary data are clearly identified
Preliminary data are not identified. Revised data are disseminated with the same level of detail as originally published. However, there is no indication in the revised data on which statistics have been updated.
4.4.3 Studies and analyses of revisions are made public
External users are not informed of the causes of revisions. As new data sources become available, compilation procedures are changed on an ongoing basis. Analysis of preliminary versus revised data is not published for major aggregates to allow an assessment of the reliability of the preliminary data.
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)
A balance of payments publication including detailed balance of payments data, charts, and tables was last published in 1997 in the format of BPM5. Since then, quarterly and annual data are released without accompanying text, tables, and charts.
5.1.2 Dissemination media and formats are adequate
The dissemination media and formats for balance of payments data do not meet users’ needs. There is no formal procedure (such as an advance release calendar) that would alert users in advance, no press release that would ensure that notice of publication is given, and no mechanism for ensuring the simultaneous release of data. Only summary data are published. The first published release is through the NBG’s Quarterly Bulletin. Summary data are published by the SDS in the Statistical Yearbook of Georgia or SDS Yearbook (in which the 2002 issue includes balance of payments data for 1997–2000).
In the absence of a press release, as soon as the data are finalized (usually 45 days after the end of the reference period for the quarterly and four months after the end of the reference period for the annual data) they are considered to be released and are available to anybody who requests them. At that time, various formats of the data are routinely sent to the NBG, MOF, the State Chancellery, the Ministry of Economy, Industry and Trade, and TACIS. An unpublished full classification/sectorization, consistent with the recommendation of the BPM5-see section 2.3.1, is sent to the IMF Statistics Department..
The SDS plans to publish balance of payments data on its website.
5.1.3 Statistics are released on a pre-announced schedule
A schedule for data release is not announced in advance.
5.1.4 Statistics are made available to all users at the same time
Balance of payments statistics are not made available to all users at the same time.
5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request
Nonpublished and nonconfidential data are provided to users upon request, usually for a fee. The availability of nonpublished statistics, 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
There is no internal documentation on the concepts, scope, classifications, basis of recording, data sources, and statistical techniques used to compile balance of payments data. Unlike most countries, a description of methods used for compiling the balance of payments is not published in the IMF’s Balance of Payments Statistics Yearbook.
5.2.2 Levels of detail are adapted to the needs of the intended audience
Metadata are not adapted to the needs of the intended audience.
5.3 Assistance to Users
5.3.1 Contact person for each subject field is publicized
All statistical releases and publications indicate the mailing address, telephone, and fax numbers, and e-mail address of the SDS Publication Division and the specific divisions (including BOPD) that are responsible for the compilation of the statistics. BOPD staff handle the enquiries.
5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available
A catalogue of publications is available but does not include information on charges. Information on how publications can be obtained is provided.
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Balance of Payments
(Compiling Agency: State Department of Statistics)
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Balance of Payments
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Financial penalties for non or late response to statistical surveys are nominal and have not been applied to statistical returns. There is a potential conflict regarding confidentiality between the Law on Statistics and the Anti-monopoly Law of Georgia. The SDS appears to lack authority over the regional offices in setting priorities for conducting balance of payments surveys. The SDS does not build working relationships with survey respondents. |
|||||
| 0.2 | Resources | X | Computing and financial resources allocated are inadequate. | |||||
| 0.3 | Quality Awareness | X | There is no body charged with oversight or guidance on quality issues and resource constraints have limited initiatives by the staff to assess the quality of statistics. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | Dissemination practices are not made known to the public. Government agencies obtain access to balance of payments statistics in advance of other users. Advance notice is not given about major changes in balance of payments methodology. | |||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | Re-invested earnings are excluded. | |||||
| 2.3 | Classification/Sectorization | X | No instrument classifications for direct and portfolio investments. | |||||
| 2.4 | Basis for recording | X | Some data are on a cash basis. | |||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | Data sources available for the compilation of data are inadequate. Surveys are not conducted (with the exception of the FDI survey, which has resulted in poor response). SDS is mainly dependent on administrative data sources. The customs data for merchandise trade are especially deficient for the nonobserved economy and are not in accordance with international standards for trade statistics. | |||||
| 3.2 | Statistical techniques | X | The statistical techniques used are deficient. Rule of thumb procedure is used to transform the value of imports from c.i.f. to f.o.b. Estimates of shuttle imports are not made based on information from periodic surveys conducted at major border points or retail outlets of shuttle traders. Instead, subjective estimates are made. Partner country data are not used to adjust the value of imports and exports. Statistical model on migration related data is not regularly updated. | |||||
| 3.3 | Assessment and validation of source data | X | Verification of relational data (e.g., reserve assets and interest income or changes in the stock of external debt and net financial flows related to external debt), and trend analysis to detect inconsistencies in the source data or errors in compilation are not routinely performed. | |||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | Net errors and omissions are not analyzed to monitor developments in their size or sign. Results of trade data reconciliation with major partner countries have not been incorporated in the trade data. Very little monitoring of the media is performed for information on international transactions. | |||||
| 3.5 | Revision studies | X | Direction and magnitude of revisions between preliminary and final data are not investigated. No record is kept on revisions. | |||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | There is no established process of consultation with users. There is no advisory group that systematically assesses the relevance of balance of payments data. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | As annual data are derived from quarterly data, the consistency of annual and quarterly data is good. However, the substantial movements in year-to-year errors and omissions indicates that consistency over time is deficient. | |||||
| 4.4 | Revision policy and practice | X | No attempt is made to document or explain revisions to the public. | |||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Summary quarterly and annual data are released without any accompanying text, tables, and charts, and do not include comparable data for earlier years. No analysis of current period changes is presented and no data are included on the SDS website. There is no pre-announced schedule of publication release dates. Priority is given to sending data to government agencies ahead of the general release. | |||||
| 5.2 | Metadata accessibility | X | No information on sources and methods is included in the SDS publications. | |||||
| 5.3 | Assistance to users | X | A catalogue of publications is available but does not include information on charges. Information on how publications can be obtained is provided. | |||||
Georgia—Data Quality Assessment Framework: Summary Presentation of Results for Balance of Payments
(Compiling Agency: State Department of Statistics)
| Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria | ||||||||
|---|---|---|---|---|---|---|---|---|
| Element | NA | Assessment | Comments on Assessment | Plans for Improvement and Target Dates | ||||
| O | LO | LNO | NO | |||||
| 0. | Prerequisites of quality | |||||||
| 0.1 | Legal and institutional environment | X | Financial penalties for non or late response to statistical surveys are nominal and have not been applied to statistical returns. There is a potential conflict regarding confidentiality between the Law on Statistics and the Anti-monopoly Law of Georgia. The SDS appears to lack authority over the regional offices in setting priorities for conducting balance of payments surveys. The SDS does not build working relationships with survey respondents. |
|||||
| 0.2 | Resources | X | Computing and financial resources allocated are inadequate. | |||||
| 0.3 | Quality Awareness | X | There is no body charged with oversight or guidance on quality issues and resource constraints have limited initiatives by the staff to assess the quality of statistics. | |||||
| 1. | Integrity | |||||||
| 1.1 | Professionalism | X | ||||||
| 1.2 | Transparency | X | Dissemination practices are not made known to the public. Government agencies obtain access to balance of payments statistics in advance of other users. Advance notice is not given about major changes in balance of payments methodology. | |||||
| 1.3 | Ethical Standards | X | ||||||
| 2. | Methodological soundness | |||||||
| 2.1 | Concepts and definitions | X | ||||||
| 2.2 | Scope | X | Re-invested earnings are excluded. | |||||
| 2.3 | Classification/Sectorization | X | No instrument classifications for direct and portfolio investments. | |||||
| 2.4 | Basis for recording | X | Some data are on a cash basis. | |||||
| 3. | Accuracy and reliability | |||||||
| 3.1 | Source data | X | Data sources available for the compilation of data are inadequate. Surveys are not conducted (with the exception of the FDI survey, which has resulted in poor response). SDS is mainly dependent on administrative data sources. The customs data for merchandise trade are especially deficient for the nonobserved economy and are not in accordance with international standards for trade statistics. | |||||
| 3.2 | Statistical techniques | X | The statistical techniques used are deficient. Rule of thumb procedure is used to transform the value of imports from c.i.f. to f.o.b. Estimates of shuttle imports are not made based on information from periodic surveys conducted at major border points or retail outlets of shuttle traders. Instead, subjective estimates are made. Partner country data are not used to adjust the value of imports and exports. Statistical model on migration related data is not regularly updated. | |||||
| 3.3 | Assessment and validation of source data | X | Verification of relational data (e.g., reserve assets and interest income or changes in the stock of external debt and net financial flows related to external debt), and trend analysis to detect inconsistencies in the source data or errors in compilation are not routinely performed. | |||||
| 3.4 | Assessment and validation of intermediate data and statistical outputs | X | Net errors and omissions are not analyzed to monitor developments in their size or sign. Results of trade data reconciliation with major partner countries have not been incorporated in the trade data. Very little monitoring of the media is performed for information on international transactions. | |||||
| 3.5 | Revision studies | X | Direction and magnitude of revisions between preliminary and final data are not investigated. No record is kept on revisions. | |||||
| 4. | Serviceability | |||||||
| 4.1 | Relevance | X | There is no established process of consultation with users. There is no advisory group that systematically assesses the relevance of balance of payments data. | |||||
| 4.2 | Timeliness and periodicity | X | ||||||
| 4.3 | Consistency | X | As annual data are derived from quarterly data, the consistency of annual and quarterly data is good. However, the substantial movements in year-to-year errors and omissions indicates that consistency over time is deficient. | |||||
| 4.4 | Revision policy and practice | X | No attempt is made to document or explain revisions to the public. | |||||
| 5. | Accessibility | |||||||
| 5.1 | Data accessibility | X | Summary quarterly and annual data are released without any accompanying text, tables, and charts, and do not include comparable data for earlier years. No analysis of current period changes is presented and no data are included on the SDS website. There is no pre-announced schedule of publication release dates. Priority is given to sending data to government agencies ahead of the general release. | |||||
| 5.2 | Metadata accessibility | X | No information on sources and methods is included in the SDS publications. | |||||
| 5.3 | Assistance to users | X | A catalogue of publications is available but does not include information on charges. Information on how publications can be obtained is provided. | |||||
APPENDIX I: Summary of the General Data Dissemination System (GDDS)
Data coverage, periodicity, and timeliness
Dissemination of reliable, comprehensive, and timely economic, financial, and socio-demographic data is essential to the transparency of macroeconomic performance and policy. The GDDS contains specific recommendations concerning coverage, periodicity, and timeliness for comprehensive frameworks as well as for data categories and indicators.
Quality
Data quality must have a high priority. Data users must be provided with information to assess quality and quality improvements. The GDDS recommends:
dissemination of documentation on methodology and sources used in preparing statistics; and
dissemination of component detail, reconciliations with related data, and statistical frameworks that support statistical cross-checks and provide assurance of reasonableness.
Integrity
To fulfill the purpose of providing the public with information, official statistics must have the confidence of their users. In turn, confidence in the statistics ultimately becomes a matter of confidence in the objectivity and professionalism of the agency producing the statistics. Transparency of practices and procedures is a key factor in creating this confidence. The GDDS, therefore, recommends:
dissemination of the terms and conditions under which official statistics are produced, including those relating to the confidentiality of individually identifiable information;
identification of internal government access to data before release;
identification of ministerial commentary on the occasion of statistical releases; and
provision of information about revision and advance notice of major changes in methodology.
Access to the public
Dissemination of official statistics is an essential feature of statistics as a public good. Ready and equal access by the public are principal requirements. The GDDS recommends; and
dissemination of advance release calendars; and
simultaneous release to all interested parties.
Plans for improvement
The GDDS recommends that plans for improvement be developed for all areas in which shortcomings exist and that these plans be disseminated.
The GDDS also recommends that any needs for assistance be identified in the metadata. This may also be helpful for donors and technical assistance providers to prioritize their activities.
For each participating member country, the GDDS metadata provide descriptions of the dimensions listed above, together with plans for improvement and needs for assistance. This information is posted on the DSBB; participating countries are encouraged to also post the metadata on their national websites.
Source: Guide to the GDDS, February 2002: http://dsbb.imf.org
APPENDIX II: Data Quality Assessment Framework—Generic Framework
(July 2001 Vintage)
The elements and indicators included here bring together the “pointers to quality” that are applicable across the five identified dimensions of data quality.
| Quality Dimensions | Elements | Indicators |
|---|---|---|
| Prerequisites of quality1/ | 0.1 Legal and institutional environment–The environment is supportive of statistics. | 0.1.1 The responsibility for collecting, processing, and disseminating statistics is clearly specified. 0.1.2 Data sharing and coordination among data producing agencies are adequate. 0.1.3 Respondents’ data are to be kept confidential and used for statistical purposes only. 0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response. |
| 0.2 Resources–Resources are commensurate with needs of statistical programs. | 0.2.1 Staff, financial, and computing resources are commensurate with statistical programs. 0.2.2 Measures to ensure efficient use of resources are implemented. |
|
| 0.3 Quality awareness–Quality is a cornerstone of statistical work. | 0.3.1 Processes are in place to focus on quality. 0.3.2 Processes are in place to monitor the quality of the collection, processing, and dissemination of statistics. 0.3.3 Processes are in place to deal with quality considerations, including tradeoffs within quality, and to guide planning for existing and emerging needs. |
|
| 1. Integrity The principle of objectivity in the collection, processing, and dissemination of statistics is firmly adhered to. |
1.1 Professionalism–Statistical policies and practices are guided by professional principles. | 1.1.1 Statistics are compiled on an impartial basis. 1.1.2 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. |
| 1.2 Transparency–Statistical policies and practices are transparent. | 1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public. 1.2.2 Internal governmental access to statistics prior to their release is publicly identified. 1.2.3 Products of statistical agencies/units are clearly identified as such. 1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques. |
|
| 1.3 Ethical standards–Policies and practices are guided by ethical standards. | 1.3.1 Guidelines for staff behavior are in place and are well known to the staff. | |
| 2. Methodological soundness The methodological basis for the statistics follows internationally accepted standards, guidelines, or good practices. |
2.1 Concepts and definitions–Concepts and definitions used are in accord with internationally accepted statistical frameworks. | 2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices: see dataset-specific framework. |
| 2.2 Scope–The scope is in accord with internationally accepted standards, guidelines, or good practices. | 2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices: see dataset-specific framework. | |
| 2.3 Classification/sectorization–Classification and sectorization systems are in accord with internationally accepted standards, guidelines, or good practices. | 2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices: see dataset-specific framework. | |
| 2.4 Basis for recording–Flows and stocks are valued and recorded according to internationally accepted standards, guidelines, or good practices. | 2.4.1 Market prices are used to value flows and stocks. 2.4.2 Recording is done on an accrual basis. 2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices. |
|
| 3. Accuracy and reliability Source data and statistical techniques are sound and statistical outputs sufficiently portray reality. |
3.1 Source data–Source data available provide an adequate basis to compile statistics. | 3.1.1 Source data are collected from comprehensive data collection programs that take into account country-specific conditions. 3.1.2 Source data reasonably approximate the definitions, scope, classifications, valuation, and time of recording required. 3.1.3 Source data are timely. |
| 3.2 Statistical techniques–Statistical techniques employed conform to sound statistical procedures. | 3.2.1 Data compilation employs sound statistical techniques. 3.2.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques. |
|
| 3.3 Assessment and validation of source data–Source data are regularly assessed and validated. | 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. | |
| 3.4 Assessment and validation of intermediate data and statistical outputs–Intermediate results and statistical outputs are regularly assessed and validated. | 3.4.1 Main intermediate data are validated against other information where applicable. 3.4.2 Statistical discrepancies in intermediate data are assessed and investigated. 3.4.3 Statistical discrepancies and other potential indicators of problems in statistical outputs are investigated. |
|
| 3.5 Revision studies–Revisions, as a gauge of reliability, are tracked and mined for the information they may provide. | 3.5.1 Studies and analyses of revisions are carried out routinely and used to inform statistical processes. | |
| 4. Serviceability Statistics are relevant, timely, consistent, and follow a predictable revisions policy. |
4.1 Relevance–Statistics cover relevant information on the subject field. | 4.1.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored. |
| 4.2 Timeliness and periodicity–Timeliness and periodicity follow internationally accepted dissemination standards. | 4.2.1 Timeliness follows dissemination standards. 4.2.2 Periodicity follows dissemination standards. |
|
| 4.3 Consistency–Statistics are consistent within the dataset, over time, and with major datasets. | 4.3.1 Statistics are consistent within the dataset (e.g., accounting identities observed). 4.3.2 Statistics are consistent or reconcilable over a reasonable period of time. 4.3.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks. |
|
| 4.4 Revision policy and practice–Data revisions follow a regular and publicized procedure. | 4.4.1 Revisions follow a regular, well-established and transparent schedule. 4.4.2 Preliminary data are clearly identified. 4.4.3 Studies and analyses of revisions are made public. |
|
| 5. Accessibility Data and metadata are easily available and assistance to users is adequate. |
5.1 Data accessibility–Statistics are presented in a clear and understandable manner, forms of dissemination are adequate, and statistics are made available on an impartial basis. | 5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts). 5.1.2 Dissemination media and formats are adequate. 5.1.3 Statistics are released on the pre-announced schedule. 5.1.4 Statistics are made available to all users at the same time. 5.1.5 Nonpublished (but nonconfidential) sub-aggregates are made available upon request. |
| 5.2 Metadata accessibility–Up-to-date and pertinent metadata are made available. | 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. 5.2.2 Levels of detail are adapted to the needs of the intended audience. |
|
| 5.3 Assistance to users–Prompt and knowledgeable support service is available. | 5.3.1 Contact person for each subject field is publicized. 5.3.2 Catalogues of publications, documents, and other services, including information on any charges, are widely available. |
The elements and indicators included here bring together the “pointers to quality” that are applicable across the five identified dimensions of data qua