This report is a summary assessment of Sri Lanka’s data dissemination practices against the IMF’s Special Data Dissemination Standard (SDDS), complemented by an in-depth assessment of the elements of data quality that underlie the national accounts, prices, government finance, monetary, and balance-of-payments statistics. Sri Lanka has made good progress in meeting most of the SDDS specifications on coverage, periodicity, and timeliness of data categories. Shortcomings exist in the access, integrity, and quality dimensions compared with the SDDS. All agencies demonstrate professionalism and are generally transparent in their practices and policies


This report is a summary assessment of Sri Lanka’s data dissemination practices against the IMF’s Special Data Dissemination Standard (SDDS), complemented by an in-depth assessment of the elements of data quality that underlie the national accounts, prices, government finance, monetary, and balance-of-payments statistics. Sri Lanka has made good progress in meeting most of the SDDS specifications on coverage, periodicity, and timeliness of data categories. Shortcomings exist in the access, integrity, and quality dimensions compared with the SDDS. All agencies demonstrate professionalism and are generally transparent in their practices and policies

I. Introduction

1. This data dissemination module of the Report on Observance of Standards and Codes (ROSC) covers a summary of Sri Lanka’s practices on the coverage, periodicity, and timeliness of the data categories specified in the IMF’s Special Data Dissemination Standard (SDDS), practices on the provision of advance release calendars for these categories, and an assessment of the quality of national accounts, prices, government finance statistics, monetary, and balance of payments statistics. This assessment is based on information (data and metadata) provided to the Statistics Department (STA) prior to and during a staff mission, and it also relies on publicly-available information.

2. Section II includes an overview of the SDDS and an assessment of Sri Lanka’s data dissemination practices against the SDDS. A summary assessment of the quality of the principal macroeconomic statistical datasets, following the assessment framework that has been developed by STA, is presented in Section III. Section IV summarizes the views of a cross section of users on the usability of Sri Lanka’s statistical data. Section V lists the recommendations made by the Fund staff for improving the quality of these data.

II. Data Dissemination Practices and the SDDS

A. Overview of the SDDS

3. The standard against which Sri Lanka’s data dissemination practices are assessed is the IMF’s SDDS 2 which is a "best practice" standard. It covers four sectors of the economy (real, fiscal, financial, and external), as well as population, and identifies four dimensions (data, access, integrity, and quality) of data dissemination for each sector. For each of these dimensions, the SDDS prescribes two to four monitorable elements, or good practices, that can be observed or monitored by the users of statistics (See Box 1). However, the IMF staff monitoring of the SDDS, as authorized by the Fund’s Board of Executive Directors, is limited to the coverage, periodicity and timeliness, and access (advance release calendars) dimension. Moreover, it should be emphasized that the SDDS is a disclosure standard, i.e., it aims to encourage the authorities to provide information to users, including information they can use to assess the suitability of the data for purposes that they identify. The SDDS itself does not aim to assess the quality of data for any specific or predetermined use.

Dimensions And Elements Of The Special Data Dissemination Standard (SDDS)

Data dimension (coverage, periodicity and timeliness)

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

Access dimension

  • the dissemination of advance release calendars (ARCs) providing at least a one-quarter ahead notice of approximate release dates, and at least a one-week ahead notice of the precise release dates; and

  • the simultaneous release of data to all users.

Integrity dimension

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

  • the identification of internal government access to data before release;

  • the identification of ministerial commentary on the occasion of statistical release; and

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

Quality dimension

  • the dissemination of documentation on statistical methodology and sources used in preparing statistics; and

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

Subscribers are required:

  • to post descriptions of their data dissemination practices (metadata) on the IMF’s Dissemination Standards Bulletin Board (DSBB). Summary methodologies, which describe data compilation practices in some detail, are also disseminated on the DSBB.

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

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

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

B. Current Dissemination Practices

4. Sri Lanka was one of the earliest countries to express strong interest in the GDDS and one of the countries for which experimental metadata were produced in 1997. Sri Lanka has adopted the GDDS as an interim stage before meeting the more demanding requirements of the SDDS. Following substantive collaboration between the Fund staff and the authorities, Sri Lanka’s metadata were posted on the GDDS website of the Fund’s Dissemination Standards Bulletin Board (DSBB) in July 2000.

5. The three institutions responsible for the compilation and dissemination of the prescribed SDDS data categories are the CBSL, the MOFP, and the DCS. The compilation and, particularly the dissemination of economic and financial statistics in Sri Lanka is highly concentrated in the CBSL. Of the data categories and indicators covered by the SDDS, CBSL is involved in all areas with the exception of employment and unemployment data, which are produced by the DCS. The DCS and the CBSL prepare independent estimates of annual national accounts and consumer prices, while the CBSL produces quarterly national accounts estimates, producer prices, production index, and wage indices. The CBSL is the primary disseminator of detailed fiscal data although the MOFP has recently expanded its dissemination of analytical fiscal data. The CBSL is also responsible for the compilation and dissemination of the analytical accounts of the banking sector, the analytical accounts of the central bank, interest rates, share price indices, balance of payments, the international reserves, merchandise trade, and exchange rates.

6. Sri Lanka provides access to these data through a variety of publications and the following Internet websites:

The CBSL’s website

The MOFP’s website http://www.EUREKA.LK/FPEA

The DCS’s website

7. The coverage, periodicity, and timeliness of macroeconomic data in Sri Lanka are summarized and compared with SDDS specifications in Table 1. As Sri Lanka is not yet an SDDS subscriber, it has not yet compiled some data in the prescribed SDDS categories.

Table 1.

Sri Lanka: Overview of Current Practices regarding Coverage, Periodicity, and Timeliness of Data Compared to the SDDS

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

Refers to current practices in Sri Lanka.

Given that the data are broadly disseminated by private means, the timeliness with which official data are published is not so important. Although dissemination is recommended via recorded telephone messages or by fax, the dissemination of these data may form part of other dissemination mechanisms (preferably, high frequency).

8. Sri Lanka meets the majority of the SDDS specifications for the data coverage dimension. However, the published analytical accounts of the banking sector do not cover all depository corporations; the production index does not conform to international guidelines; the data template on international reserves and foreign currency liquidity is not fully developed; and the data on the international investment position (IIP) is not yet compiled. Furthermore, the production index, the producer price index, the central government operations, the analytical accounts of the banking sector, and the analytical accounts of the central bank do not meet the SDDS timeliness requirements. However, Sri Lanka exceeds the SDDS specifications for timeliness for CPI, merchandise trade and central government debt.

Access dimension

9. The CBSL does not at present issue Advance Release Calendars (ARCs) for the release of its weekly and monthly data. However, its Annual Report, by law, has to be published within four months from the end of the reference year. As all CBSL data series are produced under specific schedules, it is feasible to disseminate ARCs. The CBSL data are released to users through press releases, publications, and posting on the Internet. The DCS has no ARC for price statistics. However, there is a legal requirement to publish the official CPI (CCPI) on the last day of the reference month. Data published by the DCS are released via press releases, publications and on its website.

Integrity dimension

10. The SDDS requires the disclosure of information on laws, regulations and decrees, etc. that govern the collection, compilation and dissemination of data, as well as the confidentiality of the data collected. The terms and conditions under which most official statistics are compiled and disseminated in Sri Lanka are governed by the Monetary Law Act (MLA), the Statistical Ordinance, and the Census Ordinance. These are available to the public in electronic and non-electronic formats; they provide a legal framework, with appropriate responsibilities and corresponding penalties, that supports the integrity of the statistical system.

11. The DCS releases the official CPI (CCPI) through press releases simultaneously to all users. However, for other statistics, the DCS automatically provides finalized data to government users before publication, but will also supply these data to other users on request, and the public is not informed of this practice. The CBSL and the MOFP do not provide data to government officials before their public release, and data are disseminated without ministerial commentary. All the statistical agencies do not provide advance notification of major changes in methodology, source data, and statistical techniques. In many cases involving major changes in methodology, however, released data are accompanied by a detailed technical commentary in statistical publications.

Quality dimension

12. The SDDS requires dissemination of documentation on methodology and sources, as well as component detail, reconciliations with related data, and statistical frameworks that support statistical cross-checks and provide assurance of reasonableness. Summary methodology statements and statistical techniques for the data published by CBSL, the MOFP, and the DCS are outdated, limited in coverage, and unavailable to the public for most data sets. Plans are underway at CBSL to either update or create publicly accessible metadata in the near term.

III. Summary Assessment of Data Quality

A. The Framework for Assessing Data Quality

13. Work toward a framework for assessing the quality of data has been under way in the IMF’s Statistics Department for some time. This initiative responds to a number of needs, in particular, to complement the quality dimension of the SDDS, to focus more closely on the quality of the data provided by countries to the IMF that underpin the institution’s surveillance of their economic policies, and to assess systematically the quality of the information provided for the IMF’s ROSCs. Against this background, the Statistics Department of the IMF has developed a tool that would provide a structure and a common language to efforts to assess data quality and establishes a link with the SDDS. The data quality assessment framework that has emerged comprises a generic framework that brings together internationally accepted core principles for official statistics and serves as the overarching structure for dataset-specific frameworks (for national accounts, balance of payments, monetary, government finance, and price statistics) that are organized around selected indicators of quality.

14. The Data Quality Assessment Framework (DQAF) covers five dimensions of quality and a set of prerequisites for the assessment of data quality (see below). The coverage of these dimensions recognizes that data quality encompasses quality of the institution or system behind the production of the data as well as the quality of the individual data product. Within this framework, each dimension comprises a number of elements, which are in turn associated with a set of desirable practices. The following are the statistical practices that are associated with each dimension.

  • Prerequisites of quality—the environment is supportive of statistics; resources are commensurate with needs of statistical programs; and quality is the cornerstone of statistical work.

  • Integrity—professionalism in statistical policies and practices is a guiding principle; statistical policies and practices are transparent; and policies and practices are guided by ethical standards.

  • Methodological soundness—concepts and definitions used are in accord with standard statistical frameworks; the scope is in accord with internationally accepted standards; classification and sectorization systems are in accord with internationally accepted standards; and flows and stocks are valued and recorded according to internationally accepted standards.

  • Accuracy and reliability—source data available provide an adequate basis to compile statistics; statistical techniques employed conform with sound statistical procedures; source data are regularly assessed and results validated; and revisions, as a gauge of reliability, are tracked and mined for the information they may provide.

  • Serviceability—statistics cover relevant information on the subject field; timeliness and periodicity follow internationally accepted dissemination standards; statistics are consistent over time, internally, and with major data systems; and data revisions follow a regular and publicized procedure.

  • Accessibility—statistics are presented in a clear and understandable manner, forms of dissemination are adequate, and statistics are made available on an impartial basis; up-to-date and pertinent metadata are made available; and prompt and knowledgeable support service is available.

15. A central feature of this framework is its structure, which focuses on principles of quality that are organized in an orderly progression from the abstract to the more specific. Thus, for each of the five dimensions and the set of prerequisites, a set of elements, indicative of desirable practices, and a group of indicators or pointers to these practices have been developed.

16. The findings from the application of this framework to the Sri Lanka statistical system are presented below. Assessments of six macroeconomic datasets (national accounts, consumer and producer prices, government finance statistics, monetary statistics, and the balance of payments) were conducted using information provided to STA and official information publicly available. The mission’s findings are also presented in the form of summary tables using a four-part scale (Tables 2.a-2.f).

Table 2.a.

Data Quality Assessment Framework: Summary Presentation of Results

Country: Sri Lanka Dataset:

National Accounts Statistics4

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Note: NA= Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed
Table 2.b.

Data Quality Assessment Framework: Summary Presentation of Results

Country: Sri Lanka

Dataset: Consumer Price Statistics5

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Note: NA= Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed
Table 2.c.

Data Quality Assessment Framework: Summary Presentation of Results

Country: Sri Lanka

Dataset: Consumer Price Statistics

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Note: NA= Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed
Table 2.d.

Data Quality Assessment Framework: Summary Presentation of Results

Country Sri Lanka Statistics

Dataset: Government Finance

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Note: NA= Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed
Table 2.e.

Data Quality Assessment Framework: Summary Presentation of Results

Country: Sri Lanka

Dataset: Monetary Statistics

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Note: NA= Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed
Table 2.f.

Data Quality Assessment Framework: Presentation of Results

Country: Sri Lanka

Dataset: Balance of Payments

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Note: NA= Not Applicable; O = Pracuce Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed

B. Summary Findings

17. Sri Lanka has a broad-based macroeconomic database for economic and financial analysis. Nevertheless, the mission found shortcomings in some statistical practices that have the potential for complicating the accurate and timely analysis of economic and financial developments. The main findings below are presented following the structure of the data quality assessment framework.

Prerequisites of Quality

18. The DCS prepares the annual national accounts, the official CPI, called the Colombo CPI (CCPI), as well as the Greater Colombo CPI (GCPI) (which has slightly larger geographical coverage and more up-to-date weights). The responsibility to compile national accounts is not clearly specified and the CBSL also produces annual and quarterly national accounts. This results in duplication of efforts by the two agencies The DCS has the legal obligation, under the Statistics Ordinance, to produce CPIs. However, the CBSL also produces a Colombo District CPI (CD-CPI) as well as a producer price index (PPI). This also results in a significant duplication of activities in prices. Both organizations also operate independent household income and expenditure surveys, which are used to derive the weights for the various CPIs. The resources within the DCS are adequate to meet the existing work program. The management of DCS has a positive attitude towards quality, but the organization does not have formal quality assessment programs, and does not conduct regular meetings with users to discuss their needs.

19. The CBSL produces and disseminates statistics under the provisions of Section 35 of the MLA (Monetary Law Act), which stipulates that the CBSL submit to the Minister of Finance and Planning, and publish in its Annual Report, a range of economic statistics including monetary, balance of payments, and government finance statistics (GFS). The MLA empowers the CBSL to collect data needed to carry out its mandate, which the CBSL uses to justify the compilation of prices and national accounts. The MLA obligates financial institutions to provide data to the central bank and specifies penalties for noncompliance. Similar arrangements exist for providing data for balance of payments compilation. The CBSL has a workable framework for discussions with other data producing agencies such as the DCS and the General Treasury of the MOFP. Statutory requirements ensure that respondents’ data are kept confidential. Staff, financial, and computing resources appear adequate to undertake existing statistical programs and regular budgetary reviews focus on efficient resource allocation. Overall, the a perspective obtained perhaps by a public body outside the CBSL, for reviewing data quality indicators would buttress the overall reputation of the compilation agency.

20. The MOFP and the CBSL work together closely to collect, compile, and disseminate the GFS. The CBSL, mandated with the debt management responsibility for central government, is required by law to collect and disseminate GFS. The MOFP, the source of most transaction data on the budgetary central government, has an inadequate accounting system for recording (cash or accrual) data, and its compilation procedures, conducted manually, are not sufficient for ensuring accurate data. Staff is not adequately trained in the new GFS methodology, which concerns the compilation of complete balance sheets as well as transactions based on accrual accounting. Quality processes are primarily driven by the accuracy required under budget reporting systems, to ensure accurate and internally consistent fiscal data at all levels of government. The review of fiscal data quality, however, is not seen as a routine and timely process.


21. Practices are in place at the CBSL, DCS, and the MOFP to help ensure professionalism in statistical policies and practices, transparency, and ethical standards. The documentation on the legal basis under which the CBSL and DCS operate is available publicly. Both organizations operate in a largely autonomous fashion, though this is not formally established. The CBSL compiles statistics on an impartial basis and the staff is free to choose the most appropriate data sources and methods. The DCS, however, has not been able to update the weights for the CCPl, which relate to 1949/50, even though they have made numerous attempts to do so, due to pressures from some influential quarters. All agencies scrutinize all media comments on their statistics and follow up on any observed instances of misrepresentation. Documented guidelines of the MOFP call for the proper use of data sources in compiling GFS. None of the compiling agencies give advance notification of major changes in methodology, source data, and statistical techniques. The CBSL does not allow, pre-release access to senior government officials. The DCS does not allow pre-release access to government officials for the CCPI but for other statistics, the DCS automatically provides finalized data to government users before publication but will also supply these data to other users on request, although the public is not informed of this practice. All CBSL’s staff are subject to the code of conduct and ethical standards for staff clearly specified in the CBSL’s Handbook/Manual. The CBSL and DCS’s training programs for new staff cover the required ethical standards.

Methodological Soundness

22. The overall structure of the national accounts3 generally follows the System of National Accounts 1968 (1968 SNA). No specific plan exists for implementing the 1993 SNA. The delineation of the economy and the production and asset boundary are, in principle, in line with the 1968 SNA. Although the International Standard Industrial Classification of all Activity, Rev.2, is followed, other standard classifications are not used. Regarding valuation, no clear conceptual approach is followed, and the basis for valuation differs across economic activities. For example, gross value added is denoted as factor cost values, manufacturing output is valued at ex-factory prices, while agricultural output is valued at producer prices.

23. The CPIs measure the changes in price of a representative basket of goods and services purchased by the represented households and prices are actual transaction prices paid by consumers. The classifications of goods and services used in all CPIs are not compatible with current internationally recommended practices and the weights for the CPIs are extremely out of date. The scope of all the CPIs is restricted to the Colombo area and to households with the lowest 40-50 percent of income.

24. The PPI’s methodology, set up in 1974, was lost in a bomb blast and no attempt has been made to update this methodology. The prices collected represent transactions at producer prices. The scope and the classification of establishments of the PPI covers all domestic industrial activities, but it has not been updated since 1974. This means that the number of enterprises included has been reduced over the years as businesses have ceased to operate and no new enterprises have been added. Also, the PPI excludes free trade zones and bonded warehouses.

25. The classification and sectorization systems for government finance statistics align with internationally accepted guidelines. Concepts and definitions in the central government finance statistics generally follow the recommendations of the 1986 A Manual on Government Finance Statistics (GFSM). All transactions are valued at current market prices and are recorded on a cash basis. Transactions in foreign currency are converted to local currency using the exchange rate for the day on which they take place. Debt stocks are valued at face value, and those denominated in foreign currency are converted to a domestic currency basis using the mid-point exchange rate in the market at the end of the reporting period. The MOFP and the CBSL are addressing how to report GFS (and to provide more conventional fiscal presentations) in accordance with the new GFS methodology to be published by the IMF in 2001, which entails accrual accounting and completely integrated stocks and flows.

26. The analytical framework for compiling monetary statistics used by CBSL is based on the IMF’s Guide to Money and Banking Statistics in International Financial Statistics (draft, 1984). The coverage of the Consolidated Monetary Survey M2b, which is used for policy purposes, is not complete. It excludes positions of two categories of deposit-taking institutions, namely Licensed Specialized Banks and Finance companies (whose quasi-monetary liabilities were, at end-2000, approximately 22 percent of broad money in the more comprehensive Financial Survey (see below)). The institutional coverage and sectorization of the Financial Survey is more in line with the recommendations in the Guide and the Monetary and Financial Statistics Manual (MFSM). However, some deviations are apparent for example in the treatment of repurchase agreements, and restricted deposits. Valuation principles follow Sri Lanka Accounting Standards, but are not uniformly on a market or fair value basis, as recommended in the MFSM. Accrued amounts (except for overdrafts) are on separate accrual accounts rather than incorporated in the underlying instrument. Also unlike the experimental financial survey, the monetary and financial surveys in CBSL publications do not include the full range of instrument and sectors recommended in MFSM. However, the source data obtained through the collection system generally contain adequate detail on stocks, that may permit compilation of sectoral balance sheets and the sectoral surveys as presented in MFSM.

27. Sri Lanka’s balance of payments statistics are compiled in broad conformity with guidelines presented in the Balance of Payments Manual, Fifth Edition (BPM5). Resident institutional units are in line with BMP5 concepts of economic territory and residence; however, there are some exceptions. Transactions relating to construction services and reinvested earnings are not covered, and only partial data are available on communication, computer and information services, and compensation of employees. Some differences exist with BPM5 with regard to classification of transactions (e.g., imports are on a c.i.f. basis, and the classification of goods does not identify repair on goods). The classification and sectorization of the financial account are not in line with the standard components of BPM5. Transactions are recorded at market prices, and statistical techniques exclude valuation changes from measures of financial flows derived from changes in stock data for CBSL accounts, as called for in the BPM5. As the CBSL relies on the International Transactions Reporting System (ITRS) for a large part of its services, income, and capital and financial account data, the reported transactions are recorded on a cash, rather than accrual basis.

Accuracy and Reliability

28. The accuracy of the national accounts statistics suffers from lack of sufficient data sources and statistical techniques. Sri Lanka does not have periodic comprehensive benchmarks and a system for conducting regular annual establishment surveys. A statistical business register, which would serve as the main basis for conducting sample surveys, is not available. As a result, the few surveys that are conducted do not have good sample frames. Most of the data used for regular compilation are obtained on a timely basis. However, detailed data needed to measure both output and intermediate consumption are mostly unavailable or not collected. As a result, the estimates for gross valued added are prepared directly relying heavily on fixed ratios established for the 1996 base year, often with outdated studies or ad-hoc assumptions. Quarterly indicators are used for compiling quarterly value added estimates. Except for a few key activities, the quarterly data collection procedure is essentially ad hoc. The methodology for deriving GDP at constant prices is not satisfactory. Expenditure estimates are available only annually and rely mostly on commodity flow techniques. Wherever possible, estimates are validated and checked with other sources. Analysis of revisions is made as a part of compilation process.

29. The CPIs are unreliable due to outdated weights and limited coverage. However, data collection procedures and aggregation techniques are sound. The household expenditure surveys operated by the DCS and the CBSL are based on multistage probability sample designs. Both surveys are run every five years and provide detailed data on household consumption to derive the weights of the CPIs. As noted above, the weights for the CCPI have never been updated. Also, there is no laid down policy for updating the weights for the other two CPIs, which still relate to 1985/86 for the GCPI and 1996/97 for the CD-CPI.

30. The PPI weights still relate to 1974 and the basis of their derivation is not known. Price data are collected on a monthly basis from an outdated enterprise list. Though the enterprise list is never changed, products which cease to be produced are replaced with similar ones. There are no validation procedures for the source data and the PPI is never revised even though some price quotes are late in arriving.

31. With regard to government finance statistics, annual data on budgetary central government and provincial councils are reported separately. The reason is that the provincial council data do not include data on functional classifications. The data available by economic type of transaction on budgetary central government and provincial governments permit the consolidation of data on general government for inclusion in the GFS annual compilation cycles. Annual data on local governments, which comprise a small part of general government operations and are based on accrual accounting, are not routinely collected. The integrity of GFS, as related to other statistical areas, such as monetary data, is not routinely validated. There are incomplete explanations for divergences between fiscal and monetary statistics on government financing by banks. Accordingly, the associated steps needed to report reconciled statistics are not identified. In any event, the revisions of monthly and annual fiscal data are not routinely analyzed to assess the appropriate use of provisional data.

32. A comprehensive data collection program is in place for monetary statistics covering all deposit-taking institutions. Accounting records form the basis for the reported balance sheets and supplementary tables. The reported data cover a broad range of financial instruments and economic sectors. Moreover, the balance sheets generally contain sufficient detail for classifying assets and liabilities by financial instrument and by economic sector, as defined in the MFSM. Nevertheless, a review for consistency with its recommendations may yield enhancements; for example, by seeking a separate identification of securities and shares, households/individuals and private enterprises, and, to the extent possible, disaggregation of some "other" reported items, where they are relatively large. Procedures are in place for checking monetary data for internal consistency with other datasets. The timeliness of reporting to CBSL by banks by the 20th of the subsequent month is generally in line with the CBSL directives. Delays arise due to inadequate communication links between outlying bank branches and regional offices, so that comprehensive bank data are generally available within 4-6 weeks from the end of the month. Regional development banks’ and finance companies’ data are currently available 8-9 weeks and 7-8 weeks, respectively, after the end of the reference month because of compilation and communication problems.

33. Although a data collection system has been developed for balance of payments statistics, there are some weaknesses in source data, techniques, validation and revisions’ studies. For example, the ITRS and surveys do not cover all institutions, enterprise accounts with banks abroad, and non-cash transactions (e.g., intercompany accounts, reinvested earnings etc.). The CBSL has developed some statistical techniques (price/value analysis, trend analysis, and timing adjustments to trade statistics etc.) to improve the accuracy and reliability. Although some service items (transport, travel, and government) are compared with ITRS data, there is no systematic estimation of undercoverage, non-surveyed or nonrespondent components for survey data. The ITRS does not systematically require financial institutions to reconcile reported transactions data with stock data. Revision studies are not a regular procedure in data compilation. The Annual Report tries to determine major factors contributing to errors and omissions in the accounts, but it is not clear to what extent this information guides compilation policy, or is made available to guide users.


34. An informal mechanism is used to identify users’ needs, but explicit reviews or consultations are not conducted to monitor the relevance with respect to national accounts to the users. Periodicity and timeliness are in line with the SDDS. Although the time series are usually consistent over time it is not possible to analyze structural ratios because of limited data. Also, a proper reconciliation framework such as supply and use tables is not produced. The quarterly figures are made consistent with the annual estimates by simple proration of the differences between the sum of four quarters and independent annual values. The revision practice is reasonably consistent from year to year, but a revision calendar is not publicized. Preliminary data are indicated as such.

35. There is no systematic approach to assess the needs of users for either the PPI or the CPIs. Periodicity and timeliness of the CCPI and the CD-CPI are in line with the SDDS. The timeliness of the PPI does not meet the SDDS requirements. The CPIs and PPI are consistent over time. CCPI is not consistent with the other CPIs because of the outdated weights. No checks are made to ensure that movements in the PPI are consistent with that of other price indices.

36. The MOFP and the CBSL prepare comprehensive government finance statistics on an annual basis with a lag of two quarters. Budget management and accounting systems provide summary records of monthly budgetary central government transactions and debt in two months after the end of the reference month, as against the one month timeliness in the SDDS. Fiscal data for "other expenditure" of central government is calculated as a residual; they do not reflect actual data and thereby promote transparency. MOFP’s processes for gauging relevance and practical utility of its statistics in meeting users’ needs are limited, and no routine surveys or reviews of users take place. The procedure of reporting monthly fiscal data as soon as data are available is not documented and reported. GFS data are not reviewed adequately to ensure consistency with other data such as monetary data.

37. The CBSL assesses on an ongoing basis the analytical relevance of the monetary and statistical compilation methods for appropriately capturing macroeconomic, institutional and financial sector developments. Two major studies (in 1997 and in 1999) led to a revision in the coverage of monetary surveys and initiated publication of broader money aggregates (monthly M2b and annual M4, respectively). Data periodicity, but not the timeliness, follows the SDDS recommendations. Interbank positions among commercial banks, and data reported for statutory reserve purposes, show that there are no large variations among data. In particular, the CBSL has a policy for checking monetary data on net foreign assets and net claims on government for consistency with balance of payments and government finance statistics. The general CBSL policy is that major data revisions, arising from methodological changes, are first published in the CBSL’s Annual Report, along with extensive methodological commentary and background analysis on the factors that led to the revisions.

38. The CBSL organizes monthly meetings with banks to gauge users’ views about the usefulness of balance of payments. The statistics are disseminated on a quarterly basis with a two-month lag, that meets the periodicity and timeliness prescribed by the SDDS. Trade data also meet the SDDS periodicity and timeliness requirements. International reserves data are compiled and disseminated on a weekly basis with one week lag. Comprehensive external data are compiled on a yearly basis. The balance of payments statistics are generally consistent over time and with other datasets, although there is a variable errors and omissions item in the BOP statistics. When the CBSL implemented the BPM5 framework in 1997, the annual and quarterly data were revised and disseminated in the Annual Report, and on the CBSL’s website (including a comparison table with the old data). Revisions do not follow a regular schedule. The causes of the revisions are sometimes explained in the reports.


39. The dissemination of national accounts statistics is generally satisfactory. However, the quarterly GDP estimates are published by grouping all activities into five groups. Data are usually released on a regular basis, but advance notification of release dates is not practiced. Additional non-published detailed data are not provided due to concerns about the quality of the disaggregated data. Some internal documentation on sources and methods exists, but metadata on data compilation is not prepared for publication. A list of publications is included in most CBSL publications and at its website. A central contact point for users is available, but no specific contact point for national accounts is publicized.

40. There is no advance release calendar for price statistics. However, there is a legal requirement to publish the CCPI on the last day of the reference month. Data are disseminated via press releases, publications, and on each organization’s website. Certain data, such as the PPI, are not published as press releases. Only limited metadata is available for the CPIs and there is nothing for the PPI. Additional non-published detailed data are not provided due to concerns about the quality of the disaggregated data. The CBSL has a help desk, but users often find that it is difficult to get through to the appropriate official.

41. Annual government finance statistics on central and provincial governments are disseminated by both the CBSL and the MOFP. The annual comprehensive GFS in the CBSL Annual Report allows major aggregates and balancing items to be identified and related to detailed underlying data. This information is equivalent in detail to that set out in the GFS tables. The dedicated annual government finance publication is the MOFP’s Trends in Public Finance, the most recent issue of which is for 1999. It covers summary annual and sub annual data on budgetary central government and provincial councils. Monthly and quarterly GFS, in summary presentations, are published in the CBSL Monthly Statistical Bulletin. The actual date of official publications with GFS is not pre-announced. Statistical publications are made available to all users simultaneously. Reported metadata on definitions, concepts, and compilation procedures are not sufficient. No specific contact person for GFS is publicized.

42. Presentation of monetary statistics is analogous to the presentation in IFS. Monetary data are disseminated in CBSL’s Annual Report, Monthly Bulletin, Monthly Indicators and Selected Weekly Indicators releases. Data are also posted on the CBSL’s website. More comprehensive data are published in the Monthly Bulletin and the Annual Report, which also carry detailed footnotes and commentary. A CBSL document Notes on Statistical Tables in the Monthly Bulletin (1980) provides a comprehensive description of the data published in the Monthly Bulletin. Monetary statistics are released by CBSL to all users simultaneously, but there is no pre-announced schedule for release of weekly and monthly data. Only CBSL senior management can sanction provisions of any unpublished information. The Director of Information Department is available to clarify issues relating to press releases and published data; however, this information is not publicized. A list of CBSL publications is printed in the back of every Monthly Bulletin.

43. Preliminary quarterly balance of payments statistics are disseminated via a press release, by posting on the CBSL’s website, and in the Monthly Bulletin. The presentation broadly follows BPM5 standard categories with debit and credit items provided separately for all components. Data in the Monthly Bulletin and the Annual Report carry detailed footnotes. More comprehensive and detailed balance of payments data are published in the Annual Report, which, by law, has to be published within four months from the end of the reference year. Some components of the BOP statistics are disseminated more frequently in the Selected Weekly Indicators (exchange rates, international reserves), and Monthly Indicators (external trade and some services). In principle, attempts are made to assist users with non-published sub-aggregates subject to the approval of CBSL management. The BOP statistics are released by CBSL to all users simultaneously with no regularly publicized schedule. The documentation on methodology is not easily accessible. Assistance to users is through the Information Department, although the contact person is not publicly identified.

IV. Users’ Views

44. With the help of the IMF’s Senior Resident Representative in Colombo, the mission organized a survey of data users, followed by a meeting with a cross-section of data users in Sri Lanka to ascertain their views on the relevance and usability of published macroeconomic statistics. About twenty five participants from banks, the stock market, rating agencies, academia, the financial press, and research institutions participated in the discussion at the CBSL. While users are generally satisfied with the broad range of statistics being disseminated by the CBSL (and to a smaller extent the DCS and MOF), they expressed several concerns with the coverage, timeliness, reliability, and accessibility of macroeconomic statistics. Many users were concerned about the lack of timeliness of the Monthly Bulletin, particularly the delays and uncertainties about its actual release date. Some delays result in the late release (2-3 months) of key data essential for market efficiency and performance, particularly affecting monetary and government finance statistics. Users also questioned the overall accuracy and reliability of the data in the absence of up-to date and pertinent metadata. In particular, many users called for comprehensive documentation on data sources and techniques to be made easily accessible.

45. An additional concern was their apparent inaccessibility to reports and/or personnel of compiling agencies. Users frequently had difficulty contacting appropriate personnel of CBSL to provide clarifications of data, as the Information Department of the CBSL could not provide prompt responses. Users also expressed concerns about the unreliability of data and, inconsistencies, and nontransparency within datasets such as national accounts, prices, fiscal and trade data. Further, users pointed to duplication of effort, with compiling agencies (CBSL and DCS) producing similar statistics (CPI) with sometimes different results. All participants strongly advocated the implementation of advance release calendars by the CBSL and DCS as a way of ensuring data timeliness and equal access by data users.

V. Fund Staff Recommendations

46. Based on the results of the data quality assessments and subsequent technical discussions with the Sri Lankan authorities in the respective statistical agencies, the mission proposes the following measures for their consideration to bring Sri Lanka’s statistical practices into greater compliance with international guidelines and improve the usefulness of the data for users:

National accounts

  • As an overriding step, clarify responsibility for compiling national accounts statistics.

  • Develop plans for implementing the 1993 SNA. Build into the plan the following:

    • -Standard classification of individual consumption by purpose (COICOP).

    • -Standard classification of the functions of government transactions (COFOG).

    • -Consistent valuation and basic prices for valuing output and value added.

  • Recognizing that source data development is a long-term undertaking, develop an action plan to strengthen existing statistics but with a view to implement the 1993 SNA. Key features could include:

    • -Create a statistical business register covering private non-agriculture business establishments with information from the population census (2001).

    • -Establish a system for the annual establishment surveys covered in the register.

    • -Institutionalize quarterly surveys based on proper sampling methods.

    • -Strengthen the capacity of the DCS to collect primary data.

  • Strengthen statistical techniques including:

    • -Improve methods for constant price estimates.

    • -Calculate explicitly output and intermediate consumption.

    • -Use proper benchmarking techniques to remove discrepancies between quarterly and annual national accounts.

  • Implement in the near term dissemination policy changes that increase the transparency, serviceability, and accessibility of the national accounts data. Key among these changes are:

    • -Publish, in consultation with users, more detailed quarterly GDP estimates.

    • -Implement and publicize advance release calendars.

    • -Prepare and publish detailed metadata on sources and methods.

Consumer price index

  • As an overriding objective, rationalize the CPI program to remove the current duplication of effort resulting from multiple CPIs.

  • Recognizing that user involvement could be an important force for innovation and change, set up regular meetings/seminars with users and/or undertake surveys to obtain user views on the CPI and ideas for its improvement.

  • Develop medium-term plans to improve source data.

  • Implement dissemination policy changes in the near-term such as publicizing an advance release calendar, and the production and publication of detailed metadata for the CPI.

Producer price index

  • Recognizing that user involvement could be an important force for innovation and change, set up regular meetings/seminars with users and/or undertake surveys to obtain user views on the CPI and ideas for its improvement in the near term.

  • Recognizing that the development of source data is a long-term undertaking, make plans to develop a new PPI, including current weights and a viable collection system.

  • Implement dissemination policy changes such as publicizing an advance release calendar for the CPI, in line with the IMF’s SDDS.

  • Produce and publish detailed metadata for the PPI.

General government finance statistics

  • As an overriding objective, make plans to implement an automated management and accounting system, recognizing its resource-intensive dimensions. Build into that plan:

    • -Accurate and timely reports with cash and accrual data, including those for the new GFS methodology.

    • -Complete compilation of balance sheets of government activities.

  • Improve source data and statistical techniques for the existing statistics including:

    • -Report separately data on residual calculations to allow observers and analysts to examine more transparent fiscal data.

    • -Examine the 2000 survey of all local government activities, with a view to collecting and including these in the consolidated data on general government.

  • Improve in the near term, the reported metadata on the concepts, definitions, and classification systems used in compiling government finance statistics.

Monetary statistics

  • As an overriding objective, and taking into account the institutional and resource dimensions of the situation, develop plans for implementing fully the recommendations of the MFSM, including:

    • -Review data collection systems with the view to obtaining, where needed, sufficient instrument and sectoral detail recommended in MFSM.

    • -Review valuation procedures for consistency with the market or fair value basis.

  • In the immediate term, establish a policy for providing advance notice to the public regarding near term methodological revisions.

  • Improve source data and statistical techniques over the medium term including:

    • -Review data collection procedures with a view to obtaining, where needed, sufficient instrument detail recommended in the MFSM.

    • -Ascertain, in consultation with the Fund’s Treasurer’s Department, accounting procedures for the Fund accounts.

  • Implement dissemination policy changes over the coming months to improve the transparency and serviceability of monetary statistics including:

    • -Investigate and take the steps leading to the publication of Financial Survey on a regular monthly basis with a 4-week timeliness.

    • -Expedite publication of updated methodological manual, discussing sources and methods employed in compiling monetary statistics.

    • -Establish and publicize an advance release calendar.

    • -Publicize the CBSL’s program for assisting data users, including contact person.

  • Establish an advisory body charged with reviewing the quality of monetary statistics.

Balance of payments statistics

  • In the near term, strive to obtain consistency with the BPM5 in the sectorization and classification of transactions for the current (e.g., imports f.o.b) and financial account.

  • Recognizing that source data development is a long-term undertaking, develop a plan to strengthen and improve the current BOP statistics including:

    • -Expand the coverage of BOP statistics to remedy inadequate coverage of services (e.g., construction, communications, and computers) and income (compensation of employees and reinvested income).

    • -Compile the data template on International Reserves and Foreign Currency Liquidity.

    • -Develop and compile the International Investment Position (IIP).

  • Strengthen statistical techniques including:

    • -Adopt procedures to remedy reporting weaknesses in the ITRS.

    • -Improve the reconciliation of reported transactions data with changes in stocks of financial claims.

    • -Supplement partial sample surveys with periodic benchmark surveys.

    • -Use good estimation techniques to adjust for undercoverage and nonresponse.

  • Implement dissemination policy changes to improve the transparency and serviceability of balance of payments statistics including:

    • -Develop comprehensive metadata on BOP sources, concepts, and methods.

    • -Develop an Advance Release Calendar (ARC) for the BOP statistics.


The mission was led by Emmanuel O. Kumah and comprised David V. Pritchett, Gary Barinshtein, Manik Lal Shrestha, Elva Harris (all of the IMF’s Statistics Department), and David Hughes (Expert).


A detailed description of the SDDS can be found on the IMF’s Dissemination Standards Bulletin Board (DSBB) on the Internet at


For the purpose of the Data Quality Assessment Framework for national accounts, the assessment focuses on the annual and quarterly national accounts compiled by the CBSL. However, an assessment of the DCS national accounts is also provided in the Appendix I on detailed assessment using DQAF.


The assessment covers the CBSL’s quarterly and annual national accounts.


The assessment covers the official CPI (CCPI).