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Indonesia: Report on the Observance of Standards and Codes—Data Module

Author(s):
International Monetary Fund
Published Date:
July 2005
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I. Overall Assessment

1. Indonesia subscribed to the Special Data Dissemination Standard (SDDS) on September 24, 1996; posted metadata on the Dissemination Standards Bulletin Board (DSBB) on May 21, 1997; and met the SDDS specifications for the coverage, periodicity, and timeliness of the data, as well as for the dissemination of advance release calendars on June 2, 2000. Since then, Indonesia has been in observance of the SDDS, regularly updating its metadata and maintaining its advance release calendar for all data categories. Indonesia currently uses the flexibility option for timeliness and periodicity of the labor market and general government operations data. Appendix I provides an overview of Indonesia’s dissemination practices compared to the SDDS.

2. The Report on the Observance of Standards and Codes (ROSC)—Data Module contains the following main observations. The Indonesian statistical system is undergoing fundamental transition. The statistical agencies are dealing with important challenges: they are at various stages of adopting and implementing internationally recognized best practice methodologies for each major macroeconomic dataset; they are seeking to adapt the statistical system to measure ongoing structural change in the economy, including increasing global integration; and they are reforming the statistical system to conform to the new reporting and information requirements of major institutional change, including the decentralization of governmental authority. Indonesia’s macroeconomic statistics and statistical base are broadly adequate to conduct effective surveillance at this time. The system is characterized by a strong legal environment that encourages objectivity and professionalism on the part of the statistical agencies and that underpins the overall integrity of the statistical process. The main needs are to widen the scope of the statistical framework to capture insufficiently measured economic activities and structural change, strengthen and expand the collection and analysis of the basic source data that underlie the aggregate macroeconomic statistics, improve and formalize cooperation among the major statistics-producing agencies to foster greater consistency of data among the major datasets, and accelerate the full implementation of best practice methodologies. As the quality of the statistical managers is high, and suitable levels of resources are being allocated to support the system and effect change, prospects are good that the system will adapt successfully to the changing economic environment.

3. In applying the IMF’s Data Quality Assessment Framework (DQAF), July 2003, the remainder of this section presents the mission’s main conclusions. The presentation is done at the level of the DQAF’s quality dimensions, by agency for the first two dimensions and across datasets for the remaining four.

4. With regard to prerequisites of quality, various laws and regulations ensure that the Badan Pusat Statistik (BPS), Bank Indonesia (BI), and the Ministry of Finance (MoF) have both responsibility and suitable authority to collect, compile, and disseminate the relevant statistics. Data-sharing arrangements are generally adequate between the primary data-compiling agencies and other data-producing agencies, although local government data can still be supplied under differing account formats, which greatly complicates data processing of government finance statistics (GFS). Resources are broadly commensurate with the needs of the statistical program. BPS and BI devote considerable attention to monitoring the overall quality of the statistical program and ensure that statistics remain relevant to users’ needs through regular contacts with users. In the case of the MoF, and no doubt due to the more nascent state of development of its statistical program, it would be desirable to develop a more explicit focus on the needs of data users in their operations. As to assurances of integrity, formal safeguards of the independence of statistical compilers are provided in the Statistics Law of Indonesia No. 16 of 1997 (1997 Law) and the Republic of Indonesia Act No. 23. While no similar formal arrangements are afforded to compilers of GFS, no evidence of interference exists. Statistical agencies are free to choose methodologies and appropriate data sources. Staff are well-trained, exhibiting a high degree of professionalism in their work. The terms and conditions under which statistics are compiled are generally readily available to the public. The government does not have access to statistics prior to their release, except in the case of GFS. Staff of the statistical agencies are held to a high ethical standard in the conduct of their work.

5. Concepts and definitions, in general, are methodologically sound, broadly conforming to internationally accepted standards. Monetary statistics follow the Monetary and Financial Statistics Manual (MFSM). Balance of payments statistics broadly conform to the Balance of Payments Manual, fifth edition (BPM5). Data on quarterly and annual GDP generally conform to the System of National Accounts 1968 (1968 SNA), with some changes conforming to the System of National Accounts 1993 (1993 SNA). GFS is in the process of transition to the Government Finance Statistics Manual 2001 (GFSM 2001), but local government statistics are at present compiled on a nonstandard basis. Some deficiencies appear in the scope of the datasets. Monetary statistics exclude data on mutual funds that issue deposit-like liabilities; the balance of payments statistics exclude some resident/nonresident transactions; GFS are restricted to the budgetary transactions of the general government. The basis for recording transactions, with the exception of GFS, mostly conforms with internationally accepted methodologies.

6. The accuracy and reliability of the macroeconomic statistics, while generally sound, are adversely affected in some instances by weaknesses in source data collection activities. For instance, comprehensive source data for the national accounts are collected from production industries at the expense of the nonfinancial service industries, while more effective use could be made of the International Transactions Reporting System (ITRS) in compiling balance of payments statistics. Procedures for assessing source data are generally adequate. Assessment and validation procedures for intermediate data and statistical outputs are broadly adequate. Statistical techniques include the extensive use of historical benchmarks in the case of the national accounts. Revision studies are mostly undertaken on an ad hoc basis.

7. As to serviceability, the periodicity and timeliness of the statistics meet or exceed SDDS standards, with the exception of the timeliness of general government operations. Datasets are generally internally consistent; however, the errors and omissions component of the balance of payments has been persistently large. Inconsistencies arise between merchandise trade data in the national accounts and the balance of payments, between GFS domestic financing data and monetary statistics, and between GFS and the national accounts. None are reconciled. Preliminary and revised data are clearly identified, but revision studies are only infrequently made public.

8. Accessibility of data is good, primarily through the websites of the data-producing agencies and in regular publications. Data for the most part are presented clearly with appropriate detail. Statistical publications and websites identify suitable contact points for user assistance. The lack of detailed metadata, for users of balance of payments and GFS, is a serious shortcoming.

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

II. Assessment by Agency and Dataset

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

Table 1.Indonesia: Data Quality Assessment Framework, July 2003—Summary Results
Key to symbols: O = Practice Observed; LO = Practice Largely Observed; LNO =Practice Largely Not Observed; NO = Practice Not Observed; NA = Not Applicable
DatasetsNational

Accounts
Government

Finance

Statistics
Monetary

Statistics
Balance of Payments

Statistics
Dimensions/Elements
0. Prerequisites of quality
0.1 Legal and institutional environmentOLOOO
0.2 ResourcesOLOOO
0.3 RelevanceOLNOOO
0.4 Other quality managementOLNOOO
1. Assurances of integrity
1.1 ProfessionalismOLOOO
1.2 TransparencyOLNOOLO
1.3 Ethical standardsLOOOO
2. Methodological soundness
2.1 Concepts and definitionsLOLNOOLO
2.2 ScopeLOLNOLOLO
2.3 Classification/sectorizationOLOOLO
2.4 Basis for recordingLOLNOOLO
3. Accuracy and reliability
3.1 Source dataLOLNOLOLO
3.2 Assessment of source dataLOLOOO
3.3 Statistical techniquesLOLOOLO
3.4 Assessment and validation of intermediate data and statisticalLOLOLOO
outputs
3.5 Revision studiesLNOLNOOO
4. Serviceability
4.1 Periodicity and timelinessOLOOO
4.2 ConsistencyLOLOLOLNO
4.3 Revision policy and practiceLOOOO
5. Accessibility
5.1 Data accessibilityLOLOOO
5.2 Metadata accessibilityOLNOOO
5.3 Assistance to usersOOOO
Practice observed: current practices generally meet or achieve the objectives of DQAF internationally accepted statistical practices without any significant deficiencies. Practice largely observed: some departures, but these are not seen as sufficient to raise doubts about the authorities’ ability to observe the DQAF practices. Practice largely not observed: significant departures and the authorities will need to take significant action to achieve observance. Practice not observed: most DQAF practices are not met. Not applicable: used only exceptionally when statistical practices do not apply to a country’s circumstances.
Practice observed: current practices generally meet or achieve the objectives of DQAF internationally accepted statistical practices without any significant deficiencies. Practice largely observed: some departures, but these are not seen as sufficient to raise doubts about the authorities’ ability to observe the DQAF practices. Practice largely not observed: significant departures and the authorities will need to take significant action to achieve observance. Practice not observed: most DQAF practices are not met. Not applicable: used only exceptionally when statistical practices do not apply to a country’s circumstances.
Table 2a.Indonesia: Assessment of Data Quality—Dimensions 0 and 1—Badan Pusat Statistik
0. Prerequisites of quality1. Assurances of integrity
Legal and institutional environmentProfessionalism
The 1997 Law, together with Decree No. 6 of 2000, gives the BPS a strong legal basis for compiling statistics. The BPS has reasonable data-sharing and coordination procedures with other government agencies. Confidentiality of respondents’ data is guaranteed under the 1997 Law. The BPS has effective procedures for protecting and disposing of respondents’ data. The 1997 Law specifies penalties for respondents who do not supply relevant data. However, BPS prefers to use persuasion in such cases.



Resources

Staff and computer resources are sufficient to conduct the existing statistical program. Staff are well-trained and turnover is low. The existing accommodation is conducive to good working conditions. Effective procedures ensure the efficient use of resources.
The 1997 Law established the statistical independence of the BPS. The director can only be appointed, and dismissed, by the president. Professionalism is actively promoted and supported within the BPS. For instance, recruitment and promotion are based on ability and expertise. All staff receive internal training in relevant subjects. Every opportunity is also taken to attend international courses and seminars. Peer group reviews of work process are regularly undertaken. Staff are encouraged to write and publish methodological articles. The 1997 Law ensures that the BPS is free to choose whatever it considers are appropriate data sources and methodologies. The BPS decides on the method and timing of data dissemination. The BPS undertakes press conferences to explain its data to the media and, thus, reduce the chance of misinterpretation. When such misinterpretation does take place, the BPS will contact the originator to ensure that the mistake is corrected and explained. All media references to statistics are identified and circulated within the BPS.
Relevance

The 1997 Law specified the setting up of a Statistics Community Forum, open to any interested person from any walk of life. It meets four times a year and the BPS and other participants can raise any statistical issues. There are mechanisms to raise issues outside this program, if necessary. The BPS is very active internationally, taking part in as many meetings and seminars as possible. The BPS has not undertaken any formal studies to identify new and emerging data requirements. However, they are now planning a survey on the quality of their statistics.
Transparency

The 1997 Law is included on the BPS website. The BPS publications identify where additional information can be found. There is no government access to statistics prior to their public release. Publications clearly identify the BPS by name and its logo. Whenever BPS data appear in the publications of other bodies, the source must be clearly identified. All major changes to statistics are announced in advance in the relevant BPS publications and on its website. Minor changes will just be noted when they are introduced.
Other quality management

Management is committed to data quality and cascades this down through the ranks. This issue is also covered in staff training. The BPS also demonstrates its commitment to quality to the wider community. Management monitors quality, and it is integral to the planning process.
Ethical standards

There is no written guidance on ethical standards. However, all staff are regularly reminded of the need to keep data confidential. Also, all civil servants are subject to the application of general ethical standards as set out in Government Regulation 30/1980.
Table 2b.Indonesia: Assessment of Data Quality—Dimensions 0 and 1—Ministry of Finance
0. Prerequisites of quality1. Assurances of integrity
Legal and institutional environmentProfessionalism
The responsibility for producing GFS is clearly assigned to the MoF by Law 33/2004, which mandates the setting up of a national fiscal database covering all levels of government and dissemination of information from that database to the public. The MoF works closely with the Ministry of Home Affairs (MOHA) to determine accounting standards for local governments. Local government data can be supplied under differing accounting formats, which greatly complicates processing by the MoF. Law 33/2004 gives the MoF authority to collect local government data and provides sanctions for refusal to cooperate. However, there are no arrangements to obtain data for nonbudget transactions.No laws or other formal arrangements support the professional independence of GFS compilers, but there has been no attempt by the authorities to influence statistical outputs. MoF GFS staff are not professional statisticians, but they have a generally appropriate background to compile and disseminate GFS. The MoF has retained the expertise of staff who have attended GFS training courses in Washington. The data sources used are obvious and appropriate, and the content and format of GFS are based on the IMF’s A Manual of Government Finance Statistics, 1986 (GFSM 1986) standards. The MoF can respond to correct misinterpretation or misuse of GFS.
Resources

Staff resources are adequate, but computing resources, especially software, impede efficient compilation processes. Staff training is not adequate. Periodic reviews of staff and systems are carried out, but no cost-benefit analysis is applied to statistical analyses. No specific funding is provided for statistical work, which inhibits planning for statistical developments.
Transparency

The terms and conditions under which GFS are compiled and disseminated are imbedded in various laws and by-laws, and the internal administrative rules of the MoF and MOHA. No information on the terms and conditions applying to GFS is made public. The government has internal access to GFS prior to their release to the public, but no information regarding this access is made public. The MoF is usually, but not always, identified as the source of GFS in published data. Advanced notice of changes to data sources or methodology is given to the public.
Relevance

The assessment of the relevance and practical utility of statistics in meeting users’ needs is based on feedback from users, and no systems are in place to assess the usefulness of statistical products.
Ethical standards

GFS staff are subject to the application of general ethical standards applying to all MoF (and other civil service) staff, and these standards are an important part of initial and ongoing staff training. MoF GFS staff are also subject to the provisions of the statistics law, to the extent that these provisions apply to GFS.
Other quality management

Training programs concentrate on quality issues, but because of the lack of a user orientation, MoF staff tend to focus on procedures rather than products. No processes are in place to specifically monitor the quality of GFS, or obtain information from users on new and emerging data requirements.
Table 2c.Indonesia: Assessment of Data Quality—Dimensions 0 and 1—Bank Indonesia
0. Prerequisites of quality1. Assurances of integrity
Legal and institutional environment

BI collects, compiles, and disseminates monetary and balance of payments statistics. The Republic of Indonesia Act No. 23 (May 17, 1999) endows the BI with the legal authority for collecting data for monetary statistics from banks. Other legislations—namely, Republic of Indonesia Act No. 24 and related regulations—similarly endow the BI with the legal authority for collecting data for balance of payments statistics from nonbank financial institutions. These laws and regulations make the reporting of data mandatory for reporting institutions. The Republic of Indonesia Act No. 23 (May 17, 1999) also obliges the BI to safeguard the confidentiality of individual reporters’ data, and imposes penalties on those who might disclose those data. BI has broadly adequate data-sharing arrangements with the MoF and BPS and, more recently, with the Directorate General of Customs, which delivers import and export data online to the BI.
Professionalism

Staff at the BI maintain a high degree of professionalism. The Republic of Indonesia Act No. 23 (May 17, 1999) emphasizes the independence of BI in pursuing its goals by prohibiting interference from others, including government agencies. Professionalism is actively promoted and supported within the organization—for example, the process of recruiting and promoting staff, which takes into account a candidate’s professional and educational qualifications, is primarily merit-based.
Resources

Staff resources are adequate to compile monetary and balance of payments statistics. The compilation of monetary and (to a less extent) balance of payments statistics is highly automated, and computing resources have been adequately distributed between the staff. BI staff receive formal training in the methodologies by attending the various regional training courses organized by the IMF Statistics Department.
Transparency

BFs website (www.bi.go.id) publicizes the terms and conditions under which monetary and balance of payments statistics are collected, processed, and disseminated. No internal governmental access to statistics prior to their release exists. BI’s statistical publications clearly identify them as the products of the BI. BI informs users in advance of major changes in methodology in the case of monetary statistics, but in the case of balance of payments statistics, it does so concurrently with the publication of such changes.
Relevance

BI monitors the relevance of monetary and balance of payments statistics through a survey form for user satisfaction provided through the BI website and email addresses provided on all BI publications. Staff members participate in statistical meetings/seminars organized by the international and regional organizations or by professional organizations. They also hold press conferences on the usefulness of statistics and visit universities to conduct seminars on statistics, and take these opportunities to identify user needs.
Ethical standards

BI’s Board of Governors provides guidelines for staff behavior. These guidelines are available also through Job Manuals. Staff behavior is reviewed as one of the aspects of BFs annual performance review.
Other quality management

BI has well-established processes to maintain or improve the quality of its statistical products. These include initiatives taken to enhance the awareness of quality in statistics (Mission and Vision Statement); follow-up actions to verify reported data; and programs for providing various types of training to staff.
Table 3a.Indonesia: Assessment of Data Quality—Dimensions 2 to 5—National Accounts
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
Concepts and definitions

The national accounts are broadly in line with the 1968 SNA, but are in the process of being updated to the 1993 SNA.



Scope

The published data cover annual and quarterly GDP, from both the production and expenditure approaches, and at current and constant prices. Annual supply and use tables (SUTS) are not produced. The production and asset boundaries generally conform to the 1968 SNA, but some 1993 SNA changes have been implemented. Free zones are covered in the production figures, but not in imports.



Classification/sectorization

All transactions and flows use appropriate international classifications.



Basis for recording

The valuation rules used for recording flows and stocks are generally in accordance with the 1968 SNA. However, all government data are recorded on a cash, rather than accrual, basis. Also, average monthly, rather than daily midpoint market exchange rates, are used.
Source data

There are annual censuses of production establishments with 20 or more employees. However, there is no survey of nonfinancial services. An economic census of businesses is undertaken every 10 years but is not updated in the intervening periods. The household budget survey is weak because it does not cover higher-income households.



Assessment of source data

The BPS routinely assesses source data whenever possible. Coverage of source data is not routinely assessed.



Statistical techniques

Extensive use is made of benchmark data from the five-yearly input-output (I-O) tables. Constant price techniques and coverage of informal activities could be improved.



Assessment and validation of intermediate data and statistical outputs

The five-yearly I-O tables remove the statistical discrepancy, but this is not done for intervening years. The I-O tables introduce large revisions to the annual GDP series.



Revision studies

Only ad hoc studies of specific activities are undertaken.
Periodicity and timeliness

Quarterly GDP estimates are published 45 days after the end of the period, in line with the SDDS.



Consistency

The quarterly estimates are fully consistent with the annual figures. The current and constant price figures are totally comparable. For the periods following the 2000 I-O tables, the statistical discrepancy has been shown separately in the publications. The policy is only to publish figures from the last I-O year. This means that revisions made to earlier years are not available to users other than the BI. There are inconsistencies with BI in imports and exports; and, possibly, with MoF in respect of local government figures, but these have not been investigated.



Revision policy and practice

There is an established revision policy, which is always kept and is fully explained to users. Preliminary data are clearly indicated in the publications. The results of the ad hoc revision studies are not published.
Data accessibility

The GDP figures are published in a clear manner with different levels of detail, as appropriate to the specific publication. Analysis of the current period developments is also given. Seasonally adjusted quarterly estimates are not published, even though they are available. An advance release calendar is published. The data are available to all users at the same time via a press release and on the BPS website. Some additional breakdowns can be supplied as long as they do not breach the confidentiality rules.



Metadata accessibility

A comprehensive methodological guide is included in the annual publication, in Indonesian and English. This information is also on the BPS website. The BPS updates the SDDS metadata as soon as a change occurs. Different levels of metadata are produced to meet the needs of the intended audience.



Assistance to users

All statistical releases identify a relevant contact person. A catalog in Indonesian is published every year. Details in Bahasa and English are also given on the BPS website and this is kept up-to-date.
Table 3b.Indonesia: Assessment of Data Quality—Dimensions 2 to 5—Government Finance Statistics
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
Concepts and definitions

GFS is in the process of transition toward GFSM 2001, expected to be completed by 2008. At present, GFS for the central government is on the GFSM 1986 basis, but local government is on a nonstandard conceptual and classificatory basis.



Scope

GFS covers only the central and local government budget sectors, excluding extrabudgetary funds. The MoF does not have a register of public sector units. The full range of GFSM 1986 tabulations is not available.



Classification/sectorization

GFS is based on administrative rather than institutional sectors. The local government sector uses nonstandard classifications. Functional and economic-type classifications based on GFSM 2001 come into force in 2005.



Basis for recording

Nonfinancial assets are valued at historical prices. Recording is done on a cash basis.
Source data

GFS are compiled from comprehensive central and local government budget data. Most, but not all, data support the required classifications but not the required valuation and basis for recording.



Assessment of source data

Routine assessments of source data are carried out for the central government. Local government data are assessed only when output problems are identified.



Statistical techniques

No statistical techniques are used to assess local government data. Compilation procedures are not documented. Bridge tables have been developed only for the central government.



Assessment and validation of intermediate data and statistical outputs

Regular meetings are held between the MoF and BI to review the consistency between GFS and monetary and balance of payments data. No reconciliation checks between stocks and flows are carried out.



Revision studies

No regular revision studies are carried out.
Periodicity and timeliness

Periodicity meets SDDS standards, but timeliness of general government operations data does not meet SDDS standards.



Consistency

Annual and subannual data are consistent. Time-series data are only available from 2001. Discrepancies exist between GFS and monetary data, and between deficit and financing (especially monthly and quarterly).



Revision policy and practice

Data revision is limited to the preliminary-to-final revision cycle, which is stable and predictable. Preliminary and revised data are clearly identified.
Data accessibility

GFS are disseminated mainly through the MoF websites. Central government GFS are disseminated according to GFSM 1986 recommendations, but do not provide equivalent coverage or detail. Local government GFS are disseminated in nonstandard formats. There are no preannounced release dates, but the release dates follow a well-established cycle. GFS are made available to official users before they are released to the public. Additional detail is available from the MoF, but its availability is not advertised.



Metadata accessibility

There is no published document which describes the concepts and methodology of GFS in Indonesia, except for summary information included on the SDDS website.



Assistance to users

Liaison officers or contact points are included on the websites and in press releases. GFS can only be obtained from the websites or by direct application to the MoF. These services are provided free of charge.
Table 3c.Indonesia: Assessment of Data Quality—Dimensions 2 to 5—Monetary Statistics
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
Concepts and definitions

The concepts and definitions conform to the methodology of the MFSM.



Scope

Coverage includes BI, all resident commercial banks (head offices and branches), and rural banks, but it excludes mutual funds that issue deposit-like liabilities.



Classification/sectorization

Classification and sectorization are in line with the MFSM.



Basis for recording

The basis for recording (1) uses market prices or fair prices for valuation, (2) relies on accrual accounting, (3) performs grossing and netting operations correctly, and (4) follows the MFSM methodology.
Source data

The source data on BI, commercial banks, and rural banks provide sufficient detail to classify sectors and instruments in line with the MFSM methodology. The source data on mutual funds, however, do not meet statistical requirements.



Assessment of source data

The assessment of source data is sound.



Statistical techniques

The statistical techniques used are sound.



Assessment and validation of intermediate data and statistical outputs

The intermediate data are assessed and validated against data from certain sample surveys. Reported interbank positions between the BI and commercial banks are not consistent.



Revision studies

Revisions are due to the finalization of the rural banks data. The first revision study was prepared in March 2005 and, so far, only one revision study has been prepared.
Periodicity and timeliness

The periodicity and timeliness are in line with the SDDS requirements.



Consistency

Monetary statistics are consistent within the dataset. They are broadly consistent with the balance of payments statistics, but not with GFS.



Revision policy and practice

Revisions follow a regular and transparent schedule. The revision policy is clearly stated in the BFs publication, Indonesian Financial Statistics, February 2005. Preliminary and revised data are clearly identified.
Data accessibility

Dissemination media are adequate. The statistics are released on a preannounced schedule. Nonpublished nonconfidential data are available to users on request.



Metadata accessibility

Metadata are posted on the IMF’s DSBB in the form of SDDS metadata. The DSBB is hyperlinked to the BI website. Metadata are also available from the Indonesian Financial Statistics, February 2005.



Assistance to users

BI provides adequate assistance to users. The BI publications and website provide contact information and, in addition, the BI website provides catalogs of BFs publications, documents, and other services, which are updated regularly. The Administration Division of the BFs Directorate of Economic and Monetary Statistics provides whatever assistance the potential customers might need in placing orders.
Table 3d.Indonesia: Assessment of Data Quality—Dimensions 2 to 5—Balance of Payments Statistics
2. Methodological soundness3. Accuracy and reliability4. Serviceability5. Accessibility
Concepts and definitions

Balance of payments statistics closely follow the concepts and definitions of BPM5 with a few exceptions. Of these exceptions, the most important is that the financial account does not record separately transactions in assets and liabilities.



Scope

The scope is broadly consistent with international methodology. Not all specified resident/nonresident transactions, however, are covered and shown separately in the balance of payments.



Classification/sectorization

The sectorization of institutional units follows, but is not fully in accordance with BPM5. Notably, public enterprises are classified in the government sector.



Basis for recording

The principle of market valuation of the BPM5 is applied but not fully used to value transactions. The value of transactions derived from stock data includes valuation and other changes. Transactions are not fully on an accrual basis.
Source data

Source data for balance of payments statistics are derived from a range of sources, including ITRS. Although ITRS results are collected from commercial banks, no such results for BI are collected.



Assessment of source data

The assessment of source data is generally sound. BI monitors the accuracy of the data from surveys. Nonresponse to surveys is monitored.



Statistical techniques

Survey results are adjusted for missing data. However, data on a gross basis are not collected for some items (for example, telecommunications services). Shuttle trade is not estimated.



Assessment and validation of intermediate data and statistical outputs

Intermediate results are validated against other information, where applicable.



Revision studies

A study of the revisions to data on direct investment abroad was undertaken in 2001. Another revision was made in 2004 to the data on reserve assets with the inclusion of the Asian Bond. The latest revision was related to the implementation of online reporting of export and import transactions.
Periodicity and timeliness

Periodicity and timeliness are in line with the SDDS requirements.



Consistency

Errors and omissions are substantial over a long run. Some financial transactions are not consistent with changes in the International Investment Position (IIP). Revisions to data following online reporting of export and import data have not been carried out for historical years. Discrepancies with the BPS trade data have not been reconciled.



Revision policy and practice

The revision cycle is stable and made known to the public. The data are preliminary when first released, and are identified as preliminary. The quarterly data become final 12 months after the end of the reporting period. More adequate documentation of revisions could be included in the publication of the statistical series in the database accessible to users. While revision studies are not usually made public, the Annual Report of BI has been used to explain the cause of a significant revision.
Data accessibility

The statistics are disseminated according to the standard components of the BPM5, and with time series. Additional series are disseminated to meet a range of users’ needs with various levels of detail. The statistics are disseminated in a clear manner, but without charts to facilitate analysis.



Metadata accessibility

A summary methodology on the concepts, statistical techniques, and coverage is available on BFs SDDS, which is hyperlinked to BFs website. The monthly Indonesian Financial Statistics provides a brief overview of the concepts and definitions employed in the principal balance of payments accounts.



Assistance to users

Prompt and knowledgeable service and support are available to users of balance of payments statistics. A contact person is identified on the IMF’s DSBB for the balance of payments data category and the advance release calendar. Contact point, address, phone, fax and e-mail are identified on BFs website for enquiries on all statistics released through the website.

III. Staff’s Recommendations

11. Based on the review of Indonesia’s statistical practices, discussions with the staff of data-producing agencies, and responses from data users, the mission has developed a set of recommendations. These recommendations—designed to improve Indonesia’s adherence to the internationally accepted statistical practices—would enhance the analytical usefulness of the statistics in question. Some additional technical suggestions are included in the Detailed Assessments volume.

Cross-Cutting Recommendations

  • Harmonize macroeconomic statistics across all sectors, in particular, by addressing intersectoral discrepancies between monetary statistics and GFS, as well as those between government finance and balance of payments statistics in balance of payments and national accounts.

National Accounts

  • Update census lists of enterprises continuously with registration of new enterprises and exclusion of nonoperating expenses.

  • Introduce comprehensive annual establishment surveys for nonfinancial services industries.

  • Publish annual GDP estimates with a lengthy time series (e.g., 20 years).

  • Develop a set of annual SUTS starting from 2000.

  • Expedite the conversion to the 1993 SNA.

  • Publish quarterly seasonally adjusted GDP data.

Government Finance Statistics

  • Implement new Government Accounting Standards.

  • Strengthen the current management system to track effectively changes in government cash balances.

  • Move gradually to an accrual accounting system.

  • Set up a register of all central government public sector units, classified by institutional sector.

  • Amend accounting regulations to ensure that general government units report all transactions and balances over which they exert control.

  • Compile and disseminate GFS for the general government sector and its subsectors, within six months after the end of the reference period.

  • Set up arrangements to obtain timely preliminary data for local governments.

  • Document compilation procedures for central and local government statistics.

  • Develop GFSM 2001 operating statement, statement of sources and uses of cash, and (partial) balance sheets, to the extent possible with available data, and publish these statements on the MoF websites.

Monetary Statistics

  • Collect source data on mutual funds in a format that meets statistical requirements.

  • Expand the coverage of the monetary statistics to include mutual funds.

  • Harmonize reported interbank positions between BI and commercial banks.

Balance of Payments Statistics

  • Continue the study of “Errors and Omissions,” in cooperation with BPS and Customs.

  • Publish the Balance of Payments Division’s documentation on the methodologies used to solve various problems in the balance of payments statistics.

  • Regularize the present information campaign to improve the response rates to various surveys.

  • Prepare a study of “shuttle trade.”

  • Publish more detailed metadata.

APPENDIX I: Indonesia: Overview of Current Practices Regarding Coverage, Periodicity, and Timeliness of Macroeconomic Data Compared to the Special Data Dissemination Standard (SDDS)
D=daily; W=weekly; M=monthly; Q=quarterly; A=annual; NA= not applicable; NLT= no later than
SDDS Data CategoryCoverage

(Meets SDDS)
PeriodicityTimelinessComments
SDDSIndonesiaSDDSIndonesia
Real Sector
National accountsYesQQ1QQ
Production indexYesMM6W6W
EmploymentYesQA1QNLT 6MSee Footnote 1.
UnemploymentYesQA1QNLT 6MSee Footnote 1.
Wages/EarningsYesQQ1Q15WSee Footnote 2.
Price index: Consumer pricesYesMM1M3D
Price index: Producer pricesYesMM1M1M
Fiscal Sector
General government or public sector operationsYesAA2Q9MSee Footnote 3.
Central government operationsYesMM1M1M
Central government debtYesQQ1QNLT 1Q
Financial Sector
Analytical accounts of the banking sectorYesMM1MNLT 4W
Analytical accounts of the central bankYesMW2W2W
Interest ratesYesDDNA1W
Stock market: Share price indexYesDDNAD
External Sector
Balance of paymentsYesQQ1Q3M
International reserves and foreign currency liquidity (Foreign assets of Bank Indonesia)YesM (W recommended)W for official reserves. M for reserves template1W for official reserves 1M for the reserves templateNLT 5WD for official reserves. NLT 1M for reserves template
Merchandise tradeYesMM8WNLT 1M
International Investment PositionYesAA3Q9MSee Footnote 4.
External debtYesQQ1QNLT 3M
Exchange ratesYesDDNAD
Socio-demographic data
PopulationYesAANANLT midyear

Indonesia is taking flexibility options for the periodicity and timeliness of employment and unemployment data.

Indonesia is taking a flexibility option for the timeliness of the wages and earnings data.

A flexibility option is being taken for the timeliness of the data on general government operations.

Indonesia makes use of the option to publish the IIP with a time lag of nine months while publishing external debt figures on a quarterly basis.

Indonesia is taking flexibility options for the periodicity and timeliness of employment and unemployment data.

Indonesia is taking a flexibility option for the timeliness of the wages and earnings data.

A flexibility option is being taken for the timeliness of the data on general government operations.

Indonesia makes use of the option to publish the IIP with a time lag of nine months while publishing external debt figures on a quarterly basis.

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