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Indonesia: Detailed Assessments Using the Data Quality Assessment Framework (DQAF)

Author(s):
International Monetary Fund
Published Date:
July 2005
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Detailed Assessment Using the Data Quality Assessment Framework (DQAF)

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

I. National Accounts

0. Prerequisites of quality

0.1 Legal and institutional environment

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

The Statistics Law of Indonesia No. 16 of 1997 (1997 Law) provides the legal foundation. It does not specifically state that the Badan Pusat Statistik (BPS) has responsibility for producing the national accounts. However, the Decree of the Director General of BPS No. 6 of 2000 does give BPS specific authority to publish the national accounts. It should be noted that this decree was issued under the 1997 Law and, consequently, has the same legal status. There has never been any challenge to BPS’s responsibility for compiling and disseminating the national accounts.

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

There is no regular program of discussions with data-supplying agencies. However, there are no general problems with receiving data from other agencies on a timely basis. When individual problems have been encountered, they have been quickly resolved through bilateral discussions. There is a working group trying to resolve the inconsistencies in foreign trade data between BPS and Bank Indonesia (BI)—see 4.2.3.

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

Article 21 of the 1997 Law states that respondents’ data must be kept confidential. This requirement is noted on all survey questionnaires. Failure to comply with this requirement could result in a jail term of up to five years and a fine of no more than Rp100,000,000 (around US$10,500). All questionnaires are kept in lockable facilities that can only be accessed by authorized staff. BPS has an aggregation rule that data will not be published if it relates to less than 10 individual respondents. Even so, data are still reviewed before publication to ensure that there is no indirect disclosure due to the dominant position of one entity. Individual records are sometimes provided to researchers. However, identification details are removed and the researcher has to sign a commitment to keep the data confidential. When required, records are destroyed onsite by shredding. BPS buildings have receptionists who check all people on entry. However, they can sometimes be absent from their post. Fortunately, all staff are instructed to challenge anyone they do not recognize. Also, all rooms have to be locked when not in use.

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

Article 27 of the 1997 Law states that all respondents must supply basic data on request. All of the survey data used in the national accounts are classified as basic data. The penalty for not supplying data is a term of imprisonment not exceeding 18 months and a fine of up to Rp25,000,000 (around US$2,650). However, no prosecution has ever taken place, as BPS prefers to use persuasion to ensure response. BPS regularly reviews questionnaires to try to reduce the burden on respondents by, for example, reducing the number of questions. All questionnaires give a phone number for respondents who require assistance. BPS adopts a positive attitude to respondents’ complaints, persuading them of the need to respond.

0.2 Resources

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

In total, 120 people are engaged on the national accounts program. This is considered sufficient for the size of the current workload. All new technical recruits are required to have a first degree in a relevant subject. Staff are required to undertake internal and external training. Staff turnover is very low as the working conditions are good. This means that there are some very experienced staff engaged in the work. Although salary levels are considered low, they are obviously sufficient to retain staff.

Almost all staff have their own PC and these are connected to central fileservers using a network. Compilation is undertaken using a mix of Excel worksheets and Oracle databases, which fully meet the needs of the system. All PC are protected by passwords and the central databases are further protected by individual log-in passwords. Onsite backups of data are undertaken every day. There is also an offsite backup, but this is only done every three months. Also, BPS does not have access to an emergency office complex, if their own were to be destroyed.

The office buildings are in good condition and create a satisfactory working environment. The office furniture and equipment are of good quality and are in good condition. Transportation facilities are adequate to meet the needs of BPS.

Funding of the statistical program is adequate for the current workload. The budgetary process gives BPS clear and timely information on funding for new requirements.

0.2.2 Measures to ensure efficient use of resources are implemented.

There is a formal annual performance process for all staff. Work processes are regularly reviewed to identify any changes that would improve efficiencies. If necessary, BPS could recruit outside experts to review its systems. However, this would require budgetary approval. All of the work activities are costed on a regular basis, and this information is used to reallocate resources, as necessary.

0.3 Relevance

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

The 1997 Law specified the setting up of a Statistics Community Forum open to any interested person from any walk of life. It meets around four times a year to exchange views. BPS raises issues of interest to itself and provides information on new developments. Participants can also express views on any statistical issue. The chairperson of the forum is elected by the participants. Issues that cannot wait for the next meeting of the forum are communicated to users by way of a newsletter. BPS also publicizes a contact point for users to raise issues. BPS is very active internationally, participating in numerous statistical meetings and seminars. BPS has not undertaken any formal studies to identify new and emerging data requirements. However, they are planning a survey on the quality of its statistics.

0.4 Other quality management

0.4.1 Processes are in place to focus on quality.

Management is committed to data quality and cascades this concern down through the ranks. Staff training also covers the need for data quality and there are regular peer group reviews of the work processes. The public is made aware of quality issues in the publication “An Overview of BPS.”

0.4.2 Processes are in place to monitor the quality of the statistical program.

Managers monitor work processes: for example, supervisors check the work of their team. Also, the computer systems have built in checks on all aspects of data capture and processing. A separate division is responsible for checking the consistency of data. This division can also review systems, if so requested.

0.4.3 Processes are in place to deal with quality considerations in planning the statistical program.

All aspects of quality are considered as part of the planning process. Indeed, if there are competing proposals, the one that will have the best impact on the statistics will be chosen.

Recommendations:

  • Instigate a regular program of discussions with data supplying agencies.

  • Offsite back-ups of data should be made at least once a week.

1. Assurances of integrity

1.1 Professionalism

1.1.1 Statistics are produced on an impartial basis.

The 1997 Law established the statistical independence of BPS. The Director General of BPS is appointed, and can only be dismissed, by the President. Professionalism is actively promoted and supported within 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.

1.1.2 Choices of sources and statistical techniques as well as decisions about dissemination are informed solely by statistical considerations.

The 1997 Law ensures that BPS is free to choose whatever it considers are appropriate data sources and methodologies. BPS decides on the method and timing of data dissemination.

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

BPS undertakes press conferences to explain its data to the media and, thus, reduce the chance of misinterpretation. When such misinterpretation does take place, BPS will contact the originator to ensure that the mistake is corrected and explained. All media references to statistics are identified and circulated within BPS.

1.2 Transparency

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

The 1997 Law is included on the BPS website. BPS publications identify where additional information can be found.

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

There is no government access to statistics prior to their public release.

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

Publications clearly identify BPS by name and its logo. Whenever BPS data appear in the publications of other bodies, the source must be clearly identified.

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

All major changes to statistics are announced in advance in the relevant BPS publications and on its website. Minor changes are just noted when they are introduced.

1.3 Ethical standards

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

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 the government regulation 30/1980.

Recommendation:

  • All staff, including new recruits, should be given written guidance on ethical standards.

2. Methodological soundness

2.1 Concepts and definitions

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

The national accounts are broadly in line with the 1968 System of National Accounts (1968 SNA) but are in the process of being updated to the 1993 SNA, although this could take some time to complete.

2.2 Scope

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

The national accounts largely meet the tables and accounts that the Inter-Secretariat Working Group on National Accounts (ISWGNA) has determined as a minimum requirement. The published data cover annual GDP, from both the production and expenditure approaches, at current and constant prices. However, value added components at current prices are only produced every five years in the Input-Output (I-O) tables. Experimental accounts have been produced for the whole economy, but have not been published. Neither do the national accounts fully meet the tables recommended by the ISWGNA. Quarterly GDP, from both the production and expenditure approaches, at current and constant prices are published. However, annual supply and use tables (SUTS) are not produced. Only I-O tables are produced every five years.

The GDP figures cover the whole economy, except that the free zones are not included in imports, although they are included in the production estimates. The production boundary is generally in line with the 1968 SNA. However, the 1993 SNA concepts of own-account production of all goods for own final consumption, and output of goods for own-account fixed capital formation have already been implemented. The asset boundary is also generally in line with the 1968 SNA. However, the 1993 SNA concepts of defense-related assets that could be used for civilian purposes, and valuables have already been implemented. The other 1993 SNA changes will be implemented in due course.

2.3 Classification/sectorization

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

The 1968 SNA is followed to classify institutional units, transactions, and other flows. International Standard Industrial Classification of All Economic Activities (ISIC), Rev. 3 and the Central Product Classification (CPC) are used to classify industries and products, respectively, with some country-specific changes. The Classification of Individual Consumption by Purpose (COICOP) and the Classification of the Functions of Government (COFOG) are used to classify household consumption and government expenditure, respectively.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

The valuation rules used for recording flows and stocks are generally in accordance with the 1968 SNA. Market output is valued at producer prices and output for own use is valued at equivalent market prices. Indonesia does not have a value-added tax, but other production taxes are included in intermediate consumption. Imports are valued c.i.f. in conformance with the 1968 SNA. However, customs data are only available monthly in U.S. dollars, so they can only be converted into rupiah using average midpoint exchange rates.

2.4.2 Recording is done on an accrual basis.

Transactions and flows are recorded on an accrual basis and work-in-progress is allocated to the period in which it is produced. However, all government transactions are recorded on a cash basis. It is not possible for BPS to convert all government figures onto an accrual basis. However, taxes and subsidies could be converted by identifying the average period between when they accrue and when they are actually paid.

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

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

Recommendations

  • BPS should expedite the conversion to the 1993 SNA, including the publication of all the recommended accounts and tables.

  • BPS should include the free ports in the figures for imports.

  • BPS should investigate to see if the cash figures for taxes and subsidies could be converted onto an accrual basis.

3. Accuracy and reliability

3.1 Source data

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

There is a serious imbalance in the annual enterprise surveys. There is a census of large-(100 or more employees) and medium- (20 or more employees) sized enterprises in the manufacturing industry. On the other hand, there are no annual surveys of the nonfinancial service industries. Crude estimates thus have to be used, for example, by obtaining the number of businesses from relevant professional bodies and multiplying this by an estimate of the average output. Annual surveys of these service industries need to be undertaken, even if this means sample surveys, rather than a census, have to be introduced for medium-sized manufacturers.

BPS undertakes a full economic census every 10 years, with the last in 1996. Unfortunately, this is not updated subsequently for births. However, medium and large establishments that cease activity are removed for manufacturing as they are subject to annual censuses using enumerators. Thus, over time the censuses will understate production. BPS needs to find a way to identify new businesses, and closed small establishments, during the years between censuses. Given the network of local offices in BPS, this should not be as difficult as it is in many countries. One way would be for local staff to routinely check their area for new and closed businesses. If this is not feasible, then common methods are to review telephone records; listings from public utilities, for example, electricity usage; and/or local tax records. This exercise would only work for formal businesses, whereas the census also covers informal activities. However, as noted in 3.3.2, the Labor Force Survey (LFS) could be used to measure informal activities.

As well as operating an annual census for medium and large enterprises, BPS also runs a sample survey of small enterprises. This is based on identifying and recording all such enterprises in a specific block in each district. Therefore, this sample survey cannot be considered as truly representative of the total population.

Changes to questionnaires are pilot-tested to ensure that they are feasible. Data capture takes place in the regional offices and comprehensive computer checks minimize nonsampling errors. The censuses and surveys collect actual production values, intermediate consumption, fixed capital formation, and changes in inventories.

A household budget survey, the National Economic Social Survey (NESS), collects consumption expenditures every three years. A sample of enumeration areas is first selected, and a random sample of households is then derived for each of these areas. Unfortunately, higher-income households are not covered and this seriously distorts the results. The survey is undertaken in February, so it does not reflect seasonal changes in consumption. Neither does it make use of a diary; instead, the household is asked to remember its expenditure on food during the previous week, and expenditure over as much as a year for other items. As is common in other countries, the survey only covers households, not those living in institutions. The whole of Indonesia is covered by the survey using BPS local offices.

Central government data are taken from the budget; BPS is not aware of any activity outside the budget. Data for the local government are obtained from a BPS survey. This is a census for most levels of local government, but for village councils a 10 percent sample is taken.

Detailed breakdowns of the consumer price index (CPI) and producer price index (PPI) are available to use as deflators. However, some inconsistencies exist between the classifications used for the NESS and the CPI. The reference period for the price indices is now 2000, consistent with that for GDP.

In some cases, the sources for the quarterly GDP estimates are the same as for the annual figures. In the case of production industries, a monthly production index is used, which provides reasonably reliable estimates.

Ad hoc surveys can be undertaken when required. Contacts with users and data suppliers are maintained through the Statistics Community Forum.

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

In most cases, the source data are specifically designed to meet the needs of the national accounts. In other cases, such as the central government budget and the NESS, there can be differences in the classifications used. The coverage of total economic activities is generally good. However, there are some known weaknesses in the coverage of informal activities. For the I-O tables, considerable increases have to be made to the supply figures for rice milling, livestock slaughtering, and illegal tree felling.

3.1.3 Source data are timely.

Source data can be late in arriving, but every effort is made to chase up late returns. BPS has a policy of not putting deadlines on questionnaires. This is because they feel that once the deadline has passed, it would then be impossible to obtain a response. So, instead the enumerators ask enterprises to complete and return the form as soon as possible.

3.2 Assessment of source data

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

As most of the data are collected through censuses or nonrandom samples, sampling errors are not relevant. However, they are available for the NESS. Information on identified non-sampling errors, and other aspects of survey operations, is available. Generally, source data values are not revised and coverage is not routinely assessed. Revisions from late reporting are incorporated over a two-year cycle and then again every five years, when the I-O tables are produced. Computer programs undertake comprehensive checks on the data, including consistencies with previous years and with similar businesses. BPS has no way of checking the accuracy of the central government data. It is known that there are differences between BPS and BI data on overseas trade, and these differences are monitored.

3.3 Statistical techniques

3.3.1 Data compilation employs sound statistical techniques to deal with data sources.

The computer programs ensure that there are no processing errors. No adjustments are made to unit records without checking with the respondents. Imputations for nonresponse are based on the last actual report, extrapolated forward using growth in related establishments. Data are compared with that for similar businesses.

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

The economic census run every 10 years is designed to pick up all businesses, even those of an informal nature. Unfortunately, it is known that informal activities are not being picked up for rice milling and livestock slaughtering. The current method is to ask all households if they undertake any informal activity. It would be better to ask the enumerators also to list all informal activities they see in the streets. The LFS could also be used to identify informal activities. This could be more reliable as it is run each year, rather than every 10 years like the census. Additionally, the LFS will pick up any under-reporting by businesses, that is, misstating the number of employees in the establishment census.

Output and intermediate consumption are compiled at the three-digit level of ISIC. Extensive use is made of extrapolation from the five-yearly I-O tables. This means, for instance, that the figures for the years up to and including 2002, published in 2003, were based on the 1995 I-O tables. Additionally, the estimates for trade make use of the margin rates from the I-O tables. In other cases, principally construction, use is made of the value added to output ratios from the I-O tables. These approaches are mainly focused on the nonfinancial services, but also impact on quarrying and construction. In total, they apply to around 40 percent of value added.

The estimates for imputed rent of owner-occupied dwellings are based on building up costs using data from the NESS. Work-in-progress is recorded for all activities except agriculture. This is due to the difficulty of estimating the value of the harvest at the beginning of the year. Output for agriculture and the production industries is based on the value of production. The methodologies employed for trade and other services are also based on production rather than sales. So, there is no need to make any adjustment for inventory valuations. Consumption of fixed capital is only estimated for government and this is simply derived by taking 20 percent of gross fixed capital formation (GFCF). Neither are any adjustments made to convert the government figures from cash to accruals.

One of the main methods for deriving constant price estimates is to deflate value added using appropriate components of the PPI. The other main method is to apply some quantity indicator (production index, employment, etc.) to the base-year value added. It would be better to apply these methods to output. Then, separately deflate intermediate consumption by input PPIs (PPI and CPI components), with weights from the base-year I-O tables. Trade margins at constant prices are obtained by deflation with the CPI. It would be better to apply the base-year margin rates to the constant prices figures for output and imports of the relevant products. This would be relatively easy for BPS to implement as they use a similar methodology for the current price figures. The current base year is 2000 and BPS plans to update it every five years.

Until the annual expenditure figures for 2003 where published, changes in inventories were derived by residual. Now changes in inventories are actually estimated, and have been published for all years from 2000. An investigation of the bookkeeping procedures used by enterprises found that the first-in-first-out was the most popular. BPS is using an appropriate methodology to calculate stock appreciation. The source data for household final consumption (HFC) and government final consumption (GFC) are not classified using COICOP and COFOG, respectively. However, BPS converts the figures into these classifications, but this is only possible at the one-digit level. GFCF and changes in inventories are compiled by industry and by type of asset/inventory.

Most of the expenditure components do not make use of any benchmark data, but HFC does, and this accounts for nearly 70 percent of GDP. This situation arises because the NESS is not considered reliable enough to be used for HFC. Instead, BPS extrapolates forward the I-O figures using total GDP from the production approach, with adjustments for elasticity of demand for each of the product groups. The starting point for the 2000 I-O tables was the NESS structure, but pro-rated to the existing annual total. Then significant upward and downward balancing adjustments were made to the products. However, the total for HFC at the end of this process was not much different from the starting value.

GFC correctly excludes incidental sales. Expenditure by residents in other countries and by nonresidents in Indonesia are included in imports and exports, respectively. However, these adjustments are not explicitly carried over to HFC. On the other hand, the above description of the HFC methodology could be used to justify that they are covered. BPS has figures for expenditure on gold and diamonds, and these amounts are included in GFCF as valuables.

HFC is deflated with appropriate components of the CPI. Thus, the implicit deflators are consistent with the CPI, even though they will have different weights. GFC cost components are deflated separately with components of the wholesale price index (WPI), and employment is used for wages and salaries. GFCF also use components of the WPI. Unfortunately, changes in inventories are also deflated by appropriate components of the WPI. A better method would be to deflate opening and closing levels using price indices appropriate to that period. The valuation adjustment should be separately deflated. This is straightforward as the methodology used to derive these figures calculates constant price figures. Then changes in inventories at constant prices can be derived by residual. For imports and exports, BPS has tried a number of methods, including unit values, but they did not produce reliable results. In the end, they took the value for the base year and deflated this by the index of the U.S. dollar/rupiah exchange rate. Although this may produce a reasonable-looking series, it obviously has no conceptual basis. A better approach for imports of goods would be to construct a price index using the price movements of Indonesia’s main trading partners, weighted with the value of imports in the base year. For exports, the appropriate components of the Indonesian CPI and PPI would be a reasonable option.

When quarterly figures have to be adjusted to be consistent with annual totals, BPS correctly uses the Denton technique. The compilation methods derive proper seasonally unadjusted estimates. These figures are then seasonally adjusted using the well-established X–12 technique. Unfortunately, these seasonally adjusted figures are not published because BPS feels they may confuse users. Although such figures have to be carefully presented, they will probably be very useful to users. This is because they show the trend in the growth of GDP, which may not be visible in the unadjusted figures.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Intermediate results are validated against other information, where applicable.

Data compiled for the GDP estimates are checked against other sources whenever possible, for example, trade data with the balance of payments produced by BI. However, BPS was not aware that the Ministry of Finance (MoF) also compiles estimates for local government, which should be checked against the BPS survey data.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

Although BPS was aware of the differences between their trade data and that in the balance of payments, these differences have not yet been resolved.

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

Every five years, BPS produces I-O tables to remove the statistical discrepancy. Previously, the statistical discrepancy for other years was included with changes in inventories in the expenditure figures. Since the publication of the first quarter of 2004, it has been shown separately in the publications, and is available back to 2000. The I-O tables are rather unusual in that they are the tables that are balanced, rather than the underlying SUTS, as is usually the case. So, the balancing adjustments for the production data relate to products rather than industries. Even so, when the tables for 2000 were produced, the adjustments were simply allocated to the corresponding industry. These adjustments increased total GDP by about nine percent and have been applied to the figures for subsequent years. The figures for the years 1996 to 1999 were also adjusted, using the Denton technique with the figures for 1995 and 2000 fixed. In the 1995 tables, the adjustments amounted to an increase of 17 percent, but were not allocated to the annual GDP figures. This is because they would have changed the then base year of 1993. Although national accountants would wish to avoid changes to the base year, this is not a rigid rule. Clearly, an increase to GDP of 17 percent is so significant that it should have been implemented.

Although the statistical discrepancy is removed in the five-yearly I-O tables, it is still present in the GDP figures for intervening years. So, an improvement would be to produce balanced tables for these intervening years, to remove the statistical discrepancy for all years. However, it would take up too many resources to produce I-O tables every year. It is much easier to simply produce and balance the SUTS. In fact, most countries balance on the SUTS even when they go on to produce I-O tables. Ideally, balanced SUTS should be produced at least back to the year 2000 to remove the statistical discrepancy from the figures for recent years. To convert the 2000 I-O tables to SUTS, it will be necessary to move any secondary activity in each column back to the industry from which it came. The SUTS for later years could then use the structures from the previous year and then be balanced. Alternatively, given the weakness in the figures for HFC, as noted above, this could be made the residual. This would be a simpler process as long as the resulting figures for HFC looked reasonable. Then, as changes in inventories are available for all these years, the statistical discrepancy could be removed from the accounts for these years.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used internally to inform statistical processes (see also 4.3.3).

There have never been any formal revision studies of the national accounts. However, ad hoc studies of specific activities have been undertaken. The results of these ad hoc studies have been used to inform the estimates.

Recommendations

  • Introduce comprehensive annual establishment surveys for the nonfinancial services industries.

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

  • Introduce an annual establishment sample survey for small enterprises that is fully representative for each industry.

  • Bring the NESS into line with best international practice.

  • Bring all classifications into line with international standards to avoid inconsistencies.

  • Investigate if the LFS would give reliable estimates for informal activities.

  • Investigate the availability of stocks of fixed assets for, at least, the government, with the aim of deriving consumption of fixed capital using the perpetual inventory method.

  • Derive value added at constant prices by deflating output and intermediate consumption separately.

  • Calculate trade margins at constant prices by applying base-year rates to constant price values for output and imports.

  • Until improvements are made to the NESS, consider deriving HFC by residual.

  • Introduce a more acceptable methodology for the deflation of imports and exports.

  • Regularly check the data for the local government with that produced by the MoF.

  • Allocate the revised GDP figures for 1995 from the I-O tables to the annual series and make appropriate changes to the other years.

  • Develop a set of annual SUTS starting from 2000.

  • Undertake a study of revisions to the published GDP estimates and evaluate the results.

4. Serviceability

4.1 Periodicity and timeliness

4.1.1 Periodicity follows dissemination standards.

The GDP estimates are compiled quarterly, in line with the Special Data Dissemination Standard (SDDS).

4.1.2 Timeliness follows dissemination standards.

The quarterly estimates are published 45 days after the end of the quarter, well within the three months recommended in the SDDS.

4.2 Consistency

4.2.1 Statistics are consistent within the dataset.

As noted above, there is now a separate series for the statistical discrepancy. This discrepancy is quite small, less than 1.5 percent of total GDP. However, as noted above, this may be due to the way that HFC is calculated. The constant price figures are fully consistent with the equivalent current price values. Also, the quarterly estimates add up to their annual versions. As noted in Section 3.4.3 above, supply and use tables are not compiled to address discrepancies between GDP estimates by the production and expenditure approaches.

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

BPS policy is to publish data only from the last benchmark year. Thus, only figures from 2000 have been included in recent publications. This means that the figures for 1996 to 1999, which were revised to be consistent with the new 2000 figures, have not been published. These revised figures were only produced for internal use and to satisfy a request from BI. However, there is a strong possibility that other users will need longer time series.

Breaks in time series are explained in the publications, as relevant. Also, unusual changes in data are explained in the supporting notes.

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

The data for imports and exports are known to be different from those in the balance of payments produced by BI. It is known that the MoF also produces local government data, but no reconciliation has yet been undertaken. Other relevant statistics are fully consistent.

4.3 Revision policy and practice

4.3.1 Revisions follow a regular and transparent schedule.

Two sets of annual figures are published before they become final. They can also be changed when the next set of I-O tables are produced. The quarterly figures follow the same pattern, and the quarters of the latest year are all subject to revision. The revision cycle is fully explained in the publications. Revisions are not made outside this cycle.

4.3.2 Preliminary and/or revised data are clearly identified.

In the publications, the latest year’s figures are marked as very preliminary and when published in the second year they are shown as preliminary.

4.3.3 Studies and analyses of revisions are made public (see also 3.5.1).

Only ad hoc revision studies are undertaken and these are not published.

Recommendations

  • The annual publication should include a lengthy time series (e.g., 20 years).

  • Inconsistencies with other data-producing agencies should be removed.

  • When revision studies are undertaken, the results should be published.

5. Accessibility

5.1 Data accessibility

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

The GDP figures are published clearly with charts and tables, as necessary. They are also published with different levels of detail, as appropriate to the specific publication. Analysis of the current period developments is also included in the publications. Reasonably detailed breakdowns are published, but the seasonally adjusted quarterly estimates are not given, even although they are available.

5.1.2 Dissemination media and format are adequate.

The GDP figures are disseminated in various forms to meet the needs of users, including press releases. The data are also available on BPS website.

5.1.3 Statistics are released on a preannounced schedule.

A preliminary release calendar for the year is published in the previous October. This gives approximate dates for release. The actual dates are then given a week ahead of the actual day, but this is only published via the SDDS metadata. The data are always released at 1:30 pm on this day.

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

The data are available to all users at the same time via a press release and on BPS website. A press conference takes place at the same time as the data are released.

5.1.5 Statistics not routinely disseminated are made available upon request.

Some additional breakdowns can be supplied as long as they do not breach the confidentiality rules. These are available free of charge, and this information is included in the catalog of publications.

5.2 Metadata accessibility

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

A comprehensive methodological guide is included in the annual publication, in Indonesian and English. This information is also on BPS website. BPS updates the SDDS metadata as soon as a change occurs.

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

Different levels of metadata are produced to meet the needs of the intended audience.

5.3 Assistance to users

5.3.1 Contact points for each subject field are publicized.

All statistical releases contain the relevant contact person–name, address, phone number and email address. Assistance to users is monitored, but only if instigated through the website.

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

A catalog in Indonesian is published every year. Details in Indonesian and English are also given on BPS website, and this is kept up-to-date. Prices are given as well as details of how to place an order.

Recommendation:

  • Publish the seasonally adjusted quarterly GDP figures.

  • Ensure that the advance release calendar (ARC), containing actual publication dates, is made known to all domestic users of statistics.

Table 1.Indonesia: Data Quality Assessment Framework (July 2003): Summary of Results for National Accounts(Compiling Agency: Badan Pusat Statistik)
Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria
ElementNAAssessmentComments
OLOLNONO
0. Prerequisites of quality
0.1 Legal and institutional environmentX
0.2 ResourcesX
0.3 RelevanceX
0.4 Other quality managementX
1. Assurances of integrity
1.1 ProfessionalismX
1.2 TransparencyX
1.3 Ethical standardsXNo written guidance for staff.
2. Methodological soundness
2.1 Concepts and definitionsX1968 SNA, but some 1993 SNA changes have been introduced.
2.2 ScopeXSome tables are not produced.
2.3 Classification/sectorizationX
2.4 Basis for recordingXAll government data are on a cash basis.
3. Accuracy and reliability
3.1 Source dataXPoor coverage of nonfinancial services and household consumption.
3.2 Assessment of source dataXCoverage is not routinely assessed.
3.3 Statistical techniquesXExtensive use of five-yearly I-O tables; poor coverage of some informal activities; volume estimates could be better.
3.4 Assessment and validation of intermediate data and statistical outputsXStatistical discrepancy only removed in I-O years; I-O process introduces large revisions to GDP.
3.5 Revision studiesXOnly ad hoc studies for specific activities.
4. Serviceability
4.1 Periodicity and timelinessX
4.2 ConsistencyXOnly short time series are published. There are inconsistencies with balance of payments data and exports and imports.
4.3 Revision policy and practiceXThe ad-hoc studies have not been published.
5. Accessibility
5.1 Data accessibilityXAvailable seasonally adjusted figures are not published; the ARC, incorporating actual publication dates, is only available in SDDS metadata.
5.2 Metadata accessibilityX
5.3 Assistance to usersX

II. Government Finance Statistics

0. Prerequisites of quality

0.1 Legal and institutional environment

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

Law 33/2004 on Local and Central Government Fiscal Balance requires, among other things, that the MoF provides a national government finance information system, and that government finance statistics (GFS)1 derived from this system be disseminated to the public on a regular basis.

The working arrangements relating to the collection and processing of fiscal data are set out in Law 17/2003 and the Government Regulation on Local Government Finance Information No. 11/2001 (Article 2) and MoF Decree 302/2004. Under these arrangements, two groups have been set up within the MoF. The subdirectorate of state budget consolidation is responsible for the compilation and dissemination of central government GFS, and the consolidation of central and local government data to generate general government statistics. The subdirectorate of local finance information is responsible for the compilation and dissemination of local government fiscal data. The subdirectorate of state budget consolidation relies primarily upon the directorate of treasury for the supply of data. The subdirectorate of local finance information collects data directly from local governments, but works closely with the agency for local financial administration (BAKD) in the Ministry of Home Affairs (MOHA). Working arrangements are consistent with the assignment of responsibility.

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

For the central government, there are effective procedures in place to provide a timely flow of administrative data, but there are no arrangements to obtain survey data from extrabudgetary agencies. The provision of administrative data is not fully automated to reduce the work required to provide these data. For local governments, procedures to supply data are in a process of transition. As stated in MoF Decree 154/KMK.07/2001, budget realization data are required to be submitted within six months after the completion of the budget year. However, the data can be supplied under differing accounting formats, which greatly complicates processing by the MoF. Under Law 17/2003, all local governments are required to adopt a standard accounting format by 2006.

Regular meetings are held between MoF and BI staff to reconcile and share data.

The subdirectorate of local finance information conducts annual workshops with local governments to improve the understanding of, and compliance with, the provisions of Law 33/2004, which deals with responsibility for the supply of fiscal data, among other things.

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

At present, fiscal data only relate to general government units and therefore this criteria does not apply. However, MoF staff are subject to the provisions of Statistics Law 16/1997, which requires confidential treatment of individual reporters’ data, insofar as that law applies to their work.

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

Law 33/2004 gives the MoF authority to collect data from all government agencies, and provides for sanctions—including the postponement of payment of transfers from the central to the local government—where data are not provided in accordance with MoF requirements. To date, no sanctions have been imposed. MoF authority to collect extrabudgetary data has not been tested.

0.2 Resources

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

The staff resources available are adequate to carry out the current limited production and dissemination of GFS, but staff have other duties aside from compilation and dissemination of statistics, which can result in conflicts over priorities. It is probable that additional staff resources will be required to address some of the data quality issues addressed in this ROSC. Staff training is not adequate: only two members of the subdirectorate for state budget consolidation and one member of the subdirectorate of local finance information have attended the GFSM 2001 course in Washington. New staff are given training in the operation of the statistical systems, and also receive instructions via an apprenticeship system, but this training is directed towards learning processes rather than concepts and principles.

Salary levels at present do not take account of expertise in statistical work.

Computer resources are not sufficient for the subdirectorate of state budget consolidation, with an insufficient number of computers, and, more importantly, no specialized software for statistical processing. The subdirectorate of local finance information has more computer resources, and also a specialized computer application.

Physical facilities are generally adequate, but both subdirectorates need more access to cars to assist them in their liaison and coordination tasks.

No specific funding arrangements are provided for statistical work, which leaves funding in an insecure position and inhibits planning for statistical developments.

0.2.2 Measures to ensure efficient use of resources are implemented.

Performance reviews of all staff and work processes within the MoF are conducted on an annual basis. Occasionally, outside expert assistance is sought (e.g., from universities)—in addition to technical assistance from the Fund—to evaluate statistical methodologies and systems. However, no cost-benefit analyses are applied to statistical processes.

0.3 Relevance

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

The assessment of the relevance and practical utility of statistics in meeting users’ needs is based on feedback from the users, but there are no proactive procedures to assess the usefulness of statistical products. Studies have been carried out on some aspects of new data requirements (e.g., balance sheets), but no comprehensive process is in place to identify new or emerging data requirements. The MoF takes part in domestic statistical meetings involving fiscal data issues, but it does not participate in international forums.

0.4 Other quality management

0.4.1 Processes are in place to focus on quality.

Training programs in the subdirectorate of state budget consolidation particularly concentrate on quality issues, but similar training is not provided in the subdirectorate of local finance information. Because of the lack of a user orientation, MoF staff tend to focus on procedures rather than products.

0.4.2 Processes are in place to monitor the quality of the statistical program.

No processes are in place to specifically monitor the quality of fiscal data, although the MoF is open to feedback from users on the quality of the statistics. Review of the data would only occur as a result of specific events, such as indications by important users that significant problems existed, or changes to the environment in which the statistics are compiled and disseminated.

0.4.3 Processes are in place to deal with quality considerations in planning the statistical program.

Processes have been developed to plan and manage the transition to the GFSM 2001 standard. Trade-offs in quality between timeliness and accuracy are implicitly taken into account in disseminating preliminary statistics, followed by statistics based on audited data for central government, but preliminary data are not compiled for local government.

No specific procedures are in place to obtain information from users on new and emerging data requirements.

Recommendations

  • Provide staff dedicated to the compilation and dissemination of GFS in the subdirectorates of state budget consolidation and local government finance information.

  • Develop procedures to obtain timely preliminary fiscal data from provincial and local governments.

  • Develop computer applications to allow automatic generation of GFS tabulations and reports from budget data.

  • Set up regular liaison arrangements with users of GFS to obtain feedback on the relevance of GFS, additional requirements, and users’ perceptions of data quality.

1. Assurances of integrity

1.1 Professionalism

1.1.1 Statistics are produced on an impartial basis.

No laws or other formal arrangements support the professional independence of compilers of GFS. There has been no attempt by the authorities to influence statistical outputs, and the government and other agencies appreciate the importance of allowing statistics to be produced free of interference. However, there are no effective safeguards to protect compilers from political interference, although the move to fully adopt international standards provides some support for their professional independence.

The MoF does not generally recruit statistical specialists, but because most staff have economic qualifications, in which a basic knowledge of statistical principles forms part of a wider set of skills, they do have a generally appropriate background for the tasks of compiling and using GFS. In addition, staff receive on-the-job training in carrying out statistical (as well as other) tasks, and the MoF has retained the expertise of staff who have attended the GFS training courses in Washington.

MoF staff generally are encouraged to increase their professionalism by publishing research and analysis papers in the internal MoF journal, and participating in monthly seminars.

1.1.2 Choices of sources and statistical techniques, as well as decisions about dissemination, are informed solely by statistical considerations.

There is no evidence of political interference in the choices of the sources and statistical techniques in the compilation of the GFS. The administrative sources used in compiling GFS are obvious and appropriate, and the content and format of the statistics are based on IMF standards (in the case of the local government, this process is still in transition).

Decisions to disseminate are subject to management approval, but statistics are routinely disseminated when they have been validated.

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

The MoF provides commentary in press releases to explain the data, and monitors media coverage of its data. The MoF (through the Public Relations Bureau) can respond to correct the misinterpretation or misuse of GFS (e.g., via letters to the editor).

1.2 Transparency

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

The terms and conditions 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 (apart from the laws themselves) on the terms and conditions applying to GFS is made public.

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

The government has internal access to statistics prior to their release to the public, but no information concerning this access is made public.

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

The MoF is clearly identified as the source of GFS on the websites and in press releases. MoF statistics used in other publications are sometimes attributed to the MoF, but the MoF does not insist that this should always be done.

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

Advance notice of major changes to methodology or sources is given to the public by way of press releases and conferences, and in budget documentation.

1.3 Ethical standards

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

All civil servants are subject to the application of general ethical standards as set out in Government Regulation 30/1980. These standards are an important part of both initial and ongoing staff training. In addition, MoF staff are subject to the provisions of the Statistical Law to the extent that it is relevant to their work.

Recommendation:

  • Publish information about the terms and conditions under which GFS are compiled and disseminated on the MoF websites, including information about preferential access to the GFS by the government.

2. Methodological soundness

2.1 Concepts and definitions

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

Indonesian GFS is in a period of transition. Central government GFS are currently on the GFSM 1986 basis, except that privatization transactions are classified as financing transactions in line with GFSM 2001.

Local government GFS are not yet based on international concepts and definitions. The local government (which includes provincial governments) is of considerable significance in Indonesia, accounting for approximately 40 percent of general government expenditure, although most local government revenue is by way of transfers from the central government budget under revenue-sharing arrangements. GFS for the local government is in the development phase under the requirement of Law 33/2004 for the government to set up a regional finance information system on a national basis, and for the information in that system to be “open data” which may be accessed by the public. Prior to Law 33/2004, local government data were produced mainly for administrative budget purposes.

Law 17/2003 mandates that all Indonesian governments move to an accrual accounting basis, consistent with GFSM 2001, by 2008. This transition is being carried out in stages.

Changes to the accounting classification systems will be followed by the adoption of an accrual basis of recording, and the development of full balance sheets using current market (fair value) valuation.

In the meantime, it is difficult to compile anything more than basic aggregates on the basis of GFSM 1986 for the general government sector.

2.2 Scope

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

Indonesian GFS cover the central and local government budget sectors. No extrabudgetary agencies are covered in the statistics, and there are no estimates of the magnitude of their operations. Thus, the extent to which the lack of coverage of these units detracts from the completeness of GFS is not clear. In addition to units set up outside the budget by specific legislation, such as government employee pension and health insurance funds, extrabudgetary units include so-called foundations, which have been created by line ministries for various purposes.

At present, the MoF does not have a register of all central government units, or potential central government units; therefore, information cannot be obtained on the size of the extrabudgetary sector to guide decision-making on the size of the problem and possible solutions.

Government corporations are required to carry out public service obligations, which correspond to quasi-fiscal activity. While subsidies are paid by the budget sector to fund at least some of this activity (and is therefore included in GFS), it is possible that significant amounts of quasi-fiscal activity are not captured in GFS.

Some additional details (e.g., taxes, expenditure) are available for central government, but the full range of GFSM 2001 supporting tabulations is not available. Detailed tabulations supporting the basic aggregates are not available for the local government sector.

2.3 Classification/sectorization

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

Institutional sectors and subsectors are not explicitly defined in Indonesian GFS, which is implicitly based on administrative categories.

New accounting regulations (based on Law 17/2003) for the central government budget sector, including a revised chart of accounts, have been drawn up and came into effect in 2005. The new chart of accounts includes a functional classification which is based on the GFSM 2001 classification of the functions of government (COFOG),2 and an economic type classification which is generally consistent with GFSM 2001 economic classifications.

Similarly, Law 17/2003 requires all local governments to adopt a standard accounting format, similar to the central government accounting format, by 2006. At present, most, but not all, local governments have adopted the new accounting standards, but it is not yet possible to obtain complete data for the local government sector on the new classification basis.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

Foreign debt is valued at current market value, but domestic debt is valued at face value. Stocks of nonfinancial assets are valued on a historical cost basis. A move to an accrual accounting basis is mandated by Law 17/2003 by 2008, which implies the adoption of a current market (or fair value) valuation basis for all assets and liabilities.

2.4.2 Recording is done on an accrual basis.

Recording is done on a cash basis. A move to an accrual basis, consistent with GFS standards, is mandated to be completed by 2008.

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

All transactions are shown gross, except for financing and corrective transactions. However, corrective transactions are shown in the period in which payments are made, rather than when the original transactions are recorded.

Recommendations

  • Implement new Government Accounting Standards.

  • Strengthen the management system in place by tracking effectively changes in government cash balances.

  • Move gradually to an accrual accounting system.

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

  • Extend coverage of GFS to the whole of the general government sector.

3. Accuracy and reliability

3.1 Source data

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

GFS are compiled from comprehensive central and local government administrative (budget) data. Supplementary financing data are obtained from BI for quality assurance purposes. However, no data are obtained for general government activity outside the budget processes. A register of general government units is not available to support collection of extrabudgetary data.

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

Source data for the central government budget sector, and most local government budget sectors, approximate the classifications required, but data for a significant number of local governments still use incompatible classifications. Limited supplementary data are obtained from BI for data quality assurance purposes.

Source data are on a cash basis of recording, and use historical valuation for nonfinancial assets, which are not consistent with the accounting basis required for GFSM 2001.

GFS compilers are fully aware of the differences between the actual and required valuation and time of recording, but are not able to adjust the data to the required accounting basis

3.1.3 Source data are timely.

Source data for the central budget sector are very timely, with preliminary data being available within two weeks after the reference period, and final audited data being produced approximately six months after the reference period.

Local government budget data are not timely enough to meet GFS requirements because the data are not required to be provided to the MoF until audits have been completed, and therefore the first data are not available until approximately six months after the reference period.

3.2 Assessment of source data

3.2.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and other nonsampling error; the results of the assessments are monitored and guide statistical processes.

Central government source data are analyzed quarterly, and there are regular quarterly meetings to discuss source data quality issues.

There is no routine assessment of source data for local governments; data validation is carried out when data are entered into the system and data assessments are carried out when problems are identified in the statistical output.

For the central government, regular quarterly meetings are held between the MoF and BI to assess data from different sources. However, similar meetings are not held for local government data.

3.3 Statistical techniques

3.3.1 Data compilation employs sound statistical techniques to deal with data sources.

For central government budget data, a year-on-year comparison is made of data items to highlight unusual trends in the data. No statistical techniques are used to check local government data.

Central government preliminary data are corrected when more accurate data become available. Only final data are used in compiling local government data.

Compilation procedures are not documented for either central or local government processing.

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

GFS compilation procedures entail the conversion of budget items to GFS categories. Bridge tables have been constructed to automate this procedure by linking (or ‘mapping’) central government budget items to GFS economic-type codes. No bridge tables have yet been developed for local government data.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Intermediate results are validated against other information, where applicable.

Not applicable to GFS.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

Not applicable to GFS.

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

Discrepancies between MoF central government financing data and BI monetary and balance of payments statistics are investigated. However, to date it has not been possible to reconcile MoF domestic financing and monetary data, and BI and the MoF have not persisted with the exercise. As a result, the reasons for the discrepancy have not been identified.

Bilateral reconciliations of grants and loans from international organizations are carried out via the aid pledge forum, which includes representatives of the MoF, BI, National Planning Agency, and international agencies. However, other data on external public debt stocks and related flows are not checked against creditor information.

Data are checked to ensure that they are within the expected range of values (based on time-series analysis) and outlier values further investigated.

For central government budget data, substantial discrepancies occur on a monthly and quarterly basis between the deficit (calculated as the difference between the revenue and expenditure aggregates) and financing. These discrepancies are much less for annual data, and may be the result of timing differences in the recording of cash flows (although conceptually such timing differences should not appear), but the cause of these discrepancies has not yet been determined. Equivalent comparisons have not been carried out for local government data.

No checks are carried out to assess the reasonableness of stock (debt) and flow (financing) data.

3.5 Revision studies

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

Revised data are not archived electronically and cannot be retrieved easily for revision studies. No regular revision studies are carried out, except in the context of MoF/BI reconciliation (see below), although revisions can be investigated if queries are raised by users.

The results of the reconciliation between MoF financing and BI monetary data are used to inform the reconciliation process through the development of “statistical discrepancy guidelines.”

Recommendations

  • Document compilation procedures.

  • Develop bridge tables for provincial and local governments.

  • Carry out checks on the reasonableness of provincial and local government source data.

  • Ensure consistency between deficit (net lending/borrowing) and financing transactions, and between stocks and flows.

  • Carry out routine revision analyses, and post the results on the MoF websites.

4. Serviceability

4.1 Periodicity and timeliness

4.1.1 Periodicity follows SDDS dissemination standards.

The periodicity of GFS meets, or exceeds, SDDS standards.

  • Central government operations aggregates are disseminated monthly, quarterly, and annually (SDDS recommendation: quarterly and annual central government aggregates).

  • Central government debt statistics are disseminated quarterly.

  • General government operations data are disseminated annually.

4.1.2 Timeliness follows SDDS dissemination standards.

The timeliness of GFS meets SDDS standards, except for general government operation statistics:

  • Monthly and quarterly central government operations data (revenue, expenditure, and financing) are disseminated within one month after the end of the reference period. (SDDS recommendation: quarterly central government aggregates within one quarter after the end of the reference period.)

  • Annual general government operations data are disseminated more than nine months after the end of the reference period—flexibility option has been taken. (SDDS recommendation: comprehensive annual general government data within 6–9 months after the end of the reference period.)

  • Central government debt data are disseminated within one quarter of the reference period. (SDDS recommendation: annual central government debt data within one to two quarters after the end of the reference period.)

4.2 Consistency

4.2.1 Statistics are consistent within the dataset.

The same concepts and classifications are used for monthly, quarterly, and annual statistics. Subannual data add to annual data (for final annual, after benchmarking).

On an annual basis, the cash deficit/surplus is approximately equal to financing (with an opposite sign) and major aggregates are equal to the sum of their components. However, significant discrepancies occur between the cash deficit/surplus and financing in monthly and quarterly data.

No reconciliation is carried out between stock and flow data.

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

A major data change was introduced in 2000, including changes in the account structure for both central and local governments and the move from an April to December fiscal year for central government, and it is not possible to obtain consistent time-series data for periods before 2001.

The changes affecting central government data are explained and documented in a financial note,3 and in the draft budget of 2000.

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

GFS foreign financing and debt statistics are consistent with BI external monetary and balance of payments data. However, GFS domestic financing statistics are not consistent with BI domestic monetary data.

No reconciliation is carried out between GFS and the national accounts (general government sector) produced by the national statistical agency (BPS). BPS uses central government GFS as the main data source for that subsector, but collects local government data through a survey carried out independently of the MoF.

4.3 Revision policy and practice

4.3.1 Revisions follow a regular and transparent schedule.

The preliminary-to-final revision cycle is predictable and stable, with preliminary central government data being replaced by final audited data on around August 15/16 each year. The revision cycle would be known to all regular users of the statistics.

4.3.2 Preliminary and/or revised data are clearly identified.

Preliminary and revised data are explicitly identified in table headings—all data not identified as preliminary are final.

To date, final data have not been revised.

4.3.3 Studies and analyses of revisions are made public.

No analyses of revisions are produced.

Recommendations

  • Collect and compile data for material (significant) extrabudgetary units.

  • Disseminate GFS for the general government sector and its subsectors within six months after the reference period.

  • Periodically reconcile:

    • GFS financing and BI monetary data;

    • GFS and BPS national accounts data for the general government sector.

5. Accessibility

5.1 Data accessibility

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

GFS are disseminated primarily through the MoF websites (www.depkeu.go.id [central government] and www.djpkpd.go.id [local government]) supplemented by press releases, budget documentation, and special data services.

Central government GFS are disseminated according to GFSM 1986 recommendations but do not provide the equivalent coverage, or detail, to that set out in the GFSM 1986.

Local government GFS are disseminated in nonstandard formats, and little detail is provided.

5.1.2 Dissemination media and format are adequate.

GFS are disseminated through the MoF websites and MoF press releases. Additional information is included on the central government website (www.depkeu.go.id) by way of a PDF version of the monthly MoF statistical bulletin. However, this does not provide data in as accessible form as would publishing GFS supplementary tables.

5.1.3 Statistics are released on a preannounced schedule.

Although there is no preannounced release schedule for the release of GFS, it is now a well-established practice that GFS are disseminated about one month after the end of the reference month.

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

GFS are made available to official users before they are released to the public.

5.1.5 Statistics not routinely disseminated are made available upon request.

More comprehensive or detailed statistics than those published on the MoF website can be obtained by application to the MoF. The MoF is generally willing to provide more detailed GFS, but this is at the discretion of MoF management, and depends on work pressure. The availability of additional detail is not publicized.

5.2 Metadata accessibility

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

There is no published document which describes the concepts and methodology of GFS in Indonesia.

A limited amount of information on concepts and methods is included in the Indonesian GFS SDDS metadata.

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

Only summary information on GFS concepts and methodology is available.

5.3 Assistance to users

5.3.1 Contact points for each subject field are publicized.

Liaison officers or contact points are included in the websites and MoF press releases. These contact details enable users to contact knowledgeable GFS staff.

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

GFS can only be obtained from the MoF websites, or direct application to the MoF, and these services are provided free of charge.

Recommendations

  • Disseminate GFSM 2001 operating statement, statement of sources and uses of cash, and (partial) balance sheet on the MoF websites.

  • Publish additional detailed tabulations for revenue, expense, acquisition and disposal of nonfinancial assets, and financing, on the MoF websites.

  • Disseminate summary metadata on the MoF websites.

  • Publish information about the availability of unpublished data from the MoF.

Table 2.Indonesia: Data Quality Assessment Framework (July 2003): Summary of Results for Government Finance Statistics(Compiling Agency: Ministry of Finance)
Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria
ElementNAAssessmentComments
OLOLNONO
0. Prerequisites of quality
0.1 Legal and institutional environmentXLocal government data can be supplied under differing accounting formats, which greatly complicates processing by the MoF.
0.2 ResourcesXThe statistical program is not separated from other tasks of the MoF. Computer resources need to be extended to provide better software for compiling and disseminating statistics. There are no specific measures to improve the efficiency of statistical programs.
0.3 RelevanceXThe MoF is open to feedback from GFS users, but no systems are in place to monitor user needs.
0.4 Other quality managementXGFS compilers lack a user perspective on the outputs of the GFS compilation process. There are no processes in place to monitor the quality of the GFS program, or to obtain information from users on new and emerging data requirements.
1. Assurances of integrity
1.1 ProfessionalismXThere are no laws or other formal arrangements to support the professional independence of GFS compilers.
1.2 TransparencyXNo information on the terms and conditions under which GFS are compiled and disseminated is made public. Internal government access to GFS prior to their release is not made public.
1.3 Ethical standardsX
2. Methodological soundness
2.1 Concepts and definitionsXCentral government is on GFSM1986 basis. Local government is on a nonstandard basis.
2.2 ScopeXGFS cover only budget transactions.
2.3 Classification/sectorizationXLocal government uses nonstandard classifications.
2.4 Basis for recordingXHistorical prices are used to value nonfinancial assets. Recording is on a cash basis.
3. Accuracy and reliability
3.1 Source dataXNo data are obtained for government activity outside the budget process. Valuation and accounting basis are not consistent with GFSM 2001.
3.2 Assessment of source dataXLocal government data are not routinely assessed.
3.3 Statistical techniquesXNo statistical techniques are used to assess local government data and local government bridge tables have not yet been developed.
3.4 Assessment and validation of intermediate data and statistical outputsXDiscrepancies between the deficit and financing are not resolved. Changes in stock (debt) and flow data are not compared.
3.5 Revision studiesXRegular revision studies are not carried out.
4. Serviceability
4.1 Periodicity and timelinessXGeneral government operations data do not meet SDDS standards for timeliness.
4.2 ConsistencyXA consistent time series is available only from 2001.
4.3 Revision policy and practiceXSubstantial discrepancies remain between domestic financing and monetary data, and between monthly and quarterly deficit and financing data
5. Accessibility
5.1 Data accessibilityXGFS are not provided according to standard GFS formats and levels of detail. GFS are made available to official users before they are released to the public. The availability of additional data is not advertised.
5.2 Metadata accessibilityXThere is no published documentation which describes the concepts and methodology of GFS in Indonesia, apart from material included on the SDDS website
5.3 Assistance to usersX

III. Monetary Statistics

0. Prerequisites of quality

0.1 Legal and institutional environment

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

The Republic of Indonesia Act No. 23 (May 17, 1999), Article 14, paragraph 1, states that “BI may conduct a macro or micro survey, periodically or at any time it deems necessary, to support the discharge of the tasks of BI,” which are defined as “to formulate and to implement monetary policy; to regulate and to safeguard the smoothness of the payment system; and to regulate and to supervise banks.”

Two regulations—namely, the Republic of Indonesia Act No. 23 (May 17, 1999), Article 14, paragraph 3, and the Republic of Indonesia Act No. 10 (November 10, 1998), Article 34, paragraph 1—emphasize the obligation of the commercial banks to submit their monthly financial reports (balance sheets and profit-and-loss statements), coupled with explanations, to BI in a timely manner and in a format set by BI. The General Explanation of BI Regulation No. 2/21/PBI/2000 (September 19, 2000) states that the financial reports submitted by the commercial banks would be used by BI for statistical and supervisory purposes. BI Internal Circular Letter No. 3/4/INTERN (January 29, 2001), Attachment II, defines the principal tasks of the Monetary Statistics Division as compilation of Indonesia’s monetary statistics within a monetary statistics survey and on a monthly basis. Three regulations—namely, BI Regulation No. 2/21/PBI/2000 (September 19, 2000), BI Regulation No. 5/26/PBI/2003 (December 1, 2003), and Director of BI Decree No. 28/58/KEP/DIR (August 29, 1995)—define all the procedures that are necessary to ensure an effective and timely flow to BI of financial data, respectively, from the commercial banks, Syariah (Islamic) banks, and rural banks.

BI is the only institution that compiles and disseminates Indonesia’s monetary statistics, and no conflict exists between BI and other agencies in this area.

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

Arrangements for collecting commercial bank data are broadly adequate. The project to expand the institutional coverage of the monetary statistics to mutual funds (REKSA DANA) that issue deposit-like liabilities, however, requires BI to access mutual fund data from the Capital Market Supervisory Agency (BAPEPAM) located in the MoF. Although the BAPEPAM provides mutual fund data, on an informal basis, to the Monetary Statistics Division, BI has not yet institutionalized its arrangements for data sharing with the BAPEPAM. BI holds an annual meeting with the MoF on reconciliation of monetary and government finance statistics.

0.1.3 Individual reporters’ data are to be kept confidential and used for statistical purposes only

The Republic of Indonesia Act No. 23 (May 17, 1999), Article 14, paragraph 4 obliges BI to safeguard the confidentiality of the individual unit data. BI’s Manual on the Compilation of the Commercial Banks’ Monthly Report defines the rights and obligations of commercial banks in the provision of data to BI. The Manual states that the data provided by commercial banks would be used exclusively for statistical and supervisory purposes. The Republic of Indonesia Act No. 23 (May 17, 1999), Article 71, paragraph 1 sets the penalties against BI staff, Board of Governors, as well as BI-appointed third-parties, who might disclose confidential financial data on individual banks. Such offenders could be imprisoned for 1 to 3 years and fined Rp.1–3 billion.

Board of Governors of BI Regulation No. 2/12/PDG/2000 (June 30, 2000), Article 4, Number 6, describes BI’s information technology policies with an emphasis on their ability to secure its information technology assets from various risks—namely, hacking, obliteration, an unauthorized use, as well as use by unauthorized parties, of various equipments, materials, and systems—namely, hardware and software, communication network, electronic database, and other facilities. BI Internal Circular No. 2/61/Intern (December 22, 2000), Chapter IV, Number (1)(a), regulates access to the various categories of BI staff.

BI uses aggregation of data on individual banks in the dissemination of monetary statistics—which safeguards confidentiality of data on individual banks. For regional deposit and credit aggregates, publication of data is allowed only if there exist at least two banks and, in reality, each region has more than two banks. BI staff review data prepared for dissemination to avoid possible disclosure of data on individual banks, and develop program specifications that prevent individual disclosure. Whenever individual bank data are made available to, say, academic researchers, the banks in question are not identified.

BI uses a password system to ensure access to electronic data to only those users who are authorized to access it.

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

As stated above, BI has a legal mandate to collect financial data from individual banks for statistical and supervisory purposes, and the individual banks are encouraged to report accurate data through enforcement of penalties in the event of nonreporting or misreporting. Thus, the three regulations—namely, BI Regulation No. 2/21/PBI/2000 (September 19, 2000), Articles 18 to 22, BI Regulation No. 5/26/PBI/2003 (December 1, 2003), Articles 19 to 22, and Director of BI Decree No. 28/58/KEP/DIR (August 29, 1995), Article 4—set penalties for nonreporting and misreporting of data, respectively, for the commercial banks, Syariah (Islamic) banks, and rural banks.

Within this legal framework, BI pursues multiple avenues for ensuring data response by individual banks. BI works with banks to reduce their reporting burden; adapts questions to banks’ financial terminology and accounting formats; provides a point of contact in the Monetary Statistics Division to assist banks with completing the monthly report form; and creates goodwill among banks by responding to their complaints, explaining to them the purpose of data collection, spreading awareness of the importance of good-quality statistics, and providing banks with monetary data upon request. Moreover, BI holds, on a periodic basis, seminars and lectures on data reporting activities—which also helps to strengthen cooperation with banks.

0.2 Resources

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

The present level of staffing in the Monetary Statistics Division is adequate to its needs as seven research assistants are currently available to execute various tasks—data collection, data compilation, and data dissemination. The staff have adequate skills to perform data-related tasks; some have already attended the monetary and financial statistics courses at the IMF headquarters or Singapore Regional Training Institute. The policy of BI’s Directorate of Human Resources is to maintain an adequate level of core staffing in all directorates by limiting the turnover—this is accomplished by requiring the junior staff to spend a minimum of 10 years in their present directorate before they qualify for a transfer to another directorate. BI’s salaries are competitive with those of the rest of the public sector.

Resources allocated to exploit the full potential of the technology for compilation and dissemination of monetary statistics are adequate. As part of this effort, BI’s computers are renewed every 3 to 5 years for a technology update, and commercial banks are encouraged—and most of them do—to report their data online by resorting to either BI’s extranet server or a third-party server. The computer software is distributed correctly within BI to facilitate efficient collection of financial data and management of monetary statistics, and each staff member is provided a personal computer with internet access. As stated above, Board of Governors of BI Regulation No. 2/12/PDG/2000 (June 30, 2000), Article 4, Number 6, describes BI’s information technology policies with an emphasis on their ability to secure its information technology assets from various risks.

BI provides an office building with adequate working facilities, office furniture and equipment, and transportation facilities for various data tasks. Funding provided by BI for these tasks is adequate. BI’s budgeting practices provide clear information to the financing authorities when reviewing priorities for improvements, cutbacks, or increases in certain elements of programs. Over the next three-year period, adequate financial resources have been made available for adopting BI’s monetary statistics to the MFSM methodology.

0.2.2 Measures to ensure efficient use of resources are implemented.

BI seeks efficiencies through a variety of channels. First, the annual performance review provides an opportunity to identify the strengths and weaknesses of individual staff members and reallocate work assignments in accordance with their comparative advantage. Second, reviews of work processes which, within BI, are conducted on a quarterly basis, provide opportunities to promote consistent use of concepts and categories across different areas of statistics. Third, BI uses Working Progress Indicators (IKU and SPAMKA) to measure effectiveness of resources in different tasks.

0.3 Relevance

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

BI provides monetary and financial statistics through a number of media channels—BI’s website (www.bi.go.id), its publication (Indonesian Financial Statistics), and its Weekly Press Release. The website provides a survey form for user satisfaction, and email addresses (contact points) are provided on all publications to receive a user feedback. The staff of the Monetary Statistics Division periodically visit universities to conduct seminars on monetary and financial statistics and take the opportunity to identify user needs among the research community. The staff of the Public Relations Bureau in BI’s Directorate of Strategic Planning and Public Relations periodically hold press conferences on the usefulness of monetary and financial statistics, and similarly take the opportunity to identify user needs among the journalistic community. The staff of the Monetary Statistics Division participate in statistical meetings/seminars organized by the international and regional organizations or by professional organizations. BI undertakes studies to identify new and emerging requirements in monetary statistics—thus, BI staff are currently working on a project to expand the institutional coverage of the monetary survey data to include REKSA DANA that issue deposit-like liabilities.

0.4 Other quality management

0.4.1 Processes are in place to focus on quality.

The Directorate of Economic and Monetary Statistics has a Mission and Vision Statement: its mission is to provide economic and monetary data and information that are comprehensive, reliable, accurate, timely, accessible, and prepared in accordance with international standards; and its vision is to become a reliable working unit in producing and providing economic and monetary data and information. The Monetary Statistics Division reviews monthly data reported by commercial banks and, whenever necessary, reconfirms or corrects data in consultation with them. The Directorate of Economic and Monetary Statistics, as well as the Directorate of Human Resources, conduct training activities that take various forms, such as a one-year orientation program for the new staff, 3–6 month job training program, as well as training courses for the staff promoted to higher levels and in specific aspects of information technology.

0.4.2 Processes are in place to monitor the quality of the statistical program.

The Monetary Statistics Division regularly collaborates with the Directorate of Bank Examination to conduct on-the-spot inspection of select reporting banks to ensure the quality of data reported. It regularly consults with international experts on problems encountered in monetary statistics. Moreover, the Directorate of Economic and Monetary Statistics regularly reviews metadata, either for SDDS or Indonesian Financial Statistics publication.

0.4.3 Processes are in place to deal with quality considerations in planning the statistical program.

A good example is the way in which the project to expand the coverage of the Depository Corporations Survey is being implemented. This project—together with its various work requirements—has been made an integral part of the Monetary Statistics Division’s multi-year work program. As the project specifically aims at broadening the survey coverage to include rural banks and mutual funds, it needs to resolve issues in both respects. The issue with respect to the rural banks was one of a time-lag in the reporting of data: they report monthly balance sheet data with a 3–month lag compared to the 21-day lag with which the commercial banks report the monthly balance sheet data. BI resolved this issue by including rural banks in the survey on the basis of the latest reported data, which would be revised after the actual data for the reference month became available. The issue with respect to the mutual funds is that since they report data to another entity, BAPEPAM in the MoF, the Monetary Statistics Division needs to cooperate with BAPEPAM, in order to have access to mutual fund data. Interagency cooperation necessary to such data sharing is being currently developed.

1. Assurances of integrity

1.1 Professionalism

1.1.1 Statistics are produced on an impartial basis.

The Republic of Indonesia Act No. 23 (May 17, 1999), Article 4 emphasizes the independence of BI in pursuing its goals by prohibiting interference from others, including government agencies. Moreover, the process of recruiting and promoting staff, which takes into account a candidate’s professional and educational qualifications, is primarily merit-based. All new staff are given an opportunity to attend the relevant statistical courses, and to participate in international and regional seminars, courses, and workshops organized by international and regional agencies. Such activities are also organized internally by BI and, to encourage participation, the staff are given time off their work. Research papers prepared by the staff are published in BI’s bulletins and are made available through its library.

1.1.2 Choices of sources and statistical techniques, as well as decisions about dissemination, are informed solely by statistical considerations.

Source data for monetary statistics are collected from the financial reports submitted by commercial banks and rural banks. These data are collected within the format of BI’s reporting system that reflects the statistical requirements of the MFSM methodology. At the same time, BI supplements this balance sheet data with administrative records. Decisions to disseminate monetary statistics are exclusively based on statistical considerations that are free from interference from others, including government agencies, and their timing is based on the ARC included in the SDDS metadata.

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

The Public Relations Bureau in BI’s Directorate of Strategic Planning and Public Relations comments on erroneous interpretation and misuse of monetary statistics in the media. However, since the media usually confirms monetary statistics with BI before interpreting and publishing them, instances of commentary by the Public Relations Bureau have been few.

1.2 Transparency

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

BI’s website (www.bi.go.id) publicizes the terms and conditions under which monetary statistics are collected, processed, and disseminated. Thus, the website declares that BI, which is the sole institution that is authorized to compile and disseminate monetary statistics, presents monetary and banking indicators as accurately as possible. However, owing to time lags in data compilation, as well as possible technical difficulties, the monetary statistics that are presented might be only interim statistics based on the latest available data and, therefore, open to subsequent revisions in accordance with the updated data. The Public Relations Bureau in BI’s Directorate of Strategic Planning and Public Relations makes an effort through its weekly press releases to inform the public of the terms and conditions under which monetary statistics are compiled. BI’s statistical publications identify BI as a source for additional information on BI and its products.

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

No internal governmental access to statistics prior to their release exists.

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

BI’s statistical publications identify them as the products of BI—with its name, address, logo, and insignia. For monetary statistics, no joint publication by BI and another agency exists, since the former is the sole institution with an authority to compile and disseminate monetary statistics. Whenever monetary statistics are used or published by an agency other than BI, the latter requests an acknowledgement by BI as a source of data.

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

BI provides an advanced notice to the users of monetary statistics of major changes in methodology, source data, and statistical techniques. Consistent with these changes, BI revises metadata on monetary statistics.

1.3 Ethical standards

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

Board of Governors of BI Regulation No. 3/9/PDG/2001 provides working guidelines for staff behavior, which are published in a pocket-size book. The Monetary Statistics Division has a Job Manual which provides guidelines for behavior of staff who are working specifically in the area of monetary statistics. Staff behavior is reviewed as one of the aspects of BI’s annual performance review.

2. Methodological soundness

2.1 Concepts and definitions

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

BI recently made extensive revisions to its monetary statistics. These revisions, which reflected the recommendations of the technical assistance missions from the IMF Statistics Department (STA), have brought BI’s monetary statistics broadly in line with the MFSM methodology. At the same time, the Monetary Statistics Division keeps under review the existing deviations from the MFSM methodology and, in consultation with STA, seeks to correct them.

2.2 Scope

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

According to the MFSM methodology, all resident depository corporations should be included in the institutional coverage of the Depository Corporations Survey. This means that, in the specific case of Indonesia, the Depository Corporations Survey should cover BI, commercial banks, rural banks, as well as REKSA DANA that issue deposit-like liabilities. At present, BI’s Depository Corporations Survey covers BI, 132 resident commercial banks (as of January 2005), and some 9000 rural banks—which together account for 95 percent of the total deposit collection. Depository corporations are included in this institutional coverage with their domestic headquarters, as well as their domestic branches, and no deviations from this institutional coverage exist. Mutual funds, however, are not included as they report data to another entity, BAPEPAM in the MoF, and in a format that does not meet statistical needs. Moreover, as observed in 0.1.2 above, although the BAPEPAM provides mutual funds data, on an informal basis, to the Monetary Statistics Division, BI has not yet institutionalized its arrangements for data sharing with the BAPEPAM. These issues are being addressed by the Monetary Statistics Division staff, who have already commenced a project to expand the institutional coverage of the Depository Corporations Survey to include mutual funds.

2.3 Classification/sectorization

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

BI’s classification scheme for monetary statistics is in line with the MFSM methodology. Thus, financial instruments are classified on the basis of their liquidity characteristics. The classification of financial instruments in BI’s monetary statistics is as follows.

  • Monetary gold and SDRs

  • Currency and deposits

  • Securities other than shares

  • Loans

  • Shares and other equity

  • Insurance technical reserves

  • Financial derivatives

  • Other accounts receivable/payable

Likewise, BI’s sectorization scheme for monetary statistics is in line with the MFSM methodology. Thus, institutional units are divided by resident and nonresident sectors on the basis of the residency criterion recommended in the Balance of Payments Manual, Fifth Edition (BPM5). Resident units thus defined are grouped into the following sectors:

  • Financial corporations (central bank, other depository corporations, other financial corporations);

  • Nonfinancial corporations (public nonfinancial corporations, other nonfinancial corporations);

  • General government (central government, state and local government);

  • Households;

  • Nonprofit institutions serving households.

International standards require that repurchase agreements (repos) be treated as collateralized loans. Accordingly, BI treats them as collateralized loans in its monetary statistics. Consistent with this treatment, gold swaps are also treated as collateralized loans when they involve an exchange of monetary gold for cash—domestic or foreign.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

BI and commercial banks follow the market valuation principle in the valuation of most of their assets and liabilities. Thus, in the case of both BI and commercial banks, (1) securities (foreign and Indonesian) are valued at market prices or “fair prices;” (2) loans are valued at current book values without adjustment for expected losses from possible defaults; and (3) foreign currency-denominated positions are converted at the market exchange rate prevailing on the reference date of the balance sheet. As stated in the Statement of Financial Accounting Standard (FSAF), commercial banks are instructed to use the Reuters midpoint closing rate at the end of the period (month) at 4:00 p.m. Of special note, BI’s monetary gold and SDR holdings are valued at market prices/market exchange rates.

Valuation adjustments (including holding gains and losses on instruments) are presented in the valuation changes in the balance sheets/surveys of either BI or commercial banks. These valuation adjustments (particularly holding gains and losses on instruments) are captured in the monthly report form for commercial banks.

By and large, no deviations from the internationally-accepted standards exist on the valuation principles. However, wherever deviations occur, BI publications identify and describe other accounting rules and valuation criteria that have been used.

2.4.2 Recording is done on an accrual basis

Accounting data used for monetary statistics are based on accrual accounting. Thus, transactions and other flows are recorded at the moment when economic value is created, transformed, exchanged, transferred, or extinguished. Of particular note, interest on financial assets and liabilities is treated as accruing on a continuous basis during the accounting period and, consequently, overdue interest is included in the value of the outstanding obligation. As accrual accounting requires simultaneous recording of the transaction by both parties, adjustments are made to the date of the transaction whenever the two parties record the same transaction on two different dates. No deviations from accrual accounting exist.

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

Accounting data used for monetary statistics are collected on a gross basis, and claims of a particular transactor are not netted against the liabilities to the transactor in question. In BI’s Depository Corporations Survey, however, certain statistical aggregates are presented on a “net” basis owing to the analytical usefulness of the net concepts involved. This survey thus shows Net Foreign Assets, Net Claims on Central Government, and other items (net). At the same time, in these respects, the underlying data are also shown on a gross basis. The Depository Corporations Survey is derived by canceling out all financial flows and outstanding claims and liabilities between all depository corporations, while preserving the presentation of data on all stocks and flows that are claims on (and liabilities to): financial corporations subsectors other than the depository corporations subsector, other domestic sectors, and nonresidents. No deviations from the international standards exist.

3. Accuracy and reliability

3.1 Source data

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

BI maintains a comprehensive and current register of institutional units in the financial sector. This register, which lists all depository corporations and is updated to reflect changes arising out of the entry of new units and liquidation and mergers of exiting ones, is part of the core source data for monetary statistics. BI is currently developing institutional data-sharing arrangements with the MoF that would enable it to access the register of—and data on—mutual funds, insurance companies, and pension funds, as well as finance companies. The institutional and geographic coverage of these registers is complete, and procedures adopted for their maintenance are adequate.

Commercial banks and rural banks report data to BI by using report forms designed by BI. Since its introduction in January 1972, the report form for commercial banks has been revised 11 times to take into account changes in the financial sector. The report form for rural banks, however, has not been revised since its introduction in August 1995 since the financial activities of the rural banks have remained relatively simple. A new reporting system for rural banks, however, is being developed. REKSA DANA that issue deposit-like liabilities report data to BAPEPAM by using a report form designed by BAPEPAM.

BI’s monetary statistics are more or less exclusively based on the balance sheet data as BI’s, commercial banks’ and rural banks’ balance sheets normally provide sufficient detail to classify data by financial instruments and economic sectors identified in the MFSM methodology. In cases where these balance sheets need information from outside accounting records, sectoral reports and off-balance sheet items are used. BI allows the collection of supplementary information—information from sources outside the usual data reporting schedule—for monetary statistics compilation. The Monetary Statistics Division, whenever necessary, consults with BI’s Directorate of Bank Supervision on select data issues, and such consultations occasionally lead to changes in monetary statistics. Financial markets and other sources of information—for example, the financial press and research papers—are regularly monitored to identify financial developments with a potential to impact monetary statistics, and periodic meetings with the financial supervisory authority, financial market participants, and the business community are held to identify such developments.

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

Most depository corporations prepare source data according to standards that are broadly consistent with the MFSM methodology. Commercial banks and rural banks use report forms (designed by BI) that fully meet statistical requirements. REKSA DANA that issue deposit-like liabilities, however, use a report form (designed by BAPEPAM) that does not meet statistical requirements. Consequently, BAPEPAM’s source data are not being used for monetary statistics, and mutual funds have not been incorporated into BI’s Depository Corporations Survey.

3.1.3 Source data are timely.

BI collects a major portion of the source data on a timely basis. Thus, BI’s balance sheet data are compiled on a daily basis for internal use with a lag of only one day, and on a weekly basis for external use with a lag of only about five days. Commercial banks report finalized data to BI on a monthly basis with a 21-day lag from the end of the reference month. Rural banks also report data to BI on a monthly basis, although with a three-month lag. As the data reporting lag for the latter is longer than that for the former, the rural banks are incorporated into the survey on the basis of the latest reported data, which are revised after the actual data for the reference month become available. Timeliness in source data collection is ensured through rigorous follow-up procedures that include calls to respondents and enforcement of penalties provided under the law.

3.2 Assessment of source data

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

BI staff monitor the accuracy of data reported by individual financial corporations. The monitoring system tests the internal consistency of each institution’s data (formal crosschecks) and identifies out-of-trend movements (plausibility checks). Should the staff of the Monetary Statistics Division identify inconsistent figures or implausible changes in the data reported by individual commercial banks, they make follow-up calls to the commercial banks in question. Likewise, in the case of BI’s accounting data, the staff makes follow-up calls to BI’s Directorate of Accounting and Payment System.

3.3 Statistical techniques

3.3.1 Data compilation employs sound statistical techniques to deal with data sources.

As BI’s monetary statistics are more or less exclusively based on the balance sheet data prepared by the depository corporations, they do not, by and large, rely on the use of statistical techniques. The only example of the latter is the way rural banks are incorporated into the survey. As stated above, since the data reporting lag for the rural banks (three months) is longer than that for the commercial banks (21 days), the rural banks are incorporated into the survey on the basis of the latest reported data, which are revised after the actual data for the reference month become available. This is a generally accepted method in the statistical profession, and was recommended to BI by STA missions.

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

BI does not use any other statistical procedures/statistical techniques in its monetary statistics. When the actual data do not approximate the MFSM methodology, BI does not use any specific procedures to adjust data from various sources to improve coverage. Thus, although the coverage of the Depository Corporations Survey excludes REKSA DANA that issue deposit-like liabilities, no attempt is made to broaden the coverage by using estimated data on mutual funds. As an additional point, BI does not use seasonal adjustments in its monetary statistics.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Intermediate results are validated against other information, where applicable.

BI occasionally uses other information to validate balance sheet data collected from commercial banks. A good example of this is the use of an alternative data source on central government bonds in the form of the Scriptless Security Settlement System jointly developed by BI and the MoF for cross-checking the data on the banking sector’s holdings of central government bonds. In January 2005, BI conducted a survey of consumption credit extended by a group of the 20 largest banks, and used the results to cross-check aggregate credit data. Finally, the monetary statistics staff hold meetings on a monthly basis with the Foreign Exchange, Research, and Monetary Management Departments to validate financial information that would be used for monetary statistics.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

A comparison of BI’s data with the source (reported) data on commercial banks, however, shows discrepancies in two aspects of interbank positions—namely, (1) commercial banks’ deposits with BI and (2) their holdings of BI securities. Thus, BI’s data on commercial banks’ deposits with BI differs from the commercial banks’ source (reported) data on their deposits with BI; and BI’s data on the issue of BI securities to commercial banks differs from the commercial banks’ source (reported) data on their holdings of BI securities. No source data discrepancy, however, exists between BI’s data on its claims on commercial banks and the commercial banks’ data on their liabilities to BI. On the commercial banks’ holdings of BI securities, BI assesses the reported data on stocks and flows of BI securities within sectoral balance sheets in relation to the corresponding data in its own securities database. However, since commercial banks engage in sales of BI securities in the secondary market, differences arise between BI’s record and commercial banks’ records. As no financial transactions data are reported, no reconciliation is attempted with changes in the corresponding stock data collected through balance sheets.

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

BI investigates classification/sectorization errors or omissions as a possible source of fluctuations or discrepancies in monetary statistics. BI currently presents its monetary statistics only in stock terms. At the same time, it seeks to reconcile the implied flows in monetary statistics with flows in the balance of payments statistics.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used internally to inform statistical processes (see also 4.3.3).

Monetary statistics, which are based on provisional source data, are revised when final source data become available. The only respect where provisional data are initially used and subsequently revised is the incorporation of rural banks into the Depository Corporations’ Survey. As the data reporting lag for the rural banks (three months) is significantly longer than that for the commercial banks (21 days), the rural banks are incorporated into the survey on the basis of the latest reported data, which are revised after the actual data for the reference month become available. The Monetary Statistics Division prepared the first revision study in March 2005 and, so far, only one revision study has been prepared.

4. Serviceability

4.1 Periodicity and timeliness

4.1.1 Periodicity follows dissemination standards.

Data on the Central Bank’s Survey are disseminated with a weekly periodicity (compared to the monthly periodicity required under the SDDS), and those on the Other Depository Corporations’ Survey (for commercial banks and rural banks) are disseminated with a monthly periodicity (compared to the monthly periodicity required under the SDDS).

4.1.2 Timeliness follows dissemination standards.

Data on the Central Bank’s Survey are disseminated within two weeks after the end of the reference month (compared to the two-week lag allowed under the SDDS), and those on the Other Depository Corporations’ Survey data are disseminated within four weeks (compared to the one-month lag allowed under the SDDS).

4.2 Consistency

4.2.1 Statistics are consistent within the dataset.

BI’s published data on interbank positions—BI’s position in relation to the commercial banks’ position as recorded in BI’s accounts and the commercial banks’ position in relation to BI’s position as recorded in the commercial banks’ accounts—are consistent. However, as observed in 3.4.2. above, a comparison of BI’s data with the source (reported) data on commercial banks shows discrepancies in some aspects of interbank positions (commercial banks’ deposits with BI and their holdings of BI securities). BI responds to these discrepancies by substituting its data for the commercial banks’ data—and this ensures consistent interbank positions in the published data.

BI’s monetary statistics are compiled from accounting data that are collected only in stock terms. Consequently, no attempt is made to identify and reconcile stock data with flow data within the same monetary dataset.

Positions between the depository corporations (BI, commercial banks, and rural banks) and other (nondepository) financial corporations (primarily insurance companies, pension funds, and finance companies) cannot be reconciled with each other. This is because BI does not collect—nor does it have any access to—data on most of the other financial corporations. This is because data on other financial corporations are collected by the MoF and, while BI has developed arrangements for accessing finance companies data, it has not yet developed those for accessing insurance companies and pension funds data.

Monetary aggregates are largely consistent or reconcilable with the aggregates of monetary instruments held by money holding sectors in the flow of funds accounts. Credit aggregates are largely consistent or reconcilable with the debt aggregates calculated based on the flow of funds accounts. This reflects the fact that monetary statistics provide inputs to the flow of funds accounts on these points.

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

Whenever changes in source data, methodology, or techniques are introduced, historical series for monetary statistics are reconstructed as far back as reasonably possible. Thus, when BI staff developed, with technical assistance provided by STA, an integrated monetary database involving extensive revisions to their monetary data due to changes in the sectorization of institutional units and in the classification of financial instruments, they revised monetary data series on a month-by-month basis from June 2004. Moreover, when the revised monetary data were published for the first time in the February 2005 issue of BI’s Indonesian Financial Statistics, they were accompanied by metadata explaining key methodological changes.

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

BI’s monetary statistics are neither consistent, nor reconcilable, with the MoF’s government finance statistics on the bank financing of the central government operations, but are broadly consistent with the balance of payments statistics. Although the net foreign assets in monetary statistics somewhat differs from the corresponding measure derived from the balance of payments statistics, the differences are attributable to the different exchange rates used for valuation. Whereas the monetary statistics use end-of-period exchange rates for conversion, the balance of payments statistics use exchange rates obtained at the time of transactions.

4.3 Revision policy and practice

4.3.1 Revisions follow a regular and transparent schedule.

As stated in 3.5.1 above, monetary statistics, which are based on provisional source data, are revised when final source data become available. The only significant respect where provisional data are initially used and subsequently revised is the incorporation of rural banks into the Depository Corporations’ Survey. As the data reporting lag for the rural banks (three months) is significantly longer than that for the commercial banks (21 days), the rural banks are incorporated into the survey on the basis of the latest reported data which, however, are revised after the actual data for the reference month become available. This revision follows a regular and transparent schedule: the schedule for, and the causes of, this revision are documented in the February 2005 issue of BI’s Indonesian Financial Statistics, where the monetary data with a coverage revised to include rural banks was published for the first time.

4.3.2 Preliminary and/or revised data are clearly identified.

At the time of data dissemination, users are informed of the preliminary nature, as well as of the revised nature, of the monetary data. In BI’s Indonesian Financial Statistics, for example, preliminary data are indicated by an asterisk.

4.3.3 Studies and analyses of revisions are made public (see also 3.5.1).

As stated in 3.5.1 above, the Monetary Statistics Division prepared the first revision study in March 2005 and, so far, only one revision study has been prepared. This study has not been published. This is because revisions to monetary data, which are due exclusively to the incorporation of rural banks in the survey, tend to be very small as the rural banks’ contribution to the overall financial activity is very small.

5. Accessibility

5.1 Data accessibility

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

BI disseminates monetary statistics in a clear manner. To meet a range of users’ needs, these data are disseminated with various levels of detail or disaggregation—thus, credit and deposit data are disseminated by groups of banks, groups of borrowers/holders, economic sectors, as well as geographic regions. BI does not provide diagrammatic representations (in the form of, say, charts) nor commentaries on current-period financial developments with the disseminated monetary data; does not disseminate estimated monetary data; and does not make seasonal adjustments to monetary data.

5.1.2 Dissemination media and format are adequate.

Monetary statistics are disseminated in hard copy and electronic formats—for example, through weekly press releases, BI’s Indonesian Financial Statistics, and BI’s website (www.bi.go.id). These formats of dissemination facilitate redissemmination in the media. More comprehensive and/or detailed monetary statistics, as well as longer monetary data series, can be accessed through the BI website, as well as from an electronic database maintained by BI.

5.1.3 Statistics are released on a preannounced schedule.

An ARC, which provides dates on which monetary statistics would be released in near future, is published on the SDDS website. The BI and SDDS websites are hyperlinked to each other. Monetary statistics are released according to this schedule.

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

Monetary statistics are made available to all users at the same time. The simultaneous release is achieved by placing monetary statistics on the BI website when it is ready for dissemination. The press, which is not briefed in advance, receives monetary statistics at the same time as other users.

5.1.5 Statistics not routinely disseminated are made available upon request.

Aspects of monetary statistics that are not routinely disseminated are made available to the public upon request, provided that the request does not involve disclosure of individual bank data. Requests for nonpublished and nonconfidential aspects of monetary statistics have generally come from the research community, commercial banks, and government entities. Customized tabulations of monetary statistics can be provided (without fee) upon request—and requests for such tabulations have also been received. The availability of monetary data and procedures for obtaining them are made known to the public—for example, contact points have been provided in BI’s publications and website.

5.2 Metadata accessibility

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

The SDDS website provides a comprehensive sources and methods document that includes information on concepts, scope, classifications, basis of recording, data sources, and statistical techniques, as well as differences from international standards. The SDDS metadata, which is hyperlinked to the BI website, is reviewed and updated regularly twice a year. Moreover, as observed in 4.2.2 above, when the revised monetary data was published for the first time in the February 2005 issue of BI’s Indonesian Financial Statistics, it was accompanied by metadata explaining key methodological changes.

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

General use information on monetary statistics (for example, how to locate the data) is available and published on the BI website. More specialized use information on monetary statistics (for example, background papers, working documents) is not available.

5.3 Assistance to users

5.3.1 Contact points for each subject field are publicized.

BI provides prompt and knowledgeable service and support to users of monetary statistics. All statistical releases identify at least one contact point (Administration Division of BI’s Directorate of Economic and Monetary Statistics) for enquiries by mail, telephone, and facsimile. Material to raise awareness on the use of monetary statistics is available and is usually distributed, especially to the university lecturers and students, as well as to the press reporters, during seminars on the usefulness of monetary statistics. Access points for clients to obtain monetary statistics are well advertised on the BI website and publications. Assistance to users is monitored and reviewed periodically, either from the BI website or from BI Help Desk facilities (phone number: 381-8000 or email helpdesk@bi.go.id).

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

Catalogs of publications, documents, and other services are available from the BI website. These catalogs are updated regularly. Although the prices of statistical products and services are not disclosed in the catalogs, the Administration Division of BI’s Directorate of Economic and Monetary Statistics provides whatever assistance the potential customers might need in placing orders—including, of course, price information.

Table 3.Indonesia: Data Quality Assessment Framework (July 2003): Summary of Results for Monetary Statistics(Compiling Agency: Bank Indonesia)
Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria
ElementNAAssessmentComments
OLOLNONO
0. Prerequisites of quality
0.1 Legal and institutional environmentX
0.2 ResourcesX
0.3 RelevanceX
0.4 Other quality managementX
1. Assurances of integrity
1.1 ProfessionalismX
1.2 TransparencyX
1.3 Ethical standardsX
2. Methodological soundness
2.1 Concepts and definitionsX
2.2 ScopeXREKSA DANA that issue deposit-like liabilities are excluded from the scope of monetary statistics.
2.3 Classification/sectorizationX
2.4 Basis for recordingX
3. Accuracy and reliability
3.1 Source dataXSource data collected on REKSA DANA do not meet statistical requirements.
3.2 Assessment of source dataX
3.3 Statistical techniquesX
3.4 Assessment and validation of intermediate data andXReported interbank positions are not consistent.
statistical outputs
3.5 Revision studiesX
4. Serviceability
4.1 Periodicity and timelinessX
4.2 ConsistencyXGFS domestic financing data are not reconcilable with the monetary statistics.
4.3 Revision policy and practiceX
5. Accessibility
5.1 Data accessibilityX
5.2 Metadata accessibilityX
5.3 Assistance to usersX

IV. Balance of Payments Statistics

0. Prerequisites of quality

0.1 Legal and institutional environment

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

BI is responsible for compiling and disseminating quarterly and annual balance of payments data. Within BI, the Balance of Payments Division (BOP Division) of BI’s Economic and Monetary Statistics Department is in charge of compiling the balance of payments statistics. To this end, the BOP Division is also in charge of conducting the International Transactions Reporting System (ITRS) and enterprises surveys; compiling and disseminating the balance of payments and international investment position (IIP); and analyzing and interpreting balance of payments data.

BI operates under Central Bank Act (No. 23, 1999), as amended, with Act No. 3 of 2004. Under this Act, BI determines the coverage, content, methodology and periodicity of the data it collects and compiles. Act No. 24 of 1999 (concerning the Foreign Exchange Flow and Exchange Rate System), Article 3 conveys to BI the authority to request information and data about the foreign exchange transactions conducted by a resident. BI Regulation No. 1/4/PBI/1999 concerning Survey Conducted by BI (Article 10, paragraph 1) gives BI the right to request the information and data in the form of a survey.

BI Regulation No. 1/9/PBI/1999 concerning Monitoring of Foreign Exchange Activities of Banks and Nonbank Financial Institution makes it the obligation of the banks and Nonbank Financial Institutions (NBFIs) to deliver information and data on their foreign exchange activities to BI completely, accurately, and in a timely manner. Article 2 of BI Regulation No. 4/2/PBI/2002, as amended by BI Regulation No. 5/1/PBI/2003 concerning Monitoring of Foreign Exchange Payments by Nonfinancial Institution Companies, requires any company conducting activities in foreign exchange payments to deliver complete, accurate, and timely reports presenting information and data on such activities to BI.

BI compiles balance of payments/IIP data from a number of sources, including custom records and other sources for foreign trade statistics. Suitable arrangements exist to collect relevant information in a timely manner, and no conflicts over the authorities to produce the statistics exist.

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

The system of data sharing among the compiling agencies is generally adequate. A series of agreements among different agencies have recently been set up, including a (i) Memorandum of Understanding between BI and the Directorate General of Customs dated November 5, 2002, which arranges for the delivery of online export & import data, (ii) Letter of Cooperative Agreement between BI and the Ministry of Culture and Tourism dated May 21, 2003, which arranges for the implementation of the Passenger Exit Survey (PES), (iii) Letter of Cooperative Agreement between BI and the Ministry of Culture and Tourism dated April 8, 2004, which organizes the implementation of the Outbound Survey, and (iv) Letter of Cooperative Agreement between BI and BPS dated August 24, 2004, which prepares the implementation of the Foreign Worker Survey. BI, BPS, and Customs also has a Working Group on trade data. However, BPS produces balance of payments data for purposes of compiling the national accounts. These data, which are produced for BPS’s internal use, differ from the balance of payments data produced by BI.

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

Act No. 23 of 1999, Article 14, paragraph 4 obliges BI to keep the data source and individual data confidential. BI Regulation No. 1/4/PBI/1999 (concerning Survey Conducted by BI) Article 10, paragraph 2 states that BI shall treat the source, information, and individual data as confidential. BI Regulation No. 1/9/PBI/1999 dated October 28, 1999, Article 3 and BI Regulation No. 4/2/PBI/2002 dated March 28, 2002 Article 2, paragraph 2 establish that information and data submitted to BI shall be confidential.

In the Elucidation of Article 14, paragraph 3 of Act No. 23 of 1999, it is stated that the information and data needed by BI are not used for the purpose of examination but for the purpose of producing statistics. Act No. 23 of 1999, Article 71, paragraph 1 stipulates the penalties against staff who disclose confidential data. The Regulation of BI Board of Governor No. 2/12/PDG/2000 date June 30, 2000 (further provision concerning the implementation of the regulation is prescribed by BI Circular Letter No. 2/61/INTERN dated December 22, 2000) stipulates the information technology strategy and policy of BI. An output scheme is designed as the aggregation rules of ITRS data. A special computer program is designed to process the data from the foreign direct investment (FDI) survey. BI staff review all data prepared for dissemination to avoid possible indirect disclosure of individual data. If individual data are made available to the public (e.g., for research purposes), all individual data are made anonymous.

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

Act No. 23 of 1999 concerning Bank Indonesia (Article 14, paragraph 1) gives the authority to BI to conduct surveys. Article 28, paragraph 1 of the same Act obliges banks to deliver reports, information, and explanations to BI. Act No. 24 of 1999 (concerning the Foreign Exchange Flow and Exchange Rate System), Article 3 gives BI the authority to request information and data concerning foreign exchange flows conducted by a resident. BI Regulation No. 1/4/PBI/1999 (concerning Survey Conducted by BI), Article 10, paragraph 1 gives BI the right to request the information and data object of the survey from the respondent. BI Regulation No. 1/9/PBI/1999 concerning Monitoring of Foreign Exchange Activities of Banks and Nonbank Financial Institutions specify that the banks and NBFIs have the obligation to deliver information and data on their foreign exchange activities to BI. In the same manner, BI Regulation No. 4/2/PBI/2002, as amended, with BI Regulation No. 5/1/PBI/2003 (concerning Monitoring of Foreign Exchange Payments by Nonfinancial Institution Companies), Article 2 requires any company conducting activities in foreign exchange payments to deliver complete, accurate, and timely reports, information, and data on such activities to BI.

In case of delay or noncompliance, the BOP Division uses moral suasion in contacting respondents by telephone in order to increase the response rate of the survey. Act No. 23 of 1999, Article 69 stipulates the penalties to be imposed to an entity that does not convey the information and data from the survey to BI. Act No. 24 of 1999, Article 6 stipulates the penalties to be imposed to a resident who does not give information and data on foreign exchange activities that he conducted. BI Regulation No. 1/4/PBI/1999 concerns surveys conducted by BI. Article 15 stipulates administrative sanctions to be imposed to the respondent who does not fulfill his liability. BI Regulation No.1/9/PBI/1999 concerns Monitoring of Foreign Exchange Activities of Banks and NBFIs. Article 9–12 stipulates the administrative sanctions to be imposed for noncompliance

The BOP Division also uses other means to ensure the reporting by respondents, such as considering carefully the response burden. Consequently, it redesigned and simplified the FDI survey form. In the same manner, the ITRS report form was modified to make it consistent with the respondents’ bookkeeping format. BI also organizes meetings and business lunches with survey respondents. A point of contact is indicated in the survey form. Other activities include the creation of an ITRS help-desk, an ITRS working group, training sessions for reporters on report evaluation, and report guidance.

0.2 Resources

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

Staff resources of the BOP Division are adequate to its needs. A total of 32 staff are assigned–44 percent of the staff have a higher education degree, and 50 percent have taken a balance of payments course on concept and methodology organized by the IMF. The Directorate of Human Resources of BI prepares annual plans for skills improvement to enhance the expertise of BI staff. BI has benefited from considerable technical assistance in balance of payments compilation provided by STA. Thirty-one percent of the staff have at least five years’ experience in balance of payments compilation. Recently, Internal Circular letter No. 7/4//INTERN/2005 dated January 19, 2005 allows the manager of a work unit to negotiate with the Human Resources Directorate the timing of transfer of his specialized staff to another work unit, thereby providing more stability in the career of the said specialized staff than that of general staff.

In terms of computing resources, sufficient resources are allocated and best efforts are made to exploit the full potential of effective computing technology for the compilation and dissemination of balance of payments.

The Logistic Management of BI arranges for the computer replacement and software updating periodically. Each staff is equipped with one computer, most of them with access to the internet. In terms of protection for the computer resources, the Directorate of Information Technology provides adequate protection by installing a centralized virus protection system. Servers are available in the BOP and Data Dissemination Divisions for data backup and backup cartridge (media tape). A report on Bank Reporting System (BRS) is submitted online through the BI extranet. The processing of ITRS data is done systematically through the Data Dissemination Division’s server.

0.2.2 Measures to ensure efficient use of resources are implemented.

BI put in place an effective mechanism to enhance staff performance and productivity. Staff performance appraisals are conducted annually. Regulation of BI Board of Governors No. 4/15/PDG/2002, dated November 29, 2002, organizes BI’s work plan, budget, and performance management system. BI has benefited from considerable technical assistance in balance of payments compilation provided by STA. BI’s resources used to compile balance of payments and IIP statistics are measured annually, e.g., Primary Performance Indicators (IKU).

0.3 Relevance

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

Data users are informed on the periodicity and timeliness of the balance of payments data through the SDDS website. A contact person is provided in the SDDS and BI websites (Head of Balance of Payments Statistics Division, Directorate of Economic and Monetary Statistics, Bank Indonesia, Snp@bi.go.id). A quarterly “survey on users” satisfaction is conducted by the Bureau of Governor. A quarterly coordination meeting with related institutions is conducted before the publication of balance of payments statistics. Business lunches are organized with survey respondents and ITRS reporters. A Working Group on BRS and Non Bank Financial Institution Reporting System (NBFIRS) was set up. BI also participates in statistical meetings such as the ASEAN Working Group on FDI (WGFDI). The BOP Division undertakes studies to help identify new and emerging data requirements.

0.4 Other quality management

0.4.1 Processes are in place to focus on quality.

The Directorate of Economic and Monetary Statistics has a mission statement: the mission is to provide reliable data and information on economic, financial, and monetary which are comprehensive, reliable, accurate, timely, accessible, and meet the international standard. BI emphasizes on enhancing the quality of its staff by allowing them to participate in internal and external training courses.

0.4.2 Processes are in place to monitor the quality of the statistical program.

BI performs quality checks in the process of collecting, processing, and verifying data. They involve cross-checks and, in the event of discrepancies, follow-up by staff. Internal Regulation (SE Intern) on ITRS provides the division’s job description. For its national publication, BI has set up an ARC as a means for the management to control the timeliness of statistics. Although BI does not conduct formal surveys of users of balance of payments statistics, it offers them the possibility to communicate through e-mail, mail, phone, fax, or direct visits for comments or consultation. BI also conducts regular reviews of metadata (annually), and regular reviews of its SDDS submissions (semi-annually).

0.4.3 Processes are in place to deal with quality considerations in planning the statistical program.

The BOP Division attempts to improve continuously the quality of balance of payments statistics. Examples include trying to compile the data on assets of financial account items; gathering feedback from users; and establishing a cut-off date on processing balance of payments statistics in order to achieve timeliness without ignoring the quality of the data.

1. Assurances of integrity

1.1 Professionalism

1.1.1 Statistics are produced on an impartial basis.

Act No. 23 of 1999 concerning Bank Indonesia, as amended by Act No. 3 of 2004 Article 4 ensures the independence of BI in achieving its goals by prohibiting interference from others, including other government agencies. Article 9, paragraph 2 of the act states that BI shall refuse and/or disregard any form of intervention conducted by other parties. Professionalism is actively promoted through the recruitment process, which is based on merit. Only graduates with at least a bachelor’s degree, a certain level of grade point average (GPA), and passed the Test of English as a Foreign Language (TOEFL) are recruited. The BOP Division regularly sends qualified employees to participate in seminars, workshops, and conferences sponsored by international and regional institutions. Professionalism is also promoted by encouraging staff to give lectures at the School for Staff and Leaders of Bank (SESPIBANK) and to contribute articles for publication in the Bank Indonesia Annual Report. Research and analysis are encouraged in the BOP Division, primarily for the purpose of providing information for the Board. BI does not have a tradition of publishing methodological research papers.

1.1.2 Choices of sources and statistical techniques, as well as decisions about dissemination, are informed solely by statistical considerations.

The BOP Division has the sole responsibility for determining which data sources and statistical techniques are to be used in balance of payments compilation.

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

No formal policy or well-established custom exists to deal with data misinterpretations or misuse of statistics. The BOP Division responds to erroneous interpretations of its statistics by the users of statistics or provides clarification, as required. The BOP Division monitors media coverage of its data (clipping service).

1.2 Transparency

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

The terms and conditions under which official statistics are compiled and disseminated are embodied in the legislation under which statistics are collected—the Central Bank Act (No. 23 of 1999), as amended, with Act No. 3 of 2004 and Act No. 24 of 1999 concerning the foreign exchange flow and exchange rate system. These acts are posted on the BI website, and copies of these acts are available at the following address:

Directorate of Legal, Bank Indonesia, “Tipikal” Building, Jl. M.H.Thamrin No.2, Jakarta 10110.

The metadata posted on the IMF’s Dissemination Standards Bulletin Board (DSBB) (http://dsbb.imf.org/Applications/web/dsbbhome/) provide information on the terms and conditions under which the statistics are collected, processed, and disseminated. The DSBB also contains an ARC for balance of payments statistics. BI’s website provides a link to the DSBB (and vice versa) for users who would be interested in looking at information on balance of payments metadata. The site also provides information on BI, including its responsibilities, structure, and statistical products and publications.

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

There is no government access to the data before their release to the public.

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

The balance of payments data disseminated on BI’s website and in hard copy are clearly identified as the product of BI. BI does not undertake joint publications of its data. BI does not explicitly request attribution when its statistics are used or reproduced.

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

When BI makes changes to balance of payments methodology or source data, the public is usually informed concurrently when the change is effected.

1.3 Ethical standards

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

The norms of conduct of BI personnel in the performance of their duties are subject to Regulation of BI Board of Governors No. 3/9/PDG/2001 concerning Discipline Rules for BI Employees and Regulation of BI Board of Governors No. 4/7/PDG/2002 concerning Rules of Order of BI Employees.

All new recruits participate in extensive training courses. These courses give the participants information on BI’s responsibilities, activities, and banking secrecy, and provide guidance on staff behavior and ethical standards expected of BI staff. All staff are required to sign an oath of secrecy. BI annually reviews its staff’s performance. One aspect that is included in the review is staff’s behavior. This annual review ensures that the staff will always follow the standard if they want to have a good result on their review. BI management acknowledges its status as a role model and observes the ethical standards.

2. Methodological soundness

2.1 Concepts and definitions

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

Indonesia’s balance of payments statistics generally follow the concepts and definitions set out in BPM5. Current, capital, and financial accounts of the balance of payments statement are defined broadly in accordance with the guidelines of the BPM5. The current account balance, in principle, is equal to the net capital and financial account balance. A double-entry system is applied as a basic principle, and the net residual is embedded in the errors and omissions item. Available information on financial accounts items has not yet been sufficient for recording of transactions in assets. The directional basis is employed in compiling and recording the FDI component. Resident institutional units are defined in conformity with BPM5. For example, foreign banks’ branches are considered resident of Indonesia and foreign branches of Indonesian banks are nonresident; the residence of offshore entities and enterprises operating in free trade zones is attributed to the economy in which they are located; the residence of special purposes enterprises (SPE) is attributed to the economy in which they are located; international organizations and supranational authorities are not considered resident of any national economy; while all units of general government (e.g., embassies) are considered to be resident in their own economy. However, the financial account does not provide for separate recording of transactions in assets and transactions in liabilities, owing to a lack of adequate source data. It is planned to publish such data for 2004 in Q2, 2005.

The balance of payments transactors are defined as all resident economic entities of a compiling economy engaging in transactions with nonresidents. Transactions are defined according to the guidelines of BPM5. For example, both exchanges and unrequited transfers are registered; FDI inward transactions are estimated by applying10 percent to the capital of an enterprise. The 10 percent ownership rule is prescribed by BPM5. To be considered a direct investment investor, a nonresident investor has to own at least 10 percent of the capital of a resident enterprise. Until January 2005, due to the lack of detailed information, the rule had been wrongly applied by adding up the shares of several nonresident investors, who each owns less than 10 percent of a specific enterprise. This error has now been addressed. Reserve assets are defined using the concepts of monetary authorities’ effective control and availability for use.

BI maintains an internal document that describes the current condition of the balance of payments statistics—including the deviation from the standard—and work plans and the timeframe for the improvement of the statistics to be more in line with the standard residency concept is applied in accordance to BPM5.

2.2 Scope

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

Not all resident-nonresident transactions as specified in BPM5 are covered and shown separately in the balance of payments statistics of Indonesia. Examples of items not yet covered are goods for processing, goods procured in port by carriers, repairs on goods, computer services, oil and gas exploration, e-commerce transactions, reinvested earning, direct investment (DI) abroad, portfolio investment (PI) assets, other investment assets, trade credit, and arrears. BI plans to publish data on goods for processing (starting from 2004) and goods procured in port by carriers in Q2 2005. BI and BPS formed a team, which has initiated discussions on methods to record undocumented transactions in balance of payments statistics. BI also plans to publish in Q2 2005 data on DI abroad, PI, other investment assets, and trade credit. The plan to incorporate the oil and gas sector in DI statistics is still in progress. BI is discussing with BP Migas about the data needed for DI statistics.

In principle, all resident institutional units engaged in transactions with nonresidents are covered, such as incorporated or unincorporated affiliates of nonresident companies; resident territorial enclaves in the rest of the world (e.g., embassies), free zones/bonded warehouses/factories operated by offshore enterprises under customs control, and workers who are temporarily in another country, except border workers. BI has a blueprint that describes the current condition of the balance of payments statistics—including the deviation from the standards, and work plans and the timeframe for improvement of the statistics to be more in line with the standard.

2.3 Classification/sectorization

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

The classification and attribution of institutional units to the relevant sector are not completely according to BPM5. Public enterprises’ external debts are classified under government instead of other sectors; long-term construction projects are not yet included in the FDI statistics; license fees for fishing and hunting are not yet included in current transfers. Only loans and trade credits received by FDI companies in Indonesia are recorded under the FDI while BPM5 recommends that both borrowing and lending between direct investors and direct investment enterprises should be recorded under FDI, except when those transactions are between affiliated financial intermediaries. This was due to the lack of information on lending of direct investment enterprises in Indonesia to their direct investors abroad. For the same reason, BI could not identify the transactions between affiliated financial intermediaries.

2.4 Basis for recording

2.4.1 Market prices are used to value flows and stocks.

The principle of market valuation specified in BPM5 is broadly used to value transactions, but it is not yet fully implemented. Total imports and exports are valued on an f.o.b. basis. Monetary gold is valued at market prices; data on domestic debt securities held by nonresidents obtained from the Bank Custodian are valued at book value instead of market price quotation. The value of the transactions on debt securities liabilities is derived from stock data at the beginning and the end of the period of reference. The difference represents the value of the transactions. However, this value includes also the changes due to changes in prices and other changes.

Data on transactions in domestic equity securities held by nonresidents which are reported in rupiahs (Rp) are converted to U.S. dollars using BI’s midpoint exchange rate prevailing on the transaction date. External debt transactions which are reported in foreign currencies, except those denominated in U.S. dollars, are converted to Rp and then to U.S. dollars using the monthly average exchange rates. Transaction data that are derived from position data, e.g., data on domestic debt securities, are converted to U.S. dollars using BI’s midpoint exchange rate at the end of the period.

2.4.2 Recording is done on an accrual basis.

Transactions are not completely on an accrual basis. The change in ownership of goods is considered to occur at the time the partners record the transactions in their books or accounts. Services are recorded when rendered. However, for data compiled through ITRS, services are recorded when transactions are settled. For all financial instruments bearing interest, the accrual of interest costs is approximated. Dividends are recorded on the date they are compiled, rather than the date they are declared payable. Transaction data on reinvested earnings are not published yet. However, reinvested earnings data compiled through surveys are recorded in the periods when they are declared to be reinvested, rather than the date they are earned. Loan drawings are recorded at the time of actual disbursements. Government and public enterprises loan repayments are entered when due for payment, but other sector loan repayment are entered when they are paid. For loan repayments not made when due, entries are recorded as if repayments of the contractual obligations were made and new liabilities created and recorded (as short-term or long-term liabilities) based on the new repayment schedule. Interest is calculated by applying the London Interbank Offering Rate (LIBOR) to the stock of assets or liabilities.

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

Current account transactions are recorded on a gross basis. However, in the national presentation, only transactions on goods and travel services are shown on a gross basis.

3. Accuracy and reliability

3.1 Source data

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

Source data for balance of payments statistics are derived from a comprehensive data collection program based on (i) information from government/state agencies, corporations, and from other directorates of BI, and (ii) reporting of banks, nonbank financial institutions, and corporations to BI through ITRS, external debt report, and bank monthly report.

Since the ITRS captures only external transactions that go through the banking system, there are other transactions, equally important, that do not go through the banking system, e.g., external debts, FDI, expenditures by embassies and international organizations operating in Indonesia, number of nonresident visitors, their spending in Indonesia, etc. Surveys are therefore complementary to the ITRS, and vice versa. For example: passenger transportation (debit) figures are derived from information on the number of Indonesian people going abroad from Immigration/BPS, combined with information from the Outbound Survey. Travel data are derived from a survey (PES & Outbound) conducted by the Ministry of Culture and Tourism and BPS. Since 2000, BI has conducted an FDI Survey. However, the survey result has not been incorporated into the balance of payments compilation process yet. It has been used to compile DI data in IIP statistics.

BI maintains a list of corporations and institutions that can provide the required information; the survey list is updated on an ongoing basis using information from compulsory DI surveys, the ITRS’s list of transactors, and a debt register.

The ITRS data are incorporated into the balance of payments compilation process. They are used to compile data that conventional data sources cannot fulfill: data on passenger services; freight; other transportation; communications; construction; financial services; computer and information services; royalties and license fees; other business services; personal services; and asset components of the financial account. The ITRS is a system that captures all foreign exchange transactions that are conducted through the domestic banking system (BRS), and through the Overseas Current Account (OCA) and Inter-Company Account (ICA) of the Nonbank Financial Institution Reporting System (NBFIRS) and Nonfinancial Company Reporting System (NCRS). These data cover the current account, the capital account, and the financial account. The fourth segment of ITRS, which is the BI report, is still under construction.

In addition to ITRS and the surveys, the primary data sources for transactions in goods are customs documents. The online reporting system for import documents was implemented in April 2004 and for export documents in May 2004. BI, BPS, and Customs are now cooperating to reconcile their respective data on trade. This project is ongoing. Data relating to the oil and gas industry are based on BP Migas and Pertamina reports. Data on PI liabilities are derived from the Jakarta Stock Exchange (JSX) report, the Bank Custodian report, and administrative records of the Directorate of Monetary Management of BI. Banks’ monthly reports are used to derive the investment income data of the banking sector. Data on reserve assets are provided by the Directorate of Reserve Management of BI, with transactions distinguished from valuation changes.

Where source data do not exist or are difficult to collect, the best possible secondary sources and approximation techniques are used as the basis for the estimates. One example is the use of data on pledges by the Consultative Group on Indonesia (CGI) as the source data for current transfers of government. BI also is in regular contact with the respondents, and they are often reminded of the importance of responding within the time limit to the questionnaires.

As mentioned earlier, BI, BPS, and Customs are working together to understand and find ways to reconcile trade data compiled by BPS and BI. Customs constitutes the primary source data for both agencies.

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

The design of the ITRS in Indonesia reasonably approximates the required balance of payments data. As for administrative records used to compile other balance of payments components, e.g., data on the number of Indonesian workers abroad and number of foreign workers in Indonesia, and their average income, obtained from the Ministry of Manpower, they provide reasonable approximations of the methodological requirements of the balance of payments.

3.1.3 Source data are timely.

Data collection and processing timetables are adequate to meet timeliness and periodicity for disseminating the balance of payments statistics. Respondents are made aware of the deadlines set for reporting by indicating the deadline in the survey form and announcing the deadline in the meeting with respondents. BI staff contacts the respondent to ensure the timely receipt of respondents’ data.

3.2 Assessment of source data

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

To assess the source data, BI monitors the accuracy of the data from surveys. Information about nonresponse for each of the surveys conducted is monitored. BI also tests the questionnaires. It is observed that using the simplified questionnaire tends to increase the response rate. The procedures for assessing the survey results consist of identifying outliers and other typical differences. Extreme values are confirmed with respondents, and records are maintained on the confirmation. Source data are analyzed also in the context of revisions. The source data are analyzed for underreporting/misreporting, in particular, to check for (i) temporal consistency (with the previous report) and (ii) consistency with related data sources (with the ITRS, in particular). In the ITRS, reporting by banks on their customers’ transactions is done on a best-effort basis, and usually there are limited supporting documents for which to validate the classification. Hence, the correctness of the classification of transactions is not ascertained.

Within the ITRS sections, each staff member is assigned to monitor reporting of a number of individual banks, NBFIs, and enterprises. The staff would contact the respondents that have not yet submitted the report near the deadline. Respondents are contacted to clarify any irregularities in the reported data. For BRS, there is a systematic check (validation system) of transaction normalcy. If errors are identified, the respondents are required to transmit an amended report. Penalties are assessed for late and/or erroneous reporting.

A regular meeting to reconcile data is held between (1) BI-MoF for public sector external debt data; (2) BI-BPS for international trade data; (3) BI-MoF-Bappenas for government current transfers; and (4) BI-Ministry of Manpower for compensation of employees and worker remittances data.

3.3 Statistical techniques

3.3.1 Data compilation employs sound statistical techniques to deal with data sources.

After regular scrutiny, information reported by BRS, NBFIRS, and NCRS is entered into corresponding databases. The integration of the three segments into the ITRS aggregated is done through the computerized aggregation scheme with the assistance of BI’s Data Processing Division. Information received from other sources, such as surveys, administrative records, etc., is also treated in the same manner.

Survey information is adjusted for missing data. Thus, BI adjusts the customs data to cover exports and imports of Batam and other bonded zones. Adjustments are also made in data on compensation of employees and workers remittances to cover professional workers, legal workers not reported to the Ministry of Manpower, and illegal workers.

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

Specific procedures are used to adjust data from various sources to improve consistency conforming to the requirement of BPM5. The f.o.b/c. and f. ratio that is used to convert the value of imports c. and f. to f.o.b. is estimated on the basis of a study on import documents during 2001–2003. The average value of freight is 6.8 percent of total c. and f. value and the average value of insurance is 0.5 percent. However, other series of data, which are reported in the ITRS on a net basis, are not adjusted to a gross basis, i.e., telecommunications services; and transactions in securities on secondary markets (reported net of fees and commissions). Estimates of shuttle trade have not been made but are expected to begin in 2006.

3.4 Assessment and validation of intermediate data and statistical outputs

3.4.1 Intermediate results are validated against other information, where applicable.

Information reported in the financial press is used to verify high-value direct investment (e.g., information on privatization and banking restructuring).

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

Reported data on investment income payments and receipts are regularly assessed in relation to the corresponding stock data in the IIP statistics. Data on freight earnings are regularly assessed in relation to the value/volume of the trade flows, e.g., the estimates for the f.o.b. factor for valuing imports were adjusted in 2004 to take account of higher oil prices. Data on travel-related transactions (obtained from the PES and the Outbound survey) are analyzed in relation to information compiled by the customs and immigration authorities on the numbers of international travelers entering/leaving the country. The reported financial flow data are reconciled with changes in the corresponding stock data collected for external debt and for other elements of the IIP position.

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

Staff involved in producing balance of payments data monitor developments in the errors and omissions item and seek to understand them, e.g., by cross-checks between entries in the current, capital, and financial accounts.

3.5 Revision studies

3.5.1 Studies and analyses of revisions are carried out routinely and used internally to inform statistical processes (see also 4.3.3).

A study of the revisions to the data on direct investment abroad was undertaken in 2001, which led to the revision of the classification of these data as other investment. Another revision was made in 2004 to the data on reserves assets with the inclusion of the Asian Bond as a component of reserves. The latest revision was related to the implementation of online reporting of exports and imports transactions. Documentation on revisions is maintained and updated. It includes descriptions of causes of revisions, methods used to incorporate new data sources, and the way data are adjusted (written in the division’s manual and in the worksheet).

4. Serviceability

4.1 Periodicity and timeliness

4.1.1 Periodicity follows dissemination standards.

Balance of payments statistics are disseminated quarterly, in line with the SDDS requirement.

4.1.2 Timeliness follows dissemination standards.

Quarterly balance of payments statistics are disseminated within one quarter after the reference period, as required by the SDDS.

4.2 Consistency

4.2.1 Statistics are consistent within the dataset.

Concepts, definitions, and classifications for producing quarterly and annual balance of payments statistics are the same. The sums of the quarterly statistics and the annual statistics are consistent. Annual data are derived from the quarterly data. Over the long run, the magnitude of the errors and omissions item has been significant and appears to be related to a methodology used, for instance, for unrecorded assets in the financial account. Financial transactions data have not been reconciled yet with changes in the IIP.

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

Consistent time series are generally available for an adequate period of time (at least five years). However, when the online reporting system for exports and imports was introduced in 2004, the historical series were reconstructed only as far back as 2003. Unusual changes in economic trends are explained in the commentaries included in Indonesian Financial Statistics and in the chapter relating to balance of payments in BI’s Annual Report.

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

The balance of payments data on trade in goods are reconciled with international merchandise trade data. Balance of payments data on imports are derived from merchandise trade data on imports minus freight outflow. However, in national publications, freight data are available in net value. Hence, users can not calculate the c. and f. value of imports. Owing to some discrepancies between trade data produced by BI and those by BPS, balance of payments statistics and the national accounts statistics are not consistent with each other. BI, BPS, and Customs have initiated discussions in order to find a method to reconcile the two sets of data, but to date, the two datasets have not been reconciled. The banking sector transactions in the balance of payments statistics are largely consistent with monetary and financial statistics. The balance of payments components comprising external debt data are largely consistent with the corresponding debt stocks.

4.3 Revision policy and practice

4.3.1 Revisions follow a regular and transparent schedule.

The revision cycle is made known to the public. The data are preliminary when first released and are identified as such. The quarterly data become final 12 months after the end of the reporting period. The final status of the data is implied in the publications by the lack of a symbol (r) indicating that the data are provisional. As noted by users in the user survey, they would prefer to have more documentation of revisions included in the publication of the statistical series and in the database accessible to users.

When revisions outside the regular cycle are called for (e.g., by the discovery of errors in the new source data), they are made known to the public.

4.3.2 Preliminary and/or revised data are clearly identified.

At the time of data dissemination, users are informed whenever data are preliminary. Similarly, users are informed of a revision by including the sign (r) for revised data.

4.3.3 Studies and analyses of revisions are made public (see also 3.5.1).

While studies and analyses of revisions are not contained in the balance of payments publication and in the database accessible by users, the Annual Report has been used to explain the effects on the balance of payments statistics of the introduction of a new reporting system for exports source data.

5. Accessibility

5.1 Data accessibility

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

The balance of payments statistics are disseminated according to the standard components of BPM5, and with time series. Additional series are disseminated to meet a range of users’ needs with various levels of detail (e.g., exports and imports of non-oil and gas, and oil and gas, details of government loans). The statistics are disseminated in a clear manner, but without charts, to facilitate analysis.

5.1.2 Dissemination media and format are adequate.

Statistics are disseminated in such a way that facilitates redissemination in the media, i.e., in a concise format. Current statistics and longer-time series can be accessed through the BI website.

5.1.3 Statistics are released on a preannounced schedule.

An ARC in DSBB announces the dates the statistics are to be released. The statistics are released punctually according to the preannounced schedule.

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

The public is informed of the statistics being released and of the procedures to access them (e.g., BI website, Indonesian Financial Statistics). The statistics are made available to all interested users simultaneously by posting them on the BI website and in Indonesian Financial Statistics.

5.1.5 Statistics not routinely disseminated are made available upon request.

In addition to the statistics routinely disseminated, other general statistics, e.g., the country and industrial breakdown of inward direct investment, are reported to the ASEAN Secretariat. However, no customized tabulations are provided to meet specific requests from the general public.

5.2 Metadata accessibility

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

A summary methodology on the concepts, statistical techniques, and data coverage is available on BI’s SDDS page. A comprehensive sources and methods document on DI is provided to the IMF for publication (under the Survey of Implementation of Methodological Standards for Direct Investment (SIMSDI)). The monthly Indonesian Financial Statistics provides a brief overview of the concepts and definitions employed in the principal balance of payments accounts, and summary metadata are also provided to the IMF for publication in the annual BOPSY. The SDDS summary methodologies and other related descriptions are reviewed and updated regularly. The metadata are readily accessible (e.g., BI website and Indonesian Financial Statistics) and their availability is cross-referenced in data releases.

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

While summary information is readily available, BI has not produced a detailed sources and methods document to inform analysts and other users of statistics on the balance of payments compilation methods and techniques, including departures from international standards.

5.3 Assistance to users

5.3.1 Contact points for each subject field are publicized.

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 ARC. A contact point—with address, phone, fax, and e-mail—is identified on the BI website for inquiries on all statistics released through the Web. There are no formal users’ education programs. Assistance to users is not monitored; the users’ requests for assistance have been minimal.

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

A list of BI’s publications is posted on the BI website and on the IMF’s DSBB—the Dissemination Formats. The prices of the statistical products are clearly disclosed on the IMF’s DSBB—the Dissemination Formats. The contact point for subscription is also posted.

Table 4.Indonesia: Data Quality Assessment Framework (July 2003): Summary of Results for Balance of Payments Statistics
Key to symbols: NA = Not Applicable; O = Practice Observed; LO = Practice Largely Observed; LNO = Practice Largely Not Observed; NO = Practice Not Observed; SDDS = Complies with SDDS Criteria
ElementNAAssessmentComments
OLOLNONO
0. Prerequisites of quality
0.1 Legal and institutional environmentX
0.2 ResourcesX
0.3 RelevanceX
0.4 Other quality managementX
1. Assurances of integrity
1.1 ProfessionalismX
1.2 TransparencyXWhen BI makes changes to balance of payments methodology or source data, the public is usually informed concurrently when the change is effected.
1.3 Ethical standardsX
2. Methodological soundness
2.1 Concepts and definitionsX2.1.1 Financial account does not provide for a separate recording of transactions in assets and transactions in liabilities. It is planned to publish these data for 2004 in Q2, 2005.
2.2 ScopeX2.2.1 Not all resident-nonresident transactions are covered, e.g., goods for processing, goods procured in ports by carriers, repairs on goods, computer services, oil and gas exploration, e-commerce transactions, reinvested earnings, direct investment abroad, etc. It is planned to publish these data for 2004 in Q2, 2005.
2.3 Classification/sectorizationX2.3.1 The classification of institutional units to their relevant sectors does not completely follow BPM5, e.g., public enterprises are classified under government instead of other sectors.
2.4 Basis for recordingX2.4.1 The principle of market valuation specified in BPM5 is not followed completely. Value of transactions derived from stocks data include valuation and other changes.
2.4.2 Recording of transactions is not completely done on an accrual basis.

2.4.3 Financial account transactions in assets and liabilities are not published separately.
3. Accuracy and reliability
3.1 Source dataX3.1.3 Results of ITRS are satisfactory for the banks, but the BI part was not collected. The results are not incorporated in the balance of payments compilation.
3.2 Assessment of source dataX
3.3 Statistical techniquesX3.3.1 Information from surveys for some respondents need to be adjusted for missing data. Methods of adjustment need to be improved.
3.4 Assessment and validation of intermediate data and statistical outputs.X3.3.2 Estimation technique needs to be improved. Data on a gross basis are not collected for some items, e.g., telecommunications services. Shuttle trade is not estimated.
3.5 Revision studiesX
4. Serviceability
4.1 Periodicity and timelinessX
4.2 ConsistencyX4.2.1 Substantial magnitude of errors and omissions over the long run. Financial transactions are not consistent with changes in IIP.
4.2.2 Revisions to historical trade data, after the introduction in 2004 of imports and exports online reporting, go back to 2003.
4.3 Revision policy and practiceX4.2.3 Discrepancies with BPS trade data have not been reconciled.
5. Accessibility
5.1 Data accessibilityX
5.2 Metadata accessibilityX
5.3 Assistance to usersX
APPENDIX I: Summary of the Special Data Dissemination Standard (SDDS)

The SDDS prescribes the following practices under each of the identified dimensions.

Data dimension (coverage, periodicity, and timeliness)

  • The dissemination of 18 data categories, including component detail, covering the four main sectors (real, fiscal, financial, and external) of the economy, with prescribed periodicity and timeliness.

Access dimension

  • The dissemination of ARCs providing at least one-quarter advance notice of approximate release dates, and at least a one-week advance 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.

SDDS subscribers are required to:

  • Post descriptions of their data dissemination practices (metadata) on the IMF’s DSBB. Summary methodologies, which describe data compilation practices in some detail, are also disseminated on the DSBB; and

  • 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.

The IMF staff is monitoring observance of the standard through NSDPs maintained on the Internet. Monitoring is limited to the coverage, periodicity, and timeliness of the data and to the dissemination of ARCs.

Source: http://dsbb.imf.org

APPENDIX II: Data Quality Assessment Framework—Generic Framework

(July 2003 Framework)

Quality DimensionsElementsIndicators
0. Prerequisites of quality0.1 Legal and institutional environment—The environment is supportive of statistics.0.1.1 The responsibility for collecting, processing, and disseminating the statistics is clearly specified.

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

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

0.1.4 Statistical reporting is ensured through legal mandate and/or measures to encourage response.
0.2 Resources—Resources are commensurate with needs of statistical programs.0.2.1 Staff, facilities, computing resources, and financing are commensurate with statistical programs.

0.2.2 Measures to ensure efficient use of resources are implemented.
0.3 Relevance—Statistics cover relevant information on the subject field.0.3.1 The relevance and practical utility of existing statistics in meeting users’ needs are monitored.
0.4 Other quality management—Quality is a cornerstone of statistical work.0.4.1 Processes are in place to focus on quality.

0.4.2 Processes are in place to monitor the quality of the statistical program.

0.4.3 Processes are in place to deal with quality considerations in planning the statistical program.
1. Assurances of integrityThe principle of objectivity in the collection, processing, and dissemination of statistics is firmly adhered to.1.1 Professionalism—Statistical policies and practices are guided by professional principles.1.1.1 Statistics are produced on an impartial basis.

1.1.2 Choices of sources and statistical techniques, as well as decisions about dissemination, are informed solely by statistical considerations.

1.1.3 The appropriate statistical entity is entitled to comment on erroneous interpretation and misuse of statistics.
1.2 TransparencyStatistical policies and practices are transparent.1.2.1 The terms and conditions under which statistics are collected, processed, and disseminated are available to the public.

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

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

1.2.4 Advance notice is given of major changes in methodology, source data, and statistical techniques.
1.3 Ethical standardsPolicies and practices are guided by ethical standards.1.3.1 Guidelines for staff behavior are in place and are well known to the staff.
2. Methodological soundnessThe methodological basis for the statistics follows internationally accepted standards, guidelines, or good practices.2.1 Concepts and definitions—Concepts and definitions used are in accord with internationally accepted statistical frameworks.2.1.1 The overall structure in terms of concepts and definitions follows internationally accepted standards, guidelines, or good practices.
2.2 ScopeThe scope is in accord with internationally accepted standards, guidelines, or good practices.2.2.1 The scope is broadly consistent with internationally accepted standards, guidelines, or good practices.
2.3 Classification/sectorizationClassification and sectorization systems are in accord with internationally accepted standards, guidelines, or good practices.2.3.1 Classification/sectorization systems used are broadly consistent with internationally accepted standards, guidelines, or good practices.
2.4 Basis for recording—Flows and stocks are valued and recorded according to internationally accepted standards, guidelines, or good practices2.4.1 Market prices are used to value flows and stocks.

2.4.2 Recording is done on an accrual basis.

2.4.3 Grossing/netting procedures are broadly consistent with internationally accepted standards, guidelines, or good practices.
3. Accuracy and reliabilitySource data and statistical techniques are sound and statistical outputs sufficiently portray reality.3.1 Source data—Source data available provide an adequate basis to compile statistics.3.1.1 Source data are obtained from comprehensive data collection programs that take into account country-specific conditions.

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

3.1.3 Source data are timely.
3.2 Assessment of source dataSource data are regularly assessed.3.2.1 Source data—including censuses, sample surveys, and administrative records—are routinely assessed, e.g., for coverage, sample error, response error, and nonsampling error; the results of the assessments are monitored and made available to guide statistical processes.
3.3 Statistical techniques—Statistical techniques employed conform to sound statistical procedures.3.3.1 Data compilation employs sound statistical techniques to deal with data sources.

3.3.2 Other statistical procedures (e.g., data adjustments and transformations, and statistical analysis) employ sound statistical techniques.
3.4 Assessment and validation of intermediate data and statistical outputs—Intermediate results and statistical outputs are regularly assessed and validated.3.4.1 Intermediate results are validated against other information, where applicable.

3.4.2 Statistical discrepancies in intermediate data are assessed and investigated.

3.4.3 Statistical discrepancies and other potential indicators or problems in statistical outputs are investigated.
3.5 Revision studies—Revisions, as a gauge of reliability, are tracked and mined for the information they may provide.3.5.1 Studies and analyses of revisions are carried out routinely and used internally to inform statistical processes (see also 4.3.3).
4. Serviceability

Statistics, with adequate periodicity and timeliness, are consistent and follow a predictable revisions policy.
4.1 Periodicity and timelinessPeriodicity and timeliness follow internationally accepted dissemination standards.4.1.1 Periodicity follows dissemination standards.

4.1.2 Timeliness follows dissemination standards.
4.2 Consistency—Statistics are consistent within the dataset, over time, and with major datasets.4.2.1 Statistics are consistent within the dataset.4.2.2 Statistics are consistent or reconcilable over a reasonable period of time.4.2.3 Statistics are consistent or reconcilable with those obtained through other data sources and/or statistical frameworks.
4.3 Revision policy and practiceData revisions follow a regular and publicized procedure.4.3.1 Revisions follow a regular and transparent schedule.

4.3.2 Preliminary and/or revised data are clearly identified.

4.3.3 Studies and analyses of revisions are made public (see also 3.5.1).
5. Accessibility

Data and metadata are easily available and assistance to users is adequate.
5.1 Data accessibility—Statistics are presented in a clear and understandable manner, forms of dissemination are adequate, and statistics are made available on an impartial basis.5.1.1 Statistics are presented in a way that facilitates proper interpretation and meaningful comparisons (layout and clarity of text, tables, and charts).

5.1.2 Dissemination media and format are adequate.

5.1.3 Statistics are released on a preannounced schedule.

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

5.1.5 Statistics not routinely disseminated are made available upon request.
5.2 Metadata accessibility—Up-to-date and pertinent metadata are made available.5.2.1 Documentation on concepts, scope, classifications, basis of recording, data sources, and statistical techniques is available, and differences from internationally accepted standards, guidelines, or good practices are annotated.

5.2.2 Levels of detail are adapted to the needs of the intended audience.
5.3 Assistance to users—Prompt and knowledgeable support service is available.5.3.1 Contact points for each subject field are publicized.

5.3.2 Catalogs of publications, documents, and other services, including information on any charges, are widely available.
APPENDIX III: Results of Indonesia’s Users’ Survey

A. Summary of Results

A questionnaire was sent to 39 users among the academic and research community, banks and businesses, foreign embassies and international agencies, credit rating agencies, and government agencies seeking their views on Indonesia’s macroeconomic statistics. While only 21 responses were received (including 3 from researchers, 10 from banks and businesses, 5 from the international community, 0 from credit rating agencies, and 3 from other agencies which includes a government agency), major and informed users were well represented among the respondents.

The respondents expressed their views; on the whole, they rated the official statistics as being of above-average quality. On a scale of 1 to 5, with 5 being “excellent” overall quality and 1 being “poor” overall quality, average ratings for five categories of statistics (with the highest and lowest individual ratings shown in parentheses) were:

1.Monetary statistics3.8(2, 5)
2.Prices3.6(2, 5)
3.Government finance statistics3.5(2, 5)
4.National accounts3.3(1, 4)
5.Balance of payments statistics3.2(1, 4)

Most respondents regularly used the statistics on national accounts, government finance, and prices. Somewhat less usage was made—but still substantial—of the monetary statistics and certain components of the overall balance of payments statistics, such as the merchandise trade statistics, international reserves, and foreign liquidity and external debt, but surprisingly little usage was made to the balance of payments statistics themselves. The main purposes for which the statistics were used comprised the following: economic model building and forecasting (86 percent of respondents); analysis of current developments for short-term decision-making (71 percent of respondents); and analysis of trends for long-term policy formulation (67 percent of respondents).

Given these uses of the statistics, the periodicity, timeliness, and accuracy and reliability of the statistics are important attributes as far as users are concerned. In general, users were most satisfied with the coverage, level of detail, periodicity, and timeliness of the national accounts and prices statistics, with satisfaction between 70–85 percent of respondents for national accounts statistics, and between 50–75 percent for users of price statistics. Very few respondents were satisfied with these attributes for government finance statistics, monetary statistics, and balance of payments statistics.

As to the other attributes of the statistics, a surprisingly small number of respondents were aware of the existence of an ARC. Except in the areas of national accounts and prices, most users of statistics wanted more information on revisions. Respondents also expressed a need for more explanatory information about the statistics and more detailed metadata.

Table 5.Indonesia: Questionnaire Results Analyzed by Type of User April 11, 2005
Type of RespondentTotalIn %
Total SentReceivedReceived
Banks and businesses161083
International community6583
Academic & research community7343
Credit rating agencies200
Others8338
Total392154

Results of Indonesia’s Users’ Survey April 11, 2005

Table 6.General Information About Uses of Official Macroeconomic Statistics of Indonesia
Total

Number of

Responses
1.Which official statistics do you use regularly?
  • National accounts

  • Prices

  • Government finance statistics

  • Monetary statistics

  • Balance of payments

  • Other:

    • Production indices

    • Labor market

    • Merchandise trade

    • International reserves and foreign currency liquidity

    • External debt

    • International investment position

    • Other

19



18



20



16



4



13



13



13



13



15



10



5



0
2.Where do you obtain the official statistics?
  • a. Official press releases and publications on macroeconomic statistics

  • b. Private sector summaries and analyses

  • c. Official policy papers

  • d. Publications from international organizations about the country

  • e. Other sources

9



14



10



0



17
3.Do you refer to official descriptions of the sources and methods that were used to compile the official statistics?
  • Yes

  • No

0



0
4.For what purposes do you use the official statistics?
  • a. Analysis of current developments for short-term decision making

  • b. Analysis of trends for longer-term policy formulation?

  • c. Econometric model building and forecasting

  • d. Economic research

  • e. Comparison with economic developments in other countries

  • f. General economic background

  • g. Other

15



14



18



2



0



0



0
Table 6a.General Information About Uses of Official Macroeconomic Statistics of Indonesia
NAPricesGFSMonetaryBOPOther
5.Coverage and detail
5.1In general, are you satisfied with the coverage of official statistics?
  • Yes

  • No

18



3
16



2
1



4
0



2
0



4
13



2
5.2In general, are you satisfied with the official statistics in terms of their level of detail?
  • Yes

  • No

17



4
13



1
1



5
0



0
0



6
0



2
6.Periodicity and timeliness
6.1Are you satisfied with the frequency of compilation of the official statistics (e.g., weekly, monthly, quarterly, annual)?
  • Yes

  • No

18



2
13



0
3



4
0



2
0



7
12



0
6.2.In general, do you consider that the official statistics are disseminated with the appropriate timeliness (the time lag after the period to which they pertain, e.g., 60 days after the reference period)?
  • Yes

  • No

15



4
10



2
1



8
0



4
0



8
8



2
7.Other dissemination practices
7.1Do you know if there is a publicly disseminated calendar that announces in advance the dates on which the various official statistics will be disseminated?
  • Yes

  • No

7



11
5



9
1160



13
0



15
11



2
7.2If there is a calendar of release dates, in your experience, are the official statistics released on the dates announced?
  • Yes

  • No

7



5
6



6
2



11
0



7
0



8
10



1
7.3Is there enough information about revisions to official statistics?
  • Yes

  • No

13



9
10



7
2



10
0



7
0



10
0



1
8.Accessibility
8.1Can you easily access the official statistics?
  • Yes

  • No

19



1
18



0
3



4
0



1
0



2
11



0
8.2Can you easily access information pertaining to official statistics you use (explanatory notes, methodological descriptions, reference concerning concepts, classification, statistical practice)?
  • Yes

  • No

14



7
12



5
3



6
0



6
0



7
0



0
YesNo
8.3Is the above information on methodology sufficiently clear and at an adequate level of detail to be useful to you?
8.4How do you get access to official statistics?
  • Official releases

  • Hard copy publications

  • Data specifically requested

  • Official website

  • Other

  • E-mail requests

16



5



6



0



0



12
NAPricesGFSMonetaryBOPOther
9.Overall assessment
9.1In your opinion, is the underlying methodology of official statistics sound and appropriate?
  • Yes

  • No

11



3
2



3
0



3
0



2
13



5
14



0
9.2In general, do you consider the official statistics to be unbiased and accurate?
  • Yes

  • No

13



3
2



3
0



2
0



1
0



3
0



0
9.3How would you compare the quality of official statistics of the country with those of other countries in the region?
  • Better

  • Same

  • Worse

9.4How do you assess the overall quality of the official statistics? (1 rated as poor and 5 as excellent)3.33.6



3.2
3.5



0
3.8
NA = National Accounts; Prices refers to: CPI (Consumer Price Index) and PPI (Producer Price Index); GFS = Government Finance Statistics; Monetary = Monetary Statistics; and BOP = Balance of Payments Statistics
NA = National Accounts; Prices refers to: CPI (Consumer Price Index) and PPI (Producer Price Index); GFS = Government Finance Statistics; Monetary = Monetary Statistics; and BOP = Balance of Payments Statistics

B. Comments of Respondents in Users’ Survey

1. Section A. 1. (1.6) General Information About Uses of Official Macroeconomic Statistics of (Indonesia). (Which official statistics are regularly used)

Comments:

  • The official statistics used regularly are social indicators.

  • Other—Capital Market.

  • Capital participation in International Organizations, Crude Oil, and Natural Gas.

  • Household income/expenditure survey or census.

2. Section A. 2 (2.5) General Information About Uses of Official Macroeconomic Statistics of (Indonesia). (Where national official statistics are obtained)

  • National official statistics are obtained from official websites.

  • Other sources of obtaining national official statistics are through subscribed briefing and online printed media.

  • Technical units under several government departments that produce or deal with the data needed.

  • Central Bureau of Statistics, BPS Jakarta.

  • Obtain raw data from BPS.

  • Official national statistics obtained from Bloomberg.

  • National official statistics obtained from other sources, e.g., universities.

3. Section A. 3 General Information About Uses of Official Macroeconomic Statistics of (Indonesia). (Reference to official descriptions of the sources and methods that were used to compile the official statistics)

  • Sources and methods are very important.

  • The descriptions are necessary for analyzing. Useful with simple clear explanation.

  • To understand more about the nature of the data.

  • In general, we just refer to the sources of data.

4. Section A. 4. (4.7) General Information About Uses of Official Macroeconomic Statistics of (Indonesia). (Re: Purpose of usage of official statistics)

Comments:

  • For publication of investor market update and “offering Circular/Memorandum.”

  • Forecasting FX and interest rates for traders, dealers, and clients.

5. Section B. 5. (5.1) Information Concerning Quality Aspects of the National Official Macroeconomic Statistics, Coverage, and Detail (Re: Satisfaction with the coverage of official statistics)

Comments:

  • More data needed on subnational governments.

  • However, we still need data that have not been provided yet in these national official statistics.

  • Prices and wages in ‘rural’ will be very good information to include.

  • Coverage of official statistics—late and too many revisions.

  • Yes, no other alternatives.

6. Section B. 5. (5.2) Information Concerning Quality Aspects of the National Official Macroeconomic Statistics, Coverage, and Detail (Re: Satisfaction with the official statistics in terms of their level of detail)

Comments:

  • More details needed for subnational governments and balance of payments capital account.

  • The coverage of capital market data is not complete.

  • Sometimes, need more detail which is available, but not in official statistics.

  • Monetary release does not contain loan by segment or detail for consumer loans.

  • Needs breakdown of capital account.

7. Section B. 6. (6.1) Periodicity and Timeliness (Re: Satisfaction with the frequency, compilation of the official statistics, e.g., weekly, monthly, quarterly, annual).

Comments:

  • If there is no monthly basis, make it by estimation. If possible, monthly for balance of payments.

  • Actually, we receive some data, not regularly. We made direct contact with the offices that provide those data as needed.

  • Balance of payments and capital account data need updating.

8. Section B. 6. (6.2) Periodicity and Timeliness (Re: Appropriate timeliness of dissemination of the official statistics)

Comments:

  • Data on subnational governments are very slow.

  • Time lag is too long.

  • Need to reduce time lag.

  • The value of information decrease, if the data are disseminated with longer time lag.

  • External debt is in two-month lag.

  • Balance of payments time lag should be shortened.

  • We know that the officials need time to collect and calculate the release, but sooner publication would be better.

  • BOP, especially capital account, always too late (3–6 months behind).

  • Other—social data.

  • Fiscal and balance of payments data always out of date and need updating.

  • Balance of payments, especially capital account always too late (3–6 months behind).

  • Regional GDP very late (1 year).

9. Section B. 7. (7.1) Other Dissemination Practices (Re: Knowledge of a publicly disseminated calendar that announces in advance the dates on which the various official statistics will be disseminated)

Comments:

  • Perhaps not always official, but approximate dates are known.

  • Other—Capital market.

10. Section B. 7. (7.2) Other Dissemination Practices (Re: Calendar release dates—whether the official statistics are released on the dates announced)

Comments:

  • For the rest, we have information regarding calendar of release dates.

11. Section B. 7. (7.3) Other Dissemination Practices (Re: Information about revisions to official statistics to satisfy one’s needs)

Comments:

  • Information by quarter on revised levels is very slow, if not purchased.

  • Sometimes, the revisions are for the period which has been hidden.

12. Section B. 8 (8.1) Accessibility (Re: How easily official statistics could be assessed)

Comments:

  • National accounts—Especially revisions, are very slow. Fiscal accounts are difficult to obtain.

  • It occurs since we already have a direct contact to the offices that produce those statistics.

  • Mostly from outside (other countries) sources.

  • Infrequent fiscal data update.

13. Section B. 8. (8.2) Accessibility (Re: How easily information pertaining to official statistics, e.g., explanatory notes, methodological descriptions, references concerning concepts, classifications, statistical practices could be assessed)

Comments:

  • Meetings are usually necessary.

  • Full information needed is not accessible.

  • Impossible to obtain greater detail statistics when needed.

14. Section B. 8. (8.4) Accessibility (Re: Accessibility of official statistics)

Comments:

  • Other: such as Bloomberg or CEIC.

  • We usually obtain raw data compiled by central bureau of statistics if available.

  • Official statistics—accessible through Reuters and Bloomberg.

15. Section B. 9. (9.1) Overall Assessment (Re: How sound and appropriate is the underlying methodology of official statistics)

Comments:

  • The question and the choice of answers are too definitive.

  • The methodology has many assumptions.

  • Too many errors and omissions.

16. Section B. 9. (9.2) Overall Assessment (Re: In general, how official statistics is considered, whether unbiased or accurate)

Comments:

  • Question and choice of answers are too definitive.

  • Yes, but we accept that due to metrology being used by the officials.

  • Accurate subject to constraint.

17. Section B. 9. (9.3) Overall Assessment (Re: Quality of official statistics of Indonesia with those of other comparator countries in the region)

Comments:

  • Balance of payments, and other, such as external debt are better than less developed countries such as Vietnam, Nepal, and Cambodia. Balance of payments, and other, are same with Malaysia and Thailand.

  • For monetary, breakdown for loan are less detailed than others: car loan, credit card loan, etc. are not included in BI release.

  • We have no opinion since we have not compared the quality of official statistics of Indonesia with other countries.

  • Not compared.

18. Section B. 10 (Additional comments, including areas where there is room for improvement)

Comments:

  • Need to reduce the time lag for National Accounts, Government Finance Statistics, Monetary and Balance of Payments Statistics.

  • Good information has been provided on the IMF’s website.

  • Coverage of balance of payments should be broadened, with more detail.

  • When there is change of base year—more explanation needed on why rebasing, and how, for certain sectors.

  • Inconsistency of data collecting.

  • Balance of payments data is extremely poor and untimely. Errors and omissions are simply too large to understand balance of payments dynamics in detail.

  • Some seem to need updating of the methodology, e.g., terms of trade, urban compared with rural.

Suggestions:

  • Balance of payments: Balance of payments compliance to IMF manual could be improved by enhancement of the available data such as by surveys; new data report, particularly the asset side of financial account.

  • National accounts: National accounts will be better if national accounts data, especially on expenditure side, can be broken down into more detail data, e.g., data regarding nonfood private consumption can be broken down into subsectors.

  • Overall, we hope the release can be disseminated earlier.

  • For monetary, we hope for much more detail on loans, especially by segment, consumer, etc.

  • Need breakdown of capital account, debt repayments, disbursals, FDI equity flows, etc.

  • Need to improve data to look more like IIF form.

  • Having good balance of payments data is important to track investor sentiment, capital plights, and predict financial markets.

  • Local finance data need to be updated more frequently.

GFS is used as a generic term for any type of fiscal statistics. Statistics based on the IMF government finance manuals published in 1986 and 2001 are referred to as GFSM 1986 and GFSM 2001, respectively.

The main difference is that a major group has been created for religious affairs, which is seen as an important function for the Indonesian government.

This is a document which is prepared as part of the budget process, and includes current macroeconomic developments and other information to inform budget decisions.

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