Abstract
This technical assistance report on Malaysia highlights that the mission aimed to support the Malaysian authorities in improving government finance statistics (GFS) for decision making. The mission reviewed the progress in the implementation of the accounting project to introduce accrual financial reporting standards at the federal government level. The mission identified considerable potential for collaboration between Ministry of Finance (MOF) and Department of Statistics Malaysia (DOSM) with respect to fiscal data collection for other general government sublayers and public nonfinancial corporations. The mission concluded that the general ledger structure is sufficient to produce GFS on both cash and an accrual basis. The mission suggested that collaboration between MOF and DOSM going forward would be necessary to ensure data consistency and to facilitate the explanation of remaining minor differences to users. The mission recommends that the authorities verify the causes for inconsistencies based on recent annual data, and to formally align the collaboration between the institutions.
Summary of Mission Outcomes and Priority Recommendations
1. Technical assistance (TA) missions were conducted by Mr. Hendrik Tillmann-Zorn, an IMF short-term government finance statistics (GFS) expert, during the period March 12–16, 2018, followed by remote capacity development through December 17–22, 2018.1 The missions aimed to support the Malaysian authorities in improving government finance statistics (GFS) for decision making. The mission was part of the second three-year government finance statistics (GFS) capacity development project funded by the government of Japan (JSA). The mission met with officials from the Ministry of Finance (MOF), the Bank Negara Malaysia (BNM), the Department of Statistics Malaysia (DOSM), and the Accountant General’s (AG) Department.
2. The mission would like to thank the staff of the national institutions for their courtesy and willingness to share their knowledge with the mission. It is especially grateful to the staff of the Ministry of Finance for their assistance in organizing the mission (see Appendix I for the list of officials met during the mission).
3. The mission was a follow-up to GFS TA missions in 2013 and a workshop in 2017 conducted by the GFS expert. This mission’s focus was to assist the authorities to integrate accrual based financial information into the GFS compilation process and to expand the institutional coverage of fiscal statistics towards the general government and the nonfinancial public sector.
4. The structural preconditions for using accrual and cash data from primary sources for the federal government are met, however actual data is needed to confirm the integrity of the compilation process. The mission reviewed the progress in the implementation of the accounting project to introduce accrual financial reporting standards at the federal government level. The latest version of the chart of accounts (COA) was assessed with respect to its feasibility for GFS reporting purposes. The mission concluded that the general ledger structure is sufficient to produce GFS on both a cash and an accrual basis. However, at the time the mission was conducted, no (preliminary) financial data was available. The mission therefore recommends to follow up on this issue as soon as accrual-based information is presented (expected for 2018:Q4).
5. The mission identified considerable potential for collaboration between MOF and DOSM with respect to fiscal data collection for other general government sub-layers and public nonfinancial corporations. The mission conducted a workshop with officers from MOF, DOSM, BNM, and AG to study existing data sources and compilation processes and to assess mutual data needs for fiscal statistics on a broader institutional coverage going forward. The key outcome of this assessment was that the MOF and the DOSM do currently report similar information based on different data sources or compilation procedures. This approach leads to inefficiency due to duplicate processes and bears the risk of data inconsistencies.
6. The mission reviewed all surveys conducted by MOF for extra budgetary units, state governments, local governments and nonfinancial public corporations. The objective of this assessment was to identify necessary changes to accommodate GFS reporting needs and to identify the potential for data sharing (or alignment) with DOSM. A key outcome of this activity is a list of recommended changes to those surveys to accommodate the needs of GFS and the national accounts (NA) going forward.
7. The mission also assessed the causes for inconsistencies with respect to public sector investment data. The mission evaluated the conceptual foundations and data processes underlying the different statistical reports that cover public sector capital spending. It was found that the observed differences most likely arose from different transactional classifications (i.e. the distinction of current and capital spending). The mission suggested that collaboration between MOF and DOSM going forward would be necessary to ensure data consistency and to facilitate the explanation of remaining minor differences to users. The mission recommends that the authorities verify the causes for inconsistencies based on recent annual data, and to formally align the collaboration between the institutions.
Priority Recommendations
Priority Recommendations
| April 2019 | Finalize the bridging table for the accrual-based COA and perform consistency checks/reconciliation exercises. | MOF with support of AG |
| April 2019 | Update the surveys for extrabudgetary central, state, and local governments and nonfinancial public corporations to accommodate GFS requirements. | MOF in alignment with DOSM |
| April 2019 | Develop strategy to align investment data between the MOF and the DOSM going forward. | MOF and DOSM |
Priority Recommendations
| April 2019 | Finalize the bridging table for the accrual-based COA and perform consistency checks/reconciliation exercises. | MOF with support of AG |
| April 2019 | Update the surveys for extrabudgetary central, state, and local governments and nonfinancial public corporations to accommodate GFS requirements. | MOF in alignment with DOSM |
| April 2019 | Develop strategy to align investment data between the MOF and the DOSM going forward. | MOF and DOSM |
Detailed Technical Assessment and Recommendations
A. Integration of Accrual-Based Accounting Data
8. The source data quality for fiscal statistics at the federal government level is about to improve significantly, once the financial reporting has shifted to an accrual basis. Currently Malaysia produces GFS on a cash basis from secondary sources (mainly the Economic Report and Financial Statistics from the BNM). The coverage of stocks is limited to a subset of major liabilities. While this compilation practice is generally acceptable, the availability of accrual accounting information will improve the breadth and depth of fiscal information and thereby improve the analytical value of fiscal statistics for national and international users.
9. The mission followed up on transitional steps to prepare the integration of primary accounting data into the GFS compilation process. A key element of this endeavor is to develop a comprehensive bridge table from the general ledger to the corresponding GFS classifications. This will allow the authorities to prepare budgetary central government GFS directly from the primary accounting data (i.e. the trial balances of the general ledger) and to increase the degree of automation. It will also allow compilers to integrate the stock data on assets and liabilities, and possibly some other economic flows into GFS reporting.
10. The mission reviewed the latest version of the COA and concluded that the structure and detail of the general ledger are suitable for GFS compilation. The structure of the COA largely remained intact compared to the version reviewed in 2013. However, several new accounts were introduced specifically for the recording of depreciation and appreciation. The list of classification issues created during previous missions remains valid, but it would need to be reviewed, extended, and addressed. The mission concluded that completing this task will require actual financial data (i.e. trial balances).
11. Unfortunately, (preliminary) financial data could not be provided to the mission to solve the remaining classification issues and to test the integrity of the bridging table. An important next step to complete and validate the GFS bridging table will be to classify the remaining accounts and to perform a test run with actual (cash and accrual) data. Specifically, the following steps are recommended:
a. To verify the substance of the underlying transactions for relevant accounts and confirm or determine the appropriate GFS treatment (see previous TA report for details).
b. To compile the statement of sources and uses of cash (cash inflows and outflows from operating activities, net cash flows related to investment, net cash flows from financing activities) and to compile the balancing aggregates and statistical discrepancy to check if data is complete and consistent (the so called “balancing of the accounts”).
c. To compile the statement of operations (revenue, expense, net investment in nonfinancial assets, net acquisition of financial assets, net incurrence of liabilities) and to compute the statistical discrepancy (i.e. the difference between net lending/net borrowing and financing) to check if data is complete and consistent.
d. To compile opening balance sheet stocks and assess the initial valuation of nonfinancial assets in major categories.
e. To compare cash with accrual revenue data in major revenue categories to verify the nature of differences arising from the time of recording.
f. To compare cash with accrual spending data in major expense categories to understand the nature of differences arising from the time of recording.
12. The mission recommends that as soon as possible the authorities should work with actual trial balances from the accounting system and perform the above-mentioned tests. The reconciliation work might lead to further areas requiring attention to ensure completeness and integrity of the source data and the compilation process.
13. The mission recommends that the authorities consider redesigning parts of the domestic macro-fiscal presentations to leverage the richer set of information available to decision makers and users. The MOF could use the momentum when AG is introducing the accrual based financial reports, to also change the presentation of fiscal statistics and analyses in the national statistical reports, where appropriate. Given that many of the substantial and presentational changes are similar for both IPSAS-based accrual accounting and GFS, this will make it easier for users to understand and accept differences in fiscal data formats.
| April 2019 | Finalize the bridging table for the accrual-based COA and perform consistency checks/reconciliation exercises. | MOF with support of AG |
| March 2020 | Adapt the presentation of fiscal information in the economic report to a more complete one based on an integrated balance sheet. | MOF |
| April 2019 | Finalize the bridging table for the accrual-based COA and perform consistency checks/reconciliation exercises. | MOF with support of AG |
| March 2020 | Adapt the presentation of fiscal information in the economic report to a more complete one based on an integrated balance sheet. | MOF |
B. Expansion of Institutional Coverage
14. Malaysia is planning to expand the coverage of GFS reporting to include other subsectors of the public sector and thus undertake a major step towards comprehensive fiscal reporting compliant with international standards. As currently Malaysia’s GFS is limited to the budgetary central government, the expansion to other sub-sectors will greatly increase the analytical value of fiscal statistics. The MOF currently gathers and reports some high-level aggregates for the general government sector and the nonfinancial public sector. However, the mission observed that while the surveys are quite detailed and obviously create a reporting burden for subnational government levels, their current design does not leverage the full analytic potential. The collected data is not integrated in the GFS framework and data concepts do not follow international standards. As a consequence, there is little scope for consistency checks, and fiscal analysis is limited to a general assessment of the broad fiscal position and its aggregated performance.
15. For the purpose of compilation of the national accounts, the DOSM is running parallel surveys with different analytical emphasis, partially to the same units. DOSM uses a combination of different data sources to cover extrabudgetary units, subnational governments, and nonfinancial corporations sectors. The main emphasis of this data collection is to get sufficient data for the calculation of value added components, intermediate inputs, government final consumption expenditure, and information on fixed capital formation broken down into new acquisitions and disposals of fixed assets.
16. The mission identified the need and potential for collaboration between the MOF, the DOSM and the BNM to prepare fiscal (and macroeconomic) statistics for the general government and the nonfinancial public sector (NFPS). In a workshop with representatives of MOF, DOSM, BNM, and AG, the mission assessed current data needs and collection practices of all units. A comprehensive review of the currently used data sources and survey schedules for DOSM and MOF was undertaken for (a) extrabudgetary units (i.e. statutory bodies), (b) state governments, (c) local governments, and (d) nonfinancial public corporations. The discussion addressed how data is currently gathered, the content and level of detail captured, as well as data needs for national fiscal reporting, the preparation of GFS, and the national accounts. Table 2 presents a high-level summary of the results and recommended next steps. Appendix II lists the more detailed results of this assessment on data sources and gaps to expand reporting coverage.
Alignment of Data Needs for an Expansion of Institutional Coverage
Alignment of Data Needs for an Expansion of Institutional Coverage
| Budgetary Central Government (Federal Government) |
|
|
| Extra budgetary Central government (Statutory Bodies) |
|
|
| State Governments |
|
|
| Local Governments |
|
|
| Nonfinancial Public Corporations |
|
|
Alignment of Data Needs for an Expansion of Institutional Coverage
| Budgetary Central Government (Federal Government) |
|
|
| Extra budgetary Central government (Statutory Bodies) |
|
|
| State Governments |
|
|
| Local Governments |
|
|
| Nonfinancial Public Corporations |
|
|
17. The discussion concluded that the data collected by the MOF for statutory bodies, state governments, and local governments, already roughly covers data needs of DOSM for other macroeconomic statistics. MOF’s data needs are broader with respect to period coverage (two past years, plus current year revised, and one year budgeted/projected) and with respect to transactional detail. The group tentatively concluded that the level of detail collected by MOF should generally satisfy the data needs of DOSM. Some issues could arise with respect to timing due to a later survey collection schedule. However, it appears that this could be re-solved by using data collected already in the previous year, as survey data would already comprise revised budget (and hence close to actual) data.
18. The mission assessed the structure and detail of MOF surveys and concluded that these do constitute a very good starting point but will require some modifications. Generally, the length and frequency of the surveys are considered suitable for the compilation of annual general government and nonfinancial public sector GFS. However, some gaps exist and the current structure bears the risk of incomplete coverage of flows and stocks. Respondents may not find suitable categories for relevant data and some categories may not be understood as mutually exclusive.
19. The mission sees the potential to improve the quality of survey responses for important information by (slightly) modifying the survey structure in some areas. A brief high-level assessment of aggregated data by subsector suggests that some aggregates are internally inconsistent (e.g. the totals for domestic borrowing), and that not all relevant flows and stocks may be covered. To improve the quality of the survey responses and to ensure that all relevant data is reported, the mission recommends to change the structure of the answer categories in some cases. The outline of the surveys could be based on the general GFS framework, but also reflect the structure of the respective source data frameworks (e.g. COAs or financial reports). The surveys should always allow for meaningful residual (“other”) categories to allow respondents to check that totals are consistent.
20. Specifically, the following changes or additions are likely to contribute to data quality and completeness:
a. Current Revenue and Expense transactions (operative flows) should be broken down into at least the main GFS economic classifications. They may be further subdivided into categories for national purposes (e.g. flows linked to specific legislative provisions or programs).
A simplified breakdown may be sensible for nonfinancial public corporations, as analytical interest in these details is typically limited and financial reports often do not allow to fully break down operative flows into GFS categories.
b. The split between current and capital spending should be based on international statistical standards and allow for a breakdown into at least the main asset categories (e.g. GFS four-digit codes of nonfinancial assets). The survey structure may well differ by following sector-specific logic (e.g. separate “operative” and “development” spending), but should always allow to identify the economic nature of the flows (i.e. the distinction between flows affecting net worth, and those related to investment in nonfinancial assets).
c. Information on financial transactions should be collected in a way to ensure that all relevant transactions (and possibly other economic flows) are captured and can be used for GFS reporting. The survey structure can be aligned with the respective source data logic, but all GFS categories should be captured and linkages should be clearly defined.
d. Information on the stock values of nonfinancial assets, financial assets, and liabilities should be collected in a way that allows for classification of assets according to macro-economic statistical standards.
e. The authorities could reconsider at which level of detail entities need to provide projected data. A limitation of projections to some key elements while keeping the details for historical and current (budgeted) data would certainly reduce the reporting burden and might in turn improve the overall quality of the data (for both historic and projected financials).
21. Table 3 shows a comprehensive high-level assessment of the current survey structure and lists the main changes that are recommended to facilitate GFS compilation standards:
Assessment of Survey Structure and Recommended Changes
Assessment of Survey Structure and Recommended Changes
| Extrabudgetary Central government (Statutory Bodies) | FLOWS Revenue/Receipts from Sales
STOCKS
| FLOWS Revenue/Receipts from Sales
STOCKS
|
| State Governments | FLOWS Revenue/Receipts from Sales
| FLOWS Revenue/Receipts from Sales
|
| Local Governments | FLOWS Revenue/Receipts from Sales
| FLOWS Revenue/Receipts from Sales
|
| Nonfinancial Public Corporations | FLOWS Revenue/Receipts from Sales
| FLOWS Revenue/Receipts from Sales
|
Assessment of Survey Structure and Recommended Changes
| Extrabudgetary Central government (Statutory Bodies) | FLOWS Revenue/Receipts from Sales
STOCKS
| FLOWS Revenue/Receipts from Sales
STOCKS
|
| State Governments | FLOWS Revenue/Receipts from Sales
| FLOWS Revenue/Receipts from Sales
|
| Local Governments | FLOWS Revenue/Receipts from Sales
| FLOWS Revenue/Receipts from Sales
|
| Nonfinancial Public Corporations | FLOWS Revenue/Receipts from Sales
| FLOWS Revenue/Receipts from Sales
|
22. The current surveys do not fully leverage the source data potential, specifically with respect to more comprehensive balance sheet information. The analysis of available source data per subsector suggests that much richer data than currently gathered should be available for all subsectors but the state governments. Statutory bodies, local governments, and nonfinancial public corporations all use accrual accounting and should hence have balance sheet information on nonfinancial assets and financial assets and liabilities available. The mission recommends that the authorities consider the potential to expand the scope of the collected stock information. This is particularly sensible given that such information will shortly be available for the federal government, and state governments are also planning to move towards accrual accounting in the near future. Hence a comprehensive general government (or nonfinancial public sector) balance sheet is within reach.
23. The authorities could also consider to capture (major) components of other economic flows. The nature of the relevant events will differ by subsector (e.g. revaluations due to price changes or obsolescence are more likely for public corporations) and a detailed assessment would be needed to prepare the data collection and processing. Eventually the gathering of such information would allow the authorities to comprehensively break down the changes of net worth and thereby to greatly improve the substance and presentational transparency of fiscal data.
24. It is recommended that the authorities consider information and training events as well as collecting feedback on the revision of the surveys. One or more information event(s) for (major) statutory bodies, state governments, and possibly some major state-owned enterprises (SOE) is likely to be beneficial to achieve understanding and buy-in for a more comprehensive data collection effort going forward. A more pragmatic approach will be needed for local governments. The authorities might consider a well-written survey documentation and guide or a webinar/web-based presentation.
25. The mission reviewed the current survey-based data and concluded that it may be possible to compile historical time series for general government and nonfinancial public sector level with some simplifications and restrictions. The review of the existing data structure revealed that the data in many analytically relevant areas is compliant to a GFS presentation, and could thus—with some assumptions or limitations—be used to create a historical time series at least for parts of the GFS tables. The mission recommends to consider preparing such a compilation in the future.
26. The mission would like to highlight the fact that the transition of federal government accounting and financial reporting to include accrual basis is a perfect complement to the expansion of fiscal statistics within the GFS framework to the general government and public sector. By collecting (integrated balance sheet) fiscal data on all fiscal sectors in a systematic manner, the valuable information at the federal government level can be completed to yield a comprehensive macro-economic view. Structural analysis of the fiscal position and performance will cover all macro-relevant subsectors and thus be more relevant and precise. The GFS framework is particularly well-suited to work with different data sources (e.g. the combination of cash-based accounting records at the state level for the time being with accrual-based information for all other sectors going forward).
| April 2019 | Modify the surveys for extra budgetary central, state, and local governments, and nonfinancial public corporations. | MOF in alignment with DOSM |
| April 2019 | Align data collection for general government subsectors and nonfinancial public corporations between MOF and DOSM, and develop workflow scheme for potential data sharing (incl. legal arrangements and memorandum of understanding if required). | MOF and DOSM |
| June 2019 | Issue new survey and begin new data collection. | MOF |
| December 2019 | Compile (unconsolidated) GFS data for all general government subsectors. | MOF |
| December 2019 | Compile (simplified) GFS historical time series for (unconsolidated) general government sub-sectors and possibly also nonfinancial public corporations. | MOF |
| April 2019 | Modify the surveys for extra budgetary central, state, and local governments, and nonfinancial public corporations. | MOF in alignment with DOSM |
| April 2019 | Align data collection for general government subsectors and nonfinancial public corporations between MOF and DOSM, and develop workflow scheme for potential data sharing (incl. legal arrangements and memorandum of understanding if required). | MOF and DOSM |
| June 2019 | Issue new survey and begin new data collection. | MOF |
| December 2019 | Compile (unconsolidated) GFS data for all general government subsectors. | MOF |
| December 2019 | Compile (simplified) GFS historical time series for (unconsolidated) general government sub-sectors and possibly also nonfinancial public corporations. | MOF |
C. Consistency Between Macroeconomic Statistics
27. As part of the conjoint workshop with the DOSM and the MOF, the mission analyzed causes for differences in published public investment data. Data for nonfinancial investment differs materially between the MOF reports and the national accounts. In 2016 for instance, the MOF reported “Development Expenditure” of the nonfinancial public sector of RM 142,798m whereas the DOSM reported gross fixed capital formation (GFCF) of the public sector of RM 105,504m.
28. The mission reviewed the plausible causes for the discrepancies with workshop participants. The following points were discussed:
a. Conceptual differences: While the national accounts measure “gross fixed capital formation” as increases in the (domestic) capital stock, GFS (and fiscal statistics) define nonfinancial investment more comprehensive by including non-fixed assets (e.g. most importantly naturally occurring assets) and foreign assets. The reason for this difference is presentational and is linked to different analytical objectives. As the national accounts are concerned with the measurement of production activity of an economy, the ownership exchange of non-produced assets (such as land) and acquisitions of assets in other economies are reported on separately in the sector capital accounts. For fiscal analysis, however, it is important to distinguish operative expenses from transactions that are net worth neutral. Therefore, spending on land, other non-produced or foreign assets would be presented as investment. Apart from this, however, the definitions of capital formation/investment should be the same and could thus be based on the same data.
b. Classification issues: The assessment revealed that the MOF mainly starts to identify investment of the federal government by relying on the distinction between current and development spending in the budget presentation. The DOSM, in contrast, applies a detailed assessment of spending based on the accounts from the general ledger. While the MOF does adjust for some elements (e.g. capital transfers) it is likely that the bulk of the existing differences stem from inconsistent classification of capital spending flows of the federal government.
c. Coverage issues: The assessment of the survey practices revealed that some coverage differences between the MOF and the DOSM exist. Some minor differences exist in the numbers for local governments. Finally, the MOF runs the survey for nonfinancial public corporations only at the group level and includes currently 28 companies based on legally provided selection criteria. In contrast, the DOSM runs surveys on capital formation on an entity level and includes all public corporations
d. Data collection issues: Finally, the different survey structure, timing, and response rates could explain some differences in the numbers.
29. An important step to improve the consistency of reported public investment data would be to quantitatively assess the causes for the discrepancies in the reported numbers. The mission suggested to set up a simple comparison matrix to assess the materiality of the above-mentioned possible causes for deviations using collected data for recent years. This approach will facilitate taking steps to improve the consistency (see Table 4).
Assessment of Survey Structure and Recommended Changes
Assessment of Survey Structure and Recommended Changes
| Federal Government | 41,995 | 45,962 | ||
| Statutory Bodies | N.A. | N.A. | ||
| State Governments | 8,408 | 12,445 | ||
| Local Governments | N.A. | N.A. | ||
| Total General Government | 49,931 | 56,188 | ||
| Nonfinancial Public Corporations | 94,867 | 95,309 | ||
| Total NFPS | 142,798 | 105,504 | 151,497 | |
Assessment of Survey Structure and Recommended Changes
| Federal Government | 41,995 | 45,962 | ||
| Statutory Bodies | N.A. | N.A. | ||
| State Governments | 8,408 | 12,445 | ||
| Local Governments | N.A. | N.A. | ||
| Total General Government | 49,931 | 56,188 | ||
| Nonfinancial Public Corporations | 94,867 | 95,309 | ||
| Total NFPS | 142,798 | 105,504 | 151,497 | |
30. Depending on the results of the quantitative assessment different steps could be derived to improve the situation:
a. Differences within the Federal Government subsector are most likely related to different classification decisions. This is very likely, given that the DOSM applies a detailed classification bridge whereas the MOF mainly starts from the budget-related split of current vs. development spending (with some adjustments being done). Given that the source data allows for an asset-breakdown of flows related to nonfinancial investment, and identifies foreign investment, it should be possible to ensure that both units report data based on the same classification scheme. Differences arising from conceptual definitions, such as spending on non-fixed assets and foreign assets, could be shown and explained to users.
b. Differences in the other subsectors of the general government sector might be related to a mixture of the above-mentioned classification issues or sample coverage issues. An ideal solution would be to use the same source data going forward. This would require the source data to capture the necessary asset-breakdown to measure both: GFCF and net nonfinancial investment.
c. Differences in the Nonfinancial Public Corporations Sector are most likely due to a combination of coverage issues (the MOF only reports a sample of corporations, and only at a group level), source data issues that may lead to different classification, and the conceptual differences arising from spending on different types of assets, and domestic vs. foreign investment. The solution here would be to align data collection efforts and to gather data in a sufficient level of detail to allow the preparation of bridge tables to separate out differences related to the nature of assets, the geographic location of the assets, and sample-related differences. The MOF could also consider using the DOSM data for their Economic Report to cover all public investment activity in their macro-fiscal analysis.
31. To ensure the greatest possible consistency for public investment data, the mission recommends the use of the same source data going forward, wherever possible, and to align their compilation (and presentation of results). The discussion concluded that the revised GFS surveys should accommodate the needs of national accounts compilers with respect to the timing and level of detail. While the national accounts staff might need to complement the data to include additional units, at least for the selected coverage, the data basis would then be consistent. Remaining conceptual differences (see above section) could be explained to users through a bridge table (e.g. by breaking down the data into produced and non-produced assets).
| April 2019 | Make a quantitative assessment of discrepancies for public investment data. | MOF with support of DOSM |
| April 2019 | Develop a strategy to align investment data between the MOF and the DOSM going forward. | MOF and DOSM |
| April 2019 | Make a quantitative assessment of discrepancies for public investment data. | MOF with support of DOSM |
| April 2019 | Develop a strategy to align investment data between the MOF and the DOSM going forward. | MOF and DOSM |
D. Public Sector Debt Statistics
32. The mission assessed the possibility for Malaysia to report data to the Quarterly Public Sector Debt (QPSD) Statistics database. While the published data of BNM is not directly sufficient to compile data for the QPSD template, with additional information data can be reported rather straightforward for budgetary central government. The mission developed a simple template to process data from BNM for QPSD reporting.
33. For budgetary central government BNM Tables 3.1.4 and 3.1.6 can be used as data sources with specifically identified assumptions or separate information, as necessary. Specifically, Table 3.1.4 does provides data on the outstanding amount of Treasury bills and the split between resident and nonresident counterparties. Table 3.1.6 provides information on the amount of debt maturing within one year from the reference period and the currency of denomination (see Table 5 for details).
Additional Information and Assumptions Required for PSDS-Reporting
Additional Information and Assumptions Required for PSDS-Reporting
| Budgetary Central Government | Table 1.1.1: Gross Budgetary Central Government Debt Position Short-term by original maturity
→ The data in table 3.1.4 is sufficient to populate the table Long-term by original maturity
→ The data in table 3.1.6 is sufficient to identify all long-term debt maturing in one year or less (currently only debt securities). All loans can be identified from table 3.1.4. All long-term debt securities maturing in > 1 year can be identified from as a residual from information in both tables |
Additional Information and Assumptions Required for PSDS-Reporting
| Budgetary Central Government | Table 1.1.1: Gross Budgetary Central Government Debt Position Short-term by original maturity
→ The data in table 3.1.4 is sufficient to populate the table Long-term by original maturity
→ The data in table 3.1.6 is sufficient to identify all long-term debt maturing in one year or less (currently only debt securities). All loans can be identified from table 3.1.4. All long-term debt securities maturing in > 1 year can be identified from as a residual from information in both tables |
34. For consolidated central government, additional information on the debt outstanding for statutory bodies is available, however consolidation information would be required. Some debt of the federal government is held by statutory bodies (extrabudgetary units) and some debt of statutory bodies is held by the federal government. In addition, information on the term structure and maturity profile of those instruments would be needed to populate the corresponding QPSD-table for consolidated central government. The mission recommends that the MOF collaborates with the BNM to gather the aggregated values required to populate QPSD Table 1.1.
35. The mission recommends for the authorities to report QPSD data on an ongoing basis. First submissions could be limited to the budgetary central government sector. But it would be desirable to collect data required to add the outstanding debt for statutory bodies, and particularly to gather data needed for consolidation.
| April 2019 | Initiate QPSD reporting for the budgetary central government sector. | MOF, with support of BNM |
| April 2019 | Expand coverage of QPSD reporting to the consolidated central government sector. | MOF, with support of BNM |
| April 2019 | Initiate QPSD reporting for the budgetary central government sector. | MOF, with support of BNM |
| April 2019 | Expand coverage of QPSD reporting to the consolidated central government sector. | MOF, with support of BNM |
E. Officials Met During the Mission
| En. Mohd Hassan Bin Ahmad | FPO (MOF) |
| En. Mohamad Reezal Bin Ahmad | FPO (MOF) |
| En. Mohd Hanif bin Mastuki | FPO (MOF) |
| En. Mohd Fakhrullah bin Nik Ab Kadir | FPO (MOF) |
| Puan Azlin binti Ismail | FPO (MOF) |
| Puan Mazrina Misri | FPO (MOF) |
| Puan Rahayu Ali | FPO (MOF) |
| Puan Noor Aidawati binti Hussin | FPO (MOF) |
| En. Muhamad Syah bin AB Raub | FPO (MOF) |
| Puan Noor Hazrina binti AB Hamid | FPO (MOF) |
| En. Md Farishzan bin Ismail | FPO (MOF) |
| En. Muhammad Akram bin Abd Aziz | FPO (MOF) |
| Cik Wong Seow Kim | FPO (MOF) |
| Puan Raja Dayana binti Raja Idris | FPO (MOF) |
| Cik Nor Hannanah binti Jiman | FPO (MOF) |
| Nuur Rasyiqah Zainuddin | MAKRO (MOF) |
| Wan Mohd Syahrol bin Wan Ab Rahman | EPU |
| Muhammad Azhan Mohd Nor | EPU |
| Nadian Rasali | EPU |
| Mohd Sabree Yaakub | AG |
| Deisigan Shammugam | BNM |
| Mohd Yazid Kasim | DOSM |
| Mohd Firdaus Bin Zaini | DOSM |
| Hezlin Suzliana Abdul Halim | DOSM |
| Maizura Bt Abdul Jabar | DOSM |
| N. Rajkumar a/I V. Nagathiram | DOSM |
| En. Mohd Hassan Bin Ahmad | FPO (MOF) |
| En. Mohamad Reezal Bin Ahmad | FPO (MOF) |
| En. Mohd Hanif bin Mastuki | FPO (MOF) |
| En. Mohd Fakhrullah bin Nik Ab Kadir | FPO (MOF) |
| Puan Azlin binti Ismail | FPO (MOF) |
| Puan Mazrina Misri | FPO (MOF) |
| Puan Rahayu Ali | FPO (MOF) |
| Puan Noor Aidawati binti Hussin | FPO (MOF) |
| En. Muhamad Syah bin AB Raub | FPO (MOF) |
| Puan Noor Hazrina binti AB Hamid | FPO (MOF) |
| En. Md Farishzan bin Ismail | FPO (MOF) |
| En. Muhammad Akram bin Abd Aziz | FPO (MOF) |
| Cik Wong Seow Kim | FPO (MOF) |
| Puan Raja Dayana binti Raja Idris | FPO (MOF) |
| Cik Nor Hannanah binti Jiman | FPO (MOF) |
| Nuur Rasyiqah Zainuddin | MAKRO (MOF) |
| Wan Mohd Syahrol bin Wan Ab Rahman | EPU |
| Muhammad Azhan Mohd Nor | EPU |
| Nadian Rasali | EPU |
| Mohd Sabree Yaakub | AG |
| Deisigan Shammugam | BNM |
| Mohd Yazid Kasim | DOSM |
| Mohd Firdaus Bin Zaini | DOSM |
| Hezlin Suzliana Abdul Halim | DOSM |
| Maizura Bt Abdul Jabar | DOSM |
| N. Rajkumar a/I V. Nagathiram | DOSM |
Appendix I. Data Sources and Data needs for GG/NFPS Coverage
| Budgetary Central Government (Federal Government) | Data Sources:
Transactional Coverage:
| Data Sources:
|
| Extra budgetary Central government (Statutory Bodies) | Coverage: 80 SB (Fed. Gov.) Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: 83 (Fed. Gov.) Data Sources (frequency):
Transactional Coverage:
|
| State Governments | Coverage: 13 State Governments Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: 13 State Governments Data Sources (frequency):
Transactional Coverage:
|
| Local Governments | Coverage: 150 Municipal Governments Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: 152 Municipal Governments Data Sources (frequency):
Frequency/Timing: Annual for March Transactional Coverage:
|
| Nonfinancial Public Corporations | Coverage: 28 Corporations at Group Level Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: >1.900 Corporations at Entity Level Data Sources (frequency):
Transactional Coverage:
|
| Budgetary Central Government (Federal Government) | Data Sources:
Transactional Coverage:
| Data Sources:
|
| Extra budgetary Central government (Statutory Bodies) | Coverage: 80 SB (Fed. Gov.) Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: 83 (Fed. Gov.) Data Sources (frequency):
Transactional Coverage:
|
| State Governments | Coverage: 13 State Governments Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: 13 State Governments Data Sources (frequency):
Transactional Coverage:
|
| Local Governments | Coverage: 150 Municipal Governments Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: 152 Municipal Governments Data Sources (frequency):
Frequency/Timing: Annual for March Transactional Coverage:
|
| Nonfinancial Public Corporations | Coverage: 28 Corporations at Group Level Data Sources:
Annual for June (sent out in April) Transactional Coverage:
| Coverage: >1.900 Corporations at Entity Level Data Sources (frequency):
Transactional Coverage:
|
This report covers missions 18STE85 and 19STQ75.