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Philippines

Author(s):
International Monetary Fund. Statistics Dept.
Published Date:
December 2019
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Summary of Mission Outcomes and Priority Recommendations

1. To improve the quality of the monetary and financial statistics (MFS) compiled and disseminated by the Bangko Sentral ng Pilipinas (BSP), a mission from the IMF’s Statistics Department (STA) visited Manila during April 29–May 10, 2019. The main objectives of the mission were to (i) expand the coverage of the MFS by including the other financial corporations (OFCs); (ii) assist the authorities in the compilation of the balance sheet approach (BSA) framework using existing sectoral data (MFS, international investment position, and fiscal statistics); (iii) provide hands-on training to BSP staff, in particular on the BSA framework and securities statistics in the context of the new Special Data Dissemination Standards (SDDS Plus) and the G-20 data gaps initiatives (DGI); and (iv) review the progress made by the authorities in implementing past mission recommendations. The official met during the mission are listed in Appendix I.

2. The mission worked closely with the BSP staff to achieve these objectives. As a follow-up to the April 2018 mission, the mission assisted BSP staff on finalyzing the work on the expansion of the coverage of the MFS through the compilation of data on OFCs, namely insurance companies, financial trusts, holding companies, government financial institutions, non-money market investment funds (NMMFs), and other financial intermediaries and auxiliaries. In addition, the mission provided extensive training to MFS, external sector, and flow of funds compilers. Finally, the mission discussed selected issues related to the compilation of central bank and other depository corporations (ODCs) surveys.

3. The inclusion of the OFCs—with more than 7.6 trillion pesos in total assets, a preliminary estimate, which represents around 25 percent of the total assets in the financial system—in the coverage of MFS will result in an improved integrated monetary database (IMD). The IMD will be used for national publications and to release data to the IMF’s Asia Pacific Department (APD) and STA, ensuring consistency of the disseminated data. The BSP agreed to start disseminating the new OFC data on a quarterly basis starting in September 2019, with historical series available since the first quarter of 2017.

4. The IMD is based on the standardized report forms (SRFs) developed by STA. SRFs are built by linking each relevant entry in the BSP’s accounting system to an appropriate statistical aggregate in the central bank standard report form (1SR); by linking available data for commercial banks and other deposit-taking institutions to an appropriate statistical aggregate in the ODCs standard report form (2SR); and by linking available data for OFCs to the corresponding OFCs standard report form (4SR). After these three “building blocks” are constructed, they can be consolidated into a financial corporations (FC) survey, providing a comprehensive and internationally accepted framework for monetary statistics.

5. To align the coverage of the ODC survey to statistical standards, the mission recommended the inclusion of the money market unit investment trust funds (UITFs) in the survey. The agreed inclusion of the money market UITFs will allow for better measurement of broad money and other monetary aggregates. This is a pending recommendation from the 2018 mission due to the on-going work on revising the historical series to incorporate the UITFs. The mission is of the view that, to avoid further delays, the historical series could be updated for the past five years only.

6. The 2018 mission met with the Securities and Exchange Commission (SEC) management to discuss data needs, but agreements have not been fully implemented. During the 2018 mission, the SEC agreed to provide, out of the top 1000, the list of companies by activity (to identify the financial intermediaries), with contact information and total assets. This information is critical to make sure that the largest companies are covered in the OFC survey. However, the SEC was not able to provide a complete list of financial intermediaries by total assets. The mission recommended the SEC to provide the complete list of financial intermediaries by total assets; and OFC data compilers to collect the identified financial intermediaries data from the latest publication of the top 1000 corporations supervised by the SEC to increase the sample survey.

7. With the compilation of OFC data, the Philippines is now able to produce intersectoral BSA. MFS with full coverage, together with quarterly international investment position (IIP) and public debt statistics, are the building blocks for the BSA. The BSA related work carried out by the mission comprised a seminar and the discussion of issues arising in the compilation of the BSA matrix by flow-of-funds (FOF) compilers. The issues related to the inconsistencies found between sectoral statistics, for example, between MFS and IIP, which the mission helped to solve. The seminar was well attended by FOF, MFS, and external sector statistics (ESS) compilers, setting the stage for discussing country-specific compilation issues. The mission recommended that the BSP’s FOF team compile the BSA matrix on a quarterly basis, sharing the results with the IMF’s Asian Pacific Department at least annually, as input for the yearly Article IV consultation report.

8. The mission also provided training to BSP’s FOF, MFS, and EES compilers on cross-sectoral issues. The topics covered were: (1) the BSA framework; (2) the new Handbook on Securities Statistics (HSS); (3) the new SDDS Plus (4) the G-20 DGI; (5) the recording of financial derivatives in macroeconomic statistics; and (6) the treatment of crypto-assets in macroeconomic statistics. The sessions on securities statistics, G-20 data gaps, and SDDS Plus were also attended by debt securities data providing agencies, to encourage their collaboration with the BSP.

9. To support progress in the above work areas, the mission recommended a detailed action plan with the following priority recommendations carrying particular weight to make headway in improving MFS quality and completeness. Further details on the priority recommendations and the related actions/milestones can be found in the action plan under Detailed Technical Assessment and Recommendations.

Table 1.Philippines: Priority Recommendations
Target DatePriority RecommendationResponsible Institutions
September 2019ODC data compilers to include the money market UITFs in the institutional coverage of ODCs going back to five years of monthly dataBSP
September 2019OFC data compilers to start disseminating the new OFC survey, including submission of the 4SR to STA on a quarterly basis, with a time-lag of no more than four months after the reference quarter.BSP
October 2019The FOF team to compile the BSA matrix on a quarterly basis, sharing the results with the IMF’s Asia Pacific Department at least annually, as input for the yearly Article IV consultation report.BSP

10. Further details on the priority recommendations and the related actions/milestones can be found in the action plan underDetailed Technical Assessment and Recommendations.

Background

A. Context

11. This TA mission is a follow-up of the April 2018 mission that focused on the compilation of the OFC survey. The April 2018 mission reviewed the data sources and mapping to standard report forms (4SR) of the different types of OFCs. In addition, the mission worked on the timeliness of the central bank survey and the incorporation of the money market UITFs into the ODC survey. Most of the recommendations of the 2018 were implemented during the past 12 months. Appendix II presents a more detailed implementation status of the 2018 mission recommendations. Pending issues are discussed in Section A of this report.

12. The current mission objectives and tasks are demand driven. The mission objectives and tasks were defined following BSP requests, addressed in an official letter from the BSP Governor to the Director of STA. These objectives were supported by APD. BSP’s objectives were to: (1) complete the work on the compilation of the OFC survey; (2) receive training on the BSA framework and receive assistance in the compilation of BSA matrices; and (3) receive training on securities statistics in the context of the G-20 DGI and the requirements for adhering to the SDDS Plus, including for BSP staff and staff of data providing agencies, such as the Securities and Exchange Commission (SEC), the Bureau of the Treasury, and the Philippine Dealing System Holdings Corporation. These objectives were accomplished by the mission.

B. Philippines’ Financial System

13. For MFS compilation purposes, the financial sector is divided into three subsectors: central Bank (BSP), ODCs, and OFCs. At the end of 2018, a total of 30.2 trillion pesos1 (about 185 percent of GDP) in assets were distributed between BSP (4.85 trillion), ODCs (17.8 trillion), and OFCs (7.6 trillion). The share of these sectors in total assets is 16 percent, 59 percent, and 25 percent, respectively.

Detailed Technical Assessment and Recommendations

A. Central Bank and Other Depository Corporations

14. The mission discussed selected issues regarding the compilation of SRF 1SR and SRF 2SR. Given that BSP already compiles and reports the central bank survey and the ODC survey using the SRFs, the mission did not perform a thorough review of these surveys. Instead, the mission followed up on the two issues as summarized below.

Central Bank Survey

15. The BSP sectoral balance sheet reported in the 1SR contains intra-sector accounts that should be eliminated. In the process of constructing the BSA matrices, FOF compilers noted accounts in the balance sheet prepared by the BSP’s Accounting Department that reflects assets of the BSP to itself, as well as liabilities of similar amount. These intra-sector positions are common in the ODCs (2SR), for example, representing interbank positions. However, the 1SR should not contain any intra-sector positions, as the BSP is one institutional unit only and cannot have financial assets or liabilities to itself. For example, the BSP balance sheet should not have a deposit to a branch or unit representing an asset and liability in the consolidated BSP balance sheet, as these positions (deposit in this case) within the same institutional unit should be eliminated.

16. The intra-sector positions in the 1SR pertain to funds set aside or setup for a specific purpose, to monitor activities or transactions in these funds between the BSP headquarters and BSP’s departments or regional branches. An asset account (due from administrator of fund account) and a liability account (deposit liability for a specific fund account) are recorded upon transfer of funds to the designated administrator (a BSP department or a regional branch). These entries are done to properly monitor activities or transactions in the said BSP funds. However, the entries are not asset or liabilities of the BSP with another institutional unit. Therefore, these are internal accounts that should not appear in the 1SR.

17. Recommendation: Central Bank (CB) data compilers to eliminate intra-sector positions in the 1SR.

Incorporation of the Money Market UITFs into the ODC Survey

18. TheMonetary and Financial Statistics Manual and Compilation Guide (MFSMCG) recommends the inclusion of money market UITFs in the institutional coverage of the MFS for ODCs. The MFSMCG defines the ODCs subsector as all resident financial corporations that are mainly engaged in financial intermediation and issue liabilities included in the national definition of broad money. Money market funds (MMFs) in the MFSMCG are collective investment schemes that raise funds by issuing shares or units to the public. The proceeds are invested primarily in money market instruments, MMF shares or units, transferable debt instruments with a residual maturity of not more than one year, bank deposits, and instruments that pursue a rate of return that approaches the interest rates of money market instruments. Money market UITFs, which invest in short-term, liquid, low-risk instruments, are a type of MMFs.

19. While BSP compilers have incorporated money market UITFs in the compilation system, the updated 2SR including the historical series is still pending. The money market UITFs represent around six percent of total bank assets. The mission discussed with ODC compilers the reasons for not having completed the work on updating the 2SR, which was one of the 2018 mission recommendations. The main reason is that they are still working on a long historical series of data to be revised. The mission suggested to revise the last five years as a short-term objective and update the 2SR as soon as possible.

20. Recommendation: ODC data compilers to include the money market UITFs in the institutional coverage of ODCs going back to at least five years of monthly data.

Compilation Issues Related to the ODCs Sectoral Balance Sheet (2SR)

21. Several methodological issues have been identified in the compilation of the ODCs sectoral balance sheet report form 2SR. The financial reporting package is the source data to compile the 2SR. During the compilation of the BSA matrix by financial instrument, FOF compilers identified several issues in the compilation of the 2SR using the financial reporting package as the source. These issues were discussed with the mission, which provided recommendations for proper classification following the MFSMCG methodology (Appendix III).

22. Recommendation: ODC data compilers to implement the recommended classifications in the 2SR, using Appendix III of this report.

B. Other Financial Corporations Survey

23. The OFCs are relatively sizable in the Philippines but currently not included in the MFS disseminated by the BSP. The OFCs subsector comprises public and private insurance companies, trusts, government financial institutions, holding companies, NMMFs, and other financial intermediaries and auxiliaries. The assets of the OFCs (7.6 trillion pesos in December 2018) represent around 43 percent of total ODC sector (17.8 trillion pesos). Therefore, compilation of MFS for the OFCs will significantly help inform macroeconomic and financial stability analysis. In addition, compilation and reporting of OFC data would also pave the way for the Philippines’ adherence to SDDS Plus.

24. The compilation of OFC data using report form 4SR has been completed during the mission. Thanks to the intense work of the OFC compilers, including implementation of the 2018 mission recommendations, the sectoral balance sheet of the OFC sector2 is now ready to be used to generate the OFC survey and the FC survey, which consolidates the data of the three financial sub-sectors: CB, ODCs, and OFCs. In addition, the 4SR is a key input for intersectoral balance sheet analysis. The Philippines is now in a position to compile BSA matrices using the newly compiled 4SR.

25. The new 4SR is available quarterly, with data starting on the first quarter of 2017. Annual data starting in 2012 are also available, but these data are of less quality due to the improvements in data reporting taking place for the most recent two years only, i.e., 2017 and 2018. The mission suggests using annual data starting in 2012 only for internal aggregated analysis, for example in the context of the OFC survey, alerting internal users that breaks in the series are due to the use of different data sources with a reduced coverage. For example, holding companies started submitting annual data only in 2016. Annual data for 2012–16 are not reliable enough for dissemination outside the BSP.

26. The mission reviewed the new 4SR and addressed remaining issues identified by BSP compilers. One important methodological issue was the classification of certain financial intermediaries as financial auxiliaries. While this issue has no impact on the aggregated data, it does so on the available sub-categories, which BSP compilers plan to analyze and disseminate separately. For example, OFC compilers prepared a note analyzing the OFC data to be disseminated. The mission reviewed the referred note and provided preliminary comments, except for the sub-categories that need to be updated. At the request of the OFC compilers, the mission also developed several OFC indicators (financial ratios) for more granular analysis of the OFC sector. Other methodological issues discussed were:

  • Treatment of insurance, pension and standardized guarantee schemes categories in the new MFSMCG. The mission explained the different subcategories required by the MFSMCG, as the OFC compilers are using a version of the 4SR that reflects the structure of accounts of the new MFSMCG.
  • Prepayment of insurance premiums. These premiums should not be included in trade credit, following the new MFSMCG (paragraph 4.192).
  • Instrument classification of promissory notes. Even though promissory notes are generally classified as debt securities, the instrument under review, which is issued by households, are not promissory notes as defined in the MFSMCG. • Security funds placed with the Insurance Commission. These funds should be reclassified from trade credit to other deposits with OFCs. This treatment is similar to the classification of bank deposits that are required under the deposit insurance regulation of many countries. • Deposits for stock subscription. These deposits should be reclassified from other accounts payable to equity.

27. The mission mapped the new 4SR (based on theMFSMCG) into the 4SR currently used for reporting to STA. This mapping is needed not only for reporting the new OFC data, but also because the available data on the CB (1SR) and ODCs (2SR) are compiled using the old reporting forms. Therefore, to derive the OFC and FC surveys, the 4SR data needs to be converted to the old format. The mission left a conversion file to be used by the authorities for the 4SR data transmission to STA.

28. Recommendation: OFC data compilers to start disseminating the new OFC data, including submission of the 4SR to STA on a quarterly basis, with a time-lag of no more than four months after the reference quarter.3

29. The following sections discuss two pending issues related to the coverage of the OFC survey. The first issue is on improving the data collection for SEC-supervised corporations, particularly holding and investment companies. The second issue is on the collection of data on private pension funds.

Holding and Investment Companies

30. Holding and investment companies constitute over 19 percent of OFC assets in the Philippines and they are supervised by the SEC. Holding and investment companies provide annual and quarterly data and are currently submitting information to the BSP using the standard structured template designed by the OFCS Team. The SEC only collects data on the top 1000 corporations, out of more than 16,000 SEC-supervised corporations, which include OFCs.4

31. BSP compilers have difficulties in identifying the largest holding and investment companies among the top 1000 corporations. The SEC shared information on total revenue of these companies, but for MFS purposes the best metric to identify the largest intermediaries would be total financial assets, or total assets, if financial assets are not available.

32. The 2018 mission met with SEC management to discuss data needs, but agreements have not been fully implemented. During the 2018 mission, the SEC agreed to provide, out of the top 1000, the list of companies by activity (to identify the financial intermediaries), with contact information and total assets. This information is critical to make sure that the largest companies are covered in the OFC survey. Following the agreement with the mission, the SEC provided the list of financial intermediaries included in the 2015 and 2016 top 1000 corporations, with total assets and contact information. The agency also gave the BSP with supplemental listing of selected corporations consisting of 12 investment houses, 12 underwriters, 20 brokers/dealers, 10 government securities eligible dealers, 10 mutual fund distributors, and 11 investment company advisers. Most of them are subsidiaries/affiliates of banks, hence, already covered by nonbanks with quasi banking functions. However, the SEC was not able to provide a complete list of holding companies by total assets.

33. The experience by BSP compilers on data reporting by SEC supervised corporations pointed to a need to enhance the BSP’s authority to collect data for statistical purposes, which has been addressed by BSP management. The BSP compilers not only faced difficulties in identifying and contacting the largest corporations, but also were questioned by some of these corporations about the authority of the BSP to request data from them. The 2018 mission discussed these challenges with BSP management. In February 2019, the BSP Charter was amended, providing the BSP with the authority to obtain information for statistical and policy development purposes from any person or entity, including individuals and private corporations. Republic Act 11211 (An Act Amending Republic Act Number 7653, otherwise known as “The New Central Bank Act”) was approved and signed. This new Act provides the BSP the authority to require from any person or entity, including government offices and instrumentalities, or government-owned and controlled corporations any data, for statistical and policy development purposes in relation to the proper discharge of its functions and responsibilities.

34. However, the new BSP authority to collect data from individuals and private corporations has yet to be used to improve data reporting by SEC-supervised corporations. The mission believes that the amendment to the BSP Charter is very important for improving the quality of macroeconomic statistics, including better access to data from SEC-supervised companies.

35. Recommendation: (1) SEC to provide a complete list of holding companies by total assets; (2) OFC data compilers to focus on identifying and compiling data from the latest publication5 of the top 1000 corporations supervised by the SEC to increase the sample survey (3) BSP to use the new authority to collect data from any person or entity to improve data reporting by SEC supervised corporations.

Private Pension Funds

36. Private pension funds are not regulated in the Philippines. They may be organized as special purpose trust funds,6 but no regulator is currently collecting data on them. However, the new BSP authority to collect data from any person or entity could be used to collect data directly from the biggest private pension funds.

37. These funds may hold significant amounts of domestic public sector debt. Government debt statistics on domestic securities show values for total outstanding debt securities that are significantly higher than the holdings of debt securities reported by the financial sector. This finding leaves the possibility of significant holdings by households, non-financial corporations (NFCs), or private pension funds. The mission is of the view that private pension funds may be the largest holders of government debt securities among these residual sectors.

38. Recommendation: BSP to identify a regulatory agency or unit within the institution to make an inventory of private pension funds and start collecting data (on the largest ones, at least) relevant for the compilation of the 4SR.7

C. Integrated Monetary Database and Analysis of the Other Financial Corporations

39. Since June 2010, the BSP, STA, and APD have shared an IMD that meets their publication and operational needs. The mission discussed the importance of maintaining and improving the IMD for the Philippines. The current IMD contains the SRFs for the central bank and ODCs, and the corresponding surveys. The BSP uses the IMD to disseminate data that are fully consistent with the recommendations of the Monetary and Financial Statistics Manual of 2000. The IMD contains data for December 2001 onward for the central bank and ODCs.

40. The IMD was upgraded during the mission to include the newly available data for OFCs. With the inclusion of the 4SR starting in the first quarter of 2017, the IMD is now complete. The upgraded IMD contains data from the three financial subsectors: CB, ODCs, and OFCs. With these data as source, it generates surveys for: CB (1SG), ODCs (2SG), depository corporations (3SG), OFCs (4SG), and financial corporations (FCs) (5SG). The FCs survey consolidates all financial subsectors into one single survey.

41. The mission encouraged the OFC compilers to analyze the OFCs by type of institution in national publications. The OFC sector is composed of a range of financial intermediaries with very different business models. For example, investment trusts in which investments are relatively liquid or accessible in contrast with life insurance companies where funding has a more permanent nature. Therefore, the aggregated OFC sector is best analyzed as a complement to the role of the ODC sector in the provision of credit to the rest of the economy. Also, the total ODC and OFC sector data can be used for the study of domestic and external funding of both sectors, i.e. dependence of ODCs and OFCs on foreign financing and resulting investment in the domestic economy. Considering that the 7.6 trillion assets of OFCs represent around 42 percent of banks assets of 12 trillion in 2018, the impact of adding the former assets into an FC survey covering all financial intermediaries is going to be very significant. Because of the different business models of the OFCs, the mission also suggests disseminating data on each type of OFC separately, for example, on trusts, insurance companies, NMMFs, etc.

42. Because 37 percent of the OFCs are financial trusts funded by owners’ own funds, the capital structure of the FC survey will be very different from the ODC’s, whose business model is more reliant on debt instruments than capital. In the analysis, there is a need to bear in mind, for international comparisons, that data on trusts are less available in other economies, i.e. it may not be included in the OFC survey, and that the relative size of institutional and individual trusts in the Philippines is very significant, in contrast with a much less developed collective saving schemes.

43. Recommendation: The BSP prepare new tables for internal analysis comparing the ODC and OFC sub-sectors, consolidating all financial sectors into an FC survey, and disseminating separate data on the main types of OFCs.

D. Balance Sheet Approach

Introduction

44. Integrated balance sheet analysis, focusing on the identification of vulnerabilities on a from-whom-to-whom basis, began after the Asian crisis of the 90s, including with a paper by the IMF staff in collaboration with academia on “A Balance Sheet Approach to Financial Crises” (2002). For years, countries have applied BSA analysis, including in their Article IV reports. More recently, the IMF experience over more than a decade incorporating BSA into surveillance was summarized in a policy paper entitled “Balance Sheet Analysis in Fund Surveillance” (2015).

45. In the case of the BSP, the newly accomplished full coverage of the MFS allows for BSA analysis to be conducted. The most important building block for BSA analysis are the data on the entire financial system, including the most relevant OFCs, which is now available. The other important data source is quarterly IIP,8 which is also available for the Philippines.

46. With full coverage of the financial sector and the external data (IIP), it is possible to create simplified quarterly BSA matrices on a timely basis. These matrices can shed light on the financing and investment behaviors of the nonfinancial sectors (government, nonfinancial corporations, and households/NPISH9), including assessment of vulnerabilities (maturity, currency, and capital structure mismatches). For example, given that counterparty data in MFS and IIP are available, using these data, the reliance of the government on external and financial sector funding can be monitored. The same applies to the corporate and household sectors. Following improved data availability in the future, enhancements could be carried out to include full maturity, currency, and capital structure breakdowns, which are not currently available.

47. The FOF unit compiles comprehensive annual FOF data with a time lag of 12 to 15 months after the end of the reference year, i.e. the FOF data for 2018 will be available around February 2020. The 2018 mission believed that this unit is best suited to carry out the work of compiling a simplified BSA matrix. This BSA matrix may have limited reconciliation with the FOF, as the latter use more comprehensive data sources. Also, the maturity, currency, and equity/debt breakdowns may not be available in some cases.

BSA Seminar and Compilation of BSA Matrices

48. The BSA related work carried out by the mission comprised a seminar and the discussion of issues arising in the compilation of the BSA matrix by FOF compilers. At the request of BSP, the mission delivered a seminar on the BSA based on the material presented during the recent workshop on the BSA that took place in Singapore during January 2019. In addition, the mission presented a historical perspective of the evolution of FOF compilation in OECD countries. The key messages of the seminar were: (1) the interest since the 1990’s by the international community to devote resources to compile intersectoral positions data, in addition to the flow-of-funds data currently compiled by BSP staff; (2) the need for more frequent (quarterly vs annual) and timely data for macro-financial stability analysis; and (3) the focus on a from-whom-to-whom approach, allowing the identification of creditor and debtor sectors and the financial dependence among them.

49. The seminar was well attended by FOF, MFS, and ESS compilers, setting the stage for discussing country-specific compilation issues. More than 25 BSP staff attended the seminar, which allowed for discussion of specific issues related to the compilation of the BSA by FOF compilers. The resolution of the compilation issues (mostly inconsistencies among datasets) not only improved the quality of the BSA analysis, but also is going to improve the quality and consistency of sectoral statistics, such as the MFS and ESS.

50. The identification of compilation issues was possible by using an instrument-by-instrument approach to compile the BSA. The instrument-by-instrument approach consists of compiling a BSA matrix for each financial instrument, to ensure the horizontal consistency of the compilation system. Horizontal consistency means that, for each instrument, assets by all holding sectors equal liabilities by issuing sectors. For example, the outstanding amount of debt securities issued by the general government should equal to the holdings of securities by the domestic sectors and the rest of the world. The difference between issuance (liabilities) and holdings (assets) are allocated to the residual sectors (those for which direct source data are not available).

51. The instrument-by-instrument approach also allows for a better prioritization of data quality among data sources. In the BSA, when one cell can be compiled using more than one source (for example, ODC deposits in the central bank), one source is chosen over the other depending on its presumed quality. In this regard, the central bank data (1SR) is chosen over the ODC data, when both data are not fully consistent, which is frequently the case. The prioritization of source data in the BSA compiled by STA is in most cases: (1) 1SR; (2) 2SR; (3) 4SR; (4) IIP; and (5) general government statistics (GFS). However, FOF compilers were able to identify cases were this system of prioritization of sources had to be changed, for example, by assuming that IIP data was of better quality than the 2SR or 4SR10 data for a particular instrument. For example, in the Philippines, the IIP data are of better quality for counterparty information than the 2SR for debt security liabilities. The 2SR records all offshore issuances as held by non-residents. However, the IIP reflects the necessary adjustments that removes offshore issuances held by residents. Thus, the IIP is prioritized in the instrument-by-instrument approach over the 2SR in this example. The mission noted that this situation should be transitory and that the 2SR should be corrected using improved data from ODCs, as adjustments to improve the 2SR using quarterly IIP data are impractical.11

52. FOF compilers were also able to deal with inconsistentMFSMCG and theBalance of Payments and International Investment Position Manual, sixth edition (BPM6) methodologies. These inconsistencies related to the treatment of IMF accounts denominated in domestic currency and the definition of ODCs in the MFSMCG versus the definition of deposit-taking corporations in BPM6. In the central bank sectoral balance sheet (1SR), IMF accounts denominated in domestic currency are recorded as external liabilities of the BSP, while in the IIP, these are not recognized as external liabilities, due to the net recording of these liabilities in BPM6. The definition of ODCs in the MFSMCG include institutions (MMFs) not included in the BPM6 definition of deposit-taking corporations. In addition, offshore banks without deposits by resident sectors are classified as OFCs in the MFSMCG, but as deposit-taking corporation in BPM6. FOF compilers decided to use the BPM6 methodology in these cases because BPM6 is consistent with the SNA 2008 and the BSP’s system of FOF. Therefore, exclusion of MMFs from the 2SR and inclusion of the offshore banks are needed for the compilation of the BSA matrix. Data on MMFs and offshore banks should be separately identified for proper recording in the BSA matrix.

53. In addition to MFS and ESS, the mission encouraged the use of available fiscal data. The following reports are available to BSP staff: (1) Quarterly Outstanding General Government Debt (no breakdown per instrument); (2) Monthly National Government Outstanding Debt; (3) Quarterly Outstanding Public Sector Debt (no instrument breakdown and last available data is as of September 2015); (4) Annual balance sheets of the national government, local government units and social security funds from the Commission on Audit. A complete (financial and non-financial) balance sheet of the general government is available from the Commission on Audit. The 2012–17 annual Statement of Government Operations (SGGO) was published by the DOF on 24 May 2019. The FOF team will request for the detailed SGGO, which we might be able to use for the BSA. Annual domestic government debt data were used in the preliminary compilation of the BSA.

54. Recommendation: The FOF team to compile the BSA matrix on a quarterly basis, sharing the results with the IMF’s Asian Pacific Department at least annually, as input for the yearly Article IV consultation report.

E. Securities Statistics and SDDS Plus

55. At BSP request, the mission delivered a seminar comprising three lectures on securities statistics, the G-20 DGI, and SDDS Plus. The seminar was attended by a large group of BSP staff and representatives from other agencies. These agencies (the SEC, the Bureau of Treasury, and the Philippine Dealing System Holdings Corporations) are potential source data for the compilation of securities statistics by the BSP.

56. The first lecture on securities statistics was based on theHSS of 2015. The lecture explained the main concepts and definitions of the HSS. The HSS was drafted by the IMF, the Bank for International Settlements, and the European Central Bank, and it is considered an internationally agreed methodological framework for developing securities statistics. The mission suggested using the HSS as reference for compiling securities statistics.

57. The second lecture was on the G-20 DGI. This lecture provided an overview on the G-20 DGI, focusing on recommendation 7. It also discussed the DGI-2 reporting templates, as a model to follow for non-G-20 economies for the improvement of securities statistics. The mission highlighted Table 3.1, which has been selected as the reporting template to meet SDDS Plus requirements. Appendix IV presents all G-20 reporting templates, including Table 3.1.

58. The third lecture was on the IMF data dissemination standards, including SDDS Plus. The lecture presented an overview of the original IMF data dissemination standards (SDDS and GDDS) and the new ones (SDDS Plus and E-GDDS). As of April 2019, only 18 countries have adhered to SDDS Plus. After disseminating the new 4SR and corresponding OFC survey, and developing a work plan to improve securities statistics, the mission is of the opinion and the Philippines is a strong candidate to adhere to SDDS Plus.

59. Recommendation: FOF team to continue discussing reporting requirements with the data providing agencies, using the G-20 templates and the SDDS Plus from-whom-to-whom table as reference, and agree on a work plan to improve securities statistics.

F. Financial Derivatives and Crypto-Assets

60. At BSP request, the mission explained the treatment of financial derivatives in macroeconomic statistics, focusing on the correct compilation of flow data. Flow data (transactions and other flows, in particular revaluations) cannot be estimated as the difference between stock positions. This estimation method may work for other financial instruments, but it greatly underestimates the volume of transactions and holding gains and losses (recorded in the revaluation account) that financial derivate operations generate. The mission provided guidelines to improve recording of these transactions in ESS and FOF.

61. At BSP request, the mission also delivered a lecture on the treatment of crypto-assets in macroeconomic statistics, based on the latest methodology released by STA. The Philippines may become an important market for crypto-assets, as the BSP recently authorized operations for three more virtual currency exchanges (VCE), bringing the total number of approved VCE to 10. The mission encourages the BSP to start exploring the possibility of collecting data on these exchanges for macroeconomic analysis, in particular international financial flows using crypto-assets. The mission suggests requesting aggregated data, on a quarterly basis, on gross transactions, indicating the country of origin and destination of the funds transacted. In addition, it would be useful to breakdown the parties involved in the transactions between individuals, financial corporations, and nonfinancial corporations.

Action Plan

The Action Plan below includes steps to accomplish milestones as well as the risks/verifiable indicators to achieving the outcomes. The plan is for technical compilers. Actions are prioritized (H – high, M – medium, L – low).

Table 2.Philippines: Mission’s Recommendations
PriorityAction/MilestoneRisk Assumptions/ Verifiable IndicatorsTarget Completion Date
Outcome Indicator: The financial instruments classification, sectorization, and coverage of monetary statistics fully complies with theMFSMCG methodology.
HCB data compilers to eliminate intra-sector positions in the 1SR.Intra-sector positions are eliminated in the 1SR.June 2019
HODC data compilers to include the money market UITFs in the institutional coverage of ODCs going back for at least five years of monthly data.Money market UITFs are included in the coverage of the 2SR.September 2019

Benchmark
HODC and OFC data compilers to implement the recommended classifications in the 2SR and 4SR using Appendix III of this report.2SR and 4SR are updated with the new classifications.September 2019
HOFC data compilers to start disseminating the new data, including submission of the 4SR to STA on a quarterly basis, with a time-lag of no more than four months after the reference quarter.OFC survey data published in International Financial Statistics.September 2019

Benchmark
H(1) SEC to provide a complete list of holding companies by total assets; (2) OFC data compilers to focus on identifying and compiling data from the latest publication12 of the top 1000 corporations supervised by the SEC to increase the sample survey (3) BSP to use the new authority to collect data from any person or entity to improve data reporting by SEC supervised corporations.A complete list of holding companies by total assets is provided by SEC.December 2019
MBSP to identify a regulatory agency or unit within the institution to make an inventory of private pension funds and start collecting data (on the largest ones, at least) useful for the compilation of the 4SR.A regulatory agency or unit for private pension funds is identified.August 2019
MThe BSP prepare new tables for internal analysis comparing the ODC and OFC sector, consolidating all financial sectors into an FC survey, and disseminating separate data on the main types of OFCs.New tables on OFCs are prepared.December 2019
Outcome Indicator: New standardized report form for the other financial corporations (4SR) has been used to generate the BSA matrix.
HThe FOF team to compile the BSA matrix on a quarterly basis, sharing the results with the IMF’s Asian Pacific Department at least annually, as input for the yearly Article IV consultation report.BSA matrix shared with APD quarterly, with five months timeliness.October 2019

Benchmark
Outcome Indicator: Training securities statistics, G-20 data gap, and SDDS Plus provided.
MFOF team to continue discussing reporting requirements with the data providing agencies, using the G-20 templates and the SDDS Plus from-whom-to-whom table as reference, and agree on a work plan to improve securities statistics.A work plan agreed with data providing agencies is defined.December 2019
Appendix I. Officials Met During the Mission
NameInstitution
Bangko Sentral ng Pilipinas
Mr. Diwa C. GuinigundoDeputy Governor, Monetary and Economic Sector
Mr. Francisco G. Dakila, Jr.Assistant Governor, Monetary Policy Sub-Sector
Mr. Redentor Paolo M Alegre Jr.Director, Department of Economic Statistics (DES)
Ms. Marriel M. RemullaDeputy Director, DES
Ms. Mary Rose C. EspinaBank Officer V, DES
Ms. Eva Lynne M. MarcosBank Officer V, DES
Ms. Flerida R. NallasBank Officer V, DES
Ms. Ma. Angelica B. VillenaBank Officer V, DES
Ms. Marcelina S. PerezBank Officer V, DES
Ms. Nashrine B. AlipingBank Officer IV, DES
Ms. Tatum Blaise P. TanBank Officer V, DES
Ms. Diana B. AdelanBank Officer V, DES
Mr. Antonio L. BalnegBank Officer V, DES
Ms. Leah S. LimBank Officer V, DES
Ms. Eden B. TengcoBank Officer V, DES
Ms. Mia Donna G. De JesusBank Officer V, DES
Ms. Marissa M. DuqueBank Officer IV, DES
Ms. Jean Christine A. ArmasBank Officer IV, DES
Ms. Ma. Teresa S. PerezBank Officer IV, DES
Ms. Ma. Francesca D. GrabadorBank Officer IV, DES
Mr. Rodel C. ObraBank Officer IV, DES
Ms. Kimberly B. PaycanaBank Officer IV, DES
Ms. Maria Nimfa G. SantosBank Officer IV, DES
Mr. Bernard Ahman O. EbuñaBank Officer IV, DES
Ms. Ma. Lourdes C. ReynosoBank Officer IV, DES
Ms. Marie Belarmine F. PagalunanBank Officer IV, DES
Ms. Elizabeth N. SanchezBank Officer IV, DES
Mr. Arnie-Gil DLR. HordejanBank Officer IV, DES
Ms. Mazel G. PizarroBank Officer IV, DES
Mr. Luisito T. AsuncionBank Officer IV, DES
Ms. Ma. Solina E. GoBank Officer IV, DES
Ms. Aiza Maris C. ValenzuelaBank Officer II, DES
Mr. Jonathan Leo M. CarpioBank Officer II, DES
Ms. Jennifer Louise G. PederioBank Officer II, DES
Ms. Katrina Marie F. ReyesSenior Research Specialist, DES
Ms. Krizzia Kate L. CortesSenior Research Specialist, DES
Mr. Rafael Antonio S. IbarraSenior Research Specialist, DES
Mr. Miguel Augusto H. LibreSenior Research Specialist, DES
Ms. Roma S. RodriguezSenior Research Specialist, DES
Ms. Mitzie Gaye E. HaliliSenior Research Specialist, DES
Ms. Joana Marie B. TrinidadSenior Research Specialist, DES
Ms. Katrina MendozaSenior Research Specialist, DES
Mr. Rodenel L. FallarcoSupervision and Examination Specialist I, Supervisory Data Center
Securities and Exchange Commision
Mr. Jo-Dann N. DarongSenior Security Specialist
Mr. Ulysis San JuanStatistician
Mr. Mark Ferdinand SantosSecurity Specialist
Bureau of the Treasury
Mr. Robert Dominick MarianoDirector, Research Services
Philippine Dealing System Holdings Corporation
Mr. Paul John ComiaOfficer
Ms. Ma. Theresa RavaloPresident and COO
Appendix II. Implementation Status of the 2018 Mission Recommendations
PriorityRecommendation/ MilestoneRisk Assumptions/ Verifiable IndicatorsImplementation Status (April 2019)
Outcome 1: Data are compiled and disseminated using the coverage and scope of the latest manual/guide (DQAF 2.2)
HThe BSP includes the money market UITFs in the institutional coverage of ODCs.Money market UITFs are included in the 2SR.

Benchmark
SRF for MMF partially completed.
H(1) Compile and disseminate data ontrusts quarterly, with no more than three-months’ time lag;(2) Classify non-money market UITFs as NMMFs and institutional and individual accounts trusts as captive financial institutions under the OFCs subsector; and (3) Ensure that other compilers of macroeconomic statistics classify trusts consistently with the MFS.Quarterly data on trust based on the updated structured templates included in the 4SR. BenchmarkCompleted.
H(1) BSP compiles data oninsurance companies quarterly and includes them in the OFC survey.Quarterly data on insurance companies based on the updated structured templates included in the 4SR.

Benchmark
Completed.
MBSP compilers to focus onidentifying the OFCs from the top 1000 corporations supervised by the SEC and collecting and compiling data before increasing the sample survey.Data on SEC-supervised largest companies based on the updated structured templates included in the 4SR.

Benchmark
Partially Completed. Size of corporations still based on total revenues rather than total assets.
H(1) Continue compiling quarterly data on theHome Development Mutual Fund, to be included in the OFC survey; (2) For the rest of Government Commission for Government-Owned or Controlled Corporations supervised institutions, compile data that are reported on a timely basis only, for inclusion on the OFC survey.Quarterly data on the Home Development Mutual Fund based on the updated structured templates included in the 4SR.

Benchmark
Completed.
Outcome 2: Improved timeliness of data made available internally and/or to the public (shorter delays) (DQAF 4.1.2)
HThe BSP reduces the significant lag in the availability of theSRF for the central bank (1SR) to one month after the reference period for the August to November releases, and two months for the January to July releases. The release of the end-year (December) preliminary data will be done February of the following year.Data on the central bank (1SR) are submitted to STA within one month after the reference period for August to November data and within two months for January to July data.

Benchmark
- Aug 2018-Dec 2018 data: – Completed (submitted within one month after reference period). – Jan to Feb 2019 data was completed as of 30 April 2019 and the March to April 2019 data was completed as of 30 May 2019).
Outcome 3: Staff capacity increased through training, especially on developing source data, compilation methods, and dissemination (DQAF 0.2)
HThe FOF team takes the lead in the compilation of a summarizedBSA matrix on a quarterly basis. A test of the matrix could be done using year end 2016 data.The summarized BSA matrix is produced and used internally.On-going annual compilation based on 2015–2017 data. Reconciliation issues are to be raised in the TA on 29 April – 3 May 2019.
MThe BSP preparesnew analytical tables for internal analysis comparing the ODC and OFC sector, consolidating all financial sectors into an FC survey, and disseminating separate data on the main types of OFCs.New tables on OFCs are available for internal BSP use.Completed.
Appendix III. ODC and OFC Instrument Classification Issues
AccountDefinitionCurrent classificationProposed ClassificationRemarks
1Certificates of Assignment/Participation with RecourseThis refers to the amortized cost of borrowings in the form of sale of securities to another bank/counterparty under certificates of assignment/participation with recourse.2SR – Debt securitiesLoansLoans, to the extent that these certificates are not negotiable
2Liability for short positionThis refers to the obligation of the purchaser/borrower of securities under Reverse Repurchase Agreements/ Certificates of Assignment/Participation with Recourse/ Securities Lending and Borrowing Agreements to return the securities purchased/borrowed from the seller/lender, which the former sold to third parties. This shall be recorded at fair value and any gain or loss arising from a change in its fair value shall be recognized in profit or loss under the account “Gain/(Loss) from Financial Assets and Liabilities Held for Trading.”2SR – Debt securitiesDebt securities (negative asset)Agreed classification: Debt securities (negative asset)
3Repurchase AgreementsThis refers to agreements involving the sale for cash or securities at a specified price with a commitment to repurchase the same or similar securities at a fixed price either on a specified future date or with an open maturity. Repo transactions are accounted for as collateralized borrowings. In this case, the transferred securities are not derecognized from the books of the transferor, which shall remain under the same classification they had before the transaction, in this case HFT.2SR – Debt securitiesLoansAgreed classification: Loans (or other deposits, if the repo is included in the broad money definition)
4Securities Lent Under Securities Lending Agreements (SLB)This refers to transactions that has a similar arrangement to a repo except that this is a “security driven” agreement typically initiated by financial institutions that need specific securities to cover a short sale or a customer’s failure to deliver securities sold. The transferee of securities is generally required to provide “collateral” to the transferor of securities, commonly cash but sometimes other securities, standby letters of credit or a combination thereof.2SR – Debt securitiesLoansAgreed classification: Loans or off-balance sheet. Two possibilities: (1) Securities lending backed by cash collateral is similar to a repo; (2) Securities lending that is backed by collateral other than cash (or that is not collateralized) should not be treated as a transaction and should be recorded off balance sheet by both the lender and borrower of the securities.
5Redeemable Preferred SharesThis refers to preferred shares issued which provides for redemption on a specific date, i.e., mandatorily redeemable preferred shares. This shall be measured at amortized cost using the effective interest method.2SR – Debt securitiesEquityAgreed classification: Equity
6Due to Head Office/Brs/Agcs Abroad-Phil. Branch of Foreign Banks Placements/time deposits/borrowingsThis account controls the clearing of items/transactions between the Philippine2SR – DepositsIIP – LoansAgreed classification: Deposits
7Deposit for Stock SubscriptionThis refers to funds received as deposits for stock subscription but do not meet the conditions for recognition as equity.4SR – Other accounts payable/receivable: AdvancesEquityAgreed classification: Equity
8Premium Deposit FundsAllows the policy owner to accumulate money to pay future premiums on their policy. Clients can put money into the fund at any time. Total contributions are limited to the amount required to pay premiums for the life of the policy.4SR – DepositsDepositsAgreed classification: Deposits (all interbank positions are treated as deposits)
9Promissory Notes of HouseholdsA signed document containing a written promise to pay a stated sum to a specified person or the bearer at a specified date or on demand.4SR – Debt SecuritiesLoansAgreed classification: Loans
Appendix IV. G-20 Securities Statistics Reporting Templates
Table 1.1:Debt Securities Issues by Sector, Currency, Maturity, Interest Rate and Market of Issuance. Stocks at Nominal Value
*) Money market funds do not issue debt securities.2008 SNA codes are used for sectors and subsectors.
*) Money market funds do not issue debt securities.2008 SNA codes are used for sectors and subsectors.
Table 1.2:Debt Securities Issues by Sector, Currency, Maturity, Interest Rate and Market of Issuance. Stocks at Market Value
*) Money market funds do not issue debt securities.2008 SNA codes are used for sectors and subsectors.
*) Money market funds do not issue debt securities.2008 SNA codes are used for sectors and subsectors.
Table 1.3:Debt Securities Issues by Sector, Currency, Maturity, Interest Rate and Market of Issuance. Net transactions at Market Value
*) Money market funds do not issue debt securities.2008 SNA codes are used for sectors and subsectors.
*) Money market funds do not issue debt securities.2008 SNA codes are used for sectors and subsectors.
Table 2.1:Debt Securities Holdings by Holding Sector, Issuer Residency, Currency, Maturity, Interest Rate and Market. Stocks at Market Value
2008 SNA codes are used for sectors and subsectors.
2008 SNA codes are used for sectors and subsectors.
Table 2.2:Debt Securities Holdings by Sector, Issuer Residency, Currency, Maturity, Interest Rate and Market. Net transactions at Market Value
2008 SNA codes are used for sectors and subsectors.
2008 SNA codes are used for sectors and subsectors.
Table 3.1:Debt Securities Issues and Holdings in a From-Whom-To-Whom Framework. Stocks at market value
2008 SNA codes are used for sectors and subsectors.
2008 SNA codes are used for sectors and subsectors.
1

Preliminary data for all figures in this report.

2

Except for two pending coverage issues, explained in paragraphs 29–38.

3

Before the agreed September 2019 deadline for the reporting of the 4SR to STA, a sample 4SR metadata will be provided to the OFC team for reference.

4

This estimate is based on an unofficial list given in 2015.

5

The SEC provided info based on 2015 and 2016 Top 1000 corporations. The SEC should furnish the same listing based on a more recent year reference.

6

The alternative option is when pension funds are kept in the balance sheet of the employer. In this case, there is no institutional unit that can be identified, i.e. no financial intermediary in the form of a pension fund to be included in the coverage of the OFC survey.

7

According to the authorities, considering that there is no regulatory agency in-charge of the private pension funds, in the short-term, the BSP may conduct a survey of large corporations to identify existing private pension funds, either in-house or subsidiary of these corporations. The BSP may use its authority to collect data from private companies to conduct the said survey. In the long-term, this concern may be raised at the proper forum (i.e., Economic Development Council) to identify the appropriate regulatory body to supervise and regulate the private pension funds.

8

The current compilation of the IIP does not provide currency breakdown and decomposition of the “other sectors” into NFCs and OFCs.

9

Nonprofit institutions serving households.

10

In most cases, the 4SR is used to breakdown the components of the “other sectors” in the IIP. Hence, the OFC is netted out from the IIP’s total, while the rest is classified under NFC.

11

The ESS compilers have monthly data but the timing of the report submission may be an issue.

12

The SEC provided info based on 2015 and 2016 Top 1000 corporations. The SEC should furnish the same listing based on a more recent year reference.

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