IMF Policy Paper: Fifteenth General Review of Quotas—Additional Considerations and Data Update—Statistical Appendix

The paper recaps the findings of previous staff work on the adequacy of Fund resources and tests the robustness of the earlier analysis.


The paper recaps the findings of previous staff work on the adequacy of Fund resources and tests the robustness of the earlier analysis.


1. This appendix discusses the required data, the selection of the database, and data availability and adjustments for the data series used for the quota calculations. The quota database is updated annually, and the current updated covers data through 2016, based on the latest information as of end-January 2018.

Required Data

2. The quota database requires the following data for all 189 member countries (converted into SDRs as the common denominator):1

  • GDP at market prices for three years (2014–16).

  • PPP GDP (GDP at purchasing power parity) for three years (2014–16). PPP GDP for a given economy is the volume of goods and services produced for final uses by that economy relative to other economies. It is calculated by deflating GDP at market prices by the PPP price level index, allowing comparisons across countries for a given period.

  • Current receipts (goods, services, primary income, secondary income, and capital account)2 for 13 years (2004–16). Current receipts are defined as the credit component of all economic transactions between resident and nonresident entities other than those relating to financial account transactions.

  • Current payments (goods, services, primary income, and secondary income, and capital account)3 for five years (2012–16). Current payments are defined as the debit component of all economic transactions between resident and nonresident entities other than those relating to financial account transactions.

  • Net capital flows for 13 years (2004–16). Net capital flows relate to cross-border transactions of the financial account in all external financial assets and liabilities except reserve assets, credit and loans from the Fund, and exceptional financing. This variable measures net financial flows, but the term “net capital flows” is used to maintain continuity with previous quota database terminology.

  • Official reserves, defined as the sum of the average over the 12 months of 2016 of foreign exchange, SDR holdings, reserve position in the Fund, and monetary gold valued at SDR 35 per fine troy ounce.

3. Errors and omissions have not been included in the measure of variability of current receipts and net capital flows. Errors and omissions are, by definition, a residual item, which reflects recording errors that cannot be ascribed to any particular balance of payments category. Consistent with past practice, these recording errors are not incorporated into the variables of the quota database.

4. Transactions in both reserve assets and reserve-related liabilities should, in principle, be excluded from net financial flows (referred to as “net capital flows”) so that only autonomous and not financing flows are captured. In practice, however, such data are only excluded for reserve assets while data limitations prevent their exclusion for reserve liabilities. Specifically, data on transactions in reserve assets are available for most members in International Financial Statistics (IFS) and have been excluded from net capital flows. However, because of the continuing lack of data on reserve-related liabilities for many members, changes in reserve-related liabilities have not been excluded from the measure of net capital flows in this database.4

5. Credit and loans from the Fund and exceptional financing have been excluded from the variability measure for the same reason that reserve asset changes have been excluded. Such transactions, including borrowing from the Fund, accumulation and repayment of arrears, and debt forgiveness or rescheduling, represent exceptional measures undertaken to finance balance of payments needs. In the analytic presentation of the balance of payments, exceptional financing flows are shown “below the line” because they are not autonomous balance of payments transactions. For these reasons, and consistent with past practice, these transactions are not included in the variability measure.

Construction of the Database

A. Main Sources

6. To ensure similar treatment for all countries and facilitate the comparability of results in a transparent manner, the data used in quota calculations should have a few attributes. To the extent possible, it should be comprehensive (i.e., contain all required data for all members); compiled in line with internationally accepted concepts and definitions; reported by official sources (central banks and national statistical agencies); and comparable (consistent and coherent) across time and countries.

7. As in past quota updates, the main source of data used in the quota calculations was the International Financial Statistics (IFS). The IFS data are reported to STA by central banks and national statistical agencies, and are mostly based on internationally consistent definitions, such as the BPM65 and the 1993/2008 System of National Accounts (1993/2008 SNA). STA manages this database for international statistical cooperation and publication purposes, and to support the Fund’s surveillance and use of Fund resources functions. The database embodies, to the extent possible, the application of international statistical methodologies for the compilation of economic and financial data.

8. Missing observations in the IFS data are largely supplemented using the World Economic Outlook (WEO) database.6 The combination of the two sources is based on pre-defined procedures designed for each variable, as described in the next subsection. It should be noticed that for some member countries there may be discrepancies between the IFS and the WEO datasets due to varying institutional, legal, and accounting contexts of data compilation (Boxes 1 and 2). For members where neither IFS nor WEO data were available, FIN obtains data from staff reports and IMF country desks or fills gaps with the data of adjacent years, as detailed in subsection C.

9. Finally, after the gaps are filled, the full dataset is reviewed by country desks for reasonability. In cases where discrepancies are significant and desk data are more reliable, adjustments to the final data are made. The adjustments made in this update round are described in subsection C below.

B. Initial Database – IFS Supplemented by WEO

GDP Data

10. The IFS and WEO databases provided GDP data for 188 members (all Fund members except the Syrian Arab Republic). The PPP-based GDP data derived using the WEO methodology also cover 188 members (all Fund members except the Syrian Arab Republic). Under the WEO methodology, PPP-based GDP is calculated by dividing a country’s nominal GDP in domestic currency by its PPP price index relative to the United States7 and then converting it into SDR units, using the SDR-USD exchange rate. The PPP price indices are based on the data from the International Comparison Program (ICP) for 2011 that were released in April 2014.8 These data were then extended forward (to 2016) by using the growth in relative GDP deflators (the deflator of a country divided by the deflator of the United States).9

Balance of Payments Data

11. The balance of payments data stored in the IFS database were used as reported by members to STA. Of the 189 members, the number of reporters to IFS for at least some of the years are as follows: 178 for the period 2004–16; and 176 for the period 2012–16. When data were not available for some members for the timeframe required for the quota calculations, estimates were made, largely on the basis of the WEO, as described above.10

12. The number of countries reporting their BOP data under BPM6 has been increasing and 165 Fund members now report BPM6-based balance of payments statistics to STA. The remainder that still provide data on the basis of BPM5 are then converted by STA into BPM6 format (see Box 2).

13. The BPM5-BPM6 conversion matrix was developed by the WEO team in collaboration with STA to assist IMF country desks. Compared to the previous template, the new BPM6 template used by the WEO introduced a number of changes, some of which impacted on the gap-filling procedures as follows: (i) more details became available for some series (e.g., gross flows were included on an optional basis for primary income, secondary income, and capital account, as well as for the IIP (total assets and liabilities)); and (ii) some indicators used in the calculation of the net capital flows were removed (net credit and loans from the IMF) or became optional (the exceptional financing series).

14. To the extent possible, STA collected additional information from IMF country desks on the gross flows series underlying the variables included in the quota that were not reported to WEO (optional reporting) or no longer required by the new template. WEO does not collect separate data for goods for processing or for reverse investment. Unless the authorities reported BPM6 data to desks, no imputations were made by STA for these variables. This is consistent with the generic conversion of reported IFS data where, if a country did not report data for goods for processing or reverse investment, no imputations were made.

Methodological Issues

International standards for GDP compilation are laid out in the System of National Accounts (SNA). About 50 percent of IMF members compile GDP data according to the current vintage, the 2008 SNA, most others are based on the 1993 SNA and very few still apply the 1968 SNA. The 1993 SNA extended the scope of GDP slightly, making refinement to the calculation of production of goods for own final use and adding mineral exploration, computer software, and artistic originals to capital formation. Further changes introduced by the 2008 SNA have impacted on GDP and other macro-economic aggregates for member countries. Some of the noteworthy changes brought out by the 2008 SNA are: including research and development expenditures in gross capital formation rather than in intermediate consumption, and including depreciation of research and development assets in consumption of fixed capital; including net acquisitions of weapon systems in gross capital formation rather than in government final consumption, and including depreciation of military assets in consumption of fixed capital; making refinements to the calculation of Financial Intermediation Services Indirectly Measured for loans and deposits using a reference rate and requiring implementation of the reference rate method rather than treating it as an option; and calculation of non-life insurance output using the adjusted claims and the adjusted premium supplements. This has resulted in an increase in reported GDP levels, but the size of data inconsistencies across countries due to the revisions related to different SNA vintages is likely to be smaller than other differences related to known measurement problems with GDP (e.g., under-coverage of surveys, outdated base years, or differing adjustment methods for the size of the non-observed economic activity).

With regard to BOP series for quota calculations, the current receipts and payments cover goods, services, primary income, secondary income, and the capital account. The capital account, which includes capital transfers and acquisition/disposals of non-produced nonfinancial assets, ensures comparability with previous quota calculations. Starting with July 2015 IFS issue, the IFS (and the on-line Balance of Payments Statistics database) excluded the migrants’ transfers from the capital account, in line with BPM6 guidance. These had originally been retained since the 2012 launch of the BPM6-basis generic-converted series to ensure consistency with the balance of capital account and net errors and omissions series in the BPM5-based series.

With regard to financial account transactions, the accuracy of financial account data in many countries, including those in the IFS database, is uneven and the data are generally less comprehensive than the other data used for the quota formulas. This reflects classification and practical difficulties encountered by countries in compiling the data. Financial account data, particularly on the private nonbank sector, are generally difficult and resource intensive to compile. The switch from data collection systems based predominantly on government and balance sheet records to systems (particularly surveys) incorporating large private nonbank sector transactions has been slow. Many countries are still in the midst of adapting their collection and recording systems to take account of changes in the composition and magnitude of financial transactions, including new instruments such as financial derivatives. Institutional and accounting requirements for data compilation may differ across countries and data availability on the private nonbank sector varies. In the IFS, in some instances, only aggregates and not component series are reported.

With regard to official reserves, the majority of IMF members follow accepted international practices in reporting their data for dissemination in the Fund’s main statistical publications, the IFS and the monthly online Balance of Payments Statistics database. BPM6 contains a number of clarifications for the reporting of reserve assets. Box 2, Changes with BPM6, includes clarifications on the currency composition of the official reserves. In addition, SDDS subscribers and SDDS Plus adherents disseminate data in the Data Template on International Reserves and Foreign Currency Liquidity. The updated International Reserves and Foreign Currency Liquidity: Guidelines for a Data Template (Guidelines) are consistent with BPM6.

Changes with BPM6

The Balance of Payments and International Investment Position Manual, sixth edition (BPM6) introduced a number of changes to data underlying the variables included in the quota formula. The IFS (and the on-line Balance of Payments Statistics database) began publishing data using the BPM6 presentation exclusively starting in August 2012. Full implementation of BPM6 by IMF member countries will continue over the next years (165 members reported their own BPM6 data as of end-January 2018), and as a result, there will be a mixture of BPM5 and BPM6 reporting that will affect future quota database updates. The main changes affecting quota data are:

  • Treatment of goods for processing: BPM6 captures in trade flows (recorded under services) only the explicit fees that are paid to the goods processor, rather than the full value of the goods entering and leaving the processing economy, in the case where the goods do not change ownership. This change will particularly affect those countries for which goods for processing are important in its trade; and will take longer for some countries to implement since it requires additional data collection. This modification will reduce openness for those countries where goods for processing is a significant component of their trade; variability could also be affected, especially, if revisions do not cover the full 13-year period used to estimate this variable. This change reduces the “double counting” of trade, which has been a concern in previous discussions on quota variables.

  • Migrant transfers: under BPM6, the personal effects, financial assets, and liabilities of persons changing residence are no longer covered by a capital transfer.

  • IIP coverage: The IIP is more prominent in BPM6 than in BPM5. Partly as a result of this increase in emphasis, efforts are underway to strengthen coverage of the IIP, which has been considered as a measure of financial openness. Official coverage has been improving in recent years and it is expected to continue (as of end-January 2018, 147 members reported IIP in BPM6 format).

  • Recording of foreign direct investment (FDI): FDI is included in gross financial flows and the IIP data, which have been discussed as alternative measures of financial openness in previous quota papers. Under the BPM5 methodology, some components of the direct investment account are netted out. Starting with BPM6, direct investment components are shown on a gross basis. All of the components of FDI needed to construct the BPM5 measure of FDI are collected separately (as standard components) under BPM6, and so this is a presentational change and not a change in data collection.

  • SDR allocations: The inclusion of the 2009 SDR allocations as liabilities in the financial account, and the inclusion of an equal size increase in SDR holdings as assets in the financial account, impacted the calculation of gross capital (financial) flows. Similarly, (cumulative) SDR allocations are shown in the IIP as liabilities. BPM6 did not introduce changes in the treatment of SDR holdings in the IIP; SDR holdings were recorded in the IIP under both BPM5 and BPM6. Unlike the other changes noted above, STA implemented this particular change effective with reporting of data for 2009, ensuring that the new SDR allocations implemented in that year would be recorded in all member country data consistent with the latest approved methodology. STA has traditionally used the IMF’s own data (provided by FIN) for recording positions and transactions related to SDRs in IFS.

  • Reserve assets: In the case where an economy has risk exposures that are closely related to its neighbor (perhaps due to substantial trade ties), and where it holds assets denominated in the currency of its neighbor, BPM6 clarifies that these holdings should be excluded from reserves if that currency is not convertible. Under BPM5, it was less clear whether such holdings could be included in reserves.

  • Treatment of Special Purpose Entities (SPEs): Some countries, i.e., the Netherlands, Cyprus, and Malta, have recently experienced significant revisions to their BOP and IIP data as a result of incorporating the SPEs in the BPM6 estimates. Generally, the SPEs are located in either important offshore financial centers or involved in non-financial sector activities, or both. In the external sector, the SPEs are treated as resident companies of the host countries, generally owned by multinational enterprise groups mostly active abroad and having weak ties with the host economy. In the financial sector, for example, these companies act as intra-group financial intermediaries, channeling funds whose volume and direction are regulated by the parent companies. The most affected entries in the external sector are direct and portfolio investment (flows and stocks), as well as the related investment income.

15. The data source breakdown for the period 2004–16 is as follows. Among the 178 members reporting data for IFS, 145 members’ data are derived entirely from IFS reported data, 30 members’ data are derived from a combination of IFS and WEO estimates, two members’ data are derived from IFS and WEO but have missing data for some years, and one member’s data are derived from IFS reported data and have missing data for the current year (no WEO data available). Among the 11 members not reporting any data to IFS, 8 members’ data are derived entirely from WEO estimates and for one member (San Marino), data are not available neither in IFS nor in WEO.

16. The data source breakdown for the period 2012–16 is as follows. Among the 176 members reporting data for IFS, 158 members’ data are derived entirely from IFS reported data, and 18 members’ data are obtained from a combination of IFS and WEO estimates. Among the 13 members not reporting any data for IFS, 10 members’ data are derived entirely from WEO estimates, two members (San Marino and Syrian Arab Republic) have neither IFS nor WEO data available, and for one member (Somalia) data are derived from WEO but some observations are still missing.

17. The following subsections describe for each of the data categories the general procedures employed by STA to construct the required database for the quota calculations.

Goods and Services Transactions

18. Data reported by members and maintained in IFS were used for each country. Where there were data gaps prior to or after the latest year of reporting to STA, estimates were made by applying the growth rates derived from the WEO to the closest reported data (credits and debits). For countries where no data were reported to STA, available WEO data were used. For China, P.R., Hong Kong, SAR, and Macao, SAR, goods data were adjusted for trade among the mainland, Hong Kong, SAR, and Macau, SAR based on the Direction of Trade database (details in Box 3).11

Primary Income, Secondary Income, and the Capital Account

19. Data on primary income and secondary income reported by members and maintained in IFS were used for each country. Where there were data gaps, estimates were derived using WEO data series. The adjustment procedure consisted of the following: (1) if available, WEO gross flows are used; (2) if not, and the gap was in the leading year(s) of the series (2004), then WEO net value was inserted for the leading year(s) where data were missing, either as credits if WEO showed a net credit balance or as debits if a net debit balance was shown in WEO; (3) if the gap was after a reported observation, then the WEO net value was used for each year; also, the latest reported debits and credits were carried forward; however, to assure that gross debits and credits are consistent with the net values shown, a positive adjustment is made to the carry forward credit when the net WEO value shows a higher net credit, or to the carry forward debit when the net WEO value shows a higher net debit.

20. The primary source for data on the capital account as per BPM6 is the IFS data provided by member countries. When no data are reported for IFS, the WEO gross flows were used, if available. If not, the WEO net capital account value, depending on its sign, was used to derive an estimate. In a few cases, countries reported to IFS only “net” capital account data. When a country reports to IFS only a net value for the capital account, that full value is allocated to credits (if positive) or debits (if negative). Countries reporting under BPM6 have eliminated migrants’ transfer from their capital accounts (according to BPM6, a change of ownership is no longer imputed).

Net Capital Flows12

21. The primary source for data on net capital flows is the IFS financial account data provided by member countries to STA. When no data are reported for IFS, WEO values are used to fill in the gaps, to the extent possible. While the IFS provides the financial account balance in the analytical presentation (i.e., net (standard) financial flows excluding the group consisting of (i) reserve assets, (ii) exceptional financing, and (iii) the net credit and loans from the IMF), the new WEO template no longer covers some of these components. Data on net credit and loans from the IMF for all countries were sourced from the IFS database, while the exceptional financing data for the missing data entry points were obtained from WEO and some from the desks, to the extent possible.

Direction of Trade Statistics

The Direction of Trade Statistics (DOTS) presents the value of merchandise exports and imports disaggregated according to a country’s primary trading partners. DOTS comprises official data of trade by geographical breakdown reported by country authorities to the IMF, or collected by the IMF from official sources, such as the United Nations COMTRADE and the EUROSTAT COMEXT databases. Official data are complemented with estimated data for individual countries that report (or publish) trade statistics with a delay, or do not publish trade statistics by partner country at all. The estimation of missing trade statistics based on counterpart trade and other information is a distinctive feature of DOTS. DOTS covers all IMF member countries, some non-member countries, the world, and major areas. Monthly and quarterly data are available starting 1960. Annual data are available starting 1947.

Data reported to DOTS follow the concepts and definitions of the United Nations’ International Merchandise Trade Statistics (IMTS 2010), which provides the conceptual framework and guidance for recording physical movements of goods between countries and areas. The term “merchandise” has a meaning that is close to the term “goods”.

Following the IMTS 2010 methodology, exports are recorded on free-on-board (FOB) basis and imports are recorded on cost, insurance, and freight (CIF) basis. Imports include shipping and insurance costs up to the border of the importing country, while exports exclude these costs. In addition to differences in insurance and freight costs, there are several complications that can cause inconsistencies between exports to a partner and the partner’s recorded imports FOB, or between imports FOB from a partner and the partner’s recorded exports. The main reasons for inconsistent statistics on destination and origin for a given shipment are differences in classification, time of recording, exchange rates movements, shipment and reexport through intermediate points (e.g., Rotterdam, Hong Kong, SAR), coverage, and processing errors. These asymmetries are not reconciled in the DOTS dataset. Official data by partner countries are published as reported.

On March 1, 2017, the IMF has updated its DOTS dataset. New series of DOTS include improved monthly estimates for non-reporting countries and revised data for some reporting countries to realign with national sources.

The previous DOTS estimates were based on a methodology – developed in the early 1990s – based on partner country data, total trade, regional projections from the IMF World Economic Outlook, and trend extrapolations. The old methodology had several shortcomings, which led to time-series breaks in the estimated bilateral trade series and an excessive use of projections and trend extrapolations with little or no connection with actual trade developments.

The new DOTS methodology relies on an expanded set of official sources of bilateral trade statistics; a new estimation procedure to impute missing observations of bilateral trade statistics; and other improvements, such as a streamlined list of partner countries and a refined assumption for converting imports CIF into exports FOB (and vice versa).

Exports and imports of non-reporting countries are estimated based on the assumption of symmetry with the values of imports and exports, respectively, declared by their counterpart countries. A CIF/FOB adjustment of 6 percent is used for non-reporting countries. The value of exports is equal to the value of imports from a partner divided by 1.06; the value of imports is equal to the value of exports multiplied by 1.06.

Official Reserves

22. Position data on official reserves—comprising monetary gold, SDR holdings, reserve position in the Fund, and foreign exchange holdings—were obtained from IFS.13 Monetary gold was valued at SDR 35 per fine troy ounce. In deriving annual average holdings of official reserves for 2016, for each reserve component, the average data for each of the 12 months of 2016 were summed and then divided by 12. SDR holdings and reserve position in the Fund are based on Fund accounts and data are available for the entire period. However, data for foreign exchange is not always reported for the entire 12-month period. If this is the case, the number of months for which data were reported was used to calculate the average. If a country did not report its foreign exchange and/or monetary gold holdings data to STA for publication in IFS, staff reports are used to gap fill this information (see also missing data series, below).14

Conversion to SDRs

23. The balance of payments and the GDP data series in U.S. dollars were converted to SDRs using period-average exchange rates. The reserves data are either originally available in SDRs, or converted to SDRs using monthly end-of-period exchange rates for every data point in the 12-month period.

C. Missing Data Series and Data Adjustments

Missing Data in IFS and WEO

24. Syrian Arab Republic stopped reporting its data as of 2010, and most data series had missing data from 2011 onwards (GDP, PPP GDP, current receipts and payments, and net capital flows). In those cases, the gaps in the database were filled by repeating the last observation (2010, in SDRs) for a period of five years, through 2015. The 2016 data point remained blank, and quota variable calculations were based on a shorter time frame. The data on reserves comprises only SDR holdings and reserve position in the Fund in 2016, as foreign exchange and monetary gold data were missing.

25. For Somalia, current receipts and payments data were only available from 2013 onwards, and net capital flows data were missing. To fill data gaps, desk data were used for net capital flows, and 2013 data were repeated backwards for as long as five years, back to 2008 (current receipts and net capital flows) or 2012 (current payments).

26. For San Marino, current receipts, current payments and net capital flows data were not available. Current receipts and current payments gaps were filled with desk data on exports and imports of goods and services for the period 2005–2016. The current receipts for 2004 were set to be equal to the 2005 data point. The gaps in net capital flows data were not filled, so the variability measure for San Marino comes exclusively from current receipts. The 2016 reserves data comprises only SDR holdings and reserve position in the Fund.

27. Montenegro had missing data values for current receipts and net capital flows (2004–2005). Current receipts gaps were filled with desk data and net capital flows were filled by repeating the 2006 observation.

28. Net capital flows data were missing for Marshall Islands (2004) and Tonga (2016), and the gaps were filled with desk data in both cases.

29. Among members that joined the Fund most recently, Nauru data were not available before 2008 and South Sudan data were not available before 2011. In those cases, no gap filling was made in this update, and calculations were based on a shorter time frame.

Data Adjustments

30. GDP data for Bahamas and Cameroon (market and PPP) were replaced with desk data, to reflect GDP revisions that had taken place in 2017, but were not yet incorporated in the IFS data. For Venezuela, the IFS data for market GDP was replaced with WEO data. Venezuela’s nominal GDP in national currency was the same in both sources, but distortions in the official exchange rates reported to IFS resulted in grossly inflated market GDP figures in recent years, motivating the change to WEO data.

31. After consultation with country desks, current receipts and payments data for Bahrain (2004–2016), Eritrea (2004–2016), Iraq (2004–2016), Somalia (2013–2016), Tonga (2016), and Tuvalu (2014–2016) were replaced with WEO or desk data.

32. After consultation with country desks, net capital flows data for Bahrain (2004–2016) and Iraq (2004–2016) were replaced with WEO or desk data.

33. For some countries, the IFS reserves data for 2016 had no information on the foreign exchange component. In those cases, whenever possible more accurate reserves data were extracted from WEO or country desk data. The WEO database provided reserves data for Eritrea, Iran, Tuvalu, Uzbekistan and Yemen. Country desk data were used for Kiribati, Marshall Islands, Nauru, Somalia, and Turkmenistan.

Table 1.

Distribution of Quotas and Calculated Quota Shares

(In percent)

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Source: Finance Department.

The “2008 Reform” reflects agreed quotas after the “second round” ad hoc quota increases for 54 members agreed in 2008, following the “first round” ad hoc increases for four members agreed in 2006, including proposed quotas for Kosovo, Tuvalu, South Sudan and Nauru which became members after the 2008 Reform. The “14th Review” includes proposed quota increases for South Sudan and Nauru, which became members on April 18, 2012 and April 12, 2016, respectively.

Based on the current quota formula: CQS = (0.50*GDP + 0.30*Openness + 0.15*Variability + 0.05*Reserves)A0.95, with a 60/40 blend of MERand PPP GDP. Years in parenthesis indicate the end period for the data used in the calculations. The “2008 Reform” CQS excludes Kosovo, Tuvalu, South Sudan and Nauru, which were not members at the time of the 2008 Reform. The “14th Review” CQS excludes South Sudan and Nauru, which were not members at the time of the 14th Review.

Including China, P.R., Hong Kong SAR, and Macao SAR

Table 2.

Updated Quota Formula Variables—Shares

(In percent)

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Source: Finance Department.

GDP is measured in a 3-year average.

GDP blend uses 60 percent MER GDP shares and 40 percent PPP GDP shares.

Openness is the sum of current receipts and current payments (goods, services, primary income, secondary income and capital account), measured in a 5-year average.

Variability of current receipts minus net capital flows (due to change in sign convention in BPM6), measured as the standard deviation from a centered 3-year trend over a 13-year period.

Official reserves (foreign exchange, SDR holdings, reserve position in the Fund, and monetary gold), measured in a 12-month average.

Including China, P.R., Hong Kong SAR, and Macao SAR