quotas data update and simulations · 2016-09-16 · quotas—data update and simulations—...
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© 2016 International Monetary Fund
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
IMF staff regularly produces papers proposing new IMF policies, exploring options for
reform, or reviewing existing IMF policies and operations. The following documents have
been separately released:
The Staff Report Quotas—Data Update and Simulations, prepared by IMF staff and
completed on August 9, 2016.
Staff Supplement on Quotas—Data Update and Simulations—Statistical Appendix,
completed on August 10, 2016.
The IMF’s transparency policy allows for the deletion of market-sensitive information and
premature disclosure of the authorities’ policy intentions in published staff reports and
other documents.
Electronic copies of IMF Policy Papers
are available to the public from
http://www.imf.org/external/pp/ppindex.aspx
International Monetary Fund
Washington, D.C.
September 2016
These documents were prepared by IMF staff and were presented to the Executive
Board in an informal session on September 9, 2016. Such informal sessions are used to
brief Executive Directors on policy issues, and to receive feedback from them. No
decisions are taken at these informal sessions. The views expressed in this paper are
those of the IMF staff and do not necessarily present the views of the IMF’s Executive
Board.
http://www.imf.org/external/pp/ppindex.aspx
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QUOTAS—DATA UPDATE AND SIMULATIONS—
STATISTICAL APPENDIX
Approved By Andrew Tweedie and
Louis Marc Ducharme
Prepared by the Finance and Statistics Departments
The FIN team comprised Heikki Hatanpaa, Ruifeng Zhang,
Ezgi Ozturk, Maria Albino-War, Rina Bhattacharya, Sergio
Rodriguez-Apolinar, and Diana Mikhail. The STA team
comprised He Qi, René Piché, Silvia Matei, Lisbeth Rivas,
Venkateswarlu Josyula, Aimee Cheung Kai Suet, Raja
Hettiarachchi, Ercument Tulun, Kenneth Kirkley, Martin
Cameron McConagha, Selin Subasi, and Charles Kouame.
CONTENTS
SELECTION OF THE DATABASE AND OTHER ISSUES ____________________________ 3
A. Required Data ___________________________________________________________________ 3
B. Selection of the Database ________________________________________________________ 4
C. Data Availability and Adjustments _______________________________________________ 8
BOXES
A1. Methodological Issues__________________________________________________________ 6
A2. Changes with BPM6 ___________________________________________________________ 12
TABLES
A1. Distribution of Quotas and Calculated Quotas—by Member _________________ 14
A2. Distribution of Quotas and Updated Quota Variables—by Member __________ 20
A3. Updated GDP Blend Variable—by Member ___________________________________ 26
A4. Contributions to Changes in Calculated Quota Shares (CQS)—by Member ___ 32
A5. Out-of-Lineness—by Member ________________________________________________ 38
A6. Distribution of Quotas and Updated Quota Variables—by Member __________ 44
A7. Openness Shares Under Caps and Excluding Intra Currency Union Trade—by
Member _________________________________________________________________ _____50
A8. Illustrative Calculations - Current GDP and Openness Measures, and Dropping
Variability—by Member ______________________________________________________ 56
A9. Illustrative Calculations - Current Openness Measure, Dropping Variability,
Weight Split Evenly Between GDP and Openness, and Different Combinations
of GDP Blend—by Member ___________________________________________________ 62
August 10, 2016
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QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
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A10. Illustrative Calculations - Current Openness Measure, Dropping Variability,
Weight Split Between GDP (2/3) and Openness (1/3), and Different
Combinations of GDP Blend—by Member ____________________________________ 68
A11. Illustrative Calculations - Current Openness Measure, Dropping Variability, All
Weight to GDP, and Different Combinations of GDP Blend—by Member ______ 74
A12. Illustrative Calculations - Current Openness Measure, Dropping Variability,
Weight of Openness Reduced to 0.25, and Different Combinations of GDP
Blend—by Member ___________________________________________________________ 80
A13. Illustrative Calculations - Current GDP blend, Dropping Variability, Weight
Split Evenly Between GDP and Openness, and Different Openness Measures—
by Member _____________________________________________________________________ 86
A14. Illustrative Calculations - Current GDP blend, Dropping Variability, Weight
Split Between GDP (2/3) and Openness (1/3), and Different Openness
Measures—by Member ________________________________________________________ 92
A15. Illustrative Calculations - Current GDP blend, Dropping Variability, All Weight
to GDP, and Different Openness Measures—by Member ______________________ 98
A16. Illustrative Calculations - Current GDP and Openness Measures, Dropping
Variability, and Higher Compression (0.925)—by Member ____________________ 104
A17. Illustrative Calculations - Current GDP and Openness Measures, Dropping
Variability, and Lower Compression (0.975)—by Member _____________________ 110
A18. Illustration of Allocation Mechanisms: Current Formula—by Member ________ 116
A19. Illustration of Allocation Mechanisms: Formula 1.2—by Member _____________ 122
A20. Illustration of Allocation Mechanisms: Formula 1.3—by Member _____________ 128
A21. Illustration of Allocation Mechanisms: Formula 3.2.c—by Member ___________ 134
A22. Illustration of Allocation Mechanisms: Formula 3.3.c—by Member ___________ 140
A23. Illustration of Allocation Mechanisms: Formula 1.3, Includes 5 percent Ad Hoc
Distribution based on Voluntary Financial Contributions—by Member _______ 146
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QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 3
SELECTION OF THE DATABASE AND OTHER ISSUES1
1. This appendix discusses the required data, the selection of the database, and the derivation
of the data series used for the quota calculations.
A. Required Data
2. The quota database requires the following data for all 1892 member countries (converted
into SDRs as the common denominator):3
GDP at market prices for three years (2012–14).
PPP GDP (GDP at purchasing power parity) for three years (2012–14). 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)4 for
13 years (2002–14). Current receipts are defined as the credit component of all economic
transactions between resident and nonresident entities other than those relating to financial
transactions.
Current payments (goods, services, primary income, and secondary income, and capital
account)5 for five years (2010–14). 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 (2002–14). 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 measures net financial flows.6
Official reserves, defined as the sum of average over the 12 months of 2014 of foreign exchange,
SDR holdings, reserve position in the Fund, and monetary gold valued at SDR 35 per fine troy
ounce.
1 Prepared jointly by FIN and STA. GDP and balance of payments data for the updated quota calculations were compiled by STA in coordination with FIN. The simulation results reported in Tables A8-A23 were prepared by FIN. 2 Nauru became the 189th member of the IMF on April 12, 2016.
3 The cutoff date for both IFS and WEO data was January 31, 2016; in the case of the latter, the cutoff date implied
the use of the Fall 2015 WEO database.
4 The balance of payments data are based on the Balance of Payments and International Investment Position Manual,
sixth edition (BPM6). To help ensure comparability with previous quota calculations, both current and capital
transfers—excluding exceptional financing, to the extent possible—are included here in current receipts.
5 Ibid; exceptional financing transactions are only on the credit side of the current and capital accounts.
6 The variable is referred to as “net capital flows” to maintain continuity with the term used in previous quota
calculations.
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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. 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.
5. Along the same lines, transactions in both reserve assets and reserve-related liabilities
should be excluded from net financial flows (referred to as “net capital flows”) so that only
autonomous, and not financing, flows are captured. 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. Although reserve-related liabilities are not a standard component
in BPM6, short-term reserve-related liabilities on a remaining maturity basis are a memorandum
item to the international investment position.
B. Selection of the Database
6. The database containing the variables used in the quota calculations would ideally have the
following attributes: it should be comprehensive; i.e., contain all required data—compiled in line
with internationally accepted concepts and definitions—for all members; the data would be from
official sources (central banks and national statistical agencies); and the data would be comparable
(consistent and coherent) across time and countries. This would ensure similar treatment for all
countries’ data and facilitate the comparability of results in a transparent manner.
7. As in past quota updates, the main source of data used in the quota calculations was the
Fund’s central macroeconomic database of country, regional, and global statistics. STA manages this
database (using a data processing system known as DMXplus) for international statistical
cooperation and publication purposes, and to support the Fund’s surveillance and use of Fund
resources functions.7 The database, which encompasses a number of component databases,
embodies, to the extent possible, the application of international statistical methodologies for the
7 In this paper, the data drawn from the DMXplus are referred to as the IFS database, following the practice in past
quota review papers.
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QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 5
compilation of economic and financial data. Gap-filling and aggregations are performed in the EcOS
data management system.
8. 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 BPM68 and the 1993/2008 System
of National Accounts (1993/2008 SNA). STA makes an effort to compile these data into long time
series that are consistent across time and countries. However, data gaps exist. For instance, there are
some missing data for GDP and current and financial account transactions for some countries for
some years.
9. Missing observations were largely supplemented using the WEO database; starting in June
2014, desks have been required to submit their balance of payments (BOP) and international
investment position (IIP) data under the BPM6 template introduced by the October 2014 WEO9
publication, which was used to gap-fill the missing observations. For country desks whose
authorities continue to report in BPM5 framework, a conversion matrix was used10. 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). To the extent possible, STA collected
additional information from 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 IFSdata where, if a country did
not report data for goods for processing or reverse investment, no imputations were made.
10. At the outset of the development of the database for the quota calculations, STA was aware
that for some member countries there were large differences between the IFS and the WEO data
sets. These data discrepancies between the two data sources may also have been influenced by the
varying institutional, legal, and accounting contexts of data compilation across member countries
(Boxes A1 and A2).
8 Starting with the August 2012 IFS, STA publishes data using the BPM6 presentation. Therefore, starting with the
2013 quota round, in consultation between STA and countries, data were converted to a BPM6 presentation using, in
most cases, generic conversion rules developed by STA for countries that continue to report on a BPM5 basis.
9 However, IIP data were reported for WEO publication starting with the April 2015 WEO.
10 The conversion matrix was developed by the WEO team in collaboration with STA to assist desks with the
conversion of BPM5 series to BPM6.
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QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
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Box A1. Methodological Issues
With regard to GDP data, the 1993 SNA extended the scope of GDP slightly, adding production of goods for
own final use to output and mineral exploration, computer software, and artistic originals to capital
formation. This has resulted in an increase in reported GDP levels. Most IMF members have adopted the
1993 SNA for reporting GDP data to the IFS with some of them having revised historical data. By now, the
size of data inconsistencies across countries due to the revisions related to the 1993 SNA 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).
Further changes introduced by the System of National Accounts 2008 (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 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. Where they are relevant, these changes are expected to increase GDP.
Some countries, e.g., Australia, Canada, European Union members, USA, Brazil, India, Indonesia, Mexico,
Philippines, South Africa, Uganda, and Kenya have already moved to the 2008 SNA, others are in the process
of implementing it.
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
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INTERNATIONAL MONETARY FUND 7
Box A1. Methodological Issues (concluded)
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 A2, 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 and available on
the IMF website at http://www.imf.org/external/np/sta/ir/IRProcessWeb/dataguide.htm.
http://www.imf.org/external/np/sta/ir/IRProcessWeb/pdf/guide2013.pdfhttp://www.imf.org/external/np/sta/ir/IRProcessWeb/pdf/guide2013.pdfhttp://www.imf.org/external/np/sta/ir/IRProcessWeb/dataguide.htm
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C. Data Availability and Adjustments
11. The number of countries reporting their BOP data under BPM6 has been increasing, 120
Fund members now report their own 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 A2,
Changes with BPM6). In order to compile the current receipts and payments and net capital flows,
data sets were prepared as defined above. Where members reported balance of payments statistics
to STA, the data stored in the IFS database were used as reported. Of the 189 members, the number
reporting data to IFS for at least some of the years are as follows: 176 for the period 2002–14; and
174 for the period 2010–14. 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.11 For
members where neither IFS nor WEO data were available, FIN obtained data from staff reports, and
country desks.
12. The data source breakdown for the period 2002–14 is as follows: of the 176 members
reporting data for IFS—126 are derived entirely from IFS reported data, 47 are derived from a
combination of IFS and WEO estimates, 2 are derived from IFS and WEO but have missing data for
some years, and 1 is derived from IFS reported data and has missing data for the current year (no
WEO data available); for the 12 members not reporting any data to IFS—9 are derived entirely from
WEO estimates, 1 is derived from WEO estimates but has missing data for some years, and 2 (San
Marino and Somalia) have neither IFS nor WEO data available.
13. The data source breakdown for the period 2010–14 is as follows: of the 174 members
reporting data for IFS—139 are derived entirely from IFS reported data, 34 are obtained from a
combination of IFS and WEO estimates, and 1 is derived from IFS reported data and has missing
data for the current year (no WEO data available); for the 14 members not reporting any data for
IFS—11 are derived entirely from WEO estimates, 2 (San Marino and Somalia) have neither IFS nor
WEO data available, and 1 is derived from WEO estimates but has missing data for some years.
14. The following sections 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
15. 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.,
11 The methods used to fill gaps were, in principle, largely similar to those used for the purpose of publishing World
and Regional Tables in the Balance of Payments Statistics Yearbook (BOPSY), and were used in External Review of
Quota Formulas—Quantification (4/12/2001).
(continued)
http://www.imf.org/external/np/tre/quota/2001/eng/erqfq.htmhttp://www.imf.org/external/np/tre/quota/2001/eng/erqfq.htm
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INTERNATIONAL MONETARY FUND 9
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.12
Primary income, secondary income, and the capital account
16. 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 (2002), 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.
17. 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 flows13
18. 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.
12 Balance of payments (BOP) trade in goods data are reported in IFS on a BPM6 basis and do not include goods for
processing (GFP), while the Direction of Trade Statistics (DoT) includes all trade in goods. While staff was able to
adjust for this factor in previous databases, this is no longer possible with the move to BPM6 reporting. As such,
using DoT to adjust the BPM6 data for intra-trade may lead to an over-estimation of the intra-trade flows. Based on
data available for the quota database updated through 2011, any such over-adjustment is likely to be small.
13 The term “net capital flows” refers to transactions in the financial account.
(continued)
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Official reserves
19. Position data on official reserves—comprising monetary gold, SDR holdings, reserve position
in the Fund, and foreign exchange holdings—were obtained from IFS.14 Monetary gold was valued
at SDR 35 per fine troy ounce. In deriving annual average holdings of official reserves for 2014, for
each reserve component, the data for the 12 months of 2014 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 may not be 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 (please
see missing data series, below).
GDP
20. The IFS and WEO databases provided GDP data for 186 members only (all Fund members
except Somalia, Syrian Arab Republic, and Nauru, which became the 189th member of the IMF on
April 12, 2016). The IFS database is the source of data for -131 members, WEO data were used for 18
members, and WEO growth rates were applied to the latest IFS data to estimate missing data for
3715 members. When IFS data were missing for a long period of time (i.e., most recent data are for
2009 or earlier), these have been directly replaced by WEO estimates, otherwise WEO growth rates
were applied to the last available IFS observations.
PPP GDP
21. The PPP-based GDP data reflect the new ICP rates and were derived using the WEO
methodology for 186 countries (all Fund members except Nauru, Somalia, and 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 States16 and then
converting it into SDR units, using the SDR-USD exchange rate. The PPP price indexes are based on
the data from the International Comparison Program (ICP) for 2011 that were released in April
2014.17 These data were then extended forward (to 2014) by using the growth in relative GDP
14 Consistent with the treatment of reserves for the 2001 ad hoc quota increase for China, P.R., the reserves of Hong
Kong, SAR and Macao, SAR are not included for quota calculations.
15 This includes countries which did not have IFS data for the reference three years but supplied data for the years
immediately preceding the reference period. For comparison, WEO growth rates were applied in the case of 37
countries in the database extending through 2014 (versus 35 in the previous database update).
16 The choice of the numéraire country is arbitrary and does not affect the calculations, since PPP price indexes are
adjusted to be transitive across countries.
17 See Purchasing Power Parities and Real Expenditures of World Economies – Summary of Results and Findings of the
2011 International Comparison Program, 2014.
(continued)
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INTERNATIONAL MONETARY FUND 11
deflators (the deflator of a country divided by the deflator of the United States).18 The data for
Somalia were estimated using its share in global GDP based on 11th Quota Review data (see para
23). For Syrian Arab Republic, the 2010 observation was repeated for 2011-14. For China, the PPP
GDP only includes China, P.R., and Hong Kong SAR.
Conversion to SDRs
22. The balance of payments and the GDP data series in U.S. dollars were converted to SDRs
using period-average exchange rates.
Missing data series
23. Data that were missing from IFS and WEO were obtained almost entirely from recent staff
reports. Previously, no series were available for Somalia and data from the 11th Quota Review were
being used. For 2016 update, all series of were taken from 2015 Somalia Article IV document, which
provided data only for 2013 and 2014. For the years before 2013, the data were assumed to be
equal to 2013 values. Syrian Arab Republic stopped reporting its data as of 2010; the 2010
observation has been repeated ever since. For San Marino (2002-14) and South Sudan (2002-10), all
variables except GDP and official reserves were derived from staff reports.
24. Countries for which only official reserves data were derived from staff reports include Eritrea,
Ethiopia, Guinea,19 Iran, Kiribati, Tuvalu, and Uzbekistan. For Myanmar, reserves data were gap-filled
using the area department data.
25. Gaps in data for current receipts for the following countries were filled using staff reports:
South Sudan (2005-10), Iraq (2002-04), and Montenegro (2002-5).
26. Gaps in data for net capital flows for Syrian Arab Republic (2002-06) and Marshall Islands
(2002-04) were filled using staff reports or previously reported data. For Brunei Darussalam financial
account data from the desk better reflected latest updates and were used instead of IFS data.
27. For Egypt, GDP data for 2013 and 2014 were gap-filled using area department data. For
Thailand, GDP data from the WEO October 2015 database are more updated and were used instead
of IFS data.
18 The computation of the PPP GDP data was performed by the Research Department. The data for the GDP in local
currency and the GDP deflators were obtained from the October 2015 WEO, consistent with the January 31, 2016
data cutoff date for the quota data.
19 Guinea reported foreign exchange reserves to STA for January-April 2012 only and therefore monthly desk data
were used.
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Box A2. 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 (120 members reported their own BPM6 data as of end- January 2016), 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 to do so (as of end-January 2016, 108 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.
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 13
Box A2. Changes with BPM6 (concluded)
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.
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
14 INTERNATIONAL MONETARY FUND
Tab
le A
1. D
istr
ibu
tio
n o
f Q
uo
tas
an
d C
alc
ula
ted
Qu
ota
s—b
y M
em
ber
(In
perc
en
t)
2008 R
efo
rm 2
/ 1
4th
Genera
l
Revi
ew
3/
2008
Refo
rm 4
/
(2005)
14th
Genera
l
Revi
ew
(2008)
Pre
vio
us
(2013)
Curr
ent
(2014)
United
Sta
tes
17.6
60
17.3
98
18.9
91
16.9
87
14.5
35
14.3
23
Jap
an
6.5
52
6.4
61
8.0
32
6.4
93
5.6
30
5.3
04
Chin
a 5
/3.9
94
6.3
90
6.3
90
7.9
17
11.2
59
12.0
24
Germ
any
6.1
07
5.5
83
6.2
27
5.6
78
5.0
78
5.0
58
France
4.5
02
4.2
25
4.0
16
3.7
89
3.3
82
3.2
52
United
Kin
gd
om
4.5
02
4.2
25
4.4
29
4.6
63
3.4
50
3.5
67
Italy
3.3
05
3.1
59
3.3
36
2.9
92
2.5
90
2.4
94
Ind
ia2.4
41
2.7
49
1.9
97
2.4
03
3.0
36
3.0
32
Russ
ia2.4
93
2.7
05
2.0
53
2.9
38
2.7
91
2.7
10
Bra
zil
1.7
82
2.3
15
1.7
25
2.1
53
2.3
31
2.3
34
Canad
a2.6
70
2.3
11
2.5
69
2.3
03
2.1
31
2.0
84
Saud
i A
rab
ia2.9
29
2.0
95
0.8
35
1.3
37
1.7
04
1.6
89
Sp
ain
1.6
87
1.9
99
2.3
04
2.2
36
1.8
92
1.7
93
Mexi
co1.5
20
1.8
68
1.9
70
1.7
93
1.7
34
1.7
35
Neth
erl
and
s2.1
64
1.8
31
1.9
30
1.8
57
1.7
93
2.1
11
Ko
rea, R
ep
ub
lic o
f1.4
11
1.7
99
2.2
45
2.1
08
1.9
58
1.9
62
Aust
ralia
1.3
57
1.3
78
1.3
21
1.3
96
1.5
46
1.4
99
Belg
ium
1.9
31
1.3
44
1.5
04
1.3
24
1.1
78
1.1
33
Sw
itze
rland
1.4
50
1.2
10
1.2
11
1.2
27
1.5
67
1.6
33
Turk
ey
0.6
10
0.9
77
0.9
87
1.1
48
1.1
37
1.1
20
Ind
onesi
a0.8
72
0.9
74
0.9
01
0.9
02
1.2
60
1.2
95
Sw
ed
en
1.0
04
0.9
29
0.9
93
0.9
42
0.9
56
0.9
31
Po
land
0.7
08
0.8
59
0.8
68
0.9
49
0.9
39
0.9
20
Aust
ria
0.8
86
0.8
24
0.9
13
0.8
36
0.7
51
0.7
33
Sin
gap
ore
0.5
90
0.8
16
1.0
31
1.1
95
1.3
25
1.3
10
No
rway
0.7
90
0.7
87
0.8
10
0.8
12
0.7
84
0.7
64
Venezu
ela
, R
.B. d
e1.1
15
0.7
80
0.4
28
0.4
84
0.4
73
0.4
70
Mala
ysia
0.7
44
0.7
62
0.8
59
0.7
92
0.8
10
0.7
84
Iran, I.R
. o
f0.6
28
0.7
48
0.5
94
0.6
58
0.7
91
0.7
64
Irela
nd
0.5
27
0.7
23
1.1
73
1.0
77
0.7
38
0.7
41
Denm
ark
0.7
93
0.7
21
0.8
53
0.7
31
0.6
07
0.5
84
Thaila
nd
0.6
04
0.6
73
0.8
36
0.7
89
0.9
84
0.9
87
Arg
entina
0.8
88
0.6
68
0.5
83
0.5
97
0.6
81
0.6
31
So
uth
Afr
ica
0.7
83
0.6
40
0.5
89
0.5
78
0.5
53
0.5
37
Nig
eri
a0.7
35
0.5
15
0.3
37
0.4
77
0.6
52
0.6
66
Quo
ta S
hare
sC
alc
ula
ted
Quo
ta S
hare
s 1/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 15
Tab
le A
1. D
istr
ibu
tio
n o
f Q
uo
tas
an
d C
alc
ula
ted
Qu
ota
s—b
y M
em
ber
(co
nti
nu
ed
)
(In
perc
en
t)
2008 R
efo
rm 2
/ 1
4th
Genera
l
Revi
ew
3/
2008
Refo
rm 4
/
(2005)
14th
Genera
l
Revi
ew
(2008)
Pre
vio
us
(2013)
Curr
ent
(2014)
Gre
ece
0.4
62
0.5
09
0.6
44
0.5
72
0.3
86
0.3
62
Finla
nd
0.5
30
0.5
05
0.5
45
0.5
13
0.4
37
0.4
24
United
Ara
b E
mir
ate
s0.3
15
0.4
85
0.3
85
0.7
67
0.8
26
0.8
76
Cze
ch R
ep
ub
lic0.4
20
0.4
57
0.5
08
0.5
19
0.4
98
0.4
85
Po
rtug
al
0.4
32
0.4
32
0.4
94
0.4
48
0.4
02
0.3
82
Co
lom
bia
0.3
25
0.4
29
0.3
26
0.3
81
0.4
43
0.4
46
Phili
pp
ines
0.4
27
0.4
28
0.4
65
0.4
30
0.4
65
0.4
67
Eg
ypt
0.3
96
0.4
27
0.3
82
0.4
04
0.5
06
0.4
99
Paki
stan
0.4
33
0.4
26
0.3
56
0.3
42
0.3
73
0.3
72
Ukr
ain
e0.5
75
0.4
22
0.3
38
0.4
22
0.4
33
0.4
19
Alg
eri
a0.5
26
0.4
11
0.3
74
0.4
11
0.4
85
0.4
71
Hung
ary
0.4
35
0.4
07
0.4
33
0.4
07
0.4
24
0.4
10
Kuw
ait
0.5
79
0.4
05
0.2
57
0.3
15
0.3
38
0.3
34
Isra
el
0.4
45
0.4
03
0.4
71
0.4
08
0.4
25
0.4
24
Ro
mania
0.4
32
0.3
80
0.3
02
0.3
80
0.3
86
0.3
83
Chile
0.3
59
0.3
66
0.3
50
0.3
77
0.4
49
0.4
38
Iraq
0.4
98
0.3
49
0.2
25
0.2
67
0.4
06
0.4
08
Lib
ya0.4
71
0.3
30
0.2
15
0.2
52
0.2
86
0.2
62
Peru
0.2
68
0.2
80
0.2
41
0.2
70
0.3
22
0.3
20
Luxe
mb
ourg
0.1
76
0.2
77
0.6
24
0.5
03
0.6
30
0.6
52
New
Zeala
nd
0.3
75
0.2
62
0.2
63
0.2
62
0.2
34
0.2
40
Kaza
khst
an
0.1
79
0.2
43
0.1
99
0.3
28
0.3
77
0.3
79
Vie
tnam
0.1
93
0.2
42
0.2
30
0.3
03
0.3
92
0.4
12
Syr
ian A
rab
Rep
ub
lic0.1
45
0.2
33
0.1
65
0.2
08
0.1
92
0.1
82
Bang
lad
esh
0.2
24
0.2
24
0.1
73
0.1
69
0.2
41
0.2
59
Co
ng
o, D
em
. R
ep
. o
f0.2
23
0.2
23
0.0
28
0.0
35
0.0
88
0.0
83
Slo
vak
Rep
ub
lic0.1
79
0.2
10
0.2
08
0.2
61
0.2
63
0.2
65
Zam
bia
0.2
05
0.2
05
0.0
34
0.0
39
0.0
48
0.0
51
Bulg
ari
a0.2
68
0.1
88
0.1
37
0.1
64
0.1
62
0.1
63
Mo
rocc
o0.2
47
0.1
87
0.1
86
0.1
85
0.1
90
0.1
93
Ang
ola
0.1
20
0.1
55
0.1
34
0.2
14
0.2
60
0.2
54
Ghana
0.1
55
0.1
55
0.0
50
0.0
50
0.0
81
0.0
80
Qata
r0.1
27
0.1
54
0.1
35
0.1
94
0.3
96
0.4
07
Cro
atia
0.1
53
0.1
50
0.1
54
0.1
50
0.1
24
0.1
16
Zim
bab
we
0.1
48
0.1
48
0.0
20
0.0
16
0.0
32
0.0
29
Quo
ta S
hare
sC
alc
ula
ted
Quo
ta S
hare
s 1/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
16 INTERNATIONAL MONETARY FUND
Tab
le A
1. D
istr
ibu
tio
n o
f Q
uo
tas
an
d C
alc
ula
ted
Qu
ota
s—b
y M
em
ber
(co
nti
nu
ed
)
(In
perc
en
t)
2008 R
efo
rm 2
/ 1
4th
Genera
l
Revi
ew
3/
2008
Refo
rm 4
/
(2005)
14th
Genera
l
Revi
ew
(2008)
Pre
vio
us
(2013)
Curr
ent
(2014)
Ecu
ad
or
0.1
46
0.1
46
0.1
57
0.1
47
0.1
43
0.1
47
Bela
rus
0.1
62
0.1
43
0.1
21
0.1
43
0.1
75
0.1
74
Serb
ia0.1
96
0.1
37
0.0
99
0.1
29
0.1
08
0.1
10
Cô
te d
'Ivo
ire
0.1
36
0.1
36
0.0
61
0.0
56
0.0
58
0.0
62
Leb
ano
n0.1
12
0.1
33
0.1
51
0.1
68
0.1
63
0.1
55
Sud
an
0.1
32
0.1
32
0.0
75
0.0
89
0.1
11
0.0
97
Slo
venia
0.1
15
0.1
23
0.1
32
0.1
36
0.1
23
0.1
17
Sri
Lanka
0.1
73
0.1
21
0.0
90
0.0
89
0.1
15
0.1
19
Uzb
eki
stan
0.1
16
0.1
16
0.0
65
0.0
71
0.1
06
0.1
13
Tunis
ia0.1
20
0.1
14
0.1
17
0.1
14
0.1
14
0.1
10
Om
an
0.0
99
0.1
14
0.1
20
0.1
39
0.1
69
0.1
93
Kenya
0.1
14
0.1
14
0.0
65
0.0
76
0.0
88
0.0
87
Mya
nm
ar
0.1
08
0.1
08
0.0
49
0.0
57
0.1
00
0.1
11
Yem
en
0.1
02
0.1
02
0.1
10
0.1
00
0.0
83
0.0
81
Do
min
ican R
ep
ub
lic0.0
92
0.1
00
0.1
00
0.0
97
0.1
09
0.1
10
Tri
nid
ad
and
To
bag
o0.1
41
0.0
98
0.0
59
0.0
64
0.0
76
0.0
80
Lith
uania
0.0
77
0.0
93
0.1
00
0.1
11
0.1
33
0.1
32
Uru
guay
0.1
29
0.0
90
0.0
73
0.0
77
0.0
86
0.0
84
Guate
mala
0.0
88
0.0
90
0.0
95
0.0
86
0.0
90
0.0
89
Tanza
nia
0.0
83
0.0
83
0.0
44
0.0
46
0.0
73
0.0
83
Bahra
in0.0
74
0.0
83
0.1
00
0.0
98
0.0
88
0.0
87
Aze
rbaija
n0.0
67
0.0
82
0.0
51
0.0
86
0.1
36
0.1
37
Jam
aic
a0.1
15
0.0
80
0.0
53
0.0
47
0.0
37
0.0
36
Panam
a0.0
87
0.0
79
0.0
65
0.0
79
0.0
89
0.0
99
Co
sta R
ica
0.0
78
0.0
77
0.0
83
0.0
77
0.0
72
0.0
75
Ug
and
a0.0
76
0.0
76
0.0
35
0.0
55
0.0
42
0.0
43
Jord
an
0.0
71
0.0
72
0.0
73
0.0
73
0.0
84
0.0
89
Latv
ia0.0
60
0.0
70
0.0
60
0.0
86
0.0
77
0.0
74
Afg
hanis
tan
0.0
68
0.0
68
0.0
38
0.0
41
0.0
56
0.0
84
Seneg
al
0.0
68
0.0
68
0.0
32
0.0
32
0.0
36
0.0
36
Icela
nd
0.0
49
0.0
67
0.0
43
0.1
00
0.1
26
0.1
16
Cyp
rus
0.0
66
0.0
64
0.0
69
0.0
65
0.0
55
0.0
73
Bru
nei
0.0
90
0.0
63
0.0
41
0.0
42
0.0
46
0.0
43
Eth
iop
ia0.0
56
0.0
63
0.0
47
0.0
54
0.0
75
0.0
81
El Salv
ad
or
0.0
72
0.0
60
0.0
68
0.0
60
0.0
50
0.0
49
Quo
ta S
hare
sC
alc
ula
ted
Quo
ta S
hare
s 1/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 17
Tab
le A
1. D
istr
ibu
tio
n o
f Q
uo
tas
an
d C
alc
ula
ted
Qu
ota
s—b
y M
em
ber
(co
nti
nu
ed
)
(In
perc
en
t)
2008 R
efo
rm 2
/ 1
4th
Genera
l
Revi
ew
3/
2008
Refo
rm 4
/
(2005)
14th
Genera
l
Revi
ew
(2008)
Pre
vio
us
(2013)
Curr
ent
(2014)
Cam
ero
on
0.0
78
0.0
58
0.0
63
0.0
58
0.0
49
0.0
49
Bo
snia
& H
erz
eg
ovi
na
0.0
71
0.0
56
0.0
56
0.0
56
0.0
44
0.0
43
Pap
ua N
ew
Guin
ea
0.0
55
0.0
55
0.0
26
0.0
30
0.0
29
0.0
31
Nic
ara
gua
0.0
55
0.0
55
0.0
27
0.0
26
0.0
27
0.0
27
Lib
eri
a0.0
54
0.0
54
0.0
08
0.0
13
0.0
10
0.0
10
Ho
nd
ura
s0.0
54
0.0
52
0.0
42
0.0
52
0.0
43
0.0
42
So
uth
Sud
an
0.0
52
0.0
52
n.a
.n.a
.0.0
60
0.0
49
Mad
ag
asc
ar
0.0
51
0.0
51
0.0
24
0.0
26
0.0
23
0.0
22
Est
onia
0.0
39
0.0
51
0.0
60
0.0
71
0.0
70
0.0
71
Bo
livia
0.0
72
0.0
50
0.0
41
0.0
47
0.0
60
0.0
63
Turk
menis
tan
0.0
41
0.0
50
0.0
56
0.0
62
0.0
90
0.0
93
Mo
zam
biq
ue
0.0
48
0.0
48
0.0
27
0.0
31
0.0
36
0.0
38
Gab
on
0.0
65
0.0
45
0.0
39
0.0
40
0.0
41
0.0
40
Guin
ea
0.0
45
0.0
45
0.0
15
0.0
14
0.0
17
0.0
17
Geo
rgia
0.0
63
0.0
44
0.0
25
0.0
30
0.0
35
0.0
35
Sie
rra L
eo
ne
0.0
43
0.0
43
0.0
06
0.0
06
0.0
12
0.0
12
Para
guay
0.0
42
0.0
42
0.0
43
0.0
43
0.0
58
0.0
58
Bo
tsw
ana
0.0
37
0.0
41
0.0
54
0.0
49
0.0
40
0.0
41
Nam
ibia
0.0
57
0.0
40
0.0
23
0.0
23
0.0
28
0.0
30
Mali
0.0
39
0.0
39
0.0
21
0.0
32
0.0
27
0.0
27
Baham
as,
The
0.0
55
0.0
38
0.0
25
0.0
22
0.0
17
0.0
17
Guya
na
0.0
38
0.0
38
0.0
08
0.0
07
0.0
09
0.0
09
Kyr
gyz
Rep
ub
lic0.0
37
0.0
37
0.0
14
0.0
17
0.0
22
0.0
22
Cam
bo
dia
0.0
37
0.0
37
0.0
32
0.0
34
0.0
39
0.0
40
Tajik
ista
n0.0
36
0.0
36
0.0
14
0.0
19
0.0
20
0.0
21
Mo
ldo
va0.0
52
0.0
36
0.0
18
0.0
21
0.0
25
0.0
25
Malta
0.0
43
0.0
35
0.0
39
0.0
35
0.0
63
0.0
67
Haiti
0.0
34
0.0
34
0.0
18
0.0
16
0.0
18
0.0
20
So
malia
0.0
34
0.0
34
0.0
02
0.0
02
0.0
01
0.0
11
Co
ng
o, R
ep
. o
f0.0
35
0.0
34
0.0
29
0.0
34
0.0
51
0.0
50
Rw
and
a0.0
34
0.0
34
0.0
11
0.0
11
0.0
17
0.0
17
Eq
uato
rial G
uin
ea
0.0
22
0.0
33
0.0
38
0.0
52
0.0
58
0.0
54
Nep
al
0.0
30
0.0
33
0.0
33
0.0
32
0.0
41
0.0
42
Buru
nd
i0.0
32
0.0
32
0.0
04
0.0
03
0.0
06
0.0
06
To
go
0.0
31
0.0
31
0.0
11
0.0
10
0.0
14
0.0
13
Quo
ta S
hare
sC
alc
ula
ted
Quo
ta S
hare
s 1/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
18 INTERNATIONAL MONETARY FUND
Tab
le A
1. D
istr
ibu
tio
n o
f Q
uo
tas
an
d C
alc
ula
ted
Qu
ota
s—b
y M
em
ber
(co
nti
nu
ed
)
(In
perc
en
t)
2008 R
efo
rm 2
/ 1
4th
Genera
l
Revi
ew
3/
2008
Refo
rm 4
/
(2005)
14th
Genera
l
Revi
ew
(2008)
Pre
vio
us
(2013)
Curr
ent
(2014)
Mauri
tius
0.0
426
0.0
298
0.0
313
0.0
269
0.0
436
0.0
460
Mace
do
nia
, FY
R0.0
289
0.0
294
0.0
302
0.0
303
0.0
290
0.0
289
Chad
0.0
279
0.0
294
0.0
320
0.0
318
0.0
276
0.0
283
Alb
ania
0.0
252
0.0
292
0.0
308
0.0
306
0.0
306
0.0
294
Mala
wi
0.0
291
0.0
291
0.0
099
0.0
290
0.0
130
0.0
170
Nig
er
0.0
276
0.0
276
0.0
121
0.0
129
0.0
157
0.0
146
Suri
nam
e0.0
386
0.0
270
0.0
098
0.0
104
0.0
124
0.0
121
Arm
enia
0.0
386
0.0
270
0.0
183
0.0
248
0.0
234
0.0
253
Mauri
tania
0.0
270
0.0
270
0.0
091
0.0
111
0.0
147
0.0
149
Benin
0.0
260
0.0
260
0.0
148
0.0
231
0.0
186
0.0
184
Burk
ina F
aso
0.0
252
0.0
252
0.0
190
0.0
188
0.0
215
0.0
221
Centr
al A
fric
an R
ep
.0.0
234
0.0
234
0.0
058
0.0
057
0.0
043
0.0
040
Lao
P.D
.R.
0.0
222
0.0
222
0.0
129
0.0
142
0.0
194
0.0
248
Fiji
0.0
295
0.0
206
0.0
107
0.0
120
0.0
097
0.0
105
Barb
ad
os
0.0
283
0.0
198
0.0
161
0.0
135
0.0
108
0.0
096
Ko
sovo
0.0
247
0.0
173
n.a
.0.0
162
0.0
158
0.0
155
Sw
azi
land
0.0
213
0.0
165
0.0
181
0.0
165
0.0
124
0.0
124
Mo
ng
olia
0.0
214
0.0
152
0.0
120
0.0
149
0.0
342
0.0
364
Leso
tho
0.0
146
0.0
146
0.0
102
0.0
099
0.0
092
0.0
089
Gam
bia
, The
0.0
130
0.0
130
0.0
032
0.0
032
0.0
027
0.0
027
Mo
nte
neg
ro0.0
115
0.0
127
0.0
096
0.0
146
0.0
131
0.0
123
San M
ari
no
0.0
094
0.0
103
0.0
128
0.0
122
0.0
126
0.0
113
Eri
trea
0.0
077
0.0
077
0.0
082
0.0
065
0.0
061
0.0
064
Djib
outi
0.0
067
0.0
067
0.0
049
0.0
037
0.0
036
0.0
037
Guin
ea-B
issa
u0.0
060
0.0
060
0.0
038
0.0
023
0.0
059
0.0
058
Beliz
e0.0
079
0.0
056
0.0
063
0.0
055
0.0
045
0.0
045
Tim
or-
Lest
e0.0
045
0.0
054
0.0
062
0.0
067
0.0
129
0.0
118
Vanuatu
0.0
071
0.0
050
0.0
027
0.0
023
0.0
018
0.0
020
Cab
o V
erd
e0.0
047
0.0
050
0.0
052
0.0
054
0.0
053
0.0
051
Seyc
helle
s0.0
046
0.0
048
0.0
056
0.0
052
0.0
050
0.0
057
St. L
uci
a0.0
064
0.0
045
0.0
044
0.0
038
0.0
033
0.0
032
Mald
ives
0.0
042
0.0
044
0.0
050
0.0
049
0.0
094
0.0
097
So
lom
on Isl
and
s0.0
044
0.0
044
0.0
026
0.0
025
0.0
031
0.0
030
Bhuta
n0.0
036
0.0
043
0.0
050
0.0
050
0.0
065
0.0
069
Antig
ua a
nd
Barb
ud
a0.0
057
0.0
042
0.0
046
0.0
042
0.0
031
0.0
030
Quo
ta S
hare
sC
alc
ula
ted
Quo
ta S
hare
s 1/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 19
Tab
le A
1. D
istr
ibu
tio
n o
f Q
uo
tas
an
d C
alc
ula
ted
Qu
ota
s—b
y M
em
ber
(co
nclu
ded
)
(In
perc
en
t)
So
urc
e: Fin
an
ce D
ep
art
men
t
n.a
.: n
on
-availab
le.
1/
Base
d o
n t
he c
urr
en
t fo
rmu
la: C
QS =
(0.5
0*G
DP
+ 0
.30*O
pen
ness
+0.1
5*V
ari
ab
ilit
y +
0.0
5*R
ese
rves)
^K
. G
DP
ble
nd
ed
usi
ng
60 p
erc
en
t m
ark
et
an
d 4
0
perc
en
t P
PP
exc
han
ge r
ate
s. K
is
a c
om
pre
ssio
n f
act
or
of
0.9
5. Years
in
pare
nth
ese
s in
dic
ate
th
e e
nd
peri
od
fo
r th
e IFS d
ata
use
d in
th
e c
alc
ula
tio
ns.
2/
Th
e “
2008 R
efo
rm”
refl
ect
s q
uo
tas
aft
er
the “
seco
nd
ro
un
d”
ad
ho
c q
uo
ta in
crease
s fo
r 54 m
em
bers
ag
reed
in
2008, fo
llo
win
g t
he “
firs
t ro
un
d”
ad
ho
c
incr
ease
s fo
r fo
ur
mem
bers
ag
reed
in
2006. In
clu
des
So
uth
Su
dan
an
d N
au
ru w
hic
h b
eca
me m
em
bers
on
Ap
ril 18, 2012 a
nd
Ap
ril 12
, 2016, re
spect
ively
.
Fo
r th
e t
wo
co
un
trie
s, S
om
alia a
nd
Su
dan
, th
at
have n
ot
yet
con
sen
ted
to
an
d p
aid
fo
r th
eir
qu
ota
in
crease
s, 1
1th
Revie
w p
rop
ose
d q
uo
tas
are
use
d.
3/
Incl
ud
es
So
uth
Su
dan
wh
ich
beca
me a
mem
ber
on
Ap
ril 18, 2012; re
flect
s th
e p
rop
ose
d d
ou
blin
g o
f it
s q
uo
ta a
fter
the 1
4th
Revie
w b
eco
mes
eff
ect
ive.
4/
Refl
ect
s th
e im
pact
of
ad
just
men
ts t
o c
urr
en
t re
ceip
ts a
nd
paym
en
ts f
or
re-e
xpo
rts,
in
tern
ati
on
al b
an
kin
g in
tere
st, an
d n
on
-mo
neta
ry g
old
.
5/
Incl
ud
ing
Ch
ina, P
.R.,
Ho
ng
Ko
ng
SA
R, an
d M
aca
o S
AR
.
2008 R
efo
rm 2
/ 1
4th
Genera
l
Revi
ew
3/
2008
Refo
rm 4
/
(2005)
14th
Genera
l
Revi
ew
(2008)
Pre
vio
us
(2013)
Curr
ent
(2014)
Co
mo
ros
0.0
0373
0.0
0373
0.0
0162
0.0
0194
0.0
0181
0.0
0181
Gre
nad
a0.0
0491
0.0
0344
0.0
0319
0.0
0263
0.0
0189
0.0
0192
Sam
oa
0.0
0486
0.0
0340
0.0
0253
0.0
0316
0.0
0195
0.0
0190
São
To
mé a
nd
Prí
nci
pe
0.0
0310
0.0
0310
0.0
0065
0.0
0159
0.0
0140
0.0
0139
To
ng
a0.0
0289
0.0
0289
0.0
0155
0.0
0132
0.0
0127
0.0
0129
St. K
itts
0.0
0373
0.0
0262
0.0
0231
0.0
0216
0.0
0211
0.0
0210
St. V
ince
nt
0.0
0348
0.0
0245
0.0
0263
0.0
0239
0.0
0190
0.0
0181
Do
min
ica
0.0
0344
0.0
0241
0.0
0211
0.0
0171
0.0
0123
0.0
0122
Kir
ibati
0.0
0235
0.0
0235
0.0
0176
0.0
0179
0.0
0102
0.0
0104
Mic
ronesi
a, FS
of
0.0
0214
0.0
0151
0.0
0214
0.0
0144
0.0
0145
0.0
0121
Mars
hall
Isla
nd
s0.0
0147
0.0
0103
0.0
0127
0.0
0098
0.0
0075
0.0
0086
Pala
u0.0
0147
0.0
0103
0.0
0151
0.0
0100
0.0
0077
0.0
0074
Nauru
0.0
0084
0.0
0059
n.a
.n.a
.n.a
.0.0
0036
Tuva
lu0.0
0075
0.0
0052
n.a
.0.0
0044
0.0
0024
0.0
0026
Quo
ta S
hare
sC
alc
ula
ted
Quo
ta S
hare
s 1/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
20 INTERNATIONAL MONETARY FUND
Tab
le A
2. D
istr
ibu
tio
n o
f Q
uo
tas
an
d U
pd
ate
d Q
uo
ta V
ari
ab
les—
by M
em
ber
(in
perc
en
t)
14th
Genera
l
Revi
ew
Quo
ta s
hare
s 1/
Curr
ent
2/
Pre
vio
us
3/
Curr
ent
2/
Pre
vio
us
3/
Curr
ent
2/
Pre
vio
us
3/
Curr
ent
2/
Pre
vio
us
3/
United
Sta
tes
17.3
98
19.8
19
19.9
60
12.5
58
12.7
45
13.1
01
13.8
90
1.2
34
1.3
44
Jap
an
6.4
61
5.9
33
6.4
55
4.1
58
4.2
35
5.1
29
5.5
31
10.7
16
11.0
21
Chin
a 6
/6.3
90
14.4
16
13.4
42
9.7
63
9.3
97
8.2
10
6.9
29
33.8
78
32.2
75
Germ
any
5.5
83
4.3
68
4.3
50
7.2
65
7.4
72
5.7
04
5.4
99
0.6
15
0.6
48
France
4.2
25
3.1
97
3.2
54
4.0
68
4.2
49
3.0
31
3.4
04
0.4
79
0.5
03
United
Kin
gd
om
4.2
25
3.1
47
3.0
93
4.3
75
4.4
13
4.7
16
3.9
91
0.8
33
0.8
21
Italy
3.1
59
2.5
11
2.5
65
2.7
47
2.8
70
2.6
08
2.8
53
0.4
58
0.4
93
Ind
ia2.7
49
4.1
89
4.2
07
2.0
94
2.0
68
1.4
25
1.5
03
2.5
29
2.3
97
Russ
ia2.7
05
2.9
55
3.0
53
2.2
46
2.2
22
2.6
14
2.6
77
3.5
79
4.2
85
Bra
zil
2.3
15
3.0
59
3.1
14
1.2
73
1.2
38
1.7
10
1.5
39
3.1
62
3.2
96
Canad
a2.3
11
2.0
39
2.0
81
2.4
86
2.5
28
1.7
83
1.8
89
0.6
47
0.6
32
Saud
i A
rab
ia2.0
95
1.1
88
1.1
95
1.2
30
1.2
23
2.4
98
2.6
39
6.3
51
6.2
08
Sp
ain
1.9
99
1.7
01
1.7
46
1.9
88
2.1
75
1.9
95
2.1
52
0.3
11
0.3
26
Mexi
co1.8
68
1.8
00
1.8
13
1.6
21
1.5
98
1.5
75
1.6
06
1.6
03
1.5
11
Neth
erl
and
s1.8
31
0.9
91
0.9
79
3.7
52
2.9
08
3.0
78
2.6
03
0.1
91
0.2
07
Ko
rea, R
ep
ub
lic o
f1.7
99
1.7
08
1.6
95
2.6
41
2.6
33
0.9
20
0.9
90
3.0
63
2.9
51
Aust
ralia
1.3
78
1.6
05
1.6
64
1.4
56
1.4
80
1.3
23
1.4
06
0.4
38
0.4
21
Belg
ium
1.3
44
0.5
97
0.5
97
1.9
12
1.9
73
1.3
83
1.5
61
0.1
53
0.1
66
Sw
itze
rland
1.2
10
0.7
24
0.7
34
2.1
92
2.2
21
2.4
10
1.8
71
4.3
07
4.3
07
Turk
ey
0.9
77
1.2
01
1.2
23
0.8
86
0.8
86
1.0
63
1.1
01
0.9
52
0.9
82
Ind
onesi
a0.9
74
1.7
00
1.6
32
0.8
36
0.8
28
0.7
03
0.7
22
0.9
02
0.8
71
Sw
ed
en
0.9
29
0.6
19
0.6
30
1.1
49
1.1
79
1.3
58
1.4
24
0.5
18
0.5
44
Po
land
0.8
59
0.7
68
0.7
76
1.0
25
1.0
44
0.9
30
0.9
64
0.8
46
0.9
29
Aust
ria
0.8
24
0.4
89
0.4
88
1.0
05
1.0
56
0.9
01
0.9
23
0.1
25
0.1
13
Sin
gap
ore
0.8
16
0.4
07
0.4
03
2.2
86
2.2
75
1.7
38
1.8
61
2.3
23
2.3
67
No
rway
0.7
87
0.5
37
0.5
43
0.8
17
0.8
40
1.1
81
1.2
58
0.5
52
0.5
18
Venezu
ela
, R
.B. d
e0.7
80
0.5
05
0.4
90
0.3
22
0.3
33
0.5
26
0.5
69
0.0
60
0.0
66
Mala
ysia
0.7
62
0.5
38
0.5
18
0.9
66
1.0
22
0.8
22
0.9
08
1.0
97
1.2
24
Iran, I.R
. o
f0.7
48
0.9
63
0.9
96
0.3
75
0.4
16
0.4
63
0.4
77
1.1
00
1.0
14
Irela
nd
0.7
23
0.2
77
0.2
76
1.2
25
1.2
60
1.2
57
1.1
73
0.0
12
0.0
12
Denm
ark
0.7
21
0.3
63
0.3
66
0.7
64
0.7
99
0.6
45
0.6
91
0.6
74
0.7
52
Thaila
nd
0.6
73
0.7
28
0.6
80
1.0
84
1.0
85
1.2
18
1.3
11
1.3
69
1.4
99
Arg
entina
0.6
68
0.7
94
0.8
62
0.3
77
0.3
87
0.4
38
0.4
92
0.2
25
0.3
07
So
uth
Afr
ica
0.6
40
0.5
54
0.5
78
0.5
02
0.5
00
0.3
23
0.3
49
0.3
83
0.3
94
Nig
eri
a0.5
15
0.7
91
0.7
59
0.4
26
0.4
24
0.5
40
0.5
28
0.3
42
0.4
37
Rese
rves
GD
P B
lend
4/
Op
enness
Vari
ab
ility
5/
-
QUOTAS—DATA UPDATE AND SIMULATIONS—STATISTICAL APPENDIX
INTERNATIONAL MONETARY FUND 21
Tab
le A
2. D
istr
ibu
tio
n o
f Q
uo
tas
an
d U
pd
ate
d Q
uo
ta V
ari
ab
les—
by M
em
ber
(co
nti
nu
ed
)
(in
perc
en
t)
14th
Genera
l
Revi
ew
Quo
ta s
hare
s 1/
Curr
ent
2/
Pre
vio
us
3/
Curr
ent
2/
Pre
vio
us
3/
Curr
ent
2/
Pre
vio
us
3/
Curr
ent
2/
Pre
vio
us
3/
Gre
ece
0.5
09
0.3
04
0.3
33
0.3
46
0.3
67
0.4
72
0.4
88
0.0
20
0.0
14
Finla
nd
0.5
05
0.2
97
0.3
00
0.4
84
0.5
04
0.5
89
0.6
28
0.0
79
0.0
76
United
Ara
b E
mir
ate
s0.4
85
0.5
34
0.5
29
1.2
31
1.1
98
1.0
66
0.8
60
0.6
51
0.5
35
Cze
ch R
ep
ub
lic0.4
57
0.2
84
0.2
94
0.6
61
0.6
77
0.5
36
0.5
75
0.4
83
0.4
16
Po
rtug
al
0.4
32
0.2
86
0.3
01
0.4
35
0.4
62
0.4
74
0.4
98
0.0
36
0.0
29
Co
lom
bia
0.4
29
0.5
34
0.5
32
0.2
95
0.2
90
0.2
14
0.2
23
0.3
86
0.3
61
Phili
pp
ines
0.4
28
0.4
64
0.4
50
0.3
42
0.3
37
0.4
15
0.4
40
0.6
23
0.6
73
Eg
ypt
0.4
27
0.5
85
0.5
90
0.2
72
0.2
77
0.5
23
0.5
42
0.1
15
0.1
17
Paki
stan
0.4
26
0.5
12
0.5
16
0.1
94
0.1
96
0.1
22
0.1
20
0.0
79
0.0
64
Ukr
ain
e0.4
22
0.2
79
0.3
03
0.3
54
0.3
71
0.8
67
0.8
17
0.1
13
0.1
89
Alg
eri
a0.4
11
0.3
71
0.3
76
0.2
81
0.2
88
0.5
30
0.5
60
1.6
39
1.7
29
Hung
ary
0.4
07
0.1
98
0.2
03
0.5
25
0.5
51
0.6
45
0.6
61
0.3
98
0.4
05
Kuw
ait
0.4
05
0.2
44
0.2
48
0.3
65
0.3
60
0.3
69
0.3
90
0.2
81
0.2
72
Isra
el
0.4
03
0.3
29
0.3
23
0.4
18
0.4
21
0.3
97
0.4
28
0.7
40
0.7
08
Ro
mania
0.3
80
0.2
94
0.2
96
0.3
19
0.3
16
0.5
73
0.5
85
0.3
60
0.3
91
Chile
0.3
66
0.3
66
0.3
72
0.3
99
0.4
07
0.5
33
0.5
61
0.3
47
0.3
64
Iraq
0.3
49
0.3
54
0.3
48
0.2
91
0.2
84
0.5
16
0.5
25
0.5
86
0.6
29
Lib
ya0.3
30
0.0
98
0.1
02
0.1
46
0.1
66
0.6
50
0.6
69
0.8
54
1.0
80
Peru
0.2
80
0.2
97
0.2
93
0.2
09
0.2
10
0.3
28
0.3
37
0.5
44
0.5
89
Luxe
mb
ourg
0.2
77
0.0
67
0.0
67
1.3
11
1.2
35
1.2
02
1.2
09
0.0
07
0.0
08
New
Zeala
nd
0.2
62
0.2
10
0.2
05
0.2
38
0.2
36
0.1