quotas data update and simulations · 2016-09-16 · quotas—data update and simulations—...

© 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

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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

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


2 INTERNATIONAL MONETARY FUND


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


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


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.



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.



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.



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



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



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



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)



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)



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.



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.



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.



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/



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/



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/



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/



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/



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/



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/



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

quotas data update and simulations · 2016-09-16 · quotas—data update and simulations—...

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