## _062812

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---

### I. Introduction — review mandate and objectives
- Executive Board: first formal discussion March 2012; review to be completed by January 2013.
- IMFC: expectation of agreement by January 2013; reaffirmed commitment to complete the 15th quota review by January 2014.
- G-20 Leaders (Los Cabos): formula should be "simple and transparent, consistent with the multiple roles of quotas, result in calculated shares that are broadly acceptable to the membership, and be feasible to implement based on timely, high quality and widely available data."
- Paper scope:
  - Section II: results of updating the quota database through end-2010.
  - Section III: further staff work on financial openness, variability, and financial contributions.
  - Section IV: simulations illustrating impacts of changing weights (financial openness; GDP market vs PPP blends), capturing financial contributions, and simplifying the formula.
  - No proposals made at this stage.

### II. Data sources and methodology
- Primary data source: Fund’s International Financial Statistics (IFS).
- Missing data supplemented by World Economic Outlook (WEO); remaining gaps from staff reports and, rarely, country desk data.
- Cutoff date for incorporating new data: January 31, 2012; Fall 2011 WEO used.
- PPP GDP: taken from WEO; calculated by dividing nominal GDP in local currency by PPP price level index.
- Database updated through 2010; one further data update expected in mid-2013 before the 15th General Review deadline.

### III. Aggregate and regional changes — headline findings
- EMDC aggregate:
  - Calculated quota share (CQS) of Emerging Market and Developing Countries (EMDCs) increased by 1.4 pp to 43.9 percent compared to the previous update.
  - Compared with data through 2005 (used for the 2008 Reform), aggregate CQS of EMDCs has risen by 7.7 pp.
- Regional within EMDCs:
  - Largest gain: Asia.
  - Smaller gains: Western Hemisphere and Africa.
  - Small losses: Middle East and Transition Economies.
- Advanced economies:
  - Two thirds of the decline recorded by major advanced economies (all except Canada recorded a decline).
  - Share of other advanced economies as a group fell by 0.5 pp.
- Drivers of CQS changes:
  - GDP blend: 2.0 pp increase in EMDCs’ share of the GDP blend variable due to real growth divergence.
  - Openness: EMDCs generally gained share due to stronger rebound in external flows.
  - Variability: EMDC share in variability increased.
  - Reserves: shares changed reflecting strong reserve accumulation by several individual countries.

### IV. Key formula and selected exact statistics
- Formula for Calculated Quota Shares (CQS):
  - CQS = (0.50*GDP + 0.30*Openness + 0.15*Variability + 0.05*Reserves)^K.
  - GDP blended using 60 percent market and 40 percent PPP exchange rates.
  - K is a compression factor of 0.95.
- Selected exact current shares (Table excerpts preserved exactly):
  - Advanced economies: Quota Shares 60.4; Calculated Quota Shares (Current) 57.6.
  - Major advanced economies: Quota Shares 45.3; Calculated Quota Shares (Current) 43.4.
  - United States: Quota Shares 17.7; Calculated Quota Shares (Current) 17.7.
  - China (including China, P.R., Hong Kong SAR, and Macao SAR): Quota Shares 4.0; Calculated Quota Shares (Current) 6.4.
  - Emerging Market and Developing Countries (aggregate): Quota Shares 39.6; Calculated Quota Shares (Current) 42.4.
  - Total: 100.0 (Quota Shares) and 100.0 (Calculated Quota Shares).
- Selected variable shares (Table 2 current):
  - GDP Blend (Current): Advanced economies 57.6; Emerging Market and Developing Countries 42.4.
  - Openness (Current): Advanced economies 60.2; EMDCs 39.8.
  - Variability (Current): Advanced economies 36.2; EMDCs 63.8.
  - Reserves (Current): Advanced economies 23.9; EMDCs 76.1.
- Memorandum items (Table 2):
  - EU 27 (GDP Blend Current): 30.2.
  - LICs (GDP Blend Current): 4.0.

### V. Individual country movements — top gainers and losers (exact changes in percentage points)
- Top 10 positive changes in Calculated Quota Shares:
  - China 5/ : 0.785 (GDP Blend 0.471; Openness 0.183; Variability 0.171; Reserves 0.057)
  - India: 0.172 (GDP Blend 0.116; Openness 0.046; Variability 0.037; Reserves -0.018)
  - Brazil: 0.101 (GDP Blend 0.116; Openness 0.021; Variability -0.043; Reserves 0.012)
  - Indonesia: 0.086 (GDP Blend 0.044; Openness 0.008; Variability 0.026; Reserves 0.007)
  - Singapore: 0.084 (GDP Blend 0.006; Openness 0.016; Variability 0.062; Reserves 0.002)
  - Thailand: 0.062 (GDP Blend 0.007; Openness 0.011; Variability 0.038; Reserves 0.006)
  - Switzerland: 0.059 (GDP Blend 0.005; Openness 0.009; Variability -0.016; Reserves 0.062)
  - Norway: 0.037 (GDP Blend -0.005; Openness -0.005; Variability 0.050; Reserves -0.003)
  - Iran, Islamic Republic of: 0.035 (GDP Blend 0.022; Openness 0.007; Variability 0.015; Reserves -0.009)
  - Malaysia: 0.032 (GDP Blend 0.006; Openness 0.003; Variability 0.028; Reserves -0.005)
- Top 10 negative changes in Calculated Quota Shares:
  - United States: -0.229 (GDP Blend -0.405; Openness -0.083; Variability 0.216; Reserves 0.008)
  - United Kingdom: -0.226 (GDP Blend -0.171; Openness -0.121; Variability 0.045; Reserves 0.004)
  - Italy: -0.186 (GDP Blend -0.075; Openness -0.035; Variability -0.087; Reserves -0.001)
  - France: -0.184 (GDP Blend -0.093; Openness -0.038; Variability -0.072; Reserves 0.005)
  - Japan: -0.106 (GDP Blend 0.023; Openness -0.023; Variability -0.043; Reserves -0.073)
  - Germany: -0.106 (GDP Blend -0.111; Openness -0.042; Variability 0.036; Reserves 0.001)
  - Ireland: -0.104 (GDP Blend -0.017; Openness -0.007; Variability -0.080; Reserves 0.000)
  - Spain: -0.099 (GDP Blend -0.055; Openness -0.021; Variability -0.028; Reserves 0.001)
  - United Arab Emirates: -0.080 (GDP Blend 0.048; Openness 0.013; Variability -0.138; Reserves -0.002)
  - Belgium: -0.078 (GDP Blend -0.010; Openness -0.029; Variability -0.042; Reserves 0.001)

### VI. Out-of-lineness, under- and over-representation
- Aggregate out-of-lineness increased compared to last update.
- Advanced economies are over-represented and EMDCs are under-represented by 1.6 pp (difference between calculated quota shares and 14th General Review quota shares).
- Count of under-/over-represented countries:
  - Current dataset shows 66 members under-represented (fewer than 69 in previous update).
  - (Full matrix and exact totals available in Table 4 of the source.)

### VII. IIP as a candidate measure of financial openness — data, issues, and adjustments (exact figures preserved)
- IIP coverage: data available for 109 members (compared with 102 at 2009 cut-off).
- Two near-term options:
  - Use investment income flows as proxy for financial openness:
    - Investment income already in current openness variable.
    - Correlation between IIP shares (2010) and investment income shares (2006-2010) for 109 members is 0.99.
    - Caveats: differing rates of return, under-recording, net vs gross recording.
  - Gap-fill IIP using investment income:
    - Steps: split countries by IIP availability using investment income; compute ratio of aggregate investment income; estimate aggregate IIP for missing countries; allocate across countries using investment income shares.
    - Countries reporting IIP account for about 98.5 percent of global IIP total derived via gap-filling.
- Treatment of international financial centers:
  - Examples of IIP/GDP ratios: Luxembourg 243, Ireland 33, Barbados 22; majority less than 3 (149 members).
  - Distribution is highly skewed.
  - Previous adjustments for "entrepot-like" activities were discontinued in 2008.
- Two adjustments explored:
  - Compression of IIP/GDP ratio:
    - Compression factor = 0.95 (modest impact).
    - Compression factor = 0.70 reduces mean from original 3.4 to 2.2.
  - Capping IIP/GDP ratio:
    - Cap at 95th percentile affects 10 members.
    - Cap at 90th percentile affects 19 members.
- Staff assessment: both compression and capping involve arbitrary choices; staff could pursue further subject to Directors’ views.
- Selected table rows preserved exactly:
  - Table 6 — "Ratio of IIP to GDP" (Total row, five scenarios): Total 3.43 3.15 2.16 3.11 2.72
  - Table 7 — "Measures of Financial Openness—International Investment Position" (Total row, six scenarios): Total 100.00 100.00 100.00 100.00 100.00 100.00

### VIII. Variability — alternatives examined, stability, and predictive power
- Current measure: root mean squared deviation from a three-year moving average over a recent 13-year period.
- Alternatives considered:
  - 13Y AAD: average absolute deviation from a three-year moving average (13-year period).
  - 5Y SD: five-year standard deviation relative to sample mean.
  - 10Y II: instability index over recent ten-year period, based on deviations from an OLS trend.
- Empirical performance:
  - 2009 update: all alternatives showed smaller variation than current variability; only 5Y SD close to GDP/openness variation.
  - 2010 update: 13Y AAD and 10Y II yielded smallest variation; 5Y SD showed largest variation.
  - Over longer span: 13Y AAD produces smallest variation on average, but not uniformly across subperiods.
  - Overall: results depend on period chosen; not a strong basis to select an alternative on stability alone.
- Predictive power for Fund program need:
  - Correlation of modified variability measures (adjusted for size) with program approval ≈ zero and statistically insignificant.
  - Composite indicator correlation with likelihood of a Fund program: 0.19 (statistically significant).
  - Transforming composite for size reduces correlation from 0.19 to 0.09.
- Composite variability:
  - For 28 of 32 countries with programs since 2008 (81 percent), composite variability share > GDP share.
  - For 70 of 143 non-program countries (49 percent), composite variability share > GDP share.
  - Composite calculated for 175 members; 32 had GRA programs since 2008; 13 members not covered due to data constraints.
- Staff judgment: composite provides additional information but not sufficiently robust for inclusion; staff continues to see a case for dropping variability given design difficulties.

### IX. Financial contributions — scope, measurement, and illustrative measures
- Forms of contributions identified:
  - Voluntary: NAB and bilateral support for Fund liquidity, PRGT loans, PRGT subsidies, voluntary SDR trading arrangements, technical assistance and training.
  - Mandated: FTP participation, charges and fees associated with borrowing, burden-shared contributions.
- Data/practical issues:
  - Some contributions not published and may be amended.
  - Contributions differ in magnitude and form; opportunity cost computation complicated.
  - Practical approach: include contributions on a commitment basis.
  - Aggregation: sum members’ shares across contribution forms to create aggregate measure.
- Illustrative aggregate measures constructed (definitions preserved exactly):
  - FCS I: simple average of members’ contribution shares to four voluntary financial contributions—NAB and bilateral pledges, PRGT loans, PRGT subsidies, and TA activities.
  - FCI II: same as FCS I, but includes share of members’ quarterly participation in the FTP (relative quota shares of participants in each quarter during 1992—2011).
  - FCS III: weighted average with weights: NAB/bilateral resources (0.3), FTP participation (0.3), PRGT loans and subsidies combined (0.2), TA activities (0.2).
  - FCS IV: higher of 14th Review quota share or FCS I share rebased to sum to 100 percent.
  - FCS V: distinguishes FTP participants and non-FTP participants; non-FTP = 14th Review quota share; FTP participants receive distribution of aggregate 14th Review share across participants according to relative FCS I shares.
- Aggregate distributional headline:
  - "In general, these measures tend to heavily favor advanced economies."
  - Advanced economies largest contributors in 3 of 4 categories examined.
  - Share of advanced economies in NAB and bilateral pledges combined is over 70 percent.
  - For first three measures, advanced economies’ share is 80-85 percent; fourth and fifth measures produce share close to or above 70 percent.
- Selected exact figures from source tables (preserved exactly):
  - Total100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
  - Advanced Economies (Table 8 first row): 57.65 56.12 3.95 55.38 1.76 0.07 4.57 1.09 1.18 5.39 2.4
  - Major advanced economies (Table 8): 43.44 40.61 7.31 7.36 2.04 9.25 7.54 9.37 4.66 3.07 2.3
  - United States (Table 8): 17.4 15.8 1.6 2.5 24.1 11.0 15.5 5.9 0.0 9.3 0.5
  - Japan (Table 8): 6.5 6.2 12.3 2.5 8.3 18.4 18.5 15.2 26.8 16.7 2.0
  - Emerging Market and Developing Countries (Table 8): 42.44 43.97 6.14 44.71 8.34 0.02 5.25 29.0 8.9 14.7 7.6
  - China (Table 8 note 9 grouping): 6.4 9.4 30.5 2.4 4.0 0.0 8.7 9.2 3.9 1.0 0.0
  - Memorandum items (Table 8): Total contributions (in millions of SDRs) 51,900 181,486 476,598 25,854 5,267 550
  - EU27 (Table 8 memorandum): 30.2 30.9 8.1 44.7 41.1 23.1 34.2 45.6 53.6 48.3 19.3
  - LICs (Table 8 memorandum): 4.0 2.6 2.1 0.0 0.0 1.0 0.0 0.0 0.0 3.1 1.3

### X. Illustrative simulations — simplification, PPP weights, financial openness, contributions (selected exact outcomes)
- Simulation sets presented:
  1. Simplifying formula by dropping variables.
  2. Changing market vs PPP GDP weights in GDP blend.
  3. Including financial openness explicitly (IIP gap-filled and capped).
  4. Incorporating financial contributions.
- Main simplification results (preserved findings):
  - Dropping variability: aggregate CQS of advanced economies and EMDCs unchanged; internal shifts across subgroups.
  - Dropping variability and reserves: shift toward advanced economies, especially major advanced economies.
  - Dropping openness and variability: shift toward EMDCs, strong gains in Asia and Western Hemisphere.
  - GDP-only formula: overall shares between advanced economies and EMDCs broadly unaffected; large internal redistributions (e.g., Brazil, China, India gain).
- Changing PPP weight in GDP blend:
  - Increasing PPP weight from 40 to 50 percent → 0.8 pp increase in CQS of EMDCs; China and India gain most; LICs share rises slightly.
- Increasing weight on financial openness (IIP gap-filled, capped at 95th percentile):
  - Yields "a shift of over 2 pp in favor of advanced economies."
  - Combining increased financial openness weight with dropping variability and reserves → "4–4.8 pp shift in favor of advanced economies."
- Including financial contributions (FCS III replacing reserves with same weight):
  - Leads to "a shift in shares of about 2.7 pp in favor of advanced economies," with gains broadly shared within advanced economies.
  - Variants that drop variability and add financial contributions partially mitigate impact on EMDC aggregate share.
- Representative quota-share outcomes across variants (selected exact values reproduced from source):
  - Advanced economies: 57.6; 56.1; 56.1; 56.1; 58.0; 57.7; 53.6; 54.9; 56.5.
  - Major advanced economies: 43.4; 40.6; 41.4; 41.9; 42.9; 43.3; 42.4; 43.6; 44.9.
  - United States: 17.4; 15.8; 16.2; 16.8; 17.0; 17.7; 18.5; 19.2; 20.1.
  - China (incl. China, P.R., Hong Kong SAR, Macao SAR): 6.4; 9.4; 10.1; 10.1; 9.1; 9.3; 11.6; 10.9; 10.1.
  - EMDCs: 42.4; 43.9; 43.9; 43.9; 42.0; 42.3; 46.4; 45.1; 43.5.
  - Total: 100.0 across all illustrated scenarios.
- Example coefficient sets (selected exact coefficients preserved):
  - Market GDP: 0.3000; 0.3530; 0.3900; 0.3750; 0.4200; 0.5450; 0.5700; 0.600
  - PPP GDP: 0.2000; 0.2350; 0.2600; 0.2500; 0.2800; 0.3640; 0.3800; 0.400
  - Openness: 0.3000; 0.3530; 0.3000; 0.3750; 0.3000; 0.0000; 0.0000; 0.000
  - Variability: 0.1500; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.000
  - Reserves: 0.0500; 0.0590; 0.0500; 0.0000; 0.0000; 0.0910; 0.0500; 0.000
  - Financial Contributions: 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000

### XI. Overall implications and staff plans
- Distributional tendencies:
  - Increasing GDP variable weight favors major advanced economies and some large EMDCs.
  - Larger weight on financial openness and introducing financial contributions tends to favor advanced economies.
  - EMDCs as a group gain from increasing weight of reserves and of PPP GDP.
- Data update and timeline:
  - Paper updates quota data through 2010; last update before January 2013 deadline for quota formula review.
  - Staff to perform one further update in mid-2013 and prepare a follow-up paper laying out possible options based on Directors’ views.
- Issues/questions posed to Directors (exactly as in paper):
  - Views on options for simplifying the quota formula and key variables to preserve?
  - Views on weight and composition of the GDP blend variable?
  - Merits of increasing weight on financial openness, including:
    - (i) use of gap-filled IIP data or larger weight for investment income as proxy, and
    - (ii) approaches for addressing international financial centers?
  - Do Directors agree there is a case for dropping variability given identified shortcomings?
  - Views on reflecting members’ financial contributions in quota adjustments; if included, should it be additional to or instead of the reserves variable?

*Source: IMF Finance Department — Quota Formula Review (data and analysis through 2010).*

### 1. Distribution of Quotas and Calculated Quotas ......................................................................6

### 1. Distribution of Quotas and Calculated Quotas

### I. Introduction — review mandate and objectives
- The Executive Board held its first formal discussion on the comprehensive review of the quota formula in March 2012; the review is to be completed by January 2013.
- IMFC reiterated expectation of agreement by January 2013 and reaffirmed commitment to complete the 15th quota review by January 2014.
- G-20 Leaders (Los Cabos) reiterated commitment to complete the comprehensive review of the quota formula by January 2013 and stated the formula should be:
  - "simple and transparent, consistent with the multiple roles of quotas, result in calculated shares that are broadly acceptable to the membership, and be feasible to implement based on timely, high quality and widely available data."
  - Intended to better reflect changed relative weights of IMF members in the world economy and to protect the voice and representation of the poorest members.
- Paper scope:
  - Section II: results of updating the quota database through end-2010.
  - Section III: further staff work on financial openness, variability, and financial contributions.
  - Section IV: simulations illustrating impacts of changing weights (financial openness; GDP market vs PPP blends), capturing financial contributions, and simplifying the formula.
  - No proposals made at this stage.

### II. Data sources and methodology (Box 1)
- Primary data source: Fund’s International Financial Statistics (IFS).
- Missing data supplemented by World Economic Outlook (WEO) database; remaining gaps from staff reports and, rarely, country desk data.
- Cutoff date for incorporating new data: January 31, 2012; Fall 2011 WEO used consistently with this cutoff.
- PPP GDP: taken from WEO; calculated by dividing nominal GDP in local currency by PPP price level index.
- Staff updated the quota database through 2010 using same sources and methodology as past updates; one further data update expected in mid-2013 before the 15th General Review deadline.

### III. Updated quota calculations — aggregate and regional changes (Section II)
- Aggregate change for EMDCs:
  - Calculated quota share (CQS) of Emerging Market and Developing Countries (EMDCs) increased by 1.4 pp to 43.9 percent compared to the previous update.
  - Compared with data through 2005 (used for the 2008 Reform), aggregate CQS of EMDCs has risen by 7.7 pp.
- Regional movements within EMDCs:
  - Largest gain: Asia.
  - Smaller gains: Western Hemisphere and Africa.
  - Small losses: Middle East and Transition Economies.
- Advanced economies:
  - Two thirds of the decline recorded by major advanced economies (all except Canada recorded a decline).
  - Share of other advanced economies as a group fell by 0.5 pp.
- Drivers of changes in CQS:
  - Real economic growth divergence: EMDCs recorded strong growth; most advanced economies stagnated — reflected in a 2.0 pp increase in the EMDCs’ share of the GDP blend variable.
  - EMDCs generally gained share in the openness variable due to stronger rebound in external flows.
  - Variability changes differed across countries; overall EMDC share in variability increased (partly reversing previous increase in advanced economies’ variability share).
  - Reserves shares changed reflecting strong reserve accumulation by several individual countries.

### IV. Key tables and numeric breakdowns (selected exact figures)
- Quota shares and calculated quota shares (Table 1 excerpts, all values preserved exactly):
  - Advanced economies: Quota Shares 60.4; Calculated Quota Shares (Current) 57.6.
  - Major advanced economies: Quota Shares 45.3; Calculated Quota Shares (Current) 43.4.
  - United States: Quota Shares 17.7; Calculated Quota Shares (Current) 17.7.
  - China (including China, P.R., Hong Kong SAR, and Macao SAR): Quota Shares 4.0; Calculated Quota Shares (Current) 6.4.
  - Emerging Market and Developing Countries (aggregate): Quota Shares 39.6; Calculated Quota Shares (Current) 42.4.
  - Total: 100.0 (Quota Shares) and 100.0 (Calculated Quota Shares).
- Formula specified for Calculated Quota Shares (footnote):
  - CQS = (0.50*GDP + 0.30*Openness + 0.15*Variability + 0.05*Reserves)^K.
  - GDP blended using 60 percent market and 40 percent PPP exchange rates.
  - K is a compression factor of 0.95.
- Table 2 (Distribution of Quotas and Updated Quota Variables) — selected exact current shares:
  - GDP Blend (Current): Advanced economies 57.6; Emerging Market and Developing Countries 42.4.
  - Openness (Current): Advanced economies 60.2; EMDCs 39.8.
  - Variability (Current): Advanced economies 36.2; EMDCs 63.8.
  - Reserves (Current): Advanced economies 23.9; EMDCs 76.1.
- Memorandum items exact figures (Table 2):
  - EU 27 (GDP Blend Current): 30.2.
  - LICs (GDP Blend Current): 4.0.

### V. Individual country movements — top gainers and losers (Table 3; exact changes)
- Top 10 positive changes in Calculated Quota Shares (difference between current and previous shares; values in percentage points):
  - China 5/ : 0.785 (contributions by variable: GDP Blend 0.471; Openness 0.183; Variability 0.171; Reserves 0.057)
  - India: 0.172 (GDP Blend 0.116; Openness 0.046; Variability 0.037; Reserves -0.018)
  - Brazil: 0.101 (GDP Blend 0.116; Openness 0.021; Variability -0.043; Reserves 0.012)
  - Indonesia: 0.086 (GDP Blend 0.044; Openness 0.008; Variability 0.026; Reserves 0.007)
  - Singapore: 0.084 (GDP Blend 0.006; Openness 0.016; Variability 0.062; Reserves 0.002)
  - Thailand: 0.062 (GDP Blend 0.007; Openness 0.011; Variability 0.038; Reserves 0.006)
  - Switzerland: 0.059 (GDP Blend 0.005; Openness 0.009; Variability -0.016; Reserves 0.062)
  - Norway: 0.037 (GDP Blend -0.005; Openness -0.005; Variability 0.050; Reserves -0.003)
  - Iran, Islamic Republic of: 0.035 (GDP Blend 0.022; Openness 0.007; Variability 0.015; Reserves -0.009)
  - Malaysia: 0.032 (GDP Blend 0.006; Openness 0.003; Variability 0.028; Reserves -0.005)
- Top 10 negative changes in Calculated Quota Shares (difference between current and previous shares; values in percentage points):
  - United States: -0.229 (GDP Blend -0.405; Openness -0.083; Variability 0.216; Reserves 0.008)
  - United Kingdom: -0.226 (GDP Blend -0.171; Openness -0.121; Variability 0.045; Reserves 0.004)
  - Italy: -0.186 (GDP Blend -0.075; Openness -0.035; Variability -0.087; Reserves -0.001)
  - France: -0.184 (GDP Blend -0.093; Openness -0.038; Variability -0.072; Reserves 0.005)
  - Japan: -0.106 (GDP Blend 0.023; Openness -0.023; Variability -0.043; Reserves -0.073)
  - Germany: -0.106 (GDP Blend -0.111; Openness -0.042; Variability 0.036; Reserves 0.001)
  - Ireland: -0.104 (GDP Blend -0.017; Openness -0.007; Variability -0.080; Reserves 0.000)
  - Spain: -0.099 (GDP Blend -0.055; Openness -0.021; Variability -0.028; Reserves 0.001)
  - United Arab Emirates: -0.080 (GDP Blend 0.048; Openness 0.013; Variability -0.138; Reserves -0.002)
  - Belgium: -0.078 (GDP Blend -0.010; Openness -0.029; Variability -0.042; Reserves 0.001)

### VI. Out-of-lineness, under- and over-representation (Table 4; exact figures)
- Aggregate out-of-lineness increased compared to last update:
  - Advanced economies are over-represented and EMDCs are under-represented by 1.6 pp (difference between calculated quota shares and 14th General Review quota shares).
- Aggregate comparisons (exact values from Table 4):
  - 14th General Review Quota Share (Advanced economies): 57.6; Current Calculated Quota Shares: 57.6; Difference shown in table row as -1.6 in context of group comparisons.
  - Emerging Market and Developing Countries: 42.4 (Current Calculated Quota Shares).
- Count of countries:
  - Total underrepresented countries: Current dataset shows 66 members under-represented (fewer than 69 in the previous update).
  - Total overrepresented countries: figures reported in Table 4 show shifts in totals (exact totals preserved in table: Total Underrepresented Countries 35.2 (14th General Review) vs Current 6.7? — readers should consult Table 4 for full matrix as presented).

### VII. Quota formula variables — focus areas for further technical work (Section III)
- Three topics requested for additional technical work at March discussion:
  1. How to better capture financial openness.
  2. Improving the current measure of variability to better reflect members’ underlying vulnerability and potential demand for Fund resources.
  3. Scope for including a measure of members’ financial contributions to the Fund in the quota formula.
- Financial openness — summary of views:
  - Many Directors view openness as measure of integration into the world economy and want it to remain an important variable; several favor exploring options for better capturing financial openness.
  - Other Directors favor reducing the weight on openness or dropping it, arguing:
    - Existing openness variable overstates integration into the global economy.
    - It is highly correlated with the GDP variable.
    - It is affected by data availability constraints and measurement difficulties.
  - Those skeptical of openness revisions were unconvinced of benefits of continuing work on financial openness.

### VIII. Staff next steps and analytical context
- Staff updated database through 2010 and will perform one further update in mid-2013 before the 15th General Review deadline.
- Section IV contains simulations on:
  - Increasing weight of financial openness.
  - Changing weights between market and PPP GDP in GDP blend.
  - Capturing financial contributions.
  - Simplifying the formula.
- Annexes and Statistical Appendix (circulated separately) provide technical material and individual country details for simulations.

*Source: IMF Finance Department — Quota Formula Review (data and analysis through 2010).*

### 12.      In previous work, the International Investment Position (IIP) has been identified

### _062812 - 12.      In previous work, the International Investment Position (IIP) has been identified

### IIP as a candidate measure of financial openness
- The IIP provides a quantitative measure of a member’s foreign financial asset and liability position and in principle captures the extent of investment in a country by non-residents and of investment abroad by residents.
- Recent improvements expanded the range of assets and liabilities included in IIP, but issues remain for use in the quota formula:
  - partial country coverage;
  - treatment of international financial centers with relatively large shares of global IIP;
  - conceptual differences over relevance of IIP versus other openness measures.

### Data coverage and proxied / gap-filled alternatives
- As of the cut-off date for the latest data update, IIP data were available for 109 members (compared with 102 countries at the time of the cut-off for the 2009 database).
- Two main near-term options for including a financial openness measure in the quota formula:
  - Use cross-border investment income flows as a proxy for financial openness.
    - Investment income is already included in the current openness variable and is not constrained by data availability.
    - The correlation between IIP shares (2010) and investment income shares (2006-2010) for the 109 members for which IIP data are available is 0.99.
    - Caveats: investment income flows are an imperfect substitute for IIP stocks because rates of return vary across countries, under-recording of investment income receipts has occurred, and some components are recorded on a net rather than gross basis.
  - Gap-fill the IIP series using the investment income series.
    - Required steps: (i) split countries into those with and without IIP data using investment income (2006-2010); (ii) compute ratio of aggregate investment income of countries with IIP data to countries without and apply to original IIP series to estimate aggregate IIP for all countries; (iii) allocate estimated aggregate IIP for countries without IIP data across those countries using relative shares from investment income series.
    - This approach uses published data, is transparent and replicable.
    - Countries that report IIP data account for about 98.5 percent of the global IIP total derived via gap-filling, suggesting limited aggregate distortion from gap-filling.

### Treatment of international financial centers (IIB/entrepot concerns)
- International financial centers tend to have very high ratios of IIP to GDP because they act as conduits for non-resident financial activity.
  - Example ratios of IIP to GDP: Luxembourg 243, Ireland 33, Barbados 22.
  - Majority of countries (149 members) have ratio of less than 3.
  - Distribution of IIP/GDP ratios is much more skewed than for other quota variables.
- Previous practice of making adjustments to underlying data to correct for "entrepot-like" activities was discontinued in 2008 as arbitrary and lacking strong conceptual basis.

### Two explored adjustments to dampen impact of large financial centers
- Compression of the IIP/GDP ratio:
  - Apply a compression factor to the IIP/GDP ratio, maintain original ranking, no additional data required.
  - Staff explored compression factors:
    - Compression factor = 0.95 (the same factor used for the quota formula as a whole) — only modest impact on dispersion.
    - Compression factor = 0.70 — reduces the mean of the modified IIP to GDP ratio from the original 3.4 to 2.2 (roughly equal to the average of the original series excluding the ten members with the largest IIP/GDP ratio). With 0.70 there is a more pronounced effect for top-ranking members, though they still have significantly higher ratios than the membership as a whole.
- Capping the IIP/GDP ratio:
  - Cap the ratio at a predetermined percentile (illustrative caps explored):
    - Capping at the 95th percentile affects 10 members.
    - Capping at the 90th percentile affects 19 members.
  - Caps reduce extreme values more sharply than compression; depending on cap level, some countries with very high ratios may have a lower share than under the current openness variable.

### Comparative numeric summaries and selected statistics (preserved exactly)
- Correlation and coverage:
  - Correlation between IIP shares (2010) and investment income shares (2006-2010) for the 109 members for which IIP data are available is 0.99.
  - IIP data were available for 109 members (compared with 102 at the 2009 cut-off).
  - Countries reporting IIP account for about 98.5 percent of the global IIP total derived via gap-filling.
- Selected examples from narrative and tables:
  - Ratio of IIP to GDP: Luxembourg 243, Ireland 33, Barbados 22, majority less than 3 (149 members).
  - Compression example: compression factor 0.70 reduces mean from original 3.4 to 2.2.
  - Caps explored: 95th percentile (10 members affected), 90th percentile (19 members affected).
- Table 6 — "Ratio of IIP to GDP" (Total row, five scenarios, preserved exactly in order):
  - Total 3.43 3.15 2.16 3.11 2.72
- Table 7 — "Measures of Financial Openness—International Investment Position" (Total row, six scenarios, preserved exactly in order):
  - Total 100.00 100.00 100.00 100.00 100.00 100.00

### Assessment and staff recommendation considerations
- Both compression and capping approaches involve arbitrary choices and are not entirely satisfactory:
  - Compression tends to leave financial centers with relatively high shares, though reduced from unadjusted shares.
  - Capping brings financial centers’ shares closer to other high-but-not-extreme members and could reduce their combined share in trade and financial openness.
- Staff could pursue these options further in light of Directors’ views.

*Source: _062812 - 12.      In previous work, the International Investment Position (IIP) has been identified*

### 22.      To address the instability of the current measure, staff examined a range of

### _062812 - 22.      To address the instability of the current measure, staff examined a range of

### Measures of variability and alternatives examined
- Current measure: root mean squared deviation from a three-year moving average, calculated over a recent 13-year period.
- Alternatives considered:
  - 13Y AAD: average absolute deviation from a three-year moving average (13-year period).
  - 5Y SD: five-year standard deviation calculated relative to the sample mean.
  - 10Y II: instability index calculated over a recent ten-year period, based on deviations from a trend estimated by ordinary least squares (differs from moving-average trend estimation).
- Annex II: presents additional statistical measures (average absolute deviation, median absolute deviation, maximum deviation from the mean) and an illustration of transformations.

### Empirical performance and stability findings
- Comparison across quota data updates:
  - For the 2009 data update (large shifts): all alternatives showed smaller variation than the current variability measure; only the 5Y SD showed variation close to that for GDP or openness.
  - For the 2010 update (changes from 2009 to 2010): the 13Y AAD and the 10Y II yielded the smallest variation; the 5Y SD showed the largest variation.
- Over a longer span:
  - The 13-year average absolute deviation produces the smallest variation in shares on average, but there are periods (e.g., 2004–07) where the existing variability measure yields more stable results than the alternatives.
- Overall conclusion on stability:
  - Results are highly dependent on the period chosen and do not provide a strong basis for selecting an alternative variability measure on stability considerations alone.
- Data coverage details:
  - Analysis covers the period 1990-2010 and is based on the latest quota data update for current receipts and net capital flows since 1998, and previous quota data and WEO estimates for earlier years; series account for past data revisions.

### Predictive power for potential need (use of Fund resources)
- Correlations with a binary variable indicating approval of a Fund program (data since 1990):
  - Correlation between modified variability measures (adjusted for economic size) and program approval is close to zero and statistically insignificant.
  - Composite indicator (combining current account to GDP ratio, reserve cover ratio, per capita GDP, and real GDP growth) correlation with likelihood of a Fund program: 0.19 and is statistically significant (Annex II).
  - Transforming the composite vulnerability index into a size-related variable for formula use would reduce the correlation coefficient from 0.19 to 0.09, 00.10.20.30.40.5 (note: text shows numeric reduction to 0.09, with accompanying plotted series labels).
- Interpretation:
  - The composite indicator has higher explanatory power than individual components but still does not represent a very strong association with potential need.
  - Adding more components could increase correlation but would increase data requirements and complexity.
  - Indicators may not capture characteristics of reserve currency issuers with low levels of reserves.

### Composite variability indicator: construction, properties, and limitations
- Motivation: a composite indicator can capture different kinds of vulnerabilities and thus potentially better explain potential use of Fund resources.
- Empirical outcome:
  - For 28 of 32 countries with programs since 2008 (81 percent), the composite variability share is greater than their GDP share.
  - For 70 out of 143 non-program countries (49 percent), the composite variability share is greater than their GDP share.
  - Composite indicator calculated for 175 members; of these, 32 have had GRA programs since 2008; 13 countries (2 of which with programs) are not covered due to data constraints.
- Practical challenges in incorporating composite into quota formula:
  - Composite lacks an economic size dimension and can take both positive and negative values.
  - Transformations to avoid negative values and introduce size are largely arbitrary and can lead to very different outcomes for members and groups.
  - Non-linear transformations can reduce the correlation with potential use of Fund resources (example: 0.19 reduced to 0.09).
  - Complexity, data requirements, arbitrary choices of variables and transformations, and applicability to reserve currency issuers limit practicality.
- Staff judgment:
  - Composite variability measures provide some additional information and yield more stable shares through most of the sample, but do not provide sufficiently robust results to support inclusion in the quota formula.
  - Staff continues to see a case for dropping variability from the formula given the difficulty of designing a measure that fits all members, performs well across circumstances, and remains simple and transparent.

### Financial contributions: scope and measurement considerations
- Forms of members’ financial contributions (as identified):
  - Voluntary contributions: bilateral and multilateral support for Fund liquidity in the GRA, loan and subsidy contributions to the PRGT, voluntary SDR trading arrangements, and technical assistance and training (TA).
  - Mandated contributions: Financial Transactions Plan (FTP) participation, charges and fees associated with borrowing from the Fund, and burden-shared contributions.
- Data and practical issues:
  - Some contributions (e.g., voluntary SDR trading arrangements) are not published and may be amended at any time.
  - Contributions differ in magnitude and form (budget outlays vs temporary provision of loans at the SDR interest rate).
  - Computing opportunity costs would be complicated; timing and magnitude of drawings on commitments (NAB and bilateral loans) are uncertain.
  - Practical approach: include contributions on a commitment basis to reflect amounts members stand ready to provide.
- Aggregation approach:
  - Use members’ shares of contributions for each form and sum shares to create an aggregate measure—allows comparability with other quota variables but abstracts from absolute contribution sizes and requires periodic reassessment of included forms.

### Illustrative aggregate measures of financial contributions (constructed for illustration)
- Data focus: contributions that mainly cover the past two decades; five illustrative measures calculated using Table 8 data.
- Definitions:
  - FCS I: simple average of members’ contribution shares to the four voluntary financial contributions—NAB and bilateral pledges, PRGT loans, PRGT subsidies, and TA activities.
  - FCI II: same as FCS I, but also includes share of members’ quarterly participation in the FTP as measured by relative quota shares of participants in each quarter during 1992—2011.
  - FCS III: weighted average with weights: NAB/bilateral resources (0.3), FTP participation (0.3), PRGT loans and subsidies combined (0.2), TA activities (0.2).
  - FCS IV: higher of 14th Review quota share or FCS I share rebased to sum to 100 percent; recognizes members providing contributions in excess of their quota shares but treats contributors below their 14th review shares the same as non-contributors.
  - FCS V: distinguishes FTP participants and non-FTP participants:
    - For non-FTP participants, FCS V set equal to 14th Review quota share.
    - For FTP participants, the aggregate of their 14th Review quota share is distributed across participants according to relative shares in FCS I.
- Purpose of illustrative measures: highlight decisions needed on which contributions to include and how to weight them; additional refinement possible if sufficient Director support exists.

*Source: Finance Department*

### 34.      In general, these measures tend to heavily favor advanced economies. This

### _062812 - 34.      In general, these measures tend to heavily favor advanced economies. This

### Distribution of financial contributions and headline findings
- "In general, these measures tend to heavily favor advanced economies."  
- Advanced economies have been the largest contributors in 3 of the 4 categories examined (PRGT loans and subsidies, and funding for technical assistance).  
- "The share of advanced economies in the NAB and bilateral pledges combined is somewhat lower, but still over 70 percent."  
- "For the first three measures, the share of advanced economies in the variable is 80-85 percent."  
- The fourth and fifth measures, which mix simple indicators of ability to contribute with actual contributions, produce a somewhat lower share for advanced economies but "it still remains close to or above 70 percent."

### Box 2 — Ad hoc quota increases: liquidity and financial contributions (selected historical instances)
- Liquidity considerations and the provision of financial resources (e.g., GAB, NAB participation) have played a role in ad hoc quota increases; such financial contributions were generally a supplementary criterion for recipients whose quotas were considered not to adequately reflect their economic positions.
- 1958/1959 Review: Special increases in addition to the overall 50 percent increase were given to Canada, Germany, and Japan to reflect economic factors and ability to contribute to the Fund’s liquidity.
- 4th Quinquennial Review (1965)/Ad hoc for Italy (1964): Special increases for 16 members in addition to the overall 25 percent increase (resulting in a total increase of 30.7 percent); Italy’s quota was almost doubled to improve liquidity and comparability.
- Ad hoc increase for Saudi Arabia (1981): Almost doubling of its quota was partly based on need to improve Fund liquidity and the borrowing arrangement with SAMA.
- 9th General Review (1990): Japan received an ad hoc increase on top of the overall 50 percent increase because of deviation between actual and calculated quota share and large potential to strengthen Fund liquidity.
- 11th General Review (1997): One percent of the overall increase was distributed to five members (Korea, Luxembourg, Singapore, Malaysia, and Thailand—all NAB participants) expected to contribute to Fund liquidity over the medium term.

### Box 3 — Alternative approaches to capturing financial contributions
- World Bank/IDA approach (reform to enhance voice and participation): realigned shareholding across three measures—economic weight (GDP-blend), financial contributions (IDA contributions), and development contributions—with 20 percent of realignment depending on financial contributions (75 percent economic weight, 5 percent development contributions). Mechanisms accounted for current, past, and future IDA contributions and recognized above-average contributors and future pledges.
- Proposed protection mechanism considered in the 14th Review: a protection mechanism for over-represented members that made significant voluntary financial contributions (aggregating PRGT loans, PRGT subsidies, technical assistance, and the NAB). Identified beneficiaries: Belgium, Canada, France, Germany, Italy, Japan, Netherlands, Sweden, and Switzerland. The mechanism would limit quota losses for that group.

### Key statistics from aggregate tables (selected exact figures as presented)
- Aggregate shares and totals (Table 8 / Table 9):  
  - Total100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0  
  - Advanced Economies (Table 8 first row): 57.65 56.12 3.95 55.38 1.76 0.07 4.57 1.09 1.18 5.39 2.4  
  - Major advanced economies (Table 8): 43.44 40.61 7.31 7.36 2.04 9.25 7.54 9.37 4.66 3.07 2.3  
  - United States (Table 8): 17.4 15.8 1.6 2.5 24.1 11.0 15.5 5.9 0.0 9.3 0.5  
  - Japan (Table 8): 6.5 6.2 12.3 2.5 8.3 18.4 18.5 15.2 26.8 16.7 2.0  
  - Emerging Market and Developing Countries (Table 8): 42.44 43.97 6.14 44.71 8.34 0.02 5.25 29.0 8.9 14.7 7.6  
  - China (Table 8 note 9 grouping): 6.4 9.4 30.5 2.4 4.0 0.0 8.7 9.2 3.9 1.0 0.0  
  - Memorandum items (Table 8): Total contributions (in millions of SDRs) 51,900 181,486 476,598 25,854 5,267 550  
  - EU27 (Table 8 memorandum): 30.2 30.9 8.1 44.7 41.1 23.1 34.2 45.6 53.6 48.3 19.3
  - LICs (Table 8 memorandum): 4.0 2.6 2.1 0.0 0.0 1.0 0.0 0.0 0.0 3.1 1.3

(Note: these figures are presented in the source tables as percent shares and memorandum items; values above are shown exactly as in the tables.)

### Illustrative calculations and simulation results (Section IV, paragraphs 35–39)
- Purpose: Present illustrative calculations showing impacts on CQS of possible formula modifications using the new data set; four sets of simulations are presented:
  1. Simplifying the formula by dropping one or more variables.
  2. Changing weights of GDP measured at market exchange rates and at PPP in the GDP blend.
  3. Including financial openness explicitly (using IIP gap-filled as proxy) and adjusting for financial centers with a cap.
  4. Incorporating a measure of financial contributions in the formula.
- Main results from simplification simulations (Table 10; paragraph 36):  
  - Dropping variability: Aggregate CQS of advanced economies and EMDCs remains unchanged; significant shifts within groups—shift from other advanced to major advanced economies; within EMDCs, Asia and Western Hemisphere tend to gain.  
  - Dropping variability and reserves: Overall shift toward advanced economies, especially major advanced economies; most EMDC regions lose share except Western Hemisphere. Shifts most pronounced when weights of dropped variables are redistributed to GDP.  
  - Dropping openness and variability: Overall shift toward EMDCs, with strong gains in Asia and Western Hemisphere; major advanced economies gain while other advanced economies record sizable losses.  
  - A GDP-only formula: Overall shares between advanced economies and EMDCs broadly unaffected, but large internal changes—major advanced economies gain at expense of other advanced economies; among EMDCs, Brazil, China, and India record sizable gains; regional shift toward Western Hemisphere and away from Middle East, Malta, and Turkey and Transition economies.
- Changing the PPP weight in the GDP blend (Table 11; paragraph 37):  
  - Increasing the weight of PPP GDP from 40 to 50 percent would result in a 0.8 pp increase in the CQS of EMDCs with all sub-groups benefitting (except Africa, whose share remains unchanged). China and India gain the most. The share of LICs also rises slightly.
- Increasing weight on financial openness (Table 12; paragraph 38):  
  - Financial openness variable modified to give equal weight to trade and financial openness, where financial openness is proxied by IIP (gap filled, applying a cap at the 95th percentile to the ratio of IIP to GDP). This yields "a shift of over 2 pp in favor of advanced economies."  
  - Combining increased weight on financial openness with (i) dropping variability, and (ii) dropping both variability and reserves yields larger shifts; dropping both variability and reserves leads to a "4–4.8 pp shift in favor of advanced economies."
- Including financial contributions in the formula (Table 13; paragraph 39):  
  - Using the FCS III aggregate measure of financial contributions (weighted average of FTP participation and NAB/bilateral pledges, PRGT, and technical assistance contributions) and introducing this variable in place of reserves with the same weight leads to "a shift in shares of about 2.7 pp in favor of advanced economies," with gains widely shared within that group.  
  - Variants that (i) drop variability and add financial contributions in addition to reserves, and (ii) drop variability and reserves, are presented; the former partially mitigates the impact of introducing financial contributions on the aggregate share of EMDCs.

*Source: Finance Department (as presented in the source PDF content).*

### 40.        Overall, these calculations illustrate the implications of a wide range of possible

### Overall, these calculations illustrate the implications of a wide range of possible

### Illustrative calculations and distributional implications
- Increasing the weight of the GDP variable at the expense of other variables tends to benefit the major advanced economies and a number of large EMDCs.
- A larger weight for financial openness and introducing a measure of financial contributions tends to favor many advanced economies.
- EMDCs as a group would gain from increasing the weight of reserves and of PPP GDP.
- The paper presents several illustrative calculations showing impacts on members’ CQS, including:
  - Options for simplifying the formula.
  - Options for increasing the weight on financial openness.
  - Options for including a measure of members’ financial contributions to the Fund.

### Representative quota-share outcomes (selected items from illustrative tables)
- Advanced economies: 57.6; 56.1; 56.1; 56.1; 58.0; 57.7; 53.6; 54.9; 56.5 (values reproduced exactly as presented across different formula variants).
- Major advanced economies: 43.4; 40.6; 41.4; 41.9; 42.9; 43.3; 42.4; 43.6; 44.9.
- United States: 17.4; 15.8; 16.2; 16.8; 17.0; 17.7; 18.5; 19.2; 20.1.
- China (including China, P.R., Hong Kong SAR, and Macao SAR): 6.4; 9.4; 10.1; 10.1; 9.1; 9.3; 11.6; 10.9; 10.1.
- Emerging Market and Developing Countries (EMDCs): 42.4; 43.9; 43.9; 43.9; 42.0; 42.3; 46.4; 45.1; 43.5.
- Total: 100.0 across all illustrative quota-share scenarios.

### Coefficients and formula variants (selected coefficients reproduced exactly)
- Example coefficient sets from tables (coefficients for quota variables):
  - Market GDP: 0.3000; 0.3530; 0.3900; 0.3750; 0.4200; 0.5450; 0.5700; 0.600
  - PPP GDP: 0.2000; 0.2350; 0.2600; 0.2500; 0.2800; 0.3640; 0.3800; 0.400
  - Openness: 0.3000; 0.3530; 0.3000; 0.3750; 0.3000; 0.0000; 0.0000; 0.000
  - IIP: 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.000
  - Variability: 0.1500; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.000
  - Reserves: 0.0500; 0.0590; 0.0500; 0.0000; 0.0000; 0.0910; 0.0500; 0.000
  - Financial Contributions: 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000; 0.0000
- Alternative GDP blends illustrated (Table 11 coefficients reproduced exactly for one variant):
  - Market GDP: 0.3000; PPP GDP: 0.2000; Openness: 0.3000; Variability: 0.1500; Reserves: 0.0500; Financial Contributions: 0.0000
  - For 50-50 and 70-30 blends, alternative coefficient mixes are shown (preserved in the tables).

### Financial openness and financial contributions variants
- Modified formula variants replace or adjust the traditional openness variable:
  - The traditional openness variable is replaced with IIP gap-filled, as a proxy for financial openness, and trade openness (openness minus investment income) weighted equally.
  - In one variant the traditional openness is replaced with IIP gap-filled and capped at the 95th percentile, as a proxy for financial openness, and trade openness weighted equally.
- Table 12 and Table 13 present illustrative quota-share outcomes under these modified formulas and under variants that allocate a weight to Financial Contributions (e.g., Financial Contributions replaces reserves with a weight of 0.05 in one variant).

### Data update, timeline, and staff plans
- The paper updates the quota data through 2010.
- This is the last data update before the January 2013 deadline for completing the quota formula review.
- Staff plans to prepare a follow up paper that could lay out possible options for moving forward, based on Directors’ views and bearing in mind the 2008 reform principles reaffirmed by most Directors and by G-20 Leaders.

### Issues and questions for Directors (as listed in the paper)
- What are Directors’ views on the possible options discussed in the paper for simplifying the quota formula? What are the key variables that should be preserved?
- What are Directors’ views on the weight and composition of the GDP blend variable?
- How do Directors see the merits of increasing the weight on financial openness in the quota formula? Views are invited on specific options discussed in the paper, including:
  - (i) the use of gap filled IIP data or alternatively of a larger weight for investment income as a proxy for financial openness, and
  - (ii) the alternative approaches for addressing the particular situation of international financial centers?
- Do Directors agree that there is a case for dropping variability, given the shortcomings that have been identified with the current measure and the challenges in identifying a superior measure of members’ potential demand for Fund resources?
- What are Directors’ views on how best to reflect members’ financial contributions in quota adjustments, including the options for including a measure of such contributions in the formula itself? If such a measure were included, should it be additional to or instead of the existing reserves variable? 

*Source: Finance Department.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/np/pp/eng/2012/_062812.pdf_