IMF Policy Paper: A New Quota Formula - Additional Considerations, Statistical Appendix, and Statement by the Managing Director

An informal Executive Board seminar in December 2006 made an important start in the development of a new quota formula.

Abstract

An informal Executive Board seminar in December 2006 made an important start in the development of a new quota formula.

I. Introduction

1. An informal Executive Board seminar in December 2006 made an important start in the development of a new quota formula.2 The discussion was wide ranging, raising a number of important issues that need to be considered further in the development of a formula that can achieve the objectives of the quota reform and command the required broad support within the membership.

2. This paper seeks to provide a basis for a second discussion, including by exploring issues raised at the December meeting. The paper also provides further simulations based on a wider range of assumptions regarding possible variables and their weights, as requested by many Directors. As with the last paper, it should be emphasized that this paper does not seek to propose any particular formula and that all the simulations presented should be seen as illustrative and as merely an aid to discussion. Nevertheless, it is hoped that the discussion of this paper will help lay the groundwork for beginning to narrow options and moving toward formulation of a specific proposal in the coming months.

3. The paper does not address the size of the second round ad hoc quota increases.

This question, which is closely linked to the magnitude of the increase in basic votes, will be taken up at a later stage once the discussion of the formula is more advanced.

II. Stocktaking

4. At the December seminar, there appeared to be broad acceptance of the principles that the paper suggested should guide the new formula, namely that the formula should be simple and transparent, consistent with the multiple roles of quotas in the Fund, result in calculated quota shares broadly acceptable to the membership, and be feasible to implement statistically.3 Beyond this, there were significant differences of view regarding the definition and weights of the variables, and some suggestions for additional variables beyond the traditional four (GDP, openness, variability, and reserves).

5. One overarching issue arising from the simulations provided in the previous paper is that a simple linear formula with a higher weight on GDP than in the present formulas (with GDP at market exchange rates) tended to result in a higher calculated quota share for advanced countries as a group (and a lower share for developing and transition countries) than under the existing formulas. While it can be argued that the development of the new formula should not aim at particular outcomes for groups of members, it has been questioned whether such an outcome is consistent with what many see as the broad goals of the reform, including giving a greater voice to the Fund’s most dynamic members, many of which are emerging market countries.

6. A range of specific proposals were made during the December seminar, including exploring a possible role for GDP at purchasing power parity (PPP) and a population variable. The possible introduction of a compression factor was also discussed, and there were calls for further work related to financial openness, the treatment of intra-currency union flows and the possible capping of the reserves variable. In addition, there were requests for simulations based on alternative assumptions for the scenarios provided in Quotas— Further Thoughts on a New Quota Formula (2006), including different weights for GDP and alternative compression factors. These and other issues are taken up in the remainder of this paper.

III. Variables

A. GDP conversion

7. While it is broadly accepted that GDP should play an important role in the quota formula, differences of view remain about how GDP should be converted into a common currency. To date, GDP has always been converted at market exchange rates for quota purposes. This section explores further the possible role for PPP GDP and its potential implications for calculated quota shares.4

8. This issue can be approached from the perspective of the roles of quotas in the Fund, as discussed in Quotas—Further Thoughts on a New Quota Formula (2006). Quotas provide the Fund’s financial base, play a significant role in determining members’ access to Fund resources, and, together with basic votes, determine the distribution of voting power in the Fund. Quota shares have also provided an important metric in past resource mobilization efforts, such as for the PRGF-HIPC Initiative. From the perspective of the Fund’s financial operations, GDP at market rates clearly appears the most appropriate variable. GDP at market rates has been viewed as the single most important indicator of ability to contribute to the Fund and as most relevant to a member’s capacity to borrow since it reflects the international market value of resources generated by the economy. The majority of the quota formula review group (QFRG) viewed GDP at market rates as the appropriate GDP variable, primarily from the standpoint of GDP as an indicator of capacity to contribute financial resources to the Fund.5

9. However, it has been argued that PPP GDP may be relevant to the Fund’s non-financial activities, particularly surveillance but also capacity building. While there is a close link between surveillance and Fund lending, surveillance also has broader public good aspects that are important for all members. PPP GDP is a measure of the volume of goods and services produced by an economy. This is why it is used in the World Economic Outlook (WEO) for measuring global and regional GDP and its growth. Hence, it has been argued that PPP GDP is a relevant measure of “weight” in the global economy.

10. Given that quotas have both financial and non-financial roles, it has been suggested that consideration be given to a blended GDP variable, using a combination of GDP at market rates and PPP GDP. If such a variable were to be considered, deciding the proportions of the two GDP measures in a blended variable would be a matter for the collective judgment of the membership, taking into account a range of factors including the roles of quotas, the links between these roles, and the data issues discussed below. However, to the extent that quotas remain central to the Fund’s finances, it would seem appropriate that GDP at market rates continue to play an important role.

11. As discussed previously, data quality issues have also been viewed as impeding consideration of using PPP GDP to date. The currently available data on PPP GDP have substantial weaknesses, with coverage and quality issues at a country level that could significantly complicate their use for quota purposes. These weaknesses include long lags since benchmarks were established for many members, gaps in participation that force heavy reliance on estimation, and a lack of common methodology, sources and benchmark years.

12. In recognition of these issues, a major effort is underway as part of the latest round of the International Comparison Program (ICP) to upgrade the quality of available PPP GDP data. The Board was recently briefed on this work, which is scheduled to be completed by end-2007. Its objective is to provide a consistent database on PPP GDP using a common benchmark year for the 147 economies (not all of them Fund members) participating in this voluntary program. Completion of this project should go a long way to addressing the data quality concerns surrounding use of PPP GDP for quota purposes.

13. While not insurmountable, some timing and other uncertainties remain in this regard. The current ICP round represents a major undertaking involving many participants, and slippages in the timetable cannot be excluded, which could mean that updated PPP GDP data may not be available for at least some countries by end-2007 as planned. Given the substantial methodological changes involved, it is also possible that participating countries may need time to review the new data before they are fully accepted. In addition, estimates would be required for the 41 Fund members not participating in the current ICP round, and perhaps others. Also, while preliminary discussions among participants are encouraging, there is no agreement as yet on the continuation of the ICP beyond the current round, which could have a bearing on the continued availability of high quality PPP GDP data for use in future quota calculations beyond the current reforms.

14. Use of PPP GDP would have significant implications for the distribution of calculated quota shares. While the new ICP round is likely to lead to significant changes in PPP GDP estimates for individual countries, the currently available PPP GDP data should provide at least a broad indication of the impact of incorporating a blended GDP variable into the formula. As discussed in Quotas—Further Thoughts on a New Quota Formula (2006, Table 1), the shares of different country groups in global GDP at market rates and PPP GDP differ significantly (individual country data were provided in Supplement 2 to Quotas— Further Thoughts on a New Quota Formula, 2006). Reflecting these differences, Table 1 of this paper illustrates the implications of a blended GDP variable, with a full range of blends for the weight on PPP GDP from 0 to 100 percent at intervals of 25 percentage points. For purely illustrative purposes, the total weight on GDP is assumed to be 50 percent; openness, 30 percent; variability, 15 percent; and reserves, 5 percent, with the other variables as defined in Quotas—Further Thoughts on a New Quota Formula (2006), pages 15-16. It must be stressed that the choice of variable weights and definitions is not intended to prejudice the outcome of the discussion on these issues. A single set of weights is used merely to avoid the presentation of multiple scenarios that would not shed additional light on the impact of using PPP GDP. In general, the impact is to reduce the calculated quota share of advanced countries and increase that of developing countries, with the effect more pronounced the larger the weight of PPP GDP in the blended variable. The impact varies across members depending on a variety of factors, including per capita income and the relative size of the traded and non-traded goods sectors. Country-by-country results are presented in Table 1a of a supplement to this paper being issued concurrently.

Table 1.

Scenarios Using GDP Blends 1/ (In percent)

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Source: Finance Department.

GDP at market rates and GDP at purchasing power parity rates blended in proportion indicated.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

0.5*GDP + 0.3*Openness + 0.15*Variability + 0.05*Reserves.

A GDP blend (x/y) is defined as χ percent of GDP weighted at market exchange rates and y percent weighted at PPP-exchange rates. PPP data were retrieved from the WEO database for 176 countries. For nine countries with no WEO data, PPP GDP was estimated based on each country’s share in global GDP at market rates.

Including Korea and Singapore.

PRGF-eligible countries.

B. Population

15. At the December seminar, suggestions were also made for further consideration of the inclusion of population in the new formula. Inclusion of population is by no means a new idea, and indeed has been discussed since the first formula was established at Bretton Woods. Proponents have noted that global decision-making affects the economic welfare of all individuals—that is the public goods provided by the Fund seek to maximize global economic welfare, and all individuals have a stake in those public goods.6 Basic votes may be seen as recognizing this argument at the country level, but are not related to population since all countries receive the same number of basic votes regardless of the size of their populations. Thus, a case has been made for including population in the quota formula from the perspective of measuring members’ relative stakes in the international public goods provided by the Fund. This case is in some ways similar to that for PPP GDP; the measures themselves have a correlation of 0.67 (see Quotas—Further Thoughts on a New Quota Formula, 2006, Table 2). Also, reliable data on population are generally available. In past discussions, however, inclusion of a population variable has not received broad support on the grounds that the Fund is essentially a monetary institution, and population is a non-economic variable that does not bear directly on international monetary issues. Given these considerations, and the important financial role of quotas, it would seem appropriate that if a population variable is considered, its weight should be relatively small compared with the main economic variables that have been discussed to date.

Table 2.

Scenarios Using GDP Blends and Population 1/ (In percent)

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Source: Finance Department.

GDP at market rates and GDP at purchasing power parity rates blended in proportion indicated.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

0.5*GDP + 0.3*Openness + 0.15*Variability + 0.05*Reserves.

A GDP blend (x/y) is defined as χ percent of GDP weighted at market exchange rates and y percent weighted at PPP-exchange rates. PPP data were retrieved from the WEO database for 176 countries. For nine countries with no WEO data, PPP GDP was estimated based on the countries’ share in global GDP at market rates.

(a/b/c/d/e) are the coefficients of GDP/Openness/Variability/Reserves/Population, all expressed in shares of global totals.

Including Korea and Singapore.

PRGF-eligible countries.

16. Inclusion of population in the quota formula would tend to increase calculated quota shares for developing countries. As shown in Table 1 of Quotas—Further Thoughts on a New Quota Formula (2006), the shares of major country groups in world population differ substantially from those for the main economic variables that have been considered relevant for a new formula. For example, based on 2004 data, advanced countries made up about 14 percent of the world’s population, with developing and transition countries accounting for 80 and 6 percent, respectively.

17. This said, depending on the choice of weights, including a population variable with a reduced weight for market-rate GDP can lead to results at the group level that are similar to inclusion of PPP GDP in a blended variable (based on current PPP GDP data), though with some differences at the country level. This is illustrated in Table 2 (and Table 2a of the supplement), which shows the effect of replacing 5 (and 10) percentage points of the weight on GDP at market rates in the base formula in Table 1 with a 5 (and 10) percent weight on population. These simulations yield very similar results at the group level to the formula with a 50 percent weight on a blended GDP variable with 25 percent (and 50 percent) PPP GDP. The outcomes with other PPP GDP blends and different weights on population can be similarly compared.

C. Openness

18. At the December seminar, there were calls for further work on how the variable can be modernized to include financial as well as trade openness. Issues arising from measuring gross flows rather than value added and the possible case for making an adjustment for intra-currency union flows were also discussed. A variety of views were expressed on the importance to be given to the openness variable in a new quota formula.

Financial openness

19. Financial openness has long been viewed as potentially relevant to the multiple roles of quotas. The conceptual case is broadly similar to that for the existing openness variable: in a modern world, integration in global capital markets is an increasingly important indicator of a member’s stake in the global economy and in global financial stability; it is also relevant to a member’s ability to contribute to the Fund’s finances and its potential need for Fund resources. The latter is already recognized in the proposal to modernize the measure of variability by including net capital flows as well as current receipts.7 However, data issues have so far impeded development of a satisfactory measure of financial openness.

20. In previous discussions, consideration has been given to both qualitative and quantitative measures. However, it has generally been agreed that only the latter could provide a sufficiently objective basis to be used for quota calculations.8 There are two broad options for a quantitative measure: stocks and flows.

21. A stock variable that has been considered in the past is the absolute sum of a member’s foreign financial asset and liability positions reported as part of its International Investment Position (IIP). Such a variable would seem well related conceptually to the issue of capital market integration, as it provides a quantitative measure of the extent of investment in a country by non-residents, and of offshore investment by residents of the same country. But, as noted in previous papers, data availability remains an important constraint: while there have been significant advances in the coverage of IIP data in recent years, full or partial IIP data are currently available for 106 countries, with only 85 considered comprehensive reporters.9 Staff have examined the possibility of gap filling, but do not consider this viable at present.10 Also, differences arise in the valuation of direct investment, with some countries reporting it at market value and others at book value.

22. Financial flow data could also be considered as a parallel to the use of current receipts and payments in the existing openness variable. One such option is to use investment income as a proxy for IIP. This would have the advantage of using already available data, as investment income is included as part of current receipts and payments in the existing openness measure.11 For the membership as a whole, the correlation between investment income and IIP is high at 0.98 for the subset of countries that currently report comprehensive IIP data. Differences for individual countries may reflect differences in earning rates across asset and liability classes, differences in composition, and likely under-reporting of investment income flows (and positions) in some cases.12 Table 3 shows the shares in global totals for both measures, with investment income shares presented both for the subset of IIP reporting countries and for the membership (data for individual countries are provided in Table 3a in the supplement). For the sub-group of IIP reporting countries, advanced countries account for about 90 percent of the global totals, in part reflecting the fact that non-reporters mainly comprise developing countries. Even looking at the whole membership in the case of investment income flows, however, advanced countries still account for about 81 percent of the total. Among individual countries, some members with important international financial centers have relatively large shares of both IIP and investment flows (e.g., Ireland, Luxembourg, and the United Kingdom), and further consideration would need to be given to the adequacy of the adjustments made to these data for the purpose of quota calculations (see below).13

Table 3.

Investment Income as a Proxy for IIP—Shares in Global Totals

(In percent)

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Sources: Finance and Statistics Departments.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Assets plus liabilities; shares of reporting countries; 73 members reporting in 2004.

Investment income in the current account, adjusted for international banking interest. Investment income is for the 73 countries reporting IIP in 2004.

Investment income, adjusted for international banking interest, for 177 members.

Including Korea and Singapore.

PRGF-eligible countries.

23. Investment income could be used as a proxy for IIP by treating these flows separately from other current account flows and giving them a different weight in a new openness variable.14 On average, the implicit weight of investment income in the total openness measure at present is about 10 percent, reflecting the size of investment income relative to other current account flows. To better capture financial openness, investment income flows could be given a higher weight. The precise choice of weights would need to be determined, taking account of such factors as the relative importance to be given to trade and financial considerations in the new openness measure.

24. As an alternative approach, staff have examined the possible scope for developing a measure of aggregate financial asset and liability flows. Conceptually, such an approach would focus on gross flows related to three broad categories of the financial account: foreign direct investment; portfolio investment and financial derivatives; and other investment (Box 1). In practice, however, such gross flow data are not available; instead, IFS data for the financial account reflect asset and liability flows, broken down by functional category (direct, portfolio, etc) and by instrument, where they are measured on a net basis. As such, a financial account measure can as a practical matter only reflect the aggregation of net asset and liability flows for each balance of payments functional category.15 Such a measure understates the overall scale of financial flows, and therefore may not fully capture differences in financial integration across countries. Churning (or the in-and-out movement of capital related to short-term flows) has been a concern with gross flows data; the effective netting implicit in the financial account flow data would reduce, but not necessarily eliminate, this concern.

Financial Account Functional Categories

The flow measure described in the main text is based on the aggregation of assets and liability flows recorded in each functional category in the financial account, excluding reserves. These financial account categories are:

  • Direct Investment: these transactions reflect the lasting interest of a resident entity in one economy (direct investor) in an entity in another economy.

  • Portfolio Investment and Financial Derivatives: Portfolio investment covers transactions in equity and debt securities. Financial derivatives (or secondary instruments) usually do not extend to actual delivery and are utilized for hedging risks, investment, and trading purposes. These data are reported separately in the Balance of Payments Statistics Yearbook (BOPSY); that said, only 46 members report financial derivatives flows, with many countries reporting these transactions in the portfolio investment category of the BOPSY. Also, the financial derivatives category does not exist in the WEO. For these reasons, these two categories are presented together in this report.

  • Other Investment: This is a residual category in the financial account that includes financial transactions not covered in direct investment, portfolio investment and financial derivatives, or reserve assets. The instrument classification comprises trade credits, loans, currency and deposits, and other assets and liabilities.

25. In addition to this conceptual question, data issues would also need to be resolved. Financial account data in many countries, including those reported in the IFS, are uneven in terms of accuracy and are generally less comprehensive than the other data used for the quota formulas. Also, as for other variables, gap-filling would be required for countries where data are not available through the IFS. However, gap-filling for the financial account is generally more problematic than for other quota data because WEO data involve a higher degree of netting and because financial account data are more volatile on a year-to-year basis. Staff have compiled a dataset for purely illustrative purposes, but the issue of whether such a measure is feasible statistically would need to be further considered if a financial account based flow variable were pursued.

26. Table 4 summarizes the shares in global totals of major country groups for investment income and each of the financial account categories discussed above, including the aggregate of the financial account categories. Individual country data are presented in Table 4a of the supplement. It is evident that any of these flow-based measures of financial openness would give a high weight to advanced countries; this effect is most pronounced for the financial account categories and somewhat less so in the case of investment income flows, in part due to the fact that no data adjustments have been made to the financial account data.16 In this context, an examination of the individual country data underlying these flows highlights the role played by international financial centers; for example, the share of the United Kingdom in global “other investment” is 26.1 percent, Luxembourg accounts for 11.2 percent of global FDI, and the Netherlands accounts for 10.2 percent of total portfolio investment and financial derivative flows. This applies across all financial account categories, suggesting that the data adjustment issues involved in the use of financial account flows could be particularly challenging. It is also not clear that there is a strong conceptual basis for excluding one or more categories from the measure.

Table 4.

Financial Openness Variables (In percent)

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Sources: Finance and Statistics Departments.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Investment income is the average investment income in the current account, adjusted for international banking interest.

This is the sum of the absolute value of assets and liabilities in the financial account of the Balance of Payments for direct investment.

This is the sum of the absolute value of assets and liabilities in the financial account of the Balance of Payments for portfolio investment,

including financial derivatives.

This is the sum of the absolute value of assets and liabilities in the financial account of the Balance of Payments for other investment.

This is the sum of the absolute value of assets and liabilities in the financial account of the Balance of Payments for direct investment (FDI),

portfolio investment and financial derivatives (PI), and other investment (Ol).

Including Korea and Singapore.

PRGF-eligible countries.

27. Table 5 illustrates the possible effect of explicitly including a financial element as part of the openness variable. Using the same baseline as in Table 1 for illustrative purposes, a blended openness measure has been constructed using investment income flows for which the conceptual and data issues appear on balance less problematic than for financial account flows. Again for purely illustrative purposes, equal weights have been given to the trade and financial components of openness in each case. As can be seen, advanced country shares generally increase versus the base scenario from Table 1. As demonstrated in Table 5a of the supplement, these effects are most pronounced for individual members with prominent international financial centers.

Table 5.

Simulated Quota Shares—Financial Openness (In percent)

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Source: Finance Department.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Financial openness and trade openness are blended in equal proportion. Financial openness is measured as average investment income in the current account adjusted for international banking interest. Its weight in the standard openness variable is 10.9 percent. Trade openness is the average sum of current receipts and payments, excluding investment income, adjusted for re-exports and non-monetary gold.

Including Korea and Singapore.

PRGF-eligible countries.

Intra-currency union flows

28. At the December seminar, suggestions were also made for further work on whether intra-currency union flows should be excluded from the measure of openness.17

The Fund has recognized the special characteristics of currency unions in its surveillance structure, with special modalities for members of such unions.18 In terms of the quota exercise, this raises the question of whether there is a conceptual case for making a specific adjustment to the data used for quota calculations for members of currency unions. Two aspects have been raised in this regard: (i) that the measure of openness captures gross flows rather than value added and the possibility that increases in these flows as a result of growing specialization and integration within a currency union may tend to overstate the openness of these countries from a broader global perspective; and (ii) that flows within a currency union take place in a common currency.

29. On the former, some proponents of excluding intra-currency union trade have argued that gross trade figures present a distorted picture of trade integration for members of a currency union. They note that currency union membership encourages greater vertical integration of production processes, creating an upward bias in gross trade figures versus domestic value added. The issue is complicated, however, by the difficulty of determining the degree to which the currency union itself is the driver for increased intraregional trade and vertical integration.19 Such integration is not unique to currency unions, but is also relevant to other liberalized trading regimes (e.g., free trade agreements and customs unions), raising difficult questions about where the dividing line for exclusion would be drawn. Also, vertical integration is playing an increasingly important role in global trade more broadly.20 The QFRG noted that, while economic unions can lead to substantial “double-counting” of cross-border trade relative to value added in economic activity, this issue arises whenever there is close economic integration between two or more countries and not just when a formal economic union has been established.21

30. That intra-currency union flows take place in a common currency has also been cited as a reason for their possible exclusion for the purpose of quota calculations. This argument focuses primarily on the role of quotas in determining potential access to Fund resources, and on whether intra-currency union flows should be taken into account in that regard. The existence of a currency union reduces an important source of potential balance of payments risk for its members (i.e., exchange rate risk), particularly in cases where intraunion stocks and flows account for a large share of the members’ total external balance sheet position and balance of payments. That said, currency union membership does not preclude the possibility of balance of payments difficulties arising from other sources of country-specific risk, including macroeconomic risk, political risk, and or liability-related risk arising in either the public or private sector. In 1998, the Executive Board noted that identification of balance of payments need is likely to be more difficult in currency unions, but also that circumstances could arise where such a need could be discerned, a view that was supported by the QFRG. In practice, the Fund has provided balance of payments support to a number of currency union members of the WAEMU, CEMAC, and ECCU. Pooling arrangements between members of a currency union provide some additional protection against balance of payments pressures, but such arrangements are also not unique to currency unions. Thus, while there could be a question as to whether transactions within a currency union are as relevant to a country’s potential need for Fund resources as transactions outside the currency union area, the issue is complex and not easy to resolve.

31. Were a decision taken to exclude intra-currency union flows, some difficult data issues would arise. Specifically, while time-series data for intra-currency union merchandise trade are generally available, services data are incomplete.22 Also, if the definition of openness were to be modified to explicitly include financial openness, this would raise the question of whether to also exclude intra-union financial flows and, if so, how.

32. Table 6 illustrates the potential impact of excluding intra-currency union merchandise trade flows. These calculations use the same baseline as the previous tables, and adjustments are limited to available data on intra-currency union trade. The main impact is to reduce the aggregate calculated quota share of euro-area members by 2.8 percentage points. For members of other currency unions (WAEMU, CEMAC, and ECCU), the impact is more modest as intra-currency union trade is generally smaller for these members, and they also benefit from the decline in share for euro-area members. The data for individual members are shown in Table 6a of the supplement.

Table 6.

Intra-Currency Union Trade—Openness and Variability Shares and Results of Linear Formula

(In percent)

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Sources: Finance and Statistics Departments.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Openness is defined as the sum of current receipts and current payments.

Exports and imports of goods between members within the currency unions of the EU-12, ECCU, CEMAC, and WAEMU are excluded.

0.5*GDP + 0.3Openness + 0.15*Variability + 0.05*Reserves.

Including Korea and Singapore.

Austria, Belgium, Germany, Finland, France, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, and Spain.

Antigua and Barbuda, Dominica, Grenada, St. Kitts and Nevis, St. Lucia, and St. Vincent and the Grenadines.

Cameroon, Central African Republic, Chad, Republic of Congo, Equatorial Guinea, and Gabon.

Benin, Burkina Faso, Cote d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo.

33. The above estimates for the impact on euro-area members are sensitive to the weight on openness in the new formula. As Table 6 shows, the adjustment for intra-currency union trade reduces euro-area members’ share in total openness significantly from 31.8 to 23.3 percent, and in variability from 23.1 to 21.4 percent. The resulting decline in the aggregate calculated quota share of euro-area members would be significantly larger (5.9 percentage points) using the existing formulas because the effective contribution of both current receipts and payments combined under the existing formulas is about 50 percent on average for the membership as a whole, and is even higher for euro-area members as a group.23

D. Measures of Potential Demand for Fund Resources

34. Variability has traditionally been included in the quota formulas as a measure of members’ potential need for Fund resources, as discussed in Quotas—Further Thoughts on a New Quota Formula. Variability was included in the original Bretton Woods formula and was one of the two variables recommended for inclusion in a new formula by the QFRG (along with GDP). The QFRG noted that this variable should be updated to take account of capital flows, and discussions have since centered on a variable that captures variability of current receipts and net capital flows, measured as the standard deviation from a three-year trend. Staff had proposed use of a three-year rather than a five-year trend since reversals in capital flows can be quite sudden and sometimes short-lived, and Directors generally agreed, in previous discussions, that a three-year measure would serve to smooth trends while adequately capturing fluctuations in capital flows.24

35. In the December discussion, questions were raised regarding the weight that should be assigned to variability in the new formula and whether an alternative set of variables should be considered that may better indicate a member’s vulnerability and potential need for Fund resources. It was suggested that these could be derived, for example, based on past use of Fund resources, country ratings by private firms, country spreads, and vulnerability ratios, such as short-term debt to reserves. In this context, it is worth noting that the traditional variability measure may be thought of as an attempt to capture more structural features of a member’s economy that may make it subject to external shocks.25 This is distinct from an attempt to measure actual vulnerability or likelihood of using Fund resources, as a member with high variability may nonetheless be in a strong external position with little if any probability of actually drawing on the Fund. This is also consistent with two of the other traditional quota variables—GDP and openness—that also have a bearing on the potential size of a member’s need for recourse to the Fund but not on the probability of such recourse. A proposal to use short-term measures of actual vulnerability would represent a major departure from this approach, and would also raise a number of difficult implementation issues, including that many of these measures are subject to substantial short-term volatility, may be seen as rewarding imprudent policies, and raise possible concerns about reliance on private sector judgments in the quota formula.

E. Reserves

36. In the December seminar, there were several calls for work on the feasibility of introducing a cap on the reserves variable. The rationale would be to avoid rewarding what some view as excessive reserve accumulation that could otherwise result in a higher calculated quota.

37. Designing a workable cap would pose a number of challenges. In particular, it would require reaching a consensus among the membership as to what represents a reasonable benchmark above which reserves should no longer be taken into account for the purposes of quota calculations. The optimal reserves literature provides little practical guidance in this regard, focusing on models that recognize multiple factors that may drive country-specific reserve decisions.26 Traditional reserve adequacy benchmarks (e.g., coverage of short-term external debt, imports, or current payments) have sometimes been used to define rough proxies for excess reserves, e.g., at some multiple of adequacy levels.27 However, their application to quota calculations would raise a number of difficult issues. First, it would be difficult to define a single reserve adequacy measure suited to the diverse circumstances of all members; financial indicators are more relevant for members with market access and traditional trade-based measures more suitable for others; even within these groups, optimal (and, by association, excessive) reserves would vary based on a range of broader macroeconomic factors (including the choice of exchange rate regime) and financial considerations. Second, a cap based on some reserve adequacy measures could tend to reward countries whose policies have resulted in higher vulnerabilities. In the case of a measure based on short-term liabilities, there are also important data constraints that preclude developing a uniform measure for quota calculations based on national data with sufficiently broad country coverage. Caps based on macroeconomic scale indicators (e.g., money or GDP) could also be considered, but again, would not capture the differences arising from distinctions in the underlying circumstances of members. A money-based indicator could also be seen as rewarding loose monetary policies.

38. In light of these difficulties, staff have prepared a few simple measures to illustrate the potential application of a reserve cap. For purely illustrative purposes, caps are defined as the sample mean plus one standard deviation from for the ratio of reserves to: current payments, M2, and GDP. Table 7 demonstrates the effect of a cap on members’ shares of a reserve variable in terms of the number and composition of affected countries, as well as the scale of the effect. As can be seen, the potential impact of such a cap differs considerably depending upon the specific metric chosen. Tables 8 and 8a demonstrate the effects in terms of simulated calculated quota shares under the base scenario in Table 1. In general, this effect is limited, reflecting the relatively small weight for reserves. This suggests that the potential distortions that excess reserves may create are also limited, even without such a cap.

Table 7.

Countries Affected by Reserve Caps—Shares in Global Total1/

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Source: Finance Department.

Reserve caps are defined as the average of reserves to a scaling variable (average GDP, current payments, M2) plus one standard deviation.

Average GDP 2002-04.

Average current payments 2000-04.

Quarterly average of M2 for 2004. M2 is defined as the IFS category for “Money plus Quasi Money” (line 351) except for members of the euro area, for whom it is defined, on a national residency basis, as the sum of “Currency Issued” (line 34a.n), “Demand Deposits” (line 34b.n), and “Other Deposits” (line 35..n). The 12 countries for which M2 data are not available in IFS are not included.

F. Financial Contributions

39. A proposal was made in the December discussion to include a new variable that would reflect members’ financial contributions to the Fund. The specific proposal was to include members’ contributions to the PRGF and NAB as a measure of their ability and willingness to contribute to the Fund’s finances.

40. Financial contributions have long been recognized as a relevant factor in considering increases in individual members’ quotas.28 This reflects the central role of quotas in the Fund’s finances as discussed at the beginning of this paper. In particular, there are numerous examples where past and prospective financial contributions to the Fund have been taken into account in determining increases in members’ quotas both within and outside general quota reviews: these include the quota increases agreed for certain industrial countries in the 1959 and the Fourth General Reviews aimed at improving the Fund’s liquidity, ad hoc quota increases for Italy in 1964 and Saudi Arabia in 1981; the selective increases for major oil-exporting countries in the Sixth Review; the ad hoc increase for Japan in the Ninth Review, and the additional increases for Korea, Luxembourg, Singapore, Malaysia, and Thailand in the Eleventh Review. While contributions to the Fund’s finances have been an important consideration, however, these have generally been supplemental to the issue of whether a member’s quota is out of line with its relative economic position, and they have not been included directly in the quota formulas.

41. Including such a variable explicitly in the formula would raise several practical difficulties. First, it would be necessary to define which types of contributions should be considered, and over what period, since members have contributed to the Fund’s finances in a variety of forms over time. It could also involve a degree of circularity because quota shares themselves have been used as an important guide to members’ financial contributions in the past, including for the PRGF and the NAB.29 Finally, members’ external financial positions can change, sometimes rapidly, such that past contributions may not always be a good indicator of members’ ability to contribute in future. For these reasons, it may be preferable not to include a measure of financial contributions in the quota formula itself, but rather to continue to retain the flexibility to take into account the ability of members to contribute to the Fund’s financing needs when considering actual quota increases.

IV. Additional Scenarios

42. Directors also requested additional scenarios based on those covered in Quotas— Further Thoughts on a New Quota Formula (2006). Specifically, there were requests for a wider range of assumptions regarding the weight on GDP in the formula beyond the range of 40 to 60 percent. In this context, it should be noted that, while under the existing formulas, the average contribution of GDP to calculated quota shares is 29 percent, there is substantial variance around this average.30 Table 9 (and 9a in the supplement) provides simulations based on GDP weights of 35 and 65 percent, respectively, with two alternative scenarios for the weights on openness and variability. There were also requests for simulations with alternative assumptions regarding a compression factor beyond the range of 0.9 and 0.95 in the last paper. As noted in Quotas—Further Thoughts on a New Quota Formula (2006), use of a compression factor leaves unchanged the country rankings that result from a new uncompressed formula, but narrows the resulting distribution of shares. Table 10 (and 10a in the supplement) provides simulations using a compression factor of 0.8 and 0.85. As expected, these scenarios reduce calculated quota shares for the largest economies, with all other economies gaining. Overall, developing and transition countries’ calculated shares rise with use of a compression factor, and advanced country shares decline, with a smaller compression factor leading to a greater change.

Table 9.

Linear Formulas—Scenarios Using Different Weights for GDP1/2/

(In percent)

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Source: Finance Department.

Calculated as the sum of variable weights multiplied with a country’s share in the global total of the respective variables. Weights do not reflect a variable’s contribution perse as correlation among variables is high.

Based on 1992-2004 data. Reflects the impact of adjustments to current receipts and payments for re-exports, international banking interest, and non-monetary gold.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Including Korea and Singapore.

PRGF-eligible countries.

Table 10.

Scenarios Using Various Compression Factors (In percent)

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Source: Finance Department.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Q = 0.5*Average GDP + 0.3Openness + 0.15*Variability + 0.05*Reserves.

Q = (0.5*Average GDP + 0.3Openness + 0.15*Variability + 0.05*Reserves)A0.8. This requires rescaling of calculated shares.

Q = (0.5*Average GDP + 0.3Openness + 0.15*Variability + 0.05*Reserves)^ 0.85. This requires rescaling of calculated shares.

Including Korea and Singapore.

PRGF-eligible countries.

V. Issues for Discussion

43. Directors may wish to comment on:

  • The potential for further exploring a possible blended variable combining market-rate and PPP-based GDP, recognizing the work underway to address existing data constraints.

  • Whether they also see benefit to exploring further a possible role for a population variable.

  • The merits of explicitly incorporating a financial openness measure into the current openness variable, and if so, whether they agree that a measure based on investment income appears to be the most productive starting point, taking account of limitations in IIP data, as well as the nature of financial account flows and related data issues.

  • How the issue of intra-currency union flows should be addressed, given the complexities of the issue and incomplete data on intra-currency union flows beyond merchandise trade.

  • Whether they continue to see the proposed variability measure based on deviations from a three-year trend in current receipts and net capital flows as the most promising measure of potential need for Fund resources in a new formula.

  • Whether a reserve cap is worth exploring further, or whether maintaining a limited weight on reserves would reduce the need for such a cap.

  • Whether past and prospective financial contributions to the Fund should continue to be taken into account, as appropriate, in considering actual quota increases rather than built into the quota formula itself.

Table 8.

Linear Formulas—Scenarios with Capped Reserves1/2/

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Source: Finance Department.

Calculated as the sum of variable weights multiplied with a country’s share in the global total of the respective variables.

Based on 1992-2004 data. Reflects the impact of adjustments to current receipts and payments for re-exports, international banking interest,

and non-monetary gold.

For the three countries that have not yet consented to, and paid for, their quota increases, 11th Review proposed quotas are used.

Includes ad hoc increases for China, Korea, Mexico, and Turkey; also includes Montenegro, which became a member on January 18, 2007.

Reserve caps are defined as the average of reserves to a scaling variable (average GDP, current payments, M2) plus one standard deviation.

Average GDP 2002-04.

Average current payments 2000-04.

Quarterly average of M2 for 2004. M2 is defined as the IFS category for “Money plus Quasi Money” (line 35I) except for members of the euro area, for whom it is defined, on a national residency basis, as the sum of “Currency Issued” (line 34a.n), “Demand Deposits” (line 34b.n), and “Other Deposits” (line 35..n). The 12 countries for which M2 data are not available are included with their uncapped reserves.

Including Korea and Singapore.

PRGF-eligible countries.

1

Messrs. Burton (Chair), Ahmed, Anjaria, Edwards, Hagan, Kuhn, and Kincaid; a FIN team led by Mr. Tweedie has worked closely with the group.

2

See Quotas—Further Thoughts on a New Quota Formula (2006), and Report of the Managing Director to the International Monetary and Financial Committee on IMF Quota and Voice Reform (2006).

3

A caution was raised that simplicity should not come at the expense of ensuring the formula is sufficiently robust to accommodate the diverse circumstances of all members. Some questions were also raised regarding the link between quotas and access.

4

As highlighted in Quotas—Further Thoughts on a New Quota Formula (2006), PPP leads to a larger relative GDP for developing countries because it places a higher relative weight on production in the non-tradables sector for these countries than would be implied by conversion at a market exchange rate.

5

See Report to the IMF Executive Board of the Quota Formula Review Group (2000). A minority of the group’s members viewed GDP converted at PPP rates as a better measure of real economic activity and growth.

6

The QFRG noted that the inclusion of a population variable could also capture per capita income differences (Report to the IMF Executive Board of the Quota Formula Review Group, 2000). See also Quotas—Further Thoughts on a New Quota Formula (2006). Some authors have called for the inclusion of a population variable to address a “democracy deficit.” See, for example, Mirakhor, A. and Zaidi, I., Rethinking the Governance of the International Monetary Fund, IMF Working Paper WP/06/273, December 2006 and Kelkar, V. et al, The International Monetary Fund: Integration and Democratization in the 21st Century, G-24 Technical Group Meeting, Manila, Philippines, March 2005.

7

Net capital flows here refer to financial account flows as defined in the Fund’s Balance of Payments Manual, fifth edition (BPM5), excluding changes in reserves and related items.

8

See Quota Distribution—Selected Issues (2003), for an extensive discussion of these issues and IMF Executive Board Discusses Quota Distribution Issues, Public Information Notice No. 03/106.

9

Comprehensive reporters refer to countries that have reported three years of data.

10

A recent working paper points to the challenges involved—See The External Wealth of Nations Mark II: Revised and Extended Estimates of Foreign Assets and Liabilities, 1970–2004, Philip Lane and Gian Maria Milesi-Ferretti (IMF Working Paper WP/06/69). The authors employ a range of sources for underlying data, and use a variety of valuation techniques and assumptions to estimate IIPs for 143 countries. This work has important analytical applications, but the need for substantial judgments in constructing the series would make its use highly problematic for quota calculations.

11

IFS data are available on investment income for the majority of Fund members and others are gap-filled through the WEO based on an established methodology laid out in Appendix I, page 10, of Quotas—Updated Calculations (2006). There is a small group of countries (eight) for which no IFS or WEO data on investment income are currently available, and alternative methods for gap-filling would need to be considered.

12

In addition, for countries with large portfolio equity investments, use of investment income would tend to have a downward bias, as only dividends (and not capital gains) would be captured.

13

The current quota data on investment income flows include adjustments for international banking interest (IBI), introduced with the Ninth General Review (completed in 1990). IBI is defined as interest payments by non-residents on their borrowing from domestic banks and by domestic banks on deposits held by non-residents. The actual adjustment is made by deducting the lower of gross interest paid and gross interest earned from other investments—so that only net interest for this category is recorded. Adjustments are made for the G-10, Luxembourg, China, P.R., and Hong Kong SAR. Data for China, P.R., and Hong Kong SAR were also adjusted for IBI in the context of the 2001 ad hoc quota increase for China (see Quotas—Updated Calculations, 2006).

14

To smooth short-term fluctuations in investment income, it would seem reasonable to use the same five-year average period that is applied to current receipts and payments.

15

However, this is a distinct issue from the measure of net capital flows included in the variability measure as defined in footnote 8 (i.e., the difference between net asset and liability flows in the financial account), since the same level of net capital flows could be consistent with many different levels of aggregate flows and, therefore, degrees of capital account integration.

16

As noted in footnote 14, data on investment income include adjustments for international banking interest.

17

Methodological issues related to the existing data adjustments, including in regard to entrepôt trade, have also been raised and will be taken up in a subsequent paper.

18

Regional surveillance has been formalized for four currency unions: Euro Area, Eastern Caribbean Currency Union (ECCU), Central African Economic and Monetary Union (CEMAC) and West African Economic and Monetary Union (WAEMU). See Fund Surveillance Over Members of Currency Unions (2005).

19

For a summary of debate on this issue, see Trade Volume Effects of the Euro: Aggregate and Sector Estimates, Harry Flam and Håkan Nordström, Seminar Paper No. 746, Institute for International Economic Studies, Stockholm University, June 2006 and Measuring the Trade Effects of EMU, Hamid Faruqee, IMF Working Paper WP/04/154. The first study highlights the importance of vertical integration to the effect of the single currency on intra-euro area trade, estimated at about 15 percent in the period 1998–2002 versus 1989–97. Both studies point to a positive effect of the euro on members’ trade with non-members (about 8 percent in the first study). For an alternative view, see Zooming Out: The Trade Effects of the Euro in Historical Perspective, Helge Berger and Volker Nitsch, CESifo Working Paper No. 1435, December 2004.

20

See, for example, Production fragmentation and trade integration: East Asia in a global context, Premachandra Athukorala, Nobuaki Yamashita, The North American Journal of Economics and Finance, 17 (2006) 233–256. The paper finds that, while trade in parts and components (fragmentation trade) has generally grown faster than total world manufacturing trade, the degree of dependence of East Asia on this new form of international specialization is proportionately larger than in North America and Europe. They stress, however, that there is no evidence to suggest that this has reduced the region’s dependence on the global economy, noting that growth dynamism based on vertical specialization depends on extra-regional trade in final goods, and this dependence has in fact increased over the years.

21

See Report to the IMF Executive Board of the Quota Formula Review Group (2000).

22

Direction of Trade statistics register merchandise trade imports on a CIF basis. These data are not directly comparable with IFS trade statistics, including because imports are registered on a FOB basis. The CIF statistics capture elements that are recorded as services in the IFS data.

23

For the existing formulas, contributions are estimated as the variable’s value for each member, multiplied by its coefficient in the applicable formula, expressed in relation to the member’s calculated quota. A variable’s coefficient includes the multiplicative factor (the ratio of current receipts to GDP) in the case of nonlinear formulas. If for a given country more than one formula is used, coefficients are averaged. The measurement of contributions are approximations because of the non-linearity of the existing five formulas and high correlation among the variables.

24

See Alternative Quota Formulas—Considerations (2001), Alternative Quota Formulas—Further Considerations (2002), including Table 3 and Supplement 1, Table 3; and IMF Executive Board Discusses Quota Formulas, Public Information Notice No. 02/59.

25

This is clearly an imperfect measure, however, as it cannot distinguish between external volatility resulting from structural or exogenous causes and volatility that may have resulted from imperfect policies.

26

See, for example, Country Insurance—The Role of Domestic Policies (2007).

27

Lawrence Summers, for example, suggested a rough figure of two times the adequacy measure defined by the Guidotti-Greenspan rule in “Reflections on Global Account Imbalances and Emerging Markets Reserve Accumulation,” March 24, 2006 http://www.president.harvard.edu/speeches/2006/0324_rbi.html.

28

See Quotas and Voice—Further Considerations (2005).

29

In addition, participation in the NAB is not open to all members but rather requires the agreement of both the Fund and existing participants with the requisite voting majority.

30

In particular, for some highly open economies, the effective weight on GDP is quite low under the current formulas, including because of the multiplicative element in some of the formulas.

1

There is no individual member table associated with Table 7 of A New Quota Formula—Additional Considerations.

A New Quota Formula - Additional Considerations, Statistical Appendix, and Statement by the Managing Director
Author: International Monetary Fund