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New Rates from New Weights

Author(s):
International Monetary Fund. Research Dept.
Published Date:
June 2006
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This paper updates the weights for effective exchange rate calculations, using trade data from 1999 to 2001. The weights currently used in effective exchange rate indices published in the IMF’s International Financial Statistics are based on 1989–91 data, with an adjustment to incorporate transition countries a few years later.1 Naturally, these weights fail to reflect developments in international trade relations during the subsequent decade, which was punctuated by rapid globalization and the rising importance of many emerging market countries in the global trading system.

Outdated weights can lead to an incorrect assessment of development in the effective exchange rate, a key input for the macroeconomic analysis of open economies. A prominent example can be found in the recent discussion of the U.S. current account deficit and exchange rate. With the buildup of the U.S. current account deficit to a historic level—accompanied by a substantial appreciation of its real effective exchange rate (REER)—a consensus appears to have emerged on the inevitable downward correction in both the current account deficit and the REER of the United States. However, the assessment of necessary correction in the exchange rate will vary with the prevailing trade patterns of the United States.

Another example can be found in the growing importance of China in global trade, which is beginning to have wide-ranging economic implications. However, data from the late 1980s and early 1990s cannot help us assess the ground that China has gained, or its economic significance. While the rise in China’s role is obvious to any observer, the question remains as to whose presence has diminished.

To gain insight on the effect of recent trade patterns on effective exchange rate calculations, this paper updates the weights using detailed trade data for the 164 countries that account for nearly 100 percent of global trade.2

I. Now and Then

Effective exchange rate calculations start by constructing the weights to be applied to each trade partner. An overview of the results of updating these weights is presented in two tables. Table 1 reports the new weights for a wide range of key industrial and developing countries. The trade weights are reported with respect to industrial countries—which are further divided into the United States, the euro area, Japan, and other industrial countries—and developing countries—which are reported along geographic lines as Africa, Asia (further subdivided into China, Association of South East Asian Nations [ASEAN], and the rest), Latin America, the Middle East, and the transition countries of Eastern Europe and the former Soviet Union.

Table 1.New Trade Weights
Industrial CountriesUnited StatesJapanEuro AreaOther IndustrialDeveloping CountriesAfricaAsiaChinaASEANOther AsiaLatin AmericaMid EastTransition 1Regional
NAFTA
United States0.560.000.130.190.250.440.010.230.070.050.110.170.010.020.27
Mexico0.880.690.040.080.070.120.000.070.020.020.040.030.000.010.73
Canada0.830.660.050.080.050.170.010.090.030.020.040.050.010.020.69
Latin America
Argentina0.510.180.040.190.090.490.010.120.040.030.050.320.010.020.32
Brazil0.650.270.060.220.110.350.020.110.030.020.060.180.010.030.18
Chile0.580.200.060.180.130.420.010.160.060.030.070.200.010.040.20
NIA+ASEAN2
Japan0.550.270.000.170.110.460.010.380.120.090.170.040.010.020.24
China0.690.240.190.170.100.300.010.210.000.040.170.030.010.030.20
Hong Kong SAR0.560.180.080.150.150.450.010.390.210.050.130.030.010.020.15
Korea0.640.230.180.140.090.360.010.260.110.060.090.040.020.030.13
Singapore0.590.210.140.150.090.410.010.360.060.160.140.020.010.020.26
Taiwan Province of China0.650.230.190.150.090.350.010.280.100.070.110.030.010.020.16
India0.650.190.070.250.140.340.040.190.040.040.110.030.040.040.14
Indonesia0.600.170.170.160.110.400.020.290.060.060.170.040.030.030.20
Malaysia0.630.240.150.140.090.370.010.300.050.060.190.030.010.020.23
Philippines0.670.260.190.130.080.330.010.280.040.060.180.030.010.020.23
Thailand0.640.190.200.150.100.360.010.280.060.060.160.030.010.020.20
Subregion3
Australia0.650.190.130.160.160.360.020.270.070.070.130.030.020.020.21
New Zealand0.730.170.110.140.300.270.010.180.050.040.090.040.010.020.09
Subregion4
Euro area0.600.200.080.000.320.400.030.170.050.030.090.050.020.130.27
Switzerland0.820.110.050.530.120.180.010.090.020.020.050.030.010.040.09
Denmark0.800.090.040.430.240.210.010.100.030.020.050.030.010.060.21
United Kingdom0.790.150.050.490.100.220.020.120.030.020.070.020.020.040.06
Norway0.810.100.050.350.310.180.010.100.030.020.050.020.010.040.28
Sweden0.800.110.050.430.210.200.010.090.030.020.040.030.010.060.18
Subregion4
Cyprus0.700.050.060.370.230.300.020.110.020.020.060.040.050.090.19
Turkey0.760.110.030.480.140.240.020.090.020.020.050.020.030.080.11
Hungary0.820.090.030.600.400.180.010.070.020.010.030.020.010.090.08
Poland0.790.050.020.580.140.210.010.070.020.010.040.020.010.100.12
Czech Rep.0.790.060.020.600.110.210.010.060.020.010.030.010.010.120.10
Russia0.530.100.040.280.110.470.020.170.080.020.070.040.030.220.08
Nigeria0.620.090.050.310.160.380.030.250.070.040.130.040.020.05
South Africa0.680.140.070.300.170.320.090.150.040.030.090.040.010.03
Iran, I.R* of0.540.040.060.320.120.460.020.200.050.030.110.030.090.13
Israel0.780.300.050.300.130.220.010.130.030.020.080.030.010.04
Saudi Arabia0.640.170.110.220.140.360.020.220.050.040.120.020.080.03

Consists of Eastern European and Central Asian countries.

NIA (Newly Industrialized Asia) consists of Hong Kong SAR, Korea, Singapore, and Taiwan Province of China.

Consists of NIA (see footnote 2), ASEAN(Association of Southeast Asian Nations), Australia, and New Zealand.

Consists of Norway, Sweden, Denmark, Switzerland, and United Kingdom.

Consists of Eastern European and Central Asian countries.

NIA (Newly Industrialized Asia) consists of Hong Kong SAR, Korea, Singapore, and Taiwan Province of China.

Consists of NIA (see footnote 2), ASEAN(Association of Southeast Asian Nations), Australia, and New Zealand.

Consists of Norway, Sweden, Denmark, Switzerland, and United Kingdom.

Table 2 uses the same format to report differences from the existing weights for all countries (in the current weight calculation, there also exists a different set of weights calculated only for industrial countries).

Table 2.Difference in Trade Weights (New Weights Minus Old Weights) 1
Industrial CountriesUnited StatesJapanEuro AreaOther IndustrialDeveloping CountriesAfricaAsiaChinaASEANOther Asia 2Latin AmericaMid EastTransition 3Regional
NAFTA
United States−0.12−0.05−0.06−0.010.120.040.050.02−0.030.080.010.08
Mexico0.010.18−0.05−0.09−0.04−0.01−0.010.01−0.020.17
Canada0.010.17−0.060.080.02−0.01−0.020.02−0.040.18
Latin America
Argentina−0.190.02−0.03−0.15−0.040.190.020.020.190.010.19
Brazil−0.090.07−0.030.09−0.040.090.010.010.090.020.09
Chile−0.150.03−0.03−0.12−0.030.15−0.010.050.040.010.080.030.08
NIA+ASEAN4
Japan−0.110.04−0.09−0.060.110.110.080.04−0.010.010.02
China0.090.110.03−0.04−0.09−0.100.01−0.110.01−0.10
Hong Kong SAR0.010.06−0.080.03−0.01−0.03−0.030.02−0.020.01−0.01
Korea−0.16−0.07−0.05−0.040.160.120.090.030.010.020.02
Singapore−0.080.02−0.04−0.02−0.030.080.070.040.020.020.02
Taiwan Province of China−0.12−0.04−0.05−0.040.120.110.070.030.010.03
India−0.130.04−0.04−0.08−0.040.130.010.070.030.020.020.020.030.03
Indonesia−0.090.05−0.04−0.08−0.010.090.060.030.020.020.01
Malaysia0.010.08−0.04−0.03−0.010.000.030.02−0.060.01−0.04
Philippines−0.050.050.02−0.07−0.040.050.070.020.030.02−0.010.05
Thailand−0.070.05−0.03−0.07−0.020.070.070.040.030.010.03
Subregion5
Australia−0.11−0.04−0.070.110.080.040.040.020.05
New Zealand−0.080.03−0.02−0.130.030.080.060.030.020.020.09
Subregion6
Euro area−0.100.01−0.04−0.070.10−0.020.030.030.10−0.06
Switzerland−0.050.03−0.01−0.05−0.010.050.010.010.010.03−0.01
Denmark−0.07−0.02−0.060.070.020.020.05
United Kingdom−0.050.02−0.02−0.04−0.020.050.020.020.03−0.02
Norway−0.020.01−0.030.020.020.020.03
Sweden−0.09−0.02−0.05−0.010.090.020.020.010.05−0.01
Subregion6
Cyprus−0.08−0.01−0.03−0.050.080.000.02−0.010.020.010.05−0.02
Turkey−0.030.01−0.02−0.010.030.010.01−0.010.06
Hungary0.010.03−0.010.04−0.04−0.010.00−0.010.03−0.03
Poland0.00−0.02−0.030.08−0.030.00−0.01−0.01−0.01−0.010.06−0.01
Czech Rep.0.110.030.030.05−0.110.040.010.030.01−0.190.03
Russia−0.05−0.01−0.050.010.050.020.080.020.020.040.040.03−0.11−0.03
Nigeria−0.15−0.01−0.01−0.08−0.040.150.130.060.020.050.03
South Africa−0.180.01−0.06−0.12−0.020.180.070.080.030.020.030.02
Iran, I.R. of−0.24−0.07−0.14−0.040.240.120.030.010.080.070.06
Israel−0.070.11−0.02−0.10−0.050.070.030.020.010.03
Saudi Arabia−0.120.03−0.03−0.05−0.070.120.070.040.010.020.050.01

Only differences bigger than .01 (1 percent) in magnitude are shown is the table.

Consists of Eastern European and Central Asian countries; Information Notice System weights were not computed for many countries in the group.

Most of the differences represent losses of Hong Kong SAR, Singapore, and Taiwan Province of China.

NIA (Newly Industrialized Asia) consists of Hong Kong SAR, Korea, Singapore, and Taiwan Province of China.

Consists of NIA (see footnote 4), ASEAN (Association of Southeast Asian Nations), Australia, and New Zealand.

Consists of Norway, Swedes, Denmark, Switzerland, and United Kingdom.

Only differences bigger than .01 (1 percent) in magnitude are shown is the table.

Consists of Eastern European and Central Asian countries; Information Notice System weights were not computed for many countries in the group.

Most of the differences represent losses of Hong Kong SAR, Singapore, and Taiwan Province of China.

NIA (Newly Industrialized Asia) consists of Hong Kong SAR, Korea, Singapore, and Taiwan Province of China.

Consists of NIA (see footnote 4), ASEAN (Association of Southeast Asian Nations), Australia, and New Zealand.

Consists of Norway, Swedes, Denmark, Switzerland, and United Kingdom.

The results indicate several trends in the patterns of trade. First, industrial countries remain at the heart of the international trading system, but their importance has declined significantly compared with the previous exercise. Industrial countries still account for more than half of the trade-based exchange rate weights for most countries that are reported (Table 1). In some nonindustrial countries that have particularly close trading relationships with major industrial countries (the Czech Republic, Israel, Mexico, and Poland), the weights of industrial countries approach or even exceed 80 percent. However, the weights of industrial countries have almost universally declined since the last exercise, often by quite substantial amounts (Table 2). This primarily reflects the globalization of world trade.

Within the industrial countries, the United States and the euro area are dominant, with the weight of the United States generally increasing since the last exercise while the weight of other areas has declined. The United States and the euro area are particularly important for other countries in North America and Europe, respectively (Table 1).3 By contrast, Japan’s weight is smaller than that of the United States in all reported Asian countries—except in Thailand, for which Japan commands a slightly larger weight than does the United States. The weight of the United States has generally increased, most dramatically for fellow members of the North American Free Trade Agreement (NAFTA)—Canada, and Mexico (Table 2). This reflects strong growth in the United States, possibly aided by the rise in value of the dollar, which may have affected trade weights because U.S. producers typically price in dollars whereas others price to market in the United States.4 In addition, some of the decline in the weight of the euro area comes from treating the region as a single bloc rather than as 12 different countries.

Asia is the most important developing country region, although the importance of many developing regions is increasing over time (Table 2). This reflects the globalization of the international trading system, as well as the exclusion of many transition countries from the last exercise. Emerging Asia (which excludes Japan) almost universally has a larger weight than any other developing country region, with the only major exception being the importance of intraregional trade for Latin America (Table 1). There have also been some visible shifts in the importance of regions within Asia, reflecting growth differentials. The increased role of China since the last exercise is particularly striking, and there has been a generalized rise in the importance of ASEAN countries. In contrast, the weights of other Asian countries have decreased in many cases, driven by a decline in the relative economic weight of the newly industrialized economies comprising Hong Kong SAR, Korea, Singapore, and Taiwan Province of China. Nor has there been much increase in the weight of India.

Regional trade has become more important. There is noticeable evidence of strengthened regional ties, reflecting both regional trade agreements (NAFTA, Sectoral Commission for the Common Market of the South (MERCOSUR), and the expansion of bilateral arrangements with the European Union) and the integration of emerging markets into the global trading system—for example, Asia has become more important for Australia and New Zealand.

II. Deconstructing the Weights

The Old (Existing) Weights

The aggregate trade weights reflect the sum of weights on trade in commodities, manufactures, and services. The existing calculations generate two sets of weights that differ in the scope of country coverage and in whether domestic competition is incorporated in calculating manufactures weights. The first method—to be called the Global System in this paper—covers 184 countries and uses only data on trade flows. The familiar CPI-based REERs of the IMF have been calculated by applying this Global System. The second method, to be called the Industrial System, covers only industrial countries—for which unit labor costs (ULCs) were available—but takes into account domestic sales of home-produced goods in every market. This method has been used to construct the ULC-based REERs of the IMF.

Both methods treat different trade categories in a similar manner. Individual commodities are assumed to be perfect substitutes so that the associated weights depend on the importance of other countries in the overall supply and demand for a commodity. By contrast, manufactures are assumed to be differentiated goods so that weights depend on bilateral flows across countries, augmented by the impact of third-market competition in export markets. In the Industrial System, these third-market effects depend on the importance of foreign and domestic goods in overall demand, while the Global System takes a more mechanical approach, assigning equal weights to direct and third-market competition. As far as services are concerned, only trade in tourism is included, and then only for countries for which tourism is a particularly important part of overall trade. Service weights are calculated in a similar manner to manufactures weights, using bilateral data on tourist arrivals. These weights are then combined based on the importance of different types of trade so that

Wij=αMWij(M)+αcWij(C)+αTWij(T),

where Wij(M), Wij(C), and Wij(T) denote weights calculated for manufactures, commodities, and tourism, respectively—between countries i and j—and αM and αC and αT denote the shares of these three types of trade in the overall trade of country i.

The New Weights

The new trade weights incorporate three major changes to the existing weights:

  • A uniform methodology is used for 164 countries. The system used for calculating third-market effects in the manufacturing weights for industrial countries (Industrial System) has been extended to 164 countries so that the distinction between the Global System and the Industrial System has been abolished for them. To overcome data limitations, several approximations are made, as discussed in Appendix I.

  • Services trade has been included in a more systematic manner Rather than focusing on tourism, the new weights include all trade in services in the calculation. The main issue here is that no comprehensive data on bilateral trade in services is available, except for the bilateral trade in tourism that can be proxied by data on tourist arrivals. What work has been done on trade in services tends to show that it responds to the same basic factors, such as distance, relative GDP, and cultural links, that explain trade in manufactures. Accordingly, trade in services—except for tourism—is assumed to be distributed in the same manner as trade in manufactures, and the same weights are used. However, for the countries in which tourism is a particularly important part of overall trade, separate weights are calculated for trade in tourism, using the same methodology used in the existing weights.5 Hence, the new weights are as follows:

    Wij=αM+αsWij(M)+αcWij(C)+αTWij(T),

    where Wij(M), Wij(C) and Wij (T)are country weights for manufactures, commodities, and tourism, and where αM, αS, αC, and αT denote the shares of manufactures, (nontourism) services, commodities, and tourism in overall trade.

  • The single euro-area index is calculated anew. In the existing weights, the members of the euro area are counted as individual countries. Although this practice is retained for analytic purposes, a single index is also calculated that treats the euro area as a single entity with a single exchange rate.6 Individual country weights capture country-specific competitiveness when inflation rates diverge among euro-area countries and are maintained as the unit of calculation for country-specific policy analysis. As a supplement, the single euro index is calculated to assess the euro-area-wide competitiveness against other major currencies, after intra-euro-area trade linkages have been accounted for.

Table 3 examines the impact of treating the euro area as a single entity. The first column reports the weights derived under the new methodology using this assumption, while the second column shows the weights that follow when the euro-area countries are treated as individual trade entities and their weights are then summed to get a single value for the euro area as a whole. To gain some perspective on the importance of any discrepancies, the table also reports the values for the euro area by summing existing weights for euro-area countries from the Global System. The results indicate that treating the euro area as a single entity tends to reduce its weight in other countries’ effective exchange rates, but that this effect is a relatively small part of the overall change between the old and new weights. For non-oil commodity exporters, however, the aggregation reduces the weights of the euro area noticeably, as intra-euro-area trade in commodity is netted out.7

Table 3.Weight of Euro Area by Different Methods
New WeightsOld Weight
Euro area as a regionEuro area as individual countriesEuro area as individual countries
United States0.190.200.25
Mexico0.080.090.16
Canada0.080.100.16
Argentina0.190.230.34
Brazil0.220.250.30
Chile0.180.230.30
Japan0.170.180.25
China0.170.180.21
Hong Kong SAR0.150.160.15
Korea0.140.150.19
Singapore0.150.150.17
Taiwan Province of China0.150.150.19
India0.250.270.33
Indonesia0.160.180.24
Malaysia0.140.140.18
Philippines0.130.140.21
Thailand0.150.160.22
Australia0.160.200.23
New Zealand0.140.200.27
Switzerland0.530.540.58
Denmark0.430.440.48
United Kingdom0.490.490.52
Norway0.350.360.38
Sweden0.430.430.48
Cyprus0.370.410.42
Turkey0.480.490.49
Hungary0.600.590.56
Poland0.580.590.50
Czech Republic0.600.600.56
Russia0.280.320.33
Nigeria0.310.340.39
South Africa0.300.320.41
Iran, LR. of0.320.350.46
Israel0.300.300.40
Saudi Arabia0.220.240.27

Commodity Weights

Commodity trade is assumed to occur in an integrated global market, because commodities are assumed to be perfect substitutes with a single price. As in the earlier exercise, commodities are defined at the two-digit Standard International Trade Classification (SITC) level, leading to 20 different types of commodities (see Appendix I for details). Within each commodity category, the weight country i assigns to country j is unrelated to bilateral commodity trade but is instead determined by country j’s share in the global market. The overall commodity weight is obtained by aggregating individual commodity weights, with allowances made both for the importance of each commodity category in a country’s total commodity trade and for the importance of the country in the global trade of each commodity. All things being equal, a commodity category in which a country commands a more dominant global presence is counted more heavily when individual commodity weights are aggregated to the overall commodity weight.

Trade in petroleum and energy products, however, is excluded from calculation of commodity weights, following the existing approach to calculating weights. Several reasons underlie this choice. First, except in the long run, exchange rate changes are not likely to have much effect on trade in oil or gas. Variable costs account for a very small portion of their production costs; thus, exchange rate variation can exert only a limited effect on production decisions. Next, the energy sector is largely segmented from the rest of the economy, except for its contribution to the state budget through energy revenues. The eventual effect of the energy sector on the rest of the economy is affected more by government spending decisions than by exchange rate variations. Finally, the world oil market is strongly influenced by cartels, and exchange rate variations have only indirect effects on the market.

Table 4 reports the importance of commodity trade (in overall trade) for a range of individual economies. The highest shares are for traditional non-oil commodity exporters, with commodity shares exceeding 20 percent for Chile, New Zealand, Argentina, Russia, Australia, and Brazil. At the other end of the scale, in Singapore and Taiwan Province of China, commodity trade represents about 5 percent of overall external competition. Compared with the existing Global System, the relative importance of (non-oil) commodities in overall trade has declined across the spectrum, partly owing to the inclusion of services trade under the new system.

Table 4.Difference in Commodity Shares
New (1999–2001)Global System (1989–91)Difference
Singapore0.040.12−0.08
Taiwan Province of China0.060.11−0.04
Sweden0.080.13−0.06
Mexico0.080.18−0.10
United States0.080.14−0.06
Switzerland0.080.09−0.01
United Kingdom0.080.15−0.06
Korea0.080.14−0.06
Euro area0.090.17−0.08
Turkey0.100.24−0.14
Japan0.100.16−0.06
China0.100.20−0.10
Saudi Arabia0.100.18−0.08
Hong Kong SAR0.110.090.02
Canada0.130.20−0.07
Nigeria0.130.18−0.05
India0.140.20−0.06
Norway0.150.25−0.10
Denmark0.150.29−0.14
South Africa0.170.28−0.10
Iran, I.R. of0.200.31−0.10
Brazil0.230.40−0.17
Australia0.230.34−0.11
Russia0.25
Argentina0.260.51−0.25
New Zealand0.300.47−0.17
Chile0.400.59−0.19

Manufacturing Weights

Unlike commodities, manufactures are assumed to be differentiated goods that are imperfectly substitutable across countries. The aggregate manufacturing weights consist of two effects, the competition through imports of manufactures and through exports of such goods, with the relative importance depending on the relative size of these two flows. Within exports, the weights reflect both the direct competition with the producers in the destination country and the indirect competition with them in third-country markets, which is called the third-market effect. In the new calculations—as in the Industrial System—the importance of the third-market effect is determined by the relative importance of imports of manufactures versus sales of home products of the destination countries (hence, the more closed the country, the smaller the weight). By contrast, the Global System arbitrarily assigns equal weights to direct and third-market competition.

Table 5 presents relative weights assigned to manufacturing imports under the new system and the old Global System for the set of countries included in Table 1 (the weight for exports is simply one minus this value). The countries with the highest import weights are the non-oil commodity exporters such as Australia, Chile, Argentina, and New Zealand, because such countries import many more manufactures than they export. By contrast, the lowest weights go to economies with few natural resources that import commodities and export manufactures, such as Hong Kong SAR, Singapore, Taiwan Province of China, and Japan. The middle group generally includes economies with more mixed trading patterns, such as the euro area and the United Kingdom. The United States has a very high weight accorded to imports without being a commodity exporter; this reflects the large underlying trade deficit. The old Industrial System weights show a pattern similar to the new weights, while the old Global System weights are less easy to interpret.

Table 5.Importance of Imports in Overall Manufacturing Weights
New WeightsOld Global System WeightsOld Industrial System Weights
Hong Kong SAR0.210.63
Singapore0.270.54
Taiwan Province of China0.300.36
Japan0.310.250.26
Sweden0.310.460.37
Korea0.330.39
China0.340.45
Switzerland0.360.490.46
Denmark0.370.540.39
Canada0.380.550.39
Mexico0.390.54
India0.400.56
United Kingdom0.440.540.47
Euro area0.450.390.72
Turkey0.460.57
Russia0.49
South Africa0.480.68
Brazil0.540.37
Norway0.570.660.43
United States0.580.570.61
New Zealand0.650.750.56
Argentina0.680.51
Chile0.740.84
Australia0.750.750.53

Table 6 presents the relative importance of third-market competition versus bilateral export competition in the same format as Table 5. In the new weights, the importance of third-market competition depends on the openness of the countries to which exports are sent. Hence, third-market weights are relatively small for countries, such as Canada and Mexico, which export mainly to the relatively closed U.S. market, and are larger for countries, such as Singapore, Australia, and India, whose main export markets are the relatively open Asia region. Notably, all of these weights are below 0.5, the value assigned to third-market weights in the existing Global System. The existing weights in the Industrial System show a generally similar pattern to those from the new methodology, with the exception of New Zealand.

Table 6.Importance of Third-Market Components In Manufactures Export Weights
Third-Market Weight/Bilateral Export Weight
New weightsOld global system weights 1Old industrial system weights
Canada0.221.000.08
Mexico0.241.00
Argentina0.241.00
Chile0.261.00
Brazil0.261.00
United States0.271.000.28
United Kingdom0.271.000.37
Euro area0.291.000.33
China0.291.00
Switzerland0.291.000.28
Turkey0.311.00
New Zealand0.321.000.74
Taiwan Province of China0.331.00
South Africa0.341.00
Japan0.331.000.21
Sweden0.341.000.41
Korea0.341.00
Denmark0.341.000.40
Russia0.35
Hong Kong SAR0.371.00
Australia0.391.000.23
India0.401.00
Norway0.411.000.41
Singapore0.451.00

Old CPI weighting scheme (Global System) gives equal importance to bilateral and third-market competition.

Old CPI weighting scheme (Global System) gives equal importance to bilateral and third-market competition.

Tourism Services Weights

For countries that are heavily dependent on trade in tourism services, the tourism weights are calculated in the same manner as the Industrial System for manufactures weights (details in Appendix II). Like manufactures, tourism services are viewed as differentiated products, except that the product is sold by bringing tourists into a country.

III. Reconstructing the Effective Exchange Rates

This section examines the implications of the new effective exchange rate weights for the analysis of exchange rate movements since 1995, the period most relevant for policy analysis and also the period for which the new weights are most applicable.

Given a set of weights for country i on partner countries (Wij for ji), REER indices are calculated as a geometric weighted average of bilateral real exchange rates between the home country and its trade partners. Specifically, the REER index of country i is calculated by

Ei=Πji(piRipjRj)wij,

where j refers to trade partners, P refers to CPI, and Ri and Rj are bilateral nominal exchange rates of country i and j against the U.S. dollar (measured in U.S. dollar per local currency).

General Trends

Figure 1 graphs REER indices for a wide range of countries since the start of 1995 (keeping the 1995 average equal to 100), calculated vis-à-vis about 40 major trader countries. Figure 1 reports new and existing effective exchange rates, as well as national estimates for the United States, the euro area, and Japan.

Figure 1.CPI-Based Real Effective Exchange Rate Index

(June 1995 = 100)
(June 1995 = 100)
(June 1995 = 100)
(June 1995 = 100)

The most notable change for the major currencies is the more muted appreciation and subsequent depreciation of the U.S. dollar using the new weights. The U.S. real exchange rate based on new weights rose by some 25 percent between 1995 (as a whole) and February 2002, rather than the 40 percent found using the existing weights, and fell less subsequently. This smaller appreciation is not offset by smaller depreciations of currencies such as the euro or the yen. Rather, there appears to be a tendency for most currencies to have a smaller appreciation or larger depreciation under the new weights—most real effective indices have smaller numerical values. This seemingly paradoxical result reflects underlying changes in international trade relations. The key here is the increased weight of the United States in most other countries’ effective exchange rates and the rising importance of developing countries in the U.S. effective exchange rate. Between 1995 and early 2002, many countries experienced a significant bilateral real depreciation against the U.S. dollar, which was only partly reversed subsequently. Because the U.S. dollar is generally accorded a higher weight in the new calculations, this means that outside of the United States, exchange rates have tended to depreciate more on a multilateral basis. In contrast, the new calculations for the United States put more weight on developing countries, whose exchange rates have changed less against the dollar. This leads to the unintuitive result that most REER indices are numerically smaller using the new weights since 1995.8

The U.S. real exchange rate index calculated under the new weights has been much closer to the index calculated by the U.S. authorities. The U.S. panel of Figure 1 shows that the real exchange rate index based on the new weights has tracked the Federal Reserve Board (FRB) real exchange rate index (which uses weights that are updated from year to year) much more closely than the real exchange rate index based on the existing weights. 9 For the euro and the yen, all three indices are much closer to one another than they are for the U.S. dollar.

Exchange Rates vis-à-vis Subgroups of Trading Partners

The exchange rate indices can be calculated separately vis-à-vis subgroups comprising developing and advanced countries to illustrate the roles of two groups. Figure 2 presents the exchange rate subindices measuring only the contribution of either industrial or developing countries (the overall effective exchange rate is thus a sum of these two indices). It comes out clearly that exchange rate fluctuations are larger against industrial countries than against their developing counterparts. This is not limited to the largest traders (such as the United States and the euro area), against which many countries formally peg, but is also true for the smaller industrials.10 It probably reflects a range of issues, including the fact that many emerging market countries are more open to trade, have trade patterns that are often more concentrated and hence dependent on specific currencies, and often borrow internationally in the currencies of their major trading partners. All of these will create a desire to limit exchange rate fluctuations against major trading partners—the so-called “fear of floating” syndrome (Calvo and Reinhart, 2002). In addition, the group comprises a larger number of individual countries, so fluctuations in individual countries may tend to cancel out more often.

Figure 2.Old and New Exchange Rate Index Relative to Subgroups

(CPI-Based Real Effective Exchange Rate Index, June 1995 = WO)
(CPI-Based Real Effective Exchange Rate Index, June 1995 = WO)
(CPI-Based Real Effective Exchange Rate Index, June 1995 = WO)
(CPI-Based Real Effective Exchange Rate Index, June 1995 = WO)

Though not presented here, we also calculated the exchange rate across only the industrial countries to compare the REERs based on the new weights with the existing Industrial System, which uses a more similar methodological approach (the new REERs are calculated using unit labor costs, because this is how the real exchange rates are calculated and reported under the existing Industrial System).11 The differences in the path of the real exchange rates were generally quite small, and largest for Australia and New Zealand, countries where the weight of commodities in trade changed significantly. This suggests that the main reason for the differences in Figure 1 is the differences in methodology and weights across industrial and developing countries.

Three Exchange Rate Events

To further illustrate the properties of the new and existing weights, we compare the real exchange rate movements across all countries for three recent episodes of large exchange rate movements: the Asian crisis (June 1997 to January 1998), the Argentine crisis (January to September 2002), and the U.S. dollar depreciation between February 2002 and May 2004.

Asian crisis. Table 7 shows the changes in the two multilateral exchange rates around the Asian crisis, from June 1997 to January 1998. The depreciations in the crisis countries (Indonesia, Korea, Malaysia, the Philippines, and Thailand) are similar across the two approaches, reflecting the generalized nature of the fall in their exchange rates. Elsewhere, exchange rates are generally estimated to have appreciated more (or depreciated less) in real effective terms under the new weights than under the old ones. The difference is particularly large for economies with close regional ties, including Australia, China, Japan, New Zealand, and Taiwan Province of China. Their REERs appreciated by at least 2 percentage points more under the new weights than under the old ones.

Table 7.Percent Change In Real Effective Exchange Rates During Asian Crisis(My 1997 to January 1998)
New WeightsOld Global WeightsDifference
Indonesia−67.5−67.90.3
Korea−39.6−40.00.4
Malaysia−33.9−34.20.4
Philippines−26.9−28.71.9
Thailand−42.5−43.61.1
United States10.411.1−0.7
Euro area2.82.9−0.1
Japan−0.9−2.92.1
United Kingdom6.96.70.3
Switzerland3.02.90.1
Canada−0.81.5−2.3
Australia−2.4−5.32.9
New Zealand−5.9−8.12.1
Norway3.02.50.6
Sweden1.31.5−0.2
Denmark0.50.60.0
Singapore−2.6−4.41.8
China16.912.14.8
Hong Kong SAR10.611.4−0.8
Taiwan Province of China−8.1−10.32.2
India7.45.51.9
Pakistan3.42.70.8
Argentina6.77.3−0.6
Brazil2.93.9−1.0
Chile2.22.00.2
Colombia−9.6−7.9−1.7
Mexico8.610.4−1.7
Peru6.15.50.7
Venezuela, R.B. de23.422.50.9
Hungary1.81.70.1
Poland3.93.9−0.1
Israel3.83.50.2
Turkey13.313.00.3
Egypt9.47.42.0
Iran, I.R. of19.213.06.2
Saudi Arabia10.69.31.3
Algeria11.810.21.6
Morocco4.84.30.5
Nigeria10.16.73.3
South Africa0.6−1.42.0

The Argentine crisis. Table 8 compares the changes in the two multilateral exchange rates from January to September of 2002. Again, the impact on the crisis countries (Argentina, Brazil, and the República Bolivariana de Venezuela) is similar under the two weighting schemes. Most other countries are found to have gone through a larger appreciation or a smaller depreciation under the new weights than under the old ones. In particular, Latin American countries with close ties to Argentina are found to have experienced smaller real depreciation under the new weights, together with many other emerging markets and the United States. The real depreciation of the United States and some closely linked countries is likely to have been driven by the trend depreciation of the dollar that started in February 2002. Currencies of other industrial countries, which generally appreciated during the crisis, are found to have appreciated by more under the new weights.

Table 8.Percent Change In Real Effective Exchange Rates During Argentine Crisis(January to September 2002)
NewGlobal Old SystemDifference
Argentina−45.2−49.13.9
Brazil−24.0−28.94.9
Venezuela, RB. de−35.3−38.02.7
United States−1.8−4.02.2
Euro area7.76.51.2
Japan6.24.61.6
United Kingdom3.12.40.7
Switzerland3.82.61.1
Canada2.00.31.7
Australia1.91.30.6
New Zealand6.65.31.3
Norway10.810.40.4
Sweden5.34.21.2
Denmark4.53.80.7
Indonesia14.913.21.7
Korea7.95.22.7
Malaysia−4.0−4.70.8
Philippines−5.0−5.20.2
Thailand−1.4−2.41.0
Singapore−0.9−1.40.5
China−9.9−9.3−0.7
Hong Kong SAR−4.9−5.20.3
Taiwan Province of China−3.4−4.51.1
India−1.7−3.51.8
Pakistan1.0−0.61.5
Chile−5.0−8.93.9
Colombia−10.9−16.25.2
Mexico−8.7−10.01.4
Peru−2.5−6.03.5
Hungary3.64.6−0.9
Poland−11.1−10.0−1.1
Israel−5.2−6.81.6
Turkey−12.2−11.5−0.8
Egypt−4.4−5.20.8
Iran, I.R. of−77.2−77.30.1
Saudi Arabia−5.2−7.11.9
Algeria−13.2−14.41.2
Morocco0.5−0.10.6
Nigeria−7.7−9.11.4
South Africa11.49.81.6

Depreciation in the U.S. dollar from early 2002 to 2004 (Table 9). The U.S. dollar depreciated by about 10 percent from the peak of February 2002 to May 2004 under the new weights, 4 percentage points less than under the existing weights for all countries. The smaller dollar depreciation under the new weights is again attributable to the increase in the importance of developing countries for U.S. trade and to the relative stability of the exchange rates between these developing countries and the United States. Because of the larger weight of the United States in other countries’ trade, however, other currencies are generally found to have appreciated by a larger margin (for example, the euro) or to have depreciated by a smaller margin (for example, the currencies in many developing countries). The difference is most noticeable for the Western Hemisphere countries, including Canada. These differences are much less stark if the comparison is made only with other industrial countries, whether the weights are taken from the Global System or Industrial System (Table 10). Given the significant differences between different exchange rate indices, Table 11 compares two IMF exchange rate indices and those constructed by the authorities for the dollar, euro, and yen. For the U.S. dollar, the FRB index appears to be much closer to the IMF index based on new weights than the existing index based on old weights. The contrast is much smaller for the euro and yen.

Table 9.CPI-Based Real Effective Exchange Rates During US Dollar Depreciation(Percent change from February 2002 to May
NewOld Global WeightsDifference
United States−9.6−13.74.1
Euro area22.920.82.2
Japan3.1−1.34.4
United Kingdom4.42.91.4
Switzerland3.61.62.0
Canada12.17.54.6
Australia21.719.42.3
New Zealand25.021.83.3
Norway3.42.41.1
Sweden11.29.31.9
Denmark9.78.31.4
Indonesia14.811.23.6
Korea6.01.74.3
Malaysia−11.7−13.62.0
Philippines−14.6−17.02.4
Thailand−2.8−5.72.9
Singapore−6.2−7.31.2
China−16.7−15.8−0.9
Hong Kong SAR−16.6−16.60.0
Taiwan Province of China−10.6−13.02.3
India−3.2−6.83.6
Pakistan−3.2−6.43.2
Argentina−16.1−22.26.1
Brazil−16.1−20.54.4
Chile−2.9−8.55.6
Colombia−11.7−18.26.5
Mexico−21.2−24.53.3
Peru−6.4−12.66.2
Venezuela, R.B. de−27.5−32.55.0
Hungary12.513.5−1.0
Poland−18.4−16.0−2.4
Israel−13.6−17.33.7
Turkey2.52.8−0.3
Egypt−32.5−33.91.4
Iran, I.R. of−77.4−78.20.7
Saudi Arabia−16.7−19.83.2
Algeria−12.0−14.52.5
Morocco0.6−1.21.8
Nigeria−7.5−9.82.3
South Africa51.446.84.6
Table 10.Real Effective Exchange Rate (REER) During U.S. Dollar Depredation 1(percent change from February 2002 to May 2004)
Only Industrial Countries
New weightsGlobal system weightsIndustrial system weights
Percent change in REERPercent change in REERDifference from new weightsPercent change in REERDifference from new weights
United States−20.2−20.50.2−19.2−1.0
Biro area16.014.41.713.52.6
Japan−3.5−7.23.7−2.6−0.9
United Kingdom1.30.50.80.50.9
Switzerland6.05.01.14.61.5
Canada13.78.45.214.9−1.2
Australia17.416.41.018.2−0.8
New Zealand24.122.21.826.7−2.7
Norway7.57.10.46.11.4
Sweden10.19.80.39.20.8
Denmark8.68.30.36.71.9

Real exchange fates based on unit labor costs.

Real exchange fates based on unit labor costs.

Table 11.Comparison of Exchange Rate Indices
Changes Relative to 1995 AverageChanges Relative to 2002Q1
U.S. doller
IMF newIMF old 1NationalIMF newIMF oldNational
1997Q14.59.25.7
1998Q114.420.117.1
1999Q113.118.016.0
2000Q114.021.117.3
2001Q123.032.326.4
2002Q127.839.931.0
20G3Q121.228.325.0−6.7−11.6−6.0
2003Q217.123.920.8−10.7−16.0−10.2
2003Q317.324.021.2−10.5−15.9−9.8
2003Q413.018.216.6−14.8−21.7−14.4
2004Q110.515.514.4−17.3−24.4−16.6

IMF old refers to the CPI-based real exchange rates calculated under the global system.

Euro
IMF newIMF oldNationalIMF newIMF oldNational
1997Q1−7.5−5.6−7.6
199SQ1−9.5−8.0−10.8
1999Q1−8.1−6.5−7.6
2000Q1−18.7−17.0−17.6
2001Q1−19.8−17.4−18.8
2002Q1−20.0−16.8−19.8
2003Q1−7.9−5.3−8.812.111.611.0
2003Q2−4.5−2.0−5.615.514.814.2
2003Q3−5.2−2.7−6.214.814.213.6
20D3Q4−2.4−0.5−4.017.616.415.8
2004Q1−0.51.6−1.919.518.517.8

IMF old refers to the CPI-based real exchange rates calculated under the global system.

Yen
IMF newIMF oldNationalIMF newIMF oldNational
1997Q1−22.4−2L0−21.5
1998Q1−17.1−16.9−14.5
1999Q1−13.6−12.7−9.2
2000Q1−7.6−5.4−4.2
2001Q1−13.9−11.4−12.7
2002Q1−22.5−19.8−19.7
2003Q1−20.5−19.6−48.82.00.30.9
2003Q2−21.2−21.0−19.21.3−1.20.5
2003Q3−21.2−20.9−19.11.3−1.00.6
2003Q4−17.4−17.8−15.15.02.14.6
2004Q1−18.6−19.1−16.13.80.83.6

IMF old refers to the CPI-based real exchange rates calculated under the global system.

IMF old refers to the CPI-based real exchange rates calculated under the global system.

IV. Conclusions

When trade weights based on data 10 years apart are compared, several changes in the global trade pattern stand out. While industrial countries remain the dominant force in the global trading system, their relative importance has declined, being replaced by emerging market countries, including China. In contrast to the relative decline in the importance of industrial countries as a whole, the weight of the United States has increased for most trading partners. At the same time, reflecting the rise in regionalism, the weights of regional trading partners have increased for countries in the NAFTA, Latin America, and Southeast Asia.

When new weights are used to calculate effective exchange rates, different pictures emerge for several exchange rate episodes. Starting in 1995, the new REER index for the U.S. dollar appreciated much less in the lead-up to its February 2002 peak than the existing index. Subsequently, the new index also depreciated less than did the existing index. In both cases, the new index is found to have moved much more consistently with the FRB index than the index that was calculated on the basis of old trade data.

During the Asian crisis in the late 1990s and the Argentine crisis in 2002, the REERs of industrial countries are found to have appreciated more under the new weights than under the old weights. This contrast is consistent with the rise in the importance of crisis countries in world trade over the last decade. Beyond crisis periods, the much-publicized symptom of fear of floating is observed in the real exchange rate between industrial countries and developing countries as a bloc. The real exchange rates of industrial countries calculated vis-à-vis developing countries look almost constant, relative to their real exchange rates calculated vis-à-vis the rest of industrial countries.

APPENDIX I

Data

A summary of our methodology helps put the data discussion in context. We separately calculated—for each country—(normalized) partner competitiveness weights in three categories of trade, namely, (1) commodities, (2) manufactures, and (3) tourism. Trade in services other than tourism was assumed to follow a pattern similar to trade in manufactures, and no separate weights were calculated for this category of trade. The three sets of partner weights were then aggregated to obtain an overall set of competitiveness weights—again, for each country—by weighting them by the proportion of trade in the respective trade categories. For this purpose, trade in nontourism services was lumped with trade in manufactures, because they are assumed to behave similarly.

(1) Merchandise trade: Data were obtained from the United Nations Common Format for Transient Data Exchange (COMTRADE) database at the SITC double-digit level on a bilateral basis. Averages over 1999-2001 (or as available in the period) were used in the calculations Bilateral trade flows made it possible to correct for intra-euro-area trade in constructing euro-area series from individual euro-area member country trade flows.

Commodity categories were distinguished in our exercise at the SITC double-digit level. They comprise SITC single-digit codes 0, 1, 2, 4, and SITC double-digit code 68 (nonferrous metals). (See Table A.1 for all corresponding double-digit codes and category descriptions.) Trade in each commodity category is assumed not to be distinguished by source (that is, imports of the same commodity from different countries are perfectly substitutable). Under this assumption, only total trade of each country by commodity group is needed to calculate the competitiveness weight to be accorded to the country either as a competitive producer or a consumer of that commodity. Bilateral trade from COMTRADE was aggregated by commodity for each country to create the series needed. Weights were then calculated for each commodity and then aggregated into one overall commodity weight 12 using proportions of trade in the various commodities for each country.

Table A.1.Two-Digit Standard International Trade Classification (Revision II) Categories
Food
Live animals, chiefly for food00
Meat and preparations01
Dairy products and birds eggs02
Fish, crustaceans, mollusks, preparations thereof03
Cereals and cereal preparations04
Vegetables and fruit05
Sugar, sugar preparations, and honey06
Feeding stuff for animals, not including unmilled cereals08
Miscellaneous edible products and preparation09
Agricultural Raw Materials
Tobacco and tobacco manufactures12
Hides, skins, and fur skins, raw21
Crude rubber (including synthetic and reclaimed)23
Cork and wood24
Pulp and waste paper25
Textile fibers (except wool tops) and their wastes26
Oils
Oil seeds and oleaginous fruit22
Crude animal and vegetable materials, n.e.s,29
Animal oils and fats41
Fixed vegetable oils and fats42
Animal-vegetable oils-fats, processed and waxes43
Industrial Materials
Crude fertilizers and crude materials (excluding coal)27
Metalliferous ores and metal scrap28
Nonferrous metals68
Beverages
Coffee, tea, cocoa, spices, manufactures thereof07
Beverages11
Source: UN COMTRADE Database.
Source: UN COMTRADE Database.

All other SITC codes, except the fuels group (single-digit code 3), were aggregated into a single manufactures group.13 Fuels were thus excluded from the exercise. The manufactures group, in contrast to the commodities group, is just a single composite group, trade in which is distinguished by source. Calculation of manufacturing weights, therefore, requires bilateral detail. For many countries with two observations of bilateral trade flow (export from country A to B and import by country B from A), the average of the two observations was used. For countries without their own data on bilateral trade, bilateral trade data as reported by partner countries were used.

(2) Services trade: Data were obtained from the IMF’s World Economic Outlook. This was used only to derive the share of manufacturing (that is, manufacturing plus nontourism services) in total trade.

(3) Domestic sales of (home-produced) manufactures: These data were constructed for each country by subtracting the country’s manufactures exports from an estimate of its U.S. dollar nominal gross manufacturing output. Gross manufacturing output was obtained for industrial countries from the STAN database of the Organization for Economic Cooperation and Development. However, it is not readily available from a common source for developing countries. It was, therefore, estimated from net (value-added) manufacturing data, which are available from the World Bank for a large number of countries. Based on the observed gross/net ratio for industrial countries, a ratio of 10/3 was applied to estimate gross output from the reported net manufacturing output.

For two economies—Hong Kong SAR and Singapore—the estimation based on a 10/3 ratio produced implausible results. The value of their manufacturing exports exceeded their gross output, a physical impossibility, presumably reflecting their role as a reprocessing base and the host for entrepôt trade. We, therefore, applied a ratio of 6/1 for these two economies, which would then imply a measure of openness (as measured by exports/gross output) that is consistent with what is observed for similarly open countries, such as Malaysia, Hungary, and the Czech Republic (Figure A.1).

Figure A.1.Manufactures: Exports Versus Gross Output

(Local currency, millions)

(4) Tourism trade: Data on tourist arrivals by country and total tourism exports were obtained from the World Tourism Organization. Tourism data were only kept for countries where tourism exports exceeded a threshold of 20 percent of total exports; for other countries, tourism was considered not significant (in keeping with the current approach to weight calculation) and therefore dropped. Tourism exports of 29 countries, which met the threshold criterion, were allocated to partner countries based on the number of tourist arrivals from those partner countries. These bilateral tourism data were used in calculating tourism weights in a manner similar to manufactures.

The 29 countries with bilateral tourism data are Albania, Antigua and Barbuda, The Bahamas, Barbados, Belize, Comoros, Croatia, Cyprus, Dominica, the Dominican Republic, Egypt, Eritrea, Fiji, Georgia, Greece, Grenada, Jamaica, Jordan, Lebanon, Maldives, Malta, Mauritius, Samoa, Seychelles, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Uganda, and Vanuatu.14

APPENDIX II

REER Algebra

We develop a simple example that shows that new trade weights can numerically increase or decrease all multilateral exchange rates in the same direction. Consider a three-country world. Let matrix A below denote the trade weight and vector b denote the log changes in bilateral exchange rates against the third country (denoted as the price of the third currency in terms of the first and second currencies).

A0=(012121201212120)b=(b1b20).

The multilateral exchange rates of all three countries are defined by the following vector R, where I denotes an identity matrix:

R0=(A0-I)b.

Next consider the following new trade weights and the associated real exchange rates. Under the new trade weights, the importance of the third country rose to an extreme—the first and second countries trade only with the third country:

A0(001001x1-x0)R1=(A1-I)b.

Now consider the difference between the two real exchange rates based on trade weights A1 and A2:

R1R0=(12b212b1(x12)(b1b2))

It is possible that all real exchange rates are numerically smaller or larger than the other, depending on the relative movements of trading pattern and bilateral rates against the third country. This can be expressed algebraically as follows:

Case1:R1»R0ifb1<b2<0andx<12,andCase2:R1«R0ifb1>b2>0andx<12.

If we name the three countries as the euro area, Asia, and the United States, the euro has depreciated more against the dollar than against Asian currencies (b1 >b2>0), while Asia’s share in U.S. trade has increased (x<12).. This corresponds to Case 2, causing all three real exchange rates to decline numerically.

References

Tamim Bayoumi is Assistant Director of the IMF Western Hemisphere Department. Jaewoo Lee is a Senior Economist and Sarma Jayanthi a Senior Research Officer with the IMF Research Department. We owe many thanks to Ercument Tulun for excellent assistance in compiling the trade data, as well as to Teng-Siew Boxall for generous help with old weights and tourism data. We benefited greatly from comments by numerous colleagues at the IMF, including Ketil Hviding, Gian Maria Milesi-Ferretti, and Alessandro Zanello.

The methodology for the effective exchange rate calculation was applied widely as part of the Information Notice System (INS), which was purported to facilitate surveillance over exchange rate policies. The surveillance purpose has since been deemphasized, but one legacy of the INS has been the methodology of calculating the effective exchange rate.

Hence, the updating discussed in the paper is close to but different from the full updating of exchange rate weights that encompasses all 184 countries covered by the INS. See the working paper version of this paper (Bayoumi, Lee, and Jayanthi, 2005) for further details on completing the weights calculation for all 184 countries.

Trade weights are calculated both for individual euro-area countries and for the euro area as one bloc. However, the descriptive discussion focuses on the euro area as one bloc.

Over the 1991–2001 period, U.S. growth in merchandise trade exceeded that of the euro area in both value and volume terms.

See Annex 2 of Bayoumi, Lee, and Jayanthi (2005) for detailed formulas for the weights discussed in this section.

The euro area is not the only monetary union in existence. Whereas this paper chose the euro area as the most conspicuous example in terms of its global economic weight, similar calculations can be made for other monetary unions (for example, the West African Economic and Monetary Union) as needed for policy analysis.

Intra-euro-area trade in manufactures is also netted out from trade statistics but reflected in weights as domestic sales.

See Appendix II for an illustrative algebraic analysis of a three-country example.

See Leahy (1998) for a discussion of the FRB index.

For example, it is true for Japan despite the fact that many emerging Asian economies are generally considered to be more concerned with their bilateral exchange rates against the U.S. dollar than against the yen and that the yen–U.S. dollar rate has fluctuated quite significantly.

See Bayoumi, Lee, and Jayanthi (2005) for a figure that compares two indices.

The euro area figures less prominently as a commodity competitor in our calculations because intra-euro-area commodity trade flows are no longer included in total commodity trade. An approach similar to the one employed for manufactures that also takes into account domestic demand would correct for this problem, but domestic demand would be hard to compile across a large set of countries for each commodity at the SITC double-digit level.

Hong Kong SAR’s imports were adjusted for re-exports. Imports, as obtained from COMTRADE, were nearly an order of magnitude larger than exports and clearly seemed to include a huge amount of merchandise re-exported via Hong Kong SAR. Therefore, Hong Kong SAR’s imports were corrected for reexports, assuming a margin of 15 percent. The reexports series was also obtained from COMTRADE.

Four of these countries are excluded from the Industrial System but included in the Global System—Antigua and Barbuda, The Bahamas, St. Vincent and the Grenadines, and Vanuatu.

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