the role of nominal anchor currencies in exchange rate arrangements

JOURNAL OF THE JAPANESE AND INTERNATIONAL ECONOMIES 12, 334–387 (1998)ARTICLE NO. JJ980419

The Role of Nominal Anchor Currencies in ExchangeRate Arrangements

Masahiro Kawai*,† and Shigeru Akiyama†

*World Bank, 1818 H Street, N.W., Washington, DC 20433; and †Institute of Social Science,University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113, Japan

Received July 8, 1998; revised October 14, 1998

Kawai, Masahiro, and Akiyama, Shigeru—The Role of Nominal Anchor Currenciesin Exchange Rate Arrangements

This paper studies the evolution of exchange rate arrangements of almost allcountries in the world over the period 1970–1996. It examines both officially reportedand empirically observed exchange rate arrangements. Several findings are obtained.First, the relative economic size of countries under fixed exchange rate regimes hasnot declined as dramatically as the measure based on reported arrangements wouldindicate. Second, the U.S. dollar has been the most dominant, global anchor currencybecause many developing economies, particularly those in Asia, Latin America,and the Middle East, have attempted to stabilize their exchange rates to the dollar.Third, the reserve currency composition is determined by the constructed measureof the net currency-area size in addition to the own-economic size of the reservecurrency country. Fourth, as a result of the transition to the final stage of EMU,the euro is expected to emerge as the world’s second most dominant anchor currency.While the Japanese yen will continue to play a less significant role as nominalanchor, its role in East Asia is expected to rise gradually. J. Japan. Int. Econ.December 1998, 12(4), pp. 334–387. World Bank, 1818 H Street, N.W., Washington,DC 20433 and Institute of Social Science, University of Tokyo, 7-3-1 Hongo,Bunkyo-ku, Tokyo 113, Japan. 1998 Academic Press

Journal of Economic Literature Classification Numbers F31, F33, F36.

This is a revised version of the paper presented to the NBER–TCER–CEPR TrilateralConference ‘‘International Monetary Regime in the 21st Century’’ held in Tokyo on December19–20, 1997. The authors are grateful to James Boughton, Peter Clark, and Peter Quirk foruseful conversations at the initial stage of this research and to Barry Eichengreen, TakatoshiIto, Eiji Ogawa, Shinji Takagi, Kazuo Yokokawa, and other conference participants forcomments on earlier versions of the paper. The views expressed in the paper do not representthose of the World Bank.

3340889-1583/98 $25.00Copyright 1998 by Academic PressAll rights of reproduction in any form reserved.

EXCHANGE RATE ARRANGEMENTS 335

I. INTRODUCTION

This paper examines the evolution of exchange rate arrangements ofalmost all countries in the world since the end of the Bretton Woods fixedparity system. The paper focuses particularly on the role played by theworld’s major currencies, such as the U.S. dollar, the deutsche mark, andthe Japanese yen, as nominal anchors for other countries’ exchange rate sta-bilization.

Until August 1971, when President Richard Nixon suspended the officialconvertibility of the U.S. dollar to gold, exchange rate fluctuations of manyInternational Monetary Fund (IMF) member countries had been limitedwithin a narrow margin (61%) around par values set in terms of gold orthe U.S. dollar. Soon after the Nixon shock, the industrialized world’s fixedexchange rate regime began to unravel. In the spring of 1973, the EuropeanCommunity countries severed the link between their currencies and theU.S. dollar, Japan decided not to support the Smithsonian central rate, andthe international monetary system entered a new era called the ‘‘generalizedfloating’’ system. To avoid greater exchange rate volatility, a large numberof developing countries maintained a fixed rate regime by stabilizing theirexchange rates to the major industrialized countries’ currencies, and severalWestern European countries continued to limit their exchange rate move-ments within narrow margins. The latter included the formation of the‘‘snake’’ by Belgium, France, Germany, Italy, Luxembourg, and the Nether-lands in April 1972,1 which eventually led to the establishment of theEuropean Monetary System in 1979.

Even under generalized floating, the currencies of the major industrial-ized countries continue to play a significant role as nominal anchors towhich other countries stabilize their exchange rates. In the Bretton Woodsera, the U.S. dollar and the UK pound were dominant anchor currencies.In more recent years, it is sometimes claimed that the deutsche mark and,to a limited extent, the Japanese yen have risen to nominal anchor currencystatus. This claim supports the view that a multipolar international monetarysystem is emerging, centered on the economic might of the largest countriesand entities of the world, that is, the United States, the European Union,and Japan.

Studies on currency blocs by Frankel and Wei (1993, 1994, 1995) exam-ined the roles of the U.S. dollar, the deutsche mark, and the Japaneseyen as potential nominal anchor currencies by using a selected sample of

1 England (and Ireland, which pegged its currency to the UK pound) and Denmark joinedthe snake in May 1972. Norway and Sweden also joined as associate members. Among thesecountries, only Belgium, Denmark, Germany, Luxembourg, the Netherlands, and Norwaywere stable members of the snake.

336 KAWAI AND AKIYAMA

countries. They found that while the U.S. dollar and the deutsche markare dominant nominal anchor currencies in their respective regions, i.e.,the Western Hemisphere and Western Europe, the Japanese yen is notdominant in Asia. Instead, the U.S. dollar is the dominant nominal anchor inAsia. Extending the scope of the Frankel–Wei studies, this paper examinesexchange rate arrangements for almost all countries in the world. As poten-tial nominal anchors, we focus on the currencies of five major industrializedcountries, two important currency baskets, and the currencies of potentiallyrelevant minor countries to present a comprehensive picture of the changingrole of the major and minor currencies in shaping the international mone-tary system.

The paper is organized as follows. Section II offers rich informationon exchange rate arrangements from three different perspectives. First, itreviews the evolution of ‘‘reported’’ exchange rate arrangements of IMFmember countries. Second, it examines patterns of exchange rate volatilitymeasured in terms of potential nominal anchor currencies. A currency isjudged to be a good candidate as a nominal anchor if any given country’sexchange rate vis-a-vis this particular currency exhibits the smallest volatil-ity and if the magnitude of volatility itself is small and close to zero. Third,it presents a regression analysis of the Frankel and Wei type to measurethe relative weights of nominal anchor currencies in the country’s exchangerate management. Section III discusses how exchange rate arrangementshave evolved in each region of the world since the beginning of the 1970sbased on information provided in Section II. It reports that the actualexchange rate policies adopted in different regions have distinct characteris-tics in terms of the size of exchange rate volatility and the choice of nominalanchor currencies. Section IV conducts several exercises making use ofinformation obtained in Section II. First, it calculates the economic sizesof countries under fixed and flexible exchange rate regimes using the esti-mated, conditional volatility of exchange rate movements and comparesthese results with those that would be obtained from information on re-ported arrangements. Next, it calculates the economic sizes of currencyareas formed by each of the G-5 industrialized countries (i.e., the UnitedStates, Germany, France, the United Kingdom, and Japan), the SpecialDrawing Rights (SDR), and the European Currency Unit (ECU), usingthe estimated weights of nominal anchor currencies. Finally, it calculatesthe economic sizes of currency areas that would be formed by the prospec-tive euro, the U.S. dollar, and the Japanese yen under alternative assump-tions of possible Economic and Monetary Union (EMU) membership. InSection V, we examine econometrically whether the shares of the G-5currencies held by the world’s central banks as foreign exchange reservescan be better explained by our estimated measures of currency areas in


addition to the traditionally used variable, i.e., the own-economic size of therespective reserve-currency country. Section VI offers concluding remarks.

II. REPORTED AND OBSERVED EXCHANGE RATEARRANGEMENTS

1. Reported Exchange Rate Arrangements

The IMF regularly publishes exchange rate arrangements reported by itsmember countries according to its classification scheme. Table I summarizeschanges in exchange rate arrangements, as classified by the IMF, in termsof the number of countries.2

Exchange rate arrangements are currently classified broadly into threecategories, i.e., (a) a fixed rate arrangement, (b) limited exchange rateflexibility, and (c) a more flexible rate arrangement. First, the fixed ratearrangement includes a ‘‘peg to a single currency’’ and a ‘‘peg to a basketof currencies.’’ As target currencies for single-currency pegs, the IMF liststhe U.S. dollar, the French franc, the deutsche mark, the Australian dollar,the Indian rupee, the South African rand, the Italian lira, and the Singaporedollar at end-1997. In the past, the list used to include the UK pound,the Spanish peseta, the Portuguese escudo (for their respective formercolonies), and the Russian ruble (for the newly independent, former Sovietrepublics soon after the collapse of the Soviet Union). A peg to a basketof currencies is further divided into a ‘‘peg to the SDR’’ and a ‘‘peg to acurrency composite other than the SDR.’’ While currency compositions ofthe SDR and their weights are clearly defined by the IMF, those of othercurrency composites are specific to the respective country and in mostcases are not made publicly available. To find such information, one muststatistically analyze the observed exchange rate movements and estimatethe basket composition and currency weights.

Second, the classification ‘‘limited exchange rate flexibility’’ includes‘‘flexibility limited in terms of a single currency’’ and ‘‘flexibility limited interms of a group of currencies.’’ The first subcategory (flexibility limitedin terms of a single currency) is in reality a de facto peg to the U.S. dollar.The second subcategory (flexibility limited to a group of currencies) is acooperative exchange rate arrangement maintained under the ExchangeRate Mechanism (ERM) of the European Monetary System (EMS).

2 This classification scheme has been revised several times, reflecting the widespread adop-tion of floating exchange rates. This has resulted in the expansion of the number of arrangementcategories. Due to the changes in IMF classifications, some past arrangements cannot be madecomparable to present-day categories for the columns corresponding to the years 1960, 1970,and 1980.

338 KAWAI AND AKIYAMAT

AB

LE

IE

xcha

nge

Rat

eA

rran

gem

ents

ofIM

FM

embe

rC

ount

ries

,19

60–1

997

Num

ber

ofIM

Fm

embe

rco

untr

ies

1960

1970

1980

1985

1990

1991

1992

1993

1994

1995

1996

1997

Fix

edex

chan

gera

tear

rang

emen

t71

116

9494

8681

8473

7166

6666

Peg

ged

toth

eU

.S.

dolla

r53

6539

3125

2424

2123

2221

20P

egge

dto

the

Fre

nch

fran

c2

1714

1414

1414

1414

1414

15P

egge

dto

the

UK

poun

dst

erlin

g15

301

10

00

00

00

0P

egge

dto

the

deut

sche

mar

k0

00

01

11

11

22

3P

egge

dto

the

Rus

sian

rubl

e0

00

00

06

11

00

0P

egge

dto

othe

rcu

rren

cy1

43

45

35

67

67

8P

egge

dto

SDR

——

1512

66

54

43

23

Peg

ged

toot

her

curr

ency

com

posi

te—

—22

3235

3329

2621

1920

17L

imit

edex

chan

gera

tefle

xibi

lity

——

—13

1414

1313

1414

1616

Fle

xibi

lity

limit

edvi

s-a-

vis

asi

ngle

curr

ency

ab

c5

44

44

44

44

Coo

pera

tive

arra

ngem

ents

——

88

1010

99

1010

1212

Mor

efle

xibl

eex

chan

gera

tear

rang

emen

t—

——

4153

6170

8993

100

9999

Adj

uste

dac

cord

ing

toa

set

ofin

dica

tors

ab

45

55

34

32

2—

Oth

erm

anag

edflo

atin

ga

bc

2123

2723

2932

4445

46In

depe

nden

tly

float

ing

ab

c15

2529

4456

5854

5253

Unc

lass

ified

11

11

10

00

00

00

Tot

al75

120

141

149

154

156

167

175

178

180

181

181

Not

e.T

hesu

mof

ais

3,th

esu

mof

bis

3,an

dth

esu

mof

cis

34.F

orm

embe

rsw

ith

dual

orm

ulti

ple

exch

ange

mar

kets

,the

arra

ngem

ent

show

nis

that

inth

em

ajor

mar

ket.

‘‘Peg

ged

toot

her

curr

ency

com

posi

te’’

com

pris

esth

ose

curr

enci

esw

hich

are

pegg

edto

vari

ous

‘‘bas

kets

’’of

curr

enci

esof

the

mem

bers

’ow

nch

oice

,as

dist

inct

from

the

SDR

bask

et.

‘‘Fle

xibi

lity

limit

edvi

s-a-

vis

asi

ngle

curr

ency

’’ha

ssh

own

that

all

curr

enci

esha

velim

ited

flexi

bilit

yin

term

sof

the

U.S

.dol

lar.

‘‘Coo

pera

tive

arra

ngem

ents

’’re

fers

toth

eco

oper

ativ

ear

rang

emen

tm

aint

aine

dun

der

the

Exc

hang

eR

ate

Mec

hani

smof

the

Eur

opea

nM

onet

ary

Syst

em.‘

‘Adj

uste

dac

cord

ing

toa

set

ofin

dica

tors

’’in

clud

esex

chan

gear

rang

emen

tsun

der

whi

chth

eex

chan

gera

teis

adju

sted

atre

lati

vely

freq

uent

inte

rval

s,on

the

basi

sof

indi

cato

rsde

term

ined

byth

ere

spec

tive

mem

ber

coun

trie

s.T

hela

stca

tego

ryw

asab

olis

hed

inth

efir

stqu

arte

rof

1997

.So

urce

s.IM

F,‘

‘Ann

ual

Rep

ort

onE

xcha

nge

Res

tric

tion

s,’’

1961

,197

1;In

tern

atio

nal

Fin

anci

alSt

atis

tics,

vari

ous

issu

es.


Finally, the classification ‘‘more flexible rate arrangement’’ includes‘‘other managed floating’’ and ‘‘independently floating.’’3 The subcategoryindependently floating is supposed to represent a textbook-style flexibleexchange rate regime, while this may possibly contain a heavily managed, oreven a de facto fixed, exchange rate regime. Needless to say, the subcategory‘‘managed floating’’ suggests frequent interventions by the authorities inthe foreign exchange market to control exchange rate movements.

In the spring of 1973, many industrialized countries decided to abandonfixed parity obligations of the Smithsonian Agreement, and the era ofgeneralized floating began. Since then, the number of countries on flexiblerate arrangements, specifically those on more flexible rate arrangements,has risen. Table I shows that at most only 3 of 120 countries (2.5% of thetotal) had adopted a flexible rate arrangement at end-1970 but that thenumber of countries on flexible rate arrangements increased gradually toat most 39 of 141 countries (28% of the total) at end-1980, to 53 of 154countries (34%) at end-1990, and further up to 99 countries of 181 (55%)at end-1997.

On the other hand, there are still a large number of countries thatattempt to stabilize exchange rates vis-a-vis a single currency or a basketof currencies. As of December 1997, in addition to 66 countries formallyon fixed rate arrangements, there were countries which have pursued someexchange rate stabilization by adopting limited exchange rate flexibility (16countries) or other managed floating (46 countries). It is also possible thatsome countries on independently floating have managed their exchangerates tightly to stabilize their rates in terms of a certain currency or basketof currencies.

Focusing on the details of fixed rate arrangements, as of December 1997,the U.S. dollar continues to be the most popular target currency (for 20

3 Between July 1975 and June 1982, the IMF category ‘‘floating’’ was defined in a widesense, including three subcategories of independently floating, common margins, and a set ofindicators. The first subcategory, independently floating, included various types of flexiblerate arrangements. The second subcategory, common margins, referred to the cooperativesnake arrangement maintained by a group of European countries (until February 1979) thatled to the ERM under the EMS (since March 1979). This second subcategory was renamedas the ‘‘cooperative exchange arrangement’’ in July 1982. At the time of the July 1982reclassification, the subcategory independently floating was given a narrow definition andbecame part of the newly defined three separate subcategories, i.e., independently floating,flexibility limited in terms of a single currency, and other managed floating. The third subcate-gory, a set of indicators (or ‘‘adjusted according to a set of indicators’’), was abolished in thefirst quarter of 1997. Detailed information for the 1975–1978 period is available only throughthe IMF’s internal documents, while information for the period since October 1978 can beobtained from the IMF, International Financial Statistics, beginning with the December 1979issue. Information on Hong Kong and Taiwan, not available from IMF publications, is obtainedfrom the Japan Committee for Pacific Economic Outlook (1997).


countries), followed by non-SDR currency baskets (for 17 countries), theFrench franc (for 15 countries), and the deutsche mark (for 3 countries).4

In addition, there are 16 countries which are on limited exchange rateflexibility, and 4 countries out of these are on flexibility limited in termsof a single currency, which is really a peg to the U.S. dollar. Thus, thenumber of countries de facto pegged to the U.S. dollar is 24. The Frenchfranc is a target for the exchange rate pegs of 15 African countries, 14 ofwhich are CFA Franc Area members. The number of countries peggingtheir rates to the SDR has declined rapidly, and in 1997 only 3 countriesformally pegged their currency to the SDR. It is noteworthy to observethat no country pegs its exchange rate to the Japanese yen.

In 1970, the UK pound was a target for as many as 30 countries. By themid-1980s, however, it had completely lost this position.5 As mentionedearlier, immediately following their independence from the Soviet Union,many former Soviet republics used the Russian ruble as a target currency.By June 1995, however, all had ceased to do so.

The second column of the Appendix table summarizes ‘‘reported’’ ex-change rate arrangements for each individual country for the 1990s. Similarinformation can also be presented for earlier periods.6 The following abbre-viations are used to describe various types of reported exchange rate ar-rangements: USD 5 pegged to the U.S. dollar; DM 5 pegged to thedeutsche mark; FF 5 pegged to the French franc; AD 5 pegged to theAustralian dollar; IL 5 pegged to the Italian lira; IR 5 pegged to theIndian rupee; PE 5 pegged to the Portuguese escudo; RR 5 pegged to

4 Though not shown in Table I, other target currencies for single-currency pegs include theSouth African rand (for 3 countries), the Australian dollar, the Indian rupee, the Italian lira,and the Singapore dollar (for 1 country each).

5 Until the beginning of World War II, the UK pound sterling was used more widely thanthe U.S. dollar as international currency. In the postwar Bretton Woods period the poundsterling functioned as the key currency for the Sterling Area until the latter half of the 1960s.After the devaluation of the pound in 1967, the currency’s importance declined precipitously.See Cohen (1971) and Cairncross and Eichengreen (1983) for a history of the decline of thepound sterling.

6 A complete list of information, including that on exchange rate volatility and regressionresults to be discussed later, is available upon request from the authors (see also the discussionpaper version Kawai and Akiyama [1998]). The Appendix table is compiled mainly from thelist of exchange rate arrangements published in the International Financial Statistics, theAnnual Report on Exchange Arrangements and Exchange Restrictions, the Annual Report,and the IMF’s internal documents. The International Financial Statistics (IFS) began to publisha list of exchange rate arrangements on a monthly basis starting in October 1978. Later itchanged to a quarterly basis starting in March 1987. To find the exact month of a change inexchange rate arrangements, we have tried to supplement this information by using the AnnualReport on Exchange Rate Arrangements and Exchange Restrictions and the IMF’s internaldocuments. Unresolved entries, where they remain, are marked with an asterisk in the Appen-dix table to indicate that information is based on IFS quarterly lists.


the Russian ruble; SAR 5 pegged to the South African rand; SID 5 peggedto the Singapore dollar; SDR 5 pegged to the Special Drawing Rights ofthe IMF; CC 5 pegged to other currency composite; LS 5 flexibility limitedvis-a-vis a single currency; CEA 5 cooperative exchange arrangements;AF 5 adjusted according to a set of indicators; MF 5 managed floating;IF 5 independently floating.

Although the table provides useful information as to the nature of ex-change rate arrangements for individual countries, their characteristics arenot discussed in this paper.7

2. Exchange Rate Volatility

The reported exchange rate arrangements provide useful informationabout the nature of the arrangements as reported by the individual coun-tries. However, these reported arrangements do not always describe theactual practice of exchange rate policies, nor do they offer sufficient infor-mation as to which currency or basket of currencies is chosen as a targetfor exchange rate stabilization. To fully understand what exchange ratepolicies are actually pursued, one must statistically examine the behaviorof observed exchange rates.

One way to do this is to calculate exchange rate volatility, as measuredby the standard deviation of monthly rates of change in each country’sexchange rates, and to compare the magnitude of each country’s volatilityvis-a-vis a number of currencies. A currency is a good candidate for anominal anchor if a country’s exchange rate vis-a-vis this particular currencyexhibits the lowest volatility among the currencies studied as potentialanchors. In addition, the magnitude of this volatility must be small andclose to zero.

Our definition of exchange rate volatility is the standard deviation of thefirst difference in natural logarithms of monthly exchange rates vis-a-vis theG-5 currencies, two currency baskets, or other minor, regional currencies,

Det 5 et 2 et21 5 ln(Et) 2 ln(Et21),

where Et is the level of the nominal exchange rate for currency j.The G-5 currencies are the U.S. dollar, the deutsche mark, the French

franc, the UK pound sterling, and the Japanese yen, while two explicit

7 See International Monetary Fund (1997) for discussions of exchange rate arrangementsin developing countries and the appendix in Kawai and Akiyama (1998) for both industrialand developing countries.


currency baskets are the SDR and the ECU.8 We also consider relativelyminor, regional currencies depending on a country’s economic as well asnoneconomic (i.e., colonial, historical, cultural, and geographical) relation-ships. Using information from the reported exchange rate arrangements,we include the Australian dollar, the Indian rupee, the New Zealand dollar,the Portuguese escudo, the Singapore dollar, the South African rand, andthe Spanish peseta in the list of potential nominal anchor currencies for acertain set of countries.9

We use monthly average exchange rates (IFS line code rf) for the sampleperiod of January 1970 through December 1996.10 We divide the sampleperiod into six subperiods, each of 5-year duration except for the last, thatis, January 1970–December 1974, January 1975–December 1979, January1980–December 1984, January 1985–December 1989, January 1990–December 1994, and January 1995–December 1996. The last period ofJanuary 1995 through December 1996 is combined with the preceding5-year period to construct an additional subperiod of 7 years, January1990–December 1996.11

To obtain meaningful estimates of exchange rate volatility, we havedecided to remove data observations with values of log first differencesgreater than 0.1. We have done so because countries often devalue theircurrencies to accommodate persistent differences in inflation rates vis-a-vis their nominal anchor-currency country. Without the effects of such

8 The monthly average series of SDR and ECU exchange rates vis-a-vis the U.S. dollar arealso obtained from the IFS database. However, data for ECU exchange rates are availableonly from January 1978. In order to extend the series into the earlier period, we haveconstructed hypothetical ECU series by using the values of the currencies making up theECU at the time when the ECU was first established in March 1979. To be more precise, wehave calculated the U.S. dollar value of the ECU, as the weighted sum of the U.S. dollarvalues of the ECU currencies’ units, for every month from December 1969 through January1978 and spliced this calculated series to the IFS series of the ECU at January 1978. The ECmember countries used the following fixed amounts of member currencies to construct theECU between March 1979 and September 1984: Belgian franc and Luxembourg franc, 3.80;Danish krone, 0.217; French franc, 1.15; German mark, 0.828; Irish pound, 0.00759; Italianlire, 109; Netherlands guilder, 0.286; and UK pound sterling, 0.0085. These countries had usedthe same currency units since 1975 to calculate the European Unit of Account (EUA). TheIFS database appears to report the EUA exchange rate as the ECU rate between January1978 and February 1979, before the formal introduction of the ECU in March 1979, becauseof the identical construction of these two composite currencies.

9 The Russian ruble is not used as a potential nominal anchor currency due to the lack ofa sufficient number of exchange rate data for the former Soviet republic countries.

10 Exchange rate data for Taiwan are obtained from the Central Bank of China, TaiwanDistrict Financial Statistics, various issues.

11 The recent currency and financial crisis in East Asia suggests that the region’s exchangerate movements may have deviated from the earlier patterns observed until mid-1997. Onthis ground, we have decided not to cover the recent crisis period due to a lack of a sufficientlylarge number of data.


discrete currency devaluations (or revaluations) being eliminated, calcu-lated volatility would become too large to conclude the presence or absenceof a nominal anchor currency.

The third column of the Appendix table summarizes the results of volatil-ity calculations for the period January 1990–December 1996, reporting onlythe name of the currency with the smallest volatility and its magnitude.12

The names of currencies are indicated as follows: USD 5 U.S. dollar;DM 5 deutsche mark; FF 5 French franc; JY 5 Japanese yen; UKP 5UK pound sterling; ECU 5 European Currency Unit; SDR 5 SpecialDrawing Rights; AD 5 Australian dollar; IR 5 Indian rupee; NZD 5 NewZealand dollar; PE 5 Portuguese escudo; SAR 5 South African rand;SID 5 Singapore dollar; SP 5 Spanish peseta.

Depending on the size of the volatility, the pound signs (#) are attachedto indicate the smallness of volatility; the more pound signs are attached,the smaller is the volatility. It is expected that we will be able to identifywhich currency each country has used as a target for exchange rate stabiliza-tion. If a country’s exchange rate is pegged to a particular currency, forinstance the French franc, exchange rate volatility vis-a-vis the French francshould be zero, while volatility vis-a-vis other currencies should take alarger value. If the exchange rate is variable but stabilized, instead of beingrigidly pegged, to the French franc, volatility vis-a-vis the French francshould be relatively small. If the exchange rate is not stabilized but flexible,volatility with respect to any currency should be large. By examining ex-change rate volatility over successive 5-year periods, we will be able toobserve the changing patterns of exchange rate arrangement for anygiven country.

3. REGRESSION ANALYSES OF EXCHANGERATE MOVEMENTS

The volatility analysis above is useful to identify a single nominal anchorcurrency for a given country; it reveals clear regional diversities across theindustrialized and developing economies. The effectiveness of this ap-proach, however, is limited. It is not suitable when a country adopts a policyof stabilizing its exchange rate to a basket of multiple currencies. To dealwith these more general cases, including currency basket arrangements,one must resort to regression analysis to identify a set of anchor currenciesand find their weights used for exchange rate stabilization. Exchange ratestabilization to a single currency can be interpreted as a special case in

12 Complete volatility data for earlier periods are available upon request from the authors(see also Kawai and Akiyama [1998]).


which only one currency is assigned a large positive weight, while othercurrencies’ weights are negligible.

In what follows, we estimate the type of regression equation

De jt 5 a 1 b1DeUSD

t 1 b2DeDMt 1 b3DeJY

t 1 b4DeFFt 1 b5DeUKP

t 1 ut ,

where De jt is the monthly change in the log exchange rate of currency j in

month t, a is a constant term, bk (k 5 1, 2, . . .) is the coefficient on themonthly change in the log exchange rate of currency k, and ut is the residualterm. The estimated standard error of residuals can be interpreted as an-other measure of exchange rate volatility. As before, a monthly change inthe exchange rate is defined by the first difference of the natural logarithmof the nominal exchange rate. We also add to the right-hand side theexchange rates of the SDR, ECU, and other relevant minor, regional curren-cies, reflecting country-specific characteristics. Following Frankel and Wei(1994), we express all the exchange rates in terms of a numeraire currency,the Swiss franc.13 As in the previous exercise, we have removed data obser-vations with values of log first differences greater than 0.1.

The underlying hypothesis is that every country attempts to stabilize itsexchange rate to a basket of multiple currencies. The coefficients on theright-hand–side exchange rates, bk , are interpreted as the weights in acurrency basket assigned by the country’s authorities. A single currencypeg is a special case, where the coefficient on the target currency forexchange rate pegging should be exactly unity, the coefficients on othercurrencies should all be zero, and the value of standard error of regressionresiduals should be zero. If one country’s currency is not pegged rigidly,but is only stabilized, to another particular country’s currency, the SDR,or the ECU, the coefficient estimated for the anchor currency should bestatistically significant and close to unity. Also, the standard error of residualterms should take a sufficiently small value. If a currency is pegged orstabilized to a certain basket of multiple currencies, several coefficientsshould be statistically significant and these coefficients should approxi-mately add to unity. On the other hand, if a currency is on a purely flexibleexchange rate regime, no coefficient should be statistically significant, andthe estimated standard error of the regression residuals would be rela-tively large.

13 In other papers, Frankel and Wei (1993, 1995) use the SDR as a numeraire currency,but we do not follow this procedure because our study often regards the SDR as a potentialcandidate for a nominal anchor. When we examine the behavior of the Swiss franc itself, weexpress all the exchange rates in terms of the Singapore dollar. The regression results forother Western European currencies are qualitatively very similar whether the numerairecurrency is the Swiss franc or the Singapore dollar.


Estimation results for the period 1990–1996 are summarized in the fourthcolumn of the Appendix table. These results are obtained after extensivetrial and error using many different combinations of the G-5 currencies, theSDR, the ECU, and relevant regional currencies as explanatory variables ineach currency’s regression. For each country, a regression equation withthe highest explanatory power, measured by the adjusted R2 and reasonablecoefficient estimates, is chosen and reported. The table reports currencynames and coefficients that are estimated to be positive and statisticallysignificant at least at the 5% level, the estimated standard error of regressionresiduals (std-res), the number of sample observations used (incl), andthe number of observations deleted (excl).14 Furthermore, the estimatedcoefficients are arranged in order of importance to facilitate identificationof influential currencies. Similar results can also be presented for earlierperiods to capture changing exchange rate policies over time.15 Statisticalsignificance is indicated as follows: coefficients with double asterisks (**)and single asterisks (*) are significant at the 1% and 5% levels, respectively.No asterisk indicates that the coefficient is significant at the 10% level; inthis case only the currency name is listed without the estimated coefficients.

The currencies placed on the right-hand side as explanatory variablesare indicated by symbols identical to the previous case of exchange rate vola-tility.

III. A DESCRIPTIVE SUMMARY OF EXCHANGERATE ARRANGEMENTS

Inspection of the results summarized in the Appendix table reveals thatthe reported exchange rate arrangements are largely consistent with theobserved exchange rate policies, with the exception of a few countries. Thetable provides several findings with respect to the individual countries’exchange rate arrangements. The description here mainly focuses on the1990s but refers to the earlier periods as needs arise.

1. Industrial Countries

The world’s three major currencies, the U.S. dollar, the deutsche mark,and the Japanese yen, exhibit large volatility with respect to one another.This is the essence of the current generalized floating exchange rate system.Currently there is no industrialized country which attempts to stabilize

14 Some data observations are deleted because the left-hand–side variables exceed 0.1in value.

15 A complete set of regression results including those of earlier periods is available uponrequest from the authors or from Kawai and Akiyama (1998).


exchange rates vis-a-vis the U.S. dollar, except for Canada. Canada in factdid so tightly until the 1980s and still continues to use the U.S. dollar as atarget currency. In Australia and New Zealand, target currencies havealternated among the U.S. dollar, SDR, and each other’s currencies.

Industrial countries may be divided into three broad groups: (a) theUnited States and countries that have tended to more or less stabilize theirexchange rates to the U.S. dollar, namely, Canada, Australia, and NewZealand; (b) most Western European countries that tend to stabilize theirrates to the deutsche mark, French franc, and ECU; and (c) Japan, whichdoes not stabilize its rate to the U.S. dollar or any other Western Euro-pean currency.

Looking at the first group, the weight of the U.S. dollar in Canada’sexchange rate movements has always been statistically significant and closeto unity since the beginning of the 1970s. Canada is the only country inthe industrialized world that can be said to belong effectively to the U.S.dollar bloc. The Australian and New Zealand dollars have been influencedby the U.S. dollar, each other’s currency, the SDR, and a few Europeancurrencies such as the UK pound.

The second group, the Western European countries, may be dividedfurther into five subgroups, depending on the degree of linkage with thedeutsche mark. The first subgroup includes Austria, France, the Nether-lands, and Switzerland, which have chosen the deutsche mark as theirprimary target for exchange rate stabilization. The second subgroup in-cludes Belgium, Denmark, and Luxembourg, which have chosen thedeutsche mark or the ECU as their primary target for some time but haverecently shifted increasingly toward the French franc. The third subgroupincludes Finland, Greece, Italy, and Spain, which have chosen the U.S.dollar and UK pound, in addition to the deutsche mark or French franc,as their anchor currencies. The fourth subgroup includes Iceland, Ireland,Norway, and Sweden, which have chosen the ECU as their primary targetfor exchange rate stabilization. Finally, the United Kingdom constitutesthe fifth subgroup in that it has not used any European currency for thepurpose of exchange rate stabilization and, hence, has been quite indepen-dent of European exchange rate arrangements.

Japan’s exchange rate has been moving independent of the U.S. dollarand the major European currencies. With estimated standard error of re-gression residuals of approximately 0.02, a level comparable to that ofthe United States, the Japanese yen’s exchange rate volatility has beensignificantly large and among the largest of the industrialized nations.

2. Developing Countries

(a) Africa. In Africa, there are countries which have maintained fixedexchange rate arrangements vis-a-vis single currencies. These countries


include 14 CFA Franc Area members plus Comoros, which peg their curren-cies to the French franc; Common Monetary Union members (Lesotho,Namibia, and Swaziland), which peg their rates to the South African rand;and persistent U.S. dollar peggers (Djibouti and Liberia). The regressioncoefficients for these countries are close to unity, and the standard errorof regression residuals, a conditional measure of exchange rate volatility,is small and typically less than 0.01.

A few other countries have also managed to maintain relatively stableexchange rates vis-a-vis the SDR (Seychelles), the ECU (Mauritius andTunisia in the 1990s), and the Portuguese escudo (Cape Verde).

A number of other countries have had flexible exchange rate arrange-ments with frequent changes in the list of influential major currencies overtime and with a relatively large standard error of residuals. Their targetcurrencies are often the U.S. dollar or SDR, though the magnitude ofvolatility is large. Western European currencies, such as the French franc,the UK pound sterling, the Spanish peseta, and the Portuguese escudo, arealso often target currencies, though the degree of stabilization is low.

The South African rand, the regional key currency for the CommonMonetary Union, has been affected, though not tightly, by both the U.S.dollar and the UK pound, suggesting that South Africa cannot be entirelydescribed as either a U.S.-dollar or pound-sterling area country. Its standarderror of residual terms has varied over time between 0.01 and 0.03.

(b) Asia. Many Asian economies have consistently exhibited stableexchange rates, with small values of volatility (often less than 0.01), andhave not frequently altered their target or nominal-anchor currencies overtime.16 However, only a small number of economies maintain a relativelyrigid peg; Afghanistan and Micronesia (the U.S. dollar), Bhutan (the Indianrupee), and Kiribati (the Australian dollar) are examples of such econo-mies.17 Many other Asian countries, instead of rigidly pegging their ex-change rates, tend to stabilize their rates in terms of the U.S. dollar (Bangla-desh, Indonesia, Korea, Laos, Taiwan, and Thailand), the SDR (Fiji,Myanmar, and Singapore), or important regional currencies (Brunei Darus-salam in terms of the Singapore dollar). Recently, Bangladesh and HongKong have been stabilizing their rates to the U.S. dollar.

As a result, the regression results for many Asian countries reveal that

16 The recent currency and financial turmoil in East Asia, particularly in Thailand, Indonesia,Malaysia, the Philippines, and Korea, suggests that their exchange rate movements may havedeviated from the historical patterns observed until 1996. As a result, our analysis doesnot cover the recent turmoil period because of a lack of a sufficiently large number ofdata observations.

17 The reported exchange rate arrangement of Afghanistan is independently floating startingwith December 1991, but its currency, Afghanis, is pegged to the U.S. dollar throughoutthe 1990s.


the weight of the U.S. dollar is almost always significant and large andthat the standard error of the residuals is relatively small. Pakistan, thePhilippines, and Vietnam are also countries that attempt to stabilize theirrates to the U.S. dollar. Malaysia attempts to stabilize its rates to currencybaskets, with the U.S. dollar the largest weight. Countries which oncepegged or are currently pegging their exchange rates to non-SDR basketsof currencies give some weight to the U.S. dollar in their respective baskets.These countries include Singapore and Pacific island nations such as Fiji,Papua New Guinea, the Solomon Islands, and Tonga.

There are a few exceptions in which the U.S. dollar has no role: Bhutan(tightly pegged to the Indian rupee throughout the sample period), Kiribati(tightly pegged to the Australian dollar since the 1980s), and Brunei Darus-salam (stabilized to the Singapore dollar). While Myanmar has stabilizedits currency to the SDR, the U.S. dollar’s influence can also be detectedin certain periods.

Regional currencies play important roles in Asia. The Australian, NewZealand, and Singapore dollars are sometimes included in the currencybaskets of the Pacific island nations. The Singapore dollar exerts a certaininfluence over the Malaysian ringgit and, in earlier periods, influenced theThai baht.18 The Indian rupee not only is a currency peg target for Bhutanbut also is emerging as a target for currency stabilization for Nepal. TheIndian rupee itself has been influenced by the U.S. dollar and the UK pound;the U.S. dollar’s importance in the determination of rupee movements hasrisen significantly in the 1990s.

As has been emphasized by Frankel and Wei (1993, 1994, 1995), the roleof the Japanese yen as a nominal anchor has been virtually nonexistent inAsia. There are economies that assign some weight to the Japanese yen,but the number of such economies is limited and the magnitude of thatweight is small. For example, in the 1990s, Fiji has assigned a weight of0.15 to the Japanese yen (while assigning a weight of 0.30 to the U.S.dollar), both Taiwan and Thailand have assigned about 0.11 to the yen(while respectively assigning 0.79 and 0.82 to the U.S. dollar), and Koreahas assigned 0.10 to the yen (while assigning 0.91 to the dollar). It shouldbe noted, however, that despite its small size, the weight of the Japaneseyen is bigger than that of any European currency. Essentially, though theJapanese yen is more influential than any European currency in Asianexchange rate policies, it is still far from capable of rivaling the U.S. dollarin the region.19

18 Though the Appendix table does not report regression results for recent years, the Thaibaht has had significant effects on the Laotian kip in the last several years.

19 See Hamada and Horiuchi (1987), Tavlas and Ozeki (1992), Ito (1993), Garber (1996),and Kawai (1996) for explanations of the limited use of the Japanese yen as an internationalcurrency, even in East Asia.


(c) Europe. In developing Europe, no country has persistently main-tained a rigid exchange-rate peg policy and only a few countries havemaintained stable exchange rates. Estonia has stabilized its exchange rateto the deutsche mark, while Cyprus, the Czech Republic, Latvia, and Maltaappear to be stabilizing their exchange rates to the currency baskets con-sisting of the U.S. dollar and major European currencies including theECU. Apart from these exceptions, the standard error of residuals is largein general: volatility of less than 0.02 is rare while values greater than 0.03are often observed. At such high levels of volatility, it is difficult to identifyany type of exchange rate arrangement other than flexible rate regimes.

Despite large fluctuations in their exchange rates, many countries indeveloping Europe attempt to stabilize their rates in terms of the U.S.dollar, the deutsche mark, the French franc, the UK pound, or some basketof these. The U.S. dollar has been chosen as the primary target for stabiliza-tion by Albania, Bulgaria, Lithuania, Moldova, Poland, Turkey, andUkraine. Major European currencies have provided a loose target for Mace-donia (deutsche mark), Slovak Republic (French franc), and Slovenia(deutsche mark).

(d) Middle East. Without exception all countries in the Middle Eaststabilize their exchange rates to the U.S. dollar and/or the SDR; no othermajor currency plays a nominal anchor role. Since the latter half of the1970s, Bahrain, Egypt, Iraq, Oman, Qatar, Saudi Arabia, Syria, the UnitedArab Emirates (UAE), and Yemen have pegged their exchange rates tothe U.S. dollar, either rigidly or relatively tightly; the regression coefficientson the U.S. dollar have been either exactly unity or very close to unity,and the standard error of residuals has always been less than 0.01. Iran,Kuwait, and Libya, which stabilized their exchange rates in terms of theSDR (or together with the U.S. dollar) in the early 1970s, raised the weightof the U.S. dollar later but subsequently reverted to SDR (together withthe U.S. dollar) targeting; their standard error of residuals has been keptbelow 0.01.

Israel and Lebanon have not maintained stable exchange rates amongcountries in the Middle East, with high standard errors of regression residu-als exceeding 0.02. With relatively large volatility, they have attempted toloosely stabilize their currencies in terms of the U.S. dollar and a currencybasket containing the SDR.

(e) Western Hemisphere. In Latin America, the regression coefficientson the U.S. dollar have almost always been significantly positive and closeto unity, particularly since the second half of the 1970s.20 Sterling Area

20 In the first half of the 1970s, the coefficient on the UK pound was significant and closeto unity for Sterling Area countries; these countries include Eastern Caribbean CurrencyArea members (Antigua and Barbuda, Dominica, Grenada, St. Kitts and Nevis, St. Lucia,and St. Vincent and the Grenadines), Belize, Barbados, Guyana, and Trinidad and Tobago.


countries had shifted their nominal anchor currencies from the UK poundto the U.S. dollar by the second half of the 1970s, and the U.S. dollar hassince been the major nominal anchor currency in all of Latin America.Even for countries with large exchange rate volatility, the U.S. dollar isthe primary target currency. We observe some weights assigned to theJapanese yen for Chile and Guatemala, which possibly reflects explicitexchange rate policies in these countries.

Because of the dominance of the U.S. dollar as nominal anchor currencyin Latin America, the only thing that really matters for these countries isthe degree of exchange rate stabilization to the dollar. These countries canbe classified into three groups. The first group consists of rigid U.S.-dollarpeggers, including Eastern Caribbean Currency Area (ECCA) members,Aruba, the Bahamas, Barbados, Belize, the Netherlands Antilles, and Pan-ama. The second group consists of countries which do not peg, or are unableto peg, to the U.S. dollar because of occasional currency devaluations.Still, they have stabilized their exchange rates vis-a-vis the dollar relativelytightly. This group includes Bolivia, Colombia, Costa Rica, El Salvador,Guyana, and Suriname. The third group consists of all other countries,which historically have been incapable of maintaining stable exchange ratesdue to high inflation and frequent currency devaluations. This group in-cludes Argentina, Brazil, Chile, Jamaica, and Peru. It should be noted,however, that some countries in the last group, notably Argentina, haveadopted rigid stabilization policies vis-a-vis the U.S. dollar in the mostrecent period. Not surprisingly, the regression coefficients on the U.S. dollarare close to unity in most cases even for the last group.

IV. THE RELATIVE SIZES OF MAJOR CURRENCY AREAS

In the preceding sections, we have identified what currency or basket ofcurrencies has been chosen by each country as a nominal anchor, i.e., atarget for exchange rate stabilization. In this section, we use these resultsto investigate several important issues. First, we attempt to measure therelative economic size of countries under fixed and flexible exchange rateregimes and how such relative sizes have changed over time. Second, weexamine how the relative influence of the world’s major currencies haschanged over time since the collapse of the Bretton Woods system. Third,we estimate the possible size of a currency area governed by the newEuropean single currency, the euro, relative to the size of currency areasproduced by the U.S. dollar and the Japanese yen. The objective here isto gain insight into the evolution of the international monetary system byquantitatively gauging the changing patterns of exchange rate arrangements


and the changing sizes of the major currency areas including the prospectiveeuro zone.

1. The Changing Shares of Countries under Fixed and FlexibleExchange Rate Regimes

It is often argued that since the breakdown of the Bretton Woods system,many countries have shifted away from fixed to more flexible exchangerate regimes. This argument rests typically on shifts in regimes observedfrom reported exchange rate arrangements.21 We present our own measuresof relative shares of fixed versus flexible rate arrangements and compareour results with those that would be obtained on the basis of reported classi-fication.

Our definition here is based on the magnitude of the estimated standarderrors of regression residuals, a measure of conditional volatility, derivedfrom regression equations of exchange rate movements. Since there is nodefinite demarcation line in volatility between fixed and flexible exchangerate regimes, we present two cases for both fixed and flexible rate regimes.Countries under fixed rate regimes may be defined as those with (a) volatil-ity less than 0.005 or (b) volatility less than 0.010. Countries under flexiblerate regimes may be defined as those with (c) volatility greater than 0.015or (d) volatility greater than 0.010. We have calculated the economic size,measured in terms of gross domestic product (GDP) (in U.S. dollars) ortotal trade flows (exports plus imports), of all countries falling into thesefour categories for each of the six subperiods between 1970 and 1996. Forthe sake of comparison, we have also calculated the economic size ofcountries under fixed and flexible rate regimes using reported arrangements;fixed rate regimes include a peg to a single currency, SDR, and othercurrency composite, and flexible rate regimes include managed floating andindependently floating. Our sample size is fixed at 82 countries for theentire period.22

21 For example, the World Economic Outlook (WEO) of 1997, an IMF publication, devoteda chapter to present a view that developing countries have generally shifted their exchangerate regimes from fixed to flexible rate regimes. The report compares the share of total outputof developing countries under fixed exchange rate arrangements with that of developingcountries under flexible rate arrangements. The WEO definition of exchange rate regimes isbased on reported classification, as was summarized in the first column of Table II. Morespecifically, countries under fixed rate arrangements include those reported to be on a singlecurrency peg, a peg to the SDR, and a peg to other currency composite, and countriesunder flexible rate arrangements include those reported to be on managed floating andindependently floating.

22 Note that the number of countries under investigation in the WEO study varies for eachyear. To quantitatively assess the global shifts of exchange rate regimes over time, it is moreappropriate to fix the sample size throughout the sample period.


The results are presented in Fig. 1 for the group of industrial countriesand in Fig. 2 for the group of developing countries. In each figure, wepresent measures based on GDP and total trade flows. These measuresare averages over each 5-year period, except the last one, which covers1995–1996, because the estimated standard errors of regression residualsare obtained only for each 5-year period.23 If we measure the economicsize of countries under fixed and flexible exchange rate regimes usingreported arrangements, it is clear that for both industrial and developingcountries the economic share of countries under fixed rate regimes exhibitsa trend decline and that the economic share of countries on flexible rateregimes displays a trend increase.24 On the other hand, if we measure theeconomic sizes of countries under the two regimes using the estimatedmagnitudes of exchange rate volatility, we observe no clear trend of adeclining share of fixed rate regimes or of a rising share of flexible rateregimes. In particular, many developing countries still maintain de factofixed rate regimes when the GDP-based or trade-based economic size isused. Such results are more pronounced if we adopt the less restrictivedefinition of fixed and flexible rate regimes above, i.e., distinguishing thetwo regimes by the volatility measure of 0.010. With this definition, theeconomic share of industrial countries under fixed rate regimes for the1990s is about 25% (GDP based) or 42% (trade based) and their shareunder flexible rate regimes is 75% (GDP based) or 58% (trade based). Theeconomic share of developing countries under fixed rate regimes is 51%(GDP based) or 69% (trade based) and their share under flexible rateregimes is 48% (GDP based) or 31% (trade based).

2. The Changing Relative Sizes of the Major Currency Areas

(a) Definition of Currency Areas. To calculate the economic size ofa currency area, various variables can be used; output, trade flows, andfinancial aggregates are important candidates. In this paper, we use GDPfor output, exports plus imports for trade flows, and official holdings offoreign exchange reserves, money supplies, and stock market capitalizationsfor financial aggregates, all expressed as current U.S. dollar values. Byusing these different economic variables as the basis for measuring the sizeof currency areas, we can explain how these different economic variablescharacterize the differing natures of major currency areas. In addition, weexpect to further our understanding of the changing importance of themajor currencies as nominal anchors for the rest of the world. As major

23 The measures of economic size based on reported arrangements are also averages overeach 5-year period and are obtained from the annual measures which are computed usinginformation on the year-end arrangements.

24 This is consistent with the WEO study.


FIG

.1.

Shar

esof

indu

stri

alco

untr

ies

unde

rfix

edan

dfle

xibl

eex

chan

gera

tere

gim

es,

GD

Pan

dtr

ade

base

d.(a

)Sh

ares

ofin

dust

rial

coun

trie

sun

der

fixed

rate

regi

mes

,G

DP

base

d.(b

)Sh

ares

ofin

dust

rial

coun

trie

sun

der

flexi

ble

rate

regi

mes

,G

DP

base

d.(c

)Sh

ares

ofin

dust

rial

coun

trie

sun

der

fixed

rate

regi

mes

,tra

deba

sed.

(d)

Shar

esof

indu

stri

alco

untr

ies

unde

rfle

xibl

era

tere

gim

es,t

rade

base

d.N

ote.

Fle

xibl

e(r

epor

ted

arra

ngem

ent)

refe

rsto

‘‘oth

er’’

for

the

Janu

ary

1970

–Jun

e19

82pe

riod

and

‘‘ind

epen

dent

lyflo

atin

g’’

and

‘‘man

aged

float

ing’

’fo

rth

epe

riod

afte

rJu

ly19

82.


FIG

.2.S

hare

sof

deve

lopi

ngco

untr

ies

unde

rfix

edan

dfle

xibl

eex

chan

gera

tere

gim

es,

GD

Pan

dtr

ade

base

d.(a

)Sh

ares

ofde

velo

ping

coun

trie

sun

der

fixed

rate

regi

mes

,GD

Pba

sed.

(b)

Shar

esof

deve

lopi

ngco

untr

ies

unde

rfle

xibl

era

tere

gim

es,

GD

Pba

sed.

(c)

Shar

esof

deve

lopi

ngco

untr

ies

unde

rfix

edra

tere

gim

es,

trad

eba

sed.

(d)

Shar

esof

deve

lopi

ngco

untr

ies

unde

rfle

xibl

era

tere

gim

es,

trad

eba

sed.

Not

e.F

lexi

ble

(rep

orte

dar

rang

emen

t)re

fers

to‘‘o

ther

’’fo

rth

eJa

nuar

y19

70–J

une

1982

peri

odan

d‘‘i

ndep

ende

ntly

float

ing’

’and

‘‘man

aged

float

ing’

’fo

rth

epe

riod

afte

rJu

ly19

82.


currencies, we again consider those of the G-5 countries (i.e., the UnitedStates, Germany, France, the United Kingdom, and Japan) in addition tothe SDR and the ECU.

Each of the G-5 currencies is assumed to form a currency area of itsown. If any country rigidly pegs its exchange rate to a particular currency,its entire economy, whether measured by output, trade flows, or financialaggregates, is classified as belonging to the currency area formed by thisparticular currency. If a country does not peg its exchange rate to a singlecurrency but instead stabilizes its exchange rate by assigning several differ-ent weights to a basket of multiple currencies, its economy is dividedaccording to these weights and distributed to the corresponding currencyareas. The coefficients which were estimated in the previous section to bestatistically significant, at least at the 5% level, are interpreted as the weightsassigned by the authorities to the corresponding currencies. If a countrydoes not stabilize its exchange rate against any single currency or currencybasket, its economy is considered not to belong to any currency area; itadopts flexible exchange rates vis-a-vis the major currencies.

In this calculation, we undertake the following four procedures. First, toevaluate the changing importance of the G-5 currencies, the SDR, and theECU as nominal anchors, we have decided to fix the sample size over timeby selecting only those countries for which data are available throughoutthe entire period under consideration, 1970–1996. It turns out that datafor GDP, exports, imports, official holdings of foreign exchange reserves(total reserves minus gold), and money supply (money plus quasi-money)are available for 82 countries over the entire sample period. Data for stockmarket capitalizations are available only for the 1980–1996 period. A fixedsample size is chosen in order to determine how the choice of economicvariable affects our conclusion.25

Second, to calculate the economic size of currency areas formed by theG-5 currencies, the SDR, and the ECU, we take two intermediate steps.We first calculate the size of the currency area formed by each of the

25 We use annual data for 1970 through 1996. Most data series are taken from the IFSdatabase and, if necessary, are supplemented by national sources. Data for stock marketcapitalizations are taken from the International Finance Corporation’s Emerging Stock MarketFactbook, which provides comprehensive data only for the period 1980–1996. Data for GDPand trade flows are converted into U.S. dollars at the annual average exchange rate and datafor money supply at the end-of-the-year exchange rate. We have selected only those countrieswhere data series for GDP, exports, imports, official foreign exchange reserves, and moneysupply are available from 1970 through 1994. When data for recent years 1995 and 1996 arenot available, we have constructed missing observations by extrapolating the past trend inorder to keep important countries in our sample. Countries in the former Soviet bloc areunderrepresented in our sample due to the lack of data in earlier periods. Many Africancountries are also eliminated from the sample. In terms of economic size, our sample of 82countries covers a substantial part of economic activity around the globe.


G-5 currencies, the SDR, the ECU, and the currencies of minor, regionalcountries (Australia, India, New Zealand, Portugal, Singapore, South Af-rica, Spain, and Thailand). We next distribute the currency areas formedby minor, regional currencies to the larger currency areas formed by theG-5 currencies, the SDR, and the ECU, using the estimated regressioncoefficients for the minor, regional countries.26

Third, the weights are obtained from the estimated coefficients of aregression equation, which are positive and statistically significant at the5% level or above. If the sum of the estimated coefficients is equal to orless than one, their values are used as weights. If the sum exceeds unity,all the coefficients are proportionally re-scaled to make the sum equalto one.

Finally, the economic size of a currency area is calculated for each 5-year period using the estimated coefficients for the corresponding 5-yearestimation period. This is how averages over each of the 5-year periodsare obtained.

(b) Changing economic sizes of the major currency areas. Table IIsummarizes the changing economic sizes of the major currency areas ex-pressed as percentages of the world’s total economic size.27 Since the sizesof the deutsche mark (DM) and French franc (FF) areas tend to fluctuateinversely over time, we also calculate the sum of these two currency areas(DM plus FF) as well as the combined currency area formed by the threemajor European countries (the sum of the DM, FF, and UK pound areas).

Changes in the relative economic sizes of the G-5 currency areas displaydifferent patterns depending on which variable is used to calculate theirsizes. When the size of a currency area is measured in terms of GDP (thefirst section of Table II), we observe that the share of the U.S. dollar areawas large at 53.0% of the world total in the 1970–1975 period, but hasdiminished over time by 6.0 percentage points since then to 46.9% in the1990–1996 period. The share of the combined European currency area hasrisen slightly over time and stands at 24.1% (for DM plus FF) and 31.6%(for DM 1 FF 1 UKP) in the 1990–1996 period. The economic share of

26 The regression equations for Australia and New Zealand, respectively, include the NewZealand dollar and the Australian dollar as explanatory variables on the right-hand side:

DeAD 5 aA 1 bA1 DeUSD 1 bA

2 DeDM 1 bA3 DeJY 1 bA

4 DeFF 1 bA5 DeUKP 1 bA

6 DeSDR 1 bA7 DeNZD 1 uA,

DeNZD 5 aN 1 bN1 DeUSD 1 bN

2 DeDM 1 bN3 DeJY 1 bN

4 DeFF 1 bN5 DeUKP 1 bN

6 DeSDR 1 bN7 DeAD 1 uN.

To assign the economies of Australia and New Zealand to the currency areas formed by theG-5 currencies and the SDR (the ECU does not appear on the right-hand side of eitherequation), the two estimated equations above are solved for DeAD and DeNZD and the resultingcoefficients of the G-5 currencies and the SDR are used as these weights.

27 Detailed regional breakdowns of the major currency areas for the period 1970–1989 arealso available in Kawai and Akiyama (1998).

EXCHANGE RATE ARRANGEMENTS 357T

AB

LE

IIT

heE

stim

ated

Per

cent

age

Shar

esof

Cur

renc

yA

reas

for

the

G-5

Cur

renc

ies,

the

SDR

,an

dth

eE

CU

,19

90–1

996

U.S

.D

euts

che

Fre

nch

UK

dolla

rJa

pane

sem

ark

fran

cpo

und

SDR

EC

UD

M1

FF

DM

1F

F1

UK

area

yen

area

area

area

area

area

area

Oth

erar

eaar

eaT

otal

(1)

Mea

sure

dG

ross

Dom

esti

cP

rodu

ct(G

DP

)in

Cur

rent

U.S

.Dol

lars

1970

–74

Tot

al53

.011

.011

.48.

27.

63.

92.

52.

519

.727

.210

0.0

1975

–79

Tot

al49

.412

.617

.18.

57.

32.

10.

52.

625

.532

.910

0.0

1980

–84

Tot

al51

.412

.312

.29.

97.

53.

40.

13.

122

.129

.610

0.0

1985

–89

Tot

al50

.216

.815

.77.

96.

11.

40.

01.

923

.629

.610

0.0

1990

–96

Tot

al46

.917

.512

.411

.87.

50.

71.

61.

824

.131

.610

0.0

1990

–96

Reg

iona

lbr

eakd

own

Indu

stri

alco

untr

ies

32.1

17.1

11.9

11.3

7.3

0.4

1.5

0.9

23.3

30.6

82.6

EU

-fift

een

1.0

0.0

11.0

11.3

7.0

0.0

0.9

0.7

22.3

29.4

31.9

Ger

man

y0.

00.

08.

40.

00.

00.

00.

00.

08.

48.

48.

4F

ranc

e0.

00.

00.

05.

70.

00.

00.

00.

05.

75.

75.

7U

nite

dK

ingd

om0.

00.

00.

00.

04.

50.

00.

00.

00.

04.

54.

5U

nite

dSt

ates

27.9

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

27.9

Japa

n0.

017

.10.

00.

00.

00.

00.

00.

00.

00.

017

.1O

ther

3.2

0.0

1.0

0.0

0.3

0.4

0.6

0.3

1.0

1.2

5.7

Dev

elop

ing

coun

trie

s14

.80.

30.

40.

40.

10.

40.

10.

80.

81.

017

.4A

fric

a0.

60.

00.

00.

20.

10.

00.

10.

10.

30.

41.

2A

sia

7.2

0.3

0.0

0.2

0.0

0.3

0.0

0.2

0.2

0.2

8.2

Eur

ope

0.4

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.0

0.0

0.7

Mid

dle

Eas

t1.

00.

00.

00.

00.

00.

00.

00.

10.

00.

01.

1W

este

rnH

emis

pher

e5.

70.

00.

30.

00.

00.

10.

00.

00.

30.

46.

2

(2)

Mea

sure

dby

Tot

alT

rade

Flo

ws

(Exp

orts

plus

Impo

rts)

inC

urre

ntU

.S.D

olla

rs19

70–7

4T

otal

33.8

10.0

20.5

11.0

10.2

6.1

4.8

3.6

31.5

41.7

100.

019

75–7

9T

otal

36.8

9.3

28.6

9.8

9.4

1.6

0.8

3.6

38.4

47.9

100.

019

80–8

4T

otal

38.9

9.9

21.8

12.9

9.2

2.7

0.2

4.3

34.8

44.0

100.

019

85–8

9T

otal

39.6

10.5

28.1

9.5

7.9

1.4

0.0

3.0

37.7

45.5

100.

019

90–9

6T

otal

40.5

8.8

18.9

14.8

9.1

2.4

2.8

2.7

33.7

42.8

100.

0

(con

tinue

d)


AB

LE

II—

Con

tinue

d

U.S

.D

euts

che

Fre

nch

UK

dolla

rJa

pane

sem

ark

fran

cpo

und

SDR

EC

UD

M1

FF

DM

1F

F1

UK

area

yen

area

area

area

area

area

area

Oth

erar

eaar

eaT

otal

1990

–96

Reg

iona

lbr

eakd

own

Indu

stri

alco

untr

ies

20.2

8.2

18.7

14.0

8.9

0.4

2.7

1.7

32.7

41.6

74.7

EU

-fift

een

1.2

0.0

17.2

14.0

8.6

0.0

1.8

1.2

31.1

39.8

44.0

Ger

man

y0.

00.

010

.90.

00.

00.

00.

00.

010

.910

.910

.9F

ranc

e0.

00.

00.

06.

30.

00.

00.

00.

06.

36.

36.

3U

nite

dK

ingd

om0.

00.

00.

00.

05.

80.

00.

00.

00.

05.

85.

8U

nite

dSt

ates

14.5

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

14.5

Japa

n0.

08.

20.

00.

00.

00.

00.

00.

00.

00.

08.

2O

ther

4.5

0.0

1.5

0.0

0.3

0.4

0.9

0.5

1.5

1.8

8.0

Dev

elop

ing

coun

trie

s20

.30.

60.

20.

80.

22.

00.

21.

01.

01.

225

.3A

fric

a1.

00.

00.

10.

30.

20.

00.

10.

20.

40.

52.

0A

sia

13.7

0.6

0.1

0.4

0.0

1.9

0.0

0.2

0.5

0.5

16.9

Eur

ope

0.3

0.0

0.0

0.0

0.0

0.0

0.0

0.3

0.0

0.0

0.6

Mid

dle

Eas

t1.

60.

00.

00.

00.

00.

00.

00.

20.

00.

01.

9W

este

rnH

emis

pher

e3.

70.

00.

10.

00.

00.

10.

00.

00.

10.

13.

9

(3)

Mea

sure

dby

For

eign

Exc

hang

eR

eser

ves

inC

urre

ntU

.S.D

olla

rs19

70–7

4T

otal

26.4

13.2

24.7

7.6

7.9

11.5

4.0

4.7

32.3

40.2

100.

019

75–7

9T

otal

35.5

11.5

30.2

5.7

8.2

3.3

1.2

4.3

35.9

44.2

100.

019

80–8

4T

otal

39.1

9.1

25.8

13.0

7.6

1.2

0.1

4.0

38.8

46.5

100.

019

85–8

9T

otal

36.5

14.5

25.5

10.9

7.5

1.8

0.0

3.3

36.4

43.9

100.

019

90–9

6T

otal

37.5

13.0

16.0

13.7

8.0

4.6

4.1

3.1

29.7

37.7

100.

019

90–9

6R

egio

nal

brea

kdow

nIn

dust

rial

coun

trie

s10

.411

.515

.411

.67.

90.

53.

92.

127

.034

.963

.3E

U-fi

ftee

n1.

20.

012

.411

.67.

60.

02.

11.

624

.131

.736

.5G

erm

any

0.0

0.0

7.9

0.0

0.0

0.0

0.0

0.0

7.9

7.9

7.9

Fra

nce

0.0

0.0

0.0

2.9

0.0

0.0

0.0

0.0

2.9

2.9

2.9

Uni

ted

Kin

gdom

0.0

0.0

0.0

0.0

4.0

0.0

0.0

0.0

0.0

4.0

4.0

Uni

ted

Stat

es6.

80.

00.

00.

00.

00.

00.

00.

00.

00.

06.

8Ja

pan

0.0

11.5

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

11.5

Oth

er2.

40.

03.

00.

00.

30.

51.

80.

53.

03.

38.

5D

evel

opin

gco

untr

ies

27.1

1.5

0.6

2.1

0.1

4.1

0.2

1.0

2.7

2.8

36.7

Afr

ica

0.4

0.0

0.1

0.3

0.0

0.0

0.1

0.1

0.5

0.5

1.2

Asi

a14

.81.

30.

11.

70.

13.

80.

00.

11.

81.

921

.9E

urop

e0.

50.

00.

00.

00.

00.

00.

10.

40.

00.

00.

9M

iddl

eE

ast

2.7

0.0

0.0

0.0

0.0

0.0

0.0

0.4

0.0

0.0

3.2

Wes

tern

Hem

isph

ere

8.7

0.1

0.4

0.0

0.0

0.3

0.0

0.0

0.4

0.4

9.5


(4)

Mea

sure

dby

Mon

eySu

pply

(Mon

eypl

usQ

uasi

-Mon

ey)

inC

urre

ntU

.S.D

olla

rs19

70–7

4T

otal

53.9

15.3

10.3

8.0

5.0

3.1

2.6

2.0

18.2

23.2

100.

019

75–7

9T

otal

44.8

17.9

16.3

9.4

5.3

2.9

0.5

2.8

25.8

31.0

100.

019

80–8

4T

otal

48.4

19.3

12.8

11.1

5.2

0.9

0.1

2.3

23.9

29.1

100.

019

85–8

9T

otal

41.7

26.0

16.0

8.1

5.9

0.9

0.0

1.4

24.1

30.0

100.

019

90–9

6T

otal

36.7

27.7

12.4

11.1

8.9

0.7

1.1

1.4

23.5

32.4

100.

019

90–9

6R

egio

nal

brea

kdow

nIn

dust

rial

coun

trie

s27

.827

.312

.310

.58.

80.

31.

11.

022

.831

.689

.1E

U-fi

ftee

n0.

80.

010

.610

.58.

60.

00.

60.

621

.229

.731

.7G

erm

any

0.0

0.0

7.6

0.0

0.0

0.0

0.0

0.0

7.6

7.6

7.6

Fra

nce

0.0

0.0

0.0

5.3

0.0

0.0

0.0

0.0

5.3

5.3

5.3

Uni

ted

Kin

gdom

0.0

0.0

0.0

0.0

6.2

0.0

0.0

0.0

0.0

6.2

6.2

Uni

ted

Stat

es24

.40.

00.

00.

00.

00.

00.

00.

00.

00.

024

.4Ja

pan

0.0

27.3

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

27.3

Oth

er2.

60.

01.

70.

00.

20.

30.

50.

41.

71.

95.

6D

evel

opin

gco

untr

ies

8.9

0.4

0.1

0.6

0.1

0.4

0.1

0.4

0.7

0.8

10.9

Afr

ica

0.4

0.0

0.0

0.1

0.1

0.0

0.0

0.1

0.2

0.2

0.7

Asi

a5.

70.

40.

00.

40.

00.

30.

00.

10.

50.

56.

9E

urop

e0.

10.

00.

00.

00.

00.

00.

00.

10.

00.

00.

3M

iddl

eE

ast

0.9

0.0

0.0

0.0

0.0

0.0

0.0

0.2

0.0

0.0

1.1

Wes

tern

Hem

isph

ere

1.8

0.0

0.1

0.0

0.0

0.0

0.0

0.0

0.1

0.1

2.0

(con

tinue

d)


TA

BL

EII

—C

ontin

ued

U.S

.D

euts

che

Fre

nch

UK

dolla

rJa

pane

sem

ark

fran

cpo

und

SDR

EC

UD

M1

FF

DM

1F

F1

UK

area

yen

area

area

area

area

area

area

Oth

erar

eaar

eaT

otal

(5)

Mea

sure

dby

Stoc

kM

arke

tC

apit

aliz

atio

nsin

Cur

rent

U.S

.Dol

lars

1970

–74

Tot

alN

AN

AN

AN

AN

AN

AN

AN

AN

AN

AN

A19

75–7

9T

otal

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

1980

–84

Tot

al63

.517

.75.

02.

28.

80.

60.

02.

07.

316

.110

0.0

1985

–89

Tot

al44

.333

.38.

73.

28.

11.

20.

01.

411

.819

.910

0.0

1990

–96

Tot

al50

.423

.77.

05.

79.

91.

11.

01.

112

.722

.610

0.0

1990

–96

Reg

iona

lbr

eakd

own

Indu

stri

alco

untr

ies

41.0

23.4

6.9

5.4

9.6

0.3

1.0

0.7

12.3

21.9

88.4

EU

-fift

een

0.4

0.0

5.2

5.4

9.3

0.0

0.8

0.3

10.6

19.9

21.4

Ger

man

y0.

00.

03.

40.

00.

00.

00.

00.

03.

43.

43.

4F

ranc

e0.

00.

00.

03.

10.

00.

00.

00.

03.

13.

13.

1U

nite

dK

ingd

om0.

00.

00.

00.

08.

50.

00.

00.

00.

08.

58.

5U

nite

dSt

ates

37.5

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

37.5

Japa

n0.

023

.40.

00.

00.

00.

00.

00.

00.

00.

023

.4O

ther

3.1

0.0

1.7

0.0

0.3

0.3

0.2

0.4

1.7

2.0

6.0

Dev

elop

ing

coun

trie

s9.

40.

30.

10.

30.

30.

80.

00.

40.

40.

711

.6A

fric

a0.

90.

00.

00.

00.

30.

00.

00.

20.

00.

31.

4A

sia

6.1

0.3

0.0

0.2

0.0

0.8

0.0

0.1

0.3

0.3

7.5

Eur

ope

0.1

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.0

0.0

0.2

Mid

dle

Eas

t0.

20.

00.

00.

00.

00.

00.

00.

10.

00.

00.

3W

este

rnH

emis

pher

e2.

10.

00.

10.

00.

00.

00.

00.

00.

10.

12.

2


the Japanese yen area has risen by 6.5 percentage points over time andreached 17.5% in the most recent period. To summarize, the relative eco-nomic share of the U.S. dollar area has declined noticeably since the break-down of the Bretton Woods system, while the shares of the Japanese yenarea and the combined European currency area have risen, supplementinga relative decline in the U.S. dollar area.

The fact that the relative GDP share of the United States in our sampleof 82 countries is only 27.9% in 1990–1996 while the share of the U.S. dollararea is 46.9% indicates that the dollar area extends far outside of the UnitedStates. Many developing countries belong to the U.S. dollar area, as dosome other industrial countries such as Canada and, to a lesser extent,Australia and New Zealand. In the developing world, Asia is particularlyimportant as a U.S. dollar area; the Asian U.S. dollar area has grownsteadily from 2.3% in the 1970–1974 period (not shown in Table II) to 7.2%in the 1990–1996 period. The Western Hemisphere also contributes to thelarge size of the U.S. dollar area, standing at 5.7% in 1990–1996. Thedeutsche mark area and the French franc area, 12.4% and 11.8%, respec-tively, in the 1990s, are also greater than the relative GDP shares of thesetwo countries alone (8.4% and 5.7%, respectively). This is due to the factthat currencies of many high-income countries in Western Europe are influ-enced by the DM and FF. In contrast, the size of the Japanese yen area,17.5% in the 1990s, is not much different from the relative GDP share ofJapan itself, which is 17.1%. Essentially, the rise in the relative share of theyen area is due to the rise in the share of the Japanese economy in the world.

When the size of a currency area is measured by total trade flows (exportsplus imports in the second section of Table II), a totally different pictureemerges. The share of the U.S. dollar area has not declined over time buthas instead risen by 6.7 percentage points since the early 1970s. Its sharestands at 40.5% in the 1990–1996 period, which is lower than the GDP-based share of the U.S. dollar area. The relative growth of the trade-basedU.S. dollar area is mostly due to the rapid expansion of trade flows ofAsian countries whose exchange rates are stabilized to the dollar. Thetrade-based relative share of the combined European currency area hasrisen slightly over the same period and stands at 33.7% (for DM 1 FF)and 42.8% (for DM 1 FF 1 UKP) in the 1990s, the highest of all measuresfor the combined European currency area figures.28 On the other hand,the trade-based share of the Japanese yen area has declined since the early1970s by 1.2 percentage points and stands at 8.8% in the 1990s, the lowestof all calculated measures for the yen area. The trade-based yen area hasbeen quite small, essentially because of Japan’s stagnant imports.

The rest of Table II also reports relative shares of major currency areas

28 The trade-based economic size of the combined European currency area is smaller,however, if intra-regional trade is netted out.


based on financial aggregates, namely, official foreign exchange reserves,money supplies, and stock market capitalizations. Most impressive is thefact that, based on the money supply measure, the share of the U.S. dollararea has declined substantially from 53.9% in the early 1970s to a meager36.7% in the 1990s; this is the smallest of all measures for the U.S. dollararea. The money-supply–based share of the Japanese yen area, on theother hand, has increased substantially from 15.3% in the early 1970s to27.7% in the 1990s; this is the largest calculated measure for the yen area.Based on the stock market capitalization measure, the share of the U.S.dollar area has declined over time but still maintains a very large share of50.4% in the 1990s, which is the largest for the U.S. dollar area. Thecombined European currency area based on stock market capitalizationsis only 12.7% (DM 1 FF) or 22.6% (DM 1 FF 1 UKP), the smallest ofthese measures for the combined European currency area either way.

To summarize, despite the declining proportion of the U.S. economy inthe world as a whole, the U.S. dollar area has kept its substantial size. Therelative economic share of the U.S. dollar area has shrunk over time, exceptwhen measured by total trade flows, but it is still by far the largest currencyarea in the world. The size of the U.S. dollar area is much larger than thesize of the U.S. economy itself owing to the large number of developingeconomies, particularly in Asia, Latin America, and the Middle East, whichare strongly tied to the U.S. dollar. To a much lesser extent, the deutschemark area and the French franc area are similarly larger than the respectiveeconomies on which they are based. This reflects the Western Europeaneconomies’ exchange rate stabilization policies that target these two curren-cies. Furthermore, the fact that the combined currency area for the deutschemark, the French franc, and the UK pound exceeds the U.S. dollar areain trade-based size suggests that the potential role of the prospective euro,to be introduced in January 1999, is large. In contrast, there is virtually noyen area outside Japan.

3. The Prospects of Currency Areas for the Euro, the U.S. Dollar, andthe Japanese Yen

It is of considerable interest to evaluate the impact of the creation ofthe European EMU and the introduction of a single currency, the euro,on the international monetary system. The questions are whether the newlyintroduced euro will be strong enough to seriously challenge the dominanceof the U.S. dollar and to convert the U.S.-dollar-dominated internationalmonetary system into a regime centered on both the U.S. dollar and theeuro, and what role the Japanese yen will play.29

29 See Alogoskoufis and Portes (1997) and Bergsten (1997), who argue that the introductionof the euro will challenge the U.S. dollar dominance and convert the international monetarysystem into a bipolar system centered on both the U.S. dollar and the euro.


For this purpose, we extend the previous analysis to measure the size ofa currency area formed by the prospective euro by using the regressionresults for the 1990s. More specifically, we calculate the economic sizes ofthe prospective euro area, the U.S. dollar area, and the Japanese yen area,employing the same method as the one used previously. However, a widersample of 99 countries is used for such calculation, because we limit ourfocus to only the 1990s, for which data for a larger number of countriesare available.

We consider two possible scenarios with regard to the size of the prospec-tive euro area, depending on which countries form the new EMU. Twoscenarios include the likely case of the EU-eleven (Austria, Belgium, Fin-land, France, Germany, Ireland, Italy, Luxembourg, the Netherlands, Portu-gal, and Spain) forming the EMU, and the case of the EU-fifteen (the EU-eleven plus Denmark, Greece, Sweden, and the United Kingdom) formingthe EMU. The latter scenario defines the maximum possible size of theEMU in the conceivable future. If EMU membership is confined to the 11countries, it is expected that the size of the euro area will be small whilethe size of the U.S. dollar area will remain large. On the other hand, ifEMU membership includes all European Union countries, the size of theeuro area will be correspondingly larger while the size of the U.S. dollararea will become smaller. The size of the Japanese yen area will probablynot be affected much by the scale of EMU membership.

Table III summarizes the results of these calculations. The table reportsthe relative economic shares for each of the three major currency areas,based on output (nominal GDP), total trade flows (the sum of exportsand imports), and financial aggregates (official foreign exchange holdings,money supplies, and stock market capitalizations). The table shows thatthis choice of variable, whether GDP, trade flows, or financial aggregates,influences the prospective size of the euro and U.S. dollar areas. Takingthe case of the EMU-fifteen, the GDP and financial aggregate measuresindicate that the U.S. dollar area will remain larger than the euro area.For example, using GDP, 46.4% of the world economy is covered by theU.S. dollar area, 34.7% by the euro area, and 17.5% by the Japanese yenarea. The U.S. dollar area is large because many developing countries,particularly those in Asia and Latin America, regard the dollar as the mostimportant global nominal anchor. The Japanese yen area’s share (17.5%)is only slightly larger than the weight of the Japanese economy in the world(17.0%).30 The yen area outside Japan is small and accounts for only 0.5%of the world’s GDP. This underlines the fact that the yen is not yet a full-fledged, global nominal anchor currency.

Not surprisingly, the size of the U.S. dollar area based on stock market

30 These relative share numbers correspond to the figures estimated by other authors suchas Bergsten (1997) and Masson and Turtleboom (1997).


TA

BL

EII

IT

heE

stim

ated

Size

ofth

eC

urre

ncy

Are

asfo

rth

eE

uro,

the

U.S

.D

olla

r,an

dth

eJa

pane

seY

enP

erce

ntag

eA

vera

ges

for

1990

–199

6

Cas

eof

EM

U-1

1C

ase

ofE

MU

-15

U.S

.U

KU

.S.

UK

Eur

odo

llar

Japa

nese

poun

dE

uro

dolla

rJa

pane

sepo

und

Reg

iona

lar

eaar

eaye

nar

eaar

eaO

ther

area

area

yen

area

area

Oth

erto

tal

(1)

Mea

sure

dby

Gro

ssD

omes

tic

Pro

duct

(GD

P)

inC

urre

ntU

.S.D

olla

rsIn

dust

rial

coun

trie

s28

.131

.017

.15.

00.

433

.430

.817

.10.

00.

381

.5E

U-fi

ftee

n26

.60.

20.

04.

60.

131

.50.

00.

00.

00.

031

.5C

ore-

six

coun

trie

s17

.20.

00.

00.

00.

017

.20.

00.

00.

00.

017

.2F

ive

othe

rE

MU

mem

bers

7.9

0.0

0.0

0.0

0.0

7.9

0.0

0.0

0.0

0.0

7.9

Den

mar

k,G

reec

e,Sw

eden

,UK

1.4

0.2

0.0

4.6

0.1

6.3

0.0

0.0

0.0

0.0

6.3

Uni

ted

Stat

es0.

027

.50.

00.

00.

00.

027

.50.

00.

00.

027

.5Ja

pan

0.0

0.0

17.0

0.0

0.0

0.0

0.0

17.0

0.0

0.0

17.0

Oth

er1.

53.

30.

10.

40.

31.

93.

30.

10.

00.

35.

6D

evel

opin

gco

untr

ies

1.1

15.7

0.4

0.2

1.1

1.3

15.7

0.4

0.0

1.1

18.5

Afr

ica

0.3

0.7

0.0

0.1

0.2

0.5

0.7

0.0

0.0

0.2

1.4

Asi

a0.

37.

50.

30.

00.

20.

37.

50.

30.

00.

28.

3E

urop

e0.

10.

80.

00.

00.

60.

10.

80.

00.

00.

61.

4M

iddl

eE

ast

0.0

1.0

0.0

0.0

0.1

0.0

1.0

0.0

0.0

0.1

1.2

Wes

tern

Hem

isph

ere

0.4

5.7

0.1

0.0

0.0

0.4

5.7

0.1

0.0

0.0

6.2

Tot

al29

.246

.717

.55.

21.

534

.746

.417

.50.

01.

410

0.0

(2)

Mea

sure

dby

Tot

alT

rade

Flo

ws

(Exp

orts

plus

Impo

rts)

inC

urre

ntU

.S.D

olla

rsIn

dust

rial

coun

trie

s38

.819

.18.

16.

40.

645

.818

.88.

10.

073

.1E

U-fi

ftee

n36

.50.

40.

05.

90.

243

.00.

00.

00.

00.

543

.0


Cor

e-si

xco

untr

ies

25.4

0.0

0.0

0.0

0.0

25.4

0.0

0.0

0.0

0.0

25.4

Fiv

eot

her

EM

Um

embe

rs9.

10.

00.

00.

00.

09.

10.

00.

00.

00.

09.

1D

enm

ark,

Gre

ece,

Swed

en,U

K2.

10.

40.

05.

90.

28.

50.

00.

00.

00.

08.

5U

nite

dSt

ates

0.0

14.2

0.0

0.0

0.0

0.0

14.2

0.0

0.0

0.0

14.2

Japa

n0.

00.

08.

00.

00.

00.

00.

08.

00.

00.

08.

0O

ther

2.3

4.6

0.1

0.5

0.5

2.8

4.6

0.1

0.0

0.5

7.9

Dev

elop

ing

coun

trie

s1.

922

.11.

10.

41.

42.

422

.11.

10.

01.

426

.9A

fric

a0.

51.

30.

00.

20.

40.

71.

30.

00.

00.

42.

4A

sia

1.1

14.6

1.0

0.2

0.2

1.3

14.6

1.0

0.0

0.2

17.1

Eur

ope

0.2

0.9

0.0

0.0

0.6

0.2

0.9

0.0

0.0

0.6

1.6

Mid

dle

Eas

t0.

01.

70.

00.

00.

20.

01.

70.

00.

00.

21.

9W

este

rnH

emis

pher

e0.

23.

70.

10.

00.

00.

23.

70.

10.

00.

03.

9T

otal

40.8

41.3

9.2

6.8

2.0

48.1

40.9

9.2

0.0

1.8

100.

0

(3)

Mea

sure

dby

Offi

cial

Hol

ding

sof

For

eign

Exc

hang

eR

eser

ves

inC

urre

ntU

.S.D

olla

rsIn

dust

rial

coun

trie

s31

.58.

610

.84.

50.

636

.68.

210

.80.

00.

456

.0E

U-fi

ftee

n27

.40.

50.

03.

90.

231

.90.

00.

00.

00.

031

.9C

ore-

six

coun

trie

s14

.30.

00.

00.

00.

014

.30.

00.

00.

00.

014

.3F

ive

othe

rE

MU

mem

bers

10.6

0.0

0.0

0.0

0.0

10.6

0.0

0.0

0.0

0.0

10.6

Den

mar

k,G

reec

e,Sw

eden

,UK

2.6

0.5

0.0

3.9

0.2

7.1

0.0

0.0

0.0

0.0

7.1

Uni

ted

Stat

es0.

05.

90.

00.

00.

00.

05.

90.

00.

00.

05.

9Ja

pan

0.0

0.0

10.7

0.0

0.0

0.0

0.0

10.7

0.0

0.0

10.7

Oth

er4.

12.

30.

10.

60.

44.

72.

30.

10.

00.

47.

5D

evel

opin

gco

untr

ies

3.9

35.6

2.1

0.6

1.7

4.6

35.6

2.1

0.0

1.7

44.0

Afr

ica

0.5

0.8

0.0

0.1

0.2

0.7

0.8

0.0

0.0

0.2

1.6

Asi

a2.

723

.01.

90.

40.

33.

123

.01.

90.

00.

328

.2E

urop

e0.

31.

30.

00.

00.

90.

31.

30.

00.

00.

92.

5M

iddl

eE

ast

0.0

2.5

0.0

0.0

0.4

0.0

2.5

0.0

0.0

0.4

2.9

Wes

tern

Hem

isph

ere

0.4

8.1

0.2

0.0

0.0

0.5

8.1

0.2

0.0

0.0

8.7

Tot

al35

.444

.312

.95.

12.

341

.243

.812

.90.

02.

110

0.0

(con

tinue

d)


AB

LE

III—

Con

tinue

d

Cas

eof

EM

U-1

1C

ase

ofE

MU

-15

U.S

.U

KU

.S.

UK

Eur

odo

llar

Japa

nese

poun

dE

uro

dolla

rJa

pane

sepo

und

Reg

iona

lar

eaar

eaye

nar

eaar

eaO

ther

area

area

yen

area

area

Oth

erto

tal

(4)

Mea

sure

dby

Mon

eySu

pply

(Mon

eypl

usQ

uasi

-Mon

ey)

inC

urre

ntU

.S.D

olla

rsIn

dust

rial

coun

trie

s26

.326

.126

.46.

50.

433

.026

.026

.40.

00.

385

.6E

U-fi

ftee

n24

.20.

20.

06.

10.

130

.60.

00.

00.

00.

030

.6C

ore-

six

coun

trie

s16

.10.

00.

00.

00.

016

.10.

00.

00.

00.

016

.1F

ive

othe

rE

MU

mem

bers

7.1

0.0

0.0

0.0

0.0

7.1

0.0

0.0

0.0

0.0

7.1

Den

mar

k,G

reec

e,Sw

eden

,UK

1.0

0.2

0.0

6.1

0.1

7.4

0.0

0.0

0.0

0.0

7.4

Uni

ted

Stat

es0.

023

.30.

00.

00.

00.

023

.30.

00.

00.

023

.3Ja

pan

0.0

0.0

26.3

0.0

0.0

0.0

0.0

26.3

0.0

0.0

26.3

Oth

er2.

12.

60.

10.

30.

32.

42.

60.

10.

00.

35.

4D

evel

opin

gco

untr

ies

0.9

12.2

0.5

0.2

0.7

1.1

12.2

0.5

0.0

0.7

14.4

Afr

ica

0.2

0.4

0.0

0.1

0.1

0.3

0.4

0.0

0.0

0.1

0.8

Asi

a0.

68.

80.

40.

00.

20.

68.

80.

40.

00.

210

.0E

urop

e0.

10.

30.

00.

00.

20.

10.

30.

00.

00.

20.

6M

iddl

eE

ast

0.0

0.9

0.0

0.0

0.1

0.0

0.9

0.0

0.0

0.1

1.0

Wes

tern

Hem

isph

ere

0.1

1.8

0.0

0.0

0.0

0.1

1.8

0.0

0.0

0.0

1.9

Tot

al27

.238

.326

.86.

61.

134

.038

.126

.80.

01.

010

0.0

(5)

Mea

sure

dby

Stoc

kM

arke

tC

apit

aliz

atio

nsin

Cur

rent

U.S

.Dol

lars

Indu

stri

alco

untr

ies

14.7

41.3

22.4

9.0

0.4

23.9

41.1

22.4

0.0

0.4

87.9

EU

-fift

een

12.7

0.2

0.0

8.6

0.1

21.5

0.0

0.0

0.0

0.0

21.5

Cor

e-si

xco

untr

ies

9.0

0.0

0.0

0.0

0.0

9.0

0.0

0.0

0.0

0.0

9.0

Fiv

eot

her

EM

Um

embe

rs2.

70.

00.

00.

00.

02.

70.

00.

00.

00.

02.

7D

enm

ark,

Gre

ece,

Swed

en,U

K1.

00.

20.

08.

60.

19.

90.

00.

00.

00.

09.

9U

nite

dSt

ates

0.0

37.9

0.0

0.0

0.0

0.0

37.9

0.0

0.0

0.0

37.9

Japa

n0.

00.

022

.40.

00.

00.

00.

022

.40.

00.

022

.4O

ther

2.0

3.2

0.1

0.4

0.4

2.4

3.2

0.1

0.0

0.4

6.0

Dev

elop

ing

coun

trie

s0.

710

.10.

50.

40.

41.

110

.10.

50.

00.

412

.1A

fric

a0.

00.

90.

00.

30.

20.

30.

90.

00.

00.

21.

4A

sia

0.5

6.7

0.5

0.1

0.1

0.6

6.7

0.5

0.0

0.1

7.8

Eur

ope

0.0

0.1

0.0

0.0

0.1

0.0

0.1

0.0

0.0

0.1

0.2

Mid

dle

Eas

t0.

00.

30.

00.

00.

10.

00.

30.

00.

00.

10.

3W

este

rnH

emis

pher

e0.

12.

20.

00.

00.

00.

12.

20.

00.

00.

02.

3T

otal

15.4

51.5

22.9

9.4

0.9

25.0

51.3

22.9

0.0

0.8

100.

0

Not

e.T

heco

re-s

ixco

untr

ies

incl

ude

Aus

tria

,Bel

gium

,Fra

nce,

Ger

man

y,L

uxem

bour

g,an

dth

eN

ethe

rlan

ds.F

ive

othe

rE

MU

mem

bers

incl

ude

Fin

land

,Ire

land

,Ita

ly,

Por

tuga

l,an

dSp

ain.


capitalizations (51.3%) is more than twice the size of the euro area (25.0%).The size of the U.S. dollar area is large because of the large size of U.S.stock market capitalizations (37.9%), and the size of the euro area is smallbecause of the small size of the EU-fifteen’s stock market capitalizations(21.5%). The relative size of the yen area based on stock market capitaliza-tions is relatively large (22.9%) but remains less than half that of the dollararea. This predominance of the U.S. dollar area suggests that the U.S.dollar will continue to be the world’s most important international currencyif capital market activity is an important factor determining the choice ofnominal anchor currency.

However, the trade flow measure indicates that the euro area will belarger than the U.S. dollar area. The euro area accounts for 48.1% of theworld total trade flows, the U.S. dollar area 40.9%, and the yen area a meager9.2%. Though interpretation of trade-based economic size needs cautionbecause the underlying trade flows do not net out intra-EMU trade flows,the predominance of the euro area measured by trade activity is impressive.This is especially so in contrast to the results based on stock market capitaliza-tions. Essentially, the future relative economic size of the prospective eurodepends on which economic activity will be considered more important tothe world as a whole, stock market activity or trade activity.

One neglected factor has to be mentioned. The development and growthof the economies in Eastern Europe, the Mediterranean, and the formerSoviet Union are expected to enlarge the euro area because many of theseeconomies are being considered for accession to the European Union.Given that these economies are underrepresented in our sample, our calcu-lations may have underestimated the size of the prospective euro area andoverestimated the size of the U.S. dollar area.

V. DETERMINANTS OF OFFICIAL HOLDINGS OF THE G-5CURRENCIES AS FOREIGN EXCHANGE RESERVES

One of the important roles of major international currencies is to serveas foreign exchange reserves for central banks. Researchers have investi-gated the determinants of the reserve currency roles of the major industrial-ized countries’ currencies. Dooley, Lizondo, and Mathieson (1989) exam-ined the currency composition of foreign exchange reserves, focusing onthe G-5 currencies. Using confidential data, they found that the reserve-currency composition was influenced by each country’s reported exchangerate arrangements, trade flows with reserve-currency countries, and thecurrency in which its debt service payments are denominated. Using publiclyavailable data, Eichengreen and Frankel (1996) showed that the shares ofthe U.S. dollar, the deutsche mark, and the Japanese yen held as foreignexchange reserves can be explained by the output share of the respectivemajor country in the world. Eichengreen (1998) also showed that the shares


of the same G-3 currencies held as foreign exchange reserves can be ex-plained by the shares of output and/or trade of the three countries, includinglagged variables of output and trade.

In this section, we demonstrate that our estimated measures of currencyareas are useful information in explaining variations in the shares of G-5currencies held as official foreign exchange reserves. Specifically, we showthat the holdings of foreign exchange reserves can be better explained byusing the ‘‘net currency-area size’’ in addition to the type of variable usedby Eichengreen and Frankel, the ‘‘own-economic size.’’ The net currency-area size is defined as the size of the currency area as calculated in theprevious section and reported in Table II, except that the economic sizeof each of the G-5 countries, called the own-economic size, is subtractedfrom it. Since the net currency-area size is constructed using the regressioncoefficients obtained for each 5-year period, this variable is also measuredas the 5-year average. Accordingly, we use data for 5-year averages of eachvariable and pool the observations of G-5 countries in a single regressionequation, with the number of observations in each equation totaling 25.As the own-economic size variables, we use the economic shares of theG-5 countries in the world, measured in terms of GDP or total trade flows(exports plus imports).31

The results of the regression analyses are summarized in Tables IVa andIVb.32 Table IVa reports the results when the shares of G-5 currencies heldas foreign exchange reserves are explained only by the own-economic sizeas in Eichengreen and Frankel (1996) and Eichengreen (1997). When onlyone own-economic size variable is used as an explanatory variable in addi-tion to the constant term (Table IVa), the own-economic size based onGDP produces the best result for all three groups of countries and the trade-based variable also produces a reasonable result with a highly significantcoefficient. When two own-economic size variables, GDP-based and trade-based, are used simultaneously, the explanatory power of regression im-proves for all three groups of countries. The magnitudes of the estimated

31 We have decided not to include the SDR or the ECU as foreign exchange reserves inthe regression equation because of the difficulty of defining their own-economic size variables.

32 The IMF publishes annual data for the shares of several industrial countries’ currenciesheld as foreign exchange reserves by the central banks of three groups of countries, namely,industrial countries, developing countries, and all countries (world total). The data are obtainedfrom IMF, International Financial Statistics, Supplement on International Reserves, SupplementSeries No. 6 (1983); International Financial Statistics, Supplement on International Liquidity,Supplement Series No. 14 (1987); and Annual Report, various issues. The share of the U.S.dollar as foreign exchange reserves declined appreciably in 1979 when the IMF introduceddata for the holdings of the ECU as a new item of foreign exchange reserves. We thereforetried to see if the new classification might make any difference in explaining the behavior offoreign exchange reserves by including a dummy variable in the regression equation to accountfor this change. The dummy variable, however, is never significant in any of the specificationswe have tried. Tables Va and Vb therefore report results which do not include the ECU dummy.


TABLE IVaThe Effects of the Own-Economic Size on the Holdings of Foreign Exchange Reserves:

Pooled Regressions for G-5 Currencies(Averages for 5-year Periods)

Industrial DevelopingExplanatory variables World countries countries

Constant 210.842** 211.962** 28.661**(2.591) (2.879) (2.731)

Own-economic size (GDP) 2.138** 2.174** 2.042**(0.160) (0.178) (0.169)

R2-Adjusted 0.881 0.861 0.858Nobs 25 25 25

Constant243.332** 244.469** 240.721**

(6.908) (7.581) (6.539)Own-economic size (trade)

6.255** 6.304** 6.082**(0.688) (0.755) (0.651)

R2-Adjusted0.773 0.741 0.782

Nobs 25 25 25Constant

223.224** 223.271** 222.979**(5.874) (6.779) (6.038)Own-economic size (GDP)1.571** 1.656** 1.386**

(0.286) (0.331) (0.294)Own-economic size (trade)2.055* 1.877(#) 2.377*

(0.892) (1.029) (0.916)R2-Adjusted0.900 0.874 0.887Nobs

25 25 25

Note. The numbers in parentheses are the estimated standard errors. Statistical significanceis indicated by ** (1% level), * (5% level), and (#) (10% level). The own-economic size ismeasured by using either nominal GDP or total trade flows (exports plus imports) in currentU.S. dollars.

coefficients on the own-economic size are reasonable and not very differentfrom those estimated by Eichengreen, who used time-series data.33 Forexample, the coefficient on the GDP-based, own-economic size variable isin the 2.0 to 2.2 range when included as the only explanatory variable, andin the 1.4 to 1.7 range when included in combination with the trade-based,own-economic size variable. The trade-based, own-economic size variableyields a coefficient ranging between 1.9 and 2.4, which is larger than thatof the GDP-based variable.

We next add the net currency-area size variable in the right-hand side

33 Eichengreen points out that differences in own-economic sizes across countries do notfully explain disproportionately large holdings of the U.S. dollar and that a historical factormust be taken into account in the regression equation for the U.S. dollar. Eichengreentherefore chooses to include the lagged dependent variable to explain the effects of history.


of the pooled regression equation as another factor affecting the currencycompositions of foreign exchange reserves. With this specification (TableIVb), better results are produced in terms of explanatory power. For boththe group of all countries (world) and the group of industrial countries, thebest result is obtained when the GDP-based own-economic size is used to-gether with the GDP-based net currency-area size as explanatory variables.For the group of developing countries, the best result is obtained when thetrade-based own-economic size is used along with the GDP-based net cur-rency-area size, or the GDP-based own-economic size is added to these twovariables. With the net currency-area size included, the coefficient on the own-economic size becomes smaller than without it. In all regression equations, theestimated coefficients on the net currency-area size, though smaller than thoseon the own-economic size, are always statistically significant.

VI. CONCLUDING REMARKS

This paper has examined the exchange rate arrangements adopted byindividual countries in the world. In order to assess the changing roles ofthe major currencies as nominal anchors for exchange rate stabilization,the paper has compiled information on reported exchange rate arrange-ments and has examined patterns of exchange rate volatility and estimatedregression coefficients.

Several important findings are summarized as follows. First, the industri-alized countries and the developing economies adopt different exchangerate regimes. In the industrialized world, the U.S. dollar is not a primarytarget currency for exchange rate stabilization, except in Canada and, tosome extent, Australia and New Zealand. Many countries in Western Eu-rope choose the deutsche mark, the French franc, and the ECU as theirnominal anchor currencies. In the developing world, the U.S. dollar is thefavorite nominal anchor, though significant diversity exists across regions.Africa includes rigid exchange-rate peggers as well as wild exchange-ratefloaters. Its major nominal anchor currencies are the French franc, the U.S.dollar, and the SDR. Asian economies generally attempt to stabilize theirexchange rates vis-a-vis the U.S. dollar, the SDR, and a few regional curren-cies. The Japanese yen has not played a major role as an important nominalanchor even in East Asia. Developing Europe does not experience stableexchange rates; the U.S. dollar, major Western European currencies, or abasket of these serve as loose nominal anchors for this region. The MiddleEast includes countries that successfully stabilize their exchange rates vis-a-vis the U.S. dollar and the SDR. It is one of the most stable regions in theworld in terms of exchange rate movements. The whole of Latin America isa de facto U.S. dollar area since even countries that do not explicitly pegtheir exchange rates to the U.S. dollar do assign significantly positive, andclose to unitary, weights to the dollar.

TABLE IVbThe Effects of the Own-Economic Size and the Net Currency-Area Size on the Holdings

of Foreign Exchange Reserves: Pooled Regressions for the G-5 Currencies(Averages for 5-year Periods)


Constant 210.090** 216.984** 20.478(1.715) (2.739) (1.826)

Own-economic size (GDP) 1.185** 1.993** 0.582*(0.201) (0.154) (0.213)

Net currency-area size (GDP) 0.662** 0.447** 0.575**(0.119) (0.126) (0.076)

Adjusted R2 0.948 0.908 0.959Number of observations 25 25 25

Constant 217.224* 244.258** 210.053*(7.457) (7.826) (3.730)

Own-economic size (trade) 1.794 6.202** 1.739**(1.070) (0.944) (0.461)

Net currency-area size (GDP) 0.957** 0.047 0.596**(0.203) (0.248) (0.053)


Constant 212.013** 216.636** 20.003(1.990) (2.964) (1.950)

Own-economic size (GDP) 1.555** 2.119** 0.566*(0.184) (0.155) (0.227)

Net currency-area size (trade) 0.502** 0.319** 0.579**(0.119) (0.109) (0.081)


Constant 232.484** 245.742** 29.814*(10.680) (7.424) (3.847)

Own-economic size (trade) 4.324* 6.952** 1.755**(1.614) (0.850) (0.472)

Net currency-area size (trade) 0.442 20.290** 0.595**(0.335) (0.192) (0.054)


Constant 210.159(#) 216.880* 29.579*(5.233) (6.364) (3.629)

Own-economic size (GDP) 1.184** 1.998** 0.323(0.228) (0.314) (0.208)

Own-economic size (trade) 0.011 20.021 1.394*(0.802) (1.130) (0.499)

Net currency-area size (trade) 0.661** 0.448* 0.525**(0.149) (0.161) (0.069)


(continued)

371


TABLE IVb—Continued


Constant 26.738 213.251 29.499*(7.082) (7.825) (3.787)

Own-economic size (GDP) 1.675** 2.307** 0.295(0.242) (0.431) (0.220)

Own-economic size (trade) 20.920 20.722 1.451*(1.185) (1.541) (0.517)

Net currency-area size (trade) 0.617** 0.385* 0.528**(0.191) (0.179) (0.073)


Note. The numbers in parentheses are the estimated standard errors. Statistical significanceis indicated by ** (1% level), * (5% level), and (#) (10% level). The net currency-area size isthe difference between the size of currency area as defined in Table V and the own-economicsize, all measured by either nominal GDP or total trade flows (exports plus imports).

Second, we have calculated the economic size, in terms of GDP andtrade flows, of countries under fixed and flexible exchange rate regimesusing estimated values of exchange rate volatility as a demarcation for fixedversus flexible rate regimes. Furthermore, we have compared our measuresof economic size with those that would be obtained using reported exchangerate arrangements. Our measures demonstrate that over the past 25 years,the economic share of countries under fixed rate regimes (with exchangerate volatility less than 0.005 or 0.010) has not declined as dramatically andthe economic share of countries under flexible rate regimes (with volatilitygreater than 0.015 or 0.010) has not risen as dramatically as the measurebased on reported arrangements would indicate. This indicates that changesin observed exchange rate arrangements are gradual.

Third, we have calculated the economic size, in terms of GDP, tradeflows, and financial aggregates, of major currency areas using the estimationresults obtained from exchange rate regressions for all countries in theworld. The regression coefficients on currencies which have been estimatedto be statistically significant and positive are interpreted as the weightsassigned by each country’s authorities to those currencies in exchange ratemanagement. A country’s economy is divided according to these estimatedweights and distributed to the corresponding currency areas. We havecalculated the size of currency areas formed by the G-5 countries, the SDR,and the ECU for each 5-year period and examined how they have evolvedover time. Our calculations suggest that, despite its declining trend, theU.S. dollar area continues to be large because many developing economies,particularly those in Asia and Latin America, regard the dollar as the most


important global anchor currency. The Western European currency area,despite its rising trend, is still substantially smaller than the U.S. dollararea, except when measured by trade flows. This suggests that the U.S.dollar will continue to play a key currency role. The Japanese yen hasplayed a far less significant role globally and seems destined to do so unlessa substantial structural break occurs in Asia.

Fourth, following the same method as above, we have computed theeconomic size of the prospective euro area, the U.S. dollar area, and theJapanese yen area, based on the regression results for the 1990s. Using GDPas a measure in calculating economic size, the case of EMU-15 indicates thatabout 46% of the world economy is in the U.S. dollar area, 35% in the euroarea, and 17.5% in the Japanese yen area. The strength of the U.S. dollarlies in the fact that the dollar area is far larger than the size of the UnitedStates itself, which is 27.5%; many developing countries regard the U.S.dollar as the most important nominal anchor. In particular, a substantialpart of the Asian and Western Hemisphere economies belong to the U.S.dollar area. The euro area is bigger than the size of the European Unionby about 3 percentage points. The Japanese yen area is only marginallylarger than the relative share of the Japanese economy. If trade flowsare the fundamental factors determining currency dominance, the resultssuggest a rise in the euro’s role. If these fundamentals are based on capitalmarket measures, the results suggest a much slower rise for the euro. Thetruth seems to lie somewhere in between.

Finally, we have investigated econometrically the determinants of thecomposition of G-5 currencies held as foreign exchange reserves. The empir-ical results have revealed that the reserve currency composition can bebetter explained by the constructed measure of the net currency-area aswell as by the own-economic size of the reserve currency country. Thisdemonstrates the importance of each country’s actual exchange rate ar-rangement for the choice of reserve currency holding.

The paper has not made any attempt to explain the causes of cross-country variation in exchange rate arrangements. What is clear is thatregional factors have important bearings on a nation’s choice of exchangerate regime. This choice reflects not only the degree to which a nation iscurrently integrated to global or regional economic powers in terms of itstrade, investment, or finance, but also the nation’s past colonial ties, history,politics, and geographical proximity. Other factors that affect this choicewould be the degree of openness of the economy in question, the tightnessof exchange control, and various domestic macroeconomic considerationssuch as fiscal balances and inflationary pressure. An econometric studythat tests the importance of these factors in the choice of exchange ratearrangements would be needed in order to enhance our understanding ofthe evolution of the international monetary system.

374 KAWAI AND AKIYAMAA

PP

EN

DIX

‘‘Rep

orte

d’’

and

Obs

erve

dE

xcha

nge

Rat

eA

rran

gem

ents

ofth

eIn

divi

dual

Cou

ntri

esin

the

Wor

ld,

1990

–199

6

‘‘Rep

orte

d’’

exch

ange

rate

arra

ngem

ent

Exc

hang

era

tevo

lati

lity

Sum

mar

yof

exch

ange

rate

regr

essi

onre

sult

s

Janu

ary

1990

–C

urre

ncy

inth

ere

gres

sion

equa

tion

Std-

res

Janu

ary

1990

–Dec

embe

r19

96(a

ndJa

n.19

97–)

Dec

embe

r19

96th

ees

tim

ated

coef

ficie

nts

excl

/inc

l

Indu

stri

alco

untr

ies

Uni

ted

Stat

esIF

82.0

7SD

R0.

0140

04F

F**

JY**

UK

P*

0.02

1333

0.91

30.

407

0.25

50/

84C

anad

aIF

82.0

7U

SD0.

0103

45U

SD**

EC

U0.

0102

780.

933

0/84

Aus

tral

iaIF

83.1

2N

ZD

0.01

6334

USD

**N

ZD

**U

KP

*JY

FF

SDR

0.01

3923

1.18

90.

599

0.34

60/

84Ja

pan

IF82

.07

SDR

0.02

0287

USD

**D

M0.

0249

440.

477

0/84

New

Zea

land

IF85

.04

USD

0.01

5172

SDR

**A

D**

0.01

2288

0.53

10.

502

0/84

Aus

tria

CC

73.0

3C

EA

95.0

1D

M##

0.00

0997

DM

**U

KP

0.00

0988

1.01

10/

84B

elgi

umC

EA

73.0

3F

F#

0.00

5316

FF

**D

M**

0.00

4574

0.57

60.

338

0/84

Den

mar

kC

EA

73.0

4F

F#

0.00

5599

FF

**D

M0.

0055

750.

850

0/84

Fin

land

CC

73.0

6IF

92.0

9C

EA

96.1

0E

CU

0.01

6144

UK

P**

USD

*0.

0148

710.

337

0.14

01/

83F

ranc

eC

EA

79.0

3E

CU

#0.

0052

22D

M**

UK

P*

USD

*0.

0059

570.

779

0.07

60.

066

0/84

Ger

man

yC

EA

73.0

3E

CU

#0.

0057

18F

F**

0.00

5708

0.75

40/

84G

reec

eM

F82

.12

EC

U#

0.00

6931

FF

**D

M*

UK

P**

USD

**0.

0067

060.

502

0.32

70.

182

0.08

20/

84Ic

elan

dC

C88

.06*

EC

U0.

0100

75E

CU

**U

SD**

0.00

9326

0.91

00.

153

0/84

Irel

and

CE

A79

.03

EC

U0.

0140

33E

CU

**U

KP

**0.

0134

750.

783

0.27

0/84

Ital

yC

EA

79.4

IF92

.09

CE

A96

.11

EC

U0.

0177

34F

F**

UK

P**

USD

*0.

0168

410.

638

0.41

60.

179

1/83

EXCHANGE RATE ARRANGEMENTS 375L

uxem

bour

gC

EA

73.0

3F

F#

0.00

5316

FF

**D

M**

0.00

4574

0.57

60.

338

0/84

Net

herl

ands

CE

A73

.03

DM

#0.

0010

83D

M**

FF

**0.

0009

640.

911

0.05

90/

84N

orw

ayC

C78

.12

IF92

.12

MF

95.0

5E

CU

#0.

0048

74E

CU

**0.

0048

531.

057

0/84

Por

tuga

lA

F77

.08

MF

90.1

0C

EA

92.0

4E

CU

0.01

1611

SP**

FF

DM

USD

0.00

9987

0.54

30/

84Sp

ain

CE

A89

.07

EC

U0.

0116

44F

F**

UK

P**

0.01

2193

0.82

20.

313

0/84

Swed

enC

C77

.08

IF92

.11

EC

U0.

0150

28E

CU

**U

SD**

0.01

4284

0.77

20.

217

2/82

Swit

zerl

and

IF82

.07

DM

0.01

0712

DM

**F

F0.

0104

720.

881

0/84

Uni

ted

Kin

gdom

IF82

.07

CE

A90

.10

IF92

.09

EC

U0.

0137

63F

F**

USD

*0.

0158

180.

819

0.18

81/

83D

evel

opin

gco

untr

ies

Afr

ica

Alg

eria

CC

74.0

1M

F94

.10

SDR

0.01

7981

USD

**D

M0.

0159

460.

669

6/78

Ang

ola

USD

89.0

9M

F94

.04

USD

96.0

7SD

R0.

0393

16E

CU

*D

M0.

0394

874.

569

40/2

8B

enin

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83B

otsw

ana

CC

80.0

6SA

R#

0.00

9000

SAR

**U

SD*

JY0.

0085

410.

785

0.16

2/82

Bur

kina

Fas

oF

F70

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Bur

undi

SDR

83.1

1C

C92

.04

SDR

0.01

5171

SDR

**0.

0152

470.

957

1/79

Cam

eroo

nF

F70

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Cap

eV

erde

CC

77.0

2F

F#

0.00

8408

FF

**P

E**

0.00

6870

0.64

40.

381

1/83

Cen

tral

Afr

ican

Rep

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83C

had

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83

(con

tinue

d)


AP

PE

ND

IX—

Con

tinue

d

‘‘Rep

orte

d’’

exch

ange

rate

arra

ngem

ent

Exc

hang

era

tevo

lati

lity

Sum

mar

yof

exch

ange

rate

regr

essi

onre

sult

s

Janu

ary

1990

–C

urre

ncy

inth

ere

gres

sion

equa

tion

Std-

res

Janu

ary

1990

–Dec

embe

r19

96(a

ndJa

n.19

97–)

Dec

embe

r19

96th

ees

tim

ated

coef

ficie

nts

excl

/inc

l

Com

oros

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83C

ongo

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83C

ote

D’I

voir

eF

F70

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Djib

outi

USD

78.1

2U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84E

quat

oria

lG

uine

aF

F85

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Eri

trea

MF

94.0

9(I

F97

.12*

)—

——

— —E

thio

pia

USD

70.0

1IF

93.0

5U

SD0.

0124

08U

SD**

0.01

2468

0.97

91/

83G

abon

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83G

ambi

a;T

heIF

86.0

5SD

R0.

0154

25F

F**

USD

**U

KP

**0.

0145

790.

541

0.32

40.

232

0/83

Gha

naIF

86.1

0U

SD0.

0197

16U

SD**

FF

**JY

0.01

9150

0.83

80.

590

0/84

Gui

nea

MF

88.0

9*IF

94.1

0U

SD0.

0127

18U

SD**

0.01

2371

0.89

20/

83G

uine

a-B

issa

uM

F84

.03

(FF

97.0

5)U

SD0.

0255

36U

SD**

0.02

4871

0.78

76/

78K

enya

CC

87.1

2*IF

93.1

0SD

R0.

0212

36U

SD**

UK

P*

0.02

0397

0.62

90.

245

5/79

Les

otho

SAR

70.0

1SA

R##

#0.

0000

00SA

R**

0.00

0000

1.00

00/

84L

iber

iaU

SD70

.01

(IF

97.1

2*)

USD

###

0.00

0000

USD

**0.

0000

001.

000

0/84

EXCHANGE RATE ARRANGEMENTS 377M

adag

asca

rA

F86

.10

IF94

.05

SDR

0.01

8925

SDR

**F

F0.

0190

520.

856

3/81

Mal

awi

CC

84.0

1IF

94.0

2SD

R0.

0181

39U

KP

**SD

RU

SD0.

0166

030.

401

7/74

Mal

iF

F70

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Mau

rita

nia

MF

87.0

3C

C92

.06*

IF95

.12

SDR

0.01

5053

USD

**U

KP

**0.

0138

630.

388

0.29

51/

83M

auri

tius

CC

83.0

2M

F94

.06

EC

U#

0.00

7714

EC

U**

FF

*U

SD**

0.00

5601

0.66

60.

261

0.19

00/

84M

oroc

coM

F82

.07

CC

90.0

5F

F0.

0128

91F

F**

DM

*U

SD**

UK

PSP

0.01

0779

0.80

30.

480.

201

0/84

Moz

ambi

que

CC

89.1

2A

F90

.09

IF92

.04

SDR

0.02

6253

FF

*U

SD**

0.02

5383

0.77

10.

665

7/77

Nam

ibia

n.a.

SAR

90.0

9SA

R##

#0.

0000

00SA

R**

0.00

0000

1.00

00/

84N

iger

FF

70.0

1F

F##

#0.

0000

00F

F**

0.00

0000

1.00

01/

83N

iger

iaIF

86.0

9U

SD94

.01

USD

0.02

6935

USD

**U

KP

0.02

6739

0.80

63/

79R

wan

daSD

R83

.09

IF95

.03

SDR

0.02

1194

USD

**U

KP

JY0.

0203

260.

698

8/70

Sao

Tom

e&

CC

87.0

8M

F91

.09

IF94

.12

SDR

0.02

7416

SDR

**0.

0275

98P

rinc

ipe

0.96

19/

73Se

nega

lF

F70

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Seyc

helle

sSD

R79

.11

CC

96.0

5SD

R#

0.00

7434

USD

**JY

**U

KP

**D

M0.

0074

610.

409

0.18

40.

170/

84Si

erra

Leo

neU

SD87

.12

IF90

.04

USD

0.02

4075

USD

**0.

0241

730.

944

7/77

Som

alia

CC

88.0

7M

F90

.05

IF94

.09*

USD

0.01

4131

USD

*0.

0155

781.

174

0/5

Sout

hA

fric

aIF

82.0

7SD

R0.

0151

61U

SD**

UK

P**

0.01

3545

0.62

90.

220

0/84

Suda

nU

SD87

.10

IF92

.02

MF

93.1

1IF

95.0

9M

F96

.07

USD

0.02

9930

USD

**F

FD

M0.

0294

811.

034

9/71

Swaz

iland

SAR

70.0

1SA

R##

#0.

0000

00SA

R**

0.00

0000

1.00

00/

84

(con

tinue

d)


PP

EN

DIX

—C

ontin

ued

‘‘Rep

orte

d’’

exch

ange

rate

arra

ngem

ent

Exc

hang

era

tevo

lati

lity

Sum

mar

yof

exch

ange

rate

regr

essi

onre

sult

s

Janu

ary

1990

–C

urre

ncy

inth

ere

gres

sion

equa

tion

Std-

res

Janu

ary

1990

–Dec

embe

r19

96(a

ndJa

n.19

97–)

Dec

embe

r19

96th

ees

tim

ated

coef

ficie

nts

excl

/inc

l

Tan

zani

aC

C79

.01

IF93

.08

USD

0.02

4985

USD

**0.

0249

760.

906

2/82

Tog

oF

F70

.01

FF

###

0.00

0000

FF

**0.

0000

001.

000

1/83

Tun

isia

MF

87.1

2*E

CU

#0.

0084

59E

CU

**U

SD**

UK

P0.

0070

150.

848

0.19

50/

84U

gand

aC

C89

.12*

IF92

.01

USD

0.02

8159

USD

**0.

0283

310.

984

2/82

Zai

reIF

84.1

1U

SD0.

0462

81U

SD**

JY0.

0452

551.

098

53/2

1Z

ambi

aSD

R88

.11

AF

90.0

2IF

92.1

2U

SD0.

0335

95U

SD**

JYF

F0.

0334

741.

332

19/6

5Z

imba

bwe

CC

80.1

0IF

94.0

7SD

R0.

0205

92U

SD**

UK

P*

0.01

8730

0.60

30.

228

3/81

Asi

a Afg

hani

stan

;I.S

.of

USD

87.0

6IF

91.1

2*U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84B

angl

ades

hC

C79

.11

USD

#0.

0065

84U

SD**

0.00

6595

1.02

00/

84B

huta

nIR

81.0

9IR

##0.

0001

97IR

**0.

0001

981.

000

2/82

Bru

nei

Dar

ussa

lam

n.a.

SID

96.0

3SI

D#

0.00

3203

SID

**0.

0032

570.

994

0/30

Cam

bodi

an.

a.M

F93

.06*

USD

0.02

5131

USD

**U

KP

0.02

5035

1.09

913

/46

Chi

na;P

eopl

e’s

MF

86.1

0U

SD#

0.00

9320

USD

**U

KP

DM

0.00

925

Rep

.0.

959

2/82

Fiji

CC

75.0

4U

SD#

0.00

9937

USD

**A

D**

JY**

UK

P**

NZ

D**

0.00

2722

0.29

60.

285

0.15

30.

150

0.11

10/

84H

ong

Kon

gU

SD83

.10

USD

#0.

0011

29U

SD**

JY0.

0011

421.

002

0/84

EXCHANGE RATE ARRANGEMENTS 379In

dia

MF

82.0

7IF

93.0

3U

SD0.

0129

71U

SD**

0.01

2966

0.95

22/

82In

done

sia

MF

83.0

3(I

F97

.08)

USD

#0.

0027

30U

SD**

FF

0.00

2696

0.97

50/

84K

irib

ati

AD

86.0

6A

D##

#0.

0000

00A

D**

0.00

0000

1.00

00/

84K

orea

MF

82.0

7(I

F97

.12)

USD

#0.

0066

49U

SD**

JY**

0.00

6176

0.91

10.

097

0/84

Lao

P.D

.Rep

MF

89.0

3*IF

95.0

9(M

F97

.06*

)U

SD#

0.00

6830

USD

**JY

0.00

6847

0.96

61/

83M

alay

sia

CC

75.0

9M

F93

.06*

USD

0.01

1251

SID

**U

SD**

0.01

0606

0.52

90.

512

0/84

Mal

dive

sIF

87.0

3M

F91

.12*

USD

0.01

4882

USD

**D

M0.

0134

061.

169

0/84

Mar

shal

lIs

land

sn.

a.U

SD92

.06

——

—— —

Mic

rone

sia;

Fed

Sts

n.a.

USD

94.0

1U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84M

ongo

lian.

a.U

SD91

.02

IF93

.05

USD

0.01

7539

USD

**0.

0174

670.

914

6/71

Mya

nmar

SDR

75.0

2SD

R#

0.00

8810

SDR

**U

SD0.

0088

581.

133

0/84

Nep

alC

C83

.05

IF93

.02

CC

93.0

6*IR

0.02

1026

IR**

USD

**0.

0147

560.

502

0.46

30/

84P

akis

tan

MF

82.0

7U

SD0.

0131

40U

SD**

FF

DM

0.01

2750

0.85

30/

84P

apua

New

Gui

nea

CC

78.0

1IF

94.1

0U

SD0.

0173

42U

SD**

AD

**0.

0165

630.

654

0.34

31/

83P

hilip

pine

sIF

84.1

1U

SD0.

0169

20U

SD**

0.01

6808

1.08

80/

84Si

ngap

ore

MF

87.1

2*SD

R#

0.00

8097

SDR

**U

SD**

0.00

4982

0.69

20.

383

0/84

Solo

mon

Isla

nds

CC

79.1

0U

SD0.

0129

99U

SD**

JY0.

0126

860.

869

0/84

Sri

Lan

kaM

F82

.07

USD

0.01

4196

USD

**JY

0.01

4011

0.88

90/

84T

aiw

anIF

89.0

4U

SD#

0.00

9623

USD

**F

F*

JY**

0.00

8700

0.79

70.

226

0.10

90/

84

(con

tinue

d)


PP

EN

DIX

—C

ontin

ued

‘‘Rep

orte

d’’

exch

ange

rate

arra

ngem

ent

Exc

hang

era

tevo

lati

lity

Sum

mar

yof

exch

ange

rate

regr

essi

onre

sult

s

Janu

ary

1990

–C

urre

ncy

inth

ere

gres

sion

equa

tion

Std-

res

Janu

ary

1990

–Dec

embe

r19

96(a

ndJa

n.19

97–)

Dec

embe

r19

96th

ees

tim

ated

coef

ficie

nts

excl

/inc

l

Tha

iland

CC

84.1

1(M

F97

.07)

USD

#0.

0044

01U

SD**

JY**

DM

**U

KP

**0.

0009

160.

817

0.10

80.

050.

021

0/84

Ton

gaA

D85

.09

CC

91.0

2A

D#

0.00

9445

AD

**U

SD**

NZ

D**

0.00

4802

0.45

60.

312

0.21

40/

84V

anua

tuC

C88

.02

SDR

0.01

5510

AD

**0.

0121

820.

691

0/84

Vie

tnam

USD

89.0

3M

F90

.03*

USD

0.01

6971

USD

**U

KP

0.01

6921

1.02

12/

69W

este

rnSa

moa

CC

88.0

3*U

SD0.

0159

62A

D**

SDR

USD

SID

0.01

4593

0.37

20/

84E

urop

eA

lban

iaC

C91

.09

IF92

.07

SDR

0.02

5601

USD

**0.

0251

450.

591

2/57

Arm

enia

RR

92.0

9*IF

93.1

1U

SD0.

0245

13U

SD**

UK

P0.

0243

951.

287

21/3

5A

zerb

aija

nR

R92

.12

IF94

.05

USD

#0.

0081

14U

SD**

DM

0.00

7569

1.16

21/

18B

elar

usR

R92

.09*

MF

93.1

2JY

0.03

1888

JY0.

0335

890/

8B

osni

a&

DM

95.1

2—

——

—H

erze

govi

na—

Bul

gari

aC

C90

.05

IF91

.02

(DM

97.0

9*)

USD

0.02

9766

USD

**0.

0294

170.

806

14/5

8C

roat

iaM

F93

.05

IF93

.10

MF

94.1

2*SD

R0.

0184

62JY

*F

FU

SD0.

0183

340.

307

10/3

8C

ypru

sC

C73

.07

EC

U#

0.00

7063

EC

U*

USD

**U

KP

*F

FJY

0.00

5625

0.46

90.

140

0.10

90/

84C

zech

Rep

ublic

CC

93.1

2(M

F97

.06*

)SD

R#

0.00

7791

DM

**U

SD**

UK

P0.

0041

820.

717

0.37

90/

47E

ston

iaD

M92

.06

DM

#0.

0036

54D

M**

0.00

3684

0.98

00/

54

EXCHANGE RATE ARRANGEMENTS 381G

eorg

ian.

a.—

——

— —H

unga

ryC

C82

.06

MF

95.0

3SD

R0.

0144

38U

SD**

FF

**0.

0133

350.

550

0.48

11/

83K

azak

hsta

nR

R92

.08

IF93

.11

(MF

97.1

2*)

USD

0.02

9350

USD

**0.

0281

411.

363

7/30

Kyr

gyz

Rep

RR

92.0

9*IF

93.0

5M

F95

.12*

——

—— —

Lat

via

RR

92.0

6IF

92.0

9*M

F95

.12*

(SD

R97

.12*

)SD

R0.

0156

61U

SD**

JY**

0.01

5011

0.49

20.

351

5/53

Lit

huan

iaIF

92.0

9*U

SD94

.04

USD

0.02

6616

USD

**0.

0259

561.

266

3/45

Mac

edon

iaIF

93.1

2*M

F94

.12*

DM

0.01

5040

DM

**0.

0148

061.

400

0/36

Mal

taC

C72

.07

EC

U0.

0109

44E

CU

**U

SD**

DM

0.00

959

1.19

50.

196

0/84

Mol

dova

RR

92.0

9*IF

93.0

8U

SD#

0.00

7238

USD

**0.

0073

021.

034

0/31

Pol

and

CC

86.0

6U

SD90

.01

CC

91.0

5M

F91

.10

SDR

0.01

6156

USD

**SD

R0.

0151

830.

534

3/81

Rom

ania

CC

83.0

7IF

91.0

2M

F91

.11

IF92

.06

USD

0.03

1323

USD

**U

KP

0.03

0278

0.66

313

/71

Rus

sian

Fed

erat

ion

IF92

.09*

MF

95.0

7U

SD0.

0270

07U

SD**

UK

PJY

0.02

6060

1.67

611

/25

San

Mar

ino

IL93

.10

——

—— —

Slov

akR

epub

licC

C94

.06

FF

0.01

1295

FF

**U

SD*

0.01

0344

0.99

90.

192

0/47

Slov

enia

MF

93.0

4D

M0.

0199

92D

M*

0.02

0159

1.04

51/

60T

ajik

ista

nR

R94

.05

IF95

.05

USD

0.04

2077

UK

P**

JY0.

0346

472.

030

21/1

8T

urke

yM

F82

.07

SDR

0.01

8834

USD

**0.

0183

080.

537

4/80

Tur

kmen

ista

nR

R93

.04

MF

93.1

1U

SD94

.03

MF

95.1

1U

SD0.

0240

20U

SD**

0.02

3899

1.18

818

/23

Ukr

aine

IF92

.09*

MF

95.1

2*U

SD0.

0282

16U

SD**

0.02

7365

1.31

916

/32

(con

tinue

d)


PP

EN

DIX

—C

ontin

ued

‘‘Rep

orte

d’’

exch

ange

rate

arra

ngem

ent

Exc

hang

era

tevo

lati

lity

Sum

mar

yof

exch

ange

rate

regr

essi

onre

sult

s

Janu

ary

1990

–C

urre

ncy

inth

ere

gres

sion

equa

tion

Std-

res

Janu

ary

1990

–Dec

embe

r19

96(a

ndJa

n.19

97–)

Dec

embe

r19

96th

ees

tim

ated

coef

ficie

nts

excl

/inc

l

Uzb

ekis

tan

IF95

.02

MF

95.1

1—

——

— —Y

ugos

lavi

aD

M89

.12

USD

92.0

7X

92.1

2*—

——

— —M

iddl

eE

ast

Bah

rain

LS

82.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84E

gypt

MF

87.0

5U

SD#

0.00

3783

USD

**0.

0035

210.

953

2/82

Iran

;I.R

.of

SDR

80.0

3IF

93.0

3M

F95

.05

SDR

0.01

1701

USD

**D

M*

UK

P*

JY0.

0105

620.

598

0.29

30.

129

2/82

Iraq

USD

72.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84Is

rael

CC

87.0

3M

F91

.12

SDR

0.01

2570

USD

**0.

0127

090.

593

0/84

Jord

anC

C89

.06

USD

#0.

0065

16U

SD**

SDR

**0.

0043

360.

641

0.36

80/

84K

uwai

tC

C75

.03

USD

#0.

0087

61U

SD**

JY*

UK

P0.

0073

480.

773

0.08

70/

75L

eban

onIF

82.0

7U

SD0.

0220

84U

SD**

0.02

0255

1.31

116

/68

Lib

yaSD

R86

.03

SDR

#0.

0079

46U

SD*

FF

*JY

**U

KP

**D

M0.

0078

680.

387

0.37

90.

261

0.13

21/

83O

man

USD

72.0

6U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84Q

atar

LS

82.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84Sa

udia

Ara

bia

LS

82.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84Sy

rian

Ara

bU

SD70

.01

USD

###

0.00

0000

USD

**0.

0000

00R

epub

lic1.

000

0/84

EXCHANGE RATE ARRANGEMENTS 383U

nite

dA

rab

LS

82.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

Em

irat

es1.

000

0/84

Yem

en;R

epub

licof

USD

90.0

6IF

96.0

1U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

02/

77W

este

rnH

emis

pher

eA

ntig

ua&

Bar

buda

USD

76.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84A

rgen

tina

IF89

.12

USD

91.0

3U

SD0.

0130

32U

SD**

DM

**0.

0124

230.

870

0.46

56/

78A

ruba

n.a.

USD

###

0.00

0000

USD

**0.

0000

001.

000

0/84

Bah

amas

;The

USD

70.0

1U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84B

arba

dos

USD

75.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84B

eliz

eU

SD82

.06

USD

###

0.00

0000

USD

**0.

0000

001.

000

0/84

Bol

ivia

IF85

.08

MF

98.0

3*U

SD#

0.00

3678

USD

**E

CU

0.00

3636

0.98

80/

83B

razi

lA

F70

.01

IF90

.04

MF

94.0

7U

SD0.

0364

11U

SD**

JY0.

0359

651.

172

46/3

8C

hile

AF

82.1

0(M

F97

.09*

)U

SD0.

0154

42U

SD**

JY*

0.01

5060

1.00

90.

134

0/84

Col

ombi

aA

F70

.01

MF

94.0

1U

SD0.

0117

25U

SD**

SDR

*0.

0113

660.

745

0.49

11/

83C

osta

Ric

aM

F82

.10

IF92

.02

MF

95.1

2*U

SD0.

0106

56U

SD**

FF

0.01

0694

0.96

10/

84D

omin

ica

USD

76.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84D

omin

ican

Rep

ublic

MF

88.0

2U

SD90

.08

IF91

.01

MF

94.0

9U

SD0.

0157

19U

SD**

0.01

5756

1.04

63/

81E

cuad

orM

F89

.03*

USD

92.0

9M

F92

.12*

AF

94.1

2M

F95

.10

USD

0.01

8019

USD

**0.

0179

551.

082

1/83

El

Salv

ador

MF

89.1

2*IF

90.0

6M

F95

.06

USD

#0.

0070

82U

SD**

UK

P*

0.00

6926

0.97

00.

091

2/82

Gre

nada

n.a.

USD

###

0.00

0000

USD

**0.

0000

001.

000

0/84

Gua

tem

ala

IF89

.11

USD

0.02

2889

USD

**JY

*0.

0219

651.

009

0.24

32/

82

(con

tinue

d)


AP

PE

ND

IX—

Con

tinue

d

‘‘Rep

orte

d’’

exch

ange

rate

arra

ngem

ent

Exc

hang

era

tevo

lati

lity

Sum

mar

yof

exch

ange

rate

regr

essi

onre

sult

s

Janu

ary

1990

–C

urre

ncy

inth

ere

gres

sion

equa

tion

Std-

res

Janu

ary

1990

–Dec

embe

r19

96(a

ndJa

n.19

97–)

Dec

embe

r19

96th

ees

tim

ated

coef

ficie

nts

excl

/inc

l

Guy

ana

USD

87.0

3IF

91.0

2U

SD0.

0135

97U

SD**

DM

**0.

0130

380.

871

0.47

54/

80H

aiti

USD

70.0

1IF

91.0

9U

SD0.

0282

29U

SD**

0.02

8380

0.95

75/

79H

ondu

ras

USD

70.0

1M

F90

.03

IF92

.02

MF

94.0

6U

SD0.

0164

99U

SD**

0.01

6502

0.94

14/

80Ja

mai

caU

SD89

.11

IF90

.09

USD

0.03

1780

USD

**0.

0317

710.

882

3/81

Mex

ico

MF

82.1

2IF

94.1

2U

SD0.

0163

14U

SD**

JY0.

0162

781.

006

4/80

Net

herl

ands

Ant

illes

USD

70.0

1U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84N

icar

agua

USD

70.0

1M

F90

.05

USD

91.0

3M

F93

.01

USD

0.01

5065

USD

**D

MU

KP

0.01

4301

AF

93.0

9*(M

F97

.03*

)0.

776

16/6

8P

anam

aU

SD70

.01

USD

###

0.00

0000

USD

**0.

0000

001.

000

0/84

Par

agua

yIF

89.0

3U

SD0.

0118

82U

SD**

0.01

1931

1.02

50/

84P

eru

USD

87.0

8IF

90.0

8U

SD0.

0216

08U

SD**

UK

PJY

0.02

1367

0.98

616

/68

St.K

itts

and

Nev

isU

SD76

.07

USD

###

0.00

0000

USD

**0.

0000

001.

000

0/84

St.L

ucia

USD

76.0

7U

SD##

#0.

0000

00U

SD**

0.00

0000

1.00

00/

84S.

Vin

cent

&U

SD76

.07

USD

###

0.00

0000

USD

**0.

0000

00G

rena

dine

s1.

000

0/84

Suri

nam

eU

SD70

.01

MF

94.0

7IF

94.1

0M

F95

.07

USD

0.01

1718

USD

**0.

0117

851.

015

5/79

EXCHANGE RATE ARRANGEMENTS 385T

rini

dad

&T

obag

oU

SD76

.05

IF93

.04

USD

#0.

0047

82U

SD**

FF

0.00

4733

1.03

01/

83U

rugu

ayIF

83.0

3M

F92

.06*

USD

0.01

6728

USD

**D

M0.

0165

791.

049

0/84

Ven

ezue

laIF

89.0

3M

F93

.06*

USD

94.0

7M

F96

.04

USD

0.01

8171

USD

**F

FJY

0.01

7970

0.99

06/

78

Not

e.‘‘R

epor

ted’

’E

xcha

nge

Rat

eA

rran

gem

ents

:(1

)‘‘R

epor

ted’

’ex

chan

gera

tear

rang

emen

tsar

eex

pres

sed

byth

efo

llow

ing

nota

tion

s:U

SD5

pegg

edto

the

U.S

.do

llar;

FF

5pe

gged

toth

eF

renc

hfr

anc;

DM

5pe

gged

toth

ede

utsc

hem

ark;

AD

5pe

gged

toth

eA

ustr

alia

ndo

llar;

IR5

pegg

edto

the

Indi

anru

pee;

IL5

pegg

edto

the

Ital

ian

lire;

RR

5pe

gged

toth

eR

ussi

anru

ble;

SAR

5pe

gged

toth

eSo

uth

Afr

ican

rand

;SID

5pe

gged

toth

eSi

ngap

ore

dolla

r;SD

R5

pegg

edto

the

SDR

(Spe

cial

Dra

win

gR

ight

s);C

C5

pegg

edto

othe

rcu

rren

cyco

mpo

site

;LS

5fle

xibi

lity

limit

edvi

s-a-

vis

asi

ngle

curr

ency

(the

U.S

.dol

lar)

;CE

A5

coop

erat

ive

exch

ange

arra

ngem

ents

;AF

5ad

just

edac

cord

ing

toa

set

ofin

dica

tors

;MF

5m

anag

edflo

atin

g;IF

5in

depe

nden

tly

float

ing.

(2)

The

num

bers

follo

win

gth

eab

ove

nota

tion

sin

dica

teth

em

onth

orqu

arte

rw

hen

ach

ange

inex

chan

gera

tear

rang

emen

tsis

effe

ctiv

e.E

xcha

nge

Rat

eV

olat

ility

:(3

)T

heta

ble

show

sth

ena

me

ofth

ecu

rren

cyw

hich

yiel

dsth

esm

alle

stex

chan

gera

tevo

lati

lity

vis-

a-vi

sth

eco

untr

y’s

curr

ency

and

its

mag

nitu

de.

(4)

Tri

ple

poun

ds(#

##),

doub

lepo

unds

(##)

,and

asi

ngle

poun

d(#

)re

spec

tive

lyin

dica

teth

atvo

lati

lity

isle

ssth

an0.

0001

,les

sth

an0.

001,

and

less

than

0.01

.(5

)W

hen

calc

ulat

ing

exch

ange

rate

vola

tilit

y,da

taob

serv

atio

ns(l

ogfir

stdi

ffer

ence

sof

the

coun

try’

sno

min

alex

chan

gera

te)

whi

chha

veva

lues

grea

ter

than

0.01

are

dele

ted

from

the

sam

ple.

(6)

The

nam

esof

curr

enci

esar

ein

dica

ted

byth

efo

llow

ing

nota

tion

s:U

SD5

U.S

.do

llar;

DM

5de

utsc

hem

ark;

FF

5F

renc

hfr

anc;

JY5

Japa

nese

yen;

UK

P5

UK

poun

dst

erlin

g;E

CU

5E

urop

ean

Cur

renc

yU

nit

ofth

eE

MS;

SDR

5Sp

ecia

lD

raw

ing

Rig

hts

ofth

eIM

F;

AD

5A

ustr

alia

ndo

llar;

IR5

Indi

anru

pee;

NZ

D5

New

Zea

land

dolla

r;P

E5

Por

tugu

ese

escu

do;S

AR

5So

uth

Afr

ican

rand

;SID

5Si

ngap

ore

dolla

r;SP

5Sp

anis

hpe

seta

.(7

)A

hyph

en(-

)in

dica

tes

that

noex

chan

gera

teda

taar

eav

aila

ble.

Sum

mar

yof

Exc

hang

eR

ate

Reg

ress

ions

:(8

)T

hesu

mm

ary

show

sth

ere

sult

sof

regr

essi

ones

tim

atio

n,w

here

the

log

first

diff

eren

cein

aco

untr

y’s

nom

inal

exch

ange

rate

(mea

sure

dvi

s-a-

vis

the

Swis

sfr

anc)

isre

gres

sed

onth

elo

gfir

stdi

ffer

ence

sin

the

nom

inal

exch

ange

rate

sof

the

U.S

.dol

lar,

the

deut

sche

mar

k,th

eF

renc

hfr

anc,

the

Japa

nese

yen,

the

UK

poun

dst

erlin

g,th

eSD

R,a

ndth

eE

CU

asw

ell

asot

her

rele

vant

curr

enci

es(a

llm

easu

red

vis-

a-vi

sth

eSw

iss

fran

c).T

hech

oice

ofre

leva

ntcu

rren

cies

depe

nds

onec

onom

ic,h

isto

rica

l,co

loni

al,a

ndge

ogra

phic

alco

nsid

erat

ions

.(9

)T

hefo

llow

ing

abbr

evia

tion

sin

dica

teth

ena

mes

ofcu

rren

cies

used

for

regr

essi

on:

USD

5U

.S.

dolla

r;D

M5

deut

sche

mar

k;F

F5

Fre

nch

fran

c;U

KP

5U

Kpo

und

ster

ling;

JY5

Japa

nese

yen;

EC

U5

Eur

opea

ncu

rren

cyun

it;

SDR

5sp

ecia

ldr

awin

gri

ghts

;A

D5

Aus

tral

ian

dolla

r;IR

5In

dian

rupe

e;N

ZD

5N

ewZ

eala

nddo

llar;

PE

5P

ortu

gues

ees

cudo

;SA

F5

Sout

hA

fric

anra

nd;S

ID5

Sing

apor

edo

llar;

SP5

Span

ish

pese

ta.

(10)

Whe

nes

tim

atin

gre

gres

sion

equa

tion

s,th

ose

data

obse

rvat

ions

that

have

valu

esgr

eate

rth

an0.

01fo

rth

ele

ft-h

and

–sid

eva

riab

le(t

helo

gfir

stdi

ffer

ence

ina

coun

try’

sno

min

alex

chan

gera

te)

are

dele

ted

from

the

sam

ple.

The

nota

tion

s‘‘e

xcl’’

and

‘‘inc

l’’re

spec

tive

lyin

dica

teth

enu

mbe

rsof

obse

rvat

ions

excl

uded

and

incl

uded

.(1

1)F

orea

chco

untr

y,a

regr

essi

oneq

uati

onw

ith

the

high

est

expl

anat

ory

pow

er,

mea

sure

dby

the

adju

sted

R2

and

reas

onab

leco

effic

ient

esti

mat

es,

isch

osen

and

repo

rted

.In

part

icul

ar,t

hebe

stre

gres

sion

equa

tion

sar

ech

osen

soth

atth

ees

tim

ated

coef

ficie

nts

are

alw

ays

nonn

egat

ive

and

stat

isti

cally

sign

ifica

ntat

the

10%

leve

l.(1

2)D

oubl

eas

teri

sks

(**)

,asi

ngle

aste

risk

(*),

and

noas

teri

skin

dica

tere

spec

tive

lyth

atth

eco

effic

ient

sar

esi

gnifi

cant

atth

e1%

,5%

,and

10%

leve

ls.I

fth

eco

effic

ient

issi

gnifi

cant

atth

e10

%le

vel,

only

the

nam

eof

the

curr

ency

islis

ted

wit

hout

show

ing

the

esti

mat

edco

effic

ient

.(1

3)A

hyph

en(-

)in

dica

tes

that

the

num

ber

ofda

taob

serv

atio

nsis

too

smal

lto

esti

mat

ea

mea

ning

ful

regr

essi

oneq

uati

on.

Sour

ce.

Inte

rnat

iona

lM

onet

ary

Fun

d,In

tern

atio

nal

Fin

anci

alSt

atis

tics,

vari

ous

issu

es.


REFERENCES

Alogoskoufis, G., and Portes, R. (1997). The euro, the dollar and the international monetarysystem, in ‘‘EMU and the International Monetary System’’ (P. R. Masson, T. H. Krueger,and B. G. Turtleboom, Eds.), pp. 58–78, International Monetary Fund, Washington, DC.

Barth, R. C., and Wong, C.-H., Eds. (1994). ‘‘Approaches to Exchange Rate Policy Choicesfor Developing and Transition Economies,’’ IMF Institute, Washington, DC.

Bergsten, C. F. (1997). The impact of the euro on exchange rates and international policycooperation, in ‘‘EMU and the International Monetary System’’ (P. R. Masson, T. H.Krueger, and B. G. Turtleboom, Eds.), pp. 17–48, International Monetary Fund, Washing-ton, DC.

Cairncross, A., and Eichengreen, B. (1983). ‘‘Sterling in Decline,’’ Blackwell, Oxford.

Cohen, B. J. (1971). ‘‘The Future of Sterling as an International Currency,’’ MacMillan,London/Basingstoke.

Collins, S. M. (1996). On becoming more flexible: Exchange rate regimes in Latin Americaand the Caribbean. J. Devel. Econ. 51, 117–138.

Dooley, M. P., Lizondo, J. S., and Mathieson, D. J. (1989). The currency composition offoreign exchange reserves. IMF Staff Papers 36, 385–434.

Eichengreen, B. (1998). The Euro as a Reserve Currency. J. Japan. Int. Econ. 12, 483–506.

Eichengreen, B., and Frankel, J. A. (1996). The SDR, reserve currencies, and the future ofthe international monetary system, in ‘‘The Future of the SDR in Light of Changes inthe International Financial System’’ (M. Mussa, J. M. Boughton, and P. Isard, Eds.),pp. 337–378. International Monetary Fund, Washington, DC.

Frankel, J. A., and Wei, S.-J. (1993). Is there a currency bloc in the Pacific?, in ‘‘ExchangeRates, International Trade and Monetary Policy’’ (A. Blundell-Wingnall and S. Grenville,Eds.), pp. 275–307, Reserve Bank of Australia, Sydney.

Frankel, J. A., and Wei, S.-J. (1994). Yen bloc or dollar bloc?: Exchange rate policies of theEast Asian economies, in ‘‘Macroeconomic Linkage: Savings, Exchange Rates, andCapital Flows’’ (T. Ito and A. Krueger, Eds.), pp. 295–329, Univ. of Chicago Press,Chicago.

Frankel, J. A., and Wei, S.-J. (1995). Emerging currency blocks, in ‘‘The International MonetarySystem: Its Institutions and Its Future’’ (H. Genberg, Ed.), pp. 111–170, Springer-Verlag, Berlin.

Garber, P. (1996). The use of the yen as a reserve currency. Monetary and Economic Studies,Bank of Japan, 14, 1–21.

Hamada, K., and Horiuchi, A. (1987). Monetary, financial and real effects of yen international-ization, in ‘‘Real–Financial Linkages among Open Economies’’ (S. W. Arndt and J. D.Richardson, Eds.), pp. 167–191, MIT Press, Cambridge, MA.

International Monetary Fund. (1997). ‘‘World Economic Outlook,’’ Washington DC.

Ito, T. (1993). The yen and the international monetary system, in ‘‘Pacific Dynamism and theInternational Monetary System,’’ (C. F. Bergsten and M. Noland, Eds.), pp. 299–322,Institute for International Economics, Washington, DC.

Japan Committee for Pacific Economic Outlook. (1997). ‘‘PEO/Structure Issues: ExchangeRate Fluctuations and Macroeconomic Management,’’ PECC International Secretariat,Singapore.

Kawai, M. (1996). The Japanese yen as an international currency: Performance and prospects,in ‘‘Organization, Performance and Equity: Perspectives on the Japanese Economy’’


(Ryuzo Sato, Rama V. Ramachandran, and Hajime Hori, Eds.), pp. 305–355, KluwerAcademic, Boston/London/Dordrecht.

Kawai, M., and Akiyama, S. (1998). ‘‘The Role of Nominal Anchor Currencies in ExchangeRate Arrangements with Appendices.’’ Discussion Paper Series No. F-78 (October),Institute of Social Science, University of Tokyo.

Masson, P. R., and Turtleboom, B. (1997). Characteristics of the euro, the demand for reserves,and policy coordination under EMU, in ‘‘EMU and the International Monetary System’’(P. R. Masson, T. H. Krueger, and B. G. Turtleboom, Eds.), pp. 194–224, InternationalMonetary Fund, Washington, DC.

McCauley, R. N. (1997). ‘‘The Euro and the Dollar.’’ Working Paper 50, Bank for InternationalSettlements (Basle).

Tavlas, G. S., and Ozeki, Y. (1992). ‘‘The Internationalization of Currencies: An Appraisalof the Japanese Yen,’’ Occasional Paper, 90, International Monetary Fund.

the role of nominal anchor currencies in exchange rate arrangements

Documents