ASEAN Exchange Rates: Policies and Trade Effects 9789814345606

Table of contents :
Foreword
Preface
Contents
Tables
Figures
I. INTRODUCTION
II. EXCHANGE RATE POLICIES OF ASEAN COUNTRIES
III. EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES
IV. EFFECTS OF REAL EXCHANGE RATE CHANGES ON ASEAN'S PRIMARY EXPORTS
V. SUMMARY AND CONCLUSIONS
Appendices
Bibliography

Citation preview

ASEAN ExclliiiiiJe

lliltes

The Institute of Southeast Asian Studie< was established as an autonomous organization in May 1968. It is a regi

Vl

m

TABLE 4

~

Decomposition of the Variability of Real Effective Exchange Rates in ASEAN Countries. 19n-79: A Summary

~

Indonesia

Year

1972 1973 1974 1975 1976 1977 1978 1979

E E I

E E 0 E E -

>
0 shows risk aversion "- < 0 shows risk preference "- = 0 shows risk neutrality).

Two-Country Model: One Importing and One Exporting

The profit function of the importing firm is a random variable which can be written as: (3)

EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES

where i

imported input-output coefficient

39

= .!L

Q unit domestic cost (labour plus material) of production foreign price of imports spot exchange rate (price of foreign currency in terms of domestic currency) for next period.

uc

=

Then£(1r) and V(1r)

PQ(P) - UC.Q- P* ij1Q

(4)

(P*iQJ2a]1

(5)

Substituting values from (4) and (5) into (2) we get = PQ(P) - UC.Q- P* ij1Q- A.(P*iQ)a1I

U

(6)

The first order condition for utility maximization is ou oQ

= P + Q oP &Q-

uc - P*i J 1

-

>.. (P*i)a11

=o

(7)

But from equation (1), oP!oQ = 1/a. Substituting this value and the value for P from (1) in (7) and solving for q = iQ we get,

~ (a.UC + {3.PD + f'.Y + o.CU) +

q =

(8)

Equation (8) is the import demand function for the firm. By aggregating over n identical firms we get the competitive importers demand function, q*

=

nq

=

;

(a.UC + {3.PD + 'Y· Y + o:CU) + (9)

40

ASEAN EXCHANGE RATES

Taking partial derivatives,

oq*

oit 0 * and _!!__ 0 C1jl

= =

nw"2P* 2

< 0

>..nw"2 P* < 0 for risk averse firm = 0 for neutral firm 2 > 0 for risk-loving firm.

(10)

(11)

The LDCs under discussion are small open economies and so the import supply functions they face are highly elastic. In fact, import supply functions could be assumed to be infinitely elastic without committing a serious error. Hence, either an expectation of depreciation or an expectation of increase in variability of exchange rates (bilateral) in the next period, by a risk averse firm causes the import demand function to shift back and the total volume of imports to decline.

Three-Country Model: One Importing Country and Two Exporting Countries.

In the previous model we assumed that importers could import from only one country. Now let us introduce multilateral trading relationships by assuming that there are two exporting countries from which importation is possible. Let Q; and P; for i = 2,3 be the quantities and prices respectively of imports from country 2 and 3; fii be the spot exchange rate (price of country j's currency in terms of currency l); and all other assumptions of the earlier two-country model remain the same. The profit function in this new model can be written as

Multiplying and dividing each of the last two terms on the right hand side of (12) by M1. = P2qJ1 2 + P3qJ}13 which is equal to the total value of imports, we get (13)

EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES

41

Finally, by multiplying and dividing the first term in parenthesis of equation (13) by P 2 and the last term by jl 3 and letting {3; = P;qJ1 ilM1. fori = 2,3, be the share of imports from country 2 and 3, respectively, we get

=

QP(Q) -

(14)

M1.

UC.Q -

The last term in parentheses in equation (14) is the expected importweighted exchange rate (price of trading partners currencies in terms of domestic currency) for the next period using aggregate import weight, £11 . Also international competition ensures P3 = P2/j2 3 • Substituting this in the definition of M1. and then in (14), we get, (15)

Since the only random variable in the profit function is the next period's import-weighted exchange rate, E(7r)

=

QP(Q) -

V(7r)

=

(P2iQ) 2 (f' 2

and

o V(1r) = 2 0

UC.Q -

P2iQf12E(Et 1)

Pa;;11

(16) (17)

(Pli Q)2 (f'2)2

>0

(18)

C1£11

Equation (18) indicates that increased variability of the next period's effective exchange rate increases the variability of profits. Substituting the values for E(1r) and V(1r) in (2) and solving the first order condition as in the two-country model, and aggregating over n firms, it can be shown that q*

=

ni ({3PD 2

+

'Y Y

+

oCU

+

aUC)

+ (19)

42

ASEAN EXCHANGE RATES

Taking partial derivatives,

oq*

oE(E11)

oq* and_...___ Oa£/

ncxPPJ12 2

(20)

< 0

< 0 for risk averter

=

0 for risk neutral

> 0 for risk-lover

(21)

Equations (20) and (21) show that for all types of risk behaviour expected devaluation has an adverse effect on import demands and also, for a risk averse firm, expected variability in the next period's import-weighted exchange rate causes import demands to decline.

SPECIFICATION OF AGGREGATE IMPORT DEMAND MODELS

Traditional aggregate import demand functions view imports as being a function of real income and relative prices of goods. In actual econometric usage several modifications are made in the inclusion of additional variables; definition of variables; incluSion of lagged relationships; and inclusion of simultaneous relationship. The first inclusion that has to be made in specifying an aggregate import demand function for LDCs is an explanatory variable as a proxy for quantitative restrictions that retard import flows. Although such restrictions are generally non-quantifiable, assuming that the government's policy reaction function relating to the imposition of controls varies inversely with the capacity to import, several proxies that measure capacity to import can be used. Foreign exchange reserves (both in nominal and real terms) have been used by UNCTAD (1975); lagged real export receipts have been used by Turnovsky (1968) and UNCTAD (1975); and net overseas assets have been used by Khan (1974) and Otani and Park (1976). The proxy used in this study is real export earnings (nominal export earnings deflated by import prices) lagged one period. The lag is introduced because foreign exchange must be available before imports can be ordered when exchange controls are in effect. Second, it has been observed that in LDCs the use of a relative price term in an aggregate import demand function may be inappropriate for several

EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES

43

reasons. 4 However, recent econometric studies of several LDCs by Khan, Marwah (1972), and Sharma (1975) have found that the relative price is a major explanatory variable. The reason advanced for such a finding is that, at early stages of import substitution, the demand for and price of imports may in fact increase because economies of scale have not been realized. In view of these findings, we include a relative price term in our import demand equations. Finally, in consonance with the theoretical analysis of the earlier section, two additional explanatory variables (one representing expected exchange rate change in the next period and the other a proxy for exchange risk) are included in the specification of the basic import demand model. The expected exchange rate variable indicates that if importers expect their currency to appreciate (depreciate) in the next period they will place more (less) orders this period. Exchange rate risk arises because the exchange rate when payments for imports have to be made may be different from what it is expected to be when orders are placed. Importers when placing orders have to form expectations about exchange risk (about how the observed exchange rate may vary in the next quarter compared to what it is currently expected to be when orders are placed). Also, in examining import relationship at a disaggregated level, it may be desirable to use some other activity variable besides income. In an aggregate study such as the present one, the level of GNP following Khan appears appropriate. To the extent that importers do not adjust fully to their demand curve, adjustment lags longer than the assumed period need to be considered, otherwise the estimates would have a specification bias. Lagged response of imports to changes in the explanatory variables could be studied by using the partial adjustment or distributed lag models. Since the objective of the study is not to estimate complicated lag responses which may vary across countries but to explore the effects of exchange rate variables on import flows, a more modest lagged relationship which takes into account the time lag between the placement of import orders and their receipt, is assumed. Such a lag is estimated by Hooper and Kohlhagen and Magee to be three months for industrial countries and 4.

First, there may be no domestic substitutes for imports. Second, the trade and exchange restrictions prevent imports from being competitive in the domestic economy. Third, many of the imports of LDCs may be due to tied aid and loan programmes in which case the relative price term is not relevant in placing orders.

44

ASEAN EXCHANGE RATES

perhaps longer for LDCs. However, for lack of better estimates the present study also assumes an order-delivery lag of one quarter. The lag is introduced by leading the dependent variable by one period. It is also assumed that importers' expectations about the future (next period's) spot nominal import-weighted exchange rate is fully realized, so that the actual spot rate of the next period is the currently expected rate. Such an assumption does not imply lack of uncertainty, because future spot rates are uncertain when expected. The basic linear import demand model to be estimated for the four countries is

RM,.,

=

ao + a,RP, + a2RY, + a3RX,_, + a4EE .. , + a.sERP, + a6Q2 + a1Q3 + as Q4 + U, (22)

where RMd

=

demand for total imports of goods and services, computed by dividing nominal imports by the import price index

RP

=

RY

=

RX

=

EE

=

ERP ERP1

=

relative price of imports, computed by dividing the import price index in domestic currency by the wholesale price index with 1970 = 100 real GNP, computed by dividing nominal GNP by the consumer price index real export earnings, calculated by dividing nominal exports by the import price index the quarterly average of the nominal effective exchange rate of chapter II (price of domestic currency in terms of importing partners' currencies) the various proxies used for exchange rate risk

ERP2

ERP3

standard deviation of the three intra-quarterly observations of three-monthly proportional change in nominal effective exchange rate = Gini's mean difference measure of dispersion of three intra-quarterly observations of three-monthly proportional change in nominal effective exchange rate = standard deviation of the three intra-quarterly observations of three-monthly proportional changes in real effective exchange rate (which are deviations from purchasing power parity at a multilateral level) =

EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES

Qi t

45

quarterly dummies with Qi = for quarter i = 2,3,4 = 0 otherwise = time period.

=

The expected signs of the various explanatory variables are:

Equation (22) is specified as a single equation model because it is assumed that the import supply function is infinitely (or highly) elastic with respect to price so that the price of imports can be treated as exogenous. If this were not the case, the neglect of the relationship between price and quantity of imports would introduce a bias in the ordinary least squares (OLS) estimate of the equation. All of the four countries under discussion conform well to the economists' concept of small open economies as they are price takers in the world economy; the simultaneous equation bias can therefore be neglected.

ESTIMATION RESULTS

Three variants of the basic model corresponding to different assumptions as to how importers form expectations about future variability of exchange rates are estimated for the four countries. The first variant (Model I) assumes that expectations of exchange rate risk by importers is static. They expect the variability of the relevant exchange rate to be the same in the next quarter as it was in the last quarter. This type of assumption is unrealistic because it allows no mechanism for an adjustment of expectations by importers, but is used as a first approximation. The second variant (Model II) assumes that the expectation about future variability of exchange rate is fully realized and so the actual variability next quarter is the expected variability in the present quarter. This is an extreme form of the rational expectations hypothesis. Finally, the third variant (Model Ill) assumes that the expectations of future variability are based upon their experience during the current and last three quarters. All of the three variants of the basic import demand model are estimated for South Korea, the Philippines, Taiwan, and Thailand using quarterly data (from IMF's International Financial Statistics) by the

46

ASEAN EXCHANGE RATES

OLS method. 5 The small country assumption removes the simultaneous equation bias. The use of a proxy variable for exchange rate risk removes some of the specification bias. All other omitted variables are represented by a randomly distributed error term which in turn is normally distributed with zero mean, is homoskedastic and serially independent. With these assumptions, the OLS method yields unbiased and efficient estimates. In addition, whenever auto-correlation is detected by the use of the Durbin-Watson d test, the equation is reestimated by using the Cochrane-Orcutt iterative method. The sample period for the study is from 1960 to 1976 for the Philippines; 1961 to 1976 for Thailand; 1963 to 1976 for Taiwan; and 1963 to the second quarter of 1977 for South Korea. In order to take into account any shift in the behavioural relationships that might have occurred during the Bretton Woods and the generalized floating periods, particularly with respect to the expected exchange rate and exchange rate risk variables, two separate regressions for the two periods are fitted for all countries. The results of this exercise were generally disappointing with none of the explanatory variables being significant except for Taiwan; thus, for other countries only the results of the fitting over the entire sample period are analysed. Also, in the case of Taiwan, Model I gave a poor fit. The results of the estimation of the various models are presented in tables C.1 to C.5 of Appendix C. Under certain assumptions a reasonable criterion of choice that can be used to compare the relative performance of the various proxies of exchange risk and the variants of the basic model, is the comparison of R 2 values. Three conditions need to be fulfilled to make this criterion reasonable. First, the two regressions should have the same dependent variable. Second, the number of explanatory variables in each equation must be the same. Finally, the number of observations in each regression must be the same. Such a criterion can be used, as Rao and Miller (1971) argue, to determine which of the competing definitions of an independent variable is empirically preferable and to determine the appropriate lag period. 6 We use the R 2 criterion to identify the hypothesis about exchange rate risk formation that performed the "best"; the empirically preferred proxy of exchange rate risk; and the "best" equation for each country. 5.

GNP data were not available on a quarterly basis except for South Korea and so were obtained by a reasonable interpolation method (see Appendix B).

6.

Refer to Friedman and Meiselman (1963) for such uses of the R 2 criterion.

EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES

47

Comparison of R 2 values of the different variants of the basic model for a given exchange rate risk proxy across the three different proxies reveals that in a total of nine cases where R 2 values can be compared, the fully realized expectations variant performed "better" than the static expectations variant in seven cases and "better" than the moving average variant in eight cases. 7 Similarly, a comparison of R 2 values between the different exchange rate risk proxies within a given expectations model across the three different variants of the basic model reveals that in a total of thirteen possible cases the third exchange rate risk proxy (ERP3) gave the "best" result. 8 The R 2 criterion enables comparison of the results of the variants and versions of the basic model for each country. The "best" equations for the countries are reproduced below with t values in parentheses. South Korea (1963 I -

RM,.t

=

1977 II)

.103 (.285)

.002ERP3,+1 (- 2.216) Rl

+

= .931

.606RP, (- 2.424)

+

.145RY, (3.847)

+

.634RX,_ 1 (4.438)

1.039Q2 (4.273)

+

.861Q3 (4.692)

+

.906Q4 (4.096)

d

= 1.452

SE

= .292

All of the explanatory variables have the expected sign and are significant at the 5% level. The EE variable consistently had a negative sign and so was dropped from the regressions. The price and income elasticities computed at the mean values are - .4192 and .6188 respectively. The exchange rate risk proxy is also of the theoretically expected sign and is significant. The elasticity of the risk term, however, is only - .0221.

7.

The nine possible cases in the comparison of the fully realized and static expectation variant are provided by the cases of Thailand, South Korea, and the Philippines. The static expectations model performed poorly in the case of Taiwan and so is not analysed. The nine possible cases in the comparison of the fully realized and moving average model are provided by the cases of Thailand, South Korea, and Taiwan (in the generalized floating period). The R' values of these latter variants for the Philippines and Taiwan (in the pegged period) are not comparable.

8.

The thirteen possible cases are the comparison of the results of the three variants of the model for South Korea, Thailand, and the Philippines and the results of the two variants estimated for Taiwan both in the pegged and floating periods.

48

ASEAN EXCHANGE RATES

Since the mean value of ERP3 has increased almost twice 9 in the generalized floating period as compared to the pegged period, the equation indicates that exchange rate risk has adversely affected the import demand of South Korea. Philippines (1960 I -

1976 IV)

log (RMt+t) = -

1.806 ( -1.825)

+

-

.255 log (RP,) (-1.158)

(1.86)

+

0.41 log (ERP3,+t) ( -1.77) .024Q4 (.521)

R2

= .736

d

1.007log (RY,) (6.677)

+ .271 log (EEt+t)

.323 log (RX.-t) (2.506)

+

+

+

.067Q2 (1.488)

= 1.81

SE

.117Q3 (2.622)

= .126

In this equation the relative price term is not significant. The real income and real export earnings variables are significant at the 50Jo level. The exchange rate risk variable has a negative sign and is significant at the 10% level. Thailand (1969 I -

RM,....

=

1976 IV)

.417RP, (-6.56)

.669

(2.427)

(- 2.813)

+

.476RX,_ 1 (4.018) .005Q2 (- .229)

.002Q4 (- .101)

.0563Q3 ( -2.269)

9.

.973RY,

(7.27)

.002ERP3,

.001EEt+t

(- .348)

Rl = .910

+

d

=

1.53

SE = .061

During 1960 l-1971 II, the mean value of ERP3 was 11.56 and during 1973 II-1977 II it was 21.17.

EFFECTS OF EXCHANGE RATE VARIABILITY ON IMPORT VOLUMES

49

All the variables have the expected sign, except EEt+l but this variable is not significant. The equation also indicates that exchange rate risk has been significant with the expected sign and its elasticity at the mean value is - .0288. The price and income elasticities computed at the mean values are - .0835 and .5536 respectively. Since the mean value of the exchange rate risk proxy ERP3 has increased under generalized floating, 10 the equation indicates that exchange rate risk has adversely affected the import demand of Thailand. Taiwan (1963 I -

RMt+l

=

.092RP,

.474 (.592)

.283RY, (4.867)

.005EEt+l

.00004ERP2t+l (- .041)

.012Q3 (2.088)

R2

=

=

( -1.524)

+

(- .564)

+

(1973 II -

RMt+l

1971 II)

.935

+ d

=

+ .346RX.-l (2.229)

+

.019Q2 (3.321)

.031Q4 (5.207)

1.9

SE

=

.011

1976 IV)

.160 (.345)

.310RP,

.314RY,

(- 3.797)

( -1.91)

+ .006EEt+l

.002ERP2t+l (-2.701)

(1.848)

+

.014Q3 (.815)

R2

=

.932

+ d

=

+ +

.763RXt-t (4.589) .027Q2 (1.686)

.011Q4 (.68)

2.48

SE

=

.017

The above equations indicate that the relative price term and the exchange rate risk proxy, though not significant during the pegged period, are significant in the flexible period. 11 During the generalized floating 10.

The mean value of ERP3 from 1961 1-197111 was 18.28 and during 1973 11-19761V it was 21.25.

II.

The mean value of ERP2during the period 19631-197111 was !.52 and during 1973 ll-19761Y was 13.35.

50

ASEAN EXCHANGE RATES

period, the income variable is negatively significant at the lOOJo level. An explanation of this could be that the imported goods have a close substitute and the supply elasticity of these goods is greater than demand elasticity of the import (Magee 1974). The price, income, and exchange rate risk elasticity of imports are -1.2075, - .819, and -.0683 respectively .

•

SUMMARY AND CONCLUSIONS

This chapter has analysed the alleged adverse effect of exchange rate variability on imports by considering the cases of South Korea, the Philippines, Taiwan, and Thailand. Traders in these LDCs are exposed to exchange rate risk. A theoretical framework which outlines the effect of exchange rate variability on variability of profits and trading decisions of an importing firm was used to show that an expectation of a depreciation of the domestic currency and increased variability of exchange rates will cause the importer to place fewer orders. The ''best'' equations and several others for each of the four countries indicate deleterious effect of exchange rate risk on import volumes. Since exchange rate risk measured by the mean values of the different exchange rate risk proxies has increased substantially, the present system of generalized floating has become worse for the LDCs. This result, however, has to be interpreted with care since the elasticities of imports with respect to exchange rate risk are small. It must also be considered that the exchange rate risk proxy, although with a negative sign in thirtytwo equations, had a significantly negative sign in only ten out of the thirty-nine equations estimated. The study also finds that, as expected, the third proxy of exchange rate risk (the standard deviation of quarterly deviations from purchasing power parity at a multilateral level or real exchange rate risk) performs the "best" in terms of indicating the alleged anti-trade bias. Also, the fully realized expectation hypothesis about exchange rate variability gives the best result. Finally, the present study finds that the relative price term performed well as an explanatory variable in the import demand models.

IV Effects of Real Exchange Rate Changes on ASEAN's Primary Exports

INTRODUCTION

In chapter III, a multiple regression approach was used to study the effects of increased exchange rate risk under generalized floating on import volumes. This chapter simulates the medium-term effects of historical multilateral exchange rate and price changes on the prices, volumes, and values of the major primary exports of the ASEAN countries. The method used is a modified version of the Ridler and Yandle commodity by commodity method and it involves simulation of a world trade model in which exchange rate and price changes are exogenous. The method uses a partial equilibrium model of world trade in which shifts in the world import demand and export supply functions are defined as being equal to a weighted average of percentage changes in importers' and exporters' exchange rates with respect to a numeraire currency adjusted for domestic inflation rates. As the weights are ratios of world import demand and export supply (price) elasticities, estimates of these parameters enable the computation of the percentage change in the world price of the commodity in terms of the numeraire currency. Once the effects on world price are calculated, the effects on volume and value of world trade in the commodity are also easily derived. Estimation of a country's export supply elasticity enables the compilation of the effects on volume and value of that country's exports of that particular commodity. Finally, aggregation of the effects over all commodities exported gives the total effect on the country's exports. Although the modified Ridler and Yandle method is a variant of the traditional elasticity model of trade, it is an improvement in several ways. First, unlike the traditional elasticity analysis which viewed exports and imports each as a single homogeneous product for which single trade

52

ASEAN EXCHANGE RATES

elasticities could be used, the modified Ridler and Yandle method allows for differential effects of exchange rate and price changes on different commodities according to the geographical trading pattern of the commodity and different trade elasticities between countries and commodities. This is a considerable advantage given the recent findings of Clark (1974), lsard (1974), Belanger (1976), and Bautista (1977). Second, rather than simulating the effects of a single discrete exchange rate change on an exporting or importing country, the present method enables the study of the effects of multilateral exchange rate changes as in the Smithsonian realignment or in the current generalized float. Finally, unlike in the early usage of the Ridler and Yandle method by Clark (1974) and Belanger (1976) in the present formulation, it is assumed that the decisions of exporters and importers are affected by changes in the real exchange rate rather than the nominal rate. This takes into account that in rapidly inflating countries, competitive advantage gained by depreciation may be partially or totally offset. The Ridler and Yandle method has several limitations. First, it assumes that prices alone clear the commodity market. This may not be true if stock-piling or changes in order backlogs are allowed. Unfortunately only a few models that account for stock-piling exist for primary commodities. Second, the method assumes that the commodity is traded in perfectly competitive world markets. Only under such an assumption. will a country's supply and demand function respond automatically to exchange rate and price changes. This assumption is violated in the case of a dominant world supplier with monopoly power in world markets and a supplier with a large domestic market. Finally, it assumes an absence of non-price incentive in the choice of trading partners. This means that once the world price has been determined there is no economic incentive other than on grounds of price alone to prefer one source of supply to another. All of the above assumptions hold approximately for primary commodities and some intermediate goods because they are homogenous and are traded in organized international markets. Arbitrage tends to prevent the prices of traded goods in different countries from differing by more than the exchange rate, freight, and interest rates. Manufactured goods, however, are characterized by a substantial amount of product differentiation and are not traded in organized markets; hence prices of these types of commodities are more closely related to cost in the individual producing countries. The modified Ridler and Yandle method can therefore be applied only to exports and imports of most primary products

EFFECTS OF REAL EXCHANGE RATE CHANGES ON EXPORTS

53

and intermediate goods. In the case of manufactured goods, other methods like those developed by Clark (1974), Artus (1974), and Belanger (1976) will have to be used. 1 A final problem with the modified Ridler and Yandle method is that its performance cannot be evaluated by comparing the results predicted by the model with actual data. This is because the model is partial and hence cannot account for other factors (e.g., world oil prices) besides exchange rate and price changes. Also, the model simulates the medium term effects on exports and imports without predicting the time lags. Actual changes in trade aggregates are observed only in a single year, yet the change in that year is a result of exchange rate and price changes occurring in previous years as well as in that year. Although some type of a lag structure could be easily introduced in the model, such an attempt extends beyond our objective. Although the modified Ridler and Yandle method has severe limitations it is the only existing model of international trade that can be used to simulate the effects of multilateral exchange rate changes on trade aggregates at a commodity level. The major objective of this chapter is to use the modified Ridler and Yandle method to simulate the medium term effects of historical exchange rate and price changes on the major primary exports of ASEAN. Such a study enables an examination of how world market conditions for the commodities have changed under the present system of generalized floating. Nine primary commodities or groups of commodities are considered- natural rubber, palm oil, tin metal, copra and coconut oil, rice, sugar, timber, copper, and maize. To enable a comparison of the cumulative effects of historical exchange rate and price changes during the three periods of the international monetary system, simulations are performed from July 1967 to July 1971 (the Bretton Woods period); from August 1971 to March 1973 (the unsettled period); and April 1973 to December 1979 (the generalized floating period). The effects of historical exchange rate and price changes are also simulated on an annual basis for the period after 1971.

1. Clark discusses the price-setting behaviour of an exporter or importer of manufacturing goods in terms of mark-up pricing where the mark-up is a function of capital cost, domestic and foreign capacity utilization, and the price of foreign goods that compete with the exported goods. Exchange rate affects the last of these variables. Artus discusses the price-setting behaviour in terms of profit maximization. Belanger takes the export prices generated by IMF's MERM model as being the effects of multilateral exchange rate changes on manufactured imports of LDCs.

54

ASEAN EXCHANGE RATES

This chapter outlines the analytical foundations of the modified Ridler and Yandle method; it discusses the importance of primary exports in four of the five ASEAN countries and analyses the results of the simulation. The findings are summarized briefly and conclusions drawn from them.

THE COMMODITY BY COMMODITY METHOD

Consider the total import demand (M) and total export supply (X) for a particular commodity. Abstracting from all other factors affecting demand and supply except relative prices, world trade in that particular commodity can be represented by the following model:

= D(P,M) X = S(P/) M = X= Q

M

andPxTx

Dt < 0

(1)

> 0

(2)

S1

- PMTM = pw

(3)

(4)

where M = volume of world imports X = '\1~\~m.~ ~\ ~~'t\~ ~~'\:J~'t\~ PM = world price of the commodity in importer's currency px = world p:-:;::c cf the commodity in exporter's currency pw = world price of the commodity in numeraire currency T = the exch;

~

Copra and CocoRut Oil

ttl

%Change in

%Change in

%Change in

%Change in

%Change in

Volume

Vahfe

Price

Volume

Value

July 1967 to July 1971

8Y2

Y2to1Yl

9to 9'12

10Y2

1 to 7Y2

llY2 to 18

July 1971 to Marolt 1973

9Y2

3Y2 to 7

l3to Wh

9

2Y2 to 16Y2

II Y2 to 25Y2

Aprillfflto Deoember 1'917

37Y2

-l7Y2 to - 34Y2

zo.th to 3

45

-10'12 to -71 Y2

34Y2 to -261h

April1973 to DeecaDber 1919

7SY2

-26Y2 to -53

52 to 2SY2

79

- 19Y2 to - 130Y2

59Yl to -51 Y2

1971

4Y2

-5to -10

- Y2 to -5

9

-2Y2 to -l5Y2

1972

3¥.!

4\ll to 8\ll

8 to 12'11

-\ll

2 to 14

I Y2 to 13¥.!

1973

12

-6Y2 to -12¥2

6to -1

14¥.!

-4to -.26

IO'h to - 11 Y2 tOY.! to -6¥.!

6~

to -6¥.!

1'974

7¥2

-6Y2 to -13Y2

1 to -6

14

-3 to -20¥2

1975

2Y2

3to5\ll

5\ll aoB'h

-\ll

I Y2 to 8¥.!

I to 8

1916

4

-lto-2¥2

3 to Y2

4Y2

-I to -5

4to - Y2

1977

7Y2

-lto-2\ll

6Y2 to

7

-lto-6Y2

6to Y2

1978

6\ll

-Y2to-1

6Y2 to 6

8

0

8

1979

6Y2

-7to -BY2

-Oto -7

UY2

- 3Y2 to - 24Yl

8to -13

s

~

>
-Vl m >-z m X

(")

::r

TABLE A.2

>-z 0

m

Indonesia: Decomposition of the Sum of Squares of Trend Errors of the Real Effective Exchange Rate, 1972-78 (100,000 x original units)

:;.::

~

m Vl

Year

Sum of squares

Domestic component

Foreign component

Interaction term

1972 1973 1974 1975 1976 1977 1978 1979

784.80 525.87 747.49 579.26 265.76 41.99 5075.23 1871.02

946.15 673.43 1039.01 397.64 384.42 77.57 4978.92 2149.49

81.57 408.69 246.59 180.69 22.78 98.57 244.90 238.71

-242.92 -556.24 -538.12 0.93 -141.44 -134.15 -148.59 -517.17

TABLE A.3 Malaysia: Decomposition of the Variability of Real Effective Exchange Rates. 1972-79 (1,000,000 x original units)

Year

Variability of real effective exchange rate = var (log RER)

Domestic component = var (log D)

Foreign component = var (log F)

= -2 cov (log F. log D)

1972 1973 1974 1975 1976 1977 1978 1979

12.50 319.31 38.08 384.42 16.69 56.96 56.74 46.96

15.05 717.70 192.65 1188.18 11.09 105.06 209.96 75.34

14.29 122.32 214.62 226.80 19.54 214.04 190.16 61.78

- 16.84 - 520.72 - 369.20 -1030.56 - 13.94 - 262.14 - 343.38 - 90.16

Interaction term

> '"0 '"0 tTl

z

x 0

>

Oo

'I

gg >-

gj

~

tTl

X

0

X

z>-

TABLE A.4

Cl

tTl

Malaysia: Decomposition of the Sum of Squares of Trend Errors of the Real Effective Exchange Rate. 1972-78 (100,000 x original units)

~

~ tTl rJl

Year

Sum of squares

Domestic component

Foreign component

Interaction term

1972 1973 1974 1975 1976 1977 1978

17.59 431.32 170.56 318.25 25.76 57.36 124.73

100.08 990.37 297.53 1119.55 14.55 117.25 291.75

79.32 260.76 289.90 282.02 22.78 191.90 242.99

- 161.32 - 819.81 - 416.86 -1083.32 - 11.57 - 251.79 - 410.01

TABLE A.5 Philippines: Decomposition of the Variability of Real Effective Exchange Rates, 1972-79 (1,000,000 x original units)

Year

Variability of real effective exchange rate = var (log RER)

Domestic component = var (log D)

1972 1973 1974 1975 1976 1977 1978 1979

124.68 1210.56 323.69 241.20 50.90 118.04 119.98 370.62

120.34 1468.42 533.61 542.89 89.30 48.72 37.95 226.50

Foreign component = var (log F) 3.8

64.64 233.48 68.89 13.54 251.54 131.33 45.16

Interaction term = -2 cov (log F. log D)

0.54 -322.50

-443.40 -370.58 - 51.94 -182.22 - 49.80 98.96

> "tl "tl

tTl

z

x 0

>

Oo

\0

~ ;J>

Vl

ti1

~

ti1

X

TABLE A.6

(l

Philippines: Decomposition of the Sum of Squares of Trend Errors of the Real Effective Exchange Rate, 1972-78 (100,000 x original units)

0

::r:: ;J>

z

ti1

:;.::1

~

ti1

Vl

Year

Sum of squares

Domestic component

Foreign component

Interaction term

1972 1973 1974 1975 1976 1977 1978

155.86 1000.01 2004.69 358.88 61.82 104.58 175.04

140.50 1184.19 2306.43 535.70 117.D3 58.90 60.77

32.19 126.12 258.89 90.06 20.43 218.48 146.40

- 16:83 -310.31 -560.60 -266.88 - 75.63 -172.92 - 32.13

TABLE A.7 Singapore: Decomposition of the Variability of Real Effective Exchange Rates. 19n-79 (1.000,000 x original units)

Year

Variability of real effective exchange rate = var (log RER)

Domestic component = var (log D)

Foreign component = var (log F)

1972 1973 1974 1975 1976 1977 1978 1979

110.97 810.35 80.48 177.04 85.26 68.53 43.40 32.07

36.85 2146.47 242.74 859.66 54.32 117.94 127.01 88.55

48.86 359.86 236.54 270.60 12.67 206.21 140.19 44.36

=

Interaction term -2 cov (log F. log D) 25.26 -1695.98 - 398.80 - 953.22 18.27 - 255.62 - 223.80 - 100.84

> '1:l cil

zt:l

x

>

lo ..._

~

> rn trl

~

trl

>
trl > z C/l

trl

>

:;:;

6

5

§

I 2.

-

~ " -

I.

.... g .E: ~ 3. :J ~ ~

RP,

R Y,

RX~,

EE~,

.4768 (.6032J .4743 (.5923) .5009 (1.059)

-.0919