Exchange rate of the US dollar and the J curve: the case of oil exporting countries

Energy Economics 25 (2003) 741–765

Exchange rate of the US dollar and the J curve: the case of oil exporting countries Ayoub Yousefia, Tony S. Wirjantob,* a

Department of Economics, Business and Mathematics, King’s College, University of Western Ontario, London, Ontario N6A 2M3, Canada b Department of Economics, Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON, Canada N2L 3G1 Received 3 July 2002; received in revised form 14 November 2002; accepted 2 December 2002

Abstract This study examines the effects of changes in the exchange rate of the US dollar on the trade balances of three oil-exporting countries, namely Iran, Venezuela and Saudi Arabia. An exchange rate pass-through model is applied to allow changes in the exchange rate of the dollar to affect prices of traded goods. Then, the impact of changes in prices on the quantities of imports and exports of these economies is estimated. The results suggest a partial exchange rate pass-through to these countries’ import and export prices in terms of the US dollar. While the three countries raise the price of their primary export (namely crude oil) in response to a depreciation of the dollar, Saudi Arabia’s long-run pricing strategy in securing a larger market share stands in contrast to that of the two other OPEC members. The sum of the estimated long-run price elasticities of demand for imports and exports is found to exceed unity for Iran and Venezuela, but less than unity for Saudi Arabia. 䊚 2003 Elsevier Science B.V. All rights reserved. JEL classifications: F31; F32; F14 Keywords: Trade balance; J-curve; Invoicing currency; Exchange rate pass-through; Crude oil

1. Introduction The adjustment pattern of a nation’s trade balance in response to changes in its exchange rate has been subjected to much discussion in the international trade *Corresponding author. Tel.: q1-519-888-4567x5210; fax: q1-519-725-0530. E-mail address: [email protected] (T.S. Wirjanto). 0140-9883/03/$ - see front matter 䊚 2003 Elsevier Science B.V. All rights reserved. PII: S 0 1 4 0 - 9 8 8 3 Ž 0 3 . 0 0 0 4 4 - 6

742

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

literature. The dramatic swings in the exchange rate of the US dollar and the sluggish response of the US trade balance during the 1980s sparked a new wave of interest in this area.1 According to the textbook view, depreciation of the deficit nation’s currency visa-vis a trade-partner’s currency raises the cost of import contracted in foreign currency, while export revenue contracted in domestic currency remains unchanged. The two effects together lead to a deterioration of the trade balance immediately following a depreciation of domestic currency. In the short run, import and export prices respond with little or no decline in volume. Assuming a zero initial trade balance and dominance of the exporter currency in invoicing trade contracts, the trade balance continues to deteriorate in the medium term. Over time, the relativeprice-induced volume effect comes to dominate the price effect and the trade balance improves. This pattern of the trade balance adjustment is commonly referred to as the ‘J-curve effect’. The three time spans named by Magee (1973) as the ‘currency contract’, ‘pass-through’ and ‘quantity response’ periods, respectively. The J-curve effect presupposes the Marshall-Lerner condition, which states that price elasticities of demand for imports and exports sum to greater than unity. In addition to the elasticity condition, another equally crucial prerequisite for the J-curve effect is the invoicing currency of imports and exports. For instance, if an exporter or importer uses a foreign currency in his foreign trade, his revenue or costs in terms of domestic currency will be immediately affected when the exchange rate changes. On the contrary, if he uses his own currency, a change in the exchange rate will leave his revenue or costs unaffected immediately following currency depreciation. The theoretical underpinning of the choice of invoicing currency was pioneered by Magee (1973, 1974) and subsequently adopted in the studies by Mckinnon (1979), Magee and Rao (1980) and Melvin and Sultan (1990), etc. Despite its pivotal role as a catalyst in the transmission of changes in the exchange rate to the trade balance, invoicing currency has been subjected to only few empirical investigations.2 Information on the invoicing currency has also been very limited. It was not until early in the 1970s that most European country began to collect data on the invoicing currency. Tables 1 and 2 provide some noteworthy information on the invoicing currency of international trade. First, for almost all of the countries listed in Table 1, the share of own currency used in invoicing exports is greater than the corresponding figure for invoicing imports. Second, the currencies of large countries are used more than those of small countries in invoicing international trade. For instance, more than half of the world trade, i.e. 54.8% is invoiced in 1 During the 1985:I–1988:II period, approximately 3 years, the trade-weighted average value of the dollar measured against the currencies of G-10 countries declined by over 42%. Despite this precipitous decline in the dollar’s value, the US nominal trade deficit continued to rise from $23.38 billions in 1985:I to $42.47 billions in 1987:III. Numerous empirical studies were launched to examine the causes of the sluggish response of the US nominal trade deficit to the continuous depreciation of the dollar since the first quarter of 1985. See for example Deyak et al. (1990), Hooper and Mann (1:1989), Koch and Rosenswieg (1988), Krugman and Baldwin (1987), Mann (1986), Meade (1988) and Moffett (1989). 2 For empirical investigations on the invoicing currency of international trade for the UK, Italy and the European Union, see Carse et al. (1980) and Basevi et al. (1987), respectively.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

743

Table 1 Currencies used in world trade (in percentage) Country (Region)

Canada France Germany UK US Japan Oil exporters Other developing Non-OECD Developed world (1979 weights)

Year

Est 1979 1980 1979 Est 1980 Est Est Est

Share of each country’s exports in Dollars (1)

DM (2)

Sterling (3)

85.0 11.6 7.2 17.0 98.0 61.5 100.0 85.0 85.0 54.8

0.2 10.2 82.3 3.0 1.0 1.9 0 0 2.0 14.4

1.0 3.2 1.5 76.0 1.0 0.9 0 15.0 7.0 7.5

Share of each country’s imports in Own (4) 62.4 82.3 76 98 32.7

Dollars (5)

DM (6)

Sterling (7)

95.0 28.7 33.1 29.0 85.0 93.0 50.0 72.0 52.0 54.3

1.0 14.0 43.0 9.0 4.1 2.0 10.0 7.0 14.0 14.0

2.0 3.8 3.1 38.0 1.5 2.0 8.0 4.0 9.0 6.9

Own (8) 35.8 42.8 38.0 85.0 2.0 4.0

Est indicates an estimated value. Source: Page (1981).

terms of the US dollar as shown in column 3 of Table 2. Finally, a sizable 85% of exports from developing countries, traditionally primary commodities, are invoiced in terms of the US dollar. Given the inconvertibility of the currencies of almost all developing countries, the use of the third-country currency on imports has also been predominant. Thus, the invoicing currency of trade makes the primary commodity exporting LDCs vulnerable to the changes in the exchange rate of the US dollar Table 2 International usage of currencies (in percentage and using 1979 weights)

Dollar Deutsche Mark Pound Sterling French Franc Netherlands Gui Belgian Franc Japanese Yen Swiss Franc Italian Lira Swedish Krona Schilling Danish Krone Irish Pound Finnish Markka

Country’s share in world exports

Currency’s share in exports

Cumulative share of currencies

11.7 11.1 5.9 6.3 4.1 3.6 6.6 1.7 4.7 1.8 1.0 0.9 0.5 0.7

54.8 14.4 7.5 6.4(a) 3.0(a) 2.6(a) 2.3(a) 2.1(a) 1.9(a) 1.7(a) 0.8(a) 0.8(a) 0.3(a) 0.0(a)

54.8 69.2 76.7 83.1 86.1 88.7 91.0 93.1 95.0 96.7 97.5 98.3 98.6 98.6

(a) indicates that the share is used in own trade. Source: Page (1981).

744

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

against other major currencies. Indeed, depending on the particular pattern of trade and the invoicing currencies, each developing country’s trade balance can be affected differently by the changes in the exchange rate of the US dollar. Among primary commodity groups, crude oil sets a prime example for the use of a third-country currency which is 100% US dollar. This figure is even larger than that for the exports from the US, which is 98% as shown in Table 1. As for the share of primary commodity export, the export of crude oil by OPEC members made up more than 90% of their total exports over the last two decades. The particular feature of the invoicing currency of trade of these countries makes them a suitable representative of the primary commodity exporting countries, whose trade balance responses to changes in the exchange rate of the US dollar merit, an investigation similar to those carried out for the US economy.3 To fill this gap in the literature, the present study examines the impact on the trade balances of the oil exporting countries of the changes in the exchange rate of the US dollar. Faced with the lack of data of interest, a small group of countries, hereafter, the ‘group countries’ is chosen. The group countries consist of Iran, Saudi Arabia and Venezuela, three major oil exporting countries out of the five founding members of OPEC, with two of them from the Middle East and one from the western hemisphere. The remaining part of the article is organized as follows. Section 2 develops a model for the exchange rate pass-through and quantity response of imports and exports. Section 3 describes the data and explains the choice of the exchange rates used in this study. Section 4 provides the methodology for empirical testing and reports the pretesting results. Section 5 presents a summary of empirical results and Section 6 offer tentative conclusions and policy implications. 2. The model In dealing with the trade flow analysis, it has been common to ignore the supply side of imports by making an assumption that the price elasticity of supply is infinite. In other words, import prices are considered to be exogenous to any given country. This assumption is adopted, not because a nation’s export supply elasticity is thought to be infinite, but because of the fact that it is one of many suppliers. Several arguments have been made to support the exogeneity assumption. For instance, Murray and Ginman (1976) make the argument based on the premise that firms typically operate at less than full-employment capacity, implying that the industry supply curve will be horizontal before the full-capacity production level is reached. Also, Warner and Kreinin (1983) employ import prices in terms of foreign currency in order to apply the method of ordinary least squares to estimate a singleequation demand model. 3 There are only a handful of studies on the exchange rate pass-through for LDCs, although there are a few studies, which examine the impact on the trade balances of changes in the exchange rates of the domestic currencies of these countries. See e.g. Bahmani-Oskooee (1986, 1984). A common drawback of these studies is their failure to recognize that many developing countries’currencies are inconvertible that makes it impossible for these currencies to be chosen as the invoicing currency. As a result, the third-country currency features the invoicing currency of trade of these economies.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

745

Contrary to the arguments in support of the exogeneity of import prices mentioned above, heterogeneity of manufactured commodities and imperfect competition allow different market prices to exist for similar, but not identical products in the market. That is, exporters being concerned with the market shares following a demand or supply shock do exercise a certain degree of control over prices. The study by Hooper and Mann (1989) suggests that for US imports of manufactured goods, on the average, 40–50% of the decline in the nominal exchange rate is absorbed by foreign firms by cutting profit margins in order to minimize the losses of the market share in the US. This study also concludes that Japanese firms apparently absorb a higher proportion of exchange rate fluctuations into their profit margins on their sales to the US, than they do on their sales to other countries. For similar studies, see Moffett (1989), Koch and Rosenswieg (1990), Deyak et al. (1989) and Gagnon (1990). Despite a voluminous study on this subject, the question on whether and how the markup adjustments by developed economies in response to changes in the exchange rates affect import prices of developing economies appears not to have been studied much. It is the objective of this article to empirically test the hypothesis that developing economies’ import prices would be affected by changes in the exchange rate of the US dollar. Similarly on the export front, for the group countries given the high proportion of oil in their total exports and the invoicing currency, export prices are expected to respond to changes in the exchange rate of the US dollar. The oil industry in these countries is heavily dependent upon the import of technology and many manufactured components from developed economies. The increased cost of imports following a prolonged depreciation of the US dollar could add significantly to the overall cost of production and, hence, trigger a rise in export prices. As a result, the treatment of import and export prices based on the assumption of infinite price elasticity of supply does not seem to be fully justified. Thus, in this study, in addition to the demand equations, which have traditionally been used to study trade flows, price or supply equations are included in the model as well.4 The explicit import and export price equations are expected to reflect the dynamic impact of changes in the exchange rates and supply conditions on the price of traded goods. In addition, the price equation can serve to eliminate the problem of simultaneous equation bias in the single-equation demand model. More specifically, we assume a two-country model, domestic and foreign, where domestic countries are Iran, Saudi Arabia and Venezuela and the foreign country represents the rest-of-the-world. Because in the currency-contract period, neither prices nor quantities can respond to changes in the exchange rate, we start with the analysis of the pass-through period.5 Exchange rate pass-through reflects the degree by which a nominal depreciation translates to a real devaluation. That is, with a 4 For more rationale for the application of demand and supply functions for imports and exports, see for instance Hooper (1976), Hooper and Mann (1989) and Moffett (1989). For a non-structural model which specifies the trade balance as a function of the real exchange rate, domestic and foreign scale variables (Rose, 1990). 5 For a direct relationship between changes in the exchange rate of the dollar and the trade balance during the currency contract period, see Appendix A.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

746

successful pass-through, the relative price change will be substantial and the adjustment costs should be borne by the importer. There is a sizable amount of empirical evidence, which suggest that exporters react to changes in the exchange rate by adjusting their export prices in terms of their domestic currencies in order to increase the limit in the foreign currency prices of the export goods.6 The model proposed in this article will be estimated in two stages. First, prices of imports and exports, in terms of US dollars, are estimated by using variables representing supply conditions and competitive factors, including the exchange rate of the US dollar. Second, the prices of imports and exports derived in the first stage with other variables, such as an activity variable, constitute factors that determine quantities of imports and exports. Thus, the effect of changes in the exchange rate on the merchandise trade balance is allowed to appear in two consecutive phases. First, the long-run impact of exchange rate fluctuations on the prices of the traded goods, which is the pass-through effect, is estimated. Second, the transmission of changes in the exchange rate is followed through the impact of changes in the real exchange rate on the quantities of trade. In the first stage, following Hooper and Mann (1989) we obtain import and export price equations under the condition of imperfect competition where price deviates from marginal cost of production. Suppose that the representative foreign producer sets the profit-maximizing price of exports to domestic country in its currency, which is denoted as Px*, as a markup, l*, over its marginal costs, C *, foreign country variables are identified with an asterisk. Px*sl*C*, l*)1

(1)

The domestic country’s import price in domestic currency is Pm s EPx* s El*C*

(2)

where, P m is the import price in domestic currency; E is the exchange rate, which is defined as the value of foreign currency in units of domestic currency. Thus, the import price in terms of domestic currency is modeled as a function of exchange rate, foreign cost of production and foreign producer profit markup. The markup variable is assumed to respond not only to the price elasticity of demand, but also the competitive pressure in the domestic market.7 The competitive pressure is measured by the ratio between the weighted index of domestic import substitute prices (domestic market index, denoted as P d, which is assumed to capture demand elasticity and market share) and the foreign production costs in domestic currency Pd za | * yC E~ w

l* s

x

(3)

6 The price discrimination in international trade that is triggered by exchange rate volatility has been referred to as ‘pricing to market’. See Krugman (1987). 7 By substituting EC*sw1q1yhxP m into Eq. (2), it can be shown that l*shy(1qh) where h is the price elasticity of demand, hs(≠Qy≠P m)(P m yQ).

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

747

where, a can be interpreted as the partial elasticity of the profit markup with respect to the exchange rate variable and its magnitude depends on the export supply and demand elasticities as well as the percentage of export contracts invoiced in foreign currencies.8 Substituting Eq. (3) into Eq. (2), we obtain import price as: pm s (1ya)e q apd q (1ya)c*

(4)

where, the lower-case letters denote logarithms of the variables.9 The new import price equation constitutes the long-run relationship among the following variables: Pm, the exchange rate, the index of import substitute prices at domestic market and the foreign marginal cost of production. Merchandise import prices are assumed to be positively related to the exchange rate, which is the trade-weighted value of foreign currencies in terms of domestic currency, and positively related to changes in the foreign cost of production and domestic prices.10 The import price exchange rate pass-through coefficient is given by ≠p m y≠es 1ya. If as1, the pass-through does not take place and the exchange rate changes have no effect on the import price. That is, the foreign producer adjusts its markup to absorb the full changes in exchange rate to keep its export price constant in terms of foreign currency. However, if as0, the pass-through is complete and the 8 In the medium term, with exports invoiced in terms of exporter currency, depreciation of importer currency causes a decline in demand for import that leads to a fall in export prices. The degree of passthrough will be greater; the higher is the elasticity of supply. On the other hand, with exports invoiced in importer currency, depreciation of the importer currency causes a decline in supply of export that increases the price. In this case, the degree of pass-through will be higher; the less elastic is the demand for import. In addition to the elasticity measures, the choice of invoicing currency plays a direct role over the degree of exchange rate pass-through. That is, despite the dominance of exporter currency in invoicing exports, one may allow for a mixed invoicing currency where a portion of exports is invoiced in terms of importer currency. Thus, we rewrite Eq. (2) as PmsbŽEPx*.qŽ1yb.=ŽPx., where b is the percentage of exports invoiced in terms of the exporter currency. Clearly, the exchange rate pass-through would be large with b close to one and very small with close to zero, assumingPx*. Therefore, for a desired rate of pass-through of changes in the exchange rate, the exporter may adjust its price by taking into account the value of invoicing parameter, b. With bs50% and a constant Px* , for instance, a 10% depreciation of the importer currency leads to only 5% exchange rate pass-through. 9 Despite its economic appeal of being able to interpret estimated coefficients as elasticities with respect to corresponding variables, log-linear form introduces some restriction into the model. For example, log-linear demand for imports implies that (i) importers will respond in proportion to a rise or a fall in the explanatory variables and (ii) elasticities will remain unchanged for a given range for each explanatory variable. 10 In Krugman and Baldwin (1987), Hooper and Mann (1989), Deyak et al. (1990) and Moffett (1989), merchandise import prices are assumed to be negatively related to exchange rate as it is defined as the foreign currency units per dollar. The study of the US trade flows for the 1958–1985 period by Deyak et al. (1990) suggests that the impact of quantity variables over import and export prices is not significantly different from zero. Also, Krugman and Baldwin (1:1987), by using quarterly data from 1977:II through 1986:IV, suggest that there does not appear to be any significant effect of US aggregate demand on import prices. Moreover, Haynes and Stone’s (1983) estimates of the supply of imports and exports for the US and UK suggest that more appropriate specification of aggregate supply behavior is a supply-price, not a supply-quantity specification. Given the lack of empirical support for the significance of a quantity variable, neither scale variables nor import-export quantities are incorporated in the group countries’ price equations.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

748

profit margin remains unchanged. Finally, with 0-a-1, there would be a partial pass-through of changes in exchange rate. Given higher long-run supply elasticities, one would expect a larger exchange rate pass-through in the long run than in the short run. Similar to the foreign exporter price setting behavior, we express domestic exporter’s profit-maximizing price in terms of domestic currency, which is denoted by P x, as a markup, l, over domestic marginal costs, C, PxslC

(5)

The foreign import price in foreign currency, Pm*, and markup variables are defined according to the symmetry of the model,11 w

1 h

z

x1q * |Pm*s y

Pm* s

~

C E

Px C sl E E

PfØE zb | y C ~

(6)

(7)

w

ls

x

(8)

Substituting Eq. (8) in Eq. (7) and taking logarithms, pm*s Žby 1.eq bpf qŽ1y b.c

(9)

where b is the partial elasticity of domestic markup with respect to exchange rate, which is assumed to be 0-b-1, P f is the weighted index of foreign import substitute prices and C is the marginal cost of production both in domestic currency. Again the lower-case letters denote logarithms of the variables. In the second stage, we model the quantity response. In the trade literature, a country’s volume of import is defined as a function of real income and relative prices, import prices in terms of domestic currency divided by an index of domestic import substitute prices where a degree of substitutability between imports and domestically produced goods is assumed. Similarly, demand for a country’s exports is defined as a function of the trading partners’ real income and the ratio of export prices in terms of foreign currency to the import substitute price level of the importing countries. When the relative prices are used in a log-form demand equation for imports, the own-price elasticity is constrained to be equal in magnitude, but opposite in sign to the domestic substitute price elasticity of demand for import. 11 The domestic markup variable is assumed to respond to the cost conditions at home and competitive pressure abroad. This is approximated by the ratio between the index of competing foreign product price, P f , and the domestic cost of production in domestic currency.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

749

Similarly, with the export demand equation, export price elasticity would be equal in magnitude, but opposite in sign to the foreign import substitute price elasticity. A number of studies have investigated the validity of application of the relative price in international trade analysis. For instance, Murray and Ginman (1976), concluded that the relative price specification of the traditional import demand model is inappropriate for estimating aggregate import demand parameters. Augustine and Afifi (1987), estimated appropriate import demand functions for thirty developing countries over the 1960–1982 period and concluded that consumers tend to respond faster to changes in the price of domestic goods than to equal changes in import prices. Warner and Kreinin (1983) estimated import and export demand functions for most industrial countries and for 15 LDCs by separating the relative price variable into three components, namely the domestic price, the import price in foreign currency and the exchange rate. Their results suggest that in most countries, it does not appear justified to employ a composite relative price variable and its separate components yield more accurate results. A trade flow modeled in this way allows variations in the exchange rates and price of traded goods to affect quantities separately. Yet, the exchange rate and prices, which are not necessarily statistical independent of each other, are not utilized together as explanatory variables in the single-equation demand function. As already discussed above, our modeling strategy differs from the standard trade modeling by allowing changes in the exchange rate to affect prices of traded goods. That is, the procedure allows for direct estimation of the exchange rate pass-through. Using the predicted import and export prices from Eqs. (4) and (9) as instrumental variables in the quantity equations has a number of advantages: First, if the observed prices are utilized in the quantity equations, the price elasticities of demand for imports and exports can be biased and inconsistent because of the simultaneity between prices and quantities. Such estimates are indeed weighted averages of the true elasticities of demand and supply, rather than estimates of the price elasticity of demand. Specifically, simultaneity implies correlation between the determinant variable and the error term that violates the use of the ordinary least squares procedure for the estimation of a single import or export demand equation. Second, our modeling avoids the high or perfect collinearity problem that can arise from the existence of the price and exchange rate variables in the quantity equation. Thus, we specify quantity equations as follows Qm s AmYam(Pˆ m)bmvm

(10)

Qx s AxY*ax(Pˆ m*)bxvx

(11)

where Q m and Q x are the quantities of imports and exports demanded by the domestic country and the rest of the world, respectively; Y is the real income of the domestic country; and Y * is the foreign real income computed as the weighted averages across trading partner countries. v m and v x are the log-normal stochastic error terms assumed to be i.i.d with zero mean. The expected signs of the model parameters are am, ax)0 and bm, bx-0.

750

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

3. Data Annual data series for the 1970s through the 1990s were taken from the International Financial Statistics, IMF, Direction of Trade Statistics, IMF and Federal Reserve Bulletin, The Board of Governors of the Federal Reserve System.12 The sample period begins in 1973 for two reasons: (i) For two decades before 1973, the price of crude oil had been controlled by the major oil companies with almost no reaction to market incentives. Even after nationalization of the oil industry by most OPEC members in the late 1960s and early 1970s, the long-term contracts remained dominant in the crude market. (ii) To explore the exchange rate pass-through, there seems to be little point in including data spanning the fixed exchange rate of the Bretton WoodsySmithsonian Agreement period. The end of the sample period for each country is determined by the availability of data of interest. Most of the variables used in this study are defined in Appendix B. Here we focus on the choice of the effective exchange rate only. A key issue in assessing the impact of changes in the dollar’s value on the group countries’ trade flows and, consequently, on their merchandise trade balances, is to determine which measure of the dollar exchange rate to employ. The choice of a specific measure of exchange rate of the dollar should be motivated by the nature of the trade flows being investigated. In examining the effect of changes in the exchange rate of the dollar on a bilateral trade between US and Saudi Arabia, for instance, the most appropriate measure of the dollar would be its price relative to Saudi Arabian currency (Riyal). However, when analyzing the impact of changes in the exchange rate in a multilateral trade framework, no single bilateral exchange rate could adequately reflect changes in the dollar’s value as the dollar may change in varying degrees against individual floating currencies. Thus, the use of a weighted average of all the bilateral changes, which is the effective exchange rate, is required in order to reflect the true change in the exchange value of the dollar. Studies dealing with the choice of dollar exchange rate indexes, such as Pauls (1987) and Anderson et al. (1987), suggest that no single measure of the weighted12 According to IFS, the Export and Import Unit Value Indexes are obtained from national sources. For some countries, indexes are compiled according to the Laspeyres formula with trade values for a particular year as weights. For others, they are derived from the ratio of a value index and a Laspeyres volume index resulting in a Paasche index. Other indexes are compiled using unit values for major export commodities derived from country value and volume data from IFS. We should remind ourselves that unit value indexes do not represent actual transaction prices, but an estimated average value per physical unit of a commodity category at the time of delivery. The unit value index should be interpreted with caution since a change in the unit value index generally involves an unknown combination of price change, variation in the commodity mix as well as changes in exchange rate. Clearly, measurement error inherent in the unit value index may render the statistical results less reliable. Nonetheless, faced with the lack of actual transactions prices like many other researches, we adopt unit value indexes. Indexes for export and import prices, compiled from survey data for prices at the wholesale level or directly from the exporter or importer called ‘Direct Pricing’, are shown in line 76 form IFS, where available. In the absence of national sources, data for wholesale prices are taken from world commodity markets and are converted into national currency at period average exchange rates. Indexes based on direct pricing are generally considered preferable to unit value indexes, because problems associated with the unit value bias would be much less severe.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

751

average exchange rate index is appropriate for the trade flow analysis under different circumstances of commodity groups or trading partner countries. Moreover, Magee and Rao (1980) argue that in calculating effective exchange rates, the weight assigned to each foreign currency in an index should reflect the importance of that currency with respect to the economic problem being analyzed. Therefore, to investigate the degree of exchange rate pass-through, the appropriate index should include only currencies in which contracts are invoiced regardless of the nationality of the trade partners. As such, the appropriate weight for each currency should be the share of the currency in total trade. Ideally, such an ‘invoicing-currencyweighted’ index of the effective exchange rate allows us to obtain a better estimate of the degree of exchange rate pass-through. Lack of sufficient information on the invoicing currency of trade, however, has made it impossible to construct such an index. In the past, researchers have relied on trade-weighted exchange rate indexes instead. Following previous research, we have adopted a trade-weighted-average effective exchange rate index of the US dollar based on the trade-weights of the group countries with their major trade partners. Trade-weighted effective exchange value of the US dollar is constructed for each of the group countries as an index of the period-average exchange value of the dollar against currencies of the major trade partners of each of the group countries. The weight for each currency is the ratio of the country’s 1973–1998 import from a source country divided by its total import from all major trade partner countries, except US, over the same period. For the choice of the weights, see Eq. (A.4). The major trade partners of Iran during the period under study are Japan, Belgium-Luxemburg, France, Germany, Italy and UK. The major trade partners of Saudi Arabia during the same period are Japan, France, Germany, Italy, Switzerland and UK; and those for Venezuela are Canada, Japan, France, Germany, Spain and UK. The base period of the index is 1973, which is the beginning of the period of generalized floating exchange rates system. 4. Empirical specifications and pretesting Most traditional studies in this area are based on equilibrium assumptions. As such they are prone to a potential misspecification. Indeed, if imports and exports fail to adjust instantaneously to their long-run equilibrium levels following a change in any of the factors that influence their behavior, then the estimates of the price and real income elasticities would be biased and inconsistent.13 In the presence of imperfect information, product differentiation, adjustment costs and other market imperfections, adjustment of the dependent variable to change in its explanatory variables may not be instantaneous. That is, the quantities of imports and exports 13 The equilibrium model has been adapted by Augustine and Afifi (1987) and Khan (1974). Augustine and Afifi conclude that, on an annual basis, a static equilibrium model may be justified. Similarly, Khan’s study of 15 developing countries for 1951–1969, on an annual basis, shows that for both import and export equations, a simple equilibrium formulation is adequate, where for both imports and exports the estimated adjustment period in response to changes in any explanatory variable is one year (the interval between observations).

752

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

Table 3 Augmented Dickey–Fuller tests for a unit root Variables

Iran

Saudi Arabia

Venezuela

Industrial countries

EX IM EXPI IMPI GDP GDPDF CPI WPI TWER

0.268 0.245 0.174 0.195 0.326 0.179 – 0.213 0.269

0.292 0.237 0.159 0.188 0.336 0.212 0.186 – 0.242

0.291 0.235 0.174 0.161 0.293 0.195 0.167 – 0.216

– – 0.148 0.172 0.347 0.211 0.184 0.206 –

The entry in each cell of columns 2–5 is the P-value of the ADF statistic calculated using the procedure of MacKinnon (1996). All variables are in logarithmic form. We also tested the null hypothesis of a unit root on first-difference of variables. This hypothesis was rejected in all cases.

demanded at each given relative price and real income may not be identical with the actual quantities traded. Recent empirical research on the trade flows provides relatively strong evidence on the sluggishness of the response of trade flows to price changes. See, for example, Deyak et al. (1990), Meade (1988) and Koch and Rosenswieg (1990). In addition to the dynamics issue, the potential existence of unit-root in the time-series variables is another concern to which we turn next. We start our empirical examination with the unit-root test of the variables of interest by employing the augmented Dickey and Fuller (1981) tests. The results are presented in Table 3. We use Akaike’s information criterion to select the appropriate lag lengths (see Ng and Perron, 1995) and then calculate the P-values using the procedure developed by MacKinnon (1996). For all series, we are unable to reject the unit root null hypothesis. Given evidence of a unit root in each variable, we proceed to identify the long-run relationships for the import and export prices for the three countries. We use the Johansen and Juselius (1990) maximum likelihood procedure that has been shown to be superior to the Engle et al. (1987) two-step procedure in terms of the test power. The P-values of the trace and maximum eigenvalue test results are reported in Table 4, using the procedure proposed by MacKinnon et al. (1999). Because the size of the Trace and maximum eigenvalue test statistics and, consequently, the number of cointegrating vector are sensitive to the choice of the lag length, we set up a separate vector error correction model (VECM) for each one of these variables and use the Schwarz criterion to select the appropriate lag lengths. See Reimers (1993). In the tests, we use the VEM model Case 1 in MacKinnon et al. (1999). We first determine the number of cointegrating vectors (r) in each system and then test the model. Based on the computed P values, we reject the null hypothesis of no cointegration (which states that the number of cointegrating vectors (r) is equal to zero). If we use a 5% level of significance, both the trace test and the lmax test lead us to find one cointegrating

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

753

Table 4 Cointegration tests and the number of cointegrating vectors Country

Iran

Saudi Arabia

Venezuela

The number of cointegrating vector

Import price equation

Export price equation

Trace

lmax

Trace

lmax

rs0 rF1 rF2 rs0 rF1 rF2 rs0 rF1 rF2

0.024 0.195 0.242 0.000 0.128 0.203 0.000 0.227 0.296

0.041 0.239 0.265 0.025 0.161 0.238 0.019 0.262 0.317

0.000 0.173 0.255 0.008 0.207 0.314 0.000 0.251 0.287

0.012 0.226 0.288 0.039 0.251 0.338 0.015 0.293 0.324

Each cell of the third and fourth columns contains P-values for the Trace and lmax tests of Johansen and Juselius (1990), calculated using the procedure of MacKinnon et al. (1999) for Case 1 (page 4). With the Trace test, H0:rs0 and H1 :r)0 and with the maximum eigenvalue test, we start with H0:rs 0 and H1:rs1. When we reject rFr *y1, but not rFr *, we conclude that there are r * cointegrating vectors.

vector for each of the import and export price equations for Iran, Saudi Arabia and Venezuela. Given the cointegrating relationships, we adopt a long-run import price relation stated in Eq. (4) for empirical testing as follows d * m pm t s a 0 q a 1t q a 2 e t q a 3p t q a 4c t q u t

(12)

where t is the time trend and um t is a zero-mean stationary random error term. In the short run, one would expect deviations from the long-run import price relationship that can be explained by a dynamic error correction model (ECM), where changes in the import price depend on past deviations from the long-run equilibrium and on past changes in all variables. More specifically, the ECM is given by m * * ˆm Dpm t s b0q b1u ty1q b2Dpty1q b3Detq b4Dety1q b5Dct q b6Dcty1 d m q b7Dpt q ´t

(13)

where m ˆ 0 y aˆ 1ty aˆ 2ety aˆ 3ptdy aˆ 4c*t uˆ m t s pt ya

(14)

and ´m t is a zero-mean identically and independently distributed error term. The foreign cost of production is proxied by a trade-weighted index of foreign producer prices in terms of foreign currencies, denoted by c*. The full impact of changes in the foreign cost of production and domestic prices may differ because

754

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

of the methodological differences in the way these indexes are constructed. Moreover, since an import price index based on unit values and a domestic price index may refer to different points in time, it is necessary to test for different dynamics of these variables. Furthermore, we do not impose equality restriction on the import price elasticities with respect to exchange rate and foreign cost of production; instead, we allow the two estimates to capture different dynamic influences. For the quantity equation, the foreign income variable is a trade-weighted index of foreign real income, denoted by y*. The empirical specifications of the long-run equations are obtained by taking logarithm of Eqs. (10) and (11) as m ˆm qm t sc1qc2ytqc3p t qvt

(15)

x qxt sd1qd2y*t qd3pˆ m* t qvt

(16)

Consistent with the trade literature, we have hypothesized earlier in the article that volume of trade responds to changes in relative prices only in the long run. Therefore, we do not need to proceed with the short-run analysis for the quantity equations. 5. Empirical results In this section, we discuss the empirical results in the following order: the longrun import and export price equations, the short-run import and export price equations, and the import and export quantity equations. The ordinary least squares (OLS) estimates of the long-run equations are not efficient if their distributions depend on nuisance parameters arising from serially correlated residuals and the endogeneity of the explanatory variables. In the long-run import and export price equations, the serial correlation and endogeneity can be induced by Granger causation from the innovations of the generating equations of the import and export price variables to innovations of the generating equations of their explanatory variables. One way of dealing with these problems is to use the fully modified OLS (FMOLS) proposed by Phillips and Hansen (1990). This approach corrects for the long-run serial correlation the regression’s residuals and endogeneity of the regressors. The resultant estimates are asymptotically efficient and asymptotically normal. To increase their finite-sample efficiency, we prewhiten the FMOLS estimates using a VAR(1) filter with a quadratic spectral kernel as advocated by Andrews and Monahan (1992). Also, we subject the estimated long-run relations to tests of parameter instabilities using the SupF test proposed by Hansen (1992). This test has the null hypothesis of parameter stability and the alternative hypothesis of a sharp regime shift. It treats the break point as unknown and searches it with a maximum value of the F-statistic over nearly the entire sample. In this article, we use this SupF test as a general misspecification test for the long-run equations. From Table 5, the estimated long-run exchange rate pass-through elasticities of import prices, carry the expected positive sign and are statistically significant.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

755

Table 5 Long-run import price equations

Iran (1973–1993) Saudi Arabia (1973–1986) Venezuela (1973–1998)

Constant

Trend

et

ptd

c*t

P (SupF)

0.095 (0.032) 0.063 (0.011) 0.039 (0.017)

0.012 (0.014) 0.078 (0.008) 0.054 (0.005)

0.473 (0.001) 0.846 (0.005) 0.193 (0.000)

0.644 (0.000) 0.169 (0.003) 0.856 (0.009)

0.217 (0.006) 0.434 (0.001) 0.204 (0.000)

0.223 0.279 0.254

The equation is estimated by the fully modified ordinary least squares method proposed by Phillips and Hansen (1990) with a VAR(1) prewhitening filter and a quadratic spectral kernel advocated by Andrews and Monahan (1992). P values of the standardized t-statistics are recorded in parentheses. P (SupF) is the P value of Hansen (1992) SupF test for parameter instability, calculated using the method proposed by Hansen (1997).

During the period of 1973 through the 1990s, a 10% depreciation of the dollar, for instance, caused import prices in terms of dollar to rise by 4.7, 8.5 and 1.9% for Iran, Saudi Arabia and Venezuela, respectively. The partial exchange rate passthrough figures imply that following a prolonged depreciation of the dollar exporters who invoiced their exports in terms of currencies other than the US dollar lowered their profit markups to share with the importers the burden of high import prices. Given the similar exchange rate pass-through elasticity estimates for developed economies in the literature, it appears that the group countries have not been treated differently from the developed countries. In other words, industrial countries export price reaction to a prolonged depreciation of the dollar has not been targeted to a specific destination. The estimated domestic substitute prices, which carry the expected positive signs, are all statistically significant. Also, the estimated long-run import-price elasticities of the industrial countries’ wholesale prices (i.e. cost of production) carry the expected positive signs and they are statistically significant at the 5% level of significance. These estimates can be interpreted as the degree of price linkages between the group countries and the developed economies. In particular, to the extent of the ratio of imports to total GDP of these economies, increases in the cost of production in developed economies lead to higher prices in the group countries. Table 6 reports the estimated long-run exchange rate pass-through elasticities of export prices. These estimates have the expected negative signs and are statistically significant at the 5% level of significance. In reaction to a 10% depreciation of the US dollar, for instance, Iran, Saudi Arabia and Venezuela have allowed their export prices in terms of foreign currencies to decline by 3.9, 7.7 and 1.2%, respectively. Accordingly, these nations raised their markups by 6.1, 2.3 and 8.8% to partially recoup the decline in the international purchasing power of oil revenues. As expected, we observe the three countries export prices respond differently to changes in the exchange rate of the dollar. Saudi Arabia raises its markup by far less than those of the other two countries. This may suggest that while Iran and Venezuela are concerned more with the price, Saudi Arabia as the biggest member of OPEC

756

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

Table 6 Long-run export price equations

Iran (1973–1989) Saudi Arabia (1973–1998) Venezuela (1973–1988)

Constant

Trend

et

ptf

ct

P (SupF)

y0.072 (0.013) y0.028 (0.012) y0.191 (0.007)

0.006 (0.009) 0.054 (0.008) 0.032 (0.003)

y0.392 (0.041) y0.769 (0.000) y0.115 (0.038)

0.972 (0.000) 1.065 (0.000) 0.923 (0.000)

0.248 (0.007) 0.415 (0.000) 0.187 (0.023)

0.261 0.286 0.259

The equation is estimated by the fully modified ordinary least squares method proposed by Phillips and Hansen (1990) with a VAR(1) prewhitening filter and a quadratic spectral kernel advocated by Andrews and Monahan (1992). P-values of the standardized t-statistics are recorded in parentheses. P (SupF) is the P value of Hansen (1992) SupF test for parameter instability, calculated using the method proposed by Hansen (1997).

tries to hold a bigger market share in the long run.14Whether this result is a reflection of the stock of reserve, production capacity utilization or the duration of the sales contracts cannot be deduced from our results. This outcome, however, lends support to the ‘absence of a unified OPEC policy’ view in the international crude market literature. The estimated long-run export-price elasticities with respect to the group countries’ cost of production carry the expected positive sign and are statistically significant at the 5% level of significance. The outcome is presumably the result of substantial capital import expenditures in oil industries in these economies as compared to a low variable cost of production. The foreign substitute price elasticities of export prices have the expected positive sign and they are all statistically significant. The estimates are in the range of unity, indicating an almost uniform energy price movement internationally. Finally, the SupF tests suggest that there is no compelling evidence that the long-run import and export price equations are misspecified. For the short-run import and export price equations, we have allowed import and export prices respond to changes in the exchange rate of the dollar within one year by including in the regression equations the lag of the first differences of the exchange rate variable. Initially, the short-run equations include the lags of the first differences of import and export prices, the leads and lags of the first differences of all explanatory variables and the one-period lag of the residuals of the cointegrating equations as estimates of disequilibrium errors. This procedure is advocated by Inder (1995), which is an extension of the estimation procedures proposed by Phillips and Loretan (1991), Saikkonen (1991) and Stock and Watson (1993). We also provide a battery of diagnostic tests for the adequacy of the 14 Since the US dollar is the invoicing currency of trade in crude oil, a distinction should be made among importing countries based on their domestic currencies. For the US, for instance, there will be an increase in import prices following a depreciation of the dollar. For countries other than the US, on the other hand, the domestic currency price of imports will fall by less than proportionately following a decline in the value of the US dollar. Lack of destination-specific export price data for the group countries makes it impossible to produce estimates of oil-import price exchange rate pass-through elasticities for different destinations.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

757

Table 7 Short-run import price equations

Constant uˆ m ty1 pm ty1 et ety1 c*t Dc*ty1 ptd ety2 c*ty2 LM-ARCH(1) LM-AR(1) P (SupF)

Iran

Saudi Arabia

Venezuela

0.031 (0.028) y0.426 (0.000) 0.129 (0.008) 0.337 (0.014) y0.115 (0.022) 0.723 (0.000) y0.285 (0.009) 0.563 (0.001) 0.079 (0.042) 0.043 (0.031) 0.226 0.118 0.125

0.053 (0.044) y0.822 (0.000) 0.286 (0.005) 0.565 (0.001) y0.212 (0.008) 1.168 (0.000) y0.487 (0.008) 0.104 (0.015) – –

0.077 (0.023) y0.235 (0.000) 0.086 (0.003) 0.295 (0.000) 0.143 (0.005) 0.237 (0.000) y0.072 (0.031) 0.981 (0.034) 0.030 (0.042) –

0.285 0.120 0.133

0.232 0.116 0.119

The equation is estimated using the approach suggested by Inder (1995), which includes lagged values of the dependent variable as well as lagged and lead values of each of the independent variables. The parameter estimates reported above are based on the final version of the ECMs obtained via a generalto-specific approach. P values of the standardized t-statistics are recorded in parentheses. LM-ARCH(1) is the P value of the Lagrange multiplier test against an ARCH (1) error, LM-AR(1) is the P value of the Lagrange multiplier test against an AR(1) error, and P (SupF) is the P-value of Andrews’ (1993) SupF test for parameter instability, calculated using the method proposed by Hansen (1997).

reported error correction models (ECMs). These are the Lagrange multiplier tests against an ARCH (1) and AR(1) error process as well as the parameter stability test proposed by Andrews (1990) which treats the break point as unknown. Unlike Hansen (1992) SupF test, this SupF test applies to regressions with stationary variables. The parameter estimates reported in Table 7 are based on the final versions of the ECMs obtained via a general to specific approach. The estimated coefficients of the error correction terms are all negatively signed and statistically significant, implying that import and export prices should rise over time toward their long-run equilibrium levels. The estimated short-run exchange rate pass-through elasticities of import prices are all significant and carry the expected positive sign. As expected, the elasticity estimates are smaller than the corresponding figures for the long run. In general, the results suggest a partial exchange rate pass-through to the group countries’ import prices. The parameter estimates of foreign cost of production

758

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

Table 8 Short-run export price equations Iran

Saudi Arabia

Venezuela

ety2

0.023 (0.015) y0.516 (0.000) 0.056 (0.004) 0.211 (0.001) y0.295 (0.021) 0.104 (0.052) y0.188 (0.030) 0.337 (0.000) –

cty2

–

0.040 (0.036) y0.895 (0.000) 0.024 (0.000) 0.094 (0.044) y0.409 (0.002) 0.079 (0.048) y0.093 (0.026) 0.114 (0.003) 0.038 (0.026) –

LM-ARCH(1) LM-AR(1) P (SupF)

0.217 0.112 0.123

0.055 (0.004) y0.078 (0.000) 0.092 (0.000) 0.448 (0.000) y0.113 (0.008) 0.326 (0.000) y0.374 (0.000) 0.823 (0.000) 0.124 (0.015) 0.091 (0.022) 0.285 0.118 0.129

Constant * uˆ m t-1

pm* ty1 et ety1 ct cty1 ptf

0.292 0.124 0.143

The equation is estimated using the approach suggested by Inder (1995), which includes lagged values of the dependent variable as well as lagged and lead values of each of the independent variables. The parameter estimates reported above are based on the final version of the ECMs obtained via a generalto-specific approach. P values of the standardized t-statistics are recorded in parentheses. LM-ARCH(1) is the P value of the Lagrange multiplier test against an ARCH (1) error, LM-AR(1) is the P value of the Lagrange multiplier test against an AR(1) error, and P (SupF) is the P value of Andrews’ (1993) SupF test for parameter instability, calculated using the method proposed by Hansen (1997).

variables are also statistically significant with the expected sign for all three countries. Since the exchange rate has been found to have a long-run effect on these countries’ export prices, it is reasonable to expect that it should have a short-run effect as well. Looking at the combined coefficient estimates of Det and Dety1 from Table 8, export prices from Iran and Venezuela seem to decline and that from Saudi Arabia seems to rise in terms of importing countries currencies. The short-run parameter estimates of the cost of production variables are statistically significant at the 5% level of significance. This result can be highlighted as a feature of the crude pricing mechanism by these countries, which allow a partial transmission of cost of production to export prices in the short run and in the long run. The foreign substitute price elasticity of export prices carries the expected positive sign and they are all statistically significant. The estimates are much smaller than the long-run

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

759

Table 9 Import demand equations

Iran (1973–1993) Saudi Arabia (1973–1986) Venezuela (1973–1998)

Constant

Trend

Yt

pˆ m t

P (SupF)

y0.065 (0.001) y0.055 (0.009) y0.091 (0.003)

0.093 (0.001) 0.014 (0.009) 0.008 (0.005)

0.431 (0.000) 1.154 (0.000) 2.112 (0.000)

y0.808 (0.000) y0.127 (0.000) y1.084 (0.000)

0.266 0.283 0.278

The equation is estimated by the fully modified ordinary least squares method proposed by Phillips and Hansen (1990) with a VAR(1) pre-whitening filter and a quadratic spectral kernel advocated by Andrews and Monahan (1992). P values of the standardized t-statistics are recorded in parentheses. P (SupF) is the P value of Hansen (1992) SupF test for parameter instability, calculated using the method proposed by Hansen (1997).

figures that clearly suggest an almost uniform energy price movement internationally. Finally, both ECMs pass the diagnostic tests. The long-run import and export demand equations are estimated using the prewhitened FMOLS procedure for the same reason as that for the long-run import and export price equations. Tables 9 and 10 report the long-run parameter estimates of import and export demand equations. The estimated price elasticities of demand for imports and exports are all statistically significant and with the expected signs. The estimated long-run price elasticities of demand for imports by the group countries are considerably larger than those for the demand for exports from these countries. This suggests that price elasticities of demand for export from these countries are relatively low. The price elasticity differentials are an indication of fewer substitutes for crude oil compared to those for manufactured commodities. The estimated long run exchange rate elasticities of import and export prices as well as price elasticities of demand for imports and exports can be combined to show the pattern of trade balance adjustments. Starting from a zero trade balance, Table 10 Export demand equations

Iran (1973–1989) Saudi Arabia (1973–1998) Venezuela (1973–1988)

Constant

Trend

WYt

pˆ m* t

P (SupF)

0.093 (0.016) 0.082 (0.011) 0.018 (0.020)

0.015 (0.025) 0.026 (0.015) 0.015 (0.033)

0.645 (0.000) 1.327 (0.000) 1.018 (0.000)

y0.279 (0.000) y0.108 (0.000) y0.145 (0.000)

0.227 0.214 0.238

The equation is estimated by the fully modified ordinary least squares method proposed by Phillips and Hansen (1990) with a VAR(1) prewhitening filter and a quadratic spectral kernel advocated by Andrews and Monahan (1992). P values of the standardized t-statistics are recorded in parentheses. P (SupF) is the P value of Hansen (1992). SupF test for parameter instability, calculated using the method proposed by Hansen (1997).

760

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

depreciation of the US dollar, for instance, causes trade balances of Iran and Venezuela to improve initially, because the export-price markups rise more than that of the import prices. On the contrary, Saudi Arabia’s trade balance declines initially because of a substantial increase in import prices compared with a moderate rise in export-price markup. Import and export price elasticity estimates of Saudi Arabia are however, very small (y0.13 and y0.11) failing to suggest an improvement in its trade balance in the long run. For Iran and Venezuela, the sum of the absolute values of the long-run price elasticities of demand for imports and exports exceeds unity, which calls for a trade balance improvement in the long run.15 In sum, while changes in the exchange rate of the dollar do influence these countries’ trade balances in terms of the US dollars, the balances follow different adjustment patterns and time profiles. Specifically, this study does not suggest the text-book J-curve effect for the group countries. The estimated real income elasticities of demand for imports and exports as a measure of real-income linkages are also illustrated in Tables 9 and 10. The estimated real income elasticities of demand for import carry the expected positive sign and are significant at the 5% level of significance. The estimated real income elasticities of demand for export are also statistically significant and of the correct a priori signs. Except for Iran, the group countries’ real income elasticities of demand for imports are large implying that the proportion of income growth spent by the group countries on imports from industrial countries is substantial. The large estimates of income elasticities of demand are similar to those obtained for other developing nations in the empirical trade literature. Again, there is no sign of misspecification in the import and export quantity equations. 6. Concluding remarks The present study examined the effects of changes in the exchange rate of the US dollar which serves as the third-country currency, on the trade balances of three oil exporting countries, namely Iran, Venezuela and Saudi Arabia. By adopting an exchange rate pass-through model, both import and export price and quantity equations of these nations were carefully estimated. Annual data utilized are for the period of 1973 through the 1990s. The model allows changes in the exchange rate of the dollar to affect import and export prices, and changes in price to influence the quantity of imports and exports. Based on the results obtained in this study, we offer the following tentative conclusions. Changes in the effective exchange rate of the dollar pass through partially to these countries’ import prices. A 10% depreciation of the dollar, for instance, caused import prices in terms of dollars to rise by 1.9–8.5%, leaving between 8.1 and 1.5% to be borne by the exporters as reductions in the markup of the non-dollar15 The results seem consistent with those of other studies in the literature. Goldstein and Khan (1985) in a survey of the empirical literature of the trade flow of a number of developed nations suggest that, in general, long-run elasticities (greater than two years) are approximately twice as much as short-run elasticities (0–6 months). Furthermore, the short-run elasticities generally fail to sum to unity while the long-run elasticities almost always sum to greater than unity.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

761

invoiced exports. With regard to the group countries export price strategies; all three countries raise their export prices by less than proportionately in reaction to a depreciation of the dollar. Saudi Arabia’s estimate of the export-price markup, however, is considerably lower than those of the other two countries. In the long run, Iran and Venezuela seem more concerned with price, while Saudi Arabia tries to secure a larger market share. This evidence can be interpreted to suggest that there is an absence of a unified OPEC policy view. The demand for imports and exports are all price elastic. The long-run price elasticities of demand for imports by the group countries are considerably larger than those for the demand for exports from these countries. The sum of the estimated long-run price elasticities of demand for imports and exports exceeds unity for Iran and Venezuela, which suggests an improvement in trade balances measured in US dollars. While changes in the exchange rate of the dollar do influence these countries’ trade balances, each country’s trade balance follows a different adjustment pattern. A prolonged depreciation of the dollar, for instance, leads to an improvement in the trade balances of Iran and Venezuela and a deterioration of the trade balance of Saudi Arabia. Given the traditional use of the US dollar by almost all primary commodity exporting LDC’s, these nations’ trade balances, depending on the particular pattern of trade, should likely be affected by the changes in the exchange rate of the US dollar against other major currencies as well. The estimated long-run export price elasticities with respect to foreign substitute prices indicate the existence of an almost uniform crude (energy) price adjustment mechanism internationally. Except for Iran, the group countries’ real income elasticities of demand for imports are large, which are in line with similar estimates obtained for other developing nations in the empirical trade literature. Acknowledgments The second author acknowledges a research grant from the UWySSHRC to carry out this project. Also, comments by Paul Davidson, Don P. Clark, Hui S. Chang and George Philipptos on an earlier draft of this article are gratefully acknowledged. The usual disclaimer applies. Appendix A: We generalize a static trade-balance identity in order to account for the invoicingcurrency of trade contracts: d d $ $ $ o o o TBdswPxdQxdqPx$Qx$e$qPxoQxoeoxywPm Qm qPm Qm e qPm Qm ex

(A.1)

where TBd is the nominal merchandise trade balance in terms of domestic currency, Pdx, P$x, Pox are the export unit prices invoiced in terms of domestic currency, the US dollar, and a weighted average of other currencies except the US dollar, respectively, Pdm, P$m, Pom are the import unit prices with invoicing currencies as in the exports, d $ o QxsQxdqQx$qQxo is the corresponding volume of exports, QmsQm qQm qQm is

762

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

the corresponding volume of imports, e$ is the domestic currency units per US dollar, and eo is the domestic currency units per weighted-average of major currencies, excluding the US dollar. As pointed out in the text, the group countries’ currencies play almost no role in settling international contractual obligations. The countries therefore are strictly constrained for foreign payments by their receipts from exports. Moreover, the group countries’ exports are almost entirely invoiced in dollars, no matter where the export commodities are destined, while their imports could, conceivably, be settled in terms of almost any convertible currency. Therefore, it is reasonable to set Qdx, Qdm and Qox equal to zero. Hence, Eq. (A.1) simplifies to $ $ $ o TBdsPx$Qx$e$ywPm Qm e qPm Qomeox.

(A.2)

From Eq. (A.2), changes in the exchange rate of the US dollar affect TBd directly through e$ and indirectly through eo. That is, variations in the TBd depend, among other things, on the extent to which the value of the US dollar changes against other major currencies. For instance, when the dollar depreciates against domestic currencies of the group countries, other major currencies may depreciate, gain value or remain unchanged against these currencies; i.e., e$-0, may be associated with eo-0, eo)0, or eos0. Therefore, the merchandise trade balance in terms of domestic currency can change in any direction following dollar fluctuations. This implies that the direction of change in TBd in response to changes in the dollar’s value is ambiguous. In other words, a model of trade balance in terms of domestic currency such as Eq. (A.2), which includes different exchange rates of the domestic currency, is inappropriate for analyzing the impact of changes in the exchange rate of the dollar on these countries’ trade balances. The problem with TBd, however, could be resolved when TB is written in terms of dollars $ $ o o $yo TB$sPx$Qx$ywPm Qm qPm Qm e x

(A.3)

where TB$ is the merchandise trade balance in terms of US dollars, and e$yo is the units of the US dollar per weighted average index of other major currencies. When the trade balance defined in terms of dollars, a depreciation of the dollar, e$yo)0, is clearly expected to lead to deterioration of the trade balance, while an appreciation does the opposite. Therefore, this study utilizes the dollar exchange rate and excludes from the model the exchange rates of the domestic currencies of the group countries. Eq. (A.3) when expended illustrates how a trade–weighted effective exchange rate of the US dollar should be constructed. Assume that there are only two countries in the world besides the US and the group countries. Suppose these two countries are Japan and UK. Then Eq. (A.3) is given by $ $ ¥ ¥ $y¥ £, £ $y£ TB$sPx$Qx$ywPm Qm qPm Qm e qPm Qm e x

(A.4)

where e$y¥ and e$y£ are the units of the US dollar per Japanese Yen and the Pound

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

763

Sterling, respectively. This suggests that the appropriate weights for the US dollar bilateral exchange rates are the group countries that import shares. Appendix B: Definitions of the variables and the sample periods used in this study are given below. Iran EX: Exports, billions of US dollars (1973–1996) IM: Imports, billions of US dollars (1973–1996) EXPI: Export Price Index, 1990s100, (1973–1993) IMPI: Import Price Index, 1990s100 (1973–1993) GDP: Billions of Iranian Rials, 1982 prices, (1973–1998) GDPDF: GDP Deflator, 1995s100 (1973–1997) WPI: Wholesale Price Index, 1995s100 (1973–1999) TWER: Trade-weighted effective exchange rate of the US dollar, 1973s100 (1973– 1998) Saudi Arabia EX: Exports, billions of US dollars (1973–1997) IM: Imports, billions of US dollars (1973–1997) EXPI: Export Prices of Crude Petroleum, 1995s100, Index of Prices in US dollars (1973–1998) IMPI: Import Unit Value Indexes, 1980s100 (1973–1986) GDP: GDP Volume, billions of Saudi Riyals, 1970 prices (1973–1998) GDPDF: GDP Deflator, 1995s100, (1973–1997) CPI: Consumer Price Index, 1995s100, (1973–1999) TWER: Trade-weighted effective exchange rate of the US dollar, 1973s100 (1973– 1998) Venezuela EX: Exports, billions of US dollars (1973–1998) EXPT: Exports of Petroleum, billions of US dollars (1973–1998) IM: Imports, billions of US dollars (1973–1997) EXPI: Export Prices, Crude Petroleum wholesale Prices, 1985s100 (1973–1988) IMPI: Import Price Index, 1995s100 (1973–1999) GDP: GDP Volume, billions of Bolivare, 1984 prices (1973–1999) GDPDF: GDP Deflator, 1995s100 (1973–1998) CPI: Consumer Price Index, 1995s100 (1973–1999) TWER: Trade-weighted effective exchange rate of the US dollar, 1973s100 (1973– 1998) Industrial Countries EXPI: Export Unit Values, in US dollars, 1995s100 (1973–1998) IMPI: Import Unit Values, in US dollars, 1995s100 (1973–1998) GDP: OECD-total, billions of US dollars, at the price levels and exchange rates of 1990 (1973–1997)

764

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

GDPDF: GDP Deflator, 1995s100 (1973–1998) CPI: Consumer Price Index, 1995s100 (1973–1998) WPI: Wholesale Price Index, Producer Price, 1995s100 (1973–1998) References Anderson, G.H., Karamouzis, N.V., Skaperdas, P.D., 1987. A new effective exchange rate index of the dollar and its implications for U.S. merchandise trade. Econ. Rev., Federal Reserve Bank of Cleveland Quarter 2, 2–23. Andrews, D.W.K., 1990. Tests for parameter instability and structural change with unknown change point. Econometrica 61, 821–856. Andrews, D.W.K., Monahan, J.C., 1992. An improved heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica 60, 953–966. Augustine, A., Afifi, R., 1987. An econometric examination of import demand function in thirty developing countries. J. Post Keynesian Econ. 9, 604–616. Bahmani-Oskooee, M., 1986. Determinants of international trade flows: the case of developing countries. J. Dev. Econ. 20, 107–123. Bahmani-Oskooee, M., 1984. Devaluation and the J-curve: some evidence from LDCs. Rev. Econ. Stat. 67, 500–504. Basevi, G., Cocchi, D., Lischi, P.L., 1987. The choice of currency in the foreign trade of Italy. In: Hodgman, D.R., Wood, G.E. (Eds.), Monetary and Exchange Rate Policy. The MacMillan Press Ltd. Carse, S., Williamson, J., Wood, G.E., 1980. The financing procedures of British foreign trade. Cambridge University Press. Deyak, T.A., Sawyer, C.W., Sprinkle, R.L., 1990. The effects of exchange rate changes on prices and quantities in US foreign trade. Int. Trade J. 5, 77–92. Deyak, T.A., Sawyer, C.W., Sprinkle, R.L., 1989. An empirical examination of the structural stability of disaggregated US import demand. Rev. Econ. Stat. 71, 337–341. Dickey, D.A., Fuller, W.A., 1981. Likelihood Ratio statistics for autoregressive time series with a unit root. Econometrica 49, 1057–1072. Engle, R.F., Granger, C.W., 1987. Cointegration and error correction: representation, estimation and testing. Econometrica 55, 251–276. Gagnon, J.K.M., 1990. Pricing to market in international trade: evidence from panel data on automobiles and total merchandise. International Finance Discussion Papers. Board of Governors of the Federal Reserve System, No. 389. Goldstein, M., Khan, M., 1985. Income and price effects in foreign trade. In: Jones, R.W., Kenen, P.B. (Eds.), Handbook of International Economics, Vol. 2. Elsevier Science Publishers B.V. Hansen, B.E., 1992. Tests of parameter instability in regressions with I(1) Processes. J. Bus. Econ. Stat. 10, 321–336. Hansen, B.E., 1997. Approximate asymptoticvalues for structural-change tests. J. Bus. Econ. Stat. 6067, 15. Haynes, S.E., Stone, J.A., 1983. Specification of supply behaviour in international trade. Rev. Econ. Stat. 65, 626–632. Hooper, P., 1976. Forecasting U.S. export and import prices and volumes in a changing world economy. International Finance Discussion papers, Board of Governors of the Federal Reserve System 99. Hooper, P., Mann, C.L., 1989. Exchange rate pass-through in the 1980s: the case of US imports of manufactures. Brookings Pap. Econ. Act., 1 297–337. Inder, B., 1995. Finite Sample Arguments for Appropriate Estimation of Cointegrating Vectors. Mimeo, Department of Business and Statistics, Monash University, Australia. Johansen, S., Juselius, K., 1990. Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxf. Bull. Econ. Stat. 52, 169–210. Khan, M.S., 1974. Import and export demand in developing countries. International Monetary Fund Staff Paper 21, 678–693.

A. Yousefi, T.S. Wirjanto / Energy Economics 25 (2003) 741–765

765

Koch, P.D., Rosenswieg, J.A., 1988 July–August. The US dollar and the delayed J-curve. Econ. Rev. 2–15 Federal Reserve Bank of Atlanta. Koch, P.D., Rosenswieg, J.A., 1990. The dynamic relationship between the dollar and composition of US trade. J. Bus. Econ. Stat. 8, 355–364. Krugman, P.R., Baldwin, R.E., 1987. The persistence of the US trade deficit. Brooking Pap. Econ. Act., 1 1–55. Krugman, P.R., 1987. Pricing to Market when the exchange rate changes. In: Arndt, S.W., Richardson, J.D. (Eds.), Real-Financial Linkages among Open Economies. MIT Press, Cambridge. MacKinnon, J.G., 1996. Numerical distribution functions for unit root and cointegration tests. J. Appl. Econ. 11, 601–618. MacKinnon, J.G., Haug, A.A., Michelis, L., 1999. Numerical distribution functions of likelihood ratio tests for cointegration. J. Appl. Econ. 14, 563–577. Magee, S.P., Rao, R.K.S., 1980. Vehicle and non-vehicle currencies in international trade. Am. Econ. Rev. LXX 368–373. Magee, S.P., 1973. Currency contracts, pass-through and devaluation. Brooking Pap. Econ. Act. 1, 303–325. Magee, S.P., 1974. Import prices in the currency-contract period. Brookings Pap. Econ. Act., 1 117–167. Mann, C.L., 1986. Profit margins and exchange rates. Fed. Reserve Bull. 72, 366–379. Mckinnon, Ronald I., 1979. Foreign trade regimes and economic development: A review article. J. Int. Econ. 9, 429–452. Meade, E.E., 1988. Exchange rates, adjustment and the J-curve. Fed. Reserve Bull. 633–644. Melvin, M., Sultan, J., 1990. The choice of an invoicing currency in international trade and the balance of trade impact of currency depreciation. Open Econ. Rev. 1, 251–268. Moffett, M.H., 1989. The J-curve revisited: an empirical examination for the US. J. Int. Money Finance 8, 425–444. Murray, T., Ginman, P., 1976. An empirical examination of the traditional aggregate import demand model. Rev. Econ. Stat. 58, 75–80. Ng, S., Perron, P., 1995. Unit Root tests in ARMA models with data dependent methods for the selection of the truncation lag. J. Am. Stat. Assoc. 90, 268–281. Page, S.A.B., 1981. The choice of invoicing currency in merchandise trade. Natl. Institute Econ. Rev., London (98) 60–72. Pauls, B.B., 1987. Measuring the foreign-exchange value of the dollar. Fed. Res. Bull. 73, 411–422. Phillips, P.C.B., Hansen, B.E., 1990. Statistical inference in instrumental variables regression with I(1) processes. Rev. Econ. Stud. 57, 99–125. Phillips, P.C.B., Loretan, M., 1991. Estimating long-run economic equilibria. Rev. Econ. Stud. 58, 407–436. Reimers, H., 1993. Comparison of tests for multivariate cointegration. Stat. Pap. 33, 335–359. Rose, A.K., 1990. Exchange rates and the trade balances: Some evidence from developing countries. Econ. lett. 34, 271–275. Saikkonen, P., 1991. Asymptotically efficient estimation of cointegration regressions. Econ. Theory 7, 1–21. Stock, J.H., Watson, M.W., 1993. A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica 14, 11–30. Warner, D., Kreinin, M.E., 1983. Determinants of international trade flows. Rev. Econ. Stat. 65, 96–104.