Abstract
This paper presents the results of an empirical investigation of the impact of exchange rate variation on the exports of three major Japanese industries—motor vehicles, consumer electronics, and iron and steel. The study is a disaggregated one, with the following five major Japanese exports chosen for analysis: subcompact passenger cars, color television sets, galvanized steel sheet, heavy steel plate, and tin plate.
This paper presents the results of an empirical investigation of the impact of exchange rate variation on the exports of three major Japanese industries—motor vehicles, consumer electronics, and iron and steel. The study is a disaggregated one, with the following five major Japanese exports chosen for analysis: subcompact passenger cars, color television sets, galvanized steel sheet, heavy steel plate, and tin plate.
Determining the extent to which the exchange rate influences trade flows is especially relevant for Japan. One motivation for the adoption of protectionist measures by some of Japan’s major trading partners may be doubts as to the efficiency of the yen exchange rate for adjusting Japan’s trade account. Between 1976 and 1978, in particular, while Japan’s real effective exchange rate appreciated by 24 percent, the surplus on merchandise trade grew from US$2.4 billion in 1976 to US$9.7 billion in 1977 and US$18.2 billion in 1978.1 In 1979 Japan’s trade balance finally deteriorated, registering a deficit of US$7.6 billion, but its real effective exchange rate depreciated in that year by 22 percent.
With comparable rates of technological progress and of foreign and domestic inflation assumed, the magnitude of the impact of the exchange rate on exports depends on how far an exchange rate change is passed through to foreign currency prices of exports and how far export volumes then respond to such price changes. In recent years increasing attention has been devoted to estimating the adjustment of export prices and volumes over the short run as well as over the long run. Volumes have in general been found to adjust less rapidly than prices, leading to perverse short-run movements in merchandise trade balances following an exchange rate change, or “J-curves” (Branson (1972), and Magee (1973)). Thus, this analysis places emphasis on the explicit measurement of the time lags involved in the response of export prices and volumes to exchange rate variation.
Among others, researchers at Japan’s Economic Planning Agency (EPA) have devoted considerable attention to Japan’s trade adjustment problems during the late 1970s (Komine and others (1978) and EPA (1978)). Based on the Agency’s quarterly macroeconomic model, with revised export and import equations to account for lags in adjustment, various simulation exercises were conducted within a general equilibrium framework to estimate the effects of exchange rate changes on various aspects of the Japanese economy. The results of these simulations indicated perverse short-run effects of changes in the yen exchange rate. For example, in fiscal year 1977/78 (April 1977 through March 1978), during which Japan’s nominal effective exchange rate appreciated by an estimated 22 percent and its real effective exchange rate appreciated by an estimated 13 percent (according to the International Financial Statistics of the International Monetary Fund), J-curve effects were estimated to have yielded a US$3.2 billion increase in Japan’s trade balance (EPA (1979, p. 393)). The estimated positive impact amounts to roughly one third of the US$9.7 billion increase in Japan’s trade surplus in 1977/78 over that of the previous year.
Whereas the EPA’s analysis incorporated lags in the adjustment of Japan’s exports and imports to exchange rate changes, Wilson and Takacs (1980) took the analysis one step further by estimating the impact of exchange rate expectations, or leads in adjustment, on the behavior of Japanese trade flows. Specifically, they estimated the extent to which expected appreciations of the yen exchange rate may have led to an export acceleration and import deceleration that exacerbated the perverse movement of the Japanese trade balance during the late 1970s. Their results were rather striking: the estimated J-curve for Japan’s trade balance continued to move in a perverse direction for several quarters subsequent to an exchange rate change and, for most of the adjustment period, implied a considerably larger perverse movement than that implied by a J-curve that incorporated only adjustment lags. Such a result suggests that, between 1977 and 1979, traders’ expectations of a further yen appreciation gave rise to perverse movements in the trade balance that overwhelmed the adjustment of trade flows to past exchange rate changes. Following the approach of Wilson and Takacs, this analysis also incorporates the impact of expectations of relative export prices on the demand for Japan’s exports.
As mentioned previously, this paper examines the response of Japanese exports to changes in the yen exchange rate at a highly disaggregated level, looking at specific major export products. From a theoretical viewpoint, such a disaggregated analysis avoids the aggregation problem of biased elasticity estimates made famous by Orcutt (see Orcutt (1950) and Learner and Stern (1970)). One such problem arises because the response of export prices to exchange rate changes varies across industries, since suppliers differ in the extent to which they maintain prices in line with those of foreign competitors; an aggregate demand equation therefore implies biased estimates. Another reason for the disaggregation is that tensions between Japan and her trading partners have tended to focus on specific industries, such as steel in the late 1970s and automobiles, electronic equipment, and machine tools in the 1980s. Exports of the industries sampled—that is, motor vehicles, consumer electronics, and iron and steel goods—accounted for 34 percent of the U.S. dollar value of Japan’s total exports during the 1975-79 period and have, in addition, all been involved in recent disputes between Japan and her trading partners.
Simultaneous-equations models of the supply of and demand for both exports and domestic sales of each product considered were estimated. The theoretical model specifies the following dynamic elements in the adjustment process: the extent to which an exchange rate change is passed through to foreign currency export prices over time; leads and lags in the response of export orders to relative export price changes; and delivery lags between orders and shipments. Although the analysis does take into account the indirect impact of exchange rate shifts on export prices through changes in prices of imported raw materials, the study is partial equilibrium in nature in the sense that foreign prices, wages, inventory accumulation, and the exchange rate are treated as exogenous. Given the unique characteristics of the Japanese labor market, the tendency for wage increases to be linked to profitability of firms, and the observed flexibility in real wages in Japan, the assumption of exogenous wages may not be overly restrictive. (See Komiya and Suzuki (1977) and Shinkai (1982).) In addition, wages account for a small proportion of total variable costs for all of the sample products, as indicated by input-output coefficients (see the Appendix).
I. The Model
This section presents the basic theoretical model of demand for and supply of exports and domestic sales underlying the empirical analysis presented in the paper. The additional product-specific variables included in the estimation are reviewed in the discussion of the estimation results.
Demand Side
The demand side of the model consists of four equations. For both exports and domestic sales, the model specifies a demand equation that determines factory orders and an equation that specifies actual shipments as a function of current and past orders.
Export orders are specified in real terms as a log-linear function of foreign income, the relative price of exports, and a non-price-rationing variable. (Demand theory provides little guidance on the appropriate functional form. The choice is thus essentially an empirical one, and the log-linear formulation is adopted on the basis of work by Khan and Ross (1977).) Nonprice rationing is incorporated on the assumption that, since quoted prices may be relatively sticky in the short run, goods markets are also cleared by variables such as changes in delivery dates, length of queues, or credit terms. Because nonprice rationing is essentially cyclical, it is represented by the ratio of inventories to the volume of total (export and domestic) orders.2 Past values of foreign income and the relative export price are included because recognition and other lags may delay the response of export orders to changes in these factors, and expected relative export prices are included to account for the impact of price and exchange rate expectations on current export demand. The volume of export orders (XO) at time t is therefore specified as follows:
where YF is foreign activity (in real terms); PX is the contract export price in domestic currency; R is the yen-per-foreign-currency effective exchange rate, weighted according to export market shares; PF is the weighted average foreign price, with weights as for the exchange rate (R); and IO is the ratio of inventories to total volume of orders.
Equation (1) takes account of adjustment lags in explaining export demand. Actual export shipments, however, represent a flow of goods generated by orders placed at some time in the past. With a constant delivery-lag structure, the volume of export shipments (QX) at time t is specified according to the following linear relation:
where Σbi equals 1, and bi is the share of export orders at time (t - i) shipped at time t. This equation should not be specified in log-linear form since, as orders fluctuate over time, the relative shares of current and past orders in current shipments will also vary. In addition, the vector of delivery-lag coefficients (the bi) should vary over time, as a function (for instance) of the ratio of unfilled orders to current production. Such variations are not considered here; see Hooper (1976), Ahluwalia and Hernández-Catá (1975) and Artus (1973, 1974) for a similar treatment of delivery lags in the determination of shipments and unit values of trade flows.
Domestic orders (DO) and shipments (QD) are derived analogously and are specified (with time subscripts deleted) as follows:
and
where Σdi, equals 1; YD is domestic activity (in real terms); and RPD is the relative domestic price, defined as the domestic price of the good relative to competing domestic prices. Import prices are not included in the equation because imports to Japan of the products considered in this paper are small.
Supply Side
The supply side of the model is developed within the context of a firm that discriminates between its export and domestic markets. The derivation proceeds as follows for both export and domestic sales. First, the optimal short-run price is derived from the theory of a firm that maximizes profits subject to a short-run production function; because the model considers adjustment in the short to medium term, the stock of capital is regarded as fixed. Second, the optimal adjustment path for contract prices is determined by incorporating certain longer-run considerations in addition to short-run profits. The above steps are then integrated to yield an equation for the actual contract price.
Maximizing total profits from both exports and domestic sales subject to a production function yields the familiar first-order condition that sets the optimal short-run export price (PX*) equal to a markup over marginal cost, as follows:
where NX is the price elasticity of export demand, and MC is the marginal cost of production.
The vintage capital production function of de Menil (1974) is used to determine short-run marginal cost. Under this model, machines of different vintages are each assumed to have a fixed-coefficient production function given by:
where Qv is the output from capital of vintage v; Kv is the amount of capital of vintage v in operation; Lv is the amount of labor employed by capital of vintage v; RMv is the amount of raw materials employed by capital of vintage v; and b and c are the fixed coefficients of production.
Labor and raw materials are combined by a Cobb-Douglas process into a composite variable input, with the assumption of constant returns to scale, so that a1 + a2 equals 1. Embodied technical change raises the efficiency of new machines at the rate of r1 and disembodied technical change raises the efficiency of all machines at the rate of r2.
Short-run marginal cost is derived by noting that marginal cost for the firm is equal to the marginal cost of production on the oldest machine in operation and is given by the following expression:3
where W is the wage rate; PRM is the price of raw materials; and v′ is the vintage of the oldest machine in operation. Replacing v’ by (t - U), where U is the age of the oldest machine in operation, and substituting equation (7) into equation (5) allows the optimal short-run export price to be written according to the following log-linear expression:
where
B = ln[(1 + 1/NX)-1(1/a1)a1(1/a2)a2b].
The second stage of the derivation of the export price involves the determination of its optimal adjustment path in domestic currency. The contract export price may deviate from the short-run optimum because of several factors. Prices in domestic currency may be sticky because of administrative costs of frequent price changes or general uncertainty about the reactions of either buyers or competitors to price changes. Firms exporting goods in competitive markets or those with a strong preference for maintaining or expanding market shares will be inclined, if necessary, to sacrifice short-term profits to stay in line with competitors’ prices. In addition, firms may be willing to cut prices to smooth out fluctuations in levels of inventories or in rates of capacity utilization; this applies especially to firms with a relatively high proportion of fixed costs.
The contract export price is assumed to be set to achieve the best possible compromise between the short-run profit maximization target and the additional considerations noted above. The contract export price (PX) at time t is determined by minimizing the total cost from not meeting all targets simultaneously:4
where L is the total loss subjectively perceived by suppliers; l1 is the loss coefficient associated with deviating from the short-run optimum, and l2 is that associated with not maintaining price stability. The loss related to the price-competitiveness target is split into two elements—13 reflects the loss from deviating from the competing foreign price in terms of its level, and the l4i are the loss coefficients on price changes over various time horizons that differ from those of competitors. The first coefficient measures the desire of firms to stay in line with competing prices in the long run; the second set of coefficients determines losses associated with short-run relative price changes, and k is thus finite and assumed to be small. Finally, l5 determines the loss resulting from fluctuation in real activity, which is represented by the ratio of inventories to total orders.
Minimizing the loss function (10) with respect to PX, the contract export price, while assuming a constant short-run export price elasticity of the inventory-orders ratio (NIO, PX), one obtains:
where m1 equals l1/S; m2 equals l2/S m3 equals l3/S; m4i equals l4i/S; m5 equals -l5 NIO, PX/S, and S is equal to l1 + l2 + l3 + Σl4i.
The equation determining the contract export price is now obtained by substituting equation (9) into equation (11) and combining terms:
The domestic contract price equation is similarly derived. In determining the adjustment path of the domestic price, it is assumed that firms on the domestic market achieve the best possible compromise between short-run profits, price stability, and “cyclical smoothness.” Given the limited extent of import penetration into the Japanese markets of the products sampled in this paper, the maintenance of competitiveness relative to imports is not considered. The domestic contract price (PD) is thus specified as follows:
The theoretical model utilized as a basis for the empirical analysis consists, therefore, of equations for the volumes of export orders and shipments, equations (1) and (2); the volumes of domestic orders and shipments, equations (3) and (4); the contract export price, equation (12); and the contract domestic price, equation (13).
II. Estimation Results
This section presents the results obtained by applying the theoretical model presented above to the estimation of prices and quantities (domestic and export) of Japanese subcompact passenger cars, color television sets, galvanized steel sheet, heavy steel plate, and tin plate (see the Appendix for a detailed description of the data). Separate equations for orders and shipments were estimated only for heavy steel and tin plate, owing to a lack of adequate data for the other three products. In addition to the variables specified in the basic model, explanatory variables relevant to specific products were also included. The price of gasoline relative to other consumer items (in the United States) was included in the demand equation for subcompact automobile exports, to take account of the dramatic shift in consumer preferences toward Japanese cars, particularly in the United States, as a result of the oil price increases during the 1970s. Dummy variables were employed to account for export restraint agreements during the sample period with respect to color television sets and steel products. The proxies for expected relative export prices were created by utilizing ARIMA time-series techniques to generate separate forecasts for export prices, foreign prices, and exchange rates.
The structural model of simultaneous supply and demand, also including lagged endogenous variables, was estimated according to an iterative estimation procedure appropriate for such systems.5 Statistical estimation was based on monthly data over the 1970-79 period; thus, whereas the theoretical relations of the model would be appropriate in any current applications, the estimates of its behavioral parameters are strictly applicable to only the sample period.
Regression results for the export equations are presented in Table 1. (Because of the relatively complex estimation methodology, preliminary regressions were run using single-equation techniques to determine lag lengths and to ascertain whether to include certain variables in the final estimation.) The model performs quite well, as indicated by the R2 calculated with respect to the original data (before transformation of the data to account for serial correlation), except for the equations for shipments and orders of tin plate. In addition, the estimated coefficients of the explanatory variables included in the simultaneous-equations estimation procedure all have the expected signs.
Regression Estimates for Export Volume and Price Equations
In months.
The time horizon for relative export price expectations was assumed to be three months for all products.
Significance level of F-statistics for distributed lag structure including the expected relative price terms.
Significance level of F-statistics for distributed lag structure related to foreign competing prices.
Regression Estimates for Export Volume and Price Equations
| Subcompact | Color | Galvanized | Heavy | Tin | |||
|---|---|---|---|---|---|---|---|
| Variable | Passenger Cars | Television Sets | Steel Sheet | Steel Plate | Plate | ||
| Export shipments | |||||||
| (QX) | |||||||
| XO [lag length] 1 | … | … | … | 1 [5] | 1 [5] | ||
| R2 | … | … | … | 0.729 | 0.560 | ||
| Export demand | |||||||
| (ln XO) | |||||||
| ln (PGAS) | 1.32 (5.81) | … | … | … | … | ||
| ln (IO) | 0.04 (0.77) | 0.16 (1.78) | 0.22 (3.57) | 0.61 (3.08) | 0.94 (3.34) | ||
| ln (YF) [lagged terms] | 0.97 [2] | 0.79 [2] | 1.73*** [2] | 0.94*** [2] | 0.36 [2] | ||
| ln [RPX)e2 | 0.10*** 3 | -0.78** 3 | 0.001 | -0.13 | 1.15 | ||
| ln (RPX) [lagged terms] | -2.80*** 3 [18] | -2.18** 3 [13] | -1.06 [10] | -0.65 [4] | -2.65 [15] | ||
| R2 | 0.936 | 0.915 | 0.861 | 0.823 | 0.466 | ||
| Export price | |||||||
| (ln PX) | |||||||
| ln (VCOST) | 0.15 | 0.14 | 0.070 | 0.46 | 0.023 | ||
| (3.95) | (3.61) | (1.80) | (4.88) | (1.23) | |||
| ln (IO) | -0.016 (-3.79) | … | -0.027 (-2.50) | … | … | ||
| ln (PF⋅R) 4 | 0.43*** | 0.66*** | 0.47*** | 0.54*** | 0.47*** | ||
| ln (PX/PF⋅R)-14 | 0.23*** | 0.38*** | 0.28*** | 0.29*** | 0.29*** | ||
| ln (PX/PF⋅R)-24 | 0.71*** | 0.22*** | 0.17*** | 0.13*** | 0.077*** | ||
| ln (PX)-1 | 0.42 | 0.20 | 0.46 | … | 0.50 | ||
| (6.32) | (3.77) | (4.49) | (5.78) | ||||
| R2 | 0.990 | 0.980 | 0.990 | 0.987 | 0.990 | ||
In months.
The time horizon for relative export price expectations was assumed to be three months for all products.
Significance level of F-statistics for distributed lag structure including the expected relative price terms.
Significance level of F-statistics for distributed lag structure related to foreign competing prices.
Regression Estimates for Export Volume and Price Equations
| Subcompact | Color | Galvanized | Heavy | Tin | |||
|---|---|---|---|---|---|---|---|
| Variable | Passenger Cars | Television Sets | Steel Sheet | Steel Plate | Plate | ||
| Export shipments | |||||||
| (QX) | |||||||
| XO [lag length] 1 | … | … | … | 1 [5] | 1 [5] | ||
| R2 | … | … | … | 0.729 | 0.560 | ||
| Export demand | |||||||
| (ln XO) | |||||||
| ln (PGAS) | 1.32 (5.81) | … | … | … | … | ||
| ln (IO) | 0.04 (0.77) | 0.16 (1.78) | 0.22 (3.57) | 0.61 (3.08) | 0.94 (3.34) | ||
| ln (YF) [lagged terms] | 0.97 [2] | 0.79 [2] | 1.73*** [2] | 0.94*** [2] | 0.36 [2] | ||
| ln [RPX)e2 | 0.10*** 3 | -0.78** 3 | 0.001 | -0.13 | 1.15 | ||
| ln (RPX) [lagged terms] | -2.80*** 3 [18] | -2.18** 3 [13] | -1.06 [10] | -0.65 [4] | -2.65 [15] | ||
| R2 | 0.936 | 0.915 | 0.861 | 0.823 | 0.466 | ||
| Export price | |||||||
| (ln PX) | |||||||
| ln (VCOST) | 0.15 | 0.14 | 0.070 | 0.46 | 0.023 | ||
| (3.95) | (3.61) | (1.80) | (4.88) | (1.23) | |||
| ln (IO) | -0.016 (-3.79) | … | -0.027 (-2.50) | … | … | ||
| ln (PF⋅R) 4 | 0.43*** | 0.66*** | 0.47*** | 0.54*** | 0.47*** | ||
| ln (PX/PF⋅R)-14 | 0.23*** | 0.38*** | 0.28*** | 0.29*** | 0.29*** | ||
| ln (PX/PF⋅R)-24 | 0.71*** | 0.22*** | 0.17*** | 0.13*** | 0.077*** | ||
| ln (PX)-1 | 0.42 | 0.20 | 0.46 | … | 0.50 | ||
| (6.32) | (3.77) | (4.49) | (5.78) | ||||
| R2 | 0.990 | 0.980 | 0.990 | 0.987 | 0.990 | ||
In months.
The time horizon for relative export price expectations was assumed to be three months for all products.
Significance level of F-statistics for distributed lag structure including the expected relative price terms.
Significance level of F-statistics for distributed lag structure related to foreign competing prices.
Looking first at the export demand equations, one finds that the distributed lag structure on foreign income is statistically significant at the 5 percent level for only two of the five products considered—heavy steel plate and galvanized steel sheet. 6 Further analysis suggests that the insignificance of the distributed lags for the other three products reflects an even quicker response of export demand with respect to changes in foreign income than specified. Regressions that include only current foreign income and foreign income lagged one month show a significant estimated coefficient on foreign income for subcompact cars and tin plate, and on lagged foreign income for color television sets.
Relative export prices are significant at the 5 percent level only in the export demand equations for subcompact cars and color television sets; they are significant, however, at the 15 percent level for export demand for heavy steel plate and tin plate. The non-price-rationing variable (the inventory-sales ratio) is significant for all but one product, subcompact passenger cars; it is particularly significant with a large estimated coefficient for the three steel products, suggesting the initiation of “export drives” during times of weak domestic demand.
Table 2 presents the structural equation effects of various factors on export volumes and prices in the long run. (These effects are based on single-equation results and do not take account of the simultaneity of the model. Because of the nonlinear nature of the specified model, in-sample simulation of the estimated model is required to calculate the simultaneous effects of changes in exogenous variables. The presence of the inventory sales ratio as an explanatory variable makes the model nonlinear in logarithms and prevents a reduced-form solution. Thus, reduced-form elasticities cannot be calculated.) Export demand is estimated to be quite responsive to relative price changes for subcompact cars and color television sets, but it is relatively price inelastic for the three steel products. The results shown in the first and second parts of Table 2 indicate that export shipments are estimated to adjust to a relative price change with a lag ranging from 9 months for heavy steel plate to 20 months for tin plate.
Long-Run Effects of Selected Factors on Japanese Export Volumes and Prices: Estimates of Structural Equations
The cumulative elasticity of shipments with respect to orders was constrained to be equal to 1.
Sum of the structural coefficients of relative export prices.
Cumulative elasticity estimate within 1 percent of long-run solution.
Long-Run Effects of Selected Factors on Japanese Export Volumes and Prices: Estimates of Structural Equations
| Factor | Long-Run Elasticity | Adjustment Period (In months) | ||
|---|---|---|---|---|
| Export shipments equations | ||||
| Export orders | ||||
| Heavy steel plate | 1.001 | 5 | ||
| Tin plate | 1.001 | 5 | ||
| Export demand equations | ||||
| Relative export price | ||||
| (including expectations) | ||||
| Subcompact passenger cars | -2.702 | 18 | ||
| Color television sets | -2.962 | 13 | ||
| Galvanized steel sheet | -1.062 | 10 | ||
| Heavy steel plate | -0.782 | 4 | ||
| Tin plate | -1.512 | 15 | ||
| Contract export price equations | ||||
| Foreign competing prices | ||||
| Subcompact passenger cars | 0.47 | 4 | ||
| Color television sets | 0.30 | 26 | ||
| Galvanized steel sheet | 0.21 | 363 | ||
| Heavy steel plate | 0.20 | 6 | ||
| Tin plate | 0.85 | 23 | ||
The cumulative elasticity of shipments with respect to orders was constrained to be equal to 1.
Sum of the structural coefficients of relative export prices.
Cumulative elasticity estimate within 1 percent of long-run solution.
Long-Run Effects of Selected Factors on Japanese Export Volumes and Prices: Estimates of Structural Equations
| Factor | Long-Run Elasticity | Adjustment Period (In months) | ||
|---|---|---|---|---|
| Export shipments equations | ||||
| Export orders | ||||
| Heavy steel plate | 1.001 | 5 | ||
| Tin plate | 1.001 | 5 | ||
| Export demand equations | ||||
| Relative export price | ||||
| (including expectations) | ||||
| Subcompact passenger cars | -2.702 | 18 | ||
| Color television sets | -2.962 | 13 | ||
| Galvanized steel sheet | -1.062 | 10 | ||
| Heavy steel plate | -0.782 | 4 | ||
| Tin plate | -1.512 | 15 | ||
| Contract export price equations | ||||
| Foreign competing prices | ||||
| Subcompact passenger cars | 0.47 | 4 | ||
| Color television sets | 0.30 | 26 | ||
| Galvanized steel sheet | 0.21 | 363 | ||
| Heavy steel plate | 0.20 | 6 | ||
| Tin plate | 0.85 | 23 | ||
The cumulative elasticity of shipments with respect to orders was constrained to be equal to 1.
Sum of the structural coefficients of relative export prices.
Cumulative elasticity estimate within 1 percent of long-run solution.
Relative price expectations are estimated to have a strong impact on the export demand for tin plate and for color television sets. The elasticity of tin plate export orders with respect to expected relative export prices (the sum of the estimated coefficients on the variables for relative price expectations) is estimated to amount to 1.15. This implies a considerable initial increase (decrease) in export demand for tin plate subsequent to a rise (fall) in relative export prices, owing to anticipations of further price increases (decreases) in the near future. For color television sets, however, the estimated price expectations elasticity of export demand is equal to -0.78; this indicates an initial fall (rise) in foreign demand following an effective appreciation (depreciation), reflecting expectations of a reversal in relative prices in the future. During the 1970-79 sample period, when there was a trend appreciation of the yen exchange rate, one would expect that expectations would have had a temporary positive effect on export demand; such an impact was found, by Wilson and Takacs (1980), to have been an important effect of exchange rate changes on total Japanese exports during 1972-78. The opposite result, obtained in the case of exports of color television sets, could reflect the competitive nature of the North American market during the 1970s, where customers expected that exchange rate changes soon would be offset by cost-cutting or quality-improving technological advances by Japanese suppliers.
With regard to the export price equations, the lag structures related to competing foreign prices, the lagged export price (representing the price-stability target), and the price of variable inputs are all significant at the 5 percent level, with the exception of the lagged export price for heavy steel plate (insignificant and not included) and the price of variable inputs for tin plate (significant at the 11 percent level). (Wages and raw material prices are combined into a single-variable cost term according to input-output weights in order to overcome multicollinearity problems encountered in the estimation process. See the Appendix.) The export price seems to respond to cyclical conditions in the case of sub-compact cars and galvanized steel sheet; the vintage of the capital stock is not estimated to affect the export price of any product significantly.
Reflecting the significance of the competing-price and lagged export price variables, the estimation results indicate that contract export prices can deviate significantly from levels based purely on profit-maximizing considerations. In the short run, export prices in domestic currency are estimated to respond to changes in foreign prices for all products; the implication is that exchange rate changes are not fully passed through to foreign currency prices. The results also suggest that exchange rate changes may not be fully passed through in the long run. The estimated long-run foreign price (or exchange rate) elasticity of the contract export price in yen ranges from 0.85 (for tin plate) to 0.20 (for heavy plate); that is, the pass-through estimates range, correspondingly, between 15 percent and 80 percent. The long-run elasticity estimates are all significantly different from zero except in the case of galvanized steel sheet.7 The adjustment period is estimated to be relatively short for subcompact cars and heavy steel plate and to be quite long for color television sets, galvanized steel sheet, and tin plate, although a substantial portion of the adjustment for the latter group is estimated to occur within 12 months.
III. Simulation Results
To account for simultaneity, the impact of a hypothetical 10 percent appreciation of the yen was simulated for each product over the period 1977-79. Simulations were run on the estimated models according to two constant exchange rates during 1977-79, one at the December 1976 level and the other at a level 10 percent higher, and the results were then compared to determine the impact of appreciation. The simulation exercise also incorporated estimates of the indirect impact of appreciation on contract export prices due to changes in raw material costs. 8 The simulated exchange rate effects over time are presented in Table 3. The adjustment of prices and volumes may be viewed as virtually complete within a three-year period subsequent to the hypothetical 10 percent appreciation in January 1977.
Simulated Cumulative Impact of 10 Percent Appreciation of the Yen in January 1977 on Prices and Volumes of Japanese Exports, 1977-79
(In percent)
Simulated Cumulative Impact of 10 Percent Appreciation of the Yen in January 1977 on Prices and Volumes of Japanese Exports, 1977-79
(In percent)
| Monthly Period | Contract Export Prices (In yen) | Export Orders | Export Shipments | |
|---|---|---|---|---|
| Subcompact passenger cars | ||||
| 1977 | ||||
| January | -4.1 | … | 0.6 | |
| April | -4.7 | … | -0.2 | |
| July | -4.8 | … | -2.1 | |
| October | -4.8 | … | -5.3 | |
| 1978 | ||||
| January | -4.9 | … | -8.8 | |
| April | -5.0 | … | -11.1 | |
| July | -5.0 | … | -11.6 | |
| October | -5.0 | … | -11.4 | |
| 1979 | ||||
| January | -5.1 | … | -11.1 | |
| April | -5.1 | … | -11.0 | |
| July | -5.1 | … | -10.9 | |
| October | -5.2 | … | -10.8 | |
| December | -5.2 | … | -10.8 | |
| Color television sets | ||||
| 1977 | ||||
| January | -6.1 | … | -5.0 | |
| April | -5.3 | … | -4.8 | |
| July | -4.6 | … | -8.1 | |
| October | -4.1 | … | -10.8 | |
| 1978 | ||||
| January | -3.9 | … | -12.7 | |
| April | -3.7 | … | -13.5 | |
| July | -3.6 | … | -13.8 | |
| October | -3.6 | … | -14.2 | |
| 1979 | ||||
| January | -3.6 | … | -14.4 | |
| April | -3.5 | … | -14.6 | |
| July | -3.5 | … | -14.4 | |
| October | -3.5 | … | -14.5 | |
| December | -3.5 | … | -14.7 | |
| Galvanized steel sheet | ||||
| 1977 | ||||
| January | -4.4 | … | -0.6 | |
| April | -4.8 | … | -2.3 | |
| July | -4.6 | … | -3.7 | |
| October | -4.5 | … | -4.4 | |
| 1978 | ||||
| January | -4.4 | … | -4.8 | |
| April | -4.3 | … | -4.8 | |
| July | -4.2 | … | -4.9 | |
| October | -4.2 | … | -5.0 | |
| 1979 | ||||
| January | -4.1 | … | -5.2 | |
| April | -4.1 | … | -5.1 | |
| July | -4.1 | … | -5.2 | |
| October | -4.1 | … | -5.2 | |
| December | -4.1 | … | -5.1 | |
| Heavy steel plate | ||||
| 1977 | ||||
| January | -5.3 | -1.6 | -0.1 | |
| April | -3.8 | -3.8 | -1.9 | |
| July | -3.4 | -4.4 | -3.9 | |
| October | -3.4 | -4.9 | -4.6 | |
| 1978 | ||||
| January | -3.4 | -5.1 | -5.0 | |
| April | -3.4 | -5.2 | -5.2 | |
| July | -3.4 | -5.4 | -5.3 | |
| October | -3.4 | -5.5 | -5.4 | |
| 1979 | ||||
| January | -3.4 | -5.7 | -5.6 | |
| April | -3.4 | -5.8 | -5.7 | |
| July | -3.4 | -6.1 | -5.9 | |
| October | -3.4 | -6.2 | -6.1 | |
| December | -3.4 | -6.4 | -6.2 | |
| Tin plate | ||||
| 1977 | ||||
| January | -4.4 | 5.5 | 0.7 | |
| April | -6.1 | 0.6 | 1.5 | |
| July | -6.8 | -1.7 | -0.1 | |
| October | -7.3 | -3.6 | -2.1 | |
| 1978 | ||||
| January | -7.6 | -4.2 | -3.6 | |
| April | -7.7 | -3.4 | -3.8 | |
| July | -7.9 | -2.7 | -3.2 | |
| October | -7.9 | -2.3 | -2.7 | |
| 1979 | ||||
| January | -8.0 | -2.1 | -2.3 | |
| April | -8.0 | -1.9 | -2.1 | |
| July | -8.0 | -1.9 | -1.9 | |
| October | -8.0 | -1.7 | -1.8 | |
| December | -8.0 | -1.7 | -1.8 | |
Simulated Cumulative Impact of 10 Percent Appreciation of the Yen in January 1977 on Prices and Volumes of Japanese Exports, 1977-79
(In percent)
| Monthly Period | Contract Export Prices (In yen) | Export Orders | Export Shipments | |
|---|---|---|---|---|
| Subcompact passenger cars | ||||
| 1977 | ||||
| January | -4.1 | … | 0.6 | |
| April | -4.7 | … | -0.2 | |
| July | -4.8 | … | -2.1 | |
| October | -4.8 | … | -5.3 | |
| 1978 | ||||
| January | -4.9 | … | -8.8 | |
| April | -5.0 | … | -11.1 | |
| July | -5.0 | … | -11.6 | |
| October | -5.0 | … | -11.4 | |
| 1979 | ||||
| January | -5.1 | … | -11.1 | |
| April | -5.1 | … | -11.0 | |
| July | -5.1 | … | -10.9 | |
| October | -5.2 | … | -10.8 | |
| December | -5.2 | … | -10.8 | |
| Color television sets | ||||
| 1977 | ||||
| January | -6.1 | … | -5.0 | |
| April | -5.3 | … | -4.8 | |
| July | -4.6 | … | -8.1 | |
| October | -4.1 | … | -10.8 | |
| 1978 | ||||
| January | -3.9 | … | -12.7 | |
| April | -3.7 | … | -13.5 | |
| July | -3.6 | … | -13.8 | |
| October | -3.6 | … | -14.2 | |
| 1979 | ||||
| January | -3.6 | … | -14.4 | |
| April | -3.5 | … | -14.6 | |
| July | -3.5 | … | -14.4 | |
| October | -3.5 | … | -14.5 | |
| December | -3.5 | … | -14.7 | |
| Galvanized steel sheet | ||||
| 1977 | ||||
| January | -4.4 | … | -0.6 | |
| April | -4.8 | … | -2.3 | |
| July | -4.6 | … | -3.7 | |
| October | -4.5 | … | -4.4 | |
| 1978 | ||||
| January | -4.4 | … | -4.8 | |
| April | -4.3 | … | -4.8 | |
| July | -4.2 | … | -4.9 | |
| October | -4.2 | … | -5.0 | |
| 1979 | ||||
| January | -4.1 | … | -5.2 | |
| April | -4.1 | … | -5.1 | |
| July | -4.1 | … | -5.2 | |
| October | -4.1 | … | -5.2 | |
| December | -4.1 | … | -5.1 | |
| Heavy steel plate | ||||
| 1977 | ||||
| January | -5.3 | -1.6 | -0.1 | |
| April | -3.8 | -3.8 | -1.9 | |
| July | -3.4 | -4.4 | -3.9 | |
| October | -3.4 | -4.9 | -4.6 | |
| 1978 | ||||
| January | -3.4 | -5.1 | -5.0 | |
| April | -3.4 | -5.2 | -5.2 | |
| July | -3.4 | -5.4 | -5.3 | |
| October | -3.4 | -5.5 | -5.4 | |
| 1979 | ||||
| January | -3.4 | -5.7 | -5.6 | |
| April | -3.4 | -5.8 | -5.7 | |
| July | -3.4 | -6.1 | -5.9 | |
| October | -3.4 | -6.2 | -6.1 | |
| December | -3.4 | -6.4 | -6.2 | |
| Tin plate | ||||
| 1977 | ||||
| January | -4.4 | 5.5 | 0.7 | |
| April | -6.1 | 0.6 | 1.5 | |
| July | -6.8 | -1.7 | -0.1 | |
| October | -7.3 | -3.6 | -2.1 | |
| 1978 | ||||
| January | -7.6 | -4.2 | -3.6 | |
| April | -7.7 | -3.4 | -3.8 | |
| July | -7.9 | -2.7 | -3.2 | |
| October | -7.9 | -2.3 | -2.7 | |
| 1979 | ||||
| January | -8.0 | -2.1 | -2.3 | |
| April | -8.0 | -1.9 | -2.1 | |
| July | -8.0 | -1.9 | -1.9 | |
| October | -8.0 | -1.7 | -1.8 | |
| December | -8.0 | -1.7 | -1.8 | |
The results of full model simulation indicate once again that exchange rate changes are partially offset by movements in export prices in domestic currency terms and, therefore, are not fully reflected in prices in foreign markets. The extent to which the domestic currency price is estimated to decline during the three-year period following a 10 percent appreciation ranges from a high of 8.0 percent for tin plate to 3.4 percent for heavy steel plate. The simulated decreases in export prices (in yen) are greater than those based on the structural coefficient estimates implied by the third part of Table 2; the difference can be attributed almost totally to the fall in raw material prices following an appreciation. For subcompact cars and galvanized steel sheet, the significant cyclical variable in the export price equation has an additional, albeit marginal, negative effect. The offsetting effect of lower raw material costs on export prices is most significant for heavy steel plate and for galvanized steel sheet, reflecting the importance of imported inputs in Japan’s steel industry coupled with a large estimated coefficient on the variable input cost term in the export price equation.
A relatively rapid adjustment of the export price toward its long-run position is simulated for all products; the adjustment occurs almost immediately for subcompact cars and heavy steel plate. The products are split into two groups, however, with respect to whether the domestic-currency price response increases or decreases over time. For color television sets, heavy steel plate, and galvanized steel sheet, the fall in the contract export price in yen terms decreases over time, reflecting increasing pressure to move back toward a profit-maximizing price. For subcompact cars and, in particular, tin plate, however, the price declines continuously with time. In the case of subcompact cars, the slight further increase in the price response is attributable largely to the lagged response of lower raw material prices to appreciation. The adjustment path for tin plate reflects slow adjustment from the pre-appreciation price because of a large estimated coefficient on the lagged export price; this price stickiness in turn may be due to strong supplier preference for minimizing price fluctuation so as to reduce administrative costs or to prevent the loss of goodwill among customers.
A 10 percent appreciation causes considerable declines in export volumes of subcompact cars (10.8 percent) and of color television sets (14.7 percent). Exports of the three steel products, and particularly those of tin plate, however, are quite inelastic with respect to the exchange rate; the estimated decline in volume amounts to 6 percent or less. For all items, the exchange rate responsiveness of export volumes is substantially lower than that indicated by the estimated structural relative price elasticities, primarily because the appreciation is not fully passed through to export prices in foreign currency.
The simulations indicate that export volumes adjust to appreciation with a considerable lag. Nevertheless, over three fourths of the response of shipments occurs during the first year for all five products. With the exception of tin plate exports, volumes are largely observed to decline gradually toward long-run levels. For tin plate, however, the results indicate a considerable positive response of volumes in the short run; this unusual movement reflects the estimated strong positive impact of exchange rate expectations on export orders as demand rises initially due to expectations of further appreciation in the near future.
A stronger yen is estimated to have a dampening long-run effect on the value of exports in foreign currency for two of the five products in the sample, subcompact cars and color television sets (Table 4). For these two items, export value is estimated to adjust downward as the decline in volume in the long run becomes large enough to exceed the increase in the foreign currency price. With respect to the three steel products, however, yen appreciation is estimated to cause small positive movements of export value in the long run; this counterintuitive result reflects inelastic price responsiveness of demand.
Simulated Long-Run Impact of 10 Percent Appreciation of the Yen on Export Shipment Values in Foreign Currency
(In percent)
Simulated Long-Run Impact of 10 Percent Appreciation of the Yen on Export Shipment Values in Foreign Currency
(In percent)
| Product | Response of Export Value |
|---|---|
| Subcompact passenger cars | -6.0 |
| Color television sets | -8.2 |
| Galvanized steel sheet | 0.8 |
| Heavy steel plate | 0.4 |
| Tin plate | 0.2 |
Simulated Long-Run Impact of 10 Percent Appreciation of the Yen on Export Shipment Values in Foreign Currency
(In percent)
| Product | Response of Export Value |
|---|---|
| Subcompact passenger cars | -6.0 |
| Color television sets | -8.2 |
| Galvanized steel sheet | 0.8 |
| Heavy steel plate | 0.4 |
| Tin plate | 0.2 |
The dynamic response of export values over the adjustment period may not be precisely calculated for all products, since the lack of data about orders for some items prevented estimation of the dynamic response of unit values. (Export unit value at time of delivery is a function of the order-delivery lag structure, the currency denomination of trade contracts, and exchange rate changes between order and delivery; see Artus (1974), for instance.) Nevertheless, the results indicate the presence of significant J-curve effects. In addition to an increase in the value of exports of the three steel products throughout the adjustment period, the slow response of export volumes while contract export prices increase in foreign currency terms suggests a considerable rise in the export value of subcompact cars during most of the first year after yen appreciation.
IV. Conclusions
Notwithstanding that the simulation results are strictly applicable to only the 1977-79 period, 9 several implications seem well established. For all five Japanese export items studied, the impact of exchange rate changes on exports is subject to lags on both the supply side and the demand side, with the adjustment of demand being particularly slow. Furthermore, competitors’ prices appear to play an important role in the pricing decisions of suppliers; thus, exchange rate changes are not fully passed through to export prices (in foreign currency), either in the short run or in the long run. (The estimated lack of full pass-through in the long run may reflect suppliers’ expectations of relative productivity gains, lower real wages, or offsetting future exchange rate movements.)
The analysis clearly indicates that exchange rate effects over time differ by product. The exchange rate does seem to work as a tool for adjusting Japan’s subcompact passenger car and color television exports, even though adjustment is particularly slow in the case of automobiles. (This result, of course, is based on the 1970-79 sample period and should be interpreted with caution in the presence of voluntary export restraints.) The exchange rate does not seem to have as great an impact on the various exports of Japan’s iron and steel industry; indeed, export values in foreign currency of these products are estimated to increase after appreciation. Even though such products are in general considered to be homogeneous, Japanese suppliers seem to face relatively price-inelastic foreign demand for the three steel products in the sample; this price inelasticity of demand suggests that quality may be a significant factor in world demand for Japanese iron and steel products. Moreover, the relative importance of the non-price-rationing and cyclical variables in the demand equations suggests that suppliers in the steel industry place a premium on the maintenance of stable production levels and prices.
In addition to the partial equilibrium nature of some aspects of the model, the divergence of estimated effects of an exchange rate change by product cautions one against generalizing the results obtained to an aggregate level. Although the results suggest that the full response of aggregate exports will entail a lag of at least one year and that exchange rate changes may not be fully passed through to foreign currency prices in the aggregate, additional estimation is required that would incorporate other major Japanese export industries. Further analysis would preferably be conducted on a disaggregated basis, since changes in commodity composition will alter the adjustment of Japan’s aggregate exports to shifts in exchange rates.
APPENDIX: Data Sources and Methodology
The data employed in the empirical analysis were obtained from a number of sources and were constructed as described below.
Export Shipments and Orders
Volumes of Japanese export shipments were obtained from the Japan Tariff Association, Japan Exports and Imports (Tokyo: JTA, various issues). The export commodities covered by the study are: (1) subcompact passenger cars, or passenger cars with engines of a piston displacement of not more than 2,000 cubic centimeters; (2) color television broadcast receivers, including chassis and kits; (3) heavy steel plate, or sheets and plates of iron and steel not less than 6 millimeters in thickness; (4) tin plate, or trimmed sheets, plates, hoops, and strips of iron and steel; and (5) galvanized steel sheets, plates, hoops, and strips of iron and steel.
Export order volumes of heavy steel plate and tin plate were obtained from the Japan Iron and Steel Federation (JISF).
Domestic Shipments and Orders
Volumes of domestic shipments and orders were obtained from Japan’s Ministry of International Trade and Industry (MITI) and JISF sources, respectively, with commodity coverage equivalent to that defined for export volumes above.
Foreign and Domestic Activity
Except in the case of heavy steel plate, foreign activity (YF) in the export demand equations was proxied by total world imports in real terms less (real) imports by Japan, obtained from the International Financial Statistics of the International Monetary Fund (various issues). In the case of heavy steel plate, foreign activity was defined in terms of the volume of foreign shipping under construction, since the major end-user of Japan’s heavy plate exports during the sample period was the foreign ship construction industry. Quarterly data on the gross tonnage of foreign shipping under construction were obtained from the United Nations, Monthly Bulletin of Statistics (New York, various issues); monthly estimates used in estimation were generated on the basis of these quarterly data through the TROLL software package’s spline function routine.
Domestic activity was represented by three different indices, depending on the product under consideration. In the case of subcompact cars and color television sets, both consumer items, domestic activity was represented by an index of real disposable income (YD) constructed as follows:
YD = (YDEF · JPOP)/(ASIZE · JCPI),
where YDEF is the average disposable income of Japanese employee households; JPOP is the Japanese population; ASIZE is the average family size of Japanese employee households; and JCPI is Japan’s overall consumer price index. The data used in constructing YD were obtained from the Japanese Economic Planning Agency (EPA). For the three steel products, it was assumed that domestic activity would be more appropriately represented by an index based on activity in the manufacturing and construction sectors. Regressions were run on the basis of two alternative indicators: (1) an index of manufacturing output, and (2) a composite index of manufacturing and construction activity. The composite index was calculated as:
DD = W1 · QI + W2 · QC,
where QI is the index of manufacturing output; QC is the value of construction works executed, deflated by the construction cost index; W1 is the value of total manufacturing output, adjusted annually; and W2 is the value of construction work completed, adjusted annually. The index of manufacturing output was obtained from MITI sources, and the construction data were taken from Japan, Ministry of Construction, Construction Statistics Monthly (Tokyo: JMC, various issues).
Prices
Japanese prices were obtained on a monthly basis from the Bank of Japan, Price Indices Annual (Tokyo: BOJ, various issues). Contract export price indices (based on f.o.b. value) were available corresponding to the five products covered by the study; domestic prices were represented by the wholesale price indices for the various commodities. For each product considered, the relative domestic price was defined as the ratio of its domestic price to the wholesale price index for all other commodities.
Raw material price indices were not available at the relevant product levels and were therefore proxied by indices constructed at appropriate industry levels of aggregation; that is, automobiles (subcompact passenger cars), consumer electrical appliances (color television sets), hot-rolled steel products (heavy steel plate), and cold-rolled steel products (tin plate and galvanized steel sheet). The proxy indices were calculated as weighted-average wholesale price indices of the major raw material inputs of each of the above industries, with weights according to input coefficients given by the 1970 input-output table for Japan (Japan, Administrative Management Agency (1973)).
For subcompact cars and color television sets, foreign prices in yen (R · PF) were calculated as weighted averages of foreign wholesale prices converted into yen, with the weights based on average foreign market shares of Japanese exports for each category during 1971-75. Among the major markets, monthly price series for subcompact passenger cars and color television sets were available for the United States, the United Kingdom, and Canada, which together accounted for about three fourths of Japan’s total exports for both products during the above period. The sources were U.S. Department of Labor, Bureau of Labor Statistics, Producer Prices and Price Indexes (Washington: Government Printing Office, various issues); United Kingdom, Central Statistical Office, Price Index Numbers for Current Cost Accounting (London: H. M. Stationery Office, various issues); and Canada, Ministry of Industry, Trade, and Commerce, Industry Selling Prices (Ottawa: Canadian Government Publishing Centre, various issues).
In the case of the three steel products, disaggregated prices in the relevant export markets were readily available only for the United States. The competing foreign price was thus defined as follows. For galvanized steel sheet, the foreign price was represented solely by the U.S. wholesale price of galvanized steel sheet; the North American market accounted for about one half of total Japanese exports of galvanized steel sheet during 1971-75. For heavy steel plate and tin plate, foreign prices were calculated as weighted averages of the U.S. wholesale price of the relevant product and overall wholesale price indices in other major export markets, of which the latter were obtained from the Fund’s International Financial Statistics. This treatment thus captured broad price trends in export markets outside the United States and also yen exchange rate changes in relation to those markets. The countries covered accounted for 51 percent and 54 percent, respectively, of Japanese exports of heavy steel and tin plate.
The proxies for expected relative export prices were generated by forecasting one to three months forward on the basis of ARIMA models estimated separately for the various foreign prices, exchange rates, and contract export prices used in the analysis. (The estimated ARIMA models utilized are available from the author upon request.)
The relative price of gasoline in the United States and in Japan, included respectively in the export and domestic demand equations for subcompact passenger cars, was defined in both cases as the consumer price of gasoline relative to that for all other items included in the consumer price index.
Wages
The monthly wage rate (W) was defined as equal to total regular wages (excluding bonuses) divided by total regular hours worked (excluding overtime). Because data were not available at the relevant product level of disaggregation, wage costs were assumed to be equal to those in the automobile, consumer electrical appliance, and rolled steel product industries, respectively, for sub-compact cars, color television sets, and the three steel products. Data were obtained from Japan, Ministry of Labor, Monthly Labor Statistics (Tokyo: JML, various issues).
Variable Costs
Because of multicollinearity problems encountered in preliminary regressions, a variable cost variable, defined as a geometric weighted average of raw material and wage costs, was employed in the final regressions. The weights were determined by average input-output weights for 1970-72 obtained from MITI, Census of Manufactures (Tokyo, various issues); the weights and the respective levels of disaggregation available in the Census for each product considered are listed in Table 5.
Input Variable Weights Used in Final Regression Analyses
Input Variable Weights Used in Final Regression Analyses
| Weights | |||
|---|---|---|---|
| Product | Industry | Wages | Raw material prices |
| Subcompact passenger cars | Automobiles | 0.081 | 0.919 |
| Color television sets | Televisions and radios | 0.095 | 0.905 |
| Galvanized steel sheet | Galvanized steel sheet | 0.086 | 0.914 |
| Heavy steel plate | Hot-rolled steel products | 0.098 | 0.902 |
| Tin plate | Galvanized steel | 0.229 | 0.771 |
Input Variable Weights Used in Final Regression Analyses
| Weights | |||
|---|---|---|---|
| Product | Industry | Wages | Raw material prices |
| Subcompact passenger cars | Automobiles | 0.081 | 0.919 |
| Color television sets | Televisions and radios | 0.095 | 0.905 |
| Galvanized steel sheet | Galvanized steel sheet | 0.086 | 0.914 |
| Heavy steel plate | Hot-rolled steel products | 0.098 | 0.902 |
| Tin plate | Galvanized steel | 0.229 | 0.771 |
Non-Price-Rationing Variable
The non-price-rationing variable was represented by either the inventory-sales or the inventory-orders ratio. Inventory data were obtained from MITI sources; total sales were defined as the sum of export and domestic shipments, and total orders as the sum of export and domestic orders.
Vintage of Capital Stock
Because data on the age of the oldest machine in operation were not available, such age was approximated as a linear function of the average age of the capital stock in place and the rate of capacity utilization. (This approach was motivated by de Menil (1974).) For subcompact cars and color television sets, the average age of machinery in place was estimated from firm-level balance-sheet data on plant and equipment stocks and plant and equipment investment and depreciation obtained from the Japan Industrial Development Bank. Data on machinery vintage for the steel industry were provided by Sumitomo Metal Industries. Because the balance-sheet data were available only on an annual basis, monthly estimates were generated by the TROLL software package’s spline function routine. Capacity utilization rates were available for automobiles and color television sets from MITI and were estimated for each of the three steel products from output data according to the methodology employed in the construction of the Wharton index of capacity utilization (Klein and Summers (1966)).
REFERENCES
Ahluwalia, Isher J., and Ernesto Hernández-Catá, “An Econometric Model of U.S. Merchandise Imports Under Fixed and Fluctuating Exchange Rates, 1959-73,” Staff Papers, International Monetary Fund (Washington), Vol. 22 (November 1975), pp. 791–824.
Artus, Jacques R., “The Short-Run Effects of Domestic Demand Pressure on Export Delivery Delays for Machinery,” Journal of International Economics (Amsterdam), Vol. 3 (February 1973), pp. 21–36.
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de Menil, George, “Aggregate Price Dynamics,” The Review of Economics and Statistics (Cambridge, Massachusetts), Vol. 56 (May 1974), pp. 129–40.
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Mr. Citrin, currently the Fund’s resident representative in Jamaica, holds degrees from the University of California, Berkeley, and from the University of Michigan. This paper was prepared while he was a member of the Asian Department.
International Monetary Fund (1982) and Japan, Ministry of Finance (1978, 1980). The real effective exchange rate utilized here is based on wholesale price indices.
See Gregory (1971) for an extensive treatment of the impact of nonprice elements on trade flows. Gregory considers only the effect of domestic nonprice rationing on import demand, but the same arguments may be used for including a domestic cyclical variable in the export demand equation; see also Ahluwalia and Hernández-Catá (1975) and Hooper (1976).
Although this approach is rather ad hoc, a rigorous formulation of the adjustment path of the contract price may be extremely complex because of the conflicting nature of the various goals and the fact that the additional longer-run goals are motivated by entrepreneurial preferences not easily measured by traditional economic variables. The approach is motivated by similar formulations found in Artus (1974) and Ahluwalia and Hernández-Catá (1975).
The presence of lagged endogenous variables coupled with the expectation of serial correlation, reflecting estimation over monthly time series, implies that the usual two-stage or three-stage least-squares estimation techniques are inconsistent. Estimation was therefore conducted by applying an iterative modification of a two-step procedure developed for such models by Hatanaka (1976). Distributed lag structures were incorporated according to the method derived by Shiller (1973).
The t-statistics cannot be interpreted in the usual way for the distributed lag coefficients estimated according to the Shiller lag method (1973), a Bayesian procedure that imposes prior constraints on the shape of lag structures. Thus the statistical significance of the various lag structures was tested by calculating appropriate F-statistics for their group influence.
The estimated variances of the long-run elasticity estimates were calculated according to Kmenta (1971, equation (11.40), p. 444).
Using coefficients from Japan’s 1975 input-output table (Japan, Administrative Management Agency (1978)), the EPA estimated the exchange rate elasticity of raw material prices at a sectoral level; the relevant estimates are transport equipment, 0.09; electrical equipment, 0.12; and iron and steel products, 0.23 (see EPA (1978)). The variable input cost terms are adjusted according to these estimates, with the adjustment assumed to take place smoothly over a three-month period.
The exchange rate effect on export volumes would be less during periods when exports accounted for a higher share of total sales, since the offsetting influence of the non-price-rationing variable would be greater.