The World Trade Model: Merchandise Trade

Michael Deppler; Duncan Ripley

doi:10.5089/9781451956498.024.A007

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The World Trade Model: Merchandise Trade

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Mr. Michael Deppler

Mr. Michael Deppler
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Duncan Ripley

Duncan Ripley
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Publication Date:: 01 Jan 1978

eISBN:: 9781451956498

Language:: English

Keywords:: SP; cover book; price variable; export price; unit value; price terms; competitor price; Exports; Manufacturing; Trade balance; Global; spot commodity price

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MICHAEL C. DEPPLER and DUNCAN M. RIPLEY

Abstract

MICHAEL C. DEPPLER and DUNCAN M. RIPLEY

MICHAEL C. DEPPLER and DUNCAN M. RIPLEY

This paper presents a simple model of world merchandise trade disaggregated by commodity class and by country or country grouping. The model is part of a larger model encompassing all current account transactions. It is designed principally to estimate the responsiveness of merchandise trade to variations in income and activity levels in the industrial countries. The responsiveness of trade flows to variations in prices is also considered, but the empirical results on price sensitivity appear to be less reliable.

The trade flows were disaggregated into four commodity classes: foods, raw materials, fuels, and manufactures. Disaggregation is desirable in that the determinants of import demand vary depending on the type of import. For example, many manufactured imports enter directly into final demand, whereas raw material imports are almost exclusively intermediate inputs in the production process. Similarly, the demand for manufactures is likely to be more price sensitive than is the demand for fuels or raw materials. Further, institutional factors tend to play a larger role in the determination of agricultural flows than in the determination of many other merchandise flows. Thus, it would be unrealistic to specify a single import-demand relationship that necessarily assumed a uniform pattern of demand determination across commodity classes. The benefits arising from disaggregation, however, must be weighed against the loss in manageability that necessarily accompanies this disaggregation. In view of this trade-off, the commodity detail was limited to the four groups mentioned.

The model is a closed model in that all countries are covered either individually, as for the 14 industrial countries, or within one of four country groupings. However, since the principal explanatory variables are activity and income variables in the industrial countries, interest centers on the equations for these countries; the equations for the country groups are included for completeness. Attention is focused principally on trade in manufactures and on imports of raw materials and fuels, since these flows are particularly important for the trade balances of the industrial countries.

It is expected that the model will be used for both simulation and forecasting. The presentation here concentrates on the basic relationships in the model, discussing only briefly supplementary links that are needed to make it fully functional in either of these two modes. Its usefulness in terms of simulation is expected to lie in the calculation of countries’ trade balances under alternative assumptions about economic activity levels in the industrial countries. The model is also expected to be useful in projecting countries’ trade balances for 6 to 18 months ahead, thus providing an input to the semiannual forecasting exercise of the International Monetary Fund. However, when the model is used for this purpose, it will be necessary to make liberal use of forecasts and expert information provided by country and commodity specialists in the Fund, not only for the exogenous variables in the model—for example, spot commodity prices and various components of gross national product (GNP)—but also for a number of variables that are endogenous to the model, especially variables relating to particular commodity flows—for example, agricultural trade—or to country groupings.

This merchandise model contrasts sharply with the trade model of Project LINK in that it is not integrated with explicit national models. ¹ This is a disadvantage in that some of the interdependence between the foreign and domestic sectors may not be systematically taken into account; it is an advantage in that it is possible to impose a consistent specification across countries, and in that the maintenance and use of the model are greatly facilitated. ²

The present model is quite similar to the trade model of the Organization for Economic Cooperation and Development (OECD) in basic construction.³ Total domestic demand is the dominant exogenous variable in the OECD model, and final domestic demand for manufactures is the dominant exogenous variable in this model. Both models treat domestic price levels and exchange rates as exogenous, and are specified to be semiannual to conform to the time frequency used in forecasting exercises. However, the model described here differs from the OECD model in a number of respects. The OECD model has no commodity breakdown, whereas this model distinguishes among four commodity classes. The OECD model has individual equations for 18 OECD members, composite equations for “other OECD” members, and closing equations for the rest of the world; this model covers the 14 major industrial countries, and the rest of the world is disaggregated into four regions.

I. General Model Structure

The model is semiannual. This time frequency was selected because it is the one most often used in Fund work and, in particular, in the preparation of papers on the world economic outlook. Further, a semiannual data base is expected to reflect random movements to a lesser extent than a quarterly one and to facilitate the specification of lagged relationships.

The model focuses on the trade of the 18 countries or country groups listed in Table 1, and on transactions for four categories of goods under the Standard International Trade Classification (SITC)—(SITC 0+1), (SITC 2+4), (SITC 3), and (SITC 5–8). (SITC 9 is assumed to be determined exogenously.) This disaggregation reflects the view that the determinants of trade in manufactures are quite distinct from those of trade in raw materials, fuels, or agricultural goods. Thus, to base an analysis on aggregate relationships covering all commodities could produce misleading results, especially as regards the price sensitivity of trade flows. An aggregate analysis would also make it more difficult to integrate exogenous forecasts and information relating to particular commodity flows when the model is used in a forecasting mode. Clearly, manufactures themselves might usefully be disaggregated; for example, it would be useful to distinguish between manufactured imports that enter directly into final demand and those that are used as intermediate inputs. However, difficulties with data increase extremely rapidly as the degree of disaggregation increases. Thus, the disaggregation was limited to the four groups specified here.

Table 1.

Summary of Basic Model Specification

^¹Standard International Trade Classification.

^²This variable is derived from the identity: output = domestic demand - imports + exports.

Table 1.

Summary of Basic Model Specification

Regional Disaggregation			Commodity Disaggregation	Endogenous Variables		Exogenous Variables
industrial countries			SITC ¹0+l: Foods	Import volumes by commodity class,		Final domestic demand for
	Austria		SITC 2+4: Raw materials		by country		manufactures, by country
	Belgium-Luxembourg		SITC 3: Fuels	Export volumes by commodity class,		Real personal consumption
	Canada		SITC 5–8: Manufactures		by country (excluding fuels)		expenditure, by country
	Denmark			Export volumes of fuels for Canada,		Domestic prices of
	France				the Netherlands, and the United		manufactures, by country
	Germany, Fed. Rep.				States	Domestic prices of raw
	Italy			Gross domestic product originating in			materials, by country
	Japan				the manufacturing sector, by	Exchange rates, by country
	Netherlands				country ²	Fuel prices
	Norway			Import unit values by commodity class		Implicit deflators, by country
	Sweden				(excluding fuels), by country	Spot prices for 35
	Switzerland			Export unit values by commodity class			commodities
	United Kingdom				(excluding fuels), by country	Wages in manufacturing, by
	United States			Import volumes (total), by region			country
				Export volumes (total), by region		Natural gas production (the
regions				Import unit values (total), by region			Netherlands)
	Developed primary producing			Export unit values (total), by region		Petroleum production
		countries					(Canada and the United
	Major oil exporting countries						States)
	Other developing countries					Normal output per man-hour
	Other						in manufacturing, by
							country
						Output per man-hour in
							manufacturing, by country

^¹Standard International Trade Classification.

^²This variable is derived from the identity: output = domestic demand - imports + exports.

Table 1.

Summary of Basic Model Specification

Regional Disaggregation			Commodity Disaggregation	Endogenous Variables		Exogenous Variables
industrial countries			SITC ¹0+l: Foods	Import volumes by commodity class,		Final domestic demand for
	Austria		SITC 2+4: Raw materials		by country		manufactures, by country
	Belgium-Luxembourg		SITC 3: Fuels	Export volumes by commodity class,		Real personal consumption
	Canada		SITC 5–8: Manufactures		by country (excluding fuels)		expenditure, by country
	Denmark			Export volumes of fuels for Canada,		Domestic prices of
	France				the Netherlands, and the United		manufactures, by country
	Germany, Fed. Rep.				States	Domestic prices of raw
	Italy			Gross domestic product originating in			materials, by country
	Japan				the manufacturing sector, by	Exchange rates, by country
	Netherlands				country ²	Fuel prices
	Norway			Import unit values by commodity class		Implicit deflators, by country
	Sweden				(excluding fuels), by country	Spot prices for 35
	Switzerland			Export unit values by commodity class			commodities
	United Kingdom				(excluding fuels), by country	Wages in manufacturing, by
	United States			Import volumes (total), by region			country
				Export volumes (total), by region		Natural gas production (the
regions				Import unit values (total), by region			Netherlands)
	Developed primary producing			Export unit values (total), by region		Petroleum production
		countries					(Canada and the United
	Major oil exporting countries						States)
	Other developing countries					Normal output per man-hour
	Other						in manufacturing, by
							country
						Output per man-hour in
							manufacturing, by country

^¹Standard International Trade Classification.

^²This variable is derived from the identity: output = domestic demand - imports + exports.

The 14 countries and four country groups covered are the 14 industrial countries and the groups of developed primary producing countries, major oil exporting countries, other developing countries, and the rest of the world—consisting essentially of the centrally planned economies. These country groups are consistent with the country groupings used in the International Monetary Fund’s International Financial Statistics, and were chosen both because of their analytical interest and because of the availability of data.

The model can be thought of as consisting of three principal blocks. Of major importance are the price block and the volume block for the industrial countries. Of somewhat lesser importance are price and volume relationships for the four regions. The first block determines, for each commodity class, export and import unit values for the industrial countries, given certain spot commodity prices, domestic costs and prices, and exchange rates; the second block determines the volume of exports and imports by commodity class for the industrial countries (excluding fuel exports for countries other than Canada, the Netherlands, and the United States), given prices and the level of final domestic demand. The exogenous and endogenous variables are listed in Table 1. The relationships briefly noted here are specified more fully in Tables 2 and 3, and are discussed in the subsections, specification of the price block for the industrial countries and specification of the volume block for the industrial countries. The third block relates export receipts of the country groups to activity levels in the industrial countries, and import expenditure to their foreign exchange earnings. These relationships are specified in Tables 4 and 5 and are discussed in the subsection, specification of the volume and price relationship for the four regions. Seasonal and special country dummies and lag structures are not indicated in these tables but are described in the Appendix and/or the tables that report the corresponding parameter estimates.

specification of the price block for the industrial countries

Price relationships for manufactures

In Table 2, equation 1, countries’ export prices for manufactures (unit values) expressed in the domestic currency (XPM) are explained by: (1) the costs of production represented by the cyclical (CYCLOMH) and noncyclical (NULC) components of unit labor costs in manufacturing, and by raw material costs on the domestic market (PRM); and (2) the state of demand represented by competitor prices in foreign markets expressed in the domestic currency (PFX^*LCD) and calculated as a double-weighted average of other countries’ export prices for manufactures. The variables are expressed in change in log form.

Table 2.

Industrial Countries: Price Relationships

To analyze the main issues that arise from this specification, it is helpful to begin by considering the price formation process for a profit-maximizing firm subject to: (1) diminishing returns to scale because capital is fixed in all but the long run; (2) perfect competition in the markets for the variable factors of production; and (3) less than perfect competition in the market for the firm’s output, that is, some degree of pricing discretion. In the simplest case, such a model⁴ yields a reduced form price equation of the following form, where all variables are expressed in terms of rates of change:

P = \frac{1}{1 + α η} [V C + α η C P + Y]

VC, CP, and Y represent variable costs, competitor prices, and the income (or scale) variable in the demand function for the firm’s output, respectively; α is the elasticity of the marginal cost function with respect to output (α≥0); and η is the absolute value of the price elasticity of demand in volume terms (η≥1 insofar as the individual firm is concerned).

In this expression, the profit-maximizing price charged by the firm is seen to be an increasing function of both cost (VC) and demand factors (CP and Y). In addition, the coefficients of the VC and CP variables sum to one; this implies that a 10 per cent increase in both of these variables results in a 10 per cent increase in P. Because the coefficients are nonnegative and sum to one, an increase in the relative importance of one of these variables in the price formation process entails a reduction in the role of the other. Further, the relative responsiveness of price to each of these two variables (costs and competitor prices) depends upon the quantity αη. If αη is large—because the firm’s monopoly power is limited (i.e., η is large) and/or because there are strongly increasing marginal costs (i.e., α is large)—then competitor prices tend to dominate the price formation process. In the limiting case of perfect competition, which may not be an inappropriate assumption for many of the smaller countries involved in international trade, η tends to infinity, and the coefficient of CP tends to one while that for VC tends to zero. If, on the other hand, αη is small because the “firm,” as a large supplier, enjoys a considerable amount of monopoly power and/or because production is subject to constant or near-constant returns to scale, then pricing is dominated by supply considerations. This outcome is the more likely, the longer is the time horizon of the pricing decision being considered. Other things being equal, α will tend to fall as the proportion of the factors of production that are variable rather than fixed increases.

The relative importance of cost and competitor price variables in the price equation, therefore, depends upon the quantity αη. This result is of particular interest in the present application, since this quantity is likely to be inversely related to the size of the “firm”—that is, the size of a country. Both α and η are likely to be small for a large country, since exports will represent a relatively small fraction of domestic production but a large fraction of the international market. Thus, prices will depend primarily upon costs, with competitor prices being of secondary importance. The converse would be true for small countries, with competitor prices tending to dominate the export price formation process in the short run.

The specification in Table 2 involves several departures from the theoretical model. First, a distinction is made between the cyclical and noncyclical components of unit labor costs. The latter is defined as actual compensation per man-hour deflated by potential output per man-hour.⁵ The cyclical component of labor costs is represented by the ratio of actual to “normal” output per man-hour. These specifications of the labor cost variables stem from the view that, other things being equal, firms seek to minimize the fluctuations in the prices that they charge, so that the pass-through of cyclical changes in unit labor costs is expected to be less than that of “normal” changes.⁶ Second, the “income,” or scale, variable that should logically appear in the equation in Table 2 has been omitted. This omission reflects the consistent lack of significance of this variable in all the estimated equations.

Given the requisite bilateral trade and unit value data, import unit values would be identically equal to some suitably weighted average of the export price data. In Table 2, equation 2, therefore, import unit values for manufactures are explained by a weighted geometric average of the export unit values of other industrial countries⁷ expressed in the local currency (PFMD*LCD). In addition, since exports are recorded before the corresponding imports, a weighted average of the current and last period changes in partner-country export prices was used. Weights of ⅚ and ⅙, respectively, were selected, since the recording lag is thought to average about one month.⁸ This weighted export price variable may be thought of as a world index for a particular basket of goods. However, pricing decisions for exports to a particular market may be influenced by characteristics of the particular market, such as the price and availability of domestically produced alternatives. Consequently, experiments with two additional variables—the exchange rate (LCD) and the price of domestically produced manufactures (P)— were conducted to estimate the effects of these country-specific influences that may affect bilateral pricing decisions. However, while a few of the individual country results were suggestive and plausible, the results across countries were too disparate to be retained in the final specification of the equation.

Price relationships for nonmanufactured commodities⁹

The basic exogenous information used in this block of equations (Table 2) is a set of 35 time series on spot quotations in world markets for precisely defined primary commodities.¹⁰ These data are aggregated to obtain spot price indices (e.g., PAWDX and PRWDX) with commodity coverages similar to those of the agricultural or raw material unit value indices that they are intended to explain. In a forecasting context, the projected values of these spot prices are provided by commodity experts.

The export price equations posit that the export unit values for agricultural goods or raw materials depend on spot prices in world markets (weighted on the basis of the 1970 commodity structure of the country’s exports) and labor cost developments in the exporting country. The inclusion of the first variable reflects the view that—apart from the problems discussed later of linking spot prices and unit values—most prices for a specific type of raw material and agricultural good are determined in a single world market. Hence, the export price is simply equal to this world market price, the latter being expressed in terms of domestic currency. Such a view, however, takes no account of the fact that industrial countries’ exports of these commodities often are somewhat more processed than are the commodities to which the spot prices refer. The purpose of the labor cost variable, therefore, is to account for at least part of this extra processing. On the premise that wage developments are fairly uniform across the various sectors of the economy, this allowance for additional domestic value added is based on hourly labor compensation data for manufacturing.¹¹

As was true for the price of manufactured imports, the import unit values are explained primarily in terms of the corresponding partner-country export prices, again lagged to take account of the recording lag between exports and imports. However, in the present instance, allowance must also be made for the nonavailability of unit value data broken down by major commodity groups for the four major geographic regions—regions that happen to be significant suppliers of nonmanufactures to the industrial countries. This gap in the data has been circumvented. Indices of the spot commodity price data, using as weights the 1970 commodity structure of each importing country’s imports, were included in the import price equations to reflect the influence on import prices of commodities imported from the nonindustrial countries.¹²

The use throughout the commodity block of spot price data to explain unit value indices has several drawbacks. First, the commodity coverage of the spot price data is considerably more restrictive than that of SITC 0+1 and 2+4 (i.e., the coverage of the unit values). Second, the “transactions” coverage of the spot price data (for comparable commodity classes) is (1) considerably less than that of the unit values (i.e., many transactions are carried out under long-term contracts that bear no necessary relationship to current spot quotations), and (2) temporally distinct from that of the unit values (i.e., the latter tend to reflect spot prices of an earlier period). A first consequence of these deficiencies is that, since the discrepancy in commodity coverage is most pronounced with respect to slightly processed commodities, the prices of which are likely to be somewhat less volatile than those of unprocessed commodities, there is an expectation that (other things being equal) the elasticity of the unit value series with respect to the spot price indices will tend to be less than one, particularly in the short run. The dependence of the unit values on transactions that are under long-term contracts would operate in the same direction. Second, the implication of the timing discrepancy between spot and unit value data is that one may reasonably expect the unit values to respond to changes in spot market quotations with a lag.

Finally, two sets of supplementary price equations are used in specific applications of the model. The first set is used in a forecasting mode to link domestic prices of raw materials (PRM) to an index of world spot prices for raw materials in local currency (PRWDM^*LCD) and labor cost developments. The second set of equations (which link each of the 35 individual spot commodity price series to general indicators of inflation and underutilization of resources in the industrial countries) is used, for simulation purposes, to estimate the cyclical element in commodity prices.

specification of the volume block for the industrial countries

Volume relationships for manufactures

The relationships in the volume block for manufactures are outlined in Table 3. The value series are adjusted for most countries to exclude transactions in ships and aircraft, which cause considerable variability in the series and are thought to be affected by factors not generally important in determining the demand for other manufactured goods. Trade in automobiles between the United States and Canada has also been omitted from the equations on aggregate manufactures because of its very rapid development from 1965 to 1970 after the conclusion of the U.S.-Canadian Automotive Agreement. The value series for a few countries (Belgium-Luxembourg, Switzerland, and the United Kingdom) are further adjusted to exclude transactions in pearls and precious stones, since these countries tend to import large quantities for re-export. The adjusted value series are then deflated to obtain volume series.

Table 3.

Industrial Countries: Volume Relationships

The import volume equation for the industrial countries posits that the demand for imports of manufactures is the result, in part, of a two-stage decision process. The first stage of that process determines the total final demand in the country for manufactured goods given the country’s income level, the aggregate price for manufactures, and the aggregate prices for a broad spectrum of other commodities.¹³ This stage in the decision making is outside the purview of the trade model. Given the aggregate final demand for manufactures, the problem then becomes one of deciding how much of the demand will be satisfied from domestic sources, and how much of it will be satisfied from imports. This is hypothesized to depend on relative prices. ¹⁴

The import volume figures, however, relate to goods that are used as intermediate inputs as well as those that enter directly into final demand, while the specification suggested earlier focuses on the final demand component. Thus, it was necessary to modify this specification somewhat to take into account determinants that exert particularly strong influence on the demand for intermediate inputs. Consequently, the demand variable was specified as a weighted average of manufacturing output (QM) and final domestic demand for manufactures (DVM), with weights reflecting the share of manufactured imports used as intermediate inputs and the share going directly to final demand, respectively.

It is also important to distinguish between the responsiveness of imports to short-term fluctuations and the responsiveness to longerterm developments. To introduce this distinction into the relationships for manufactured imports, the demand variable presented here was deflated by an index of potential output in manufacturing to provide a measure of fluctuations in demand around its longer-term value; the index of potential output in manufacturing was included separately to capture the responsiveness of imports to the longer-run growth of the economy. The relationships are specified in logarithmic form.

If one ignores certain timing problems and difficulties in the proper classification of trade flows, countries’ exports to a particular market at a particular time must equal the level of imports in that market multiplied by the share of the exporting country in that market.¹⁵ Thus, to determine a pattern of exports consistent with the predetermined level of imports it is necessary to explain bilateral market shares. However, for an 18-region world, this would require approximately 300 bilateral relationships to be determined for manufactures alone. The data requirements and computational difficulties involved in a straight-forward approach to the estimation of such relationships for a model with commodity disaggregation would be severe.

Under these circumstances, it is useful to consider what the restrictions that underlie the import demand function may imply for export determination, and perhaps what further reasonable simplifying assumptions or approximations might be introduced that would significantly reduce the number of separate parameters that need to be estimated. It has been assumed that the elasticity of substitution between manufactured imports from any two exporting countries is the same for all countries competing in a given market, and that the elasticities are constant over time. If the allocation of shares in a particular market is independent of the size of the market, then it can be shown that the allocation of import demand among exporting countries can be formulated as

XVM_ij = b_ij^δj(P_ij/P_j)^-δj. MVM_j

where XVM_ij is the volume of exports of country i to country j; MVM_j i is the volume of imports of country j; P_ij is the price of exports of country i to country j; P_j is the average price of exports to country j; and δ_j is the elasticity of substitution in market j.¹⁶ This formulation provides the basis for the equations for the export of manufactures in the model presented here. It was modified in several respects, however. To make the data requirements more manageable and to facilitate the use of the model in a forecasting mode, price and demand variables were aggregated across countries. The foreign market variable (that is, the weighted average of imports in partner countries) reflects the influence of changes in demand in foreign markets. In addition, exports may grow or contract, as a result of changes in market shares. This may occur, for example, as a result of movements in relative prices, or increasing productive capacity in the manufacturing sector. To reflect these influences, a relative price variable was included in the equation as well as an index reflecting the growth in potential output of the manufacturing sector in the exporting country relative to that in competitor countries. Thus,

XVM_i = α₀(FM_i)^α1(RXPM_i)^α2(RQMT_i)^α3(Z_i)^α4

where XVM_i is the volume of manufactured exports from country i; FM _i is the foreign market for country i; RXPM_i is the export price of manufactures for country i relative to that of competitor countries, calculated as a double-weighted index of export prices; RQMT_t is the ratio of potential output in the manufacturing sector in country i relative to that in competitor countries, calculated as a double-weighted index of potential output series; and Z_i represents other exogenous variables relating to country i.¹⁷

Volume relationships for nonmanufactured commodities

The specification of the manufactures block draws on consumer demand theory, but the specification must be simplified and then modified to reflect the substantial proportion of manufactured imports that are used as intermediate goods. For raw materials and fuels, the specification is based on the assumption that imports of these commodities constitute intermediate inputs in the production process. It is postulated that a given increase in output from the manufacturing sector tends to require a proportional increase in the imports of raw materials and fuels; changes in commodity imports may coincide with changes in manufacturing output, or may lag by one period as a result of transportation and delivery delays. It is also assumed that imported raw materials (fuels) can be stockpiled in anticipation of future need, with the expectation of future need being reflected by the current rate of change in manufacturing output.

Clearly, it is not possible from this specification to identify individually the “stockpiling” effect from the lagged effect corresponding to delivery delays. To reflect their joint influence, however, both the current level of output in manufacturing (QM) and its value lagged by one period are entered as exogenous variables in the import demand function for raw materials and fuels. The coefficient on the lagged value of manufacturing output can be positive or negative.¹⁸ The more sensitive that raw material (fuel) imports are to the rate of change in output, however, the greater will be the probability that the coefficient on the lagged output variable will be negative.

It was postulated that imported raw materials and fuels are generally not competitive with home-produced raw materials and fuels, since these imports consist of goods that are not produced domestically, or are produced in inadequate quantity. Thus, there would be little price sensitivity.¹⁹ However, to capture to some extent the effects of the unusual developments in 1974, two dummy variables were introduced in the equations for fuel imports. A shift dummy to take into account the extremely large change in the relative price of oil in 1974, and an embargo dummy taking the value one in the first half of 1974 and minus one in the second half were introduced.

The volume of food imports (MVA) is related to real consumption expenditure (CC) on the assumption that these imports either immediately or after some processing are destined for the domestic consumer. The determination of the level of real consumer expenditure falls outside the scope of the model. No attempt is made to measure the sensitivity of agricultural imports to changes in domestic food prices. This is so because, to the extent that domestically produced agricultural goods do compete with imported goods, the relevant relative food price ratios are likely to show little movement; to the extent that there are no domestic substitutes, it is more probable that a variation in the import price will affect a wide range of expenditure decisions rather than just the food budget. Consequently, the relative price variable entering the food-import equation is the ratio of the GNP deflator to the price of food imports. It is introduced in an attempt to measure the overall substitution between imported foods and all goods produced domestically.

Export volumes for raw materials and agricultural goods are estimated to close the model, as noted earlier. Foreign market variables (FA and FR) consisting of a weighted average of imports of raw materials or agricultural goods in the individual industrial countries and country groups from the 14 industrial countries taken as a whole are calculated, and these are the principal explanatory variables. As has been discussed earlier, it is assumed that a particular type of raw material or agricultural good is homogeneous and that there is a single world price for such a good. Thus, no relative price term enters these export equations.

specification of the volume and price relationship for the four regions

To provide complete country coverage is outside the scope of the model and of the available data base. However, to add some degree of realism to the equations, the “rest of the world” was disaggregated into four country groups, with particular characteristics being shared by the countries within each group. Because of the aggregative nature of these group relationships, however, and the heterogeneity across countries within each group despite common characteristics, the ad hoc nature of relationships given in Table 4 must be acknowledged. Further, because of a lack of data, disaggregation of export and import equations by commodity class was not possible.

Table 4.

Regions: Volume and Price Relationships

The total volume of exports of each of the four regions (XVT) is explained by reference to the level of output in manufacturing in the industrial countries (QMIND). The weights used to construct each of these indices are based on the importance of the various industrial markets for the exports of the country group. The levels of output in manufacturing were also used as relative weights, reflecting the view that a “world” rather than a “bilateral” approach might be more appropriate for these countries. However, they did not perform quite as well as the “bilateral” variables.

Similar specifications are used to determine import demand in each of the four regions: imports are explained on the basis of a foreign exchange constraint.²⁰ This type of specification is clearly not as appropriate for the more developed countries as it is, for example, for the non-oil developing countries. For the centrally planned economies, the specification produces a reasonable fit; but the causality may run in the opposite direction, that is, import needs may well determine foreign exchange receipts rather than the converse.

Imports in volume terms (MVT) are explained by the purchasing power of these country groups (XPP). In principle this purchasing power variable should cover countries’ net foreign exchange holdings as well as reflect their current receipts and their ability to borrow. In the estimated relationships, the purchasing power variable is proxied by the total value of the regions’ exports (including within-region exports), deflated by their aggregate import price index.

The equations determining aggregate export unit values for each of three regions (excluding the centrally planned economies, for which no price data are published) specify that this index is determined by a weighted average of spot commodity prices of agricultural goods and raw materials, with the weights reflecting the importance of the individual commodities in the trade of the region, a unit value index for the world price of manufactures, and a unit value index reflecting the price of petroleum.²¹ The inclusion of the “world” unit value index for manufactures reflects the view that the manufactured export prices for these countries move in line with the export prices of the industrial countries, that is, that these regions are price takers as far as manufactured exports are concerned. This assumption appears reasonable, and further support for this approach arises from the impracticality of collecting data on domestic cost and price developments for the primary producing countries.

The import unit values for the regions are related to a unit value index for petroleum, a weighted average of the export prices for manufactures of the industrial countries (with the weights reflecting the relative importance of the particular country in the imports of the region), and weighted averages of raw material and agricultural export unit values of the industrial countries. The agricultural and raw material export unit values of the industrial countries were included rather than a weighted average of commodity spot prices in the import unit value equations for several reasons: it was thought that the commodities covered by the spot price indices were not particularly representative of the commodity composition of imports of the regions; a substantial portion of the raw materials and agricultural goods imported by the regions originates in the industrial countries.

II. Model Parameters

The historical data base for the model consists of semiannual observations for the period 1955–60, depending on availability, to the first half of 1976. However, unless otherwise noted in the tables, the estimation period is from the first half of 1964 to the first half of 1976, and the equations were estimated by ordinary least squares. The dummy variables used are described in the footnotes to the tables; a rational is provided either in the footnotes or in the Appendix.

estimation of the price block for the industrial countries

Price parameters for manufactures

Table 5 presents estimates of the export unit value equations for manufactures for the industrial countries. To take account of the simultaneity of this block of equations, that is, the interdependence of competitor prices, a type of two-stage least-squares estimation procedure was used. In the first stage, XPM_j for each country j was regressed on the exogenous variables for country j and the exogenous variables for all other countries. The latter, however, were first averaged across countries, using the same weights as those used to construct the competitor price variable. The resulting predicted values of XPM_j for all i were then averaged to compute a predicted version of PFX_j which was then used in the equations shown in Table 5; these equations were estimated using ordinary least squares.

Table 5.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Manufactures, First Half 1963–First Half 1976¹

^¹The t-statistics are given in parentheses.

^²Because of collinearity problems, the equation assumes that two thirds of the adjustment to changes in normal unit labor costs or competitor prices takes place within the current half year.

^³Constrained estimates.

^⁴These variables are 0 everywhere except as follows: (a) Belgium-Luxembourg—1965 (first half) = –1, 1965 (second half) = ½, 1970 (first half) = –1, and 1970 (second half) = 1; (b) Italy—1963 (second half) = 1 and 1968 (first half) = –1; (c) Japan—1975 (first half) = 1 and 1975 (second half) = 1; and (d) the Netherlands—1974 (first half) = 1 and 1974 (second half) = 1. The dummies for Japan, the Netherlands, and Italy in 1963 are associated with cyclical developments, the oil price increase, and strikes, respectively. The other dummies pick up seemingly random developments, which, however, affect the structural coefficients of the equation.

Table 5.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Manufactures, First Half 1963–First Half 1976¹

Explanatory Variable	Austria	Belgium Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom ²	United States
Constant	–0.003 (0.5)	–0.007 (1.3)				–0.005 (1.7)					0.007 (3.7)	0.010 (3.1)
Domestic raw materials prices ³	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075
Normal unit labor costs		0.51 (2.8)			0.56 (4.4)	0.57 (5.2)	0.19 (1.7)	0.29 (1.7)					0.28 (4.1)	1.03 (4.4)
Normal unit labor costs (-1)			0.49 (1.8)	0.26 (2.1)				0.29 (1.4)				0.37 (2.2)	0.14 (4.1)	0.50 (2.2)
Cyclical unit labor costs					–0.19 (1.6)		–0.21 (1.4)					–0.14 (2.2)		–0.46 (3.4)
Competitor prices	1.02 (5.4)	0.44 (2.8)	0.46 (2.7)	0.66 (6.0)	0.40 (4.5)	0.25 (3.8)	0.44 (4.4)	0.58 (5.0)	0.24 (1.5)	1.31 (6.6)	0.56 (6.8)	0.20 (2.4)	0.34 (6.8)
Competitor prices (-1)						0.15 (2.5)					0.43 (5.2)	0.12 (1.3)	0.17 (0.68)
Dummies ⁴		0.08 (5.0)					–0.11 (6.0)	–0.08 (4.6)	0.09 (5.4)
SEE	0.023	0.017	0.024	0.015	0.019	0.010	0.017	0.018	0.016	0.029	0.010	0.010	0.012	0.014
R ²	0.51	0.71	0.52	0.69	0.68	0.75	0.86	0.87	0.74	0.56	0.89	0.47	0.88	0.80
D-W	2.34	1.79	1.88	2.16	2.44	2.00	2.52	2.12	1.96	1.47	2.44	2.55	1.72	2.06

^¹The t-statistics are given in parentheses.

^²Because of collinearity problems, the equation assumes that two thirds of the adjustment to changes in normal unit labor costs or competitor prices takes place within the current half year.

^³Constrained estimates.

Table 5.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Manufactures, First Half 1963–First Half 1976¹

Explanatory Variable	Austria	Belgium Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom ²	United States
Constant	–0.003 (0.5)	–0.007 (1.3)				–0.005 (1.7)					0.007 (3.7)	0.010 (3.1)
Domestic raw materials prices ³	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075	0.075
Normal unit labor costs		0.51 (2.8)			0.56 (4.4)	0.57 (5.2)	0.19 (1.7)	0.29 (1.7)					0.28 (4.1)	1.03 (4.4)
Normal unit labor costs (-1)			0.49 (1.8)	0.26 (2.1)				0.29 (1.4)				0.37 (2.2)	0.14 (4.1)	0.50 (2.2)
Cyclical unit labor costs					–0.19 (1.6)		–0.21 (1.4)					–0.14 (2.2)		–0.46 (3.4)
Competitor prices	1.02 (5.4)	0.44 (2.8)	0.46 (2.7)	0.66 (6.0)	0.40 (4.5)	0.25 (3.8)	0.44 (4.4)	0.58 (5.0)	0.24 (1.5)	1.31 (6.6)	0.56 (6.8)	0.20 (2.4)	0.34 (6.8)
Competitor prices (-1)						0.15 (2.5)					0.43 (5.2)	0.12 (1.3)	0.17 (0.68)
Dummies ⁴		0.08 (5.0)					–0.11 (6.0)	–0.08 (4.6)	0.09 (5.4)
SEE	0.023	0.017	0.024	0.015	0.019	0.010	0.017	0.018	0.016	0.029	0.010	0.010	0.012	0.014
R ²	0.51	0.71	0.52	0.69	0.68	0.75	0.86	0.87	0.74	0.56	0.89	0.47	0.88	0.80
D-W	2.34	1.79	1.88	2.16	2.44	2.00	2.52	2.12	1.96	1.47	2.44	2.55	1.72	2.06

^¹The t-statistics are given in parentheses.

^²Because of collinearity problems, the equation assumes that two thirds of the adjustment to changes in normal unit labor costs or competitor prices takes place within the current half year.

^³Constrained estimates.

Several of the regression equations shown in Table 5 have been constrained to pass through the origin. While this constraint has little effect on the reported results for most countries, it does yield somewhat more plausible coefficients than would otherwise have been true in several instances. Similarly, the coefficients on the variable for raw materials prices tended to be either too high (e.g., in the ⅙ to ⅓ range for the United Kingdom, Belgium-Luxembourg, the Federal Republic of Germany, the Netherlands, Sweden, and Japan) or too low (e.g., 0 or negative for the United States, France, Italy, and Canada), and were consequently constrained to 0.075. This value is consistent with an average of the estimates obtained from input-output matrices. A difficulty associated with making the constraints country specific is that the coverage of the raw material price variables varies considerably across countries and bears an often uncertain relationship to that of the input-output matrices.

In Table 5, the cyclical productivity variables are of secondary importance. As expected, the coefficients tend to be small. Indeed, the variable is excluded from more than two thirds of the equations. The relative lack of success of these variables (as well as measures of demand pressure in foreign markets, which were also experimented with) is thought to be due in part to the cyclical element embedded in the competitor price variable, which plays an important role in many of the equations.²²

The dominant variables in the export unit value equations are normal unit labor costs and competitor prices. Indeed, the coefficients for these two variables sum to approximately unity for the majority of countries. The importance of the competitor price variable is particularly striking: it is included in the equations for all countries except the United States. Further, while the classification is not unambiguous, there is a tendency for the magnitude of the coefficient of the competitor price variable relative to that for normal unit labor costs to be inversely related to the country’s size. Thus, competitor prices are relatively more important than labor costs in export price formation for Austria, Denmark, Italy, the Netherlands, Norway, and Sweden, while the reverse is true for the United States. For the other countries—Belgium-Luxembourg, Canada, France, the Federal Republic of Germany, Japan, Switzerland, and the United Kingdom—the competitor price and the unit labor cost coefficients are approximately equal. With perhaps a few exceptions, these results are more or less in accordance with a priori expectations as to the relative market position of the various countries. However, the results pertain only to a short-run analysis. In the longer term, prices cannot diverge markedly from costs. This implies that the importance of costs must increase as the time horizon is extended, and/or that costs are in fact endogenous (rather than exogenous) and depend upon competitor prices. In either case, it is clear that the equations in Table 5 are viable only for the short run and for rates of increase in domestic costs that, after correction for exchange rate changes, are not drastically out of line with cost developments elsewhere.

The import unit value equations for manufactures shown in Table 6 are straightforward. Changes in import prices depend only on changes in partner-country export prices. That is, separate trend influences, as reflected by a constant term, are also excluded from the equations. Constant terms were significant in only two countries—Austria and Switzerland—and in each of these, the corresponding slope coefficient diverged from unity (e.g., to 1.6 for Austria). The resulting import unit value equations specify that import prices follow partner-country export prices with a one-month lag. The coefficients all cluster around unity; the average is 0.95, and only the coefficients for Canada and the Federal Republic of Germany are significantly different from one.

Table 6.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Manufactures, First Half 1963–First Half 1976 ¹

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and⅙, respectively.

Table 6.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Manufactures, First Half 1963–First Half 1976 ¹

Explanatory Variable	Austria	Belgium Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Partner-country export prices ²	1.15 (5.4)	0.99 (6.7)	0.76 (17.3)	1.00 (10.4)	1.00 (10.5)	0.56 (4.4)	0.89 (12.7)	0.86 (4.7)	1.06 (6.8)	0.95 (10.9)	1.02 (14.9)	0.97 (8.0)	0.98 (14.0)	1.11 (14.3)
see	0.028	0.024	0.009	0.018	0.023	0.021	0.023	0.044	0.021	0.013	0.013	0.014	0.022	0.017
R ²	0.47	0.56	0.88	0.70	0.77	0.41	0.77	0.39	0.28	0.75	0.82	0.59	0.78	0.81
D-W	2.33	1.88	2.57	1.48	1.65	1.66	2.10	2.35	1.90	2.42	1.75	1.69	1.25	2.26

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and⅙, respectively.

Table 6.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Manufactures, First Half 1963–First Half 1976 ¹

Explanatory Variable	Austria	Belgium Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Partner-country export prices ²	1.15 (5.4)	0.99 (6.7)	0.76 (17.3)	1.00 (10.4)	1.00 (10.5)	0.56 (4.4)	0.89 (12.7)	0.86 (4.7)	1.06 (6.8)	0.95 (10.9)	1.02 (14.9)	0.97 (8.0)	0.98 (14.0)	1.11 (14.3)
see	0.028	0.024	0.009	0.018	0.023	0.021	0.023	0.044	0.021	0.013	0.013	0.014	0.022	0.017
R ²	0.47	0.56	0.88	0.70	0.77	0.41	0.77	0.39	0.28	0.75	0.82	0.59	0.78	0.81
D-W	2.33	1.88	2.57	1.48	1.65	1.66	2.10	2.35	1.90	2.42	1.75	1.69	1.25	2.26

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and⅙, respectively.

The simplicity of the equations given in Table 6 is due partly to rejections of alternative results that were not, taken at face value, incompatible with the a priori arguments set out earlier. For instance, the addition of the domestic price variable (P), on the assumption that exporters consider price developments in specific markets in the price formation process, results in equations with noticeably lower standard errors of estimate for the United States, Belgium-Luxembourg, and Sweden. These results were rejected, however, because the coefficients of the P variable tended to be too large. For the United States, the coefficient was approximately unity and highly significant, while the coefficient for PFMD was not significant. Such coefficients seem too extreme to be accepted for working purposes. In the other two countries with large P coefficients—Belgium-Luxembourg and Sweden—the importance of the P variable could well be the result of causation running in the opposite direction from that postulated, that is, from import to domestic prices; consequently, this variable was again excluded from the final specification.

Price parameters for nonmanufactured commodities ²³

Tables 7–10 present the parameter estimates for the export and import unit value equations for agricultural products and raw materials. Generally, these equations support the main relationships that are postulated for these prices. Thus, while the export unit values for nonmanufactures depend in large part upon world market prices for similar commodities, there is also a domestic value-added component that responds to changes in domestic wage costs. Similarly, on the import side, it is clear that developments in world commodity prices have an influence on industrial country import unit values quite apart from that exerted via the export unit values for the industrial countries.

Table 7.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Agricultural Goods, Ssecond Half 1962–First Half 1976 ¹

^¹The t-statistics are in parentheses.

^²For Denmark, this variable is intended to allow for the effect of entry into the European Economic Community. The variable is equal to zero prior to the first half of 1973.

^³Cochrane-Orcutt autoregressive correction.

^⁴Estimate is affected by the origin constraint. SEE is a better measure of the goodness of fit.

Table 7.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Agricultural Goods, Ssecond Half 1962–First Half 1976 ¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–2.14 (1.9)	2.33 (12.9)	0.54 (3.0)	0.48 (0.4)	1.41 (5.3)	3.37 (14.0)	–0.16 (0.4)	1.69 (3.0)	3.40 (13.9)	0.13 (0.6)	2.20 (3.8)		1.31 (3.3)	0.05 (0.4)
Wages		0.18 (9.6)	0.17 (3.6)	0.50 (3.8)	0.34 (5.1)	0.12 (4.6)	0.20 (6.3)	0.37 (11.1)	0.31 (5.7)	0.40 (12.8)			0.67 (7.5)	0.28 (6.9)
Spot commodity prices		0.19 (6.5)	0.09 (1.5)	0.06 (1.0)	0.18 (2.1)		0.15 (1.9)			0.12 (2.6)		0.16 (3.2)		0.45 (9.5)
Spot commodity prices (–1)	0.31 (1.9)		0.52 (6.5)		0.14 (1.6)	0.13 (2.4)	0.23 (3.1)	0.15 (2.4)		0.15 (2.6)	0.54 (5.7)	0.08 (1.2)	0.07 (1.1)	0.24 (3.3)
Spot commodity prices (–2)			0.20 (3.3)							0.11 (2.4)		0.18 (3.6)		0.05 (1.1)
Dummies²				0.11 (2.5)
Rho³	0.81 (6.9)		0.35 (2.4)	0.91 (20.3)	0.52 (3.1)			0.40 (2.1)	0.80 (6.7)	0.40 (2.2)	0.95 (30.9)	0.87 (8.3)	0.92 (26.6)	0.25 (1.3)
SEE	0.080	0.028	0.033	0.036	0.039	0.037	0.052	0.047	0.030	0.031	0.046	0.034	0.025	0.023
R ²	0.58	0.%	0.99	0.97	0.98	0.77	0.96	0.97	0.95	0.98	0.97	0.53⁴	0.99	0.99
D-W	1.33	1.23	2.02	1.86	2.10	1.43	1.59	1.76	2.00	2.00	1.83	1.41	1.52	1.99

^¹The t-statistics are in parentheses.

^²For Denmark, this variable is intended to allow for the effect of entry into the European Economic Community. The variable is equal to zero prior to the first half of 1973.

^³Cochrane-Orcutt autoregressive correction.

^⁴Estimate is affected by the origin constraint. SEE is a better measure of the goodness of fit.

Table 7.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Agricultural Goods, Ssecond Half 1962–First Half 1976 ¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–2.14 (1.9)	2.33 (12.9)	0.54 (3.0)	0.48 (0.4)	1.41 (5.3)	3.37 (14.0)	–0.16 (0.4)	1.69 (3.0)	3.40 (13.9)	0.13 (0.6)	2.20 (3.8)		1.31 (3.3)	0.05 (0.4)
Wages		0.18 (9.6)	0.17 (3.6)	0.50 (3.8)	0.34 (5.1)	0.12 (4.6)	0.20 (6.3)	0.37 (11.1)	0.31 (5.7)	0.40 (12.8)			0.67 (7.5)	0.28 (6.9)
Spot commodity prices		0.19 (6.5)	0.09 (1.5)	0.06 (1.0)	0.18 (2.1)		0.15 (1.9)			0.12 (2.6)		0.16 (3.2)		0.45 (9.5)
Spot commodity prices (–1)	0.31 (1.9)		0.52 (6.5)		0.14 (1.6)	0.13 (2.4)	0.23 (3.1)	0.15 (2.4)		0.15 (2.6)	0.54 (5.7)	0.08 (1.2)	0.07 (1.1)	0.24 (3.3)
Spot commodity prices (–2)			0.20 (3.3)							0.11 (2.4)		0.18 (3.6)		0.05 (1.1)
Dummies²				0.11 (2.5)
Rho³	0.81 (6.9)		0.35 (2.4)	0.91 (20.3)	0.52 (3.1)			0.40 (2.1)	0.80 (6.7)	0.40 (2.2)	0.95 (30.9)	0.87 (8.3)	0.92 (26.6)	0.25 (1.3)
SEE	0.080	0.028	0.033	0.036	0.039	0.037	0.052	0.047	0.030	0.031	0.046	0.034	0.025	0.023
R ²	0.58	0.%	0.99	0.97	0.98	0.77	0.96	0.97	0.95	0.98	0.97	0.53⁴	0.99	0.99
D-W	1.33	1.23	2.02	1.86	2.10	1.43	1.59	1.76	2.00	2.00	1.83	1.41	1.52	1.99

^¹The t-statistics are in parentheses.

^²For Denmark, this variable is intended to allow for the effect of entry into the European Economic Community. The variable is equal to zero prior to the first half of 1973.

^³Cochrane-Orcutt autoregressive correction.

^⁴Estimate is affected by the origin constraint. SEE is a better measure of the goodness of fit.

Table 8.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Raw Materials, Second Half 1962–First Half 1976¹

^¹The t-statistics are in parentheses.

^²Price of petroleum for Belgium-Luxembourg and the United States; dummy variable taking on the value 1 from 1974 on for Denmark, to reflect a jump in the price of nonmineral oils.

^³Cochrane-Orcutt autoregressive correction.

Table 8.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Raw Materials, Second Half 1962–First Half 1976¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–1.89 (3.7)	2.41 (6.5)		2.71 (4.6)	0.66 (3.0)	2.56 (5.1)	–1.38 (1.6)	–3.20 (4.9)	1.24 (1.3)		3.05 (15.4)	0.88 (1.9)	0.82 (2.5)
Wages			0.55 (8.6)		0.28 (10.5)		0.47 (4.1)	0.09 (4.2)	0.45 (2.9)		0.32 (7.9)	0.64 (6.9)	0.37 (4.7)
Spot commodity prices			0.25 (4.8)					0.17 (1.7)		0.18 (2.2)			0.19 (2.6)
Spot commodity prices (–1)		0.18 (3.7)	0.09 (1.7)		0.40 (4.6)	0.26 (2.8)	0.31 (3.4)	0.36 (2.4)		0.25 (2.6)		0.15 (2.7)
Spot commodity prices (–2)	0.28 (4.0)		0.14 (2.5)	0.32 (2.9)	0.14 (1.6)	0.17 (1.7)	0.13 (1.3)	0.34 (3.2)	0.19 (1.8)	0.46 (5.6)		0.09 (1.4)
Dummies²		0.16 (6.3)		0.54 (5.7)									0.29 (9.4)
Rho³	0.93 (19.4)	0.83 (8.4)	0.97 (34.4)	0.73 (6.0)		0.83 (7.8)	0.88 (14.8)	0.27 (1.4)	0.86 (8.5)	0.96 (78.8)	0.55 (3.3)	0.89 (15.5)
SEE	0.047	0.031	0.024	0.102	0.050	0.049	0.046	0.050	0.057	0.046	0.032	0.033	0.053
R ²	0.92	0.97	0.99	0.91	0.95	0.83	0.97	0.92	0.91	0.97	0.92	0.99	0.98
D-W	1.55	1.44	1.12	1.36	1.87	1.75	1.10	1.78	1.02	0.85	1.75	1.49	1.75

^¹The t-statistics are in parentheses.

^²Price of petroleum for Belgium-Luxembourg and the United States; dummy variable taking on the value 1 from 1974 on for Denmark, to reflect a jump in the price of nonmineral oils.

^³Cochrane-Orcutt autoregressive correction.

Table 8.

Fourteen Industrial Countries: Estimates of Export Unit Value Equations for Raw Materials, Second Half 1962–First Half 1976¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–1.89 (3.7)	2.41 (6.5)		2.71 (4.6)	0.66 (3.0)	2.56 (5.1)	–1.38 (1.6)	–3.20 (4.9)	1.24 (1.3)		3.05 (15.4)	0.88 (1.9)	0.82 (2.5)
Wages			0.55 (8.6)		0.28 (10.5)		0.47 (4.1)	0.09 (4.2)	0.45 (2.9)		0.32 (7.9)	0.64 (6.9)	0.37 (4.7)
Spot commodity prices			0.25 (4.8)					0.17 (1.7)		0.18 (2.2)			0.19 (2.6)
Spot commodity prices (–1)		0.18 (3.7)	0.09 (1.7)		0.40 (4.6)	0.26 (2.8)	0.31 (3.4)	0.36 (2.4)		0.25 (2.6)		0.15 (2.7)
Spot commodity prices (–2)	0.28 (4.0)		0.14 (2.5)	0.32 (2.9)	0.14 (1.6)	0.17 (1.7)	0.13 (1.3)	0.34 (3.2)	0.19 (1.8)	0.46 (5.6)		0.09 (1.4)
Dummies²		0.16 (6.3)		0.54 (5.7)									0.29 (9.4)
Rho³	0.93 (19.4)	0.83 (8.4)	0.97 (34.4)	0.73 (6.0)		0.83 (7.8)	0.88 (14.8)	0.27 (1.4)	0.86 (8.5)	0.96 (78.8)	0.55 (3.3)	0.89 (15.5)
SEE	0.047	0.031	0.024	0.102	0.050	0.049	0.046	0.050	0.057	0.046	0.032	0.033	0.053
R ²	0.92	0.97	0.99	0.91	0.95	0.83	0.97	0.92	0.91	0.97	0.92	0.99	0.98
D-W	1.55	1.44	1.12	1.36	1.87	1.75	1.10	1.78	1.02	0.85	1.75	1.49	1.75

^¹The t-statistics are in parentheses.

^²Price of petroleum for Belgium-Luxembourg and the United States; dummy variable taking on the value 1 from 1974 on for Denmark, to reflect a jump in the price of nonmineral oils.

^³Cochrane-Orcutt autoregressive correction.

Table 9.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Agricultural Goods, First Half 1963–First Half 1976¹

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and ⅙, respectively.

^³Cochrane-Orcutt autoregressive correction.

Table 9.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Agricultural Goods, First Half 1963–First Half 1976¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–5.69 (12.3)	–6.05 (13.2)	0.96 (3.2)	–0.18 (0.5)	0.67 (5.6)	1.52 (4.6)	–5.09 (13.9)	–5.37 (9.8)	2.40 (8.9)	0.29 (2.5)	0.28 (0.7)	1.54 (4.1)	2.38 (27.3)	1.55 (5.7)
Partner-industrial country export prices²	1.08 (12.7)	1.10 (7.6)		0.46 (4.3)	0.96 (10.4)	0.80 (9.6)	0.97 (9.2)	0.25 (1.5)	0.50 (8.5)		0.47 (3.0)		0.64 (9.8)	0.14 (0.9)
Spot commodity prices			0.58 (5.4)	0.17 (2.7)	0.06 (1.0)		0.07 (1.2)	0.17 (1.7)		0.41 (7.2)	0.09 (1.3)	0.18 (4.5)		0.26 (3.1)
Spot commodity prices (–1)		0.35 (3.5)	0.10 (0.7)	0.20 (2.7)				0.61 (5.5)		0.35 (5.6)	0.18 (3.6)	0.25 (6.0)	0.23 (2.3)	0.33 (3.3)
Spot commodity prices (–2)			0.25 (2.3)								0.12 (1.7)	0.12 (3.1)
Rho³	0.27 (1.3)		0.70 (5.0)	0.64 (4.5)		0.21 (1.1)	0.65 (4.4)	0.34 (1.8)	0.81 (9.2)		0.87 (9.6)	0.97 (41.6)	0.64 (4.1)	0.81 (9.6)
SEE	0.029	0.049	0.041	0.028	0.028	0.032	0.025	0.035	0.014	0.025	0.020	0.016	0.020	0.029
R ²	0.948	0.966	0.980	0.979	0.984	0.841	0.994	0.985	0.977	0.984	0.991	0.985	0.997	0.988
D-W	2.20	1.09	1.16	1.89	1.82	1.93	2.12	1.79	1.45	2.29	1.43	1.88	2.00	2.26

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and ⅙, respectively.

^³Cochrane-Orcutt autoregressive correction.

Table 9.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Agricultural Goods, First Half 1963–First Half 1976¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–5.69 (12.3)	–6.05 (13.2)	0.96 (3.2)	–0.18 (0.5)	0.67 (5.6)	1.52 (4.6)	–5.09 (13.9)	–5.37 (9.8)	2.40 (8.9)	0.29 (2.5)	0.28 (0.7)	1.54 (4.1)	2.38 (27.3)	1.55 (5.7)
Partner-industrial country export prices²	1.08 (12.7)	1.10 (7.6)		0.46 (4.3)	0.96 (10.4)	0.80 (9.6)	0.97 (9.2)	0.25 (1.5)	0.50 (8.5)		0.47 (3.0)		0.64 (9.8)	0.14 (0.9)
Spot commodity prices			0.58 (5.4)	0.17 (2.7)	0.06 (1.0)		0.07 (1.2)	0.17 (1.7)		0.41 (7.2)	0.09 (1.3)	0.18 (4.5)		0.26 (3.1)
Spot commodity prices (–1)		0.35 (3.5)	0.10 (0.7)	0.20 (2.7)				0.61 (5.5)		0.35 (5.6)	0.18 (3.6)	0.25 (6.0)	0.23 (2.3)	0.33 (3.3)
Spot commodity prices (–2)			0.25 (2.3)								0.12 (1.7)	0.12 (3.1)
Rho³	0.27 (1.3)		0.70 (5.0)	0.64 (4.5)		0.21 (1.1)	0.65 (4.4)	0.34 (1.8)	0.81 (9.2)		0.87 (9.6)	0.97 (41.6)	0.64 (4.1)	0.81 (9.6)
SEE	0.029	0.049	0.041	0.028	0.028	0.032	0.025	0.035	0.014	0.025	0.020	0.016	0.020	0.029
R ²	0.948	0.966	0.980	0.979	0.984	0.841	0.994	0.985	0.977	0.984	0.991	0.985	0.997	0.988
D-W	2.20	1.09	1.16	1.89	1.82	1.93	2.12	1.79	1.45	2.29	1.43	1.88	2.00	2.26

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and ⅙, respectively.

^³Cochrane-Orcutt autoregressive correction.

Table 10.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Raw Material Prices, First Half 1963–First Half 1976¹

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and ⅙, respectively.

^³Cochrane-Orcutt autoregressive correction.

Table 10.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Raw Material Prices, First Half 1963–First Half 1976¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–4.76 (3.5)	–2.09 (4.4)	0.60 (1.3)	–1.65 (3.7)	–0.27 (1.9)	0.52 (1.8)	–5.92 (14.2)	–5.50 (11.3)	1.44(2.3)	–1.20 (5.4)	0.32 (0.6)	1.59 (7.0)	1.88 (46.2)	3.56 (30.4)
Partner-industrial country export prices²	0.88 (3.8)	0.84 (10.1)	0.41 (3.6)	0.92 (4.7)	0.67 (11.3)	0.66 (9.6)	0.72 (7.9)	0.26 (4.6)	0.65 (5.2)	0.80 (10.1)	1.05 (8.8)	0.56 (6.0)	0.56 (18.0)	0.31 (11.1)
Spot commodity prices		0.12 (2.3)	0.60 (4.0)					0.35 (6.7)	0.06 (1.5)					0.19 (7.7)
Spot commodity prices (–1)				0.20 (1.8)	0.41 (7.6)	0.34 (5.5)	0.38 (3.9)	0.39 (5.3)				0.10 (2.2)	0.34 (8.4)
Spot commodity prices (–2)										0.14 (1.5)		0.12 (3.2)	0.11 (2.5)
Price of petroleum									0.27 (5.4)					0.95 (46.1)
Rho³	0.93 (16.3)	0.75 (6.3)	0.83 (7.6)	0.68 (4.4)	0.31 (1.6)	0.46 (2.9)	0.48 (2.8)	0.66 (4.3)	0.72 (5.1)	0.32 (1.5)	0.66 (4.5)	0.92 (33.7)	0.25 (1.3)
SEE	0.056	0.023	0.038	0.084	0.024	0.021	0.035	0.020	0.017	0.027	0.054	0.015	0.016	0.014
R ²	0.927	0.979	0.971	0.891	0.991	0.955	0.989	0.987	0.994	0.982	0.946	0.983	0.996	0.999
D-W	2.14	2.03	2.39	1.17	1.96	2.02	1.99	1.76	2.27	1.77	2.48	1.73	1.82	2.43

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and ⅙, respectively.

^³Cochrane-Orcutt autoregressive correction.

Table 10.

Fourteen Industrial Countries: Estimates of Import Unit Value Equations for Raw Material Prices, First Half 1963–First Half 1976¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–4.76 (3.5)	–2.09 (4.4)	0.60 (1.3)	–1.65 (3.7)	–0.27 (1.9)	0.52 (1.8)	–5.92 (14.2)	–5.50 (11.3)	1.44(2.3)	–1.20 (5.4)	0.32 (0.6)	1.59 (7.0)	1.88 (46.2)	3.56 (30.4)
Partner-industrial country export prices²	0.88 (3.8)	0.84 (10.1)	0.41 (3.6)	0.92 (4.7)	0.67 (11.3)	0.66 (9.6)	0.72 (7.9)	0.26 (4.6)	0.65 (5.2)	0.80 (10.1)	1.05 (8.8)	0.56 (6.0)	0.56 (18.0)	0.31 (11.1)
Spot commodity prices		0.12 (2.3)	0.60 (4.0)					0.35 (6.7)	0.06 (1.5)					0.19 (7.7)
Spot commodity prices (–1)				0.20 (1.8)	0.41 (7.6)	0.34 (5.5)	0.38 (3.9)	0.39 (5.3)				0.10 (2.2)	0.34 (8.4)
Spot commodity prices (–2)										0.14 (1.5)		0.12 (3.2)	0.11 (2.5)
Price of petroleum									0.27 (5.4)					0.95 (46.1)
Rho³	0.93 (16.3)	0.75 (6.3)	0.83 (7.6)	0.68 (4.4)	0.31 (1.6)	0.46 (2.9)	0.48 (2.8)	0.66 (4.3)	0.72 (5.1)	0.32 (1.5)	0.66 (4.5)	0.92 (33.7)	0.25 (1.3)
SEE	0.056	0.023	0.038	0.084	0.024	0.021	0.035	0.020	0.017	0.027	0.054	0.015	0.016	0.014
R ²	0.927	0.979	0.971	0.891	0.991	0.955	0.989	0.987	0.994	0.982	0.946	0.983	0.996	0.999
D-W	2.14	2.03	2.39	1.17	1.96	2.02	1.99	1.76	2.27	1.77	2.48	1.73	1.82	2.43

^¹The t-statistics are in parentheses.

^²Weighted average of current and previous period partner-country export prices using weights of ⅚ and ⅙, respectively.

^³Cochrane-Orcutt autoregressive correction.

Nonetheless, the statistical results, as evidenced by the large standard errors of estimate, are frequently unsatisfactory. The average of these errors across all equations in Tables 7–10 is 3½ per cent. A third of the standard errors falls in each of the following categories: less than 3 per cent, 3 to 4 per cent, and 4 per cent or more. Several factors account for at least part of these rather large errors. First, the standard errors for many of the equations are greatly affected by several extreme residuals, so that, in many cases, the median error is likely to be smaller than the average error. Second, while these extreme observations often appear to be random (for example, large price changes during the 1960s, when foreign trade prices were quite flat), others can be traced to specific shortcomings of the model. For instance, the omission of wood from the list of spot commodity price indices is a critical shortcoming insofar as Canadian and Scandinavian exports are concerned. In the main, however, the worst equations are those that refer to trade flows of secondary importance both to the country in question and to international trade generally. Third, the residuals from the various equations are often correlated across countries, which suggests that certain common influences may not have been taken into account. Symptomatic of this is the fact that the addition of a dummy variable that takes the value one from 1974 onward to the equations in Tables 8 and 10 would yield statistically significant coefficients in virtually every raw material price equation. This dummy could be interpreted as reflecting the large change in relative fuel prices, but petroleum is known not to be covered in the raw material unit value indices for most of these countries. In short, there was an explosion in foreign trade prices for raw materials in 1974 that is inadequately accounted for by the equations.

The standard errors tend to be larger in the equations for raw materials, given in Tables 9 and 10, than for agricultural products, given in Tables 7 and 8. One possible explanation is that long-term contracts are more pervasive in trade in raw materials than in agricultural trade. Some support for this thesis is provided by the somewhat longer lags (particularly on the export side) between spot prices and unit values for raw materials than for agricultural products. A second distinguishing characteristic of the tables is that the results on the import side tend to be somewhat better than those on the export side. The explanation here must stem from the near-identity character of the import equation, since it includes a weighted average of the export price indices of industrial trading partners.

It is difficult to evaluate the magnitudes of the parameters in Tables 7–10, since it is unclear what “reasonable” estimates for these parameters are. On the export side, the spot price data serve both an input cost and a competitor price function, but the importance of these functions is not clear. On the import side, the influence of the spot price data is partly embedded in the partner-country export price variable. With these considerations in mind, note that the cumulated coefficients for the spot price data tend to be rather small, mostly between ¼ and ½, in all the tables. The exceptions—the parameters for Canadian agricultural export prices and Japanese raw material import prices—generally seem to be of the right magnitude.

There is a wide diversity of lags between changes in spot prices and unit values, as evidenced in Tables 7–10. While this diversity makes generalizations somewhat hazardous, the evidence suggests that the lags on the export side are somewhat longer than those on the import side. This is consistent with the notion that the spot price data in the export equations partly serve an “input cost” function, so that a pass-through lag that does not apply to imports is added to the spot-price unit value lag for exports. Finally, as already mentioned, the average lags seem to be somewhat longer for raw materials than for agricultural products.

estimation of the volume block for the industrial countries

Volume parameters for manufactures

The parameter estimates for the import and export volume equations for manufactures are given in Tables 11–12. The price terms used here are based on unit value indices and, for imports, the domestic wholesale price for manufactures. Partly to avoid errors in measurement bias arising from the use of unit value indices as both deflators and price measures, and to economize on the number of variables that need to be introduced in the equations, a variable reflecting short-term developments in relative prices (an average of the relative price terms over the two preceding periods) and one representing longer-term developments (an average over the period from one and one-half years to four years, or three to seven periods, earlier) were introduced. The joint impact of these price terms for both imports and exports of manufactures are summarized in Table 13. Given the rather long lags in the response of flows to price movements that have been found in empirical studies, the omission of the current level of relative prices was not thought to have serious consequences.

Table 11.

Fourteen Industrial Countries: Estimates of Volume Equations for Manufactured Imports¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³SDYR (e.g., SD71) indicates that dummy represents a change in seasonal pattern starting in YR (e.g., 1971). DYR12 (e.g., D196612) indicates a dummy that takes the value 1 for the first half year (1966:1), and -1 for the second half year (1966:2). DYR (1) YR (2) (e.g., D196768) indicates a dummy that takes the value 1 for the second half of YR (1) (1967:2) and -1 for the first half of year YR (2) (1968:1). DYRPR (e.g., D197201) is a dummy that takes on the value of 1 for the year and period indicated (e.g., 1972:1). CDYRPR (e.g., CD196801) is a constant shift dummy taking the value of 1 from YR, PR (e.g., 1968:1). For Austria, dummy I takes the value 0.5 for the second half of 1972, and 1 thereafter; dummy II = D197601. For Belgium-Luxembourg, dummy I is CD197401; dummy II = D196612. For Denmark, dummy I = D197601. For France, dummy I = CD196801. For the Federal Republic of Germany, dummy I = D197302 + D197401. For Italy, dummy I reflects the effects of strikes on trade in manufactures. For Japan, dummy I = 1, 2, 3 for the second half of 1972 through the second half of 1973, and remains at 3 thereafter; dummy II = 1 for 1965. For the Netherlands, dummy I = CD197401; dummy II = D197301. For Norway, dummy I = CD197301. For the United Kingdom, dummy I = 1 for the first half of 1973, and 2 thereafter. For the United States, dummy I takes the value of 1, 2, …, 7 from the first half of 1968 through the second half of 1970, and remains at 7 thereafter; dummy II = 1 for the second half of 1973, 0 for the first half of 1974, and -1 for the second half of 1974.

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 11.

Fourteen Industrial Countries: Estimates of Volume Equations for Manufactured Imports¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	8.75 (17.4)	7.21 (7.6)	8.28 (10.4)	9.85 (14.3)	8.41 (11.9)	9.41 (3.1)	8.65 (8.8)	10.67 (3.4)	10.44 (15.2)	9.14 (5.4)	7.96 (9.5)	7.58 (13.7)	7.80 (7.9)	8.14 (11.7)
Seasonal dummy²	0.009 (0.8)	–0.052 (3.8)	–0.054 (3.8)	–0.028 (2.2)	–0.071 (5.0)	0.007 (0.6)	–0.000 (0.0)	0.018 (1.1)	–0.023 (2.4)	–0.028 (2.5)	–0.052 (5.1)	–0.040 (2.0)	–0.057 (3.8)	–0.006 (0.5)
Time trend	0.012 (6.6)	0.034 (6.7)	0.006 (1.7)	0.017 (6.3)	0.026 (11.3)	0.016 (0.7)	0.030 (12.4)	–0.004 (0.0)	0.008 (5.6)	–0.010 (1.2)	0.007 (4.2)	0.011 (6.9)	0.034 (12.3)	0.035 (8.3)
Demand	1.67 (15.5)	1.27 (5.4)	1.29 (7.2)	1.92 (12.4)	1.38 (8.6)	1.89 (10.2)	1.57 (7.1)	2.04 (9.4)	1.76 (11.3)	1.62 (4.6)	1.33 (7.1)	1.29 (10.3)	1.32 (6.0)	1.27 (9.0)
Price (1-2)		0.47 (1.2)	0.85 (1.6)	0.19 (0.8)	0.82 (3.2)	0.39 (1.8)		0.90 (4.1)		0.93 (3.8)	2.07 (4.6)		0.43 (2.7)	1.92 (6.5)
Price (3-7)				1.44 (3.6)		0.51 (1.1)		0.55 (1.1)		2.18 (3.5)
Potential output	1.25	1.25	1.25	1.25	1.25	1.71 (2.0)	1.25	1.45 (1.3)	1.25	1.25	1.25	1.25	1.25	1.25
Dummy I³	0.069 (3.1)	–0.110 (4.7)		0.073 (2.1)	0.066 (2.3)	–0.112 (4.2)	0.78 (2.1)	0.078 (3.0)	0.190 (8.9)	0.071 (1.8)			0.039 (2.6)	0.010 (1.3)
Dummy II³	0.129 (4.1)	–0.075 (3.1)						–0.133 (3.5)	0.118 (4.3)					–0.062 (2.7)
SEE	0.025	0.032	0.035	0.029	0.035	0.028	0.068	0.044	0.023	0.027	0.023	0.051	0.036	0.031
R ²	0.96	0.94	0.88	0.88	0.97	1.00	0.87	0.99	0.86	0.96	0.88	0.81	0.96	0.97
D-W	1.81	1.82	2.02	2.05	1.84	1.90	1.64	2.31	1.78	1.71	2.13	2.05	2.20	2.18
Time⁴	1966:1–1976:1		1965:1–1976:1	1965:1–1976:1			1965:1–1976:1				1966:1–1976:1		1965:1–1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 11.

Fourteen Industrial Countries: Estimates of Volume Equations for Manufactured Imports¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	8.75 (17.4)	7.21 (7.6)	8.28 (10.4)	9.85 (14.3)	8.41 (11.9)	9.41 (3.1)	8.65 (8.8)	10.67 (3.4)	10.44 (15.2)	9.14 (5.4)	7.96 (9.5)	7.58 (13.7)	7.80 (7.9)	8.14 (11.7)
Seasonal dummy²	0.009 (0.8)	–0.052 (3.8)	–0.054 (3.8)	–0.028 (2.2)	–0.071 (5.0)	0.007 (0.6)	–0.000 (0.0)	0.018 (1.1)	–0.023 (2.4)	–0.028 (2.5)	–0.052 (5.1)	–0.040 (2.0)	–0.057 (3.8)	–0.006 (0.5)
Time trend	0.012 (6.6)	0.034 (6.7)	0.006 (1.7)	0.017 (6.3)	0.026 (11.3)	0.016 (0.7)	0.030 (12.4)	–0.004 (0.0)	0.008 (5.6)	–0.010 (1.2)	0.007 (4.2)	0.011 (6.9)	0.034 (12.3)	0.035 (8.3)
Demand	1.67 (15.5)	1.27 (5.4)	1.29 (7.2)	1.92 (12.4)	1.38 (8.6)	1.89 (10.2)	1.57 (7.1)	2.04 (9.4)	1.76 (11.3)	1.62 (4.6)	1.33 (7.1)	1.29 (10.3)	1.32 (6.0)	1.27 (9.0)
Price (1-2)		0.47 (1.2)	0.85 (1.6)	0.19 (0.8)	0.82 (3.2)	0.39 (1.8)		0.90 (4.1)		0.93 (3.8)	2.07 (4.6)		0.43 (2.7)	1.92 (6.5)
Price (3-7)				1.44 (3.6)		0.51 (1.1)		0.55 (1.1)		2.18 (3.5)
Potential output	1.25	1.25	1.25	1.25	1.25	1.71 (2.0)	1.25	1.45 (1.3)	1.25	1.25	1.25	1.25	1.25	1.25
Dummy I³	0.069 (3.1)	–0.110 (4.7)		0.073 (2.1)	0.066 (2.3)	–0.112 (4.2)	0.78 (2.1)	0.078 (3.0)	0.190 (8.9)	0.071 (1.8)			0.039 (2.6)	0.010 (1.3)
Dummy II³	0.129 (4.1)	–0.075 (3.1)						–0.133 (3.5)	0.118 (4.3)					–0.062 (2.7)
SEE	0.025	0.032	0.035	0.029	0.035	0.028	0.068	0.044	0.023	0.027	0.023	0.051	0.036	0.031
R ²	0.96	0.94	0.88	0.88	0.97	1.00	0.87	0.99	0.86	0.96	0.88	0.81	0.96	0.97
D-W	1.81	1.82	2.02	2.05	1.84	1.90	1.64	2.31	1.78	1.71	2.13	2.05	2.20	2.18
Time⁴	1966:1–1976:1		1965:1–1976:1	1965:1–1976:1			1965:1–1976:1				1966:1–1976:1		1965:1–1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 12.

Fourteen Industrial Countries: Estimates of Volume Equations for Manufactured Exports¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For Austria, dummy I = 2 for the second half of 1972 and -1 for 1973. For Belgium-Luxembourg, dummy I = SD6973. For the Federal Republic of Germany, dummy I = D196802; dummy II = 1 for 1970. For Japan, dummy I = 1,2,…, 7 from the first half of 1968 through the first half of 1971 (i.e., 1968:1–1971:1), and 7 thereafter; dummy II is the level of capacity utilization in Japanese manufacturing. For the Netherlands, dummy I = SD71. For Norway, dummy I = CD197301. For the United Kingdom, dummy I = CD197301. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 12.

Fourteen Industrial Countries: Estimates of Volume Equations for Manufactured Exports¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–0.34 (0.4)	0.13 (1.2)	2.10 (3.1)	–0.29 (0.2)	2.36 (3.3)	–0.87 (1.7)	–0.54 (0.4)	–3.06 (1.3)	2.61 (2.3)	1.20 (0.55)	–1.20 (1.5)	1.03 (2.1)	0.90 (0.5)	–2.51 (2.4)
Seasonal dummy²	0.045 (4.8)	–0.027 (2.3)	–0.021 (1.3)	0.021 (1.3)	–0.068 (10.3)	0.022 (4.9)	–0.000 (0.0)	0.079 (4.7)	0.020 (1.4)	–0.021 (1.1)	–0.021 (2.4)	0.029 (1.5)	–0.056 (4.5)	–0.026 (3.1)
Time trend	–0.006 (0.7)	–0.012 (2.6)	0.002 (0.4)	–0.006 (0.6)	0.013 (2.6)	–0.003 (0.9)	–0.013 (1.4)	–0.038 (2.4)	0.013 (1.6)	0.009 (0.4)	0.002 (0.2)	0.011 (0.5)	0.000 (0.0)	–0.024 (4.0)
Foreign demand	1.08 (6.4)	1.03 (10.4)	0.69 (7.1)	1.08 (4.7)	0.70 (7.0)	1.11 (17.6)	1.12 (6.2)	1.45 (4.6)	0.65 (3.8)	0.75 (1.8)	1.14 (8.6)	0.82 (2.3)	0.90 (3.6)	1.32 (10.0)
Price (1-2)	–0.77 (3.7)	–1.42 (6.0)		–0.83 (3.2)	–1.58 (9.4)	–0.03 (0.2)		–1.73 (5.8)	–0.14 (0.6)	–1.48 (3.5)	–1.82 (5.8)	–1.02 (2.7)	–0.12 (0.4)	–0.29 (1.5)
Price (3-7)	–0.27 (0.7)	–1.60 (3.9)		–0.10 (0.3)	–0.39 (1.4)	–0.63 (3.3)			–1.73 (3.6)	–1.41 (1.2)	–0.01 (0.0)	–0.55 (0.9)	–0.42 (1.1)	–1.22 (5.3)
Potential output	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
Dummy I³		0.014 (1.6)						0.033 (4.1)	–0.022 (2.0)	–0.067 (1.9)			–0.059 (2.3)
Dummy II³								–0.51 (3.2)
SEE	0.022	0.019	0.042	0.033	0.017	0.011	0.035	0.040	0.026	0.046	0.022	0.048	0.031	0.021
R ²	1.00	1.00	0.97	0.98	1.00	1.00	0.98	0.98	1.00	0.98	1.00	0.96	0.99	1.00
D-W	2.21	2.18	1.40	2.37	2.02	1.93	1.48	1.20	2.48	1.90	1.98	2.11	1.96	2.38
Time⁴		1966:1–1976:1		1967:1–1976:1			1967:1–1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 12.

Fourteen Industrial Countries: Estimates of Volume Equations for Manufactured Exports¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–0.34 (0.4)	0.13 (1.2)	2.10 (3.1)	–0.29 (0.2)	2.36 (3.3)	–0.87 (1.7)	–0.54 (0.4)	–3.06 (1.3)	2.61 (2.3)	1.20 (0.55)	–1.20 (1.5)	1.03 (2.1)	0.90 (0.5)	–2.51 (2.4)
Seasonal dummy²	0.045 (4.8)	–0.027 (2.3)	–0.021 (1.3)	0.021 (1.3)	–0.068 (10.3)	0.022 (4.9)	–0.000 (0.0)	0.079 (4.7)	0.020 (1.4)	–0.021 (1.1)	–0.021 (2.4)	0.029 (1.5)	–0.056 (4.5)	–0.026 (3.1)
Time trend	–0.006 (0.7)	–0.012 (2.6)	0.002 (0.4)	–0.006 (0.6)	0.013 (2.6)	–0.003 (0.9)	–0.013 (1.4)	–0.038 (2.4)	0.013 (1.6)	0.009 (0.4)	0.002 (0.2)	0.011 (0.5)	0.000 (0.0)	–0.024 (4.0)
Foreign demand	1.08 (6.4)	1.03 (10.4)	0.69 (7.1)	1.08 (4.7)	0.70 (7.0)	1.11 (17.6)	1.12 (6.2)	1.45 (4.6)	0.65 (3.8)	0.75 (1.8)	1.14 (8.6)	0.82 (2.3)	0.90 (3.6)	1.32 (10.0)
Price (1-2)	–0.77 (3.7)	–1.42 (6.0)		–0.83 (3.2)	–1.58 (9.4)	–0.03 (0.2)		–1.73 (5.8)	–0.14 (0.6)	–1.48 (3.5)	–1.82 (5.8)	–1.02 (2.7)	–0.12 (0.4)	–0.29 (1.5)
Price (3-7)	–0.27 (0.7)	–1.60 (3.9)		–0.10 (0.3)	–0.39 (1.4)	–0.63 (3.3)			–1.73 (3.6)	–1.41 (1.2)	–0.01 (0.0)	–0.55 (0.9)	–0.42 (1.1)	–1.22 (5.3)
Potential output	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00	1.00
Dummy I³		0.014 (1.6)						0.033 (4.1)	–0.022 (2.0)	–0.067 (1.9)			–0.059 (2.3)
Dummy II³								–0.51 (3.2)
SEE	0.022	0.019	0.042	0.033	0.017	0.011	0.035	0.040	0.026	0.046	0.022	0.048	0.031	0.021
R ²	1.00	1.00	0.97	0.98	1.00	1.00	0.98	0.98	1.00	0.98	1.00	0.96	0.99	1.00
D-W	2.21	2.18	1.40	2.37	2.02	1.93	1.48	1.20	2.48	1.90	1.98	2.11	1.96	2.38
Time⁴		1966:1–1976:1		1967:1–1976:1			1967:1–1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 13.

Fourteen Industrial Countries: Relative Price Elasticities for Manufactures¹

^¹These elasticities are based on Tables 11 and 12. The short-term response elasticity is the coefficient on the average of the relative price term over the two preceding periods; the longer-term response is the coefficient on the average for the three to seven preceding periods. The cumulative response coefficient is the sum of these two; t-statistics are given in parentheses.

Table 13.

Fourteen Industrial Countries: Relative Price Elasticities for Manufactures¹

	Imports			Exports
Country	Short-term response	Longer-term response	Cumulative response	Short-term response	Longer-term response	Cumulative response
Austria	—	—	—	–0.77	–0.27	–1.04
				(3.7)	(0.7)	(2.9)
Belgium-Luxembourg	0.47 (1.2)	—	0.47 (1.2)	–1.42 (6.0)	–1.60 (3.9)	–3.02 (7.1)
Canada	0.85 (1.6)	—	0.85 (1.6)	—	—	—
Denmark	0.19 (0.8)	1.44 (3.6)	1.63 (3.3)	–0.83 (3.2)	–0.10 (0.3)	–0.93 (3.7)
France	0.82 (3.2)	—	0.82 (3.2)	–1.58 (9.4)	–0.39 (1.4)	–1.97 (6.8)
Germany, Fed. Rep.	0.39 (1.8)	0.51 (1.1)	0.90 (2.2)	–0.03 (0.2)	–0.63 (3.3)	–0.66 (4.2)
Italy	—	—	—	—	—	—
Japan	0.90 (4.1)	0.55 (1.1)	1.45 (2.6)	–1.73 (5.8)	—	–1.73 (5.8)
Netherlands	—	—	—	–0.14 (0.6)	–1.73 (3.6)	–1.87 (3.5)
Norway	0.93 (3.8)	2.18 (3.5)	3.11 (4.1)	–1.48 (3.5)	–1.41 (1.2)	–2.89 (3.1)
Sweden	2.07 (4.6)	—	2.07 (4.6)	–1.82 (5.8)	–0.00 (0.0)	–1.82 (2.7)
Switzerland	—	—	—	–1.02 (2.7)	–0.55 (0.9)	–1.57 (2.7)
United Kingdom	0.43 (2.7)	—	0.43 (2.7)	–0.12 (0.4)	–0.42 (1.1)	–0.54 (1.2)
United States	—	1.92 (6.5)	1.92 (6.5)	–0.29 (1.5)	–1.23 (5.3)	–1.52 (10.7)

Table 13.

Fourteen Industrial Countries: Relative Price Elasticities for Manufactures¹

	Imports			Exports
Country	Short-term response	Longer-term response	Cumulative response	Short-term response	Longer-term response	Cumulative response
Austria	—	—	—	–0.77	–0.27	–1.04
				(3.7)	(0.7)	(2.9)
Belgium-Luxembourg	0.47 (1.2)	—	0.47 (1.2)	–1.42 (6.0)	–1.60 (3.9)	–3.02 (7.1)
Canada	0.85 (1.6)	—	0.85 (1.6)	—	—	—
Denmark	0.19 (0.8)	1.44 (3.6)	1.63 (3.3)	–0.83 (3.2)	–0.10 (0.3)	–0.93 (3.7)
France	0.82 (3.2)	—	0.82 (3.2)	–1.58 (9.4)	–0.39 (1.4)	–1.97 (6.8)
Germany, Fed. Rep.	0.39 (1.8)	0.51 (1.1)	0.90 (2.2)	–0.03 (0.2)	–0.63 (3.3)	–0.66 (4.2)
Italy	—	—	—	—	—	—
Japan	0.90 (4.1)	0.55 (1.1)	1.45 (2.6)	–1.73 (5.8)	—	–1.73 (5.8)
Netherlands	—	—	—	–0.14 (0.6)	–1.73 (3.6)	–1.87 (3.5)
Norway	0.93 (3.8)	2.18 (3.5)	3.11 (4.1)	–1.48 (3.5)	–1.41 (1.2)	–2.89 (3.1)
Sweden	2.07 (4.6)	—	2.07 (4.6)	–1.82 (5.8)	–0.00 (0.0)	–1.82 (2.7)
Switzerland	—	—	—	–1.02 (2.7)	–0.55 (0.9)	–1.57 (2.7)
United Kingdom	0.43 (2.7)	—	0.43 (2.7)	–0.12 (0.4)	–0.42 (1.1)	–0.54 (1.2)
United States	—	1.92 (6.5)	1.92 (6.5)	–0.29 (1.5)	–1.23 (5.3)	–1.52 (10.7)

It was hoped that a disaggregation of trade flows into manufactured and nonmanufactured commodities would result in reasonable and significant coefficients on the relative price terms for manufactures. From Table 13, this will be seen to be true for export and import volume equations for the majority of the industrial countries. The principal exception is Italy. For most of the European countries for which the price coefficients were significant, imports responded in large part to changes in relative prices within three periods; for Denmark, Norway, and the United States, the import response to price movements tended to be slower. A similar though less pronounced pattern of price coefficients was found for exports, with the response time for the Federal Republic of Germany, the Netherlands, and the United States being substantially slower than for the other countries. The price coefficients by themselves suggest that a sustained fall in domestic prices relative to those abroad would tend to contribute to an improvement in the balance on manufactures for Japan, Norway, Sweden, and the United States.²⁴ For a number of the other countries, the price effects on the value of exports and imports resulting from a change in relative prices would tend to be offsetting, so that the outturn for the trade balance for manufactures is much less certain.

These measures of price sensitivity must be viewed with caution. There are a number of reasons why these price measures based on unit values and domestic wholesale prices may perform rather poorly. These reasons include differences in coverage, the influence of import prices on the domestic price level, the effects of competitor prices on export price formation, and simple errors in measurement.

In the equations for imports, the coefficients on fluctuations in the demand for manufactures variable range from about 1.3 to 2. The demand coefficients for Japan, Denmark, and the Federal Republic of Germany tend to be larger (though not significantly larger in a statistical sense) than those of other countries. As a result of substantial collinearity with the trend term, the coefficients on potential output tended to have large standard errors and did not generally appear to be reliable considered one at a time. Consequently, the average of the coefficients for the 14 countries was calculated and used to constrain the coefficients for which satisfactory estimates had not been obtained.²⁵

The principal explanatory variables for the equations for manufactured exports are the weighted averages of manufactured imports in the 14 industrial countries and four regions. The coefficients on the foreign market variable ranged from about 0.6 to 1.5. In Table 12, Japanese exports show the greatest sensitivity to short-term variations in foreign demand followed at some distance by those of the United States, Sweden, Italy, and the Federal Republic of Germany; the Dutch, Canadian, French, and Norwegian coefficients show much lower levels of responsiveness.²⁶ At the same time, the large negative trend coefficient for Japan suggests that the responsiveness of exports to short-term fluctuations in foreign demand may exceed their responsiveness to longer-term developments.²⁷ The trend variable for the other industrial countries in Table 12 does not tend to play an important role.

There was little fluctuation in the rate of growth of potential output over the period of estimation, with the result that the potential output variables and time trends were highly collinear. Consequently, the estimated coefficients had large standard errors and frequently displayed the wrong sign. Only the coefficient for the Federal Republic of Germany appeared satisfactory. When the estimation period is extended, it is expected that more reasonable coefficient estimates will be obtained. For the time being, however, it is necessary for purposes of medium-term projection to be able to take into account the implication for countries’ export performances of the deceleration in the growth rates of potential output from the mid-1970s. To this end, the coefficients on the potential output variable were constrained to one. The constraining of these parameters had only a small effect on the estimated coefficients for the other exogenous variables excepting the trend and constant terms.

A number of dummy variables were included in the individual country equations for manufactures and other commodities and are described briefly in the footnotes to the tables. Many of these are designed to pick up changes in seasonal patterns and institutional changes that have had a significant impact on trade flows. A rationale for the inclusion of many of these dummies is immediately forthcoming, for example, the effects of the oil embargo on fuel imports, or the effects of strikes on trade flows, and further information on these dummies is provided in the Appendix.

Volume parameters for nonmanufactured commodities

The equations for the import and export volumes for raw materials are given in Tables 14–15. They do not tend to be very satisfactory. However, for forecasting purposes, exogenous information provided by country and commodity specialists on raw material and agricultural flows is introduced.

Table 14.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Raw Materials¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For Austria, dummy I = D196869; dummy II = CD197102. For Canada, dummy I = 19, 20, …, 29 from the first half of 1964 through the first half of 1969 (i.e., 1964:1–1969:1), and 30 thereafter. For Denmark, dummy I = CD197401; dummy II = D197601. For Japan, dummy I = 19, 20, …, 32 from 1964:1–1971:2, and 32 thereafter; dummy II = D196901. For Sweden, dummy I = 19, 20, …, 34 from 1964:1–1972:2, and 34 thereafter. For the United Kingdom, dummy I = SD6671. For the United States, dummy I = 19, 20, …, 28 from 1964:1–1968:2, and 29 thereafter; dummy II = SD6870. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 14.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Raw Materials¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdon	United States
Constant	–14.60 (9.9)	–4.43 (2.5)	1.22 (0.3)	–10.40 (3.6)	–2.89 (1.8)	–1.51 (1.3)	0.80 (0.6)	–1.92 (3.4)	–6.20 (3.6)	–5.13 (0.9)	–14.69 (4.4)	–2.99 (1.6)	–7.02 (3.1)	3.36 (2.1)
Seasonal dummy²	–0.031 (1.7)	–0.031 (1.7)	0.052 (2.1)	–0.013 (0.5)	–0.111 (7.5)	0.011 (0.8)	–0.025 (1.4)	–0.021 (1.5)	0.042 (1.9)	0.045 (1.2)	0.077 (4.2)	–0.066 (2.0)	–0.043 (2.0)	0.000 (0.0)
Time trend	–0.039 (6.8)	–0.008 (1.5)	0.012 (1.4)	–0.022 (2.3)	–0.007 (1.4)	0.007 (2.6)	0.002 (0.4)	–0.014 (3.6)	–0.023 (3.9)	–0.005 (0.3)	–0.021 (2.8)	0.000 (0.1)	–0.019 (6.7)	–0.006 (3.4)
Output in manufacturing	1.64 (4.9)	1.26 (4.6)	1.06 (1.9)	2.24 (4.4)	1.54 (6.9)	1.10 (5.6)	0.63 (3.0)	0.93 (5.9)	1.38 (2.9)	1.52 (1.2)	0.95 (1.8)	0.88 (2.3)	2.29 (6.4)	1.37 (7.3)
Output in manufacturing (–1)	1.02 (2.7)	0.01 (0.3)	0.53 (0.9)	–0.08 (0.2)	–0.56 (2.4)	–0.28 (1.4)	0.04 (0.2)	0.06 (0.4)	0.14 (0.3)	–0.12 (0.1)	1.52 (2.6)	0.07 (0.2)	–0.79 (2.1)	–1.05 (5.6)
Dummy I³	0.100 (3.0)		–0.017 (2.1)	–0.160 (2.6)				0.002 (2.0)			–0.038 (5.6)		0.045 (2.9)	0.022 (4.6)
Dummy II³	–0.180 (4.9)			0.340 (4.0)				–0.102 (3.1)						0.033 (2.2)
SEE	0.044	0.044	0.060	0.065	0.037	0.030	0.039	0.031	0.056	0.090	0.045	0.066	0.039	0.032
R ²	0.96	0.93	0.80	0.84	0.95	0.96	0.90	0.98	0.86	0.75	0.80	0.61	0.77	0.82
D-W	1.70	1.75	1.63	1.92	1.77	1.87	2.21	1.94	2.05	1.92	2.21	1.69	1.86	2.09
Time⁴						1966:1–1976:1	1966:1–1976:1	1966:1–1976:1				1968:1–1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 14.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Raw Materials¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdon	United States
Constant	–14.60 (9.9)	–4.43 (2.5)	1.22 (0.3)	–10.40 (3.6)	–2.89 (1.8)	–1.51 (1.3)	0.80 (0.6)	–1.92 (3.4)	–6.20 (3.6)	–5.13 (0.9)	–14.69 (4.4)	–2.99 (1.6)	–7.02 (3.1)	3.36 (2.1)
Seasonal dummy²	–0.031 (1.7)	–0.031 (1.7)	0.052 (2.1)	–0.013 (0.5)	–0.111 (7.5)	0.011 (0.8)	–0.025 (1.4)	–0.021 (1.5)	0.042 (1.9)	0.045 (1.2)	0.077 (4.2)	–0.066 (2.0)	–0.043 (2.0)	0.000 (0.0)
Time trend	–0.039 (6.8)	–0.008 (1.5)	0.012 (1.4)	–0.022 (2.3)	–0.007 (1.4)	0.007 (2.6)	0.002 (0.4)	–0.014 (3.6)	–0.023 (3.9)	–0.005 (0.3)	–0.021 (2.8)	0.000 (0.1)	–0.019 (6.7)	–0.006 (3.4)
Output in manufacturing	1.64 (4.9)	1.26 (4.6)	1.06 (1.9)	2.24 (4.4)	1.54 (6.9)	1.10 (5.6)	0.63 (3.0)	0.93 (5.9)	1.38 (2.9)	1.52 (1.2)	0.95 (1.8)	0.88 (2.3)	2.29 (6.4)	1.37 (7.3)
Output in manufacturing (–1)	1.02 (2.7)	0.01 (0.3)	0.53 (0.9)	–0.08 (0.2)	–0.56 (2.4)	–0.28 (1.4)	0.04 (0.2)	0.06 (0.4)	0.14 (0.3)	–0.12 (0.1)	1.52 (2.6)	0.07 (0.2)	–0.79 (2.1)	–1.05 (5.6)
Dummy I³	0.100 (3.0)		–0.017 (2.1)	–0.160 (2.6)				0.002 (2.0)			–0.038 (5.6)		0.045 (2.9)	0.022 (4.6)
Dummy II³	–0.180 (4.9)			0.340 (4.0)				–0.102 (3.1)						0.033 (2.2)
SEE	0.044	0.044	0.060	0.065	0.037	0.030	0.039	0.031	0.056	0.090	0.045	0.066	0.039	0.032
R ²	0.96	0.93	0.80	0.84	0.95	0.96	0.90	0.98	0.86	0.75	0.80	0.61	0.77	0.82
D-W	1.70	1.75	1.63	1.92	1.77	1.87	2.21	1.94	2.05	1.92	2.21	1.69	1.86	2.09
Time⁴						1966:1–1976:1	1966:1–1976:1	1966:1–1976:1				1968:1–1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 15.

Fourteen Industrial Countries: Estimates of Volume Equations for Exports of Raw Materials¹

^¹The t-statistics are in parentheses.

^²Cochrane-Orcutt autoregressive correction for second-order serial correlation. The coefficients are estimated to be 1.34 (9.2) and -0.81 (5.6).

^³This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴For Austria, dummy I = D197601. For Canada, dummy I = CD197502. For France, dummy I = CD197201. For Sweden, dummy I - 25, …, 31 from the first half of 1967 through the first half of 1970 (i.e., 1967:1–1970:1), and 31 thereafter; dummy II = D197601. For Switzerland, dummy I = 0.5 for 1973:2 and 1 for 1974:1. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁵The sample period is indicated only when it is different from 1964:1–1976:1.

Table 15.

Fourteen Industrial Countries: Estimates of Volume Equations for Exports of Raw Materials¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark²	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–1.07 (1.1)	–2.04 (1.9)	–0.03 (0.2)	–1.33 (0.8)	–0.26 (0.2)	–2.21 (2.0)	0.80 (0.8)	–3.13 (1.9)	–0.91 (0.7)	–3.16 (2.6)	–7.12 (9.6)	–4.33 (1.9)	–2.80 (1.8)	–3.45 (1.9)
Seasonal dummy³	0.044 (2.2)	–0.020 (0.9)	0.053 (3.2)	–0.141 (11.6)	–0.051 (2.8)	0.040 (1.9)	–0.068 (3.2)	0.116 (3.1)	0.077 (3.1)	0.008 (0.3)	0.105 (8.0)	0.009 (0.2)	–0.092 (3.2)	–0.015 (0.5)
Time trend	–0.012 (2.4)	–0.012 (2.9)	0.010 (3.9)	–0.007 (0.7)	0.007 (1.5)	0.039 (12.2)	0.006 (1.4)	0.012 (1.1)	0.020 (3.9)	0.001 (0.4)	–0.011 (5.4)	–0.007 (0.8)	0.001 (0.1)	–0.022 (3.1)
Foreign demand	1.26 (5.9)	1.42 (6.8)	0.95 (6.0)	1.35 (3.3)	1.00 (5.3)	1.15 (6.2)	0.80 (3.8)	1.52 (4.0)	1.03 (4.1)	1.59 (6.7)	2.36 (17.3)	2.07 (3.5)	1.46 (4.7)	1.51 (5.8)
Dummy I⁴	0.310 (5.7)		–0.270 (7.3)		0.083 (2.5)						–0.052 (6.8)	0.315 (3.1)
Dummy II ⁴											–0.198 (5.9)
SEE	0.048	0.057	0.041	0.087	0.044	0.036	0.052	0.092	0.062	0.047	0.027	0.091	0.072	0.076
R ²	0.91	0.84	0.94	0.86	0.97	0.97	0.91	0.95	0.96	0.79	0.96	0.79	0.92	0.82
D-W	1.77	1.82	1.65	2.40	1.66	1.63	1.63	1.95	2.02	1.60	2.69	2.16	1.74	1.65
Time⁵						1970:1–1976:1				1967:1–1976:1	1967:1–1976:1	1970:1–1976:1

^¹The t-statistics are in parentheses.

^²Cochrane-Orcutt autoregressive correction for second-order serial correlation. The coefficients are estimated to be 1.34 (9.2) and -0.81 (5.6).

^³This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁵The sample period is indicated only when it is different from 1964:1–1976:1.

Table 15.

Fourteen Industrial Countries: Estimates of Volume Equations for Exports of Raw Materials¹

Explanatory Variable	Austria	Belgium-Luxembourg	Canada	Denmark²	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–1.07 (1.1)	–2.04 (1.9)	–0.03 (0.2)	–1.33 (0.8)	–0.26 (0.2)	–2.21 (2.0)	0.80 (0.8)	–3.13 (1.9)	–0.91 (0.7)	–3.16 (2.6)	–7.12 (9.6)	–4.33 (1.9)	–2.80 (1.8)	–3.45 (1.9)
Seasonal dummy³	0.044 (2.2)	–0.020 (0.9)	0.053 (3.2)	–0.141 (11.6)	–0.051 (2.8)	0.040 (1.9)	–0.068 (3.2)	0.116 (3.1)	0.077 (3.1)	0.008 (0.3)	0.105 (8.0)	0.009 (0.2)	–0.092 (3.2)	–0.015 (0.5)
Time trend	–0.012 (2.4)	–0.012 (2.9)	0.010 (3.9)	–0.007 (0.7)	0.007 (1.5)	0.039 (12.2)	0.006 (1.4)	0.012 (1.1)	0.020 (3.9)	0.001 (0.4)	–0.011 (5.4)	–0.007 (0.8)	0.001 (0.1)	–0.022 (3.1)
Foreign demand	1.26 (5.9)	1.42 (6.8)	0.95 (6.0)	1.35 (3.3)	1.00 (5.3)	1.15 (6.2)	0.80 (3.8)	1.52 (4.0)	1.03 (4.1)	1.59 (6.7)	2.36 (17.3)	2.07 (3.5)	1.46 (4.7)	1.51 (5.8)
Dummy I⁴	0.310 (5.7)		–0.270 (7.3)		0.083 (2.5)						–0.052 (6.8)	0.315 (3.1)
Dummy II ⁴											–0.198 (5.9)
SEE	0.048	0.057	0.041	0.087	0.044	0.036	0.052	0.092	0.062	0.047	0.027	0.091	0.072	0.076
R ²	0.91	0.84	0.94	0.86	0.97	0.97	0.91	0.95	0.96	0.79	0.96	0.79	0.92	0.82
D-W	1.77	1.82	1.65	2.40	1.66	1.63	1.63	1.95	2.02	1.60	2.69	2.16	1.74	1.65
Time⁵						1970:1–1976:1				1967:1–1976:1	1967:1–1976:1	1970:1–1976:1

^¹The t-statistics are in parentheses.

^²Cochrane-Orcutt autoregressive correction for second-order serial correlation. The coefficients are estimated to be 1.34 (9.2) and -0.81 (5.6).

^³This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁵The sample period is indicated only when it is different from 1964:1–1976:1.

The principal explanatory variables for the volume of raw material imports are indices of real output (value added) in the manufacturing sector. The countries whose short-term elasticity of “demand” for imports of raw materials is less than 1.0 include the Federal Republic of Germany, Italy, and the United States.²⁸ The coefficients for Austria, Denmark, and Sweden exceed 2 and seem excessively large, but in each case these coefficients are accompanied by large negative trend coefficients. Anticipated needs for raw materials appear to play a relatively important role in determining raw material imports in France, the United Kingdom, and the United States.²⁹

The coefficients on the foreign market variable for raw material exports, which are shown in Table 15, are significant for all the industrial countries, although they vary in magnitude from 2.36 for Sweden, which again displays a large negative trend coefficient, to 0.80 for Italy.

In general, these volume equations are characterized by rather poor fits and large standard errors. Fortunately, raw material exports do not tend to be very important for most of the industrial countries, with the exception of Canada, Sweden, and, to a lesser extent, the United States; in 1975, raw material exports accounted for 19, 15, and 10 per cent of total exports in value terms for these three countries.

Part of the variability of the raw materials series may be spurious, and the result of deflating value’ series by unrepresentative unit value series.³⁰ It may be worth considering alternative deflators for the value series, or whether—although theoretically less acceptable—some specification in value terms might produce more reliable results.

The coefficients for the agricultural goods equations are given in Tables 16 and 17. As expected, the standard errors tend to be large and the multiple correlation coefficients low, especially for agricultural exports. Part of the reason for the poor statistical fit can be found in the numerous government and regional agreements that affect this trade and the vagaries of weather. For example, U.K. and Danish agricultural exports appear to have been significantly affected by the entrance of these countries into the European Economic Community. To capture certain supply and demand factors, indices of agricultural output for the various countries were introduced, but were never significant.

Table 16.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Agricultural Goods¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For the Federal Republic of Germany, dummy I = D196502. For Italy, dummy I = ⅔ for the second half of 1974, 1 for the first half of 1975, and –0.5 for the second half of 1975. For Japan, dummy I = SD6973. For the Netherlands, dummy I = 1 for the first half of 1971 through the first half of 1972 (i.e., 1971:1–1972:1). For the United Kingdom, dummy I = SD6773. For the United States, dummy I = D196901. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 16.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Agricultural Goods¹

Explanatory Variable	Austria	Belgium- Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	6.44 (11.8)	5.69 (5.7)	6.90 (12.1)	4.70 (18.0)	8.12 (10.1)	8.19 (60.1)	6.14 (2.0)	5.89 (96.0)	6.08 (16.7)	4.58 (50.0)	5.58 (26.0)	6.60 (57.0)	7.80 (3.7)	9.04 (14.6)
Seasonal dummy²	–0.006 (0.2)	0.037 (0.9)	0.150 (7.9)	0.027 (1.1)	–0.077 (3.3)	0.044 (4.3)	0.011 (0.4)	–0.063 (2.1)	–0.010 (0.7)	–0.104 (4.0)	–0.026 (1.0)	0.014 (1.0)	0.020 (1.4)	–0.000 (0.1)
Time trend	–0.046 (2.6)	0.025 (0.8)	–0.024 (1.3)	0.018 (2.2)	–0.032 (1.2)	–0.012 (4.3)	0.033 (4.3)	0.042 (24.0)	0.022 (2.0)	0.012 (4.7)	0.007 (1.1)	–0.002 (5.9)	–0.000 (0.2)	–0.033 (1.6)
Consumer expenditure	2.75 (3.7)	0.10 (0.1)	1.99 (2.7)	0.97 (1.2)	2.25 (2.2)	1.54 (8.1)	0.14 (0.8)		0.99 (2.3)		0.26 (0.5)	1.95 (9.8)		2.83 (2.6)
Price (1–2)	0.45 (0.7)	0.96 (3.6)	0.36 (4.7)	0.34 (0.8)	0.09 (0.3)	0.35 (2.6)	0.54 (2.7)	0.42 (5.2)	0.26 (0.4)	0.38 (2.7)	0.46 (3.3)	0.22 (1.8)	0.16 (3.1)	0.34 (1.4)
Dummy I³						0.10 (3.5)	–0.08 (2.0)	0.060 (2.6)	–0.12 (3.0)				–0.04 (4.5)	–0.10 (1.8)
Dummy II³
SEE	0.054	0.094	0.047	0.047	0.056	0.025	0.068	0.058	0.041	0.064	0.058	0.033	0.023	0.052
R ²	0.88	0.57	0.95	0.90	0.91	0.98	0.94	0.97	0.99	0.82	0.78	0.93	0.61	0.81
D-W	1.78	1.47	2.02	1.55	1.41	1.93	1.76	1.77	2.30	1.67	1.83	1.89	2.16	2.13
Time⁴	1968:1– 1976:1	1966:1– 1976:1		1969:1– 1976:1					1965:1– 1976:1					1965:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 16.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Agricultural Goods¹

Explanatory Variable	Austria	Belgium- Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	6.44 (11.8)	5.69 (5.7)	6.90 (12.1)	4.70 (18.0)	8.12 (10.1)	8.19 (60.1)	6.14 (2.0)	5.89 (96.0)	6.08 (16.7)	4.58 (50.0)	5.58 (26.0)	6.60 (57.0)	7.80 (3.7)	9.04 (14.6)
Seasonal dummy²	–0.006 (0.2)	0.037 (0.9)	0.150 (7.9)	0.027 (1.1)	–0.077 (3.3)	0.044 (4.3)	0.011 (0.4)	–0.063 (2.1)	–0.010 (0.7)	–0.104 (4.0)	–0.026 (1.0)	0.014 (1.0)	0.020 (1.4)	–0.000 (0.1)
Time trend	–0.046 (2.6)	0.025 (0.8)	–0.024 (1.3)	0.018 (2.2)	–0.032 (1.2)	–0.012 (4.3)	0.033 (4.3)	0.042 (24.0)	0.022 (2.0)	0.012 (4.7)	0.007 (1.1)	–0.002 (5.9)	–0.000 (0.2)	–0.033 (1.6)
Consumer expenditure	2.75 (3.7)	0.10 (0.1)	1.99 (2.7)	0.97 (1.2)	2.25 (2.2)	1.54 (8.1)	0.14 (0.8)		0.99 (2.3)		0.26 (0.5)	1.95 (9.8)		2.83 (2.6)
Price (1–2)	0.45 (0.7)	0.96 (3.6)	0.36 (4.7)	0.34 (0.8)	0.09 (0.3)	0.35 (2.6)	0.54 (2.7)	0.42 (5.2)	0.26 (0.4)	0.38 (2.7)	0.46 (3.3)	0.22 (1.8)	0.16 (3.1)	0.34 (1.4)
Dummy I³						0.10 (3.5)	–0.08 (2.0)	0.060 (2.6)	–0.12 (3.0)				–0.04 (4.5)	–0.10 (1.8)
Dummy II³
SEE	0.054	0.094	0.047	0.047	0.056	0.025	0.068	0.058	0.041	0.064	0.058	0.033	0.023	0.052
R ²	0.88	0.57	0.95	0.90	0.91	0.98	0.94	0.97	0.99	0.82	0.78	0.93	0.61	0.81
D-W	1.78	1.47	2.02	1.55	1.41	1.93	1.76	1.77	2.30	1.67	1.83	1.89	2.16	2.13
Time⁴	1968:1– 1976:1	1966:1– 1976:1		1969:1– 1976:1					1965:1– 1976:1					1965:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 17.

Fourteen Industrial Countries: Estimates of Volume Equations for Exports of Agricultural Goods¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For Austria, dummy I = 1 from the second half of 1975 on. For Belgium-Luxembourg, dummy I = CD197401. For Denmark, dummy I = CD197302. For France, dummy I = D196801; dummy II = CD196802. For the Federal Republic of Germany, dummy I = CD196901. For the Netherlands, dummy I = CD196802. For Norway, dummy I = CD197302. For Sweden, dummy I = CD197302. For the United Kingdom, dummy I = CD197302. For the United States, dummy I = D197302; dummy II = CD196802. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 17.

Fourteen Industrial Countries: Estimates of Volume Equations for Exports of Agricultural Goods¹

Explanatory Variable	Austria	Belgium- Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	1.41 (1.16)	3.80 (64.7)	–0.49 (0.2)	2.69 (1.6)	–0.74 (2.4)	0.62 (0.3)	–0.91 (0.3)	6.32 (3.3)	5.04 (3.4)	–0.87 (0.6)	3.48 (27.0)	0.49 (0.4)	4.03 (2.5)	–10.29 (3.6)
Seasonal dummy²	0.025 (0.9)	0.027 (1.3)	0.23 (4.1)	0.019 (1.5)	–0.034 (1.2)	–0.006 (0.2)	0.11 (3.1)	0.22 (7.1)	0.005 (0.3)	0.034 (1.7)	–0.096 (2.2)	0.117 (3.5)	0.116 (4.8)	–0.027 (0.9)
Time trend	0.012 (1.7)	0.073 (36.0)	0.027 (2.5)	–0.000 (0.3)	0.016 (1.8)	0.054 (4.5)	0.007 (0.6)	–0.039 (4.3)	0.036 (6.9)	0.003 (0.4)	0.032 (7.1)	0.019 (2.4)	0.033 (4.2)	–0.036 (2.9)
Foreign demand	0.55 (2.1)		1.17 (2.1)	0.57 (2.1)	1.01 (2.8)	0.60 (1.4)	1.09 (2.2)	0.10 (0.3)	0.12 (2.6)	1.12 (3.4)		1.00 (3.3)	0.19 (0.7)	2.47 (6.1)
Dummy I³	0.50 (10.0)	–0.21 (5.7)		0.082 (2.9)	0.087 (1.1)	0.137 (2.2)			0.090 (2.6)	–0.14 (3.8)	–0.16 (2.1)		0.11 (2.8)	0.187 (2.8)
Dummy II³					0.13 (2.2)									–0.184 (3.9)
SEE	0.056	0.052	0.099	0.031	0.066	0.080	0.086	0.056	0.043	0.048	0.108	0.057	0.056	0.063
R ²	0.99	0.99	0.62	0.87	0.97	0.98	0.88	0.91	0.98	0.88	0.76	0.72	0.97	0.91
D-W	1.58	1.60	2.00	1.89	1.42	2.11	1.91	2.10	2.09	1.47	1.71	1.43	2.16	1.65
Time⁴	1967:1– 1976:1		1970:1– 1976:1	1965:1– 1976:1				1970:1– 1976:1				1970:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 17.

Fourteen Industrial Countries: Estimates of Volume Equations for Exports of Agricultural Goods¹

Explanatory Variable	Austria	Belgium- Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	1.41 (1.16)	3.80 (64.7)	–0.49 (0.2)	2.69 (1.6)	–0.74 (2.4)	0.62 (0.3)	–0.91 (0.3)	6.32 (3.3)	5.04 (3.4)	–0.87 (0.6)	3.48 (27.0)	0.49 (0.4)	4.03 (2.5)	–10.29 (3.6)
Seasonal dummy²	0.025 (0.9)	0.027 (1.3)	0.23 (4.1)	0.019 (1.5)	–0.034 (1.2)	–0.006 (0.2)	0.11 (3.1)	0.22 (7.1)	0.005 (0.3)	0.034 (1.7)	–0.096 (2.2)	0.117 (3.5)	0.116 (4.8)	–0.027 (0.9)
Time trend	0.012 (1.7)	0.073 (36.0)	0.027 (2.5)	–0.000 (0.3)	0.016 (1.8)	0.054 (4.5)	0.007 (0.6)	–0.039 (4.3)	0.036 (6.9)	0.003 (0.4)	0.032 (7.1)	0.019 (2.4)	0.033 (4.2)	–0.036 (2.9)
Foreign demand	0.55 (2.1)		1.17 (2.1)	0.57 (2.1)	1.01 (2.8)	0.60 (1.4)	1.09 (2.2)	0.10 (0.3)	0.12 (2.6)	1.12 (3.4)		1.00 (3.3)	0.19 (0.7)	2.47 (6.1)
Dummy I³	0.50 (10.0)	–0.21 (5.7)		0.082 (2.9)	0.087 (1.1)	0.137 (2.2)			0.090 (2.6)	–0.14 (3.8)	–0.16 (2.1)		0.11 (2.8)	0.187 (2.8)
Dummy II³					0.13 (2.2)									–0.184 (3.9)
SEE	0.056	0.052	0.099	0.031	0.066	0.080	0.086	0.056	0.043	0.048	0.108	0.057	0.056	0.063
R ²	0.99	0.99	0.62	0.87	0.97	0.98	0.88	0.91	0.98	0.88	0.76	0.72	0.97	0.91
D-W	1.58	1.60	2.00	1.89	1.42	2.11	1.91	2.10	2.09	1.47	1.71	1.43	2.16	1.65
Time⁴	1967:1– 1976:1		1970:1– 1976:1	1965:1– 1976:1				1970:1– 1976:1				1970:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

From Table 16, half of the consumer expenditure elasticities were significant and all but one of these parameter estimates (that is, excluding the coefficient for the Netherlands at 0.99) exceeded unity.³¹ If a confidence limit of two standard errors is used, however, only three of the expenditure elasticities differ significantly from unity. The countries whose short-term expenditure coefficients tend to be large are also characterized by negative trend coefficients. The short-term price variable was significant for about half of the industrial countries, and consistently had the expected sign.

In Table 17, the agricultural foreign market variable was significant for half of the countries, and, except for the United States, tended toward one. The very large U.S. market coefficient was accompanied by a large negative time trend.

The volume block for fuels consists solely of import equations for the 11 industrial countries that, over the historical period, have not produced oil and gas domestically in significant quantities.³² For the other 3 countries—the United States, Canada, and the Netherlands—both import and export volume equations for fuel have also been estimated.

The responsiveness of fuel imports to changes in manufacturing output for 8 non-oil producing industrial countries ranges between 1.1 and 1.5. Austria’s short-term responsiveness to fluctuations in manufacturing output seems extremely low, but its imports show a strong trend rate of growth; Swiss responsiveness appears to be well below that of other countries with no significant trend over time.

Fuel price increases in 1974 must have affected fuel consumption, but it is difficult to disentangle the short-term effects of the very sharp worldwide recession, the embargo of 1974, and the longer-term contemporaneous increase in relative fuel prices on fuel consumption. The embargo dummy was significant for 4 countries, with its average value suggesting that about 10 per cent of fuel imports was affected for these countries. The shift variable reflecting the effects of higher relative fuel prices on fuel consumption was significant for 8 countries. However, its coefficient appears to be excessively large for Belgium-Luxembourg. The coefficients for Norway and the United Kingdom may also exaggerate the effect of the fuel price increase somewhat, since North Sea oil started to become important after this increase. The dummy coefficients for the other countries, however, suggest a reduction of between 10 and 20 per cent in the volume of fuel imports in response to the fuel price increase.

The Dutch economy is heavily dependent on domestically produced natural gas, and a large portion of its fuel imports are destined for reexport. Consequently, two additional variables were added to the import volume equation—an index of domestic gas production and the volume of fuel exports, in logs.³³ Both were significant with the expected sign. The level of domestic petroleum production was entered in the Canadian petroleum import equation but had the wrong sign and was not significant. However, the domestic supply variable played an important role in the determination of U.S. imports of fuel. U.S. fuel imports appear to be quite responsive, with a one-period lag, to fluctuations in domestic manufacturing output. Both the U.S. and Dutch import equations show significant and large positive time trend, indicating perhaps the strong growth in demand for energy from the non-manufacturing sector. Simple export volume equations for these three countries were estimated. They are given in Table 19. For Canada and the United States, domestic petroleum production is extremely significant with a coefficient slightly in excess of one. For the Netherlands, the principal explanatory variable is a weighted average of the petroleum imports of its major trading partners.³⁴

Table 18.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Fuels¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³The shift variable takes the value 1 after 1973. The embargo dummy takes the value 1 for the first half of 1974 and –1 for the second half of 1974 except for Belgium-Luxembourg, Norway, and the United Kingdom; for Belgium-Luxembourg, the embargo dummy took the values 2, 1, and –3 for the second half of 1973, the first half of 1974, and the second half of 1974, respectively; for Norway and the United Kingdom, the embargo dummy took the value 1 for the second half of 1973 and –1 for the first half of 1974. For Austria, dummy I = CD197101. For Canada, dummy I = D196902; dummy II = SD71. For the Federal Republic of Germany, dummy I = 21, …, 24 for the first half of 1965 through the second half of 1966 (i.e., 1965:1—1966:2), and 24 thereafter. For the Netherlands, dummy I is an index representing natural gas production; dummy II is the volume of Dutch fuel exports. For Sweden, dummy I = 21, …, 30 for 1965:1–1969:2, and 31 thereafter. For Switzerland, dummy I = SD6567. For the United States, dummy I is an index reflecting the domestic output of crude petroleum. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 18.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Fuels¹

Explanatory Variable	Austria	Belgium- Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–0.88 (0.3)	–5.04 (1.3)	–4.23 (2.8)	–4.18 (1.5)	–8.33 (3.7)	–6.73 (5.1)	–1.74 (1.1)	–4.28 (4.6)	–6.44 (2.0)	–1.87 (0.4)	–4.27 (1.0)	–0.75 (0.5)	–7.84 (2.3)	–8.22 (2.6)
Seasonal dummy²	0.138 (3.7)	0.033 (0.9)	0.290 (4.6)	–0.033 (1.2)	–0.023 (1.3)	0.017 (1.5)	0.048 (2.3)	–0.002 (0.2)	0.029 (1.4)	0.036 (1.2)	0.118 (5.9)	0.020 (0.8)	–0.056 (2.7)	–0.028 (1.1)
Time trend	0.044 (3.2)	0.021 (1.7)	–0.010 (1.8)	0.001 (0.9)	–0.007 (0.9)	0.018 (4.5)	0.007 (1.0)	0.005 (0.8)	0.022 (2.1)	0.015 (1.0)	–0.022 (2.6)	0.002 (0.4)	0.014 (2.8)	0.045 (8.2)
Output in manufacturing	2.03 (2.5)	0.83 (1.4)	0.84 (1.7)	1.24 (2.0)	1.31 (4.5)	0.78 (3.8)	0.41 (1.4)	0.63 (3.1)	1.07 (2.2)	1.71 (1.6)	0.36 (0.6)	0.63 (2.2)	0.21 (0.4)	0.10 (0.2)
Output in manufacturing (–1)	–1.49 (1.9)	0.36 (0.6)	0.32 (0.6)	0.03 (0.5)	0.20 (0.8)	0.37 (2.1)	0.48 (1.9)	0.48 (2.3)	0.02 (0.0)	–0.90 (0.8)	0.75 (1.2)	0.05 (0.2)	1.25 (2.5)	1.12 (2.8)
Shift 1974³	–0.18 (2.4)	–0.52 (7.3)		–0.11 (1.8)	–0.00 (0.1)	–0.12 (4.6)	–0.20 (5.1)	–0.02 (0.3)	–0.17 (2.1)	–0.23 (3.6)		–0.10 (2.4)	–0.33 (6.6)	–0.07 (0.8)
Embargo³	–0.045 (0.7)	–0.078 (3.2)		–0.080 (1.3)	–0.046 (1.5)	–0.029 (1.5)	–0.030 (0.8)	–0.043 (1.1)	–0.020 (0.6)	–0.140 (8.0)	–0.100 (3.0)	–0.050 (1.4)	–0.140 (3.5)	–0.015 (0.3)
Dummy I³	–0.26 (3.4)		–0.150 (2.5)			0.042 (4.4)			–0.21 (2.4)		–0.031 (4.2)	0.076 (3.4)		–1.710 (4.8)
Dummy II³			–0.114 (5.1)						0.53 (5.1)
SEE	0.087	0.087	0.054	0.063	0.039	0.025	0.047	0.026	0.036	0.67	0.045	0.043	0.048	0.062
R ²	0.92	0.90	0.93	0.85	0.98	0.99	0.94	1.00	0.98	0.87	0.91	0.86	0.93	0.97
D-W	1.60	1.75	1.92	1.95	2.11	2.01	2.45	2.03	1.81	1.75	1.83	1.85	1.71	1.66
Time⁴						1965:1– 1976:1	1965:1– 1976:1	1965:1– 1976:1	1967:1– 1976:1		1965:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 18.

Fourteen Industrial Countries: Estimates of Volume Equations for Imports of Fuels¹

Explanatory Variable	Austria	Belgium- Luxembourg	Canada	Denmark	France	Fed. Rep. of Germany	Italy	Japan	Netherlands	Norway	Sweden	Switzerland	United Kingdom	United States
Constant	–0.88 (0.3)	–5.04 (1.3)	–4.23 (2.8)	–4.18 (1.5)	–8.33 (3.7)	–6.73 (5.1)	–1.74 (1.1)	–4.28 (4.6)	–6.44 (2.0)	–1.87 (0.4)	–4.27 (1.0)	–0.75 (0.5)	–7.84 (2.3)	–8.22 (2.6)
Seasonal dummy²	0.138 (3.7)	0.033 (0.9)	0.290 (4.6)	–0.033 (1.2)	–0.023 (1.3)	0.017 (1.5)	0.048 (2.3)	–0.002 (0.2)	0.029 (1.4)	0.036 (1.2)	0.118 (5.9)	0.020 (0.8)	–0.056 (2.7)	–0.028 (1.1)
Time trend	0.044 (3.2)	0.021 (1.7)	–0.010 (1.8)	0.001 (0.9)	–0.007 (0.9)	0.018 (4.5)	0.007 (1.0)	0.005 (0.8)	0.022 (2.1)	0.015 (1.0)	–0.022 (2.6)	0.002 (0.4)	0.014 (2.8)	0.045 (8.2)
Output in manufacturing	2.03 (2.5)	0.83 (1.4)	0.84 (1.7)	1.24 (2.0)	1.31 (4.5)	0.78 (3.8)	0.41 (1.4)	0.63 (3.1)	1.07 (2.2)	1.71 (1.6)	0.36 (0.6)	0.63 (2.2)	0.21 (0.4)	0.10 (0.2)
Output in manufacturing (–1)	–1.49 (1.9)	0.36 (0.6)	0.32 (0.6)	0.03 (0.5)	0.20 (0.8)	0.37 (2.1)	0.48 (1.9)	0.48 (2.3)	0.02 (0.0)	–0.90 (0.8)	0.75 (1.2)	0.05 (0.2)	1.25 (2.5)	1.12 (2.8)
Shift 1974³	–0.18 (2.4)	–0.52 (7.3)		–0.11 (1.8)	–0.00 (0.1)	–0.12 (4.6)	–0.20 (5.1)	–0.02 (0.3)	–0.17 (2.1)	–0.23 (3.6)		–0.10 (2.4)	–0.33 (6.6)	–0.07 (0.8)
Embargo³	–0.045 (0.7)	–0.078 (3.2)		–0.080 (1.3)	–0.046 (1.5)	–0.029 (1.5)	–0.030 (0.8)	–0.043 (1.1)	–0.020 (0.6)	–0.140 (8.0)	–0.100 (3.0)	–0.050 (1.4)	–0.140 (3.5)	–0.015 (0.3)
Dummy I³	–0.26 (3.4)		–0.150 (2.5)			0.042 (4.4)			–0.21 (2.4)		–0.031 (4.2)	0.076 (3.4)		–1.710 (4.8)
Dummy II³			–0.114 (5.1)						0.53 (5.1)
SEE	0.087	0.087	0.054	0.063	0.039	0.025	0.047	0.026	0.036	0.67	0.045	0.043	0.048	0.062
R ²	0.92	0.90	0.93	0.85	0.98	0.99	0.94	1.00	0.98	0.87	0.91	0.86	0.93	0.97
D-W	1.60	1.75	1.92	1.95	2.11	2.01	2.45	2.03	1.81	1.75	1.83	1.85	1.71	1.66
Time⁴						1965:1– 1976:1	1965:1– 1976:1	1965:1– 1976:1	1967:1– 1976:1		1965:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 19.

Canada, the Netherlands, and the United States: Estimates of Volume Equations for Exports of Fuels¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For Canada and the Netherlands, dummy I = CD197401; for the United States, dummy I = CD197302. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 19.

Canada, the Netherlands, and the United States: Estimates of Volume Equations for Exports of Fuels¹

Explanatory Variable	Canada	Netherlands	United States
Constant	0.87 (5.01)	–4.94 (2.4)	6.08 (24.6)
Seasonal dummy²	–0.056 (2.9)	–0.023 (0.5)	0.102 (2.0)
Time trend	0.021 (3.9)	0.039 (2.3)	0.006 (0.7)
Domestic petroleum production	1.31		1.31
Domestic petroleum production	(11.4)		(2.3)
Fuel imports in partner countries		1.44
Fuel imports in partner countries		(4.0)
Dummy I³	–0.16 (3.6)	–0.45 (3.5)	–0.32 (2.4)
SEE	0.048	0.093	0.124
R ²	1.00	0.94	0.66
D-W	2.16	1.81	1.38
Time⁴		1967:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For Canada and the Netherlands, dummy I = CD197401; for the United States, dummy I = CD197302. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

Table 19.

Canada, the Netherlands, and the United States: Estimates of Volume Equations for Exports of Fuels¹

Explanatory Variable	Canada	Netherlands	United States
Constant	0.87 (5.01)	–4.94 (2.4)	6.08 (24.6)
Seasonal dummy²	–0.056 (2.9)	–0.023 (0.5)	0.102 (2.0)
Time trend	0.021 (3.9)	0.039 (2.3)	0.006 (0.7)
Domestic petroleum production	1.31		1.31
Domestic petroleum production	(11.4)		(2.3)
Fuel imports in partner countries		1.44
Fuel imports in partner countries		(4.0)
Dummy I³	–0.16 (3.6)	–0.45 (3.5)	–0.32 (2.4)
SEE	0.048	0.093	0.124
R ²	1.00	0.94	0.66
D-W	2.16	1.81	1.38
Time⁴		1967:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For Canada and the Netherlands, dummy I = CD197401; for the United States, dummy I = CD197302. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from the first half of 1964 through the first half of 1976 (i.e., 1964:1–1976:1).

regional relationships

Statistical descriptions of the relationships estimated for the four regions are given in Tables 20–22. The aggregate volume of exports for the regions are determined by the level of activity in the industrial countries, with the weights on manufacturing output in the industrial countries being related to the pattern of trade of the particular region. The coefficients on the industrial activity variables suggest that the volume of exports in the short term for the non-oil regions is particularly sensitive to the rate of change in activity.³⁵ For each of the regions, the time trend coefficient was positive, and for the non-oil exporting regions, large and highly significant.

Table 20.

Four Regions: Estimates of Volume Equations for Aggregate Exports¹

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³Dummy I for the other developed countries = CD197301 to reflect the expansion of the European Economic Community and the contraction of the European Free Trade Association. Dummy I for the centrally planned economies = 19, …, 32 for the first half of 1964 through the second half of 1971 (i.e., 1964:1–1971:2), and 32 thereafter. Dummy I for the oil exporting countries = CD 197401 to reflect the effects of the change in the relative price of petroleum. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 20.

Four Regions: Estimates of Volume Equations for Aggregate Exports¹

Explanatory Variable	Other Developed Countries	Centrally Planned Economies	Oil Exporting Countries	Other Developing Countries
Constant	4.38 (6.1)	1.54 (3.4)	3.67 (4.3)	6.50 (19.0)
Seasonal dummy²	0.024 (1.6)	0.108 (12.6)	0.011 (0.7)	0.014 (1.9)
Time trend	0.035 (9.7)	0.036 (15.4)	0.007 (1.0)	0.030 (19.5)
Manufacturing output in industrial countries	0.96 (3.6)	0.81 (4.7)	0.89 (2.3)	1.12 (9.0)
Manufacturing output in industrial countries (–1)	–0.16 (0.6)	0.75 (4.3)	0.22 (0.7)	–0.60 (5.0)
Dummy I³	–0.11 (3.8)	–0.008 (2.5)	–0.12 (2.4)
Dummy II³			–0.037 (1.0)
SEE	0.030	0.021	0.038	0.015
R ²	0.98	0.99	0.97	0.99
D-W	2.45	2.31	1.79	1.61
Time⁴	1968:1– 1976:1			1968:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 20.

Four Regions: Estimates of Volume Equations for Aggregate Exports¹

Explanatory Variable	Other Developed Countries	Centrally Planned Economies	Oil Exporting Countries	Other Developing Countries
Constant	4.38 (6.1)	1.54 (3.4)	3.67 (4.3)	6.50 (19.0)
Seasonal dummy²	0.024 (1.6)	0.108 (12.6)	0.011 (0.7)	0.014 (1.9)
Time trend	0.035 (9.7)	0.036 (15.4)	0.007 (1.0)	0.030 (19.5)
Manufacturing output in industrial countries	0.96 (3.6)	0.81 (4.7)	0.89 (2.3)	1.12 (9.0)
Manufacturing output in industrial countries (–1)	–0.16 (0.6)	0.75 (4.3)	0.22 (0.7)	–0.60 (5.0)
Dummy I³	–0.11 (3.8)	–0.008 (2.5)	–0.12 (2.4)
Dummy II³			–0.037 (1.0)
SEE	0.030	0.021	0.038	0.015
R ²	0.98	0.99	0.97	0.99
D-W	2.45	2.31	1.79	1.61
Time⁴	1968:1– 1976:1			1968:1– 1976:1

^¹The t-statistics are in parentheses.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 21.

Four Regions: Estimates of Equations for Aggregate Imports¹

^¹The t-statistics are in parentheses. Equations (1) are in volume terms; equations (2) are in value terms. Equations (1) are specified in real terms, and equations (2) in nominal terms.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^³For other developed economies, dummy I = 21, …, 32 for the first half of 1965 through the second half of 1971 (i.e., 1965:1–1971:2), and 32 thereafter. For the centrally planned economies, dummy I = SD72. For the oil exporting countries, dummy I = 21,…, 39 from 1965:1–1974:1, and 39 thereafter. (See Table 11, footnote 3, for an explanation of these symbols.)

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 21.

Four Regions: Estimates of Equations for Aggregate Imports¹

Explanatory Variable	Other Developed Economies		Centrally Planned Economies		Oil Exporting Countries		Other Developing Countries
Explanatory Variable	(1)	(2)	(1)	(2)	(1)	(2)	(1)	(2)
Constant	0.90 (11.1)	–1.72 (2.6)	0.53 (3.0)	–0.88 (1.9)	–2.74 (8.5)	–6.47 (1.5)	1.07 (6.1)	–0.36 (0.7)
Seasonal dummy²	0.028 (2.4)	0.034 (2.8)	0.085 (5.3)	0.070 (3.6)	–0.009 (0.3)	–0.005 (0.2)	0.024 (2.2)	0.023 (2.2)
Time trend	0.007 (2.2)	0.027 (2.5)	0.014 (5.5)	0.004 (0.4)	0.131 (4.9)	0.135 (2.2)	–0.017 (5.4)	0.009 (1.4)
Purchasing power			0.86 (9.1)		0.20 (3.1)		0.17 (2.0)
Purchasing power (1–2)	0.57 (7.0)		–0.24 (2.4)		0.25 (2.6)		0.36 (3.5)
Export receipts				1.01 (6.9)		0.11 (1.0)		0.23 (1.9)
Export receipts (1–2)		0.24 (1.0)		–0.14 (0.5)		0.14 (1.0)		0.59 (3.6)
Import price		1.25 (6.9)		0.06 (0.4)		1.61 (2.3)		0.54 (2.5)
Import price (1–2)		–0.62 (7.4)		0.16 (1.2)		–0.14 (0.1)		–0.36 (3.5)
Dummy I³	0.006 (2.0)		–0.060 (5.8)	–0.060 (5.7)	–0.103 (4.2)	–0.112 (2.0)
SEE	0.027	0.028	0.024	0.024	0.059	0.058	0.025	0.023
R ²	0.98	1.00	0.99	1.00	0.99	0.99	0.99	1.00
D-W	1.38	1.35	1.73	2.0	1.56	1.75	1.32	1.63
Time⁴	1965:1– 1976:1	1965:1– 1976:1	1964:1– 1976:1	1964:1– 1976:1	1965:1– 1976:1	1965:1– 1976:1	1966:1– 1976:1	1966:1– 1976:1

^¹The t-statistics are in parentheses. Equations (1) are in volume terms; equations (2) are in value terms. Equations (1) are specified in real terms, and equations (2) in nominal terms.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 21.

Four Regions: Estimates of Equations for Aggregate Imports¹

Explanatory Variable	Other Developed Economies		Centrally Planned Economies		Oil Exporting Countries		Other Developing Countries
Explanatory Variable	(1)	(2)	(1)	(2)	(1)	(2)	(1)	(2)
Constant	0.90 (11.1)	–1.72 (2.6)	0.53 (3.0)	–0.88 (1.9)	–2.74 (8.5)	–6.47 (1.5)	1.07 (6.1)	–0.36 (0.7)
Seasonal dummy²	0.028 (2.4)	0.034 (2.8)	0.085 (5.3)	0.070 (3.6)	–0.009 (0.3)	–0.005 (0.2)	0.024 (2.2)	0.023 (2.2)
Time trend	0.007 (2.2)	0.027 (2.5)	0.014 (5.5)	0.004 (0.4)	0.131 (4.9)	0.135 (2.2)	–0.017 (5.4)	0.009 (1.4)
Purchasing power			0.86 (9.1)		0.20 (3.1)		0.17 (2.0)
Purchasing power (1–2)	0.57 (7.0)		–0.24 (2.4)		0.25 (2.6)		0.36 (3.5)
Export receipts				1.01 (6.9)		0.11 (1.0)		0.23 (1.9)
Export receipts (1–2)		0.24 (1.0)		–0.14 (0.5)		0.14 (1.0)		0.59 (3.6)
Import price		1.25 (6.9)		0.06 (0.4)		1.61 (2.3)		0.54 (2.5)
Import price (1–2)		–0.62 (7.4)		0.16 (1.2)		–0.14 (0.1)		–0.36 (3.5)
Dummy I³	0.006 (2.0)		–0.060 (5.8)	–0.060 (5.7)	–0.103 (4.2)	–0.112 (2.0)
SEE	0.027	0.028	0.024	0.024	0.059	0.058	0.025	0.023
R ²	0.98	1.00	0.99	1.00	0.99	0.99	0.99	1.00
D-W	1.38	1.35	1.73	2.0	1.56	1.75	1.32	1.63
Time⁴	1965:1– 1976:1	1965:1– 1976:1	1964:1– 1976:1	1964:1– 1976:1	1965:1– 1976:1	1965:1– 1976:1	1966:1– 1976:1	1966:1– 1976:1

^¹The t-statistics are in parentheses. Equations (1) are in volume terms; equations (2) are in value terms. Equations (1) are specified in real terms, and equations (2) in nominal terms.

^²This dummy takes the value 0 for the first half year and 1 for the second half year.

^⁴The sample period is indicated only when it is different from 1964:1–1976:1.

Table 22.

Four Regions: Estimates of Equations for Aggregate Export and Import Unit Value Indices¹

^¹The t-statistics are in parentheses.

^²Coefficients constrained to match commodity structure of trade in 1974.

^³The data for these countries are not available. The data are, therefore, defined by the equation that is based on the commodity structure of these countries’ trade in 1974.

^⁴Unit value basis.

^⁵Spot prices.

^⁶Cochrane-Orcutt autoregressive correction.

Table 22.

Four Regions: Estimates of Equations for Aggregate Export and Import Unit Value Indices¹

	Exports				Imports²
Explanatory Variable	Other developed economies	Centrally planned economies³	Oil exporting countries²	Other developing countries	Other developed economies	Centrally planned economies³	Oil exporting countries	Other developing countries
Constant	–1.52 (4.8)			–3.25 (11.3)
Price of manufactures⁴	0.50 (6.3)	0.62	0.02	0.30 (5.1)	0.70	0.70	0.80	0.61
Price of fuels⁴	0.11 (4.3)	0.15	0.95	0.03 (1.3)	0.10	0.06	0.02	0.20
Price of other primary commodities⁵	0.33 (9.0)			0.44 (10.2)
Price of other primary commodities (-1)⁵				0.25 (4.6)
Price of foods⁴		0.12	0.01		0.10	0.13	0.14	0.12
Price of raw materials⁴		0.11	0.02		0.10	0.10	0.04	0.06
Rho⁶	0.75 (7.2)
R ²	0.97			0.99
SEE	0.017			0.019
D-W	1.80			1.60

^¹The t-statistics are in parentheses.

^²Coefficients constrained to match commodity structure of trade in 1974.

^³The data for these countries are not available. The data are, therefore, defined by the equation that is based on the commodity structure of these countries’ trade in 1974.

^⁴Unit value basis.

^⁵Spot prices.

^⁶Cochrane-Orcutt autoregressive correction.

Table 22.

Four Regions: Estimates of Equations for Aggregate Export and Import Unit Value Indices¹

	Exports				Imports²
Explanatory Variable	Other developed economies	Centrally planned economies³	Oil exporting countries²	Other developing countries	Other developed economies	Centrally planned economies³	Oil exporting countries	Other developing countries
Constant	–1.52 (4.8)			–3.25 (11.3)
Price of manufactures⁴	0.50 (6.3)	0.62	0.02	0.30 (5.1)	0.70	0.70	0.80	0.61
Price of fuels⁴	0.11 (4.3)	0.15	0.95	0.03 (1.3)	0.10	0.06	0.02	0.20
Price of other primary commodities⁵	0.33 (9.0)			0.44 (10.2)
Price of other primary commodities (-1)⁵				0.25 (4.6)
Price of foods⁴		0.12	0.01		0.10	0.13	0.14	0.12
Price of raw materials⁴		0.11	0.02		0.10	0.10	0.04	0.06
Rho⁶	0.75 (7.2)
R ²	0.97			0.99
SEE	0.017			0.019
D-W	1.80			1.60

^¹The t-statistics are in parentheses.

^²Coefficients constrained to match commodity structure of trade in 1974.

^³The data for these countries are not available. The data are, therefore, defined by the equation that is based on the commodity structure of these countries’ trade in 1974.

^⁴Unit value basis.

^⁵Spot prices.

^⁶Cochrane-Orcutt autoregressive correction.

Imports are explained in terms of the current purchasing power of a region’s export receipts and the average value over the preceding year. In the first column under each heading (Table 21) the demand for imports is explained in volume terms, and the foreign exchange variables are deflated by the price of imports. However, this formulation constrains the effects of an increase of 10 per cent in export receipts and an increase of 10 per cent in import prices to offset one another precisely as far as import volume is concerned. In addition, given the degree of measurement error that may well be involved in the unit value indices for the regions, it may be desirable not to deflate import expenditure and export receipts by these indices but rather to express the relationship in nominal terms and to introduce the price indices as independent explanatory variables. The equations estimated in value terms are reported in the second column under each heading in Table 21.

For the centrally planned economies, the oil exporting countries, and the less developed countries, both the current and the lagged purchasing power variables were significant in explaining the volume of imports. For the centrally planned economies, the coefficient on the current purchasing power variable is close to unity, and the negative sign on the lagged purchasing power variable again suggests particular sensitivity to fluctuations in the rate of change as well as the absolute level of the regions’ foreign exchange receipts. For the other developed countries, only the lagged purchasing power variable was significant and had the right sign. The sum of these coefficients ranged from 0.45 to 0.62. Assuming that export receipts are the sole source of foreign exchange, then the sum of these coefficients should approximate the ratio of the value of exports to the value of imports. For the centrally planned economies, this ratio is approximately one, and for the oil exporting countries, substantially in excess of unity (even in 1970). For the other two regions, it is approximately three fourths. Under the first specification, the sums of the coefficients fall short of these ratios.

When import expenditures are regressed on export receipts and the import price variable, the current import price coefficients tend to be very significant, though not statistically significantly different from unity. This suggests little immediate impact on import volume from an import price increase. To the extent that this is true, the constraint imposed on price effects in the earlier formulation may have biased downward the purchasing power variable coefficients. For the other developed economies and the developing economies, the coefficients on lagged prices are also significant and negative, suggesting a lagged response in import volume to import price changes. Current export receipts for the centrally planned economies, like the current purchasing power variable in the import volume equation, is highly significant with a coefficient of approximately unity; since for these countries the ratio of export receipts to import expenditure is approximately unity, this coefficient suggests that fluctuations in export receipts are fully and immediately translated into fluctuations in import expenditure. Lagged export receipts play a dominant role in the relationship for the other developing countries; the sum of the coefficients on export receipts is approximately equal to the ratio of export receipts to import expenditure. This suggests that, for these countries also, fluctuations in export receipts are fully reflected in fluctuations in import expenditure. For the oil countries and the other developed countries, changes in export receipts play a very small role in determining changes in imports in the short run.

Partly because of collinearity problems, which resulted in coefficients that were incompatible with the known commodity structure of these countries’ trade, and because of a lack of price data for the centrally planned economies, only two of the eight aggregate price equations in Table 22 are estimated. All the other equations reflect the commodity structure of the trade of these country groups in 1974. The coefficients in the two equations that have been estimated—those for the export prices of the developed and developing non-oil primary producing countries—are compatible with those obtained from the commodity composition of trade.

To close the model presented earlier for forecasting or simulation purposes, it is necessary to derive estimates of the volume of imports of agricultural, raw material, and manufactured goods for the four geographical regions considered. These volume estimates are needed in the calculation of the foreign market variables for raw materials and agricultural and manufactured goods used to explain the exports of the industrial countries. This linkage is now obtained by applying exogenously given value shares to the total value of imports to obtain a value estimate by commodity class, and by then deflating these value estimates by unit value deflators constructed from data that are available for the industrial countries.

III. Conclusion

The preceding sections have described the specification of the model and the estimated relationships. The performance of the individual equations over the estimation period can be judged from the summary statistics that have been presented. However, the model was intended primarily to explain movements in industrial countries’ aggregate external flows, not movements in individual commodity flows in isolation. Disaggregation was expected to contribute to the performance of the model at an aggregate level. To obtain measures of the model’s performance at this level over the period of estimation, further calculations were necessary.

To obtain aggregate measures of the goodness of fit, the root-mean-square-error statistic was calculated for the volume of exports and imports, the unit values of exports and imports, and countries’ trade balances.³⁶ These calculations were made with the original semiannual data base from the first half of 1970 through the first half of 1976.³⁷ The root-mean-square errors obtained from the semiannual data are given in Table 23, and those obtained from annual data are given in Table 24.

Table 23.

Fourteen Industrial Countries: Root-Mean-Square Errors, Based on Semiannual Data, First Half 1970-First Half 1976

Table 23.

Fourteen Industrial Countries: Root-Mean-Square Errors, Based on Semiannual Data, First Half 1970-First Half 1976

Country		Volume of Trade		Unit Value		Value of Trade					Trade Balance
Country		Exports	Imports	Exports	Imports	Exports	Imports	Exports	Imports		Trade Balance
		Per cent						Billion U.S. dollars			As per cent of exports
Austria		1.8	1.8	2.3	2.5	2.4	2.4	0.1	0.1	0.1	2.9
Belgium-Luxembourg		1.1	2.1	3.0	1.8	2.9	2.6	0.3	0.3	0.4	3.2
Canada		1.8	2.4	1.4	0.9	2.0	2.2	0.2	0.3	0.3	2.3
Denmark		2.0	2.4	1.4	1.9	2.2	3.1	0.1	0.1	0.1	5.2
France		2.0	2.1	1.6	2.1	2.7	2.3	0.6	0.5	0.8	3.6
Germany, Fed. Rep.		0.8	1.7	1.6	1.8	2.0	2.3	0.8	0.7	0.8	2.2
Italy		3.0	3.6	1.5	0.9	2.6	3.0	0.4	0.5	0.4	3.9
Japan		2.3	2.1	2.3	1.5	2.6	1.8	0.5	0.4	0.7	3.3
Netherlands		2.5	1.7	1.1	2.0	2.6	2.1	0.3	0.3	0.5	3.6
Norway		2.3	2.6	2.5	1.3	2.5	3.0	0.1	0.1	0.2	5.2
Sweden		1.9	2.2	1.2	1.3	1.7	2.9	0.1	0.2	0.2	3.0
Switzerland		4.4	3.8	1.9	1.4	4.0	3.9	0.2	0.2	0.4	6.5
United Kingdom		2.3	2.0	1.2	1.9	1.8	3.0	0.3	0.7	0.7	4.1
United States		2.2	1.8	1.2	1.8	2.8	2.9	1.1	1.2	1.9	4.2
	Total	0.8	0.8	0.9	0.9	1.2	1.2	2.4	2.6	2.6	1.3

Table 23.

Fourteen Industrial Countries: Root-Mean-Square Errors, Based on Semiannual Data, First Half 1970-First Half 1976

Country		Volume of Trade		Unit Value		Value of Trade					Trade Balance
Country		Exports	Imports	Exports	Imports	Exports	Imports	Exports	Imports		Trade Balance
		Per cent						Billion U.S. dollars			As per cent of exports
Austria		1.8	1.8	2.3	2.5	2.4	2.4	0.1	0.1	0.1	2.9
Belgium-Luxembourg		1.1	2.1	3.0	1.8	2.9	2.6	0.3	0.3	0.4	3.2
Canada		1.8	2.4	1.4	0.9	2.0	2.2	0.2	0.3	0.3	2.3
Denmark		2.0	2.4	1.4	1.9	2.2	3.1	0.1	0.1	0.1	5.2
France		2.0	2.1	1.6	2.1	2.7	2.3	0.6	0.5	0.8	3.6
Germany, Fed. Rep.		0.8	1.7	1.6	1.8	2.0	2.3	0.8	0.7	0.8	2.2
Italy		3.0	3.6	1.5	0.9	2.6	3.0	0.4	0.5	0.4	3.9
Japan		2.3	2.1	2.3	1.5	2.6	1.8	0.5	0.4	0.7	3.3
Netherlands		2.5	1.7	1.1	2.0	2.6	2.1	0.3	0.3	0.5	3.6
Norway		2.3	2.6	2.5	1.3	2.5	3.0	0.1	0.1	0.2	5.2
Sweden		1.9	2.2	1.2	1.3	1.7	2.9	0.1	0.2	0.2	3.0
Switzerland		4.4	3.8	1.9	1.4	4.0	3.9	0.2	0.2	0.4	6.5
United Kingdom		2.3	2.0	1.2	1.9	1.8	3.0	0.3	0.7	0.7	4.1
United States		2.2	1.8	1.2	1.8	2.8	2.9	1.1	1.2	1.9	4.2
	Total	0.8	0.8	0.9	0.9	1.2	1.2	2.4	2.6	2.6	1.3

Table 24.

Fourteen Industrial Countries: Root-Mean-Square Errors, Based on Annual Data, 1970–75

Table 24.

Fourteen Industrial Countries: Root-Mean-Square Errors, Based on Annual Data, 1970–75

		Volume of Trade		Unit Value		Value of Trade					Trade Balance
Country		Exports	Imports	Exports	Imports	Exports	Imports	Exports	Imports		Trade Balance
		Per cent						Billion U.S. dollars			As per cent of exports
Austria		1.3	1.0	1.2	1.8	1.4	1.5	0.1	0.1	0.2	2.2
Belgium-Luxembourg		0.6	1.2	2.2	1.1	2.1	1.4	0.5	0.4	0.5	2.0
Canada		1.6	1.9	1.0	0.5	1.9	1.9	0.4	0.4	0.6	2.0
Denmark		1.4	2.3	0.9	1.9	1.2	2.9	0.0	0.2	0.2	4.4
France		1.2	1.1	1.3	1.9	2.1	1.7	1.0	0.6	1.3	2.8
Germany, Fed. Rep.		0.6	1.1	1.5	1.4	1.7	0.9	1.4	0.5	1.4	1.6
Italy		2.4	1.9	1.0	0.7	2.0	1.7	0.4	0.4	0.7	2.9
Japan		1.1	1.0	1.5	0.4	1.9	0.9	0.9	0.4	1.2	2.6
Netherlands		0.5	1.4	0.5	1.2	0.7	1.2	0.2	0.3	0.3	1.2
Norway		1.1	2.1	2.1	0.8	2.3	2.5	0.1	0.2	0.2	4.2
Sweden		1.4	1.3	1.0	0.8	1.1	1.3	0.2	0.1	0.2	1.8
Switzerland		1.7	1.8	1.5	0.9	1.5	2.1	0.2	0.2	0.3	2.8
United Kingdom		1.7	1.6	0.9	1.8	1.0	2.7	0.3	1.3	1.3	3.4
United States		1.8	1.4	0.9	1.5	2.4	2.7	1.9	2.4	3.5	3.8
	Total	0.5	0.6	0.7	0.8	0.9	1.1	3.8	5.0	3.4	0.8

Table 24.

Fourteen Industrial Countries: Root-Mean-Square Errors, Based on Annual Data, 1970–75

		Volume of Trade		Unit Value		Value of Trade					Trade Balance
Country		Exports	Imports	Exports	Imports	Exports	Imports	Exports	Imports		Trade Balance
		Per cent						Billion U.S. dollars			As per cent of exports
Austria		1.3	1.0	1.2	1.8	1.4	1.5	0.1	0.1	0.2	2.2
Belgium-Luxembourg		0.6	1.2	2.2	1.1	2.1	1.4	0.5	0.4	0.5	2.0
Canada		1.6	1.9	1.0	0.5	1.9	1.9	0.4	0.4	0.6	2.0
Denmark		1.4	2.3	0.9	1.9	1.2	2.9	0.0	0.2	0.2	4.4
France		1.2	1.1	1.3	1.9	2.1	1.7	1.0	0.6	1.3	2.8
Germany, Fed. Rep.		0.6	1.1	1.5	1.4	1.7	0.9	1.4	0.5	1.4	1.6
Italy		2.4	1.9	1.0	0.7	2.0	1.7	0.4	0.4	0.7	2.9
Japan		1.1	1.0	1.5	0.4	1.9	0.9	0.9	0.4	1.2	2.6
Netherlands		0.5	1.4	0.5	1.2	0.7	1.2	0.2	0.3	0.3	1.2
Norway		1.1	2.1	2.1	0.8	2.3	2.5	0.1	0.2	0.2	4.2
Sweden		1.4	1.3	1.0	0.8	1.1	1.3	0.2	0.1	0.2	1.8
Switzerland		1.7	1.8	1.5	0.9	1.5	2.1	0.2	0.2	0.3	2.8
United Kingdom		1.7	1.6	0.9	1.8	1.0	2.7	0.3	1.3	1.3	3.4
United States		1.8	1.4	0.9	1.5	2.4	2.7	1.9	2.4	3.5	3.8
	Total	0.5	0.6	0.7	0.8	0.9	1.1	3.8	5.0	3.4	0.8

The goodness-of-fit measures given in Table 23 suggest that the errors associated with the fitted unit value series for the industrial countries have tended to be smaller than the errors associated with the country volume predictions. For imports, this result may reflect the importance of fuel prices in the determination of aggregate import unit values over the measurement period, and the fact that fuel prices are determined exogenously.

The results for export volumes are superior to those for import volumes for 8 of the 14 countries, and especially for Belgium-Luxembourg and the Federal Republic of Germany. This reflects in part the relatively greater importance of manufactures in the exports than in the imports of industrial countries, and the relatively weaker performance of the relationships for nonmanufactured commodity flows; it may also reflect the greater explanatory power of the foreign market variable for manufactures than the variable reflecting the domestic demand for manufactures.

The measures of error based on annual data suggest that the performance of the model on an annual basis is superior to its performance on a semiannual basis.³⁸ That is to say, errors between half years seem to be offsetting rather than compounding for 9 of the 14 countries.³⁹ For Canada, there appears to be a compounding error in the aggregation of semiannual data. These results suggest that the magnitude of the response of trade flows to changes in economic activity over a period of one year are more accurately represented than the timing of this response between half years.

On an annual basis, the dollar trade balance error varies from a high of $3.5 billion for the United States, to $1.2–1.4 billion for France, the Federal Republic of Germany, Japan, and the United Kingdom, to a low of $0.2 billion for the Nordic countries. These simple dollar figures, while of substantial interest, must be placed in perspective to arrive at a judgment on just how well or how badly the model may be expected to perform.

Clearly, the dollar trade balance error will tend to increase as the size of import and export flows increases; when the error calculation is based on the difference between the actual and the predicted trade balance deflated by the value of exports, the magnitude of the error is similar across countries, ranging from 2 to 4 per cent, as is shown in Table 24. Further, an annual dollar trade balance error must be judged against the swings in trade balances that countries have experienced. For example, between 1974 and 1976 Japan experienced an increase in its trade balance of $8½ billion, while between 1974 and 1975 the United States, France, Italy, the Federal Republic of Germany, and the United Kingdom experienced swings of $14½ billion, $4½ billion, $4½ billion, $7½ billion, and $5 billion, respectively. Against this background, the dollar trade balance errors start to look more moderate. Finally, in model applications it is anticipated that information provided by various experts will be incorporated. The dollar trade balance errors for nonmanufactures, which are given in Table 25 and are discussed in some detail later, are quite large for a number of countries, especially the United States. When use is made of outside information on commodity developments, these errors should be reduced substantially. Thus, while the dollar trade balance errors for all goods taken together appear large in absolute terms, when account is taken of the size of trade flows, the volatility of the observed trade balance, and the source of the errors, they would appear to be acceptable.

Table 25.

Fourteen Industrial Countries: Root-Mean-Square Error, Based on Annual Data for Trade Balances by Commodity Class, 1970–75

(In billions of U.S. dollars)

Table 25.

Fourteen Industrial Countries: Root-Mean-Square Error, Based on Annual Data for Trade Balances by Commodity Class, 1970–75

(In billions of U.S. dollars)

Country	Agricultural Goods	Raw Materials	Fuels	Manufactures	All Commodities
Austria	0.0	0.0	0.0	0.1	0.2
Belgium-Luxembourg	0.1	0.1	0.1	0.3	0.5
Canada	0.3	0.3	0.1	0.5	0.6
Denmark	0.1	0.1	0.0	0.2	0.2
France	0.8	0.2	0.1	0.6	1.3
Germany, Fed. Rep.	0.5	0.2	0.1	0.9	1.4
Italy	0.4	0.3	0.1	0.6	0.7
Japan	0.2	0.3	0.3	0.8	1.2
Netherlands	0.1	0.1	0.2	0.4	0.3
Norway	0.0	0.1	0.0	0.1	0.2
Sweden	0.0	0.1	0.1	0.3	0.2
Switzerland	0.0	0.0	0.0	0.3	0.3
United Kingdom	0.1	0.1	0.3	1.1	1.3
United States	0.7	0.5	1.1	2.0	3.5

Table 25.

Fourteen Industrial Countries: Root-Mean-Square Error, Based on Annual Data for Trade Balances by Commodity Class, 1970–75

(In billions of U.S. dollars)

Country	Agricultural Goods	Raw Materials	Fuels	Manufactures	All Commodities
Austria	0.0	0.0	0.0	0.1	0.2
Belgium-Luxembourg	0.1	0.1	0.1	0.3	0.5
Canada	0.3	0.3	0.1	0.5	0.6
Denmark	0.1	0.1	0.0	0.2	0.2
France	0.8	0.2	0.1	0.6	1.3
Germany, Fed. Rep.	0.5	0.2	0.1	0.9	1.4
Italy	0.4	0.3	0.1	0.6	0.7
Japan	0.2	0.3	0.3	0.8	1.2
Netherlands	0.1	0.1	0.2	0.4	0.3
Norway	0.0	0.1	0.0	0.1	0.2
Sweden	0.0	0.1	0.1	0.3	0.2
Switzerland	0.0	0.0	0.0	0.3	0.3
United Kingdom	0.1	0.1	0.3	1.1	1.3
United States	0.7	0.5	1.1	2.0	3.5

As a final set of performance measures, and to better document the major sources of error in the model, goodness-of-fit measures were calculated from the annual data for the trade balances by commodity class, by country. These results are presented in Table 25. Clearly, the balance on agricultural trade is a major source of error for a number of countries. For four countries (Canada, Denmark, France, and Italy), each with substantial agricultural exports, the error on agricultural balance is at least half the error on the aggregate trade balance. The absolute size of the error for the United States is also quite large. The errors in dollar terms for fuel balances tend to be smaller than for agricultural balances, with the noted exceptions of the United States, and, to a lesser extent, the United Kingdom and the Netherlands. As mentioned earlier, fuel prices are considered to be exogenous, so that the fuels balance error stems exclusively from errors in volume predictions and—for all countries except Canada, the United States, and the Netherlands—estimates of the volume of fuel imports; thus, the relatively good performance on fuels is perhaps not surprising. The errors on raw materials balances, as well as those on agricultural balances, tend to be relatively large for countries exporting substantial quantities of raw materials, namely, Canada and Sweden. Again, the absolute size of the error on the raw materials balance for the United States is large at $0.5 billion but is smaller than the errors on the other three balances.

Given the dollar value of trade in manufactures for the industrial countries, the errors on the balances do not appear excessively large; however, their relative size varies substantially from country to country. The errors on manufactures balances are quite small for the Federal Republic of Germany and Japan when one considers the value of these countries’ manufactured exports, and large for the United States and the United Kingdom. This may reflect in part the better overall performance of the model on the export side and the relatively small role played by manufactured imports in the Federal Republic of Germany and Japan.

Several general areas for further work suggest themselves. These include the consideration of alternative specifications and estimation techniques, as well as the development of supplementary relationships to facilitate a number of model applications. Further work would seem to be warranted on the volume block for manufactured goods and, in particular, the selection of the most appropriate explanatory price variable. The relative price measures used at present are based on unit value indices that have well-known drawbacks, especially for small open economies. In addition, the price elasticities, while generally significant, appear to be fairly low. It may well prove fruitful to experiment with competitiveness measures based on domestic prices, or even domestic costs. The realism of the equations explaining the volume of imports by region would be enhanced if the purchasing power variable covered foreign exchange earnings from all sources, instead of restricting them to export earnings.

As regards the price block, one area meriting attention would be that of recasting the export price equations for manufactures into a framework that would encompass both short-term and longer-term perspectives (e.g., by making domestic costs endogenous for the smaller countries and by bringing in supply considerations). Thus, while the present structure is reasonably satisfactory for short-term forecasting purposes, it is much less so over the longer term. To improve the explanation of the price movements for nonmanufactures, perhaps the most fruitful approach would be to try to increase the commodity coverage of the spot price data to make it more comparable with the coverage of the unit value series. Another possibility is to take account of the cross-country correlation of the residuals, which is often quite marked. It appears at this time less certain that such techniques would prove fruitful for the volume block, since the cross-country correlation of error terms is less apparent.

The model presented here focuses exclusively on a country’s external sector, with domestic demand, prices, and costs being taken as exogenous. For forecasting purposes, it may be useful to endogenize some of these variables by relating them to other domestic variables for which reliable forecasts can be obtained (various components of gross national product). Further, as discussed earlier, the model focuses on customs data, whereas what is of ultimate interest is balance of payments data; thus, a technique is needed to convert the model results to a balance of payments basis.

Finally, while the trade balance of countries is of substantial interest in itself, the current account balance is perhaps of even greater interest. A model relating to invisible flows for the industrial countries is under preparation and, when completed, will be integrated with the merchandise trade model presented here.

APPENDIX: Documented List of Dummy Variables

^¹DYR12—for example, D196612—indicates a dummy that takes the value 1 for the first half year and – 1 for the second half year. DYR(1)YR(2)—for example, D196869—indicates a dummy that takes the value 1 for the second half year (1)—for example, 1968:2—and –1 for the first half year (2)—for example, 1969:1. DYRPR—for example, D197601—indicates a dummy that takes the value 1 for the year and period indicated—for example, 1976:1. CDYRPR—for example, CD196801—is a shift dummy taking the value 1 from the year and period indicated—for example, 1 from 1968:1 onward. When this notation cannot conveniently indicate the form taken by the dummy variable, it is given a simple name (e.g., PM 72 for policy measures initiated in 1972, or CROP 75 for good crops in 1975) and is described fully in the right-hand column, following the interpretation.

Dummy¹	Dependent Variable	Interpretation
austria
D196869	Imports of raw materials	Stocking in anticipation of border tax measures by the Federal Republic of Germany.
CD197101	Imports of fuels	Effect of termination of bilateral payments arrangements with members of the Council for Mutual Economic Assistance.
CD197102	Imports of raw materials
EEC 7273	Imports of manufactures	Stimulatory effects of trade liberalization between the European Economic Community (EEC) and Austria. This dummy takes the value 0.5 for the second half of 1972, and 1 thereafter.
PM 72	Exports of manufactures	Distortion resulting from introduction of value-added tax. This dummy takes the value 2 for the second half of 1972 and –1 for both the first half and the second half of 1973.
CROP 75	Exports of agricultural goods	Effects of bumper crop. This dummy takes the value 1 for the second half of 1975 and the first half of 1976.
D197601	Exports of raw materials	Effect of good crop on raw material exports of agricultural origin.
D197601	Imports of manufactures	Effects of temporary tax measures.
belgium-luxembourg
D196612	Imports of manufactures	Effects of shipping strike in the United Kingdom.
CD197401	Imports of manufactures Exports of agricultural goods	Excessive fall in trade resulting from inclusion of some fuel price effects in deflator.
canada
Dl96902	Imports of fuels	Effects of dock strike in the United States.
CD197401	Exports of fuels	Effects of policies taken to reduce Canadian fuel exports.
denmark
CD197302	Exports of agricultural goods	Effects of entrance into the EEC.
CD197401	Imports of raw materials	Reduction in relative importance of imports from Sweden, owing to EEC membership.
D197601	Imports of raw materials	Effects of temporary tax measures.
D197601	Imports of manufactures	Effects of temporary tax measures.
france
CD196801	Imports of manufactures	Effects of EEC tariff liberalization.
D196801	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CD197201	Exports of raw materials	Effects of liberalization in certain types of commodity trade within the EEC.
federal republic of germany
D196502	Imports of agricultural goods	Poor harvest in 1965.
D196802	Exports of manufactures	Anticipation of imposition of border tax.
CD196901	Exports of agricultural goods	Effects of EEC agricultural arrangements.
PM 70	Exports of manufactures	Effects of imposition of border tax. This dummy takes the value 1 for 1970, and 0 elsewhere.
PM 73	Imports of manufactures	Reduction in imports in response to restrictive domestic policies. This dummy takes the value 1 for the second half of 1973 and the first half of 1974, and 0 elsewhere.
italy
PM 74	Imports of agricultural goods	Effects of import deposit requirement for consumer goods. This dummy takes the value 0.67 for the second half of 1974, 1 for the first half of 1975, and –0.5 for the second half of 1975; elsewhere, it is 0.
japan
PM 65	Imports of manufactures	Effects of restrictive domestic policies. This dummy takes the value 1 for 1965, and 0 elsewhere.
AUTO 68	Exports of manufactures	Effects of the rapid increase in automobile exports. This dummy is 0 until the second half of 1967, and then increases from 1 in the first half of 1968 to 7 in the first half of 1971, and remains at 7 thereafter.
D196901	Imports of raw materials	Effects of U.S. dock strike.
PM 72	Imports of manufactures	Effects of trade liberalization. This dummy is 0 through the first half of 1972, 1 in the second half of 1972, 2 in the first half of 1973, and 3 thereafter.
netherlands
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CROP 71	Imports of agricultural goods	Good crop in 1970 and 1971. This dummy takes the value 1 for the first half of 1971 through the first half of 1972, and is 0 elsewhere.
D197301	Imports of manufactures	Probable error in deflator, owing to wide exchange rate variations over period.
CD197401	Imports of manufactures	Effects of enlargement of EEC.
CD197401	Exports of fuels	Effects of policies taken to moderate natural gas exports.
norway
CD197301	Imports of manufactures Exports of manufactures	Effects of enlargement of the EEC.
CD197302	Exports of agricultural goods	Effects of enlargement of the EEC.
sweden
CD197302	Exports of agricultural goods	Effects of enlargement of the EEC.
D197601	Exports of raw materials	Effects of domestic antirecession measures relating to investment and stockpiling.
switzerland
DESTOCK 74	Exports of raw materials	Destocking of inventories. This dummy takes the value 0.5 for the second half of 1973 and 1 for the first half of 1974. Elsewhere, it is 0.
united kingdom
CD197301	Exports of manufactures	Effects of entry into the EEC.
EEC 73	Imports of manufactures	Effects of entry into the EEC. This dummy takes the value 1 in the first half of 1973, and 2 thereafter.
CD197302	Exports of agricultural goods	Effects of entry into the EEC.
united states
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
D196901	Imports of agricultural goods	Effect of dock strike.
AUTO 68	Imports of manufactures	Effect of rapid increase in Japanese car imports. For a description of this dummy, see AUTO 68 for Japanese manufactured exports.
PM 73	Imports of manufactures	Effects of voluntary Japanese export restrictions. This dummy takes the value 1 in the second half of 1973 and –1 in the second half of 1974. Elsewhere, it is 0.
D197302	Exports of agricultural goods	Effects of world food shortage.
CD197302	Exports of fuels	Policies taken to discourage fuel exports.

Dummy¹	Dependent Variable	Interpretation
austria
D196869	Imports of raw materials	Stocking in anticipation of border tax measures by the Federal Republic of Germany.
CD197101	Imports of fuels	Effect of termination of bilateral payments arrangements with members of the Council for Mutual Economic Assistance.
CD197102	Imports of raw materials
EEC 7273	Imports of manufactures	Stimulatory effects of trade liberalization between the European Economic Community (EEC) and Austria. This dummy takes the value 0.5 for the second half of 1972, and 1 thereafter.
PM 72	Exports of manufactures	Distortion resulting from introduction of value-added tax. This dummy takes the value 2 for the second half of 1972 and –1 for both the first half and the second half of 1973.
CROP 75	Exports of agricultural goods	Effects of bumper crop. This dummy takes the value 1 for the second half of 1975 and the first half of 1976.
D197601	Exports of raw materials	Effect of good crop on raw material exports of agricultural origin.
D197601	Imports of manufactures	Effects of temporary tax measures.
belgium-luxembourg
D196612	Imports of manufactures	Effects of shipping strike in the United Kingdom.
CD197401	Imports of manufactures Exports of agricultural goods	Excessive fall in trade resulting from inclusion of some fuel price effects in deflator.
canada
Dl96902	Imports of fuels	Effects of dock strike in the United States.
CD197401	Exports of fuels	Effects of policies taken to reduce Canadian fuel exports.
denmark
CD197302	Exports of agricultural goods	Effects of entrance into the EEC.
CD197401	Imports of raw materials	Reduction in relative importance of imports from Sweden, owing to EEC membership.
D197601	Imports of raw materials	Effects of temporary tax measures.
D197601	Imports of manufactures	Effects of temporary tax measures.
france
CD196801	Imports of manufactures	Effects of EEC tariff liberalization.
D196801	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CD197201	Exports of raw materials	Effects of liberalization in certain types of commodity trade within the EEC.
federal republic of germany
D196502	Imports of agricultural goods	Poor harvest in 1965.
D196802	Exports of manufactures	Anticipation of imposition of border tax.
CD196901	Exports of agricultural goods	Effects of EEC agricultural arrangements.
PM 70	Exports of manufactures	Effects of imposition of border tax. This dummy takes the value 1 for 1970, and 0 elsewhere.
PM 73	Imports of manufactures	Reduction in imports in response to restrictive domestic policies. This dummy takes the value 1 for the second half of 1973 and the first half of 1974, and 0 elsewhere.
italy
PM 74	Imports of agricultural goods	Effects of import deposit requirement for consumer goods. This dummy takes the value 0.67 for the second half of 1974, 1 for the first half of 1975, and –0.5 for the second half of 1975; elsewhere, it is 0.
japan
PM 65	Imports of manufactures	Effects of restrictive domestic policies. This dummy takes the value 1 for 1965, and 0 elsewhere.
AUTO 68	Exports of manufactures	Effects of the rapid increase in automobile exports. This dummy is 0 until the second half of 1967, and then increases from 1 in the first half of 1968 to 7 in the first half of 1971, and remains at 7 thereafter.
D196901	Imports of raw materials	Effects of U.S. dock strike.
PM 72	Imports of manufactures	Effects of trade liberalization. This dummy is 0 through the first half of 1972, 1 in the second half of 1972, 2 in the first half of 1973, and 3 thereafter.
netherlands
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CROP 71	Imports of agricultural goods	Good crop in 1970 and 1971. This dummy takes the value 1 for the first half of 1971 through the first half of 1972, and is 0 elsewhere.
D197301	Imports of manufactures	Probable error in deflator, owing to wide exchange rate variations over period.
CD197401	Imports of manufactures	Effects of enlargement of EEC.
CD197401	Exports of fuels	Effects of policies taken to moderate natural gas exports.
norway
CD197301	Imports of manufactures Exports of manufactures	Effects of enlargement of the EEC.
CD197302	Exports of agricultural goods	Effects of enlargement of the EEC.
sweden
CD197302	Exports of agricultural goods	Effects of enlargement of the EEC.
D197601	Exports of raw materials	Effects of domestic antirecession measures relating to investment and stockpiling.
switzerland
DESTOCK 74	Exports of raw materials	Destocking of inventories. This dummy takes the value 0.5 for the second half of 1973 and 1 for the first half of 1974. Elsewhere, it is 0.
united kingdom
CD197301	Exports of manufactures	Effects of entry into the EEC.
EEC 73	Imports of manufactures	Effects of entry into the EEC. This dummy takes the value 1 in the first half of 1973, and 2 thereafter.
CD197302	Exports of agricultural goods	Effects of entry into the EEC.
united states
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
D196901	Imports of agricultural goods	Effect of dock strike.
AUTO 68	Imports of manufactures	Effect of rapid increase in Japanese car imports. For a description of this dummy, see AUTO 68 for Japanese manufactured exports.
PM 73	Imports of manufactures	Effects of voluntary Japanese export restrictions. This dummy takes the value 1 in the second half of 1973 and –1 in the second half of 1974. Elsewhere, it is 0.
D197302	Exports of agricultural goods	Effects of world food shortage.
CD197302	Exports of fuels	Policies taken to discourage fuel exports.

SUMMARIES

Control Over International Reserves—andrew d. crockett (pages 1–24)

Concern continues to be expressed that there is no adequate mechanism for controlling the volume of world reserves. This paper considers whether the objective of controlling aggregate reserves is still appropriate under current international monetary arrangements and discusses some of the means that have been proposed to achieve such control.

Both the demand for and the supply of world reserves have changed as a result of the shift to flexible exchange rates and the growth of private capital markets as means of financing payments disequilibria. There has probably been a shift in the demand function for owned reserves, both because of exchange rate flexibility and greater access to other sources of balance of payments finance. There seems no reason to doubt, however, that reserve demand is still systematically related to such factors as prospective payments imbalances and the costs of holding reserves, although recent developments may have made the function less stable.

On the supply side, the old paradigm of an exogenously given supply of reserves is no longer applicable. Creditworthy countries can hold the volume of reserves that they desire, and individual countries can use international capital markets to increase their reserves without depriving other countries. Although the supply of reserves in this sense is no longer under effective control, the terms and conditions under which reserve borrowing takes place are influenced, directly or indirectly, by the actions of national monetary authorities in their respective money markets.

Mechanisms designed to achieve greater control over reserve growth would have to rely on direct constraints on individual countries. The desirability of imposing such constraints must be assessed in the light of how effective liquidity control can be in achieving the objective of more timely and effective adjustment. In this connection, the surveillance of exchange rate policies provided for in the International Monetary Fund’s Proposed Second Amendment to the Articles of Agreement may be a more effective weapon than direct control of liquidity.

Relative Price Effects on Export Performance: The Case of Nonelectrical Machinery—jacques r. artus and susana c. sosa (pages 25–47)

This paper explores the effects of changes in export price competitiveness at a disaggregated level. A case study is considered, namely, the effects of relative price changes among the three main exporters of nonelectrical machinery—the Federal Republic of Germany, the United States, and the United Kingdom—on their relative export performance. All direct and cross-price elasticities of demand in a number of foreign markets are estimated in a consistent fashion. These markets are the members of the OECD—which has been divided into two groups, the European Economic Community (EEC) and the rest of the OECD—and the developing countries.

The study has two major focuses: (1) It attempts to test the validity of the “elasticity pessimism” that has arisen following the apparent failure of the large exchange rate changes and relative price changes of the period 1969–73 to affect trade balances significantly. (2) It attempts to eliminate certain methodological flaws that reduce the usefulness of many existing empirical studies on foreign trade price elasticities. Concern with the methodological aspects has led to the present consideration of relative price effects in the world market for a specific group of products rather than to a broad study of countries’ total import and export flows.

The results support the view that changes in price competitiveness have had a significant effect on market shares in the world market for nonelectrical machinery. Price effects are, however, not extremely large, and are felt rather slowly. When the substitution elasticity is assumed to be the same between any pair of supplying countries, the estimated long-run (three-year) substitution elasticities are 1.75 (0.17) in the EEC market, 0.90 (0.17) in the market constituted by the rest of the OECD countries, and 1.69 (0.24) in the market made up of developing countries. The corresponding long-run export price elasticities are –0.66 (0.04) for the Federal Republic of Germany, –0.64 (0.04) for the United States, and –1.04 (0.07) for the United Kingdom. Short-run (one-year) export price elasticities are quite low: they range from –0.06 (0.04) for the United States to –0.09 (0.06) for the United Kingdom.

Some evidence suggests that the substitution elasticities between products of the United Kingdom and the Federal Republic of Germany, and between products of that country and the United States, may be lower than the elasticitiy between U. K. and U.S. products. When the assumption that the substitution elasticity is the same between all pairs of supplying countries is dropped, the long-run export price elasticity estimates are –0.50 (0.12) for the Federal Republic of Germany, –2.13 (0.39) for the United Kingdom, and –1.06 (0.20) for the United States. The relatively low price elasticity obtained for exports from the Federal Republic of Germany tends to substantiate the widespread belief that nonprice factors play an important role in determining demand for that country’s exports.

The Monetary Approach to the Exchange Rate: Some Empirical Evidence—john f. o. bilson (pages 48–75)

This paper examines the empirical validity of a simple monetary model of exchange rate determination. The model stresses that the exchange rate, which is the relative price of two monies, is determined by the relative supplies of, and demands for, the two monies, rather than by the condition for flow equilibrium in the balance of payments. It follows from this approach that the exchange rate is determined by the relative money supplies, the levels of real income, and the nominal interest rates in the two countries under consideration. The monetary model provides a useful tool for exchange rate analysis because it (a) clearly defines the role of speculation among the determinants of the exchange rate; (b) provides a workable definition of the equilibrium exchange rate; and (c) directly relates the equilibrium rate to the underlying instruments of monetary policy.

The model is tested using data on the deutsche mark/pound rate during the current floating rate period. This particular rate was chosen because of the large variance in the variable stressed by the monetary approach. The empirical tests broadly support this approach, although the need for a more complete empirical model is evident.

A Stylized Model of the Devaluation-Inflation Spiral—carlos a. rodriguez (pages 76–89)

A simple macroeconomic model is developed in order to analyze some of the dynamic elements of the devaluation-inflation spiral in the presence of a real government deficit financed through credit creation by the central bank. It is concluded that under those circumstances the objectives of price stability and external balance are inconsistent. Assuming that the government devalues whenever reserves reach a minimum acceptable level, the likely outcome of the process is a typical cycle during which the price level follows three distinct phases: (1) a jump at the moment of devaluation, (2) positive but decelerating inflation, and, finally (3) a stable price level (with falling reserves). It is shown that even though the need for exchange rate devaluation may come at a time of stable prices, both the exchange rate and the price level are endogenous variables with no direct causality relation between them over the whole of the typical cycle. Both exchange rate and price level movements are led by monetary developments, which are in turn determined entirely by the monetization of the fiscal deficit.

Short-Run Forecasting of Commodity Prices: An Application of Autoregressive Moving Average Models—ke-young chu (pages 90–111)

The paper reviews the relative merits of using final equations in autoregressive integrated moving average (ARIMA) forms for forecasting, compared with reduced forms. It also attempts to apply the method of ARIMA models to a short-run simulation of commodity prices.

Although both can be derived from a given economic model, a reduced form and a final (ARIMA) equation have different capabilities in forecasting, since they are derived from different sets of assumptions and require different information bases for forecasting. The foremost merit of final equations in forecasting economic time series is simplicity. An equation can be identified and estimated on the basis of a single time series and used for forecasting the time series. However, it is difficult to perform a policy analysis and to utilize information on the future realizations of exogenous variables and structural errors with final equations.

The paper summarizes the results of estimation and simulation for the monthly prices of ten primary commodities, uses the forecasts of the monthly prices to generate the forecasts of annual prices, and compares them with the actual prices and—for the annual prices—with the forecasts generated by annual models. The results show that the ARIMA scheme is quite useful for some commodities and suggests that it is better than alternative simple methods, such as the random walk model, for most of the commodities.

The World Trade Model: Merchandise Trade—michael c. deppler and duncan m. ripley (pages 147–206)

This paper presents a simple semiannual model of world merchandise trade disaggregated by commodity class and by country or country grouping. It is designed principally to estimate the responsiveness of merchandise trade to variations in income and activity levels in the industrial countries. The responsiveness of trade flows to variations in prices is also considered, but the empirical results on price sensitivity appear to be less reliable. The trade flows are disaggregated into four commodity classes—foods, raw materials, fuels, and manufactures—and 18 geographic areas—the 14 industrial countries treated individually and 4 country groups (developed primary producing countries, major oil exporting countries, other developing countries, and the rest of the world—consisting essentially of the centrally planned economies).

The model can be thought of as having three principal blocks. The first block determines, for each commodity class, export and import unit values for the industrial countries, given certain spot commodity prices, domestic costs and prices, and exchange rates; the second determines the volume of exports and imports by commodity class for the industrial countries, given prices and the level of final domestic demand. The third block relates export receipts of the country groups to activity levels in the industrial countries, and import expenditure to their foreign exchange earnings. These relationships are estimated on a semiannual basis; the estimation period generally covers the first half of 1964 to the first half of 1976.

It is expected that the model will be used for both simulation and forecasting. Its usefulness in terms of simulation is expected to lie in the calculation of countries’ trade balances under alternative assumptions about economic activity levels in the industrial countries. The model is also expected to be useful in projecting countries’ trade balances for 6 to 18 months ahead, thus providing an input to the semiannual forecasting exercises of the International Monetary Fund.

RESUMES

RESUMENES

Publications of the International Monetary Fund

BOOKS

Balance of Payments Manual, 4th edition, 1977. US$4.00.

The Monetary Approach to the Balance of Payments: A Collection of Research Papers by Members of the Staff of the International Monetary Fund. 1977. US$4.00.

The International Monetary Fund, 1966–1971: The System Under Stress. (2 vols.). Margaret Garritsen de Vries. 1976. US$15.00 the set (Vol. I, US$11.00, Vol. II, US$6.00).

The International Monetary Fund, 1945–1965: Twenty Years of International Monetary Cooperation. (3 vols.). J. Keith Horsefield and others. 1969. US$12.50 the set (US$5.00 a volume).

Membership and Nonmembership in the International Monetary Fund: A Study in International Law and Organization. Joseph Gold. 1974. US$10.00.

Instruments of Monetary Policy in the United States: The Role of the Federal Reserve System. Ralph A. Young. 1973. US$1.25.

The Stand-By Arrangements of the International Monetary Fund: A Commentary on Their Formal, Legal, and Financial Aspects. Joseph Gold. 1970. US$4.00.

International Reserves: Needs and Availability. Proceedings, IMF Seminar. 1970. US$6.00.

Surveys of African Economies

Vol. 5. Botswana, Lesotho, Swaziland, Burundi, Equatorial Guinea, and Rwanda. 1973.
Vol. 6. The Gambia, Ghana, Liberia, Nigeria, and Sierra Leone. 1975.
Vol. 7. Algeria, Mali, Morocco, and Tunisia. 1977.

Also published in French. US$5.00 a volume (US$2.50 to university libraries, faculty members, and students).

Central Banking Legislation: A Collection of Central Bank, Monetary and Banking Laws. Vol. II. 1967. US$10.00.

PERIODICALS

Balance of Payments Yearbook. Annual, 11 monthly booklets, and supplement. US$20.00 (US$8.00 to university libraries, faculty members, and students).

Direction of Trade. Monthly, with annual supplement. US$16.00 a year (US$6.00 to university libraries, faculty members, and students).

International Financial Statistics. Monthly, in English, French, or Spanish. US$35.00 a year (US$14.00 to university libraries, faculty members, and students). Delivery by airspeed outside United States, US$30.00 additional. Specify language desired.

Staff Papers. Four times a year. US$7.00 a volume (US$2.50 a single issue). US$3.00 a volume to university libraries, faculty members, and students (US$1.00 a single issue).

Combined subscription rate for preceding four periodicals, US$26.00.

Government Finance Statistics Yearbook. Vol. I. 1977. US$10.00 a volume. (US$4.00 to university libraries, faculty members, and students).

IMF Survey. 23 issues a year, in English, French, or Spanish. US$10.00 a year. Specify language desired.

Finance and Development (jointly with World Bank). Quarterly in English, French, Spanish, or German. Available on application. Specify language desired.

TAPE SUBSCRIPTIONS

Series from International Financial Statistics, from Direction of Trade, from Balance of Payments Yearbook, and from Government Finance Statistics Yearbook are available on tape for computer users. Price for each title, US$1,000 a year (US$400 to universities) to single users and US$5,000 a year to time sharers. A tape subscription includes a subscription to the book version.

Address inquiries to

The Secretary

International Monetary Fund, Washington, D.C. 20431 U.S.A.

Mr. Deppler, Senior Economist in the Current Studies Division of the Research Department, is a graduate of Brown and Georgetown Universities.

Ms. Ripley, Assistant Chief of the External Adjustment Division of the Research Department, is a graduate of Wellesley College and Harvard University.

For a description of Project LINK, see The International Linkage of National Economic Models, ed. by Robert J. Ball (Amsterdam, 1973).

For example, some of the LINK models are quarterly and others annual, so that the time perspective is not necessarily consistent across models; further, some models now have a four-commodity breakdown for trade, whereas others still work with aggregate exports and imports. Finally, it has been difficult to obtain recent updates for a number of national models.

See Lee Samuelson, “A New Model of World Trade,” OECD Economic Outlook: Occasional Studies(Paris, December 1973).

See, for example, Michael Bruno, “Price and Output Adjustment: Micro Foundations and Macro Theory,” Harvard Institute of Economic Research, Discussion Paper No. 534 (mimeographed, February 1977); Michael C. Deppler, “Product Differentiation and the Modeling of International Trade Flows” (unpublished doctoral dissertation, Georgetown University, February 1976).

The potential output per man-hour series are based on Jacques R. Artus, “Measures of Potential Output in Manufacturing for Eight Industrial Countries, 1955–78,” Staff Papers, Vol. 24 (March 1977), pp. 1–35.

Experimentation with several types of excess demand variables was largely unproductive, partly because of collinearity problems.

Because of lack of data, the nonindustrial countries are not included in the average.

Equations that did not impose any restriction on the length of the recording lag (except that it be no greater than six months) proved to be inferior to those reported here for all but two countries, Belgium-Luxembourg and the United Kingdom.

Fuel prices are exogenous to the model.

The 35 commodity prices refer to four kinds of coffee (Colombia milds, other milds, unwashed arabica, and robusta), three sugar price quotations (prices in the United States, the European Economic Community (EEC), and the world market), cocoa, tea, bananas, lamb, beef, rice, wheat, maize, soybeans, groundnut oil, copra, palm oil, soybean meal, groundnut cake, fish meal, cotton (long and medium), wool (fine and coarse), jute, sisal, hides, rubber, copper, tin, aluminum, zinc, lead, nickel, and iron ore. These quotations appear in the Commodity Prices table in the International Monetary Fund’s International Financial Statistics.

This specification is especially useful in that it limits the number of exogenous variables that must be taken into account.

Initially, the export and import unit value equations related the unit values only to the spot commodity price data. The specification described in the text takes into account value added in the industrial countries through the inclusion of a variable representing wage developments in the determination of export prices, and the inclusion of partner-country export prices in the import equation. The inclusion of these variables substantially improved the statistical results and reduced the importance of the autoregressive correction.

The approach used in this paper is similar to that suggested by Paul S. Armington, “A Theory of Demand for Products Distinguished by Place of Production,” Staff Papers, Vol. 16 (March 1969), pp. 159–76. Strictly speaking, this two-stage procedure is valid for groups of commodities such that the marginal rates of substitution between any two goods within the “group” is not affected by the quantity consumed of any goods outside the group under consideration.

A single relative price term can be justified if the elasticity of substitution between imports from any two sources for a given country is independent of the sources, and if the unit value index approximates a trade-weighted price index.

Let M_j be the level of imports in market j, and w_ij the share of country i in the imports of country j. Then, ignoring asymmetries, X_ij = w_ij · M_j, where X_ij are the exports of country i to market j.

This is the approach followed in the OECD trade model and is one of the alternative specifications used in Project LINK to derive exports from imports. A first-order approximation to this expression may be formulated.

$X V M \underset{i j}{t} = w_{i j}^{o} . M V M \overset{t}{j} - δ_{j} . w_{i j}^{o} . M V M \overset{t}{j} (\frac{Δ P_{i}}{P_{i}} - \underset{k}{Σ} w_{i j}^{o} \frac{Δ P_{k}}{P_{k}})$

where $w_{i j}^{o}$ is the share of country j’ s imports originating in country i in the base period.

In this specification it would also have been useful to distinguish between the impact of short-term fluctuations in foreign demand and the impact of longer-term developments. Because of a high degree of collinearity between the exogenous variables, however, no attempt was made to include a “longer-term” demand variable.

One might hypothesize that imports of raw materials, MVR, would be determined by the current and lagged level of output, QM_t, and QM_t-1, and the rate of change of output that affects manufacturers’ views as to whether to increase or decrease stockpiles. Thus,

M V R = α_{0} . {(Q M)}^{α_{1}} . {(Q M_{t - 1})}^{α_{2}} . {(Q M_{t} / Q M_{t - 1})}^{α_{3}} (1)

where α₁, α₂, α₃ > 0

When an equation of the following form

\begin{matrix} M V R = β_{0} . {(Q M_{t})}^{β_{1}} . {(Q M_{t - 1})}^{β_{2}} & (2) \end{matrix}

is estimated, however, the coefficient on the lagged level of output can be either positive or negative, since β₂ = α₂ – α₃.

A lagged value of the ratio of the gross national product (GNP) deflator to the import unit value for raw materials was introduced in the equations, but was significant for only 2 of the 14 countries—the Netherlands and Switzerland—and was excluded from the final specification

This specification represents a simplification of the specification based on a foreign exchange constraint used by William L. Hemphill, “The Effect of Foreign Exchange Receipts on Imports of Less Developed Countries,” Staff Papers, Vol. 21 (November 1974), pp. 637–77.

For the centrally planned economies, aggregate export and import unit values were derived by combining commodity unit value data to reflect the overall commodity composition of the trade of these countries.

The dummy variable for Japan used in Table 5 may be a proxy for a cyclical variable. Cyclical variables tended to be significant when this dummy was excluded, but insignificant if either the dummy was included or the observation period was shortened to exclude the period covered by the dummy.

Fuel prices are exogenous to the model.

For these countries, the cumulative elasticities for both export and import volume equations exceed unity in absolute value, so that, other things being equal, the value of exports would tend to increase and the value of imports decrease with a change in relative prices.

The coefficients on the explanatory variables other than the trend term and constant and the standard errors of estimate were largely unaffected when the constraint on the output coefficient was varied.

It is difficult to compare these results with those reported for other models because of differences in specification, estimation periods, and the introduction of contraints for the foreign market variable. Very approximate comparisons with the results reported for the models of Project LINK, however, suggest that the order of magnitude of the coefficients reported here are not unreasonable. The LINK models suggest a very high demand elasticity for Japan (3.0 for exports to the United States and 1.8 for other exports), a “foreign market” coefficient of 1.3 for the Federal Republic of Germany, of 0.8 for the Netherlands, and 0.5 for the United Kingdom. See Ball (cited in footnote 1).

Assume that the long-term development of demand for exports can be represented by an exponential time trend. Thus, LDEMT = α₁ + α₂ · TD where LDEMT is the longer-term demand variable, in logs, TD is a time trend, and LDEM is the observed value of demand in logs. Then

LXVM = β₁ + β₂ · (LDEM – LDEMT) + β₃ · (LDEMT) + β₄ · Z

Where β₂ represents the responsiveness of exports to short-term fluctuations in demand about its longer-term value; β₃ represents the longer-run elasticity; and Z represents other exogenous variables. If the equation is estimated as

LXVM = γ₁ + γ₂ · TD + γ₃ · LDEM + γ₄ · Z

it follows that

γ₂ = (β₃ – β₂) · α₂

Of course, the time-trend coefficient may also reflect the effects of long-term trends in other variables not included in the export equation. To the extent that this is true, the interpretation of a negative time trend as indicating a higher short-term than longer-term demand elasticity would not necessarily hold.

The figures here are based on the sum of the coefficients for the two output variables. France, Japan, and Switzerland were not included in this group, since the sum of their coefficients was so close to unity.

This is suggested by the negative coefficients on the lagged output variable.

Unit values for raw materials alone were not available for a number of countries. Proxy deflators consisting of weighted average unit value indices for partner countries were used. This procedure may have resulted in spurious movement of the volume series.

Lagged values of real consumer expenditure were introduced but were not found to be significant.

Clearly, domestic fuel production is becoming important for the United Kingdom and Norway. Thus, import equations based on historical data are of somewhat doubtful value for future projections, and export equations will be needed. It will not be possible to empirically estimate the effects of these supplies by normal econometric techniques for some time.

These variables are represented in Table 18 as dummies I and II, respectively.

Weights for 1970 were used in the construction of this variable. The index of domestic gas production was included in one specification of the equation, but its coefficient was both insignificant and had the wrong sign.

If the relationships were expressed as

X V T = α_{1} \cdot Q M I N D^{α_{2}} \cdot {(\frac{Q M I N D}{Q M I N D_{- 1}})}^{α_{3}}

then α₂ and α₃ for the other developed countries, centrally planned economies, and less developed countries would be (0.16, 0.80), (0.06, 0.75), and (0.52, 0.60), respectively.

The price equations for manufactures are specified in terms of first differences of the logarithms of the indices; to obtain the indices required for the conversion of volume series to values, the estimated price changes were applied to the observed unit value series, lagged one period. The predicted price for fuels was set equal to the observed price in these calculations, since fuel prices are taken as exogenous.

Flows that were treated as exogenous, for example, pearls and precious stones, and, for a number of countries, exports of fuels, were added in again to obtain the totals used in these calculations, since the resulting aggregate figures for volumes and unit values will more closely approximate the aggregate figures used in the work of the Fund, and the difference between the value of exports and imports will more closely approximate countries’ trade balances.

In many cases, the estimation period was the first half of 1964 through the first half of 1976, but a few equations were estimated on data starting with the first half of 1970. Because of these equations and because of particular concern with the performance of the model over the recent past, the measures of goodness of fit relate to the model’s explanatory power between the first half of 1970 and the first half of 1976.

In fact, the performance of the model generally tends to improve with aggregation, be it across commodity class, across countries, or across time periods.

For these 9 countries, the mean-square error on an annual basis is less than twice the mean-square error on a semiannual basis.

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IMF Staff papers: Volume 25 No. 1

Author:

International Monetary Fund. Research Dept.

Volume/Issue:: Volume 1978: Issue 001

Publisher:: International Monetary Fund

ISBN:: 9781451956498

ISSN:: 1020-7635

Pages:: 234

DOI:: https://doi.org/10.5089/9781451956498.024

Keywords
I. General Model Structure
II. Model Parameters
III. Conclusion
- APPENDIX: Documented List of Dummy Variables
SUMMARIES
RESUMES
RESUMENES
Publications of the International Monetary Fund

Dummy¹	Dependent Variable	Interpretation
austria
D196869	Imports of raw materials	Stocking in anticipation of border tax measures by the Federal Republic of Germany.
CD197101	Imports of fuels	Effect of termination of bilateral payments arrangements with members of the Council for Mutual Economic Assistance.
CD197102	Imports of raw materials
EEC 7273	Imports of manufactures	Stimulatory effects of trade liberalization between the European Economic Community (EEC) and Austria. This dummy takes the value 0.5 for the second half of 1972, and 1 thereafter.
PM 72	Exports of manufactures	Distortion resulting from introduction of value-added tax. This dummy takes the value 2 for the second half of 1972 and –1 for both the first half and the second half of 1973.
CROP 75	Exports of agricultural goods	Effects of bumper crop. This dummy takes the value 1 for the second half of 1975 and the first half of 1976.
D197601	Exports of raw materials	Effect of good crop on raw material exports of agricultural origin.
D197601	Imports of manufactures	Effects of temporary tax measures.
belgium-luxembourg
D196612	Imports of manufactures	Effects of shipping strike in the United Kingdom.
CD197401	Imports of manufactures Exports of agricultural goods	Excessive fall in trade resulting from inclusion of some fuel price effects in deflator.
canada
Dl96902	Imports of fuels	Effects of dock strike in the United States.
CD197401	Exports of fuels	Effects of policies taken to reduce Canadian fuel exports.
denmark
CD197302	Exports of agricultural goods	Effects of entrance into the EEC.
CD197401	Imports of raw materials	Reduction in relative importance of imports from Sweden, owing to EEC membership.
D197601	Imports of raw materials	Effects of temporary tax measures.
D197601	Imports of manufactures	Effects of temporary tax measures.
france
CD196801	Imports of manufactures	Effects of EEC tariff liberalization.
D196801	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CD197201	Exports of raw materials	Effects of liberalization in certain types of commodity trade within the EEC.
federal republic of germany
D196502	Imports of agricultural goods	Poor harvest in 1965.
D196802	Exports of manufactures	Anticipation of imposition of border tax.
CD196901	Exports of agricultural goods	Effects of EEC agricultural arrangements.
PM 70	Exports of manufactures	Effects of imposition of border tax. This dummy takes the value 1 for 1970, and 0 elsewhere.
PM 73	Imports of manufactures	Reduction in imports in response to restrictive domestic policies. This dummy takes the value 1 for the second half of 1973 and the first half of 1974, and 0 elsewhere.
italy
PM 74	Imports of agricultural goods	Effects of import deposit requirement for consumer goods. This dummy takes the value 0.67 for the second half of 1974, 1 for the first half of 1975, and –0.5 for the second half of 1975; elsewhere, it is 0.
japan
PM 65	Imports of manufactures	Effects of restrictive domestic policies. This dummy takes the value 1 for 1965, and 0 elsewhere.
AUTO 68	Exports of manufactures	Effects of the rapid increase in automobile exports. This dummy is 0 until the second half of 1967, and then increases from 1 in the first half of 1968 to 7 in the first half of 1971, and remains at 7 thereafter.
D196901	Imports of raw materials	Effects of U.S. dock strike.
PM 72	Imports of manufactures	Effects of trade liberalization. This dummy is 0 through the first half of 1972, 1 in the second half of 1972, 2 in the first half of 1973, and 3 thereafter.
netherlands
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
CROP 71	Imports of agricultural goods	Good crop in 1970 and 1971. This dummy takes the value 1 for the first half of 1971 through the first half of 1972, and is 0 elsewhere.
D197301	Imports of manufactures	Probable error in deflator, owing to wide exchange rate variations over period.
CD197401	Imports of manufactures	Effects of enlargement of EEC.
CD197401	Exports of fuels	Effects of policies taken to moderate natural gas exports.
norway
CD197301	Imports of manufactures Exports of manufactures	Effects of enlargement of the EEC.
CD197302	Exports of agricultural goods	Effects of enlargement of the EEC.
sweden
CD197302	Exports of agricultural goods	Effects of enlargement of the EEC.
D197601	Exports of raw materials	Effects of domestic antirecession measures relating to investment and stockpiling.
switzerland
DESTOCK 74	Exports of raw materials	Destocking of inventories. This dummy takes the value 0.5 for the second half of 1973 and 1 for the first half of 1974. Elsewhere, it is 0.
united kingdom
CD197301	Exports of manufactures	Effects of entry into the EEC.
EEC 73	Imports of manufactures	Effects of entry into the EEC. This dummy takes the value 1 in the first half of 1973, and 2 thereafter.
CD197302	Exports of agricultural goods	Effects of entry into the EEC.
united states
CD196802	Exports of agricultural goods	Effects of EEC agricultural arrangements.
D196901	Imports of agricultural goods	Effect of dock strike.
AUTO 68	Imports of manufactures	Effect of rapid increase in Japanese car imports. For a description of this dummy, see AUTO 68 for Japanese manufactured exports.
PM 73	Imports of manufactures	Effects of voluntary Japanese export restrictions. This dummy takes the value 1 in the second half of 1973 and –1 in the second half of 1974. Elsewhere, it is 0.
D197302	Exports of agricultural goods	Effects of world food shortage.
CD197302	Exports of fuels	Policies taken to discourage fuel exports.

Export and Import Unit Values for Manufactures
$\begin{array}{l} (1) & Δ L N (X P M_{i}) = a_{0} + a_{1} Δ L N (P R M_{i}) + a_{2} Δ L N (N U L C_{i}) + a_{3} Δ L N (C Y C L O M H_{i}) \\ + a_{4} Δ L N (P F X_{i} *_{L C D_{i}}) \end{array}$
$\begin{matrix} (2) & Δ L N (M P M_{i}) = \end{matrix} b_{0} + b_{1} Δ L N (P F M D_{i} *_{L C D_{i}})$
Export and Import Unit Values for Foods and Raw Materials
$\begin{matrix} (3) & L N (X P R_{i}) = c_{0} + c_{1} L N (P R W D X_{i} *_{L C D_{i}}) + c_{2} \end{matrix} L N (W M_{i})$
$\begin{matrix} (4) & L N (X P A_{i}) = d_{0} + d_{1} L N (P A W D X_{i} \end{matrix} *_{L C D_{i}}) + d_{2} L N (W M_{i})$
$\begin{matrix} (5) & L N (M P R_{i}) \end{matrix} = e_{0} + e_{1} L N (P R W D M_{i} _{L C D_{i}}) + e_{2} L N (P F R D_{i} _{L C D_{i}})$
$\begin{matrix} (6) & L N (M P A_{i}) = f_{o} + f_{1} \end{matrix} L N (P A W D M_{i} _{L C D_{i}}) + f_{2} L N (P F A D_{i} _{L C D_{i}})$
Description of Variables
CYCLOMH_i	Ratio of actual to normal output per man-hour, OMH_i/NOMH_i
LCD _i	Exchange rate variable for country i, calculated as the number of currency units of country i per U.S. dollar, expressed in index form, 1970 = 100.
MPA_i	Index of import unit values of agricultural goods in country i, expressed in the currency of country i, 1970 = 100.
MPM_i	Index of import unit values of manufactures in country i, expressed in the currency of country i, 1970 = 100.
MPR_i	Index of import unit values of raw materials in country i, expressed in the currency of country i, 1970 = 100.
NOMH_i	“Normal” output per man-hour in manufacturing, in country i.
NULC_i	Normal unit labor costs in manufacturing, WM_i/NOMH_i, in country i, expressed in the currency of country i, 1970 = 100.
OMH_i	Output per man-hour in manufacturing, in country i.
PAWDM_i	Index of world spot prices of agricultural goods in U.S. dollars, with weights for the 15 individual agricultural commodities reflecting the relative importance of the commodities in country i’s imports in 1970.
PAWDX_i	Index of world spot prices of agricultural goods in U.S. dollars, with weights for the 15 individual agricultural commodities reflecting the relative importance of the commodities in country i’s exports in 1970.
PFAD_i	Average of partner-country export unit value indices in U.S. dollars for agricultural goods. $L N (P F A D_{i}) = \underset{j}{Σ} {s a m}_{j i} *_{L N (X P A_{j} / L C D_{j})}$
PFMD_i	Average of partner-country export unit value indices in U.S. dollars for manufactures. $L N (P F R D_{i}) = \overset{Σ}{j} s r m_{j i} *_{L N} (X P R_{j} / L C D_{j})$
PFX_i	Double-weighted index reflecting an average of competitors’ prices in U.S. dollars for manufactures. Thus, $L N (P F X_{i}) = \underset{j}{Σ} s m x_{i j} * \underset{l \neq i}{Σ} ((s m m_{i j} / 1 - s m m_{i j})) *_{L N} (X P M_{l} / L C D_{l}))$
PRM_i	Index of domestic costs of raw materials in country i, in the currency of country i, 1970 = 100.
PRWDM_i	Index of world spot prices of raw materials in U.S. dollars, with the weights for the 20 individual goods reflecting the relative importance of the goods in country i’s imports in 1970.
PRWDX_i	Index of world spot prices of raw materials in U.S. dollars, with the weights for the 20 individual goods reflecting the relative importance of the goods in country i’s exports in 1970.
skm_ij	Share of commodity k imports from industrial countries in market j originating in country i, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r(raw materials).
skx_ij	Share of commodity k exports of country i going to market j, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r(raw materials).
WM_i	Index of compensation per man-hour in manufacturing in country i, expressed in the currency of country i, 1970 = 100.
XPA_i	Index of export unit values of agricultural goods from country i, expressed in the currency of country i, 1970 = 100.
XPM_i	Index of export unit values of manufactured goods from country i, expressed in the currency of country i, 1970 = 100.
XPR_i	Index of export unit values of raw materials from country i expressed in the currency of country i, 1970 = 100.

Export and Import Unit Values for Manufactures
$\begin{array}{l} (1) & Δ L N (X P M_{i}) = a_{0} + a_{1} Δ L N (P R M_{i}) + a_{2} Δ L N (N U L C_{i}) + a_{3} Δ L N (C Y C L O M H_{i}) \\ + a_{4} Δ L N (P F X_{i} *_{L C D_{i}}) \end{array}$
$\begin{matrix} (2) & Δ L N (M P M_{i}) = \end{matrix} b_{0} + b_{1} Δ L N (P F M D_{i} *_{L C D_{i}})$
Export and Import Unit Values for Foods and Raw Materials
$\begin{matrix} (3) & L N (X P R_{i}) = c_{0} + c_{1} L N (P R W D X_{i} *_{L C D_{i}}) + c_{2} \end{matrix} L N (W M_{i})$
$\begin{matrix} (4) & L N (X P A_{i}) = d_{0} + d_{1} L N (P A W D X_{i} \end{matrix} *_{L C D_{i}}) + d_{2} L N (W M_{i})$
$\begin{matrix} (5) & L N (M P R_{i}) \end{matrix} = e_{0} + e_{1} L N (P R W D M_{i} _{L C D_{i}}) + e_{2} L N (P F R D_{i} _{L C D_{i}})$
$\begin{matrix} (6) & L N (M P A_{i}) = f_{o} + f_{1} \end{matrix} L N (P A W D M_{i} _{L C D_{i}}) + f_{2} L N (P F A D_{i} _{L C D_{i}})$
Description of Variables
CYCLOMH_i	Ratio of actual to normal output per man-hour, OMH_i/NOMH_i
LCD _i	Exchange rate variable for country i, calculated as the number of currency units of country i per U.S. dollar, expressed in index form, 1970 = 100.
MPA_i	Index of import unit values of agricultural goods in country i, expressed in the currency of country i, 1970 = 100.
MPM_i	Index of import unit values of manufactures in country i, expressed in the currency of country i, 1970 = 100.
MPR_i	Index of import unit values of raw materials in country i, expressed in the currency of country i, 1970 = 100.
NOMH_i	“Normal” output per man-hour in manufacturing, in country i.
NULC_i	Normal unit labor costs in manufacturing, WM_i/NOMH_i, in country i, expressed in the currency of country i, 1970 = 100.
OMH_i	Output per man-hour in manufacturing, in country i.
PAWDM_i	Index of world spot prices of agricultural goods in U.S. dollars, with weights for the 15 individual agricultural commodities reflecting the relative importance of the commodities in country i’s imports in 1970.
PAWDX_i	Index of world spot prices of agricultural goods in U.S. dollars, with weights for the 15 individual agricultural commodities reflecting the relative importance of the commodities in country i’s exports in 1970.
PFAD_i	Average of partner-country export unit value indices in U.S. dollars for agricultural goods. $L N (P F A D_{i}) = \underset{j}{Σ} {s a m}_{j i} *_{L N (X P A_{j} / L C D_{j})}$
PFMD_i	Average of partner-country export unit value indices in U.S. dollars for manufactures. $L N (P F R D_{i}) = \overset{Σ}{j} s r m_{j i} *_{L N} (X P R_{j} / L C D_{j})$
PFX_i	Double-weighted index reflecting an average of competitors’ prices in U.S. dollars for manufactures. Thus, $L N (P F X_{i}) = \underset{j}{Σ} s m x_{i j} * \underset{l \neq i}{Σ} ((s m m_{i j} / 1 - s m m_{i j})) *_{L N} (X P M_{l} / L C D_{l}))$
PRM_i	Index of domestic costs of raw materials in country i, in the currency of country i, 1970 = 100.
PRWDM_i	Index of world spot prices of raw materials in U.S. dollars, with the weights for the 20 individual goods reflecting the relative importance of the goods in country i’s imports in 1970.
PRWDX_i	Index of world spot prices of raw materials in U.S. dollars, with the weights for the 20 individual goods reflecting the relative importance of the goods in country i’s exports in 1970.
skm_ij	Share of commodity k imports from industrial countries in market j originating in country i, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r(raw materials).
skx_ij	Share of commodity k exports of country i going to market j, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r(raw materials).
WM_i	Index of compensation per man-hour in manufacturing in country i, expressed in the currency of country i, 1970 = 100.
XPA_i	Index of export unit values of agricultural goods from country i, expressed in the currency of country i, 1970 = 100.
XPM_i	Index of export unit values of manufactured goods from country i, expressed in the currency of country i, 1970 = 100.
XPR_i	Index of export unit values of raw materials from country i expressed in the currency of country i, 1970 = 100.

Manufactures
$\begin{matrix} (1) & L N (M V M_{i}) = a_{0} + a_{1} L N (A V G_{i} / Q M T_{i}) + a_{2} L N (Q M T_{i}) + a_{3} \end{matrix} L N (R M P M_{i})$
$\begin{array}{l} (2) & L N (X V M_{i}) = b_{0} + b_{1} L N (F M_{i}) + b_{2} L N (R Q M T_{i}) + b_{3} L N (R X P M_{i}) \end{array}$
Raw Materials, Fuels, and Agricultural Goods
$\begin{matrix} (3) & L N (M V R_{i}) = c_{0} + c_{1} \end{matrix} L N (Q M_{i})$
$\begin{array}{l} (4) & L N (M V F_{i}) = d_{0} + d_{1} + L N (Q M_{i}) \end{array}$
$\begin{matrix} (5) & L N (M V A_{i}) = e_{0} + e_{1} L N \end{matrix} (C C_{i}) + e_{2} L N (P Y_{i} / M P A_{i})$
$\begin{matrix} (6) & L N (X V R_{i}) \end{matrix} = f_{0} + f_{1} L N (F R_{i})$
$\begin{array}{l} (7) & L N (X V A_{i}) = g_{0} + g_{1} L N (F A_{i}) \end{array}$
Description of Variables
AVG_i	Average of output in manufacturing (QM_i) and real final domestic demand for manufactures (DVM_i), both in index form, 1970 = 100, with the weights reflecting the share of manufactured imports going to intermediate and final demand, respectively. $A V G_{i} = (1 - S H_{i}) _{Q M_{i}} + S H_{i} _{(D V M_{i})}$
CC_i	Index of real personal consumption expenditure in country i, 1970 = 100.
FA _i	Foreign market variable for agricultural goods, calculated as $F A_{i} = \underset{j}{Σ} s a m_{i j} M V A_{j} A_{j}$ where A_j reflects the share of country j’s imports of agricultural goods coming from the industrial countries.
FM_i	Foreign market variable for manufactures, calculated as $F M_{i} = \underset{j}{Σ} s m m_{i j^{}} M V M_{j^{}} M_{j}$ where M_j reflects the share of country j’s imports of manufactured goods coming from the industrial countries.
FR_i	Foreign market variable for raw materials, calculated as $F M_{i} = \underset{j}{Σ} s m m_{i j} * M V M_{j} * M_{j}$
	where R_j reflects the share in country j’s imports of raw materials coming from the industrial countries.
LCD_i	Exchange rate variable for country i, calculated as the number of currency units of country i per U.S. dollar, expressed in index form, 1970 = 100.
MPA_i	Index of import unit values of agricultural goods in country i, expressed in the currency of country i, 1970 = 100.
MPF_i	Index of import unit values of fuels in country i, expressed in the currency of country i, 1970 = 100.
MPM_i	Index of import unit values of manufactures in country i, expressed in the currency of country i, 1970 = 100.
MPR_i	Index of import unit values of raw materials in country i, expressed in the currency of country i, 1970 = 100.
MVA_i	Import volume of agricultural goods for country i.
MVF_i	Import volume of fuels for country i.
MVM_i	Import volume of manufactured goods for country i.
MVR_i	Import volume of raw materials for country i.
PMM_i	Index of unit values for imports of manufactures for country i, calculated as a weighted average of export unit values. $L N (P M M_{i}) = \underset{j}{Σ} s m m_{j i} \cdot L N (X P M_{j}^{*} L C D_{i} / L C D_{j})$
PY_i	Gross national product deflator for country i, expressed in the currency of country i, 1970 = 100.
QM_i	Index of value added in manufacturing in country i, 1970 = 100.
QMT_i	Index of potential output in manufacturing in country i.
RMPM_i	Index of domestic prices of manufactures (P_i) relative to import price of manufactures (MPM_i). This index is calculated as $R M P M_{i} = P_{i} / M P M_{i}$
RQMT_i	Index of growth in potential output in manufacturing in country i relative to competitors’ growth in potential output in manufacturing. $L N (R Q M T_{i}) = L N (Q M T_{i}) - \underset{j}{Σ} s m x_{i j} \cdot \underset{k}{Σ} s m m_{k j} \cdot L N (Q M T_{k})$
RXPM_i	Index of export unit values of manufactures in country i relative to competitors’ price index. $L N (R X P M_{i}) = L N (X P M_{i}) - \underset{j}{Σ} s m x_{i j} \cdot L N (P M M_{j} \cdot L C D_{i} / L C D_{j})$
skm_ij	Share of commodity k imports from industrial countries in market j originating in country i, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r (raw materials).
skx_ij	Share of commodity k exports from country i to market j, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r (raw materials).
XPM_i	Index of export unit values of manufactured goods from country i, expressed in the currency of country i, 1970 = 100.
XVA_i	Export volume of agricultural goods from country i.
XVM_i	Export volume of manufactures from country i.
XVR_i	Export volume of raw materials from country i.

Manufactures
$\begin{matrix} (1) & L N (M V M_{i}) = a_{0} + a_{1} L N (A V G_{i} / Q M T_{i}) + a_{2} L N (Q M T_{i}) + a_{3} \end{matrix} L N (R M P M_{i})$
$\begin{array}{l} (2) & L N (X V M_{i}) = b_{0} + b_{1} L N (F M_{i}) + b_{2} L N (R Q M T_{i}) + b_{3} L N (R X P M_{i}) \end{array}$
Raw Materials, Fuels, and Agricultural Goods
$\begin{matrix} (3) & L N (M V R_{i}) = c_{0} + c_{1} \end{matrix} L N (Q M_{i})$
$\begin{array}{l} (4) & L N (M V F_{i}) = d_{0} + d_{1} + L N (Q M_{i}) \end{array}$
$\begin{matrix} (5) & L N (M V A_{i}) = e_{0} + e_{1} L N \end{matrix} (C C_{i}) + e_{2} L N (P Y_{i} / M P A_{i})$
$\begin{matrix} (6) & L N (X V R_{i}) \end{matrix} = f_{0} + f_{1} L N (F R_{i})$
$\begin{array}{l} (7) & L N (X V A_{i}) = g_{0} + g_{1} L N (F A_{i}) \end{array}$
Description of Variables
AVG_i	Average of output in manufacturing (QM_i) and real final domestic demand for manufactures (DVM_i), both in index form, 1970 = 100, with the weights reflecting the share of manufactured imports going to intermediate and final demand, respectively. $A V G_{i} = (1 - S H_{i}) _{Q M_{i}} + S H_{i} _{(D V M_{i})}$
CC_i	Index of real personal consumption expenditure in country i, 1970 = 100.
FA _i	Foreign market variable for agricultural goods, calculated as $F A_{i} = \underset{j}{Σ} s a m_{i j} M V A_{j} A_{j}$ where A_j reflects the share of country j’s imports of agricultural goods coming from the industrial countries.
FM_i	Foreign market variable for manufactures, calculated as $F M_{i} = \underset{j}{Σ} s m m_{i j^{}} M V M_{j^{}} M_{j}$ where M_j reflects the share of country j’s imports of manufactured goods coming from the industrial countries.
FR_i	Foreign market variable for raw materials, calculated as $F M_{i} = \underset{j}{Σ} s m m_{i j} * M V M_{j} * M_{j}$
	where R_j reflects the share in country j’s imports of raw materials coming from the industrial countries.
LCD_i	Exchange rate variable for country i, calculated as the number of currency units of country i per U.S. dollar, expressed in index form, 1970 = 100.
MPA_i	Index of import unit values of agricultural goods in country i, expressed in the currency of country i, 1970 = 100.
MPF_i	Index of import unit values of fuels in country i, expressed in the currency of country i, 1970 = 100.
MPM_i	Index of import unit values of manufactures in country i, expressed in the currency of country i, 1970 = 100.
MPR_i	Index of import unit values of raw materials in country i, expressed in the currency of country i, 1970 = 100.
MVA_i	Import volume of agricultural goods for country i.
MVF_i	Import volume of fuels for country i.
MVM_i	Import volume of manufactured goods for country i.
MVR_i	Import volume of raw materials for country i.
PMM_i	Index of unit values for imports of manufactures for country i, calculated as a weighted average of export unit values. $L N (P M M_{i}) = \underset{j}{Σ} s m m_{j i} \cdot L N (X P M_{j}^{*} L C D_{i} / L C D_{j})$
PY_i	Gross national product deflator for country i, expressed in the currency of country i, 1970 = 100.
QM_i	Index of value added in manufacturing in country i, 1970 = 100.
QMT_i	Index of potential output in manufacturing in country i.
RMPM_i	Index of domestic prices of manufactures (P_i) relative to import price of manufactures (MPM_i). This index is calculated as $R M P M_{i} = P_{i} / M P M_{i}$
RQMT_i	Index of growth in potential output in manufacturing in country i relative to competitors’ growth in potential output in manufacturing. $L N (R Q M T_{i}) = L N (Q M T_{i}) - \underset{j}{Σ} s m x_{i j} \cdot \underset{k}{Σ} s m m_{k j} \cdot L N (Q M T_{k})$
RXPM_i	Index of export unit values of manufactures in country i relative to competitors’ price index. $L N (R X P M_{i}) = L N (X P M_{i}) - \underset{j}{Σ} s m x_{i j} \cdot L N (P M M_{j} \cdot L C D_{i} / L C D_{j})$
skm_ij	Share of commodity k imports from industrial countries in market j originating in country i, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r (raw materials).
skx_ij	Share of commodity k exports from country i to market j, in value terms, in 1970, where k = a (agriculture), m (manufactures), and r (raw materials).
XPM_i	Index of export unit values of manufactured goods from country i, expressed in the currency of country i, 1970 = 100.
XVA_i	Export volume of agricultural goods from country i.
XVM_i	Export volume of manufactures from country i.
XVR_i	Export volume of raw materials from country i.

Volume Relationships
$\begin{matrix} (1) & L N (M V T_{j}) = a_{0} + a_{1} L N (X P P_{j}) \end{matrix}$
$\begin{matrix} (2) & L N (X V T_{j}) = b_{0} + b_{1} L N (Q M I N D_{j}) \end{matrix}$
Price Relationships
$\begin{matrix} (3) & L N \end{matrix} (X P T D_{j}) = c_{0} + c_{1} L N (P P W D) + c_{2} L N (P F W D) + c_{3} L N (P M M W D)$
$\begin{matrix} (4) & = d_{0} + d_{1} L N (P A W D) + d_{2} L N (P F W D) + d_{3} L N (P R W D) \\ + d_{4} L N (M P M D_{j}) \end{matrix}$
Description of Variables
LCD_j	Exchange rate variable for country j, calculated as the number of currency units of country j per U.S. dollar, expressed in index form, 1970 = 100.
MPTD_j	Index of import prices (total) of region j in U.S. dollars, 1970 = 100.
MPMD_j	$\underset{i}{Σ} s m m_{i j} L N (X P M_{i} / L C D_{i})$
MVT_j	Total import volume for region j.
PAWD	Index of agricultural export unit value indices for the industrial countries in U.S. dollars, 1970 = 100.
PFWD	Index of fuel unit value indices for the industrial countries in U.S. dollars, 1970 = 100.
PMWD	Index of industrial country export unit value indices for manufactures in U.S. dollars, 1970 = 100.
PRWD	Index of raw material export unit value indices for the industrial countries in U.S. dollars, 1970 = 100.
PPWDX_j	Index of world spot prices for food and raw materials, weighted on the basis of the 1968–70 commodity structure of region j’s exports in U.S. dollars, 1970 = 100.
QMIND_j	Index of output in manufacturing in industrial countries, where weights reflect the relative importance of industrial countries as export markets for region j in 1970.
smm_ij	Share of manufactured imports from industrial countries in area j originating in country i, in value terms in 1970.
XPM_i	Index of export prices of manufactured goods from country i, expressed in the currency of country i, 1970 = 100.
XPP_j	Purchasing power of region j’s exports in terms of its imports. Thus, $X P P_{j} = X V T_{j} * X P T D_{j} / M P T D_{j}$
XPTD_j	Index of export prices (total) of region j, expressed in U.S. dollars, 1970 = 100.
XVT_j	Volume of total exports of region j.

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Abstract

I. General Model Structure

specification of the price block for the industrial countries

Price relationships for manufactures

Price relationships for nonmanufactured commodities9

specification of the volume block for the industrial countries

Volume relationships for manufactures

Volume relationships for nonmanufactured commodities

specification of the volume and price relationship for the four regions

II. Model Parameters

estimation of the price block for the industrial countries

Price parameters for manufactures

Price parameters for nonmanufactured commodities 23

estimation of the volume block for the industrial countries

Volume parameters for manufactures

Volume parameters for nonmanufactured commodities

regional relationships

III. Conclusion

APPENDIX: Documented List of Dummy Variables

SUMMARIES

RESUMES

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Price relationships for nonmanufactured commodities⁹

Price parameters for nonmanufactured commodities ²³