Chapter

2. Exchange Rates and Trade Balance Adjustment in Emerging Market Economies

Author(s):
Charalambos Tsangarides, Carlo Cottarelli, Gian Milesi-Ferretti, and Atish Ghosh
Published Date:
September 2008
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Among the central questions for the work of the IMF is the role of the exchange rate in external adjustment. Determining the exchange rate correction required to reestablish external viability is crucial in the design of IMF-supported programs, and estimates of the effects of exchange rate movements on the external balance may also be required in surveillance contexts. Although there is an extensive academic literature on estimating “trade equations” (Appendix 2.1), most studies focus on imports or exports (but not both), making it difficult to infer the impact on the aggregate trade balance. Moreover, most studies are based on the experience of advanced countries or on large samples of developing countries, with few focusing on emerging market countries. To help fill this gap, this chapter examines the impact of exchange rate movements on the balance of trade in goods and nonfactor services (hereafter, the “trade balance”), based on a panel of 46 (mostly) middle-income countries over the period 1980–2005.1

Beyond its sample coverage, the analysis in this chapter offers three innovations relative to the existing literature. First, it articulates—and quantifies—the various channels through which a given movement of the exchange rate can affect the aggregate trade balance. Second, it classifies countries according to their predominant export—oil, non-oil commodities, or manufactures—to allow for differences in the response of the trade balance to exchange rate movements that might arise from the structure of the country’s exports. Third, in considering the impact of a change in the nominal exchange rate on the trade balance, the analysis takes account of the endogenous dynamics of domestic prices and costs as well as the effect on imports arising from balance sheet and wealth effects on aggregate demand. Throughout this chapter the emphasis is on the foreign currency value of the trade balance, as opposed to the literature’s traditional focus on the domestic currency trade balance, in part because the focus here is on the external viability of emerging market economies that typically borrow in foreign currencies.

This chapter asks how a permanent change in the nominal exchange rate—for concreteness, a depreciation—can affect the trade balance. Clearly, a permanent nominal depreciation will have an immediate impact on the prices of imports and of exports, but it will also set in motion domestic price and cost dynamics—so there will not be a fully corresponding permanent movement of the real exchange rate. Whether the long-run effect is larger or smaller than the immediate impact depends on the relative magnitudes of two opposing forces: the speed at which the volume elasticities rise in the long run as consumers and producers have greater scope for substitution, and the speed at which relative prices return to their initial values (assuming that the economy was initially in equilibrium), which will tend to dampen long-run volume changes.

The effect on the foreign currency value of exports is shown to depend on the structure of the country’s exports. For a country that mainly exports commodities (for which demand is more likely to be fully elastic at the given world price), the exchange rate depreciation does not change export prices measured in foreign currency terms but may induce a positive supply response by raising the domestic currency price of exports relative to nontraded goods. With volumes increasing, the foreign currency value of exports should rise as well. By contrast, for countries that predominantly export manufactures (or other differentiated products whose demand is likely to be downward sloping), the depreciation in the nominal exchange rate might encourage firms to take advantage of the currency movement to raise market share by allowing the foreign currency price to fall; if so, this will elicit higher demand. However, even if there is a positive supply response, the decline in the dollar price means that the net effect on the value of exports is, at least theoretically, ambiguous.

Turning to imports, assuming the country is “small” in the market for its imports, the depreciation (and consequent volume response) should not alter the foreign currency price. Nevertheless, there will be a volume effect that arises both from substitution away from imports whose price relative to nontraded goods has risen, and from balance sheet and wealth effects of the exchange rate depreciation on domestic absorption and thus on import demand. Since foreign currency prices remain constant, the decline in import volumes implies a corresponding reduction in the foreign currency value of imports.

Piecing together these various effects yields the aggregate impact of a nominal depreciation on the trade balance. Since this impact operates through the effects on the value of exports and of imports—possibly in opposing directions—the net effect depends on their initial magnitudes, that is, on whether the country has an initial trade surplus or deficit. In the benchmark case of initially balanced trade, we find that short-run elasticities (expressed as the change in the trade balance–to–export ratio for a 1 percent depreciation of the nominal exchange rate) average 0.45 for oil and non-oil commodity exporters, but only 0.15 for manufacturing exporters—mainly because the fall in the dollar price for manufactured goods more than offsets the higher export volume. In the longer run, however, price elasticities are similar across different types of exporting countries, ranging from 0.6 to 0.7. To put this in perspective, an elasticity of 0.7 implies that, for a country with an export-to-GDP ratio of 35 percent (the sample average), a 10 percent depreciation in the nominal exchange rate would improve the trade balance by about 2½ percent of GDP (conversely, an appreciation would deteriorate the trade balance).2 For manufacturing exporters, which have a long-run elasticity at the lower end of the range given earlier, the improvement is only somewhat smaller—around 2 percent of GDP.

When trade is not initially balanced, the response is not symmetric to whether the country has an initial surplus or deficit. The larger the initial surplus, the less likely a depreciation is to (further) improve the trade balance or an appreciation to reduce the surplus—or, even if the impact has the expected sign, its magnitude will be smaller than when trade is initially balanced. By contrast, the larger the initial deficit, the more likely a depreciation is to improve the trade balance or an appreciation to (further) deteriorate the deficit—and the magnitude of the impact will be larger than when trade is initially balanced.

The remainder of this chapter is organized as follows. The second section discusses the various channels through which the exchange rate may have an impact on the trade balance. The third section describes the country sample and classification by type of exports. The fourth section presents the main empirical results. The fifth section concludes. Appendices survey the literature and discuss data, econometric, and robustness issues.

The Analytics of Trade Balance Adjustment

An exchange rate change—for concreteness, a permanent nominal depreciation—may be the result of exchange rate policy (a devaluation under a peg or an intervention under a float) or of other macroeconomic policies and shocks. In the latter case, the exchange rate will be one of many channels through which the effect of monetary and fiscal policies on the trade balance is manifested; other, possibly more direct channels are not considered here. Abstracting from how it comes about, the exchange rate change will set in motion changes in other relative prices. But which prices are relevant? For an exporter of commodities—demand for the product of which is perfectly elastic at the world price—the depreciation cannot change the foreign currency price. Moreover, since demand is not the constraint, any volume response is determined by the supply side. The relevant equation becomes

where xcvol is the volume of exports of goods and nonfactor services and px and cpi are, respectively, the export deflator (in domestic currency) and the consumer price index. Oil prices are used as the export deflator for oil exporters, and non-oil commodity prices (weighted by the country’s commodity exports) are used as the export deflator for non-oil commodity exporters.

While the price-taking assumption for commodity exporters implies that foreign demand should affect only the market price, it is possible that world demand is not perfectly elastic, so that demand is not fully reflected in the price. In such cases, the output of partner countries might play an independent role in the supplier’s decision. Thus, to reduce the risk of omitted-variable bias, the output of partner countries, weighted by their share in the exports of the exporting country (Y*), is added to the volume equation of commodity exporters. The supply of commodities is also assumed to depend on resource availability—the economy’s cyclical position (gap) and the scope for expanding production through improvements in productivity (Δcap)—proxied by the change in GDP per capita in purchasing power parity terms.

In such cases, the depreciation may elicit such a supply response by raising the domestic currency price of exports relative to nontradables—proxied by the consumer price index (CPI). But since the depreciation will also increase the CPI (or, more generally, costs for exporters such as wages or imported inputs), the effect on the relative price for exporters will be positive, but not one-to-one with the depreciation, and will tend to decline over time. The higher relative price—especially if persistent—will draw resources into the export sector, eliciting a positive volume response.3 Since the foreign currency price of exports has remained unchanged and volumes have increased, the value of exports should rise. Finally, although the elasticity of exports in respect to a given relative price change may be expected to increase over time, rising costs mean that the effect of the depreciation on the relative price tends to diminish, so the volume response in the longer run may be smaller or larger than the response in the short run, depending on which of the two forces dominates.

For exporters of manufactures—or other differentiated products that face a downward-sloping demand curve—the depreciation will, for a given local currency price of exports, reduce the foreign currency price (relative to foreign competitors), eliciting greater demand:

where xmvol is the volume of goods and nonfactor services exports, px is the export price deflator (in domestic currency), ulc is the trade-weighted average of the (domestic currency equivalent of) unit labor costs in the country’s trading partners, and Yt* is the output of partner countries weighted by their share in the exports of the exporting country.

The supply function is implicitly defined by the pricing equation, whereby exporters determine the local currency price of exports according to conditions in the destination market and local costs—for instance, unit labor costs in manufacturing in the destination market, the exchange rate (to capture pricing to market), and the CPI as a proxy for domestic costs (inasmuch as the CPI reflects the prices of nontraded goods, this term also captures the competition from the nontraded goods sector for domestic resources such as labor).

Manufacturing exporters are assumed to set the local currency price of their goods according to conditions in the destination market and local costs. The manufacturing export price is assumed to depend on the trade-weighted average of unit labor costs in manufacturing in the country’s export markets (in foreign currency terms, ulc*), the exchange rate e (which captures the pricing-to-market behavior), and the consumer price index (cpi) as a proxy for domestic costs. The variables Δcap (growth of GDP per capita in purchasing power parity terms) and gap (real GDP relative to its Hodrick-Prescott trend) control for resource availability. Thus,

This supply function—the pricing equation—will also respond to the cyclical position of the domestic economy and developments in productivity.4 Typically, therefore, there will be at least some response of the local currency price of exports to a depreciation. Hence, although the depreciation will reduce the foreign currency price, it will be less than a proportionate decline. The fall in the relative price of exports, in turn, increases the volume of exports—though, again, given endogenous price dynamics, this might be different in the short run than in the long run. In sum, the crucial difference between exporters of commodities and those of manufactures is that, for the latter, the foreign currency price falls (which is how the positive volume response comes about). Since prices for manufactures exports decline while volumes increase, the net effect on the U.S.-dollar value of exports is a priori ambiguous.

Turning to imports, assuming the country is small in the world market, a depreciation leads to a corresponding increase in the domestic currency price of imports—though, if the CPI rises as well, the relative price of imports will not increase fully in line with the depreciation. Standard import demand functions postulate that the volume of imports depends negatively on the relative price of imports and positively on economic activity or aggregate demand (usually proxied by real GDP growth). The higher relative price leads to substitution away from imports—necessarily reducing the dollar value of imports as volumes decline.5

Although most empirical studies treat aggregate demand as exogenous when considering the impact of a depreciation on the demand for imports, experience in recent capital account crises suggests that adverse balance sheet effects from large devaluations can lead to a collapse of economic activity, thus reducing imports (and improving the trade balance). Even in less extreme situations, exchange rate movements can have balance sheet effects on firms—or wealth effects on households—thus affecting aggregate demand and, indirectly, the volume of imports. In this context, several equations need to be estimated.

The consumer price index is assumed to depend on import prices and domestic costs. The import price is proxied by movements in the nominal exchange rate, assuming immediate and full pass-through to the domestic price. Domestic costs are assumed to depend on changes in productivity, Δcap, and the output gap, gap (real GDP relative to the Hodrick-Prescott trend):

Since experience in capital account crises suggests that the balance sheet impact of large depreciations can have pervasive effects on economic activity, an equation is estimated for real absorption to the real (CPI-deflated) exchange rate (with an interactive dummy for countries with external debt ratios above 40 percent of GDP) and to real disposable income:6

where avol is real absorption, e is the nominal exchange rate, cpi is the consumer price index, D is a dummy variable that is unity if the external debt–to–GDP ratio exceeds 40 percent and zero otherwise, and YD is real disposable income (GDP minus government revenues). Absorption then feeds into the demand for imports:

where mvol is the volume of imports, pm is the local currency import price deflator, cpi (the consumer price index) proxies the price deflator of nontradables, and avol is the real absorption.

Piecing together these various effects on exports and on imports yields the impact of a depreciation in the nominal exchange rate on the trade balance. Since there are different—sometimes opposing—effects on exports than on imports, the net impact on the trade balance depends upon the relative magnitudes of the effects. Indeed, akin to the Marshall-Lerner condition, there is a corresponding condition for a depreciation (appreciation) to improve (deteriorate) the foreign currency value of the trade balance (Appendix 2.2). Although assuming that the country’s trade position is initially in balance provides a useful benchmark, the effects of a depreciation in the nominal exchange rate are sensitive to the initial trade position.

Country Classification and Estimation Strategy

As noted earlier, this chapter goes beyond the existing literature by looking not only at the effects of relative price changes on volumes, but also at the pass-through effect of changes in the nominal exchange rate on relative prices and the combined impact on export and import values. The sample in this chapter covers 46 emerging market economies (see Table 2.A.2), most of which are classified as middle-income countries (according to the World Bank’s World Development Indicators); two low-income countries (India and Pakistan) are included given their importance in world trade and their access to market financing.7 Annual data covering the period 1980–2005 are used in all estimations except the inflation equation, which is estimated beginning in the early 1990s, given the evidence suggesting that exchange rate pass-through to domestic prices has weakened over time.

As discussed previously, the response of exporters to a depreciation in the exchange rate is likely to depend upon the market structure of the good they export—in particular, the elasticity of global demand for their products. Ideally, this would be incorporated in the analysis by considering each country’s exports separately (at least broad categories), and then aggregating to obtain the full effect on the trade balance. In the absence of the requisite data, however, countries are categorized according to their dominant export—oil, non-oil commodities, or manufacturing.8 One disadvantage of this approach is that this analysis, like that of other studies that focus on macro aggregates, cannot consider intersectoral effects, such as the crowding out of manufactures in response to booming commodity exports.

How representative of the full range of a country’s exports is this classification? For countries classified as oil exporters, the average share of oil in merchandise exports is 77 percent; for non-oil commodity exporters and manufactures exporters, the average shares of non-oil commodities and manufactures, respectively, are around 65 percent; across categories, the lowest share of the predominant export in the country’s exports is around 45 percent (Table 2.A.2 lists the export classification of countries and period coverage). For each of the three exporter categories used in this study, Figure 2.1 compares the average of the export deflators (which, for each country, is a weighted average of the deflators of the country’s actual exports) for the countries in that category to the price that is assumed to be relevant to the decisions for that category of exporters—the oil price for oil exporters, nonfuel commodity prices for other commodity exporters, and the unit labor costs in the manufacturing sector of destination markets for manufactures. The close correspondence between these prices and the countries’ overall export price deflators suggests that this broad categorization by the predominant export in a country may indeed be reasonable.

Figure 2.1.Price Deflators, 1980–2005

(Average across all countries in category; indices, 2000 = 100)

Source: International Monetary Fund, World Economic Outlook database.

Note: Panel (a) displays foreign unit labor costs in manufacturing (ULC), weighted by trade exports to advanced economies. In panel (b), oil price is the simple average of three spot prices: Brent, West Texas, and Dubai. Panel (c) shows the nonfuel commodity export price, weighted by commodity shares of non-oil exports to the world.

Since commodity prices and import prices are assumed to be exogenous, only two price equations need to be estimated: the price equation for manufacturing exports and the response of the CPI to a change in the exchange rate.9 Four trade volume equations are estimated (one for imports, and one for each of the three categories of exports—though the latter are estimated jointly using interactive regressors for each category). In addition, an equation for the volume of absorption is estimated to capture the response of absorption to changes in the real exchange rate—the nominal exchange rate deflated by the CPI.10

Estimation using a panel of countries poses some econometric challenges, in particular as a result of the possible nonstationarity of the data and the likelihood that country effects are correlated with the lagged dependent variable. Arellano and Bond (1991) first derived an estimator that is valid under these conditions, under which it is possible to take advantage of the number of cross-sectional units (46 countries) being large relative to the number of time periods (an average of 24 years). Their estimator was later modified by Blundell and Bond (1998) to incorporate levels and first differences as instruments; it is this estimator that is used in this chapter.11 In regard to instrumentation, the relative price variables are instrumented by their lagged values in the export and import volume equations to limit possible simultaneity bias. Moreover, real absorption is also instrumented in the import demand function by lags of the real exchange rate and disposable income in addition to its own lagged values.

As a robustness test of the basic results, alternative estimators based on cointegration tests are also used. The first estimator, the mean group (MG) estimator, consists of estimating separate autoregressive distributed lag models for each country, in which dependent and independent variables enter on the right-hand side. The MG estimator then derives the full-panel estimates as simple averages of individual country coefficients. The second estimator recognizes that the long-run response of the dependent variable to exchange rate changes might be the same across countries and uses this restriction by pooling the individual long-run regression coefficients; it is therefore referred to as the pooled mean group (PMG) estimator. These alternative estimation techniques yield broadly similar results, suggesting that the findings are robust (see Appendix 2.5 for details).

Empirical Results

Exports

Export volume equations for the three categories of exporters are estimated jointly using interactive terms. For the commodity exporters, the relative price coefficient is expected to be positive, as these exporters are assumed to be small in the world commodities markets and therefore unable to influence the world price. Moreover, since there may be lags in the supply response—and resources are unlikely to shift to the export sector if price movements are temporary—a three-year backward average of the relative price is used. Coefficient estimates are reported in Table 2.1.

Foreign demand has a large impact on exports across the three categories, with short-run elasticities ranging from about 0.5 for non-oil commodity exports to 1.8 for manufactures and over 3.0 for oil. Long-run elasticities are generally higher (except for in the case of oil exports) and remain high even with the inclusion of a trend term to proxy for increased product variety and declining trade costs. Turning to the effects of relative prices, the elasticities are substantially smaller than the income elasticities. For manufactures, the elasticity is negative, representing a demand response, and is statistically significant.12 The magnitude of the coefficient implies that a 1 percent decrease in the price of the home country’s exports (relative to those of foreign competitors) would increase the volume of exports by 0.5 percent in the short run and by 0.8 percent in the long run. For commodities, the price elasticities—though positive, as expected for supply responses—are considerably lower in magnitude. This is consistent with the view that the supply of exhaustible resources is fairly inelastic with respect to price; only the price elasticity of non-oil commodities is statistically significant.

Table 2.1.Export Volumes: Coefficient Estimates and Implied Elasticities
Oil Exporters (Supply)Non-oil Commodity Exporters (Supply)Manufacturing Exporters (Demand)
Coefficient estimatesLong-run elasticitiesCoefficient estimatesLong-run elasticitiesCoefficient estimatesLong-run elasticities
Volume
First lag0.83***0.83***0.83***
Relative price1
Contemporaneous0.050.250.30*0.21–0.48***–0.83**
First lag–0.01–0.27*0.34***
Income effects2
Contemporaneous3.23*0.93*–0.542.45***1.78**2.10**
First lag–3.07*0.96–1.42
Change in per capita
GDP (PPP terms)
Contemporaneous0.77***0.22
First lag0.140.25
Output gap
First lag0.07–0.01
Diagnostic statistics Number of186310511
observations
Number of countries91423
R20.960.960.96
Tests (all three sectors are estimated jointly)
Hansen test32.57
Arellano-Bond test–4.16***
for AR(1)
Arellano-Bond test–0.84
for AR(2)
Number of51
instruments
Source: IMF staff estimates.Note: All variables are defined in logarithm, except for output gap, which is defined in percent of GDP.

World non-oil commodity prices divided by CPI for non-oil commodity exporters; world oil price divided by CPI for oil exporters; and export deflator divided by the unit labor cost of trading partners for manufacturing exporters. All prices are defined in domestic currency. For commodity exporters (oil and non-oil), the relative price is a three-year moving average.

Real GDP of trading partners for all export equations.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.Note: All variables are defined in logarithm, except for output gap, which is defined in percent of GDP.

World non-oil commodity prices divided by CPI for non-oil commodity exporters; world oil price divided by CPI for oil exporters; and export deflator divided by the unit labor cost of trading partners for manufacturing exporters. All prices are defined in domestic currency. For commodity exporters (oil and non-oil), the relative price is a three-year moving average.

Real GDP of trading partners for all export equations.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

While the volume equations yield the effect of a relative price change on exports, determining the impact of a depreciation in the nominal exchange rate requires a pricing equation that links the exchange rate to relative prices. For manufactures, the pricing equation determines the domestic currency price of exports and represents the exporters’ supply function (Table 2.2).13 Export prices respond positively to unit labor costs of competitors and to domestic costs—as proxied by the CPI—as well as to the nominal exchange rate, possibly because of pricing-to-market strategies. Indeed, the direct impact of a 1 percent depreciation of the nominal exchange rate is to elicit a 0.58 percent increase in the local currency price of exports. In addition, however, since the CPI enters the pricing equation with a coefficient of 0.40—and itself increases by 0.25 percent in response to a depreciation in the nominal exchange rate (Table 2.3)14—the total response is 0.68 percent (0.58 + (0.40 x 0.25)). Therefore, if the exchange rate depreciates by 1 percent, the foreign currency price of manufactures falls by 0.32 percent (–1 + 0.68).15 The combination of a small pass-through effect and an inelastic volume response to price changes yields a very small short-run elasticity of manufactures’ export volumes to depreciation in the nominal exchange rate of 0.15 (=–0.48 x–0.32) percent. Moreover, since this volume response (0.15) is less than the foreign currency price response (–0.32 percent), the depreciation lowers the U.S.-dollar value of manufacture exports in the short run (though in the long run the U.S.-dollar value of exports remains roughly unchanged; see Table 2.5). The CPI equation used in this chapter does not control for a country’s exchange rate regime. Since a country with a fixed exchange regime is likely to experience a smaller pass-through of exchange rate changes into domestic prices—and thus a larger movement of relative prices—the effect of a nominal depreciation on the trade balance will be larger in such a country (see Table 2.A.5).

Table 2.2.Pricing Equation for Manufacturing Exporters: Coefficient Estimates and Implied Elasticities
Coefficient EstimatesLong-Run Elasticities
Export deflator
First lag0.73***
Exchange rate in local currency per U.S. dollar
Contemporaneous0.58***0.90***
First lag–0.34***
Unit labor costs of competitors1
Contemporaneous0.20**0.58***
First lag–0.05
CPI index (logs) (proxy for domestic costs)
Contemporaneous0.40***0.09
First lag–0.38***
Diagnostic statistics
Number of observations511
Number of countries23
R20.99
Tests
Hansen test14.19
Arellano-Bond test for AR(1)–1.60
Arellano-Bond test for AR(2)–0.66
Number of instruments42
Source: IMF staff estimates.

Unit labor costs of trading partners for manufacturing exporters; in foreign currency.

*significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.

Unit labor costs of trading partners for manufacturing exporters; in foreign currency.

*significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

For oil and non-oil commodities, the foreign currency price of exports is determined in international markets, so a nominal depreciation leads to a corresponding increase in the domestic currency price of exports. The relative price that is relevant for spurring resources to shift into the export sector, however, is assumed to be the export price relative to the CPI. Taking account of the impact on the CPI, a 1 percent depreciation in the nominal exchange rate raises the relative price of oil and non-oil commodity exports by 0.75 (1—0.25) percent (Table 2.3). Although the short-run supply response is weak—amounting to 0.05 to 0.30 percent for oil and non-oil commodities—the U.S.-dollar value of exports rises slightly, since the foreign currency price is constant and there is a positive (albeit small) volume response (see Table 2.5).16

Table 2.3.Inflation Rate: Coefficient Estimates and Implied Elasticities(Post-1994)
Coefficient EstimatesLong-Run Elasticities
Inflation rate
First lag0.45***
Nominal exchange rate change
Contemporaneous10.25***0.53***
First lag–0.015
Change in per capita GDP (PPP terms)
First lag–0.06
Output gap
First lag0.08
CPI
First lag–0.0957**
Nominal exchange rate
First lag0.04
Nominal exchange rate interacted with dummy for above potential output
First lag0.02
Diagnostic statistics
Number of observations506
Number of countries46
R20.8
Tests
Hansen test42.57
Arellano-Bond test for AR(1)–3.3***
Arellano-Bond test for AR(2)–0.77
Number of instruments49
Source: IMF staff estimates.Note: The inflation rate and nominal exchange rate change have been transformed to lie in the interval (–100, 100) percent to limit the impact of outliers.

The long-run coefficient is the average of the coefficient for countries that are above their output trend and that for countries that are not.

*significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.Note: The inflation rate and nominal exchange rate change have been transformed to lie in the interval (–100, 100) percent to limit the impact of outliers.

The long-run coefficient is the average of the coefficient for countries that are above their output trend and that for countries that are not.

*significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Imports

For imports, a standard import demand function is estimated in which the relative price is the import deflator divided by the CPI, and real absorption is the “activity” variable.17 The resulting price elasticities of—0.18 in the short run and—0.43 in the long run are economically and statistically significant (Table 2.4). Reflecting the typically high “activity” elasticity of imports in middle-income and emerging market countries, the absorption elasticity is well over unity: that is, 1.64 in the short run and 1.55 in the long run. Hence, as was the case for exports, the income effects are much larger than the relative price effects.

Table 2.4.Volume of Imports and Absorption: Coefficient Estimates and Implied Elasticities
Coefficient EstimatesLong-Run ElasticitiesCoefficient EstimatesLong-Run Elasticities
Import volumeReal domestic demand
First lagFirst lag0.89***
Relative price for import demand1Real exchange rate1
Contemporaneous–0.18**–0.43**Contemporaneous–0.07**0.09
First lag0.09First lag0.08***
Real domestic demandReal exchange rate (for high-debt countries)
Contemporaneous1.64***1.55**Contemporaneous–0.08***–0.61***
First lag–1.31***First lag
Ratio of disposable income to CPI
Contemporaneous0.23***0.64*
First lag–0.16**
Change in fiscal balance (percent of GDP)0.00
Broad money growth, real0.00***
Diagnostic statisticsDiagnostic statistics
Number of observations824Number of observations824
Number of countries41Number of countries41
R20.97R20.96
TestsTests
Hansen test14.10Hansen test31.73
Arellano-Bond test for AR(1)–3.68***Arellano-Bond test for AR(1)
Arellano-Bond test for AR(2)0.72Arellano-Bond test for AR(2)–1.46
Number of instruments27Number of instruments57
Source: IMF staff estimates.

Using CPI as the deflator.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.

Using CPI as the deflator.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Beyond the direct substitution effect, a depreciation in the nominal exchange rate may affect imports indirectly, via wealth or balance sheet effects on absorption.18 To the extent that a country is a net external debtor (has a negative net foreign asset position), the depreciation raises the real burden of that debt. By contrast, for countries with trade surpluses that are also net creditors, it is appreciation pressures that have a negative effect on absorption (and thus import volumes). In addition, disposable income and wealth of firms and households are eroded by the rise in the consumer price index that results from the exchange rate depreciation. In the absence of data on the currency composition of sectoral balance sheets, Table 2.4 models real absorption as a function of the real (CPI-deflated) exchange rate depreciation (with an interactive dummy for countries with external debt ratios above 40 percent of GDP) and of real disposable income.19 Recalling that a 1 percent depreciation of the nominal exchange rate increases the CPI immediately by 0.25 percent (Table 2.3), the estimates imply that real absorption would decline, via the external wealth term, by some 0.11 percent ((0.07 + 0.08) x 0.75) for those countries with debt ratios above 40 percent of GDP; the corresponding effect in the long run would be 0.24 percent.20

Finally, combining the substitution and balance sheet effects, a 1 percent depreciation of the nominal exchange rate reduces import volumes by 0.32 percent in the short run and by 0.58 percent in the long run. Since the country is assumed to be small in the market for its imports, and therefore foreign exporters do not price to its market, this translates into a corresponding change in the value of imports.21

Trade Balance

The trade balance response to a depreciation in the nominal exchange rate differs across the three country types—oil, non-oil commodities, and manufactures exporters—and may also differ within each category depending on whether the country is initially in surplus or deficit. As shown in Table 2.5, the short-run elasticity of the trade balance in foreign currency for a 10 percent depreciation of the nominal exchange rate—starting from balanced trade—is lower among manufactures exporters (0.15) than for commodity exporters (averaging about 0.45). For example, if a country has an export-to-GDP ratio of 35 percent, slightly above the average export-to-GDP ratio in the sample, a 10 percent depreciation in the nominal exchange rate would have an immediate impact on the trade balance of a manufactures exporter of only 0.4 percent of GDP but would improve a commodity exporter’s trade balance by anywhere between 1¼ and 2 percent of GDP. For all groups of countries, however, most of the improvement in the trade balance comes from the impact on imports (Table 2.5).

Over the medium term, the impact of an exchange rate depreciation on the trade balance converges for the various categories of exporters—with a 10 percent depreciation leading to an improvement in the trade balance of about 2–2½ percent of GDP depending on the class of exporter. The speed of adjustment depends on the various dynamics of relative prices responding to the change in the exchange rate and of import and export volumes responding to relative price movements. To provide a sense of the trajectory of the long-run equilibrium, Figure 2.2 plots the change in the export deflator and export volume for exporters of manufactures following a 10 percent depreciation and the effects on the trade balance for all three export categories (in percent of GDP), assuming a country with export-to-GDP and import-to-GDP ratios of 35 percent. The simulations shown in the figure suggest that for exporters of manufactures, there is no long-run pass-through of a currency depreciation to the foreign currency price, so that the valuation effect approaches zero over time. This of course reduces the initial adverse impact of the depreciation on the value of exports (expressed in foreign currency) and leads to a gradual improvement in the trade balance (Figure 2.3, panel (a)). The trade balance of oil and non-oil commodity exporters improves on impact because of the sharp fall in imports but then stabilizes over time because of the waning effects of the currency depreciation on imports. For all three categories of exporters, most of the adjustment in the trade balance takes place within five years of a 10 percent exchange rate depreciation, with the effect leveling out within seven years.

Table 2.5.Effects of Devaluations on Export-Import Values and on the Trade Balance for Different Classes of Exporters(Percent change for a depreciation of 10 percent)
Short-Run EffectsLong-Run Effects
Oil exportersNon-oil commodity exportersManufacturing exportersOil exportersNon-oil commodity exportersManufacturing exporters
Export value in foreign currency0.040.23–0.170.120.10–0.01
Import value in foreign currency–0.32–0.32–0.32–0.58–0.58–0.58
Initial trade balance is in equlibrium (α = 1.00)1
Trade balance in foreign currency0.360.550.150.700.680.57
Initial trade balance is in deficit (α = 0.75)1
Trade balance in foreign currency0.350.490.190.670.660.57
Initial trade balance is in surplus (α = 1.25)1
Trade balance in foreign currency0.370.600.110.730.700.57
Source: IMF staff estimates.Note: Results are based on the Arellano-Bond estimator. Initial trade balance is equal to zero, with elasticity defined as · = (dTB/xval)/(de/e).

α is defined as the ratio of exports to imports (see Appendix 2.2).

Source: IMF staff estimates.Note: Results are based on the Arellano-Bond estimator. Initial trade balance is equal to zero, with elasticity defined as · = (dTB/xval)/(de/e).

α is defined as the ratio of exports to imports (see Appendix 2.2).

As indicated previously, the response of a country’s trade balance to a depreciation in the nominal exchange rate may also depend on whether the country has an initial surplus or deficit—particularly in the case of manufactures exporters, because for them, the export value response has an effect on the trade balance opposite to that of the import value response. From Appendix 2.2, given the larger (negative) price elasticity of imports compared to the value of exports, the modified Marshall-Lerner condition is more likely to be satisfied—and hence a depreciation (appreciation) is more likely to improve (deteriorate) the U.S.-dollar value of the trade balance, the larger are imports in relation to exports—that is, the larger is the initial trade deficit. The sensitivity of the trade balance response to initial conditions is shown in Figure 2.3 (panels (b) and (c)), which compares the trade balance dynamics starting from an initial surplus and an initial deficit, respectively. For example, assuming exports at 35 percent of GDP and imports at 28 percent of GDP, a 10 percent depreciation would raise the trade balance for a country that exports manufactures by slightly less than 2 percent of GDP in the medium term—marginally lower than in the case of a trade balance. Conversely, assuming exports at 35 percent of GDP and imports at 45 percent of GDP, a 10 percent depreciation would raise the trade balance for a country that exports manufactures by an amount just above 2½ percent of GDP over the medium term.

Figure 2.2.Profiles for Exports, Imports, and Trade Balances

(Percent change following a 10 percent nominal exchange rate depreciation)

Source: International Monetary Fund staff estimates.

Note: The profiles shown in the figure assume a 10 percent depreciation of the nominal exchange rate for a country with export and import ratios at 35 percent of GDP. In panel (b), “imports” refers to all countries; “exports” refers to oil and non-oil commodity exporters.

Conclusions

The analysis presented in this chapter suggests several important findings. The response of a country’s trade balance depends crucially on the market structure of its exports, in particular, whether it primarily exports goods for which there is highly elastic demand at a given world price, or differentiated products with downward-sloping demand curves. As regards imports, wealth and balance sheet effects on domestic absorption are an important additional channel through which the exchange rate may affect the trade balance in emerging market economies. Export volume and pricing-to-market elasticities tend to be quantitatively small, so most of the response of the trade balance comes from the behavior of imports. Given the larger (negative) price elasticity of imports compared to the value of exports, the impact of an exchange rate movement will depend on the initial trade balance, with a condition akin to the Marshall-Lerner condition governing whether a depreciation (appreciation) in the nominal exchange rate will improve (deteriorate) the trade balance, measured in foreign currency terms, of a country that is small in the market for its imports but large in its export market. Specifically, the larger the initial trade surplus, the less likely that this condition will be fulfilled—or at least the smaller the impact of an exchange rate movement on the trade balance.

Figure 2.3.Effect of a Depreciation on the Trade Balance

(Percent change following a 10 percent nominal exchange rate depreciation)

Source: International Monetary Fund staff estimates.

Note: The profiles presented in this figure show changes in the trade balance (in percent of GDP) following a 10 percent depreciation of the nominal exchange rate in period 0. The export ratio is fixed at 35 percent of GDP, and the import ratio is 35 percent in panel (a), 28 percent in panel (b), and 45 percent of GDP in panel (c).

Overall, the estimated elasticities are by no means negligible; a 10 percent nominal depreciation leads to an improvement in the trade balance of about 2 to 2½ percent of GDP, depending on the class of exporter and assuming an export-to-GDP ratio similar to the average for the countries in our sample (35 percent). Moreover, the impact of external adjustment on economic activity and output would of course be correspondingly larger than in the absence of an exchange rate adjustment. Of course, these results need to be interpreted with care, given the caveats raised earlier. It should also be noted that the chapter focuses on the average impact of a change in the nominal exchange rate on the trade balance and therefore does not differentiate between countries whose real exchange rates are in equilibrium during the sample period and those whose real exchange rates are out of equilibrium. In principle, the closer the real exchange rate is to its equilibrium value, the more a depreciation in the nominal exchange rate is likely to be eroded through a rise in domestic costs and pricing behavior of exporters. Finally, it bears emphasizing that the results pertain to middle-income countries and therefore cannot be used on their own to examine global imbalances; for example, as previously noted, pricing to market on the import side is largely absent in this sample of countries even though studies on advanced economies show that these effects are quantitatively important—implying a more limited impact of the exchange rate on the volume of imports for such countries.

Overview of the Empirical Literature on Trade Volume Price Elasticities and Pricing to Market

The literature on trade elasticities—a partial-equilibrium approach to studying external adjustment using price (and income) elasticity of imports (or exports)—has a long history in empirical international trade. Since the seminal contribution of Houthakker and Magee (1969)), which has influenced much of the subsequent research in this area, the literature has used developments in methodologies, theory-based inclusion of additional variables, and increased sample sizes to further refine the estimates.22 As illustrated in the survey of Goldstein and Khan (1985), past empirical explorations have largely focused on advanced economies, but recent papers have increasingly covered developing and other emerging market countries.

This appendix examines some of the more recent estimates of price elasticities based on aggregate macroeconomic data on import and export volumes, both for industrial and developing countries. Estimates of price elasticities of export and import demand vary greatly depending on the sample of countries, definition of relative price,23 choice of control variables, time period, and underlying methodology. The elasticities reported in Table 2.A.1 may to some extent be compared with the short-run and long-run volume elasticities in Table 2.1 and the import demand volume elasticities reported in Table 2.4, though it should also be noted that the estimates in Table 2.1 distinguish between classes of exports and those for manufactures are based on the estimation of a demand function. Recognizing the time-series properties of the variables underlying the estimation of trade elasticities, most recent papers—unlike Houthakker and Magee (1969), with its simple ordinary least squares (OLS) estimates—use a cointegration framework à la Johansen (1988). In addition to this line of research, trade economists have also estimated equations with specified micro foundations, generally yielding higher elasticities. This is generally attributed to the effect of aggregation over different goods. It should be noted, however, that cost heterogeneity among producers within a sector also implies different levels of pass-through from exchange rates to aggregate prices; more precisely, if a country devalues, the less efficient firms exporting to the country are likely to exit. This means that the calculated pass-through to prices will be greater when micro data are used than when aggregate price indices are used, and thus—for a given volume change—the volume elasticities derived from micro studies will have an upward bias.

Table 2.A.1.Estimates of Price Elasticities in Selected Papers
PeriodNumber of CountriesExportsImports
Average1RangeAverage1Range
Houthakker and Magee (1969))1951–66152–0.5–2.4 to 1.7–0.4–1.7 to 1
Reinhart (1994)1968–92123–0.3–1.0 to 0.34–0.6–1.4 to 0.3
Senhadji (1998)1960–93775–0.3–0.9 to 06
775–1.1–6.7 to 07
Senhadji and Montenegro (1999)1960–93755–0.2–1.0 to 06
755–1.0–4.7 to 07
Caporale and Chui (1999)1960–922130.5–1.9 to 1.18–0.5–3.3 to 0.18
213–1.2–6.1 to 09–0.5–1.2 to–0.19
Hooper, Johnson, and Marquez (2000)1950–971072–0.3–0.5 to–0.16–0.1–0.2 to 06
72–0.9–1.6 to–0.27–0.4–0.9 to–0.17
Marquez (2002)1980 to late 1990s83–2.1–6.2 to–0.3–0.7–1.1 to–0.3
Bahmani-Oskooee and Kara (2005)Mid-1970s to 1990s283–1.0–5.8 to 3.3–1.2–3.6 to 2.4

Simple average of country estimates.

Industrial countries only.

Developing countries only.

Industrial countries’ demand for developing country exports.

Industrial and developing countries.

Short-run estimates.

Long-run estimates.

Dynamic ordinary least squares (DOLS) estimator à la Stock and Watson (1993).

Autoregressive distributed lag (ARDL) estimator à la Pesaran and Shin (1996).

Period coverage differs, from mid-1950s to early 1970 to either 1996:Q4 or 1997:Q1.

Simple average of country estimates.

Industrial countries only.

Developing countries only.

Industrial countries’ demand for developing country exports.

Industrial and developing countries.

Short-run estimates.

Long-run estimates.

Dynamic ordinary least squares (DOLS) estimator à la Stock and Watson (1993).

Autoregressive distributed lag (ARDL) estimator à la Pesaran and Shin (1996).

Period coverage differs, from mid-1950s to early 1970 to either 1996:Q4 or 1997:Q1.

What are the main findings of the empirical literature? Reinhart (1994), in an early application of the literature using a cointegration framework, examines the relationship between relative prices and imports and exports in 12 developing countries in Asia, Africa, and Latin America. She finds very low price elasticities, well below unity, suggesting that price swings need to be large to affect trade patterns. Hooper, Johnson, and Marquez (2000) focus on trade elasticities for G-7 countries. They develop a system of equations for real imports and exports, as well as real GDPs and relative prices, also allowing for dynamic adjustments by specifying error correction equations. They generally find more elastic coefficients in the long run than in the short run. Marquez (2002) also examines the specific case of East Asian countries, finding much higher long-run price elasticities for imports and exports. He also finds—with the exception of Indonesia—the sum of long-run price elasticities to be less than–1, indicating an improvement in the current account balance in response to a real exchange rate depreciation.

Other recent papers have applied the Pesaran-Shin (1996) approach to autoregressive distributed lag (ARDL) modeling. Senhadji (1998) and Senhadji and Montenegro (1999) apply this technique to a sample of more than 70 countries to estimate comparable sets of price (and income) elasticities, for both the short and the long run. Both papers find that—consistent with Hooper, Johnson, and Marquez (2000)—whereas average price elasticities are close to zero in the short run, they approach unity in the long run. Furthermore, they document a wide range of estimates for the cross section of countries in the sample. Caporale and Chui (1999) calculate import and export price (and income) elasticities for a sample of 21 countries, both industrial and emerging. Although they also report results of the dynamic OLS methodology, à la Stock and Watson (1993), they find that the ARDL approach produces coefficients more consistent with theoretical priors. Most recently, Bahmani-Oskooee and Kara (2005) apply the ARDL methodology to a sample of 28 countries, concluding that almost all price elasticities are negative and highly significant. They find that whereas developing countries tend to have price elasticities of less than unity, no clear pattern is found among industrial countries. They also conclude that the Marshall-Lerner condition is met in the long run and thus that a devaluation will generally improve a country’s trade balance.

As noted previously, use of more micro-level data by trade economists has yielded much higher elasticities. In an influential paper, Riedel (1988) finds Hong Kong SAR’s manufactured goods to face an infinitely elastic demand in world markets. Although larger elasticities for small open economies are in line with trade theory, Panagariya, Shah, and Mishra (1996) find the infinite magnitude of Riedel’s estimates implausible because of weaknesses in the methodology being used. Examining demand for Bangladesh’s garment products in the U.S. market, using a well-specified demand equation, they find own-price elasticity to exceed (in absolute value) 65 in most specifications. Regarding import demand, Kee, Nicita, and Olarreaga (2004) estimate more than 300,000 import demand elasticities for 4,625 goods in 117 countries, finding a simple average of–1.67 (and a median of–1.08). They find import demand to be more elastic at a disaggregated level and elasticities to be higher among larger countries and lower-income countries. Some authors (for example, Abeysinghe and Choy, 2005) have examined the effect on export volume price elasticities of high import content in exports, finding evidence of lower elasticities.

Pricing to Market and Exchange Rate Pass-Through for Emerging Markets

The literature on the analysis of the relationship between exchange rate movements and goods prices is more recent than that on trade elasticities but correspondingly also voluminous, especially for industrial countries. It has focused on two related areas of research: pricing to market and exchange rate pass-through. Recent papers on prices and exchange rate movements have examined whether pricing to market exists and the extent of the corresponding markup adjustment. Goldberg and Knetter (1997) argue that pricing-to-market studies for industrial countries find convincing evidence of price discrimination even among seemingly homogenous goods. Gaulier, Lahreche-Revil, and Mejean (2006) examine pricing-to-market behavior for a set of 130 industrial and developing countries and find some evidence of pricing-to-market behavior in more than half of the industries examined and especially for final consumption goods. Studies on specific industries in emerging markets also suggest pricing-to-market behavior. Lee (1995) and Kim (2004) find pricing-to-market behavior among Korean export industries, and Tongzon and Menon (1994) report pricing-to-market behavior for export industries in Singapore.

Motivated by the rise in industrial organization and strategic trade theory, empirical studies have examined the pass-through of exchange rate movements to both aggregate import prices and import prices of specific industries. Much of this literature focuses on industrial countries, in particular the United States and Japan, and employs a single-equation estimation approach to assess the effects of the exchange rate change. The range of estimates varies across countries, with those for the United States centered on 20 percent in the short run and 40 percent in the long run (Marazzi and others, 2005), and those for countries of the Organization for Economic Cooperation and Development centered on 46 percent in the short run and 65 percent in the long run (Campa and Goldberg, 2005). For G-7 countries, Ihrig, Marazzi, and Rothenberg (2006) estimate a pass-through effect of 40 percent for the period 1990–2004.

Applied work for emerging market and developing countries is more limited. Barhoumi (2005a, 2005b) finds that the long-run exchange rate pass-through to import prices for a panel of developing countries varies between 64 percent and 83 percent depending on the chosen estimation methodology. Sahminan (2002) finds a similar long-run pass-through estimate of about 83 percent on average for Thailand, Singapore, and the Philippines. Taking account of the effects of market concentration, Lee (1997) estimates that about 62 percent of exchange rate movements pass through to import prices across industries in Korea and that higher market concentration among specific industries weakens the pass-through effect.

Appendix 2.2 Marshall-Lerner Redux

The traditional Marshall-Lerner condition specifies when a depreciation of the exchange rate will improve the trade balance, measured in local currency terms, of an economy that is “small” in both its export and import markets.24 An analogous condition determines whether the trade balance, measured in foreign currency terms, of a country that is large in its export market will improve, and may be derived as follows. Let the trade balance in U.S. dollars be defined as TB*=px*xvol(px*)pm*mvol(pm)

, where px*=px/e
, px is the local currency export price, e is units of national currency per U.S. dollar, pm is the local currency import price, and px*
is the foreign currency import price, and the subscript vol indicates the volume (of exports or imports). Differentiating this expression with respect to the exchange rate yields

Defining the exchange rate elasticity (in national currency per U.S. dollar) of the local currency price as ηepx

and the foreign price elasticity of the export volume (from the demand function) as ηpx*xvol
gives

and

and the change in the value of exports may be written.

Likewise, dmval*=dpm*mvol+pm*dmvol=pm*dmvol

. Assuming that the foreign currency price of imports is fixed, then the domestic price of imports is given by pm=pm*e
. Differentiating this equation yields dpm=pm*de
(that is, the exchange rate feeds through fully to domestic import prices), and, as was shown above to be the case for dxvol,

Hence

Combining terms,

where xval*=αmval*

and α is the ratio of exports to imports. Hence, the Marshall-Lerner condition will be met (that is, an exchange rate depreciation will improve the trade balance) if and only if

A crucial assumption in the derivation just outlined is that there is some degree of pricing to market. However, if there is no pricing to market (in other words, if ηepx=0

) and we assume that α = 1 so that trade is in balance, the foregoing inequality collapses into the familiar Marshall-Lerner condition, that is,

A corresponding condition can be derived for the commodity exporters, who are assumed to face fully elastic world demand but whose export volume may respond to changes in domestic relative prices.

Appendix 2.3 Data Description and Sample

Export volume refers to exports of goods and services expressed in domestic currency at 2000 prices.

The export deflator for oil exporters is the average spot oil price converted into domestic currency.

The export deflator for non-oil commodity exporters is the weighted average spot commodity price index based on the share of non-oil commodities in the exports of the commodity exporters and converted into domestic currency.

Domestic prices are represented by the consumer price index.

Foreign income is the output of partner countries weighted by their share in the exports of the exporting country.

The change in capacity is measured by the change in GDP per capita in purchasing power parity terms.

The output gap is measured as the log difference between actual output and trend output calculated using a Hodrick-Prescott filter over 20 years.

The export deflator for manufacturing exporters is export value divided by export volume, both in domestic currency.

The relative export price for manufacturing exporters is the trade-weighted average of the domestic currency equivalent of unit labor costs in the country’s trading partners.

Real absorption is output minus net exports expressed in domestic currency at 2000 prices.

Real disposable income is output minus government revenues deflated by the CPI.

Import volume refers to imports of goods and services expressed in domestic currency at 2000 prices.

The import deflator is import value divided by import volume, both in domestic currency.

All variables are taken from the World Economic Outlook database. The sample of countries (see Table 2.A.2) encompasses all of the middle-income countries listed in the World Bank’s World Development Report, except for countries with a population of less than one million and transition economies. It also includes India and Pakistan, given their importance in world trade and access to market financing.

Appendix 2.4 Robustness Tests

This appendix describes the results of four robustness tests, specifically, tests of (1) the effect of structural changes on volume elasticities, (2) evidence on weakening pass-through effects of devaluations to inflation (with high-inflation cases controlled for), (3) for manufacturers, evidence of pricing-to-market behavior, even if large exporters are dropped from the sample, and the absence of terms-of-trade effects on the supply of these goods, and (4) estimates that show that import prices change almost one-to-one with a change in exchange rates.

The reported export volume elasticities may be affected by numerous factors, in particular, structural changes that might lead to differences in trade patterns and to changes in trade costs. Such structural changes might explain the relatively large income elasticities obtained and, more importantly, could call into question the classification based on trade shares discussed in the chapter.

Table 2.A.2.Country Sample
Country and Exporter ClassBeginning DateCountry and Exporter ClassBeginning Date
Oil exportersManufacturing exporters
Algeria1980Botswana1982
Egypt1988Brazil1982
Gabon1980China1980
Iran, Islamic Republic of1981India1980
Libya1991Indonesia1988
Oman1991Jamaica1980
Syrian Arab Republic1980Jordan1982
Trinidad and Tobago1982Korea, Republic of1980
República Bolivariana de Venezuela1980Lebanon1992
Malaysia1987
Non-oil commodity exportersMauritius1980
Argentina1981Mexico1982
Bolivia1981Morocco1980
Chile1980Namibia1982
Colombia1981Pakistan1983
Costa Rica1986Philippines1980
Dominican Republic1980Singapore1982
Ecuador1991South Africa1980
El Salvador1982Sri Lanka1982
Guatemala1984Swaziland1982
Honduras1980Thailand1982
Panama1980Tunisia1983
Paraguay1980Turkey1980
Peru1982
Uruguay1982
Note: The end date of the samples for all countries is 2005.
Note: The end date of the samples for all countries is 2005.

To examine these factors, Table 2.A.3 presents estimates of export volume elasticities where a time trend has been added. As shown in the table, income elasticities are somewhat lower than those presented in Table 2.1 without a time trend; although the relative price elasticities are also smaller, the difference in magnitude here seems less striking. More importantly, given how countries are assigned to the three export categories in this chapter, estimation over a shorter time period reduces the risk that changes in trade patterns might have led to countries’ being classified according to trade shares that might no longer be valid. However, estimation of our sample over a shorter time period (1992–2005) (see Table 2.A.3) leads only to the reclassification of the Dominican Republic as a manufacturing exporter (rather than a non-oil commodity exporter) and yields broadly similar results in regard to price and income elasticities.

An additional source of sample bias might arise when borderline countries—for example, those that might have broadly similar trade shares in two of the three categories defined—are forced into a single category. In effect such an aggregation disregards some of characteristics of a country’s trade patterns. For example, Egypt is classified as an oil exporter in the estimations in this chapter but could have also been classified as a manufacturing exporter. Dropping these borderline cases (not shown) does not meaningfully change the estimates regarding volume elasticities.

Table 2.A.3.Export Volumes (Long-Run Elasticities) in Different Samples
Number of ObservationsNumber of CountriesRelative PriceIncome Effects
Baseline with time trend
Oil18690.160.86*
Non-oil310140.021.42**
Manufacturing51123–0.60**1.98***
Total1,00746
Shorter time period (1992–2005)
Oil11790.24***0.58
Non-oil169130.14**1.27**
Manufacturing31224–0.61***2.04***
Total59846
Source: IMF staff estimates.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

As to the inflation equation, it is generally argued that the pass-through effect from changes in the nominal exchange rate has declined over time. These pass-through effects are also influenced by high-inflation events, though to some extent the estimates in this chapter control for the latter by transforming the inflation rate and the change in the nominal exchange rate so that both lie in the interval (–100, 100) percent. As expected, Table 2.A.4 shows that pass-through effects are indeed smaller in recent years, declining from 0.35 to 0.21 in the short run and from 0.91 to 0.64 in the long run. The table also shows that excluding high-inflation cases (those with annual inflation rates of over 10 percent) results in slightly lower pass-through effects. It is also worth noting that fewer high-inflation cases exist post-1994 than is the case over the preceding 15 years: 20 percent of the observations after 1994 are high-inflation cases, compared to about 54 percent in the sample covering the 1980–1994 period.

The price equations discussed in this chapter do not control for a country’s exchange rate regime. Since a country with a fixed regime is likely to experience a smaller pass-through of exchange rate movements into domestic prices, this could in turn increase any improvement in the trade balance that would arise from a permanent nominal depreciation. Indeed, as shown in Table 2.A.5, a 10 percent depreciation would generate an improvement in the trade balance about 50 percent greater among countries with fixed regimes, compared with all countries (that is, those with flexible regimes as well as those with fixed regimes).

Table 2.A.4.Inflation Equation: Effect of a Change in Exchange Rates
Number of ObservationsShort RunLong Run
Period 1980–20051,0070.35***0.91***
Period 1995–2005 (baseline)5060.21***0.64***
Period 1980–2005 (low inflation only)16340.12**0.88***
Period 1995–2005 (low inflation only)14060.09**0.56***
Source: IMF staff estimates.Note: Specification mimics that of the equation estimated in Table 2.3.

Data with annual inflation rates of less than 10 percent.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level.

Source: IMF staff estimates.Note: Specification mimics that of the equation estimated in Table 2.3.

Data with annual inflation rates of less than 10 percent.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level.

The chapter also argues that pricing-to-market behavior applies to manufacturing exporters. But could this be influenced by the economic importance of some of the countries in the sample? Table 2.A.6 shows that the existence of pricing-to-market behavior remains a valid conclusion even if the five largest emerging market economies, all of which are manufacturing exporters, are excluded from the sample; the short- and long-run pricing-to-market coefficients are largely unchanged (0.89 and 0.87 in the long run and 0.58 and 0.53 in the short run). Moreover, as indicated in note 13, the volume of exports of manufactures does not respond to movements in the internal terms of trade because the export deflator relative to domestic prices (as measured by the CPI) has an insignificant negative coefficient (–0.08) when this variable is added to the specification in Table 2.1, but the coefficient on relative export prices remains stable and significant at–0.16. As was the case for the price equation, the results of the pricing-to-market equation (not shown) remain largely unchanged when (1) high-inflation cases are dropped or (2) the estimation period is 1995–2005.

Table 2.A.5.Impact on the Trade Balance of a 10 Percent Depreciation(In percent of GDP)
Commodity ExportersManufacturing Exporters
Short runLong runShort runLong run
Fixed- and flexible-regime countries1.61.80.31.6
Fixed-regime countries1.62.90.32.5
Table 2.A.6.Pricing Equation for Manufacturing Exporters for Different Samples
BaselineWith Five Largest Countries Dropped1
Coefficient estimatesLong-run elasticitiesCoefficient estimatesLong-run elasticities
Export deflator
First lag0.73***0.73***
Exchange rate in local currency per
U.S. dollar
Contemporaneous0.58***0.89***0.53***0.87***
First lag–0.34***–0.30***
Unit labor costs of competitors
Contemporaneous0.20**0.57***0.18**0.69***
First lag–0.050.01
CPI index (logs) (proxy for domestic costs)
Contemporaneous0.40***0.090.41***0.05
First lag–0.38***–0.40***
Change in per capita GDP (PPP terms)
Contemporaneous–0.06–0.12
First lag0.090.01
Output gap
First lag–0.010.07
Diagnostic statistics
Number of observations511396
Number of countries2318
R20.990.99
Tests
Hansen test14.1910.74
Arellano-Bond test for AR(1)–1.60–1.43
Arellano-Bond test for AR(2)–0.66–0.53
Source: IMF staff estimates.

China, Mexico, Korea, India, and Brazil—64 percent of total sample GDP in 2002.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.

China, Mexico, Korea, India, and Brazil—64 percent of total sample GDP in 2002.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Finally, the chapter assumes that pricing-to-market behavior does not apply to the imports of the emerging market economies. Implicitly, it is assumed that imports into these countries are so diversified that an exchange rate depreciation will translate into immediately higher import prices in domestic currency. Table 2.A.7 provides estimates for a basic form of price equation for imports. The estimation at left applies only to manufacturing exporters and the one at right to all countries in the sample. In both cases the evidence is quite overwhelming: pricing to market does not appear to apply to the imports of emerging market economies. In fact, the adjustment in the domestic price of imports is particularly rapid—both short- and long-run coefficients are 1. Adding foreign labor costs yields similar results regarding the reaction of import prices in domestic currency to a change in exchange rates.

Table 2.A.7.Pricing Equation for Imports
Manufacturing ExportersAll Countries in Sample
Coefficient estimatesLong-run elasticitiesCoefficient estimatesLong-run elasticities
Import deflator
First lag0.77***0.76***
Exchange rate in local currency per U.S. dollar
Contemporaneous0.97***0.99***0.97***1.01***
First lag–0.73***–0.73***
Diagnostic statistics
Number of observations5111,007
Number of countries2346
Tests
Hansen test21.2945.24
Arellano-Bond test for AR(1)–2.17**–3.38***
Arellano-Bond test for AR(2)–0.85–0.21
Source: IMF staff estimates.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Source: IMF staff estimates.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level; estimation with intercept.

Appendix 2.5 Estimation Procedures

This appendix discusses alternative estimation methods and the robustness of the chapter’s main findings.

Arellano-Bond Estimator

The baseline specification is estimated using the Blundell and Bond (1998) generalized methods of moments system estimator, which is a refinement of the earlier Arellano and Bond (1991) estimator and exploits the fact that the number of cross-sectional units (countries) is large relative to the number of time periods. Under these conditions, the estimators satisfy asymptotic properties of normality and stationarity.

Since the price and volume series used in this chapter are persistent, they are assumed to follow an AR(1) model. An unobserved unit-specific time-invariant effect that is stochastic allows for heterogeneity across countries. Although the disturbances are assumed to be uncorrelated across countries, they are likely correlated with the lagged dependent variable, requiring the use of first differences to eliminate this effect. Controlling for the serial correlation induced by first-differencing requires instruments that are lagged one additional period because of the dependence of the differenced error term on its lagged value. Therefore, variables that could be considered endogenous, such as the relative price terms in the volume equations, are estimated with lags of two periods. Since the first-differenced error term has a first-order moving representation of serial correlation, the generalized method of moments estimator provides a framework for correcting for this bias and hence obtaining efficient coefficient estimates.25

Although the equations are estimated in level terms, they can be rewritten in terms of changes and lagged levels to derive short-run and long-run elasticities. For example, take a generic equation expressed in levels with one lagged dependent term and a contemporaneous and lagged exogenous term:

This equation can be transformed into the following representation:

In this case the short-run elasticity of X with respect to Y is δ0, and the long-run elasticity is (δ0 + δ1)/(1–β).

These elasticities are calculated in each of the estimated equations and allow for comparability with the estimates derived from the two estimators discussed in the next two subsections.

Mean Group and Pooled Mean Group Estimators

As the time-series dimension of the data increases, alternative estimators based on cointegration tests are commonly used. Therefore, to confirm the validity of the baseline specification estimates presented in the chapter, estimates are also obtained from two alternative estimators. The first estimator—the mean group estimator—was proposed by Pesaran and Smith (1995) and consists of estimating separate autoregressive distributed lag models for each country in which dependent and independent variables enter on the right-hand side. The MG estimator then derives the full-panel estimates as simple averages of individual country coefficients. The second estimator recognizes that the long-run response of the dependent variable to exchange rate changes might be the same across countries, and Pesaran, Shin, and Smith (1999) propose a maximum-likelihood-based estimator referred to as “pooled mean group” that pools the individual long-run regression coefficients. The existence of the required cross-sectional long-run homogeneity—and hence the suitability of the PMG estimator—can be tested using a Hausman-type statistic (the h-statistic).

Mean Group and Pooled Mean Group Estimates

To conserve degrees of freedom while allowing for reasonably rich dynamics, the number of lags used to obtain the MG and PMG estimates is set to a maximum of two. The estimation period is 1980–2005 for all the countries in the sample.

The results for the oil-exporting group are consistent with the prior that the supply of oil exports is fairly inelastic in terms of price, since the price elasticity estimates vary only between 0.25 and 0.43 (see Table 2.A.8). By the same token, the volume elasticity of oil exports to world income is very low at 0.35 using the PMG estimator, suggesting that the supply of oil is not particularly sensitive to income developments. This contrasts with the results for non-oil commodity exports, which display considerably greater sensitivity to world income growth and lower sensitivity to price changes.

Table 2.A.8.Trade Elasticities and Estimation Methodologies
Oil Exporters (Supply)Non-oil Commodity Exporters (Supply)Manufacturing Exporters (Demand)Import Demand (All Countries)
System generalized method of moments (Tables 2.1 and 2.4)
Long-run price elasticities0.250.21–0.83**–0.43***
Long-run income elasticities10.93***2.45***2.10***1.55***
Number of observations186310511824
Mean group estimator (Pesaran and Smith, 1995)
Long-run price elasticities0.240.160.30–0.73
Long-run income elasticities10.961.984.96***2.13***
Number of observations2673306021,177
Pooled mean group estimator (Pesaran, Shin, and Smith, 1999)
Long-run price elasticities0.43***0.28***0.59–0.56***
Long-run income elasticities10.35***2.21***2.11***1.70***
Number of observations1923306021,177
Source: IMF staff estimates.

Note: Demand equation for system GMM and supply equation for group estimators are presented.

Real GDP of trading partners for all export equations and domestic real GDP for the import equation.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level.

Source: IMF staff estimates.

Note: Demand equation for system GMM and supply equation for group estimators are presented.

Real GDP of trading partners for all export equations and domestic real GDP for the import equation.

significant at 10 percent level;

significant at 5 percent level;

significant at 1 percent level.

Exports of manufactures have the greatest sensitivity to trading partners’ income. Moreover, the h-statistic for this variable rejects the long-run cross-country homogeneity assumption, indicating considerable cross-country heterogeneity in the way manufacturing exports respond to changes in trading partners’ income. If the cross-country homogeneity restriction is relaxed (in other words, if the focus is shifted to the MG estimator), the estimates indicate no significant response of export volumes to relative price movements (that is, a statistically nonsignificant long-run price elasticity of 0.30). Although the long-run price elasticity of export volumes using the Arellano-Bond procedure is significantly negative (about–0.83), the price elasticity estimate excludes pass-through effects that, when included, result in a long-run volume response to a currency depreciation of only 0.01. In other words, both the MG estimator and the Arellano-Bond estimator suggest that the long-run volume response is small. This weak response might reflect the large costs of moving into and out of export markets.

Regarding the import equation, the estimates overwhelmingly point to a highly significant income elasticity of imports in the range of 1.6 to 2.1. A low h-statistic value indicates that the long-run slope homogeneity assumption cannot be rejected; that is, the PMG estimator is preferred to the MG estimator. This points to a relative price elasticity of–0.56 and an income elasticity of 1.70, very close to the estimates obtained using the Arellano-Bond procedure—respectively,–0.43 and 1.55.

In sum, the results from the three estimators indicate that these estimates are robust to alternative assumptions about the importance of the time-series component of the data. They show that, generally, imports are more sensitive to relative price movements than exports of manufactures and that the latter respond strongly to movements in foreign income. Moreover, the long-run effect of a depreciation is quite similar. In this regard, Table 2.A.9 indicates that a 1 percentage point depreciation leads to an improvement of slightly more than one-half percentage point in the trade balance for manufacturing exporters starting from a position of balanced trade; both the Arellano-Bond and PMG estimators provide similar results. For oil and non-oil exporters, the improvement is stronger when the PGM estimator is used—averaging 0.84—because of the higher estimated long-run export supply price elasticities, but the difference between the results obtained using the two estimators is small, averaging about 0.15 percent.

Table 2.A.9.Long-Run Effects of Devaluations on Export-Import Values and on the Trade Balance (in Foreign Currency) for Different Classes of Exporters(Percent change for a depreciation of 1 percent)
Oil ExportersNon-oil Commodity ExportersManufacturing Exporters
Estimates using the Arellano-Bond estimator0.700.680.57
Estimates using the pooled mean group estimator0.880.810.59
Source: IMF staff estimates.Note: Initial trade balance equal to zero with elasticity defined as η = (dTB/xval)/(de/e).
Source: IMF staff estimates.Note: Initial trade balance equal to zero with elasticity defined as η = (dTB/xval)/(de/e).
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We wish to thank Mark Allen, Carlo Cottarelli, Andy Rose, and colleagues at the IMF for comments received on an earlier version of this chapter. Research assistance was provided by Olivia Carolin, Barbara Dabrowska, and Sibabrata Das.

1

The effect of exchange rate changes on factor services and transfers, which would need to be added to the analysis to fully assess the role of exchange rate changes in external adjustment, is not examined in this chapter.

2

To allow for a zero trade balance, elasticities are defined as η = (dTB/xval)/(de/e). Hence dTB/GDP (xval/GDP) x h x (de/e) = 0.35 x 0.70 x 0.1 = 0.0245.

3

This effect is likely to be smaller among nonrenewable resources. However, even in the case of commodities such as oil, a positive supply response might occur as some oil reserves that were previously uneconomical to extract become profitable at higher relative prices.

4

The export demand function and the pricing equation together determine manufactures exporters’ profitability, which may have longer-term implications for the supply of exports, which are not fully captured here. For instance, following an exchange rate appreciation, if exporters maintain the domestic currency price, the exchange rate appreciation will translate into a higher foreign currency price, reducing demand, and thus revenues and profits—if there are fixed costs, profitability will fall as well. If exporters wish to maintain market share, they need to lower the domestic currency price of exports, partially offsetting the exchange rate impact. But their ability to lower prices would depend on what happens to their costs (for instance, imported inputs—proxied by the exchange rate—and domestic costs, proxied by the CPI). Over time, the reduced profitability may lead to firms’ exiting, further lowering exports. This last effect is difficult to capture empirically, however, as noted later in the chapter.

5

The effect on the local currency value of imports is ambiguous, as the higher price might outweigh the lower volume. It is this ambiguity that gives rise to the traditional Marshall-Lerner condition, which is the condition under which a devaluation will improve the domestic currency value of the trade balance.

6

Ideally, estimation of the impact of exchange rate changes on aggregate demand would take full account of the local and foreign currency components of household wealth (including net foreign asset positions, housing wealth, and stock market valuation); in practice, only crude proxies are available.

7

On the other hand, transition economies are excluded because of the significant structural changes they experienced during the 1990s and because their trade patterns prior to transition were dominated by administrative trading arrangements among members of the Council for Mutual Economic Assistance.

8

The dominant export category is obtained from the export classification over the period 1980–2005, and the country grouping may differ from the current World Economic Outlook classification. Robustness tests (reported in Appendix 2.4) show that elasticities estimated for the period 1992–2005 based on trade shares over that period yield results broadly similar to those presented in the main body of this chapter. Although nonfactor services are included in the econometric analysis, they are grouped with the principal goods export category, which may be problematic in cases in which services represent a large fraction of exports (for example, Jamaica). It is worth noting, however, that excluding Jamaica and other countries that are borderline in their classification does not change the chapter’s main conclusions. Also, it would be preferable to exclude reexports from the data for manufacturing exporters; for example, the calculations in note 2 are based on the assumption of an export-to-GDP ratio of 35 percent. If reexports are important, the effective export ratio—and thus the impact of an exchange rate movement on the trade balance—will be correspondingly smaller.

9

Treating import prices as exogenous is supported by estimation results presented in Appendix 2.4; specifically, both the short- and long-run import price elasticities with respect to the nominal exchange rate are very close to unity.

10

Most export functions estimations do not distinguish between the class of goods exports; see Senhadji and Montenegro (1999) for country-specific estimates of export elasticities.

11

The asymptotic bias of the estimator being used is less than that of fixed-effects estimators (Alonso-Borrego and Arellano, 1999), and even in the presence of unit roots, the estimator has very small biases (Binder, Hsiao, and Pesaran, 2005).

12

Inclusion of the export price relative to the CPI (to capture resource shifts from the nontraded goods sector) yields a statistically insignificant negative coefficient, in contrast to the positive coefficient that would normally result from a supply response (see Appendix 2.4). The pricing equation, however, does include the CPI as a proxy for domestic costs and the price of nontraded goods. Limiting the sample to the 1992–2005 period to allow for increased competition in manufactures has no effect on the coefficient estimates.

13

Although the assumption of pricing to market is more plausible for large emerging market countries, excluding these countries has no effect on the coefficient estimates (see Table 2.A.6).

14

The results in Table 2.3 are based on the post-1994 sample (rather than the period 1980–2005) because of a common finding in the literature that exchange rate pass-through to consumer prices has declined in recent years. This is confirmed here; estimation on the full (1980–2005) sample yields an immediate pass-through of 0.36 percent and a long-run pass-through of 0.91 percent, compared to 0.21 percent and 0.64 percent for the post-1994 sample. The post-1994 period also eliminates most episodes of hyperinflation. Inflation rates are transformed by π = π/(1 + π), so that they lie in the interval (–100, 100), in order to reduce the effect of outliers, and an estimation excluding annual inflation rates higher than 10 percent provides similar results (see Table 2.A.4).

15

If exports of manufactures have a high import content, the pass-through effect is likely to be even smaller, because the depreciation will raise costs by more than the increase in the CPI.

16

Particularly for nonrenewable commodities, a small supply elasticity is to be expected.

17

Although imports could also be split according to import category, the assumption made here is that imports are much more diversified than exports.

18

Support for this view is provided in Becker and Mauro (2006) and Frankel (2005).

19

Defining the interactive dummy for balance sheet effects to reflect countries that have both (1) gross external debt ratios of more than 40 percent of GDP and (2) negative net foreign asset positions (based on the Lane and Milesi-Ferretti [2006] database) leads to very similar results.

20

The effect of the increase in the CPI on real income is excluded here because nominal income would also likely be affected by the depreciation. Simply assuming that the increase in the CPI would lead to a corresponding reduction in real disposable income would likely overestimate the impact of the exchange rate depreciation.

21

As previously noted, this assumption is supported by the evidence that, among emerging markets, both the short- and long-run import price elasticities with respect to the nominal exchange rate are very close to unity (see Table 2.A.7). This contrasts with estimates as low as 0.2 among G-7 countries (see Appendix 2.1).

22

References to earlier research, including an influential methodological critique by Orcutt (1950), can be found in Goldstein and Khan’s (1985) review.

23

A variety of measures have been used to proxy relative prices of imports and exports. Houthakker and Magee (1969) define the relative price of imports as the ratio of the price index of imports into a given country to the country’s wholesale price index and the relative price of exports as the ratio of the price index of a country’s (real) exports to the export price index of the other exporting countries. Reinhart (1994) uses a simple ratio of import unit values (in domestic currency) to CPI and export unit values deflated by industrial countries’ consumer prices (in U.S. dollars). Senhadji (1998) uses the ratio of the import deflator to the GDP deflator as a measure of the relative price of imports, and Senhadji and Montenegro (1999) define the relative price of exports as the export price of the home country relative to the price of its competitors.

24

On empirical evidence for the Marshall-Lerner condition, see Rose and Yellen (1989).

25

In terms of specification tests, while the first-differenced error term has first-order serial correlation, it should not be subject to second-order serial correlation; this hypothesis is tested following the methodology proposed by Bond and Windmeijer (2002). With more than three periods, the model is overidentified, and the general method of moments test for overidentifying restrictions can be used to ascertain the number of instruments; it should be noted, however, that this test loses statistical power as the number of time-series data points increases (Bowsher, 2002).

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