Chapter 4 Do Financial Crises Have Lasting Effects On Trade?
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International Monetary Fund. Research Dept.
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English
Print Publication Date:
06 Oct 2010
Keywords:
WEO; exchange rate; debt; labor market; fiscal policy; advanced economy; deficit; economy; spending cut; trade dynamics; crisis economy; partner output; trade protectionism; crisis trade dynamics; Exports; Trade balance; Banking crises; Global
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Abstract

This chapter looks at trade dynamics following banking and debt crises, to help us understand how trade might evolve for economies recently affected by such crises. Imports of the crisis economy tend to fall substantially in the short term—beyond what would be expected from the decline in output—and they stay depressed through the medium term. In contrast, exports of the crisis economy are not as badly affected. These findings suggest that the recovery of import demand in the United States and much of western Europe may be even more anemic than suggested by their relatively weak projected output recoveries. Thus, the narrowing of the large current account deficits of some crisis countries such as the United States that occurred in 2009 may prove to be quite durable. For economies that experience a crisis, the chapter underscores the importance of embracing structural reforms to help support the recovery of output and trade. For economies that rely heavily on external demand for their growth, the chapter’s findings highlight the urgency of reorienting growth by strengthening domestic demand.

One of the most notable features of the Great Recession was the “sudden, severe, and synchronized” collapse in trade in late 2008 and early 2009 (Baldwin, 2009). In the half-year encompassing the last quarter of 2008 and the first quarter of 2009, the annualized drop in world imports was more than 30 percent, with roughly equal declines experienced by advanced and emerging economies (Figure 4.1). The fall in trade spared no one—all economies experienced a drop in both exports and imports during this period. Likewise, growth in trade in virtually all product categories went from positive in the second quarter of 2008 to negative by the first quarter of 2009.

Figure 4.1.
Figure 4.1.

The Great Trade Collapse

The collapse in world trade in late 2008 and early 2009 was sudden, severe, and synchronized.

Sources: CPB Netherlands Bureau of Economic Policy Analysis; and IMF staff calculations.

The rapid recovery in trade that began in the second half of 2009 has been remarkable as well. World imports grew at an annualized rate of more than 20 percent in the last two quarters of 2009 and the first quarter of 2010. However, as this chapter shows, trade remains below its precrisis trend, and for some economies—particularly those hit by a banking crisis—it remains below precrisis levels. Because the recent crises occurred in large, advanced economies that account for a substantial portion of global demand, the speed and extent of their trade recovery will affect the growth prospects not only of the crisis economies but also of their trading partners.

This chapter looks at trade dynamics following banking and debt crises, to help us understand how trade might evolve for economies that are affected by such crises. It continues the research agenda pursued in recent issues of the World Economic Outlook to analyze the medium-term macroeconomic consequences of crises. This chapter addresses the following questions:

  • To what extent has trade recovered from the recent global recession? Have the speed and extent of the recovery differed among economies, particularly between those that suffered a banking crisis and those that did not? Has the recovery varied across different product groups?

  • How has trade behaved in the wake of previous banking and debt crises? Do such crises have lasting effects on trade?

  • What factors apart from the level of output are associated with sharp declines in trade following a crisis? And what role can postcrisis policies and conditions play in enhancing the recovery of trade?

  • What are the implications for the recovery of trade from the recent crisis? And what lessons can be drawn for the future?

Much of the recent literature on trade and crises has focused on the recent global downturn and specifically on explaining the “Great Trade Collapse”—that is, on why world trade fell by much more than GDP.1 Only a few papers have looked at the full dynamics of trade—both declines and recoveries—following earlier crises. Among these, Freund (2009) describes the evolution of world trade following four previous global downturns. She finds that the size of the decline in world trade during these episodes is almost five times the corresponding decline in world GDP. She also finds that, while world trade growth resumes quickly following a global downturn, it takes more than three years for trade to reach predownturn levels. This chapter does not focus on trade dynamics following global downturns but instead on what happens to the trade of individual economies that experience a banking or debt crisis; it should thus be seen as a complement to Freund’s work.2

This chapter uses a methodology derived from the “gravity model,” the standard workhorse for modeling trade flows. The gravity model is widely used to explain the level of bilateral trade flows on the basis of individual characteristics of each partner (size and level of economic development) as well as the characteristics of the country pair (distance between them and whether they share a common border, language, or currency). However, the standard gravity model best describes patterns of trade between economies rather than over time and therefore may not provide an accurate picture of what happens to aggregate trade for a particular economy in the aftermath of a crisis. This chapter therefore uses a “collapsed” version of the gravity model, estimated in differences, that analyzes changes in aggregate trade flows.3 We examine episodes of banking and debt crises over the past 40 years and track the changes in imports and exports both to estimate the overall trade declines and to measure the association of various factors such as output and exchange rate dynamics with the postcrisis behavior of trade.

The main findings of the chapter are as follows:

  • There is a sharp decline in an economy’s imports following a crisis—16 percent, on average—and this decline is persistent, with imports remaining below normal (that is, below their predicted level in the absence of a crisis) even over the medium term. Depressed output does not explain the entire decline in postcrisis imports.

  • Exports of the crisis economy are not as adversely affected. There is a small and gradual decline in exports, so that, in the medium term, exports are on average about 8 percent below their predicted level in the absence of a crisis. And unlike for imports, all of the export decline can be explained by adverse output dynamics; after controlling for output declines, export performance is no different from normal.

  • Weak output remains the most important factor in the decline of imports in both the short and the medium term, but other factors also play a role. In particular, impaired credit conditions are associated with a weaker recovery in imports (above and beyond the impact of weak credit on output), especially in the medium term. In the short term, increased exchange rate volatility and currency depreciation are associated with import losses. There is no evidence that tariffs and antidumping measures rise, on average, during crisis periods. There is also evidence to suggest that “the composition effect” can account for at least a portion of postcrisis import losses: during crises, demand falls primarily in products that comprise a larger share of trade than of output, such as durables.

  • Pre- and postcrisis conditions and policies affect the behavior of trade following a crisis. Import losses tend to be greater for economies entering a crisis with a relatively weak current account position—suggesting that external imbalances tend to diminish following a crisis. Imports also fare worse when the crisis is accompanied by greater currency depreciation and exchange rate volatility, relatively weaker credit conditions, and larger increases in protectionism.

These findings suggest that the full recovery of import demand in countries that recently suffered a banking crisis—including the United States and the United Kingdom—may be even more protracted than suggested by their relatively slow projected output recovery. Thus, the narrowing of the large current account deficits in some crisis countries such as the United States that occurred in 2009 may prove to be quite durable. For economies that experience a crisis, the chapter underscores the importance of embracing structural reforms to help support the recovery of output and trade. For economies that rely heavily on demand from those countries for their growth, the chapter’s findings highlight the urgency of rebalancing growth by strengthening domestic demand.

It is important to emphasize from the outset that this chapter seeks to identify patterns and correlations rather than to establish causality between various policies and initial conditions on one hand and postcrisis trade dynamics on the other. Many of the variables we explore, including credit and the exchange rate, are likely to be simultaneously determined with trade. For example, do adverse credit conditions in the aftermath of a crisis hinder trade finance and reduce trade flows? Or are weak credit and anemic trade both manifestations of depressed postcrisis economic conditions? Sorting out these possibilities is beyond the scope of this chapter.

The remainder of the chapter is structured as follows. The first section describes the behavior of trade following the recent global downturn, documenting both the collapse in trade and the recovery to date, and exploring differences across economies and product categories. The second section uses a regression framework to analyze earlier crisis episodes, providing estimates of the size of import and export losses in both the short and medium term. The third section examines the extent to which postcrisis import dynamics are associated with various factors such as credit, protection, and exchange rate dynamics. The fourth section discusses implications for the global economic outlook.

Has Trade Recovered?

As noted above, the collapse in trade between late 2008 and early 2009 was quite severe. The annualized quarter-over-quarter drop in global real GDP in the last quarter of 2008 and the first quarter of 2009 averaged just under 6 percent, but the drop in global real imports was five times as large, averaging over 30 percent (Figure 4.2, top panel). The emerging consensus is that much of the outsize decline in trade can be explained by the “composition effect.” That is, the increased uncertainty following the bankruptcy of Lehman Brothers in September 2008 and the subsequent freezing of credit markets led to a collapse in demand for “postponable” items such as capital goods and consumer durables. And because those items account for a much larger share of trade than of GDP, the former fell by much more than the latter.4 Box 4.1 discusses the role of the composition effect and vertical linkages—the use of imported intermediate goods to produce exports—in the recent trade collapse.

Figure 4.2.
Figure 4.2.

The Recovery in Trade

Growth in world trade is now above precrisis rates. But trade has not fully recovered, with substantial differences between economies that had a financial crisis and those that did not.

Sources: CPB Netherlands Bureau of Economic Policy Analysis; Haver Analytics; IMF, Direction of Trade Statistics; and IMF staff calculations.Note: The precrisis linear trend, denoted by the dashed line, is based on data between January 2001 and December 2007.

The Role of the Composition Effect and Intermediate Goods in the Great Trade Collapse

The Great Recession was accompanied by a collapse in global trade. This box documents the role of two sets of forces in the trade collapse.1 The first is the “composition effect” and its contribution to the outsize decline in global trade relative to GDP. The second is the extent to which trade in intermediate goods made global trade more or less resilient to the global recession.

The focus on these two forces is motivated by two key facts:

  • The contraction in final demand during the recent crisis was asymmetric across sectors, with demand for durables falling by considerably more than demand for nondurables or services. For example, demand for durables in the United States and the European Union fell by more than 30 percent and 20 percent, respectively, whereas demand for nondurables and services fell by only 1 to 3 percent (first figure, top panel).2 Because durable goods have a larger weight in trade flows than in final demand (bottom panel), the asymmetrical changes in demand across sectors caused global trade to fall by more than aggregate demand.

  • Two-thirds of global trade comprises intermediate inputs to production rather than final goods, and these two categories respond differently to a contraction in final demand. Intermediate goods are linked only indirectly to final demand, whereas final goods are linked directly. In addition, durables, nondurables, and services have different weights in overall trade flows for final and intermediate goods.

We use a multicountry, three-sector (durables, nondurables, services) framework to compute the relative contributions of these two factors to the collapse in global trade during 2008–09. Our framework combines information from national input-output matrices with detailed data on bilateral trade flows for both intermediate and final goods to establish various interrelationships—for example, the extent to which durable goods imported from Mexico into the United States are used to produce services that are subsequently exported to Canada.3

uch04fig01

Ingredients of the Composition Effect

Source: Bems, Johnson, and Yi (forthcoming).1 EU15: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom.2 Data based on the most recent national input-output tables, which for most economies cover the post-2000 period.
uch04fig02

Elasticity of Global Trade to GDP1

Source: Bems, Johnson, and Yi (forthcoming).1 Data refer to 2009:Q1/2008:Q1. One-sector and two-sector models use the same change in final demand as the three-sector model but impose restrictions on its distribution across sectors. The two-sector model restricts the demand change to be equal for durables and nondurables. The one-sector model restricts the change to be equal for durables, nondurables, and services.

In this framework, changes in final demand shape trade flows through two channels: (1) Imports of final goods change proportionally to domestic final demand within each sector. (2) Imports of intermediate goods change proportion-ally to gross production within each sector, which itself responds to changes in final demand at home and abroad. If final demand changes symmetrically across sectors, then trade flows are proportional to aggregate production and GDP. However, with asymmetrical demand changes, this proportionality does not hold.

How Important Was the Composition Effect?

To estimate the size of the composition effect, we calculate how much output and trade would fall under our framework given the observed sector-specific final demand changes in the United States, the European Union, and the rest of the world. We then compare the simulated response of trade and output to what actually happened during the Great Recession. Our framework estimates a fall in global trade that exceeds the fall in global GDP by a factor of 2.8, explaining more than 70 percent of the observed trade elasticity in the data (second figure). For comparison, a more restrictive, two-sector framework with the same size demand changes for durables and nondurables accounts for 60 percent of the collapse; and a one-sector framework, which eliminates all composition effects, generates a fall in trade that is roughly proportional to GDP.

These results are consistent with other recent efforts to quantify composition effects. Eaton and others (2010) find that asymmetrical demand changes account for 80 percent of the global decline in the trade-to-GDP ratio during the crisis in a three-sector Ricardian trade frame-work. Levchenko, Lewis, and Tesar (forthcoming) report that, for the U.S. economy, sectors with larger reductions in domestic output had larger drops in trade.

How Important Was Trade in Intermediate Goods?

To gauge the role of intermediate goods trade in the crisis, we compare the responses of trade in intermediate and final goods to crisis-induced changes in final demand. As noted, both intermediate and final goods trade would respond proportionally to demand changes that were symmetric across sectors. With asymmetrical demand changes and given the assumptions of our framework, the response of trade in final goods depends on the size of sectoral demand asymmetries and sectoral trade weights, whereas the response of trade in intermediate goods depends on the size of sectoral supply asymmetries and sectoral trade weights. All the necessary ingredients for the estimation are obtained from the framework.

Simulations show that trade in intermediate goods was more resilient to the decline in final demand during the recent global downturn. The relative resilience of trade in intermediates to observed changes in final demand can be explained by two factors:

  • The sectoral asymmetries for changes in gross production (derived from our framework) are smaller than the observed sectoral asymmetries in final demand (third figure, top panel).4

  • Durables have a smaller weight in intermediate goods trade relative to their weight in final goods trade (bottom panel).

The differences in the responses of trade in intermediate and final goods are quantitatively large. The elasticity of global trade in final goods to GDP is estimated at 4.3, whereas the same elasticity for trade in intermediates is 2.0. These results are broadly consistent with the chapter’s finding that, in crisis episodes, trading partners with greater production sharing show smaller declines in exports to the crisis economy.

uch04fig03

The Composition Effect for Trade in Final Goods and Intermediates

Source: Bems, Johnson, and Yi (forthcoming).1 Sectoral demand contraction based on data. Sectoral contraction in gross production are model-based estimates.2 Data based on the most recent national input-output tables, which for most economies cover the post-2000 period.
The authors of this box are Rudolfs Bems, Robert C. Johnson, and Kei-Mu Yi. 1 The discussion is based on Bems, Johnson, and Yi (forthcoming). 2 The United States and European Union together account for more than half of global demand and are representative of the observed sectoral demand contraction in the rest of the world. 3 See Johnson and Noguera (2010) for details. The frame-work is parameterized by combining national input-output tables with bilateral trade data, both obtained from the Global Trade Analysis Project. 4 This result follows from the observation that services constitute a relatively large input in the production of durables and, as a result, a contraction in final demand for durables can significantly decrease the gross production of services.

The recovery in world trade began in the second half of 2009 and appears quite strong: the annualized growth in world real imports in the last two quarters of 2009 and the first quarter of 2010 was over 20 percent. So has trade fully recovered? Unfortunately, it has not, and the extent of the recovery differs substantially across economies and across products. An important distinction across economies seems to be whether an economy recently went through a banking crisis.5 In economies that avoided a crisis, imports are just slightly below the precrisis peak reached in the second quarter of 2008, although this still leaves them almost 15 percent below a simple extrapolation of the 2001–07 precrisis trend (Figure 4.2, middle panels).6 In contrast, imports in the crisis economies remain more than 20 percent below their precrisis levels and almost 40 percent below their precrisis trend. Because the crisis economies include the United States and much of western Europe, which account for a sizable portion of global import demand, exports remain substantially below trend for crisis and noncrisis economies alike (Figure 4.2, bottom panels). In both sets of economies, exports remain about 25 to 30 percent below precrisis trends.

The extent of the recovery has also differed across various product categories. Among the four categories shown in Figure 4.3, consumer nondurables declined the least during the collapse, and the subsequent recovery has brought trade in these products almost completely back to its precrisis trend. Primary goods (a category that includes commodities and that went through a boom just prior to the crisis) and intermediate goods both experienced sharp declines, but both are less than 10 percent below their precrisis trend. In contrast, and as mentioned earlier, the largest collapse was in capital and consumer durables, and while there has been some recovery, trade in that product category still remains almost 20 percent below its precrisis trend.

Figure 4.3.
Figure 4.3.

Trade Dynamics in Different Product Groups

(Trade volume index, 2008:Q1 = 100)

Sources: Global Trade Atlas; and IMF staff calculations.Note: The precrisis linear trend is based on data between January 2001 and December 2007. Data only cover imports of the following: Argentina, Australia, Brazil, Canada, China, Japan, Korea, Russia, South Africa, Turkey, and United States.

In sum, while the global trade collapse spared no one, import dynamics were particularly adverse for economies that went through a banking crisis. And while the recovery in trade has commenced, it is highly uneven, with imports of crisis economies still substantially below precrisis trends or even precrisis levels. Finally, among product groups, capital and consumer durables remain farthest from closing the gap. Are these just transitory deviations from normal, or might these gaps persist? Where might trade be headed from here? The following section examines the historical record for some clues.

Trade Dynamics Following Previous Crises

The global reach and scale of the recent financial crisis have few precedents, but history is replete with individual economies experiencing either a banking or a debt crisis. Laeven and Valencia (2008, 2010), whose crisis dates are used in this chapter, identify 129 episodes of systemic banking crises since 1970—defined as situations in which the financial sector experiences a large number of defaults, nonperforming loans increase sharply, and all or most of the aggregate banking system capital is used up. They also identify 63 episodes of sovereign debt crises over the same period—defined as an episode of sovereign debt default and/or restructuring.7 We focus here on banking and sovereign debt crises because the most recent crises in the large advanced economies have been systemic banking crises and because the prospect of a sovereign debt crisis in a number of economies has been increasing. The chapter does not focus on currency crises, because trade dynamics following such crises are fundamentally different—the most important characteristic of currency crises is, by definition, a large exchange rate decline, which greatly influences the postcrisis dynamics of both imports and exports. In addition, large and abrupt depreciations did not characterize the most recent financial crises in advanced economies. Nevertheless, in this analysis we investigate the role of the exchange rate—changes in both its level and its volatility—in influencing the behavior of trade following banking and debt crises.

Our methodology for analyzing postcrisis trade is derived from the gravity model, the standard work-horse in the empirical trade literature.8 The gravity model relates the level of bilateral trade flows—or alternatively, import and export flows separately—to characteristics of the importing and exporting economies (most notably size and level of development) as well as to country-pair characteristics such as distance between them and whether they share a common border or language. These and other time-invariant country-pair characteristics can also be controlled for by the inclusion of country-pair dummy variables. The gravity model has been in use since the 1960s, and its popularity has derived in large part from its ability to empirically fit the trade data, that is, to describe what normal bilateral trade flows should be, given economies’ fundamentals. The literature has used this framework to investigate a number of questions, including the impact of trade agreements (Frankel, Stein, and Wei, 1996), currency unions (Rose, 2000), exchange rate volatility (Thursby and Thursby, 1987), and war (Glick and Taylor, 2010; and Martin, Mayer, and Thoenig, 2008). The use of the gravity model has also been supported by recent attempts to strengthen its theoretical microfoundations (see Anderson and Van Wincoop, 2003, among others).

The approach taken in this paper is a collapsed version of the gravity model that uses aggregate imports or exports of a given economy rather than bilateral trade flows. This is done because our primary concern is in describing the evolution of aggregate trade, not bilateral trade. And the model is estimated in growth rates rather than in levels to better model the dynamics of trade over time. The results are robust to estimating the standard bilateral gravity model in changes as well as to other changes in specification. (Appendix 4.2 outlines the econometric specifications used and the robustness of the main results to alternative econometric specifications.)

Our sample consists of 154 advanced as well as emerging and developing economies covering the period 1970–2009. Bilateral and aggregate import and export flows for each economy are obtained from the IMF’s Direction of Trade Statistics (DOTS) database. We also extend the NBER-UN World Trade Flows database (Feenstra and others, 2005) to analyze trade patterns by product category. (Data sources are outlined in Appendix 4.1.) Growth in aggregate imports and exports is then modeled as a function of contemporaneous and lagged values of a crisis dummy variable, changes in economic fundamentals (primarily economic size, as proxied by GDP), and changes in the (import-or export-weighted) characteristics of its trading partners.9 To control for economies’ characteristics that do not change over time, country dummies are also included. Finally, all our specifications include time dummies to control for factors that affect all economies’ trade simultaneously, such as global downturns or increases in global uncertainty or risk aversion.

What Happens to Imports and Exports after a Crisis?

We first estimate the unconditional behavior of an economy’s imports and exports—that is, without controlling for output—to gauge the extent to which trade is affected in the aftermath of a crisis. On average, imports fall by about 8 percent in the crisis year (Figure 4.4, top-left panel; Table 4.1). An additional drop of about 8 percent occurs the following year. There is little sign of recovery in subsequent years, so that by the fifth year after the crisis, imports remain about 19 percent below their level predicted in the absence of a crisis. Tat pattern—a sharp short-term drop in imports followed by little or no recovery in the medium term—is also evident when looking at debt crises and banking crises separately, although medium-term effects are more adverse for the former (Figure 4.4, middle-left and bottom-left panels). The differences in import dynamics between the two types of crisis are not statistically significant, however.

Figure 4.4.
Figure 4.4.

Import and Export Losses, Not Controlling for Output

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Blue lines indicate the impulse response function – the effect of a crisis on imports and exports relative to what would be predicted in the absence of a crisis. Predictions are based on contemporaneous and lagged crises, and country and time dummies.
Table 4.1.

Baseline Regressions and Implied Changes in the Levels of Imports and Exports

article image
Source: IMF staff calculations. Note: The table presents the results of regressing the growth in imports/exports on an indicator for crisis and its five lags, country, and year fixed effects. Robust standard errors clustered by country are reported in parentheses. ***, **, and * indicate significance at the 1, 5, and 10 percent level, respectively. Columns (3) and (7) control for own and partner growth in GDP, and for measures of trade-weighted crises in partner countries and their lags. The implied changes in the levels of imports/exports in columns (2), (4), (6), and (8) are calculated as the cumulative sum of the estimated coefficients on the crisis indicator and its lags from the regressions shown in columns (1), (3), (5), and (7), respectively.

Impulse response function.

The effect on exports is smaller and more gradual (Figure 4.4, top-right panel). There is no sharp drop in exports in the short term; exports drop by only 3 percent on average at the onset of a crisis. There is, however, a gradual deterioration in exports, so that by the fifth year after a crisis, exports are on average about 8 percent lower than normal, and the difference is marginally significant. The smaller decline in exports relative to imports implies that, on average, the external trade balance tends to improve after a crisis. Similar patterns of gradual export decline are observed for debt and banking crises separately, although the variation in export losses is larger following debt crises (Figure 4.4, middle-right and bottom-right panels). As was the case for imports, the differences in export dynamics between the two types of crisis are not statistically significant, and in the subsequent analysis we simply look at banking and debt crises together.10

These results are robust to the use of a number of alternative methodologies for estimating losses. The first and simplest methodology for calculating losses, adopted from Chapter 4 of the October 2009 World Economic Outlook, looks at deviations of imports and exports from a precrisis trend. A second robustness test is to include autoregressive terms in the estimation to more closely parallel the specification used in studies such as Romer and Romer (2010) and Cerra and Saxena (2008). Third, the full bilateral gravity model in changes is estimated, using both the full sample and the top 20 partners of each country. Finally, to address the concern that our findings may be driven by large depreciations accompanying banking and debt crises, we isolate episodes that did not coincide with currency crises. All methodologies produce qualitatively similar results. Further details on these robustness tests are reported in Appendix 4.2.

Does Output Fully Explain the Behavior of Imports and Exports?

Previous studies, including Chapter 4 of the October 2009 World Economic Outlook and Cerra and Saxena (2008), find that output declines significantly following financial crises and stays depressed over the medium term. Is the behavior of trade described above simply a reflection of these postcrisis output dynamics? To address this issue, we control for output by adding GDP of both the home economy and trading partners. Whereas standard gravity models assume that the elasticity of trade to output is uniform across economies and over time, we relax this assumption in our analysis because these elasticities are crucial for assessing whether trade behavior is fully explained by output.11 The top panel of Figure 4.5 and Table 4.1 suggest that while depressed output contributes significantly to the adverse evolution of imports, it does not explain all of it. Controlling for output reduces the estimated import losses substantially—by about 10 percentage points in both the short and the medium term (Table 4.1). However, the import losses remain significantly different from zero.

Figure 4.5.
Figure 4.5.

Import and Export Losses, Controlling for Output

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Blue lines indicate the impulse response function – the effect of a crisis on imports and exports relative to what would be predicted in the absence of a crisis. Predictions are based on a collapsed gravity model in changes, with contemporaneous and lagged crises, home and trade-weighted partner output, a trade-weighted partner crisis dummy, and country and time dummies.

The finding that output does not explain all of the adverse behavior of imports is robust to several tests. One possibility is that the estimated elasticity of imports to output picks up the sensitivity of imports to long-term or trend movements in output; if the elasticity of imports to cyclical fluctuations or during crisis periods is larger, then imposing a fixed elasticity would result in large unexplained declines in imports during cyclical downturns or crises, even after controlling for output. To test for this, we allow the coefficient on output to vary during crisis and noncrisis periods; we also allow it to vary across the trend and cyclical components of output, where the trend and cycle were separated using a Hodrick-Prescott filter. In both cases, the elasticity of imports to higher-frequency movements in output was indeed found to be significantly higher. Finally, we include lags of GDP growth in the specification. Nevertheless, the adverse behavior of imports remained, even after controlling for output. It is also robust to the use of alternative methodologies described in Appendix 4.2.

In contrast to import behavior, much of the behavior of exports following a crisis seems to be associated with adverse output dynamics (Figure 4.5, bottom panel). After controlling for output, exports are close to normal, and the estimated deviation is not statistically different from zero either in the short or the medium term. Because of this, the remainder of the chapter focuses on imports, which seem to bear the primary impact of crises.

Do Dynamics Differ across Products, Trading Partners, and Crises?

The previous section noted significant differences in the behavior of trade in various product categories during the most recent global downturn. Is this pattern also borne out in earlier crises? Figure 4.6 shows some similarities between the most recent global downturn and earlier crises, but it also shows some differences.12 In the past, as in the more recent global downturn, capital and consumer durables experienced the largest short-term decline, with an average drop of almost 15 percent in the second year after the crisis, even after controlling for changes in output. There was little sign of recovery in imports for this product category over the medium term. The other three product categories also experienced significant drops in the short term but of less than 10 percent. However, these product categories exhibited further deterioration over the medium term, which is somewhat puzzling, especially because the analyses that find these losses already control for output.13

Figure 4.6.
Figure 4.6.

Import Losses in Different Product Groups, Controlling for Output

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Blue lines indicate the impulse response function – the effect of a crisis on imports relative to what would be predicted in the absence of a crisis. Predictions are based on a collapsed gravity model in changes, with contemporaneous and lagged crises, home and trade-weighted partner output, a trade-weighted partner crisis dummy, and country and time dummies.

It is also possible that different trading partners’ exports to the crisis economy are affected in different ways. Are some trading partners’ exports more resilient than others? One factor that does seem to matter is the strength of international production linkages—the use of intermediate imported goods in the production of exports.14 Greater production sharing tends to make trade more resilient: the more vertically integrated a crisis economy is with a trading partner, the smaller the decline in imports from that trading partner (Figure 4.7). The finding is consistent with the idea of a “beachhead effect,” with firms that have incurred the sunk costs of entering a relationship unwilling to leave simply because conditions turn bad.15

Figure 4.7.
Figure 4.7.

Import Losses and Production Linkages, Controlling for Output

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Sources: Johnson and Noguera (2010); and IMF staff calculations.Note: Blue lines indicate the impulse response function – the effect of a crisis on imports relative to what would be predicted in the absence of a crisis. Predictions are based on a gravity model in changes, with contemporaneous and lagged crises, home and partner output and output per capita, partner crisis dummies, and importer-exporter and time dummies. Importer-exporter pairs are split into those with above-median value-added-to-exports ratios as of 2006 (low production linkages) and those below the median (high production linkages). The value-added-to-exports ratios are from Johnson and Noguera (2010).

Finally, we evaluate whether trade dynamics differ if a crisis coincides with a global downturn, where the latter is defined as in Freund (2009).16 About one-fifth of earlier crisis episodes occurred during years of global downturns. Economies that experienced a crisis during a global downturn had deeper import and export losses, both unconditionally and after conditioning on output (Figure 4.8). The unconditional import losses remain larger than the export losses, and so, even in these cases, net exports of the crisis economies still tend to improve. This suggests that such financial crises may result in deeper trade losses than historical episodes that did not coincide with a global downturn.

Figure 4.8.
Figure 4.8.

Trade Losses during Global Downturns

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Lines indicate the impulse response function—the effect of a crisis on imports and exports relative to what would be predicted in the absence of a crisis. Predictions of unconditional losses are based on contemporaneous and lagged crises, country and time dummies, and interactions of contemporaneous and lagged crises with years of global downturns. Predictions of conditional losses are based on a collapsed gravity model in changes, with contemporaneous and lagged crises, home and trade-weighted partner output, a trade-weighted partner crisis dummy, country and time dummies, and interactions of contemporaneous and lagged crises with years of global downturns. The definition of global downturns follows Freund (2009), and includes 1975, 1982, 1991, 2001, and 2008.

Do Precrisis Conditions Matter?

The import dynamics in Figures 4.4 and 4.5 present only the average behavior across all historical crisis episodes. But might import dynamics differ depending on precrisis conditions? For example, an economy that entered the crisis with a relatively deteriorated current account balance may see more of an adjustment in relative prices, so that imports may fare relatively worse than in an economy that entered a crisis with a more favorable current account position. The top panels of Figure 4.9 suggest that this is the case. For the subsample of crisis episodes with above-median precrisis current account balances, there was no deterioration in imports after controlling for output; for the subsample with below-median precrisis current account balances, the import loss after controlling for output was much larger and more persistent.

Figure 4.9.
Figure 4.9.

Precrisis Characteristics and Import Losses, Controlling for Output

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Blue lines indicate the impulse response function – the effect of a crisis on imports relative to what would be predicted in the absence of a crisis. Predictions are based on a collapsed gravity model in changes, with contemporaneous and lagged crises, home and trade-weighted partner output, a trade-weighted partner crisis dummy, and country and time dummies. Crisis episodes are split into those for which the current account balance, degree of financial openness, and trade openness are, respectively, above or below the crisis sample median in year t –1.

Similarly, economies with a higher degree of financial or trade openness entering the crisis seemed to experience a smaller import loss (Figure 4.9, middle and bottom panels). While the exact nature of the association between precrisis open-ness and postcrisis trade dynamics is unclear, we have two conjectures. First, greater financial open-ness could mean less dependence on the domestic banking sector, especially for trade finance. If this is the case, then a banking crisis that damages the domestic financial sector could have less of an impact in more financially open economies. Second, the association between trade openness and post-crisis dynamics could be related to the greater trade resilience of more vertically integrated economies, because economies with the strongest production linkages also tend to have relatively high measured levels of trade integration.

What Factors are Associated with Postcrisis Import Dynamics?

If output does not explain all the behavior of imports following a crisis, then what does? Potential additional explanations, which have been discussed in the context of the recent crisis, include the following:

  • Impaired credit: Banking crises in particular are associated with a tightening of credit conditions—Abiad, Dell’Ariccia, and Li (forthcoming) find that when a downturn is associated with a banking crisis, a “creditless recovery” (one in which real credit growth is negative) becomes twice as likely. If the downturn is also preceded by a credit boom, the likelihood of a creditless recovery quadruples and becomes a near certainty. Difficulty in obtaining credit may have deleterious effects on imports, above and beyond any effects weak credit might have on aggregate demand.17

  • Increased protectionism: In the aftermath of a crisis, interest groups that favor protecting domestic production may be strengthened.18 Increased protection need not come in the form of increased tariffs; it may also be manifest in increased use of antidumping measures and other forms of “murky protectionism,” such as clauses in stimulus packages that restrict spending to domestic producers. Box 4.2 discusses the use of protectionist measures and their effect on trade in the wake of the recent crisis.

  • Exchange rate dynamics: Imports may be adversely affected by changes in both the level and the volatility of exchange rates. Kaminsky and Reinhart (1999) note that many banking crises are also associated with sharp depreciations of the currency; in such cases the swing in relative prices would hurt imports but boost exports. In addition, exchange rate variability may increase during crisis periods, and increased variability has been shown to adversely affect trade (Thursby and Thursby, 1987).

  • The composition effect: Because certain product categories represent a greater share of trade than of output, a fall in demand for these products will result in a larger drop in trade than in output. Crises may lead to a greater fall in demand for goods than for services, for example, and most trade is in goods, whereas services account for the bulk of output. And within goods, durables form a larger share of trade than of output. As noted in Box 4.1, the composition effect seem to explain much of the outsize drop in trade during the recent crisis. Unfortunately, the lack of comprehensive historical data on the composition of demand precludes a detailed investigation of this particular mechanism, but below we present some evidence that suggests that composition effects played at least a partial role even in earlier crises.

For these mechanisms to be associated with the observed postcrisis import dynamics, not only should these factors have an adverse effect on imports, they should also tend to worsen during crisis periods. To investigate the role of each of these mechanisms, we follow a three-step approach. In the first step, we estimate impulse-response functions to gauge how credit, protection, and exchange rate dynamics evolve in the aftermath of a crisis. In the second step, we estimate the elasticity of imports with respect to these factors. The third step combines the first two steps to obtain an estimate of how much each mechanism can account for postcrisis import dynamics. Details are described in Appendix 4.2. It should be emphasized that none of this analysis attempts to identify causation, only association; we want to know how much of an import decline we would predict given the behavior of the various correlates.

The results of the first step of this three-step methodology are shown in Figure 4.10, which shows how the level and volatility of the real effective exchange rate (REER), credit, and tariffs evolve on average following a crisis. The REER depreciates in the short term by about 6 percent on average in the first two years of the crisis and stays depreciated in subsequent years, but the variation around this average is quite large. There is also a significant increase in the volatility of the REER in the short term that declines over the medium term. Credit to the private sector, measured relative to GDP, steadily declines in the years following a crisis, with an average decline of more than 15 percentage points by the fifth year. Although the magnitude of this decline looks quite large, it should be noted that many banking crises were preceded by excessive credit growth. Finally and somewhat surprisingly, there is no evidence that protectionism, as measured by the average tarif level, increases following a crisis. There is a statistically insignificant change in average tariffs following a crisis in both the short and medium term.19 This last finding, however, should not be interpreted to mean that overall protection does not rise, given that increased protectionism may manifest itself in “murky” forms (mentioned above), which are difficult to detect in the data.

Figure 4.10.
Figure 4.10.

The Postcrisis Evolution of Various Mechanisms

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Blue lines indicate the impulse response function—the effect of a crisis relative to what would be predicted in the absence of a crisis. Predictions are based on contemporaneous and lagged crises and country and time dummies.1 Exchange rate volatility is measured as the annual standard deviation of monthly real effective exchange rate depreciation.

The estimated elasticity of imports to mechanisms other than output is outlined in Table 4.2.20 The estimated elasticity of imports to the REER, at about 0.09, is substantially smaller than estimates from other studies. This may be due to the fact that the model estimates only the contemporaneous association between the REER and imports.21 The estimated elasticity of imports to REER volatility and credit are both statistically significant and of the expected sign. The estimated elasticity of imports to tariffs, while negative as expected, is not statistically significant.

Table 4.2.

Estimated Elasticity of Imports

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Source: IMF staff calculations. Note: Elasticity is estimated by regressing the log of imports on the log of the variables of interest and economy- and year-fixed effects. ***, **, and * indicate significance at the 1, 5, and 10 percent level, respectively. Standard errors (not reported) are clustered by economy and corrected for heteroscedasticity.

Real effective exchange rate.

Combining these results allows us to estimate the average contribution of these various mechanisms (Figure 4.11). The estimated contribution of output is derived as the difference between the unconditional import loss reported in Figure 4.4 and the import loss controlling for output in Figure 4.5. At the onset of a crisis (year t), the decline in output accounts for about half of the overall loss in imports in that year; increased exchange rate volatility accounts for another one-fifth of the import loss. Real depreciation and weak credit together account for less than 10 percent of the loss in the crisis year, so that about 20 percent of the import loss in the year of the crisis remains unaccounted for. In subsequent years, output remains the most important contributor to depressed imports, accounting for anywhere between 50 and 60 percent of the total import loss. The role of exchange rate volatility diminishes over time, a reflection of the fact that the surge in volatility in the immediate aftermath of a crisis subsides over time. The role of credit, in contrast, increases over time because credit steadily worsens following a crisis; by the fifth year, weak credit conditions account for about 10 percent of the total import loss.

Figure 4.11.
Figure 4.11.

Decomposition of Import Losses

(Percent; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Unconditional import losses (see Figure 4.4) are decomposed into changes attributable to the fall in output and credit, a rise in exchange rate volatility, depreciation, and changes in tariffs. The contribution of output is computed as the difference between the unconditional and conditional import losses (see Table 4.1). The contribution of the remaining factors is calculated as the product of the elasticity of imports with respect to each factor and the change in the factor following crises (depicted in Figure 4.10), as a percent of the unconditional change in imports after crises.1 REER = real effective exchange rate.

Although these mechanisms help account for a significant portion of the estimated postcrisis import loss, between 20 and 35 percent of the latter remains unexplained. To what extent might the composition effect account for the unexplained component? This chapter’s focus on trade in goods, and the lack of detailed historical data on the demand share of durables and nondurables for a wide range of economies preclude inclusion of composition effects in our three-step methodology. But there is some evidence to suggest that such effects were important in earlier crises as well.22 Imports fall much more than output if two conditions are satisfied: demand for some goods must fall more than for others, and those goods must account for a larger share of trade than of output. Across a sample of 48 economies and 26 crisis episodes for which data are available, tradable investment goods (machinery and equipment) account for 18 percent of trade but only 8 percent of GDP (Figure 4.12). And the postcrisis decline in machinery and equipment is much larger—imports of these goods decline by more than one-third by the second year after a crisis, more than 10 times the postcrisis decline in the rest of GDP over the same period.23 Calculations in Appendix 4.2 suggest that, even when focusing narrowly on these investment durables, the composition effect can explain at least a portion of the postcrisis fall in imports.

Figure 4.12.
Figure 4.12.

Import Losses and Composition Effects

(Percent)

Source: IMF staff calculations.Note: The average share of machinery and equipment in GDP and share of capital durables in imports in a sample of 48 countries is shown in the top panel. The estimated impulse response two years after a crisis is shown in the bottom panel. The estimated impulse response function is based on contemporaneous and lagged crises and country and time dummies.

The three-step methodology provides only an estimate of the average contribution of the various mechanisms to import dynamics. For example, although the size of the average depreciation is small following a crisis, it is also clear from Figure 4.10 that there is substantial variation around this average. Is it possible that economies whose currencies depreciated more substantially had imports that evolved differently than those whose currencies did not depreciate as much? Figure 4.13 sheds some light on these possibilities; once again, all the reported import losses already control for output. Crisis episodes with a relatively large depreciation seem to be associated with more depressed imports than those with smaller depreciations (top panels). Crises during which the increase in exchange rate volatility was lower, or credit conditions were better, seem to be associated with less import deterioration (middle panels).24 Finally, there is evidence that Crises during which tariffs increased by relatively more were associated with worse import performance, particularly in the short term, consistent with the findings in Box 4.2 regarding the recent crisis.

Figure 4.13.
Figure 4.13.
Figure 4.13.

Postcrisis Characteristics and Import Losses, Controlling for Output

(Percent deviation from normal; years on the x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Blue lines indicate the impulse response function – the effect of a crisis on imports relative to what would be predicted in the absence of a crisis. Predictions are based on a collapsed gravity model in changes, with contemporaneous and lagged crises, home and trade-weighted partner output, a trade-weighted partner crisis dummy, and country and time dummies. Crisis episodes are split into those during which depreciation, the change in real effective exchange rate volatility, and the change in credit to GDP between t = 0 and t = 5 are, respectively, above or below the crisis sample median. In the case of tariffs, the figure reports conditional imports after crises with a change in the trade liberalization index above and below the 75th percentile.Source: IMF staff calculations.Note: Blue lines indicate the impulse response function—the effect of a crisis on imports relative to what would be predicted in the absence of a crisis. Predictions are based on a collapsed gravity model in changes, with contemporaneous and lagged crises, home and trade-weighted partner output, a trade-weighted partner crisis dummy, and country and time dummies. Crisis episodes are split into those during which depreciation, the change in real effective exchange rate volatility, and the change in credit to GDP between t = 0 and t = 5 are, respectively, above or below the crisis sample median. In the case of tariffs, the figure reports conditional imports after crises with a change in the average tariff above and below the 75th percentile.

Summary and Implications for the Outlook

This analysis finds that crises tend to depress imports substantially in the short term—above and beyond any import compression due to lower output—and that imports tend to stay depressed through the medium term. Imports tend to decline more if the economy entered the crisis with a relatively unfavorable current account balance and if the crisis resulted in a relatively large decline in the REER or poor credit conditions. Finally, exports exhibit a smaller and more gradual decline that can be fully accounted for by changes in output.

How do those results inform the outlook for trade? As the world economy emerges from the Great Trade Collapse of 2008–09, recent data make it just as easy to view the trade recovery glass as being half full as it is to view it as half empty. Optimists can point to strong growth in world trade since the second half of 2009, while pessimists can lament that imports and exports remain far below precrisis trends, or even below precrisis levels for some economies. Which perspective is justified? Although caution should be exercised when drawing implications for the recent, more global crisis from historical crisis episodes, we use the evidence in this chapter to try to shed light on where trade might be headed.

The recent financial crisis has been concentrated in many large, advanced economies (Table 4.3), and so this chapter’s findings have implications not just for individual economies but also for the global recovery and for global trade patterns. The 13 countries that recently had a systemic banking crisis account for about 40 percent of global demand, with the three largest countries—Germany, the United Kingdom, and the United States—accounting for more than one-third of global demand. Including 10 additional countries that Laeven and Valencia (2010) identify as having had a “borderline” systemic banking crisis, the recent crisis countries account for over half of world demand and output. This chapter’s estimates of postcrisis trade dynamics are consistent with the sharp and substantial drop in import demand that has been evident in these countries. More important for the outlook, this analysis suggests that these countries’ imports are likely to remain depressed for a number of years, even more than their tempered output projections would suggest. If, in addition, some economies fall into a sovereign debt crisis—which this analysis finds to be associated with more acute import losses—prospects for global import demand will dim even further. For economies that rely heavily on external demand for growth, the chapter’s findings underscore the importance of rebalancing toward domestic sources of growth or, more generally, of developing “twin engines” of growth.

Table 4.3.

Systemic Banking Crises, 2007–09

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Source: Laeven and Valencia (2010). Note: Laeven and Valencia (2010) define systemic banking crises as cases in which at least three of their listed interventions took place, whereas borderline cases are those that “almost meet” their definition of a systemic crisis.

The analysis also suggests that import dynamics may differ across the crisis countries. For countries that entered the crisis with a relatively weak current account, such as the United Kingdom and the United States, import demand is likely to be even more anemic. Exports to the United Kingdom are also weighed down by the substantial depreciation of the pound sterling since 2008. Finally, real credit in these two economies is decelerating or even contracting, which the chapter suggests will also weaken imports beyond its effects on output.

The fact that these countries’ exports are not expected to decline nearly as much as their imports implies a likely improvement in the external balances of the crisis countries and a deterioration in the balances of their partners. Because the United States accounted for a large part of the global imbalances that widened substantially in the early 2000s, a silver lining from the recent crisis is the narrowing of the U.S. external deficit, and this chapter suggests that this narrowing may be more durable than in the absence of a financial crisis. On the other hand, the finding that imports decline mostly for investment-related goods suggests that the post-crisis outlook for innovation and potential growth could be diminished.

Protectionism in the Recent Crisis

The extent of trade protectionism before and during the recent crisis has been subject to significantly different interpretations. This box addresses the question by drawing on recent research by IMF staff (Gregory and others, 2010). New trade restrictions have so far been limited to a small share of global trade but have had a strong negative impact on trade flows. This box suggests ways for economies to avoid allowing rising trade protectionism to interfere with the recovery.

Trade became much freer during the second half of the 20th century. Among major western European and North American countries, average tariffs fell from 15 to 4 percent between the 1950s and mid-2000s. In many major developing economies, tariffs increased or remained very high until the 1980s but have since come down sharply. Nonetheless, the pace of trade reforms waned after the mid-2000s as protectionist sentiment began to increase, and so substantial trade restrictions were still in place when the crisis hit. Moreover, gaps in World Trade Organization (WTO) commitments leave a wide scope for legal backsliding on trade policy. Tariffs—the most transparent and easily monitored trade policy instrument—provide an illustrative example. Some economies can raise tariffs substantially without exceeding their WTO bindings (first figure).

Once the crisis took hold in mid-2008, political leaders’ awareness of the risks of protectionism, backed by increased monitoring activities, helped limit the protectionist response. Mindful of both the disastrous results of protectionism during the 1930s and the contribution of trade to macroeconomic performance, the Group of 20 (G20) economies pledged in November 2008 to “refrain from raising new barriers to investment or to trade in goods and services, imposing new export restrictions, or implementing WTO inconsistent measures to stimulate exports.” In April 2009 and again in June 2010, G20 leaders extended this pledge and asked the WTO and other institutions to monitor adherence.

Several other factors have worked to limit the protectionist response to the crisis:

uch04fig04

Simple Average Tariff Rates: 2008

(Percent)

Source: World Trade Organization, World Tariff Profiles 2009.1 MFN = Most favored nation.

  • Multilateral rules and institutions have clarified the types of policy actions considered responsible. The strong WTO-based trade system has been central.

  • Trade declined much more rapidly than overall economic activity. The ratio of imports to GDP declined as well. Although job losses mounted, they were not, by and large, blamed on trade.

  • Macroeconomic and financial sector policies were supportive of trade.

Even so, once the crisis took hold, a number of trade restrictions were introduced. The sharp rise in unemployment and its continued high levels may help explain the increased frequency of industry requests for trade remedies. In addition, there was increased use of unconventional measures, which are harder to quantify.

However, the extent of trade restrictions is unclear, and various monitoring efforts have come to quite different conclusions. None of the watchdogs suggest that we have seen, or are likely to see, an extreme protectionist surge like that of the 1930s, but their assessments differ markedly. The June 2010 joint report of the WTO, Organization for Economic Cooperation and Development (OECD), and United Nations Conference on Trade and Development (unctad) indicates that “protectionist policy responses have been limited, although there are still instances of restrictive measures taken… [T]here continues to be few instances of new import restrictions and a greater use of export restrictions, but some G20 governments have also taken steps to facilitate trade” (WTO, OECD, and unctad, 2010). In contrast, the sixth report of Global Trade Alert (GTA), which is associated with the London-based Centre for Economic Policy Research and supported by the World Bank, also released in June 2010, concludes that “as far as open markets were concerned, 2009 was a terrible year” and that “much of the discrimination put in place then has yet to be removed” (GTA, 2010).

Gregory and others (2010) explore the impact of both conventional and more unconventional “behind the border” measures highlighted in the GTA reports, such as technical barriers to trade, procurement, and regulatory measures. The analysis matches data from GTA monitoring of measures taken between mid-2008 and late 2009 with detailed product-level data on bilateral monthly trade flows.1 The second figure illustrates the varied nature of these protectionist measures. There is strong evidence that, after an economy imposed import restrictions on a particular product, its imports fell in succeeding months relative to world trade in the same product (third figure). Allowing for various time-varying fixed effects, more sophisticated econometric analysis suggests that trade in the affected products dropped an average of 3 to 8 percent after the imposition of restrictions. However, in the aggregate, restrictions implemented during the study period decreased trade by 0.25 percent, because these measures affected only a small share of global trade.

Looking ahead, sustained high unemployment, uneven growth, an unwinding of government stimulus measures, and growing economic imbalances may increase protectionist pressure. In some economies, such pressure may also emerge from high commodity prices or a surge in capital inflows, which may lead to rapid currency appreciation.

Gaps in WTO commitments leave ample scope for further trade restrictions, and a failure by all economies to vigorously resist protectionism could threaten the economic recovery and slow future growth. Maintaining and enhancing the monitoring of protectionist measures and sustaining high-level political awareness of the associated macroeconomic risks will help. But the surest way to avoid such a downside scenario is to tighten multilateral trade commitments by completing the WTO Doha Round. This can be viewed as a key part of the exit strategy from the global economic crisis.

uch04fig05

Measures included in Gregory and Others (2010)

(Number of measures)

Source: Global Trade Alert Database.
uch04fig06

Bilateral Trade Flows subject to Measures Implemented in November 2008

(Index, October 2008 = 100)

Source: IMF staff calculations.
The main author of this box is Robert Gregory. 1 Extending the data set through May 2010 does not substantially change the results of the analysis.

Domestic policymakers who might be concerned about the harmful effects of a financial crisis on exports may be reassured by the chapter’s findings that declines in exports are, on average, small and gradual. Moreover, these effects can be accounted for by weaker output, suggesting that addressing the factors that depress output on the supply side will help exports recover as well.

Finally, although domestic policymakers may care more about the consequences for exports than for imports, the global nature of the recent crisis means that a coordinated and protracted slump in import demand across a wide swath of economies bodes ill for the global recovery. Not surprisingly, the chapter finds that boosting output will considerably help imports to recover. In that regard, productivity-enhancing structural reforms could help raise growth. The chapter’s findings suggest that, beyond supporting domestic demand, taking steps to improve credit conditions, keeping protectionist tendencies at bay, and avoiding excessive exchange rate volatility may help support the recovery of trade. A conclusion of the Doha Round of global trade talks would also reinforce the revival of global trade.

Appendix 4.1. Data Sources

The primary data sources for the chapter are the IMF’s Direction of Trade Statistics (DOTS), World Economic Outlook (WEO), and International Financial Statistics (IFS) databases; the NBER-UN World Trade Flows database (2005); and Laeven and Valencia (2008, 2010). Additional data sources are listed in Table 4.4, and the WEO analytical regions are in Table 4.5.

Table 4.4.

Data Sources

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Table 4.5.

Country Groupings

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Crisis indicators are from Laeven and Valencia (2008, 2010). Laeven and Valencia (2010) present new and comprehensive data on the starting dates and characteristics of systemic banking crises over the period 1970 –2009, building on earlier work by Caprio and others (2005), Laeven and Valencia (2008), and Reinhart and Rogoff (2009). They update the Laeven and Valencia (2008) database on systemic banking crises to include the recent episodes following the U.S. mortgage crisis of 2007 and identify 129 episodes since 1970.

Laeven and Valencia (2008) also identify debt crisis episodes based on sovereign debt default and restructuring by relying on information from Beim and Calomiris (2001), World Bank (2002), Sturzenegger and Zettelmeyer (2006), and IMF staff reports. The information compiled includes the year of sovereign default on private lending and the year of debt rescheduling. Using this approach, they identify 63 episodes of sovereign debt default and restructuring since 1970.

Data on bilateral and aggregate imports and exports from the DOTS database are reported in current U.S. dollars. These are deflated using the world import and export price deflators from the IFS database, to determine each economy’s real imports and exports. The series on real GDP in U.S. dollars is from the WEO database. Import and export-weighted partner GDP and GDP per capita are constructed using real GDP in U.S. dollars and import and export weights from the DOTS database. These weights vary each year according to the actual import and export flows between economies.

Data on imports and exports by product category are constructed from the NBER-UN World Trade Flows database (see Feenstra and others, 2005). The database is first extended using the UN COMTRADE database. The codes from the Standard International Trade Classification, Revision 2, that identify products in the NBER-UN trade data are matched to the UN Broad Economic Classification (BEC) codes. These are then classified into Capital Goods, Consumer Durables, Consumer Nondurables, Intermediate Goods, and Primary Goods, following Pula and Peltonen (2009).

The current account balance is taken from the WEO database. Trade openness is measured as the ratio of the sum of imports and exports to GDP. Financial openness is calculated as the sum of foreign assets and foreign liabilities divided by GDP, using the updated and extended External Wealth of Nations Mark II Database (see Lane and Milesi-Ferretti, 2007).

Bank credit to the private nonfinancial sector is taken from the IFS database. Breaks in these data are identified using the IFS Country Notes publication, and data are growth-spliced at these points. The real effective exchange rate (REER) data are from the IMF’s Information Notice System. The volatility of the REER is calculated as the standard deviation of the monthly REER change in each year. The measure of trade liberalization is from the IMF Structural Reforms Database and is described in IMF (2008).

Bilateral data on production sharing are from Johnson and Noguera (2010).

The Global Trade Atlas data at the four-digit level of the Harmonized Commodity Description and Coding System (HS) are used to trace trade in types of products since 2001. These data cover the following: Argentina, Australia, Brazil, Canada, China, Japan, Korea, Russia, South Africa, Turkey, and the United States. The monthly data are converted to a quarterly frequency, deflated by specific commodity price deflators—from the WEO database for selected primary goods and from the CPB Netherlands Bureau of Economic Policy Analysis for the remaining products—and are seasonally adjusted. The HS four-digit codes are matched to the BEC and classified into Capital Goods, Consumer Durables, Consumer Nondurables, Intermediate Goods, and Primary Goods, following Pula and Peltonen (2009).

Appendix 4.2. Methodology and Robustness Tests

Estimating Unconditional Import Losses

The analysis25 first estimates the unconditional dynamics of imports in the aftermath of crises using a “collapsed” gravity model of trade in changes. In the baseline regression specification in the text, the growth in an economy’s aggregate imports, Δ ln Mit, is expressed as a function of a dummy variable indicating whether a crisis started in year t, five lags of this dummy variable, and country and time dummies:

Δ ⁢ ln ⁡ M i t = α i + π t + Σ α k c r i s i s i , t − k + ϵ i t . ( 4.1 )
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The robustness of the estimated unconditional import losses from the baseline specification is verified by using the following five alternative specifications:

  • Alternative 1: Deviation from precrisis trend— This procedure measures import loss as a simple deviation of ln Mit from a precrisis trend, ln Trit, where the latter is a linear trend based on a precrisis window from (t – 7) to (t – 1). The mean import loss k years after a crisis is just the average of this import loss, (ln Mit – ln Trit), across all crisis episodes. This is equivalent to estimating the following equation, either in levels or changes:
    ln⁡Mit−ln⁡Trit=Σβkcrisisi,t−k+ϵit.(4.2)
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    This procedure is similar to the procedure used in Chapter 4 of the October 2009 World Economic Outlook for estimating output losses following a crisis.26 In contrast to the baseline, this methodology allows for an episode-specific trend, as opposed to the country-specific trend that is captured by αi in the baseline specification. However, it does not control for global conditions as is done in the baseline.

  • Alternative 2: Baseline specification with autoregressive terms—The baseline specification is augmented by including four lags of the growth of imports on the right-hand side, paralleling the specifications used in Romer and Romer (2010) and Cerra and Saxena (2008):

Δ ln ⁡ M i t − α i + π t + Σ ρ l Δ ⁢ ln ⁡ M i , t − 1 + Σ α k c r i s i s i , t − k + ε i t . ( 4.3 )
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  • Alternative 3: Bilateral gravity in changes—A directional gravity model (that is, one with bilateral imports or exports as opposed to bilateral trade) is estimated in changes. The growth in bilateral imports of an economy from each trading partner, Δ ln Mim t, is regressed on a crisis indicator and its lags, as well as on time and importer-exporter pair dummies:

Δ ⁢ ln ⁡   M i m p , exp ⁡ , t ⁢ =   α i m p , exp ⁡ ⁢ + π t + Σ α k ′ ⁢     crisis imp , t - k + ɛ imp , exp , t ⋅ ( 4.4 )
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  • Alternative 4: Bilateral gravity in changes, using top 20 partners—This specification is identical to the directional gravity model in changes as described in equation (4.4) but focuses only on the top 20 partners from which an economy imports. This is done because our primary concern is in describing the behavior of aggregate trade, rather than average bilateral trade. The standard gravity model weights all bilateral trade observations equally regardless of the size of the bilateral trade relationship. But trade is highly uneven—in the sample used in this chapter, the top 20 trading partners account for 89 percent of an economy’s total imports, on average, even though the average economy imports from 175 economies. In other words, about 90 percent of the observations in a typical gravity model account for only 10 percent of total trade. The behavior of aggregate trade will more closely follow the dynamics of larger trading partners.

  • Alternative 5: Baseline specification, excluding banking and debt crises that were accompanied by a currency crisis—This specification is identical to the baseline equation (4.1) but focuses only on “pure” banking and debt crises. More specifically, we exclude banking and debt crisis episodes that were accompanied or preceded by a currency crisis as defined in Laeven and Valencia (2008).

As Table 4.6 and Figure 4.14 illustrate, the estimated impulse response functions of imports using these different approaches are similar both qualitatively and quantitatively. This confirms the finding that there are large and statistically significant unconditional import losses after crises.

Table 4.6.

Unconditional Import Losses: Estimated Impulse Response Functions Using Alternative Methodologies

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Source: IMF staff calculations.
Figure 4.14.
Figure 4.14.

Import Losses, Not Controlling for Output: Alternative Methodologies

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.

Import Losses Controlling for Output

The import losses controlling for output are also computed using the baseline model in changes, this time with a set of controls derived from the standard gravity model. Specifically, the growth of imports, Δ ln Mit, is modeled as a function of the growth in the economy’s output, Δ ln GDPit, its partners’ import-weighted output, Δ ln PGDPit, contemporaneous and lagged values of a dummy variable indicating a crisis in the economy, crisisi, t–k, an import-weighted indicator of incidence of crises in trading partners (plus five lags), pcrisis it–k, and country and time dummies α i and πt:

Δln ⁢ M it ⁢ = α i ⁢ + π t ⁢ +   Σα k ⁢ crisis i , t - k +   ( β 1 r + β 2 r × D t ≥ 1990 ) Δ ⁢ ln ⁡ G D P i t + β 3 Δ ⁢ ln ⁡   P G D P i t + Σ ⁢ δ k p c r i s i s i , t − k ⁢ ɛ i t ⋅ ( 4.5 )
ch04lev3sec2

As discussed in the text, the elasticity of imports to output is crucial for assessing whether the evolution of trade is fully explained by output. To be as general as possible, we allow the output elasticities of imports and exports in the baseline specification to vary across the 10 WEO analytical regions described in Table 4.5. We also allow each of these regional elasticities to vary between the pre- and post-1990 periods. The estimated elasticities, shown in Table 4.7, range from 0.8 to 4.5 and are in general higher for the post-1990 period.

Table 4.7.

Estimated Elasticity of Imports to Output: Panel Regression with Country and Time Dummies

article image
Source: IMF staff calculations.

Commonwealth of Independent States.

The following tests were performed to check the robustness of the conditional import losses presented in the text:

  • Robustness Test 1: Distributed lag specification—We augment the specification to include lagged output growth. The elasticity of imports to contemporaneous and lagged output is allowed to vary across regions and between the pre- and post-1990 periods.

  • Robustness Test 2: Uniform elasticity of imports to output—We report the results from a specification that would most closely mirror a collapsed gravity specification in changes. Namely, as is standard in the literature, we impose the same elasticity of imports to output across economies and over time.

  • Robustness Test 3: Bilateral gravity (all controls) in changes—Rather than focusing on the economy’s aggregate imports, we estimate a unidirectional (bilateral) gravity model in changes. The specification is as in equation (4.4) but contains the standard gravity controls: the growth in the economy’s and partners’ output as well as a set of dummies for crises occurring in both home and partner economies, indicators for whether the country pair is in a currency union or free trade agreement, and time and importer-exporter pair dummies. The elasticity with respect to an economy’s output is allowed to vary across regions and between the pre- and post-1990 periods.

  • Robustness Test 4: Allowing the elasticity of imports to vary across cyclical versus trend components of output—Imports may be more responsive to cyclical than to trend movements in output; if so, the baseline approach would overestimate the fall in imports controlling for output. To test this, we allow the elasticity of imports to vary across the trend and cyclical components of output, where the trend and cycle were separated using a Hodrick-Prescott filter. As in the baseline, the import elasticity with respect to both the cyclical and trend components of output are allowed to vary across WEO regions and between the pre- and post-1990 periods.

  • Robustness Test 5: Controlling for changes in the REER and relative prices—Import dynamics may differ after crises due to changes in the REER and relative price levels. Equation (4.5) is augmented to control for changes in REER and the domestic price level, proxied by the change in the GDP deflator.

  • Robustness Test 6: Controlling for changes in domestic aggregate demand—An economy’s GDP may not be a good proxy for absorption in the importing economy, and to the extent that absorption declines more than GDP during Crises, the estimated import losses after controlling for output may be overstated. We replace growth in output by growth in domestic absorption (consumption plus investment) on the right-hand side of equation (4.5).

  • Robustness Test 7: Allowing the elasticity of imports to output to differ across economies—We further increase the flexibility of our specification by estimating separately the elasticity of imports to output for each of the 154 economies in the sample.

  • Robustness Test 8: Allowing the elasticity of imports to output to vary across crisis versus noncrisis periods—Similar to Robustness Test 4, the sensitivity of imports to output may be particularly high in times of crisis. We thus allow the coefficient on output to vary during crisis and noncrisis periods.

The results of these robustness tests are presented in Table 4.8 and Figure 4.15. The finding that imports remain below their normal levels following a crisis, even after controlling for output, is confirmed across all these robustness checks. While the standard errors increase substantially once we allow the estimated elasticity of imports to output to vary across economies, the point estimates remain very similar to the baseline specification.

Table 4.8.

Conditional Import Losses: Robustness of Estimated Impulse Response Functions

article image
Source: IMF staff calculations. Note: All columns include economy- and year-fixed effects. Columns (1), (2), and (4) – (7) allow the elasticity of imports to output (or its cyclical and trend component and consumption and investment) to vary by WEO regions and after 1990. In column (8), the elasticity of imports to output is allowed to vary by economy.

REER = real effective exchange rate; PPP = purchasing power parity.

Figure 4.15.
Figure 4.15.

Import Losses, Controlling for Output: Robustness

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.

Decomposition of Unconditional Import Losses

We use a three-step approach to evaluate the importance of different mechanisms in explaining the unconditional import losses, as detailed below. It is important to keep in mind that this is simply an accounting exercise that attempts to decompose the unconditional import losses based on observed correlations. The true contributions of the various mechanisms might differ from these estimated correlations.

Step 1: We document whether crises are followed by persistent changes in tariffs, credit, the REER, and exchange rate volatility by estimating equation (4.1) with the mechanisms of interest as the dependent variable.

Step 2: We estimate the elasticity of imports with respect to the various mechanisms in the following regression framework:
ln⁡ Mit=αi+πt+ (βGDP,r⁢+βGDP,r⁢× Dt≥1990) ln⁢  ⁢GDPit+βTariff⁢ln⁡ Tarrifit+βcr⁢ ln⁡ Creditit+βREERln⁡ REERit+βvol⁢ ln⁡ Volatilityit+Σαk⁢ crisisi,t−k+β3⁢ ln⁡ PGDPit+Σ⁢  δk⁢pcrisisi,t−k+ɛit(4.6)
article image

Step 3: We combine the estimates from steps 1 and 2 to quantify the contribution of various mechanisms. In particular, the estimated change in the mechanism following a crisis in step 1 is multiplied by the estimated elasticity of imports with respect to that mechanism in step 2. The contribution of each mechanism is then expressed as a fraction of the unconditional import losses. The contribution of output is computed as the difference between the unconditional import losses from equation (4.1) and import losses conditional on output from equation (4.5).

Composition Effects during Earlier Crises: A Back-of-the-Envelope Calculation

If GDP and imports had the same composition of goods and services, and if, within each sector, imports changed proportionally to domestic final demand, imports would be expected to fall by as much as GDP after a crisis. However, if there are differences in the composition of imports and GDP, and if goods and services that constitute a larger share of trade than of GDP experience a relatively larger decline in demand following a crisis, imports will fall more than GDP even in the absence of changes in other factors (such as credit, exchange rates, or degree of protectionism) described in the chapter. For example, part of the outsize decline in imports relative to GDP in the recent crisis has been attributed to the resilience in the demand for services relative to manufactured goods. Since demand for manufactured goods experienced a relatively larger decline and since manufactured goods comprise a larger share of trade than of GDP, overall imports declined more than GDP (Borchert and Mattoo, 2009).

We first investigate whether historically there is a difference in the behavior of manufactured goods and services following crises. Since detailed data on the demand side are not available, we use sectoral value-added data to document whether there are differences in the behavior of services versus industry after crises. Somewhat surprisingly, this does not appear to be the case. The estimated drop in services is very similar to the decline in industry value added after crises (Figure 4.16, top panel).27 Given this similarity in the dynamics of services and industry, the different shares of services in output and trade do not appear to be a likely explanation.

Figure 4.16.
Figure 4.16.

The Postcrisis Evolution of Various Components of GDP

(Percent deviation from normal; years on x-axis; crisis begins at t = 0)

Source: IMF staff calculations.Note: Lines indicate the impulse response function – the effect of a crisis on imports relative to what would be predicted in the absence of a crisis. Predictions are based on contemporaneous and lagged crises, and country and time dummies.

However, within the “manufactured goods” category, there are compositional differences between output and trade. Across a sample of 48 economies for which disaggregated data on gross fixed investment are available, (capital) durables, measured by tradable investment goods—namely, machinery and equipment—account for only 8 percent of GDP. For the same set of economies, the average share of (capital) durables in imports is 18 percent.28 Although the data coverage is rather scant—only 26 of the identified crises can be included in the analysis—we provide some back-of-the-envelope calculations to estimate the contribution of these composition effects in explaining import losses following crises.

We begin with the following two identities:

GDP gth ⁢ =     sh dur GDP ⁢ ×   DUR GDP gth + ( 1 − s h d u r G D P ) × O T H E R G D P g t h ( 4.7 )
ch04lev2sec11
IMP gth ⁢ =     sh dur IMP ⁢ ×   DUR IMP gth + ( 1 − s h d u r I M P ) × O T H E R I M P g t h , ( 4.8 )
ch04lev2sec11

where GDPgth and IMPgth are the growth rates in GDP and imports, respectively; shdurGDP and shdurIMP are the share of (capital) durables in GDP and imports, respectively; DURGDPgth and DURIMPgth are the growth rate in the (capital) durable component of GDP and imports, respectively; and OTHERGDPgth and OTHERIMPgth are the growth rate in other com-ponents of GDP and imports, respectively.

Assuming the elasticity of imports of different products to GDP is 1, equation (4.8) can be rewritten as

I M P g t h = s h d u r I M P ×   D U R G D P g t h ×   ( 1 ⁢ -   sh dur IMP ) ⁢   ×   OTHER GDP gth ⋅ ( 4.9 )
ch04lev2sec11

Subtracting (4.7) from (4.9) implies

I M P g t h − G D P g t h = ( s h d u r I M P − s h d u r G D P ) ×   ( DUR GDP gth ⁢ -   OTHER GDP gth ) . ( 4.10 )
ch04lev2sec11

Based on equation (4.10), we define the composition effect as the extent to which the difference between the growth rates of GDP and imports is explained by different compositions of GDP and imports. It is a product of two factors: (1) differences in the share of durables in imports and GDP and (2) differences in the growth of durables and other components following a crisis. If either of these differences is zero, composition cannot be an explanation for observing import losses controlling for output.

Table 4.9 and Figure 4.16 present the findings from this exercise. The impulse response functions of investment in machinery and equipment and the rest of GDP are shown in Figure 4.16 (bottom panel).29 The postcrisis decline in investment, and in particular in machinery and equipment, is much larger than the postcrisis decline in the rest of GDP over the same period. As presented in column (6) of Table 4.9, for this selected sample of crises, the composition effect can explain 5 to 13 percent of the unconditional import loss. It is important to keep in mind that these composition effects are calculated only from the different shares and post-crisis behavior of machinery and equipment relative to the rest of output; other composition effects—most notably, from consumer durables—may also be present. In addition, composition effects may already be reflected in the higher elasticity of imports to output that is allowed for in our baseline specification. Thus, these estimates of the size of the composition effect could be thought of as a lower bound.

Table 4.9.

Import Losses and Composition Effects

article image
Source: IMF staff calculations. Note: All estimates in columns (1), (2), and (4) are significant at the 1 percent level. Standard errors (not reported) are clustered by economy and corrected for heteroscedasticity. The actual import loss is estimated for the subsample of economies and crises for which disaggregated investment data are available. The share of import loss explained by composition effects in column (6) is calculated as the estimated composition effect in column (5) divided by the actual import loss multiplied by 100.

References

  • Abiad, Abdul, Giovanni Dell’Ariccia, and Bin Li, forthcoming, “Creditless Recoveries,” IMF Working Paper (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Alessandria, George, Joseph P. Kaboski, and Virgiliu Midrigan, forthcoming, “The Great Trade Collapse of 2008–09: An Inventory Adjustment?” IMF Economic Review, (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Altomonte, Carlo, and Gianmarco I.P. Ottaviano, 2009, “Resilient to the Crisis? Global Supply Chains and Trade Flows,” in The Great Trade Collapse: Causes, Consequences and Prospects, ed. by Richard Baldwin . Available at http://www.voxeu.org/index.php?q=node/4289.

    • Search Google Scholar
    • Export Citation

  • Amiti, Mary, and David E. Weinstein, 2009, “Exports and Financial Shocks,” NBER Working Paper No. 15556 (Cambridge, Massachusetts: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Anderson, James, and Eric Van Wincoop, 2003, “Gravity with Gravitas: A Solution to the Border Puzzle,” American Economic Review, Vol. 93, No. 1, pp. 170–92.

    • Search Google Scholar
    • Export Citation

  • Baldwin, Richard, 1988, “Hysteresis in Import Prices: The Beachhead Effect,” American Economic Review, Vol. 78, No. 4, pp. 773–85.

    • Search Google Scholar
    • Export Citation

  • Baldwin, Richard, ed., 2009, The Great Trade Collapse: Causes, Consequences and Prospects. Available at http://www.voxeu.orgindex.php?q=node/4297.

    • Search Google Scholar
    • Export Citation

  • Baldwin, Richard, and Daria Taglioni, 2006, “Gravity for Dummies and Dummies for Gravity Equations,” NBER Working Paper No. 12516 (Cambridge, Massachusetts: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Beim, David, and Charles Calomiris, 2001, Emerging Financial Markets, appendix to Chapter 1 (New York: McGraw-Hill/Irwin).

  • Bems, Rudolfs, Robert Johnson, and Kei-Mu Yi, forthcoming, “Demand Spillovers and the Collapse of Trade in the Global Recession,” IMF Economic Review (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Berman, Nicolas, and Philippe Martin, 2010, “The Vulnerability of Sub-Saharan Africa to the Financial Crisis: The Case of Trade,” CEPR Discussion Paper No. 7765 (London: Centre for Economic Policy Research).

    • Search Google Scholar
    • Export Citation

  • Bernard, Andrew, J. Bradford Jensen, Stephen J. Redding, and Peter K. Schott, 2009, “The Margins of U.S. Trade,” American Economic Review Papers and Proceedings, Vol. 99, No. 2, pp. 487–93.

    • Search Google Scholar
    • Export Citation

  • Borchert, Ingo, and Aaditya Mattoo, 2009, “The Crisis-Resilience of Services Trade,” Policy Research Working Paper 4917 (Washington: World Bank).

    • Search Google Scholar
    • Export Citation

  • Bown, Chad, 2010, “Fourth Quarter 2009 Protectionism Data: Requests for New Trade Barriers Fall for the First Time in Crisis; But Newly Imposed Barriers Increase,” a Monitoring Update to the Global Antidumping Database, February (Washington: World Bank).

    • Search Google Scholar
    • Export Citation

  • Caprio, Gerard, Daniela Klingebiel, Luc Laeven, and Guillermo Noguera, 2005, “Appendix: Banking Crisis Database,” in Systemic Financial Crises: Containment and Resolution, ed. by Patrick Honohan and Luc Laeven (Cambridge, United Kingdom: Cambridge University Press).

    • Search Google Scholar
    • Export Citation

  • Cerra, Valerie, and Sweta Saxena, 2008, “Growth Dynamics: The Myth of Economic Recovery,” American Economic Review, Vol. 98, No. 1, pp. 439–57.

    • Search Google Scholar
    • Export Citation

  • Chor, Davin, and Kalina Manova, 2010, “Off the Clif and Back? Credit Conditions and International Trade during the Global Financial Crisis” (unpublished; Stanford, California: Stanford University).

    • Search Google Scholar
    • Export Citation

  • Eaton, Jonathan, Sam Kortum, Brent Neiman, and John Romalis, 2010, “Trade and the Global Recession” (unpublished; Chicago, Illinois: University of Chicago). Available at http://home.uchicago.edu/~kortum/papers/EKNR.pdf.

    • Search Google Scholar
    • Export Citation

  • Feenstra, Robert, Robert Lipsey, Haiyan Deng, Alyson Ma, and Hengyong Mo, 2005, “World Trade Flows: 1962–2000,” NBER Working Paper No. 11040 (Cambridge, Massachusetts: National Bureau of Economic Research).

    • Search Google Scholar
    • Export Citation

  • Frankel, Jeffrey, Ernesto Stein, and Shang-Jin Wei, 1996, “Regional Trading Arrangements: Natural or Supernatural?” American Economic Review, Vol. 86, No. 2, pp. 52–56.

    • Search Google Scholar
    • Export Citation

  • Friedman, Jed, and James Levinsohn, 2003, “The Distributional Impacts of Indonesia’s Financial Crisis on Household Welfare: A ‘Rapid Response’ Methodology,” The World Bank Economic Review, Vol. 16, No. 3, pp. 397–423.

    • Search Google Scholar
    • Export Citation

  • Freund, Caroline, 2009, “The Trade Response to Global Downturns: Historical Evidence,” Policy Research Working Paper No. 5015 (Washington: World Bank).

    • Search Google Scholar
    • Export Citation

  • Glick, Reuven, and Alan M. Taylor, 2010, “Collateral Damage: Trade Disruption and the Economic Impact of War,” The Review of Economics and Statistics, Vol. 92, No. 1, pp. 102–27.

    • Search Google Scholar
    • Export Citation

  • Global Trade Alert, 2010, “Unequal Compliance: The 6th GTA Report” (London). Available at http://gta-analysis/unequal-compliance-6th-gta-report.

    • Search Google Scholar
    • Export Citation

  • Gregory, Rob, Christian Henn, Brad McDonald and Mika Saito, 2010, “Trade and the Crisis: Protect or Recover,” IMF Staff Position Note 10/07 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Iacovone, Leonardo, and Veronika Zavacka, 2009, “Banking Crises and Exports: Lessons from the Past,” Policy Research Working Paper No. 5016 (Washington: World Bank).

    • Search Google Scholar
    • Export Citation

  • International Monetary Fund (IMF), 2008, “Structural Reforms and Economic Performance in Advanced and Developing Countries,” Research Department paper. Available at http://www.imf.org/external/np/res/docs/2008/0608.htm.

    • Search Google Scholar
    • Export Citation

  • Johnson, Robert C., and Guillermo Noguera, 2010, “Accounting for Intermediates: Production Sharing and Trade in Value Added” (unpublished; Hanover, New Hampshire: Dartmouth College).

    • Search Google Scholar
    • Export Citation

  • Kaminsky, Graciela, L., and Carmen M. Reinhart, 1999, “The Twin Crises: The Causes of Banking and Balance of Payments Problems,” American Economic Review, Vol. 89, No. 3, pp. 473–500.

    • Search Google Scholar
    • Export Citation

  • Kwack, Sung Yeung, Choong Y. Ahn, Young S. Lee, and Doo Y. Yang, 2007, “Consistent Estimates of World Trade Elasticities and an Application to the Effects of Chinese Yuan (RMB) Appreciation,” Journal of Asian Economics, Vol. 18, No. 2, pp. 314–30.

    • Search Google Scholar
    • Export Citation

  • Laeven, Luc, and Fabian Valencia, 2008, “Systemic Banking Crises: A New Database,” IMF Working Paper 08/224 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Laeven, Luc, and Fabian Valencia, , 2010, “Resolution of Banking Crises: The Good, the Bad, and the Ugly,” IMF Working Paper 10/146 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Lane, Philip R., and Gian Maria Milesi-Ferretti, 2007, “The External Wealth of Nations Mark II,” Journal of International Economics, Vol. 73, No. 2, pp. 223–50.

    • Search Google Scholar
    • Export Citation

  • Levchenko, Andrei, Logan Lewis, and Linda Tesar, forthcoming, “The Collapse of International Trade during the 2008-2009 Crisis: In Search of the Smoking Gun,” IMF Economic Review (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Martin, Philippe, Tierry Mayer, and Mathias Thoenig, 2008, “Make Trade, Not War?” Review of Economic Studies, Vol. 75, No. 3, pp. 865–900.

    • Search Google Scholar
    • Export Citation

  • O’Rourke, Kevin, 2009, “Government Policies and the collapse in Trade during the Great Depression,” in The Great Trade Collapse: Causes, Consequences and Prospects, ed. by Richard Baldwin . Available at http://www.voxeu.org/index.php?q=node/4267.

    • Search Google Scholar
    • Export Citation

  • Pula, Gabor, and Tuomas Peltonen, 2009, “Has Emerging Asia Decoupled? An Analysis of Production and Trade Linkages Using the Asian International Input-Output Table,” ECB Working Paper No. 993 (Frankfurt: European Central Bank).

    • Search Google Scholar
    • Export Citation

  • Reinhart, Carmen, and Kenneth Rogoff, 2009, This Time Is Different: Eight Centuries of Financial Folly (Princeton, New Jersey: Princeton University Press).

    • Search Google Scholar
    • Export Citation

  • Romer, Christina, and David Romer, 2010, “The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks,” American Economic Review, Vol. 100, No. 3, pp. 763–801.

    • Search Google Scholar
    • Export Citation

  • Ronci, Marcio, 2004, “Trade Finance and Trade Flows: Panel Data Evidence from 10 Crises,” IMF Working Paper 04/225 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Rose, Andrew, 2000, “One Money, One Market: Estimating the Effect of Common Currencies on Trade,” Economic Policy, Vol. 15, No. 30, pp. 7–46.

    • Search Google Scholar
    • Export Citation

  • Senhadji, Abdelhak, 1998, “Time-Series Estimation of Structural Import Demand Equations: A Cross-country Analysis,” IMF Staff Papers, Vol. 45, No. 2 (Washington: International Monetary Fund).

    • Search Google Scholar
    • Export Citation

  • Sturzenegger, Federico, and Jeromin Zettelmeyer, 2006, Debt Defaults and Lessons from a Decade of Crises, Chapter 1, Table 1 (Cambridge, Massachusetts: MIT Press).

    • Search Google Scholar
    • Export Citation

  • Thursby, Marie, and Jerry Thursby, 1987, “Bilateral Trade Flows, the Linder Hypothesis, and Exchange Risk,” Review of Economics and Statistics, Vol. 69, No. 3, pp. 488–95.

    • Search Google Scholar
    • Export Citation

  • World Bank, 2002, Global Development Finance, appendix on commercial debt restructuring (Washington: World Bank).

  • World Trade Organization (WTO), Organization for Economic Cooperation and Development (OECD), and United Nations Conference on Trade and Development (UNCTAD), 2010, “Report on G20 Trade and Investment Measures (November 2009 to Mid-May 2010)” (Paris, June). Available at www.unctad.org/templates/Download.asp?docid=13369&lang=1.

    • Search Google Scholar
    • Export Citation

The main authors of this chapter are Abdul Abiad, Prachi Mishra, and Petia Topalova, with support from Gavin Asdorian, Stephanie Denis, and Andy Salazar. Donald Davis was the external consultant.

1

See Baldwin (2009) and papers therein for a comprehensive analysis of the recent collapse in global trade.

2

Similar in spirit and methodology to this chapter is the analysis by Berman and Martin (2010) of the vulnerability of sub-Saharan African economies to financial crises in advanced economies. They find that a financial crisis has a moderate but long-lasting effect on trading partners’ exports but that the effect is larger for African exporters.

3

Estimating the “full” bilateral gravity model in differences gives similar results, as described in Appendix 4.2, which outlines the robustness tests performed as part of this analysis.

4

A related but distinct explanation is that firms chose to run down inventories in response to increased uncertainty; see Alessandria, Kaboski, and Midrigan (forthcoming) for evidence from the United States.

5

As discussed below, our banking crisis episodes are taken from Laeven and Valencia (2010).

6

Of course, the precrisis trend may reflect unsustainable growth dynamics that ultimately led to a crisis and hence may not be considered “normal.” The methodology used in this chapter does not rely on deviations from precrisis trends, but estimates normal trade flows given countries’ fundamentals.

7

Among the banking and debt crises in the Laeven-Valencia data set are 10 cases in which the two coincide. An analysis of these “twin banking and debt crises” suggests that trade dynamics following these episodes were qualitatively similar to those with only one type of crisis, although the effects were slightly more accentuated. We do not highlight these in the chapter, however, given the limited number of observations.

8

See Baldwin and Taglioni (2006) for a survey of the use of gravity models in the literature, as well as the pitfalls faced in estimating them.

9

Most gravity models in the literature are typically estimated in levels and also include GDP per capita. When estimating the model in changes, however, there is a very high correlation between the growth rates of GDP and GDP per capita, and so we exclude the latter in our baseline specification. The results reported below are very similar if one includes own and trading partners’ growth in GDP per capita.

10

The larger and more persistent losses in imports relative to exports may reflect the consequences of weak balance sheets (or other financial difficulties) for domestic demand. Although lower domestic demand directly reduces import volumes, it may also reduce residents’ consumption of exportable goods, freeing up room for more exports.

11

Specifically, we allow the elasticity to vary across regions as defined in the World Economic Outlook database (defined in Appendix 4.1) and also to vary between the pre-1990 and post-1990 periods. Assuming a uniform elasticity results in larger estimated import losses, as reported in Appendix 4.2.

12

It should be noted that the behavior of imports illustrated in Figure 4.3 covers only 13 economies and includes both crisis and noncrisis economies, whereas Figure 4.6 shows the behavior of imports in these product groups for crisis economies only. In addition, Figure 4.3 presents unconditional import losses, whereas Figure 4.6 shows losses after controlling for output and other variables.

13

If past crises typically occurred in lower-income countries with weak social safety nets, it is possible that crises and the resulting (uncushioned) rise in unemployment would lead to declines even in consumer nondurables. See, for example, Fried-man and Levinsohn (2003) for an analysis of the impact of the 1997 Asian crisis on Indonesian households. The effects would remain even in the regressions that control for output if the measured GDP decline failed to adequately capture the adverse impact on poorer households.

14

We measure the intensity of production linkages between two countries by the ratio of value-added to exports (VAX) of Johnson and Noguera (2010). The VAX ratio, constructed from input-output tables and bilateral trade across a large sample of countries, captures the extent to which the exports from country A to country B are used as intermediate goods in the production of country B’s exports.

15

See Baldwin (1988), who proposed beachhead effects as one potential explanation for hysteresis in international trade. Our findings are also consistent with other studies, such as that by Altomonte and Ottaviano (2009), who note the resilience of trade between western and central Europe during the recent crisis, and Bernard and others (2009), who document the resilience of intra-Asian “supply chain” trade following the Asian crisis.

16

Specifically, Freund (2009) defines global downturns as years when world real GDP growth is (1) below 2 percent, (2) more than 1.5 percentage points below the previous five-year average, and (3) at its minimum relative to the previous two years and the following two years. The procedure identifies the following global downturns: 1975, 1982, 1991, 2001, and 2008.

17

See Amiti and Weinstein (2009), Iacovone and Zavacka (2009), and Chor and Manova (2010) for the importance of trade finance and credit in explaining export performance during crises.

18

For example, the Great Depression was followed by a “wholesale rise in protectionism,” which not only slowed the process of economic recovery but created lasting protectionist legacies in a number of countries (see O’Rourke, 2009).

19

The number of antidumping measures imposed by a country also does not increase significantly following crises.

20

As noted above, the estimated elasticity of imports with respect to output in the baseline specification varies across regions and over time. These elasticities are discussed in Appendix 4.2.

21

Estimates of this elasticity in the literature vary by horizon (Senhadji, 1998, for example, finds an elasticity close to zero in the short term but higher than 1 in the long term), as well as across countries (Kwack and others, 2007, have elasticities that range from 0.4 to 1.2 across a wide range of countries). Using the higher estimates found in the literature will, of course, increase the fraction of import loss that can be accounted for by postcrisis declines in the REER.

22

Box 4.1 uses a more sophisticated framework and more disaggregated data to obtain more precise estimates of the role of the composition effect in explaining the most recent trade collapse.

23

One possibility is that a decline in credit availability following a crisis affects demand for durables more than demand for other goods.

24

These findings are robust to the use of alternative proxies that more closely track trade finance as opposed to the measure of general credit conditions that is used here. Specifically, it is robust to using the change in the outstanding stock of external short-term debt, which includes short-term credit for trade (Ronci, 2004).

25

We focus on import dynamics here, since the chapter’s results suggest that imports are where the impact of a crisis on trade is primarily manifested.

26

The results from estimating equation (4.2) in levels or changes are identical because, as in Chapter 4 of the October 2009 World Economic Outlook, the import losses are normalized so that the loss in the year before the crisis (t – 1) is zero. The primary differences between the procedure used here and in Chapter 4 of the October 2009 World Economic Outlook are the following: (1) the definition of crisis (debt crises combined with banking crises versus banking crises only), (2) the precrisis window used to calculate the trend [(t – 7) to (t – 1) versus (t – 10) to (t – 3)], and (3) the choice of dependent variable (imports versus GDP per capita).

27

The overall output loss is slightly lower than the loss of services and industry due to the resilience of agricultural production to crises.

28

The definition of “durables” in the trade and output data is not identical because these series come from different, not always comparable, data sources. However, it is unlikely that differences in definitions account for the differences in the shares of these goods in imports and output.

29

Given the share of durables in GDP, as well as the decline in overall GDP, we can also calculate how much demand for other components of GDP falls after crises.

Annex: IMF Executive Board Discussion of the Outlook, September 2010

The following remarks by the Acting Chair were made at the conclusion of the Executive Board’s discussion of the World Economic Outlook on September 20, 2010.

Executive Directors observed that the global economic recovery is proceeding broadly as projected, despite disturbances in financial markets. The recovery is losing momentum temporarily during the second half of 2010 and will likely remain weak in the first half of 2011, as extraordinary policy stimulus is gradually withdrawn. Directors welcomed signs that financial conditions have begun to normalize, aided by policy coordination and announcements of a front-loading of fiscal adjustment in Europe. A more robust, self-sustaining global recovery will require progress in achieving both internal and global demand rebalancing, sup-ported by healthy financial systems.

Directors noted that the observed asymmetry in growth performances will likely persist. In most advanced and a few emerging market economies, recoveries are proceeding at a sluggish pace, and large internal adjustments remain needed to achieve internal rebalancing from stimulus-led to private-sector-led growth. On the other hand, growth in many emerging market and developing economies continues to be vigorous, on the back of improved macroeconomic policy frameworks and a stronger financial footing. Downside risks to near-term global growth remain elevated and concentrated in advanced economies. These emanate from heightened uncertainty in financial markets, fragile real estate markets, continued household deleveraging, and persistently high unemployment. However, the probability of a sharp global slowdown, including stagnation or contraction in advanced economies, appears low.

Directors agreed that fiscal consolidation is a top priority in countries with relatively high public debt. They highlighted the urgency of adopting credible strategies for medium-term consolidation and debt stabilization, including through legislation where necessary. At the same time, policymakers should stand ready to act if global growth threatens to slow appreciably more than expected. In this regard, consideration could be given to postponing consolidation in countries with fiscal room and credibility to do so. In all but the most vulnerable countries, automatic stabilizers should be allowed to operate. Directors stressed that medium-term consolidation plans should be based on realistic growth projections and include reforms to limit rapidly escalating spending programs such as pension entitlements and public health care and tax incentives to boost the supply potential and discourage debt.

In light of subdued inflation pressures, Directors generally considered that monetary policy in most advanced economies should remain highly accommodative, including through unconventional measures if needed, and should be the first line of defense against any larger-than-projected weakening of activity as fiscal stimulus is being unwound. In emerging market economies with rising inflation or asset price pressures, monetary tightening has been broadly appropriate. For all economies, the implications of fiscal consolidation and developments in financial and asset markets for inflation would also need to be taken into account when setting monetary policy.

Directors underscored the urgent need for restoring financial sector health and making progress in regulatory reforms in a coordinated manner, especially among advanced economies. To enable an early exit from fiscal support as well as address legacy problems, priorities include restructuring and resolving weak financial institutions; implementing measures to shore up bank capital adequacy, liquidity, and stability of funding sources; and improving coordination of supervision to avoid rapid cross-border amplification of shocks. Further advancement toward building a stronger financial regulatory framework is crucial to underpin market confidence and enhance global financial stability.

Directors emphasized that medium-term growth prospects depend on progress in implementing structural policies to give forceful impetus to global demand rebalancing. In this regard, many emerging market economies would need to further reorient toward domestic demand, not only because import recovery in advanced economies will likely trail behind precrisis trends, but also to achieve balanced growth that addresses their own consumption and investment needs. For economies with excessive external surpluses, this would entail allowing further exchange rate flexibility and appreciation in response to sustained capital inflows, while safeguarding financial stability with macroprudential or other targeted measures. These measures should be complemented by structural reforms aimed at enhancing social safety nets and shifting toward optimal saving-investment patterns. Similarly, measures to boost net exports would be crucial for economies with excessive current account deficits. Continued fiscal adjustment and financial sector reforms that discourage excessive spending are also key.

Directors noted that structural policies that strengthen growth over the medium term would help support the required normalization of macroeconomic policies in advanced economies. Labor market policies, coupled with complementary product and services market reforms, should aim to promote competition and enhance growth and job creation, and with sufficient support for the unemployed.

Directors underscored the critical importance of continued policy effort and coordination at both the regional and global levels—as demonstrated during the global crisis and more recently during the European sovereign debt market turmoil. While policy requirements now differ considerably across countries, it is essential that countries continue to work together toward the common goal of achieving strong, sustained, and balanced growth over the medium term. Directors also emphasized the need to avoid negative spillovers as well as trade and investment protectionism.

Statistical Appendix

The Statistical Appendix presents historical data, as well as projections. It comprises five sections: Assumptions, What’s New, Data and Conventions, Classification of Countries, and Statistical Tables. The assumptions underlying the estimates and projections for 2010–11 and the medium-term scenario for 2012–15 are summarized in the first section. The second section presents a brief description of changes to the database and statistical tables. The third section provides a general description of the data and of the conventions used for calculating country group composites. The classification of countries in the various groups presented in the World Economic Outlook is summarized in the fourth section.

The last, and main, section comprises the statistical tables. Data in these tables have been com-piled on the basis of information available through late September 2010. The figures for 2010 and beyond are shown with the same degree of precision as the historical figures solely for convenience; because they are projections, the same degree of accuracy is not to be inferred.

Assumptions

Real effective exchange rates for the advanced economies are assumed to remain constant at their average levels during the period August 4–September 1, 2010. For 2010 and 2011, these assumptions imply average U.S. dollar/SDR conversion rates of 1.516 and 1.520, U.S. dollar/euro conversion rates of 1.308 and 1.284, and yen/U.S. dollar conversion rates of 88.5 and 84.2, respectively.

It is assumed that the price of oil will average $76.20 a barrel in 2010 and $78.75 a barrel in 2011.

Established policies of national authorities are assumed to be maintained. The more specific policy assumptions underlying the projections for selected economies are described in Box A1.

With regard to interest rates, it is assumed that the London interbank offered rate (LIBOR) on six-month U.S. dollar deposits will average 0.6 percent in 2010 and 0.8 percent in 2011, that three-month euro deposits will average 0.8 percent in 2010 and 1.0 percent in 2011, and that six-month yen deposits will average 0.6 percent in 2010 and 0.4 percent in 2011.

With respect to introduction of the euro, on December 31, 1998, the Council of the European Union decided that, effective January 1, 1999, the irrevocably fixed conversion rates between the euro and currencies of the member states adopting the euro are as follows.

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Established on January 1, 2008.

Established on January 1, 2001.

Established on January 1, 2008.

Established on January 1, 2009.

Established on January 1, 2007.

Economic Policy Assumptions Underlying the Projections for Selected Economies

Fiscal Policy Assumptions

The short-term fiscal policy assumptions used in the World Economic Outlook (WEO) are based on officially announced budgets, adjusted for differences between the national authorities and the IMF staff regarding macroeconomic assumptions and projected fiscal outturns. The medium-term fiscal projections incorporate policy measures that are judged likely to be implemented. In cases where the IMF staff has insufficient information to assess the authorities’ budget intentions and prospects for policy implementation, an unchanged structural primary balance is assumed, unless indicated otherwise. Specific assumptions used in some of the advanced economies follow (see also Tables B5, B6, B7, and B9 in the statistical Appendix for data on fiscal net lending/borrowing and structural balances).1

Argentina: The 2010 forecasts are based on the 2009 outturn and IMF staff assumptions. For the outer years, the IMF staff assumes unchanged policies.

Australia: Fiscal projections are based on the 2010–11 budget, 2010 economic statement, 2010 pre-election economic and fiscal outlook, and IMF staff projections.

Austria: Fiscal projections for 2010 are based on the authorities’ budget, adjusted for differences in the IMF staff’s macro framework. For 2011 the IMF staff includes the central government’s spending ceilings (approved by Parliament) and the health insurance package savings for all years (2011–15).

Belgium: Projections for 2010 are IMF staff estimates based on the 2010 budgets approved by the federal, regional, and community parliaments and further strengthened by the Intergovernmental Agreement 2009–10. Projections for the outer years are IMF staff estimates, assuming unchanged policies.

Brazil: The 2010 forecasts are based on the budget law and IMF staff assumptions. For the outer years, the IMF staff assumes unchanged policies, with a further increase in public investment in line with the authorities’ intentions.

Canada: Projections use the baseline forecasts in the latest Budget 2010—Leading the Way on Jobs and Growth. The IMF staff makes some adjustments to this forecast for differences in macroeconomic projections. The IMF staff forecast also incorporates the most recent data releases from Finance Canada and Statistics Canada, including federal, provincial, and territorial budgetary out-turns through the end of 2010:Q1.

China: For 2010–11, the government is assumed to continue and complete the stimulus program it announced in late 2008, although the lack of details published on this package complicates IMF staff analysis. Specifically, the IMF staff assumes the stimulus is not withdrawn in 2010, and so there is no significant fiscal impulse. Stimulus is withdrawn in 2011, resulting in a negative fiscal impulse of about 1 percent of GDP (reflecting both higher revenue and lower spending).

Denmark: Projections for 2010–11 are aligned with the latest official budget estimates and the underlying economic projections, adjusted where appropriate for the IMF staff’s macroeconomic assumptions. For 2012–15, the projections incorporate key features of the medium-term fiscal plan as embodied in the authorities’ 2009 Convergence Program submitted to the European Union.

France: Projections for 2010 are based on the 2010 budget and the latest Stability Program and are adjusted for differences in macroeconomic assumptions. Projections for the outer years incorporate the IMF staff’s assessment of current policies and implementation of announced adjustment measures.

Germany: Projections for 2010 are based on the 2010 budget, adjusted for the differences in the IMF staff’s macro framework and estimates of the implementation of the fiscal stimulus measures. The IMF staff’s projections for 2011 and beyond reflect the authorities’ adopted core federal government budget plan, adjusted for the differences in the IMF staff’s macro framework and assumptions on fiscal developments in state and local governments, the social insurance system, and special funds.

Greece: Macroeconomic and fiscal projections for 2010 and the medium term are consistent with the policies agreed to between IMF staff and the authorities in the context of the Stand-By Arrangement. Fiscal projections assume a strong front-loaded fiscal adjustment in 2010, followed by further measures in 2011–13. Growth is expected to bottom out in late 2010 and gradually rebound after that, coming into positive territory in 2012.

Hong Kong SAR: Projections are based on the authorities’ medium-term fiscal projections.

Hungary: The 2010 forecast is based on the implementation of the budget and the macro framework discussed during the Sixth Review of the Stand-By Arrangement. The IMF staff assumes measures will be undertaken in addition to those outlined by the authorities for 2011–15: in 2011, 1¾ percent of GDP, to achieve a fiscal target of 2.8 percent of GDP and in the medium term to ensure fiscal sustainability.

India: Historical data are based on budgetary execution data. Projections are based on available information on the authorities’ fiscal plans, with some adjustments for the IMF staff’s assumptions. Projections are based on the budget itself as well as the semiannual budget review. Sub-national data are incorporated with a lag of up to two years; general government data are thus finalized long after central government data. IMF presentation differs from Indian national accounts data, particularly regarding subsidies and certain loans.

Indonesia: The 2009 outturn for the overall fiscal deficit was 1.6 percent of estimated GDP. The outturn was lower than the revised budget deficit, largely as a result of lower interest payments and underspending on personnel, material goods, and other spending. About 85 percent of the announced 2009 stimulus measures were implemented (1.1 percent of GDP), with revenue measures comprising nearly three-quarters of the total package. The 2010 revised budget draft envisages a budget deficit higher than projected by the IMF staff. The IMF staff builds in a cushion for a track record of underexecution, the 2010 deficit is likely to be below the announced deficit target. The IMF staff’s overall deficit projection is about 1.5 percent of GDP.

Ireland: Fiscal projections for 2010 are based on the 2010 budget, adjusted for financial sector support and differences in macroeconomic assumptions between the IMF staff and the authorities. So far during 2010, the government has injected about €22 billion in capital to banks. The Central Statistics Office of Ireland has determined that €8.3 billion of the €22 billion should be reported as expenditure in the budget. The statistical treatment of the remaining amount is to be determined at a later stage. On this basis, the IMF staff projections include the €8.3 billion in the 2010 deficit. For 2011–12, IMF staff projections incorporate most of the adjustment efforts announced by the authorities in their Stability Program Update, although two-thirds of these measures have not been specified or agreed to by the government. For the remainder of the projection period and in the absence of specifically identified measures, the projections do not incorporate further budgetary adjustments. The authorities have announced their intention to further lower the deficit below 3 percent of GDP by 2014 and have identified broad areas in which to target savings but have yet to specify and put in place measures to realize these savings.

Italy: The fiscal projections incorporate the impact of the 2010 budget law and fiscal adjustment measures for 2010–13 as approved by the government in May 2010 and modified during parliamentary approval during June–July. The IMF staff projections are based on the authorities’ estimates of the policy scenario, including the above medium-term fiscal consolidation package and adjusted mainly for differences in the macroeconomic assumptions and for less optimistic assumptions concerning the impact of revenue administration measures (to combat tax evasion). After 2013, a constant structural primary balance (net of one-time items) is assumed.

Japan: The 2010 projections assume that fiscal plans will be implemented as announced by the government. The medium-term projections typically assume that expenditure and revenue of the general government are adjusted in line with current underlying demographic and economic trends (excluding fiscal stimulus).

Korea: The fiscal projections assume that fiscal policies will be implemented in 2010 as announced by the government. The 2010 budget scales back stimulus measures relative to 2009, implying a negative fiscal impulse estimated at 2 percent of GDP. Expenditure numbers for 2010 correspond to the expenditure numbers presented in the government’s budget proposal. Revenue projections reflect the IMF staff’s macroeconomic assumptions, adjusted for the estimated costs of tax measures included in the multiyear stimulus package introduced last year and discretionary revenue-raising measures included in the 2010 budget. The medium-term projections assume that the government will continue with its consolidation plans and balance the budget (excluding social security funds) in 2014.

Mexico: Fiscal projections are based on (1) the IMF staff’s macroeconomic projections; (2) the modified balanced budget rule under the Fiscal Responsibility Legislation, including the use of the exceptional clause; and (3) the authorities’ projections for spending, including for pensions and health care, and for wage restraint. For 2010–11, projections take into account departure from the balanced budget target under the exceptional clause of the fiscal framework, which allows for a small deficit reflecting cyclical deterioration in revenues.

Netherlands: Fiscal projections for the period 2009–11 are based on Bureau for Economic Policy Analysis budget projections, after adjusting for differences in macroeconomic assumptions. For the remainder of the projection period, the projection assumes unchanged policies.

New Zealand: Fiscal projections are based on the authorities’ 2010 budget and IMF staff estimates. The New Zealand fiscal accounts switched to generally accepted accounting principles beginning in fiscal year 2006/07, with no comparable historical data.

Portugal: For 2010, fiscal projections are based on the 2010 budget, adjusted for differences between the government’s and the IMF staff’s macroeconomic assumptions. For 2011 and beyond, the IMF staff largely incorporates the specific fiscal measures in the medium-term fiscal plan, adjusted for the IMF staff’s macroeconomic projections.

Russia: Projections for 2010 are based on the nominal expenditures in the 2010 budget, including the June supplementary budget, and the IMF staff’s revenue projections. Projections for 2011–13 are based on the non-oil deficit in percent of GDP implied by the draft medium-term budget and on the IMF staff’s revenue projections. The IMF staff assumes an unchanged non-oil federal government balance in percent of GDP during 2013–15.

Saudi Arabia: The authorities systematically underestimate revenues and expenditures in the budget relative to actual outturns. IMF staff projections of oil revenues are based on WEO baseline oil prices discounted by 5 percent, reflecting the higher sulfur content in Saudi crude oil. Regarding non-oil revenues, customs receipts are assumed to grow in line with imports, investment income in line with the London interbank offered rate (LIBOR), and fees and charges as a function of non-oil GDP. On the expenditure side, wages are assumed to rise above the natural rate of increase, reflecting a salary increase of 15 percent distributed during 2008–10, and goods and services are projected to grow in line with inflation over the medium term. In 2010 and 2013, 13th-month pay is awarded based on the lunar calendar. Interest payments are projected to decline in line with the authorities’ policy of repaying public debt. Capital spending in 2010 is projected to be higher than in the budget by about 32 percent and in line with the authorities’ announcement of $400 billion in spending over the medium term. The pace of spending is projected to slow over the medium term, leading to a tightening of the fiscal stance.

Singapore: For fiscal year 2010/11, projections are based on budget numbers. For the remainder of the projection period, the IMF staff assumes unchanged policies.

South Africa: Fiscal projections are based on the authorities’ 2010 intentions as stated in the budget review published February 17, 2010, and on discussions conducted during the June Article IV consultation.

Spain: For 2010, fiscal projections incorporate the impact of measures in the 2010 budget, the latest Stability Program, and a May fiscal package. For 2011 and beyond, fiscal projections are based on the authorities’ medium-term plan, adjusted for the IMF staff’s macroeconomic projections.

Sweden: Fiscal projections for 2010 are in line with the authorities’ projections. The impact of cyclical developments on the fiscal accounts is calculated using the Organization for economic Cooperation and Development’s latest semi-elasticity.

Switzerland: Projections for 2009–15 are based on IMF staff calculations, which incorporate measures to restore balance in the federal accounts and strengthen social security finances.

Turkey: Fiscal projections assume the authorities adhere to their budget target for 2010 and to their known policy intentions as stated in the Medium-Term Program unveiled in September 2009.

United Kingdom: Fiscal projections are based on the authorities’ 2010 budget, announced in June 2010. These projections incorporate the announced medium-term consolidation plans from 2010 onward. The projections are adjusted for differences in forecasts of macroeconomic and financial variables.

United States: Fiscal projections are based on policies outlined in the Administration’s Mid-Session Budget Review for fiscal year 2011. The authorities’ federal projections are adjusted by the IMF staff for differences in the budget forecasts of key macroeconomic and financial variables and are converted to a general government basis. The estimates of fiscal deficit are adjusted for one-off items (the cost of financial sector support).

Monetary Policy Assumptions

Monetary policy assumptions are based on the established policy framework in each country. In most cases, this implies a nonaccommodative stance over the business cycle: official interest rates will increase when economic indicators suggest that inflation will rise above its acceptable rate or range, and they will decrease when indicators suggest that prospective inflation will not exceed the acceptable rate or range, that prospective output growth is below its potential rate, and that the margin of slack in the economy is significant. On this basis, the LIBOR on six-month U.S. dollar deposits is assumed to average 0.6 percent in 2010 and 0.8 percent in 2011 (see Table 1.1). The rate on three-month euro deposits is assumed to average 0.8 percent in 2010 and 1.0 percent in 2011. The interest rate on six-month Japanese yen deposits is assumed to average 0.6 percent in 2010 and 0.4 percent in 2011.

1 The output gap is actual minus potential output, as a percent of potential output. Structural balances are expressed as a percent of potential output. The structural budget balance is the budgetary position that would be observed if the level of actual output coincided with potential output. Changes in the structural budget balance consequently include effects of temporary fiscal measures, the impact of fluctuations in interest rates and debt-service costs, and other noncyclical fluctuations in the budget balance. The computations of structural budget balances are based on IMF staff estimates of potential GDP and revenue and expenditure elasticities (see the October 1993 World Economic Outlook, Annex I). Net debt is defined as gross debt minus financial assets of the general government, which include assets held by the social security insurance system. Estimates of the output gap and of the structural balance are subject to significant margins of uncertainty.

See Box 5.4 of the October 1998 World Economic Outlook for details on how the conversion rates were established.

What’s New

  • Starting with the October 2010 World Economic Outlook, the emerging and developing economies’ Western Hemisphere region has been renamed Latin America and the Caribbean (LAC), the country group composites will be calculated only when 90 percent or more of the weighted data are represented, and data for Kosovo are included in the emerging and developing economies aggregates.

  • Country weights calculated as nominal GDP valued at purchasing-power-parity (PPP) exchange rates as a share of total world GDP have been updated to reflect revisions to countries’ historical GDP data and projections.

Data and Conventions

Data and projections for 183 economies form the statistical basis for the World Economic Outlook (the WEO database). The data are maintained jointly by the IMF’s Research Department and regional departments, with the latter regularly updating country projections based on consistent global assumptions.

Although national statistical agencies are the ultimate providers of historical data and definitions, international organizations are also involved in statistical issues, with the objective of harmonizing methodologies for the compilation of national statistics, including analytical frameworks, concepts, definitions, classifications, and valuation procedures used in the production of economic statistics. The WEO database reflects information from both national source agencies and international organizations.

Most countries’ macroeconomic data presented in the WEO conform broadly to the 1993 version of the System of National Accounts (SNA). The IMF’s sector statistical standards—the Balance of Payments Manual, Fifth Edition (BPM5), the Monetary and Financial Statistics Manual (MFSM 2000), and the Government Finance Statistics Manual 2001 (GFSM 2001)—have all been aligned with the 1993 SNA. These standards reflect the IMF’s special interest in countries’ external positions, financial sector stability, and public sector fiscal positions. The process of adapting country data to the new standards begins in earnest when the manuals are released. However, full concordance with the manuals is ultimately dependent on the provision by national statistical compilers of revised country data; hence, the World Economic Outlook estimates are only partially adapted to these manuals. Nonetheless, for many countries the impact of conversion to the updated standards will be small on major balances and aggregates. Many other countries have partially adopted the latest standards and will continue implementation over a period of years.

Consistent with the recommendations of the 1993 SNA, several countries have phased out their traditional fixed-base-year method of calculating real macroeconomic variable levels and growth by switching to a chain-weighted method of computing aggregate growth. The chain-weighted method frequently updates the weights of price and volume indicators. It allows countries to measure GDP growth more accurately by reducing or eliminating the downward biases in volume series built on index numbers that average volume components using weights from a year in the moderately distant past. Currently, macroeconomic price and volume data for the following economies are based on chain-weighted methodology: Albania, Algeria, Australia, Austria, Azerbaijan, Belarus, Belgium, Bulgaria, Canada, Colombia, Cyprus, the Czech Republic, Denmark, Estonia, the euro area, Finland, France, Georgia, Germany, Greece, Guatemala, Hong Kong SAR, Hungary, Iceland, Ireland, Israel, Italy, Japan, Kazakhstan, Korea, Lithuania, Luxembourg, Malta, Mauritania, the Netherlands, New Zealand, Norway, Poland, Portugal, Romania, Russia, Singapore, Slovenia, Spain, Sweden, Switzerland, Ukraine, the United Kingdom, and the United States.

Composite data for country groups in the World Economic Outlook are either sums or weighted averages of data for individual countries. Unless noted otherwise, multiyear averages of growth rates are expressed as compound annual rates of change.1 Arithmetically weighted averages are used for all data for the emerging and developing economies group except inflation and money growth, for which geometric averages are used. The following conventions apply.

  • Country group composites for exchange rates, interest rates, and growth rates of monetary aggregates are weighted by GDP converted to U.S. dollars at market exchange rates (averaged over the preceding three years) as a share of group GDP.

  • Composites for other data relating to the domestic economy, whether growth rates or ratios, are weighted by GDP valued at PPP as a share of total world or group GDP.2

  • Composites for data relating to the domestic economy for the euro area (16 member countries throughout the entire period unless noted other-wise) are aggregates of national source data using GDP weights. Annual data are not adjusted for calendar-day effects. For data prior to 1999, data aggregations apply 1995 European currency unit exchange rates.

  • Composite unemployment rates and employment growth are weighted by labor force as a share of group labor force.

  • Composites relating to the external economy are sums of individual country data after conversion to U.S. dollars at the average market exchange rates in the years indicated for balance of payments data and at end-of-year market exchange rates for debt denominated in currencies other than U.S. dollars. Composites of changes in foreign trade volumes and prices, however, are arithmetic averages of percent changes for individual countries weighted by the U.S. dollar value of exports or imports as a share of total world or group exports or imports (in the preceding year).

  • Unless noted otherwise, group composites are computed if 90 percent or more of the share of group weights is represented.

Classification of Countries

Summary of the Country Classification

The country classification in the World Economic Outlook divides the world into two major groups: advanced economies, and emerging and developing economies.3 This classification is not based on strict criteria, economic or otherwise, and it has evolved over time. The objective is to facilitate analysis by providing a reasonably meaningful method for organizing data. Table A provides an overview of the country classification, showing the number of countries in each group by region and summarizing some key indicators of their relative size (GDP valued by PPP, total exports of goods and services, and population).

Some countries remain outside the country classification and therefore are not included in the analysis. Cuba and the Democratic People’s Republic of Korea are not IMF members, and their economies therefore are not monitored by the IMF. San Marino is omitted from the group of advanced economies for lack of a fully developed database. Likewise, the Marshall Islands, the Federated States of Micronesia, Palau, Somalia, and Tuvalu are omitted from the emerging and developing economies group composites because of data limitations.

General Features and Composition of Groups in the World Economic Outlook Classification

Advanced Economies

The 33 advanced economies are listed in Table B. The seven largest in terms of GDP—the United States, Japan, Germany, France, Italy, the United Kingdom, and Canada—constitute the subgroup of major advanced economies, often referred to as the Group of Seven (G7). The 16 members of the euro area and the four newly industrialized Asian economies are also distinguished as subgroups. Composite data shown in the tables for the euro area cover the current members for all years, even though the membership has increased over time.

Table A.

Classification by World Economic Outlook Groups and Their Shares in Aggregate GDP, Exports of Goods and Services, and Population, 20091

(Percent of total for group or world)

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The GDP shares are based on the purchasing-power-parity valuation of countries’ GDP. The number of countries comprising each group reflects those for which data are included in the group aggregates.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Table B.

Advanced Economies by Subgroup

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On July 1, 1997, Hong Kong was returned to the People’s Republic of China and became a Special Administrative Region of China.

Table C lists the member countries of the European Union, not all of which are classified as advanced economies in the World Economic Outlook.

Table C.

European Union

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Emerging and Developing Economies

The group of emerging and developing economies (150 countries) includes all those that are not classified as advanced economies.

The regional breakdowns of emerging and developing economies are central and eastern Europe (CEE), Commonwealth of Independent States (CIS), developing Asia, Latin America and the Caribbean (LAC), Middle East and north Africa (MENA), and sub-Saharan Africa (SSA).

Emerging and developing economies are also classified according to analytical criteria. The analytical criteria reflect the composition of countries’ export earnings and other income from abroad; a distinction between net creditor and net debtor countries; and, for the net debtor countries, financial criteria based on external financing sources and experience with external debt servicing. The detailed composition of emerging and developing economies in the regional and analytical groups is shown in Tables D and E.

Table D.

Emerging and Developing Economies by Region and Main Source of Export Earnings

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Note: Mongolia, which is not a member of the Commonwealth of Independent States, is included in this group for reasons of geography and similarities in economic structure.
Table E.

Emerging and Developing Economies by Region, Net External Position, and Status as Heavily Indebted Poor Countries

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Dot instead of star indicates that the net debtor’s main external finance source is official financing.

Dot instead of star indicates that the country has reached the completion point.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

The analytical criterion, by source of export earnings, distinguishes between categories: fuel (Standard International Trade Classification—SITC 3) and nonfuel and then focuses on nonfuel primary products (SITCs 0, 1, 2, 4, and 68). Countries are categorized into one of these groups when their main source of export earnings exceeds 50 percent of total exports on average between 2004 and 2008.

The financial criteria focus on net creditor countries, net debtor countries, and heavily indebted poor countries (HIPCs). Countries are categorized as net debtors when their current account balance accumulations from 1972 (or earliest data available) to 2008 are negative. Net debtor countries are further differentiated on the basis of two additional financial criteria: official external financing and experience with debt servicing.4 Countries are placed in the official external financing category when 65 percent or more of their total debt, on average between 2004 and 2008, is financed by official creditors.

The HIPC group comprises the countries that are or have been considered by the IMF and the World Bank for participation in their debt initiative known as the HIPC Initiative, which aims to reduce the external debt burdens of all the eligible HIPCs to a “sustainable” level in a reasonably short period of time.5 Many of these countries have already benefited from debt relief and graduated from the initiative.

List of Tables

Medium-term Baseline Scenario

Table A1.

Summary of World Output1

(Annual percent change)

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Real GDP.

In this table, Other Advanced Economies means advanced economies excluding the United States, Euro Area countries, and Japan.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Table A2.

Advanced Economies: Real GDP and Total Domestic Demand1

(Annual percent change)

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When economies are not listed alphabetically, they are ordered on the basis of economic size.

From the fourth quarter of the preceding year.

Table A3.

Advanced Economies: Components of Real GDP

(Annual percent change)

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In this table, Other Advanced Economies means Advanced Economies excluding the G7 and Euro Area countries.

Changes expressed as percent GDP in the preceding period.

Table A4.

Emerging and Developing Economies: Real GDP1

(Annual percent change)

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For many countries, figures for recent years are IMF staff estimates. Data for some countries are for fiscal years.

Data for some countries refer to real net material product (NMP) or are estimates based on NMP. For many countries, figures for recent years are IMF staff estimates. The figures should be interpreted only as indicative of broad orders of magnitude because reliable, comparable data are not generally available. In particular, the output growth of new private enterprises in the informal economy is not fully reflected in the recent figures.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Private analysts are of the view that real GDP growth has been lower than the official reports since the last quarter of 2008.

The percent changes in 2002 are calculated over a period of 18 months, reflecting a change in the fiscal year cycle (from July–June to January–December).

The Zimbabwe dollar ceased circulating in early 2009. Data are based on staff estimates of price and exchange rate developments in U.S. dollars. IMF staff estimates of U.S. dollar values may differ from the authorities’ estimates. Real GDP is in constant 2009 prices.

Table A5.

Summary of Inflation

(Percent)

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In this table, Other Advanced Economies means advanced economies excluding the United States, Euro Area countries, and Japan.

Based on Eurostat’s harmonized index of consumer prices.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Table A6.

Advanced Economies: Consumer Prices

(Annual percent change)

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December–December changes. Several countries report Q4–Q4 changes.

Based on Eurostat’s harmonized index of consumer prices.

Table A7.

Emerging and Developing Economies: Consumer Prices1

(Annual percent change)

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In accordance with standard practice in the World Economic Outlook, movements in consumer prices are indicated as annual averages rather than as December–December changes during the year, as is the practice in some countries. For many countries, figures for recent years are IMF staff estimates. Data for some countries are for fiscal years.

December–December changes. Several countries report Q4–Q4 changes.

For many countries, inflation for the earlier years is measured on the basis of a retail price index. Consumer price index (CPI) inflation data with broader and more up-to-date coverage are typically used for more recent years.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Private analysts estimate that CPI inflation has been considerably higher. The authorities have created a board of academic advisors to assess these issues.

The percent changes in 2002 are calculated over a period of 18 months, reflecting a change in the fiscal year cycle (from July–June to January–December).

The Zimbabwe dollar ceased circulating in early 2009. Data are based on staff estimates of price and exchange rate developments in U.S. dollars. Staff estimates of U.S. dollar values may differ from authorities’ estimates.

Table A8.

Major Advanced Economies: General Government Fiscal Balances and Debt1

(Percent of GDP unless noted otherwise)

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Note: The methodology and specific assumptions for each country are discussed in Box A1 in the Statistical Appendix.

Debt data refer to the end of the year. Debt data are not always comparable across countries.

Percent of potential GDP.

Beginning in 1995, the debt and debt-service obligations of the Treuhandanstalt (and of various other agencies) were taken over by the general government. This debt is equivalent to 8 percent of GDP, and the associated debt service to ½ to 1 percent of GDP.

Excludes sizable one-off receipts from the sale of assets, including licenses.

Excludes one-off measures based on the authorities’ data and, in the absence of the latter, receipts from the sale of assets.

Table A9.

Summary of World Trade Volumes and Prices

(Annual percent change)

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Average of annual percent change for world exports and imports.

As represented, respectively, by the export unit value index for manufactures of the advanced economies and accounting for 83 percent of the advanced economies’ trade (export of goods) weights; the average of U.K. Brent, Dubai, and West Texas Intermediate crude oil prices; and the average of world market prices for nonfuel primary commodities weighted by their 2002–04 shares in world commodity exports.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Average of U.K. Brent, Dubai, and West Texas Intermediate crude oil prices.

For manufactures exported by the advanced economies.

Table A10.

Summary of Balances on Current Account

(Billions of U.S. dollars)

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Reflects errors, omissions, and asymmetries in balance of payments statistics on the current account, as well as the exclusion of data for international organizations and a limited number of countries. Calculated as the sum of the balances of individual Euro Area countries. See “Classification of Countries” in the introduction to this Statistical Appendix.

In this table, Other Advanced Economies means Advanced Economies excluding the United States, Euro Area countries, and Japan.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Table A11.

Advanced Economies: Balance on Current Account

(Percent of GDP)

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Calculated as the sum of the balances of individual Euro Area countries.

Corrected for reporting discrepancies in intra-area transactions.

Table A12.

Emerging and Developing Economies: Balance on Current Account

(Percent of GDP)

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Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

The Zimbabwe dollar ceased circulating in early 2009. Data are based on IMF staff estimates of price and exchange rate developments in U.S. dollars. IMF staff estimates of U.S. dollar values may differ from the authorities’ estimates.

Table A13.

Emerging and Developing Economies: Net Financial Flows1

(Billions of U.S. dollars)

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Net financial flows comprise net direct investment, net portfolio investment, other net official and private financial flows, and changes in reserves.

Excludes grants and includes transactions in external assets and liabilities of official agencies.

A minus sign indicates an increase.

The sum of the current account balance, net private financial flows, net official flows, and the change in reserves equals, with the opposite sign, the sum of the capital account and errors and omissions.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Table A14.

Emerging and Developing Economies: Private Financial Flows1

(Billions of U.S. dollars)

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Private financial flows comprise direct investment, portfolio investment, and other long- and short-term investment flows.

Table A15.

Emerging and Developing Economies: Reserves1

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In this table, official holdings of gold are valued at SDR 35 an ounce. This convention results in a marked underestimation of reserves for countries that have substantial gold holdings.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.

Reserves at year-end in percent of imports of goods and services for the year indicated.

Table A16.

Summary of Sources and Uses of World Savings

(Percent of GDP)

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Note: The estimates in this table are based on individual countries’ national accounts and balance of payments statistics. Country group composites are calculated as the sum of the U.S. dollar values for the relevant individual countries. This differs from the calculations in the April 2005 and earlier issues of the World Economic Outlook, where the composites were weighted by GDP valued at purchasing power parities as a share of total world GDP. For many countries, the estimates of national savings are built up from national accounts data on gross domestic investment and from balance-of-payments-based data on net foreign investment. The latter, which is equivalent to the current account balance, comprises three components: current transfers, net factor income, and the resource balance. The mixing of data source, which is dictated by availability, implies that the estimates for national savings that are derived incorporate the statistical discrepancies. Furthermore, errors, omissions, and asymmetries in balance of payments statistics affect the estimates for net lending; at the global level, net lending, which in theory would be zero, equals the world current account discrepancy. Despite these statistical shortcomings, flow of funds estimates, such as those presented in these tables, provide a useful framework for analyzing developments in savings and investment, both over time and across regions and countries.

Calculated from the data of individual Euro Area countries.

Georgia and Mongolia, which are not members of the Commonwealth of Independent States, are included in this group for reasons of geography and similarities in economic structure.