## _wp11283 - 1. Additional Figures

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---

### Introduction and scope
- Focus: vulnerability of commodity-exporting emerging markets to sharp falls in commodity prices and the policies that can shield them.
- Period of analysis: 1970–2010.
- Sample: 64 emerging and large commodity-exporting advanced economies.
- Two complementary approaches used:
  - Cross-sectional study of episodes of sharp negative terms-of-trade shocks.
  - Panel data approach.
- Adjusted measure used for terms of trade: captures the income effect of changes in trade prices by taking into account the initial export and import ratios to GDP (the direct impact of changes in export and import deflators on the trade balance, given volumes). This adjustment incorporates trade openness into the terms-of-trade measure.

### Real commodity price construction and broad patterns
- Real price construction:
  - Commodity prices—in U.S. dollars—are deflated by a weighted average of the wholesale price indices (WPIs) of five countries (France, Germany, Japan, the U.K., and the U.S.) whose currencies comprise the IMF’s Special Drawing Right (SDR) basket (with the euro succeeding the French franc and German mark in the euro era).
  - Each country’s WPI is converted to U.S. dollars using the average exchange rate of the period, and the average is computed using the weights of the SDR basket.
  - Purpose: to strip the measure of real commodity prices of the mechanical numeraire effect due to changes in the U.S.-dollar exchange rate.
- Historical magnitude and category-specific changes since 2003:
  - Energy and metal prices have tripled since 2003 and current prices are around the historic peaks of the 1970s.
  - Food prices increased around 50 percent since 2003; current food prices are still about 50 percent below their average level of the 1970s.
  - Agricultural raw material prices evolved similarly to food prices, though the long-run decline has been less marked.
- Volatility and persistence (monthly data, 1958–2011):
  - Energy: Std. dev. (dlog) = 0.709; HLS (24 months) = 8.2 years.
  - Metals: Std. dev. (dlog) = 0.709; HLS = 3.9 years.
  - Agricultural raw materials: Std. dev. (dlog) = 0.262; HLS = 3.0 years.
  - Food: Std. dev. (dlog) = 0.801; HLS = 12.9 years.
  - Cereals (include corn, rice, soybeans, and wheat): Std. dev. (dlog) = 0.584; HLS = 5.8 years.
- Comovement and global drivers:
  - In the last decade the first principal component accounted for almost 85 percent of the variance of commodity prices, with prices of all categories positively correlated with this common factor.
  - In the 1970s and 1980s, the first principal component accounted for about 65 percent of the variance; it was positively correlated with metals and food but negatively correlated with energy.
  - Increasing importance of China in global demand contributed to the strong common factor in recent decades.
- Interpretation highlights:
  - Food prices have been less volatile and their shocks more persistent than those of metals and energy.
  - Cereals display relatively higher volatility and lower persistence within food.

### Commodity dependence, concentration, and regional patterns
- Definitions:
  - Dependence: importance of net commodity exports in relation to the country’s GDP (indicator of vulnerability to a commodity price shock).
  - Concentration: share of gross commodity exports in total exports (indicator of flexibility to adjust to a shock).
- Regional and country-level patterns (selected figures preserved as in source):
  - South America:
    - Net commodity exports represented 10 percent of GDP in 2010, compared with 6 percent in 1970.
    - On average, commodities still account for 60 percent of total exports of goods and services in the region.
    - Metal exporters (Chile and Peru): metals account on average for about 60 percent of total exports.
    - Energy exporters (Colombia, Ecuador, Venezuela): energy accounts on average for about 80 percent of total exports; commodity exports average 20 and 17 percent of GDP respectively for metal and energy exporters, versus 8 percent in other countries in the region.
  - Mexico and Central America:
    - Subregion was a large commodity exporter in 1970 (8 percent of GDP) and presently shows balanced trade in commodities.
    - Importance of commodity exports fell from about 50 percent of total exports in 1970–80 to around 25 percent in 2010.
    - Mexico recorded a decline in net energy exports from 4½ to 1½ percent of GDP between 1980 and 2010; energy exports now amount to 13 percent of total exports (compared with about 50 percent in 1980).
  - Emerging Asia:
    - Evolved from being a net commodity exporter (around 6 percent of GDP in 1970) to being a net importer (almost 3 percent of GDP) in 2010.
    - Commodity exports fell from about 60 percent of total exports in the 1970s to less than 20 percent in 2010.
  - Commodity-exporting advanced economies (Australia, Canada, New Zealand, Norway):
    - Dependence increased from an average of 6 percent of GDP in 1970 to 13 percent in 2010.
    - Norway: net commodity exports represented 23 percent of GDP in 2010, with net oil exports accounting for 21 percent of GDP.
- Net effect:
  - Latin America remains on average as exposed to commodities-related risk as four decades ago, though higher export diversification has increased flexibility in many countries.
  - Energy and metal exporters in Latin America remain particularly vulnerable due to higher dependence and concentration in commodities sensitive to the global cycle.

### Identification, sample, and empirical methods
- Adjusted terms-of-trade measure:
  - Accounts for the income effect of changes in export and import deflators given volumes and initial export and import ratios to GDP; formal expression provided in the source.
- Two empirical approaches (sample: 1970–2010; 64 countries):
  - Cross-sectional episodes:
    - Criterion: cumulative drop in adjusted terms of trade of at least 3 percentage points of GDP from peak to trough with negative changes in at least two consecutive years.
    - Identified 98 episodes.
    - Average peak-to-trough time span: 4½ years.
    - Only two-thirds of episodes show negative cumulative growth (relative to preshock average); fraction falls to one-half for episodes in the 2000s.
  - Panel approach:
    - Fixed effects panel focusing on year-by-year impact and amplification by fundamentals.
    - Threshold for "large and negative shocks" set at -1.5 percentage points of GDP (about 20 percent of annual observations).
    - Allows inclusion of fiscal and financial variables with better recent data (e.g., dollarization, primary fiscal balance).

### Cross-sectional results — stylized findings
- Robust associations:
  - Output loss is smaller in countries with a stronger external position as reflected in current account measures (levels and changes).
  - The negative impact of a weak external position is larger when preceded by larger terms-of-trade booms.
  - More flexible exchange rate regimes are associated with smaller declines in output during busts—evidence that exchange rate flexibility enhances adjustment to external disturbances.
- Financial openness and integration:
  - Higher capital account openness (Chinn and Ito index) appears associated with larger output costs on average, suggesting procyclical capital inflows in many cases.
  - When using a measure of international financial integration (sum of external assets and liabilities as percent of GDP), the sign reverses: financial integration helps buffer shocks when fundamentals are strong.
- External factors:
  - VIX, 10-year U.S. Treasury yield, and world real GDP growth are significant determinants of output performance during busts.
- Non-robust or null findings:
  - No robust evidence that external/public debt, international reserves, or credit booms systematically explain cross-country differences in output performance during busts.

### Panel results — direct effects and amplification/mitigation
- Direct effect of terms-of-trade shocks:
  - A negative terms-of-trade shock of 1 percentage point of GDP leads to 0.13 percent lower growth in the same year and 0.08 percent lower growth in the second year.
- Amplification and mitigation by fundamentals (large negative shocks, and shocks preceded by booms):
  - Stronger fiscal position (higher primary fiscal balance) at time of shock mitigates impact—effect considerably stronger when shocks are preceded by booms.
  - Exchange rate flexibility during booms operates as an important shock absorber.
  - Financial dollarization is an important shock amplifier for boom-bust cycles.
    - Interaction: exchange rate flexibility loses power as a shock absorber in the presence of high financial dollarization (balance-sheet effects).
  - Capital account openness on average does not smooth trade shocks; result reverses if using financial integration measure (consistent with cross-sectional finding on interaction with fundamentals).
  - External debt and other stock variables (public debt, net foreign assets) generally do not show robust amplification/mitigation effects in these specifications.

### Illustrative simulation (Figure 14 assumptions and outcomes)
- Scenario assumptions consistent with 2008–09:
  - 40 percent drop in all commodity prices → -2.8 percentage points of GDP terms-of-trade shock (based on LA7 average net commodity exposure).
  - Slowdown in global growth of 3.3 percent.
  - Fall of 137 basis points in US 10-year T-bond yield.
  - Increase of 14 points in the VIX.
- Representative simulated outcomes:
  - For an average LA7 country the simulated impact is shown as a substantial GDP growth hit.
  - Example reported outcomes under the assumptions:
    - Average LA7 country with strong policies: -0.47 (percentage points of GDP growth under the assumptions).
    - Country with weaker policies: -6.1 (percentage points of GDP growth under the assumptions).
- Note: Assumed uniform 40 percent shock across all commodities may overstate for some countries and understate for others given commodity mix sensitivities.

### Annex findings on “mismanaging abundance”
- Episodes of sharp negative terms-of-trade shocks were often preceded by significant improvements in terms of trade.
- Despite preceding booms providing an opportunity, affected countries generally did not take advantage to improve fundamentals and shield against future shocks.
- Empirical contrasts:
  - Countries with preceding booms showed an average cumulative terms-of-trade improvement of about 10 percentage points of GDP against 0 for the rest of the sample in the three years preceding the fall, but did not perform better overall.
  - Booming countries grew at broadly the same pace as other countries before the bust, but decelerated more markedly afterward despite terms-of-trade drops of similar magnitudes.
- Policy-response patterns associated with missed opportunities:
  - Booming countries showed strong improvements in their current accounts during the boom, but significantly larger deteriorations in their underlying (price-adjusted) positions.
  - Booming countries did not allow their nominal exchange rates to appreciate more, although their real exchange rates still appreciated more on account of higher inflation.
  - Booming countries also missed the opportunity to strengthen their fiscal positions: their primary balances did not improve during the boom either in relative terms to other countries or in absolute terms.

### Policy implications and recommendations
- Fiscal policy and buffers:
  - Prudent fiscal management in booms (avoiding deterioration of underlying fiscal and external positions) mitigates the impact of subsequent busts.
  - Maintaining a stronger current account before a bust reduces output loss.
- Exchange rate policy:
  - Exchange rate flexibility is a powerful shock absorber, but its effectiveness is limited in highly dollarized economies due to balance-sheet effects.
- Financial sector and dollarization:
  - Reducing financial dollarization reduces amplification of shocks; policies to limit currency mismatches can enhance the benefit of exchange rate flexibility.
- Capital account and financial integration:
  - Financial openness can help buffer shocks when fundamentals are strong and financial integration is deep; premature or poorly managed liberalization can be counterproductive.
- Reserves and market access:
  - International reserves did not show robust mitigating effects, possibly because authorities were reluctant to use reserves during crises; policy frameworks should clarify reserve use in contingencies and maintain credible access to financing.
- Broader conclusion on policy stance:
  - Countercyclical policies during booms matter: policies and fundamentals preceding large negative terms-of-trade shocks—especially during booms—significantly shape macroeconomic outcomes.

*Source: _wp11283 - 1. Additional Figures (excerpt).*

### 1.  Additional Figures .................................................................................................

### _wp11283 - 1.  Additional Figures

### Introduction and scope
- Focus: vulnerability of commodity-exporting emerging markets to sharp falls in commodity prices and the policies that can shield them.
- Period of analysis: 1970–2010.
- Sample: 64 emerging and large commodity-exporting advanced economies.
- Two complementary approaches used:
  - Cross-sectional study of episodes of sharp negative terms-of-trade shocks.
  - Panel data approach.
- Adjusted measure used for terms of trade: captures the income effect of changes in trade prices by taking into account the initial export and import ratios to GDP (the direct impact of changes in export and import deflators on the trade balance, given volumes). This adjustment incorporates trade openness into the terms-of-trade measure.

### Major findings and stylized facts on commodity prices
- The recent commodity price boom is remarkable in historical terms, but less so for food prices, which are still significantly below their 1960s–70s levels after trending downward for several decades.
- Commodity prices are sensitive to global output, but sensitivity differs by commodity (for example, food prices are less sensitive), implying varying vulnerability across exporters of different commodities.
- The current price cycle (relative to previous cycles) shows high comovement of prices, mainly reflecting global demand as a dominant common driver.
- Regional and historical patterns:
  - Latin America is, on average, as dependent on commodities today as 40 years ago; explicitly: South America remains clearly dependent, while Mexico and Central America have significantly reduced dependence.
  - Most countries in Latin America have seen a trend toward more diversified export structures, except large metal and energy exporters.
  - Emerging Asia shifted from being a strong net commodity exporter in 1970 to being a net importer in 2010 and recorded marked export diversification.

### Role of commodity dependence, concentration, and openness
- Definitions used in the paper:
  - Dependence: importance of net commodity exports in relation to the country’s GDP (information on vulnerability to a commodity price shock).
  - Concentration: share of gross commodity exports in total exports (information on flexibility to adjust to a shock).
- The adjusted terms-of-trade shock (which accounts for trade openness) provides a more robust link to economic impact than the traditional export-price/import-price ratio.
- Despite commodity reliance being important, the adjusted terms-of-trade shock alone does not explain how countries fare during sharp trade price busts; other factors amplify or mitigate the impact.

### Policies, fundamentals, and amplification/mitigation of shocks
- Pre-shock policies and fundamentals substantially influence the economic impact of negative terms-of-trade shocks, especially when busts are preceded by booms.
- Factors that tend to amplify the negative output effects:
  - Limited exchange rate flexibility.
  - Weak external position.
  - Loose fiscal policy.
  - Financial dollarization (acts as a shock “amplifier”).
- Financial integration with the rest of the world:
  - A higher degree of financial integration helps to buffer shocks when country fundamentals are relatively good, but not necessarily otherwise.

### Organization of the paper (structure of content)
- Section II: Key stylized facts on commodity prices, idiosyncratic behavior of different commodities, and comovement.
- Section III: Extent of emerging markets’ commodity dependence; differences across regions and shifts in trade structures.
- Section IV: Role of policies and fundamentals—especially during commodity booms—in determining output impacts of subsequent negative terms-of-trade shocks.
- Section V: Conclusions and policy implications.

*Source: _wp11283 - 1.  Additional Figures (excerpt). *

### References to commodity prices in the rest of the paper are always in real terms.

### _wp11283 - References to commodity prices in the rest of the paper are always in real terms.

### Real commodity price construction
- Commodity prices—in U.S. dollars—are deflated by a weighted average of the wholesale price indices (WPIs) of five countries (France, Germany, Japan, the U.K., and the U.S.) whose currencies comprise the IMF’s Special Drawing Right (SDR) basket (with the euro succeeding the French franc and German mark in the euro era).
- Each country’s WPI is converted to U.S. dollars using the average exchange rate of the period, and the average is computed using the weights of the SDR basket.
- Purpose: to strip the measure of real commodity prices of the mechanical numeraire effect due to changes in the U.S.-dollar exchange rate.

### Historical patterns, magnitude, and volatility
- Broad observations:
  - Except for a brief interruption during the 2008–09 global crisis, commodity prices have increased sharply over the last decade, with the IMF broad commodity price index reaching levels similar to those recorded during the price booms in the 1970s.
  - The recent boom is notable for its magnitude and for being broad based across commodity categories.
- Category-specific changes since 2003:
  - Energy and metal prices have tripled (in the latter case from record low levels) since 2003, and current prices are around the historic peaks of the 1970s.
  - Food prices increased around 50 percent since 2003; current food prices are still about 50 percent below their average level of the 1970s.
  - Evolution of agricultural raw material prices is similar to food prices, though the long-run decline has been less marked.
- Volatility and persistence (Table 1, monthly data, 1958–2011):
  - Energy: Std. dev. (dlog) = 0.709; HLS (24 months) = 8.2 years.
  - Metals: Std. dev. (dlog) = 0.709; HLS = 3.9 years.
  - Agricultural raw materials: Std. dev. (dlog) = 0.262; HLS = 3.0 years.
  - Food: Std. dev. (dlog) = 0.801; HLS = 12.9 years.
  - Cereals (include corn, rice, soybeans, and wheat): Std. dev. (dlog) = 0.584; HLS = 5.8 years.
- Interpretation:
  - Food prices have been less volatile and their shocks more persistent than those of metals and energy.
  - Within food, cereals display relatively higher volatility and lower persistence than meat and fishery.

### Comovement and global factors
- Comovement dynamics:
  - Prices across all categories have tended to move in the same direction in the last decade due to the dominant role of global demand.
  - Pronounced comovement also occurred in response to financial shocks (2008–09 crisis; second half of 2011).
  - In prior decades correlations were lower and sometimes negative (e.g., 1970s oil shocks, Gulf War early 1990s).
- Principal components analysis (Table 2):
  - In the last decade, the first principal component accounted for almost 85 percent of the variance of commodity prices, with prices of all categories positively correlated with this common factor.
  - In the 1970s and 1980s, the first principal component accounted for about 65 percent of the variance; it was positively correlated with metals and food but negatively correlated with energy.
  - Interpretation: increasing importance of China in global demand contributed to the strong common factor in recent decades.

### Commodity dependence and export concentration: regional comparisons
- Definitions:
  - Commodity dependence: total net exports of basic products relative to GDP (indicator of potential effect of a commodity price shock on domestic output).
  - Commodity export concentration: gross commodity exports in percent of total exports of goods and services (indicator of export diversification and adjustment capacity).
- Regional and country-level patterns:
  - South America:
    - Net commodity exports represented 10 percent of GDP in 2010, compared with 6 percent in 1970.
    - Metals and energy account for the largest shares of net commodity exports.
    - On average, commodities still account for 60 percent of total exports of goods and services in the region, though diversification has occurred in several countries (Argentina, Brazil, Uruguay).
    - Metal exporters (Chile and Peru): metals account on average for about 60 percent of total exports.
    - Energy exporters (Colombia, Ecuador, Venezuela): energy accounts on average for about 80 percent of total exports; commodity exports average 20 and 17 percent of GDP respectively for metal and energy exporters, versus 8 percent in other countries in the region.
  - Mexico and Central America:
    - The subregion was a large commodity exporter in 1970 (8 percent of GDP) and presently shows balanced trade in commodities.
    - Importance of commodity exports fell from about 50 percent of total exports in 1970–80 to around 25 percent in 2010.
    - Mexico recorded a decline in net energy exports from 4½ to 1½ percent of GDP between 1980 and 2010; energy exports now amount to 13 percent of total exports (compared with about 50 percent in 1980).
  - Emerging Asia:
    - Evolved from being a net commodity exporter (around 6 percent of GDP in 1970) to being a net importer (almost 3 percent of GDP) in 2010.
    - Commodity exports fell from about 60 percent of total exports in the 1970s to less than 20 percent in 2010.
    - Emerging Asia imports of commodities rose, reflecting increasing energy needs in rapidly expanding economies (China exception: commodity imports increased both as fraction of total imports and as percent of GDP).
  - Commodity-exporting advanced economies (Australia, Canada, New Zealand, Norway):
    - Dependence increased from an average of 6 percent of GDP in 1970 to 13 percent in 2010.
    - Norway: net commodity exports represented 23 percent of GDP in 2010, with net oil exports accounting for 21 percent of GDP.
- Net effect:
  - Latin America remains on average as exposed to commodities-related risk as four decades ago, though higher export diversification has increased flexibility in many countries.
  - Energy and metal exporters in Latin America remain particularly vulnerable due to higher dependence and concentration in commodities that are sensitive to the global cycle.

### Macroeconomic impact of terms-of-trade busts: identification and methods
- Adjusted terms-of-trade measure:
  - Accounts for the income effect of changes in export and import deflators given volumes and initial export and import ratios to GDP.
  - Formal expression provided in the source for the adjusted ToT change (uses percentage change in export and import deflators and previous-year export/import-to-GDP ratios).
- Two complementary empirical approaches (sample: 1970–2010; 64 emerging and large commodity-exporting advanced economies):
  - Cross-sectional analysis of episodes with cumulative drop in adjusted terms of trade of at least 3 percentage points of GDP from peak to trough (with negative changes in at least two consecutive years). Identified 98 episodes.
    - Average peak-to-trough time span: 4½ years.
    - Only two-thirds of episodes show negative cumulative growth (relative to preshock average); fraction falls to one-half for episodes in the 2000s.
  - Panel approach with fixed effects, focusing on year-by-year impact and amplification by fundamentals; threshold for "large and negative shocks" set at -1.5 percentage points of GDP (about 20 percent of annual observations).
    - Allows inclusion of fiscal and financial variables with better recent data (e.g., dollarization, primary fiscal balance).

### Cross-sectional results: key findings (summary of Table 3 and Figure 12)
- Robust findings:
  - Output loss is smaller in countries with a stronger external position as reflected in current account measures (levels and changes).
  - The negative impact of a weak external position is larger when preceded by larger terms-of-trade booms.
  - More flexible exchange rate regimes are associated with smaller declines in output during busts—evidence that exchange rate flexibility enhances adjustment to external disturbances.
- No robust evidence that external/public debt, international reserves, or credit booms systematically explain cross-country differences in output performance during busts (possible reasons: market access heterogeneity; reluctance to use reserves during crises).
- Financial openness:
  - Higher capital account openness (Chinn and Ito index) appears associated with larger output costs on average, suggesting procyclical capital inflows in many cases.
  - When using a measure of international financial integration (sum of external assets and liabilities as percent of GDP), the sign reverses: financial integration helps buffer shocks when fundamentals are strong.
- Other external factors (VIX, 10-year U.S. Treasury yield, world real GDP growth) are significant determinants of output performance during busts.
- Representative magnitudes (based on regression results and Figure 12):
  - Benefit of a 1-percent-of-GDP higher current account balance on cumulative output growth differs depending on preceding ToT boom (figure based on column 10 of Table 3; ToT boom ~ 6 percent at 75th percentile, No boom ~ roughly zero at 25th percentile).
  - Benefit of a flexible exchange rate regime similarly larger if bust was preceded by a boom.

### Panel results: amplification and mitigation (summary of Table 4 and Figure 13)
- Direct effect of terms-of-trade shocks:
  - A negative terms-of-trade shock of 1 percentage point of GDP leads to 0.13 percent lower growth in the same year and 0.08 percent lower growth in the second year (column estimates; significance noted).
- Amplification/mitigation by fundamentals (focus on large negative shocks and shocks preceded by booms):
  - Stronger fiscal position (higher primary fiscal balance) at time of shock mitigates impact—effect considerably stronger when shocks are preceded by favorable conditions (booms).
  - Exchange rate flexibility during booms operates as an important shock absorber.
  - Financial dollarization is an important shock amplifier for boom-bust cycles.
    - Interaction: exchange rate flexibility loses power as a shock absorber in the presence of high financial dollarization (balance-sheet effects).
  - Capital account openness on average does not smooth trade shocks; result reverses if using financial integration measure (consistent with cross-sectional finding on interaction with fundamentals).
  - External debt and other stock variables (public debt, net foreign assets) generally do not show robust amplification/mitigation effects in these specifications.
- Illustrative simulation (Figure 14; LA7 average and two fictional countries):
  - Scenario assumptions consistent with 2008–09:
    - 40 percent drop in all commodity prices → -2.8 percentage points of GDP terms-of-trade shock (based on LA7 average net commodity exposure).
    - Slowdown in global growth of 3.3 percent.
    - Fall of 137 basis points in US 10-year T-bond yield.
    - Increase of 14 points in the VIX.
  - Result: For an average LA7 country the simulated impact is shown as a substantial GDP growth hit; a country with stronger policies sees much smaller impact; a country with weaker policies sees a much larger hit (figure reports example outcomes: average LA7 country with strong policies (-0.47), country with weaker policies (-6.1) in percentage points of GDP growth under the assumptions).
  - Note: Assumed uniform 40 percent shock across all commodities may overstate for some countries and understate for others given commodity mix sensitivities.

### Policy implications and recommendations
- Countercyclical policies during booms matter:
  - Prudent fiscal management in booms (avoiding deterioration of underlying fiscal and external positions) mitigates the impact of subsequent busts.
  - Maintaining a stronger current account before a bust reduces output loss.
- Exchange rate policy:
  - Exchange rate flexibility is a powerful shock absorber, but its effectiveness is limited in highly dollarized economies due to balance-sheet effects.
- Financial sector considerations:
  - Reducing financial dollarization reduces amplification of shocks; policy measures to limit currency mismatches can enhance the benefit of exchange rate flexibility.
- Capital account management:
  - Financial openness can help buffer shocks when fundamentals are strong and financial integration is deep; premature or poorly managed liberalization can be counterproductive.
- Use of reserves and market access:
  - International reserves did not show robust mitigating effects, possibly because authorities were reluctant to use reserves during crises; this suggests policy frameworks should clarify reserve use in contingencies and maintain credible access to financing.

### Conclusions
- Latin America—especially South America—remains among the most commodity-dependent regions; dependence has, for many countries, remained broadly unchanged for 40 years.
- Emerging Asia shifted from net exporter to net importer of commodities and has increased export diversification, reducing vulnerability to pure price shocks.
- Empirical evidence from cross-sectional and panel methods indicates that policies and fundamentals preceding large negative terms-of-trade shocks—especially during booms—significantly shape macroeconomic outcomes.
  - Key policy buffers: strong fiscal position, flexible exchange rate (subject to currency-structure constraints), prudent current account management, reduced dollarization, and appropriate sequencing of financial openness.
- Other external factors (global growth and financial conditions) play important roles; in adverse tail events simultaneous deterioration across multiple external fronts amplifies downside risks and reinforces the need for prudent macroeconomic management during favorable times.

*Source: _wp11283 - References to commodity prices in the rest of the paper are always in real terms.*

### ANNEX 1. ADDITIONAL FIGURES

### ANNEX 1. ADDITIONAL FIGURES

### A. Episodes of Commodity Price Booms and Busts
- Figures illustrate multiple historical commodity price shock episodes with indexed price baselines:
  - First oil price shock (December 1973 = 100)
  - Second oil price shock (April 1979 = 100)
  - Gulf War oil price shock (July 1990 = 100)
  - Recent commodity price shock (December 2004 = 100)
- Series plotted include: Energy, Metals, Food, Advanced economies industrial production growth, VIX (right scale).
- Sources for figures: IMF, World Economic Outlook; Haver Analytics; and authors' calculations.

### B. Net Commodity Exports — Selected Latin American Countries
- Charts present Net Commodity Exports (Percent of GDP) for selected countries and regions across 1970–2010:
  - Argentina; South America; Mexico and Central America
  - Brazil; Chile; Colombia; Mexico; Peru; Venezuela
  - Ecuador; Costa Rica; El Salvador; Uruguay; Guatemala
- Commodity categories shown: Agriculture and related products; Animals and related products; Metals; Energy; Other raw materials; Total.
- Sources for figures: World Integrated Trade Solutions database; and authors' calculations.

### C. Gross Commodity Exports — Selected Latin American Countries
- Charts present Gross Commodity Exports (Percent of total exports of goods and services) for the same set of Latin American countries across 1970–2010.
- Commodity categories shown: Agriculture and related products; Animals and related products; Metals; Energy; Other Raw Materials; Total (percent of GDP, right scale).
- Sources for figures: World Integrated Trade Solutions database; and authors' calculations.

### D. Net Commodity Exports — Selected Asian Countries
- Charts present Net Commodity Exports (Percent of GDP) for selected Asian countries across 1970–2010:
  - China; India; Indonesia; Korea; Malaysia; Philippines; Thailand
- Commodity categories shown: Agriculture and related products; Animals and related products; Metals; Energy; Other raw materials; Total.
- Sources for figures: World Integrated Trade Solutions database; and authors' calculations.

### E. Gross Commodity Exports — Selected Asian Countries
- Charts present Gross Commodity Exports (Percent of total exports of goods and services) for the same Asian countries across 1970–2010.
- Commodity categories shown: Agriculture and related products; Animals and related products; Metals; Energy; Other Raw Materials; Total (percent of GDP, right scale).
- Sources for figures: World Integrated Trade Solutions database; and authors' calculations.

### F. Net Commodity Exports — Selected Advanced Economies
- Charts present Net Commodity Exports (Percent of GDP) for selected advanced economies across 1970–2010:
  - Australia; Canada; New Zealand; Norway
- Commodity categories shown: Agriculture and related products; Animals and related products; Metals; Energy; Other raw materials; Total.
- Sources for figures: World Integrated Trade Solutions database; and authors' calculations.

### G. Gross Commodity Exports — Selected Advanced Economies
- Charts present Gross Commodity Exports (Percent of total exports of goods and services) for the same advanced economies across 1970–2010.
- Commodity categories shown: Agriculture and related products; Animals and related products; Metals; Energy; Other Raw Materials; Total (percent of GDP, right scale).
- Sources for figures: World Integrated Trade Solutions database; and authors' calculations.

### Annex 2 — The Cost of Mismanaging Abundance: key empirical findings
- Episodes of sharp negative terms-of-trade shocks were often preceded by significant improvements in terms of trade.
- Despite preceding booms providing an opportunity, affected countries generally did not take advantage to improve fundamentals and shield against future shocks.
- Empirical split of episodes between countries with the largest improvements in terms of trade (in the three years preceding the fall) and the rest shows:
  - Countries with preceding booms displayed significantly better terms of trade (an average cumulative impact of about 10 percentage points of GDP against 0 for the rest of the sample), but did not perform better overall.
  - Booming countries grew at broadly the same pace as other countries before the bust, but decelerated more markedly afterward despite terms-of-trade drops of similar magnitudes.
- Policy-response patterns associated with “missed opportunities”:
  - Countries with preceding booms showed strong improvements in their current accounts during the boom, but significantly larger deteriorations in their underlying (price-adjusted) positions.
  - Booming countries appear not to have allowed their nominal exchange rates to appreciate more, although their real exchange rates still appreciated more on account of higher inflation.
  - Booming countries also missed the opportunity to strengthen their fiscal positions: their primary balances did not improve during the boom either in relative terms to other countries or in absolute terms.
- Note: "This pattern holds is median (rather than means) are used." (footnote text as in source)

### Annex 2 — Charts summarizing comparisons
- Economic Performance in Countries with and without Preceding Terms of Trade Booms:
  - Series and scales shown include Terms of trade (Adjusted terms of trade, cumulative since t-3) and Growth (Percent).
  - Legend: Countries with preceding terms of trade booms (mean); Other countries (mean).
- Key Fundamentals in Countries with and without Preceding Terms of Trade Booms:
  - Series shown include Underlying current account (Percent of GDP; Prices held constant at t-3 levels), Current account (Percent of GDP), Bilateral nominal exchange rate (Index, t–3 = 100), Bilateral real exchange rate (Index, t–3 = 100).
  - Increases indicate appreciation.

### Annex 3 — Cross-sectional approach: list of explanatory and control variables
- Dependent variable: output performance during the episode of terms-of-trade bust
  - Y: Cumulative deviation of GDP growth during the episode (t+1, t+K+1) from average growth in the five years prior to the shock (t-4,t), where t is the year before the shock, and k is the number of years with declining (adjusted) terms of trade, defined so that a lower (more negative) value means a greater output loss.
- Terms of trade
  - ToT_A: Cumulative change in adjusted terms of trade from t+k (trough) to t (peak).
  - ToT_A Prev: Cumulative change in adjusted terms of trade from t-3 to t.
- External position
  - CA: Current account balance, in percent of GDP, in period t.
  - CA_2: Current account balance, in percent of GDP, change from t-3 to t.
  - ExtDebt: External debt, in percent of GDP, change from t-3 to t.
  - FXRes: Foreign reserves, in percent of GDP, in period t.
  - FXRes_2: Foreign reserves, in percent of GDP, change from t-3 to t.
- Fiscal Position
  - PubDebt: Public debt, in percent of GDP, level in period t.
  - PubDebt_2: Public debt, in percent of GDP, change from t-3 to t.
- Other country conditions/fundamentals
  - ER Regime: ER flexibility, based on Ilzetzki, Reinhart, and Rogoff (2008) de facto index, at t. Dummy = 1 if index is between 1 and 4 (fixed), 0 if between 4 and 13 (flexible).
  - Volfx: Standard deviation of the monthly percentage changes of the nominal exchange rate (over a 12-month window), as a proxy for exchange rate flexibility.
  - KA Openness: Chinn and Ito (2008) capital account openness index, average t-2 to t.
  - Fin. Integ.: Measure of financial integration, defined as the sum of total external assets and liabilities, in percent of GDP.
  - Credit Boom: Dummy = 1 if a credit boom occurred in the three years preceding the shock, as identified by either Gourinchas, Landerretche, and Valdes (2001) or Mendoza and Terrones (2008).
- Controls: external conditions
  - U.S. Tbond: Change in U.S. Treasury bond real interest rate (in percent) after the shock: difference between average (t+1,t+K+1) and average (t-2,t).
  - VIX: Change in the VIX after the shock: difference between average (t+1,t+K+1) and average (t-2,t).
  - WGDPGrowth: World real GDP growth (in percent): difference between average (t+1,t+K+1) and average (t-2,t).

*Sources: figures — IMF, World Economic Outlook; Haver Analytics; World Integrated Trade Solutions database; and authors' calculations.*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2011/_wp11283.pdf_