## wpiea2019251-print-pdf — Section 1–3 summary

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---

### Overview and purpose
- Examines direct, first-round spillover effects on the rest of the world from a potential managed-trade element in a U.S.–China trade agreement.
- Focuses on a highly-stylized scenario in which China closes the bilateral trade deficit with the U.S. by purchasing U.S. goods while China’s total imports do not change (the additional U.S. purchases are entirely at the expense of purchases from the rest of the world).
- Aims to identify likely affected third countries and sectors under alternative assumptions about how China would allocate extra purchases.

### Modeling approaches used
- Size-based approach
  - Assumes China scales up purchases among the top-ten 2-digit HS products it currently imports from the U.S.
  - Allocation across those top-ten products is proportional to where there is scope for scaling up.
  - Spillovers to third countries computed using China’s top-ten exporters for each product, in proportion to their current export exposure to China for those products.
- Cascading approach
  - Uses 6-digit bilateral trade data and considers all trading partners rather than top-ten exporters.
  - Assumes commodities are redirected before manufactures; items with long contracts/production cycles (e.g., aircraft) are used last.
  - Closes the trade gap by exhausting potentially redirected commodity imports first, then part of manufacturing imports.
- Hybrid approach
  - Identifies 2-digit sectors assumed to be in a deal and then redirects within those sectors using 6-digit bilateral trade data across all trading partners.
  - Allocation at the 2-digit level follows top-ten product market shares; redirection within sectors is granular.

### Key assumptions
- China closes the bilateral trade deficit by purchasing U.S. goods and keeps total imports unchanged.
- Trading relationships are difficult to change overnight, so scaling up occurs where substantial existing trade links exist.
- Scale of increases is capped so total purchase of each product does not exceed China’s total imports of that product.
- Commodities are treated as more substitutable than manufactures; aircraft and similar items are treated as least substitutable.

### Size-based approach — product allocation shares (Figure 2)
- Electronics, 13
- Machinery, 12
- Vehicles, 11
- Oil seeds, 8
- Aircraft, 3
- Optical, 11
- Mineral fuels/oils, 13
- Plastics, 12
- Precious stones, 12
- Wood pulp, 4

### Size-based approach — main quantitative findings
- Baseline bilateral trade deficit used: USD 337bn in 2017 (trade deficit of goods and services).
- Estimated export diversion (aggregate, scenario described):
  - USD 61bn from European Union countries (significant exposure in vehicles, machinery, and aircraft)
  - USD 54bn from Japan (machinery, vehicles, and electronics)
  - USD 46bn from Korea (electronics, opticals, plastics)
  - USD 45bn from ASEAN countries (electronics, plastics, machinery)
- Export diversion exposure as share of 2017 GDP (selected economies):
  - Higher than 3 percent of GDP for OMN, AGO, SGP, and KOR
  - Higher than 2 percent of GDP for MYS, VNM, and THA
  - Around 1 percent of GDP for DEU and JPN
  - Brazil: 1.3 percent of GDP (predominantly due to oil seeds, e.g., soya beans)
- Small oil-exporting countries and small commodity exporters may face especially large export-diversion effects as shares of GDP.

### Alternative allocation scenarios (Figure 5)
- Alternative scenario 1: Allocation concentrated on a subset of top products (major six products)
  - Allocation shares:
    - Electronics, 25
    - Machinery, 22
    - Vehicles, 17
    - Oil seeds, 9
    - Aircraft, 3
    - Mineral fuels/oils, 25
  - Result: More pronounced export diversion for Germany, Japan, and ASEAN economies due to electronics, machinery, and vehicles; oil exporters face larger GDP-share impacts.
- Alternative scenario 2: Allocation proportional to China’s import structure (excluding U.S.)
  - Allocation shares:
    - Electronics, 34
    - Machinery, 13
    - Vehicles, 6
    - Oil seeds, 3
    - Aircraft, 1
    - Optical, 7
    - Mineral fuels/oils, 23
    - Plastics, 6
    - Precious stones, 6
    - Wood pulp, 2
  - Result: ASEAN economies and Korea would have higher export diversion due to electronics exposure; small oil exporters would again have higher exposure as a share of GDP.

### Cascading approach — key mechanics and aggregate figures (Section III)
- Uses HS-6-digit bilateral UN Comtrade data for around 200 economies.
- China imported about US$ 130bn worth of goods from the U.S. in 2017; China exported about US$ 526bn worth of goods to the U.S. in 2017, implying a trade gap of about US$ 400bn (Figure 7).
- There are about US$ 600bn worth of China’s 2017 imports from countries excluding the U.S. that could potentially be substituted with U.S. imports; because the trade gap is less than US$ 600bn, not all of this set is used in gap-filling.
- With the commodity-first ordering, the trade gap exhausts potentially redirected commodity imports and part of manufacturing imports.

### Cascading approach — distribution of extra purchases used to fill the gap (share of total, Figure 8)
- Chemicals & Allied Industries: 16.0
- Machinery / Electrical: 25.6
- Mineral Products: 16.0
- Plastics / Rubbers: 10.4
- Stone / Glass: 8.6
- Metals: 7.3
- Vegetable Products: 4.6
- Foodstuffs: 2.5
- Wood & Wood Products: 2.7
- Textiles: 2.8
- Animal & Animal Products: 2.5
- Raw Hides, Skins, Leather, & Furs: 0.6
- Footwear / Headgear: 0.3

### Cascading approach — country-level exposure findings
- Small commodity exporters at high risk (examples): Mongolia (coal, copper), Turkmenistan (petroleum gas), Congo (cobalt).
- East Asian economies with diversified exports but high exposure: Taiwan Province of China, Malaysia, Vietnam, Singapore, Korea, Thailand.
- Robustness: repeating the exercise on 2016 data yields very similar set of countries at risk.

### Hybrid approach — method and key quantified outcomes (Section IV)
- Starts from the top-ten product allocation used in the size-based approach and applies allocation at HS-6-digit level across the larger sample (~200 economies).
- Allocation constrained so it does not exceed (i) China’s current imports from the rest of the world at the 6-digit level, and (ii) the U.S. current exports to the rest of the world at the 6-digit level.
- Within each 2-digit product, the 6-digit allocation follows the cascading method.
- Key quantified outcomes:
  - Mongolia: export exposure amounting to 12.2 percent of GDP.
  - Turkmenistan: export exposure amounting to 9.4 percent of GDP.
  - Vietnam, Malaysia, Singapore: export diversion in the range of 2 to 4 percent of GDP (due to electronics and machinery).
  - Germany: export diversion of around 1 percent of GDP (vehicles, machinery, electronics).
  - European exporters could see declines of exports of around US$ 84 billion (Figure 11).
- Note: total export diversion in US dollar terms can differ between the size-based and hybrid approaches due to the inclusion of more countries in the hybrid approach.

### Comparison of the three approaches (Section V)
- Broad concordance: all three approaches point to substantial exposure for some economies; differences in magnitudes arise from sectoral assumptions and country coverage.
- Specific comparative findings:
  - Advanced economies:
    - Japan, Germany, Australia: export exposure around 1 percent of GDP across approaches.
    - Switzerland: exposure of 2-3 percent of GDP.
    - Korea: exposure of 3.0 (size-based), 2.8 (cascading), and 2.1 (hybrid) percent of GDP.
  - Asian economies:
    - Singapore and Malaysia: around 3-4 percent of GDP.
    - Vietnam: around 2-4 percent of GDP.
    - Thailand: around 2 percent of GDP.
  - Emerging markets:
    - South Africa: around 2-3 percent of GDP.
    - Russia: 0.4-0.6 percent of GDP.
    - Indonesia: 0.3-0.6 percent of GDP.
- Consistency across methods:
  - Of the 39 economies reported in the size-based approach, differences in export diversion (as a share of GDP) between size-based and hybrid are: within 1 percentage point for 35 economies, and within 0.1 percentage point for 8 economies.
- Cascading approach highlights additional risk for small commodity exporters not captured in the size-based approach.

### Concluding thoughts and policy implications (Section VI)
- Central conclusion:
  - In the absence of a meaningful boost in China’s domestic demand and imports, bilateral purchase commitments (a managed-trade component of a U.S.–China deal) are likely to generate substantial trade diversion effects and significant losses for affected countries if accompanied by market segmentation.
- Key caveats and limitations:
  - Scenarios assume perfect substitution of imports across countries and do not account for rigidities in global value chains, established relationships, or contracts.
  - Export diversion is distinct from potential loss to value added; impacts on value added depend on ease of switching production lines and other factors.
  - Results are sensitive to sectoral assumptions: greater burden on primary products and homogeneous commodities makes smaller commodity-exporting countries appear more affected.
  - Analysis focuses narrowly on the managed-trade aspect; it does not incorporate general equilibrium repercussions or other potential characteristics of a comprehensive deal.
- Policy recommendation:
  - Trade tensions between the U.S. and China should be quickly resolved through a comprehensive agreement that supports the international system and avoids managed trade.

### Appendix and data highlights
- By value in 2017, potentially redirectable goods account for about US$ 700 billion of imports by China.
- 2017 U.S. trade deficit in goods with China: US$ 396 billion.
- Hypothetical managed-trade scenario assumes a managed trade agreement fully closes the trade gap (US$ 396 billion) and fills the gap by redirecting China’s imports in this order: commodities, manufactured goods, products such as aircraft and transportation goods including cars, miscellaneous goods.
- Implementation detail: For each 6-digit item, China’s imports from each trading partner (excluding the U.S.) are reduced in proportion to their share in total imports by China of that good; aggregating yields "exports at risk."

### Origin of value added in China's exports to the U.S. (selected years)
- 2015:
  - CHN, 82.3
  - KOR, 2.1
  - USA, 2.0
  - TWN, 1.7
  - JPN, 1.7
  - DEU, 0.8
  - ROW, 9.3
- 2008:
  - CHN, 76.7
  - JPN, 3.4
  - USA, 2.2
  - KOR, 2.2
  - TWN, 2.0
  - DEU, 1.0
  - ROW, 12.6
- Empirical observation: "China’s role in reducing the U.S. overall trade deficit has been limited in recent times." The U.S. bilateral trade balance with China in value-added terms was 13 percent lower in 2015 compared to gross terms (OECD TiVa database); China’s gross exports to the U.S. (final destination) included 82.3 percent of China’s domestic value added in 2015, up from 76.7 percent in 2008.

*Source: IMF Working Paper WP/19/251 (Sections I–III, staff calculations and UN Comtrade data as presented in the source PDF).*

### Section 1

### wpiea2019251-print-pdf - Section 1

### Overview and purpose
- The paper examines direct, first-round spillover effects on the rest of the world from a potential managed-trade element in a U.S.–China trade agreement.
- It focuses on a highly-stylized scenario in which China closes the bilateral trade deficit with the U.S. by purchasing U.S. goods while China’s total imports do not change (the additional U.S. purchases are entirely at the expense of purchases from the rest of the world).
- The analysis aims to identify likely affected third countries and sectors under alternative assumptions about how China would allocate extra purchases.

### Three modeling approaches used
- Size-based approach
  - Assumes China would scale up purchases among the top-ten 2-digit HS products it currently imports from the U.S.
  - Allocation of extra purchases across those top-ten products is proportional to where there is scope for scaling up.
  - Spillovers to third countries are computed using China’s top-ten exporters for each product, in proportion to their current export exposure to China for those products.
- Cascading approach
  - Uses 6-digit bilateral trade data and considers all trading partners rather than top-ten exporters.
  - Assumes commodities are redirected before manufactures; items with long contracts/production cycles (e.g., aircraft) are used last.
  - Closes the trade gap by exhausting potentially redirected commodity imports first, then part of manufacturing imports.
- Hybrid approach
  - Identifies 2-digit sectors assumed to be in a deal and then redirects within those sectors using 6-digit bilateral trade data across all trading partners.
  - Allocation at the 2-digit level follows top-ten product market shares; redirection within sectors is granular.

### Key assumptions highlighted
- China closes the bilateral trade deficit by purchasing U.S. goods and keeps total imports unchanged.
- Trading relationships are difficult to change overnight, so scaling up occurs where substantial existing trade links exist.
- The scale of increases is capped so total purchase of each product does not exceed China’s total imports of that product.
- Commodities are treated as more substitutable than manufactures; aircraft and similar items are treated as least substitutable.

### Size-based approach — product allocation shares (Figure 2)
- Electronics, 13
- Machinery, 12
- Vehicles, 11
- Oil seeds, 8
- Aircraft, 3
- Optical, 11
- Mineral fuels/oils, 13
- Plastics, 12
- Precious stones, 12
- Wood pulp, 4

### Size-based approach — main quantitative findings
- Baseline bilateral trade deficit used: USD 337bn in 2017 (trade deficit of goods and services).
- Estimated export diversion (aggregate, scenario described):
  - USD 61bn from European Union countries (significant exposure in vehicles, machinery, and aircraft)
  - USD 54bn from Japan (machinery, vehicles, and electronics)
  - USD 46bn from Korea (electronics, opticals, plastics)
  - USD 45bn from ASEAN countries (electronics, plastics, machinery)
- Export diversion exposure as share of 2017 GDP (selected economies):
  - Higher than 3 percent of GDP for OMN, AGO, SGP, and KOR
  - Higher than 2 percent of GDP for MYS, VNM, and THA
  - Around 1 percent of GDP for DEU and JPN
  - Brazil: 1.3 percent of GDP (predominantly due to oil seeds, e.g., soya beans)
- Small oil-exporting countries and small commodity exporters may face especially large export-diversion effects as shares of GDP.

### Alternative allocation scenarios (Figure 5) and their implications
- Alternative scenario 1: Allocation concentrated on a subset of top products (major six products)
  - Allocation shares:
    - Electronics, 25
    - Machinery, 22
    - Vehicles, 17
    - Oil seeds, 9
    - Aircraft, 3
    - Mineral fuels/oils, 25
  - Result: More pronounced export diversion for Germany, Japan, and ASEAN economies due to electronics, machinery, and vehicles; oil exporters face larger GDP-share impacts.
- Alternative scenario 2: Allocation proportional to China’s import structure (excluding U.S.)
  - Allocation shares:
    - Electronics, 34
    - Machinery, 13
    - Vehicles, 6
    - Oil seeds, 3
    - Aircraft, 1
    - Optical, 7
    - Mineral fuels/oils, 23
    - Plastics, 6
    - Precious stones, 6
    - Wood pulp, 2
  - Result: ASEAN economies and Korea would have higher export diversion due to electronics exposure; small oil exporters would again have higher exposure as a share of GDP.

### Cross-cutting insights and policy implications
- The type of products featured in the deal strongly determines which third countries are most affected.
  - Deals emphasizing U.S. sales of vehicles, machinery, and electronics to China would generate substantial diversion affecting the European Union, Japan, and Korea.
  - Deals emphasizing commodities (e.g., oil seeds, mineral fuels) would put small commodity exporters at risk.
- Magnitude and sectoral incidence of trade diversion vary considerably across the three approaches; more granular data reveal greater risk to smaller, highly China-exposed economies.
- Complementarity with other literature:
  - Findings align with other studies that identify direct exposures (e.g., Korea, Malaysia, Japan) and commodity-sensitive countries (e.g., Brazil for soybeans).
  - The paper focuses on higher data disaggregation and a relatively shorter-term, first-round perspective; channels such as global value chain disruptions are acknowledged but beyond this paper’s scope.
- Policy message:
  - The analysis points to advantages of a comprehensive agreement that supports the international system and avoids managed bilateral trade arrangements, to reduce trade diversion risks for third countries.

*Source: IMF Working Paper WP/19/251, Section I–II (authors: Eugenio Cerutti, Shan Chen, Pragyan Deb, Albe Gjonbalaj, Swarnali A. Hannan, and Adil Mohommad).*

### Section 2

### Results from Alternative Scenarios of the Trade Deal

### III. The cascading approach using granular trade data for all trading partners
- Method summary:
  - Uses HS-6-digit bilateral UN Comtrade data for around 200 economies.
  - Constructs export diversion by summing potential redirection to the U.S. of each 6-digit good imported by China from other partners, provided the U.S. also exported that product in 2017.
  - Total U.S. exports are assumed unchanged from 2017 levels—no increase in U.S. production is assumed.
  - Redirection ordering ("cascade"): commodities redirected first, then manufactured goods; goods involving prior contracts (e.g., aircraft) are least likely or excluded.
- Key quantified outcomes and mechanics:
  - China imported about US$ 130bn worth of goods from the U.S. in 2017; China exported about US$ 526bn worth of goods to the U.S. in 2017, implying a trade gap of about US$ 400bn (Figure 7).
  - There are about US$ 600bn worth of China’s 2017 imports from countries excluding the U.S. that could potentially be substituted with U.S. imports; because the trade gap is less than US$ 600bn, not all of this set is used in gap-filling.
  - With the commodity-first ordering, the trade gap exhausts potentially redirected commodity imports and part of manufacturing imports.
- Distribution of extra purchases used to fill the gap (share of total, Figure 8):
  - Chemicals & Allied Industries: 16.0
  - Machinery / Electrical: 25.6
  - Mineral Products: 16.0
  - Plastics / Rubbers: 10.4
  - Stone / Glass: 8.6
  - Metals: 7.3
  - Vegetable Products: 4.6
  - Foodstuffs: 2.5
  - Wood & Wood Products: 2.7
  - Textiles: 2.8
  - Animal & Animal Products: 2.5
  - Raw Hides, Skins, Leather, & Furs: 0.6
  - Footwear / Headgear: 0.3
- Country-level exposure findings (Figure 9 and text):
  - Small commodity exporters are at high risk (examples): Mongolia (coal, copper), Turkmenistan (petroleum gas), Congo (cobalt).
  - East Asian economies with diversified exports but high exposure: Taiwan Province of China, Malaysia, Vietnam, Singapore, Korea, Thailand.
  - Robustness: repeating the exercise on 2016 data yields very similar set of countries at risk.

### IV. The hybrid approach — combining aspects of the size-based and cascading approaches
- Method summary:
  - Starts from the top-ten product allocation used in the size-based approach.
  - Applies allocation at HS-6-digit level across the larger sample (~200 economies).
  - Allocation constrained so it does not exceed (i) China’s current imports from the rest of the world at the 6-digit level, and (ii) the U.S. current exports to the rest of the world at the 6-digit level.
  - Within each 2-digit product, the 6-digit allocation follows the cascading method.
- Key quantified outcomes:
  - Small economies could face significant export diversion if China diverts imports from a large set of countries.
  - Hybrid estimates (examples):
    - Mongolia: export exposure amounting to 12.2 percent of GDP.
    - Turkmenistan: export exposure amounting to 9.4 percent of GDP.
  - Asian economies: Vietnam, Malaysia, Singapore—export diversion in the range of 2 to 4 percent of GDP (due to electronics and machinery).
  - Advanced economy example: Germany—export diversion of around 1 percent of GDP (vehicles, machinery, electronics).
  - European exporters could see declines of exports of around US$ 84 billion (Figure 11).
- Note: total export diversion in US dollar terms can differ between the size-based and hybrid approaches due to the inclusion of more countries in the hybrid approach.

### V. Comparing the results of the three approaches
- Broad concordance: all three approaches point to substantial exposure for some economies; differences in magnitudes arise from sectoral assumptions and country coverage.
- Specific comparative findings:
  - Advanced economies:
    - Japan, Germany, Australia: export exposure around 1 percent of GDP across approaches.
    - Switzerland: exposure of 2-3 percent of GDP.
    - Korea: exposure of 3.0 (size-based), 2.8 (cascading), and 2.1 (hybrid) percent of GDP.
  - Asian economies:
    - Singapore and Malaysia: around 3-4 percent of GDP.
    - Vietnam: around 2-4 percent of GDP.
    - Thailand: around 2 percent of GDP.
  - Emerging markets:
    - South Africa: around 2-3 percent of GDP.
    - Russia: 0.4-0.6 percent of GDP.
    - Indonesia: 0.3-0.6 percent of GDP.
- Consistency across methods:
  - Of the 39 economies reported in the size-based approach, differences in export diversion (as a share of GDP) between size-based and hybrid are: within 1 percentage point for 35 economies, and within 0.1 percentage point for 8 economies.
- Cascading approach highlights additional risk for small commodity exporters not captured in the size-based approach.

### VI. Concluding thoughts and policy implications
- Central conclusion:
  - In the absence of a meaningful boost in China’s domestic demand and imports, bilateral purchase commitments (a managed-trade component of a U.S.–China deal) are likely to generate substantial trade diversion effects and significant losses for affected countries if accompanied by market segmentation.
- Key caveats and limitations (explicitly noted):
  - Scenarios assume perfect substitution of imports across countries and do not account for rigidities in global value chains, established relationships, or contracts.
  - Export diversion is distinct from potential loss to value added; impacts on value added depend on ease of switching production lines and other factors.
  - Results are sensitive to sectoral assumptions: greater burden on primary products and homogeneous commodities makes smaller commodity-exporting countries appear more affected.
  - Analysis focuses narrowly on the managed-trade aspect; it does not incorporate general equilibrium repercussions or other potential characteristics of a comprehensive deal.
- Policy recommendation:
  - Trade tensions between the U.S. and China should be quickly resolved through a comprehensive agreement that supports the international system and avoids managed trade.
- Analytical utility:
  - The paper’s three approaches provide illustrative scenarios using granular bilateral trade data and differing sectoral assumptions to shed light on first-round spillovers across a wide set of countries.

### Appendix A: The U.S. bilateral trade deficit with China — additional context
- Macropoint:
  - Targeting bilateral trade balances will not help reduce a country’s overall current account deficit; current account balances are best addressed through macroeconomic policies affecting saving and investment.
- Value-added facts:
  - The U.S. bilateral trade balance with China in 2015 was 13 percent lower in value added compared to gross terms (OECD TiVa database).
  - China’s gross exports to the U.S. (final destination) included 82.3 percent of China’s domestic value added in 2015, up from 76.7 percent in 2008; the remainder of value added came from economies including Germany, Japan, Taiwan Province of China, Korea, and the U.S.
- Implication:
  - Policies affecting U.S.–China bilateral trade have direct implications for the rest of the world through supply chain linkages.

*Source: IMF staff calculations and UN Comtrade data as presented in Section 2 of the source PDF.*

### Section 3

### wpiea2019251-print-pdf - Section 3

### Origin of value added in China's exports to the U.S. (selected years and partners)
- 2015:
  - CHN, 82.3
  - KOR, 2.1
  - USA, 2.0
  - TWN, 1.7
  - JPN, 1.7
  - DEU, 0.8
  - ROW, 9.3
- 2008:
  - CHN, 76.7
  - JPN, 3.4
  - USA, 2.2
  - KOR, 2.2
  - TWN, 2.0
  - DEU, 1.0
  - ROW, 12.6
- Note: "Origin of value added for gross exports from China to the U.S. (final destination)." Source: OECD TiVa database.

### Empirical observations on China's role in U.S. trade deficit adjustments
- Key findings:
  - "China’s role in reducing the U.S. overall trade deficit has been limited in recent times."
  - IMF 2019a (Chapter 4, Box 3) documents that:
    - (i) overall trade adjustments are not necessarily driven by disproportionate adjustments of the top deficit partners,
    - (ii) large adjustments of the top deficit partners do not guarantee large adjustments in overall trade balance.
  - Empirical note: "the U.S. trade deficit with China widened in recent cases of improvement of the U.S. overall trade deficit from troughs, suggesting that overall trade deficits can be reduced without large corrections in trade balances of key deficit partners."

- Chart indicators referenced (descriptive):
  - U.S. Trade Balance (In percent US GDP) series include:
    - Overall (rhs)
    - China, Gross (U.S. Census Bureau)
    - China, Gross (OECD TiVA)
    - China, Value Added
  - Change in U.S. Trade Balance During Recent Troughs (percentage points) includes series for:
    - Overall
    - China (gross, U.S. Census Bureau)
    - China (gross, OECD TiVa)
    - China (value added)

### Appendix B — Data and methodology of the second approach
- Data:
  - HS6-digit bilateral trade between the U.S. and all its trading partners, and China and all its trading partners.
  - Approximately 5299 individual product lines for each country pair.
  - Baseline year: 2017; robustness check with 2016.
- Objective:
  - Estimate total potential for redirection of China’s imports from other countries to imports from the U.S.
- Restrictions and assumptions:
  - A good imported by China is potentially redirectable only if that 6-digit good is also exported by the U.S.
  - China’s total imports of any particular good remain at the 2017 level (i.e., no change in market size).
- Key statistics:
  - By value in 2017, potentially redirectable goods account for about US$ 700 billion of imports by China.
  - 2017 U.S. trade deficit in goods with China: US$ 396 billion.
- Hypothetical managed-trade scenario:
  - Assumes a managed trade agreement fully closes the trade gap (US$ 396 billion).
  - Gap-filling performed sequentially by redirecting China’s imports in this order:
    - commodities,
    - manufactured goods,
    - products such as aircraft and transportation goods including cars,
    - miscellaneous goods.
  - Rationale: widely traded relatively homogenous goods (such as soy) are easier to substitute than sophisticated manufactured goods or goods subject to lengthier contractual obligations (such as aircraft).
- Implementation of redirection:
  - Closing the US$ 396 billion gap exhausts all potentially redirected commodity imports and part of the identified set of manufacturing imports.
  - For each 6-digit item, China’s imports from each trading partner (excluding the U.S.) are reduced in proportion to their share in total imports by China of that good.
  - Aggregating across redirected 6-digit goods yields, for each non-U.S. trading partner, a measure of "exports at risk."
  - This measure corresponds to Figure 2 in the text.
- Robustness check:
  - The exercise was also conducted using 2016 data and "obtain a similar picture."

*Source: wpiea2019251-print-pdf - Section 3*

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_Source: https://www.imf.org/-/media/files/publications/wp/2019/wpiea2019251-print-pdf.pdf_