## 1. International trade

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### Executive summary: key findings
- World gross exports as a share of global output are "almost three times" the level in the early 1950s.
- Noncommodity trade rose to "more than 20 percent of global gross domestic product (GDP) in 2008."
- Three dominant trends:
  - The rise of emerging market economies (EMEs) as systemically important trading partners.
  - The growing role of global supply chains and vertical specialization.
  - A shift of technology content toward dynamic EMEs and diffusion of high-technology exporters.
- Technology-led declines in transportation and communication costs enabled fragmentation of production; intermediate goods cross borders multiple times before final assembly.
- Advanced economies tend to be upstream (relatively small foreign contents in their exports); EMEs tend to be downstream (relatively large shares of imported content).
- The Asian supply chain is more dispersed than North American or European supply chains and often passes through a hub (Japan) before final destination, making it potentially more vulnerable to disruptions.
- EMEs (notably China) have substantially increased the share of high-technology exports since 1995, boosted by processing trade and significant imported contributions from Japan and other Asian countries.
- Export similarity across countries has increased; quality-adjusted export measures (EXPY) indicate some EMEs have export quality exceeding expectations given GDP per capita, implying an EXPY-induced future growth push.

### The evolving structure of global trade
- Drivers of expansion and interconnectedness:
  - Trade liberalization since the early 1950s (first in advanced economies, later in many developing countries).
  - Growth in vertical specialization and the emergence of global supply chains.
- Convergence and intraindustry trade:
  - Intraindustry trade share increased steadily and is highest for machinery, chemicals, and manufactures.
  - Countries integrated in supply chains (e.g., China, Thailand, Mexico) experienced higher changes in intraindustry trade between 1985 and 2009.
- Key quantitative transformations:
  - Foreign content embedded in gross exports (FVA) has almost doubled since 1970, to 33 percent in 2005.
  - Growth in vertical specialization accelerated recently, increasing by more than 20 percent in the 10-year period up to 2005.

### Global supply chains and sectoral patterns
- Position in supply chain and price sensitivity:
  - Downstream position cushions impact of relative price changes on exports and imports because of higher foreign content in exports.
  - Adjustment in the trade balance occurs mainly outside supply chains; exports to supply chain partners are more resilient to relative price changes.
- Sectoral responses to exchange rate changes (selected results):
  - Appreciation induces an increase in the share of high-technology exports in China and (to a lesser extent) the euro area.
  - Depreciation results in an increase in the share of medium-high-technology exports in Japan and the United States, largely driven by changes in the auto sector.
  - This pattern reflects higher imported input proportions in high-technology products versus higher domestic content in medium-high-technology products.
- Quantitative findings on vertical specialization and hubs (2004 data and IMF staff estimates):
  - Measures of vertical specialization (Imported contents embodied in gross exports; Indirect exports sent to third countries; Upstream or downstream position (3)/(2)):
    - EU15: 11.4, 20.9, 1.8
    - Japan: 12.2, 30.8, 2.5
    - United States: 12.9, 26.9, 2.1
    - Korea: 33.9, 23.1, 0.7
    - China: Hong Kong SAR: 27.5, 19.5, 0.7
    - Taiwan Province of China: 41.1, 27.2, 0.7
    - China: Mainland: 35.7, 12.5, 0.4
    - EU accession countries: 30.8, 11.3, 0.4
    - Mexico: 48.0, 10.0, 0.2
  - Hubs’ value added contained in gross exports (Total; In imports from the hub; In imports from the neighbors):
    - China: 8.0, 6.8, 1.2
    - Mexico: 31.3, 31.0, 0.3
    - EU accession: 17.5, 17.3, 0.2
  - Additional measures:
    - About 15 percent of Japanese value added embodied in Chinese products goes through other countries in Asia before reaching China.
    - The increase in foreign value added (FVA) contributed about 37 percent to the growth in advanced countries’ gross manufacturing exports between 1995 and 2005.
    - Growth in high-technology exports was almost entirely driven by growth in FVA between 1995 and 2005.
    - Services imports contribute about 12 percent of the contribution of FVA in advanced countries’ manufacturing exports in 2005.

### Network analysis and systemic interconnectedness
- Network results:
  - China emerged, along with the United States, as a major systemically important trading hub over the past decade.
  - Systemic importance reflects both trade size and the increase in number of significant trading partners.
  - There is "almost a perfect overlap" between countries hosting systemically important trade centers and systemically important financial centers (top 25 jurisdictions overlap in 2009), with exceptions such as Luxembourg and Ireland (financial only) and Malaysia and Thailand (trade only).
- Implication: jurisdictions hosting both systemic trade and financial sectors warrant focused risk-based surveillance on cross-border spillovers and contagion.

### Box: "Factory Asia" — structural features and dynamics
- Historical relocation and recycling of comparative advantage:
  - Mid-1980s onward: Japanese firms moved labor-intensive assembly to NIEs; later NIEs relocated lower-end assembly to China and ASEAN, producing a "recycling of comparative advantage."
- Structural features of regional supply chains:
  - Asian supply chain: goods-in-process cross borders several times and often pass through a hub (Japan); e.g., about 15 percent of Japanese value added embodied in Chinese products goes through other countries in Asia before reaching China.
  - NAFTA and Europe: almost all FVA in other regions is imported directly from the hub—the United States in NAFTA and EU15 in Europe.
  - Processed value added flowing back to the hub is significant for the United States and EU15; less so for Japan.
- Role of FDI and diffusion of high-technology exporters:
  - Between 1995 and 2008 contributions of high-technology exports to overall export growth (not adjusted for foreign content):
    - China: more than 30 percent
    - United States: 26 percent
    - Germany: 17 percent
    - Japan: 11 percent
  - Adjusted for domestic value added (DVA):
    - China: 24 percent
    - United States: 29 percent
    - Germany: 20 percent
  - FDI motives differ: U.S. FDI driven by market access; Japanese FDI motivated by factor-price differentials.

### Supply-chain implications of natural disasters: March 11, 2011 Pacific earthquake (Japan)
- Japan’s role and vulnerabilities:
  - Japan is upstream in the Asian supply chain and a major supplier of sophisticated intermediate inputs, particularly in transport and electrical machinery sectors.
  - Significant proportions of FVA in other Asian countries’ gross exports come from Japan (e.g., Hong Kong SAR and China for electronic equipment; Thailand and Taiwan for motor vehicles).
  - A disruption in production of key intermediate inputs in Japan has the potential to spill over to production in other countries in the supply chain.
- Short-term impacts and firm-level signals:
  - Japanese exports plunged in April 2011 (high-frequency data).
  - Exports of vehicles were hit particularly hard compared to machinery; exports to the United States were harder hit compared to China.
  - Equity prices and supply projections suggest impacts are likely to be short-lived, though downside risks remain if disruptions are prolonged and inventories run out.
  - Substitution is harder in subsectors where Japanese exporters have a high market share and where patent protection matters (e.g., microcontroller units).

### Modeling approach, simulations, and historical perspective
- Modeling framework:
  - Two-stage approach:
    - Stage 1: partial equilibrium model at HS six-digit level with Armington-style preferences and sectoral elasticities to simulate import-demand responses to relative price changes.
    - Stage 2: input-output tables adjust imports for trade-induced changes in aggregate demand via Leontief matrix and imported input coefficients.
  - Elasticity calibration and data handling:
    - Import demand elasticity literature range cited: –2 to –3.
    - Authors use Broda and Weinstein elasticities scaled to a mean of 2.25 and report an import-weighted mean elasticity of 2.4.
    - Country-specific import demand elasticities: Kee, Nicita, and Olarreaga (2008) elasticities scaled to a mean of –1 resulting in an import weighted mean of –0.79.
    - Outliers capped at mean plus 2 standard deviations; missing observations filled using higher-aggregation product elasticities.
- Simulation design (baseline 2008 trade):
  - Illustrative policy shocks:
    - China: 10 percent increase in relative prices (real appreciation).
    - United States: 10 percent decline in relative prices (real depreciation).
    - Illustrative: 10 percent relative price increase in the euro area and 10 percent decline in Japan.
  - Selected aggregate simulated impacts (high-level qualitative results):
    - A 10 percent depreciation for the United States would result in a 14 percent expansion in exports and a 7 percent contraction in imports; together these translate into a 40 percent improvement in the trade balance and roughly a halving of the U.S. current account deficit-to-GDP ratio.
    - A 10 percent real exchange appreciation in China would lead to a 50 percent reduction in its merchandise trade surplus.
    - Downstream countries (e.g., China) exhibit smaller export responses and relatively small import growth owing to high imported content in exports.
  - Pass-through assumptions and timing:
    - Empirical pass-through estimates cited: about 0.6 in the short run and 0.75 in the long run (Campa and Goldberg, 2005).
    - U.S. import market pass-through: 0.25 in the short run and 0.4 in the long run.
    - Imperfect pass-through implies larger nominal exchange rate changes are needed to generate a given shift in international relative prices.
    - Adjustment timing: about half of the long-run adjustment in trade balances would materialize within the first 2 years, and 80 percent within 6 years.
- Historical (DAREER) evidence and calibration:
  - The DAREER uses a midpoint ratio of long-run to short-run impacts of 3:
    - Implication: a third of the impact of a 10 percent change in the REER would manifest in the first year.
  - Historical regularity: on average, the trade balance improved (deteriorated) by 0.17 percent of GDP for every percentage point depreciation (appreciation) of the DAREER.
  - Simulation consistency: a 10 percent real depreciation corresponds to a 1.4 percentage point of GDP improvement in the U.S. trade balance under partial pass-through.

### Export similarity, quality measures (ESI and EXPY) and implications
- Export Similarity Index (ESI):
  - ESI measures similarity of export structures at six-digit product level; ESI = 1 means identical structures, 0 means completely dissimilar.
  - Export structures of EMEs are increasingly similar to advanced economies; the ESI adjusted for destination-quality differences still shows increased overlap (notably China, Indonesia, Vietnam, Poland, Turkey), albeit smaller than unadjusted ESI.
- EXPY (Hausmann, Hwang, and Rodrik, 2007):
  - EXPY assigns to each product a weighted average income level of countries producing that product to gauge export sophistication.
  - Findings:
    - Japan consistently increased export value (EXPY) over time relative to G-7 peers.
    - EMEs’ EXPY remains below advanced countries’ EXPY; China outperforms other large emerging markets on EXPY.
    - Countries with higher-than-expected EXPYs relative to GDP per capita tend to grow more subsequently; expected strong EXPY-induced growth push for China, India, Thailand; positive though smaller for many eastern European countries.

### Policy implications and recommendations
- Surveillance and risk assessment:
  - Consider systemic trade–financial overlaps when assessing cross-border spillovers.
  - Focus surveillance on jurisdictions hosting both systemically important trade and financial sectors.
  - Incorporate supply-chain structures when evaluating vulnerabilities to shocks (policy or natural disasters).
- Trade policy and supply-chain resilience:
  - Protecting the free flow of inputs and outputs should be a top priority given higher vulnerabilities of dispersed regional supply chains (Asia).
  - Policy options include binding unilateral tariff cuts in multilateral agreements (Doha) or including all key players in regional FTAs such as the Trans-Pacific Partnership (TPP).
  - Excluding a key player such as China in regional FTAs could create bilateral tensions potentially disruptive to supply chain trade flows.
- Domestic policies to facilitate upgrading and resilience:
  - Create an environment enabling firms to undertake quality upgrading to better absorb international price shocks.
  - Provide a reliable macroeconomic environment and aim to lower:
    - Costs of doing business; and
    - Costs of establishing trade relationships.
  - Enabling firms to respond to unfavorable exchange rate movements via quality upgrading is identified as the most promising strategy when sectors face symmetric relative price shocks.
- Specific caution on "just-in-time" models:
  - The March 11, 2011 earthquake in Japan highlights potential limits of just-in-time production; prolonged disruptions could force reconsideration of inventory strategy and sourcing networks.

### Selected appendix measures and exact statistics (preserved)
- Foreign Value Added (FVA) share in exports: formula and computation guidance described (u·A_M·L·E / E_k).
- Selected FVA share in gross exports (Table A2.1, Percent of gross exports):
  - AUS: 1995 = 13.9, 2005 = 14.1
  - CHN: 1995 = 15.5, 2005 = 27.4
  - DEU: 1995 = 20.8, 2005 = 27.8
  - USA: 1995 = 9.5, 2005 = 12.3
  - IRL: 1995 = 45.5, 2005 = 51.2
  - HUN: 1995 = 47.7, 2005 = 56.1
  - TWN: 1995 = 34.9, 2005 = 48.5
- Selected FVA content in gross exports by country of origin (Table A2.2, Billions of U.S. dollars, 2005):
  - China: FVA = 232.50; Service = 43.05; DVA = 615.23
  - Japan: FVA = 100.98; Service = 17.73; DVA = 563.09
  - USA: FVA = 136.38; Service = 28.09; DVA = 968.55
  - Germany: FVA = 310.00; Service = 58.15; DVA = 805.57
- Selected FVA share in gross exports by country of origin (Table A2.3, Percent of gross exports, 2005):
  - China: FVA = 27.4; Service = 5.1; DVA = 72.6
  - Japan: FVA = 15.2; Service = 2.7; DVA = 84.8
  - USA: FVA = 12.3; Service = 2.5; DVA = 87.7
  - Germany: FVA = 27.8; Service = 5.2; DVA = 72.2
- Box 6 sectoral simulation summary:
  - A 10 percent depreciation for the United States → 14 percent expansion in exports; 7 percent contraction in imports; 40 percent improvement in the trade balance.
  - A 10 percent real exchange appreciation in China → 50 percent reduction in its merchandise trade surplus.
- Box 7 historical elasticity:
  - On average, the trade balance improved (deteriorated) by 0.17 percent of GDP for every percentage point depreciation (appreciation) of the DAREER.

_This paper was prepared by a staff team led by Nagwa Riad and comprising Luca Errico, Christian Henn, Christian Saborowski, Mika Saito, and Jarkko Turunen, assisted by Tushara Ekanayake, Alex Massara, and Nick Young. The work was guided by Richard Harmsen, Ranil Salgado, and Tamim Bayoumi._

### 1. International trade.  I. Riad, Nagwa.  II.  International Monetary Fund.

### 1. International trade

### Executive summary: key findings
- World gross exports as a share of global output are "almost three times" the level in the early 1950s.
- Noncommodity trade rose to "more than 20 percent of global gross domestic product (GDP) in 2008."
- Three dominant trends characterize recent trade expansion:
  - The rise of emerging market economies (EMEs) as systemically important trading partners.
  - The growing role of global supply chains and vertical specialization.
  - A shift of technology content toward dynamic EMEs and diffusion of high-technology exporters.
- Technology-led declines in transportation and communication costs enabled fragmentation of production across countries; intermediate goods cross borders multiple times before final assembly.
- The extent of imported inputs in a country’s exports distinguishes "downstream" (high imported content, assembly/processing) from "upstream" (hub) positions in supply chains.
- Advanced economies tend to be upstream with relatively small foreign contents in their exports and relatively large contributions to downstream countries’ exports; EMEs tend to be downstream with relatively large shares of imported content in their exports.
- The Asian supply chain is more dispersed than North American or European supply chains: goods-in-process cross borders several times and often pass through a hub (Japan) before final destination; in contrast, North America and Europe typically import almost all foreign input directly from their hub (United States in NAFTA; EU15 in Europe).
- The dispersion of the Asian supply chain makes it potentially more vulnerable to disruptions (policy-induced or natural disasters).
- EMEs (notably China) have substantially increased the share of high-technology exports since 1995, boosted by processing trade and significant imported contributions from Japan and other Asian countries.
- China is moving upstream: imports from China contribute significantly to advanced countries’ high-technology exports.
- Export similarity across countries has increased over time, raising competitive pressures; quality-adjusted export measures suggest some EMEs have export quality exceeding expectations given GDP per capita.
- Countries with higher-than-expected income value of exports (per Hausmann, Hwang, and Rodrik (2007) methodology) can expect additional growth push in the future.

### The evolving structure of global trade
- Trade expansion and increased interconnectedness have been driven by:
  - Trade liberalization since the early 1950s (first in advanced economies, later in many developing countries).
  - Growth in vertical specialization and the emergence of global supply chains.
- Regional production networks emerged and eventually became global as production stages localized where cost-effective.
- A practical implication: countries in global supply chains have higher share of imported content in their exports.
- The analysis in the paper uses three complementary approaches:
  - Network analysis to determine systemically important trading countries.
  - Input-output-based analysis to examine growth of global supply chains at aggregate and sectoral levels.
  - A partial equilibrium approach to analyze implications of sectoral trade patterns on global rebalancing and trade outlook.

### Global supply chains and sectoral patterns
- Position in supply chain affects sensitivity to relative price changes:
  - Downstream position cushions impact of relative price changes on both exports and imports due to higher foreign content in exports (appreciation also makes imports relatively cheaper).
- Sectoral responses to exchange rate changes differ across countries:
  - Appreciation induces an increase in the share of high-technology exports in China and (to a lesser extent) the euro area.
  - Depreciation results in an increase in the share of medium-high-technology exports in Japan and the United States, largely driven by changes in the auto sector.
  - This pattern reflects higher imported input proportions in high-technology products versus higher domestic content in medium-high-technology products.
- Adjustment in the trade balance occurs mainly outside supply chains:
  - Exports to supply chain partners are more resilient to relative price changes.
  - Two reasons: cost of breaking trade relationships in supply chains is high (lower substitution elasticities), and dominant regional suppliers are harder to substitute for given their share of exports to partners.

### Network analysis and systemic interconnectedness
- Network-based analysis documents emergence of China, along with the United States, as major systemically important trading hubs over the past decade.
- Systemic importance reflects both the size of trade and the increase in number of significant trading partners.
- There is "almost a perfect overlap" between countries hosting systemically important trade centers and systemically important financial centers.
- Such countries could be natural focuses for risk-based surveillance on cross-border spillovers and contagion.

### Policy implications and outlook
- The growing role of global supply chains and increased trade interconnectedness imply:
  - Greater exposure to cross-border shocks, especially for dispersed supply chains (e.g., Asian production networks).
  - Potential for more muted effects of exchange rate appreciation for downstream EMEs due to high imported content in exports.
  - Sectoral reallocation of trade in response to relative price changes, with high-technology and medium-high-technology sectors responding differently across countries.
- Surveillance and policy should consider:
  - Systemic trade–financial overlaps when assessing cross-border spillovers.
  - Supply-chain structures when evaluating vulnerabilities to shocks (policy or natural disasters).
  - The distributional and sectoral implications of rebalancing among key players (China, euro area, Japan, United States).

*This paper was prepared by a staff team led by Nagwa Riad and comprising Luca Errico, Christian Henn, Christian Saborowski, Mika Saito, and Jarkko Turunen, assisted by Tushara Ekanayake, Alex Massara, and Nick Young. The work was guided by Richard Harmsen, Ranil Salgado, and Tamim Bayoumi.*

### Introduction

### _dp1201 - Introduction

### A. The Diffusion of Key Players in Global Trade
- Emerging market economies have moved from peripheral players to major centers of global trade.
- By 2010, China became the second largest trading partner after the United States, overtaking Germany and Japan.
- Trade was 57 percent of GDP in 2008 in China, almost triple the ratio of the United States.
- In the early 1970s, the United States, Germany, and Japan together accounted for more than a third of global trade.
- By 1990, the global trading landscape had become more diversified to include several EMEs, especially in East Asia.
- Growth in trade was strongest for Europe and Asia.
- Interregional trade was virtually unchanged at about 12 percent of world GDP between 1980 and 2009, while intraregional trade grew particularly strongly in Europe and Asia.
- The structure of trade shifted toward a rising share of higher-technology goods; the contribution of high-technology and medium-high-technology exports such as machinery and transport equipment increased, whereas that of lower-technology products such as textiles declined.
- Technology-intensive export structures generally offer better prospects for future economic growth; trade in high-technology products tends to grow faster than average and has larger spillover effects on skills and knowledge-intensive activities.
- Technology absorption is “capability” driven and depends on the national ability to harness and adapt technologies rather than on factor endowments (Lall, 2000).

### Drivers of Changing Trade Patterns
- Trade liberalization:
  - Among major western European and North American countries, average tariffs fell from 15 percent to 4 percent during 1952–2005, with the bulk of this decline occurring during the 1950s and 1960s (WTO, 2007).
  - Tariffs increased or remained very high until the 1980s in many major developing countries but have since come down sharply as well.
- Increase in vertical specialization in production:
  - Technology-led declines in transportation and communication costs allowed fragmentation of production processes along vertical trading networks across countries.
  - Foreign content embedded in gross exports (foreign value added, FVA) has almost doubled since 1970, to 33 percent in 2005.
  - Growth in vertical specialization accelerated recently, increasing by more than 20 percent in the 10-year period up to 2005.
- Convergence in income levels:
  - As countries converged in income levels and factor composition, trade relative to GDP increased, taking the form of intraindustry trade.
  - Intraindustry trade as a share of overall trade has increased steadily and is highest for products such as machinery, chemicals, and manufactures.
  - Countries integrated in supply chains (e.g., China, Thailand, Mexico) experienced higher changes in intraindustry trade between 1985 and 2009.

### Key Statistics on Value Added and Trade Composition
- Table 1 (as presented):
  - FVA share of gross exports0.180.240.270.33
  - Growth in FVA share31.321.5
  - Contribution of FVA exports to growth in exports/GDP32.555.9
- For countries heavily engaged in assembly and processing trade (e.g., Singapore), gross exports can be more than twice as high as domestic value added (DVA) exports.
- Advanced economies tend to be upstream in global supply chains, EMEs tend to be further downstream.
- China’s imports content:
  - The increase in the share of imported content was particularly pronounced for China (where the share of imported content increased by 12 percentage points), and for Germany and Japan (7 percentage points).
- For Germany, if foreign content from the euro area is considered part of DVA, overall foreign content in Germany’s exports declines to 19.6 percent in 2005 and to about 13.5 percent in 1995.

### B. Growing Trade Interconnectedness
- Growth in trade interconnectedness has increased the cross-border transmission of shocks through the trade channel.
- Network analysis identifies jurisdictions with systemically important trade sectors and shows several trends over the past decade:
  - Marked shift in relative rankings of individual jurisdictions, with China moving to first place in 2009 up from ninth in 1999.
  - China and the United States emerged as major systemically important trading centers, with China increasing both size and number of significant trading partners.
  - China surpassed Japan as a more significant regional and global consumer; China increased the number of its significant trading partners and became a more central importer.
  - European countries retained importance as “central” in the global trade network, owing more to interconnectedness than size.
- Strong overlap between countries with systemically important trade and financial sectors:
  - Almost perfect overlap between the top 25 jurisdictions with systemic financial sectors and the top 25 jurisdictions with systemic trade sectors in 2009.
  - Exceptions: Luxembourg and Ireland (systemic importance limited only to the financial sector), and Malaysia and Thailand (systemic importance limited only to the trade sector).
- Jurisdictions hosting both systemic trade and financial sectors warrant particular attention and further analysis on risks associated with their activities, especially through systemically important financial institutions and nonfinancial corporations.

### C. The Growing Role of Global Supply Chains
- Vertical specialization increased since the mid-1990s and contributed significantly to the rise of major exporting countries.
- China’s role:
  - The share of imported content in China’s exports increased by 12 percentage points.
  - China’s exports have high content of FVA that is from Asia: more than half of FVA is from the region, including other east Asian (OEA) economies.
  - Rapid growth in Chinese real household consumption (more than doubled) and gross fixed capital formation (nearly fivefold) shifted China’s role to a major importer and downstream assembly center.
- Germany’s role:
  - Most FVA in Germany’s exports comes from other EU countries, including EU accession countries; about 70 percent of FVA in exports of EU accession countries is from advanced euro area countries, Russia, or EFTA countries.
  - Germany functions more as an upstream hub in regional supply chains.
- EMEs and processing trade:
  - EMEs tend to have relatively large imported contents in their exports and a smaller share of indirect exports to third countries, confirming their downstream position in global supply chains.
  - Processing trade accounts for a significant share of exports from China and many other Asian EMEs, involving lower value added production processes using imported intermediates to assemble final goods for export.

*Source: _dp1201 - Introduction*

### Box 2). Mexico has a somewhat similar role, owing to specialized duty free

### Box 2. “Factory Asia”

### Origins and dynamics
- Prior to the mid-1980s, east Asian trade was suppressed by “dual track” development strategies that blocked imports of manufactured goods while fostering export-oriented industries.
- Starting in the mid-1980s, rapid trade liberalization and a surge in intraregional trade emerged in east Asia.
- In response to the strong appreciation of the yen in the mid-1980s, Japanese firms shifted labor-intensive assembly operations to newly industrialized economies (NIEs).
- As NIE currencies appreciated (Korean won, Singaporean dollar, etc.), NIEs relocated lower-end, labor-intensive assembly processes to countries such as China and the ASEAN countries.
- Successive relocations produced a “recycling of comparative advantage” characteristic of the Asian supply chain, enabling NIEs, then China and ASEAN countries, to develop comparative advantage in manufacturing exports and progressively upgrade industrial capacity.
- In the 1990s, China’s emergence intensified competition for jobs and investment in east Asia, accelerating unilateral liberalization in the region.
- Regionalism in east Asia began only in 2000 when China expressed interest in an FTA with ASEAN. ASEAN-Japan FTA, Korea-ASEAN FTA, and Japan-Korea FTA are argued to be reactions to the ASEAN-China FTA (ACFTA).
- Factory Asia was established without “real” regionalism; there is neither WTO discipline locking in the unilateral tariff cuts that created Factory Asia nor “top-level management” to substitute for WTO discipline in east Asia.

### Structural features of regional supply chains (Asia, NAFTA, Europe)
- Two key distinguishing features:
  - Extent of dependence on a regional hub:
    - The Asian supply chain extends across several countries with goods-in-process crossing borders several times, including through the hub (Japan), before reaching their final destination.
      - For instance, about 15 percent of Japanese value added embodied in Chinese products goes through other countries in Asia before reaching China.
    - In contrast, in NAFTA and Europe almost all the FVA in other regions is imported directly from the hub—the United States in NAFTA and EU15 in Europe.
  - Extent of processed value added flowing back to the hub:
    - A significant amount of U.S. value-added (and EU15 value added to a lesser extent) returns home after further processing abroad, which is not necessarily the case for Japan.
    - Processing trade in Asia therefore relies heavily on the region as a whole.
- Sectoral implication:
  - The role of global supply chains for trade in high-technology goods has increased over time, especially in China.
  - The share of imported content in exports of high-technology goods increased for China, Japan, the United States, and the European advanced economies since the mid-1990s.
  - The increase is particularly pronounced for China—the imported content of Chinese high-technology exports increased by close to 30 percentage points from the mid-1990s to the mid-2000s.

### Quantitative measures from Koopman and others (2004 data) and IMF staff estimates
- Table 3. Measures of Vertical Specialization across Borders: 2004 (columns: (2) Imported contents embodied in gross exports; (3) Indirect exports sent to third countries; (4) Upstream or downstream position, (3)/(2))
  - EU15: 11.4, 20.9, 1.8
  - Japan: 12.2, 30.8, 2.5
  - United States: 12.9, 26.9, 2.1
  - Korea: 33.9, 23.1, 0.7
  - China: Hong Kong SAR: 27.5, 19.5, 0.7
  - Taiwan Province of China: 41.1, 27.2, 0.7
  - China: Mainland: 35.7, 12.5, 0.4
  - EU accession countries: 30.8, 11.3, 0.4
  - Mexico: 48.0, 10.0, 0.2
  - Note: Column (3) includes indirect exports that return to home country.

- Table 4. Hubs’ Value Added Contained in Gross Exports (columns: Total; In imports from the hub; In imports from the neighbors)
  - China: 8.0, 6.8, 1.2
  - Mexico: 31.3, 31.0, 0.3
  - EU accession: 17.5, 17.3, 0.2
  - Note: For China, Mexico, and EU accession countries, hubs are Japan, the United States, and the EU, respectively.

- Additional quantitative findings:
  - About 15 percent of Japanese value added embodied in Chinese products goes through other countries in Asia before reaching China.
  - The increase in foreign value added (FVA) contributed about 37 percent to the growth in advanced countries’ gross manufacturing exports between 1995 and 2005.
  - Growth in high-technology exports was almost entirely driven by growth in FVA between 1995 and 2005.
  - China’s contribution to advanced countries’ growth in manufacturing exports is significant and concentrated in high- and medium-high-technology sectors.
  - Services imports contribute about 12 percent of the contribution of FVA in advanced countries’ manufacturing exports in 2005.

### Diffusion of high-technology exporters and role of FDI
- Between 1995 and 2008:
  - Contribution of high-technology exports to overall export growth (not adjusted for foreign content):
    - China: more than 30 percent
    - United States: 26 percent
    - Germany: 17 percent
    - Japan: 11 percent
  - Adjusted for domestic value added (DVA):
    - China: 24 percent
    - United States: 29 percent
    - Germany: 20 percent
    - Mexico: notable increase in high-technology contribution when only DVA is considered (no exact percentage provided)
- FDI facilitates technology diffusion across global supply chains:
  - U.S. FDI is generally driven by market access considerations.
  - Japanese FDI is motivated by factor-price differentials across borders arising from relative abundance of unskilled labor in Asia.
  - Labor-intensive stages of production (e.g., final assembly) are moved to host countries with lower unskilled labor costs; skilled-labor-intensive activities (e.g., marketing, patenting, innovation) are retained in headquarters.
- Factors enabling EMEs to upgrade technology content of exports:
  - Geographical proximity to advanced countries.
  - Existence of an educated workforce.
  - A favorable business environment.
  - Countries that gained most in exports of high-technology products over the last decade had initial conditions in 1995 featuring an intermediate level of development and some presence in high-technology sectors.

### Policy implications
- The greater regional dispersion in the Asian supply chain has important policy implications:
  - Any disruption of trade flows, particularly intraregional trade flows in Asia, could have large negative spillover effects on domestic production in partner countries.
  - Protecting the free flow of inputs and outputs should be a top priority.
  - Policy options to protect supply chain trade flows include binding the region’s unilateral tariff cuts under the Doha Round or including all key players in regional FTAs such as the Trans-Pacific Partnership (TPP).
  - Excluding a key player such as China in regional FTAs could create bilateral tensions potentially disruptive to supply chain trade flows.

*Source: IMF staff estimates using OECD Input-Output Tables, UN Comtrade, and OECD STAN data.*

### Box 4. (concluded)

### Box 4. (concluded)

### High-Technology Exports, R&D, and Royalties
- R&D spending on HT sectors (Percent of GDP) is shown for Korea, Japan, USA, Singapore, Germany across 1995–2006 (figure data not reproduced here).
- Royalties and license fees are reported both as Percent of GDP and in Billions of U.S. dollars across 1995–2010 (figure data not reproduced here).
- ISIC-30 (Computers and Office Equipment), ISIC-32 (Electronics and Communication) export series are shown across 1988–2010 with detailed product-level entries such as:
  - "automatic data processing machinery"
  - "parts and accessories of automatic data processing machinery, incl. printing machinery"
  - "electronic integrated circuits, transmission apparatus, transistor and semiconductor"
  - "telephone, microphones, record players, tape recorders, radio"
  (figure series not numerically transcribed here).

### Upgrading of Export Baskets in Low-Income Countries (LICs)
- Many LICs have experienced an upgrade in their export baskets; the incidence of medium-high- and high-technology products in LIC non-oil exports increased notably between 1995 and 2008.
- Box Figure 5.1: Share of medium-high- and high-technology products in non-oil exports:
  - Share in 1995: about 3 to 4 percent (aggregate baseline across LIC groups).
  - Share in 2008: about 7 percent for African LICs, and 12 to 16 percent for LICs in Asia and the Middle East and Central Asia.
- Destination decomposition (Box Figures 5.2 and 5.3):
  - A significant share of medium-high- and high-technology exports by LICs in 2008 occurred between African LICs themselves.
  - Emerging market economies (EMEs) are important destinations for LIC medium-high- and high-technology exports:
    - China, Singapore, and Thailand for Asian LICs.
    - South Africa for African LICs.
    - Mexico for LICs in the Western Hemisphere.
- In 2008, the share of non-oil exports in overall exports for LICs was:
  - 28 percent for LICs in Africa,
  - 35 percent in the Middle East and Central Asia,
  - 81 percent in the Western Hemisphere,
  - 83 percent in Asia.
- Advanced economies remain important destinations for LIC exports, more so for lower-technology than higher-technology products; nevertheless, exports of medium-high- and high-technology products to Japan (for Asian LICs) and to the United States (for LICs in the Western Hemisphere) increased.

### Rising Export Similarity and Export Similarity Index (ESI)
- Export structures of EMEs are increasingly similar to those of advanced economies, partly reflecting the expansion of global supply chains.
- The Export Similarity Index (ESI) measures similarity of export structures (six-digit product shares); an ESI value of 1 corresponds to identical export structures and 0 to completely dissimilar structures.
- Observations:
  - Japan competes most with Korea, the United States, and European countries.
  - The U.S. export structure remains similar to other advanced economies.
  - China has traditionally competed with other Asian countries; its export structure has been converging with advanced economies such as Germany and the United States.
- Adjustment to ESI to account for destination-quality differences:
  - The ESI is recalculated by distinguishing products by five destination markets using the World Bank income classification (high-income OECD, high-income non-OECD, upper middle income, lower middle, low-income). Product “A” exported to a low-income country is treated as a different product from product “A” exported to a high-income country.
  - Even after this adjustment, increased overlap in export structures between EMEs (notably China, Indonesia, Vietnam, Poland, Turkey) and advanced countries persists, albeit to a lesser extent than unadjusted ESI.

### Export Quality, EXPY, and Growth Implications
- Gross exports data may not capture quality differences within the same product category; products can be differentiated by price and quality.
- The EXPY indicator (Hausmann, Hwang, and Rodrik, 2007) assigns to each six-digit product category a weighted average income level of countries producing that product, gauging export sophistication.
- Findings:
  - Japan has consistently outperformed the G-7 countries in increasing the value (income level) of its exports (EXPY) over time (figure data not numerically transcribed here).
  - Despite catch-up, EMEs’ EXPY remains below advanced countries’ EXPY; EMEs’ exports are still skewed toward lower-income product categories, including China which nevertheless strongly outperforms other large emerging markets on this metric.
  - Countries with higher-than-expected EXPYs relative to GDP per capita tend to grow more in subsequent years (EXPY-induced growth push). The growth push is expected to be most pronounced for Asian countries such as China, India, and Thailand, and positive though smaller for many eastern European countries.
- Interpretation:
  - The shift in technology content and convergence in export structures can reflect higher complementarity from outsourcing of labor-intensive production to low-wage countries, as well as increased competition.
  - Examples: growing proportion of Japanese machinery exports assembled in China (Japan’s upstream role), technological intensity shifting from western to eastern Europe (Czech Republic, Hungary, Poland), U.S. outsourcing of some high-technology activities to NAFTA partners (Mexico) and Central America.

### Past Trends, Trade Outlook, and Price Sensitivity in Global Supply Chains
- Integration of rapidly growing EMEs is likely to shift global demand sources away from advanced economies.
- With China overtaking Japan as the second largest economy in 2010, East Asian countries are projected to emerge as the largest trading bloc by 2015, surpassing NAFTA and the euro area (figure data not numerically transcribed here).
- Global supply chains affect trade responsiveness to relative price changes:
  - Higher imported content in exports is likely to lower the sensitivity of trade to exchange rate changes because cheaper imported intermediates offset more expensive exports when the domestic currency appreciates.
  - Advanced countries with exports concentrated in medium-high-technology goods and higher domestic value added (DVA) are likely to be more sensitive to relative price changes.
  - EMEs with higher foreign value added (FVA) in their exports are likely to be less sensitive.
- Global supply chains also increase producer linkages across countries and raise potential adjustment costs and vulnerabilities (disruptions can have spillovers).

### Supply Chain Implications of the March 11, 2011 Pacific Earthquake in Japan (Box 6)
- The March 11, 2011 Pacific earthquake in Japan is likely to test the resilience of the Asian supply chain; analysis focuses on semiconductor and automobile industries as most vulnerable.
- Japan’s regional trade role and recent patterns:
  - Asian intraregional trade expanded rapidly since 1990, driven by dynamic economies such as China.
  - Japan’s intraregional exports as a share of global GDP remained remarkably stable, even during the crisis, and account for more than two-thirds of industrial countries’ intraregional trade.
  - Japanese exports to the region accounted for almost 60 percent of overall exports in 2010, mostly concentrated in machinery, chemicals, and transport equipment.
  - Japan’s trade structure is shifting from exports of high-technology final products toward exports of sophisticated intermediate inputs; Japan is an important global supplier of sophisticated manufacturing inputs, particularly in transport and electrical machinery sectors.
- Japan’s role in foreign value added (FVA):
  - Japan is upstream in the Asian supply chain; foreign content in gross exports of many Asian countries is relatively high (more than 80 percent in electronic equipment in Singapore).
  - A significant proportion of FVA in those gross exports comes from Japan, especially for:
    - Hong Kong SAR and China (electronic equipment),
    - Thailand and Taiwan (motor vehicles).
  - A disruption in production of key intermediate inputs in Japan due to the earthquake has the potential to spill over to production in other countries in the supply chain.
- Empirical signal:
  - High-frequency Japanese trade data show exports plunged in April 2011 (figure note; series not numerically transcribed here).

*Italic: Source: _dp1201 - Box 4. (concluded)_ (IMF PDF content unit).*

### Box 6. (continued)

### Box 6. (continued)

### Japan’s export shares and partner import dependence (Box Table 6.1)
- Japan exports (percent of world exports; reporting): 34.3, 10.0, 15.0, 17.1
- Imports from Japan (percent 4-digit imports) by partner:
  - China: Mainland: 35.7, 37.1, 19.6, 23.5
  - China: Hong Kong SAR: 23.2, 7.6, 15.2, 30.6
  - India: 12.2, 10.0, 7.8, 15.0
  - Indonesia: 48.6, 31.1, 35.1, 20.1
  - South Korea: 40.6, 34.6, 25.3, 18.7
  - United States: 53.2, 20.2, 17.8, 27.7
  - European Union: 27.2, 25.2, 6.4, 33.3
- Note: HS codes referenced in table: 8486, 8408, 8541, 8703 (see source table note for exact product descriptions).

### Short-term impact of the Pacific earthquake on Japanese exports and firms
- Sectoral and partner heterogeneity:
  - Exports of vehicles were hit particularly hard compared to machinery.
  - Exports to the United States were harder hit compared to China, reflecting higher weights of final goods (cars) in U.S. exports versus intermediates (parts and accessories) to China.
  - Within vehicles, final goods (cars subsector) declined more than intermediates (parts and accessories), possibly reflecting inventory effects.
- Market signals and firm-level outcomes:
  - Equity prices and supply projections by industry analysts suggest the overall impact of the disruption along the supply chain is likely to be short-lived.
  - Many affected Japanese firms’ returns remained significantly below expectations in the period covered.
  - Staff micro analysis of firms’ equity returns in the semiconductor industry indicates:
    - Initial impact on upstream (input suppliers), midstream (memory makers), and downstream (PC and handset makers) firms, especially during elevated nuclear-meltdown concerns.
    - Effects did not persist for all firms in the ensuing month, partly due to a prior buildup in global semiconductor inventory, which may provide some cushion possibly until 2011:Q3.
  - In the automobile sector:
    - Concerns centered on disruptions to microcontroller units (MCUs).
    - Equity returns for Japanese MCU manufacturers experienced significantly negative abnormal returns (ARs) since March, coinciding with weak returns for Japanese auto manufacturers.
    - Japanese MCU manufacturers scaled back production globally; equity markets suggest competitors may substitute for lost production.
- Supply-chain outlook:
  - Supply chain implications of the Pacific earthquake are likely to be transitory, although downside risks remain.
  - Short-term substitution is harder in subsectors where Japanese exporters have a high market share.
  - Firms may endure losses during Japanese production recovery via inventory adjustment or temporary shutdowns.
  - Sophisticated subproducts may be protected by patent rights, making short-term substitution difficult.
  - If disruptions are prolonged and inventories run out, firms may be forced to replace Japanese suppliers.

### Modeling approach: sectoral elasticities and input-output linkage
- Methodology:
  - A partial equilibrium approach combined with input-output table analysis is used to analyze sectoral trade-flow responses to relative price changes.
  - Step 1: Model import-market demand responses and shifts in trade structure at the product level, reflecting import-demand and substitution elasticities and imported intermediate input intensity.
  - Step 2: Use input-output tables to determine changes in composition of import demand resulting from shifts in export structure.
  - Data: Imports at the six-digit level for 162 countries from UN Comtrade.
  - Assumptions: Exchange rate changes assumed exogenous and analysis abstracts from other macroeconomic responses.
  - Elasticities: Demand elasticity at HS six-digit; substitution elasticity at HS two-digit.
- Advantages and limitations:
  - Advantages: avoids aggregation bias of CGE models; allows high product detail and transparent assumptions; flexible to adjust parameters and account for global supply chains.
  - Limitations: models each product as a separate market in isolation; inter- and intrasectoral linkages and economy-wide impacts are not fully captured.

### Simulation design and key qualitative results
- Simulated policy shocks (baseline 2008 trade):
  - China: 10 percent increase in relative prices (real appreciation).
  - United States: 10 percent decline in relative prices (real depreciation).
  - For illustration: 10 percent relative price increase in the euro area and 10 percent decline in Japan.
- Aggregate simulated impacts (high-level qualitative results):
  - A 10 percent depreciation for the United States would result in a 14 percent expansion in exports and a 7 percent contraction in imports; together these translate into a 40 percent improvement in the trade balance and roughly a halving of the U.S. current account deficit-to-GDP ratio.
  - A 10 percent real exchange appreciation in China would lead to a 50 percent reduction in its merchandise trade surplus.
  - Downstream position in a supply chain cushions the impact of relative price changes on exports and imports (China’s downstream position leads to smaller export response and relatively small import growth).
  - Japan’s upstream position and strength in consumer discretionary goods (vehicles and transport equipment) with low foreign content and high price sensitivity drive a larger impact of a 10 percent depreciation on Japanese exports.
- Pass-through and pricing-to-market effects:
  - Imperfect exchange rate pass-through and pricing-to-market mitigate adjustment in trade flows to exchange rate changes; accounting for less than perfect pass-through reduces exchange rate impacts on exports and imports significantly.
  - Empirical pass-through estimates cited: about 0.6 in the short run and 0.75 in the long run (Campa and Goldberg, 2005).
  - U.S. import market pass-through estimates noted: 0.25 in the short run and 0.4 in the long run.
  - Imperfect pass-through implies a larger nominal exchange rate change is needed to generate a given shift in international relative prices.
- Adjustment dynamics:
  - Adjustment in trade flows is gradual due to high fixed costs in production and trade relationships.
  - Estimated timing: about half of the long-run adjustment in trade balances would materialize within the first 2 years, and 80 percent within 6 years.

### Sectoral effects
- China:
  - An appreciation results in an increase in the share of machinery and electronics (high-technology) in overall exports and a decline in textiles (low-technology).
  - This reflects limited price sensitivity and larger contribution of imported intermediate inputs in high-technology goods.
  - Appreciation supports upgrading of Chinese exports in technology content and reduces reliance on low-skill manufacturing.
- Euro area:
  - Response to appreciation is more muted, reflecting lower contribution of FVA in high-technology exports.
- Japan and United States:
  - A depreciation results in important shifts in the share of medium-high-technology exports, largely driven by the auto sector.
  - Medium-high-technology exports are more sensitive to relative price changes due to higher domestic value added (DVA) and consumer discretionary character.

*Source: IMF staff analysis as presented in Box 6 (continued) of the chapter.*

### Box 7. Impact of Exchange Rate Changes and Trade Flows—A Historical Perspective

### Box 7. Impact of Exchange Rate Changes and Trade Flows—A Historical Perspective

### Method and key modeling assumptions
- A dynamically adjusted REER (DAREER) is used to account for the gradual realization of the impact on trade flows of changes in the real exchange rate.
- Rationale for gradual response:
  - Export relationships are costly to establish and production facilities are hard to redeploy in the short run.
  - In the case of an appreciation, exporting firms may initially attempt to maintain market share at the cost of profits, or await an offsetting exchange rate movement.
- A simple autoregressive model traces the dynamic adjustment of trade flows to exchange rate shifts, based on the relationship between short-run and long-run elasticities.
- Following Goldstein and Khan (1985) and Senhadji and Montenegro (1999), the ratio of long-run to short-run impact is in the range of 2 to 5.
- The analysis uses a midpoint ratio of 3 as the key parameter determining the speed of adjustment.
  - Implication: a third of the impact of 10 percent change in the REER would manifest in the first year of the shock, with the remaining impact (6.5 percent) unfolding asymptotically.
- The DAREER is constructed as a weighted average of realized REER shocks, with weights obtained from the autoregressive specification and more recent shocks given higher weights.
- Note: Chart assumes a ratio of long-run to short-run pass-through of 3 in a first-order autoregressive model.

### Properties of the DAREER and historical patterns
- The DAREER has historically been less volatile compared to the unadjusted REER, given that exchange rate fluctuations in proximate years often offset each other.
- For the United States (focus of exposition):
  - Swings of 10 percent or more in the DAREER were relatively infrequent.
  - The DAREER exhibited only two long waves of appreciation and depreciation since the 1980s, with attendant worsening and improvement in trade and current account balances.
- Historical analysis confirms the negative relationship between external balances and movements in the DAREER.

### Historical evidence and comparison with simulations (Box Table 7.1)
- Peak-to-trough analysis is based on 2-year averages because the DAREER for the United States moved only gradually.
- Empirical regularity:
  - On average, the trade balance improved (deteriorated) by 0.17 percent of GDP for every percentage point depreciation (appreciation) of the DAREER.
  - This is close to simulation results suggesting a 1.4 percentage point of GDP improvement in the trade balance in the United States in response to a 10 percent real depreciation (assuming partial pass-through).
- Selected figures reported in Box Table 7.1 (historical episodes and simulated scenario):
  - Change in dynamically adjusted REER (percent): 9.7–14.6; 10.9–7.7; –10.0
  - Current account adjustment (percent of GDP): –2.7; 3.0; –2.4; 1.9; 1.4 (simulated)
  - Ratio: CA change/DAREER change: –0.3–0.2–0.2–0.3–0.2–0.1
  - Trade balance adjustment (percent of GDP): –1.8; 1.9; –1.9; 1.5; 1.4 (simulated)
  - Ratio: TB change/DAREER change: –0.2–0.1–0.2–0.2–0.2–0.1
- Note: The analysis uses current account and trade balance adjustments resulting under the assumption of imperfect exchange rate pass-through to ensure consistency, since changes in the DAREER are inherently exchange rate changes (derived from the REER), not changes in relative prices in destination markets.

### Historical time-series behavior (United States)
- DAREER (1982 = 100) and external balances:
  - The graphical series show DAREER movements over 1982–2008 and the contemporaneous Current account (% of GDP) and Trade balance (% of GDP) on the right-hand side.
  - The historical response of external balances to changes in the DAREER is closely aligned with the simulation results.

### Summary findings
- The simulation results are broadly consistent with responses observed during historical episodes of exchange rate changes.
- A pass-through calibration with a long-run to short-run ratio of 3 produces realistic timing: about one-third of a 10 percent REER shock occurs in year 1, remainder accumulates (6.5 percent) over time.
- Historical peak-to-trough evidence for the United States implies modest but economically meaningful adjustments in current account and trade balances in response to large DAREER shifts; estimated elasticities (trade balance response per percentage point DAREER change) are close to simulated values.

*Sources: IMF, World Economic Outlook database, INS, and staff estimates.*

### Conclusion and Policy Implicati ons

### Conclusion and Policy Implicati ons

### Exchange rate effects on trade and supply chains
- Exports of the three advanced economies—and in particular Japan—are significantly more sensitive to relative price changes given that these countries are located upstream in the production process.
- Trade with supply chain partners is generally more resilient to exchange rate changes and rebalancing takes place predominantly outside the supply chain.
- Imports from supply chain partners upstream in the production process also tend to increase less or even fall in response to an exchange rate appreciation in the simulation country; this is especially the case in China, a downstream country in the production process.
- Real exchange rate shifts of the magnitude considered would not result in a substantial reorganization of trading networks and production chains.
- The magnitude of the trade response to exchange rate shifts differs by sector but the overall structure of export and import baskets remains broadly unchanged in the countries under consideration.
- Subsectoral asymmetries to exchange rate shifts are not large enough to alter sectoral export shares significantly; export structures are path-dependent, reflecting long cumulative processes of learning, agglomeration, institution building, and business culture.
- Exchange rate appreciation may lead to an increase in a country’s share of high-technology exports and may induce intraproduct quality upgrading; high quality goods are less sensitive to price shocks, enabling exporting firms to better withstand competitive pressures from relative price shifts.
- In China and other EMEs with potential to appreciate, appreciation-driven effects may lead to increasing convergence in both product types exported and quality levels from currently disparate values.

### Resilience, disruptions, and implications of supply chain integration
- The growing importance of global supply chains increases the international transmission of shocks, including policy-induced ones.
- Compared to Europe or North America, global supply chains in Asia are more integrated regionally and their export structure is more intertwined, making them more vulnerable to country- or product-specific disruptions.
- Protecting the free flow of inputs as well as outputs should be a top priority.
  - Potential avenues include binding the region’s unilateral tariff cuts in the WTO by concluding Doha, or including all the key players in regional FTAs such as the TPP.
  - Excluding a key player such as China from regional FTAs could create bilateral tensions and potentially undermine the free flow of goods underpinning the Asian supply chain.
- The recent earthquake in Japan tests supply chain resilience:
  - Substitution away from Japanese exporters may be difficult in the short term given Japan’s dominant market position in key sophisticated intermediate inputs and possible patent-related constraints.
  - A prolonged disruption and rundown of inventories may force firms to replace Japanese exports from other sources.
  - A rethinking of the “just-in-time” production model may result in a reorientation of production and sourcing networks in global supply chains.

### Policy recommendations to increase resilience and facilitate upgrading
- Create an environment enabling firms to undertake quality upgrading of products to better absorb international price shocks.
- Provide a reliable macroeconomic environment and aim to lower:
  - Costs of doing business; and
  - Costs of establishing trade relationships.
- Enabling firms to respond to unfavorable exchange rate movements via quality upgrading is identified as the most promising strategy when sectors face symmetric relative price shocks.

### Appendix 1 — A methodology for assessing systemic trade interconnectedness (overview)
- Purpose: assess global trade channel spillovers by defining “systemic” trade sectors and identifying jurisdictions hosting them, complementing financial interconnectedness analysis.
- Data source: IMF Direction of Trade Statistics (DOTS) database; trade in this analysis includes goods/merchandise but excludes services.
- Two-stage approach:
  - First stage: jurisdictions ranked based on trade size and interconnectedness indicators.
    - Size indicators (nominal U.S. dollars): (i) total exports (X); (ii) total imports (M); (iii) total turnover (X + M); and (iv) total turnover relative to nominal GDP.
    - Size ranking: jurisdictions ranked in each of the four indicators separately and the median rank of the four indicators taken as the single ranking for trade size.
    - Interconnectedness indicators: network analysis using a materiality threshold that excludes trade relationships representing less than 0.1 percent of a jurisdiction’s GDP; Aij is total turnover between jurisdiction i and jurisdiction j; Nij = 1 if Aij > 0, and 0 otherwise.
    - Four centrality measures used (each jurisdiction ranked in each measure and median rank taken as single interconnectedness ranking):
      1. “In-degree” = ∑j Nji
      2. “Closeness” = inverse of average distance ∑jδij/(n – 1)
      3. “Betweenness” = (∑j≠i∑k≠igik(i)/gjk)/(n – 1)(n – 2)
      4. “Prestige” (eigenvector centrality): vi = ∑j Rji vj; v = R′v; solution is eigenvector associated with the unit eigenvalue
    - Note: because both exports and imports are considered, the network is “undirected”; equal weights across the four measures make the network “unweighted” with binary values (0, 1). 
  - Second stage: combine rankings of size and interconnectedness into a composite index of trade systemic importance.
    - A weighted average “baseline” index is calculated to allow analysis of the relative significance of size and interconnectedness in systemic importance.
    - Sensitivity analysis: tested weight combinations 0.8/0.2, 0.7/0.3, 0.6/0.4, and 0.5/0.5 (size/interconnectedness); while weight changes affect some individual country ratings at the margin, they do not introduce significant changes in the listing of jurisdictions in the upper echelons of the ranking.

*Prepared by Luca Errico and Alexander Massara (Statistics Department); Appendix references: 34, 35, 36, 37, 38, 39.*

### Appendix 2: Measures Used to Characterize Global Supply Chains

### Appendix 2: Measures Used to Characterize Global Supply Chains

### Definition and Calculation of Foreign Value Added (FVA) / Vertical Specialization (VS)
- FVA share in exports = u·A_M·L·E / E_k
  - u is a row vector of ones.
  - A_M is the imported inputs coefficients matrix.
  - L is the Leontief matrix.
  - E is a column vector of gross exports in each sector.
  - E_k is the total exports.
- Interpretation of computation steps:
  - Multiply the column vector of gross exports E by the Leontief matrix (I–A_D)–1, where I is the identity matrix and A_D is the domestic input coefficient matrix, to compute gross output needed to produce those exports.
  - Multiply gross output by import input coefficients to compute total foreign inputs contained in gross exports.
  - Divide total foreign inputs by total exports to obtain the FVA content share of gross exports.
- Imported intermediates include:
  - Imported intermediates used directly in output.
  - Intermediates used to produce domestic intermediate inputs that are then used in output.
  - Inputs from agriculture, services, and mining sectors are included even when focus is on manufacturing exports.
- FVA shares are calculated under the assumption that the same ratio of intermediates to output holds for exports.

### Data Sources, Coverage, and Method for Bilateral Decomposition
- Primary input-output data source: STAN/OECD input-output tables (as in Hummels, Ishii, and Yi (2001)).
  - Input-output data are available for 36 emerging and advanced countries.
  - FVA shares in gross exports are computed for 36 countries (see Table A2.1).
  - FVA contents in billion U.S. dollars (not shown in Table A2.1) are aggregated to compute the VS share of world exports shown in Table 1 in the main text.
- To further decompose foreign value added by source country:
  - Following Koopman and others (2010), bilateral sectoral trade data from COMTRADE are supplemented for Japan, China, the United States, and Germany.
  - Note: There are no data on bilateral trade in services; foreign services are not decomposed into their countries of origin but are included as a separate imported input.

### Key Statistics from Tables (preserving reported values exactly)
- Selected FVA share in gross exports (Table A2.1, Percent of gross exports):
  - AUS: 1995 = 13.9, 2005 = 14.1
  - CHN: 1995 = 15.5, 2005 = 27.4
  - DEU: 1995 = 20.8, 2005 = 27.8
  - USA: 1995 = 9.5, 2005 = 12.3
  - IRL: 1995 = 45.5, 2005 = 51.2
  - HUN: 1995 = 47.7, 2005 = 56.1
  - TWN: 1995 = 34.9, 2005 = 48.5
- Selected FVA content in gross exports by country of origin (Table A2.2, Billions of U.S. dollars):
  - China 2005:
    - FVA = 232.50
    - Service = 43.05
    - DVA = 615.23
  - Japan 2005:
    - FVA = 100.98
    - Service = 17.73
    - DVA = 563.09
  - USA 2005:
    - FVA = 136.38
    - Service = 28.09
    - DVA = 968.55
  - Germany 2005:
    - FVA = 310.00
    - Service = 58.15
    - DVA = 805.57
- Selected FVA share in gross exports by country of origin (Table A2.3, Percent of gross exports):
  - China 2005:
    - FVA = 27.4
    - Service = 5.1
    - DVA = 72.6
  - Japan 2005:
    - FVA = 15.2
    - Service = 2.7
    - DVA = 84.8
  - USA 2005:
    - FVA = 12.3
    - Service = 2.5
    - DVA = 87.7
  - Germany 2005:
    - FVA = 27.8
    - Service = 5.2
    - DVA = 72.2

### Notes on Sectoral and Regional Aggregations
- Sector technology classification used in tables:
  - LT = low technology
  - MLT = medium-low technology
  - MHT = medium-high technology
  - HT = high technology
- Regional and grouping abbreviations:
  - EU27 refers to the European Union 27.
  - OEA = other east Asia (Hong Kong SAR, India, Indonesia, Korea, Malaysia, Philippines, Singapore, Taiwan Province of China).
  - “Rest of world” and “Service” used as aggregated origins in the decomposition tables.
- Gross exports (not shown in the tables) are equal to FVA + DVA.

*Source: IMF staff estimates using OECD Input-Output Tables, UN Comtrade and OECD STAN data.*

### Appendix 5: Data and Modeling Strategy

### Appendix 5: Data and Modeling Strategy

### Objective and data
- Objective: quantify at a high level of product detail the implications of sectoral and supply chain linkages on the trade impact of relative price changes.
- Data: imports by trading partner at the HS2002 six-digit level sourced from UN Comtrade.
- Year chosen for analysis: 2008 (rationale: (i) more countries reported data for 2008 at this level of disaggregation than for 2009; (ii) trade flow composition presumably less distorted by the crisis-induced collapse in trade).

### Modeling approach (two stages) — overview
- Stage 1: partial equilibrium model determines change in consumer demand for imports in every import market.
- Stage 2: input-output tables (discussed in main text) adjust imports in response to the trade-induced change in aggregate demand.
- Key stated advantages:
  - (i) avoids aggregation bias implicit in CGE models using aggregate trade flows;
  - (ii) simple and transparent assumptions;
  - (iii) illustrates changing trade patterns at a high level of product detail enabling quantification of sectoral and supply chain linkages (results produced at the HS six-digit level and can be aggregated to compute RCA, export similarity (ESI), and technology content metrics).

### Limitations and scope
- Each product is modeled as a separate market and in isolation from other markets.
- Inter- and intrasectoral linkages or economy-wide impacts of changes in relative prices are not fully captured.
- Model primarily useful for analysis of sectoral and supply chain linkages; limitations should be kept in mind for aggregate-level predictions.

### First stage: partial equilibrium model of import demand — mechanics and assumptions
- Export price response to a real exchange rate shift is adjusted for sectoral variation in foreign content: export prices in a given sector change by the share of domestic content in the export value multiplied by the exchange rate shift.
  - Example: a 10 percent exchange rate depreciation leads to a 5 percent fall in export prices in a sector with 50 percent domestic content in exports, and by 8 percent in a sector with 80 percent domestic content.
- Consumer choice framework: representative consumer with Armington (1969)-style preferences chooses imported goods in two steps:
  - (1) substitution between different exporters’ national varieties following relative price changes;
  - (2) change in overall demand for the good as a result of the change in the average price of the product.
- Ex ante price of all product varieties normalized to unity; if percentage change in relative prices is x, consumer price of each variety becomes 1 + x.
- Six core assumptions (as stated):
  - First: sector-level elasticities determine magnitude of demand response of trade flows to relative price changes.
  - Second: standard Armington (1969) assumption of imperfect substitutability between imports from different trading partners (within each product category).
  - Third: a change in relative prices is defined as a change in relative prices facing the consumer in each importing economy.
  - Fourth: no direct substitution between different products is allowed (each product modeled as a separate market and in isolation).
  - Fifth: parameterization aimed at computing long-term impacts of relative price changes.
  - Sixth: given partial equilibrium nature, inter- and intrasectoral linkages (e.g., factor reallocation) or economy-wide impacts cannot be considered.
- Technical implication: since demand responses are based on elasticities, market entry by new exporters as a result of price changes is not modeled (zero trade flows remain unchanged at zero).
- Elasticities used:
  - Literature range suggested: –2 to –3 (cited Crozet and Koenig (2010) and Obstfeld and Rogoff (2005)).
  - The authors use Broda and Weinstein (2006) and Broda, Greenfield, and Weinstein (2006) elasticities scaled to a mean of 2.25 as attained in Crozet and Koenig (2010).
  - This scaling "results in an import-weighted mean elasticity of 2.4."
  - Country-specific import demand elasticities: Kee, Nicita, and Olarreaga (2008) elasticities are used but scaled to a mean of –1 which results in an import weighted mean of –0.79.
- Data treatment:
  - Outliers removed by capping elasticities at value equal to the mean plus 2 standard deviations.
  - Missing observations filled using product elasticities at higher aggregation levels, at the country level, where available.
  - For substitution elasticities, authors prefer elasticities estimated at SITC three-digit level to minimize upward bias from summing high-disaggregation changes.

### Second stage: adjusting imports for trade-induced change in aggregate demand
- Rationale: changes in exports affect total value added and aggregate demand; impacts on imports of intermediates and final goods must be accounted for beyond the first-stage prediction.
- Method:
  - Use input-output tables to compute fall in value added consistent with first-stage change in exports.
  - Use input-output tables to determine change in imports of intermediates and final goods (by sector) resulting from falling/rising aggregate demand.
  - Input-output tables distinguish two-digit ISIC sectors and intermediate vs final goods; sectoral impacts split across subsectors according to market share where trade data are more disaggregated.
- Data and parameter notes:
  - Imported inputs coefficients matrix denoted A_M.
  - Marginal propensity to imports by sector denoted mpm.
  - Value added row vector denoted v and Leontief matrix denoted L.

### Appendix 6: feeding simulation results into the current account — formulas
- Change in GDP from change in exports:
  - dY = v·L·dE
    - where dY is the change in GDP, v is a row vector of value added in each sector, L is the Leontief matrix, and dE is a column vector of changes in exports in each sector.
- Change in imports of intermediate inputs:
  - dtntM = A_M · L · dE
    - where dtntM is a column vector of the change in imports of intermediate inputs by sector and A_M is the imported inputs coefficients matrix.
- Change in imports of final goods:
  - dfinM = mpm · dY
    - where dfinM is a column vector of the change in imports of final goods by sector and mpm is a column vector of marginal propensity to imports by sector.
- The overall effect of the simulation results is summarized in Section A in Chapter 3.

*Source: Appendix 5: Data and Modeling Strategy, _dp1201*

### References

### _dp1201 - References

### References cited
- Tanaka, Kiyoyasu, 2009, “Vertical Foreign Direct Investment: Evidence from Japanese and U.S. Multinationals Enterprises,” Institute of Economic Research, Hitsobashi University, Global COE Hi-Stat Discussion Paper Series 046 (Kunitachi City, Japan: Institute of Economic Research).
- Thorbecke, Willem, 2011, “The Effect of Exchange Rate Changes on Trade in East Asia,” ADBI Working Papers 263 (Manila: Asian Development Bank Institute).
- ———, and Gordon Smith, 2010, “How Would an Appreciation of the Renminbi and Other East Asian Currencies Affect Chinese Exports,” Review of International Economics, Vol. 18, No. 1, pp. 95–108.
- Wakasugi, Ryuhei, Banri Ito, and Eiichi Tomiura, 2008, “Offshoring and Trade in East Asia: A Statistical Analysis,” Asian Economic Papers, Vol. 7, pp. 101–124.
- Wang, Zhi, and Shang-Jin Wei, 2008, “What Accounts for the Rising Sophistication of China’s Exports?” NBER Working Paper 13771 (Cambridge, MA: National Bureau of Economic Research).
- Wang, Zhi, William Powers, and Shang-Jin Wei, 2009, “Value Chains in East Asian Production Networks—An International Input-Output Model Based Analysis,” Office of Economics Working Paper 2009-10-C (Washington, DC: U.S. International Trade Commission).
- World Trade Organization, 2007, World Trade Report (Geneva).
- Yi, Kei-Mu, 2003, “Can Vertical Specialization Explain the Growth of the World Trade?” Journal of Political Economy, Vol. 111, No. 1, pp. 52–102.
- Changing Patterns of Global Trade

*Source: _dp1201 - References*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/dp/2012/_dp1201.pdf_