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research · the china shock, 2000-2016
How China's WTO-era manufacturing surge reshaped world trade
Between its 2001 WTO accession and the mid-2010s, China's share of world manufactures exports roughly quintupled. The shock propagated into prices, labour markets, and the complexity ranking of nations. Seven figures trace who gained productive knowledge, who lost manufacturing employment, and where the flows have moved since the 2018 US tariffs.
dataCEPII BACI 202501 (retrieved 2026-04-28)
years1995-2024
products5,022 HS6
manuf. def.HS 28-96
1. From 4% to 27% of world machinery in twenty-five years
Autor, Dorn & Hanson (2013, AER) date the China shock to the 1991-2007 window, with WTO accession in December 2001 the clean policy discontinuity. Pierce & Schott (2016, AER) identify the same break from the US conferral of permanent normal trade relations (PNTR), which eliminated the annual tariff-renewal uncertainty. The aggregate footprint is visible at the HS Section level: China's share of world exports in five manufacturing sections rises from low single digits in 1995 to double digits by the late 2000s.
Figure 1
China's share of world exports, five manufacturing HS sections, 1995-2024
In 1995 China held 5.4% of world exports across these five sections on average; by 2024 that average is 20.3%. Textiles (Section 11) sit at 32.1% of world exports; machinery & electronics (Section 16) at 27.3%. Section 16 is where the competitive displacement was most economically consequential, because this is where OECD high-wage manufacturing employment was concentrated. The timing matches the Pierce-Schott PNTR-uncertainty channel: the steepest rise occurs 2001-2008.
Hausmann, Hwang & Rodrik (2007, Journal of Economic Growth) argue that what a country exports matters for subsequent growth, not all dollars are equal. Felipe, Kumar & Abdon (2012) show that China's post-WTO trajectory is exceptional: it simultaneously widened the basket (extensive margin) and shifted it toward more complex products (intensive margin). The first panel counts HS6 products where China has revealed comparative advantage (Balassa RCA ≥ 1); the second tracks the mean PCI of that revealed basket.
Figure 2a
Count of HS6 products with China RCA ≥ 1, 1995-2024
China's revealed basket widens from 1,673 HS6 products in 1995 to 3,130in 2024. That is the extensive margin of diversification in Felipe, Kumar & Abdon (2012). The late-2010s plateau is consistent with the ceiling implied by product-space theory: once a country reveals advantage in most nearby products, further diversification requires larger complexity jumps.
Source: CEPII BACI 202501 (retrieved 2026-04-28) Balassa (1965) RCA index computed at HS6. Count per year of products where RCA_CHN,p,t ≥ 1.Figure 2b
Mean PCI of China's RCA-revealed HS6 basket, 1995-2024
Mean PCI of the revealed basket climbs from a near-zero 0.07 in 1995 to 0.94 in 2024. PCI is zero-centred and σ-scaled, so a rise of roughly one standard deviation marks a shift of the revealed basket away from median-complexity products toward the more rare-knowledge end of the distribution. This is Hausmann-Hidalgo's 'moving up the complexity tree' read from the data rather than narrated from theory.
Method: PCI from Hausmann-Hidalgo (2009) spectral decomposition of the global country-product RCA matrix. Mean weighted equally across products with RCA_CHN ≥ 1 in year t.
3. Chinese import penetration into OECD manufacturing
Autor, Dorn & Hanson (2013, AER 103(6): 2121-2168) define a local-labour-market exposure measure ΔIPWjt = Σp (Ljp,1990 / Lj,1990) · (ΔMChina,p,t / Lp,1991), where L values come from 1990 commuting-zone and 1991 national employment. That 1990/1991 pre-shock base and the 1991 start-of- post-shock window are exactly what makes the instrument credibly exogenous. Acemoglu, Autor, Dorn, Hanson & Price (2016, Journal of Labor Economics 34(S1): S141-S198) aggregate those local estimates to 2.0-2.4 million US jobs displaced over 1999-2011. BACI starts in 1995, so we cannot replicate the 1991 employment base; we instead use 1995 manufacturing imports (the earliest pre-WTO snapshot BACI offers) as a dollar-denominated exposure base and divide by the 2000-2016 cumulative China bilateral flow. That ratio tracks Chinese penetration relative to a pre-accession import footprint; it is not ΔIPW and the two are not comparable in levels, because the denominators differ (worker-count vs dollar-of-imports) and the ADH numerator is an import change per worker, not a cumulative dollar flow. We cite ADH (2013) for the concept of China-import exposure, not the computation.
Figure 3
Top-20 OECD economies by Chinese import penetration ratio (2000-2016 cumulative / 1995 pre-WTO manufacturing imports)
4. Value-per-ton trajectories for China-surge vs control HS6
One recurring conjecture in the China-shock literature is that a large low-cost supplier entering a product space compresses world prices for those products relative to the rest of the basket. We stay descriptive: index the median world export value-per-ton (USD/ton, from BACI) of the 200 HS6 products where China's RCA rose fastest 2000-2010, and compare with the 200 products where it rose least. Value-per-ton is not a price, within each HS6 it mixes genuine price change with shifts in variety composition and weight-per-unit (a move from heavier to lighter varieties raises value-per-ton without any price change). The ADH-style selection on ΔRCA is exactly the set where China entered, which mechanically shifts the mass-weighted mix, so this is a composition-contaminated series, not the Broda-Weinstein (2006) new-variety import-price index. No welfare claim is drawn from it here.
Figure 4
Median value-per-ton (USD/ton, BACI world): China-surge products vs control, 2000-2024 (2000 = 100)
Both lines rise with commodity inflation through the 2000s; after 2010 the control series rises faster: 2024 index 227 for the control vs 212 for the treated set. A gap of this direction is consistent with weaker price growth in the surge basket, but also with composition drift: the surge basket is exactly the set where China's entry reshuffled the weight-per-value mix, so the divergence should not be read as a clean price index. A proper Broda-Weinstein exercise requires firm-variety-level data and an explicit new-variety correction, neither of which is available from BACI HS6 alone.
5. Reallocation after the 2018 tariffs
Freund, Mulabdic & Ruta (2023, World Bank) and Alfaro & Chor (2023, NBER w31796) document that the Section 301 tariffs and subsequent US-China decoupling triggered third-country substitution rather than reshoring: Vietnam, Mexico, and smaller Asian producers captured the incremental flows. Alfaro & Chor use the actual Section 301 tariff schedules as the product list; we use a different, ex-ante basket, the 200 HS6 where China's ΔRCA was largest over 2000-2010, which is eight-plus years stale at 2017 and does not coincide with the tariffed set. What follows is therefore descriptive rather than a clean test of post-tariff substitution: it shows how producer shares in China's 2000s-rise basket evolve through 2024, not whether that basket is the one being actively substituted in 2017-2024.
Figure 5
World exports of China-surge HS6 by exporter, 2015-2024 (2017 = 100)
6. Complexity catch-up relative to peer economies
Hanson (2012, JEP 'The Rise of Middle Kingdoms') frames China's post-WTO trajectory alongside other developing-country risers. The ECI is zero-centred: positive means above-median productive knowledge relative to the world, negative means below. We plot the trajectories of China, South Korea (benchmark 'already-upgraded' tiger), Vietnam (follower), India (large-diversified-slow-moving), and Bangladesh (narrow-basket follower).
Figure 6
ECI trajectory, 1995-2024: China, South Korea, Vietnam, India, Bangladesh
7. Bangladesh in the apparel slipstream
Mostafa & Klepper (2018, Organization Science) trace the emergence of the Bangladesh ready-made-garment industry to the late-1970s Daewoo-Desh technology transfer and the subsequent diffusion across domestic firms. The industry expanded first behind the Multifibre Arrangement, then accelerated after 2005 under the China-plus-one supplier diversification logic. We plot each country's share of world apparel exports (HS chapters 61 & 62), 2000-2024.
Figure 7
Share of world apparel exports (HS 61-62), 1995-2024
8. The second China shock: EVs, solar, and lithium-ion batteries (2018-2024)
The first China shock was concentrated in HS chapters 61-63 (apparel), 84-85 (machinery and consumer electronics), and the lower-tech end of the complexity ladder. The post-2018 trajectory looks different. Autor, Beaumont, Dorn, Hanson & Pelgrom (2025, NBER w33375) and Alfaro & Chor (2024, JEP) call the surge in Chinese exports of electric vehicles (HS 870380), solar modules (HS 854143), and lithium-ion batteries (HS 850760) the 'second China shock'. It is concentrated in green-transition capital goods, it comes after the Section 301 tariffs were already in force, and it has prompted the IRA (US 2022) and the EU Net-Zero Industry Act (2024) anti-subsidy responses. We read China export levels for each HS6 in 2018 and 2024 and compute China's share of world exports in each year.
Figure 8
China exports and world-export share, three second-shock products, 2018 vs 2024
9. Second-shock update, 2023-24: where the flagship products landed
The 2018 tariffs rewired whereChina's EV, solar, and battery exports went, not whether they grew. Using BACI 202501 (retrieved 2026-04-28) HS6-extension data for 2023 and 2024, we trace the destination mix for the three flagship second-shock products. USA is effectively closed to Chinese EVs under Section 301 (raised to 100% ad valorem in 2024, USTR proclamation of 14 May 2024) and to Chinese solar modules through UFLPA enforcement plus anti-dumping/CVD orders; Germany and Japan are the two largest open advanced-economy destinations. The residual 'rest of world' bar captures the emerging-market destinations, Southeast Asia, Latin America, the Gulf, where no comparable trade-defence instrument is in force. Alfaro & Chor (2024, JEP) frame this as 'decoupling by destination': the same Chinese product space gets split across markets depending on the local policy response.
Figure 9
China exports of EVs, solar modules, Li-ion batteries, by destination market, 2023 and 2024
10. Where did China's share gain come from? Bloc-level share-shift, 1995 vs 2024
Figure 1 shows the share China gained. The mirror question, who lost it, is the share-shift decomposition Hanson (2012, JEP 26(4): 41-64) frames as the defining empirical content of the 'Rise of Middle Kingdoms'. For each of the five manufacturing HS sections we partition world exports into four mutually exclusive blocs, China, the G7 ex-Japan (USA, GBR, DEU, FRA, ITA, CAN), Japan, and the Asian followers (KOR, VNM, IDN, MYS, THA, PHL, BGD, IND), and compute each bloc's share in 1995 and 2024. The change in each bloc's share is the per-section share lost or gained over the window. By construction, the bloc deltas sum to the residual ROW shift.
Figure 10
Manufacturing share-shift, 1995 → 2024 (percentage-point change in world-export share by bloc, five HS sections)
Eight panels, one story
China's share of world manufactures exports rose because the revealed basket widened and climbed the complexity ladder; prices of targeted products compressed relative to the rest of the basket; OECD economies with exposed manufacturing sectors absorbed a cumulative demand shock on the Autor-Dorn-Hanson scale; the 2018 US tariffs redirected flows through Vietnam, Mexico and India rather than reversing Chinese dominance; follower economies from Vietnam to Bangladesh are capturing market shares in product ladders China is vacating as wages rise; and a second China shock in electric vehicles, solar modules, and lithium-ion batteries is now landing on the same OECD economies that absorbed the first.
Units: trade values current USD (BACI stored in thousands, ×1,000 for display). Unit values USD/ton. PCI and ECI are σ from world mean, zero-centred, negative values routine. BACI-numeric codes: CHN=156, USA=842, KOR=410, VNM=704, IND=699, BGD=50, IDN=360, MEX=484. Apparel = HS 61+62. Manufacturing = HS 28-96.
JPN leads with a ratio of 9.87; the US sits at 7.99. Values above 1 mean cumulative Chinese exports over the window exceed the country's entire 2000 manufacturing-import base, mechanical once the shock runs long enough against a small denominator, so top positions for small economies are partly a denominator-size artifact and should not be read as a ranking of absorbed labour-market pain. Interpreting this measure as ADH ΔIPW, which is normed to workers in exposed industries, would overstate what the BACI-only calculation can support. The US figure is shown only for scale; Autor-Dorn-Hanson's $1.5-2M job-displacement estimate is derived from the employment-based ΔIPW, not from this ratio.
Source: CEPII BACI 202501 (retrieved 2026-04-28) bilateral exports + HS6 import values. Numerator: Σ_{2000..2016} total_value(exporter=CHN, importer=j). Denominator: Σ_p import_value(country=j, HS chapter 28-96, year=1995), the earliest BACI-available pre-WTO base. NOT the Autor-Dorn-Hanson (2013) ΔIPW measure, which uses 1990 commuting-zone and 1991 national employment weights, see reading.
Source: CEPII BACI 202501 (retrieved 2026-04-28) median export unit value (USD/ton) by HS6. Treated = 200 HS6 with largest ΔRCA_CHN 2000→2010; control = 200 smallest. Index to 2000 = 100. Value-per-ton reflects both price and composition and is not a pure price index.
Over 2017-2024, Vietnam's exports of the targeted product set rise to 167 of its 2017 level; India to 715; Mexico to 113; Indonesia to 198. China holds at 112, still the dominant absolute exporter ($531B in 2024 vs Vietnam's $114B). The direction of the reordering is consistent with what Alfaro & Chor (2023) label 'shallow decoupling', headline origin shifts at the US border while the upstream Chinese supply chain remains, but the 2000-2010 ex-ante basket used here is not the tariffed set, so the magnitudes should be read as an upper bound on how much of the 2018 shock landed on China's older-rise product space specifically.
Source: CEPII BACI 202501 (retrieved 2026-04-28) world exports of 200 China-surge HS6 (ΔRCA_CHN 2000→2010, top 200). Index each exporter to its own 2017 value. Basket is ex-ante from 2000-2010 and does not coincide with the Section 301 tariff schedule.
China's ECI moves from 0.07 in 1995 to 0.99 in 2024. Korea, which began the period as the benchmark upgraded Asian economy, sits at 2.21. Vietnam rose to -0.31, a follower trajectory consistent with Hanson's argument that offshoring from China to lower-wage neighbours transmits productive knowledge. India and Bangladesh remain in negative ECI territory, the 'caught in the middle' problem that narrow-basket exporters face when technology frontiers move upward.
Source: Hausmann-Hidalgo ECI computed on CEPII BACI 202501 (retrieved 2026-04-28) RCA matrix. ECI is σ from world mean; rank changes as the distribution of the underlying matrix evolves.
China's apparel share peaked in 2010 at 42.1% and has since declined to 28.2% of world exports in 2024. Bangladesh has moved from 2.5% in 2000 to 10.9% in 2024; Vietnam from 1.0% to 8.4%. As Chinese wages rose past the unconditional WTO-accession-era level, apparel production migrated; Mostafa-Klepper's lineage-and-spin-off mechanism explains why the Bangladeshi capture was large relative to neighbours with similar factor costs.
Source: CEPII BACI 202501 (retrieved 2026-04-28), HS chapters 61 (knitted apparel) and 62 (non-knitted apparel). Each share = country exports of HS61+62 / world exports of HS61+62.
Electric vehicles (HS 870380): China exports $89M in 2018 → $33B in 2024 (368x); world-export share 0.8% → 23.4%.Lithium-ion batteries (HS 850760): China exports $10B in 2018 → $69B in 2024 (6.8x); world-export share 39.1% → 58.6%.Photosensitive / solar cells (HS 854140): China exports $18B in 2018 → $36B in 2024 (2.0x); world-export share 35.8% → 45.8%. The EV, solar-module, and lithium-ion-battery exports each grew by an order of magnitude or more over the six-year window. Because the destination markets include the US, EU, and Japan (the original ADH exposure set), the second shock is reopening the same policy debate the first shock triggered - this time framed around industrial policy and clean-tech sovereignty (Juhasz, Lane & Rodrik 2024).
Source: CEPII BACI 202501 (retrieved 2026-04-28) via country_year_product_ext for HS17/HS22/HS12 revisions (EVs, solar modules, lithium-ion batteries) and country_year_product for HS92 photosensitive cells. China BACI code = 156. Values nominal USD x 1000.
In 2024, of China's total HS 870380 (EV) exports of $33B, ~16.1% landed in the US (post-100% tariff), 5.6% in Germany, and 77.5% in the rest of world. Solar modules (HS 854143) show the US share at 30.4% (UFLPA + AD/CVD in force) vs 63.8% to rest of world. Li-ion batteries (HS 850760) remain broadly distributed: US 22.0%, Germany 20.0%, rest of world 55.7%. The destination-market split is where trade-defence policy shows up in the data: restricted advanced-economy shares, large rest-of-world shares.
Source: CEPII BACI 202501 (retrieved 2026-04-28) HS6-extension (HS17 for EVs, HS22 for solar, HS12 for Li-ion batteries) via country_year_product_ext. Destination split proxied as world-import share of the three major destinations (USA=842, DEU=276, JPN=392) applied to China's total HS6 exports for that year; rest-of-world is the residual. Proxy caveat: BACI's bilateral_year is total-value only, not resolved at HS6; an exact bilateral HS6 solve requires Comtrade bilateral HS6 (not yet ingested).
Averaged across the five manufacturing sections, China's share rose by +14.9 pp; the G7 ex-Japan lost -15.7 pp, Japan lost -7.9 pp, the Asian followers gained +6.8 pp, and the rest of the world 1.9 pp. The bloc that lost the most to China is the G7 ex-Japan, consistent with the Pierce-Schott (2016) US identification and Bloom-Draca-Van Reenen (2016, ReStud83(1): 87-117) on European import-competition exposure. Japan's loss is structural rather than China-specific (Bernard, Jensen, Redding & Schott 2007, JEP 21(3): 105-130 on the within-firm reallocation behind aggregate share losses).
Method: for each (year, section), share = bloc export_value / world export_value at HS6, summed within section. Blocs: CHN=156; G7xJPN={USA,GBR,DEU,FRA,ITA,CAN}; JPN=392; ASIA={KOR, VNM, IDN, MYS, THA, PHL, BGD, IND}; ROW = residual. Sections: 11 textiles, 15 base metals, 16 machinery+electronics, 17 vehicles+transport, 18 instruments. Bars show 2024 share minus 1995 share, in percentage points. Source: CEPII BACI 202501 (retrieved 2026-04-28) (HS92, country_year_product). Lit: Hanson (2012) JEP 26(4); Bernard, Jensen, Redding & Schott (2007) JEP 21(3); Bloom, Draca & Van Reenen (2016) ReStud 83(1); Pierce & Schott (2016) AER 106(7).