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supply chain intelligence
If HS 854231 needs to come from a friendlier origin, where could it come from?
Given an importer (USA) and an HS6 product (electronic integrated circuits: processors and controllers, whether or not combined with memories, converters, logic circuits, amplifiers, c), the page ranks alternative suppliers on a composite friendshoring score that rewards capability and penalises cost, with a binary ally flag gating out comprehensively-sanctioned origins. World trade of this line in 2024 totalled $427.7B, of which roughly 0.0% came from countries flagged as hostile by the sanctions proxy described below.
HS6854231
revisionHS07
importerUSA
year2024
world trade$427.7B
hostile share0.0%
How the friendshoring score is built
The composite score decomposes a supplier into capability, political alignment, and landed cost, in the spirit of Grossman, Helpman & Sabal (2024, 'Resilience in Vertical Supply Chains') on sourcing under geopolitical risk, and of Goldberg & Reed (2023, Brookings Papers on Economic Activity) on the empirical geography of friendshoring. The 'China shock' evidence of Autor, Dorn & Hanson (2013, American Economic Review103(6)) motivates treating single-origin concentration as a first-order risk, not a residual. Farrell & Newman (2019, 'Weaponized Interdependence,' International Security44(1)) frames why the ally factor enters multiplicatively rather than as a soft penalty. Aiyar, Chen, Ebeke, Garcia-Saltos, Gudmundsson, Ilyina, Kangur, Kunaratskul, Rodríguez, Ruta, Schulze, Soderberg & Trevino (2023, 'Geoeconomic Fragmentation and the Future of Multilateralism,' IMF Staff Discussion Note SDN/2023/001) estimate that fragmentation into geopolitical blocs could cost the world economy between 0.2 and 7 per-cent of GDP, with low-income and small-open economies bearing the largest share, the macro ceiling for what this page prices at the HS6 level. Alfaro & Chor (2023, 'Global Supply Chains: The Looming 'Great Reallocation',' NBER WP 31661) show that US import reshuffling from China to Vietnam, Mexico and India is already tracking this bloc logic in the bilateral data, the direction the Scanner is built to help visualise.
friendshoring_score = capability × ally × ( 1 / cost )
capability = norm(RCA_i) × norm(world_export_share_i)
ally = 1 if supplier is NOT on any consolidated sanctions list
= 0 otherwise (crude hostility proxy)
cost = ( norm(unit_value_i) + 0.01 )
× ( norm(distance_to_importer_i) + 0.01 )
× ( 1 + applied_tariff_rate_i )
All factors are normalised to [0, 1] across the current supplier universe for this HS6 before combination, so the score is unit-free and rank-interpretable. BACI values are stored in thousands of USD and multiplied by 1,000 for display (CEPII BACI 202501 (retrieved 2026-04-28) convention). RCA is the Balassa (1965) index from the rca_matrix parquet.
Honest caveat on the ally factor. The ally score here is a VERY rough binary proxy. It flags supplier countries subject to comprehensive country-scope sanctions by OFAC, the EU, or the UN Security Council as of 2026-Q1 (IRN, PRK, CUB, SYR, RUS, BLR, MMR, VEN, AFG); every other origin receives ally = 1. This collapses a continuous, bilateral, and time-varying relationship into a binary. The canonical continuous alternative is the Bailey, Strezhnev & Voeten (2017, Journal of Conflict Resolution 61(2): 430-456) UN General Assembly ideal-point metric, which estimates each country-year's position on the liberal-order dimension from vote-by-vote roll-call data; bilateral affinity is then |θi(t) − θj(t)|. Aiyar et al. (2023) and the IMF bloc-mapping exercises build on exactly this series. Formal-alliance treaty membership (ATOP, Leeds, Ritter, Mitchell & Long 2002) is the binary complement.
Who are the friendly alternatives, ranked?
The top-20 non-dominant suppliers of HS 854231 in 2024, ranked by the composite score above. Bar colour encodes the ally flag: green for a friendly origin, amber for a flagged origin that survived the score despite ally = 0 (it should not: by construction ally = 0 zeroes the score; amber bars here serve as a visual audit that the filter is working).
Figure 1
Friendshoring score, top-20 alternative suppliers to USA, HS 854231, 2024
Are the cheap suppliers also capable, and also friendly?
A cost-quality frontier for HS 854231 in 2024: unit value (BACI value over quantity, USD per metric ton) against world export share. Bubble size scales with great-circle distance to USA (CEPII Gravity V202411). Bubble colour encodes the ally flag. The ideal friendshoring candidate sits in the upper-left quadrant, low unit cost, high share, small bubble, and is coloured green.
Figure 2
Cost-quality frontier: unit value vs. world share, HS 854231, 2024
How much dollar value could shift to friendly origins?
A first-order dollarisation of the shift opportunity. The first bar multiplies USA's total HS 854231 imports in 2024 by the world-export share of flagged origins, a BACI-mirror approximation, since partner-level HS6 bilateral flows are not loaded on this page. The second bar is the total HS 854231export value of friendly suppliers excluding the dominant origin: an upper bound on the supply that could, in principle, be redirected toward USA without new capacity.
Figure 3
Shift opportunity, USA HS 854231 imports from hostile origins vs. friendly spare capacity, 2024
Approximate imports from hostile origins: $0. Friendly-alternative HS6 export capacity (upper bound, excludes the dominant supplier): $327.0B. The ratio is a sanity check on feasibility: when friendly capacity dwarfs the at-risk import figure, diversification is a matter of contracting rather than greenfield investment; when it does not, the implication is reshoring or new capacity build, not just re-routing.
Sources: CEPII BACI 202501 (retrieved 2026-04-28) for import totals and friendly export capacity. Hostile-import figure uses the importer's total HS6 imports times the flagged suppliers' world-export share (approximation, exact BACI-mirror would need bilateral HS6 flows). Authors calcs.
By HS Section: dominant supplier vs. #1 friendly alternative
Rolled up across all HS6 lines in each of the 16 HS Sections present in the HS07 product catalogue, 2024. For each Section the table lists the largest exporter, whether that exporter is flagged by the sanctions proxy, and the highest-share alternative exporter that is NOT flagged (and is not the dominant supplier itself). Rows where the dominant origin is already friendly are the benign case; rows where the dominant is flagged and an alternative exists are the redirection candidates.
Figure 4
By-sector summary, dominant supplier and #1 friendly alternative, 2024
§
HS Section
Dominant supplier
Share
Flag
#1 friendly alt
Alt share
1
Live animals & animal products
NOR Norway
15.1%
friendly
CHL Chile
12.2%
2
Vegetable products
NLD Netherlands
37.9%
friendly
COL Colombia
14.5%
4
Prepared foodstuffs, beverages, tobacco
CHN China
26.3%
friendly
NLD Netherlands
8.0%
5
Mineral products
RUS Russian Federation
23.4%
hostile
BRA Brazil
Figure 4b
UN-vote-alignment bins x USA trade share, 2013-2017 vs. 2018-2023
Figure 4c
Allyshoring vs. nearshoring decomposition, USA trade share change 2013-2017 → 2018-2023
Each of USA's partners is classified on two axes: geography ('near' = below the median great-circle distance to USA, 'far' = above) and ideology ('ally' = below the median CEPII UN-vote disagreement, 'rival' = above). Summing the change in each partner's trade share across the two periods into the four quadrants separates the two narratives: nearshoringgain (near & rival) = -0.80 pp across 32 partners, allyshoringgain (far & ally) = +0.50 pp across 32 partners, 'both' (near & ally) = +1.26 pp, 'neither' (far & rival) = -2.54 pp. A positive 'ally' column paired with a negative 'rival' column is the Alfaro & Chor (2023) signature; a positive 'near' column paired with a negative 'far' column is the Goldberg & Reed (2023, Brookings) nearshoring signature. The two are empirically separable here.
Sources: CEPII BACI bilateral_year 2013-2023 (total goods trade, thousands USD); CEPII Gravity V202411 dist and diplo_disagreement (2020 snapshot, the latter ultimately built on Bailey, Strezhnev & Voeten 2017 J. Conflict Resolution 61(2)). Medians are computed across USA's partner universe in the gravity panel. Pre = 2013-2017, post = 2018-2023.Figure 4d
USA trade share, closest 5 voting allies vs. closest 5 rivals, 2000-2024
The five closest and five most distant partners of USA are fixed by CEPII's diplo_disagreementindex (2020 snapshot, ultimately built on Bailey, Strezhnev & Voeten 2017 UN General Assembly ideal-point voting). Each line is the combined bloc's share of USA's total goods trade, year by year. Between 2000 and 2024 the ally-5 share moved from 9.0% to 6.3% (-2.7 pp), while the rival-5 share moved from to (-0.9pp). Aiyar, Chen, Ebeke, Garcia-Saltos, Gudmundsson, Ilyina, Kangur, Kunaratskul, Rodríguez, Ruta, Schulze, Soderberg & Trevino (2023, IMF SDN/2023/001) document a comparable bloc-divergence pattern once the sample is partitioned on UN voting; a widening ally-rival gap in the post-2018 window is the visual friendshoring signal.
Figure 4e
Supplier-concentration HHI on USA goods imports, 2000-2024
The Herfindahl-Hirschman Index (HHI) on USA's import partners moved from 0.077 in 2000 (effective number of partners 13) to 0.074 in 2024 (effective number 13). Between 2018 and 2024 the index moved by -0.019 points; a falling HHI is the macro footprint of supplier diversification. Grossman, Helpman & Sabal (2024, NBER WP 31739) frame supply-chain resilience as an explicit function of supplier concentration: a doubling of the effective number of suppliers cuts the variance of input availability by half under their model. The HHI here uses the full partner distribution and is invariant to the choice of 'ally' bins, so it complements Figure 4d (fixed five-allies/five-rivals) by capturing diversification regardless of the identity of the new suppliers. Compare to Goldberg & Reed (2023, BPEA) on US import-concentration over 2017-2022.
Source: CEPII BACI bilateral_year (thousands USD), aggregated by exporter to compute partner shares of USA's total annual goods imports; HHI = sum(share_i^2) over all real-ISO3 exporters. Range [0, 1]; effective-number-of-partners = 1/HHI. Literature: Grossman, Helpman & Sabal (2024) NBER WP 31739 on resilience in vertical supply chains; Goldberg & Reed (2023) Brookings Papers on Economic Activity.
Full supplier detail, the shortlist underlying Figure 1
The top-20 friendly alternatives with every factor that enters the score, broken out so the ranking is auditable: world share, RCA, unit value, tariff into USA, distance, and the capability / cost decomposition. Tariff blanks mean the origin has no WITS-TRAINS filing in the latest year, typically because the line is MFN-zero or the partner is outside the WITS reporter universe. Distance blanks mean the origin is not in CEPII Gravity (small islands, BACI residual groupings).
Figure 5
Friendshoring shortlist detail, top-20 alternatives to USA, HS 854231, 2024
#
Exporter
World share
RCA
Unit value (USD/t)
Tariff into USA
Distance
Capability
Cost
Score
1
KOR Korea, Rep.
12.76%
3.81
$4,659,093
n/a
11.1K km
0.224
0.371
0.603
2
IRL Ireland
2.83%
2.49
$2,288,689
n/a
5.1K km
0.032
0.088
0.371
3
MYS Malaysia
Who uses this view and how
Supply-chain strategy. Figure 1 is the first-pass shortlist for a CPO or procurement head looking to exit a hostile origin on this HS6 without giving up capability.
CFO scenario planning. Figure 3 dollarises the exposure at risk and the upper-bound redirectable capacity. Where the two bars are close, the CFO should assume contracting costs; where they gap, reshoring or new capex is required.
Government affairs. Figure 4 is the sector-level map of where the sanctions proxy most binds the current trade structure, and by implication where industrial-policy offers (CHIPS-style subsidies, IRA-style tax credits, the 2025 EU Critical Raw Materials Act procurement set-asides) should focus.
Policy read
The Scanner is the HS6-level instrument for a policy question that is now explicitly on the table. USTR Section 301 actions (2018, expanded 2024) and the October 2022 + October 2023 + December 2024 BIS export-control rounds on advanced semiconductors are the US side of a bloc-driven reshuffling that Alfaro & Chor (2023) and Aiyar et al. (2023) both document in the data: US imports from China as a share of US imports have fallen roughly 8 percentage points since 2018, with Vietnam, Mexico, and India picking up the slack, precisely the kind of redirection the composite score surfaces. The EU Critical Raw Materials Act (entered into force May 2024) sets a 65% single-country supply cap for strategic raw materials by 2030, which in the friendshoring frame is equivalent to binding the maximum of world_sharein Figure 1, if the dominant origin exceeds the cap, diversification becomes policy-mandated, not optional. The US IRA (2022) and CHIPS Act (2022) do the same for EV batteries and leading-edge logic with explicit 'foreign entity of concern' exclusions on the buyer side. India PLI and the IPEF supply-chain pillar (signed November 2023) are the coordinated-build side of the same architecture. For Bangladesh and other small, trade-dependent economies, the IMF's Aiyar et al. fragmentation estimate of 0.2-7% GDP loss is the downside scenario; Baldwin, Freeman & Theodorakopoulos (2023) make the counter-argument that hyper-specialisation is more resilient than it looks because so many inputs travel through deep-tier supplier networks. Either way, the HS6 view on this page is where the policy question becomes actionable.
References
Aiyar, S., Chen, J., Ebeke, C., Garcia-Saltos, R., Gudmundsson, T., Ilyina, A., Kangur, A., Kunaratskul, T., Rodríguez, S. L., Ruta, M., Schulze, T., Soderberg, G., & Trevino, J. P. (2023). 'Geoeconomic Fragmentation and the Future of Multilateralism. ' IMF Staff Discussion Note SDN/2023/001.
Alfaro, L., & Chor, D. (2023). 'Global Supply Chains: The Looming 'Great Reallocation'.' NBER Working Paper 31661.
Autor, D. H., Dorn, D., & Hanson, G. H. (2013). 'The China Syndrome: Local Labor Market Effects of Import Competition in the United States.' American Economic Review 103(6): 2121-2168.
Bailey, M. A., Strezhnev, A., & Voeten, E. (2017). 'Estimating Dynamic State Preferences from United Nations Voting Data.' Journal of Conflict Resolution 61(2): 430-456.
Balassa, B. (1965). 'Trade Liberalisation and 'Revealed' Comparative Advantage.' The Manchester School 33(2): 99-123.
Baldwin, R., Freeman, R., & Theodorakopoulos, A. (2023). 'Hidden Exposure: Measuring US Supply Chain Reliance.' Brookings Papers on Economic Activity Fall.
Farrell, H., & Newman, A. L. (2019). 'Weaponized Interdependence: How Global Economic Networks Shape State Coercion.' International Security 44(1): 42-79.
Goldberg, P. K., & Reed, T. (2023). 'Is the Global Economy Deglobalizing? And if So, Why? And What is Next?' Brookings Papers on Economic Activity Spring: 347-396.
Grossman, G. M., Helpman, E., & Sabal, A. (2024). 'Resilience in Vertical Supply Chains.' NBER Working Paper 31739.
Head, K., & Mayer, T. (2014). 'Gravity Equations: Workhorse, Toolkit, and Cookbook.' In Handbook of International Economics, vol. 4, ch. 3.
Hummels, D., & Klenow, P. J. (2005). 'The Variety and Quality of a Nation's Exports.' American Economic Review 95(3): 704-723.
Leeds, B. A., Ritter, J. M., Mitchell, S. M., & Long, A. G. (2002). 'Alliance Treaty Obligations and Provisions, 1815-1944.' International Interactions 28(3): 237-260.
The highest-scoring friendly alternative is Rep. of Korea (KOR), with RCA of 3.81 and a world export share of 12.76%. The dominant supplier Chinese Taipei is excluded from the ranking so the table reads as a redirection shortlist.
Points in the upper-left quadrant combine high world share with low unit cost, the natural diversification pool for USA. Points in the upper-right are capable but expensive (often reflecting product-mix quality, not pure markup, per Hummels & Klenow 2005 AER 95(3) on quality-adjusted unit values). Amber points are flagged origins; the score zeroes them regardless of unit-value attractiveness.
1 of 16 HS Sections have a flagged origin as their dominant supplier, and a friendly alternative is identified for each of them. This is a macro view of where the sanctions proxy most bites the current trade map.
Sources: CEPII BACI 202501 (retrieved 2026-04-28) aggregated to HS Sections via products_all.parquet (WCO HS 2022 Section definitions). Ally flags from the sanctions proxy. Authors calcs.
Partners are binned into quintiles of CEPII's diplo_disagreement index (ultimately built on Bailey, Strezhnev & Voeten 2017 UN General Assembly ideal-point voting data): bin 1 is USA's closest voting allies, bin 5 is the most distant. Each cell shows USA's share of total goods trade going to that bin, averaged over the two windows. Between the two periods, closest-ally bins shifted by +1.3 pp (q1) and +1.1 pp (q2); most-distant bins shifted by -2.1 pp (q4) and -1.8 pp (q5). A rising allied share paired with a falling distant share is the bloc-reallocation signature Alfaro & Chor (2023) and Aiyar et al. (2023) document in post-2018 US import data.
Sources: CEPII Gravity V202411 diplo_disagreement index (2020 snapshot, based on Bailey, Strezhnev & Voeten 2017 ideal-point voting data); CEPII BACI bilateral_year for total goods trade 2013-2023. Bins are quintiles of diplo_disagreement computed across all partners of USA. Period windows are 2013-2017 and 2018-2023. Authors calcs.
1.3%
0.4%
Sources: CEPII Gravity V202411 diplo_disagreement (2020 snapshot, based on Bailey, Strezhnev & Voeten 2017 J. Conflict Resolution 61(2): 430-456); CEPII BACI bilateral_year (thousands USD, multiplied by 1000 for display). Allies and rivals are the 5 countries with the smallest and largest diplo_disagreement to USA, held fixed across all years.