Given an importer (USA) and an HS6 product (Electronic integrated circuits: processors and controllers, whether or not combined with memories, converters, logic circuits, amplifiers, clock and timing circuits, or other circuits), the page ranks alternative suppliers on a composite friendshoring score that rewards capability and penalises cost, using a continuous, year-varying UNGA alignment term and an explicit median-alignment filter for the shortlist. World trade of this line in 2024 totalled $427.7B. Suppliers below USA's full-panel median alignment represented roughly 39.8% of that total.

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_index × ( 1 / cost )

  capability = norm(RCA_i) × norm(world_export_share_i)
  ally_index = 1 - ally_dist / (max_c theta_c(t) - min_c theta_c(t))
  ally_dist  = |theta_importer(t) - theta_supplier(t)|
  cost       = ( norm(unit_value_i) + 0.01 )
             × ( norm(distance_to_importer_i) + 0.01 )
             × ( 1 + applied_tariff_rate_i )

Capability and cost inputs are normalised across the current supplier universe for this HS6. The ally_index is separately normalised to [0, 1] with the full UNGA panel's vote-year span, so the combined score is unit-free and rank-interpretable within this request. BACI values are stored in thousands of USD and multiplied by 1,000 for display (CEPII BACI 202601 (retrieved 2026-06-01) convention). RCA is the Balassa (1965) index from the rca_matrix parquet.

Honest caveat on the ally factor.This page uses the Bailey, Strezhnev & Voeten (2017, Journal of Conflict Resolution 61(2): 430-456) UN General Assembly ideal-point panel. ally_dist(i, j, t) = |theta_i(t) - theta_j(t)|, the BSV absolute ideal-point distance. ally_index(i, j, t) = 1 - ally_dist / (max_c theta_c(t) - min_c theta_c(t)), in [0, 1]. 1 means an identical UNGA position, 0 means as far apart as that year's two extremes. Normalising by the year's own span, not by a constant, keeps it comparable across years as the assembly spreads or converges. is_ally(i, j, t) = 1 when ally_dist is below the median distance from the importer to every country with an ideal point that year. The median split is the page's own established convention: Figure 4c already median-splits diplo_disagreement. It is computed over the full UNGA panel, not the HS6 supplier universe, so the cut does not move with the product. The vote year is max(year) at or below the BACI year, here 2024, and observations are never carried forward beyond the panel.

ally_index is affine in ally_dist within an importer-year, so it never reorders suppliers for a given importer. Its attainable range depends on where the importer sits: an importer at an extreme can reach 0, while one near the centre bottoms out near 0.5. Score levels are therefore not comparable across importers. The median split makes roughly half of all observed UNGA members "allies" of any importer-year by construction. It is a relative-alignment cut, not a hostility, embargo, or policy-risk classification. UNGA ideal-point distance is a proxy for revealed foreign-policy alignment and not a measure of alliance, export-control regime or sanctions exposure. Non-members may be unobserved: TWN stops in 1971, while HKG and MAC never appear. Such suppliers receive no score and are disclosed rather than filled. Figures 4b to 4e remain on the 2020 diplo_disagreement snapshot stored in Legacy gravity_bilateral table (exact release provenance unverified) and are not recomputed from this panel.

Who are the above-median-aligned alternatives, ranked?

The top-20 non-dominant suppliers of HS 854231 in 2024, ranked by the composite score above. The shortlist is explicitly filtered to is_ally = 1, the importer-year's below-median ideal-point distance, and ranked with the continuous ally_index term.

Excluded for missing 2024 ideal points: HKG, S19, together representing 24.16% of current HS6 world supply.

Are the cheap suppliers also capable, and closely aligned?

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 (Legacy gravity_bilateral table (exact release provenance unverified)). Bubble colour encodes the full-panel median alignment split for vote year 2024: green is above-median alignment, amber is below-median alignment, and grey has no usable ideal point. The ideal friendshoring candidate sits in the upper-left quadrant with a small bubble and green marker.

How much dollar value could shift to more closely aligned 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 below-median-aligned origins, a BACI-mirror approximation because partner-level HS6 bilateral flows are not loaded on this page. The second bar is the total HS 854231 export value of above-median-aligned suppliers excluding the dominant origin, an upper bound on supply that could be redirected toward USA without new capacity.

By HS Section: dominant supplier vs. #1 above-median-aligned 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 its ideal-point distance is above or below USA's full-panel median, and the highest-share alternative on the above-median-aligned side. An unavailable cell means the supplier lacks a 2024ideal point or the alignment layer could not be read.

Full supplier detail, the shortlist underlying Figure 1

The top-20 above-median-aligned alternatives with every factor that enters the score, broken out so the ranking is auditable: world share, RCA, unit value, tariff into USA, distance, UNGA alignment index, 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).

Who uses this view and how

• Supply-chain strategy. Figure 1 is the first-pass shortlist for a CPO or procurement head looking to replace a below-median-aligned origin on this HS6 without giving up capability.
• CFO scenario planning. Figure 3 compares the approximate import value allocated to below-median-aligned origins with upper-bound redirectable capacity. It is a sourcing scenario, not an estimate of regulatory or financial exposure.
• Government affairs. Figure 4 is the sector-level map of where the dominant supplier falls below the importer's median UNGA alignment and where an above-median-aligned alternative exists. That relative map can be read alongside, but does not encode, industrial-policy eligibility.

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. United Nations General Assembly Ideal Points, doi:10.7910/DVN/LEJUQZ, Harvard Dataverse v39.0, CC0 1.0.
• 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.