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Fetching primary parquet sources and computing exhibits.
This scanner overlays USA's bilateral supply dependence in 2024(from CEPII BACI) with the Worldwide Governance Indicators (Kaufmann, Kraay & Mastruzzi 2011) at the source country. Upper-right cells in Figure 1 are the cells a board asks about: a big share of a critical inflow coming from a place with brittle institutions. Framing follows Farrell & Newman (2019), 'Weaponized Interdependence,' in which concentrated network nodes become instruments of statecraft.
Each point is one of USA's top 30 supplier countries in 2024. Horizontal axis is that origin's share of USA's total goods imports. Vertical axis is the composite WGI score, the simple mean of the six Kaufmann-Kraay-Mastruzzi estimates (Control of Corruption, Political Stability and Absence of Violence/Terrorism, Government Effectiveness, Regulatory Quality, Rule of Law, Voice and Accountability), each running from about -2.5 (worst) to +2.5 (best). Negative y-values indicate below-world-average institutional quality; the dashed reference marks the 205-country median for 2024, currently -0.05. Dot size encodes import value. Amber dots are sanctions-flagged origins (OFAC SDN + EU consolidated financial sanctions counts above threshold).
WITH raw AS (
SELECT b.exporter_code, SUM(b.total_value) AS v
FROM 'bilateral_year/year=2024/*.parquet' b
JOIN (SELECT MIN(code) code FROM 'countries.parquet' WHERE iso3='USA') i
ON i.code = b.importer_code
GROUP BY b.exporter_code
), wgi AS (
SELECT iso3,
AVG(value) AS risk_index
FROM 'wgi.parquet'
WHERE year = 2024
GROUP BY iso3
)
SELECT c.iso3, raw.v/ SUM(raw.v) OVER () AS share, wgi.risk_index
FROM raw JOIN (SELECT iso3, MIN(code) code FROM 'countries.parquet' GROUP BY iso3) c ON c.code=raw.exporter_code
LEFT JOIN wgi ON wgi.iso3 = c.iso3
ORDER BY raw.v DESC LIMIT 30;Table of the top 15 supplier countries ranked by import value into USA. For each we report the supply share, the Political Stability and Absence of Violence/Terrorism estimate (WGI PV.EST) separately as the headline single indicator most aligned with the word 'political risk' in operational contexts, the composite WGI score as a broader institutional-quality summary, and the sanctions flag from the OFAC SDN + EU consolidated financial sanctions feeds. The sanctions flag marks countries subject to a comprehensive or country-specific OFAC/EU sanctions program (for example North Korea, Myanmar, and the DR Congo), not a simple count of listings: jurisdictions with many address-resident SDN entries but no country program (such as China or Mexico) are not flagged (see Drezner 2024, 'Sanctions and the State of the World,' Contemporary Security Policy).
The snapshot at source in Figure 1 misses the direction of travel. The Kaufmann-Kraay-Mastruzzi Political Stability and Absence of Violence/Terrorism estimate (PV.EST) is updated annually by the World Bank from ~30 underlying data sources and is the single WGI indicator closest to the operational meaning of 'political risk.' Below is the 15-year trajectory (2010-2024) for USA's five largest supplier origins, each a real WGI pull. A downward trend in a top-5 origin is the signal a treasury or operations desk watches: it precedes the moment where Figure 1 would recolour that point from blue to amber.
For each of USA's top suppliers currently in the high-exposure / high-risk quadrant (supply share ≥ 5% and composite WGI < 0, or sanctions-flagged), we list the three alternate origins with the largest global export footprint whose WGI composite exceeds the at-risk supplier's by at least 0.5 standard-deviation-equivalent units and that are not themselves sanctions-flagged. Capability is proxied by global export share in 2024 from BACI bilateral records; a near-zero share means the alternate is unlikely to absorb commercially meaningful redirected demand.
Collapsing the whole supplier book into a single scalar per year: for each year compute USA's bilateral imports from every origin, weight each origin's mean of available estimates across six WGI indicators by its share of that year's imports, and sum. The construction is a TradeWeave descriptive composite. Caldara & Iacoviello's GPR index (2022) measures geopolitical risk using newspaper coverage; it is a different measure. A rising line indicates higher weighted governance scores among the covered suppliers. WGI-missing origins contribute no score, and their import weights are not redistributed, so changes in coverage can also move this series. Comparisons with ICRG, V-Dem, press-freedom scores or sovereign CDS spreads have not been tested here.
Acemoglu & Robinson (2012, Why Nations Fail, Crown) argue that inclusive institutions and long-run prosperity reinforce each other; the positive cross-sectional slope between institutional quality and real income per capita is one of the most replicated facts in growth economics (La Porta, Lopez-de-Silanes, Shleifer & Vishny 1999 Quarterly Journal of Economics114(4): 1193-1229; Rodrik, Subramanian & Trebbi 2004 Journal of Economic Growth 9(2): 131-165, 'Institutions Rule'). Each point below is a country with both a World Bank WGI composite (mean of the six Kaufmann-Kraay-Mastruzzi estimates, vintage 2024) and a WDI NY.GDP.PCAP.CD value (2023). This is the cross-country frame that contextualises Figures 1-5: points below the regression fit have weaker institutions than their income level predicts, and vice versa.
Martin, Mayer & Thoenig (2008, Review of Economic Studies75(3): 865-900, 'Make Trade Not War?') argue that bilateral trade reduces the incidence of interstate conflict but that multilateral openness can cut the other way by lowering the opportunity cost of war with any single partner. Anderton & Carter (2001, Defence and Peace Economics12(5): 445-462) and Glick & Taylor (2010, Review of Economics and Statistics 92(1): 102-127) quantify the trade-cost shadow of conflict. ACLED event-level data is not yet ingested in the workbench, so this panel uses the Kaufmann-Kraay-Mastruzzi Political Stability and Absence of Violence/Terrorism estimate (PV.EST, higher = less violence) as the conflict-intensity proxy, and the World Bank WDI NE.TRD.GNFS.ZS (trade as % of GDP) as trade openness. Each point is one country in 2024; the importer USA is highlighted.
The V-Dem Polyarchy index (Coppedge, Gerring, Knutsen, Lindberg, Teorell et al. 2024, V-Dem Codebook v14) is the canonical multiplicative democracy measure and the natural regressor for a democracy-trade scatter; V-Dem is not yet ingested in the workbench, so we substitute the WGI Voice & Accountability estimate (VA.EST), which Teorell, Coppedge, Lindberg & Skaaning (2019, Studies in Comparative International Development 54(1): 71-95, 'Measuring Polyarchy across the globe, 1900-2017') document correlates with V-Dem Polyarchy at roughly 0.9 across the full country panel. Trade openness is the World Bank WDI NE.TRD.GNFS.ZS (trade as % of GDP). Rodrik (2000, AER Papers & Proceedings90(2): 140-144) and Persson & Tabellini (2004, Journal of Economic Perspectives 18(1): 75-98) treat democracy and openness as mutually reinforcing; Levchenko (2013, Journal of Development Economics 100: 47-65) formalises institutional quality as a comparative-advantage determinant of exports of institution-dependent goods.
Berkowitz, Moenius & Pistor (2006, 'Trade, Law, and Product Complexity,' Review of Economics and Statistics 88(2): 363-373) document that legal institutions matter more for trade in complex, contract-intensive goods than for primary commodities. Nunn (2007, QJE 122(2): 569-600) and Levchenko (2007, Review of Economic Studies 74(3): 791-819) formalise this as the institutions-as-comparative-advantage channel: countries with stronger rule of law specialise in production whose value chain depends on enforceable contracts. The natural cross-section is WGI Rule of Law (RL.EST) on the horizontal axis against the Hausmann-Hidalgo Economic Complexity Index (ECI) on the vertical axis. Each point is one country in 2024 with both indicators observed. The importer USA is highlighted.
Weak institutions at the other end of a supply chain are not automatically a risk for the buyer; they become one when concentration is high, when substitutes are scarce (Farrell & Newman 2019), or when a shock reprices political stability quickly. Figures 1 and 2 catch the dependence-dimension; Figure 3 gives the direction of travel; Figure 4 points to commercially plausible substitutes; Figure 5 collapses the whole book into one number that a risk committee can track month over month against benchmarks like ICRG political, V-Dem liberal democracy, Reporters Without Borders press freedom, or 5Y sovereign CDS. The policy read for a trade ministry is symmetric: when USA's portfolio composite declines, it is a cue that diversification treaties or critical-minerals agreements with higher-WGI peers need acceleration.
| $156.7B |
| 5.0% |
| 0.12 |
| 1.36 |
| flag (117) |
| 5 | JPN Japan | $144.4B | 4.6% | 1.13 | 1.42 | 20 |
| 6 | VNM Vietnam | $140.5B | 4.4% | 0.01 | -0.34 | 21 |
| 7 | KOR Korea, Rep. | $134.6B | 4.3% | 0.64 | 0.99 | 2 |
| 8 | S19 Chinese Taipei | $95.6B | 3.0% | n/a | n/a | n/a |
| 9 | IRL Ireland | $88.8B | 2.8% | 0.71 | 1.49 | 8 |
| 10 | IND India | $88.6B | 2.8% | -0.79 | -0.15 | flag (135) |
| 11 | ITA Italy | $70.4B | 2.2% | 0.31 | 0.66 | 74 |
| 12 | GBR United Kingdom | $64.3B | 2.0% | 0.26 | 1.17 | flag (181) |
| 13 | THA Thailand | $63.9B | 2.0% | -0.68 | -0.27 | 52 |
| 14 | FRA France | $54.0B | 1.7% | -0.24 | 0.91 | 35 |
| 15 | CHE Switzerland | $51.3B | 1.6% | 0.98 | 1.67 | 69 |
SELECT iso3, year, value FROM 'wgi.parquet' WHERE indicator = 'PV.EST' AND iso3 IN (top 5 supplier ISO3s to USA) AND year >= 2010 ORDER BY iso3, year;
WITH wgi_composite AS (
SELECT iso3, year, AVG(value) AS ri
FROM 'wgi.parquet'
WHERE indicator IN ('CC.EST','PV.EST','GE.EST','RQ.EST','RL.EST','VA.EST')
GROUP BY iso3, year
), shares AS (
SELECT b.year, c.iso3 AS ex_iso3,
SUM(b.total_value) / NULLIF(SUM(SUM(b.total_value)) OVER (PARTITION BY b.year), 0) AS share
FROM 'bilateral_year/**/*.parquet' b
JOIN 'countries.parquet' c ON c.code = b.exporter_code
WHERE b.importer_code = (SELECT MIN(code) FROM 'countries.parquet' WHERE iso3='USA')
GROUP BY b.year, c.iso3
)
SELECT s.year, SUM(s.share * w.ri) AS weighted
FROM shares s JOIN wgi_composite w ON w.iso3 = s.ex_iso3 AND w.year = s.year
GROUP BY s.year ORDER BY s.year;WITH wgi_comp AS (
SELECT iso3, AVG(value) AS wgi_comp
FROM 'wgi.parquet'
WHERE indicator IN ('CC.EST','PV.EST','GE.EST','RQ.EST','RL.EST','VA.EST')
AND year = 2024 AND value IS NOT NULL
GROUP BY iso3
), gdp AS (
SELECT iso3, value AS gdp_pc FROM 'wdi_data.parquet'
WHERE indicator='NY.GDP.PCAP.CD' AND year=2023 AND value>0
)
SELECT w.iso3, w.wgi_comp, g.gdp_pc
FROM wgi_comp w JOIN gdp g ON g.iso3=w.iso3
WHERE regexp_matches(w.iso3, '^[A-Z0-9]{3}$');WITH pv AS (SELECT iso3, value AS pv_est FROM 'wgi.parquet' WHERE indicator='PV.EST' AND year=2024),
open AS (SELECT iso3, value AS openness FROM 'wdi_data.parquet' WHERE indicator='NE.TRD.GNFS.ZS'
QUALIFY ROW_NUMBER() OVER (PARTITION BY iso3 ORDER BY year DESC)=1)
SELECT pv.iso3, pv.pv_est, o.openness FROM pv JOIN open o ON o.iso3=pv.iso3
WHERE regexp_matches(pv.iso3,'^[A-Z0-9]{3}$');WITH va AS (SELECT iso3, value AS va_est FROM 'wgi.parquet'
WHERE indicator='VA.EST' AND year=2024),
open AS (SELECT iso3, value AS openness FROM 'wdi_data.parquet'
WHERE indicator='NE.TRD.GNFS.ZS'
QUALIFY ROW_NUMBER() OVER (PARTITION BY iso3 ORDER BY year DESC)=1)
SELECT va.iso3, va.va_est, o.openness FROM va JOIN open o ON o.iso3=va.iso3
WHERE regexp_matches(va.iso3,'^[A-Z0-9]{3}$');WITH rl AS (
SELECT iso3, value AS rl_est FROM 'wgi.parquet'
WHERE indicator='RL.EST' AND year=2024 AND value IS NOT NULL
), eci AS (
SELECT c.iso3, e.eci FROM 'eci_rankings.parquet' e
JOIN (SELECT iso3, MIN(code) code FROM 'countries.parquet'
WHERE regexp_matches(iso3,'^[A-Z0-9]{3}$') GROUP BY iso3) c
ON c.code=e.country_code
WHERE e.year=2024
)
SELECT eci.iso3, rl.rl_est, eci.eci FROM rl JOIN eci ON eci.iso3=rl.iso3;