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political risk intelligence
Where does USA buy from, and how politically fragile is the other end of the pipe?
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.
importerUSA (USA)
BACI year2024
WGI year2023
suppliers showntop 30
total top-30 imports$2.88T
mean risk index4.79
Dependence versus governance risk at source
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 207-country median for 2023, currently -0.56. Dot size encodes import value. Amber dots are sanctions-flagged origins (OFAC SDN + EU consolidated financial sanctions counts above threshold).
Figure 1
USA import dependence versus WGI composite at origin, 2024
2 origins sitin the high-exposure, below-average-governance quadrant (supply share ≥ 5% and composite WGI < 0): Mexico (15.5%, risk -3.43); China (14.1%, risk -2.03). The size of the dot is the absolute dollar flow: a small but high-risk origin is less materially exposing than a big and high-risk origin of the same governance score.
Sources: CEPII BACI 202501 (retrieved 2026-04-28) bilateral_year for shares (2024); World Bank Worldwide Governance Indicators, source id 3, estimates scaled approx. -2.5 to +2.5 (WGI 2023); OFAC SDN XML enhanced feed and EU consolidated financial sanctions XML for sanctions-flag. BACI value converted to USD by x1000 convention. Authors calcs.
Top at-risk corridors
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 with 100 or more combined SDN listings resident at addresses in that country, a practical proxy for material US and EU sanctions presence (see Drezner 2024, 'Sanctions and the State of the World,' Contemporary Security Policy).
Figure 2
Top 15 supplier corridors into USA, 2024, with governance and sanctions flags
#
Supplier
Imports (2024)
Supply share
Political stab. (PV)
WGI composite
Sanctions
1
MEX Mexico
$491.3B
15.5%
-4.42
-3.43
1131
2
CHN China
$448.8B
14.1%
-3.59
-2.03
1138
3
CAN Canada
$400.0B
12.6%
5.76
10.04
52
4
DEU Germany
$156.5B
Political-stability trajectory at the top 5 supplier origins
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 (2010-2023) 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.
Figure 3
WGI Political Stability (PV.EST) trend for USA's top 5 suppliers, 2010-2023
Diversification pathways
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.
Figure 4
Alternative origins with lower governance risk, for USA's flagged corridors
At-risk supplier
Supply share
Risk
Alternate origins (global export share · risk)
MEX Mexico
15.5%
-3.43
CHN China (15.7% · -2.03) · DEU Germany (6.6% · 9.22) · KOR Rep. of Korea (3.3% · 7.16)
CHN China
14.1%
-2.03
DEU Germany (6.6% · 9.22) · KOR Rep. of Korea (3.3% · 7.16) · JPN Japan (3.3% · 9.44)
2 of USA's top suppliers meet the at-risk definition. For each, the table lists three operationally plausible alternates with higher WGI scores and material global export capacity.
Sources: CEPII BACI 202501 (retrieved 2026-04-28) bilateral_year (2024) for global export shares; World Bank WGI source id 3 composite (2023); sanctions country_flags parquet from OFAC SDN + EU consolidated financial sanctions. Rule: alternate risk_index > at_risk risk_index + 0.5 and not sanctions-flagged, then rank by global export share. Authors calcs.
Portfolio governance quality of USA's supplier book
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 six-indicator WGI composite by its share of that year's imports, and sum. The construction is a direct country-level analogue of the import-weighted political risk index in Caldara & Iacoviello (2022, 'Measuring Geopolitical Risk,' American Economic Review 112(4): 1194-1225). A rising line means the average dollar spent on imports goes to a better-governed origin; a falling line means sourcing is drifting toward weaker institutions. Complementary measures from the International Country Risk Guide (ICRG) monthly ratings, V-Dem's liberal democracy index, Reporters Without Borders press-freedom score, and sovereign CDS spreads would rescale but not reverse the direction.
Figure 5
Import-weighted WGI composite for USA's supplier book, 2009-2023
The weighted composite moved from 6.38 in 2009 to 3.06 in 2023, a change of -3.32 composite-standard-deviation units over fifteen years. The metric is mechanically driven by two forces: changes in where USA sources from (the weights), and changes in source-country governance at constant weights. Both show up together in this single curve.
Sources: World Bank WGI (CC.EST, PV.EST, GE.EST, RQ.EST, RL.EST, VA.EST), source id 3, 2010-2023; CEPII BACI 202501 (retrieved 2026-04-28) bilateral_year. Weighting method following Caldara & Iacoviello (2022) AER 112(4): 1194-1225. Authors calcs.
The institutions-income link: global reference frame
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 2023) and a WDI NY.GDP.PCAP.CD value (2022). 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.
Figure 6
WGI composite × log GDP per capita, 200 countries, 2023
Conflict intensity × trade openness: the global cross-section
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 2023; the importer USA is highlighted.
Figure 7
Political stability × trade openness, 179 countries, 2023
Democracy and trade openness: the Polyarchy-via-WGI cross-section
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, Sundström, Holmberg, Rothstein, Alvarado Pachon & Mert Dalli (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 (2008, Journal of Economic Perspectives 19(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.
Rule of law and the export of complex, contract-intensive 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 2023 with both indicators observed. The importer USA is highlighted.
Figure 9
WGI Rule of Law (RL.EST) × Economic Complexity Index (ECI), 200 countries, 2023
Policy read
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.
How operational risk and C-suite teams use this
Board-level supplier review. Figure 1 is a one-screen read-out of which origins on the import book cross both material-dependence and weak-governance lines.
Sanctions screening. The flag column in Figure 2 surfaces origins where counterparty due diligence must be layered on top of commercial sourcing decisions.
Diversification playbook. Figure 4 gives an alternate-origin shortlist bounded by actual global export capacity, not aspirational geographies.
Book-level tracking. Figure 5's single scalar slots alongside ICRG political, V-Dem liberal democracy, Reporters Without Borders, or 5Y sovereign CDS on a monthly risk dashboard.
References
Drezner, D. W. (2024). 'Sanctions and the State of the World.' Contemporary Security Policy.
Farrell, H., & Newman, A. L. (2019). 'Weaponized Interdependence: How Global Economic Networks Shape State Coercion.' International Security 44(1): 42-79.
Kaufmann, D., Kraay, A., & Mastruzzi, M. (2011). 'The Worldwide Governance Indicators: Methodology and Analytical Issues.' Hague Journal on the Rule of Law 3(2): 220-246.
Caldara, D., & Iacoviello, M. (2022). 'Measuring Geopolitical Risk.' American Economic Review 112(4): 1194-1225.
PRS Group. International Country Risk Guide (ICRG) Methodology. East Syracuse, NY. (ICRG political, financial, and economic risk ratings, monthly.)
Coppedge, M., Gerring, J., Knutsen, C. H., Lindberg, S. I., Teorell, J., et al. (2024). V-Dem Codebook v14. Varieties of Democracy Project, University of Gothenburg.
Reporters Without Borders (2024). World Press Freedom Index 2024. Paris.
US Treasury, Office of Foreign Assets Control. Specially Designated Nationals and Blocked Persons List (enhanced XML feed).
European Union. Consolidated List of Persons, Groups and Entities Subject to EU Financial Sanctions (XML feed, data.europa.eu).
0of the top 15 supplier countries are sanctions-flagged (OFAC+EU combined count ≥ 100). The highest supply share among below-average-governance origins (composite < 0) in this table is Mexico at 15.5%.
Sources: CEPII BACI 202501 (retrieved 2026-04-28) (shares, 2024); World Bank WGI source id 3 (PV.EST, composite), 2023; US Treasury OFAC SDN XML and EU consolidated financial sanctions XML (address-country counts). Composite = mean of available WGI estimates. Authors calcs.
Five trend lines for the top-5 supplier origins to USA. The PV.EST scale is approximately −2.5 (worst) to +2.5 (best); negative values mark below-world-average stability. The WGI methodology aggregates governance perceptions from ~30 sources and is documented in Kaufmann, Kraay & Mastruzzi (2011). Read the slope, not the level: a multi-year decline in a major source is the concentration-risk metric that Farrell & Newman (2019) formalise as 'weaponisable' dependence.
Source: World Bank Worldwide Governance Indicators, source id 3, PV.EST estimate 2010-2023. CEPII BACI 202501 (retrieved 2026-04-28) bilateral_year for top-5 supplier selection. Authors calcs.
Pearson correlation between the WGI composite (2023) and log10(GDP per capita, current USD, 2022) across 200 countries is 0.82. A one-unit rise in the composite (roughly one-third of the full WGI scale) associates with a ~10.0× movement in income on the visual fit, but the link is descriptive, not causal. Acemoglu, Johnson & Robinson (2001 AER91(5): 1369-1401) use settler mortality as an instrument to argue the direction runs from institutions to income, with follow-up debate in Glaeser, La Porta, Lopez-de-Silanes & Shleifer (2004 Journal of Economic Growth 9(3): 271-303) that human capital drives both. Either way, importer corridors with WGI above the fit line are resilient for their income class; corridors below it carry latent political risk.
Sources: World Bank WGI (CC+PV+GE+RQ+RL+VA, 2023); World Bank WDI NY.GDP.PCAP.CD (2022). log-y axis, ISO3 filter regexp_matches(iso3, '^[A-Z0-9]{3}$'). Cites Acemoglu & Robinson (2012) Why Nations Fail, Crown; Acemoglu, Johnson & Robinson (2001) AER 91(5): 1369-1401.
Pearson correlation between PV.EST (2023) and log10 trade openness across 179 countries is 0.49. Low-PV (high-conflict) economies cluster at low-to-moderate openness, with a few exceptions (small-state entrepots whose openness is driven by transit trade, not by a peace-through-commerce mechanism). The reverse-causation caveat from Barbieri (1996, Journal of Peace Research33(1): 29-49) applies: openness and stability are co-determined, so the correlation is a descriptive summary rather than evidence of the 'trade-builds-peace' channel that Martin, Mayer & Thoenig identify with panel variation. Once ACLED is ingested, this panel will be rebuilt on fatality-count-per-year as the conflict intensity measure.
Sources: World Bank WGI PV.EST, source id 3, 2023; World Bank WDI NE.TRD.GNFS.ZS (trade % GDP), latest year within 2020-2023. ISO3 filter regexp_matches(iso3, '^[A-Z0-9]{3}$'). Cites Martin, Mayer & Thoenig (2008) RES 75(3): 865-900; Anderton & Carter (2001) Def Peace Econ 12(5); Glick & Taylor (2010) RESTAT 92(1): 102-127. ACLED event data not yet ingested into the workbench.
Pearson correlation between VA.EST (2023) and log10 trade openness across 175 countries is 0.31. High-VA democracies cluster at moderate-to-high openness; low-VA regimes span the full openness range because some small resource- or transit-dependent autocracies (GNQ, TKM, as well as entrepot regimes) carry high openness without democratic institutions. The scatter is partial-correlation only; the Rodrik (2000) and Levchenko (2013) channels run through contract-enforceability, which VA.EST captures imperfectly. With V-Dem Polyarchy ingested, this panel will be rebuilt on the multiplicative Polyarchy score and stratified by whether openness growth preceded or followed democratic consolidation.
Sources: World Bank WGI VA.EST, source id 3, 2023; World Bank WDI NE.TRD.GNFS.ZS latest year within 2020-2023. ISO3 filter regexp_matches(iso3, '^[A-Z0-9]{3}$'). Cites Teorell et al. (2019) SCID 54(1): 71-95 on the VA.EST × V-Dem Polyarchy correlation; Rodrik (2000) AER P&P 90(2); Levchenko (2013) JDE 100: 47-65. V-Dem Polyarchy not yet ingested into the workbench.
Pearson correlation between RL.EST and ECI across 200 countries: 0.72. The Berkowitz-Moenius-Pistor (2006) prediction is a positive, meaningful slope: stronger rule of law goes with the export of more complex, contract-intensive goods. The upper-right cluster (high RL, high ECI) is the German-Japanese-Korean machinery and electronics complex; the lower-left (weak RL, low ECI) is fragile-state and resource-dependent economies; off-diagonal points (especially upper-left, strong RL but low ECI) are small high-institution states whose export basket is concentrated by geography (Iceland, Luxembourg). The cross-sectional slope is an association, not identification: Acemoglu, Johnson & Robinson (2001 AER 91(5): 1369-1401) instrument institutions with settler mortality precisely because the OLS regression here is contaminated by reverse causality and omitted-variable bias from human capital (Glaeser et al. 2004, JEG 9(3): 271-303).
Sources: World Bank WGI source id 3, RL.EST (2023); Atlas of Economic Complexity ECI via eci_rankings.parquet (2023); countries.parquet for ISO3 join. ISO3 filter regexp_matches(iso3, '^[A-Z0-9]{3}$'). Cites Berkowitz, Moenius & Pistor (2006) Review of Economics and Statistics 88(2): 363-373; Nunn (2007) QJE 122(2): 569-600; Levchenko (2007) Review of Economic Studies 74(3): 791-819; Hausmann & Hidalgo (2009) PNAS 106(26): 10570-10575.