Where does global trade expose compliance teams to anti-bribery risk?

A counterparty's operating environment drives most of the residual anti-bribery and corruption exposure on a trade lane. This lens overlays institutional-quality scores on bilateral flows for 2024 so that a compliance, investigations, or FCPA advisory team can see where the risk concentrates. Global view.

A note on the governance metric

The Transparency International Corruption Perceptions Index (CPI) and the World Bank Worldwide Governance Indicators (WGI) Control of Corruption estimate (CC.EST, scale roughly −2.5 to +2.5) are the canonical country-level corruption-risk metrics in the Kaufmann, Kraay & Mastruzzi (2010, Hague Journal on the Rule of Law 3(2)) methodology. WGI CC.EST is ingested in the workbench (data/parquet/wgi.parquet) and is used directly in Figure 5. For Figures 1-4 the workbench uses the World Bank Doing Business aggregate score (eodb_score, 0-100, higher is better institutional quality), which is present for 183 economies in vintage 2020 and supplies the wider country coverage needed for the sectoral and bilateral joins. The substitution is imperfect: EODB weights regulatory burden and contract enforcement more heavily than perceptions of graft, and the Doing Businessreport was discontinued in 2021 after methodology concerns (Machiavello, Murrell & Stanton, 2021 review of the WB Independent Evaluation). TODO for workbench ingest: add CPI annual series so all five figures can be rendered against the Transparency International metric.

Trade volume against governance score

Each point is a country active in 2024 BACI totals for which an EODB score is available. The horizontal axis is EODB (higher is better institutional quality); the vertical axis is total merchandise trade (exports plus imports, USD). Points to the left of the median line sit in the below-median institutional-quality cohort used to drive Figures 2 and 3.

Which HS sections carry the most low-governance exposure

For each HS Section (I-XXI, WCO Harmonized System 2022 nomenclature), we sum2024 world export value by exporter and report the USD value originating in a below-median-EODB country. Shift-share of corruption risk across trade portfolios is a standard FCPA due-diligence screen (Svensson, 2005, Journal of Economic Perspectives19(3) on the difficulty of measuring corruption; Olken & Pande, 2012, Annual Review of Economics 4, on corruption measurement in development economics).

Bilateral risk hot-list

Top-20 exporter × importer pairs in 2024 where the exporter sits below the EODB median and bilateral trade value is among the largest in BACI. This is the raw shortlist an FCPA compliance team would pull for due diligence on local agents, customs clearance chains, and third-party payment flows. Cressey's fraud triangle (opportunity, pressure, rationalisation; Cressey 1953, Other People's Money) and the OECD Foreign Bribery Report (2014) both highlight high-value cross-border transactions into low-governance jurisdictions as the canonical risk lane.

Third-party intermediation hubs

Global-value-chain research and the tax-haven literature identify a handful of jurisdictions that intermediate a disproportionate share of world trade: Hong Kong SAR, Singapore, United Arab Emirates, Switzerland, Netherlands, Luxembourg. These entrepots combine low final-sale exposure, established re-export regimes, and dense trade finance. Fisman & Wei (2004, JPE 112(2)) on Hong Kong-China discrepancies established empirical tests for trade misinvoicing; the Tax Justice Network's Corporate Tax Haven Indexand Garcia-Bernardo, Fichtner, Takes & Heemskerk (2017, Scientific Reports 7) on the network of offshore financial centres map the same nodes. In the gravity-of-corporate-tax-avoidanceframework (Damgaard, Elkjaer & Johannesen 2024, Review of Economics and Statistics), these hubs are the structural intermediaries through which trade and investment are routed for tax and regulatory reasons. Their combined (imports + exports) volume in 2024 is a floor, not a measure, of re-routed trade.

Control of Corruption trend for the largest trade partners

Switching governance metric for this panel, from EODB to the World Bank WGI Control of Corruption estimate (CC.EST, scale approximately −2.5 to +2.5, higher = tighter control). The metric is the canonical corruption-perceptions composite in the Kaufmann-Kraay-Mastruzzi (2011) methodology and is the one Mauro (1995, Quarterly Journal of Economics110(3): 681-712) on corruption and growth and Olken & Pande (2012, Annual Review of Economics 4: 479-509) in the measurement review lean on. Below is the 2010-2023 trajectory for the top six economies by 2024 two-way trade. FCPA compliance teams read the slope as a forward indicator: a multi-year decline means the local environment is tightening toward higher graft exposure, regardless of where the level currently sits. Cross-country comparisons of CC.EST are broadly consistent with Transparency International's CPI, which would replace this panel once ingested.

Control of Corruption versus export complexity

A complementary cross-section: plot the Kaufmann-Kraay-Mastruzzi Control of Corruption estimate (CC.EST, WGI 2024) against the Hausmann-Hidalgo Economic Complexity Index (ECI) for every country that has both in 2024. ECI summarises the sophistication and diversity of a country's export basket from the Hausmann & Hidalgo (2009, PNAS 106(26): 10570-10575) product-space methodology and the Atlas of Economic Complexity (Hausmann, Hidalgo et al. 2014, MIT Press). Stronger control of corruption is robustly correlated with more complex export baskets, a link consistent with Mauro (1995 QJE) on corruption-growth, Mo (2001 JCE) on corruption and growth channels, and the broader institutions-development literature. The scatter frames corruption-lens's sector and lane results (Figures 2-3) in the export-basket-capability dimension: low-governance origins dominating the FCPA shortlist sit, as a rule, in the low-complexity quadrant, and vice versa.

Does corruption cost more trade where the export basket is more complex?

Figure 6 plots the unconditional link. The policy-relevant question sits one level deeper: does the same one-unit decline in Control of Corruption cost an economy more trade when its basket is more complex? Hausmann, Hwang & Rodrik (2007, Journal of Economic Growth 12(1): 1-25) and Nunn (2007, QJE 122(2): 569-600) argue that sophisticated products are relational and contract-intensive, which makes them more sensitive to graft than primary commodities. The test is a 4-parameter OLS on the country cross-section in 2024: ln(trade) = α + β₁·CC + β₂·ECI + β₃·(CC×ECI) + ε. A positive β₃ means corruption bites harder as complexity rises. We also split the sample into ECI terciles and estimate a simple bivariate β(CC) inside each stratum, so the heterogeneity is legible without reading a regression table.

Resource curse residual: corruption versus income, with oil exporters flagged

The unconditional Acemoglu-Robinson (2012, Why Nations Fail) link runs from institutions to long-run prosperity, with WGI Control of Corruption a stand-in for the institutional axis. The resource-curse literature (Sachs & Warner 1995, NBER WP 5398; Mahdavi 2015 AER 105(5): 100-104; Ross 2012, The Oil Curse, Princeton) argues that fuel-dependent economies systematically score worse on governance than their per-capita income would predict. Each point below is a country with both WGI CC.EST in 2024 and a recent World Bank WDI NY.GDP.PCAP.CDobservation. Amber points mark countries where HS Section V (mineral fuels and related products) exceeds 40% of total goods exports in 2024, the OPEC + major petro-state cohort.

Policy read

Corruption is not a uniform tax on trade, it is a wedge that concentrates in specific sectors (Figure 2), specific bilateral lanes (Figure 3), and specific intermediary jurisdictions (Figure 4). The policy instrument set that works on each is different: sector-heavy exposure needs FCPA/UK Bribery Act control refresh and OECD Anti-Bribery Convention enforcement; bilateral lane exposure needs enhanced due diligence on local agents; intermediary-hub exposure needs beneficial-ownership registries and re-invoicing controls (FATF 2020 TBML). The 2010-2023 CC.EST slopes in Figure 5 are the early-warning channel: rising slopes validate local anti-corruption reforms, falling slopes flag deteriorating environments before sector or bilateral stats catch up.

How compliance and FCPA advisory use this

• Third-party due diligence. Figure 3 is the raw shortlist for enhanced due diligence: high-value lanes into or out of low-governance exporters.
• Sector heat mapping. Figure 2 drives the annual ABC risk assessment by HS section, feeding into FCPA and UK Bribery Act control-design refresh cycles.
• Entrepot flags. Figure 4's intermediary hubs warrant transaction testing for re-invoicing, trade-based money laundering (TBML), and sanctions evasion risk; see FATF (2020) Trade-Based Money Laundering: Trends and Developments.
• Investigations triage. When an allegation surfaces, this lens tells an investigations lead whether the lane itself is an outlier (well above the country's normal exposure) or ordinary course.

References

• Cressey, D. R. (1953). Other People's Money: A Study in the Social Psychology of Embezzlement. Free Press.
• Damgaard, J., Elkjaer, T., & Johannesen, N. (2024). 'The Global FDI Network: Searching for Ultimate Investors.' Review of Economics and Statistics, forthcoming.
• Financial Action Task Force (2020). Trade-Based Money Laundering: Trends and Developments. Paris.
• Fisman, R., & Wei, S.-J. (2004). 'Tax Rates and Tax Evasion: Evidence from 'Missing Imports' in China.' Journal of Political Economy 112(2): 471-496.
• Garcia-Bernardo, J., Fichtner, J., Takes, F. W., & Heemskerk, E. M. (2017). 'Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network.' Scientific Reports 7: 6246.
• Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). 'The Worldwide Governance Indicators: Methodology and Analytical Issues.' Hague Journal on the Rule of Law 3(2): 220-246.
• Mauro, P. (1995). 'Corruption and Growth.' Quarterly Journal of Economics 110(3): 681-712.
• OECD (2014). OECD Foreign Bribery Report: An Analysis of the Crime of Bribery of Foreign Public Officials. OECD Publishing, Paris.
• Olken, B. A., & Pande, R. (2012). 'Corruption in Developing Countries.' Annual Review of Economics 4: 479-509.
• Svensson, J. (2005). 'Eight Questions about Corruption.' Journal of Economic Perspectives 19(3): 19-42.
• Tax Justice Network (2024). Corporate Tax Haven Index 2024. London.
• Transparency International (2024). Corruption Perceptions Index 2024. Berlin. [Ingest pending.]
• World Bank (2020). Doing Business 2020: Comparing Business Regulation in 190 Economies. Washington, DC. (Final release; series discontinued 2021.)