How IPI Intelligence
reconstructs the truth

What it measures

Quantifies unreported and underreported bilateral trade flows between Iran and its trading partners by analyzing systematic discrepancies in mirror trade statistics.

Data sources

• ■UN Comtrade bilateral trade database (182K+ records)
• ■IMF Direction of Trade Statistics (DOTS)
• ■World Bank WITS
• ■Partner country customs declarations

Methodology

Compares Iran's self-reported imports and exports against partner-country declarations for identical trade flows. Applies standard CIF/FOB adjustment (1.10x per IMF methodology) to account for shipping and insurance costs. Calculates a Shadow Trade Index (STI) per partner and per commodity code, where STI represents the proportion of trade not captured in Iran's official statistics. Iran ceased reporting to Comtrade after 2022, enabling detection of fully unreported trade flows in 2023–2024 using partner-only declarations.

Output

Shadow Trade Index by partner country and HS2 commodity code, annual time series (1998–2024), partner-level corridor rankings, and aggregate shadow economy estimates.

What it measures

Monitors capital movement patterns into and out of Iran using balance-of-payments data, central bank reserves, exchange rate differentials, and cross-border financial flow indicators.

Data sources

• ■IMF Balance of Payments (BOP)
• ■Bank Markazi (Central Bank of Iran) published data
• ■FRED (Federal Reserve Economic Data)
• ■World Bank financial indicators

Methodology

Triangulates official BOP data against observable capital movement proxies including parallel exchange rate spreads, foreign reserve changes, and trade-finance gap analysis. Models capital flight using the World Bank residual method and hot money methodology. Monitors the rial parallel market premium as a real-time stress indicator.

Output

Monthly capital flow estimates, flight risk indicators, parallel market premium tracking, and foreign reserve sustainability projections.

What it measures

A composite index (0–100) measuring the realized economic impact of international sanctions on Iran, disaggregated by sector.

Data sources

• ■US EIA oil production and export data
• ■OPEC market reports
• ■World Bank economic indicators
• ■FRED macroeconomic series
• ■UN Comtrade trade volumes

Methodology

Constructs a weighted composite from five sub-indices: energy production impact, trade volume suppression, financial sector isolation, technology access restriction, and GDP growth differential versus comparable economies. Benchmarked against pre-sanctions baselines (2000–2011) and peer-country controls (Turkey, Iraq, UAE). Sub-index weights reflect sector contribution to GDP.

Output

Quarterly composite index, sector-level sub-indices, effectiveness trajectory charts, and peer-country comparison tables.

What it measures

Maps the corporate ownership network of entities linked to the Islamic Revolutionary Guard Corps and its subsidiaries across Iran's economy.

Data sources

• ■OFAC SDN list and related sanctions designations
• ■EU consolidated sanctions list
• ■Donya-e-Eqtesad financial reporting
• ■Tehran Stock Exchange (TSETMC) corporate filings
• ■Open-source procurement records

Methodology

Builds an entity-relationship graph from sanctions designations, corporate registry data, and financial reporting. Identifies beneficial ownership chains, board-member overlaps, and procurement patterns. Cross-references with TSETMC listed companies to map publicly traded entities with IRGC linkages.

Output

Entity relationship maps, sector concentration analysis, sanctions exposure scoring, and ownership chain documentation.

What it measures

A composite 0–100 risk score assessing Iran's overall economic and investment risk environment, disaggregated into five sub-indices updated monthly.

Data sources

• ■All IPI algorithm outputs (mirror trade, capital flows, sanctions effectiveness)
• ■World Bank WDI (GDP, trade, inflation, unemployment)
• ■IMF WEO macroeconomic estimates
• ■EIA energy production data
• ■Central Bank of Iran published indicators

Methodology

Constructs a weighted composite from five sub-indices: economic risk (GDP growth, inflation, unemployment), trade risk (volume changes, partner diversification), sanctions risk (enforcement intensity, evasion capacity), financial risk (exchange rate pressure, capital flight, banking isolation), and market access risk (FDI flows, regulatory barriers). Each sub-index is normalized 0–100 and weighted by explanatory power. Monthly recalculation with trend classification (improving, stable, worsening).

Output

Monthly composite risk score, five sub-index time series (1990–present), trend analysis, risk band classification, and driver attribution.

What it measures

Scores each major economic sector (0–100) on readiness for foreign investment in a post-transition scenario.

Data sources

• ■World Bank WDI
• ■FAO agricultural data
• ■EIA energy infrastructure data
• ■IMF economic forecasts
• ■IPI proprietary analysis

Methodology

Evaluates five dimensions per sector: infrastructure condition (weighted from production data trends), regulatory complexity, workforce availability, market demand, and competitive positioning versus regional peers. Incorporates time-decay adjustments for infrastructure degradation under sanctions and benchmarks against reconstruction timelines in comparable economies.

Output

Sector-level readiness scores, investment prioritization matrix, risk-adjusted return estimates, and timeline projections.