Governance (v1.0)

Subnational Grand Corruption Index

The Subnational Grand Corruption Perceptions Index (SGCI) provides a standardized measure of individuals’ perceptions of grand corruption at the subnational level. The SGCI is constructed using a Principal Component Analysis (PCA) of eleven corruption dimensions: executive, legislative, judicial, state institutions, taxation, authorities, local governance, politicians, civil service, severity of corruption, and government officials. Missing dimensions were imputed using chained regression models, leveraging relationships between dimensions across a dataset covering 807 surveys and 1,326,656 respondents from 1,473 subnational regions in 178 countries (1995–2022). Within dimensions, questions were harmonized to maximize cross-survey comparability.

The index is scaled from 0 (most corrupt area in the dataset) to 100 (least corrupt area), with higher values indicating lower levels of perceived grand corruption. Unlike the Subnational Petty Corruption Experiences Index (SPCI), which captures firsthand experiences of bribery, the SGCI reflects individual perceptions of corruption among high-level public officials and institutions.

By providing granular, subnational estimates of perceived grand corruption, the SGCI enables policymakers to identify systemic governance failures and develop institutional reforms that enhance accountability, reduce elite capture, and strengthen the rule of law. It is also valuable for researchers studying the drivers and consequences of corruption at a high level. Alternatively, one might be interested in perceptions explicitly, or in the discrepancy between expert and citizen perceptions. The SGCI is the first globally available and comparable index that fully isolates individual perceived grand corruption from petty corruption experiences, expert assessments, or composite measures.