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Harry Cassin
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Andy Spalding
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Jessica Tillipman
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Richard L. Cassin
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Elizabeth K. Spahn
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Cody Worthington
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Julie DiMauro
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Thomas Fox
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Marc Alain Bohn
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Bill Waite
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Russell A. Stamets
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Richard Bistrong
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Eric Carlson
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New corruption index adds forecasting

Measuring corruption across time is one of the most difficult tasks in governance studies. Early measures, like Transparency International’s CPI, focused on the perceptions of experts. More recently, however, governments, compliance officers, and investors have sought measures of corruption that provide greater forecasting abilities.

A new free corruption analysis tool, the Corruption Risk Forecast (CRF), provides both greater detail and predictive metrics. Developed through a partnership between two non-profits, the European Centre for Anti-Corruption and State-Building (ERCAS) and the Center for International Private Enterprise (CIPE), the CRF offers several advantages over previous corruption indices.

The CRF relies on 30 fact-based indicators directly linked to observed sources instead of subjective coding of non-numerical data, which varies from year to year. The data used in the CRF is granular and comprehensive, spanning from the accessibility of land or business ownership information to the online disclosure of government mining concessions.

Altogether, the CRF provides a broad-based and nuanced understanding of how 120 countries (with adequate data) manage — or don’t manage — corruption.

“We have a model of corruption, based on societal enablers and disablers, which allows us to predict where a country is going,” says Professor Alina Mungiu-Pippidi, Director of ERCAS, whose peer-reviewed academic work forms the basis of the forecast. “One example of enabler is fiscal transparency, while the lack of many citizens with broadband Internet connections (e-citizens) acts as a disabler. The data stretches 12 years back, and the trends interact in a model close to real-life, allowing us to predict evolutions for the near future.”

This information provides new analytical tools for compliance work. For example, a compliance officer tasked with assessing corruption risk for a new factory being built in Poland would be able to use the CRF to access free data on the evolution of administrative transparency over time or find a link to the government’s building permits page. They could also examine Poland’s public integrity context features against its neighbors or countries from the same income group to make more informed decisions.

Explore the data and detailed explanations of the methodology on the recently launched CRF website.

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