What’s Wrong With the Corruption Perceptions Index

The Corruption Perceptions Index (CPI) is a widely used tool for evaluating perceived levels of public sector corruption across 180 countries. Compiled annually by Transparency International since 1995, the index scores nations on a scale from 0 (highly corrupt) to 100 (very clean) based on assessments by experts and business leaders. The 2023 CPI, covering the period from May 2022 to April 2023, places Denmark, Finland, and New Zealand at the top of the list, while Somalia, South Sudan, and Syria are ranked as the most corrupt. Investigative Journalism Reportika exposes critical methodological flaws and biases that undermine the reliability of the Corruption Perceptions Index, as detailed in the following sections.

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Methodological Flaws

1. Reliance on Perception-Based Data: The CPI’s reliance on perception-based data—collected from expert assessments and business leaders—leads to subjective scores influenced by media exposure and individual biases. For example, China, ranked 76th with a score of 42, has extensive government control over media, likely influencing business executives’ views and potentially leading to lower perceived corruption. In contrast, countries with a freer press receive higher corruption perceptions despite open reporting, highlighting the subjectivity inherent in perception-based scores.
   
   
2. Source Consistency and Cross-Country Comparability: The CPI requires a range of data sources that cover a global set of countries. However, in countries like Somalia, ranked 177th with a score of 13, and South Sudan, ranked 177th with 13, limited data availability leads to imputed scores that does not accurately reflect corruption. This process risks generalizations that oversimplifies the distinct corruption profiles of each nation, especially in regions with constrained data sources.
   
   
3. Standardization and Rescaling Issues: The CPI’s methodology involves standardizing scores on a scale from 0 to 100, where 0 is highly corrupt, and 100 is low corruption. Reversing scores from sources like the Economist Intelligence Unit creates inconsistencies, especially in countries like Brazil, ranked 104th with a score of 36, and India, ranked 93rd with 39, where regional corruption complexities differ significantly. This approach oversimplifies local dynamics, failing to capture the nuanced corruption issues within diverse national contexts.
   
   
4. Lack of Transparency in Private Source Data: Transparency International does not release original scores from private data sources, which limits transparency in CPI results. In countries like Saudi Arabia, ranked 53rd with a score of 52, and Qatar, ranked 40th with 58, restricted media environments influence executive perceptions. Without access to these original data points, it’s difficult to understand how these scores were derived or to critique their objectivity, which obscures the true corruption landscape.
   
   
5. Overemphasis on Public Sector Corruption: The CPI emphasizes public sector corruption, often missing corruption in the private sector and organized networks, which significantly affects corruption perceptions. In countries like Russia, ranked 141st with a score of 26, and Mexico, ranked 133rd with 29, private sector corruption and ties to organized crime play a significant role. By focusing predominantly on the public sector, the CPI understates corruption in nations where private sector misconduct is equally influential.
   
   

6. Inconsistent Sampling Across Regions: The CPI combines data sources with uneven coverage across different countries and regions, leading to regional biases. In Western countries like Sweden, ranked 6th with a score of 82, and New Zealand, ranked 3rd with 85, more comprehensive data sources ensure robust rankings. Conversely, in many Sub-Saharan African countries with limited data, the CPI relies on perception and imputed scores, which does not fully capture the region’s complex corruption challenges. This imbalance skews perceptions of corruption in lower-income nations where reliable data is scarce.

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Unexpected or Flawed discrepancies

• China (Rank: 76) vs. Trinidad and Tobago (Rank: 76): China, ranked 76th with a score of 42, is a highly centralized state where opaque governance and high-level corruption allegations are common. Trinidad and Tobago, which shares the same rank and score, faces corruption issues primarily at the bureaucratic level. The close ranking does not capture the vast difference in the scale and systemic nature of corruption, with China’s state policies operating in a far less transparent environment than Trinidad and Tobago’s more open governance.

• Vietnam (Rank: 83) vs. South Africa (Rank: 83): Vietnam, ranked 83rd with a score of 41, is governed with significant state control, allowing for persistent, high-level corruption that often goes unchecked. South Africa, also at 83rd with the same score, is a democratic nation where corruption is frequently exposed by a free press, and efforts toward transparency are ongoing. The equal rank here downplays South Africa’s institutional measures against corruption, which contrast with Vietnam’s centralized, politically influenced anti-corruption campaigns.

• United Arab Emirates (Rank: 26) vs. Taiwan (Rank: 28): The UAE, ranked 26th with a score of 68, operates with limited public oversight and extensive state control, placing it close to Taiwan, ranked 28th with 67 points. Taiwan, a democratic nation with stringent transparency standards, upholds stronger anti-corruption policies than the UAE. This close scoring overlooks Taiwan’s well-established institutional checks, compared to the UAE’s centralized, lower-transparency governance.

• Qatar (Rank: 40) vs. Portugal (Rank: 34): Qatar, ranked 40th with a score of 58, has less transparent governmental processes, while Portugal, ranked 34th with a score of 61, benefits from strong EU-backed anti-corruption frameworks and public accountability measures. The narrow score gap downplays the checks on power in Portugal, contrasting sharply with Qatar, where decision-making often occurs without similar transparency or public oversight.
  
  
• Russia (Rank: 141) vs. Uganda (Rank: 141): Russia and Uganda are both ranked 141st with a score of 26, yet the types of corruption differ significantly. Russia faces systemic corruption ingrained at high levels of government, with centralized control enabling widespread graft. Uganda’s corruption, while prevalent, is typically localized within its bureaucracy and lacks the organized scale seen in Russia. The similar score does not reflect these contrasting corruption dynamics, which vary greatly in scope and influence across their political systems.

Controversies

Following are the controversies surrounding the Corruption Perceptions Index (CPI) raised by different countries:

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• China: China has dismissed the CPI as biased and politically motivated, arguing that it disproportionately focuses on perceived corruption rather than measurable improvements. Chinese officials contend that the index overlooks their extensive anti-corruption campaigns, including the high-profile “Tigers and Flies” crackdown. They also accuse Transparency International (TI) of using Western-centric parameters that fail to account for cultural and governance differences.
  
  
• Russia: The Russian government views the CPI as an instrument of political pressure, claiming it unfairly portrays the country as highly corrupt. Officials argue that the index does not recognize Russia’s legal reforms or the work of its Anti-Corruption Directorate. Russia also criticizes the CPI’s heavy reliance on subjective perceptions, which it believes are influenced by geopolitical narratives.

The Corruption Perception Index (CPI) faces criticism for its methodology, which has raised concerns about accuracy and bias. Political scientist Dan Hough points out that corruption is a complex issue and cannot be adequately represented by a single score; for example, the types of corruption seen in rural Kansas differ vastly from those in New York City, yet the CPI scores them similarly. Experts also argue that relying on perceptions rather than tangible instances of corruption reinforces stereotypes and does not capture true corruption levels.

The CPI only assesses public sector corruption, neglecting significant cases in the private sector, such as the VW emissions scandal or the Odebrecht bribery case. Transparency International’s Global Corruption Barometer, which uses direct public surveys, has also been criticized for an elite bias. Additionally, some media misuse CPI scores as indicators of government performance without explaining the nuances, as seen when Bangladesh’s CPI scores improved due to a methodology change, which local media misinterpreted as reduced corruption. Furthermore, Alex Cobham in Foreign Policy argues the CPI fosters an elite-driven bias that can mislead public perception and policy. Transparency International warns that high CPI scores do not mean a nation is free from international corruption, as in Sweden’s case, where its state-owned TeliaSonera faced bribery allegations abroad despite Sweden’s high CPI ranking.

Global Corruption Barometer

Since its debut in 2003, Transparency International’s Global Corruption Barometer (GCB) has aimed to provide a public opinion survey that captures people’s direct experiences with and views on corruption worldwide. Unlike the Corruption Perceptions Index (CPI) discussed above, the GCB attempts to gauge corruption through everyday citizen experiences. However, IJ-Reportika’s analysis identifies several critical issues with the GCB’s methodology that raise questions about the reliability and validity of its findings.

Methodological Flaws in in the Global Corruption Barometer

• Insufficient Sample Sizes: The GCB’s sample sizes are alarmingly small compared to national populations, limiting the representativeness of its findings. For example:
  • China: With a population of about ~1.4 billion, only 4,068 participants were surveyed—representing approximately 0.00029% of the population.
  • India: Out of ~1.4 billion people, only 2,802 participants were included, accounting for a mere 0.0002% of the population.
  • Pakistan: Surveyed only 1,078 participants out of a population of over 230 million, roughly 0.00047%.
  • United Kingdom: With over 67 million people, only 1,004 respondents contributed, representing 0.0015% of the population.
  • Russia: With a population of nearly 146 million, only 1,507 participants were surveyed, which is about 0.001% of the population.
    
• Non-Representative Sampling: The limited number of participants, especially in large, diverse countries, risks producing non-representative results by under-sampling important demographic or geographic groups.
  
• Potential for Elite Bias: Responses from business and social elites reflects national biases, particularly in countries where political influences shape the public narrative on corruption.
  
• Inconsistent Definitions of Corruption: Varying individual interpretations of “corruption” undermine the GCB’s comparability across countries.
  
• Lack of Transparency on Sampling Methodology: Transparency International’s limited disclosure about how respondents are chosen raises questions about the GCB’s consistency and reliability across countries.

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The Corruption Perceptions Index (CPI) has long been a key reference for understanding global corruption trends, but its methodology and subjective nature raise critical concerns. While it sheds light on important issues, the CPI’s reliance on expert opinions and perceptions often overlooks ground realities and context-specific nuances. Addressing these flaws is essential to ensure that such indices serve as reliable tools for combating corruption rather than perpetuating misconceptions or influencing policy unfairly. A more robust, transparent, and inclusive approach is needed to accurately measure corruption and empower global efforts toward greater accountability and governance.