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Corruption Perceptions Index

The Corruption Perceptions Index (CPI) is an annual composite index published by that ranks 180 countries and territories by perceived , drawing on assessments from experts and executives across multiple sources. Launched in 1995, it assigns scores from 0, indicating highly corrupt conditions, to 100 for very clean governance, with aggregation involving rescaling and averaging of at least three sources per country to ensure robustness. The index has gained prominence as a for efforts, highlighting trends such as the persistent high rankings of , , and alongside low scores for countries like and , though global averages remain below 50, signaling entrenched challenges. Despite its influence on policy and public discourse, the CPI faces substantive critiques for conflating perceptions—potentially skewed by media amplification, Western-centric viewpoints in source institutions, or respondent biases—with empirical reality, thereby risking inaccurate portrayals of dynamics and perverse incentives in governance reforms.

History and Development

Origins with Transparency International

was established in 1993 by Peter Eigen, a retired official who had observed corruption's pervasive impact during his tenure managing development programs in . Eigen, along with nine co-founders, created the Berlin-based nongovernmental organization to expose corrupt practices, advocate for in , and mobilize global action against and graft, at a time when international efforts to address corruption were minimal and lacked systematic measurement. In 1995, two years after its founding, introduced the Corruption Perceptions Index (CPI) as its inaugural research tool to quantify and publicize perceptions of . The index aggregated data from existing expert assessments and surveys, initially covering 45 countries with scores derived from perceptions of , kickbacks, and other corrupt acts in and . This launch aimed to elevate from an overlooked issue to a measurable barrier to and democratic stability, providing a comparative ranking that highlighted stark disparities, such as high-corruption nations in and versus cleaner in . Under Eigen's chairmanship from 1993 to 2005, the CPI's origins underscored Transparency International's emphasis on perception-based metrics to influence policy, as actual data was scarce and enforcement mechanisms absent globally. Early editions, like the 1995 index, explicitly tied low scores to impoverishment and reduced public services, arguing that unchecked diverted resources from essential sectors such as and . The initiative's design reflected a pragmatic approach, relying on available survey sources rather than direct empirical audits, which Eigen described as a means to compel governments and international bodies to prioritize reforms.

Key Milestones and Methodological Shifts

The Corruption Perceptions Index (CPI) was first published on October 4, 1995, by , ranking 45 countries and territories based on aggregated perceptions of drawn from five independent surveys and expert assessments conducted primarily in 1994. This inaugural edition established the index as a composite measure without a formal statistical aggregation formula, relying instead on simple averaging of available source data, and scored countries on a 10-point scale where 10 indicated least corrupt. Subsequent annual editions expanded coverage progressively, reaching 91 countries by 2001 and exceeding 100 by the mid-2000s, as additional global surveys became available and incorporated more data sources to broaden representation, though early methodologies retained the 0-10 scale and allowed inclusion of older data without strict temporal limits. By 2011, the index covered 182 countries, but comparability across years remained limited due to varying numbers of sources (sometimes as few as one per country) and inconsistent standardization, which could introduce volatility from source fluctuations rather than genuine changes in corruption perceptions. In 2012, implemented a comprehensive methodological revision following an expert review to improve reliability and enable . Key changes included rescaling to a 0-100 (0 highly corrupt, 100 very clean), restricting sources to those published within the prior two years for timeliness, mandating a minimum of three sources per , and adopting a standardized z-score aggregation process using raw source data to minimize bias from disparate scales. This shift discontinued backward comparability with pre-2012 scores but allowed for consistent monitoring thereafter, as the framework has since emphasized statistical robustness over ad hoc adjustments. Minor refinements have occurred post-2012, such as the 2024 update to the aggregation parameters for the World Economic Forum's Executive Opinion Survey due to its revised sampling methodology, which adjusted the baseline year but preserved overall score stability and cross-year equivalence. These evolutions reflect ongoing efforts to adapt to evolving data availability while prioritizing empirical aggregation over subjective weighting.

Expansion and Global Adoption

The Corruption Perceptions Index (CPI), first published by in 1995, initially evaluated perceived public-sector corruption in 45 countries and territories based on available expert assessments and business surveys. By 1998, coverage had expanded to 85 countries, reflecting increased data availability from additional sources and growing interest in systematic corruption measurement; this rose further to 99 countries in 1999 as incorporated more international risk assessments and domestic surveys. The index's scope continued to broaden throughout the , surpassing 160 countries by 2009, driven by the proliferation of global datasets from organizations like the and private risk consultancies, enabling broader aggregation while maintaining methodological consistency in rescaling perceptions to a common scale. By the 2024 edition, the CPI encompassed 180 countries and territories, providing near-global coverage and facilitating cross-country comparisons amid rising demand for governance benchmarks. This expansion paralleled the CPI's swift global adoption as a for , with annual releases quickly amplified by international media, prompting public discourse and policy scrutiny in affected nations. reported that the index's debut triggered widespread coverage, elevating from a peripheral issue to a central topic in global development agendas, including influences on aid allocation by donors and reforms in emerging markets. Its integration into reports by bodies like the and underscored its role in shaping strategies, though adoption has been critiqued for over-relying on perceptions rather than verified incidents, potentially skewing priorities toward visible bureaucratic graft over entrenched . By the , the CPI informed national integrity systems in over 100 countries, with governments citing rankings to justify legislative changes, such as laws in and , while businesses used scores for investment risk assessments. The index's proliferation also coincided with Transparency International's organizational growth, establishing over 100 national chapters by 2020 that localized CPI insights into advocacy, further embedding the metric in regional policy debates despite source biases in expert surveys favoring Western perspectives. This global uptake has sustained the CPI's annual production, with methodological refinements—like the shift to a 0-100 —enhancing comparability and without altering core perceptual foundations.

Methodology

Source Data Selection and Sources

The Corruption Perceptions Index selects data sources that provide quantitative assessments of public sector corruption perceptions based on expert evaluations or business surveys. To qualify, sources must meet four key criteria: they must measure perceptions of corruption in the public sector; employ a robust and transparent methodology; encompass multiple forms of corruption, such as bribery, diversion of public funds, and abuse of public office; and have been published within the previous two years to ensure timeliness. These standards aim to prioritize data from independent institutions with demonstrated expertise in governance and risk analysis, excluding sources reliant on unverified anecdotal evidence or lacking comparability across countries. For inclusion in a given year's CPI, a or must appear in at least three qualifying sources to enable aggregation while minimizing coverage gaps; in practice, the draws from up to 13 sources per edition, sourced from 12 distinct providers to diversify inputs and reduce single-source dominance. The 2024 CPI utilized the following 13 sources, each capturing perceptions through surveys of executives, experts, or risk analysts:
  • African Development Bank Country Policy and Institutional Assessment (2023): Expert ratings on transparency and in 54 African countries.
  • Bertelsmann Stiftung Sustainable Governance Indicators (2024): Assessments of prevention in 30 and countries.
  • Bertelsmann Stiftung Transformation Index (2024): Expert surveys on enforcement in 137 developing and economies.
  • Economist Intelligence Unit Country Risk Service (2024): Evaluations of and budget transparency risks in 131 countries.
  • Freedom House Nations in Transit (2024): Qualitative reviews of anti- efforts in 29 post-communist states.
  • Global Insight Country Risk Ratings (2023): Business risk scores for 209 countries.
  • IMD World Competitiveness Yearbook (2024): Executive opinions on prevalence in 67 economies.
  • Political and Economic Risk Consultancy Asian Intelligence (2024): Surveys on issues in 16 countries.
  • The PRS Group International Country Risk Guide (2024): risk assessments for 140 countries.
  • World Bank Country Policy and Institutional Assessment (2023): Staff evaluations of accountability in 74 low-income countries.
  • World Economic Forum Executive Opinion Survey (2024): Business leader views on and fund misuse in 117 countries.
  • World Justice Project Rule of Law Index (2024): Expert questionnaires on public office abuse in 142 countries.
  • Varieties of Democracy (V-Dem) dataset (version 14, 2024): Coded expert assessments of in 179 countries.
This selection process favors data from multilateral organizations, think tanks, and commercial risk providers, though it excludes certain formerly used sources (e.g., GAN Integrity reports after ) due to discontinued direct data provision. periodically reviews source eligibility to maintain methodological consistency, with external validations confirming the approach's robustness for perception-based ranking.

Rescaling and Aggregation Processes

The rescaling of source data in the Corruption Perceptions Index (CPI) standardizes disparate scales from individual surveys or assessments into a uniform 0–100 range, where 0 indicates a of highly corrupt public sector practices and 100 indicates very clean practices. For each selected source, raw country scores are first converted to z-scores by subtracting the source's global mean score and dividing by its global standard deviation, ensuring comparability across sources with varying measurement approaches and distributions. These z-scores are then mapped to the CPI's anchor scale derived from the 2012 edition, which had a global mean of 45 and standard deviation of 20: the rescaled score equals the z-score multiplied by 20 and added to 45. Values below 0 are set to 0, and those exceeding 100 are capped at 100, preserving the relative positioning while anchoring to historical continuity. Aggregation follows rescaling by computing an unweighted of the rescaled scores from all eligible sources covering a given or , typically requiring at least three sources for inclusion to ensure reliability. Eligible sources must provide data from the previous two calendar years and meet 's criteria for expert or business perceptions of corruption, excluding those focused on or petty alone. This averaging process yields the final CPI score, with no additional weighting applied to sources despite variations in their sample sizes or methodologies, a choice justified by to treat each source as an equally valid perception signal but criticized for potentially amplifying outliers from less robust datasets. The aggregated score is accompanied by a , calculated as approximately two standard errors (reflecting 95% uncertainty bounds), derived from the standard deviation of the rescaled source scores for that . This , updated in to emphasize the 0–100 scale continuity, aims to mitigate year-to-year volatility from source fluctuations but introduces dependency on the arbitrary 2012 anchor, which may embed historical perception biases into subsequent indices without adjustment for evolving global corruption dynamics. Parallel independent calculations by staff verify the rescaled and aggregated results, with discrepancies resolved through review to maintain procedural .

Uncertainty Reporting and Score Calculation

The Corruption Perceptions Index (CPI) score for a or is calculated as the simple average of the rescaled scores derived from the selected data sources, with a minimum requirement of three sources to ensure reliability. The rescaled scores are standardized to a 0-100 scale, where 0 indicates highly corrupt and 100 very clean, using a transformation based on the 2012 global mean (45) and standard deviation (20) of the CPI for cross-source comparability: rescaled score = (z-score × 20) + 45, with values capped at 0 or 100. Final scores are rounded to the nearest whole number. Uncertainty in the CPI score arises from variability across the limited number of data sources (typically 3 to 13 out of a total pool of 13), reflecting differences in and perceptions. A (Σ) quantifies this uncertainty and is computed using the formula Σ = [(N - n)/(N - 1)] × (σ / √n), where N = 13 (total available sources), n = number of sources covering the country, and σ = standard deviation of the rescaled scores for that country. This incorporates a finite correction factor to adjust for the small total source pool, providing a more accurate estimate of sampling variability than a simple of the mean. The reported measure of uncertainty includes a 90% , calculated as the CPI score ± (1.645 × Σ), which captures the range within which the true score is likely to lie given source discrepancies. For instance, wider intervals occur for countries with fewer sources or greater source disagreement, signaling higher uncertainty in rankings. These intervals are published alongside scores to emphasize that the CPI measures perceived with inherent imprecision, not absolute levels. for year-over-year changes is assessed if the confidence intervals exclude zero, using metrics like Cohen's d.

Validity Assessments Within the Framework

assesses the validity of the Corruption Perceptions Index (CPI) within its perceptual framework by selecting data sources that demonstrate methodological reliability, institutional reputation, and conceptual alignment with perceptions, including , , and diversion of public funds. Sources must employ documented collection methods, provide quantitative granularity with at least a four-point scale, ensure cross-country comparability, and offer multi-year data for . This selection process aims to capture consistent expert and views on levels over the past two years, with a minimum of three sources required per country to mitigate single-source distortion. Individual sources incorporated into the CPI undergo checks, such as s by country experts, regional coordinators, and advisory boards to verify score plausibility and alignment with qualitative evidence. For instance, the Stiftung's Transformation Index employs a six-stage for expert evaluations, while the Development Bank's Country Policy and Institutional Assessment features phased endorsements through sector experts and open discussions. At the aggregation level, conducts parallel independent calculations by in-house researchers and academic advisors, followed by to confirm accuracy and comparability. To quantify aggregation validity, the CPI reports uncertainty through standard errors and 90% intervals, reflecting inter-source variability and potential inconsistencies in perceptions. The methodological revision standardized rescaling using global means and standard deviations, enabling year-to-year comparability, with robustness evaluated by the European Commission's in 2017. These measures position the CPI as a reliable composite of perceptions, though limited to domains assessed by established institutions like the and . Academic analyses have tested the CPI's foundational assumptions of source independence and equal weighting, finding evidence against them based on 2016 data from 176 countries, where individual sources exhibited unequal impacts and correlations, such as close alignment with the World Bank's Control of Corruption indicator. This suggests potential overemphasis on dominant source clusters, undermining the framework's claim of balanced perceptual aggregation, though proponents argue the multi-source approach still yields coherent rankings. No comprehensive internal consistency metrics, such as across sources, are publicly detailed by .

Scoring and Rankings

Annual Score Computation and Ranking

The Corruption Perceptions Index (CPI) score for each is computed annually by through a multi-step aggregation of perception-based data from independent sources. Eligible sources, limited to a maximum of 13 per edition, are selected based on criteria including methodological rigor, focus on corruption (such as and ), quantitative scoring with at least four points on a scale, cross-country comparability, and coverage of no fewer than 16 countries. These sources typically include assessments from institutions like the and , with data drawn from publications in the preceding two years to maintain timeliness. A qualifies for only if it features in at least three such sources, resulting in coverage of approximately 180 countries and territories each year. Raw data from selected sources undergo to ensure uniformity. Scales are reversed for any sources where higher values indicate less , and values are imputed using statistical methods referenced to a year (originally , with updates for changes like those in data). Each source's scores are then transformed into z-scores (with 0 and standard deviation 1) using the baseline year's global parameters, followed by rescaling to a 0-100 index where 0 denotes highly corrupt perceptions and 100 very clean. The final CPI score is the simple average of these rescaled values across the available sources for the country, rounded to the nearest whole number; imputed values are excluded from this averaging to prioritize observed data. This process incorporates quality controls, including independent parallel calculations by staff. Uncertainty in the score is quantified via a and 90% , derived from the formula for adjusted for the number of sources (σ/√n, with finite population correction where n is the number of sources for the country and N=13 total sources). of year-over-year changes is assessed using effect sizes like Cohen’s d and Hedges’ g, with only changes reflected across a majority of sources deemed meaningful. The , revised in for enhanced comparability, has remained consistent since, enabling longitudinal analysis despite annual updates to source data. Rankings are assigned by ordering countries in descending order of their CPI scores, with awarded to the highest-scoring (least corrupt perceived) country. Ties in scores lead to shared ranks, and the total number of ranked entities (around 180) can fluctuate slightly based on coverage. Annual CPI releases, typically in January or February, reflect aggregated perceptions from the prior period and include notations for statistically insignificant shifts to caution against overinterpreting minor variations. This ranking process prioritizes relative positioning but is sensitive to the inclusion or exclusion of countries due to availability.

2024 Scores and Global Overview

The Corruption Perceptions Index (CPI) for 2024, released by on February 11, 2025, evaluates perceived levels of public sector corruption in 180 countries and territories on a scale from 0 (highly corrupt) to 100 (very clean), aggregating data from 13 independent sources including expert assessments and business surveys. The global average score stood at 43, unchanged from prior years, indicating persistent stagnation in efforts worldwide. More than two-thirds of countries scored below 50, highlighting widespread perceptions of corruption as a barrier to effective and . Denmark maintained its position as the least corrupt nation with a score of 90, marking the seventh consecutive year at the top, followed closely by at 88 and at 84. Other high performers included (83), , , and (all 81), (80), and the (78). At the opposite end, scored the lowest at 8, with (9) and (10) rounding out the bottom three, reflecting entrenched challenges in conflict-affected and authoritarian regimes. Additional low scorers encompassed (12), several African states like , , and (all 13), and others such as (13), (14), , and (both 15). Since the 2012 baseline, only 32 countries have shown meaningful improvement in their scores, while 148 have stagnated or declined, underscoring a lack of progress in global measures despite increased awareness. Regional variations persist, with full democracies averaging 73 points compared to 47 for flawed democracies and 33 for non-democratic regimes, suggesting a between institutional and lower perceived . The region saw a modest 1-point increase to 39, its first in over a , though and the experienced a second consecutive year of decline. The Corruption Perceptions Index (CPI), initiated in 1995 by Transparency International, tracks annual perceptions of public sector corruption across countries, revealing broad stagnation in scores over time. The global average has hovered below 50 since the early 2000s, with two-thirds of countries scoring under that threshold in recent editions, indicating persistent high perceptions of corruption in most nations. While methodological changes, such as rescaling to a 0-100 range in 2012, complicate direct pre-2012 comparisons, post-2012 data show that only a minority of countries have achieved statistically significant improvements, often linked to targeted anti-corruption reforms, whereas many others exhibit flat or declining trajectories. High-performing countries, particularly in , have demonstrated exceptional stability. Denmark's CPI score averaged 92.8 from 1995 to 2024, peaking at 100 in 1998 and stabilizing around 90 in the 2020s (90 in 2023 and 2024). maintained scores of 87-88 from 2021 to 2023, while held steady at 84-85 over the same period. These consistent high scores reflect entrenched institutional strengths, including transparent and effective enforcement, though minor fluctuations occur due to varying expert assessments. , another perennial leader, scored 83-85 in recent years, building on earlier gains from rigorous policies implemented since the 1960s. A subset of countries has recorded notable score increases since , frequently attributed to leadership-driven reforms. Uzbekistan improved from 17 in to 28 in 2021, with continued progress linked to post-2016 liberalization efforts reducing . identifies 32 countries with significant gains over this timeframe, including and , where and enhancements correlated with higher perceptions among surveyed experts. Such improvements, however, remain exceptions, as causal links between policies and perception shifts require validation beyond aggregate indices, given the CPI's reliance on subjective expert and business surveys potentially influenced by media narratives. Declines in scores have affected even established low-corruption jurisdictions, signaling potential erosions in public trust. New Zealand's score fell from 88 in 2021 to 85 in 2023, amid concerns over political integrity. The United States dropped to 65 in 2024, a decline from mid-70s levels in the 2010s, coinciding with polarized governance perceptions. Over the preceding five years to 2024, 13 countries saw significant deteriorations, including Austria (to 67) and Canada (to 75), often tied to weakening accountability mechanisms in TI's analysis. These trends underscore the CPI's sensitivity to elite opinion shifts, which may amplify or lag actual institutional changes, necessitating cross-verification with objective corruption incident data for causal inference.

Regional and Subnational Variations

The Corruption Perceptions Index (CPI) exhibits pronounced regional disparities, with and the consistently achieving the highest average scores, reflecting stronger institutional frameworks and enforcement mechanisms, though scores have declined for the second consecutive year due to weakening . In contrast, records the lowest regional average of 33 out of 100 in 2024, attributed to entrenched networks, resource mismanagement, and inadequate across many nations. The Americas average 42, hampered by and infiltration in public institutions, while the saw a marginal increase to 39—the first rise in over a decade—amid ongoing authoritarian consolidation and conflict-driven graft. scores have trended downward, with regional leaders failing to curb elite influence despite in select areas, and and rank as the second-lowest, exacerbated by autocratic governance and fragile .
Region2024 Average CPI Score
33
42
& 39
These regional patterns correlate with structures, where stronger democracies in yield lower perceived (averaging around 70 historically, though precise 2024 figures remain unspecified in aggregates), versus non-democratic regimes globally averaging 33. Subnational variations within countries further underscore that national CPI scores mask heterogeneous corruption risks, often higher in remote, resource-dependent, or politically marginalized areas. The Comprehensive Subnational Corruption Index (SCI), aggregating data from 807 surveys spanning 1995–2022 across 1,473 subnational units in 178 countries, decomposes corruption into grand () and petty (everyday bureaucratic) components, revealing systematic intra-country divergences driven by local institutional capacity and economic incentives. For instance, the SCI indicates elevated corruption in peripheral regions of federal states like and , where weaker oversight amplifies petty compared to urban or southern cores with better . Such granular measures highlight causal factors like decentralized power without checks, contrasting uniform national perceptions in CPI aggregation. Empirical studies using subnational data confirm these variations predict localized outcomes, such as reduced delivery in high-corruption provinces, independent of national trends.

Empirical Validity and Criticisms

Perceptions Versus Actual Corruption Measurement

The Corruption Perceptions Index (CPI) aggregates subjective assessments of corruption from surveys of executives, risk analysts, and experts, rather than direct observations of corrupt acts. These perceptions are drawn from sources such as the World Economic Forum's Executive Opinion Survey and the World Bank's enterprise surveys, which capture opinions on bribe payments, favoritism in decisions, and legal system efficacy. However, actual —defined as the abuse of public power for private gain—involves clandestine transactions like kickbacks or , making objective quantification difficult without comprehensive audits or victim surveys, which are rare at the national level. Empirical studies reveal that perceptions correlate modestly with proxies for actual but are distorted by non-corruption factors. In a 2006-2007 of village projects, villagers' perceptions of aligned with objectively measured "missing expenditures" (averaging 24% of budgets), yet the link was weak: a 10% rise in missing funds increased the probability of perceiving by only 0.8 percentage points, after controlling for baseline views. Perceptions were further biased by demographics (e.g., linked to 5-7% greater perceived per year of schooling) and village traits like ethnic fragmentation, which inflated reports without corresponding rises in actual losses. Similarly, cross-country analyses show experiences (e.g., reported bribe incidence from firm surveys) predict CPI scores with small effect sizes—a 10% increase in experience shifts indices by less than 0.5 standard deviations—while confounders like GDP and Protestant cultural traditions independently lower perceived by up to 1-2 points on the 0-10 scale. Critics argue these discrepancies undermine CPI's reliability as a corruption gauge, as perceptions often reflect media salience, recent scandals, or stereotypes rather than incidence rates. For instance, low-income countries face a "poor is bad" , where amplifies assumed independent of evidence, while informational cascades—respondents echoing prior rankings—perpetuate inertia in scores. Objective alternatives, such as petty frequencies from household surveys or via public procurement data, show inconsistent alignment; some nations rank high in CPI despite elevated audit-detected irregularities, suggesting elite-sourced perceptions overlook graft. Although CPI correlates with indirect outcomes like rates among small firms, its aggregation masks such gaps, potentially misguiding policy toward visibility over prevalence.

Methodological Biases and Elite Influence

The Corruption Perceptions Index (CPI) derives its scores from aggregated surveys of business executives and country experts, creating a methodological reliance on perceptions that systematically underrepresents experiences of average citizens. This -centric approach favors assessments of grand-scale issues, such as in or favoritism in policy-making, which directly impact international commerce, while downplaying petty in service delivery that affects daily life in both low- and high-income settings. For instance, in nations scoring highly like (rank 6, score 82 in 2023), respondents report low due to efficient high-level , yet citizen-facing bureaucratic graft may persist undetected in these metrics. Elite influence manifests through the selection and incentives of respondents, many of whom operate in business networks prioritizing regulatory predictability and ease over granular enforcement. These groups' views can be shaped by amplification of scandals—disproportionately in countries with open presses—rather than comprehensive evidence, as seen in comparable scores for disparate cases like (rank 76, score 42) and (rank 76, score 42) in recent editions, despite vast differences in systemic scale. Inconsistent regional sampling exacerbates this, with denser elite coverage in yielding more favorable imputations compared to data-sparse areas like , where limited inputs lead to extrapolated low scores without robust verification. Further biases arise from effects, where respondents anchor judgments to prior CPI rankings or economic stereotypes, fostering self-perpetuating narratives decoupled from on-ground realities. A documented "poor is bad" effect compounds this, with CPI scores correlating tightly to GDP levels, attributing perceived to itself rather than isolated acts—evident in studies showing subjective assessments influenced by national wealth irrespective of control variables for governance quality. is strained by opaque private datasets from organizations like risk consultancies, which may embed Western-centric priors favoring market-liberal models, as many contributing bodies (e.g., ) originate from or align with such perspectives, potentially undervaluing alternative institutional adaptations in non-Western contexts.

Empirical Correlations and Causal Limitations

The Corruption Perceptions Index (CPI) exhibits a strong positive with GDP levels across countries, with studies estimating that a one standard deviation increase in perceived (reversed CPI) is associated with a long-run decline in real GDP of approximately 17%. Similarly, higher CPI scores correlate with faster rates, as evidenced by analyses showing that reductions in perceived contribute to cumulative GDP gains over time, though the magnitude varies by institutional context. The index also positively correlates with indicators, with correlation coefficients of 0.33 for developed economies and 0.46 for developing ones, suggesting that perceptions of low align with stronger legal frameworks that enforce . These correlations extend to other development outcomes, including lower and higher public investment efficiency, where countries with CPI scores above 70 tend to allocate more resources to and without significant leakage. However, such associations are derived from perception-based aggregated from and surveys, which may reflect media coverage or cultural biases rather than objective incidence, leading to overestimation of links in media-heavy environments. Causal inference from CPI to economic outcomes remains limited due to endogeneity and reverse causality; wealthier nations with robust institutions may foster perceptions of low independently of actual bribe levels, as economic prosperity enables better enforcement and . tests indicate bidirectional relationships, where GDP growth can precede improvements in CPI scores by enhancing institutional quality, challenging claims that anti-corruption perceptions alone drive . Confounding variables, such as colonial history or , further complicate attribution, with some analyses showing that CPI variations explain only a fraction of growth differences after controlling for depth. Methodological constraints in CPI construction exacerbate causal ambiguities, as the index aggregates sources with potential interdependencies—e.g., risk assessments that incorporate —creating feedback loops that inflate apparent effects without isolating corruption's unique role. Empirical models attempting variables, like historical prevalence as a for institutional persistence, yield mixed results on directionality, underscoring that perceptions serve as proxies for broader rule-of-law clusters rather than direct causal drivers of outcomes. Thus, while CPI highlights associative patterns, policymakers risk misattributing , potentially overlooking structural reforms in favor of perception-focused interventions with unproven impacts.

Specific Controversies and Case Studies

One notable involves 's persistently high CPI rankings despite significant scandals linked to state-influenced entities. In 2015, ranked fourth with a score of 89 out of 100, yet TeliaSonera, a partially state-owned firm (with the Swedish government holding a substantial stake through the state pension fund), faced revelations of paying approximately $300 million in bribes to Uzbekistan officials between 2000 and 2007 to secure mobile licenses. The , exposed in 2012 and leading to executive resignations and fines exceeding $1 billion by 2017, highlighted grand in international operations but did not immediately erode 's CPI score, illustrating a between revealed facts and expert/business perceptions aggregated by the index. Critics argue this reflects an elite bias in CPI sources, where domestic low-level perceptions overshadow transnational corporate misconduct involving public entities. Hungary's declining CPI scores have sparked accusations of methodological and ideological bias against non-Western-aligned governance models. Hungary scored 42 in the 2022 CPI, the lowest among EU states, prompting the government to establish the Integrity Authority on October 3, 2022, to audit EU funds and counter perceptions of graft. Hungarian analysts contend that the score derives from subjective inputs by opposition-leaning domestic experts and international surveys influenced by media narratives critical of Prime Minister Viktor Orbán's administration, rather than empirical upticks in corruption, as evidenced by stable conviction rates and recovered assets from past probes. This case underscores discrepancies where CPI aggregates overlook contextual factors like centralized procurement reforms aimed at efficiency, potentially conflating policy choices with corruption, while sources like Transparency International Hungary emphasize unchecked executive power as the driver. In , official responses have labeled the CPI as geopolitically motivated, with scores around 42 (ranking 76th in 2023) dismissed despite President Xi Jinping's anti-corruption campaign since 2012, which prosecuted over 1.5 million officials by 2020 for and . argues that controlled media reduces scandal visibility, artificially stabilizing perceptions downward, while ignoring systemic reforms like the established in 2018, which expanded oversight beyond the . Similar critiques from , scoring 26 (141st in 2023), highlight how CPI's reliance on Western-sourced data penalizes state-led economies, contrasting localized graft in comparator nations like at the same score, where verifiable scandals are more media-exposed. These disputes reveal causal limitations in perception-based metrics, where source selection—favoring outlets potentially biased against authoritarian systems—may embed unacknowledged priors over objective indicators like enforcement statistics.

Relationships to Broader Phenomena

Numerous empirical studies document a strong negative correlation between Corruption Perceptions Index (CPI) scores and economic growth indicators, with countries exhibiting higher perceived public-sector corruption (lower CPI scores) experiencing slower GDP growth and lower per capita income levels. For example, cross-country regressions show that the unconditional correlation between reversed CPI values (where higher numbers denote greater perceived corruption) and the logarithm of real per capita GDP stands at -0.71, indicating that nations perceived as more corrupt tend to have substantially lower economic output. This pattern holds particularly in developing economies, where perceived corruption is associated with reduced investment efficiency, distorted resource allocation, and heightened uncertainty for businesses, collectively impeding long-term development. Long-run estimates from analyses further quantify the impact: a one-standard-deviation increase in perceived (reversed CPI) is linked to approximately a 17% decline in real per capita GDP over time, with the effect amplified in countries featuring low rates or weak institutions. Similarly, in regions like , higher CPI scores (indicating lower perceived ) correlate positively with annual GDP growth rates, as evidenced by fixed-effects models controlling for country-specific factors, suggesting that reduced bribery and enhance productivity and . have echoed these findings, noting that less corrupt environments (higher CPI scores) boost fiscal revenues through improved tax compliance and attract greater , thereby supporting sustained development trajectories. Beyond growth rates, CPI scores exhibit robust associations with broader development metrics, such as formation and quality; for instance, economies with CPI scores above 70 (e.g., and ) consistently rank higher in innovation indices and , while those below 40 face persistent stagnation. These links underscore how perceived erodes public trust in institutions, diverting resources from productive uses like and to , though reverse —where economic prosperity itself lowers corruption perceptions—complicates direct attribution. Empirical evidence from governance-focused regressions reinforces that reforms improving CPI rankings can yield measurable gains in , particularly when paired with institutional strengthening.

Connections to Justice Systems and Rule of Law

Empirical analyses have identified a positive correlation between Corruption Perceptions Index (CPI) scores and indicators, with coefficients ranging from 0.33 in developed countries to 0.46 in developing nations, indicating that stronger legal frameworks and enforcement mechanisms are associated with perceptions of lower corruption. The World Justice Project's Index, which assesses factors like constraints on government powers and absence of , overlaps significantly with CPI methodology, as both rely partly on expert assessments of institutional integrity. A weakening of systems globally since has coincided with stagnating or declining CPI scores in many countries, where inadequate and enforcement enable for corrupt actors. For instance, in regions like the , assaults on judicial autonomy—such as political interference in appointments—have been linked to higher perceived , as courts fail to hold powerful elites accountable, perpetuating cycles of and favoritism. This bidirectional dynamic is evident: erodes public in legal institutions by fostering , while frail mechanisms, including delayed trials and low conviction rates for graft, amplify perceptions of systemic graft. Studies emphasize that serves as a causal against , with de facto autonomy—measured by tenure security and budgetary control—correlating more strongly with reduced bureaucratic malfeasance than formal legal provisions alone. In high-CPI nations like those in , robust prosecutorial organs and internal judicial checks minimize , contrasting with low-scoring states where politicized courts shield incumbents, as seen in case analyses of and . However, CPI's reliance on perceptions introduces potential bias, as amplification of high-profile judicial scandals in otherwise functional systems may inflate scores downward, underscoring the index's limits in isolating causal efficacy from visibility effects.

Comparisons with Alternative Corruption Indices

The Corruption Perceptions Index (CPI), produced annually by since 1995, aggregates perceptions of public-sector corruption from business executives and country experts across multiple third-party sources, yielding scores from 0 (highly corrupt) to 100 (very clean). In comparison, the World Bank's Control of Corruption (CoC) indicator, part of the (WGI) dataset introduced in 1996 and updated biannually, also relies primarily on subjective assessments but draws from a broader array of 30+ sources, including surveys of households, firms, and cross-country investor assessments, alongside expert polls. Both indices exhibit high static cross-sectional correlations, often exceeding 0.9, reflecting similar reliance on elite and business perceptions of grand corruption, though CoC incorporates some diplomatic and risk-rating data that may capture more comprehensively. However, they diverge in longitudinal changes; for instance, panel-adjusted analyses show CPI and WGI CoC yielding inconsistent trends over time for the same countries, with CPI more sensitive to media-driven perception shifts.
IndexOrganizationBasisKey SourcesGranularity and Coverage
CPIPerceptions (expert/business)13+ surveys/polls (e.g., , Foundation)Aggregate public-sector score; 180 countries annually since 2012
CoC (WGI)Perceptions with some risk assessments30+ sources (e.g., , Political Risk Services)Aggregate control over corruption; 200+ countries/territories biannually
V-Dem Corruption IndicesVarieties of Democracy ProjectExpert-coded perceptions3,000+ country experts per variableDisaggregated (e.g., bribery, public-sector ); 202 countries from 1789-present
The Varieties of Democracy (V-Dem) project's corruption measures, developed since , offer a more disaggregated alternative through expert-coded data on specific corruption forms—such as , , and in executive, legislative, judicial, and public sectors—calibrated with models to reduce individual bias. Unlike the CPI's singular composite, V-Dem's indices (e.g., index scaling 0-1, higher indicating more corruption) enable analysis of corruption subtypes and show weaker correlations with CPI in dynamic panels, highlighting cases where CPI stability masks V-Dem-detected shifts in petty versus grand corruption. V-Dem's expert recruitment emphasizes diverse ideological backgrounds and cross-validation, potentially mitigating the elite echo-chamber effect in CPI sources, which often overweight business views of bribe-paying for contracts over undetected low-level graft. Efforts at objective alternatives remain limited due to corruption's clandestine nature, which hinders verifiable data collection; for example, the Index of Public Integrity (IPI), launched in 2015 by the Government Transparency Institute, uses administrative proxies like anti-corruption laws, press freedom, and scores to forecast corruption risk, correlating moderately with CPI (around 0.7) but avoiding perceptions entirely. Such proxies reveal CPI's conflation of corruption with broader governance failures, as perception indices like CPI and often proxy institutional quality rather than incidence rates, with business surveys biased toward high-value interactions in developing economies. Comparative studies underscore that while CPI ranks correlate with and V-Dem aggregates, they underperform in , as perceptions lag actual reforms (e.g., post-audit detections) and amplify biases from source selection, where Western-dominated expert pools undervalue cultural variances in informal norms.

Impact and Policy Considerations

Influence on International Aid and Investment

The Corruption Perceptions Index (CPI) is frequently referenced by international donors and organizations as a for assessing risks in aid recipient countries, with lower scores prompting calls for enhanced conditionality or measures in distribution. For example, following the release of CPI rankings, policymakers have advocated for revamping foreign strategies to prioritize countries with higher perceived integrity, as seen in discussions around Afghanistan's low scores in the early . However, empirical evidence reveals limited actual impact on (ODA) flows; a cross-country analysis by Alesina and Weder (1999) found that governments perceived as corrupt, as proxied by similar indicators, receive no less than those viewed as honest, suggesting donors prioritize geopolitical or strategic factors over perceptions. In contrast, the CPI exerts a more discernible influence on (FDI), where lower scores signal heightened risk and deter inflows. Egger and Winner (2006) analyzed bilateral FDI among countries and determined that corruption perceptions, measured via the CPI, impose a negative effect on investment volumes, with a one-standard-deviation increase in perceived reducing FDI by approximately 10-15%. Complementary studies confirm this pattern: higher CPI scores correlate positively with FDI, as investors associate better perceptions with reduced risks and stronger , evidenced in from developing economies where a unit improvement in CPI boosts FDI inflows by 0.5-1% annually. This effect holds across source countries, including and Chinese investors, though magnitudes vary by institutional context, with stronger deterrence in rule-of-law oriented destinations. Critics argue that the CPI's sway on may overemphasize subjective opinions from surveys, potentially overlooking on-the-ground reforms and amplifying media-driven biases that misallocate away from high-potential but low-ranked economies. Nonetheless, econometric models consistently isolate perceived as a causal barrier to FDI, independent of other variables like GDP growth or market size, underscoring the index's role in shaping sentiment.

Policy Uses and Misapplications

The Corruption Perceptions Index (CPI) informs policy formulation by providing governments with a comparative to assess integrity and track progress over time. Since its launch in 1995, national authorities have referenced CPI scores to justify legislative changes, such as strengthening or whistleblower protections, aiming to elevate rankings and signal commitment to international standards. For example, countries like have cited improvements in CPI scores—from 5.7 in 2000 to 76 in 2023 on the 0-100 scale—as evidence of successful initiatives reducing petty . International financial institutions, including the , incorporate CPI data alongside other indicators to evaluate risks in project approvals, influencing loan conditions tied to compliance. Donor agencies and multilateral bodies use CPI rankings to guide foreign aid allocation, often prioritizing recipients with higher perceived to minimize diversion risks. Empirical analyses show that nations scoring above on the CPI receive disproportionately larger shares of relative to , as donors perceive lower leakage potential; for instance, a study found a positive correlation between CPI improvements and inflows in . Investors, including multinational enterprises, consult CPI scores for , with surveys indicating that a 10-point CPI increase correlates with up to 1.5% higher as a percentage of GDP, reflecting reduced perceived barriers. Despite these applications, misapplications of the CPI in settings stem from its in subjective perceptions rather than corruption incidence, potentially leading to misguided interventions. Linking aid conditionality directly to CPI rankings can engender a "corruption trap," wherein low-scoring developing countries—frequently those with nascent institutions—are withheld funds essential for capacity-building, perpetuating stagnation; a 2010 highlighted how such mechanisms reinforce by favoring established performers over those requiring targeted support. In , EU funding suspensions tied to CPI perceptions (scoring 42 in 2022) prompted the establishment of the Integrity Authority on October 3, 2022, ostensibly to monitor public spending, yet critics contend this diverted resources toward performative compliance rather than addressing root causes like private-sector influence. Financial regulators and banks have misused CPI scores as simplistic risk proxies in compliance frameworks, such as enhanced under anti-money laundering rules, exacerbating from low-ranked nations without verifying local ; a 2020 survey of financial professionals revealed widespread misinterpretation of CPI , resulting in blanket de-risking that hampers legitimate trade in affected economies. The index's aggregation of elite and business surveys embeds Western-centric biases, overlooking private-sector corruption or cultural variances in , which can incentivize superficial reforms over systemic change—such as prioritizing media-friendly audits while neglecting . These distortions underscore the peril of treating CPI as a causal diagnostic , as perceptions often lag institutional realities or amplify media-driven narratives, yielding policies that reward over verifiable outcomes.

Reforms, Alternatives, and Future Directions

implemented significant methodological reforms to the Corruption Perceptions Index in 2012, shifting the scale to a 0-100 range (0 indicating highly corrupt and 100 very clean) and standardizing aggregation procedures to enhance year-to-year comparability of scores. These changes addressed prior criticisms of inconsistent scoring by requiring at least three data sources per country and applying a z-score followed by rescaling, reducing volatility from fluctuating source availability. By 2024, the index aggregated data from 13 independent sources, including expert assessments and business surveys, to mitigate individual source biases, though it retains reliance on perceptions rather than objective incidents. Academic critiques have proposed further refinements, such as statistically testing and excluding insignificant data sources from the composite score; one analysis of the CPI found that removing underperforming sources improved the modified index's with economic outcomes compared to the original. However, has not adopted such data pruning, maintaining that broader inclusion captures diverse perceptual angles despite potential noise. Alternatives to the CPI emphasize objective metrics or disaggregated corruption types to overcome perception-based limitations. The World Bank's Control of Corruption indicator, part of its , draws from similar perceptual sources but incorporates more statistical controls and covers additional governance dimensions, showing strong but imperfect correlation with CPI scores (r ≈ 0.9). The Varieties of Democracy (V-Dem) project's corruption indices provide expert-coded measures of executive, legislative, judicial, and public sector , enabling granular analysis that reveals discrepancies with CPI aggregates, such as higher political corruption in high-income democracies. Fact-based approaches like the T-Index rank countries using verifiable corruption convictions and asset recoveries, aiming to incentivize enforcement over reputational signaling, though coverage remains limited to judicial data from select jurisdictions. The Unbundled Corruption Index prototypes multi-dimensional scoring across petty, grand, and forms, addressing CPI's of with low income levels, where poor countries score low regardless of enforcement efforts. The Bayesian Corruption aggregates perceptions via probabilistic modeling to estimate underlying corruption probabilities, offering intervals absent in CPI point estimates. Future directions for corruption measurement prioritize hybrid objective-perceptual models and expanded scope beyond perceptions. acknowledges CPI limitations in capturing graft, financial secrecy, and cross-border flows, suggesting integration with tools like registries for holistic assessments. Proposed advancements include leveraging from court records and blockchain-tracked transactions for , verifiable indices, potentially reducing elite biases in expert surveys that favor visible scandals over systemic issues. Despite CPI's enduring influence, persistent stagnation in global scores (two-thirds of countries showing no improvement from 2012-2023) underscores the need for indices linking perceptions to causal interventions, such as efficacy, to guide over ranking exercises.

References

  1. [1]
    Corruption Perceptions Index 2024 - Transparency.org
    The Corruption Perceptions Index 2024 ranks 180 countries by their perceived levels of public sector corruption. Find out the scores and read our analysis.2023CPI 2024: Highlights and ...Our Work In Indonesia2010 - CPICPI Media Page
  2. [2]
    The ABCs of the CPI: How the Corruption Perceptions Index is…
    Feb 11, 2025 · The Corruption Perceptions Index (CPI) is the most widely used global corruption ranking in the world. It measures how corrupt each country's public sector is ...
  3. [3]
    [PDF] Corruption Perceptions Index Technical Methodology Note
    The Corruption Perceptions Index (CPI) was established in 1995 as a composite indicator used to measure perceptions of corruption in the public sector in ...
  4. [4]
    [PDF] Is it wrong to rank? A critical assessment of corruption indices
    It is not clear to what extent the level of corruption reflects the frequency of corrupt acts, the damage done to society or the size of the bribes. The polls ...
  5. [5]
    A critique on the Corruption Perceptions Index: An interdisciplinary ...
    Our methodology enables policymakers to identify the critical data sources that a given country should focus on in order to improve its position in the CPI ...
  6. [6]
    The Corruption Perceptions Index (CPI): the Good, the Bad and the ...
    Feb 3, 2016 · The Ugly: perhaps the most telling criticism of the CPI is that it not only acts as a poor guide to policy, but actively creates perverse ...
  7. [7]
    Our story - Transparency.org
    The year began with a sobering analysis of how corruption has contributed to the current threat to democracy as part of the Corruption Perceptions Index. Our ...
  8. [8]
    1995 - CPI - Transparency.org
    The Corruption Perceptions Index was first launched in 1995, when Transparency International was two years old.
  9. [9]
    [PDF] Transparency International publishes 1997 Corruption Perception ...
    1 “Every day the poor scores in the CPI are not being dealt with, means more impoverishment, less education, less health care,” stated Eigen. Yet, the index ...
  10. [10]
    [PDF] NEW ZEALAND BEST, INDONESIA WORST IN WORLD POLL OF ...
    The 1995 Transparency International (TI) Corruption Index is an initiative taken by the. Berlin-based international non-governmental organisation, TI, together ...
  11. [11]
    Corruption Perceptions Index 2012 - Publications - Transparency.org
    Dec 5, 2012 · The Corruption Perceptions Index measures the perceived levels of public sector corruption in countries worldwide. Based on expert opinion, ...Missing: methodology | Show results with:methodology
  12. [12]
    [PDF] Corruption Perceptions Index Technical Methodology Note
    This year the baseline year t changed due to a new aggregation method of the. World Economic Forum Executive Opinion Survey. The new parameters are.
  13. [13]
    Corruption Perceptions Index, 2024 - Our World in Data
    The Corruption Perceptions Index (CPI) ranks countries and territories based on the perceived level of public sector corruption, as judged by experts and ...
  14. [14]
    [PDF] New Corruption Indexes of Transparency International
    Oct 23, 1999 · TI also published the fifth annual Corruption Perceptions Index (CPI), which this year ranks a record 99 countries, up from 85 in 1998. The CPI ...<|control11|><|separator|>
  15. [15]
    Transparency International Releases Latest Corruption Perceptions ...
    Feb 11, 2025 · The CPI ranks 180 countries and territories by their perceived levels of public sector corruption, and considers factors such as bribery, ...<|separator|>
  16. [16]
    Research - Transparency.org
    Our two flagship research tools measure corruption around the world. The annual Corruption Perceptions Index (CPI) ranks countries and territories by their ...
  17. [17]
    [PDF] Corruption Perceptions Index: Short Methodology Note
    The CPI is calculated using 13 different data sources from 12 different institutions that capture perceptions of corruption within the past two years. These ...
  18. [18]
    [PDF] Corruption Perceptions Index 2024: Full Source Description
    The indicators are calculated using quantitative data from international organisations and supplemented by qualitative assessments from recognised country ...
  19. [19]
    [PDF] Corruption Perceptions Index Technical Methodology Note
    Any rescaled scores which take values of less than 0 are made equal to 0 and any rescaled scores which exceed 100 are capped to 100. 3. Aggregate the rescaled ...
  20. [20]
    Corruption Perceptioons Index (CPI): Definition, Country Rankings
    Transparency International launched the index in 1995.1 As of 2020, the index ranks 180 countries and territories, where the average score is 42 out of 100 ...Missing: milestones | Show results with:milestones
  21. [21]
    [PDF] corruption perceptions index
    As corruption grows in scale and complexity, over two thirds of countries now score below the mid-point on Transparency International's Corruption Perceptions.
  22. [22]
    [PDF] Corruption Perceptions Index 2023: Full Source Description
    13 data sources were used to construct the Corruption Perceptions Index (CPI) ... data from the EOS is provided to Transparency International by the. Forum. It ...
  23. [23]
    CPI 2024: Highlights and insights - News - Transparency.org
    Feb 11, 2025 · The CPI ranks 180 countries and territories according to the levels of public-sector corruption perceived by experts and businesspeople.Missing: methodology | Show results with:methodology
  24. [24]
    2023 Corruption Perceptions Index: Explore the… - Transparency.org
    How does your country measure up in the 2023 Corruption Perceptions Index?View latest · 2023 · 2022
  25. [25]
    Denmark Corruption Index - Trading Economics
    Corruption Index in Denmark averaged 92.80 Points from 1995 until 2024, reaching an all time high of 100.00 Points in 1998 and a record low of 87.00 Points in ...
  26. [26]
    2022 Corruption Perceptions Index: Explore the… - Transparency.org
    Corruption Perceptions Index 2022 · 90. Denmark1 · 87. Finland2 · 87. New Zealand2 · 84. Norway4 · 83. Singapore5 · 83. Sweden5 · 82. Switzerland7 · 80. Netherlands8.
  27. [27]
    [PDF] Corruption Perception Index 2021
    Uzbekistan is one of the most consistent improvers in the. CPI, from a score of just 17 in. 2012 to 28 this year. Reforms adopted since 2016 contributed to ...
  28. [28]
    Transparency International's Corruption Perception Index 2024
    Feb 12, 2025 · The CPI 2024 highlights that 32 countries have significantly improved in the fight against corruption since 2012 whereas 148 countries have ...<|control11|><|separator|>
  29. [29]
    2024 Corruption Perceptions Index - Transparency International
    Feb 11, 2025 · The report has exposed serious corruption levels across the globe, with more than two-thirds of countries scoring below 50 out of 100.
  30. [30]
    [PDF] Corruption Perceptions Index (CPI) 2023
    Transparency International's. Global Corruption Barometer revealed the prevalence of corruption around election processes in Asia and the Pacific. These ...<|control11|><|separator|>
  31. [31]
    CPI 2024 for Sub-Saharan Africa: Weak anti-corruption measures…
    Feb 11, 2025 · The lowest scorers declined further on this year's CPI: Equatorial Guinea (13), Eritrea (13), Somalia (9) and South Sudan (8).
  32. [32]
    CPI 2024 for the Americas: Corruption fuels… - Transparency.org
    Feb 11, 2025 · With a regional average score of 42 out of a possible 100 points on the 2024 Corruption Perceptions Index (CPI), the Americas must take ...
  33. [33]
    Comprehensive Subnational Corruption Index (SCI) - Governance
    The Comprehensive Subnational Corruption Index (SCI) provides a widely available standardized measure of overall corruption at the subnational level, combining ...
  34. [34]
    The Subnational Corruption Database: Grand and petty ... - Nature
    Jun 25, 2024 · The SUBCPI and SUBCCI Datasets contains subnational and national estimates of total corruption obtained by superimposing the subnational ...
  35. [35]
    (PDF) The Subnational Corruption Database: Grand and petty ...
    Jun 10, 2024 · This data descriptor presents the Subnational Corruption Database (SCD), which provides data on corruption in 1,473 subnational areas of 178 ...Missing: examples | Show results with:examples
  36. [36]
    [PDF] Different Indicators of Corruption - World Bank Document
    The CPI is a composite index meaning that it utilizes a variety of different sources to arrive at each country's score (see Table 1). One of the essential ...<|separator|>
  37. [37]
    [PDF] Corruption Perceptions vs. Corruption Reality - MIT Economics
    Mar 11, 2009 · After all, since corruption is illegal, regularly and directly observing corrupt activity is almost always impossible. If citizens have accurate ...
  38. [38]
    [PDF] What Do Corruption Indices Measure? - University of Houston
    We check whether the WB and CPI results might be affected by uncertainty in these aggregate perception measures (captured by the variance of their components): ...
  39. [39]
    Objective Validation of Subjective Corruption Perceptions? | GAB
    Apr 18, 2014 · The paper finds that, at least for small- and medium-sized firms, the extent of tax evasion is negatively correlated with the CPI score for the ...
  40. [40]
    What does the Corruption Perceptions Index tell us—and ... - EUIdeas
    Jan 31, 2024 · By ranking countries and highlighting domestic graft, the CPI fails to reflect how corruption can be facilitated by networks operating beyond ...
  41. [41]
    What's Wrong With the Corruption Perceptions Index
    Dec 10, 2024 · The Corruption Perception Index (CPI) faces criticism for its methodology, which has raised concerns about accuracy and bias.
  42. [42]
    Page not found
    No readable text found in the HTML.<|separator|>
  43. [43]
    [PDF] Corruption and Economic Growth: New Empirical Evidence - ifo Institut
    The cumulative long-run effect of corruption on growth is that real per capita GDP decreased by around 17% when the reversed CPI increased by one standard ...
  44. [44]
    Corruption and economic growth: New empirical evidence
    The empirical evidence tends to suggest that corruption decreases economic growth, especially in countries with low investment rates and low-quality governance.Missing: validity | Show results with:validity
  45. [45]
    [PDF] Corruption, income, and rule of law: empirical evidence from ...
    The results confirm the argument that there exists a positive correlation between. RL and CPI for both developed (0.33) and developing countries (0.46). In ...
  46. [46]
    [PDF] The impact of corruption on growth and inequality
    Corruption undermines the purpose and integrity of regulation as it enables corrupt officials to circumvent regulations or bend them for their own interests.
  47. [47]
    8 Corruption, Growth, and Public Finances in - IMF eLibrary
    Mauro (1998) has shown that corruption may have no impact on total government spending. He has also shown that corrupt countries spend less for education and ...
  48. [48]
    Full article: Causality between corruption and the level of GDP
    In spite of many desirable features of the CPI, it has several limitations. One limitation is that the CPI deals only with limited structure of people and ...
  49. [49]
    [PDF] HOW CORRUPTION AFFECTS GROWTH 1 - OhioLINK ETD Center
    corruption index is known as the Corruption Perceptions Index (CPI). The CPI ... Other studies have found that economic growth causes corruption levels to fall ( ...Missing: outcomes | Show results with:outcomes<|control11|><|separator|>
  50. [50]
    Corruption Perception Index (CPI), as an Index of Economic Growth ...
    As it is shown in Figure 1 and Table 1, there is generally a positive relationship between the level of corruption (CPI) and the per capita GDP (y), for all ...
  51. [51]
    Bidirectional relationship between corruption and economic ...
    Usually, the higher up in the public hierarchy the corrupt official or officials are, the more money is involved in the corruption transaction, and they ...Missing: outcomes | Show results with:outcomes
  52. [52]
    Investigating the Relationship between Public Governance and the ...
    This study aims to investigate the relationship between public governance and the Corruption Perception Index (CPI) while also examining the impact of national ...
  53. [53]
    The TeliaSonera Scandals: A Swedish Trauma | OCCRP
    May 29, 2015 · Even though TeliaSonera is partly government-owned, it is the largest publicly owned firm in relatively corruption-free Sweden. Yet in ...
  54. [54]
    Trouble at the top: why high-scoring countries aren't corruption-free…
    Jan 29, 2019 · The top seven countries in the Corruption Perceptions Index 2018 consist of the four Nordic nations – Denmark, Finland, Sweden and Norway – plus New Zealand, ...
  55. [55]
    Facts vs. Perceptions – The Controversy Around Corruption ...
    Jan 31, 2023 · Perceptions are not facts and more often than not they are not backed by any evidence. The CPI is subject to criticism for a number of reasons, ...
  56. [56]
    Nézőpont Institute: Transparency's corruption index is misleading ...
    Jan 22, 2025 · This discrepancy is particularly problematic for Hungary, where CPI scores often underpin international criticisms. The study reveals that these ...
  57. [57]
    [PDF] Hungary is the most corrupt Member State of the European Union
    The survey has been criticized from time to time, and in response, Transparency International asked the European Commission for a credibility (robustness) test ...
  58. [58]
    Economic Issues No. 6 -- Why Worry About Corruption?
    Both indices are on a scale from 0 (most corrupt) to 10 (least corrupt). The corruption index used in this paper is the simple average of both indices, which ...
  59. [59]
    [PDF] Impact of Corruption on Economic Growth in Central America
    The empirical estimation results are presented in Table 1 It is important to note that the higher CPI score you have, the less corruption there is in that ...Missing: studies | Show results with:studies
  60. [60]
    The True Cost of Global Corruption – IMF F&D
    Curbing corruption can yield significant fiscal benefits. Our research suggests that revenues are higher in countries perceived to be less corrupt; the ...
  61. [61]
    Governance for Inclusive Growth in - IMF eLibrary
    Apr 23, 2021 · Dozens of peer-reviewed empirical studies show that poor governance and corruption are associated with lower economic growth, lower investment, ...
  62. [62]
    [PDF] Does Economic Growth Reduce Corruption? Theory and Evidence ...
    A striking fact about government corruption is that, no matter how you measure it, it is higher in poor countries. For example, the 10 least corrupt countries ...
  63. [63]
    The impact of corruption on economic growth in developing ...
    Empirical research also links corruption to governance or political structures and economic growth. ... Corruption Perceptions Index (CPI) compiled by ...
  64. [64]
    Absence of Corruption - WJP Rule of Law Index
    Factor 2 of the WJP Rule of Law Index measures the absence of corruption in government. The factor considers three forms of corruption: bribery, ...
  65. [65]
    2023 Corruption Perceptions Index: Weakening… - Transparency.org
    Jan 30, 2024 · 2023 Corruption Perceptions Index: Weakening justice systems leave corruption unchecked · Russia's war against Ukraine (36) posed immense ...Missing: criticisms | Show results with:criticisms
  66. [66]
    2023 Corruption Perceptions Index for the Americas reveals…
    Jan 30, 2024 · The lack of judicial independence undermines the rule of law, promotes corruption and leads to impunity for the corrupt and powerful. With the ...
  67. [67]
    CPI 2023: Corruption and (in)justice - News - Transparency.org
    Jan 30, 2024 · While the declining levels of the rule of law worldwide affect efforts to hold corruption offenders to account, corruption also contributes to ...
  68. [68]
  69. [69]
    [PDF] Which Data Do Economists Use to Study Corruption?
    In 1999, researchers at the World Bank introduced the Worldwide Governance Indicators with one dimension focused on control of corruption (Kaufmann, Kraay, &.
  70. [70]
    [PDF] measuring corruption:a comparison between the transparency interna
    For the purpose of the CPI, which focuses on the cor- ruption in the public sector, it is necessary to define corruption. TI defines “corruption as the abuse of.
  71. [71]
    [PDF] Measuring Changes in Corruption over Time - Justin Esarey
    Oct 16, 2025 · We find that panel-adjusted versions of the CPI, WBGI, BCI, V-Dem, and ICRG corruption measures are weakly correlated, but give very different ...
  72. [72]
    [PDF] Assessing The Varieties of Democracy Corruption Measures
    A measure's quality can also be assessed comparatively, so we examine content validity in relation to other measures. Applying this tool to the V-Dem measures, ...
  73. [73]
    Political Corruption Index, 2024 - Our World in Data
    The political corruption index is by V-Dem, based on expertestimates, and ranges from 0 to 1 (most corrupt).
  74. [74]
    Index of Public Integrity Methodology - Corruption Risk Forecast
    The Index of Public Integrity (IPI) identifies proximate measures for factors identified in research as impacting corruption risk for 114 countries.
  75. [75]
    Corruption Index Today, Election Tomorrow, Aid Revamp the Day ...
    In reaction to news of brazen corruption in Afghanistan and the release of the new Corruption Perceptions Index ... foreign aid strategy and programs, one ...
  76. [76]
    Corrupt Governments Receive no less Foreign Aid | NBER
    An NBER Working Paper by Alberto Alesina and Beatrice Weder shows instead that corrupt governments receive as much aid as honest ones.
  77. [77]
    Does corruption matter for FDI flows in the OECD? A gravity analysis
    Apr 17, 2021 · Egger and Winner (2006) produce three results: 1) corruption, as measured via the Corruption Perception Index (CPI), has a negative impact on ...
  78. [78]
    [PDF] Foreign Direct Investment, Corruption, and Democracy
    ... corruption perception and the level of democracy influence foreign direct ... index, the less corrupt the country is perceived to be by international investors.
  79. [79]
    The impact of corruption on Foreign Direct Investment inflows
    The findings revealed a significant positive correlation between the Corruption Perceptions Index (CPI) and FDI, while GDP growth and inflation showed no ...
  80. [80]
    [PDF] The Impact of Perceived Corruption Index on Foreign Direct ...
    This thesis evaluates the impact of corruption perception index (CPI) on foreign direct investment (FDI) flows from China and 34 OECD source countries to 54 ...
  81. [81]
    Effects of corruption on foreign direct investment - ScienceDirect.com
    In this paper, we provide novel evidence on the adjustment of multinational enterprises (MNEs) to corrupt environments. We examine if the corruption barrier ...
  82. [82]
    A Study of Corruption, Foreign Aid, and Economic Growth
    Apr 30, 2013 · Foreign aid donors increasingly demand that aid is used efficiently and effectively ... Corruption Perceptions Index, within a recipient ...
  83. [83]
    Does corruption perception matter to investors?
    Apr 2, 2024 · Based on surveys with experts and business leaders, the CPI assigns scores and ranks to countries based on the perceived level of corruption in ...<|separator|>
  84. [84]
  85. [85]
    The potential negative impact of the misuse of Transparency ...
    Jul 17, 2020 · The results of the research have evidenced that there is a lack of understanding of the methodology used to compile the CPI within the financial ...Missing: causality | Show results with:causality<|separator|>
  86. [86]
    Corrupting Perceptions: Why Transparency International's Flagship ...
    Jul 23, 2013 · The Corruption Perceptions Index (CPI) is derived by aggregating 13 different perception surveys. There is a striking commonality in the people ...Missing: milestones | Show results with:milestones
  87. [87]
    Comparing the V-Dem and CPI Measures of Corruption
    This index includes measures of several types of corruption (such as bribery, theft, and embezzlement), which cover acts of corruption in the executive, ...
  88. [88]
    T-Index Methodology - Corruption Risk Forecast
    The 'Transparency International Corruption Perceptions Index (CPI) is an average of expert scores produced by a variety of agencies assessing corruption at the ...
  89. [89]
    The Unbundled Corruption Index (UCI): Prototyping a multi ...
    Mar 6, 2025 · To provide an alternative to the likes of the CPI, in 2020 I prototyped a multi-dimensional measure of corruption: the Unbundled Corruption ...
  90. [90]
    The Bayesian Corruption Index - QoG Data Finder
    Aug 25, 2023 · The Bayesian Corruption Index is a composite index of the perceived overall level of corruption: with corruption refered to as the abuse of public power for ...<|control11|><|separator|>
  91. [91]
    CPI 2024: Trouble at the top - News - Transparency.org
    Feb 11, 2025 · Recent findings from Transparency International highlight how funds from corrupt officials in Africa often flow into financial centres that ...Missing: criticisms | Show results with:criticisms