1.1 Abstract

This report investigates how different dimensions of governance relate to one another across a diverse set of low and lower middle income countries. It focuses on corruption control and the quality of the business regulatory environment, which are two widely used indicators of institutional performance. The analysis asks whether improvements in one area tend to coincide with improvements in the other, and how these patterns vary across regions and over time. Using descriptive comparisons, regional trends, and country level profiles, the report maps broad patterns in governance. The findings show that corruption control and regulatory quality are connected but not perfectly aligned. Many countries experience uneven reform paths in which strengths in one area coexist with weaknesses in another. Regional differences are persistent, and country trajectories reveal both long term improvement and episodes of institutional decline. Overall, the report highlights the multidimensional nature of governance and shows that institutional development is often complex, uneven, and shaped by context.

1.2 Introduction

Institutional quality has become central to debates about development, state capacity, and long-term economic performance. Governments that can regulate markets effectively and prevent the misuse of public office are better equipped to support investment, provide public goods, and maintain political stability. Yet institutional performance varies widely across the world, and understanding these differences requires systematic measurement. This report focuses on two specific governance dimensions: (1) control of corruption, captured by the Worldwide Governance Indicators (WGI), and (2) the quality of the business regulatory environment, assessed through the Country Policy and Institutional Assessment (CPIA). Corruption weakens state capacity by distorting incentives and undermining public trust, while regulatory quality shapes how firms interact with the state through licensing, enforcement, and administrative procedures. These dimensions are conceptually distinct, but they may reinforce each other, raising an important empirical question: how closely do corruption control and business regulatory quality move together?

To answer this question, a country–year dataset was used for 86 countries spanning 2005 to 2023. The sample includes 42 countries from Africa, 18 from Asia, 11 from Latin America and the Caribbean, 10 from Oceania, and 5 from Europe, reflecting the World Bank’s coverage of low- and lower-middle-income contexts. The report documents four types of descriptive patterns: global trends, regional trajectories, cross-sectional associations, and country-level governance profiles using a quadrant classification that compares each country against median global performance. As African countries form a huge majority of the dataset, a special focus is put on the region later in the report, to reveal trends in that region specifically.

Rather than identifying causal mechanisms, the goal is to map how institutional characteristics cluster and diverge. By combining time-series plots, regional heatmaps, correlation analysis, and interactive country-level scatterplots, the study provides a structured descriptive overview of governance relationships across the global South. These patterns may be informative for scholars of institutional development, practitioners designing governance reforms, and analysts concerned with investment, risk, or policy environments in emerging economies.

1.3 Data and Measurement

This analysis draws on two publicly available World Bank governance datasets covering 86 countries from 2005 to 2023. The first dataset is the Worldwide Governance Indicators (WGI) World Bank (2024b), which provide annual estimates of Control of Corruption on a standardized scale ranging from –2.5 (weak governance) to +2.5 (strong governance). These scores are derived from a combination of expert assessments, household surveys, business surveys, and institutional diagnostics. As a perception-based measure, WGI captures how corruption is experienced and reported across institutional and societal actors. The second dataset is the Country Policy and Institutional Assessment (CPIA) score for the Business Regulatory Environment World Bank (2024a), which ranges from 1 (very weak) to 6 (very strong). Unlike WGI, CPIA scores are produced by World Bank country economists who assess the clarity, predictability, and administrative quality of business-related regulations. They reflect how transparent, streamlined, and market-friendly a country’s policy environment is, focusing on entry barriers, licensing, operational rules, and enforcement processes. For each country, annual values were averaged across the full 2005–2023 period to construct a stable representation of long-run governance performance. This approach smooths out year-to-year volatility and allows consistent quadrant classification. Countries were then grouped into five geographic regions using World Bank categories: Africa (42 countries), Asia (18), Latin America & Caribbean (11), Oceania (10), and Europe (5). Regional aggregates were calculated by averaging country scores within each region for each year, enabling the construction of time-series heatmaps. To document the relationship between corruption control and regulatory quality, a Pearson correlation coefficient was computed using the panel dataset. The resulting value (r ≈ 0.45) provides a summary measure of their global association. However, the study places greater emphasis on visual and descriptive patterns than on statistical inference, reflecting its exploratory and mapping-oriented purpose. Further, each country was assigned to one of four governance quadrants: High CC / High BREG, High CC / Low BREG, Low CC / High BREG, or Low CC / Low BREG. This was based on whether its long-run scores fall above or below the global medians. This classification allows for regional comparisons and helps reveal which countries combine strengths across dimensions and which exhibit asymmetric or weaker governance structures.

1.4 Ethical and Methodological Considerations

This project relies exclusively on publicly accessible aggregate data and therefore presents minimal ethical risk. All information is derived from institutional assessments produced by the World Bank, avoiding any use of individual-level or sensitive personal data. Nevertheless, several methodological and ethical considerations shaped the analysis. First, both WGI and CPIA indicators reflect constructed governance measures, not objective recordings of corruption or regulatory quality. WGI is partly perception-based, which introduces potential biases related to media coverage, expert networks, or shifts in international expectations. CPIA scores are produced by World Bank economists, raising questions about evaluator subjectivity and institutional framing. This report therefore avoids treating the scores as absolute judgments of a country’s governance quality and instead interprets them as comparative indicators useful for identifying patterns across countries and regions. Second, governance metrics often carry normative assumptions about what constitutes good institutions. Regulatory efficiency, for instance, may be valued differently in countries with distinct administrative traditions or development priorities. By grounding the analysis in descriptive visualization rather than rankings, this project aims to avoid reinforcing simplified narratives about “good” or “bad” governance. Instead, it presents patterns while acknowledging that context matters. Third, the use of long-run averages, while helpful for smoothing noise, may obscure short-term governance shifts caused by elections, conflicts, or major reforms. To mitigate this limitation, the study pairs cross-sectional quadrant classification with regional time-series heatmaps, allowing readers to observe both stability and change. Finally, the analysis does not infer causality. While corruption control and regulatory quality are moderately correlated, the relationship is likely shaped by deeper structural, political, and historical factors. Treating the indicators descriptively respects the methodological limits of the data and avoids overinterpreting cross-national patterns.

2.1 Global snapshot: corruption control and business regulation in 2023

To begin, we focus on the most recent year in the dataset, 2023, and explore how closely the two governance indicators move together across countries. Each point in Figure 1 represents a single country’s scores for Control of Corruption and the Business Regulatory Environment in 2023. The fitted regression line summarizes the overall association between the two indicators in this cross-section.

The pattern is clearly upward sloping: countries that score higher on control of corruption also tend to have stronger business regulatory environments. At the same time, the points are quite dispersed around the line, indicating that the relationship is far from deterministic. Some countries with relatively similar corruption scores differ noticeably in their regulatory ratings, and vice versa. Taken together, this suggests a moderate positive relationship between the two dimensions of governance - strong enough to be meaningful, but loose enough to leave room for different institutional combinations.

2.2 Global patterns over time

While the 2023 snapshot illustrates cross-sectional variation, examining global averages over time highlights how governance has evolved across the 86 IDA-eligible countries in the dataset. Figures 2 and 3 show the annual mean of each indicator from 2005 to 2023.

Figure 2 reveals three clear patterns in the global average Control of Corruption. First, corruption perceptions across the sample remain consistently negative, the average score never rises above –0.55, underscoring how widespread corruption challenges remain in low- and lower-middle-income countries. Second, the line displays a long period of stagnation between 2006 and 2013, where global corruption control fluctuates narrowly around –0.60 with no meaningful improvement. Third, after 2014, the average begins a modest upward climb, interrupted by temporary dips, and reaches its highest point in 2023. While the improvement is small in magnitude, the upward trend suggests a gradual strengthening of governance norms or anti-corruption reforms in parts of the global South, although still far from eliminating systemic corruption risks.

The trend in the Business Regulatory Environment (Figure 3) tells almost the opposite story. The global average score steadily declines from around 3.30 in 2005 to below 3.00 in 2020, before stabilizing slightly in the final years. This downward trajectory signals that the regulatory environment became more challenging for firms across the sample over the past two decades. Several factors could be driving this pattern: conflict and fragility in many IDA-eligible countries, regulatory reversals during periods of political instability, or stricter assessment standards by the World Bank over time. Even with small improvements after 2020, the global average remains meaningfully lower than in the mid-2000s.

Taken together, these two time-series reveal a striking divergence: Control of Corruption shows mild improvement, especially after 2015. Business Regulatory Quality shows sustained deterioration, particularly between 2008 and 2019. This divergence highlights that improving perceptions of corruption does not automatically translate into a stronger regulatory environment. Institutional reforms may be uneven across governance domains, and countries may prioritize anti-corruption efforts without achieving broader regulatory modernization. The patterns also reinforce the core theme of this report: different governance dimensions often move together but can also diverge in important ways.

2.4 Within-region patterns: corruption control and business regulation

Figure 6 examines the relationship between corruption control and the business regulatory environment within each region, rather than across all countries at once. This disaggregation shows that while the global relationship is moderately positive, the strength and shape of the association vary substantially across regions.

The scatterplots reveal a positive relationship between corruption control and regulatory quality in every region, but the strength of this relationship differs. Europe shows the tightest clustering and the steepest upward slope, indicating that improvements in corruption control tend to go hand-in-hand with stronger business regulatory systems. Latin America and the Caribbean also display a strong positive association, with many countries moving toward the top-right corner of the distribution. Asia presents a moderate but clear positive relationship, though with wider variability in regulatory scores. Africa shows the greatest dispersion: while some countries like Rwanda perform well on regulatory measures despite modest corruption scores, many others remain low on both metrics. Oceania displays a mild relationship driven by a small set of countries with similar institutional configurations. Together, these patterns reaffirm that the two governance dimensions generally reinforce one another but can diverge in contexts of institutional asymmetry. Figure 6 reinforces that while corruption control and regulatory quality tend to move together globally, the strength, consistency, and direction of this relationship are strongly shaped by regional histories, political structures, and developmental contexts.

3.1 Country-level governance profiles: Quadrant classification

Figure 7 provides a summary view of countries’ average governance performance over the 2005–2023 period by plotting mean scores for Control of Corruption against mean scores for the Business Regulatory Environment. The figure divides the space into four quadrants using the sample medians of each indicator. This simple classification highlights how countries cluster into distinct governance profiles and reveals that institutional strengths and weaknesses tend to be multidimensional rather than isolated.

High CC, high BREG (upper-right quadrant)

Countries in this quadrant exhibit both comparatively strong corruption control and relatively high-quality regulatory environments. These cases represent the most institutionally capable states within the sample, even though many remain lower-income or transition economies. They are disproportionately concentrated in Europe & Central Asia and parts of Oceania. Examples include countries such as Georgia, Rwanda, and several small island states, which have pursued sustained governance reforms over the past two decades. These countries show that meaningful institutional strengthening is possible even outside high-income contexts, though often under specific political or historical conditions.

High CC, low BREG (lower-right quadrant)

A smaller set of countries performs relatively well on corruption control but exhibits weaker business regulatory environments. These cases imply partial reform trajectories in which integrity, transparency, or anticorruption efforts advance more rapidly than administrative or regulatory modernization. Some Oceania and Asian countries appear here, along with a handful from Africa. This pattern suggests that progress in corruption control does not automatically translate into a supportive regulatory environment. It also reinforces the broader finding that governance components can evolve at different speeds depending on political priorities and capacity constraints.

Low CC, high BREG (upper-left quadrant)

Countries in this quadrant show relatively weak corruption control but somewhat stronger regulatory frameworks. Although fewer countries fall into this category, it remains meaningful, especially for parts of Latin America and the Caribbean, along with several Asian states. These cases reflect institutional asymmetry in which relatively strong rules and regulatory structures exist but are undermined in practice by limited enforcement or persistent corruption. This configuration can create unpredictability for firms because procedures may be well designed on paper but inconsistently applied due to informal practices or governance gaps.

Low CC, low BREG (lower-left quadrant)

This is the largest and most heavily populated quadrant, dominated by many Sub-Saharan African countries, several Asian states, and some Caribbean economies. These countries face systemic governance challenges, with both poor corruption control and weak regulatory environments. Many are fragile or conflict-affected states where institutional capacity has been undermined by instability, economic stress, or longstanding governance constraints. This quadrant also contains some large and influential economies where entrenched patronage systems or administrative fragmentation limit meaningful reform. The clustering here highlights how weaknesses in corruption control and regulatory quality often reinforce each other, contributing to persistent low-governance equilibria.

Interpretation and significance

The quadrant classification clarifies how countries differ in their governance trajectories, even though corruption control and regulatory quality remain positively correlated overall. Three insights emerge clearly: Institutional strength tends to be multidimensional. Countries that perform well in corruption control often also perform strongly in regulatory quality, indicating that governance improvements usually occur in clusters rather than isolation. Asymmetric governance profiles exist but are relatively uncommon. Countries with strong regulatory environments but weak corruption control or vice versa highlight the limits of narrow, single-issue reform programs. Without broader institutional modernization, isolated improvements may have reduced long-term impact. Low-governance traps are widespread in developing regions. Many countries remain concentrated in the weakest quadrant where both corruption control and regulatory structures lag. These patterns reflect challenges rooted in conflict, administrative fragility, political instability, or limited fiscal capacity. Figure 7 provides a clear framework for identifying which countries are moving toward stronger governance systems and which remain stuck in weaker institutional equilibria. It also sets the stage for deeper analysis of what differentiates positive outliers from persistent underperformers, an issue that becomes important in understanding long-term governance trajectories.

3.2 Strength of association over time

Figure 8 shows how the correlation between Control of Corruption and the Business Regulatory Environment has evolved from 2005 to 2023. While the relationship remains consistently positive, its strength fluctuates across the period, suggesting that the link between these two governance dimensions is neither static nor uniform over time. Pearson correlation measures the strength and direction of a linear relationship between two variables, ranging from –1 to +1. In this context it helps quantify how closely changes in corruption control move together with changes in the business regulatory environment, allowing us to assess whether improvements in one dimension tend to coincide with improvements in the other. A stronger positive value indicates that the two indicators rise and fall together, while weaker or negative values suggest decoupling or divergent institutional trajectories.

Stable and moderately strong association in the early period (2005–2013): Between 2005 and the early 2010s, the correlation remains relatively stable, clustering around r ≈ 0.50–0.55. This indicates a moderately strong and persistent relationship, where improvements in corruption control tend to coincide with better regulatory quality. The brief rise around 2010, where the correlation peaks above 0.55, may reflect global governance reform momentum following the mid-2000s wave of anti-corruption and business-environment initiatives.

Notable weakening around 2014–2018: The most significant change occurs between 2014 and 2018, when the correlation drops sharply to r ≈ 0.38—the weakest relationship in the entire series. This decline suggests a period during which several countries strengthened regulatory frameworks without comparable improvements in corruption control, or

Corruption control deteriorated while regulatory scores remained stable: This decoupling could be linked to political instability in key regions, asymmetric reform patterns, or external shocks affecting institutional performance—especially in the Middle East & North Africa and parts of Latin America.

Partial recovery after 2018: 2019 onward, the correlation gradually rebounds, rising into the 0.45–0.47 range by the early 2020s.While still below the levels of the mid-2000s, this recovery suggests a reconvergence between the two governance indicators—possibly reflecting renewed global emphasis on transparency, regulatory modernization, and institutional strengthening following the disruptions of the mid-2010s.

Interpretation and implications

Three insights emerge from the time-varying correlation pattern: Governance dimensions are linked but not perfectly synchronized. Their relationship weakens or strengthens in response to global political cycles, reform waves, and region-specific shocks. Periods of divergence reflect institutional asymmetry. Countries can improve regulatory quality while corruption remains entrenched, or vice versa. These mismatches highlight the difficulty of achieving balanced reform. The long-term trend remains consistently positive. Despite fluctuations, countries with stronger corruption control tend to also have stronger business regulatory environments, confirming a structural relationship between integrity and institutional capacity. Overall, the dynamic pattern reinforces the idea that governance improvement is neither linear nor uniform. The relationship between corruption control and regulatory quality is shaped by broader political and economic shifts, making it essential to track their co-movement over time rather than relying on a single-year snapshot.

3.3 Regional composition of governance quadrants

Figure 9 shows how countries across different regions are distributed across the four governance “profiles” or quadrants—derived from whether a country scores above or below the global median on Control of Corruption (CC) and Business Regulatory Environment (BREG). This quadrant approach helps classify governance systems into meaningful clusters and reveals clear regional patterns in how governance strengths and weaknesses combine.

Africa’s distribution is heavily concentrated in the Low CC, low BREG quadrant, reflecting persistent constraints in both corruption control and regulatory capacity across much of the continent. A smaller but meaningful share of countries appears in Low CC, high BREG, signalling that certain administrations have managed to strengthen regulatory frameworks even where corruption remains entrenched. A small group falls into the High CC, high BREG category, representing Africa’s stronger governance performers such as Rwanda or Cabo Verde, though these remain exceptions rather than the norm. Asia shows a more balanced distribution across governance quadrants. A significant share of countries occupies the High CC, high BREG category, illustrating stronger institutional environments in parts of East and Southeast Asia. At the same time, Asia retains sizeable representation in both Low CC categories, capturing governance variation from countries with robust administrative systems to those facing persistent corruption and regulatory weaknesses. Asia’s profile thus highlights wide internal diversity, encompassing both some of the strongest and weakest performers globally. Europe stands out for having the highest concentration of countries in the High CC, high BREG quadrant, consistent with stronger rule-of-law traditions, higher state capacity, and more mature regulatory institutions. A moderate share appears in Low CC, high BREG, reflecting transitional economies where regulatory reforms have advanced more rapidly than corruption control. Overall, Europe is the region most heavily weighted toward “strong governance” outcomes. Latin America & the Caribbean displays substantial spread across all governance profiles, underscoring long-standing institutional heterogeneity in the region. There is significant presence in the Low CC, low BREG category, aligning with governance challenges in parts of the Caribbean, Central America, and the Andean region. Simultaneously, the region also includes a notable share of High CC, high BREG performers, demonstrating that some states have successfully strengthened both regulatory systems and corruption control. The NA category reflects missing data for a few countries rather than a meaningful governance classification. Oceania exhibits a distinctive pattern, with most countries falling into the High CC, low BREG quadrant. This combination suggests that while corruption tends to be relatively well-controlled, regulatory capacity varies significantly, especially among smaller island states. A minority of countries appear in the High CC, high BREG category, capturing higher-capacity states within the region.

Interpretation and Broader Insights

Across regions, three important governance themes emerge: Institutional strength clusters geographically. Europe has the highest concentration of countries with strong performance in both corruption control and regulatory quality. Africa sits at the opposite end, with a large share in the weakest quadrant. These patterns highlight how geography and political history strongly shape governance capacity. Mixed-performance quadrants reveal critical nuance. Many regions show countries in Low CC, high BREG or High CC, low BREG, indicating that corruption control and regulatory efficiency do not always develop together. This decoupling underscores that governance strengthening is multidimensional and rarely linear. Internal diversity is substantial, especially in Asia and Latin America. These regions contain both strong and weak performers, demonstrating that regional averages cannot capture the full complexity of governance outcomes. Country-specific trajectories matter greatly. Figure 9 reveals how governance profiles cluster regionally, offering insight into how political institutions, administrative capacity, and regional development paths shape long-term governance outcomes.

3.4 Biggest improvers and decliners in corruption control

Figure 10 highlights the countries that experienced the largest long-term changes—both improvements and declines—in the World Governance Indicators’ Control of Corruption measure between 2005 and 2023. These trajectories offer insight into how corruption dynamics shift under different political, economic, and institutional conditions.

Major Improvers

Côte d’Ivoire shows one of the most dramatic improvements. From extremely low ratings in the mid-2000s, the country’s score rises sharply after 2011. This turnaround aligns with political stabilization following years of conflict, renewed institutional reforms, and stronger state capacity, underscoring the role of post-conflict reconstruction in restoring governance effectiveness. Rwanda’s upward trajectory is steady and sustained, reflecting its long-standing emphasis on public-sector reform, anti-corruption enforcement, and centralized state capacity-building. By the mid-2010s, Rwanda achieves one of the highest improvements in the dataset, indicating effective alignment between governance systems and anti-corruption objectives. São Tomé and Príncipe experience a gradual but consistent rise suggests incremental improvements in bureaucratic integrity and political oversight. While the country starts from a low baseline, its upward momentum indicates successful governance reforms in a small-island administrative context. Micronesia’s improvement is marked by a sudden jump around 2012–2013, followed by consistently positive scores. Such a discrete shift likely reflects specific legal or administrative reforms, donor-supported institutional strengthening, or data recalibration tied to governance oversight programs. Tonga exhibits a significant early improvement, with scores rising sharply after 2009 before stabilizing. The gains coincide with political reforms increasing democratic participation and checks on executive authority, which strengthened perceived integrity.

Major Decliners

Eritrea shows one of the steepest declines, with its corruption-control score deteriorating steadily throughout the period. This reflects increasing authoritarian centralization, limited fiscal transparency, and ongoing governance constraints that weaken institutional accountability. Madagascar experiences a clear downward trend, especially following periods of political crisis and instability. The trajectory underscores how repeated disruptions in political order undermine public administration and oversight capacity. Nicaragua’s decline is notable for its scale and persistence. Beginning around 2012, its corruption-control rating drops sharply, corresponding to rising authoritarian tendencies, weakened institutional checks, and reduced judicial independence. By the 2020s, Nicaragua becomes one of the dataset’s sharpest governance deteriorations. St. Lucia’s corruption-control score drops abruptly around 2014–2015 and remains low afterward. Such an abrupt decline may reflect governance challenges triggered by fiscal stress, political conflict, or public-sector integrity failures. Yemen shows the largest collapse in governance quality. Following the onset of civil conflict around 2014–2015, its corruption-control score plummets, aligning with a breakdown of state institutions, severe political fragmentation, and disruptions in administrative capacity. Yemen represents the clearest example of conflict-driven systemic governance failure.

Interpretation and Broader Patterns

Three clear themes emerge: Conflict and political instability are the strongest predictors of decline. Countries like Yemen, Madagascar, and Eritrea show that institutional collapse rapidly erodes corruption-control capacity.Reform-driven improvements are possible but require sustained commitment. Côte d’Ivoire, Rwanda, and Tonga demonstrate that governance can improve markedly with political stabilization, targeted reforms, and administrative modernization. Sudden jumps often reflect policy reform episodes or external oversight. Micronesia and São Tomé & Príncipe illustrate how small states may exhibit stepwise improvements linked to specific governance interventions. The biggest improvers and decliners reveal how governance trajectories are shaped by political transitions, institutional strength, and the presence or breakdown of mechanisms for integrity and accountability.

4.1 Focus on Africa

As African countries constitute the largest share of the overall dataset, it is essential to focus on this region to understand how corruption control and business regulatory quality evolve together over time. Africa’s numerical dominance, combined with its wide institutional diversity from relatively high-capacity reformers to fragile and conflict-affected states, makes it the most informative region for interpreting broader global governance patterns. Figure 11 therefore isolates African countries to examine how closely these two governance indicators move within states across the 2005 to 2023 period. The results show substantial variation in institutional coupling across the continent. A small group of countries, such as Rwanda, Mauritius, and Cabo Verde, exhibit very strong positive correlations. In these cases, improvements in corruption control tend to coincide with simultaneous gains in business regulatory quality, which suggests episodes of coordinated reform where integrity systems, administrative capacity, and regulatory processes strengthen together rather than in isolation. Most African countries fall into the moderate or weak positive range. Examples such as Ghana, Kenya, and Senegal illustrate this middle pattern. The two governance indicators generally move in the same direction but only loosely. This implies incremental or sector-specific reforms in which progress in one domain may not immediately or fully translate into improvements in the other, and in which political transitions or external shocks can make reform trajectories uneven. A meaningful minority of countries, including Burundi, Somalia, and the Democratic Republic of the Congo, display negative correlations. In these states, improvements in one dimension often coincide with deterioration in the other. Such patterns reflect environments where institutional change is fragmented or destabilized by conflict, leadership turnover, or partial reforms that unintentionally strengthen one aspect of governance while weakening another. The African distribution shows that governance reforms are not uniformly synchronized within countries. A few states demonstrate coherent and mutually reinforcing institutional strengthening, many experience partial or uneven reform paths, and some exhibit clear divergence between integrity systems and regulatory quality. Because Africa is both the largest and most internally varied region in the dataset, understanding this spread is crucial for interpreting global patterns of institutional development and assessing whether governance reforms tend to reinforce or offset one another over time.

4.2 Conclusion

This report has used two World Bank indicators, Control of Corruption from the Worldwide Governance Indicators and the Business Regulatory Environment score from the CPIA, to map how different dimensions of governance cluster together across 86 low and lower middle income countries between 2005 and 2023. The analysis has been descriptive by design. Rather than searching for single causes, it has focused on documenting where corruption control and business regulation move together, where they diverge, and how these patterns vary across regions and over time.

Three main findings stand out. First, corruption control and regulatory quality are positively related at the global level, but only moderately so. The overall correlation of roughly 0.45 and the upward sloping clouds in Figures 1, 6, and 7 show that countries with stronger integrity systems usually also have better business regulation. At the same time, there is a lot of dispersion around the trend line. Many countries sit in the middle of the distribution, and a non-trivial number fall into asymmetric quadrants where performance on one dimension is noticeably stronger than on the other. Governance strengths therefore tend to be multidimensional, but they are not perfectly synchronized.

Second, the time series results underline that governance does not improve in a smooth or uniform way. Global averages show a mild upward drift in corruption control since the mid 2010s, alongside a gradual decline in the quality of the business regulatory environment. The time-varying correlation in Figure 8 reinforces this picture. Periods in which the two indicators move in lockstep are followed by episodes of partial decoupling, especially around 2014 to 2018, before some reconvergence in the early 2020s. These dynamics suggest that reform efforts, crises, and external shocks can affect different parts of the institutional landscape in distinct ways. Anticorruption campaigns, regulatory tightening, or fiscal stress may help one dimension while leaving the other stagnant or even weaker.

Third, regional and country level patterns highlight how strongly geography and political history shape institutional outcomes. Europe and Oceania contain a high share of countries in the High CC, High BREG quadrant, consistent with stronger rule of law traditions and more mature regulatory systems. Africa and parts of Asia and Latin America are more heavily represented in the Low CC, Low BREG quadrant, with fragile and conflict affected states clustered at the very bottom. Within Africa in particular, country level correlations range from strongly positive to clearly negative, showing that even within a single region some states experience coordinated institutional strengthening while others face fragmented or unstable reform paths. The biggest improvers and decliners in corruption control illustrate these dynamics in concrete form, with post conflict recovery, political liberalization, and state collapse all leaving distinct signatures in the data.

These findings have several implications. For researchers, they show that it is risky to treat governance as a single latent trait that moves up or down in one piece. Different dimensions can develop at different speeds, and long run averages can conceal important variation over time and across regions. For practitioners and policy makers, the results highlight the importance of coherent reform strategies. Countries that have improved in both corruption control and regulatory quality tend to be those where reforms were broad in scope, sustained over many years, and supported by political coalitions that protected them from reversal. Partial or narrowly targeted reforms appear more fragile, especially in settings where conflict, economic stress, or international shocks undermine institutional capacity.

The analysis also has clear limitations. It relies on two specific World Bank indicators that are shaped by expert judgment and perceptions, and it focuses on IDA eligible countries rather than the full global system. The use of simple correlations and quadrant classifications cannot capture the deeper political economy mechanisms that generate change. Future work could extend this descriptive mapping in several directions. One option would be to link these governance profiles to outcomes such as investment, growth, or social spending. Another would be to examine the timing of specific reform episodes, elections, or conflicts to better understand why some countries move between quadrants while others remain stuck.

Despite these limits, the report has shown that even relatively simple tools, used carefully, can reveal meaningful structure in cross national governance data. Corruption control and business regulatory quality are related, but they do not move in lockstep. Regions differ sharply in their institutional configurations, and within each region individual countries trace distinctive trajectories over time. Recognizing this complexity is a necessary first step for any attempt to explain why governance looks the way it does, and for designing reform strategies that are both ambitious and realistic.

World Bank. 2024a. “Country Policy and Institutional Assessment (CPIA).” https://databank.worldbank.org/source/country-policy-and-institutional-assessment.
———. 2024b. “Worldwide Governance Indicators (WGI).” https://www.worldbank.org/en/publication/worldwide-governance-indicators.