The British Crown Dependency of Jersey was ranked as the most politically stable country worldwide in 2023, ahead of the Cayman Islands and Liechtenstein. The Caribbean Islands are known for their favorable conditions for large international companies and wealthy individuals, with no income and fortune tax. Lowest stability in Syria On the other end of the scale, Syria had the lowest political stability. The Middle Eastern-country suffered from a civil war between 2012 and 2024, with the Syrian government battling a range of military groups, including the terrorist organization Islamic State. Fragile State Index Another way of measuring political stability is the Fragile States Index, compiled annually by the Fund for Peace. In 2024, Somalia was ranked as the most fragile state ahead of Sudan. The index measures state fragility on a range of economic, social, and political indicators.

The average for 2023 based on 193 countries was -0.07 points. The highest value was in Liechtenstein: 1.61 points and the lowest value was in Syria: -2.75 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

The average for 2023 based on 20 countries was -0.17 points. The highest value was in Costa Rica: 0.98 points and the lowest value was in Haiti: -1.43 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

The average for 2023 based on 24 countries was 0.47 points. The highest value was in Aruba: 1.43 points and the lowest value was in Haiti: -1.43 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

Syria, with a score of minus 2.75, was ranked as the politically least stable country worldwide in 2023 ahead of Iraq and Somalia. The country has been riddled by civil war since 2012, with the Syrian government battling a range of different factions. Syrian Civil War has resulted in large number of refugees The ongoing fighting and resulting instability in Syria has led to 6.2 million people fleeing the country, making it the largest source country of refugees worldwide. Over half of the Syrian refugees today live in neighboring Turkey. Fragile State Index Another way of measuring political stability is the Fragile States Index compiled annually by the Fund for Peace. In 2024, Somalia was ranked as the most fragile state ahead of Sudan. The index measures state fragility on a range of economic, social, and political indicators.

The average for 2023 based on 11 countries was -0.02 points. The highest value was in Singapore: 1.42 points and the lowest value was in Burma (Myanmar): -2.13 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

Country Risk Assessment helps businesses to confidently evaluate global markets by incorporating country evaluation into strategic planning. Analysing trends over time to forecast and proactively plan for potential market shifts.

Country Risk Assessment is an estimate of the average credit risk of a country’s businesses. It is drawn up based on macroeconomic, financial and political data. It offers: - An indication of a country’s potential influence on businesses’ financial commitments. - Insight into the economic and political environment that could impact credit risk.

Dataset Structure and Content: Assessment Coverage: 20 sample companies with country risk evaluations Geographic Diversity: Multiple countries represented via ISO-3166 alpha2 country codes.

Risk Classification System: The dataset employs a standardized A-E rating scale to categorize country risk levels: A1: Very good macroeconomic outlook with stable political context and quality business climate (lowest default probability) A2: Good macroeconomic outlook with generally stable political environment A3: Satisfactory outlook with some potential shortcomings A4: Reasonable default probability with potential economic weaknesses B: Uncertain economic outlook with potential political tensions C: Very uncertain outlook with potential political instability D: Highly uncertain outlook with very unstable political context E: Extremely uncertain outlook with extremely difficult business conditions (highest default probability)

Application Context: This sample demonstrates how country risk assessments can be systematically documented and tracked over time. Each assessment includes comprehensive evaluations of the macroeconomic environment, political stability, and business climate factors that directly influence payment behavior and default probabilities. The dataset structure allows for both current and historical tracking, enabling trend analysis and comparative risk evaluation across different national markets. It serves as a representative example of how comprehensive country risk data can be organized and utilized for strategic business decision-making. Note: This is sample data intended to demonstrate the structure and capabilities of a country risk assessment system.

Learn More For a complete demonstration of our Country Risk Assessment capabilities or to discuss how our system can be integrated with your existing processes, please visit https://business-information.coface.com/economic-insights to request additional information.

In 2023, Mali had the lowest score in the political stability and absence of violence or terrorism index in West Africa, at minus 2.73 points. Therefore, the country was considered completely politically unstable. In that year, all the West African countries recorded negative index values.

The average for 2023 based on 47 countries was -0.66 points. The highest value was in Botswana: 1.04 points and the lowest value was in Mali: -2.73 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

Countries use economic sanctions as a way to force their opponents to make policy concessions. Such external pressure may, as the designers of sanctions often intend, affect the degree of domestic support for the target's political leaders. It may even threaten the leaders’ survival in office. We investigate how these dual pressures—preference for policy concessions and concern about target leaders’ political future—shape the use of sanctions in the context of political relations between the sanctioning and sanctioned countries. The political relations between the two countries matter because a decline in the likelihood of the target leader's political survival results in a cost for the sanctioner when the target is a friendly regime and generates a benefit when the targeted regime is an adversary. Therefore, we argue, and show statistically, that economic coercion is more likely for friendly governments when they are politically stable and unfriendly governments when they are politically vulnerable. We illustrate our causal mechanism using declassified primary sources for two case studies of US sanctions against Chile.

In 2024, Norway was considered the world's least fragile state with an index score of **** on a scale from zero to ***, where a higher score suggests the state is more fragile. Finland was ranked as the second most stable country globally, followed by Iceland. Meanwhile, Somalia was ranked as the most fragile state. The Fragile States Index assigns each country a score based on a range of social, economic, and political indicators.

Political stability in North Africa remains a significant challenge, with all countries in the region recording negative index values in the political stability and absence of violence/terrorism index. As of 2023, Sudan recorded the lowest stability score in the region at -2.47. The country has seen a sharp and sustained decline in stability since 2020. This was in the aftermath of the 2019 protests, which led to the ousting of President Omar al-Bashir. The political situation worsened further in April 2023 as a result of the conflict between the Sudanese Armed Forces (SAF) and the Rapid Support Forces (RSF), triggering widespread displacement and insecurity. Corruption, repression, and media control A lack of political freedoms and press freedom plays a significant role in shaping perceptions of instability. According to the World Press Freedom Index in 2024, countries like Egypt and Algeria fall into the categories of a “very serious” or “difficult” situation for media freedom, scoring 25.1 and 41.98 out of 100, respectively. Even relatively higher scorers such as Tunisia and Morocco remain in the “difficult” range. Limited press freedom and government control over information reduce transparency and restrict public oversight. This environment facilitates systemic corruption, as independent media are unable to investigate or report on abuses of power. Repressive state measures, including censorship and legal threats against journalists, further undermine institutional checks and balances. Combined with weak governance and the influence of organized crime, these dynamics contribute to persistent political instability across the region. Organized criminal networks The consequences of restricted transparency are reflected in high levels of perceived corruption and deeply embedded criminal networks. According to the 2024 Corruption Perceptions Index, Libya scored just 13 out of 100, while Egypt, Algeria, Morocco, and Tunisia all scored below 40, indicating high public concern about government corruption. These concerns align with findings from the ENACT Organized Crime Index, which highlights the dominance of state-embedded actors and criminal networks in the region. With scores of 7.67 and 5.67 respectively, the data suggests that criminal activities are often closely tied to political and institutional power structures. This interconnection between corrupt governance and organized crime further erodes public trust and reinforces the perception, and reality, of chronic instability across North Africa.

Country Risk Assessment helps businesses to confidently evaluate global markets by incorporating country evaluation into strategic planning. Analysing trends over time to forecast and proactively plan for potential market shifts.

Country Risk Assessment is an estimate of the average credit risk of a country’s businesses. It is drawn up based on macroeconomic, financial and political data. It offers: - An indication of a country’s potential influence on businesses’ financial commitments. - Insight into the economic and political environment that could impact credit risk.

Dataset Structure and Content: Assessment Coverage: 20 sample companies with country risk evaluations Geographic Diversity: Multiple countries represented via ISO-3166 alpha2 country codes.

Risk Classification System: The dataset employs a standardized A-E rating scale to categorize country risk levels: A1: Very good macroeconomic outlook with stable political context and quality business climate (lowest default probability) A2: Good macroeconomic outlook with generally stable political environment A3: Satisfactory outlook with some potential shortcomings A4: Reasonable default probability with potential economic weaknesses B: Uncertain economic outlook with potential political tensions C: Very uncertain outlook with potential political instability D: Highly uncertain outlook with very unstable political context E: Extremely uncertain outlook with extremely difficult business conditions (highest default probability)

Application Context: This sample demonstrates how country risk assessments can be systematically documented and tracked over time. Each assessment includes comprehensive evaluations of the macroeconomic environment, political stability, and business climate factors that directly influence payment behavior and default probabilities. The dataset structure allows for both current and historical tracking, enabling trend analysis and comparative risk evaluation across different national markets. It serves as a representative example of how comprehensive country risk data can be organized and utilized for strategic business decision-making. Note: This is sample data intended to demonstrate the structure and capabilities of a country risk assessment system.

Learn More For a complete demonstration of our Country Risk Assessment capabilities or to discuss how our system can be integrated with your existing processes, please visit https://business-information.coface.com/economic-insights to request additional information.

IntroductionThe One Health concept has proposed an integrated and unified approach aiming for health balance and enhancement by recognizing the interdependence of human, animal, and environmental health. The COVID-19 pandemic has pushed global One Health initiatives and policy improvement toward preventive measures for future pandemics, particularly of zoonotic origin. Such a scenario may be particularly relevant for South America, which is considered highly vulnerable due to its natural biodiversity superposed to socioeconomic and environmental issues, demanding effective methods and indicators for proper One Health strategies and goals that are aligned with macroregional contexts.MethodsAccordingly, the present study aimed to assess the One Health Index (OHI) in South American countries, along with potential interactions with socioeconomic indicators. The results obtained using clustering analysis and permutational multivariate analysis of variance (PERMANOVA) have revealed a positive association between the OHI and the Human Development Index (HDI) but not with gross domestic product (GDP).ResultsAlthough South American countries with political stability, robust investment in health, and progressive policies have shown a higher OHI, better environmental health is not associated with better human and animal health. In addition, although the Amazon biome— spanning 9 of the 12 South American countries—has positively impacted environmental health, this benefit contrasts with the rudimentary local human health systems, highlighting the complexity of One Health within the South American context. The lack of stronger indicators for animal health was also considered an important weak point for a true OHI assessment. Nonetheless, countries with more developed livestock have presented better animal health, which may not reflect an overall animal health indicator, as companion and wildlife animal health indicators were not available.DiscussionAlthough lower (within-country) scale analysis such as states and metropolitan areas may better shape internal differences, the study herein has clearly shown One Health inequalities and challenges among South American countries. Equally important, forests and other natural areas in developing countries, particularly the Amazon, should receive incentives to promote sustainable economic growth. This approach would help prevent sacrificing environmental health for the benefit of human and livestock animal health.

Country Risk Assessment helps businesses to confidently evaluate global markets by incorporating country evaluation into strategic planning. Analysing trends over time to forecast and proactively plan for potential market shifts.

Country Risk Assessment is an estimate of the average credit risk of a country’s businesses. It is drawn up based on macroeconomic, financial and political data. It offers: - An indication of a country’s potential influence on businesses’ financial commitments. - Insight into the economic and political environment that could impact credit risk.

Dataset Structure and Content: Assessment Coverage: 20 sample companies with country risk evaluations Geographic Diversity: Multiple countries represented via ISO-3166 alpha2 country codes.

Risk Classification System: The dataset employs a standardized A-E rating scale to categorize country risk levels: A1: Very good macroeconomic outlook with stable political context and quality business climate (lowest default probability) A2: Good macroeconomic outlook with generally stable political environment A3: Satisfactory outlook with some potential shortcomings A4: Reasonable default probability with potential economic weaknesses B: Uncertain economic outlook with potential political tensions C: Very uncertain outlook with potential political instability D: Highly uncertain outlook with very unstable political context E: Extremely uncertain outlook with extremely difficult business conditions (highest default probability)

Application Context: This sample demonstrates how country risk assessments can be systematically documented and tracked over time. Each assessment includes comprehensive evaluations of the macroeconomic environment, political stability, and business climate factors that directly influence payment behavior and default probabilities. The dataset structure allows for both current and historical tracking, enabling trend analysis and comparative risk evaluation across different national markets. It serves as a representative example of how comprehensive country risk data can be organized and utilized for strategic business decision-making. Note: This is sample data intended to demonstrate the structure and capabilities of a country risk assessment system.

Learn More For a complete demonstration of our Country Risk Assessment capabilities or to discuss how our system can be integrated with your existing processes, please visit https://business-information.coface.com/economic-insights to request additional information.

CODE.PY OUTPUT

Institutional Benchmarking and Regression Results

To contextualize institutional performance, we first compare India and Pakistan against the global mean of common-law economies on three governance indicators: Protecting Minority Investors (PMI), Enforcing Contracts (EC), and a composite index of the Legal-Political Environment. The global averages for common-law countries are:

• PMI: 18.6

• EC: 37.9

• Legal-Political Environment: 7.44 (on a 0–10 scale)

Relative to these benchmarks:

• India outperforms the PMI average by 5.6 ranks, but underperforms EC by 125.1 ranks and legal-political environment by 2.74 points.

• Pakistan underperforms on all three: +9.4 ranks in PMI (worse), +118.1 ranks in EC, and –4.24 points on legal-political environment.

These gaps suggest that formal investor protections (PMI) are stronger in India, but contract enforcement and broader institutional trust lag significantly in both countries.

Regression Analysis: Institutional Predictors of Governance Outcomes

We ran robust Ordinary Least Squares (OLS) regressions with Control of Corruption (cc), Rule of Law (rl), and Political Stability (pv) (from the Worldwide Governance Indicators) as predictors of country performance in both PMI and EC.

✅ Protecting Minority Investors (PMI)

• Model Fit: R² = 0.364; F(3, 182) = 46.91; p < 0.001

• Significant predictors:

  • Rule of Law (β = –62.74, p < 0.001): Strong negative relationship, consistent with countries with weaker rule of law having higher PMI ranks (i.e., worse protections).

  • Political Stability (β = +22.28, p < 0.001): Higher stability is associated with better (lower) PMI rank.

  • Control of Corruption (β = +15.91, p = 0.078): Marginally significant.

✅ Enforcing Contracts (EC)

• Model Fit: R² = 0.389; F(3, 182) = 52.32; p < 0.001

• Significant predictors:

  • Rule of Law (β = –47.55, p < 0.001): Again, weak rule of law predicts poor performance.

  • Political Stability (β = +11.27, p = 0.029): More stable environments enforce contracts more efficiently.

  • Control of Corruption was not significant (p = 0.61).

These results underscore the salience of Rule of Law and Political Stability in explaining variation in corporate governance effectiveness across countries.

Peer-Adjusted Z-Scores: Rule of Law and Judicial Independence

To further refine the comparison, we standardized India and Pakistan’s scores relative to global peers using z-scores:

• India: Judicial Independence z = +1.39, Rule of Law z = +1.28

• Pakistan: Judicial Independence z = +0.25, Rule of Law z = –0.95

This highlights India’s relative institutional strength in legal capacity, while Pakistan falls below global norms, particularly on rule of law.

CODE2.PY OUTPUT

Summary Statistics and Cross-National Comparison

We begin by comparing key governance indicators for India and Pakistan over the 1996–2020 period using data from the V-Dem dataset. Table X reports descriptive statistics for six core institutional quality variables:

• v2x_rule: Rule of Law

• v2x_jucon: Judicial Constraints on the Executive

• v2xlg_legcon: Legislative Constraints

• v2x_freexp: Freedom of Expression

• v2x_polyarchy: Electoral Democracy Index

• v2x_corr: Control of Corruption

Key Observations from the 23-year panel:

• Rule of Law (v2x_rule): India displays a high mean score of 0.579 (SD = 0.029), while Pakistan lags significantly behind at 0.237 (SD = 0.023).

• Judicial Constraints (v2x_jucon): India again leads with a mean of 0.814, compared to 0.537 for Pakistan.

• Control of Corruption (v2x_corr): Interestingly, Pakistan scores higher (0.868) than India (0.566), suggesting a potential data artifact or performative anti-corruption signaling.

These descriptive statistics show a consistent pattern of stronger rule-of-law institutions in India. However, India’s governance edge does not hold across all indicators—especially corruption control, which exhibits counterintuitive results.

T-Test Results: India vs. Pakistan

We formally test whether the differences in means between India and Pakistan are statistically significant using two-sample t-tests:

The highly significant differences in nearly all variables confirm that India and Pakistan follow distinct institutional trajectories—though India’s relative weakness in corruption control invites further scrutiny under the CMF framework.

Structural Breaks in India’s Democratic Governance

Using the ruptures package and a rolling t-test approach, we detect structural breakpoints in India’s democratic trajectory:

• Based on v2x_polyarchy, break years are identified at 2011, 2016, and 2021.

• The rolling t-test method suggests more granular shifts starting as early as 2001, with notable accelerations around 2011–2019.

These breakpoints align with major political and constitutional developments in India and support the CMF argument that formal continuity in legal benchmarks may obscure deeper institutional volatility.

CODE3.PY OUTPUT

Summary Statistics and Institutional Quality Comparison: India vs. Pakistan

We begin by reporting descriptive statistics for two core institutional variables—Control of Corruption (v2x_corr) and Judicial Constraints on the Executive (v2x_jucon)—drawn from the V-Dem dataset for the years 1996–2020:

• Control of Corruption (v2x_corr):

  • India: Mean = 0.566, SD = 0.027, indicating relatively consistent performance with moderate corruption control.

  • Pakistan: Mean = 0.868, SD = 0.051, suggesting surprisingly strong corruption scores, but with greater variability. This may reflect methodological distortions or performative anti-corruption institutions that lack substantive checks—a key focus of our Critical Macro-Finance (CMF) interpretation.

• Judicial Constraints (v2x_jucon):

  • India: Mean = 0.814, SD = 0.013, indicating strong and stable judicial oversight over executive actions.

  • Pakistan: Mean = 0.537, SD = 0.140, reflecting weaker, more volatile institutional constraints.

T-Test Results: Are India and Pakistan Statistically Different?

Two-sample t-tests confirm that these differences are highly statistically significant:

These results validate the hypothesis that India and Pakistan exhibit substantially divergent institutional trajectories—though not always in expected directions. India shows stronger judicial oversight, while Pakistan appears to outperform in corruption metrics, warranting

This study investigates the relationship between democracy and innovation across 61 developing countries from 2013 to 2020, utilizing data from Global Innovation Index. Employing the Freedom House Index and Polity2 indicators as proxies for democracy, research employs Ordinary Least Squares (OLS), Fixed Effects and SystemGMM techniques to analyze their impact on innovation. The findings of the study reveal no statistically significant relationships between democracy and innovation in developing nations within specified timeframe. Through empirical analysis, including various econometric approaches, it is observed that the level of democracy as measured by these indicators, does not appear to exert a discernable impact on the innovation landscape of these countries. These results carry important implications for public policy. While the promotion of democracy remains a crucial goal, especially for societal development and political stability, this study suggests that solely focusing on enhancing democratic institutions might not necessarily yield immediate direct improvements in the innovation capacities of developing nations. Policymakers and stakeholders involved in fostering innovation ecosystems in these regions may need to consider a more nuanced approach, encompassing factors beyond the scope of democratic governance to effectively spur innovation. Understanding the nuanced relationship between democracy and innovation in developing countries has significant implications for designing targeted policies aimed at enhancing innovation capacities, economic growth and overall societal development in these regions.

Cambodia is emerging as one of the region’s most attractive countries for new business expansion and investments, driven by political stability and high economic growth over the past two decades, according to Lieutenant General Hun Manet.

Based on the Temporal Exponential Random Graph Models (TERGM), this paper applies global intellectual property trade data between countries to investigate the impact and mechanism of institutional distance on the intellectual property trade network. The study finds that the smaller the institutional distance between countries, the more conducive it is to build an intellectual property trade network. This conclusion remains valid after controlling for geographical adjacency, use of a common language, existence of colonial relationships, and characteristics of the intellectual property trade network. Moreover, through regression by year, it is found that this impact increases year by year. Further, after regressing on sub-indicators of institutional distance, it is found that the smaller the distance in political stability, government efficiency, and regulatory quality, the greater the probability of generating an intellectual property trade relationship. Mechanism analysis reveals that economies with smaller institutional distances are more likely to sign trade agreements, thereby generating trade relationships and promoting the establishment of intellectual property trade networks. In order to deeply participate in the intellectual property trade network, countries should actively align with international institutional norms and sign bilateral or multilateral trade agreements with countries with similar institutional levels to enhance the production level and export of intellectual property.

The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature, among others. The current version of the database, which is now hosted at the IDB, expands its coverage to about 180 countries for 42 years, 1975–2017. Researchers at the World Bank Development Research Group first compiled the database in 2000 (see citation information below). It has become one of the most cited databases in comparative political economy and comparative political institutions. Almost 3000 studies have used this database so far as a source of institutional and political data in their empirical analysis.