Social capital and stock price crash risk: cross-country evidence

Explaining digital payments adoption with econometrics and explainable machine learning: cross-country evidence from a global household survey

This study examines the determinants of adoption of the International Financial Reporting Standards for Small and Medium-Sized Entities (IFRS for SMEs) using cross-country evidence. Despite the growing importance of SMEs in global economies, empirical research on the adoption of IFRS for SMEs remains limited compared to studies on full IFRS. Drawing on data from 88 countries that have adopted IFRS for SMEs, this study investigates whether governance quality, prior experience with full IFRS, and cultural factors influence adoption decisions. Secondary data were obtained from the IFRS Foundation and the World Bank and analyzed using regression techniques. The findings indicate that governance-related factors do not constitute significant barriers to the adoption of IFRS for SMEs. Furthermore, experience with full IFRS and language-related cultural factors are not found to be significant determinants of adoption. These results suggest that IFRS for SMEs represents a flexible and broadly applicable reporting framework that can be implemented across diverse institutional environments. The study contributes to the international accounting literature by providing large-sample empirical evidence on IFRS for SMEs adoption and offers policy-relevant insights for regulators and standard setters seeking to promote harmonized financial reporting for SMEs.

This study investigates the impact of key economic and financial variables on the Corruption Perception Index (CPI) across countries. The objective is to identify the most significant predictors of perceived corruption. The analysis employs a variety of quantitative methods, including Linear Regression, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Attention-RNN, and Random Forest models. The results demonstrate that GDP per capita is the most influential factor in explaining variations in corruption perceptions. Among financial sector indicators, variables reflecting active banking operations (such as outstanding loans and deposits) showed stronger predictive power than digitalization metrics (e.g., number of bank branches and ATMs). This suggests that the intensity of financial activity plays a more critical role than the mere availability of banking infrastructure. The study concludes that fostering economic growth and stimulating active engagement with the formal financial system are effective strategies for reducing corruption perceptions. Policy recommendations include addressing unemployment and promoting the formalization of remittance flows.

Purpose This study aims to investigate the drivers and barriers that influence women’s capacity to innovate in public services. A theoretical framework and related hypotheses are proposed by drawing on new public management theory, self-determination theory and gender theory. Design/methodology/approach The hypotheses are tested on survey data gathered in six European countries (N = 736). Findings The results show that women managing public services innovation face more barriers and drivers than men in the European context. Barriers to public services innovation in Europe are gendered. Originality/value The findings presented here challenge some assumptions from new public management theory and self-determination theory. Also, the role of women in managing public services innovation appears to be evolving over time. The implications of these findings for research and policy are highlighted.

This research paper focuses on the role of average working hours (AVHs) of the labor force in explaining the variation in QOL across countries, which is an important but unexplored area in the empirical literature. Using data from 62 countries and employing several econometric techniques, we show that long AVHs are detrimental for improved QOL. The sub-sample results demonstrate that AVHs have a significant detrimental impact on the QOL of the population only in the case of developing countries. However, in the case of developed countries, the influence of AVHs is insignificant as these countries are enjoying relatively reduced AVHs as compared to developing countries. Moreover, our results indicate that the labor force participation rate, human capital, government expenditures, internet use, and electricity consumption are the main driving forces behind a better QOL both in developed and developing countries. Finally, we found evidence that trade openness is an irrelevant factor in explaining the variation in QOL as it is insignificant in most of the specifications despite possessing a positive coefficient.

ABSTRACT We present a practical measure of the sensitivity of the income poverty headcount ratio (at-risk-of-poverty rate) to OECD-type equivalence scales, along with a method to assess the robustness of poverty comparisons across time and/or space. Using 2004–2021 EU-SILC microdata for 31 European countries, we estimate how small changes in adult and child weights affect poverty rates, country rankings, and individual non/poor classifications. We find that the sensitivity of the income poverty headcount to equivalence-scale weights is substantial and varies across countries. Sensitivity depends on both household structure and the income distribution, often in nonlinear ways, so the same change in weights can increase the poverty rate in one context and reduce it in another. While many country rankings are broadly stable across plausible weight combinations, equivalence adjustments can reclassify individuals and shift ranks, particularly in countries with certain types of household compositions or higher inequality. These patterns highlight that relying on a single equivalence scale may easily misrepresent poverty, and that robustness checks and complementary non-monetary indicators are important for accurate poverty assessment.

ABSTRACT ESG policy uncertainty may reshape monetary policy transmission during the green transition. We examine how global and domestic ESG policy uncertainty affects monetary policy effectiveness in China, the United States, and Japan. Extending a New Keynesian framework, we link ESG uncertainty to expected transition costs and risk premia that shift money demand and capital spreads. Bayesian VAR results show global ESG uncertainty dominates domestic shocks. China eases initially then tightens as spreads widen; the United States tightens persistently with strong spread repricing; Japan responds weakly. We provide cross-country evidence and a framework integrating ESG uncertainty into monetary policy analysis.

As a cornerstone of the modern financial safety net, the Lender of Last Resort (LOLR) is essential in mitigating liquidity crises and containing financial contagion. However, during periods of economic stability, risk-taking incentives in the banking sector may undermine its effectiveness. Using quarterly panel data from 55 countries over the period 2010–2023, this study employs a two-way fixed effects model to assess the impact of LOLR support on systemic financial risk and its transmission mechanisms. We find that LOLR support significantly increases systemic risk during stable economic periods. Mechanism analysis indicates that this effect is channeled through the erosion of bank asset liquidity, expansion of financial leverage, and deterioration in asset quality. Moreover, the adverse impact is more pronounced in emerging economies, bank-dominated financial systems, countries with low capital adequacy ratios, underdeveloped regulatory frameworks, and lower levels of digital technology adoption. This study provides cross-country evidence on the potential negative consequences of central bank rescue functions during calm periods and offers important policy insights for optimizing the LOLR framework and building a more resilient financial safety net.

As demand for AI hardware increases, semiconductor industry policies, through subsidies, tax credits, and targeted financing, are expanding, leading to uneven distribution of policy support documents and strategic frameworks, as well as long implementation delays. This paper proposes a replicable measurement process to identify semiconductor-related interventions in global trade alerts through iterative validation. Each indicator is categorized according to value chain objectives and policy tools, providing a dataset and evaluation framework for semiconductor research.

Abstract Consumption of transportation fuels and red meat is a major contributor to climate change. The difficulties in implementing price-based instruments to address the climate impact of these goods have led several researchers and government authorities to float the idea of using rationing. However, little attention has been devoted to understanding what the general public thinks about such prescriptive measures and, of this work, none have explored the individual-level mechanisms behind the acceptability of climate-motivated rationing. Utilizing original large-scale survey data from five countries, this study examines how political ideology and perceived fairness, effectiveness, and intrusiveness of government intervention are related to the public acceptability of fossil fuel and meat rationing. It is demonstrated that these factors explain variation in the acceptability of fuel and meat rationing among respondents in the US and Germany, slightly so in Brazil, but to a lesser extent among respondents in India and South Africa. In contrast to prior research, perceived intrusiveness has a particularly strong impact on attitudes towards rationing, trumping the effects of perceived fairness and effectiveness. Political ideology is predictive of acceptability of fuel rationing in all countries but South Africa, while it explains less or no attitudinal variation regarding meat rationing. The findings contribute to expanding the current literature which has almost exclusively focused on public opinion of carbon taxes. Particularly, the cross-country differences add important nuances about these key determinants, raising questions over the universality of prior scientific insights and prompting further research in culturally and politically diverse contexts.

Policy impacts on bioenergy development: Cross-country evidence based on analysis

Despite seven decades of international commitment—from the 1948 Universal Declaration of Human Rights through SDG 3.8—universal health coverage remains stubbornly out of reach. Two billion people, predominantly informal sector workers, lack access to sustainable health insurance. This entry explains the underlying cause: sustainable health insurance requires specific behavioral and institutional conditions for collective action—conditions that existing health insurance models systematically fail to satisfy, thereby structurally excluding informal populations. The Trinity Law framework formalizes these conditions as three multiplicatively interacting requirements—Trust (T), Consensus (C), and Dual Benefit (DB)—expressed as S = T × C × DB. Empirical analysis of community-based health insurance schemes across 24 countries identifies a robust trust threshold (τ* ≈ 0.68) operating as a behavioral phase transition: below this level, cooperation collapses; above it, participation becomes self-sustaining. Cross-country evidence from 274 organizations across 155 countries confirms consensus thresholds (C* ≈ 0.59), while analysis of 158,763 observations validates dual benefit mechanisms. The multiplicative structure explains why partial reforms fail: weakness in any single component drives overall sustainability toward zero. Applied to health insurance, this framework distinguishes conventional systems—Bismarckian employment-based, Beveridgean tax-financed, and commercial health insurance from sustainable systems like participatory community-based microinsurance that satisfy all three Trinity Law conditions through participatory design, transparent governance, and aligned incentives. The persistent UHC gap reflects not implementation failures but fundamental design incompatibilities that the Trinity Law makes explicit. This entry has three objectives: first, it states the Trinity Law conditions; second, it summarizes the empirical evidence for each component; third, it applies the framework to classify major health insurance models. Supporting datasets and code are available in the referenced Zenodo repositories. The term ‘law’ follows the tradition of social science regularities like the ‘law of demand’: a robust empirical pattern with strong predictive validity, not a claim to physical certainty.

Digital transformation has emerged as a major catalyst for reform in contemporary public administration, reshaping how governments design, deliver, and evaluate public services. This literature review synthesizes key findings from international studies to map the dynamics of technological innovation and bureaucratic adaptation in the era of digital government. The results demonstrate that technologies such as artificial intelligence, blockchain, cloud computing, and the Internet of Things accelerate administrative processes, enhance accuracy, reduce service costs, and strengthen transparency and accountability. However, the review also emphasizes that technological advancement alone is insufficient; the success of digital transformation depends on the capacity of public institutions to reorganize work structures, build digital competencies, and shift bureaucratic culture toward more adaptive and collaborative practices. Furthermore, digital participation platforms have expanded opportunities for citizen engagement, yet persistent digital divides—driven by socio-demographic disparities and unequal access to infrastructure—pose significant challenges to inclusive participation. The literature also reveals recurring barriers related to infrastructure readiness, cybersecurity, resistance to change, and limited digital literacy among public employees. Cross-country evidence from Turkey, Singapore, Italy, Iran, and the UAE shows similar transformation patterns, highlighting bureaucratic adaptation as a mediating factor between technological innovation and governance outcomes. Overall, this review offers an integrated conceptual understanding of digital transformation in public services and underscores the need for holistic strategies that combine technological investment, organizational reform, and inclusive governance to ensure sustainable and equitable digitalization.

Purpose Patient experience is commonly assessed through surveys that measure health gains and perceptions of episodes of care. This approach reveals fatigue and falling response rates, indicators of misalignment between patients and healthcare providers. This study proposes to broaden the patient experience perspective beyond episodes. By assuming a patient journey in which digital technology is increasingly prominent, this study aims to identify the capabilities that healthcare provider organisations should develop to enhance patient experience. Design/methodology/approach The study employed a structured six-step process of thematic analysis within a qualitative research design. Data were collected through semi-structured interviews with healthcare executives from 11 countries. The data were thematically coded using MAXQDA software. To reinforce reliability, the triangulation for convergence technique was applied using data from 88 abstracts published during 2023 and 2024. This secondary data from 21 countries corroborated the findings. Findings Grounded in the theories of structuration and dynamic capabilities, the study proposes the Honeycomb capabilities framework and develops six propositions. This framework contributes to the management of healthcare provider organisations by identifying key capabilities to enhance patient experience. The study formulated implications for research, practice and society. Research limitations/implications CX in healthcare is not PX. The two concepts have different roots in literature and practice and should not be used interchangeably. PX concept extension is necessary in scope and measurements to align practice with praxis. This study reinforces the thesis from Seidl and Whittington (2014) that the SAP research agenda should be enlarged and interplay with other research streams. Practical implications Managers should assume responsibility and be accountable for PX. PX is not a departmental function but an HCPO mission. HCF can be a roadmap to develop dynamic capabilities at the top management level. Social implications Many of the benefits of prominent public policies, such as open data policies or common data spaces, depend on patients’ behaviours, including adoption, engagement, altruism, consent or choices. In turn, these behaviours require a positive PX, which relies on HCPOs and the patient’s relationship. Originality/value This study proposes a novel approach to patient experience by augmenting its scope beyond the patient encounters. The finding suggests that healthcare managers are accountable for developing specific dynamic capabilities to succeed. The study design, grounded in cross-country evidence, facilitates the generalisation.

Type of the article: Research ArticleAbstractAs emphasized by the FATF, IMF, and World Bank, technological readiness and institutional quality are increasingly decisive in shaping AML effectiveness. By mitigating money-laundering vulnerabilities, strengthening AI readiness, and enhancing institutional quality, tax collection efficiency can be improved and fiscal leakages reduced. These improvements expand the fiscal space available for national budgets, strengthening the financial foundations of public administration. The study aims to examine the impact of Government AI Readiness on AML risk, measured by the Basel AML Index, and the moderating role of institutional quality as captured by the Rule of Law Index. An unbalanced panel dataset that covers up to 168 countries for 2020–2024 was analyzed using fixed effects and random effects models, with variable transformations applied where necessary. All estimations were performed in R Studio. The results indicate that a one-point increase in the Government AI Readiness Index is associated with a 0.048–0.040 point reduction in the Basel AML Index, while a one-unit increase in log GDP per capita decreases the Basel AML Index by 0.54–0.34 points, holding other factors constant. The interaction term between AI readiness and the Rule of Law Index is positive (0.067–0.072), confirming that the risk-reducing effect of AI readiness diminishes as institutional quality strengthens. These findings support the hypotheses and confirm the complementary roles of technological preparedness and institutional integrity in shaping AML outcomes. Fixed effects analysis reveals structural vulnerabilities in AML in Gabon and China, while Sweden exhibits the lowest residual risk after accounting for AI readiness and institutional strength.AcknowledgmentThis article was supported by the Ministry of Education and Science of Ukraine (project No. 0123U101945 – National security of Ukraine through prevention of financial fraud and money laundering: war and post-war challenges).

This comparative review is about how sex ratio imbalances affect marriage, culture, and economy. Taking Australias historical experience as the main reference (quasi-natural experiment), and cross-country evidence in 2015-2025, we identify three linked channels: (1) labor market outcomes and gender roles; (2) marriage and household economic behavior particularly housing demand, saving, and portfolio choice; and (3) persistence of culture and the protective role of institutions. A higher proportion of males raises the intensity of marriage competition, increases housing demand (including multi-home purchases) and the value of parental housing wealth, drives households to save more and, in some context, to hold riskier asset portfolios. It may also embed gender norms, entrench traditional female roles, and affect womens labor participation with heterogeneous impacts on crime depending on welfare and governance capacity. Public goods such as sanitation enter marriage matching and can make a difference to marriage surplus. Compared to China, the long-run sedimentation of culture versus a rapid and financialized housing channel are illustrated through a comparison of Australia, China, India, Sweden, etc. A final conclusion of this review is that institutions and policy may alter the above three channels. Policy implications include (1) addressing the root cause of imbalances; (2) decoupling marriage from housing; (3) coordinating housing finance policy; (4) more investment in childcare and anti-discrimination; (5) improving public goods; (6) strengthening social governance.

Tax evasion and climate change are usually examined in separate domains, public finance and environmental policy. Yet growing scholarship highlights their intersection: fiscal non-compliance undermines governments’ ability to fund and enforce effective climate action. This paper reviews literature linking tax evasion to climate change across four dimensions: the erosion of fiscal space, the shadow economy’s environmental harm, corporate tax avoidance and weak environmental, social and governance (ESG) performance, and the role of tax havens in financing polluting activities. The review finds that tax evasion reduces the fiscal capacity needed for climate mitigation and adaptation, sustains shadow economy activities that contribute to deforestation and pollution, and is consistently associated with weaker corporate environmental and sustainability practices. It also shows that tax havens facilitate the financing and concealment of environmentally destructive operations, thereby weakening global environmental governance. The review contributes by synthesizing fragmented debates into a unified framework and identifying gaps, including limited cross-country evidence and weak integration of tax compliance into climate finance. It concludes that combating tax evasion is not only a fiscal priority but also a climate imperative.

Despite the growing interest in income inequality, cross-country evidence often shows variation between measures and databases, which complicates research and policy evaluation. The objective of the article is to compere the consistency of data on income inequality in postsocialist countries from Central and Eastern Europe and Central Asia for the commonly used measures on the basis of leading databases in this area. Other such analyses typically focus on individual measures, databases or specific countries, which prompted the idea to fill the research gap for a targeted country group. The formulated hypotheses were to test the consistency of the following: development trends, the rankings of countries from the most to the least equal in terms of income, and the values for different measures indicated by databases. The study reveals high correlations in income inequality trends over the long term, particularly among the EU subgroups. Certain consistency was observed in the context of identifying countries with extreme income equality or inequality, and in the rankings between different measures from the same database. However, there was no full consistency, especially in non- EU countries, which highlights the impact of the methodological differences. This article contributes to the existing body of research on income inequality by providing a broad analysis of the consistency and variability of the related data across different measures and databases, with a particular focus on post-socialist countries. It points to the importance of careful data selection when analyzing income inequality in the indicated group of countries, as individual differences between measures, databases and countries tend to affect the final results of the research.

Fostering sustainable futures through global peace and eco-innovation: A cross-country evidence