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The purpose of this research is to evaluate corruption in the context of India, spanning the period between 1988 and 2021. Additionally, it aims to provide an in-depth comprehension of the factors that drive its prevalence and to propose policy directives for addressing these underlying issues.

The study instead of relying on perception-based measures, takes a distinct approach by formulating a corruption index derived from reported instances, thus ensuring a more objective assessment. Furthermore, we employ stochastic frontier analysis to tackle the issue of under-reporting within the corruption index based on reported cases. Subsequently, an auto regressive distributed lag (ARDL) methodology is applied to ascertain the principal drivers of corruption, encompassing both long and short factors.

This study reveals that corruption in India is notably influenced by economic growth and income inequality. Conversely, government effectiveness and globalization display a tendency to mitigate corruption. However, our rigorous analysis demonstrates that financial development does not wield a substantial influence in our study. Moreover, our inquiry uncovers a nonlinear relationship between economic growth and corruption. Additionally, we ascertain that the long run and short run impacts of corruption remain relatively stable across both models utilized in our study.

This study differs from previous research in the subsequent manners. Primarily, we employed an objective measure to formulate the corruption index, coupled with addressing the underreporting issues via stochastic frontier analysis. Moreover, this study pioneers the identification of a non-linear relationship between corruption and economic growth within the Indian context, a facet unexplored in previous investigations.

This study aims to investigate the intricate relationship between corruption and the credit costs faced by small and medium-sized enterprises (SMEs) in OECD countries, a critical yet underexplored area in financial crime research. The primary aim is to dissect and understand how corruption impacts SMEs’ access to credit, highlighting a significant yet overlooked aspect of financial crime. This research seeks to fill a gap in the literature by providing empirical insights into the economic consequences of corruption, specifically on SMEs financing.

This study used secondary panel data from the World Bank and OECD databases. The data covered the period 2007–2020 for 25 OECD countries. This study used interest rate for SMEs loans as a dependent variable and GDP per capita, inflation and corruption index as independent variables. This study used the panel autoregressive distributed lag (ARDL) model to examine the relationship between variables.

The empirical findings derived from Panel ARDL postulate an intriguing dichotomy in the effects of GDP per capita, inflation rate and corruption on interest rates in both the short and long run. It was discerned that an increase in GDP per capita and inflation rate correlates with a decrement in interest rates in the long run, suggesting a potential compromise by central banks between controlling inflation and fostering economic growth.

This paper makes a novel contribution to the field of financial crime by illuminating the often-overlooked economic dimensions of corruption in the context of SMEs financing. It provides a unique perspective on the ripple effects of corrupt practices in credit markets, enriching the academic discourse and informing practical approaches to combating financial crime.

This study aims to analyze the effects of e-government on corruption prevalence by using a sample of 29 European countries over the period 2012–2019.

This paper uses the panel corrected standard errors (PCSE) model to mitigate the problems of cross-sectional dependence. The PCSE model is also considered to reexamine the findings when the presence of heteroscedasticity, fixed effects and endogeneity issues are taken into account. The theoretical model incorporates one-year-lagged explanatory variables to deal with endogeneity. The autoregressive distributed lag method using the dynamic fixed effects estimator is chosen to deal with the time and country-fixed effects in the effort to measure the short- and long-run effects of e-government more precisely.

The results indicate that e-government plays a critical role in improving the population’s perception of corruption. Furthermore, e-government appears to have an effect in the short run. Notably, the estimation results show that there is a nonlinear relationship between e-government, especially user centricity and key enablers and the corruption perception index in the U-shaped curve.

The short-run and nonlinear effects of e-government on corruption prevalence suggest that the fight against corruption requires countries to pursue a consistent and continuous improvement and development of the e-government system.

The authors contribute to the literature by providing a consistent and precise answer to this relationship in the case of European countries. Another contribution of the work is to use diverse indicators to reflect e-government in a typical country, which helps us confirm the reliability and robustness of the findings.

This study aims to contribute to the existing literature by empirically investigating the impact of digital competitiveness and technology on corruption under the moderating effect of some cultural and economic control variables and providing evidence on the links between corruption and various cultural dimensions at the country level.

The cross-sectional sample covers 61 countries (41 high-income and 20 lower-income countries) during the 2016–2020 period, and the analysis was carried out for both the full sample and the subsamples.

The results provide clear evidence supporting the hypothesis that digitalisation and technology significantly affect the perceived level of corruption under the moderating role of cultural framework and economic development. Furthermore, the most significant cultural dimensions of corruption are individualism versus collectivism, uncertainty avoidance, long-term orientation and indulgence versus restraint, even if, in some cases, its influence might be felt differently when the results are estimated on subsamples. Thus, in the case of indulgence versus restraint, high-income countries with higher indulgence scores would register higher scores for the corruption perception index and thus a better control of corruption, while for lower-income countries, the more indulgent these countries are, the weaker the corruption control will be. Furthermore, our results validate a powerful and significant correlation between the index of economic freedom and corruption in both digitalisation and technology.

This study may have relevant implications for policymakers who need to recognise the role of digitalisation and technology in the fight against corruption but considering the cultural and economic characteristics specific to each country.

To the authors' knowledge, the relationship between digital competitiveness, technology and corruption within an economic and cultural framework, while highlighting the differences between high-income and lower-income countries, has not been previously documented in the literature. Thus, this article argues that the level of digital competitiveness and the adoption of technology would significantly impact the level of perceived corruption, although this impact could be felt differently by countries in the high-income category compared to countries in the lower-level income category.

This study explored the tax evasion and corruption–economic development nexus in Ghana and the moderating role of institutional quality in this relationship.

To achieve this objective, this study employed the structural equation modelling (SEM) strategy and maximum likelihood (ML) estimation method on selected quarterised data from 1996 to 2020.

The study found that tax evasion has a positive impact on GDP per capita and urbanisation but a negative impact on the Economic Freedom of the World Index (EFWI). The study revealed that corruption has a positive relationship with GDP per capita but relates with EFWI inversely. Finally, the study found that institutional quality moderates the nexus between tax evasion and corruption and economic development.

The findings imply that the quality of state institutions has a significant impact on the government's ability to control tax evasion and corruption in order to drive economic development.

One novelty of the study is the examination of the combined effects of tax evasion and corruption as exogenous variables in a single econometric model. Again, to moderate the multivariate relationships of the study, the principal component analysis (PCA) was used to create an institutional quality index. The study recommends that policymakers implement comprehensive tax evasion and corruption reduction strategies simultaneously in order to increase tax revenues for economic development and SDGs achievement.

This study aims to examine anti-corruption disclosure (ACD) following government legislation, specifically the UK Bribery Act, 2010, through focusing on the UK extractive industry.

This study uses content analysis for data analysis with an ACD checklist developed to capture ACD in annual reports during the period 2003–2019.

The study found an increase in ACD following 2010, with companies answering ACD questions and addressing categories that they previously ignored.

Most of the previous studies have examined voluntary ACD; this study contributes to the literature by applying an index developed from government regulation to investigate the difference that regulation can make to disclosure. Hence, this study provides evidence of how, from an institutional perspective, legislation plays an important role in facilitating and endorsing anti-corruption reporting.

This study aims to examine the impact of economic freedom and corruption on bank stability in sub-Saharan Africa (SSA).

This study uses 38 countries in SSA from 2008 to 2019 using system GMM technique.

The authors found that greater economic freedom increases economic efficiency through improving bank stability. Besides this, the authors also find that banks in environments with greater business freedom, financial freedom, trade freedom and investment freedom are less prone to solvency. The results also show that corruption improves bank stability, suggesting evidence of the “grease the wheels” hypothesis.

The results suggest to policymakers that a high economic freedom may be an appropriate policy toward enhancing bank stability. Besides this, the results also suggest to policymakers to prioritize addressing the core issues that encourage corruption to extort bribes.

This study provides insightful discussion on whether economic freedom and its subcomponents and corruption have an effect on bank stability in SSA.

This paper aims to investigate whether the perceived level of corruption influences companies' decision to address principles and standards aimed, inter alia, at fighting corruption [i.e. Sustainable Development Goals (SDGs), (2) United Nations Global Compact (UNGC), (3) International Standards Organisation (ISO) 26,000 and (4) Organisation for Economic Co-operation and Development (OECD) Guidelines] in companies' sustainability reporting.

The paper uses a sample of 1,171 sustainability reports published in the year 2017 by organisations from Asia and Africa's low- and middle-income countries.

Results from the Probit model reveal that corruption negatively affects corporate sustainability reporting activity. Indeed, the more companies are exposed to high levels of corruption, the less likely they appear to engage in sustainability reporting. Furthermore, the authors find clear regional and sector-level differences in the extent to which companies engage in sustainability reporting. The results show that Asian companies operating in the agricultural and financial services sectors exhibit significantly higher reporting activity, whilst those operating in the construction and mining sectors report less than the sectors' peers.

The authors' findings provide important implications for understanding companies' behaviour in the sustainability reporting in emerging economies as well as for designing corporate social responsibility (CSR) disclosure initiatives in the future.

This paper provides a better understanding of the impact of corruption on companies' reporting behaviour in the context of emerging economies.

This study aims to examine the association between anti-corruption corporate disclosure and earnings management practices by bringing evidence from a developed market.

The study uses data from non-financial FTSE 100 Shares in 2016 and 2017. This study develops a disclosure index to capture the anti-corruption disclosures and run pooled, fixed effects and generalized methods of moments regression models to explore the anti-corruption disclosure–earnings management association. This study also disentangles discretionary accruals into positive and negative, use adjusted discretionary accrual computation and take a more conservative view on discretionary accruals computation as an additional analysis.

The results show a negative and significant association between anti-corruption disclosure and earnings management practices. When disentangling discretionary accruals (overvalued/positive and undervalued/negative), the authors found that higher anti-corruption disclosures were negatively associated with positive discretionary accruals, but not associated with negative discretionary accruals. The additional analysis confirmed the previous results, showing that anti-corruption disclosures are perceived as a substantive practice, rather than a mere disclosure practice for legitimacy reasons.

This study contributes to debate on the symbolic versus the substantive uses of anti-corruption disclosures in the UK context.

This study investigated the moderating role of democracy in the relationship between corruption and foreign direct investment. The purpose of this study is to understand whether corruption has different effects on the location decisions of multinational enterprises (MNEs) depending on the regime type.

This study explored how institutional context influenced the impacts of corruption on the location decisions of MNEs, specifically using a sample of Chinese cross-border mergers and acquisitions between 2000 and 2020.

This study assessed the role of democracy in the relationship between corruption and the location decisions of Chinese MNEs. In general, this study found that Chinese MNEs were hindered by host country corruption, but that these detrimental effects were weaker in the presence of more effective democratic institutions.

This study contributes to the literature on institutional factors in international business through its simultaneous investigation of the effects of both democracy and corruption on the location decisions of MNEs. Moreover, there is a prevailing view that Chinese MNEs are willing to enter countries with high corruption, but the results of this study indicate that they are risk-averse in ways similar to their Western counterparts.