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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.

As a consequence of the proposal of the Carbon Neutral and Carbon Peak policy in 2020, the Chinese Government is paying more attention to developing sustainability performance. This study aims to assess the direct influence of country-level and corporate anti-corruption measures on environmental, social and governance (ESG) and its three dimensions, besides ascertaining the moderating role of firm size.

This study used the system generalized method of moments on a sample of 820 Chinese listed firms from 2012 to 2021.

The findings show that country-level and corporate corruption negatively affect ESG performance. Corporate anti-corruption measures have a more pronounced positive influence on the sustainability performance of small firms than large firms due to the limited resources, lower political position and weaker refusal power of small firms.

The study has great implications for governments, corporate boards and ESG rating agencies. Government and corporate boards should mitigate the risks of country-level and corporate corruption to attain sustainable development goals. Rating agencies should add country-level and corporate corruption into the ESG evaluation system.

Some empirical results have proven that anti-corruption measures help reduce the emission of carbon dioxide, but few evidence shows how country-level and corporate corruption affect ESG and its three dimensions.

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.

Corruption is a major social problem, and scholars have devoted considerable attention to this phenomenon. However, less attention has been paid to how corruption spreads among organizations and what factors can make its spread more likely. This study aims to fill the gap by modelling corruption as an interorganizational contagion.

The authors used social contagion theory to model corruption as an interorganizational contagion, influenced by the susceptibility of organizations and the strength of contagion sources. The study analysed 736 medium and large Italian municipalities over a five-year period, with 3,146 observations (excluding missing data). The authors conducted a longitudinal analysis using panel logistic regression techniques and performed robustness and endogeneity checks through a dynamic panel data model.

The authors found that municipalities with a higher percentage of corrupt neighbouring municipalities were more likely to experience corruption. The probability of experiencing corruption was also significantly higher for municipalities with weaker organizational resistance to corruption contagion.

Previous studies have not clearly explained the organizational mechanisms behind the spread of corruption at the interorganizational level. The study suggests that corruption contagion at the municipal level occurs via reduced uncertainty in decision-makers and is influenced by the prevalence of corruption locally. The spread can be driven by conscious or unconscious mechanisms. This study challenges the idea that corruption contagion is immediate and inevitable. Organizational resistance to corruption can affect the risk of contagion, highlighting the importance of anti-corruption controls and ethical systems in preventing it.

This paper attempts to develop a simple, static model of tax administration that is capable of explaining the widespread collusive petty tax administration corruption observed in developing countries.

This paper utilizes a positivist research framework and adopts a theoretical method of analysis, although secondary data will also be mentioned to support theoretical arguments whenever it is appropriate to do so.

A high rate of collusive tax corruption is inevitable in developing countries.

The model is static and needs to be extended into a dynamic model.

Traditional enforcement tools such as higher audits or a higher penalty regime against tax evasion do not work. Tax simplification can lessen the incidence of tax corruption.

Fighting tax corruption requires significant changes in the attitudes of taxpayers and tax auditors.

This paper combines the literature on Kantian economics and tax compliance in an innovative fashion.

There is an extensive research stream devoted to evaluating host country political risk as it relates to foreign investment decisions, and in today’s geopolitical climate, this type of risk is becoming increasingly salient to business leaders. Despite notable advancements related to understanding the importance of government-related risk, inconsistent conceptualizations and findings remain. Thus, the purpose of this paper is to offer a comprehensive overview of how host country political risk has been conceptualized, measured and studied in relation to multinational enterprises' (MNEs’) investment decisions. After reviewing the relevant literature, five major aspects of non-violent (government type, public corruption, leadership change) and violent (armed conflict, terrorism) political risk were identified. The organization and review of each aspect of political risk provide insights on fruitful directions for future research, which are discussed.

To identify research articles on political risk and foreign investment, 13 leading management and international business journals were searched using relevant keywords (January 2000 to January 2023). Moreover, reviewing articles from these journals led to locating and reviewing additional relevant articles that the authors cited. Keyword searches were also conducted on Google Scholar and Web of Science in an effort to identify relevant articles outside of the 13 targeted journals.

Both violent and non-violent aspects of host country political risk have been studied in relation to MNEs' investment decisions. Specifically, five major aspects of host country political risk were identified (government type, public corruption, leadership change, armed conflict and terrorism). Although the general consensus is that risk related to the government often creates obstacles for MNEs, conceptualizations, measures and findings in prior research are not uniform.

This paper provides a comprehensive overview of host country political risk and foreign investment. In doing so, the aspects of political risk are identified, organized and overviewed.

The phenomenon of corruption requires extra handling to achieve zero corruption. The purpose of this paper is to examine the integrated governance, risk management and compliance (GRC) implementation, the quality of internal audits and management's commitment to improving the ability to detect corruption and its impact on the company's financial performance.

This paper used primary and secondary data. Financial statement data and survey results from participants in 69 state-owned companies were analyzed using the Partial Least Square method.

There was a positive and significant effect of the integrated GRC implementation, quality of internal audit and management's commitment to increasing the organization's internal capability in detecting corruption. However, the failure to detect corruption mediates the effect of management commitment on financial performance. Besides, the organization's three internal factors could be better because their functions could be more optimal and require further improvement.

State-owned companies are continuing to be restructured, so these results can be helpful for now. However, they must update continuously with developments related to the composition and classification of state-owned companies.

Organizations can improve their ability to detect corruption in the workplace by using an early warning system such as the integrated GRC, internal audit quality and a high commitment from management.

To the author's limited knowledge, empirical research on integrated GRC implementation, internal audit quality and management commitment are still rare if they improve the detection of corruption ability. It uses the factors that cause corruption in the fraud hexagon to analyze the financial performance.

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 aims to investigate the effect of public corruption on the performance and risk of financial institutions domiciled in the USA..

This study uses the US Department of Justice’s (DOJ) Public Integrity Section Reports to proxy corruption. The analysis is performed by bank size and includes robustness checks for omitted variables and endogeneity concerns.

The results show that a corrupt environment is associated with lower bank performance without a reduction in risk. Larger banks tend to underestimate the increase in credit risk. Small- and medium-size banks seek to “re-capture” returns in corrupt districts by reducing their liquidity.

The implication of this research is that financial institutions do not thrive in corrupt environments and are unlikely to participate in corrupt practices. Overall, this study documents the tangible harm inflicted by corrupt practices.

A practical implication is that banks may attempt to re-capture lower returns resulting from corrupt environments by extending more risky loans, specifically, commercial real estate loans.

This study demonstrates the costly impact of corruption on large and small banks. While larger banks report higher share of non-performing loans, smaller banks show an increase in the provision for loan and lease losses, suggesting that smaller banks may be more risk averse.

Prior studies investigate corruption in US firms while excluding financial institutions. This study fills this gap by investigating the effect of public corruption on the performance and risk of financial institutions domiciled in the USA.