Level Of Corruption Research Articles

Assessing Corruption in Times of Crisis: Empirical Evidence from Greece

<p class="MsoNormal" style="margin-top: 12.0pt;"><span lang="EN-US" style="mso-bidi-font-size: 10.5pt; font-family: 'Cambria',serif; mso-fareast-font-family: 宋体; mso-bidi-font-family: 'Times New Roman';">The goal of this paper is to provide an overall presentation of corruption as occupational fraud building on the findings of an empirical study conducted in Greece. As uncertainty leads to increased levels of corruption, Greece was chosen due to the prolonged period of uncertainty the county faces, caused by the 2010 financial crisis and followed by the Covid pandemic crisis. 400 questionnaires reviewing corruption perception were gathered and analyzed by gender, age, marital status, education level, position, occupation, and monthly income, as well as urban vs rural area of residence. The findings of the study were compared with and critically evaluated against those of the previous studies for Greece. Respondents in age group 36-49 believe that if appropriate measures are taken it is possible to tackle corruption in the public sector, in contrast to people aged 18-35 who disagree completely. Residents of rural areas do not consider corruption to be a serious problem and are more willing to whistleblowing (in contrast to residents of urban areas). The study findings have important practical implications in the context of designing effective corruption reduction policies.</span></p>

Systemic corruption: A nightmare to service delivery in Nigeria public tertiary institutions

The level of corruption in Nigeria public tertiary institutions is alarming and has drawn the attention of concerned individuals in both the academics and industries. The aim of this paper is to examine the effect of systemic corruption on service delivery of Nigeria public tertiary institutions. The study utilised a quantitative research approach. Data were collected from 364 staff of selected public tertiary institutions in south-eastern Nigeria using a structured questionnaire. Hypotheses were tested using International Business Machine Statistical Package for the Social Sciences (IBM-SPSS) version 27 that runs multiple regression analysis (MRA). The findings reveal that fraud, nepotism, bribery and abuse of power have significant and negative effect on the service delivery of public tertiary institutions in Nigeria. The study therefore, concluded that systemic corruption has significant and negative effect on service delivery of Nigeria public tertiary institutions. The study recommended that all cases of corruption, regardless of their nature, be handled as serious crimes, carrying lengthier and more punitive prison terms.

Злочини “білих комірців” під час війни

Abstract. The article focuses on the issue of white-collar crime, examining its pervasive and harmful impact on society, especially during periods of social and political instability. White-collar crime typically involves offenses committed by individuals in high-status positions—such as business executives, government officials, and politicians—who exploit their social standing and access to resources for personal or financial gain. These crimes often include actions like economic fraud, bribery, and tax evasion, which erode the foundations of trust, integrity, and transparency in public and private institutions. The article provides an in-depth analysis of various types of white-collar crimes, detailing how economic fraud involves the misappropriation of assets through deception, while bribery enables unlawful influence in decision-making processes, and tax evasion deprives the state of necessary funds for public services. Each of these crimes undermines public confidence in governance and financial systems, often with far-reaching consequences for the economy and society. Ukraine faces unique challenges in combating white-collar crime, especially given its high levels of corruption and ongoing geopolitical conflict. The article emphasizes the latent, often concealed nature of such crimes, which allows offenders to avoid detection and punishment, further emboldening corrupt practices. The article also examines how the war has intensified the need for judicial reform and stronger measures to address white-collar crime, including the imposition of sanctions and more rigorous investigative processes. The conflict has shifted judicial priorities, requiring a heightened focus on cases where criminal acts may also threaten national security. This new context has led to more stringent enforcement and penalties for those whose financial misconduct intersects with issues of national integrity and resilience. Overall, white-collar crime is a pressing issue, as it destabilizes economies, undermines public trust in institutions, and fosters inequality by allowing influential perpetrators to act with relative impunity. Its concealed nature and the often-complex networks involved make it challenging to investigate and prosecute, especially in wartime when resources are stretched, and legal processes may be disrupted. In Ukraine, the impact of white-collar crime is particularly pronounced, as both corruption and the ongoing war have exacerbated and transformed the landscape of these offenses. The article underscores the importance of developing a robust legal framework, increasing transparency, and involving civil society in efforts to expose and combat white-collar crime, thus protecting the nation’s stability and social welfare. Keywords: white-collar crime; economic fraud; bribery; tax evasion; corruption; martial law; legal sanctions.

Learning Strategies for the Practice of Taboos in Shaping the Character of the Malay generation in Bintan, Kepulauan Riau, Indonesia

The issue of the conduct of the nation's generation is increasingly worrisome, exacerbated by the rapid pace of globalization that further deteriorates the situation. Experts are continuously formulating ideas and strategies to improve the conduct of the nation's generation but have yet to achieve maximum results. The increasing number of ill-mannered students, disobedient children to their parents, and the high level of crime and corruption displayed by the nation's generation prove that this nation is experiencing decay. This study aims to explore and deeply understand how the practice of prohibitions can cultivate the conduct and ethics of the Malay generation. Additionally, it seeks to comprehend the challenges faced in the current practice of prohibitions and to provide an alternative to strategies for learning conduct and ethics. This study is a qualitative case study conducted through interviews using purposive sampling techniques, involving 16 study participants consisting of leaders and religious figures, academics, community leaders, and community groups. The semi-structured interview served as the primary instrument, while documentation and observation were used as secondary sources in data collection for this study. The study found that the practice of prohibitions is still upheld and serves as a proven strategy for enhancing the ethics of the Malay community in Bintan Island, Riau Archipelago, once upon a time, as it involves familial relationships as educators. However, a weakness of this strategy is its inherent dependence on outdated, superstitious, and illogical practices. The research results also indicate that the advancement of time and globalization have distanced the Malay generation from the practice of prohibitions, leading to a deterioration of conduct. Through this study, the researcher proposes a framework for an educational strategy for learning conduct as an alternative to the practice of prohibitions that is logical and easily understood by any generation.

Economic Growth and Inflation Responses Caused by Political Condition and Corruption Shocks in Supporting SDGs: Case Study of Asean Countries

Objective: The research objective of this study is to examine and analyze the interaction of economic growth, inflation, political condition, and corruption in ASEAN to support the achievement of SDGs in each country. Theoretical Framework: The theories used in this study are Philips' theory related to inflation and unemployment, aggregate demand theory related to inflation and output, institutional theory for political stability and corruption. Method: The method used is PVAR for the period 2010-2023. The first stage is testing and analyzing the stationary panel with the LLC test approach. The second stage is testing and analyzing the shock response of macroeconomic variables with political conditions and corruption. Results and Discussion: The estimation results show that the variables used in this study are stationary at the level level, so there is no need to conduct a cointegration test. The impulse response results show that the interaction of economic variables is responsive to the performance of political stability and corruption. Research Implications: The policy recommendations provided by this study are to maintain political stability and reduce the level of corruption. In addition, the governments of each ASEAN country need to strengthen cooperation related to law, economy, and others. This will be able to support the achievement of SDGs in each country.

Does Corruption Control Enhance ESG-Induced Firm Value? Insights from Machine Learning Analysis

This study adopts advanced causal machine learning (ML) techniques to investigate the impact of country-level corruption on the market valuation of firms’ environmental, social, and governance (ESG) performance. By employing double-debiased machine learning (DML) and linear regression analysis, we find that ESG performance positively influences firm value. This positive relationship is more pronounced for firms operating in countries with lower levels of corruption. The use of DML enhances effect identification and yields findings that closely align with those derived from linear regression, thereby providing robust support for the pivotal role of corruption control in enhancing ESG-induced firm value.

What drives tax morale in selected North African economies? Empirical evidence from Algeria, Morocco and Tunisia using simulated ARDL and GMM quantile regressions

This study attempts to analyze the driving factors of tax morale in selected North African countries over the period 1984-2022. For this purpose, we use simulated ARDL and Frequency Domain Causality for time-series analysis and GMM-QR for dynamic panel analysis. According to long-run empirical estimations, educational growth positively contributes to enhancing tax morals in Algeria, Morocco, and Tunisia, whereas GDP and corruption contribute negatively. However, this relationship fluctuates in the short term. In addition, all independent variables positively and significantly maintain causality for tax morals. Furthermore, the dynamic estimation confirms the above relationship in the long-run in the panel. Although education and GDP maintained the same relationship in the GMM-QR estimation, corruption levels remained insignificant during the quantile period. Considering the pioneering study of the area, this study suggests some key factors that should be given more attention for enhancing tax morals in the region and ultimately improving the tax-to-GDP ratio.

Comparative Analysis of Business Environment Dynamics in Central and Eastern Europe: A Multi-Criteria Approach

The COVID-19 pandemic has negatively impacted the world economy and global society. However, small- and medium-sized enterprises are among the most vulnerable and affected groups of businesses, and in some cases, life-saving interventions have resulted in serious existential implications. The difficulties of insufficient demand, non-negligible fixed costs, and inadequate financing are unsustainable for many firms. Thus, the main aim of this study is to evaluate the variables influencing business activities, apply macroeconomic variables to compare the business environments in fifteen European countries, and utilize appropriate statistical techniques to confirm the results. Significant differences exist in the business climate across selected European countries, as identified by the TOPSIS method, CPI, and GCI. Low levels of corruption, strong economic stability, and high competitiveness make countries like Germany and Austria attractive for business environments. Estonia is also a leader in technological innovation and low corruption. Conversely, Bulgaria and Romania are struggling with higher levels of corruption and reduced competitiveness, potentially impeding business endeavours. The Visegrad Group countries are in the middle of the spectrum, scoring average to good but with opportunities for improvement in corruption and innovation. Overall, the business climate in these countries is diverse, reflecting their unique economic, political, and social circumstances.

Exploring the Impact of Corruption and Governance on Poverty in Developing Countries: A Comparative Analysis of Pakistan, India, and Bangladesh

The article examines the effect of corruption and governance on poverty, especially in Pakistan, India, and Bangladesh. The paper brings to the foreground the roles that the World Bank and the United Nations have played in fashioning development policies in these countries. Nevertheless, those interventions demonstrate a very strong dependency on the existing local governance systems and the levels of corruption that hamper poverty reduction strategies. In terms of its methodology, the research utilises a qualitative secondary data analysis method whereby data collected from different journals, reports, and institutional documents are analysed. Thus, it allows for comparative analysis of the quality of governance as well as the impact of the latter on poverty in the three countries. The analysis shows that due to relatively stable governance in India, the poverty rate has decreased; however, Pakistan and Bangladesh may face higher negative changes due to the corruption and bad policy implementation. These vices in the so-called ‘‘third world’’ nations have soaked up funding that would have otherwise been used to develop the nation, compromised the needs of the needy, and slowed down poverty eradication. On this note, the study concludes that international interventions regarding governance should be sensitive to the local governance factors and corruption indices. A top-down approach is inefficient, and a bottom-up approach is necessary to fit each country’s needs to fight poverty and assist in sustainable development.

Regulatory and legal framework for the prevention of corruption in the activities of the National Police of Ukraine

The article analyses the legal mechanisms and tools for combating corruption in the system of law enforcement agencies of Ukraine in the National Police. It is determined that corruption remains a serious problem for the democratic development of Ukraine and undermines public confidence in state institutions. This is especially true of law enforcement agencies, on whose activities public order and security depend. The author emphasises the importance of legal acts regulating the work of the police and implementing anti-corruption measures. The author outlines the key problems in anti-corruption activities, including insufficient internal control, imperfect legislative framework and the need to harmonise it with European standards. Particular attention is paid to the role of such documents as the Law of Ukraine ‘On Prevention of Corruption’ and the ethical rules of conduct for police officers, which lay the legal basis for the fight against corruption. The introduction of an electronic asset and income declaration system, control over conflicts of interest, and ethical behaviour of police officers are important tools for preventing abuse. Attention is focused on the role of civil society organizations and the media in shaping public control over the activities of law enforcement agencies. Public oversight and openness of the police are critical for increasing public trust and reducing corruption risks. It was determined that the basis for the formation of anti-corruption policy in the National Police is international standards, as well as laws of Ukraine, which determine the principles of corruption prevention. In particular, the role of special anti-corruption bodies that monitor the implementation of legislation and investigate corruption cases is important. Such cooperation between state institutions allows us to create a more effective and coordinated system of combating corruption. The author concludes that to effectively combat corruption, it is necessary not only to improve the legislative framework, but also to ensure its proper implementation, through training and raising the legal culture of police officers. Only through a comprehensive approach can we achieve a significant reduction in the level of corruption in the law enforcement system and increase its efficiency.

Political corruption and cost stickiness: Evidence from China

AbstractThis study investigated the effect of local corruption on the cost behaviour of publicly traded firms in China over the period from 2007 to 2017. Our findings show that firms situated in regions with higher corruption levels tend to exhibit greater cost stickiness, primarily driven by managerial empire‐building incentives and rent‐seeking behaviours. This effect is particularly pronounced in firms subject to greater government intervention, weaker internal controls, fewer political connections, and less market competition. Furthermore, this corruption‐induced cost behaviour is found to negatively impact firm value. The results underscore the critical role of institutional environments, particularly corruption, in shaping corporate cost management strategies. This study provides valuable insights into how corruption influences economic outcomes for firms and offers guidance for managers, regulators, and investors to address these challenges and optimise cost management practices.

The role of green finance and natural resources rent in eradicating energy poverty – the case of the Sub-Saharan African countries

This research addresses energy poverty in Sub-Saharan African (SSA) countries, emphasizing improved access to clean cooking electricity and technologies in urban areas. Urbanization in the SSA region has intensified the problem, with informal settlements relying on traditional and polluting cooking methods, causing indoor air pollution, environmental damage, and economic struggles. The research employs the Methods of Moments Quantile Regression with fixed effects to assess the factors that enhance access to clean energy and technologies for cooking in the urban areas. The data of forty-four SSA countries during the timeframe spanning 2004 to 2020 is used. This research adds to the growing body of literature on how energy poverty can be eradicated, considering the few studies that has been done to address this issue. Specifically, the effect of green finance and financial development on energy poverty has not been widely done, thus this research covers the literature gap present. The major results of this research depicts that financial development, government effectiveness, natural resources rents and technological innovations are fundamental in improving access to clean electricity in the urban areas of the SSA nations. We also show that economic growth, foreign direct investment and green finance are counterproductive in fostering the access to clean electricity in this region. This research show that the resource curse hypothesis does not hold in the SSA countries in the context of energy poverty. The major policies presented in this research calls for the developing countries to promote financial development, technological innovations and natural resource rents in alleviating energy poverty. Corruption levels and political instability in these countries should be reduced.

DOES CORRUPTION HAS A POSITIVE IMPACT ON ECONOMIC GROWTH?

The problem of corruption is a common problem and continues to this day in Indonesia. The level of corruption that does not improve causes losses and inefficiency in the economy. The high level of corruption has been an obstacle to economic progress and growth in Indonesia so far. This research aims to find out more about the impact of worsening corruption on foreign investment, the Rupiah exchange rate against the dollar, and economic growth. This research uses secondary data obtained from the central statistics agency for 16 years. Research data processing uses PLS. Based on the research results, it was found that the level of corruption affects the level of foreign investment and the Rupiah exchange rate against the Dollar but not economic growth. This research also found that foreign investment can mediate the relationship between the level of corruption and economic growth. In this research, it was found that the higher the level of corruption, the more foreign capital will enter. This is because countries with high levels of corruption have poor administrative systems so that by using bribes the investment process can run more easily. The greater the foreign capital that enters, the greater the capital in economic activities so that economic growth will increase. This is certainly not a good thing the Indonesian government needs to improve the quality of its bureaucracy so that corrupt practices do not get worse

A comprehensive benchmarking of a U-Net based model for midbrain auto-segmentation on transcranial sonography

Background and objectiveTranscranial sonography-based grading of Parkinson's Disease has gained increasing attention in recent years, and it is currently used for assistive differential diagnosis in some specialized centers. To this end, accurate midbrain segmentation is considered an important initial step. However, current practice is manual, time-consuming, and bias-prone due to the subjective nature. Relevant studies in the literature are scarce and lacks comprehensive model evaluations from application perspectives. Herein, we aimed to benchmark the best-performing U-Net model for objective, stable and robust midbrain auto-segmentation using transcranial sonography images. MethodsA total of 584 patients who were suspected of Parkinson's Disease were retrospectively enrolled from Beijing Tiantan Hospital. The dataset was divided into training (n = 416), validation (n = 104), and testing (n = 64) sets. Three state-of-the-art deep-learning networks (U-Net, U-Net+++, and nnU-Net) were utilized to develop segmentation models, under 5-fold cross-validation and three randomization seeds for safeguarding model validity and stability. Model evaluation was conducted in testing set in three key aspects: (i) segmentation agreement using DICE coefficients (DICE), Intersection over Union (IoU), and Hausdorff Distance (HD); (ii) model stability using standard deviations of segmentation agreement metrics; (iii) prediction time efficiency, and (iv) model robustness against various degrees of ultrasound imaging noise produced by the salt-and-pepper noise and Gaussian noise. ResultsThe nnU-Net achieved the best segmentation agreement (averaged DICE: 0.910, IoU: 0.836, HD: 2.793-mm) and time efficiency (1.456-s). Under mild noise corruption, the nnU-Net outperformed others with averaged scores of DICE (0.904), IoU (0.827), HD (2.941 mm) in the salt-and-pepper noise (signal-to-noise ratio, SNR = 0.95), and DICE (0.906), IoU (0.830), HD (2.967 mm) in the Gaussian noise (sigma value, σ = 0.1); by contrast, intriguingly, performance of the U-Net and U-Net+++ models were remarkably degraded. Under increasing levels of simulated noise corruption (SNR decreased from 0.95 to 0.75; σ increased from 0.1 to 0.5), the nnU-Net network exhibited marginal decline in segmentation agreement meanwhile yielding decent performance as if there were absence of noise corruption. ConclusionsThe nnU-Net model was the best-performing midbrain segmentation model in terms of segmentation agreement, stability, time efficiency and robustness, providing the community with an objective, effective and automated alternative. Moving forward, a multi-center multi-vendor study is warranted when it comes to clinical implementation.

A Cross-national Study on How Corruption Affects Happiness

Abstract: Corruption and subjective well-being are of interest to scholars, governments, and legislators. The study builds on existing literature that explores the interplay between economic, cultural, and political factors and happiness, with a particular focus on the less-examined role of governance quality, as measured by corruption levels. While scholars generally see corruption as a predictor of happiness, the direction of that effect is unclear. Using cross-national data from 133 countries, this paper investigates the impact of corruption on individuals happiness. Employing an Ordinary Least Squares (OLS) regression analysis, the research controls for other critical variables such as GDP, democracy index, and education, and tests the hypothesis that lower corruption is associated with higher happiness. The perceived corruption is statistically significant on predicting happiness when it is solely considered, but the situation changed when controlling GDP. The paper reveals that economy plays important role as a intervening variables between corruption and happiness. The paper is a helpful guides for policymakers and governments in making effective anti-corruption measures for enhancing happiness at a national level.

Indirect Value of Public Infrastructure Technology

Although prior research has primarily focused on the direct value of information technology (IT) and IT adoption by individuals and firms, this study explores the indirect value of IT in the form of public infrastructure technology. By exploiting a spatial discontinuity in water monitoring stations, we discover that firms located immediately upstream of water monitoring stations exhibit significantly lower levels of corruption than firms located immediately downstream. These findings are particularly noteworthy given that water monitoring stations have the potential to generate significant indirect value as they are not explicitly designed to mitigate corruption. Further analyses reveal that public infrastructure technology alone does not hold the key to mitigating corporate corruption. Instead, it is the synergistic interplay between public infrastructure technology and organizational change that drives the outcome. These findings contribute to a deeper understanding of the broader IT value landscape, emphasizing the indirect value of technological advancements in public infrastructure that were not originally intended for such benefit. Additionally, our findings highlight the benefits of leveraging existing infrastructure technology to address emerging societal needs. This paper was accepted by D. J. Wu, information systems. Funding: J. Liu acknowledges financial support from the National Natural Science Foundation of China [Grant 72402127], Shanghai Pujiang Program [Grant 23PJC059] and the Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission [Grant 23CGA10]. S. Pei acknowledges financial support from the National Natural Science Foundation of China [Grant 72302139]. X. (M.) Zhang acknowledges financial support from the Hong Kong Research Grants Council [Grants GRF 14500521, GRF 14501320, GRF 165052947, and TRS:T31-604/18-N]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01145 .

Corruption impedes good governance in Somalia’s public sector

Purpose The purpose of this paper is to understand the level of corruption in Somalia and the causes that lead to corruption that in turn hampers good governance. Design/methodology/approach The paper relies on the data collected from Somali’s public institutions, international actors, newspaper articles and peer-reviewed literature. The degree of corruption is assessed with the Corruption Perceptions Index by Transparency International and the Control of Corruption provided by the World Bank. Findings The finding shows that the level of corruption in Somalia is high and complex because of the following reasons: weak governance and poverty, culture and tradition which include favoritism based on clan membership, lack of accountability mechanism and absence political will. Measures undertaken for anti-corruption, for instance, the establishment of the National Anti-Corruption Commission and legislation for its support face barriers and challenges that include political influence, lack of capacities among the undertaking institution and lack of participation by the public. Originality/value This research adds value to the knowledge of corruption in Somalia by identifying the concrete socio-political antecedents for corruption and the problems of fighting it. This paper further presents the following detailed strategies to address corruption: enhancing the operational and financial integrity of the Independent Anti-Corruption Commission; restructuring the civil service and merging it into a merit-based system; enhancing Public Financial Management (PFM) reforms; independence of the judiciary; and sustaining development in digital technology adoption in governance and procurement.

Suspicious activity reporting in emerging economies: the case of Iran

PurposeCountries with high levels of corruption can experience collusion between powerful elites and accountants to conceal, disguise and clean the proceeds of criminality. This study investigates the willingness of accountants to report evidence of money laundering in an emerging economy, Iran, notwithstanding potential personal and professional risks implicit in such due diligence. It evaluates the relevance of personal characteristics of accountants to the propensity to report, and the implications for policy makers in terms of audit team composition.Design/methodology/approachThe methodology is quantitative. Data was gathered by means of a suspicious activity scenario-based questionnaire administered to 1,128 of Certified Public Accountants in Iran, of which 281 responses were received. Four hypotheses were tested relating to the implications, if any, of gender, age, education and working experience for the propensity to report red flags indicative of money laundering.FindingsData revealed that accountants were generally more willing to report activity indicative of money laundering than was anticipated in an environment perceived to be characterised by professional and personal risks. Older accountants are more risk averse and more likely to report suspicious activity than younger counterparts who tend to disregard borderline indicators of money laundering. A significant red flag indicator of money laundering is a client's reluctance to provide information regarding controlling shareholders, debtors and creditors or to explain contrived and opaque corporate structures. Audit teams may be more effective when gender-balanced: female accountants tend to be more willing to report suspicious activity than male counterparts, reducing the risk of interference by powerful elites.Research limitations/implicationsThe time frame over which the research was conducted was a single year; if it had been conducted over several years it may have revealed more nuanced and evolving reporting behaviour. The study was limited to Iran: a cross-comparison with another emerging economy or economies may have revealed useful contrasts.Originality/valueThe study contributes to behavioural accounting research in emerging economies. Limited empirical data is available regarding the influence of personal characteristics of accountants on their willingness to report suspicious activity in corrupt environments where personal safety and professional security may be at risk from powerful elites. It evaluates the implications of these for suspicious activity reporting policy, and for improving the effectiveness of the scrutineering role of audit teams. An innovative questionnaire was designed which may be suitable for future comparable research in emerging economies.

ARTIFICIAL INTELLIGENCE AS AN INNOVATIVE TOOL OF CORRUPTION PREVENTION IN JUDICIARY: THE ADVANTAGES

There has been made an attempt in the article to assess the possibility and expediency of application of information and communication technologies and their highest manifestation – artificial intelligence – as an anti-corruption tool in the judiciary. The essence and modern forms of the artificial intelligence phenomenon and its connection with information and communication technologies have been analyzed. There has been researched national and foreign legal regulation on the application of artificial intelligence both in the field of public administration in general and in the field of the judiciary and administration of justice in particular. The cases of the most «significant» corruption events in the judiciary have been presented and an attempt to find out the reasons of the failure of traditional tools to prevent corruption has been made. There has been called into question the ability of the state to overcome such a negative socio-power phenomenon as corruption without the implementation of radical steps which have long been overdue and became even more actualized during the armed conflict. Some positive examples of the information and communication technologies use in the judiciary have been demonstrated. Separate advantages of using artificial intelligence as a new tool for preventing corruption in the administration of justice have been briefly systematized. There has been emphasized that artificial intelligence due to its impartiality is fully capable to ensure the realization of the right to a fair trial, preserving time, financial and human resources, and reducing the level of corruption. At the same time, there has been underlined that without studying the risks and threats of using computer programs at this level of their development, relying only on them as a panacea for the destruction of corruption practices is imprudent and premature. Finally, an impulse for further research of artificial intelligence and its features as a tool of corruption prevention in the judicial system has been given.

How does auditing outgoing officials' natural resource asset management policies affect carbon emission efficiency? Evidence from a debiased machine learning model

Reducing carbon emissions to improve environmental quality has been the Chinese government's unwavering dedication in recent years. Several policies have been implemented with the objective of driving carbon reduction. The implementation of the outgoing leadership natural resources audit policy has played a pivotal role in encouraging local government officials to prioritize both economic and environmental development in their pursuit of performance metrics. However, whether the implementation of this policy contributes to an enhancement in carbon emission efficiency requires further empirical validation. This study, utilizing panel data from 282 cities across China, explores the potential impact of the audit policy (specifically referring to the outgoing leadership natural resources asset audit policy, without ambiguity) on carbon emission efficiency through the application of a debiased machine learning model. The results of the study show that the audit policy has been crucial in greatly raising the regional level of carbon emission efficiency. Furthermore, mechanistic analysis results suggest that the audit policy can enhance regional carbon emission efficiency by influencing green innovation and raising government environmental awareness and green financial levels. Based on the heterogeneity analysis, the regions east of the Hu Line, cities with low levels of corruption, less stringent economic growth objectives, and areas with high levels of public environmental concern are the areas where auditing rules have the greatest influence on carbon emission efficiency. In conclusion, based on the comprehensive results of this study, a series of policy recommendations are presented to further advance China's efforts in carbon reduction, ultimately achieving a more sustainable balance between economic and environmental development objectives.