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The purpose of this paper is to investigate the influence of macroeconomic cyclical indicators and country governance on bank non-performing loans in African countries.

Data was collected from the 53 African countries covering 2005–2021. The paper develops an empirical model to examine the impact of country governance in reducing macroeconomic cycle-induced adverse effects on bank credit risk. This research estimates Random Effects models and the General Method of Moment to examine the link between microeconomic and governance factors on bank non-performing loans. Stata version 15.1 was used to conduct panel regression analysis.

The findings of the study revealed that the generalized method of moments findings contributes valuable insights into the persistence of NPLs over time and the specific effects of variables on NPL levels. The study findings highlight that the debt-to-GDP ratio, unemployment, regulatory quality, government effectiveness and inflation have significant relationships with NPLs, shedding light on their specific contributions to credit risk dynamics.

The focus on a specific set of determinants for NPLs, which may not capture all the factors that influence NPL levels. Thus, the study did not consider the impact of macroeconomic shocks, such as natural disasters or global economic crises, which can have a significant impact on NPLs.

Policymakers should prioritize maintaining sustainable debt levels, promoting employment growth and controlling inflation rates to mitigate credit risk and reduce nonperforming loans. Also, enhancing regulatory quality and government effectiveness is crucial in ensuring financial stability and minimizing non-performing loans in Africa.

This paper provides a new possible solution to minimise bank non-performing loans risk by examining interactions of country governance regarding the macroeconomic cycle behaviour.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0729

Excessive borrowing significantly contributes to pushing businesses towards default and their transition into zombie enterprises. Despite government efforts to implement deleveraging policies and guide bank credit flows, it’s essential to delve into the internal dynamics that steer the borrowing behavior of these zombie enterprises at a micro level. To gain a comprehensive understanding of the issue, this study focuses on examining the incentives that drive corporate executives of zombie enterprises to consistently engage in large-scale borrowing from banks.

In this study, panel data analysis is utilized, incorporating firm-, industry- and year-fixed effects. Drawing from data pertaining to listed companies in China spanning from 2007 to 2020, we employ a one-by-one identification method to pinpoint zombie enterprises. Ultimately, a total of 2,533 samples of zombie enterprises were obtained.

The results indicate that as bank loans to zombie enterprises increase, executive monetary compensation decreases, while on-the-job consumption by executives increases, and they are less likely to be forced into rotation. Mechanism testing reveals that corporate performance partially mediates the relationship between bank loans and executive monetary compensation, but this mediation is ineffective for on-the-job consumption and job rotation. Further investigation suggests that the property rights nature of central enterprises and modified audit opinions can exacerbate the adverse impact of bank loans on the monetary compensation of zombie corporate executives, without significantly affecting on-the-job consumption or job rotation. Conversely, executive power does not enhance the positive effects of bank loans on monetary compensation or on-the-job consumption, but it diminishes the negative impact of bank loans on the forced rotation of zombie executives.

These results indicate that while bank loans may have a negative impact on corporate value, they function as safeguards for the positions and interests of executives. As a result, bank loans serve as incentives for executives of zombie enterprises.

This study holds theoretical significance as it explores the motivations behind non-performing loans in high-borrowing enterprises, sheds light on corporate governance challenges encountered by zombie enterprises and provides policy insights aimed at addressing the underlying causes of persistent non-performing loans in high-borrowing enterprises, including zombie enterprises.

After half a decade of balance sheet clean-up prompted by the Reserve Bank of India’s (RBI) asset quality review (AQR), Indian banks are back on track for increased loan growth. Being a financial vehicle for the economy, loan growth cannot be put on hold for a long period of time. But it is also important to understand that loan growth carries an inherent risk of default. A trade-off exists between loan growth, non-performing loans (NPLs) and bank profitability. Our study highlights the importance of understanding this relationship.

For our study, we have taken a sample of India’s private and public sector banks. The dataset consists of the financials of our sample for the period 2006–2021. Two-step differenced generalized method of moments (SYS-GMM) estimation has been used to establish the relationship. The mediating role of NPLs in the relationship between loan growth and profitability is examined by the mediation analysis using structural equation modeling (SEM) and the Sobel test. We have used Stata 16.1 for the analysis of our dataset.

The findings of our study suggest that bank lending is a major contributor to the bank’s earnings. Loan growth after a certain point has a negative impact on profitability, and it also adds to the NPLs of the bank. The study result indicates that moderate loan growth is key to steady and stable growth in the Indian banking industry.

Our study is directed toward understanding the positive and negative manifestations of loan growth. We develop a framework to understand this relationship and then empirically prove it. The study is beneficial for employees and policymakers alike to minimize the negative impact of loan growth.

The issue of the simultaneous impact of loan growth on NPLs and profitability has not been studied in the Indian banking sector. Also, this study adds to the present literature by studying the mediation effect of the NPLs on the loan growth and profitability relationship.

This study empirically tests the use of loan loss provisions (LLPs) for earnings and capital smoothing when emphasis is laid on banks' riskiness and adoption of the International Financial Reporting Standards (IFRSs) in Nigeria.

Annual bank-level data are hand-extracted between 2007 and 2017 from annual reports of a sample 16 deposit money banks (DMBs), and analysed using appropriate panel regression models subsequent to a number of diagnostic tests including heteroscedasticity, autocorrelation and cross-sectional dependence. The use of both reported LLPs (TLLP) and discretionary LLPs (DLLP) for earnings and capital management is tested to advance the practice in the literature.

Generally, the study finds that Nigerian DMBs manage capital via LLPs, while mixed results are obtained for earnings smoothing. However, during IFRS, Nigerian DMBs' management of capital is identifiable with TLLP, while smoothing of earnings is peculiar to DLLP. Additionally, evidence of the improvement in loan loss reporting quality expected during IFRS for riskier Nigerian DMBs, could not be attained. This is corroborated by the study's findings of the use of both TLLP and DLLP for earnings and capital management during IFRS by DMBs in solvency crisis against the only use of TLLP to manage capital found for the entire period.

The evidential capital and earnings lopsidedness may subject Nigerian DMBs' going-concern to a lot of questions.

The study sets a foremost record in the empirical test of managerial opportunistic behaviour embedded in earnings and capital concurrently while accounting for loan losses by all categories of Nigerian DMBs in terms of riskiness, following accounting regime change.

The COVID-19 pandemic has profoundly impacted the global economy, disrupting supply chains, causing job losses and altering consumer demand. In Malaysia, the real estate sector has been notably affected, with increased property impairments and overhang due to unprecedented uncertainty. Understanding these effects is crucial for policymakers and investors to prevent real estate and banking crises. This study aims to analyse the relationships between macroeconomic factors during the pandemic on property impairments and overhang, providing insights for maintaining macroeconomic stability. The findings will inform strategies for mitigating economic shocks, identifying opportunities, and guiding real estate policies in Malaysia and potentially globally.

This research article uses a time series ARDL regression analysis to examine pivotal macroeconomic factors including income, housing process, interest rates and unemployment on property loan impairments and property supply overhang in Malaysia. ARDL is effective to measure and analyse time series data, especially to understand the lagged impacts of macroeconomic factors. This can be seen by various economists in analysing macroeconomic factors affecting non-performing loans or the real estate finance using regression analyses both in Malaysia and other regions. The observations are gathered before, during and after the COVID-19 pandemic, spanning a five-year period with monthly frequency from 2018 to 2022.

The study emphasizes the critical importance of effectively managing unemployment and implementing policy interventions, such as moratoriums, to stabilize the economy and reduce the risk of loan impairments during crises like the COVID-19 pandemic. Additionally, this study highlights a significant inverse relationship between income per capita and loan impairments, underscoring the necessity for policies that promote economic growth and income equality. Initiatives targeting job creation, education and skills development can elevate income levels, thereby decreasing loan impairments. Lower lending interest rates during the pandemic also help mitigate the risk of loan impairments by facilitating borrowing, stimulating economic activity and enhancing financial well-being. Furthermore, the study suggests that while lower interest rates incentivize property developers and investors, understanding the intricate interaction between housing prices and supply is crucial for policymakers and stakeholders to effectively manage the housing market and ensure adequate housing supply, especially during crises.

This paper provides insight for policymakers, regulators, investors and property consultants into the dynamic effects of key macroeconomic factors amidst a global recession in how they impact the real estate market with regards specifically to all types of property loan impairments and property supply overhang. The observations are limited to the COVID-19 period, spanning five years with monthly data from 2018 to 2022. This understanding can facilitate the development of targeted strategic monetary policies and investment decisions in case of future recessions.

Policymakers should prioritize initiatives such as moratoriums and job creation programs to mitigate economic downturns. Additionally, financial institutions need to adjust lending practices in response to lower interest rates, while stakeholders in the housing market must understand the complex dynamics between housing prices and supply to ensure a balanced market. Overall, addressing underlying economic factors and implementing targeted policies are essential for building resilience and promoting sustainable economic growth amidst challenging circumstances.

Initiatives aimed at fostering income equality, creating employment opportunities and ensuring housing accessibility contribute to greater social cohesion and well-being. By promoting financial inclusion and building resilience to crises, societies can mitigate the adverse social impacts of economic challenges such as unemployment and housing affordability. Overall, addressing socioeconomic disparities and promoting inclusive growth are essential for fostering a more equitable and resilient society.

The originality and uniqueness of this study lie in its comprehensive analysis of the impact of COVID-19 on loan impairments and housing supply. While previous studies have focused on the pandemic’s effects on specific segments of the real estate market or property prices, this study provides a broad overview of its impact on property loan impairments and housing supply overhang. Finally, this study highlights the social and practical implications. Overall, this study offers a distinctive analysis of COVID-19’s impact on the real estate market and its implications for policymakers, real estate professionals and investors.

The comparison between economic growth and the character of monetary policy is one of the most frequently studied issues in policymaking. However, the number of studies incorporating a dynamic time warping approach to analyse the similarity of macroeconomic variables is relatively small.

The study aims at assessing the mutual similarity among various variables representing the financial sector (including the monetary policy by the central bank) and the real sector (e.g. economic growth, industrial production, household consumption expenditure), as well as cross-similarity between both sectors.

The analysis is based on the dynamic time warping (DTW) method, which allows for capturing various dimensions of changes of considered variables. This method is almost non-existent in the literature to compare financial and economic time series. The application of this method constitutes the main area of value added of the research. The analysis includes five variables representing the financial sector and five from the real sector. The study covers four countries: Czechia, Hungary, Poland and Romania and the 2010–2022 period (quarterly data).

The results show that variables representing the financial sector, including those reflecting monetary policy, are weakly correlated with each other, whereas the variables representing the real economy have a solid mutual similarity. As regards individual variables, for example, GDP fluctuations show relatively substantial similarity to ROE fluctuations – especially in Czechia and Hungary. In the case of Hungary and Romania, CAR fluctuations are consistent with GDP fluctuations. In the case of Poland and Hungary, there is a relatively strong similarity between the economy's monetisation and economic growth. Comparing the individual countries, two clusters of countries can be identified. One cluster includes Poland and Czechia, while another covers Hungary and Romania.

This study aims to transcend geographical boundaries and provide insights into innovative strategies used by Indian Asset Reconstruction Companies (ARCs) in managing distressed assets. The study examines the origins, evolution, challenges and opportunities faced by ARCs to derive lessons that can be universally applicable and serve as a valuable blueprint for global investors and institutions seeking effective strategies in managing distressed assets. From a legal and compliance angle, this opens up many perspectives that would help plug loopholes and grey zones within the legal ambit for organisations and institutions.

The study invokes a critical review of existing literature, news, discussions and publicly available information from reliable sources such as the central bank’s websites to develop the viewpoints and provide recommendations.

ARCs face challenges, recovering only 19.15% of distressed assets in 2022. Despite constraints like funding, governance issues and regulatory hurdles, there is a substantial opportunity for investors in the Rs. 9.6 lakh crore non-performing assets. The study suggests strategic assessments by banks, emphasises ARCs’ roles in specific sectors and calls for regulatory adjustments. With diverse investors and favourable regulations, this evolving landscape offers significant global opportunities for policymakers and investors in distressed assets.

This study serves as a valuable guide for shaping resilient policies, fostering cross-border collaborations and optimising distressed asset management strategies on a global scale.

This study breaks new ground by examining the private ARCs sector within an emerging economy’s dynamics, presenting insights relevant to global distressed markets. This study serves as a unique resource for those navigating the complexities of distressed markets globally, providing insights that can inform strategies, policies and academic discussions in the broader financial landscape.

This study focuses on the banking systems evaluation in Portugal, Italy, Ireland, Greece and Spain (known as the PIIGS) during the financial and post-financial crisis period from 2009 to 2018.

A conditional robust nonparametric frontier analysis (order-m estimators) is used to measure banking efficiency combined with variables highlighting the effects of Non-Performing Loans. Next, a truncated regression is used to examine if institutional, macroeconomic, and financial variables affect bank performance differently. Unlike earlier studies, we use the Corruption Perception Index (CPI) as an institutional variable that affects banking sector efficiency.

This research shows that the PIIGS crisis affects each bank/country differently due to their various efficiency levels. Most of the study variables — CPI, government debt to GDP ratio, inflation, bank size — significantly affect banking efficiency measures.

The contribution of this article to the relevant banking literature is two-fold. First, it analyses the efficiency of the PIIGS banking system from 2009 to 2018, focusing on NPLs. Second, this is the first empirical study to use probabilistic frontier analysis (order-m estimators) to evaluate PIIGS banking systems.

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.

We study how capital requirements, intended as a measure to ensure security for the financial system, can create moral hazard for banks in dealing with distressed debts.

Over the period spanning from 1993 to 2019, we manually gathered data on 1953 firms, identifying a total of 2,146 distress events, with 804 instances resulting in bankruptcy fillings.

Our analyses at the loan level and the bank level consistently show that loans of distressed firms are much more likely to be extended when the lenders are closer to the capital requirement limit. Exploiting the discontinuity in the predetermined maturity date of loans, we provide causal evidence on the relationship between capital ratios and extension likelihood. Distressed loans that are due just before the report date (end of a quarter) are much more likely to be extended than loans due just after the report date, after controlling for loan and firm characteristics. Additional analyses show that the effects are stronger when external financing is more costly and when the banks are poorly capitalized.

Our paper presents the first causal evidence of capital requirements on lending distortion, contributing to our understanding of the dynamics within the banking sector and providing policy implications for promoting financial stability and regulatory efficacy.